SLM Additive Manufacturing has demonstrated great potential for aerospace applications when structural elements of individual design and/or complex shape need to be promptly supplied. 3D-printable AlSi10Mg (RS-300) alloy is widely used for the fabrication of different structures in aerospace industry. The importance of the evaluation of residual stresses that arise as a result of complex 3D-printing process thermal history is widely discussed in literature, but systematic assessment remains lacking for their magnitude, spatial distribution, and comparative analysis of different evaluation techniques. In this study we report the results of a systematic study of residual stresses in a 3D-printed double tower shaped samples using several approaches: the contour method, blind hole drilling laser speckle interferometry, X-ray diffraction, and Xe pFIB-DIC micro-ring-core milling analysis. We show that a high level of tensile and compressive residual stresses is inherited from SLM 3D-printing and retained for longer than 6 months. The stresses vary over a significant proportion of the material yield stress. All residual stress evaluation techniques considered returned comparable values of residual stresses even regardless of dramatically different dimensional scales from millimeters for the Contour Method down, laser speckle interferometry and XRD and down to small fractions of a mm (70 μm) for Xe pFIB-DIC ring-core drilling. The use of residual stress evaluation is discussed in the context of optimizing the printing strategy to enhance the mechanical performance and long-term durability.

Intrinsically Disordered Proteins (IDPs) play crucial roles in signal transduction, cell differentiation, and transcriptional regulation. Many disrupted genes associated with mental disorders are identified as IDPs, and emerging evidence suggests the functional role of IDPs in neuropsychiatric disorders. However, few studies comprehensively explore the functional association between protein disorder properties and different mental diseases. To address this gap, we collected disrupted gene sets for seven mental diseases (MDD, SCZ, BP, ID, AD, ADHD, ASD) and a control gene set from normal brains using DisGeNET and GeneCards databases. The state-of-the-art predictor IUPred2A was then utilized to calculate the disorder properties , followed by a thorough comparison between the disordered proteins in mental diseases and healthy controls. Functional enrichment analysis and protein-protein interaction networks were conducted to investigate the IDPs’ functional roles in psychiatric diseases. Additionally, we demonstrated the role of IDPs in protein binding formations through a case study of alpha-synuclein using protein docking. Our findings reveal that differentially expressed proteins in mental disorders, especially in ASD and ADHD, exhibit more IDPs than those in healthy controls. IDPs in psychiatric disorders are significantly enriched in neurodevelopmental pathways and play an important role in in gene expression regulation. Our results indicate distinct functional patterns of disorder proteins among mental diseases and healthy controls. When comparing the IDPs between ASD and ADHD, we observed that IDPs in ADHD are more likely linked to the synaptic signaling and regulation, while IDPs in ASD are more tendentiously related to diverse and complex biological processes. Our work offers valuable insights into the important functions of IDPs in psychiatric disorders, enhancing our understanding of the molecular mechanisms involved in psychiatric disorders.

The classical Einstein’s Field Equation has been derived previously by demanding that the Clausius relation dS = δQ/T holds. In this letter, we show that the semiclassical Einstein’s Field Equation can be recovered using the generalized entropy Sgen by using the non-equilibrium thermodynamics where the Clausius relation is replaced by the entropy balance relation dS = δQ/T +diS, where diS is some internal entropy. Moreover, since the quantum fields violate the classical focusing, we, therefore, have to use quantum focusing in this case. Using then Jacobson’s idea of thermodynamics of spacetime we recover the semiclassical equation of motion. We, therefore, in a sense also show the validity of the semiclassical approximation, a crucial approach for establishing a number of important ideas such as the Hawking effect.

Nasal polyposis is defined by a Th2-driven chronic inflammation of the nose and sinus with polyps visible in the nasal fossae. It is a prevalent disease with a significant impact on the HRQL. Allergy, allergic rhinitis, asthma, and aspirin intolerance are frequently associated. The management is individual. The first line of treatment is a long-term treatment with intranasal corticosteroids. Oral corticosteroids should be used with caution. When the medical treatment fails the patient is eligible for sinus surgery. In case of symptomatic recurrence after both medical treatment and ethmoidectomy, biologics are nowadays a very promising treatment effective on all the respiratory tract. Dupilumab seems in the literature the molecule of choice. However, besides the international guidelines published by EPOS and Euforea, the molecule prescribed depends also on the availability of it in each country and the criteria edited by the health authorities to get reimbursement. Long treatment is mandatory. Traditional medical treatment is necessary as a complement to biologics.

This paper investigates women’s empowerment and their active involvement in governance aimed at promoting sustainable development. The study focuses on examining the roles and processes of co-creation of nature-based solutions (NBS) for water management in Milan. Three research directions were explored: 1) to determine gender-based roles within local governance; 2) to detect semantic groups of NBS based on stakeholders' gender; c) to analyze gender-based linguistic and conceptual patterns of NBS. To achieve our objectives, we converted a sample of audio-video interviews of local stakeholders into textual data along with metadata indicating speakers' roles and gender. Descriptive statistics were applied to explore the governance's roles. We employed a combination of textual analysis and network analysis to identify thematic groups of NBS, and applied a word embedding approach to uncover linguistic patterns indicative of semantic sub-structures. The findings revealed significant demographic diversity. Male stakeholders perceive sustainable development as a process driven by the circular economy and the coordination of territorial authorities, while female stakeholders envision a transformative approach rooted in science, culture, and collaboration. The semantic sub-structure analysis highlighted a tendency among male governance to emphasize specialized skills, whereas female governance placed greater emphasis on problem definition rather than resolution.

This general review assesses the impact of physical exercise on oxidative and nitrosative stress and the counteractive role of antioxidants, drawing from a systematic literature search up to March 2024 in databases like PubMed and Web of Science. The review highlights studies on the effect of exercise on the production of reactive oxygen species (ROS) and reactive nitrogen species (RNS) and antioxidant responses in both human and animal models based on rigorous inclusion and exclusion criteria. Due to the variety of exercise types and participants' characteristics, a narrative synthesis approach was adopted. The findings indicate that moderate exercise boosts antioxidant defenses, known as hormesis, whereas excessive physical activity may increase oxidative and nitrosative damage. The review also explores the complex effects of antioxidant supplementation, revealing that while natural dietary antioxidants support health, high-dose supplements could potentially hinder positive adaptations to exercise. Recommendations for athletes and the general active population highlight the importance of balancing exercise and dietary intake to optimize health benefits. The review concludes with a call for more detailed research on tailored exercise and nutrition plans to dissect these intricate relationships further.

In higher education, the cultivation of research competency is pivotal for students’ critical thinking development and their subsequent transition into the professional workforce. While statistics plays a fundamental role in supporting the completion of a research project, it is often perceived as challenging, particularly by students in majors outside mathematics or statistics. The connection between students’ statistical proficiency and their research competency remains unexplored despite its significance. To address this gap, we utilized the supervised machine learning approach to predict students’ research competency, as represented by their performance in a research methods class, with predictors of students’ proficiency in statistical topics. Predictors relating to students’ learning behavior in a statistics course such as assignment completion and academic dishonesty are also included as auxiliary variables. Results indicate that the three primary categories of statistical skills—namely, understanding of statistical concepts, proficiency in selecting appropriate statistical methods, and statistics interpretation skills— can be used to predict students’ research competency, as demonstrated by their final course scores and letter grades. This study advocates for strategic emphasis on the identified influential topics to enhance efficiency in developing students’ research competency. Findings could inform instructors in adopting a strategic approach to teaching the statistical component of research for enhanced efficiency.

Composite fiber materials are superior materials due to their high strength and light weight. Composites reflect the properties of their constituents, which is proportional to the volume fraction of each phase. There are different fiber reinforcement types and each affects it’s flexural, tensile and compression strength. When selecting a composite for a specific application, the forces excreted on the composite must be known in order to determine the reinforcement type. Unidirectional fiber reinforcement will allow very strong load resistance but only in one direction where as a random orientated fiber reinforcement can resist less load but can maintain this quota in all directions. These materials are said to be anisotropic. Certain composite fibers, taking into consideration there weights, are physically stronger than conventional metals. This research deals with the analysis of three composite materials with different reinforcement types, volume fraction and phase content. It was found that material A (glass epoxy) was the strongest in the longitudinal direction with a flexural strength of 534 MPa in the longitudinal and 420 MPa in the transverse direction. The flexural stresses of material B (glass silicone) and material C (glass polyester) where both found in the 120 to 135 MPa range. Differences were due to their differences in matrix composition and reinforcement type.

Forest education is pivotal for achieving the Sustainable Development Goals and promoting sustainable forest management in the face of global challenges. However, existing programs struggle to keep up with rapidly changing crises and uncertainties that contribute to deforestation and forest degradation. To address these challenges, integrating innovative approaches into forest education is crucial. This paper demonstrates the transformative use of a role-playing game as an innovative teaching method for integrated forest management. The game provides students with practical experience and a comprehensive understanding of landscape approaches, using the Congo Basin as a case study. Our research focuses on sustainable forest governance, stakeholder roles, and valuing natural assets and ecosystem services, supporting the transformation of economic, political, and social/cultural relationships at various scales. We highlight the potential of innovative forest education to foster sustainability, trigger critical thinking, resolve conflicts, and prevent costly forest losses.

As an active device, air source heat pumps (ASHP) are widely used for heating and cooling in buildings. However, in cold regions, their efficiency decreases, and frost formation becomes a significant issue during winter. This paper proposes a new scheme that couples air source heat pumps with passive heating. By using software simulations and mathematical models, the new scheme is compared to traditional ASHP systems to analyze its heating performance in rural homes during winter in China’s cold regions. According to the simulation and calculation analysis, on the coldest day of winter, the coupling scheme can provide approximately 99.41kWh of heat to the interior, surpassing the 86.67kWh required to maintain an indoor temperature of 20℃. The system’s power consumption is 36.96 kWh, which is 66.88% lower than that of traditional heat pump heating. The study shows that a coupled system of air source heat pumps and passive heating has better heating performance in cold regions. By incorporating phase change materials and heat storage media to address the shortage of solar energy at night, the system can meet the heating needs throughout the entire day.

Detection and measurement of pain are crucial in designing effective pain management interventions to alleviate suffering and prevent functional decline in the medical domain. Traditional methods of pain identification rely on verbal patient reports or observable signs, which can be imprecise or subjective due to variability in patient self-assessments. Hence, there is a pressing need for automated methods to standardize pain measurement procedures. This paper proposes a novel facial expression-based automated pain assessment system as a behavioral indicator for pain evaluation. Our system integrates a fusion structure comprising Convolutional Neural Networks (CNNs) and Tensor-based extended Quantitative Expression Descriptors Analysis (TXQEDA). This innovative approach allows for joint learning of robust pain-related facial expression features from raw facial images, combining RGB appearance with shape-based latent representation. We extensively evaluated our proposed model using the UNBC-McMaster dataset for pain classification and intensity estimation. Our results demonstrate the efficacy of the proposed technique, achieving an impressive accuracy of 99.10% for pain level classification. Furthermore, our system excels in pain intensity estimation, showcasing its potential to provide precise and reliable assessments of pain severity. Overall, our research underscores the importance of automated pain assessment systems in improving patient care and clinical outcomes. By leveraging advanced deep learning techniques and fusion strategies, our proposed model offers a promising approach for standardizing pain measurement procedures and enhancing the quality of pain management interventions.

The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible paradigm. However, to date, the essential rationale for and analysis of classical reversible computing (RC) has not yet been expressed in terms that leverage the modern formal methods of non-equilibrium quantum thermodynamics (NEQT). In this paper, we begin developing an NEQT-based foundation for the physics of reversible computing. We use the framework of Gorini-Kossakowski-Sudarshan-Lindblad dynamics (a.k.a. Lindbladians) with multiple asymptotic states, incorporating recent results from resource theory, full counting statistics, and stochastic thermodynamics. Important conclusions include that, as expected: (1) Landauer's Principle indeed sets a strict lower bound on entropy generation in traditional non-reversible architectures for deterministic computing machines when we account for the loss of correlations; and (2) implementations of the alternative reversible computation paradigm can potentially avoid such losses, and thereby circumvent the Landauer limit, potentially allowing the efficiency of future digital computing technologies to continue improving indefinitely. We also outline a research plan for identifying the fundamental minimum energy dissipation of reversible computing machines as a function of speed.

Planar catechin (PCat), a natural antioxidant with a fixed 3D catechin structure on a plane, exhibits radical-scavenging activity approximately five times stronger than the conventional catechin. We synthesized a compound, PCat–TrOH, by binding Trolox (TrOH), an α-tocopherol analog, to PCat to enhance its antioxidant effect against oxidative stress, such as lipid peroxidation. TrOH shows radical-scavenging activity about 6.5 times greater than PCat, and PCat–TrOH exhibited a similar level of radical-scavenging activity to TrOH. Additionally, PCat–TrOH demonstrated twice the radical-scavenging activity against reactive oxygen species compared to PCat or TrOH. This compound is also expected to exhibit an excellent antioxidant effect against lipid peroxidation caused by radical chain reactions, through interactions with vitamin C, similar to that in the case of α-tocopherol.

