Pseudopregnancy (PPG) is a common reproductive disorder in dairy goats, characterized by the accumulation of sterile fluid in the uterus and persistence of a corpus luteum, leading to temporary infertility and reduced farm efficiency. This study mainly aimed to determine the profile of pregnancy-associated glycoproteins (PAGs) in dairy goats, and to evaluate the potential of the PAGs/P4 ratio as a novel biomarker for PPG diagnosis. A total of 605 Saanen and crossbreed goats were evaluated via transabdominal ultrasonography, at 34.5 ± 0.5 days after bucks´ removal, in four intensive dairy farms, and presenting an overall incidence of 7.8%. Blood samples from PPG (n = 47), non-pregnant (NPG; negative control; n = 11) and pregnant (PG; positive control; n=10) does were collected for PAG and P4 analysis. Plasmatic levels of PAGs of PPG was similar (0.08 ± 0.02) to NPG (0.13 ± 0.04; p >0.05), but lower than PG group (1. 45 ± 0.04 S-N OD; p <0.001). PAGs/P4 ratio was lower in PPG (0.01 ± 0.11; p < 0.001)) than in NPG (0.24 ± 0.23) and PG (0.18 ± 0.23) groups. The sensitivity and specificity of this biomarker to diagnosis PPG was 98.8% and 100%, respectively. The area under the survival curve (AUC) was 99.6 for cut-off of 0.04 and 97.9% of sensibility and specificity. This study suggests that the PAGs/P4 ratio can serve as a reliable biomarker for PPG diagnosis, helping to distinguish it from pregnancy and non-pregnancy, and improving reproductive management in dairy goats.

Maintaining patient trust, providing quality care, and safeguarding patients' rights and safety, all of which require strong adherence to ethical principles. This study assessed the key differential factors influencing healthcare ethics (HCE) practice in two Ghanaian hospitals. This study employed an analytical cross-sectional design, utilizing simple random sampling to recruit 382 healthcare professionals. Bivariate analysis was conducted using Chi-square tests and T-tests, while Random Forest analysis was applied to identify variables of relative importance to HCE practice. The study found no significant differences in HCE knowledge or practices between the facilities. However, in both facilities, knowledge of HCE significantly influenced HCE practice, indicating that individuals with better knowledge of HCE were more likely to practice HCE. Further, the analysis identified age, knowledge, education, and facility type as the most relevant factors in general. In the sub-analysis, the key factors varied between facilities: for Facility A, age, knowledge, gender, and the intention to change profession were most relevant, while for Facility B, knowledge, education, gender, and age were the dominant factors. HCE training programs should be tailored to meet the unique needs of each facility to ensure effectiveness since factors influencing HCE may vary by facility.

The present study investigates the general characteristics of mesoscale eddies in the Global Ocean, as identified and tracked by the TOEddies algorithm (Laxenaire et al., 2018) implemented on a global scale. Applied to satellite observations (AVISO/DUACS) of Absolute Dynamic Topography (ADT), TOEddies provides daily information on eddy dynamical characteristics (e.g., size and intensity) over a 30-year period (1993-2023) and identifies complex eddy-eddy interactions that lead to eddy splitting and merging. By capturing the multiple merging and splitting events that a single eddy can undergo, TOEddies generates a complex network of eddies that challenges the conventional view of a single trajectory associated with a single eddy. Furthermore, it offers an original assessment of interconnected eddy trajectories. A statistical description of the average characteristics of the eddies and their spatial distributions (generation, disappearance and merging/dividing is first provided. A comparative analysis of existing global eddy datasets is then presented. Among the years of observations, several coherent, long-lived mesoscale eddies with lifetimes exceeding 1.5 years stand out. However, we find that only a small fraction of these eddies is comparable between datasets, while their dynamic properties can differ substantially. Furthermore, the detection of eddies from altimetry is combined with 23 years of Argo profile co-localised measurements (2000-2023), allowing us to further investigate their contribution to the global subsurface ocean.

Diabetic foot sepsis (DFS) is the leading cause of lower extremity amputations and timely initiation of effective antimicrobial therapy is paramount during its management. This study investigated causative microorganisms and their antimicrobial susceptibility profile in patients with DFS. Methods: A retrospective review was conducted on patients who were 18-years and older admitted for DFS. . Data collected included demographic: information, comorbidities, clinical findings, type of specimen collected for microbiology and microbiology results, treatment and outcomes. Data was analysed using STATA/SE version 17.0 and a p-value of 0.05 considered statistically significant. Results: Hundred and sixty-eight records were found of which 64.3% of patients were male who also had a median (IQR) age of 58 years (IQR 54-65). In comparison, females had a median age of 61 years (IQR 54-67). The microbiology results were available in 63.1% of the records and 60.4% were taken from tissue specimens (60.4%) and 14.2% from pus swabs (14.2%). Enterococcus faecalis was cultured in 16%, Proteus mirabilis 10%, and Staphylococcus aureus in 8%. Amoxicillin/Clavulanic acid was prescribed for 69% of the cases. Resistance to at least one antimicrobial was observed in 88% of Staphylococcus aureus and 80% of Proteus mirabilis species. Conclusions: Diabetic foot sepsis commonly affects males around the age of 60 years. The commonly cultured organism in patients with DFS are Enterococcus faecalis 16%, Proteus mirabilis 10%, and Staphylococcus aureus. Amoxicillin/Clavulanic acid as the primary antimicrobial therapy and in close to 40% of patients, with DFS, antimicrobial treatment is not preceded by collection of a specimen for MC&S despite high rates of resistance seen in the common cultured organisms. This data may assist with updating local guidelines so as to better manage this condition in an evidenced based way.

N-methyl-D-aspartate receptors (NMDARs) are critical components of the mammalian central nervous system, involved in synaptic transmission, plasticity, and neurodevelopment. This review focuses on the structural and functional characteristics of NMDARs, with a particular emphasis on the GRIN2 subunits (GluN2A-D). The diversity of GRIN2 subunits, driven by alternative splicing and genetic variants, significantly impacts receptor function, synaptic localization, and disease manifestation. We explore the physiological properties and developmental regulation of these subunits, highlighting their roles in the pathophysiology of various NDDs, including ASD, epilepsy, and schizophrenia. By reviewing current knowledge and experimental models, including mouse models and human-induced pluripotent stem cells (hiPSCs), this article aims to elucidate different approaches through which the intricacies of NMDAR dysfunction in NDDs are currently being explored. The comprehensive understanding of NMDAR subunit composition and their mutations provides a foundation for developing targeted therapeutic strategies to address these complex disorders.

