In fuel-cell technological development, one of the most important objectives is to minimize the amount of Pt, the most employed material as oxygen reduction and methanol oxidation electro-catalyst. In this paper we report the synthesis and characterization of Te nanotubes (TeNTs) decorated with Pt nanoparticles, readily prepared from stirred aqueous solutions of PtCl2 containing a suspension of TeNTs and ethanol acting as a reducing agent, avoiding the use of any hydrophobic surfactants as capping stabilizing substance. The as obtained TeNTs decorated with Pt nanoparticles (TeNTs/PtNPs) have been fully characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), selected area diffraction patterns (SAD), X-ray photoelectron spectroscopy (XPS) and cyclic voltammetry (CV). We demonstrate that the new material can be successfully employed in fuel cell either as anodic (for methanol oxidation reaction) and cathodic (for oxygen reduction reaction) electrode with high efficiency in terms of related mass activities and on-set improvement. Remarkably, the cell operates in aqueous electrolyte buffered at pH 7.0, thus avoiding acidic or alkaline conditions that may lead e. g. to Pt dissolution (at low pH) and paving the way for the development of biocompatible devices and on chip fuel cells.

Nanocellulose is cellulose in the form of nanostructures, i.e. features not exceeding 100 nm at least in one dimension. These nanostructures include nanofibrils, e.g. in bacterial cellulose; nanofibers, e.g. in electrospun matrices; nanowhiskers and nanocrystals. These structures can be further assembled into bigger 2D and 3D nano-, micro- and macro-structures, such as nanoplatelets, membranes, films, microparticles and porous macroscopic matrices. There are four main sources of nanocellulose: bacteria (Gluonacetobacter), plants (trees, shrubs, herbs), algae (Cladophora) and animals (Tunicata). Nanocellulose has emerged for a wide range of industrial, technology and biomedical applications, e.g. for adsorption, ultrafiltration, packaging, conservation of historical artifacts, thermal insulation and fire retardation, energy extraction and storage, acoustics, sensorics, controlled drug delivery, and particularly for tissue engineering. Nanocellulose is promising for use in scaffolds for engineering of blood vessels, neural tissue, bone, cartilage, liver, adipose tissue, urethra and dura mater, for repairing connective tissue and congenital heart defects, and for constructing contact lenses and protective barriers. This review is focused on applications of nanocellulose in skin tissue engineering and wound healing as a scaffold for cell growth, for delivering cells into wounds, and as a material for advanced wound dressings coupled with drug delivery, transparency and sensorics. Potential cytotoxicity and immunogenicity of nanocellulose are also discussed.

Recent evidence indicates that the risk of being diagnosed with cancer in a tissue is strongly correlated (0.80) with the number of stem cell divisions accumulated by the tissue. Since cell division can generate random mutations during DNA replication, this correlation has been used to propose that cancer is largely caused by the accumulation of unavoidable mutations in driver genes. However, no correlation between the number of gene mutations and cancer risk across tissues has been reported. Because many somatic mutations in cancers originate prior to tumor initiation and the number of cell divisions occurring during tumor growth is similar among tissues, here I use whole genome sequencing information from 22,086 cancer samples and incidence data from the largest cancer registry in each continent to study the relationship between the number of gene mutations and the risk of cancer across 33 tissue types. Results show a weak positive correlation (mean = 0.14) between these two parameters in each of the five cancer registries. The correlation became stronger (mean = 0.50) when gender-related cancers were excluded. Results also show that 1,003 samples from 29 cancer types have zero mutations in genes. These data suggest that cancer etiology can be better explained by the accumulation of stem cell divisions than by the accumulation of gene mutations. Possible mechanisms by which the accumulation of cell divisions in stem cells increases the risk of cancer are discussed.

This review focuses on the regulation and modulation of human DNA polymerase δ (Pol δ). The emphasis is on mechanisms that regulate the activity and properties of Pol δ in DNA repair and replication. The areas covered are the degradation of the p12 subunit of Pol δ, which converts it from a heterotetramer (Pol δ4) to a heterotrimer (Pol δ3), in response to DNA damage and also during the cell cycle. The biochemical mechanisms that lead to degradation of p12 are reviewed, as well as the properties of Pol δ4 and Pol δ3 that provide insights into their functions in DNA replication and repair. The second focus of the review involves the functions of two Pol δ binding proteins, PDIP46 and PDIP38, both of which are multi-functional proteins. PDIP46 is a novel activator of Pol δ4, and the impact of this function is discussed in relation to its potential roles in DNA replication. Several new models for the roles of Pol δ3 and Pol δ4 in leading and lagging strand DNA synthesis that integrate a role for PDIP46 are presented. PDIP38 has multiple cellular localizations including the mitochondria, the splicesosomes and the nucleus. It has been implicated in a number of cellular functions, including the regulation of specialized DNA polymerases, mitosis, the DNA damage response, Mdm2 alternative splicing and the regulation of the Nox4 NADPH oxidase.

Abstract: High step-up voltage gain nonisolated DC-DC converter have attracted much attention in photovoltaic, fuel cells and other renewable energy system applications. In this paper, by combining input current ripple-free boost cell with coupled-inductor voltage-doubler cell, an input current ripple-free high voltage gain nonisolated converter is proposed. In addition, passive lossless clamp circuit is adopted to recycle the leakage inductor energy and to reduce the voltage spike across the power switch. By utilizing voltage-doubler cell consisting of diode and capacitor, the voltage stress of switch is further reduced and the resonance between the leakage inductor and the stray capacitor of the output diode is eliminated. A low switch-on-resistance low-voltage-rated MOSFET can therefore be employed to reduce the conduction loss and cost. The reverse recovery loss of output diode is reduced, and the efficiency of converter can be improved. Furthermore, the proposed converter can achieve nearly zero input current-ripple and make the design of electromagnetic interference (EMI) filter easy. Steady state analysis and operation mode of the converter is performed. Finally, experimental results are presented to verify the analysis results of the proposed converter.

It has been declared repeatedly that cancer is a result of molecular genetic abnormalities. However, there has been no working model describing the specific functional consequences of the deranged genomic processes that result in the initiation and propagation of the cancer process during carcinogenesis. We no longer need to question whether or not cancer arises as a result of a molecular genetic defect within the cancer cell. The legitimate questions are: how and why? This article reviews the preeminent data on cancer molecular genetics and subsequently proposes that the sentinel event in cancer initiation is the aberrant production of fused transcription activators with new molecular properties within normal tissue stem cells. This results in the production of vital oncogenes with dysfunctional gene activation transcription properties, which leads to dysfunctional gene regulation, the aberrant activation of transduction pathways, chromosomal breakage, activation of driver oncogenes, reactivation of stem cell transduction pathways and the activation of genes that result in the hallmarks of cancer. Furthermore, a novel holistic molecular genetic model of cancer initiation and progression is presented along with a new paradigm for the approach to personalized targeted cancer therapy, clinical monitoring and cancer diagnosis.

Carbonate reservoirs, influenced by depositional and diagenetic processes and characterized by features like faults and vugs that impact storage capacity, require more than traditional Borehole Imaging logs (BHI) for accurate porosity data. This data is essential for geological assessments, production forecasting, and reservoir simulations. This work aims to address this limitation by developing methods to measure and monitor the sustainability of carbonate reservoirs and exploring the application of sustainability principles to their management. The study integrates BHI and conventional logs from two wells to classify porosity-based facies within the Barra Velha Formation (BVF) in the Santos Basin. The methodology involves four steps: (i) analyzing conventional logs; (ii) segmenting BHI logs; (iii) integrating conventional and segmented BHI logs using Self-Organizing Maps (SOM); and (iv) interpreting the resulting classes. Matrix porosity values and non-matrix pore sizes categorize the porosity into four facies (A to D). Facies A has high non-matrix porosity with 14,560 small megapores, 5,419 large megapores, and 271 gigapores (71.9%, 26.76%, and 1.34% of the 20,250 pores, respectively). Facies B shows moderate non-matrix porosity with 8,669 small megapores, 2,642 large megapores, and 33 gigapores (76.42%, 23.29%, and 0.29% of the 11,344 pores, respectively) and medium matrix porosity. Facies C exhibits low non-matrix porosity with 7,749 small megapores, 2,132 large megapores, and 20 gigapores (78.27%, 21.53%, and 0.20% of the 9,901 pores, respectively) and medium matrix porosity. Facies D has low non-matrix porosity with 9,355 small megapores, 2,346 large megapores, and 19 gigapores (79.82%, 20.02%, and 0.16% of the 11,720 pores, respectively) and low matrix porosity. The novelty of this work lies in integrating data from two sources to classify porosity across the Pre-Salt reservoir interval, serving as a proxy for preliminary litho-facies identification without core data. This study advances our understanding of carbonate reservoir sustainability and heterogeneity, offering valuable insights for robust, sustainable reservoir characterization and management in the context of global environmental and geological changes.

Some of the barriers preventing Virtual Reality (VR) from being widely adopted are the cost and unfamiliarity of VR systems. Here we propose that in many cases the specialized controllers shipped with most VR head-mounted displays can be replaced by a regular smartphone, cutting the cost of the system, and allowing users to interact in VR using a device they are already familiar with. To achieve this, we developed SmartVR Pointer, an approach that uses smartphones as a replacement for the specialized controllers for two essential operations in VR: selection and navigation by teleporting. In SmartVR Pointer a camera mounted on the head-mounted display (HMD) is tilted downwards so that it points to where the user will naturally be holding their phone in front of them. SmartVR Pointer supports three selection modalities: tracker-based,gaze-based, and combined/hybrid. In the tracker-based SmartVR pointer selection we use image-based tracking to track a QR code displayed on the phone screen and them map the phone’s position to a pointer shown within the field of view of the camera in the Virtual Environment. In the gaze-based selection modality the user places the pointer using their gaze and taps on the phone for selection. The combined technique is a hybrid between head-gaze-based interaction in VR and smartphone-based Augmented Reality. It allows the user to control a VR pointer that behaves like a mouse pointer by moving their smartphone to select objects within the virtual environment, and to interact with the selected objects using the smartphone’s touch screen. The touchscreen is used for selection and dragging. SmartVR Pointer is simple and requires no calibration and no complex hardware assembly or disassembly. We demonstrate successful interactive applications of SmartVR Pointer in a VR environment with a demo where the user navigates in the virtual environment using teleportation points on the floor and then solves a Tetris-style key-and-lock challenge.

The shift towards Personalized Cancer Medicine (PCM) represents a significant transformation in cancer care, emphasizing tailored treatments based on genetic understanding of cancer at the cellular level. This review draws on recent literature to explore key factors influencing PCM implementation, highlighting the role of innovative leadership, interdisciplinary collaboration, and coordinated funding and regulatory strategies. Success in PCM relies on overcoming challenges such as integrating diverse medical disciplines, securing sustainable investment for shared infrastructures, and navigating complex regulatory landscapes. Effective leadership is crucial for fostering a culture of innovation and teamwork, essential for translating complex biological insights into personalized treatment strategies. The transition to PCM necessitates not only organizational adaptation but also the development of new professional roles and training programs, underscoring the need for a multidisciplinary approach and the importance of team science in overcoming the limitations of traditional medical paradigms. The conclusion underscores that PCM's success hinges on creating collaborative environments that support innovation, adaptability, and shared vision among all stakeholders involved in cancer care.

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare but severe adverse event that was first observed during the global vaccination campaign against SARS-CoV-2 infection, specifically in those receiving adenoviral vector-based vaccines for Coronavirus disease 2019 (COVID-19). VITT develops 4 to 42 days post-vaccination and is characterized by the development of platelet-activating anti-platelet factor 4 (PF4) antibodies, leading to thrombocytopenia and thrombosis at unusual sites. The rise in awareness and subsequent prompt recognition of VITT was paramount in reducing mortality. Moreover, as vaccination campaigns around the world continue, a better understanding of VITT not only has important clinical implications but is also crucial for future vaccine development. In this review, we summarize the clinical features, pathophysiology, and incidence rates of VITT as well as highlight other anti-PF4 antibody-mediated disorders of growing clinical significance.

Since the advent of the Internet, there has been a significant shift from wired to wireless communication between devices. The volume of data transmitted has surged, primarily driven by the exponential growth of network services, Internet of Things (IoT) devices, and online users. This trend became especially pronounced with the onset of the COVID-19 pandemic, as the Internet's role and significance expanded dramatically. People began to spend more time online, engaging in activities like e-learning, remote work, and online shopping. Concurrently, concerns about the security of wireless communication channels have escalated. As more data is stored and transmitted over the Internet, cybercriminals are actively seeking unauthorized access to it to further their malicious objectives. Through a comprehensive literature review in the realm of wireless network security and privacy, it has become evident that several factors render these networks susceptible to vulnerabilities. The aim of this paper is to shed light on the major and common security and privacy challenges faced by existing wireless networks. Additionally, it seeks to demonstrate the array of techniques available to mitigate these issues. Ultimately, this paper will culminate in an in-depth analysis of cybersecurity measures to address the issues in wireless networks.

The ever-evolving landscape of technology continually drives the demand for more robust and secure systems. Intrusion Detection and Prevention Systems (IPS) play a pivotal role in safeguarding digital infrastructures. IPS harnesses a blend of cutting-edge technologies, specifically Network-Based, Wireless-Based, and Host-Based Intrusion Detection Systems (IDS), to fortify network security. This multifaceted approach enhances the system's capacity to scrutinize incoming data and network traffic, effectively reducing the risk of intrusion. In the realm of malicious activity detection, IPS employs a diverse array of techniques and mechanisms. Our proposed IPS integrates both anomaly-based and signature-based analysis approaches. In signature-based analysis, intrusions are identified by matching data collected from various activities with pre-defined signatures, employing rule-based methods to detect anomalies effectively. In the anomaly-based analysis approach, the system juxtaposes current activities with a baseline of normal behaviour to flag any deviations. This is achieved through distance-based methods, ensuring a well-rounded approach to threat detection. Our comprehensive prevention system encompasses a suite of security measures, including anti-virus software, Deep Packet Inspection, and Quarantine. These components work in synergy to detect and thwart malicious activities effectively. Even when concealed or hidden, the IPS remains a reliable sentinel, ensuring the integrity of your digital ecosystem. This review delves into the intricate web of terminologies and concepts surrounding Intrusion Detection and Prevention Systems, shedding light on the evolving technology landscape and the critical role IPS plays in bolstering cybersecurity.