Metallic nanoparticles (NPs), among polymeric NPs, liposomes, micelles, quantum dots, dendrimers, or fullerenes, are becoming more and more important due to their potential use in the novel medical therapies. Titanium dioxide (titanium(IV) oxide, titania, TiO2) is an inorganic compound that owes its recent rise in scientific interest to photoactivity. After the illumination in aqueous media with UV light, TiO2 produces an array of reactive oxygen species (ROS). The capability to produce ROS and thus induce cell death has found application in the photodynamic therapy (PDT) for the treatment of a wide range of maladies, from psoriasis to cancer. Titanium dioxide NPs were studied as photosensitizing agents in the treatment of malignant tumors as well as in photodynamic inactivation of antibiotic-resistant bacteria. Both TiO2 NPs themselves, as well as their composites with other molecules, can be successfully used as photosensitizers in PDT. Moreover, various organic compounds can be grafted on TiO2 NPs, leading to hybrid materials. These nanostructures can reveal increased light absorption allowing their further use in targeted therapy in medicine. In order to improve efficient anticancer therapy, many approaches utilizing titanium dioxide were tested. The most significant studies are discussed in this review.

Endemic freshwater fish from semiarid environments are among the most threated species in the world due to the water overexploitation and habitat fragmentation problems. Stepped or pool-type fishways are used worldwide to reestablish longitudinal connectivity and mitigate fish migration problems. Many of them are being installed or planned in rivers of semiarid environments, however, very few studies about fish passage performance through pool-type fishways has been carried out to date on these regions. The present work focuses on the passage performance of two potamodromous cyprinids endemic of these regions, with different ecological and swimming behavior: southern Iberian barbel (Luciobarbus sclateri) and Iberian straight-mouth nase (Pseudochondrostoma polylepis), in two of the most common types of stepped fishways: vertical slot and submerged notch with bottom orifice fishways. Experiments were carried out during the spawning season in the Segura River (South-Eastern Spain), using a PIT tag and antennas system. Ascent success was greater than 80%, with a median transit time lower than 17 minutes per meter of height in all trials and for both species and fishway types. Results show that both types of fishways, if correctly designed and built, provide interesting alternatives for the restoration of fish migration pathways on these regions.

The availability of current land cover and land use (LCLU) information for monitoring the status of land resources has considerable value in ensuring sustainable land use planning. Similarly, the need to provide updated information on the extent of LCLU change in West Africa has become apparent, given the increasing demand for land resources driven by the rapid population growth in the sub-region. SERVIR West Africa, a regional consortium jointly supported by USAID and NASA to foster the use of geospatial and earth observation data and science for decision-making on critical environmental and food security challenges, in collaboration with the Food and Agriculture Organization of the United Nations (FAO), is building technical capacity in the sub-region to develop and implement harmonized regional land cover classification system for LULC change monitoring in West Africa, based on the Land Cover Meta Language (LCML-ISO 19144-2). This article focuses on the process, potential opportunities, outputs of this collaboration, exemplary use cases, and recommendations for the next steps.

During the COVID-19 pandemic, the term “behavioural fatigue” became the centre of policy debates in Great Britain. These debates involved deciding when to go into lockdown and whether behavioural interventions could be effective. Behavioural interventions can only succeed where people’s capabilities, opportunities, and motivations to perform target behaviours are supported. Our retrospective data analyses examine the relationships between people’s capabilities, opportunities, motivations, and behaviours, i.e., adherence to lockdown guidelines. Our cross-sectional analyses include 17,962 unique participants in Great Britain who completed a survey over the initial 30 days of the first lockdown (April 2020). We examine trends in responses to each scale and then the relationships between the scales using Granger’s causality test with tests for stationarity and cointegration. A mixture of increasing and decreasing trends were identified for capabilities and opportunities. Decreasing trends were identified for motivation and behaviour. Granger’s causality tests found that capability forecasts opportunity and behaviour and that motivation forecasts opportunity. The discussion reiterates that to realize and maintain behaviour changes, policies surrounding people's capabilities, opportunities, and motivations must continue to support target behaviours.

Coaches are the main people who have an impact on the mental and psychological performance of athletes as well as their physical performance. The purpose of this study is to investigate the effect of perceived coaching behaviors on the anger and aggression levels of male athletes. This study was conducted with 748 male athletes with an active license who are over 18 years of age and participate in individual and team sports branches. In this study, the "Coaching Behavior Assessment Ques-tionnaire" and the “Competitive Aggressiveness and Anger Scale" were used as data collection tools. The study results showed that athletes’ levels of evaluation of the coaching behaviors were high, while the levels of aggressiveness and anger in sports were low. It was determined that there is a negative low-level relationship between the athletes’ evaluation levels of the coaching be-haviors and the aggressiveness and anger levels in sports and that the coach’s behaviors predict the anger and aggressiveness levels of the athletes by 9% and 6%, respectively. The results of this study show that the attitudes and behaviors of coaches can affect the emotional states of male athletes and have the potential to increase or decrease their anger and aggressiveness levels. Coaches who exhibit positive, supportive, and modeling behaviors help create a healthy sports environment and help male athletes maintain emotional balance.

Based on non-invasive neuroimaging techniques and graph theory-based network analyses, many researchers have tried to use small-world network model to elucidate sex differences in the brain. This manuscript aims to compile the related research findings from the past few years and summarize the sex differences in human brain networks from the perspective of small-world properties. We reviewed published reports examining altered small-world properties in both the functional and structural brain networks between males and females. Based on four patterns of altered small-world properties proposed--randomization, regularization, stronger small-worldization and weaker small-worldization, we found that current results point to a significant trend toward more regularization in females and more randomization in males in the functional brain networks. As for particular topological properties, the most consistent findings include a significant shift toward higher global efficiency in males and higher local efficiency in females in the functional network studies. On the other hand, there seems to be no consensus to date on the sex differences in small-world properties of the structural brain networks. Nevertheless, we noticed that the sample sizes in many published studies are limited, and future studies with larger samples are warranted to obtain more reliable results. We anticipate that the conclusions in this manuscript will contribute to a deeper understanding of neurobiological mechanisms underlying the sex differences in the brain.

Fine dust causes various disorders, including cardiovascular, neurological, renal, reproductive, motor, systemic, respiratory, and cancerous diseases. Therefore, it is necessary to study functional materials to prevent these problems. In this study we used various methods, including quantitative PCR, flow cytometry, ELISA, and Alizarin O staining, to study the beneficial effects of erucic acid against fine dust. Erucic acid and erucic acid-induced exosomes (EIE) strongly suppress the attenuation of osteocytic differentiation and inflammation induced by fine dust. Erucic acid effectively suppresses inflammation in fibroblasts exposed to fine dust. Notably, despite exposure to fine dust, EIE promoted osteocytic differentiation in adipose-derived stem cells (ASC) and osteogenesis in macrophages, in addition to phagocytosis. Dramatic upregulation of RunX2 and BMP7 by EIE indicates that it is a strong activator of osteocytic differentiation in ASC and protects them from the effects of fine dust. Moreover, EIE induces immune activity and acts as an osteogenic trigger for macrophages. Therefore, this study suggests the potential use of erucic acid and erucic acid-induced exosomes (EIE) as biomaterials to prevent environment-borne diseases.

The quality of healthcare services is a very important indicator of social welfare in developed and emerging countries. Good quality levels are critical to ensuring patient safety, improving health outcomes, increasing patient satisfaction, optimizing resource utilization, and meeting regulatory requirements. The stable and sustainable operation of medical institutions urgently requires the establishment of a reliable and effective medical quality performance evaluation platform. However, the complexity of the evaluation process, involving numerous evaluators and the consideration of different subjective and objective criteria, poses significant challenges and essentially constitutes a group multi-criteria decision-making problem. This article uses the overall medical environment of the institution, medical service attitude, medical security, administrative service measures, etc. as measurement standards to deal with this challenge. It proposes a medical service quality measurement model suitable for both qualitative and quantitative analysis. In view of the heterogeneity of information, the two-tuple fuzzy language calculation method is introduced to enable evaluators to skillfully manage diverse information and effectively avoid potential information omission problems in the subjective evaluation integration process. The effectiveness and feasibility of the model were demonstrated by applying it to the operational framework of a medical institution in central Taiwan.

Given the long-standing debate about the nature of the concept of disease, the objective of this study was to understand how doctors categorize a condition as a disease or not and what kind of information they use. A survey with a set of clinical vignettes was designed, and a group of physicians were asked to interpret those situations as a disease or not and to motivate their choice with a short written text. Thematic analysis of the answers resulted in four themes: the temporal dimension of a disease, reification of disease, disease as an existential condition, and disease as a motivation to action. The respondents’ interpretations were very heterogeneous, supporting the idea that physicians do not share a common prototypical concept of disease. An interpretation of these results according to a critical realist and systemic approach suggested that the doctor-patient relationship is the context able to influence the interpretation of a condition as a disease or not as the final outcome of a process in which both objective, subjective, and socially mediated elements are taken into consideration.

In recent years, additive manufacturing of products made from 5000 series alloys has grown in popularity for marine and automotive applications. In this work, we compare of mechanical properties characteristics of aluminum alloy 5056 material produced by wire-arc additive technology and rolling. We carried out tension tests under quasi-static loading and impact toughness tests under impact loading. The results show that upon similar ultimate tensile strength and ductility, material after additive manufacturing demonstrates decreased resistance against dynamic loading than material manufactured by the typical method of casting and rolling. This decrease in properties was explained through macro- and microstructure analysis.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) challenges include understanding what triggered SARS-CoV-2 emergence, how this RNA virus is evolving or how the genomic variability may impact the primary structure of proteins that are targets for vaccine. We analyzed 19471 SARS-CoV-2 genomes and 199,984 spike glycoprotein sequences available at the GISAID database from all over the world and 3335 genomes of other Coronoviridae family members available at Genbank, collecting SARS-CoV-2 high-quality genomes and distinct Coronoviridae family genomes. Here, we identify a SARS-CoV-2 emerging cluster containing 13 closely related genomes isolated from bat and pangolin that showed evidence of recombination, which may have contributed to the emergence of SARS-CoV-2. The analyzed SARS-CoV-2 genomes presented 9632 single nucleotide polymorphisms (SNPs) corresponding to a variant density of 0.3 over the genome, and a clear geographic distribution. SNPs are unevenly distributed throughout the genome and hotspots for mutations were found for the spike gene and ORF 1ab. We describe a set of predicted spike protein epitopes whose variability is negligible. All predicted epitopes for the structural E, M and N proteins are highly conserved. This result favors the continuous efficacy of the available vaccines.

Micronutrient deficiencies are a major public health problem. Beans are an important plant-based source of iron, zinc and copper, but their absorption is reduced in the presence of anti-nutrients such as phytates, polyphenols and tannins. Soaking and discarding the soaking water before cooking is unanimously recommended, but this can result in mineral loss. Data on the consequences for mineral bioaccessibility is still limited. This study aimed to evaluate iron, zinc and copper bioaccessibility in black beans cooked (regular pan, pressure cooker) with and without the soaking water. Minerals were quantified by ICP-MS, myo-inositol phosphates (InsP₅, InsP₆) by HPLC ion-pair chromatography, total polyphenols using Folin-Denis reagent and condensed tannins using Vanillin assay. Mineral bioaccessibility was determined by in vitro digestion and dialysis. All treatments resulted in a statistically significant reduction of total polyphenols (30%) and condensed tannins (20%). Only when discarding the soaking water a loss of iron (6%) and copper (30%) was observed, and InsP₆ was slightly decreased (7%) in one treatment. Bioaccessibility of iron and zinc were low (about 0.2% iron and 35% zinc), but copper presented high bioaccessibility (about 70%). Cooking beans under pressure without discarding the soaking water resulted in the highest bioaccessibility levels among all household procedures. Discarding the soaking water before cooking did not improve the nutritional quality of the beans.

Background Corpus callosum abnormalities (CCA) are midline developmental brain malformations and are usually associated with a wide spectrum of other neurological and non-neurological abnormalities. The study aims to highlight the diagnostic role of fetal MRI to characterize heterogeneous corpus callosum abnormalities using the latest classification system. It also helps to identify associated anomalies, which have prognostic implications on the postnatal outcome. Methods In this study, retrospective data from antenatal women who underwent fetal MRI between January 2014 and July 2023 at Rush University Medical Center were evaluated for CCA and classified based on structural morphology. Patients were further assessed for associated neurological and non-neurological anomalies. Results The most frequent class of CCA was complete agenesis (79.1%), followed by hypoplasia (12.5%), dysplasia (4.2%) and hypoplasia with dysplasia (4.2%). Amongst them, 17% had isolated CCA, while the majority (83%) had complex forms of CCA associated with other CNS and non-CNS anomalies. Out of the complex CCA cases, 58% were associated with other CNS anomalies, while 8% were associated with non-CNS anomalies. 17% of cases had both. Conclusion The use of fetal MRI is valuable in the classification of abnormalities of the corpus callosum after the confirmation of a diagnosis suspected on prenatal ultrasound. This technique is an invaluable method for distinguishing between isolated and complex forms of CCA, especially in the cases of apparent isolated CCA. The use of diffusion-weighted imaging or diffusion tensor imaging in fetal neuroimaging is expected to provide further insights into white matter abnormalities in fetuses diagnosed with CCA in the future.