Estuaries and deltas possess significant socioeconomic importance and exhibit high ecological value because of their dynamic geomorphic processes and unique geographical advantages. However, delta recession and the instability of river regimes have become worldwide issues due to intensive human interventions in upstream river basins and local areas in recent decades. This study focuses on a typical example, the South Branch of the Changjiang Estuary, to explore its morphological evolution in the past decades and near future and propose suitable solutions to enhance the stability of the river regimes. Based on bathymetric data analysis, we find significant channel-shoal adjustment within the South Branch from 1958 to 2016, characterized by substantial erosion and deposition on decadal timescales. After 1997, the South Branch experienced overall erosion due to the reduced fluvial sediment supply. Disturbances on the Baimao Shoal and Biandan Shoal further aggravated the river regime’s stability. Numerical predictions for future evolution trends indicate continuous erosion in the South Branch over the next 20 years, with further adjustments to the channel-shoal pattern. Hydrodynamic modeling of the proposed measures demonstrates an increased ratio for the North Baimao Shoal Channel, leading to enhanced stability of the channel-shoal system. These integrated governance measures have been incorporated in the new round of renovation planning for the Changjiang Estuary. The findings provide valuable scientific guidance for the comprehensive management of the Changjiang Estuary and offer insights applicable to other large estuaries.

There is a growing urgency to address society’s complex issues, many of which are incorporated within the Sustainable Development Goals (SDGs). Higher education has a special role and responsibility to support and promote these goals. The SDG framework helps students understand SDGs, but special competencies are necessary to address them effectively. Sustainability competencies impart the personal/emotional development missing from current programming, but higher education institutions have been reluctant to introduce them into the curricula. This study examines the ongoing debate about integrating sustainability competencies into higher education curricula. We employed a scoping review to synthesize the current issues and highlight key barriers to changing the curricula. Contrary to a commonly expressed theme in the literature, scholarly opinion has converged around a singular model for sustainability competencies, the framework proposed by Wiek et al. (2011) and the 2021 update. Integrating sustainability competencies into management education responds to SDG-4 (quality education) and yields far-reaching impacts. The interconnectedness of the goals means that students acquire the competency to understand, address, and promote various SDGs. Given the absence of a policy decision to integrate sustainability competencies into higher education curricula, this paper provides a timely summary of the issues to focus on discussion and potential action. The focus is on business schools and changing management education. Business schools have been selected given the heightened demand from society for businesses to be more involved in and share responsibility for complex global issues like sustainability.

The widespread adoption of the QWERTY keyboard layout, designed primarily for English, presents significant challenges for speakers of indigenous languages such as Quechua, particularly in the Puno region of Peru. This research examines the extent to which the QWERTY layout affects the writing and digital communication of Quechua speakers. Through an analysis of the Quechua language’s unique alphabet and character frequency, combined with insights from local speakers, we identify the limitations imposed by the QWERTY system on the efficient digital transcription of Quechua. The study further proposes alternative keyboard layouts, including optimizations of QWERTY and DVORAK, designed to enhance typing efficiency and reduce the digital divide for Quechua speakers. Our findings underscore the need for localized technological solutions to preserve linguistic diversity while improving digital literacy for indigenous communities. The proposed modifications offer a pathway toward more inclusive digital tools that respect and accommodate linguistic diversity.

During their life cycle, plants constantly respond to environmental changes. Abiotic stressors affect the photosynthetic and respiratory processes of plants. Reactive oxygen species (ROS) are produced during aerobic metabolism and play an important role as regulatory mediators in signaling processes, activating the plant's protective response to abiotic stress and restoring "oxidation-reduction homeostasis". Cells develop normally if the rates of ROS production and the ability to neutralize them are balanced. To implement oxidation-reduction signaling, this balance must be disrupted either by an increase in ROS concentration or a decrease in the activity of one or more antioxidant systems. Under abiotic stress, plants accumulate excessive amounts of ROS and if the ROS content exceeds the threshold amount dangerous for living organisms, it can lead to damage to all major cellular components. Adaptive resistance of plants to abiotic stressors depends on a set of mechanisms of adaptation to them. The accumulation of ROS in the cell depends on the type of abiotic stress, the strength of its impact on the plant, the duration of its impact and the recovery period. The aim of this review is to provide a general understanding of the processes occurring during ROS homeostasis in plants, oxidation-reduction processes in cellular compartments in response to abiotic stress and the participation of ROS in signaling processes activating adaptation processes to abiotic stress.

Ephrin type A receptor 2 (EphA2) binds to membrane-bound ligands, ephrin A1, A2, and A5, eliciting bidirectional signaling. This signaling regulates many physiological processes, such as tissue development, homeostasis, and regeneration. The dysregulation of the EphA2-ephrins axis contributes to various diseases, including cancers. The high expression of EphA2 is observed in various cancers, which promotes cancer malignancy, whereas its levels are relatively low in most normal adult tissues. Therefore, EphA2 is a promising target for cancer therapy. In this study, we developed anti-human EphA2 monoclonal antibodies using the Cell-Based Immunization and Screening method. Among them, a clone Ea₂Mab-7 (IgG₁, κ) exhibited a high affinity and sensitivity in flow cytometry. The dissociation constant values of Ea₂Mab-7 for CHO/EphA2 and MDA-MB-231 cells were determined as 7.7 × 10⁻⁹ M and 2.1 × 10⁻⁹ M, respectively. Furthermore, Ea₂Mab-7 can detect endogenous EphA2 in western blot and immunohistochemistry. Therefore, the Ea₂Mab-7 is highly versatile for basic research and is expected to contribute to clinical applications, such as antibody therapy and tumor diagnosis.

This paper examines the impact of neoliberal urbanism on socio-spatial inequalities in Chile, focusing on housing commodification and urban fragmentation. Utilizing a thematic analysis of key academic literature from the past two decades, the study explores the ethical challenges faced by urban practitioners in reconciling profit-driven urban development with the right to the city. The findings highlight how neoliberal policies have intensified segregation in cities like Santiago, where wealth and resources are concentrated in affluent areas, while peripheral, impoverished regions suffer from limited access to services. This dynamic perpetuates cycles of exclusion and marginalization, challenging efforts toward spatial justice. The paper also considers potential alternative frameworks for urban governance and policymaking that could foster more inclusive, equitable urban environments. Ultimately, the study calls for a redefinition of urban planning strategies to prioritize social equity over market imperatives, advocating for a more participatory and democratic approach to urban development.