Based upon 30-years of research by the author a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 population is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem a new approach to bed modelling has been developed which plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence for over-utilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the current most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.

The paper discusses how joint damage and deterioration affect the seismic response of existing reinforced concrete frames with sub-standard beam-column joints. The available simplified modeling techniques are critically reviewed to propose a robust, yet computationally efficient technique for simulating the nonlinear behavior of substandard beam-column joints. Improvements over the existing models include simulation of the cyclic deterioration of joint stiffness and strength as well as pinching in the hysteretic response, implemented considering a deteriorating hysteretic rule. A fibre-section forced-based inelastic beam-column element is developed; considering improved material models and fixed-end rotation due to bond failure, rebars-slip and inelastic extension, to simulate the deteriorating cyclic behavior of existing pre-cracked beam-column members. For the assessment of frames with substandard exterior beam-column joints, a nonlinear model for the exterior joint is developed and validated through a full-scale quasi-static cyclic test performed on a substandard T-joint connection. The proposed model allows considering structural performance in risk assessment while accounting for true inelastic mechanisms at the joints.

This work presents results of property researches of fabricated samples of silica few-mode optical fiber (FMF) with induced chirality under twisting 10 and 66 revolutions per meter, core diameter 11 µm, typical “telecommunication” cladding diameter 125 µm and improved height of quasi-step refractive index profile. Proposed FMF supports 4 guided modes over “C”-band. We represent results of computed characteristics, as well as experimentally measured spectral responses of laser-excited optical signals, including researches and analysis of few-mode effects, occurring after fiber Bragg grating writing.

Advanced ceramics are recognized as key enabling materials possessing combinations of properties not achievable in other material classes. They are characterized by very high thermal, chemical and mechanical resistance and also usually have a lower density than metals. These properties predestine ceramics for many different applications, especially space applications.In the aerospace sector aerospike nozzles promise performance and application advantages compared to classic bell nozzles but are also inherently more complex to manufacture due to their shape. AM methods drastically simplify or even enable the fabrication of those complex structures while minimising the number of individual parts. The applicability of ceramic AM (“CerAMfacturing”) on rocket engines and especially nozzles is consequently investigated in the frame of the “MACARONIS” project, a cooperation of the Institute of Aerospace Engineering at Technische Universität Dresden and the Fraunhofer Institute for Ceramic Technologies and Systems (IKTS) in Dresden. The goal is to develop novel large size aerospike thrust nozzles including areas of highest resolution and fineness. Finding a suitable AM process that enables the realisation of both aspects is extremely challenging. One possibility could be the hybridization of shaping methods, in that case CerAM VPP (ceramic additive manufacturing via vat photopolymerization) and CerAM FFF (ceramic additive manufacturing via fused filament fabrication) in combination with sinter joining. This contribution focuses on the high resolution CerAM VPP process, in particular the development, characterization and testing of a new photoreactive Al₂O₃ suspension validated by AM of novel aerospike nozzles.

Manufacturing systems need to meet I4.0 guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets. The proposal of specific paradigms is exposed for managing these components, as is the case of multi-agent systems (MAS) that attribute intelligence to objects. The implementation of resource coalitions with evolutionary architectures (EAS) applies cooperation and capabilities’ association. Therefore, this work focuses on designing a method for modeling the asset administration shell (AAS) as virtual elements orchestrating intelligent agents (MAS) that attribute cooperation and negotiation through contracts to coalitions based on the engineering capabilities concept. The systematic method suggested in this work is partitioned for the composition of objects, AAS elements, and activities that guarantee the relationship between entities. Finally, Production Flow Schema (PFS) refinements are applied to generate the final Petri net models (PN) and validate them with Snoopy simulations. The results achieved demonstrate the validation of the procedure, eliminating interlocking and enabling liveliness to integrate elements behavior.

Maintaining a healthy cyber society is a big challenge due to the users’ freedom of expression and behaving. It can be solved by monitoring and analyzing the users’ behavior and taking proper actions towards them. This research aims to present a platform that monitors the public content on Twitter by extracting tweet data. After maintaining the data, the users’ interactions are analyzed using Graph Analysis methods. Then the users’ behavioral patterns are analyzed by applying Metadata Analysis, in which the timeline of each profile is obtained; also, the time-series behavioral features of users are investigated. Then in the Abnormal Behavior Detection Filtering component, the interesting profiles are selected for further examinations. Finally, in the Contextual Analysis component, the contents will be analyzed using natural language processing techniques; A binary text classification model (SVM + TF-IDF with 88.89% accuracy) for detecting if the tweet is related to crime or not. Then, a sentiment analysis method is applied to the crime-related tweets to perform aspect-based sentiment analysis (DistilBERT + FFNN with 80% accuracy); because sharing positive opinions about a crime-related topic can threaten society. This platform aims to provide the end-user (Police) suggestions to control hate speech or terrorist propaganda.

Background: In Transcranial Direct Current Stimulation (tDCS) the injected current gets distributed across the brain areas. The motive is to stimulate the target region-of-interest (ROI), while minimizing the current in non-target ROIs. For this purpose, determining the appropriate current-dose for an individual is difficult. Aim: To introduce Dose-Target-Determination-Index (DTDI) to quantify the focality of tDCS and examine the dose-focality relationship in three different populations. Method: Here, we extended our previous toolbox i-SATA to the MNI reference space. After a tDCS montage is simulated for a current-dose, the i-SATA(MNI) computes the average (over voxels) current density for every region in the brain. DTDI is the ratio of average current density at target ROI to the ROI with maximum value (peak region). Ideally target ROI should be the peak region, so DTDI shall range from 0 to 1. Higher the value, the better the dose. We estimated the variation of DTDI within and across individuals using T1-weighted brain images of 45 males and females distributed equally across three age groups- (a) Young adults (20 ≥ x ˂ 40 years), (b) Mid adults (40 ≥ x ˂ 60 years), and (c) Older adults (60 ≥ x ˂ 80 years). DTDI’s were evaluated for the frontal montage with electrodes at F3 and right supra-orbital for three current doses 1mA, 2mA, and 3mA with the target ROI at left middle frontal gyrus. Result: As the dose is incremented, DTDI may show (a) increase, (b) decrease, and (c) no change across the individuals. The focality decreases with age and the decline is stronger in males. Higher current dose at older age can enhance the focality of stimulation. Conclusion: DTDI provides information on which tDCS current dose will optimize the focality of stimulation. DTDI recommended dose should be prioritised based on the age (> 40 years) and sex (especially males) of an individual. The toolbox i-SATA(MNI) is freely available.

Technological advances in game-mediated robotics provide an opportunity to engage children with cerebral palsy (CP) and other neuromotor disabilities in more frequent and intensive therapy by making personalized, programmed interventions available 24/7 in children’s homes. Though shown to be clinically effective and feasible to produce, little is known of the subjective factors impacting acceptance of what we term assistive/rehabilitative (A/R) gamebots by their target populations. This research describes the conceptualization phase of an effort to develop a valid and reliable instrument to guide the design of A/R gamebots. We conducted in-depth interviews with 8 children with CP and their families who had trialed an exemplar A/R gamebot, PedBotHome, for 28 days in their homes. The goal was to understand how existing theories and instruments were either appropriate or inappropriate for measuring the subjective experience of A/R gamebots. Key findings were the importance of differentiating the use case of therapy from that of assistance in rehabilitative technology assessment, the need to incorporate the differing perspectives of children with CP and those of their parents into A/R gamebot evaluation, and the potential conflict between the goals of preserving the quality of the experience of game play for the child while also optimizing the intensity and duration of therapy provided during play.

Breast cancer is the most common cause of death for women worldwide. Thus, the ability of artificial intelligence systems to predict and classify breast cancer is very important. In this paper, a hybrid ensemble method classification mechanism is proposed based on a majority voting mechanism. First, the performance of different state-of-the-art machine learning classification algorithms for the Wisconsin Breast Cancer Dataset (WBCD) were evaluated. The three best classifiers were then selected based on their F3 score. F3 score is used to emphasize the importance of false negatives (recall) in breast cancer classification. Then, these three classifiers, simple logistic Regression learning, stochastic gradient descent learning and multilayer perceptron network, are used for ensemble classification using a voting mechanism. We also evaluated the performance of hard and soft voting mechanism. For hard voting, majority-based voting mechanism was used and for soft voting we used average of probabilities, product of probabilities, maximum of probabilities and minimum of probabilities-based voting methods. The hard voting (majority-based voting) mechanism shows better performance with 99.42% as compared to the state-of-the-art algorithm for WBCD.

In the present paper, the (p,q)-Hermite based Apostol type Frobenius-Euler polynomials and numbers are firstly considered and then diverse basic identities and properties for the mentioned polynomials and numbers, including addition theorems, difference equations, integral representations, derivative properties, recurrence relations. Moreover, we provide summation formulas and relations associated with the Stirling numbers of the second kind.

In recent years, demand has been increasing for target detection and tracking from aerial imagery via drones using onboard powered sensors and devices. We propose a very effective method for this application based on a deep learning framework. A state-of-art embedded hardware system empowers small flying robots to carry out the real-time onboard computation necessary for object tracking. Two types of embedded modules were developed: one is designed using a Jetson TX or AGX Xavier, and the other is based on an Intel Neural Compute Stick. These are suitable for real-time onboard computing power on small flying drones with limited space. A comparative analysis of current state-of-art deep-learning-based multi-object detection algorithms was carried out utilizing the designated GPU-based embedded computing modules to obtain detailed metric data about frame rates as well as the computation power. We also introduce an effective target tracking approach for moving objects. The algorithm for tracking moving objects is based on the extension of simple online and real-time tracking. It was developed by integrating a deep-learning-based association metric approach (Deep SORT), which uses a hypothesis tracking methodology with Kalman filtering and a deep-learning-based association metric. In addition, a guidance system that tracks the target position using a GPU-based algorithm is introduced. Finally, we demonstrate the effectiveness of the proposed algorithms by real-time experiments with a small multi-rotor drone.

Carbon supported nanoparticles of monometallic Ni catalyst and binary Ni-Transition Metal (Ni-TM/C) electrocatalytic composites were synthesized via chemical reduction method, where TM stands for the doping elements Fe, Co, and Cu. The chemical composition, structure and morphology of the Ni-TM/C materials were characterized by X-ray photoelectron spectroscopy (XPS), X-ray diffractometry (XRD), transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM) and energy-dispersive X-ray spectroscopy (EDS). The electrochemical properties towards hydrogen oxidation reaction in alkaline medium were studied using the rotating disc electrode and cycling voltammetry methods. A significant role of the TM dopant in the promotion of the hydrogen electrooxidation kinetics of the binary Ni-TM/C materials were revealed. A record-high in exchange current density value of 0.060 mA cm²_Ni was measured for Ni₃Fe₁/C, whereas the monometallic Ni/C counterpart has only shown 0.039 mA cm²_Ni. In order to predict the feasibility of the electrocatalysts for hydrogen chemisorption, density functional theory was applied to calculate the hydrogen binding energy and hydroxide binding energy values for bare Ni and Ni₃TM₁.

Tree species composition is an important key element for biodiversity and sustainable forest management, and hyperspectral data provide detailed spectral information, which can be used for tree species classification. There are two main challenges for using hyperspectral imagery: a) Hughes phenomena, meaning by increasing the number of bands in hyperspectral imagery, the number of required classification samples would increase exponentially, and b) in a more complex environment, such as riparian mixed forest, focusing on spectral variability per pixel may not be adequate for definability of tree species. Therefore, the focus of this study is to assess spectral-spatial dimensionality reduction of airborne hyperspectral imagery by using minim noise fraction (MNF) transformation, and object-based image analysis (OBIA). An airborne prism experiment (APEX) hyperspectral imagery was used. A study area was a riparian mixed forest located along the Salzach river, and six tree species including Picea abies, Populus (canadensis and balsamifera), Fraxinus excelsior, Alnus incana, and Salix alba were selected. A machine learning algorithm random forest (RF) was used to train and apply a prediction model for classification. Using a spectral dimensionality reduced APEX, a pixel-level classification was also done. According to a confusion matrix, the object-level classification of MNF-derived components achieved the overall accuracy of 85 %, and kappa coefficient of 0.805. The performance of classes according to producer’s accuracy varied between 80% for Fraxinus excelsior, Alnus incana, and Populus canadensis to 90% for Salix alba and Picea abies. Comparison the results to a pixel-level classification, showed a better performance of object-level classification (an overall accuracy of 63% and Kappa coefficient of 0.559 were achieved for pixel-level classification). The performance of classes using pixel-based classification varied 45 % for Alnus incana to 80% for Picea abies. In general, Spectral-spatial complexity reduction using MNF transformation and object-level classification yielded a statistically satisfactory results.

Systemic Lupus Erythematosus (lupus) and B-cell lymphoma (lymphoma) are serious diseases. Lupus and lymphoma co-occur at higher-than-expected rates and primarily depend on B-cells for their pathology, implicating shared inflammation-related B-cell molecular mechanisms as a potential cause of co-occurrence. We consequently implemented a novel Immune Imbalance Transcriptomics (IIT) algorithm and applied IIT to lupus, lymphoma, and healthy B-cell RNA-seq data to find shared- and contrasting mechanisms potentially targetable for treatment. We observed 8,562 genes significantly dysregulated in both lupus and lymphoma. Of those genes, we found 5,335 to have a significant immune imbalance, defined as significant dysregulation by both diseases, as determined by IIT. Gene Ontology (GO) term and pathway enrichment of IIT genes yielded immune-related “Neutrophil Degranulation” and “Adaptive Immune System”, validating that the IIT algorithm isolates biologically relevant genes in immunity and inflammation. We found that 389 IIT gene products are drug-targetable with established or repurposed drugs. Among our results, we found 40 known and 349 novel lupus targets, along with 151 known and 238 novel lymphoma targets. Known disease drug targets in our IIT results further validate that IIT isolates genes with disease-relevant mechanisms. We anticipate the IIT algorithm and shared and contrasting gene mechanisms uncovered here will contribute to the development of immune-related therapeutic options for lupus and lymphoma patients.