Peroxiredoxins play central roles in the detoxification of reactive oxygen species and have been modelled across multiple organisms using a variety of kinetic methods. However, the peroxiredoxin dimer-to-decamer transition has been underappreciated in these studies despite the 100-fold difference in activity between these forms. This is due to the lack of available kinetics and theoretical framework for modelling this process. Using published isothermal titration calorimetry data, we obtained association and dissociation rate constants of 93.0 µM-4·s-1 and 102 s-1, respectively, for the dimer-decamer transition of human PRDX1. We developed an approach that greatly reduces the number of reactions and species needed to model the peroxiredoxin decamer oxidation cycle. Using these data, we simulated horse radish peroxidase competition and NADPH-oxidation linked assays and found that the dimer-decamer transition had an inhibition-like effect on peroxidase activity. Further, we incorporated this dimer-decamer topology and kinetics into a published and validated in vivo model of PRDX2 in the erythrocyte and found that it almost perfectly reconciled experimental and simulated responses of PRDX2 oxidation to hydrogen peroxide insult. By accounting for the dimer-decamer transition of peroxiredoxins, we were able to resolve several discrepancies between experimental data and available kinetic models.

The oncologic disease is a big global health issue that causes thousands of deaths annually, and it has a significant impact in the life quality of patients. Prostate cancer (PCa) is the second most diagnosed cancer and the fourth leading cause of cancer-related death in men in the western world. Delineation of pathogenetic pathways and key driver molecular alterations involved in PCa development has provided a roadmap for the evaluation of biomarkers in predicting disease outcome and to identify potential therapeutic targets. Chemotherapeutic agents introduced from the 1990s include the taxanes (paclitaxel, docetaxel and cabazitaxel), which are the most anticancer drugs used for PCa treatment. This review presents the current knowledge about the onset and development of PCa, state-of-art on the use of taxane-based therapy, and their combination with targeting different transmembrane oncoproteins in PCa. The silencing of some transmembrane proteins can improve taxane sensitivity, and therefore, may be a mechanism to improve the ef-fectiveness of these drugs in PCa treatment. This combined therapy needs to be explored as po-tential therapeutic agent for reducing cell proliferation, migration, and invasiveness in PCa.

Background: During the stay in the neonatal intensive care unit, parents play a crucial role in the care of their infants. Recent studies reported a decrease in parental participation due to Coronavirus Disease (COVID-19) pandemic that determined restricted access policies in hospitals. The aim of this study is to describe the barriers to a good parents’ participation during the stay in the neonatal intensive care unit in the COVID-19 era. Methods: A quantitative observational study was carried out. Results: 270 parents participated in this study. Mothers’ participation in care seems to be higher as compared to fathers (p = 0.017). Parents who lived the birth of their first child reported a better level of participation in care when compared to those who lived the birth of their second born (p = 0.005). Parents of extremely preterm neonates reported a lower interaction with their infant if compared to parents of term newborns (p < 0.001). Conclusions: Some more disadvantaged categories have reported lower scores: cultural and linguistic minorities, parents of multiple children and fathers. COVID-19 pandemic made several Family Centred Care activities not possible with a higher impact on those who benefited the most of these facilities. This study was prospectively registered by the IRB-CRRM of the University “G. d’Annunzio” Chieti-Pescara on the 23/01/2024 with registration number CRRM;2023_12_07_01.

External hoof characteristics, balance, and conformation have been extensively studied in horses; however, mules remain understudied in these aspects. This study evaluated the size, shape, and symmetry of untrimmed and unshod forelimb hooves, compared the symmetry between forelimb hooves and stratified external forelimb hoof measurements based on the body condition score of mules raised in the foothill plains of northern Thailand. The forelimb hooves of 38 mules were photographed and 33 parameters, including angular and linear measurements, were analyzed. Despite the absence of shoeing and trimming, these mules exhibited optimal left-right forelimb hoof symmetry, with no significant (p < 0.05) differences in: outer wall length and inner wall length (OWL - IWL); sole length and sole width (SLS - SW); dorsal hoof wall length and heel length (DHWL - HL); and frog length and frog width (FL - FW). However, significant (p < 0.05) differences were observed within each body condition score group for forelimb hoof measurements for DHWL, IWL, heel separation (HS), heel bulb distance (HBD), SW, FW, and FL. These findings provide valuable insights into mule welfare and management, contributing to understanding of the interplay between overall health and hoof conformation in the study area.

This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation-Impervious-Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study the urban environmental conditions of 47 neighborhoods of Porto Alegre city, Brazil. Porto Alegre has had the smallest population growth rate of all 27 state capitals in the last two decades in Brazil, with an increase of 11.55% in inhabitants from 1,263 million in 1991 to 1,409 million in 2010. We applied the environmental Kuznets curve (EKC) theory in order to test the influence of the economically-related scenario on the spatial nature of social-environmental arrangement of the city at neighborhood scale. Our results suggest that the economically-related scenario exerts a non-negligible influence on the physically driven characteristics of the urban environmental conditions as predicted by EKC theory. The linear inverse correlation R2 between household income (HI) and LST is 0.36 and has shown to be comparable to all other studied variables. Future research may investigate the relation between other economically-related indicators to specific land surface characteristics.

The result of the multidisciplinary collaboration of researchers from different areas of knowledge to validate a solar radiation model is presented. The MAPsol is a 3D local-scale adaptive solar radiation model that allows to estimate direct, diffuse and reflected irradiance for clear sky conditions. The model includes the adaptation of the mesh to complex orography and albedo, and considers the shadows cast by the terrain and buildings. The surface mesh generation is based on surface refinement, smoothing and parameterisation techniques and allows the generation of high quality adapted meshes with a reasonable number of elements. Another key aspect of the paper is the generation of a high-resolution digital elevation model (DEM). This high-resolution DEM is constructed from LiDAR data and its resolution if two times more accurate than the publicly available DEMs. The validation process uses direct and global solar irradiance data obtained from pyranometers at the University of Salamanca located in an urban area affected by systematic shading from nearby buildings. This work provides an efficient protocol for studying solar resources, with particular emphasis on areas of complex orography and dense buildings where shadows can potentially make solar energy production facilities less efficient.

Nowadays, diamonds are widely used in science and technology. However, the properties of diamonds due to their defects are not fully understood. In addition to optical methods, positron annihilation spectroscopy (PAS) can be successfully used to study defects in diamonds. Positrons are capable of detecting vacancies, small and large clusters of vacancies induced by irradiation, by providing information about their size, concentration, and chemical environment. By mapping in the infrared (IR) range, it is possible to consider the admixture composition of the main inclusions of the whole plate. The article presents the results of the study of defects in synthetic diamond plates, one of which was irradiated by electrons. Presents data about the distribution of the defect concentration obtained by Infrared spectroscopy. PAS with a monochromatic positron beam can be used as a non-destructive technique of detecting defects (vacancy) distribution over the depth of diamond plates.

Despite their obvious differences, biological systems at different scales tend to exhibit common organizational patterns. Unfortunately, these commonalities are usually obscured by the parcelled terminology employed by various scientific sub-disciplines. To explore these commonalities, this papers a comparative study of diverse applications of the maximum entropy principle, ranging from amino acids up to societies. By presenting these studies under a common language, this paper establishes a unified view over seemingly highly heterogeneous biological scenarios.

This study concerns calculation and comparison of Fe, Co, Ni and Cu deposition rates in tungsten codeposition process based on electrodeposition of numerous tungsten alloys. 8 different tungsten alloys containing from 2 to 5 metals were electrodeposited in constant conditions in order to compare exact reduction rates. Calculated rates enabled control of the alloy composition precise enough to obtain a high-entropy WFeCoNiCu alloy with well-balanced composition. Introduction of copper to form the quinternary alloy was found to catalyze the whole process, increasing deposition rates of all components of the high-entropy alloy.

Flash flood is one of the most significant natural disasters in China, particularly in mountainous area, causing heavy economic damage and casualties of life. Accurate risk assessment is critical to an efficient flash flood management. There are more than 530,000 small watersheds in 2058 counties in China where flash flood should be prevented. In practice, with limited fund and different risk levels, the priorities of each small watershed for flash flood prevention and control are also needed for an efficient flash flood management. This paper, take Licheng county in China as an example, aims to give out these priorities for management. First, sensitive indexes are identified among index system, which includes 9 indexes based on underlying surface characteristics of small watershed in hilly region. Second, the range of each index and the rank division of each index for evaluation are determined. Based on the rank divisions for evaluation, the flash flood risk grade eigenvalue (H) is calculated by Variable Fuzzy Method (VFM ) using 1000 samplings generated by Latin hypercube sampling method. Third, the key sensitivity factors that affect flash flood risk grade eigenvalue (H) are assessed by two different global sensitivity analysis methods -- stepwise regression analysis and mutual entropy. Both results indicate that watershed slope (S) is the most sensitive factor; the second is antecedent precipitation index (CN); while other factors are slightly different sensitive in sequence. This study shows that stepwise regression analysis and mutual information analysis are appropriate for the sensitivity analysis of mountain flash flood risk. Finally, based on watershed slope (S), the priorities of flash flood prevention and control of 119 small watersheds in Licheng county are given out.

Confined masonry (CM) is a construction system which consists of masonry wall panels enclosed by vertical and horizontal reinforced concrete confining elements. The presence of these confining elements distinguishes CM from unreinforced masonry system and makes this technology suitable for construction of structures in regions subjected to intense seismic or wind actions. CM construction has been used in many countries and regions, and has performed well in past earthquakes. The purpose of the paper is to review past research studies related to the seismic in-plane and out-of-plane behaviour of CM structures. The authors have identified the key design and construction parameters which were considered in past research studies and have performed statistical analyses to establish their influence on the seismic performance of CM buildings. For the purpose of this study the authors have compiled databases of previous experimental studies on CM wall specimens which were used for statistical analyses. Finally, the paper discusses research gaps and needs for future research studies which would contribute to the understanding of seismic behaviour and failure mechanisms of CM walls.

The rapid development of multicopters has led to many security problems. In order to prevent multicopters from invading restricted areas or famous buildings, an Anti-UAV Defense System (AUDS) has been developed and become a research topic of interest. Topics under research in relation to this include electromagnetic interference guns for unmanned aerial vehicles (UAVs), high-energy laser guns, US military net warheads, and AUDSs with net guns. However, these AUDSs use either manual aiming or expensive radar to track UAVs. This paper proposes a dual-axis rotary platform with UAV automatic tracking. The tracking platform uses visual image processing technology to track and lock the dynamic displacement of a UAV. When a target UAV is locked, the system uses a nine-axis attitude meter and laser rangefinders to measure its flight altitude and calculates its longitude and latitude coordinates through sphere coordinates to provide UAV monitoring for further defense or attack missions. Tracking tests of UAV flights in the air were carried out using a DJI MAVIC UAV at a height of 30 meters to 100 meters. It was set up for UAV image capture and visual recognition for tracking under various weather conditions by a thermal imager and a full-color camera respectively. When there was no cloud during the daytime, the images captured by the thermal imager and full-color camera provide a high-quality image recognition result. However, under dark weather, black clouds will emit radiant energy and seriously affect the capture of images by a thermal imager. When there is no cloud at night, the thermal imager performs well in UAV image capture. When the UAV is tracked and locked, the system can effectively obtain the flight altitude and longitude and latitude coordinate values.

The morphology, internal architecture, and emplacement mechanisms of the Central Atlantic Magmatic Province (CAMP) lava flows of the Hartford and Deerfield basins (USA) are presented. The Talcott, Holyoke, and Hampden formations within the Hartford basin constitute distinct basaltic units, each exhibiting chemical, mineralogical, and structural differences corresponding to flow fields. Each flow field was the result of several sustained eruptions that produced both inflated pahoehoe flows and subaquatic extrusions: 1–5 eruptions in the Talcott formation and 1-2 in Holyoke and Hampden basalts, where simple flows are dominant. The Deerfield basin displays the Deerfield basalt unit, characterized by pillow lavas and sheet lobes, aligning chemically and mineralogically with the Holyoke basalt unit. Overall, the studied flow fields are composed of thick, simple pahoehoe flows that display the entire range of pahoehoe morphology, including inflated lobes. The three-partite structure of sheet lobes, vertical distribution of vesicles, and segregation structures are typical. The characteristics of the volcanic pile suggest slow emplacement during sustained eruptive episodes and are compatible with a continental basaltic succession facies model. The studied CAMP basalts of the eastern United States are correlated with the well-exposed examples on both sides of the Atlantic Ocean (Canada, Portugal, and Morocco).