This paper analyzes Chipotle Mexican Grill’s public relations strategy in response to the 2015 E. coli outbreak that severely impacted its reputation and financial standing. The company’s delayed initial response exacerbated the crisis, leading to a significant decline in stock prices and consumer trust. However, through leadership changes, enhanced safety protocols, strategic marketing campaigns, and customer loyalty programs, Chipotle gradually rebuilt its image and began to recover financially. The paper explores the short- and long-term effects of the crisis on Chipotle and outlines key lessons for companies facing similar PR challenges, emphasizing the importance of swift crisis management, transparency, and proactive communication in restoring public confidence.

Plant‒fungal associations often drive plant invasion success by increasing host growth, disease resistance, and tolerance to environmental stress. In this study, to determine whether the numerically dominant foliar endophyte Colletotrichum can directly enhance the resistance of the invasive plant Ageratina adenophora to disease and environmental stressors, we planted sterile A. adenophora seedlings, inoculated them with three endophytic fungal strains of Colletotrichum with distinct genetic backgrounds and compared their role in the resistance of A. adenophora to the pathogenicity of three foliar pathogens from the Didymellaceae family, as well as to abiotic stress, including drought and nutrient stress. We observed that the foliar endophyte Colletotrichum reduced photosynthesis-related physiological indicators, increased resistance-related indicators, and decreased the biomass of A. adenophora in the absence of pathogen attack, drought and nutrient stress. However, some endophytic Colletotrichum strains exhibit positive effects on resistance to certain foliar pathogen attacks, and some endophytes increase the biomass of A. adenophora under drought or nutrient stress. Our results revealed that there are certain positive effects of foliar Colletotrichum endophytes on A. adenophora in response to biotic and abiotic stresses, which may be beneficial for its invasion.

The increasing volume of Municipal Solid Waste (MSW), including biodegradable plant residues such as pruning, leaves, and kitchen waste, presents a substantial environmental challenge due to the limited availability of landfill space and the resulting environmental contamination. Sustainable waste management practices, encompassing recycling and waste-to-energy conversion through biological or thermochemical processes, are imperative. In the Municipality of Athens, Greece, significant quantities of green waste generated from public and private gardening activities provide a valuable opportunity for energy recovery and landfill waste reduction. In accordance with Directive 2008/98/EC, Athens emphasizes waste prevention, reuse, recycling, and recovery. This study examines alternative bio-waste and green waste management systems, with examples from Europe, focusing on the Athens Directorate of Urban Green Spaces and Urban Wildlife. It discusses methods for assessing the energy value of pruning residues, providing a definitive disposal framework. Additionally, it presents a technoeconomic study of one of the Municipal Swimming Pools in the Municipality of Athens, investigating the production and distribution of thermal energy to meet the heating needs of the pool facilities. This research identifies key constraints and their impact on decision-making, highlighting the potential for alternative green waste management. It advocates modern recycling techniques in line with national and Community legislation, demonstrating significant environmental and economic benefits.

The WHO is so passionate about good health for all meanwhile the emerging counselling discipline is a complimentary arm whose interest is to fully complement those efforts through helping humankind in issues that may be affecting the health and the overall well-being. The researcher has discovered through studies and general knowledge that men tend to delay in seeking health help compared to women. Men appear to be reluctant in seeking professional assistance in problems pertaining to their health, marriages, work place, infertility, sexual dysfunction and other social life ills subsequently leading to depression, suicides, excessive uptake of alcohol, violence, mental psychosis and physical disabilities or premature death. Studies have shown that men are socially constructed to be strong from a tender age and they grow into adulthood believing that they are strong both physical and emotional hence they are supposed to withstand any situation affecting them. Masking and faking have been regarded as sign of being a real man, however these social constructs, perceptions and expectations appear to be the root cause of problems manifesting daily in men’s behavior towards seeking health help. This study therefore endeavors to find out more about the factors or determinants influencing men’s reluctance to seeking help in areas concerning their health in Industrial site of Victoria Falls. The study serves as additional educational awareness guide for the significant other, while issues unraveled help in gender mainstreaming programs for gender equality when it comes to societal hegemonizing of men’s health. Moreover, the exploration of influencing factors or determinants, causes and effects of men’s reluctance in seeking health help were scrutinized as well as possible solutions. There has been much realization of more various literature on women’s issues than men because women in general have been known to open up and talk through their issues unlike men hence the aim is to focus on men in order to understand the attitude and perceptions underlying the reluctance to seek medical care regularly and promptly. When communities get to understand that men too, feel the pain both emotionally and physically, may be then, men would not fear stigmatization but come out to seek health help promptly and communities would realize that some cultural expectations placed on men result in more harm than good.

VEXAS syndrome, a monogenic X-linked disorder resulting from mutations in the UBA1 gene, has emerged as a key model for unraveling the links between systemic inflammatory or autoimmune diseases (SIAD) and myelodysplastic syndromes (MDS). This syndrome is characterized by the presence of vacuoles, X-linked inheritance, autoinflammation and somatic mutation patterns, highlighting a unique intersection between genetic and immunological dysregulation. Apart from VEXAS, 10% to 30% of individuals diagnosed with MDS exhibit SIAD phenotypes, a significant increase compared to the 5% incidence in the general population. In this comprehensive review, we aim to elucidate the molecular mechanisms driving the pro-inflammatory environment in MDS, focusing on the contribution of VEXAS syndrome to this complex interplay. We examine how UBA1 mutations disrupt cellular homeostasis, triggering inflammatory pathways. Furthermore, we explore the broader implications of these findings for the pathogenesis of MDS, proposing that the inflammatory dysregulation of VEXAS may shed light on mechanisms of disease progression and identify potential therapeutic targets in MDS. Through an integrated analysis of genetic, immunological and clinical data, this review seeks to deepen our understanding of the complex relationship between systemic inflammation and hematological malignancies, paving the way for new diagnostic and therapeutic strategies.