K+ channels do play a role in cell shape changes observed during cell proliferation and apoptosis. Research suggested that the dynamics of aggregation of Aquaporin-4 (AQP4) into AQP4-OAPs isoforms can trigger cell shape changes in malignant glioma cells. Here, we investigated the relationship between AQP4 and some K+ channels in the malignant glioma U87 line. The U87 cells transfected with the human M1-AQP4 and M23-AQP4 isoforms were investigated for morphology, gene expression of KCNJ8, KCNJ11, ABCC8, ABCC9, KCNMA1, and Cyclin genes by RT-PCR, recording the whole-cell K+ ions currents by patch-clamp experiments. AQP4 aggregation into OAPs increases the plasma membrane functional expression of the Kir6.2 and SUR2 subunits of the KATP channels, and of the KCNMA1 of the BK channels in U87 cells leading to a large increase in inward and outward K+ ion currents. These changes were associated with changes in morphology with a decrease in cell volume in the U87 cells and an increase in the ER density. These U87 cells accumulate in the mitotic and G2 cell cycle. The KATP channel blocker zoledronic acid reduced cell proliferation in either M23 AQP4-OAPs and M1 AQP4-tetramers transfected cells leading to early and late apoptosis, respectively. BK channel sustains the efflux of K+ ions associated with the M23 AQP4-OAPs expression in the U87 cells, but it is downregulated in the M1 AQP4-tetramers cells; KATP channels are effective in the M1 AQP4-tetramers and M23 AQP4-OAPs cells. Zoledronic acid can be effective in targeting pathogenic M1 AQP4-tetramers cell phenotype inhibiting KATP channels and inducing early apoptosis.

Rasagiline (Azilect®) is a selective monoamine oxidase B (MAO-B) inhibitor that provides symp-tomatic benefit in Parkinson’s disease (PD) treatment and found to exert preclinical neuroprotec-tive effects. Here, we investigated the neuroprotective signaling pathways of rasagiline in the PC12 neuronal cultures exposed to an ischemic-like insult. Exposure of neurons to oxy-gen-glucose deprivation for 4 h followed by 18 h of reoxygenation caused 40% aponecrotic cell death. Rasagiline induced dose-dependent neuroprotection by decreasing cell death and produc-tion of the neurotoxic reactive oxygen species, and reducing the nuclear translocation of glycer-aldehyde-3-phosphate dehydrogenase (GAPDH). Rasagiline increased protein kinase B (Akt) phosphorylation and decreased protein expression of the ischemia-induced α-synuclein protein, in correlation to the neuroprotective effect. Treatment with rasagiline induced nuclear shuttling of transcription factor Nrf2 and increased the mRNA levels of the antioxidant enzymes heme oxy-genase-1, (NAD (P) H- quinone dehydrogenase, and catalase. These results indicate that rasagiline provides neuroprotection in the ischemic neuronal cultures with inhibition of α-synuclein and GAPDH-mediated aponecrotic cell death, and via mitochondrial protection, as by increasing mi-tochondria-specific antioxidant enzymes by a mechanism involving the Akt/Nrf2 redox-signaling pathway. These findings may be exploited for neuroprotective drug development in PD and stroke therapy.

The terpolymers of N-vinylpyrrolidone (VP) with acrylic acid and triethylene glycol methacrylate were synthesized with more than 90% yield by radical copolymerization in ethanol from monomeric mixtures of different composition (98 : 2 : 2, 95 : 5: 2 and 98 : 2: 5). Their physical and chemical characteristics such as monomer composition, absolute molecular masses and hy-drodynamic radii in aqueous media at different temperature were determined. The temperature effect on the behavior of terpolymers in water and aqueous saline buffer solution with pH 7.4 has been studied and the ability of a copolymer enriched with dimethacrylates units was discovered to respond to a temperature change in these media. On the basis of terpolymers and linear polyvi-nylpyrrolidone (PVP), polymer compositions of hydrophobic dye methyl pheophorbide a, MPP, that is fluorescent in the red region of the spectrum, were obtained; the sizes of the polymer nanostructures of MPP in water were determined. The structures based on terpolymers were demonstrated to be more stable than MPP-PVP ones. It was carried out the quantum-chemical modelling of the possible structures of MPP-copolymer that formed as a result of intermolecular interaction between MPP and terpolymer’s chains; the possibility of the formation of hydrogen bonds between the donors of the electrons of terpolymer units and the proton donors of the MPP molecule was shown. Using the MTT test, it was established that copolymers of various compositions are low toxic for non-tumor Vero cells and HeLa tumor cells. It was shown that the cytotoxicity of polymer particles loaded with MPP for FetMSC and HeLa cells increased. Using fluorescence microscopy, the accumulation and distribution of polymer particles in non-tumor (FetMSC) and tumor (HeLa) cells was studied and an increase in the accumulation of MPP with both types of particles was shown.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a promising chemotherapeutic agent because of its selective apoptotic action on cancer cells. However, resistance to TRAIL-induced apoptosis remains a challenge in many cancers. The gintonin-enriched Panax ginseng extract fraction (GEF) has diverse pharmacological benefits. We explored the combined efficacy of GEF and TRAIL in inducing apoptosis in human renal cell carcinoma (RCC) cells. The effect of GEF treatment on viability, clonogenic potential, wound healing, and TRAIL-induced apoptotic signaling of RCC cells was studied in vitro. Our investigation revealed that GEF pre-treatment sensitized RCC cells to TRAIL-induced apoptosis, as evidenced by DNA fragmentation and cell proliferation, colony formation, and migration inhibition. This sensitization was linked to the upregulation of death receptors 4 and 5 and alterations in apoptotic protein expression; notably, decreased expression of Mu-2-related death-inducing gene, a novel anti-apoptotic protein. Our findings underscore the necessity of caspase activation for GEF/TRAIL-induced apoptosis using the pan-caspase inhibitor Z-VAD-FMK. It demonstrates that GEF sensitizes human RCC cells to TRAIL-induced apoptosis by upregulating DR4/5 and modulating apoptotic protein expression. These findings suggest a promising strategy for overcoming TRAIL resistance in cancer therapy and highlight the potential of GEF as a valuable adjunct to TRAIL-based treatments.

The massive amount of human biological, imaging and clinical data produced by multiple and diverse sources, necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels as well as their orchestration and links are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof of concept study cases. Personalized simulations over the actual anatomy of a patient have been carried out. The hypermodel has also applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin based clinical decision support system and the core of future in silico trial platforms, although additional retrospective adaptation and validation is necessary.

To better understand how immunity develops against SARS-CoV-2 during the pandemic period of 2020 to 2022, we analyzed the immune response of a small group of university staff and students who were either infected or vaccinated. We investigated the levels of receptor-binding domain (RBD)-specific and nucleocapsid (N)-specific IgG and IgA antibodies in serum and saliva samples taken early (around 10 days after infection or vaccination) and later (around 1 month later), as well as N-specific T-cell responses. One patient who had been infected in 2020 developed serum RBD and N-specific IgG antibodies, but declined 8 months later, then mRNA vaccination in 2021 produced a higher level of anti-RBD IgG than natural infection. In the vaccination of naïve individuals, vaccines induced anti-RBD IgG, but it declined after 6 months. A third vaccination boosted the IgG level again, albeit to a lower level than after the second. In 2022, when the Omicron variant became dominant, familial transmission occurred even among vaccinated people. In infected individuals, the levels of serum anti-RBD IgG antibodies increased later, while anti-N IgG peaked earlier. The N-specific activated T cells expressing IFN- or CD107a were detected early. In saliva, SARS-CoV-2-specific IgG but not IgA was detected. Interestingly, two individuals showed a temporary peak in RBD- and N-specific IgA antibodies in their saliva on the second day after infection. Thus, SARS-CoV-2 infection triggers typical immune responses in humans against acute viral infections, but mucosal immune responses, which are temporarily induced early during infection, may be more important for protection than current intramuscular vaccines.

Chronic lymphocytic leukemia (CLL) is characterized by dysfunctional B cells. Immune checkpoint molecules such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), and programmed death-1 (PD-1) are upregulated in patients with CLL and may correlate with prognostic markers such as beta-2 microglobulin (B2M). The aim of this study was to evaluate the levels of immune checkpoints on B-cell subsets and to further correlate them with B2M levels in patients with CLL. We recruited 21 patients with CLL and 12 controls. B cell subsets and the levels of immune checkpoint expression were determined using conventional multi-color flowcytometry. Basal levels of B2M in patients with CLL were measured using an Enzyme-linked immunosorbent assay. Patients with CLL had increased levels of activated B cells when compared to the control group, p< 0.001. The expression of PD-1 and CTLA-4 were increased on activated B cells and memory B cells, p< 0.05. There were no associations between B2M levels and the measured immune checkpoints on B cell subsets, after adjusting for sex and age. African patients with CLL express elevated levels of PD-1 and CTLA-4 immune checkpoints on activated and memory B cell subsets. However, there is no correlation between these immune checkpoint expressions and B2M levels.

We have previously developed several successful decellularization strategies yielding porcine cardiac extracellular matrices (pcECMs), which exhibit tissue-specific bioactivity and bioinductive capacity when cultured with various pluri- and multipotent stem cells. Here, we studied the tissue-specific effects of the pcECM on seeded human mesenchymal stem cells (hMSCs) phenotype using reverse transcribed quantitative polymerase chain reaction (RT-qPCR) arrays for cardio-vascular related genes. We further corroborated interesting findings at the protein level (flow cytometry and immunological stains) as well as bioinformatically using several mRNA sequencing and protein databases of normal and pathologic adult tissue expression, as well as during human embryonic organogenesis. We discovered that upon seeding of human mesenchymal stem cells (hMSCs) on the pcECM they displayed partial MET toward endothelial phenotypes (CD31+) and morphologies, which were preceded by an early spike (~day 3 onward after seeding) in HAND2 expression at both the mRNA and protein levels compared to plate controls. CRISPR-Cas9 knockout (KO) of HAND2 and its associated antisense long non-coding RNA (HAND2-AS1) regulatory region resulted in proliferation arrest, hypertrophy, and senescent-like morphology. Bioinformatic analyses revealed that HAND2 and HAND2-AS1 are highly correlated in expression, are expressed in many different tissue types albeit at distinct yet tightly regulated expression levels. Deviation (down or up regulation) from these basal tissue expression levels are associated with a long list of pathologies. We thus suggest that HAND2 expression levels may finetune cell plasticity possibly affecting senescence and mesenchymal-to-epithelial transition states, through yet unknown mechanisms. Targeting this pathway may represent a promising new therapeutic approach for a wide range of diseases, including cancer, degenerative disorders, and aging. Nevertheless, further investigations are required to better understand the molecular players involved, potential inducers and inhibitors of this pathway, and eventually potential therapeutic applications.

Acute myeloid leukemia (AML) is the second common hematologic malignancy in children. The incidence of childhood AML is much lower than acute lymphoblastic leukemia (ALL), which makes the childhood AML a rare disease in children. The role of genetic abnormalities in AML classification, management and prognosis prediction is much more important than before. The WHO classification of myeloid neoplasms and the European LeukemiaNet (ELN) classification were both revised in 2022. The application of the new information in childhood AML will be upcoming in the next few years. The frequency of each genetic abnormality in adult and childhood AML is different, therefore, in this review we emphasize in well-known genetic subtypes in childhood AML, including Core-binding factor AML (CBF AML), KMT2Ar (KMT2A/11q23 rearrangement) AML, normal karyotypes AML with somatic mutations, unbalanced cytogenetic abnormalities AML, NUP98 11p15/NUP09 rearrangement AML and acute promyelocytic leukemia (APL). Current risk group classification, management algorithm in childhood AML and novel treatment modalities, such as targeted therapy, immune therapy, chimeric antigen receptor (CAR) T-cell therapy are reviewed. Finally, the indications of hematopoietic stem cell transplantation (HSCT) in AML are discussed.

Background: Metastatic oral squamous cell carcinoma (OSCC) is associated with poor patient prognosis. Metastasis is a complex process involving various proteins, tumor cell alterations including changes caused by the epithelial-to-mesenchymal transition (EMT) process, and interactions with the tumor microenvironment (TME). In this study, we investigate a combined protein marker system consisting of connexin 43 (Cx43), EMMPRIN (CD147), E-cadherin and vimentin during the invasive metastatic process of OSCC and the possibility of using this system for prognosis prediction. Methods: The protein expression profiles of Cx43, EMMPRIN, E-cadherin and vimentin were investigated by immunohistochemistry in tissue samples from 24 OSCC patients. The metastatic process was mapped through different regions of interest (ROI) of adjacent healthy oral mucosa (OM), center of primary OSCC, invasive front (IF), and local cervical lymph node metastases (LNM). Disease-free survival (DFS) and overall survival (OS) were the primary clinical endpoints. Results: Significant changes in the expression profiles of the different marker proteins were detected between the different ROIs (all p values &lt; 0.05). Multivariable Cox regression analysis revealed a significant effect of increased EMMPRIN expression towards IF on DFS (p = 0.019) and OS (p = 0.023). The combined predictive analysis showed a significant predictive value of the marker system for DFS (p = 0.0017) and OS (p = 0.00044). Conclusions: The combined marker system was able to significantly predict patient prognosis. An increase in EMMPRIN expression towards IF showed the strongest effect and could be an interesting new antimetastatic therapy approach.

The Onion Route Network (also called TOR) is by far the most efficient and widely used anonymity platform with millions of users daily and an expanding size and capacities. Since its public deployment in 2002, the Onion Routing network (also known as TOR) has maintained its leading position and dozens of propositions aiming to improve its performance and enhance the security (anonymity and privacy) have been made. Given the significance of this research area, this work seek to contribute into the improvement of TOR by investigating and testing revolutionary cryptographic and routing mechanism. This work is justified by the current TOR vulnerability and observed weaknesses, and set the challenging aim of covering these security flaws by proposing the relevant security and performances improvement such as the authenticated-encryption for onion construction, the lightened onion encapsulation approach and the secured circuit selection and cell routing mechanisms. The obtained results from implementing the proposed improvements and testing them into a TOR-like simulation platform permit to validate not only, the performances and security contributions brought by the improvement, but also the suitability of their potential implementation into the real TOR network.