This study investigates how root environment acidification impacts tea seedlings and the role of magnesium (Mg) in mitigating these effects. We examine varying pH and Mg levels' influence on tea seedlings' resistance to abiotic stress, focusing on antioxidant capacity and nutritional content. In a hydroponic experiment, we varied root pH (3.5, 5.0, 6.5) and Mg concentrations (0.01, 0.4, 0.8 mM), assessing parameters like antioxidant capacity, peroxidative damage, and nutritional content at 1, 7, 15, and 30 days post-treatment. Root environment acidification and Mg deficiency worsened peroxidative damage in tea plant leaves and roots. Increased Mg supplementation enhanced antioxidant enzyme activity, reducing malondialdehyde and mitigating oxidative damage from root environment acid stress. Under acid stress, 0.8 mM Mg significantly increased tea leaf polyphenols, amino acids, and water-soluble extracts. Mg notably boosted chlorophyll content, surpassing lower Mg levels at pH 5. Additionally, Mg reversed root vitality inhibition induced by acid stress, leading to increased nitrogen, potassium, and Mg concentrations in leaves, promoting balanced nutrient absorption. Mg supplementation is crucial for enhancing tea plant antioxidant capacity, alleviating growth inhibition from root environment acid stress, and improving chlorophyll content and root vitality, highlighting Mg's significance in tea cultivation and broader agricultural practices.

Naturally fermented dairy products are an important component of the human diet. They are a valuable source of nutrients as well as vitamins and minerals. Their importance as a source of probiotic bacterial strains should not be overlooked. A number of studies highlights the positive effects of species of the Lactobacillacea on the intestinal microbiota, the overall homeostasis of the body, as well as a complementary treatment for some diseases. However, data on the effects on intestinal epithelial cells of postmetabolites released by bacteria are incomplete. This is likely due to the fact that these effects are species and strain specific. In the present study, we investigated the effects of postmetabolites produced by a pre-selected candidate probiotic strain Limosilactobacillus fermentum on HT-29 intestinal epithelial cells. Our data showed a pronounced proliferative effect, evaluated by flow cytometry, quantification of cell population, and determination of mitotic index. This was accompanied by stabilization of the cell monolayer, measured by increase of TEER (trans epithelial electric resistance) and reorganization of actin filaments. The data obtained are a clear indication of the positive effects, that the products secreted by L. fermentum strain 53 have on the intestinal epithelial cells.

The US opioid overdose epidemic has risen to an all-time high. Prescription opioids often serve as a gateway to illicit opioids which have appreciable overdose potential. Recent investigations have highlighted the efficacy and safety of marijuana-based products for pain management. Providing alternative pain treatment options may help mitigate the opioid epidemic. The distribution of codeine, fentanyl, hydrocodone, morphine, and oxycodone per 100K people and by 3-digit zip codes and overdose rates from 2014 to 2018 in California, which legalized recreational marijuana in 2016, were compared to Texas, where marijuana is functionally prohibited. Drug weights were obtained from the Automation of Reports and Consolidated Orders System and converted to oral morphine milligram equivalents. Overdose data was retrieved from the Centers for Disease Control’s WONDER database. California (-43.7%) and Texas (-27.3%) showed significant reductions in cumulative opioid distribution from 2014 to 2018. Opioid distribution per 100K people decreased -38.9% in California relative to -26.4% in Texas. Opioid and heroin overdoses increased between 1999 and 2019 by +11.6% in California but +272.7% in Texas. This evidence supports marijuana legalization as a mitigating factor to the opioid epidemic and opioid misuse.

This review paper aims to understand the current processing plant maintenance systems and further identify on-stream phased array corrosion mapping (PACM) to reduce turnaround maintenance (TAM) activity during plant operations. Reducing the TAM duration and extending the TAM interval are common goals of most researchers. Thus, a detailed review was performed to understand the maintenance systems and the problems faced. Furthermore, a review of the current PACM application and the possibility of applying it during on-stream inspection was also per-formed. PACM has better detectability for localized corrosion, and the results can be obtained for a range of thicknesses, which is the main advantage of this method. The challenge is to apply it to a surface with high temperatures, owing to the greater probe contact and the limitation of ultrasonic properties. This literature review provides a more precise direction for future research to evaluate PACM on piping that can be utilized in inspection during plant operation at elevated temperatures. Detecting and monitoring corrosion growth without shutdown.

Psoriasis is a lifelong, systemic, immune mediated inflammatory skin condition, affecting 1-3% of the world’s population, with an impact on quality of life similar to diseases like cancer or diabetes. Genetics are the single largest risk factor in psoriasis, with GWAS studies showing that many psoriasis risk genes lie along the IL23/Th17 axis. Potential psoriasis risk genes determined through GWAS can be annotated and characterised using functional genomics, allowing the identification of novel drug targets and the repurposing of existing drugs. The pathogenesis of psoriasis is complex and focusing on the IL23/Th17 axis can provide insight into key cell types, cytokines and intracellular signaling pathways involved. Examination of currently available biological treatments, time to relapse post drug withdrawal and rates of drug primary/secondary drug failure show the need for greater understanding of the underlying genetic mechanisms of psoriasis and how they can impact treatment. This could allow for patient stratification towards the treatment most likely reduce dis-ease burden for the longest period possible.

In recent years, bacterial resistance to conventional antibiotics has become a major concern in the medical field. The global misuse of antibiotics in clinics, personal use, and agriculture has accelerated this resistance, making infections increasingly difficult to treat and rendering new antibiotics ineffective more quickly. Finding new antibiotics is challenging due to the complexity of bacterial mechanisms, high costs and low financial incentives for the development of new molecular scaffolds, and stringent regulatory requirements. Additionally, innovation has slowed, with many new antibiotics being modifications of existing drugs rather than entirely new classes. Antimicrobial peptides (AMPs) are a valid alternative to small molecule antibiotics offering several advantages, including broad-spectrum activity and a lower likelihood of inducing resistance due to their multifaceted mechanisms of action. However, AMPs face challenges such as stability issues in physiological conditions, potential toxicity to human cells, high production costs, and difficulties in large-scale manufacturing. A reliable strategy to overcome the drawbacks associate with the use of small molecule antibiotics and AMPs is the combination therapy, namely the simultaneous co-administration of two or more antibiotics or the synthesis of covalently linked conjugates. This review is intended to cover and critically analyze the design, synthetic strategies, antibacterial activity and, when possible, the cytotoxicity of antibiotic-AMPs conjugates.

The extent of access to energy of displaced populations in settlements and camps in Africa is largely 14 unknown. A multitude of contextual factors, such as the location and the characteristics of housing, 15 the legal status, the socio-cultural background, and the availability of humanitarian and public ser- 16 vices impact the living conditions and the needed energy services. Limitations in accessing energy 17 services have direct, multilayered, and far-reaching implications, including impacts on health, nu- 18 trition, education, protection, and livelihood. The objective of this article is to contribute to a more 19 comprehensive overview of the current state of energy access in displacement contexts on the Afri- 20 can continent by identifying and utilizing existing data. After a screening of the vast and various 21 available information, setting up of a database, consolidating the gathered data as well as assessing 22 the quality through a quality assessment method, the currently available information is visualized 23 and discussed. Considerable differences in the access to electricity for displaced persons across the 24 countries are found. For both electricity and clean cooking, the availability for displaced persons 25 ranges from nearly no access at all up to an access rate of 100%. More strikingly, the results also 26 show that besides South Africa and countries in the Maghreb region, the access to both clean cook- 27 ing and electricity for displaced persons is very low. At the same time, the fragmented data availa- 28 bility, the poor data quality, and the questionable expediency of available data allows neither solid 29 theoretical conclusions nor planning of effective practical implementation measures. Novel inter- 30 disciplinary research, conceptual frameworks and indicators are needed for the purpose of compa- 31 rability and consistency. Future research has the potential to more comprehensively capture the 32 current state of access to energy in displacements contexts and in a next step to examine how energy 33 is interwoven in the lives of displaced people to derive a set of more detailed context-sensitive en- 34 ergy indicators. It is essential that the concerned persons, the displaced persons themselves are in- 35 cluded in the research in a meaningful way.

This study investigates the effects of xylitol, a natural sugar alcohol, on tumor progression in syngeneic mouse cancer models. Xylitol has been known for its dental health benefits, but emerging evidence suggests broader biological roles, including potential anti-cancer properties. We explored xylitol's impact on two mouse cancer models: 4T1 mammary carcinoma and B16F10 melanoma. Xylitol's efficacy in inhibiting cancer cell lines and modulating tumor progression was assessed using immunocompetent female mice. The experiments involved intratumoral and peri-tumoral administration of a 20% xylitol solution in two mouse strains: BALB/c (4T1 mammary carcinoma) and C57BL/6 (B16F10 melanoma). Tumor volume, histopathology, and metabolomic analyses were conducted to gauge xylitol's influence. The study revealed that xylitol administration initially reduced tumor growth in the B16F10 melanoma model, accompanied by alterations in tumor metabolism. However, similar effects were not observed in the 4T1 mammary carcinoma model, and melanoma tumor growth re-commenced after stroma deterioration permitted xylitol solution leakage. These findings suggest that xylitol may have potential as an adjunct therapy in cancer treatment, specifically in melanoma. The differential response between the two cancer models underscores the complexity of cancer biology and the need for further investigation into xylitol's mechanisms of action and its role in cancer therapy.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

Addressing non-unions involves stabilizing the affected area through osteosynthesis and improving bone biology using bone grafts. However, there is no consensus on the optimal treatment method. This study aims to compare outcomes of non-union revision using conventional treatment methods (metal hardware ± graft) versus osteosynthesis with the human, allogeneic cortical bone screw (Shark Screw®). Thirty-four patients underwent conventional treatment, while 28 cases received Shark Screws®. Patient demographics, bone healing, time to bone healing, and complications were assessed. Results revealed a healing rate of 96.4% for the Shark Screw® group, compared to 82.3% for the conventionally treated group. The Shark Screw® group exhibited a tendency for faster bone healing (9.4±3.2 vs. 12.9±8.5 weeks, p=0.05061). Hardware irritations led to six metal removals in the conventional group versus two in the Shark Screw® group. The Shark Screw® emerges as a promising option for personalized non-union treatment in the foot, ankle, and select lower leg cases, facilitating effective osteosynthesis and grafting within a single construct, promoting high union rates, low complications, and a rapid healing process.

Urban sprawl propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, substantially alters ecosystem services. Hence, the quantification of urban sprawl is crucial for effective urban planning, and environmental and ecosystem management. Like many megacities in fast growing developing countries, Chennai, the capital of Tamilnadu and one of the business hubs in India, has experienced extensive urban sprawl triggered by the doubling of total population over the past three decades. We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed spatial metrics to quantify the extent of urban sprawl within a 10km suburban buffer of Chennai. The rate of urban sprawl was quantified using Renyi’s entropy, and the urban extent was predicted for 2027 using land-use and land-cover change modeling. A 70.35% increase in urban areas was observed for the suburban periphery of Chennai between 1991 and 2016. The Renyi’s entropy value for year 2016 was ≥ 0.9, exhibiting a two-fold rate of urban sprawl. The spatial metrics values indicate that the existing urban areas of Chennai became denser and the suburban agricultural, forests and barren lands were transformed into fragmented urban settlements. The forecasted urban growth for 2027 predicts a conversion of 13670.33ha (16.57 % of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value of 1.7. Our findings are relevant for urban planning and environmental management in Chennai and provide quantitative measures for addressing the social-ecological consequences of urban sprawl and the protection of ecosystem services.

The Internet of Things (IoT) aims to connect all objects and facilitate data interchange, with data accuracy being paramount. While IoT has seen extensive adoption in conventional sectors, its application in the petroleum industry, especially with downhole equipment, poses challenges due to the extreme high-temperature and high-pressure conditions, making accurate measurements elusive. This Paper we aim to enhance the accuracy of downhole pressure measurements in slim-hole drilling parameter monitoring, mitigate the temperature influences on strain gauges, and surmount the intrinsic limitations of the traditional BP neural network, such as sluggish convergence speeds, high sensitivity to initial weights and biases, unstable learning rates, and a tendency to fall into local minima. This study introduces a temperature compensation model using a chaotic-initiated adaptive whale optimization algorithm (C-I-WOA) to optimize a BP neural network, which is henceforth referred to as the C-I-WOA-BP model. Initially, we harnessed chaotic mapping techniques to refine the initialization process of the whale optimization algorithm (WOA) population, thereby bolstering the heterogeneity of the algorithm. Subsequently, we integrated an adaptive weight recalibration mechanism, refined the encompassing methodology of the WOA, and bolstered its capabilities for expansive global scouting and meticulous local refinement in the solution arena. Subsequently, the WOA was used to optimize the weight coefficients of the BP neural network. Finally, we conducted a detailed comparative analysis by juxtaposing the performance metrics of the BP, C-WOA-BP, I-WOA-BP, and C-I-WOA-BP networks. The experimental results indicate that the C-I-WOA-BP model demonstrates faster convergence speed, superior global search capabilities, and enhanced local exploitation potential compared to the other models. Additionally, it provides a more stable and accurate reduction in temperature-induced errors in drilling pressure parameter measurements.