Jute fiber reinforced composites have become a very promising alternative to synthetic fiber composites because of their favorable environmental characteristics, cost efficiency, and good mechanical properties. The present review provides a comprehensive examination of the manufacturing processes and mechanical properties of composites reinforced with jute fibers. This study investigates the influence of several fabrication methods, such as hand lay-up, compression molding, injection molding, pultrusion, etc. on the mechanical properties of the composites. It also provides the SWOT analysis of various manufacturing processes of jute fiber reinforced composites. The important aspects including fiber orientation, fiber-matrix adhesion, and the effects of different surface treatments on improving mechanical characteristics such as tensile strength, flexural strength, and impact resistance are discussed. The difficulties associated with moisture absorption, degradation, and the lack of uniformity in jute fibers, as well as approaches to alleviate these problems are presented. The goal of this study is to establish a basis for future investigation and advancement in enhancing the mechanical properties of jute fiber reinforced composites.

Pyridine was degraded in a rotating photodisc reactor (RPR) using zinc oxide (ZnO) doped with aluminum nanoparticles (ZnO-Al) as a catalyst and natural light lamps. The reactor disks, made of clay, have a surface area of 329.7209 m². The reactor was operated as a semi-batch system, handling a volume of 14.8 L and a hydraulic residence time (HRT) of 72 hours at 54 rpm with a constant flow rate. The results indicated an average degradation of 50.6% after an HRT of 72 hours, with a maximum degradation of 62%. Characterization results confirmed the effectiveness of the doping process, showing an aluminum concentration of 4.11% by mass in the catalyst, as determined by X-ray techniques. Overall, the doping process proved effective for the zinc oxide catalyst, as evidenced by a reduction in the catalyst bandgap from 3.37 eV for undoped ZnO to 3.08 eV for the doped version, making it sufficiently active under natural light.

This paper presents a comprehensive review of the transformative impact of 3D printing technology on smart cities. As cities face rapid urbanization, resource shortages, and environmental degradation, innovative solutions such as additive manufacturing (AM) offer potential pathways for sustainable urban development. By synthesizing 66 publications from 2015 to 2024, the study examines how 3D printing improves urban infrastructure, enhances sustainability, and fosters community engagement in city planning. Key benefits of 3D printing include reducing construction time and material waste, lowering costs, and enabling the creation of scalable, affordable housing solutions. The paper also addresses emerging areas such as the integration of 3D printing with digital twins (DT), machine learning (ML), and AI to optimize urban infrastructure and predictive maintenance. It highlights the use of smart materials and soft robotics for structural health monitoring (SHM), and repairs. Despite the promising advancements, challenges remain in terms of cost, scalability, and the need for interdisciplinary collaboration among engineers, urban planners, and policymakers. The findings suggest a roadmap for future research and practical applications of 3D printing in smart cities, contributing to the ongoing discourse on sustainable and technologically advanced urban development.

pending

The main weakness of non-silicone hydrogel contact lenses is their low oxygen permeability (Dk). Hence, we have tried to optimize their Dk using various concentrations and lengths of the ethylene glycol dimethacrylate (EGDMA) crosslinker in a mixture of N, N- Dimethylacrylamide and Cyclohexyl methacrylate monomers. After synthesizing the different contact lenses, we evaluated the impact of the different EGDMA conditions on their chemical, optical, and mechanical properties. The water content, the contact angle, the refractive index, the transmittance, and the young moduli of the synthesized lenses were slightly affected by crosslinker conditions. On the contrary, the elongation at break and, more importantly, the oxygen permeability, which reached values of up to 74.93 Fatt units, were considerably impacted by crosslinker conditions. This study demonstrates, for the first time to our knowledge, that, in addition to water, other usual hydrogel components, like crosslinkers, can modulate the Dk of non-silicone contact lenses. It also provides a simple and scalable method to fabricate more permeable non-silicone lenses.

Ovarian cancer is diagnosed at a locally advanced stage in two-thirds of cases. The first line of treatment consists of cytoreductive surgery (CRS) combined with neoadjuvant and/or adjuvant chemotherapy. However, CRS can be associated with high rates of postoperative complications (POCs) and detection of fragile patients at high risk of POCs is important. The American College of Surgeons Surgical Risk Calculator (ACS-SRC) provides a predictive model for early POCs (30 days) for any given surgical procedure. This study aimed to evaluate the performance of the ACS-SRC in predicting the occurrence of early POCs for patients undergoing CRS for ovarian cancer. This was a retrospective study that included patients undergoing CRS for advanced ovarian cancer between January 2010 and December 2022. Early POCs were reviewed and the rate of POCs was compared with those predicted by the ACS-SRC to evaluate its accuracy (i.e., discrimination and calibration). A total of 218 patients were included, 112 of whom underwent extensive surgery/resection. A total of 94 complications were recorded. This cohort demonstrated correct calibration of the ACS-SRC for the prediction of surgical site infection (SSI), readmission, and the need for nursing care post-discharge (NCPD; transfer to revalidation center or need for nursing care at home). Using both the discrimination and calibration methods, the score only predicted NCPD. In this study, the ACS-SRC was shown to be of little value for patients undergoing cytoreductive surgery for ovarian peritoneal carcinomatosis, as it only accurately predicted NCPD.

Quantum computing operates using qubits, the basic units of quantum information, which enable quantum algorithms to solve complex problems that classical computers cannot efficiently handle. This review provides a comparative analysis of several promising qubit technologies, including superconducting qubits, topological qubits, spin qubits, photonic qubits, ion trap qubits, and nitrogen-vacancy (NV) centers in diamonds. We discuss the operational principles, key researchers and institutions in each field, current advancements, challenges, and future directions for these technologies. This paper aims to present a thorough overview of the different approaches in qubit technologies and their potential impacts on quantum computing’s future landscape.

Cells compartmentalize biochemical processes taking advantage of physical barriers in the form of membranes. Eukaryotes have a wide diversity of membrane-based compartments that can be used in this context, with the main ones being the extracellular membrane, which separates the inside from the outside of the cell, and the nuclear membrane, that separates the nucleus from the cytoplasm. The nuclear membrane not only isolates and protects the DNA and the transcription and replication processes from the other processes that are taking place in the cytoplasm, but also has an active role in the regulation of cellular signaling. The TGF-ß pathway is one of the most important and conserved signaling cascades, and it takes advantage of compartmentalization using a well-tuned balance between import and export rates of active and inactive forms of key proteins. Thus, compartmentalization serves as an additional regulatory mechanism, physically isolating transcription factors from their targets, influencing the dynamics and strength of signal transduction. his contribution focuses on this biophysical layer of regulation. It begins with an in-depth review of the TGF-ß pathway and the main regulatory processes underlying this compartmentalization mechanism. Next, we focus on several contributions that study how this compartmentalization shapes the dynamics and ultimately the cell response, and how this separation can be used as readout of several cellular responses. Finally, we introduce a simplified mathematical approach to study this process derived using a generalized formulation.