CRCMSS/pMMR contain a significantly increased fraction of TREM2+ macrophages (TAMs) and CD66+ neutrophils (TANs) together with decrease of CD4-CD8-CD3+ double negative T lymphocytes (DNTs); no differences were revealed by the analysis of myeloid and plasmacytoid dendritic cell populations. A fraction of tumor-infiltrating T-cells display an exhausted phenotype, co-expressing PD-1 and TIM-3. Remarkably, expression of PD-L1 on fresh tumor cells and TAMs was undetectable even after in vitro stimulation with interferon-γ. These findings confirm the immune suppressive microenvironment of CRCMSS/pMMR characterized by dense infiltration of TAMs, occurrence of TANs, lack of DNTs, T-cell exhaustion and interferon-γ unresponsiveness by host and tumor cells. Appropriate bypass strategies should consider these combinations of immune escape mechanisms in CRCMSS/pMMR.

People with sickle cell disease (SCD) are at greater risk of severe illness and death from respiratory infections, including COVID-19 than people without SCD (Centers for Disease Control and Prevention, USA). Vaso-occlusive crises (VOC) in SCD and severe SARS-CoV-2 infection are both characterized by thrombo-inflammation mediated by endothelial injury, complement activation, inflammatory lipid storm, platelet activation, platelet-leukocyte adhesion, and activation of the coagulation cascade. Notably, lipid mediators, including thromboxane A2, significantly increase in severe COVID-19 and SCD. In addition, the release of thromboxane A2 from endothelial cells and macrophages stimulates platelets to release microvesicles which are harbingers of multicellular adhesion and thrombo-inflammation. Currently, there are limited therapeutic strategies targeting platelet-neutrophil activation and thrombo-inflammation in either SCD or COVID-19 during acute crisis. However, due to many similarities between the pathobiology of thrombo-inflammation in SCD and COVID-19, therapies targeting one disease may likely be effective in the other. Therefore, the preclinical and clinical research spurred by the COVID-19 pandemic, including clinical trials of anti-thrombotic agents, are potentially applicable to VOC. Here, we first outline the parallels between SCD and COVID-19; second, review the role of lipid mediators in the pathogenesis of these diseases and lastly, examine the therapeutic targets and potential treatments for the two diseases.

Nicastrin (NICT) is a transmembrane protein physically associated with the polytypical aspartyl protease presenilin that plays a vital role in the correct localization and stabilization of presenilin to the membrane-bound γ-secretase complex. This complex is involved in the regulation of a wide range of cellular events including cell signaling and the regulation of endocytosed membrane proteins for their trafficking and protein processing. Mehtods: In Trypanosoma cruzi, the causal agent of the Chagas disease, an NICT-like protein (Tc/NICT) was identified with a short C-terminus orthologous to the human protein, a large ectodomain (ECD) with numerous glycosylation sites and a single core transmembrane domain containing a putative TM-domain (457GSVGA461) important for the γ-secretase complex activity. Results: Using the Spot-synthesis strategy with Chagasic patient sera, five extracellular epitopes were identified and synthetic forms were used to generate rabbit anti-Tc/NICT polyclonal serum that recognized a ~72-kDa molecule in immunoblots of T. cruzi epimastigote extracts. Confocal microscopy suggests that Tc/NICT is localized in the flagellar pocket, which is consistent with data from our previous studies with a T. cruzi presenilin-like protein. Phylogenetically, Tc/NICT was localized within a subgroup with the T. rangeli protein that are clearly detached from the other Trypanosomatidae such as T. brucei. These results, together with a comparative analysis of the selected peptide sequence regions between the T. cruzi and mammalian proteins suggest a divergence from the human NICT that might be relevant to Chagas disease pathology. As a whole, our data show that an NICT-like protein is expressed in the infective and replicative stages of T. cruzi and may be considered further evidence for a γ-secretase complex in trypanosomatids.

With an estimated 3 to 5 million human cases annually and the potential to infect domestic and wild animal populations, influenza viruses are one of the greatest health and economic burdens to our society [1] and pose an ongoing threat of large-scale pandemics. Despite our knowledge of many important aspects of influenza virus biology, there is still much to learn about how influenza viruses replicate in infected cells, for instance how they use entry receptors or exploit host cell trafficking pathways. These gaps in our knowledge are due, in part, to the difficulty of directly observing viruses in living cells. In recent years, advances in light microscopy, including super-resolution microscopy and single-molecule imaging, have enabled many viral replication steps to be visualised dynamically in living cells. In particular, the ability to track single virions and their components, in real time, now allows specific pathways to be interrogated providing new insights to various aspects of the virus-host cell interaction. In this review, we discuss how state-of-the-art imaging technologies, notably quantitative live-cell and super-resolution microscopy, are shedding new nanoscale and molecular insights into influenza virus replication and revealing new opportunities for developing antiviral strategies.

Separation and interpretation of rebellious Circulating Tumor Cells (CTCs) originating from the primary tumor or cancer tissue plays a significant role in diagnostics, cancer progression analyses, suitable medicine exploration, and treatment proficiency examination. Cancer metastasis occurs when CTCs spread throughout the body and invade healthy tissues, leading to new tumors in that area. Although a dramatic rate of deaths begins from spreading CTCs around the body, valuable measures have been made to control their development. However, the first step is separating these harmful cells from the bloodstream and investigating their features. Having examined the characteristics of CTCs as cancer’s main strength, researchers can introduce complementary treatments that can affect cancerous cells without damaging the healthy cells. Therefore, according to their unique characteristics, numerous techniques have been established for continuous and fast separation and sorting of CTCs. Nevertheless, few separators enjoy the efficient performance and appropriate accuracy and can be produced in mass numbers due to the available fabrication equipment. Microfabrication advancements enable separators to combine the advantages of active and passive methods in a small-scale platform for probing individual cells and separation purposes. Reduction in reagents, sample volume, analysis time, and less harmfulness to patients are some of the motivations that encourage researchers to employ microfluidic instruments for CTCs separation from other blood cells over the last two decades. However, microfabrication limitations mean effective separators, and the diagnostic option they provide, are not readily available. Addressing these limitations requires optimizing the design and fabrication of separators such that they are reduced in their size and fabrication cost, while also maintaining high-throughput separating capability. The emergence of the Lab-On-a-Chip (LOC) and then Lab-On-a-CD (LOCD) technologies, having more inherent benefits than conventional microfluidic devices, has created new opportunities and become increasingly widespread in recent years. Evidence suggests that employing single methodologies or integrating approaches without sufficient understanding of potential outcomes is unlikely to result in successful diagnostic results. This paper contributes an extensive review of several separation systems, including fundamental theories and experimental details, and describes detailed operating principles and device performance.

The study presents a mathematical modeling for supporting the premise that our body is composed of blockchain systems. A cell population is considered a space with peer-to-peer communication networks for applying blockchain protocol. Transaction is defined as gene expression that constantly occurs for protein synthesis in each cell. The transaction process proceeds according to the blockchain protocol with sharing and recording the data on the blockchain ledger. The premise comes from the clues of the previous research such that the cell population is a complex structured network system having cell-to-cell connections. Although individual cells exhibit stochastic nonlinear dynamic behavior, cell population shows consensus behavior that reaches to ensemble through interaction among cells. It is inferred that gene expression is not regulated by the corresponding cell only nor determined by external intelligence such as the brain. This is achieved through a consensus through stochastic interactions between cells over the whole cell population. These findings imply that mathematical blockchain modeling is a suitable for gene expression process. The original contribution of the study is a methodology for applying mathematically the blockchain protocol to the real biological gene expression process. In other words, the DNA sequence is converted into a numeral bit sequence that makes it possible to implement the blockchain protocol. A new DNA sequence scheme is proposed with adding methylated cytosine and adenine as the 5th and 6th bases for including epigenetic information which has profound effect on gene expression and regulation. The methodology was applied to the real biological synthesis process of protein samples. The protein is composed of amino acids that are encoded by triplet codons of 216 kinds with 6 base RNA sequence. The gene expression information is traced backward from a synthesized protein sample, amino acids of codons, RNA transcript up to DNA sequence. One of the results is a numeric value in the form of a bit sequence with which mathematical blockchain modeling is applicable. The cryptographic authentication and the consensus process are mathematically proven to work properly by the blockchain protocol. It implies that the same protein is synthesized, but with different epigenetic data, then protein's latent material properties will certainly be different. Although the result has not been justified by the biologic experiment yet, it is sure that the biological hidden algorithm inside DNA sequence will be revealed by the binary bit-logic with physical on/off states which is mathematically proven. The research will greatly contribute to disease treatment and medicine development as well as epigenetics in the future.

The Particle-In-Cell (PIC) method has been developed in order to investigate microscopic phenomena, and with the advances of computing power, newly developed codes have been used for several fields such as astrophysical, magnetospheric, and solar plasmas. PIC applications have grown extensively with large computing powers available on supercomputers such as Pleiades and Blue Waters in the US. For astrophysical plasma research PIC methods have been utilized for several topics such as reconnection, pulsar dynamics, non-relativistic shocks, relativistic shocks, relativistic jets, etc. PIC simulations of relativistic jets have been reviewed with the emphasis on the physics involved in the simulations. This review summarizes PIC simulations, starting with the Weibel instability in slab models of jets, and then focuses on global jet evolution in helical magnetic field geometry. In particular we address kinetic Kelvin-Helmholtz instabilities and mushroom instabilities.

Pseudopterosin, produced by the sea whip of the genus Antillogorgia, possesses a variety of promising biological activities including potent anti-inflammatory effects. However, few studies examined pseudopterosin in the treatment of cancer cells and, to our knowledge, the ability to inhibit triple negative breast cancer (TNBC) proliferation or invasion has not been explored. Thus, we evaluated the as yet unknown mechanism of action of pseudopterosin: Pseudopterosin was able to inhibit proliferation of TNBC. Interestingly, analyzing breast cancer cell proliferation after knocking down glucocorticoid receptor α (GRα) revealed that anti-proliferative effects of pseudopterosin were significantly inhibited when GRα expression was reduced. Furthermore, pseudopterosin inhibited invasion of MDA-MB-231 3D tumor spheroids embedded in an extracellular-like matrix. Remarkably, the knockdown of GRα in 3D tumor spheroids revealed increased ability of cells to invade the surrounding matrix. In a co-culture, encompassing peripheral blood mononuclear cells (PBMC) and MDA-MB-231 cells, production of interleukin 6 (IL-6) and interleukin 8 (IL-8) significantly increased compared to monoculture. Notably, pseudopterosin proved to block cytokine elevation, representing key players in tumor progression, in the co-culture. Thus, our results reveal pseudopterosin treatment as a potential novel approach in TNBC therapy.

Stroke remains a major cause of death and disability in the United States and around the world. Solid safety and efficacy profiles of novel stroke therapeutics have been generated in the laboratory, but most failed in clinical trials. Investigations into the pathology and treatment of the disease remain a key research endeavor in advancing scientific understanding and clinical applications. In particular, cell-based regenerative medicine, specifically stem cells transplantation, may hold promise as stroke therapy because grafted cells and their components may recapitulate the growth and function of the neurovascular unit, which arguably represents the alpha and omega of stroke brain pathology and recovery. Recent evidence has implicated mitochondria, organelles with a central role in energy metabolism and stress response, in stroke progression. Recognizing that stem cells offer a source of healthy mitochondria, potentially transferrable into ischemic cells, may provide a new therapeutic tool. To this end, deciphering cellular and molecular processes underlying dysfunctional mitochondria may reveal innovative strategies for stroke therapy. Here, we review recent studies capturing the intimate participation of mitochondrial impairment in stroke pathology, and showcase promising methods of healthy mitochondria transfer into ischemic cells, to critically evaluate the potential of mitochondria-based stem cell therapy for stroke.

Engineering of drug nanocarriers combining fine-tuned mucoadhesive/mucopenetrating properties is currently being investigated to ensure more efficient mucosal drug delivery. Aiming to improve the transmucosal delivery of hydrophobic drugs, we designed a novel kind nanogel produced by the self-assembly of amphiphilic chitosan graft copolymers ionotropically crosslinked with sodium tripolyphosphate. In this work, we synthesized for the first time chitosan-g-poly(methyl methacrylate) nanoparticles thiolated by the conjugation of N-acetyl cysteine. First, we confirmed that both non-crosslinked and crosslinked nanoparticles in the 0.05-0.1% w/v concentration range display very good cell compatibility in two cell lines that are relevant to oral delivery, Caco2 cells that mimic the intestinal epithelium and HT29-MTX cells that produce mucin. Then, we evaluated the effect of crosslinking, nanoparticle concentration and thiolation on the permeability in vitro utilizing monolayers of (i) Caco2 and (ii) Caco2:HT29-MTX cells (9:1 cell number ratio). Results confirmed that the ability of the nanoparticles to cross Caco2 monolayer was affected by the crosslinking. In addition, thiolated nanoparticles interact more strongly with mucin, resulting in a decrease of the apparent permeability coefficient (Papp) compared to the pristine nanoparticles. Moreover, for all the nanoparticles, higher concentration resulted in lower Papp suggesting indicating that the transport pathways could undergo saturation.

The recent Zika virus (ZIKV) outbreak in Americas surprised all of us because of its rapid spread and association with neurologic disorders including fetal microcephaly, brain and ocular anomalies and Guillain-Barré syndrome. In responding to this global health outcry, unprecedented and world-wide efforts are taking place to study the ZIKV etiology. Much have been learned about this virus in the areas of epidemiology, clinical manifestation, viral sequences and protein structures, as well as effects of ZIKV infection on fetal brain development and microcephaly. However, the molecular mechanism underlying ZIKV-mediated neurologic disorders remains elusive. Some critical questions include: 1) what type of virologic changes has taken place that increased the viral virulence? 2) which ZIKV protein(s) is responsible for the enhanced viral pathogenicity? And 3) how the newly adapted and pathogenic ZIKV strains alter their interactions with host cells leading to neurologic disorders? The goal of this review is to explore the molecular insights into the ZIKV-host interactions with special focuses on host cell receptor usage for viral entry, host cellular and immune antiviral responses, ZIKV counteraction and ZIKV-induced cytopathic effects. Our hope with this literature review is to inspire additional studies focusing on molecular studies of ZIKV-host Interactions.