1) Background: Intellectual disability is more common in low- and middle-income countries than in high-income countries. Stigma and discrimination have contributed to barriers to people with intellectual disability accessing healthcare. As part of a larger study on caregiving of children with intellectual disability in urban Cape Town, South Africa, we interviewed a sub-group of families who had never used the intellectual disability services available to them, or who had stopped using them; 2) Methods: We employed a qualitative research design and conducted semi-structured interviews to explore the views and perspectives of parents and caregivers of children with intellectual disability who are not using specialised hospital services. We developed an interview guide to help explore caregivers’ and parents’ views; 3) Results: Results revealed that caregivers and parents of children with intellectual disability did not use the service due to financial difficulties, fragile care networks and opportunity costs, community stigma and lack of safety, lack of faith in services and powerlessness at effecting changes, and self-stigmatisation; 4) Conclusion: Current findings highlight a need for increased intervention at community level and collaboration with community-based projects to facilitate access to services, and engagement with broader issues of social exclusion.

Microarray patches (MAPs) have the potential to be a safer, more acceptable, easier to use, and more cost-effective means for the administration of vaccines than injection by needle and syringe. Here, we report findings from a randomized, partially double-blind, placebo-controlled Phase I trial using the Vaxxas high-density MAP (HD-MAP) to deliver a measles rubella (MR) vaccine. Healthy adults (N = 63, age 18–50 years) were randomly assigned 1:1:1:1 to four groups: uncoated (placebo) HD-MAPs, low-dose MR HD-MAPs (~3,100 median cell-culture infectious dose [CCID50] measles, ~4,300 CCID50 rubella); high dose MR-HD-MAPs (~9,300 CCID50 measles, ~12,900 CCID50 rubella); or a sub-cutaneous (SC) injection of an approved MR vaccine, MR-Vac (≥1,000 CCID50 per virus). The MR vaccines were stable and remained viable on HD-MAPs when stored at 2–8°C for at least 24 months. When MR HD-MAPs stored at 2–8°C for 24 months were transferred to 40°C for 3 days in a controlled temperature excursion, loss of potency was minimal, and MR HD-MAPs still met World Health Organisation (WHO) specifications. MR HD-MAP vaccination was safe and well-tolerated; any systemic or local adverse events (AEs) were mild or moderate. Similar levels of binding and neutralizing antibodies to measles and rubella were induced by low-dose and high-dose MR HD-MAPs and MR-Vac. The neutralizing antibody seroconversion rates at day 28 after vaccination for the low-dose HD-MAP, high-dose HD-MAP and MR-Vac groups were 37.5%, 18.8% and 35.7% respectively for measles and 37.5%, 25.0% and 35.7% respectively for rubella. Most participants were seropositive for measles and rubella antibodies at baseline, which appeared to negatively impact the number of participants that seroconverted to vaccines delivered by either route. The data reported here suggest HD-MAPs could be a valuable means for delivering MR-vaccine to hard-to-reach populations and support further development. Clinical trial registry number: ACTRN12621000820808.

The ongoing emergence of SARS-CoV-2 virus variants remains a source of concern because it is accompanied by the potential for increased virulence as well as evasion of immunity. Here we show that, although having an almost identical spike gene sequence as another Omicron variant (BA.5.2.1), a BA.4 isolate lacked all the typical disease characteristics of other isolates seen in the Golden Syrian hamster model despite replicating almost as effectively. Animals infected with BA.4 had similar viral shedding profiles to that seen with BA.5.2.1 (up to day 6 post infection) but they all failed to lose weight or present with any other significant clinical signs. We hypothesize that this lack of detectable signs of disease during infection with BA.4 was due to a small (nine nucleotide) deletion (∆686-694) in the viral genome (ORF1ab) responsible for production of non-structural protein 1 which resulted in the loss of three amino acids (aa 141-143).

Ebola virus (EBOV) is a negative-sense RNA virus that can infect humans and nonhuman primates with severe health consequences. Development of countermeasures requires a thorough understanding of the interaction between host and pathogen, and the course of disease. The goal of this study was to further characterize EBOV disease in a uniformly lethal rhesus macaque model, in order to support development of a well-characterized model following rigorous quality standards. Rhesus macaques were intramuscularly exposed to EBOV and one group was euthanized at predetermined time points to characterize progression of disease. A second group was not scheduled for euthanasia in order to analyze survival, changes in physiology, clinical pathology, terminal pathology, and telemetry kinetics. On day 3, sporadic viremia was observed and pathological evidence was noted in lymph nodes. By day 5, viremia was detected in all EBOV exposed animals and pathological evidence was noted in the liver, spleen, and gastrointestinal tissues. These data support the notion that EBOV infection in rhesus macaques is a rapid systemic disease similar to infection in humans, under a compressed time scale. Biomarkers that correlated with disease progression at the earliest stages of infection were observed thereby identifying potential “trigger--to-treat” for use in therapeutic studies.

SARS-CoV-2 infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. However, strategies to predict the course of SARS-CoV-2 infection in CVD patients at the time of hospital admission are still missing. Here, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 participants, including 20 uninfected and 37 acutely SARS-CoV-2-infected CVD patients and 37 healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T cell subsets. Moreover, we identified an immune signature characterised by mucosal-associated invariant T (MAIT) cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.

The establishment of a well characterized non-human primate model of Zika virus (ZIKV) infection is critical for the development of medical interventions. In this study, challenging Indian rhesus macaques (IRMs) with ZIKV strains of the Asian lineage resulted in dose dependent peak viral loads between days 2 and 5 post infection; and a robust immune response which protected the animals from homologous and heterologous re-challenge. In contrast, viremia in IRMs challenged with an African lineage strain was below the assays lower limit of quantitation and the immune response was insufficient to protect from re-challenge. These results corroborate previous observations but are contrary to reports using other African strains obviating the need for additional studies to elucidate the variables contributing to the disparities. Nonetheless, the utility of an Asian lineage ZIKV IRM model for countermeasures development was verified by vaccinating animals with a formalin inactivated reference vaccine and demonstrating sterilizing immunity against a subsequent subcutaneous challenge.

The many problems faced by the theory of general relativity (GR) have always motivated us to explore the modified theory of GR. Considering the importance of studying the black hole (BH) entropy and its correction in gravity physics, we study the correction of thermodynamic entropy for a kind of spherically symmetric black holes under the generalized Brans-Dicke (GBD) theory of modified gravity. We derive and calculate the entropy and heat capacity. It is found that when the value of event horizon radius~$r_+$~is small, the effect of the entropy correction term on the entropy is very obvious, while for larger values~$r_+$~, the contribution of the correction term on entropy can be almost ignored. In addition, we can observe that as the radius of the event horizon increases, the heat capacity of BH in GBD theory will change from a negative value to a positive value, indicating that there is a phase transition in black holes. Given that studying the structure of geodesic lines is important for exploring the physical characteristics of a strong gravitational field, we also investigate the stability of the geodesic motion of particles in static spherically symmetric BHs within the framework of GBD theory. Concretely, we analyzes the dependence of the innermost stable circular orbit on model parameters. Also, the geodesic deviation equation is also applied to investigate the stable circular orbit of particles in GBD theory. The conditions for the stability of BH solution and the limited range of radial coordinates required to achieve stable circular orbit motion are given. Finally, we show the locations of stable circular orbits, and obtain the angular velocity, the specific energy and angular momentum of the particles which move in circular orbits.

Advanced composite materials have drawn significant interest in the last years as an alternative to traditional materials due to their higher performance. However, industry struggle to provide low-cost, higher occupational safety, lower footprint with composites, making them suitable for holistic analyses. Therefore, the material design becomes an essential element that can impact the competitiveness, particularly in terms of productivity, circularity, safety, sustainability, and quality of the value chain. The Material Design-for-eXcellence is a state-of-art methodology for material performance multi-dimensional assessment along its life cycle phases, either useful to support ma-terial selection for new products or also to new material design support optimizing resource effi-ciency. In this methodology, the material behaviour and its multiple characteristics assessment, and the manufacturing processes efficiency are evaluated. The framework considers the analogy of product design holistic approaches, as Lean Design-for-X, to organize and assess the mul-ti-dimensional performance for each “X” Material Property. In this work, it was possible to observe that the bio-based composites solutions could be a good sustainable alternative for several sectors. Every day researchers are creating more new materials, having a diversity of properties at different scales, Material Design-for-eXcellence must also in the near future consider other factors. Hence, additional studies are thus foreseen to explore and develop this new tool.

Oxygen and hydrogen isotopes (18O and 2H) in polar ice offer strong evidence of both long-term and abrupt climate changes. However, reliably estimating surface air temperatures from past climates has proven difficult because the relationship between 18O and temperature cannot be calibrated. In this study, we investigated the 17O and 18O of modern rain and ice cores using published data. We found that precipitation 17O is influenced by two factors: mass-dependent fractionation (MDF) that occurs during ocean evaporation, and mass-independent fractionation (MIF) that happens in the stratosphere. The MDF contribution remains constant and can be understood from studying tropical rain, as the overall movement of mass in the tropics is upward towards the stratosphere. On the other hand, the MIF effect comes from the mixing of stratospheric air in the troposphere, which is a result of the Brewer-Dobson circulation. This MIF effect on precipitation 17O increases from the tropics towards the poles. Therefore, the relative 17O and 18O composition, denoted as '17O, in modern precipitation can be calibrated with surface air temperature, creating a new, independent tool for estimating past temperatures. We used this calibration along with '17O of Antarctic and Greenland ice cores and our results for past temperatures are in excellent agreement with those from borehole thermometry or gas phase analysis of air trapped in the ice. The 17O method overcomes the problems associated with using 18O for paleothermometry. Our findings align with climate models that suggest a weakening of the Brewer-Dobson circulation during the Last Glacial Maximum. Furthermore, our method could be used to monitor future changes in response to a warming climate caused by increasing greenhouse gases.

Molecular mimicry between human and microbial/viral/parasite peptides is common and for a long time is associated with the etiology of autoimmune disorders provoked by exogenous pathogens. Increasing evidence accumulated from the past years suggests a strong correlation between the SARS-CoV-2 infection and autoimmunity. The article analyzes the immunogenic potential of the peptides shared between SARS-CoV-2 spike glycoprotein (S-protein and antigens of human endocrinocytes involved in most common autoimmune endocrinopathies. Totally the study revealed 14 pentapeptides shared by S-protein of SARS-CoV-2 and autoantigens of thyroid, pituitary, adrenal cortex and Langerhans’ islets beta-cells, 12 of them belong to immunoreactive epitopes of SARS-CoV-2. The discussion of the data links the results with clinical correlates of COVID-associated autoimmune endocrinopathies. Most common of them is an autoimmune thyroid disease, so the majority of shared pentapeptides belong to marker autoantigens of this disease. Most important in pathogenesis of severe COVID-19, according authors’ opinion, can be autoimmunity against adrenals, because their adequate response prevents from excessive systemic action of inflammatory mediators which cause cytokine storm and hemodynamic shock. The criticism of antigen mimicry concept is given with a statement that peptide sharing is not a guarantee, but just a prerequisite of autoimmunity excess provocation. The last event occurs in carriers of certain HLA haplotypes and in case when shared peptide is used in antigen processing only [1 figure, 5 tables, bibliography 38 references].

In this paper we take China’s one child policy as an example and investigate its environmental impact. We develop a model for an economy using a standard overlapping generation model extended with human capital, endogenous fertility, and changing life expectancy. To model the environmental impact of economic activities, we use a modified IPAT model. We show that China’s one child has a very strong positive impact on the environment, particularly if we consider the whole human legacy.

We present an analytic calculation of the cooperative decay of a one-dimensional chain of N two-level atoms in the single-excitation configuration. Whereas the subradiant decay is zero for infinite lattices, we prove that for finite lattice the subradiant decay rate decreases as 1/N. We compare the results obtained using the scalar and the vectorial model. The calculations provide simple analytic expressions for the decay rate of the excitation, for arbitrary lattice spacing.