In this work, a new hybrid compound3,4-diaminopyridinium perchlorate with the formula (C5H8N3)ClO4abbreviated 3,4-DAPP was synthesized in aqueous solution at room temperature by the slow evaporation method. It crystallizes in the monoclinic system,with a non-centrosymmetric space group P21with the following parameters: a=5.1261 (9), b=9.3003 (17),c=8.6659 (16) Å and β=102.595 (7) °. However, the supramolecular crystal structure was built from perchlorate anions (ClO4)- and organic diaminopyridinum cations (C5H8N3)+connected with hydrogen bonds to form a three-dimensional network. Fourier transform infrared (FTIR) and Raman spectra indicate that the vibrational modes correspond to both inorganic and organic entities. According to Hirschfeld’s analysis, the crystal packing is mainly stabilizedby the presence of hydrogen bonds O⋯H (50%), as well as the crystal void analysis indicates the mechanical stability of the structure. Furthermore, the thermal behavior studied by thermogravimetric (TGA-DTA) and differential scanning calorimetry (DSC) appears to have good stability up to 280°C. Finally, the optical properties were investigated by UV-Vis absorption and photoluminescence spectroscopy along with density-functional theory DFT calculations, whichexhibit emission property, and a band gap energy of 3.9 eV.Additionally, biological activity tests revealed that 3,4-DAPP exhibited moderate antibacterial activity, particularly against Bacillus cereus, though it was less effective than 3,4-diaminopyridine (3,4-DAP) against several other bacteria, indicating that the perchlorate group in 3,4-DAPP may reduce its antimicrobial efficacy.

The clinical outcome for children diagnosed with acute lymphoblastic leukemia is a testimony to the success of modern medicine. Over the past several decades, survival has climbed from ∼ 10% to > 90% for certain subgroups. Yet, the outcome for those with relapsed disease is often poor and survivors struggle with a multitude of healthcare issues, some of which are lifelong. In recent years, the advent of widespread sequencing of tumors has made available previously unrecognized subtypes of leukemia patients who have the potential to benefit from the addition of targeted therapies. Indeed, the promise of precision medicine encompassing a person's environment, genetics and lifestyle is likely to have profound impact on further tailoring therapies that are likely to improve outcomes, diminish toxicity and ultimately pave the pathway for a healthier population.

The study presents a methodology, used in the design development of stepper motors. The methodology unites virtual and physical techniques to assess the structure under development at its various design stages. Virtual prototyping is used twice, at the concept and early design stages. Concept check aims to give more general directions for further design development, while the simulations at the detailed design stage allow assessing various design parameters at a high level of confidence. The testing of a physical prototype is used to validate simulation results. It is also used to check the design just before it's finished. The presented methodology is demonstrated in an industrial use case for stepper motor development for hydraulic valve application.

Credit scoring is a cornerstone of financial risk management, enabling financial institutions to assess the likelihood of loan default. However, widely recognized contemporary credit risk metrics, like FICO or Vantage scores, remain proprietary and inaccessible to the public. This study aims to devise an alternative credit scoring metric that mirrors the FICO score, using an extensive dataset from Lending Club. The challenge lies in the limited insights available on both the precise analytical formula and the comprehensive suite of credit-specific attributes integral to the FICO score's calculation. Our proposed metric leverages basic information provided by potential borrowers, eliminating the need for extensive historical credit data. We aim to articulate this credit risk metric in a closed analytical form with variable complexity. To achieve this, we employ a symbolic regression method anchored in Genetic Programming (GP). Here, Occam's razor principle guides evolutionary bias towards simpler, more interpretable models. To ascertain our method's efficacy, we juxtapose the approximation capabilities of GP-based symbolic regression with established machine learning regression models, such as Gaussian Support Vector Machines (GSVMs), Multi-Layer Perceptrons (MLPs), Regression Trees and Radial Basis Function Networks (RBFNs). Our experiments indicate that GP-based symbolic regression offers comparable accuracy with these benchmark methodologies. Moreover, the resultant analytical model offers invaluable insights into credit risk evaluation mechanisms, enabling stakeholders to make informed credit risk assessments. This study contributes to the growing demand for transparent machine learning models by demonstrating the value of interpretable, data-driven credit scoring models.

The global aging population has experienced rapid growth in recent decades, leading to an increased prevalence of psychiatric disorders, particularly depression, among older adults. Depression in the elderly is often compounded by chronic physical conditions and various psychosocial factors, significantly impacting their quality of life. This paper explores the epidemiology of geriatric depression, highlighting the influence of gender, race, and socio-economic status on its prevalence. The classification and diagnosis of geriatric depressive disorders, based on ICD-11 and DSM-5 criteria, reveal the complexity of managing these conditions in older adults. Personalized Medicine (PM) emerges as a promising approach, focusing on tailoring treatments to the individual’s genetic, clinical, and environmental characteristics. However, the application of PM in this demographic faces challenges, particularly in the context of pharmaceutical forms. The need for age-appropriate drug delivery systems is critical, given the prevalence of polypharmacy and issues such as dysphagia among the elderly. This study emphasizes the importance of developing patient-centric formulations to enhance the effectiveness of personalized therapy in geriatric patients.

AI-driven applications are rapidly growing, and more applications are joining the market competition. As a result, the AI-as-a-Service (AIaaS) model is experiencing rapid growth. Many of these AIaas-based applications are not properly optimized initially. Once they start experiencing a large volume of traffic, different challenges start revealing themselves. One of these challenges is maintaining a profit margin for the sustainability of the AIaaS application-based business model, which depends on the proper utilization of computing resources. This paper introduces the Resource Award Predictive (RAP) model for AIaaS cost optimization called RAP-Optimizer. It is developed by combining a Deep Neural Network (DNN) with the simulated annealing optimization algorithm. It is designed to reduce resource underutilization and minimize the number of active hosts in cloud environments. It dynamically allocates resources and handles API requests efficiently. The RAP-Optimizer reduces the number of active physical hosts by an average of 5 per day, leading to a 45% decrease in server costs. The impact of the RAP-Optimizer has been observed over a 12-month period. The observational data show a significant improvement in resource utilization. It effectively reduces operational costs from $2,600 to $1,250 per month. Furthermore, the RAP-Optimizer increases the profit margin by 179%, from $600 to $1,675 per month. The inclusion of the Dynamic Dropout Control (DDC) algorithm in the DNN training process mitigates overfitting, achieving a 97.48% validation accuracy and a validation loss of 2.82%. These results indicate that the RAP-Optimizer effectively enhances resource management and cost-efficiency in AIaaS application, making it a valuable solution for modern cloud environments.