Abstract: DNA fragmentation factors 40 and 45 (DFF40 and DFF45) and B-cell lymphoma 2 (Bcl-2) expression were evaluated in the normal human endometrium and myometrium. DFF40, DFF45, and Bcl-2 expression was assessed via immunohistochemistry in the proliferative, secretory, and atrophic endometrium and myometrium collected postmenopausally and premenopausally during the proliferative and secretory phases of the menstrual cycle. The endometrium showed significantly higher DFF40 and DFF45 expression than that in the uterine myometrium; compared to the stroma, endometrial glands showed the highest expression in pre- and postmenopausal specimens. Glandular expression of DFF45 was dependent on the menstrual cycle, reaching its highest level in the secretory endometrium. The glandular expression of DFF40 and DFF45 was significantly lower in postmenopausal specimens than that in premenopausal tissue. No cycle-dependent changes were reported for stromal or myometrial DFF40 or DFF45 expression. Compared to the endometrial stroma and myometrium, Bcl-2 showed the highest expression in the glandular proliferative endometrium and the lowest expression in the stromal secretory endometrium and myometrium during the secretory phase of the cycle. DFF45 and Bcl-2 showed menstrual cycle-dependent expression, which was limited to the glandular layer of the endometrium.

Salt marshes in the southern North Sea are part of the UNESCO World Heritage Site Wadden Sea, the largest unbroken system of intertidal sand and mud flats in the world. They provide a very high nature value while significantly contributing to coastal flood and erosion risk management as a nature-based element of flood and erosion risk management systems for the densely populated coastal area. Climate change-induced sea-level rise is a significant concern: An integrated approach to salt marsh management adapted to the effects of climate change necessitates a understanding of the impact of different management strategies. This review commences with a description of the biogeomorphological conditions and processes in salt marshes for a better understanding of the natural dynamics and how they are influenced by management and climate change. In a second step, the impact of salt marshes on hydrodynamic processes and their role as nature-based element of flood and erosion risk management is presented. Management options and implementation methods are discussed and analysed concerning coastal flood management and nature conservation requirements. In conclusion, a targeted salt marsh management needs to consider the initial conditions and the development aims of the specific site integrated in a conceptual framework. Salt marshes have the potential to adapt to sea-level rise, thereby contributing to the long-term protection of coastal areas.

This paper explores the influence of GenAI chatbot (ChatGPT) and AI-based simulation (SimVenture) on the start-up intention through the mediating roles of entrepreneurship educational outcomes; entrepreneurship cognition, entrepreneurship competencies, and innovation spirit of students in higher education institutions in the Middle East. The proposed conceptual framework was empirically tested with partial least squares structural equation modeling using 166 survey responses from fourth-year undergraduate students enrolled in business administration programs in four higher education institutions in the Middle East region. The findings reveal that ChatGPT significantly promotes start-up intention, while ChatGPT has insignificant influence on entrepreneurship educational outcomes. Conversely, the SimVenture platform negatively influences start-up intention. Additionally, the SimVenture platform significantly improves entrepreneurship educational outcomes; thereby entrepreneurship educational outcomes directly influence start-up intention. Furthermore, the mediation paths show ChatGPT has an insignificant indirect influence on start-up intention through the mediating roles of entrepreneurship educational outcomes, while the SimVenture platform exhibits a notable indirect influence on startup intentions through improved entrepreneurship educational outcomes. These findings seek to provide insights for higher education institutions in the Middle East region in leveraging GenAI chatbot (ChatGPT) and AI-based simulation (SimVenture) to enhance entrepreneurial knowledge, awareness, competencies, and the spirit of innovation, which leads to promoting students’ intentions to start their businesses. Theoretically, the study contributes to filling the gap in the existing literature between AI tools and entrepreneurship education. This study is among the first to empirically explore the influences of GenAI chatbot (ChatGPT) and AI-based simulation (SimVenture) on entrepreneurship educational outcomes and the intention of students to embark on entrepreneurial ventures. It highlights the need for understanding AI technologies as distinct pedagogical tools.

This multi-center retrospective study evaluated the diagnostic performance of a deep learning (DL)-based application for detecting, classifying, and highlighting suspected aortic dissections (ADs) on chest and thoraco-abdominal CT angiography (CTA) scans. CTA scans from over 200 U.S. and European cities acquired on 52 scanner models from 6 manufacturers were retrospectively collected and processed by CINA-CHEST (AD) (Avicenna.AI, La Ciotat, France) device. The di-agnostic performance of the device was compared with the ground truth established by the majority agreement of three US board-certified radiologists. Furthermore, the DL-algorithm's time-to-notification was evaluated to demonstrate clinical effectiveness. The study included 1,303 CTAs (mean age 58.8 ± 16.4 years old, 46.7% male, 10.5% positive). The device demonstrated a sensitivity of 94.2% [95% CI: 88.8% – 97.5%] and a specificity of 97.3% [95% CI: 96.2% - 98.1%]. The application classified positive cases by AD types with an accuracy of 99.5% [95% CI: 98.9% – 99.8%] for type A and 97.5 [95% CI: 96.4% – 98.3%] for type B. The application did not miss any type A cases. The device flagged 32 cases incorrectly, primarily due to acquisition artefacts and aortic pathologies mimicking AD. The mean time to process and notify of potential AD cases was 27.9 ± 8.7 seconds. This deep learning-based application demonstrated strong performance in detecting and classifying aortic dissection cases, potentially enabling faster triage of these urgent cases in clinical settings.

This paper investigates the effect of innovative cross-sectional configurations on Low-Cost Bamboo Composite (LCBC) structural members. The study employs both experimental and numerical methods with different resin matrices and bamboo species. In this study, LCBC short columns are designed with different innovative cross-sectional configurations in an attempt to overcome the costly production processes of engineered bamboo. This approach uses bundles of bamboo, both in culm and strip forms. A compatible, environmentally responsible, and economically justifiable resin matrix is used to fabricate an LCBC member. The production of LCBC members does not necessitate highly advanced technology. This capability enables the production of LCBC members in custom-designed cross-sectional shapes and lengths. This study introduces the Russian doll (RD), Big Russian doll (BRD), Hawser (HAW), and Scrimber (SCR) cross-sectional configurations. Extra-large, large, medium, and small sizes of bamboo are employed. Synthetic Epoxy (EXP), a Bio-based Experimental soft filler (BE1), Bio-Epoxy (BE2), Furan-based (PF1) matrices are applied. Furthermore, Moso, Guadua, Madake, and Tali bamboo species are incorporated. The results of this study reveal that the most efficient cross-sectional configuration for compressive strength is the HAW configuration, closely followed by SCR configuration. LCBC members with bio-resins have shown excellent promise in competing in strength with those made with their synthetic counterparts. The theoretical and numerical modeling of the LCBC members showed excellent correlation with the experimental results which provides the capacity to design LCBC for engineering projects. The LCBC design can be further developed with more bamboo and less resin content.

As a service business models have been ranked by management consultants the management innovation of 2020, and yet are scarcely theorized. Therein, value stipulations in customer contracts lead to the shift from product to service. However, there is no available research about the nature, formula and decisional process about these value stipulations. The motive for this research is to fill in this gap. The goal is to provide first insight about value stipulations in as a service business models: their formula and decisional methodology. The article is a multiple theory building case study on leading platform as a service providers, which aims to contruct the paradigm of the value decision methodology to invest in this technology by purchasing it from dedicated vendors. The methodology works to identify the management instruments involved in the decisional activities to invest in digital technology, where each management instrument is assumed to match an activity at seller and buyer; the sequence of the activities using the Critical Path Method gives the decisional process. Dependent variables are the elements of the as a service business contracts: the customer offering (product-service solution) and the value created, captured and delivered by the solution. Independent variables are given by empirical data analysis. Findings show a relationship between dependent variable value in the as a service business model contracts and independent variables governance objective, strategy, as a service business model type, activity management techniques (roadmap, program, project, operations, lean start-up), capital allocation techniques (equity, debt, options, venture capital typology). If innovation is exploitative, then the customer offering is known and value is determinable via roadmap – project management techniques (program, project, an operations) and capital allocation techniques for precictable environment, If innovation is radical, then the customer offering is not known and value is a target used to architect the solution via lean start-up innovation techniques funded by venture capital. The contribution is a new theoretical construct and deep insight into the practice of digital transformation considering all inherent issues.

(1) Background: Adolescent well-being is a multifaceted construct embedded in family, school, and peer socialization contexts. By adopting a social-psychological perspective we test the association between three sources of support (parents, teachers, peers) and specific components of subjective well-being (cognitive, affective, global-and-domain-specific) to determine whether there is a functional specialization of the role that these crucial socialization agents play for adolescents to attain well-being in specific life domains. (2) Methods: Cross-sectional Albanian data from Wave 3 of the Children’s Worlds International Survey (www.isciweb.org) were used, including 2,339 adolescents (age range 9-13; girls = 49.3%). A structural equation model (SEM) was employed to explore associations between supportive relationships with parents, teachers, and peers and adolescent well-being. (3) Results: Findings support a functional specialization hypothesis as parental support was significantly related to global cognitive and affective well-being; teacher support was significantly related with school satisfaction; and significant relations were found between peer support and almost all well-being variables (context-free, domain-based life satisfaction and affective subjective well-being). (4) Conclusions: Findings contribute to a more nuanced understanding of the role of supportive relationships with adults and peers in adolescents’ proximal socialization contexts (family, school, peer groups) and specific components of subjective well-being.

This work presents first time successfully fabricated silica few-mode microstructured optical fiber (MOF) with hollow GeO2-doped ring core and strongly induced twisting up to 790 revolutions per meter. Some technological issues for manufacturing of GeO2-doped supporting elements for large hollow cores as well as described above complicated spun MOFs are discussed. We introduce some results of tests, performed for pilot samples of designed and manufactured described above untwisted and twisted MOFs with outer diameter 65 µm and hollow ring core inner diameter 30.5 µm under wall thickness 1.7 µm and refractive index difference n=0.030, including their geometrical parameters, basic transmission characteristics and measurements of far-field laser beam profile patterns.

This paper uses the numerical results of surveys sent to Huelva’s (Andalusia, Spain) households to determine the degree of knowledge they have about the urban water cycle, needs, values, and attitudes regarding water in an intermediary city with low water stress. In previous research, we achieved three different households’ clusters. The first one grouped households with high knowledge of the integral water cycle and a positive attitude to smart devices at home. The second cluster described households with low knowledge of the integral water cycle and high sensitivity to price. The third one showed average knowledge and predisposition to have a closer relationship with the water company. This paper continues with this research line, applying Classification and Regression Trees (CART) to determine which hierarchy of variables/factors/ independent components obtained from the surveys are the decisive ones to predict the range of household water consumption in Huelva. Positive attitudes towards improved cleaning habits for personal or household purposes are the highest hierarchy component to predict the water consumption range. Second in the hierarchy, the variable Knowledge Global Score about the integral urban water cycle, associated with water literacy, also contributes to predicting the water consumption range. Together with the three clusters obtained previously, these results will allow us to design water demand management strategies (WDM) fit for purpose that enable Huelva’s households to use water more efficiently.

With the unceasing advancement in wide-bandgap (WBG) semiconductor technology, the minimal reverse-recovery charge Qrr and other more powerful natures of WBG transistors enable totem-pole bridgeless PFC to become a dominant solution for energy storage systems (ESS). This paper focuses on design and implementation of a control structure for a totem-pole boost PFC with newfangled enhancement-mode Gallium Nitride (eGaN) FETs, not only to simplify the control implementation, but also to achieve high power quality and efficiency. The converter is designed to convert a 90-264-VAC input to a 385-VDC output for a 2.6-kW output power. Lastly, to validate the methodology, an experimental prototype is characterized and fabricated. The uttermost efficiency at 230 VAC attains 99.14%. The lowest total harmonic distortion in the current (ITHD) at high line condition (230 V) reaches 1.52% while the power factor gains 0.9985.

Exercise-based cardiac rehabilitation requires patients to perform a set of certain prescribed exercises a specific number of times. Local muscular endurance (LME) exercises are an important part of the rehabilitation program. Automatic exercise recognition and repetition counting, from wearable sensor data is an important technology to enable patients to perform exercises independently in remote settings, e.g. their own home. In this paper we first report on a comparison of traditional approaches to exercise recognition and repetition counting, corresponding to supervised machine learning and peak detection from inertial sensing signals respectively, with more recent machine learning approaches, specifically Convolutional Neural Networks (CNNs). We investigated two different types of CNN: one using the AlexNet architecture, the other using time-series array. We found that the performance of CNN based approaches were better than the traditional approaches. For exercise recognition task, we found that the AlexNet based single CNN model outperformed other methods with an overall 97.18% F1-score measure. For exercise repetition counting , again the AlexNet architecture based single CNN model outperformed other methods by correctly counting repetitions in 90% of the performed exercise sets within an error of ±1. To the best of our knowledge, our approach of using a single CNN method for both recognition and repetition counting is novel. In addition to reporting our findings, we also make the dataset we created, the INSIGHT-LME dataset, publicly available to encourage further research.

The cornerstone of molecular magnetism is a detailed understanding of the relationship between structure and magnetic behaviour, i.e. the development of magneto-structural correlations. Traditionally, the synthetic chemist approaches this challenge by making multiple compounds that share a similar magnetic core but differ in peripheral ligation. Changes in the ligand framework induce changes in the bond angles and distances around the metal ions which are manifested in changes to magnetic susceptibility and magnetisation data. This approach requires the synthesis of series of different ligands and assumes that the chemical/electronic nature of the ligands and their coordination to the metal, the nature and number of counter ions and how they are positioned in the crystal lattice, and the molecular and crystallographic symmetry have no effect on the measured magnetic properties. In short, the assumption is that everything outwith the magnetic core is innocent, which is a huge oversimplification. The ideal scenario would be to have the same complex available in multiple structural conformations, and this is something that can be achieved through the application of external hydrostatic pressure, correlating structural changes observed through high pressure single crystal X-ray crystallography with changes observed in high pressure magnetometry, in tandem with high pressure inelastic neutron scattering (INS), high pressure electron paramagnetic resonance (EPR) spectroscopy and high pressure absorption/emission/Raman spectroscopy. In this review, which summarises our work in this area over the last 15 years, we show that the application of pressure to molecule-based magnets can (reversibly): (1) lead to changes in bond angles, distances and Jahn-Teller orientations; (2) break and form bonds; (3) induce polymerisation/depolymerisation; (4) enforce multiple phase transitions; (5) instigate piezochromism; (6) change the magnitude and sign of pairwise exchange interactions and magnetic anisotropy and (7) lead to significant increases in magnetic ordering temperatures.