Efficient oxygen evolution reaction (OER) electrocatalysts are highly desired in the field of water electrolysis and rechargeable metal-air batteries. In this study, a chelate polymer, composed of copper (II) and dithiooxamide, was used to derive an efficient catalytic system for OER. Upon potential sweep in 1M KOH, copper (II) centers of the chelate polymer were transformed to CuO and Cu(OH)2. The carbon-dispersed CuO nanostructures formed a nanocomposite which exhibits an enhanced catalytic activity for OER in alkaline media. The nanocomposite catalyst has overpotential of 280 mV (at 1 mA/cm2) and a Tafel slope of 81 mV/dec in 1M KOH solution. It has a seven-fold higher current than IrO2/C electrode, per metal loading. A catalytic cycle is proposed, in which, CuO undergoes electrooxidation to Cu2O3 that further decomposes to CuO with releasing oxygen. This work reveals a new method to produce an active nanocomposite catalyst for OER in alkaline media using a non-noble metal chelate polymer and a porous carbon. This method can be applied to the synthesis of transition metal oxide nanoparticles used in the preparation of composite electrodes for water electrolyzers and can be used to derive cathode materials for aqueous-type metal-air batteries.

Zero-dose children, or children who have not received any routine vaccination, are a priority population for global health policy makers as these children are at high risk of mortality from vaccine-preventable illnesses. We conducted a narrative review to identify potential interventions, both within and outside of the health sector, to reach zero-dose children. We reviewed peer-reviewed and grey literature and identified 59 relevant resources. Additionally, we interviewed six key informants to enhance synthesis of our findings. Data were organized into three priority settings: (1) urban slums, (2) remote or rural communities, and (3) conflict settings. We found that zero-dose children in the three-priority settings face differing barriers to vaccina-tion and, therefore, require context-specific interventions, such as leveraging slum health commit-tees for urban slums or integrating with existing humanitarian response services for conflict set-tings. Three predominant themes emerged for grouping the various interventions: (1) community engagement, (2) health systems strengthening and integration, and (3) technological innovations. The barriers to reaching zero-dose children are multifaceted and nuanced to each setting, there-fore, no one intervention is enough. Technological interventions especially must be coupled with community engagement and health systems strengthening efforts. Evaluations of the suggested interventions are needed to guide scale up, as the evidence-base around these interventions is rel-atively small.

Pathological aseptic calcification is the most common form of structural valvular degeneration (SVD), leading to premature failure of heart valve bioprostheses (BHVs). The processing methods used to obtain GA-fixed pericardium-based biomaterials determine the hemodynamic characteristics and durability of BHVs. This article presents a comparative study of the effects of several processing methods on the degree of damage to the ECM of GA-fixed pericardium-based biomaterials as well as on their biostability, biocompatibility, and resistance to calcification. Based on the assumption that preservation of the native ECM structure will enable the creation of calcinosis-resistant materials, this study provides a soft biomimetic approach for the manufacture of GA-fixed biomaterials using gentle decellularization and washing methods. It has been shown that the use of soft methods for preimplantation processing of materials, ensuring maximum preservation of the intactness of the pericardial ECM, radically increases the resistance of biomaterials to calcification. The data obtained are of interest for the development of new calcinosis-resistant biomaterials for the manufacture of BHVs.

Environmental physical and chemical factors controlling the abundance and biodiversity of zooplankton in permafrost-affected lakes are poorly known yet they determine the response of the ecosystems to on-going climate change and water warming. Here we assessed the current status of zooplankton communities of lake ecosystems in the North-West of the Bolshezemelskaya tundra (Nenets Autonomous district), and provide new information about the composition and structure of zooplankton. Results demonstrate that the structure of zooplankton communities is influenced by morphometric features of lakes and the degree of their overgrowth by macrophytes. According to the level of zooplankton development, most tundra lakes were of the oligotrophic type with an average biomass of up to 1 g/m3. The largest number of species was observed in zooplankton communities of small lakes with an area of up to 0.02 km2 and overgrown with macrophytes. The analysis of factors that influence the formation of the lakes zoocenosis demonstrated that the species composition and quantitative characteristics of zooplankton are chiefly controlled by pH and water mineralization. A comparison of the results obtained with the literature data on the lakes of this region collected 60 years ago confirms that the ecosystems of the studied lakes are in a stable state. Overall, these new insights will improve our knowledge of factors controlling the zooplankton spatial dynamics in unique but quite abundant thermokarst lakes of NE European Tundra, subjected to on-going climate warming.

Thermal plasma technique is becoming prominent in the treatment of variety of waste ranging from municipal solid waste, incinerator residue, hospital waste, electronics waste and industrial sludge. Application of the new treatment technology to petroleum sludge requires information on the nature and characteristics of the sludge that will be use to optimize the treatment system. In this investigation, petroleum sludge obtained from Petronas Melaka was characterized for its physical and chemical features. Proximate and ultimate analysis as well as determination of elemental composition were carried out. The sludge was found to contain high moisture (78.91%), low ash (5.06%), low volatiles (5.52%) and high fixed carbon (10.51%). The sludge has a TOC of 54.48% and HHV of 23.599MJ/kg. Despite the high moisture content, the higher heating value (HHV) is high when compared to literature values. The high value of HHV may be associated with the high fixed carbon, low ash content and high value of TOC. The apparent density of the sludge is slightly lower. Fourteen heavy metals are detected in significant quantities. Proper waste management that will safely dispose the sludge is required. The waste disposal technique should take into cognizant the possibility of leaching of heavy metals into ground water on one hand and the gasification of lighter ones on the other.

Small RNAs (sRNA) are epigenetic regulators of essential biological processes that have been linked to the onset and progression of leukemia, including acute adult T-cell leukemia-lymphoma (ATLL) caused by the retrovirus Human T-lymphotropic virus type 1. Here, we describe the sRNA profile of a 30-year-old female with ATLL at diagnosis and after maintenance therapy, with the goal of correlating their expression levels with response to therapy.

Organophosphate pesticides are used in large quantities. However, they exhibit toxic effects on non-target organisms. Dimethoate and its oxo-analog omethoate inhibit acetylcholinesterase and are toxic for mammals. Moreover, they show extreme toxicity for bees. Once in the environment, they undergo chemical transformations and decomposition. We show that dime-thoate and omethoate decompose rapidly in alkaline aqueous solutions (half-lives 5.7 and 0.89 days) but are highly stable in acidic solutions (half-lives 124 and 104 days). These differences are explained using quantum chemical calculations, indicating that a weaker P–S bond in omethoate is more susceptible to hydrolysis, particularly at a high pH. The toxicity of these pesticides solutions decreases over time, indicating that no or very little highly toxic omethoate is formed during hydrolysis. Presented data can be used to predict dimethoate and omethoate concentrations in contaminated water depending on pH. Presented results suggest that alkaline hydrolysis of organophosphates has an advantage over other techniques for their removal since there is no risk of omethoate accumulation and increased toxicity of contaminated water.

We developed a novel machine learning algorithm to augment clinical diagnosis of prostate cancer utilizing first and second-order texture analysis metrics and novel application of machine learning radiomics analysis. We successfully discriminated between significant prostate cancers versus non-tumor regions and provided accurate prediction between Gleason score cohorts with statistical sensitivity of greater than 0.91 sensitivity across three separate cohorts. Tumor heterogeneity and prediction between GS cohorts were quantified using two feature selection approaches and two classifiers with tuned hyperparameters (including grid search and randomized search). There was a total of 71 patients analyzed in this study. Multiparametric MRI, incorporating T2WI and the ADC maps, were used to derive radiomics features. Recursive feature elimination (RFE), the least absolute shrinkage and selection operator (LASSO), and two classification approaches, including a support vector machine (SVM) (with grid search) and random forest (RF) (with randomized search), were utilized to differentiate between non-tumor regions versus significant cancer and prediction among Gleason score groups. In T2WI images, the RFE feature selection approach combined with RF and SVM classifiers outperformed LASSO with SVM and RF classifiers regarding performance. The detection precision of the radiomics framework depending on multiple imaging modalities was lower than the diagnostic accuracy of single imaging modality model with every machine learning approach assessed. The best performance was achieved by combining LASSO and SVM into a model that used both T2WI and ADC. This model had an area under the curve (AUC) of 0.91. Radiomic features computed from ADC and T2WI images were used to predict three groups of Gleason score using two kinds of feature selection methods (RFE and LASSO), RF and SVM classifier models with tuned hyperparameters. Using combined sequences (T2WI and ADC map images) and combined radiomics (1st and GLCM features), LASSO, with a feature selection method with RF, was able to predict G3 with the highest sensitivity at a level AUC of 0.92. To predict G3 for single sequence (T2WI images) using GLCM features, LASSO with SVM achieved the highest sensitivity with an AUC of 0.92.

Cellular biomolecular condensates termed ribonucleoprotein (RNP) granules often are enriched in messenger RNA (mRNA) molecules relative to the surrounding cytoplasm. Yet, the spatial localization and diffusion of mRNAs in close proximity to phase separated RNP granules is not well understood. In this study, we performed single molecule fluorescence imaging experiments of mRNAs in live cells in the presence of two types of RNP granules, stress granules (SG) and processing bodies (PB), which are distinct in their molecular composition and function. We developed a photobleaching- and noise-corrected colocalization imaging algorithm that was employed to determine the accurate positions of individual mRNAs relative to the granule’s boundaries. We found that mRNAs are often localized at granule boundaries, an observation consistent with recently published data. We suggest that mRNA molecules become spontaneously confined at the RNP granule boundary similar to the adsorption of polymer molecules at liquid-liquid interfaces, which is observed in various technological and biological processes. We also suggest that this confinement could be due to a combination of intermolecular interactions associated with, first, the screening of a portion of the RNP granule interface by the polymer and, second, electrostatic interactions due to a strong electric field induced by a Donnan potential generated across the thin interface.

Matrix Factorization is a long established method employed for analyzing and extracting valuable insight recommendations from complex networks containing user ratings. The execution time and computational resources demanded by these algorithms pose limitations when confronted with large datasets. Community detection algorithms play a crucial role in identifying groups and communities within intricate networks. To overcome the challenge of extensive computing resources, we present a novel parallel computation framework utilizing community information available in the rating network. Our proposed approach named as Community-based Matrix Factorization(CBMF), parallelizes matrix factorization technique by dividing the network into communities using existing community detection algorithms. We prove that this parallel approach not only increases the quality of recommendations in connection with Root Mean Square Error (RMSE), but also yields substantial performance improvement. We empirically evaluate our idea on diverse datasets and present comprehensive experimental results. These results serve as empirical evidence of the effectiveness and performance gains offered by our parallel computation framework.

Isotope detection and identification is paramount in many fields of science and industry, such as in the fusion and fission energy sector, in medicine and material science, and in archeology. The isotopic information provides fundamental insight on the research questions related to these fields as well as insight on product quality and operational safety. However, isotope identification with the established mass-spectrometric methods is laborious and requires laboratory conditions. In this work, Microwave-Assisted Laser-Induced Breakdown Spectroscopy (MW-LIBS) is introduced for isotope detection and identification utilizing radical and molecular emission. The approach is demonstrated with stable B and Cl isotopes in solids and H isotopes in liquid using emission from BO and BO2, CaCl, and OH molecules, respectively. MW-LIBS utilizes the extended emissive plasma lifetime and molecular emission signal integration times up to 900 s to enable use of low ~4 mJ ablation energy without compromising signal intensity and, consequently, sensitivity. On the other hand, long plasma lifetime gives time for molecular formation. Increase in the signal intensity towards the late microwave-assisted plasma was prominent in BO2 and OH emission intensities. As MW-LIBS is online-capable and requires minimal sample preparation, it is an interesting option for isotope detection in various applications.

The emergence of immune checkpoint inhibitors (ICIs) has dramatically changed the treatment landscape for patients with metastatic non-small cell lung cancer (NSCLC). These achievements inspired investigators and pharmaceutical companies to conduct clinical trials in patients with early-stage NSCLC because both adjuvant and neoadju-vant platinum-based doublet chemotherapies (PT-DCs) showed only a 5% improve-ment in the 5-year overall survival. IMpower010, a phase 3 trial (P3), showed that ad-juvant PT-DC followed by maintenance atezolitumab significantly prolonged dis-ease-free survival than adjuvant PT-DC alone (hazard ratio, 0.79; stage II to IIIA). Since conventional therapies, including chemotherapy and radiotherapy, can promote im-munogenic cell death, which releases tumour antigens from dead tumour cells, ICI combination therapies with conventional therapies are widely proposed. Checkmate 816 trial (P3) indicated a significantly higher pathological complete response rate of neoadjuvant nivolumab/PT-DC combination therapy than neoadjuvant PT-DC alone (odds ratio, 13.9, for stage IB to IIIA). Detection of circulating tumour DNA is highly anticipated for the evaluation of minimal residual disease. Multimodal approaches and new ICI agents are being attempted to improve the efficacy of ICI treatment in phase 2 trials. This review presents the development of perioperative treatment using ICIs in patients with NSCLC while discussing problems and perspectives.