Aging affects structure and functions of all organs and systems in the organism. Significant changes in the hormonal levels are registered in elderly individuals. They often become a predisposition for chronic diseases, including cardiovascular, neurodegenerative, and metabolic disorders. Therefore, immense scientific efforts are concentrated in the investigation of molecular mechanisms and drugs with potential to diminish the senescent hormonal changes. Sirtuin 1 (SIRT1), a member of the sirtuin deacetylases family, has been extensively studied as regulator of multiple pathways related to antioxidant properties, optimal immune response and metabolism. SIRT1 plays a crucial role in regulating various hormonal pathways and maintaining homeostasis. In the present work we review the interplay between SIRT1 and hormonal regulations, including endocrine role of the hypothalamic-pituitary-thyroid, -adrenal, -gonadal, and -liver axes, of other endocrine glands and of non-endocrine tissues in aging body. The application of natural SIRT1 activators, such as resveratrol, curcumin, paeonol, and Buyang Huanwu Decoction, for treatment of senescence and aging is discussed. SIRT1 activators improve mitochondrial function, reduce oxidative stress, and promote longevity but their clinical application is limited by low bioavailability and poor permeability across biological barriers. For this reason, advanced delivery strategies, including nose-to-brain drug delivery and nanotechnology-based formulations, are reviewed.

This study investigates the impact of environmental factors on intradialytic blood pressure in hemodialysis patients, using a four-year retrospective analysis. Employing a Generalized Estimating Equation (GEE) model, we examined the associations between clinical variables, meteorological conditions (temperature, humidity, wind speed, and precipitation), and blood pressure outcomes, including systolic blood pressure (SBP) and mean arterial pressure. Our results reveal that higher temperatures, increased humidity, and stronger wind speeds are significantly associated with lower SBP and mean arterial pressure. In contrast, higher daily precipitation correlates with elevated mean arterial pressure. Among clinical factors, erythropoiesis-stimulating agent (ESA) dosage shows a positive association with both SBP and mean arterial pressure while a history of intradialytic hypotension and increased interdialytic weight gain are negatively correlated. Additionally, serum potassium levels were inversely related to SBP and mean arterial pressure. These findings highlight the importance of incorporating environmental variables into predictive models for intradialytic blood pressure management. We propose tailored interventions, such as weather-adapted fluid management strategies, personalized treatment plans, and patient education, to mitigate potential adverse effects. This study provides a foundation for enhancing patient-centered care and improving the quality of life for hemodialysis patients amid global climate changes.

Carl Woese’s thesis of cellular evolution emphasized that the last universal common/cellular ancestor (LUCA) must have evolved by drawing from “global inventions”. Yet, existing theories regarding the origin(s) of LUCA have mostly centered upon scenarios that LUCA had evolved mostly independently. In an earlier paper, we have advanced a new thesis regarding the origin(s) of LUCA that extends Woese’s original insights. Our thesis centers upon the possibility that different vesicles and protocells can merge with and acquire each other as a form of variation, selection, and retention, driven by wet-and-dry cycles and other similar cyclical processes. In this paper, we use computer simulation to show that under a variety of simulated conditions, LUCA can indeed be produced by our proposed processes. We hope that our study can stimulate laboratory testing of some key hypotheses that vesicles’ absorption, acquisition, and merger has indeed been a central force in driving the evolution of LUCA.

In the aerospace industry, the performance of materials on extreme conditions is crucial. This study addresses the development of nanoparticle-reinforced composite materials to improve thermal properties and flame retardancy in aerospace applications. As first approach, Zinc oxide (ZnO) nanoparticles were synthesized and incorporated into carbon fibers through the dip coating process. Subsequently, composite laminates were manufactured using the vacuum bag infusion method. The materials were subjected to flammability tests, following FAA regulations, to evaluate their performance against flame spread. The laminates reinforced with ZnO presented promise performances, suggesting a need for optimization in the incorporation of nanoparticles for safer and more efficient applications in the aerospace industry.

This study applied the principal-agent model to interpret the impact of routine biased technological change (RBTC) on the structure of employment relations. RBTC increases the proportion of routine tasks in work activities, due to their fixed procedural nature, routine tasks reduce uncertainties in the principal-agent problem. Employers, being able to predict work contingencies and to verify employee efforts, find the benefit of offering standard labor contracts is reduced, thereby increasing the ratio of non-standard employment. This study applied logistic regression based on the Program for the International Assessment of Adult Competencies (PIAAC) survey data to verify this framework. The results indicated that with each standard deviation increased in routine task intensity, the odds ratio of non-standard employment increased by 13.6%. This effect was heterogeneous in various institutional contexts. This study expends the toolkit for analyzing employment relations problems, and extends the scope of RBTC to employment relations.

With the rapid development of wireless communication networks, using AI to predict complex city-scale network traffic has become a significant research challenge. This paper, based on a Graph Convolutional Network (GCN) architecture, proposes a novel wireless network traffic prediction algorithm focused on predicting city-level communication traffic data at an hourly granularity. The algorithm enhances prediction accuracy through two key innovations: first, we introduce a hierarchical attention architecture that combines dynamic and static attention mechanisms. The static attention mechanism, based on wireless channel models, captures fixed spatial relationships between base stations, such as inter-station distances and stable connections. The dynamic attention mechanism, on the other hand, dynamically adjusts to account for time-varying traffic patterns, such as rush hours and holiday effects, enabling the model to adapt to temporal variations in network traffic. These two attention mechanisms are seamlessly integrated within the model through feature concatenation and interactive learning, allowing the model to capture both spatial and temporal characteristics of network traffic simultaneously. Secondly, we innovatively introduce a strategy for adjusting the aggregation iterations of the Graph Convolutional Network (GCN) based on the Laplacian matrix. By leveraging the spectral information provided by the Laplacian matrix, we dynamically determine the depth of the graph convolutional network, thereby avoiding issues of over-smoothing or underfitting and ensuring stable performance in complex network structures. Experimental results demonstrate that the proposed algorithm significantly outperforms existing methods across multiple dataset, particularly in predicting network traffic data with intricate spatiotemporal characteristics.