This paper describes a proposed fractional filter-based multi-scale underwater and hazy image enhancement algorithm. The proposed system combines a modified global contrast operator with fractional order-based multi-scale filters used to generate several images, which are fused based on entropy and standard deviation. The multi-scale-global enhancement technique enables fully adaptive and controlled colour correction and contrast enhancement without over exposure of highlights when processing hazy and underwater images. This in addition to illumination/reflectance estimation coupled with global and local contrast enhancement. The proposed algorithm is also compared with the most recent available state-of-the-art multi-scale fusion de-hazing algorithm. Experimental comparisons indicate that the proposed approach yields better edge and contrast enhancement results without halo effect, colour degradation and is faster and more adaptive than all other algorithms from the literature.

Given the importance of peroxisome proliferator-activated receptor (PPAR)-gamma in epidermal inflammation and carcinogenesis, we analyzed transcriptomic changes observed in epidermal PPARγ deficient mice (Pparg-/-epi). Gene set enrichment analysis revealed a close association with epithelial malignancy, inflammatory cell chemotaxis and cell survival. Single cell sequencing of Pparg-/-epi mice verified changes to the stromal compartment, including increased inflammatory cell infiltrates, particularly neutrophils and an increase in fibroblasts expressing myofibroblast marker genes. A comparison of transcriptomic data from Pparg-/-epi and publicly available human and or mouse actinic keratoses (AK) and cutaneous squamous cell carcinomas (SCCs) revealed strong correlation between the datasets. Importantly, PPAR signaling was the top common inhibited canonical pathway in AK and SCC. Both AKs and SCCs also had significantly reduced PPARG expression and PPARγ activity z-scores. Smaller reductions in PPARA expression and PPARα activity and increased PPARD expression but reduced PPARδ activation were also observed. Reduced PPAR activity was also associated with reduced PPARα/RXRα activity while LPS/IL1-mediated inhibition of RXR activity was significantly activated in the tumor datasets. Notably. these changes are not observed in normal sun-exposed skin relative to non-exposed skin. Finally, Ppara and Pparg were heavily expressed in sebocytes while Ppard was highly expressed in myofibroblasts, suggesting a role for PPARδ in myofibroblast differentiation. In conclusion, these data indicate PPARγ and possibly PPARα represent key tumor suppressors by acting as master inhibitors of the inflammatory changes found in AKs and SCCs.

(1) Background: Double-strand breaks (DSBs) in a single nucleus are usually measured using the sperm chromatin structure assay (SCSA), sperm chromatin dispersion (SCD) test, and comet assay (CA). We developed mono-dimensional single-cell pulsed-field gel electrophoresis (1D-SCPFGE) and angle-modulated two-dimensional single-cell pulsed-field gel electrophoresis (2D-SCPFGE) to observe DNA fragmentation in separated motile sperm. (2) Methods: We set up comparative standards, calibration curves, the required sensitivity, and eligibility criteria for test sperm to validate their measurement principles. (3) Results: We revealed that the conventional methods overlooked the interference of nucleoproteins in their measurements. In-gel proteolysis improves the measurement accuracies of 1D- and 2D-SCPFGE. We recommend using naked DNA for comparative standards and test specimens. Moreover, we have observed several dysfunctions that may induce DNA damage in the separated motile sperm. Overall, our discussion highlights the need to revisit the conventional univariable analyses based on the SCSA, SCD test, and CA. (4) Conclusions: Human infertility is a complex syndrome, and the aim of quality control in intracytoplasmic sperm injection is to identify the underlying dysfunctions remaining in the separated motile sperm that render them ineligible for injection. Well-designed, multivariable analyses with special consideration to confounding factors are necessary in future cohort studies.

The article studies and analyzes a hybrid power source system, lithium battery, and fuel cell assisted by flexible photovoltaic panels for hybrid electric vehicles (HEVs). The new configuration operates based on optimizing the performance of the dual power source to maximize the available energy and operating time. The operational mode simulates specific driving conditions in urban, peripheral, and intercity routes under variable driving patterns and traffic conditions. The simulation results show that the new configuration increases the hybrid electric vehicle performance, providing higher reliability despite the more complex design. The proposed system reduces the external power supply dependence and avoids unexpected sudden stops due to energy exhaustion. The new configuration also extends the vehicle driving range depending on driving mode and route conditions. The vehicle driving range extension may reach up to 276.3 km. The hybridization of fuel cells with lithium battery and PV panel assistance enhances battery management, reducing battery servicing and increasing lifespan. The proposed topology is cheaper than a single fuel cell power system by 17.2%, reducing the total cost related to the single battery power system if we consider the battery recharge for its entire lifespan. The cost saving is 2.6% for the American market and 14.8% for the European one.

Cognitive impairment is a condition which affects aging patient populations and is becoming more prevalent as the geriatric population expands. It is categorized by the extent of cognitive decline, memory loss, functional abilities, and the capability to perform daily tasks. Based on the degree of impairment, it is classified as mild cognitive impairment or dementia. Considering the debilitating nature of cognitive decline and its impact on quality of life, prevention is key. In addition, given the gradual progression of the underlying causes of cognitive decline, early diagnosis and appropriate management has the potential to offer clinical advantages and better patient outcomes. Management options discussed vary from pharmaceutical regimens to neurosurgical interventions, with differing outcomes based on etiology of cognitive impairment.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

The ability of recombinant, SARS-CoV-2 Spike (S) protein to modulate the production of two COVID-19 relevant, pro-inflammatory cytokines (IL-6 and IFN-γ) in PBMC cultures of healthy, pre-Covid-19 subjects was investigated. We observed that cytokine production was largely and diversely modulated by the S protein depending on antigen or mitogen stimulation, as well as on the protein source, insect (S-in) or human (S-hu) cells. While both proteins co-stimulated cytokine production by polyclonally CD3-activated T cells, PBMC activation by the mitogenic lectin Concanavalin A (Con A) was up modulated by S-hu protein and down-modulated by S-in protein. These modulatory effects were likely mediated by the S glycans as demonstrated by direct Con A-S binding experiments and use of yeast mannan as Con A binder. While being ineffective in modulating memory antigenic T cell responses, the S proteins and mannan were able to induce IL-6 production in unstimulated PBMC cultures and upregulate the expression of Mannose Receptor (CD206), a marker of anti-inflammatory M2 macrophage. Our data point to a relevant role of N-glycans, particularly N-mannosidic chains, decorating the S protein in the immunomodulatory effects here reported. These novel biological activities of the S glycan ectodomain may add to the comprehension of Covid-19 pathology and immunity to SARS-CoV-2.

Carbon footprint mitigation actions have become a key issue for companies involved in urban freight transport. The electrification of the delivery fleets is one of the crucial sustainable actions carried out. To this end, it is necessary to explore several fleet renewal strategies over a finite planning horizon evaluating different types of electric powertrains for light commercial vehicles. The primary goal of this purpose-built analysis is to assist and boost the fleet managers' decisions when transitioning to alternative-fuelled vans, intending to maximize cost savings and reduce greenhouse gas emissions inventory. The model presented in this work is a Multi-Objective Linear Programming hybrid analysis taking into account the vehicle and energy supply infrastructure costs and the emissions reported in each inventory scope following the Greenhouse Gas Protocol sustainability guidelines. From this perspective, the conducted research offers a novel approximation to fleet management problems enabling a break-down cost analysis and an evaluation of the annual emissions company report. The comprehensive numerical simulations carried out over different study scenarios in Spain demonstrate that the optimization approach does not only show effective fleet renewal strategies but also identifies critical factors that impact the fleet's competitiveness, offering valuable insights for fleet managers and policymakers to meet carbon footprint reductions in a cost-effectively way.

Perovskite solar cells have shown significant progress, but their commercialization remains hindered by lead-based toxicity. Many nontoxic perovskite-based solar cells have demonstrated potential such as Cs2AgBi0.75Sb0.25Br6, but their power-conversion efficiency is inadequate. To address this issue, some researchers are focusing on emerging acceptor-donor-acceptor'-donor-acceptor (A-DA'D-A) type non-fullerene acceptors (NFAs) for Cs2AgBi0.75Sb0.25Br6 to find effective electron transport layers for high-performance photovoltaic responses with low voltage drops. In this comparative study, four novel A-DA'D-A types NFAs such as BT-LIC, BT-BIC, BT-L4F, and were used as an electron transport layer (ETL) for the proposed devices, FTO/PEDOT: PSS/ Cs2AgBi0.75Sb0.25Br6/ETL/Au. Comprehensive simulations were conducted to optimize the devices. The simulations showed that all optimized devices exhibit photovoltaic responses, with the BT-BIC device having the highest power conversion efficiency (13.2%) and the BT-LIC device having the lowest (6.8%). The BT-BIC as ETL provides fewer interfacial traps and better band alignment, enabling greater open-circuit voltage for efficient photovoltaic responses.

Coffee processing generates a huge amount of waste which contains many natural products. Here, we report the discovery of a panel novel cell-penetrating and metal-ion binding microproteins designated coffeetide cC1a-c and cL1-6 from the husk of two popular coffee plants, Coffea canephora and Coffea liberica, respectively. Combining sequence determination and database search, we showed that the prototypic coffeetide cC1a is a 37-residue, eight-cysteine microprotein with a hevein-like cysteine motif but without a chitin-binding domain. NMR determination of cC1a revealed a compact structure that confers it resistance to heat and proteolytic degradation. Disulfide mapping together with chemical synthesis revealed that cC1a has a ginsentide-like, and not a hevein-like, disulfide connectivity. In addition, transcriptomic analysis showed that the 98-residue micrcoproten-like coffeetide precursor contains a three-domain arrangement like ginsentide precursors. Molecular modeling together with experimental validation revealed a Mg2+ and Fe3+ binding pocket at the N-terminus formed by three glutamic acids. Importantly, cC1a is amphipathic with a continuous stretch of 19 apolar amino acids, and which enables its cell penetration to target intracellular proteins, despite being highly negatively charged. Our findings suggest that coffee by-products could provide a source of ginsentide-like bioactive peptides that have potential to target intracellular proteins.

ORF6 is responsible for suppressing the immune response of cells infected by the SARS-CoV-2 virus. It is also the most toxic protein of SARS-CoV-2, and its actions are associated with the viral pathogenicity. Here we study in silico and in vitro the structure of the protein, its interaction with RAE1, and the mechanism of action behind its high toxicity. We show both computationally and experimentally that SARS-CoV-2 ORF6, embedded in the membranes of the endoplasmic reticulum, binds to RAE1 and sequesters it in the cytoplasm, thus depleting its availability in the nucleus and impairing nucleocytoplasmic mRNA transport. This negatively affects the cellular genome stability by compromising the cell cycle progression into the S-phase and by promoting the accumulation of RNA-DNA hybrids. Understanding the multiple ways in which ORF6 affects DNA replication may also have important implications for elucidating the pathogenesis of SARS-CoV-2 and developing therapeutic strategies to mitigate its deleterious effects on host cells.

The cytoplasmic membrane is the fundamental component of all living cells, which participates in various physiological processes, such as material exchange, stress response, cell recognition, signal transduction, cellular immunity, apoptosis, pathogenicity, etc. The normal function of a cytoplasmic membrane requires stable organization of transmembrane protein-lipid microdomains, transmembrane protein-cell wall microdomains, and cytoskeleton-transmembrane protein microdomains. Here, we review the mechanisms and functions of various membrane lipid components, fatty acid content and saturation, membrane curvature, and cell wall and cytoskeleton in plasma membrane homeostasis affecting the pathogenicity of pathogenic fungi. Pathogenic fungi maintains plasma membrane homeostasis and contributes to fungal virulence by maintaining plasma membrane assembly, structural and functional integrity of pathogenic fungi at various stages of cell development through interactions among lipid components of cytoplasmic membranes, transmembrane proteins, cytoskeleton and cell wall components, etc.

Background: Strong indicators of inflammation, such as C-reactive protein (CRP), hypersensitive CRP (hs-CRP), and a series of hematological indices, including platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), hematocrit (HCT) and red blood cell distribution width (RDW), are regarded related with the incidence of contrast induced nephropathy (CIN) closely. Whereas, it remains unclear whether they can function as predictors of CIN onset. The objective of this meta-analysis was to determine the relationship between above indicators and CIN incidence among patients receiving coronary intervention. Methods: Clinical studies were retrieved from the electronic databases of PubMed, EMBASE, Google Scholar, Clinical Trials, and science direct from their inception to June 3rd, 2020. Meta-analysis was performed on pool eligible studies. Two reviewers screened all titles and abstracts and independently assessed all articles. Results: A total of 26 studies involving 29,454 patients were included in the meta-analysis. Pooled analysis results revealed that patients with higher CRP (odds ratio [OR]=1.06, 95% confidence interval [CI]: 1.01–1.12, P=0.02), hs-CRP (OR=1.03, 95% CI: 1.01–1.06, P=0.004), NLR (OR=1.11, 95% CI: 1.01–1.20, P=0.02), RDW (OR=1.35, 95% CI: 1.19–1.53, P<0.00001), and lower HCT (OR=0.94, 95% CI: 0.92–0.97, P=0.0003) all exhibited significantly higher CIN rates, but there was no significant association between PLR and CIN risk (OR=1.12, 95% CI: 0.99–1.26, P=0.07). Conclusion: The meta-analysis reported here demonstrates that pre-angiography CRP/hs-CRP and some hematological indices are associated with CIN.

The world is moving to the next phase of the energy transition with high penetrations of renewable energy. Flexible and scalable redox flow battery (RFB) technology is expected to play an important role in ensuring electricity network security and reliability. Continuous performance improvements will further enhance their value by reducing parasitic losses and maximizing available energy conversion over broader operating conditions. Concentration overpotentials from poor internal reactant distribution at high and low states of charge (SOC) limit power densities and are thus an important area of investigation. However, efforts to address these coupled electrochemical phenomena can compromise mechanical performance. Modelling and simulation of cell design innovations have shown it is possible to reduce losses from pump energy while increasing the availability of active species where required. The combination of wedge-shaped cells with static mixers investigated in this paper can reduce pressure drop and improve energy efficiency. Toroidal vanadium redox flow battery (VRB/VRFB) designs incorporating this innovation are presented for further development to improve community engagement with the technology.