Mammals have two insulin-like growth factors (IGF) that are key mediators of somatic growth, of tissue differentiation and cellular responses to stress. Thus, the mechanisms that regulate the bioavailability of IGFs are important in both normal and aberrant development. IGF-I levels are primarily controlled via the growth hormone-IGF axis, in response to nutritional status, and also reflect metabolic diseases and cancer. One mechanism that controls IGF bioavailablity is the binding of circulating IGF to a number of binding proteins that keep IGF in a stable, but receptor non-binding state. But even before IGF is released from the cells that produce it, it undergoes an obligatory association with a ubiquitous chaperone protein, GRP94. This binding is required for secretion of a properly folded, mature IGF. This chapter reviews the known aspects of the interaction and highlights the specificity issues yet to be determined. The IGF-GRP94 interaction provides a potential novel mechanism of idiopathic short stature, involving the obligatory chaperone and not just IGF gene expression. It also provides a novel target for cancer treatment, as GRP94 activity can be either inhibited or enhanced.

Magnetic Resonance Imaging (MRI) is a powerful, non-invasive and nondestructive tool, capable of providing three-dimensional (3D) images of living organisms. The use of magnetic contrast agents has allowed clinical researchers and analysts to enormously increase the sensitivity and specificity of MRI since these substances change the intrinsic properties of the tissues within a living body, increasing the information present in the images. The advances in nanotechnology and materials science as well as the research of new magnetic effects have been the driving forces that propel the use of magnetic nanostructures as promising alternatives to the commercial contrast agents used in MRI. This review discusses the principles associated with the use of contrast agents in MRI as well as the most recent reports focused on nanostructured contrast agents. The potential applications of gadolinium (Gd) and manganese Mn-based nanomaterials and iron oxide nanoparticles in this imaging technique are discussed as well, from their magnetic behavior to the mainly used materials and nanoarchitectures. Then, it is also addressed the recent efforts made to develop new types of contrast agents based on synthetic antiferromagnetic and high-aspect ratio nanostructures. Furthermore, the application of these materials in theragnosis, either as contrast agents and controlled drug release, contrast agents and thermal therapy or contrast agents and radiosensitizers, is also presented.

Cardiovascular Diseases (CVDs) are still menacing and killing adults worldwide, notwithstanding the tremendous effort, to decrease their related mortality and morbidity. Lately, a growing body of evidences indicated that inflammation plays a pivotal role in the pathogenesis and complications of CVDs. A receptor of the immunoglobulin superfamily, triggering receptor expressed on myeloid cells -1 (TREM-1) was shown to induce and to amplify the inflammation in both acute and chronic diseases pathogenesis and progression and hence it is one of the important factors that complicates CVDs. Thus, studies endeavored to investigate the role played by TREM-1 in CVDs with respect to their etiologies, complications and possible therapeutics. We examined here, for the first time, the most relevant studies regarding TREM-1 involvement in CVDs. We summarized the finding after critically analyzing them and made some suggestions for furtherance of the investigations with the aim to utilize TREM-1 and its pathways for diagnostic, management and prognosis of CVDs. Overall, TREM-1 was found to be involved in the pathogenesis of acute and chronic cardiovascular conditions like Acute myocardial infraction (AMI) and atherosclerosis as well. Although most therapeutic approaches are yet to be elucidated, present research outcome displays a promising future to utilize TREM-1 pathway as potential target to understand and manage CVDs.

The feasibility of using full ion kinetics, instead of gyrokinetics, in simulating low-frequency Ion-Temperature-Gradient (ITG) instabilities in tokamaks has recently been demonstrated by Sturdevant et al. [Physics of Plasmas 24, 081207 (2017)]. In that work, a variational integrator was developed to integrate the full orbits of ions in toroidal geometry, which proved to be accurate in capturing both the short-time scale cyclotron motion and long time scale drift motion. The present work extends that work in three aspects. First, we implement a relatively simple full orbit integrator, the Boris integrator, and demonstrate that the accuracy of this integrator is also sufficient for simulation of ITG instabilities. Second, the equilibrium magnetic configuration is extended to general toroidal configuration specified numerically, enabling simulation of realistic equilibria reconstructed from tokamak experiments. Third, we extend that work to the nonlinear regime and investigate the nonlinear saturation of ITG instabilities. To verify the new numerical implementation of the orbit integrator and magnetic configuration, the linear electrostatic ITG frequency and growth rate are compared with those given in Sturdevant's work and good agreement is found.

During the last decades, the production systems have developed different strategies to increase their competitiveness in the global market. In a manufacturing and services systems, Lean Manufacturing has been consolidated through the correct implementation of its tools. The present paper presents a case study developed in a Food Packer company where a Simulation Model was considered as an alternative to reduce the waste time generated by the poor distribution of operations and transportation areas for a product within the factory. As a matter of fact, the company has detected problems on the layout distribution that prevents to fulfill the market demand. In addition, the principal aim was to create a simulation model to test different hypothetical scenarios and alternative designs for the layout distribution without modifying its facilities. Moreover, the implemented methodology was based on classical models of simulation projects and a compendium of the manufacturing systems optimization by simulation process used during the last ten years. Also, a mathematic model supported by the Promodel ® simulation software was developed considering the company characteristics; along with the model development, it was possible to compare the production system performance from the percentage of used locations, the percentage of resources utilization, the number of finished products, and the level of Work in Process (WIP). Finally, the verification and validation stages were performed before running the scenarios in the real production area. The results generated by the implementation of the project represent an increase of 68% in the production capacity and a reduction of 5% in the WIP. In addition, both outcomes are associated with the resources management, which were reassigned to other production areas.

The self-organization properties of C70 fullerene molecules in a xylene/tetrahydrofuran binary mixture were studied for the first time by optical absorption, refractometry, and dynamic light scattering. A correlation has been established between the change in the refractive index of the C70/xylene/tetrahydrofuran solution and the degree of self-organization of C70 molecules in the medium at various concentrations and storage periods of the solution. It is shown that the features of the optical absorption spectrum of C70/xylene/tetrahydrofuran at a fixed low concentration of the fullerene are sensitive to its storage time. It was determined that the beginning time of the formation of C70 nanoclusters and their final size depend on the concentration of fullerene and the time of keeping the solution. The observed nature of the C70 fullerene solution in a binary mixture may help to elucidate the mechanism of self-organization in the future.

This paper studies the dividend optimization problem in the entropy regularization framework by following the same continuous-time reinforcement learning setting as in Wang et al. (2020). The exploratory HJB is established and the optimal exploratory dividend policy is a truncated exponential distribution. We show that, for suitable choices of the maximal dividend paying rate and the temperature parameter, the value function of the exploratory dividend optimization problem could be significantly different from the value function in the classical dividend optimization problem. In particular, the value function of the exploratory dividend optimization problem could be classified into three cases based on its monotonicity. Numerical examples are also presented to show the impact of temperature parameter on the solution.

This paper presents a novel algorithm, the multi-objective nonlinear interval PageRank (MONIPR) Algorithm. This algorithm extends the conventional PageRank (PR) algorithm, integrating nonlinear interval computation and multi-objective considerations into the computation process. The MONIPR algorithm bridges a research gap in integrating nonlinear interval approaches and multi-objective problems into the PR algorithm, which were traditionally treated separately. In addition, this research adopts the constrained interval arithmetic proposed to address the limitations of the conventional PR algorithm, which tends to overlook uncertainties and results in deterministic outcomes. In addition, we use a numerical example to demonstrate the proposed algorithm, contrasting it with the conventional approaches. A numerical example demonstrates the algorithm's performance by comparing the rank intervals obtained with the traditional crisp Markov chain and PR algorithm. The results highlight the ability of the proposed algorithm to provide a range of possible rank intervals, considering both uncertainty and multi-objectives. The findings suggest potential applications in decision-making, uncertainty quantification, and systems analysis.

The Failure Mode and Effect Analysis (FMEA) is often used to improve a system's reli-ability. This paper proposes a new approach that aims to overcome the most critical defects of the traditional FMEA. This new methodology combines the Entropy and Best Worst Method (BWM) methodology with the EDas and System Dynamics, FMECA: The EN-B-ED Dynamic FMECA. The main innovation’s point of the proposed work is the presence of an unknown factor (Cost), that allows to obtain an objective weighted factor, a risk index when a machine failure occurs. The criticality analysis has been carried out using software (Vensim PLE x64) to simulate System Dynamics models to identify corrective actions and evaluating the possible implementation of these ac-tions. The methodology proposed is applied to a case study in a relevant Italian com-pany in the agri-food sector.

Beyond the usual ferromagnetic and paramagnetic phases present in spin systems, the usual q-state clock model, presents an intermediate vortex state when the number of possible orientations q for the system is equal to 5 or larger. Such vortex states give rise to the Berezinskii-Kosterlitz-Thouless (BKT) phase present up to the XY model in the limit q→∞. Based on information theory, we present here an analysis of the classical order parameters plus new short-range parameters defined here. Thus, we show that even using the first nearest neighbors spin-spin correlations only, it is possible to distinguish the two transitions presented by this system for q greater than or equal to 5. Moreover, the appearance at relatively low temperature and disappearance of the BKT phase at a rather fix higher temperature is univocally determined by the short-range interactions recognized by the information content of classical and new parameters.

The entropy of a system gives a powerful insight into its microscopic degrees of freedom, however standard experimental ways of measuring entropy through heat capacity are hard to apply to nanoscale systems, as they require the measurement of increasingly small amounts of heat. Two alternative entropy measurement methods have been recently proposed for nanodevices: through charge balance measurements and transport properties. We describe a self-consistent thermodynamic framework for treating few-electron nanodevices which incorporates both existing entropy measurement methods, whilst highlighting several ongoing misconceptions. We show that both methods can be described as special cases of a more general relation and prove its applicability in systems with complex microscopic dynamics – those with many excited states of various degeneracies.

Complex systems can be described as the network of interactions between their components. In directed networks, information, energy and matter flow in dominant directions. Undirected networks, on the other hand, cannot easily capture these asymmetries. The local flow of information depends on the node spin, which is a function of the number of incoming and outgoing links attached to it. And yet, how the heterogeneous association between in-degree and out-degree constraints global dynamics remains poorly understood. Here, we develop a new theoretical model to study the relationship between node directionality and global flow dynamics. Our computational analysis of random and scale-free directed networks indicates that structural diversity constrains the dimensionality of reachable dynamical space. These results suggest how local directionality might be an universal driver of global dynamics in many systems, from social networks, to technological systems to the connectome.

Modulation of the amplitude of high-frequency cortical field activity locked to changes in phase of a slower brain rhythm is known as phase-amplitude coupling (PAC). The study of this phenomenon has been gaining traction in neuroscience because of several reports on its appearance in normal and pathological brain processes in humans as well as across different mammalian species. This has led to the suggestion that PAC may be an intrinsic brain process that facilitates brain inter-area communication across different spatiotemporal scales. Several methods have been proposed to measure the PAC process, but few of these enable detailed study of its time course. It appears that no studies have reported details of PAC dynamics including its possible directional delay characteristics. Here, we study and characterize the use of a novel information theoretic measure that may address this limitation: local transfer entropy. We use both simulated and actual intracranial electroencephalographic data, and in both cases we observe initial indications that local transfer entropy can be used to detect the onset and offset of modulation process periods revealed by mutual information phase-amplitude coupling (MIPAC). We review our results in the context of current theories about PAC in brain electrical activity, and discuss technical issues that must be addressed to see local transfer entropy more widely applied to PAC analysis.

This article presents a new method of segmenting grayscale images by minimizing Shannon's neutrosophic entropy. For the proposed segmentation method, the neutrosophic information components, i.e., the degree of truth, the degree of neutrality and the degree of falsity are defined taking into account the belonging to the segmented regions and at the same time to the separation threshold area. The principle of the method is simple and easy to understand and can lead to multiple thresholds. The efficacy of the method is illustrated using some test gray level images. The experimental results show that the proposed method has good performance for segmentation with optimal gray level thresholds.

While laminar flow heat transfer and mixing in microfluidic geometries has been investigated experimentally, as has the effect of geometry-induced turbulence in microfluidic flow (it is well documented that turbulence increases convective heat transfer in macrofluidic flow), little literature exists investigating the effect of electrokinetically-induced turbulence on heat transfer at the micro scale. Using recently observed experimental data, this work employed computational fluid dynamics coupled with electromagnetic simulations to determine if electrokinetically-forced, low-Reynolds number turbulence could be observed in a rectangular microchannel with using Newtonian fluids. Analysis of the results was done via comparison to the experimental criteria defined for turbulent flow. This work shows that, even with a simplified simulation setup, computational fluid dynamics (CFD) software can produce results comparable to experimental observations of low-Reynolds turbulence in microchannels using Newtonian fluids. In addition to comparing simulated velocities and turbulent energies to experimental data this work also presents initial data on the effects of electrokinetic forcing on microfluidic flow based on entropy generation rates.