Key findings include the modelling of the material behavior when ZnAl15% wires were subjected to the tensile test at different speeds, with strain rate sensitivity coefficient m = 0.0128, demonstrating that this type of alloy is especially sensitive to the strain rate. Besides, the optimal friction coefficient (µ) for the drawing process of this material was experimentally identified as µ = 0.28, the ideal drawing die angle was determined to be 2α = 10°, and the alloy's deformability limit has been established by a reduction ratio r ≤ 22.5%, that indicates good plastic deformation capacity. The experimental results confirmed that the proposed models are feasible for the design and optimization of industrial processes to improve the efficiency and quality of ZnAl15% alloy wire production.

Background/Objectives: Remote monitoring (RM) of cardiac implantable electronic devices for adults offers improved patient outcomes. However, bedside transmitters utilized so far are not optimal due to limited patient adherence. The goal of this study was to evaluate the efficacy of RM regarding the connectivity of smartphone app-based solutions, adherence to planned automatic follow-ups, and occurrence of alert-based events. Methods: We evaluated the adult heart failure (HF) population with implanted cardiac resynchronization therapy defibrillator (CRT-D) divided into two arms: with app-based RM (abRM) and without app-based RM (control). Results: A total of 81 patients (median age of 69.0) were included in our study. 65 patients received a CRT-D with abRM functionality, and 16 did not. 12 patients had no smartphone, and 2 provided no consent, resulting in their transfer to the control group. Finally abRM arm consisted of 51 patients, while 30 patients were in the control group. Median period of follow-up lasted 12 months. Among abRM patients, 98.0% successfully transmitted their first scheduled follow-up, and 80.4% were continuously monitored. Alert-based events were mainly related to arrhythmic events and device functionality with significantly shorter median time to notification (1 day vs. 101 days; p<0.0001) in the abRM group. Conclusions: Our study showed a high level of compliance with timely initial transmission and adherence to scheduled remote follow-ups. Patient enrollment eligibility was a major challenge due to the limited accessibility of smartphones in the population. App-based RM demonstrated an accurate notification of events and patient-initiated transmissions in emergencies, regardless of location.

Hepatitis B virus (HBV) can cause chronic infections, significantly increasing the risk of death from cirrhosis and hepatocellular carcinoma (HCC). A key player in chronic HBV infection is covalently closed circular DNA (cccDNA), a stable episomal form of viral DNA that acts as a persistent reservoir in infected hepatocytes and drives continuous viral replication. Despite the development of several animal models, few adequately replicate cccDNA formation and maintenance, limiting our understanding of its dynamics and the evaluation of potential therapeutic interventions targeting cccDNA. In this study, we aimed to develop a mouse model to investigate cccDNA formation and maintenance. We infected C57BL/6 mice with recombinant adeno-associated virus (rAAV) carrying a 1.3-overlength HBV genome (genotype C) and collected liver tissue at various time points to assess cccDNA levels and viral replication. Our results demonstrated the successful establishment of a chronic hepatitis B mouse model using rAAV-HBV1.3, which supported persistent HBV infection with sustained cccDNA expression in hepatocytes. Serum levels of HBsAg and HBeAg were elevated for up to 12 weeks, while alanine transaminase (ALT) levels remained within the normal range, indicating limited liver damage during this period. We confirmed HBV DNA expression in hepatocytes, and importantly, cccDNA was detected using qPCR after Plasmid-Safe ATP-Dependent DNase treatment, which selectively removes non-cccDNA forms. This established model provides a valuable platform for studying the long-term maintenance of cccDNA in chronic HBV infection and offers an important tool for testing novel therapeutic strategies aimed at targeting cccDNA.

Background: Fabry disease is a rare, X-linked, lysosomal disorder caused by pathogenic variants in GLA and consequent deficient activity of alpha-galactosidase A, resulting in glycosphingolipid storage. Although many systemic manifestations of the disease have been documented, the association between Fabry disease and erysipelas has not previously been reported. Objective: To describe a case series of thirteen patients with Fabry disease and erysipelas and identify potential predisposing factors in this population. Patients and Methods: We retrospectively studied a cohort of 223 French patients with a confirmed molecular and enzymatic diagnosis of Fabry disease. Results: Twelve of the 223 patients with Fabry disease had experienced one or more episodes of erysipelas for a total of 70. All 12 patients had classic Fabry disease. There were ten males and two females, one of whom had highly skewed X chromosome inactivation silencing the wild type GLA allele. Lymphedema of the lower legs (10/11), male gender (10/12), and clinically advanced classic Fabry disease (11/12) were the characteristics identified in patients who experienced erysipelas. No patient with the later-onset form of Fabry disease had any episode of erysipelas. Conclusion: Our findings suggest that clinicians should be aware of the risk of erysipelas in patients with Fabry disease and promptly prevent or treat any skin wound or infection in those with lower limbs lymphedema.

Background: This study aims to investigate the influence of Body Mass Index (BMI) on the doses received by organs at risk (OAR) during high-dose-rate (HDR) vaginal cuff brachytherapy in pa-tients diagnosed with early-stage endometrial carcinoma. Understanding the relationship be-tween BMI and OAR doses could enhance treatment planning and minimize complications. Methods: We collected brachytherapy data for 242 endometrial cancer patients treated with ad-juvant HDR vaginal cuff brachytherapy. The patients were categorized based on their BMI into normal weight, overweight, and obese groups. Dosimetric data were collected for OARs, includ-ing the bladder, rectum, and sigmoid colon and also for dose fractionation, D90 and the active length of the brachytherapy cylinder. The analysis included comparing the doses received by each organ across different BMI categories using appropriate statistical methods Results: Preliminary findings indicated a significant variation in the doses to OARs correlating with BMI classifications. Obese patients exhibited slightly higher mean doses to the rectum and bladder compared to those with a normal BMI. The statistical analysis demonstrated that as BMI increased, the dose to these organs at risk also tended to increase, suggesting a need for ad-justed treatment planning strategies in this population. Conclusions: Obesity is a key concern in endometrial cancer patients, with higher BMI linked to slightly increased doses to the rectum and sigmoid, though treatment remained homogeneously delivered.Future work should focus on refining dosimetric techniques and exploring strategies to mitigate OAR exposure in patients with higher BMI.