Extracellular vesicles (EVs) are involved in intercellular communication during carcinogenesis and cancer cells are able to secrete EVs, in particular exosomes containing molecules, that can be transferred to recipient cells to induce pathological processes and significant modifications, as metastasis, increase of proliferation and carcinogenesis evolution. FZD proteins, a family of receptors comprised in the Wnt signaling pathway, play an important role in carcinogenesis of gastroenteric tract. Here, a still unrecognized role of Frizzled 10 (FZD10) protein was identified. In particular, the presence of FZD10 and FZD10-mRNA in exosomes extracted from culture medium of the untreated colorectal, gastric, hepatic and cholangio cancer cell lines, was detected. A substantial reduction in the FZD10 and FZD10-mRNA level was achieved in FZD10-mRNA silenced cells and in their corresponding exosomes and, concomitantly a significant decrease in viability of the silenced cells compared to their respective controls was observed. Interestingly, the incubation of silenced cells with exosomes extracted from culture medium of the same untreated cells promoted a remarkable restoration of the cell viability and, also, of the FZD10 and FZD10-mRNA level, thus indicating that the FZD10 and FZD10-mRNA delivering exosomes may be potential messengers of cancer reactivation and play an active role in long-distance metastatization

Background: Recent developments in our understanding of the interactions between long non-coding RNA (lncRNA) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein-RNA interaction networks. Results: Analysis of alternative splicing events across 39 lncRNA wildtype and knockout RNA-sequencing datasets from three human cell lines: HeLa (Cervical Cancer), K562 (Myeloid Leukemia), and U87 (Glioblastoma), resulted in high confidence (fdr < 0.01) identification of 4432 skipped exon events and 2474 retained intron events, implicating 759 genes to be impacted at post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockout were specific to the cell type, in agreement with the finding that genes affected by alternative splicing also displayed enriched functions in a cell type specific manner. To understand the mechanism behind this cell-type specific alternative splicing patterns, we analyzed RNA binding protein (RBP)-RNA interaction profiles across the spliced regions. Conclusions: Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron-exon junctions, in a cell type specific manner. The cellular functions affected by alternative splicing were also affected in a cell type specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs due to altered titration of the RBPs from their target loci. We propose that such lncRNA sponges can extensively rewire the post-transcriptional gene regulatory networks by altering the protein-RNA interaction landscape in a cell-type specific manner.

Following an initial mechanical insult, traumatic spinal cord injury (SCI) induces a secondary wave of injury, resulting in a toxic lesion environment inhibitory to axonal regeneration. This review focuses on the glial cell line-derived neurotrophic factor (GDNF) and its application, also in combination with other factors and cell transplantations, for repairing the injured spinal cord. As recent decades of studies strongly suggest combinational treatment approaches hold the greatest therapeutic potential for the central nervous system (CNS) trauma, future directions of combinational therapies will also be discussed.

A comprehensive design framework is proposed for optimizing sparse MIMO (multiple-input, multiple-output) arrays to enhance multi-target detection. The framework emphasizes efficient utilization of antenna resources, including strategies for minimizing inter-element mutual coupling and exploring alternative grid-based sparse array (GSA) configurations by efficiently separating interacting elements. Alternative strategies are explored to enhance angular beamforming metrics, including beamwidth (BW), peak-to-sidelobe ratio (PSLR), and grating lobe limited field of view. Additionally, a set of performance metrics is introduced to evaluate virtual aperture effectiveness and beamwidth loss factors. The study employs the desirability function and explores optimization strategies for the partial sharing of antenna elements in multi-mode radar applications. A novel machine learning initialization approach is introduced for rapid convergence. Observations include the potential for peak-to-sidelobe ratio (PSLR) reduction in dense arrays and insights into GSA feasibility and performance compared to uniform arrays. The study validates the efficacy of the proposed framework through simulated and measured results. The study underscores the importance of effective sparse array processing in multi-target scenarios and highlights the advantages of the proposed design framework, offering clarity on sparse array efficiency and applicability in processing hardware providing clarity on its advantages over uniform and nonuniform arrays.

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, Random Forest), unsupervised learning models (K-means clustering), and neural networks (Multi-Layer Perceptron) to predict and identify ice formation patterns. Experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real-time, optimizes de-icing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance.

Introduction. “Vein definition” for locally advanced pancreatic ductal adenocarcinoma (LA PDAC) assumes portal-to-superior mesenteric vein (PV/SMV) unreconstructability due to tumor involvement or occlusion. Radical pancreatectomies with SMV resection without PV/SMV reconstruction are scarcely discussed in the literature. Retrospective analysis of 19 radical pancreatectomies for “low” LA PDAC with SMV and all its tributaries resection without PV/SMV reconstruction has shown zero mortality, overall morbidity – 56%, Dindo-Clavien – 3-10,5%, R0- rate – 82%, mean operative procedure time – 355±154 min, mean blood loss – 330±170 ml, delayed gastric emptying– 25%, clinically relevant postoperative pancreatic fistula – 8%. In three cases surgery was associated with superior mesenteric (n2) and common hepatic artery (n1) resection. Surgery was completed without vein reconstruction (n13) and with inferior mesenteric-to-splenic anastomosis (n6). There were no cases of liver, gastric, or intestinal ischemia. A specific complication of the SMV resection without reconstruction was 2-3 days-long intestinal edema (48%). Median overall survival – 25 months, median progression-free survival – 18 months. All the relapses, except two, were distant. The possibility of successful SMV resection without PV/SMV reconstruction can be predicted before surgery by CT-based reconstructions. The mandatory anatomical conditions for the procedure were: 1) preserved SMV-SV confluence; 2) occluded SMV for any reason (tumor or thrombus); 3) well-developed inferior mesenteric vein collaterals with dilated intestinal veins; 4) no right-sided vein collaterals, and 5) no varices in the upper abdomen. Conclusion: “Low” LA PDACs involving SMV with all its tributaries can be radically and safely resected in highly and specifically selected cases without PV/SMV reconstruction with an acceptable survival rate.

Introduction/Aim: Central sensitivity to thyroid hormones refers to the sensitivity of the hypothalamic-pituitary-thyroid (HPT) axis to changes in circulating free thyroxine (fT4). The relationship between fT4 levels and iodine intake is complex. The aim of the present study was to assess central sensitivity to thyroid hormones in pregnancy against iodine intake. Materials & Methods: One thousand one hundred two blood and urine samples were collected from pregnant women (with a mean age+SD of 30.4+4.6 years) during singleton pregnancies; women with known/diagnosed thyroid disease were excluded. Specifically, TSH & fT4 and 24-hour urinary iodine excretion (UI) were measured in each trimester and at two months postpartum. The Thyroid Feedback Quantile-based Index (TFQI) was calculated to assess central sensitivity to thyroid hormones. For the statistical analysis of TFQI by time period, analysis of variance (ANOVA) was used, while Pearson's correlation was used to assess TFQI versus UI. Results: The mean TFQI index ranged from -0.06 (first trimester) to -0.07 (two months postpartum), while the corresponding UI was 141 and 172 μg/L, respectively. The TFQI-UI correlation was negative (Pearson r: -0.325, p: 0.04 and r: -0.399, p: 0.023), for UI values over 250 μg/L, in the first and the third trimester of pregnancy, respectively. Discussion: TFQI is a new index reflecting central sensitivity to thyroid hormones. Lower TFQI indicates higher sensitivity to thyroid hormones. In our sample TFQI was inversely related to iodine intake, in the first trimester of pregnancy (the critical period of organogenesis) and the third trimester (the critical period of fetal growth). Thus, the observed changes in TFQI may reflect different ways of central action of thyroid hormones, according to the phase of pregnancy. The negative association between maternal TFQI (indicative of central sensitivity to thyroid hormone) and urine iodine levels during the third trimester of pregnancy may reflect the combined influence of maternal and fetal thyroid function. Our results are intriguing and have the potential to enhance our comprehension of the changes in the HPT axis’ function via variations in central sensitivity to thyroid hormones and its interplay with nutritional iodine status during pregnancy.

Hexakis(2-alkoxy-1,5-phenyleneimine) macrocycles were synthesized using a simple one−pot procedure through by precipitation−driven cyclization. The acetal−protected AB−type monomers, 2-alkoxy-5-aminobenzaldehyde diethyl acetals, underwent polycondensation in water or acid−containing tetrahydrofuran. The precipitation−driven cyclization based on imine dynamic covalent chemistry and π−stacked columnar aggregation played a decisive role in the one−pot synthesis. The progress of the reaction was analyzed by MALDI−TOF mass spectrometry. The macrocycles with alkoxy chains were soluble in specific organic solvents such as chloroform, allowing their structures to be analyzed by NMR. The shape−anisotropic, nearly planar, and persistent macrocycles aggregated into columnar assemblies in polymerization solvents, driven by aromatic π−stacking. The octyloxylated macrocycle OcO−Cm6 exhibited an enantiotropic columnar liquid crystal−like mesophase between 165°C and 197°C. In the SEM image of (S)-(−)-3,7-dimethyloctyloxylated macrocycle (−)BCO-Cm6, columnar substances with a diameter of 100−200 nm were observed. The polymerization solution for 2-(2-methoxyethoxy)ethoxy)ethoxylated macrocycle (TEGO−Cm6) gelled and showed thixotropic properties by forming a hydrogen bond network.

Over the years, machine learning has emerged as a tool for automated translation and has been studied relentlessly for decades. RBMT, SMT, and NMT models have been used to achieve machine translation and the results have drastically improved from when research in this field first began. Although a few general-purpose translators such as Google Translate or Microsoft Translator have accurate translations compared to that of a human translator, many pieces of text containing highly technical terms or homonyms are often mistranslated completely. When considering the necessity and importance of translating technical patents from different domains, accuracy in translation is not something that can be compromised. This motivates the need to improve the performance of machine translation further. The scope of this paper covers three open-source machine translation models for the purpose of patent documentation translation from English to Japanese, evaluates their performance on patent data, and proposes a methodology that enabled us to improve one of the model’s BLEU score by 41.22%, achieving a BLEU score of 46.18.

Fibroblast activation protein (FAP) is a membrane-tethered serine protease overexpressed in the reactive stromal fibroblasts of &gt; 90% human carcinomas, which makes it a promising target for developing radiopharmaceuticals for imaging and therapy of carcinomas. Here, we synthesized two novel (R)-pyrrolidin-2-yl-boronic acid-based FAP-targeted ligands; SB02055 (DOTA-conjugated (R)-(1-((6-(3-(piperazin-1-yl)propoxy)quinoline-4-carbonyl)glycyl)pyrrolidin-2-yl)boronic acid) and SB04028 (DOTA-conjugated ((R)-1-((6-(3-(piperazin-1-yl)propoxy)quinoline-4-carbonyl)-D-alanyl)pyrrolidin-2-yl)boronic acid). natGa- and 68Ga-complexes of both ligands were evaluated in preclinical studies and compared to previously reported natGa/68Ga-complexed PNT6555. Enzymatic assays showed that FAP binding affinities (IC50) of natGa-SB02055, natGa-SB04028 and natGa-PNT6555 were 0.41±0.06, 13.9±1.29 and 78.1±4.59 nM, respectively. PET imaging and biodistribution studies in HEK293T:hFAP tumor-bearing mice showed that while [68Ga]Ga-SB02055 presented with a nominal tumor uptake (1.08±0.37 %ID/g), [68Ga]Ga-SB04028 demonstrated clear tumor visualization with ~1.5-fold higher tumor uptake (10.1±0.42 %ID/g) compared to [68Ga]Ga-PNT6555 (6.38±0.45 %ID/g). High accumulation in the bladder indicated renal excretion of all three tracers. [68Ga]Ga-SB04028 displayed low background level uptake in most normal organs, and comparable to [68Ga]Ga-PNT6555. However, since its tumor uptake was considerably higher than [68Ga]Ga-PNT6555, the corresponding tumor-to-organ uptake ratios for [68Ga]Ga-SB04028 were also significantly greater than [68Ga]Ga-PNT6555. Our data demonstrate that (R)-(((quinoline-4-carbonyl)-D-alanyl)pyrrolidin-2-yl)boronic acid is a promising pharmacophore for the design of FAP-targeted radiopharmaceuticals for cancer imaging and radioligand therapy.

In synthetic diamond plate, the intrapulse correlated dynamics of self-phase modulation and spontaneous Raman scattering by optical phonons were for the first time directly investigated for tightly focused (focusing numerical aperture NA = 0.25) positively-chirped visible-range ultrashort laser pulses with variable durations (0.3-9.5 ps) and energies, transmitted through the sample. The observed modulation of the transmitted light spectra and Stokes Raman scattering spectra for the different pulse durations were related to nonthermal excitation of nonlinear phonon polarization and its eventual picosecond-scale suppression due to thermal decay of optical phonons on the timescale of electron-phonon thermalization in the material.

It is known that the elastic characteristics of polyamides change with increasing temperature, in particular, the Young's modulus decreases significantly. This fact is practically not taken into account in design calculations of metal-polymer plain (MP) bearings, operating under conditions of the boundary and dry friction. The purpose of the study is the analysis of the effect of temperature on the change of the Young's modulus and, accordingly, the contact strength and triboresource according to the developed method of calculating MP bearings. MP bearings with a bushing made of polyamide PA6 reinforced with glass or carbon dispersed fibers were investi-gated. Quantitative and qualitative regularities of change of the maximum contact pressures and resource of the bearings at temperature increase under conditions of boundary and dry friction are established. The pressures in the bearing bushing made of PA6+30GF will be lower than for the bushing made of PA6+30CF. The resource of the bushing made of PA6+30CF will be significantly greater than for PA6+30GF. For thermoplastic polymers, the increase in temperature will have a useful practical effect due to the decrease in the rigidity of the polymer composites of the bearing bushing.

Viral infections leading to inflammation have been implicated in several common diseases such as Alzheimer’s disease (AD) and type 1 diabetes (T1D). Of note, herpes simplex virus 1 (HSV-1) has been reported to be associated with AD. We sought to identify the transcriptomic changes due to HSV-1 infection and anti-viral drug (acyclovir, ACV) treatment of HSV-1 infection in dissoci-ated cells from human cerebral organoids (dcOrgs) versus stem cell-derived pancreatic islets (sc-islets) to gain potential biological insights into the relevance of HSV-1-induced inflammation in AD and T1D. We observed that differentially expressed genes (DEGs) in HSV-1-infected sc-islets were enriched for genes associated with several autoimmune diseases, most significantly T1D but also rheumatoid arthritis, psoriasis, Crohn’s disease, and multiple sclerosis, whereas DEGs in HSV-1-infected dcOrgs were exclusively enriched for genes associated with AD. ACV treatment of sc-islets did not rescue transcript expression of autoimmune disease-associated genes. Finally, we identified gene ontology categories that were enriched for DEGs that were in common across, or unique to, viral treatment of dcOrgs and sc-islets, such as categories involved in the transferase complex, mitochondrial and autophagy function. Collectively, this studies pro-vide insight to the molecular effects of inflammation in AD and T1D.