Recent studies have demonstrated an important role for vitamin C in the epigenetic regulation of cancer-related genes via DNA demethylation by the ten-eleven translocation (TET) methylcytosine dioxygenase enzymes. DNA methyltransferase (DNMT) reverses this, increasing DNA methylation and decreasing gene expression. Dual oxidase (DUOX) enzymes produce hydrogen peroxide (H2O2) in normal pancreatic tissue but are silenced in pancreatic cancer (PDAC). Treatment of PDAC with pharmacologic ascorbate (P-AscH-, intravenous, high dose vitamin C) increases DUOX expression. We hypothesized that inhibiting DNMT may act synergistically with P-AscH- to further increase DUOX expression and cytotoxicity of PDAC. PDAC cells demonstrated dose-dependent increases in DUOX mRNA and protein expression when treated with DNMT inhibitors. PDAC cells treated with P-AscH- + DNMT inhibitors demonstrated increased DUOX expression, increased intracellular oxidation, and increased cytotoxicity in vitro and in vivo compared to either treatment alone. These findings suggest a potential therapeutic, epigenetic mechanism to treat PDAC.

Purpose: This study investigated the hypotensive effect of RKI-1447, a Rho kinase inhibitor, in a porcine ex vivo pigmentary glaucoma model. Methods: Twenty-eight porcine anterior chambers were perfused with medium supplemented with 1.67 × 10⁷ pigment particles/mL for 48 hours before treatment with RKI-1447 (n = 16) or vehicle control (n = 12). Intraocular pressure (IOP) was recorded and outflow facility was calculated. Primary trabecular meshwork cells were exposed to RKI-1447 or vehicle control; effects on the cytoskeleton, motility, and phagocytosis were evaluated. Result: Compared to baseline, the perfusion of pigment caused a significant increase in IOP in the RKI-1447 group (P = 0.003) at 48 hours. Subsequent treatment with RKI-1447 significantly reduced IOP from 20.14 ± 2.59 mmHg to 13.38 ± 0.91 mmHg (P = 0.02). Pigment perfusion reduced the outflow facility from 0.27 ± 0.03 at baseline to 0.18 ± 0.02 at 48 hours (P < 0.001). This was partially reversed with RKI-1447. RKI-1447 caused no apparent histological changes in the micro- or macroscopic TM appearance. RKI-1447-treated primary TM cells showed significant disruption of the actin cytoskeleton both in the presence and absence of pigment (P < 0.001) but no effect on TM migration was observed. Pigment-treated TM cells exhibited a reduction in TM phagocytosis, which RKI-1447 reversed. Conclusion: RKI-1447 significantly reduces IOP by disrupting TM stress fibers and increasing TM phagocytosis. These features may make it useful for the treatment of secondary glaucomas with an increased phagocytic load.

Objective: The Rho GTPase/Rho kinase pathway is an important target in glaucoma treatment. This study investigated the hypotensive effect of RKI-1447, a Rho kinase inhibitor developed for cancer treatment, in a porcine ex vivo pigmentary glaucoma model. Materials and Methods: Twenty-eight fresh porcine anterior chambers were perfused with pigment medium (1.67 × 10⁷ pigment particles/mL) for 48 hours before being subjected to the RKI-1447 (n = 16) or the vehicle control (n = 12). Another twelve eyes with normal medium perfusion served as the control. The intraocular pressure (IOP) was recorded at two-minute intervals and the outflow facility was calculated. To investigate the intracellular mechanism of the IOP reduction, primary trabecular meshwork cells were exposed to RKI-1447 or the vehicle control and then analyzed for changes in cytoskeleton, motility, and phagocytosis. Results: Compared to the baseline, the perfusion of pigment caused a significant increase in IOP in the RKI-1447 group (P = 0.003) at 48 hours. Subsequent treatment with RKI-1447 significantly reduced IOP from 20.14 ± 2.59 mmHg to 13.38 ± 0.91 mmHg (P = 0.02). Pigment perfusion reduced the outflow facility from 0.27 ± 0.03 at baseline to 0.18 ± 0.02 at 48 hours (P < 0.001). This was partially reversed with RKI-1447. RKI-1447 exhibited no apparent changes in the micro- or macroscopic appearance, including histology. Primary TM cells exposed to RKI-1447 showed a significant disruption of the actin cytoskeleton both in the presence and absence of pigment exposure (P < 0.001) but no effect on TM migration was observed. Pigment-treated TM cells exhibited a reduction in TM phagocytosis, which RKI reversed. Conclusions: RKI-1447 is a novel ROCK inhibitor that significantly reduces IOP by disrupting TM stress fibers and increasing TM phagocytosis. These features may make it especially useful for the treatment of secondary glaucomas with an increased phagocytosis load but also for other open angle glaucomas.

A temperate deep lake, Lake Kuttara, Hokkaido, Japan (148 m deep at maximum) was completely frozen every winter in the 20th century. However, unfrozen conditions of the lake over winter occurred four times in the 21st century, which is probably due to global warming. In order to understand how thermal regime of the lake responds to climate change, its heat storage change was calculated by estimating heat budget of the lake and monitoring water temperature at the deepest point for September 2012–June 2016. As a result, temporal change of the heat storage from the heat budget was very consistent with that from the direct temperature measurement (determination coefficient R² = 0.827). The 1978–2017 data at a meteorological station near Kuttara indicated that there are significant (less than 5% level) long-term trends for air temperature (0.024 °C/yr) and wind speed (−0.010 m/s/yr). A sensitivity analysis for the heat storage from the heat budget estimate and an estimate of return periods for mean air temperature in mid-winter allow us to conclude that the lake could be unfrozen once per about two year in a decade.

Fault detection in PV arrays and inverters is critical for ensuring maximum efficiency and performance. Artificial intelligence (AI) learning can be used to quickly identify issues, resulting in a sustainable environment with reduced downtime and maintenance costs. As the use of solar energy systems continues to grow, the need for reliable and efficient fault detection and diagnosis techniques becomes more critical. This paper presents a novel approach for fault detection in photovoltaic (PV) arrays and inverters, combining AI techniques. It integrates Elman Neural Network (ENN), Boosted Tree Algorithms (BTA), Multi-layer Perceptron (MLP), and Gaussian Processes Regression (GPR) for enhanced accuracy and reliability in fault diagnosis. It leverages their strengths for accuracy and reliability of fault diagnosis. Feature engineering-based sensitivity analysis was utilized for feature extraction, the fault detection and diagnosis were assessed using several statistical criteria including PBAIS, MAE, NSE, RMSE, and MAPE. Two intelligent learning scenarios are carried out, the first scenario is done for PV array fault detection with DC power (DCP) as output. The second scenario is done for inverter fault detection with AC power (ACP) as the output. The proposed technique is capable of detecting faults in PV arrays and inverters, providing a reliable solution for enhancing the performance and reliability of solar energy systems. Real-world solar energy dataset is used to evaluate the proposed technique, with results compared to existing detection techniques and obtained results show that it outperforms existing fault detection techniques, achieving higher accuracy and better performance. The GPR-M4 optimization justified reliably among all the models with MAPE=0.0393, and MAE=0.002 for inverter fault detection and MAPE=0.091, and MAE=0.000 for PV array fault detection.

Molecular analysis of growing teratoma syndrome has not been extensively studied. Here, we report a 14-year-old boy with a growing mass during treatment for a mixed germ cell tumor of the pineal region. Tumor markers were negative; thus, growing teratoma syndrome was suspected. A radical resection via the occipital transtentorial approach was performed, and histopathological examination revealed a teratoma with malignant features. Methylation classifier analysis confirmed the diagnosis of teratoma, and DMRT1 loss and 12p gain were identified by copy number variation analysis, potentially elucidating the cause of growth and malignant transformation of the teratoma. The patient remains in remission after intense chemoradiation treatment as a high-risk germ cell tumor.

Three dietary treatments were assayed in 350 milking Murciano-Granadina multiparous goats in full-lactation: a control diet and two experimental diets, one including flaked linseed (FL) and the other salmon oil (SO). Neither dietary treatment affected the daily milk yield, cheese yield or the physicochemical parameters of the milk and cheese. With regard to the fatty acid profile (FA), the milk and cheese from animals whose diet was supplemented with SO had a higher percentage of fatty acids than those obtained with the FL supplemented diet, except for C18:0, C18:1, C18:2 n-6, trans-9, trans-12 C18:2, cis-9, trans-11 C18:2, C18:3 and C19:0, which reached their highest levels in milk obtained with the diet supplemented with FL. The decrease in the percentage of C16:0 was greater in the milk derived from the FL diet than from the SO diet. The FL supplemented diet improved the nutritional value of milk due to a reduction in saturated fatty acids (SFA) and an increase in polyunsaturated acids (PUFA) and conjugated linoleic acid (CLA). The decrease in n-6/n-3 in observed milk was more pronounced with the FL diet. No differences in the sensory profile were found for the milk and cheese derived from the different dietary treatments. Keywords: goat, flaked linseed, salmon oil, fatty acid, sensory profile.

Deep learning (DL) algorithms used for DOTATATE PET lesion detection typically require large, well-annotated training datasets. These are difficult to obtain due to low incidence of gastroenteopancreatic neuroendocrine tumors (GEP-NETs), and the high cost of manual annotation. Furthermore, networks trained and tested with data acquired from site specific PET/CT instrumentation, acquisition and processing protocols have reduced performance when tested with offsite data. This lack of generalizability requires even larger, more diverse training datasets. The objective of this study is to investigate the feasibility of improving DL algorithm performance by better matching the background noise in training datasets to higher noise, out-of-domain testing datasets. 68Ga-DOTATATE PET/CT datasets were obtained from two scanners: Scanner1, a state-of-the-art digital PET/CT (GE DMI PET/CT; n=83 subjects), and Scanner2, an older-generation analog PET/CT (GE STE; n=123 subjects). Set1, the data set from Scanner1 was reconstructed with standard clinical parameters (5 minutes; Q.Clear) and list-mode reconstructions (VPFXS 2, 3, 4, and 5-minutes). Set2, data from Scanner2, representing out-of-domain clinical scans, used standard iterative reconstruction (5 minutes; OSEM). Reconstructed datasets were divided into training, validation, and testing datasets in a 60%, 20%, 20% proportion, and a deep neural network was trained with each: Network1 for Scanner1 and Network2 for Scanner2. DL performance (Network1) was tested with out-of-domain test data (Set2). To evaluate the effect of training sample size, we tested DL model performance using a fraction (25%, 50%, and 75%) of Set1 for training. Scanner1, list-mode 2-minute reconstructed data demonstrated the most similar noise level compared that of Set2, resulting in the best performance (F1=0.713). This was not significantly different compared to the highest performance, upper-bound limit using in-domain training for Network2 (F1=0.755; p-value=0.103). Regarding sample size, the F1 score significantly increased from 25% training data (F1=0.478) to 100% training data (F1=0.713; p&lt;0.001). List-mode data from modern PET scanners can be reconstructed to better match the noise properties of older scanners. Using existing data and their associated annotations dramatically reduces the cost and effort in generating these datasets, and significantly improves the performance of existing DL algorithms. List-mode reconstructions can provide an efficient, low-cost method to improve DL algorithm generalizability.

Background: Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and large extent of non-additive genetic variance associated with its autotetraploid genome. Methods: To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as autotetraploid and diploid dosage, plus allele ratios) and SNP marker subsetting (all available SNPs; only genic regions; only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used Genotyping by Sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and onset of flowering, assessed on 143 genotyped plants from a genetically-broad European reference population and their phenotyped half-sib progenies. Results: On average, allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), SNP subsetting offered an advantage compared with any tested subsettings (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting reached better performances. We also released Legpipe2, a SNP calling pipeline tailored for reduced representation (GBS, RAD) medium-sized genotyping experiments.

The Shimensi super-large tungsten polymetallic deposit is located in Late Jurassic- Early Cretaceous Porphyry-Skarn tungsten ore belt in the south Yangtze metallogenic belt. There are 3 types of mineralization: veinlet-disseminated type, thick quartze vein type and hydrothermal crypto-explosive breccia type. Based on geological studies, this paper presents new petrographic, microthermometric, laser Raman spectroscopic and hydrogen and oxygen isotope research of the fluid inclusions from the deposit. The results show that there are five different types of fluid inclusions: liquid-rich inclusions, vapor-rich inclusions, pure liquid inclusions, pure vapor inclusions, and fluid inclusions containing a solid crystal. The homogenization temperatures of the fluid inclusion range from 140℃-270℃, the salinities are 3%-5% NaCleq and the densities of ore-forming fluid range from 0.64 g/cm3 to 0.99 g/cm3. For the analyses of Laser Raman spectroscopic, the ore-forming fluids can be approximated by a Ca2+-Na+-SO42--Cl- fluid system with small amount of CO2, CH4 and N2. Otherwise, the datas of the pressure, pH and Eh show a fluid metallogenic environment of low pressure, weak acid and weak reduction. The values of the homogenization temperature in 3 types of orebodies suggest that the mineralization is characterized by the decrease of the temperature under the condition of the fluid immiscibility. The H-O isotope values are interpreted to indicate that the ore-forming fluids are mainly composed of magmatic water, and also the meteoric water was added with the process of the magma rising.