Recent developments in microfluidics and biomaterials have enabled the creation of organs-on-chips (OoCs), which provide a controlled and lifelike in vitro microenvironment resembling an actual organ. Organ-on-a-chip technology offers a tremendous opportunity for efficient, cost-effective, and ethical drug testing and research. However, the high throughput and large quantities of data these complex microenvironments produce make it difficult for researchers to effectively analyze the data and draw valuable conclusions. Convolutional Neural Networks (CNNs) are most aptly positioned to address many of OoC’s challenges because of their ability to interpret microscopic images and facilitate the analytical process. Despite the growing field of AI, there have been a limited number of studies summarizing the various applications of CNNs in OoCs. This review aims to provide 1) an overview of the technology involved with CNNs and OoCs 2) an insight into the state-of-the-art applications of CNNs in OoCs including device parameters, predicting and tracking cell trajectories, super-resolution image segmentation, and image classification, and 3) an overview of existing challenges and opportunities ahead for clinical translation of this technology. Various applications of CNNs have been classified by the type of task. Different CNN models such as Faster R-CNNs, fully convolutional networks (FCNs), and Mask R-CNNs are explained and highlighted. This review article can be used as a resource for a better understanding of the potential of CNNs in biomedical research and clinical applications, particularly OoCs.

CAR-T cell therapy has emerged as a groundbreaking approach in cancer treatment, leveraging the immune system to target and eliminate cancer cells. While currently focused on hematologic malignancies, the future holds promise for expanding CAR-T cell therapy to diverse cancers, enhancing its efficacy, and improving safety profiles. Recent advances in tumor immunology have propelled CAR-T cell therapy as a game-changer in treating diseases such as relapsed/refractory B-cell acute lymphocytic leukemia (B-ALL), non-Hodgkin lymphoma (NHL), and multiple myeloma (MM). Six CAR-T cell products have received FDA approval for treating R/R B cell malignancies. However, challenges persist, including complications like cytokine release syndrome (CRS), coagulopathy, and cytopenias. Strategies to mitigate these complications involve targeting distinct antigens with dual- or multi-targeted CAR-T cells and enhancing immunogenicity. Additionally, γδ CAR-T cells show promise in recognizing antigen- negative leukemia cells in an MHC-independent manner while reducing the risk of inducing graft-versus-host disease (GVHD). As CAR-T cell therapy continues to evolve through innovation and discovery, it holds the potential to revolutionize cancer treatment, offering new hope to patients and reshaping the landscape of oncology with its precision and efficacy.

The design and integration of intelligent energy management systems in hybrid Electric Vehicle (EV) charging stations, leveraging Industry 4.0 and renewable energy sources, is crucial for advancing sustainability, efficiency, and technological development. This paper introduces a pioneering hybrid EV charging station that employs hybrid power sources, combining photovoltaic panels, a battery, and a fuel cell, each operating at 240V and 14A. Utilizing wireless power transfer technology, the system comprises five integral blocks: a power source, a boost converter, a High-Frequency (HF) inverter, transfer coils, and EV batteries. The optimization process involves two key stages: i) maximum power point tracking optimization of the boost converter, ensuring maximum power generation by varying the duty cycle between 10% and 90%, and ii) the HF phase employing a class-ϕ2 inverter at 30 MHz, synchronized with the resonant frequency of wireless power transfer coils. Control is executed through a digital signal processor card utilizing zero-voltage switching for efficient operations. This design enhances sustainability in EV charging solutions by optimizing power transfer through the use of hybrid sources.

In our study, we investigated the prognostic significance of hematological markers—NLR (Neutrophil-to-Lymphocyte Ratio), PLR (Platelet-to-Lymphocyte Ratio), and RDW-CV (Red Blood Cell Distribution Width - Coefficient of Variation)—in 117 glioblastoma patients. Data collected from January 2016 to December 2018 included demographics, clinical scores, and treatment regimens. Unlike previous research, which often examined these markers solely before surgery, our unique approach analyzed them at multiple stages: preoperative, postoperative, and before adjuvant therapies. We correlated these markers with overall survival (OS) and progression-free survival (PFS) using statistical tools, including ANOVA, Cox regression, and Kaplan-Meier survival analyses, employing SPSS version 29.0. Our findings revealed notable variations in NLR, PLR, and RDW-CV across different treatment stages. NLR and PLR decreased after surgery, with some stabilization post-STUPP phase (NLR: p=0.007, η2p=0.06; PLR: p=0.001, η2p=0.23), while RDW-CV increased post-surgery and during subsequent treatments (RDW-CV: p &lt; 0.001, η2p=0.67). Importantly, we observed significant differences between the preoperative phase and other treatment phases. Additionally, higher NLR and RDW-CV at the second-line treatment and disease progression were associated with an increased risk of death (NLR at 2nd line: HR=1.03, p=0.029; RDW-CV at progression: HR=1.14, p=0.004). We proposed specific marker cutoffs that demonstrated significant associations with survival outcomes when applied to Kaplan-Meier survival curves (NLR at 2nd line &lt; 5: p&lt;0.017; RDW-CV at progression &lt; 15: p=0.007). Elevated NLR and RDW-CV at later treatment stages correlated with poorer OS and PFS. No significant preoperative differences were detected. These biomarkers may serve as non-invasive tools for glioblastoma management.

Rapid increase in urbanization and industrialization due to increase in human population has led to increase in global warming resulting to climate change that affects the ecosystem. Unusual natural disasters such as cyclones, storms, floods, weather fluctuations, rising seal levels, transitional ecosystems and coastal disruptions are major adverse effects of climate change. There are huge worrisome concerns and uncertainties about the future of the planet earth due to climate change caused by high carbon emissions. Global aggressive policies in control of Carbon-dioxide (CO2) emissions from several combustion mechanisms have paved way for alternative/ clean energy sources. Green hydrogen is a promising means of clean energy sources for commercial power generation stations and other crucial systems such as hydrogen fuel cell vehicles (HFCVs) , motors, drives, backup power for buildings, and also serving as a source of electrical energy for remote locations. The goal of this study is to review the current level of Sub-Saharan African nations’ preparedness to adopt green hydrogen as a way to mitigate local energy supply issues and strengthen their individual economies.

Several factors impact the durability of concrete bridge decks, including traffic loads, fatigue, temperature changes, environmental stress, and maintenance activities. Detecting problems such as corrosion, delamination, or concrete degradation early on can lower maintenance costs. Nondestructive evaluation (NDE) techniques can detect these issues at early stages. Each NDE method, meanwhile, has limitations that reduce the accuracy of the assessment. In this study, multiple NDE technologies were combined with machine learning algorithms to improve the interpretation of half-cell potential (HCP) and electrical resistivity (ER) measurements. A parametric study was performed to analyze the influence of five parameters on HCP and ER measurements, such as degree of saturation, corrosion length, delamination depth, concrete cover, and moisture condition of delamination. The results were obtained through finite element simulations and used to build two machine learning algorithms, a classification algorithm and a regression algorithm, based on the Random Forest methodology. The algorithms were tested using data collected from a bridge deck in the BEAST® facility. Both machine learning algorithms were effective in improving the interpretation of ER and HCP measurements using data from multiple NDE technologies.

Tumour microenvironment, composed of pro- and anti-tumour immune cells, affects cancer cells behaviour. We aimed to evaluate if tumour-infiltrating lymphocyte (TIL) density and TILs subtypes in core biopsies at diagnosis of breast cancer patients could predict pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably anti-tumour (CD8+, CXCL13+) and pro-tumour (PD-1+, FOXP3+) immune cells. A prospective, non-interventional study including 171 participants undergoing NST was performed. The median TIL density for the entire cohort was 10% (IQR: 3.5-23.8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably). In the multivariable logistic regression model, TIL density was an independent predictor of pCR (p=0.012, OR 1.27; 95% CI 1.05-1.54) when controlled for age (p=0.232), Ki-67 (p=0.001), node-negative status (p=0.024), and HER2+/triple negative vs luminal B-like subtype (p&lt;0.001). In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR. In conclusion, TIL density and its subtypes are associated with pCR.

In the past decade, targeted therapies for solid tumors, including non-small cell lung cancer (NSCLC), have advanced significantly, offering tailored treatment options for patients. However, individuals without targetable mutations pose a clinical challenge, as they may not respond to standard treatments like immune-checkpoint inhibitors (ICIs) and novel targeted therapies. While the mechanism of action of ICIs seems promising, the lack of a robust response limits their widespread use. Although the expression levels of programmed death ligand 1 (PD-L1) on tumor cells are used to predict ICI response, identifying new biomarkers, particularly those associated with the tumor microenvironment (TME), is crucial to address this unmet need. Recently, inflammatory cytokines such as interleukin-1 beta (IL-1β) have emerged as a key area of focus and hold significant potential implications for future clinical practice. Combinatorial approaches of IL-1β inhibitors and ICIs may provide a potential therapeutic modality for NSCLC patients without targetable mutations. In this review, we discuss the role of IL-1β in NSCLC, its involvement in inflammatory pathways, and explore its potential role in the treatment of NSCLC.

Engineered nanomaterials (ENMs) are of significant relevance due to their unique properties, which have been exploited for widespread applications. Cerium oxide nanoparticles (CeO2-NPs) are one of most exploited ENM in the industry due to their excellent catalytic and multi-enzyme mimetic properties. Thus, toxicological effects of these ENMs should be further studied. Acute and subchronic toxicity of CeO2-NPs were assessed. First an in vitro multi-dose short-term (24h) toxicological assessment was performed in three different cell lines: A549 and Calu3, representing the lung tissue, and 3T3 as an interstitial tissue model. After that, a sub-chronic toxicity assessment (90 days) of these NPs was carried out on a realistic and well stablished reconstituted primary human airway epithelial model (MucilAir™), cultured at the Air-Liquid Interface (ALI), to study long-term effects of these particles. Results showed minor toxicity of CeO2-NPs in acute exposures. However, in subchronic exposures, cytotoxic and inflammatory responses were observed in the human airway epithelial model after 60 days of exposure to CeO2-NPs. These results suggest that acute toxicity approaches may underestimate the toxicological effect of some ENM, highlighting the need of subchronic toxicological studies in order to accurately assess the toxicity of ENM and their cumulative effects in the organism.

Distributed deformation based on Fiber Bragg Grating sensors or other kinds of strain sensors can be used to evaluate safety in operating periods of bridges. However, most of the published researches about distributed deformation monitoring are focused on solid rectangular beam rather than box girder—a kind of typical hollow beam widely employed in actual bridges. Considering that the entire deformation of a single-cell box girder contains not only bending deflection but also two additional deformations respectively caused by shear lag and shearing action, this paper again revises the improved conjugated beam method (ICBM) based on the LFBG sensors to satisfy the requirements for monitoring two mentioned additional deformations. The best choice for the LFBG sensor placement in box gilder is also proposed in this paper due to strain fluctuation on flange caused by shear lag effect. Results from numerical simulations show that most of the theoretical monitoring errors of the revised ICBM are 0.3%~1.5%, and the maximum error is 2.4%. A loading experiment for a single-cell box gilder monitored by LFBG sensors show that most of the practical monitoring errors are 6%~8%, and the maximum error is 11%.

All cancer registries constantly show striking differences in cancer incidence by age and among tissues. For example, lung cancer is diagnosed hundreds of times more often at age 70 than at age 20, and this cancer in nonsmokers occurs thousands of times more frequently than heart cancer in smokers. An analysis of these differences using basic concepts in cell biology indicates that cancer is the end-result of the accumulation of cell divisions in stem cells. In other words, the main determinant of carcinogenesis is the number of cell divisions that the DNA of a stem cell has accumulated in any type of cell from the zygote. Cell division, process by which a cell copies and separates its cellular components to finally split into two cells, is necessary to produce the large number of cells required for living. However, cell division can lead to a variety of cancer-promoting errors, such as mutations occurring during DNA replication, chromosome aberrations arising during mitosis, errors in the distribution of cell-fate determinants between the daughter cells, and failures to restore physical interactions with other tissue components. Some of these errors are spontaneous, others are promoted by endogenous DNA damage occurring during quiescence, and others are influenced by pathological and environmental factors. The cell divisions required for carcinogenesis are primarily caused by multiple local and systemic physiological signals rather than by errors in the DNA of the cells. As carcinogenesis progresses, the accumulation of DNA errors promotes cell division and eventually triggers cell division under permissive extracellular environments. The accumulation of cell divisions in stem cells drives not only the accumulation of the DNA alterations required for carcinogenesis, but also the formation and growth of the abnormal cell populations that characterize the disease. This model of carcinogenesis provides a new framework for understanding the disease and has important implications for cancer prevention and therapy.

The exploring comprehensive review of cutting-edge techniques for securing cloud-stored data and managing sensitive information in the context of smart cities through the application of Ciphertext-Policy Attribute-Based Encryption (CP-ABE). It highlights the innovative integration of blockchain technology with CP-ABE, which introduces a decentralized and tamper-resistant key management system, thereby enhancing the overall security framework in cloud environments where data sharing is prevalent. Introducing an online/offline multi-authority CP-ABE scheme, characterized by hidden policies, offers significant advancements in protecting user attributes and access structures, ensuring that sensitive information remains confidential even during encryption and decryption processes. This dual approach not only fortifies security but also optimizes the efficiency of data-sharing mechanisms. Furthermore, the paper delves into implementing hidden sensitive policies and keyword search techniques within smart city infrastructures, which are designed to facilitate secure and efficient data retrieval. These techniques ensure that while data remains accessible to authorized users, privacy is rigorously maintained. Collectively, these approaches represent significant strides in bolstering the security and confidentiality of data in both cloud-based and smart city applications, addressing the growing demand for robust and efficient data management solutions in increasingly interconnected environments.

Keywords: Artificial Intelligence in Implantology; AI in Dental Implantology; Machine Learning in Dental Implantology; Deep Learning in Implant Dentistry; Robotics in Dental Implantology; AI-Based Implant Planning.