Sirtuin 1 (SIRT1), a member of the NAD+-dependent deacetylases, plays a pivotal role in epigenetic regulation related to aging. As the most extensively studied sirtuin, SIRT1 influences numerous cellular processes including metabolism, DNA repair, and cell survival, by deacetylating both histone and non-histone proteins. Epigenetic modifications in SIRT1, such as DNA methylation and post-translational histone modifications, have profound effects on gene expression and chromatin structure, contributing to age-related pathologies including metabolic disorders, neurodegeneration, and cancer. SIRT1 also interacts with several transcription factors such as p53 and FOXO, regulating stress responses and cellular senescence. Its activity is modulated by factors such as NAD+ availability and specific activators like resveratrol, which have been explored for their potential to delay aging processes. The role of SIRT1 in promoting longevity is linked to its involvement in the regulation of key pathways like calorie restriction, a well-established method for extending lifespan in various species. Understanding SIRT1's epigenetic mechanisms offers promising therapeutic avenues for addressing aging and associated diseases.

Agroecosystem function is related to the positioning of the agroecosystem and its connectivity relationship with the surrounding landscape. Herein three methodologies are presented, which allow assessment of the links between agroecosystems and the surrounding matrix, yielding information for promoting patterns and mechanisms which foster biodiversity and the provision of multiple ecosystem services such as biological pest control, as well as energy flows and material exchanges. Through the use of 11 indicators a methodology (Assessment of Beneficial Insect Habitat Suitability-ABIHS) was applied in two northern California vineyards to determine whether each agrolandscape provided suitable environmental opportunities to sponsor biological insect pest control. The Main Agroecological Structure [MAS] applied in Chilean family farms, elucidates some of the relationships between farms and their biophysical environment, generating data to analyze the links between agroecosystem landscapes, management practices, and insect diversity in family farms. Agrarian metabolism (AM) applied in Spanish agrolandscapes, quantifies the biophysical and energy flows in agricultural systems testing whether such flows are capable of reproducing and/or improving fund elements such as soil, biodiversity, and landscape vegetation, in successive production cycles. The three methodologies provide key information for the design of sustainable agroecosystems in the context of an agroecological transition.

The recreational waters of hotels are widely used by locals and travelers all around the world and this impacts public health. In this regard, WHO frequently offers recommendations - especially in the COVID-19 era - so operators and managers of public pools, hot tubs or splash pads should continue to follow. This study aims to evaluate the microbiological results of COVID-19 sanitation protocols in recreational waters in hotels during the summer periods of post-COVID-19 (2020–2022) and compare them with those of pre-COVID-19 (2019). We found positive samples for different parameters in the period of 2019: 11.5 % for total coliforms (18/157), 12.2% for common aerobic bacteria (19/156), 2.9% for E. coli (5/170), and 18.2% for P. aeruginosa (27/148). For the pandemic years, the percentages of positive samples were: 8.1% for total coliforms (40/493), 1.3% for common aerobic bacteria (7/526), 1.3% for E. coli (7/526), and 18.4% for P. aeruginosa (83/450). The study found that the relative risk (RR) from the presence of P. aeruginosa in recreational waters with chlorination 25°C. Although non-compliance decreased at the beginning of the pandemic due to strict health protocols, this gradually stopped.

For the first time, we describe phylogenomic signatures of an epidemic lineage of vesicular stomatitis Indiana virus (VSIV). We applied multiple evolutionary analyses to a dataset of full-length genome sequences representing the circulation of an epidemic VSIV lineage in the US between 2019 and 2020. Based on phylogenetic analyses, we predicted the ancestral relationship of this lineage with a specific group of isolates circulating in the endemic zone of Chiapas, Mexico. Subsequently, our findings indicate that the lineage diversified into at least four different subpopulations during its circulation in the US. We identified single nucleotide polymorphisms (SNPs) that differentiate viral subpopulations and assessed their potential relevance using comparative phylogenetic methods, highlighting the preponderance of synonymous mutations during the differentiation of these populations. Purifying selection was the main evolutionary force favoring the conservation of this epidemic phenotype, with P and G genes as the main drivers of the evolution of this lineage. Our analyses identified multiple codon sites under positive selection and the association of these sites with specific functional domains at P, M, G, and L proteins. Based on ancestral reconstruction analyses, we showed the potential relevance of some of the sites identified under positive selection to the adaptation of the epidemic lineage at the population level. Finally, using a representative group of viruses from Colorado, we established a positive correlation between genetic and geographical distances, suggesting that positive selection on specific codon positions might have favored the adaptation of different subpopulations to circulation in specific geographical settings. Collectively, our study reveals the complex dynamics that accompany the evolution of an epidemic lineage of VSIV in nature. Our analytical framework provides a model for conducting future evolutionary analyses. The ultimate goal is to support the implementation of an early warning system for vesicular stomatitis virus in the US, enabling early detection of epidemic precursors from Mexico.

Tear fluid is emerging as a valuable resource for biomarker discovery, but its low sample volume and dynamic composition pose significant challenges for analytical testing. Most tear proteomics studies have focused on samples collected with Schirmer strips, while capillary tube collection has received less attention. To address these challenges, we developed a novel in-capillary trypsin digestion workflow that requires as little as 0.5 μL of tear fluid for bottom-up shotgun proteomics. This method uses liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify a higher number of proteins with enhanced efficiency compared to previously reported methods, which typically required 5-10 μL of pooled tear fluid. Using the same microcentrifuge tube for both tear collection and sample processing, this streamlined workflow simplifies sample handling and minimizes both sample loss and experimental errors associated with sample transfer. This method also efficiently reduced sample processing time to under 2 hours prior to overnight trypsin digestion, compared to the 5-8 hours required by other methods. With this workflow, we identified 500-800 proteins per 0.5 μL sample without the need for fractionation, allowing for at least three technical replicates. This optimized workflow greatly enhances the efficiency of tear proteomics for biomarker discovery.

Medullary thyroid carcinoma (MTC) is a rare and aggressive tumor, often requiring systemic treatment in advanced or metastatic stages, where drug resistance presents a significant challenge. Given the role of cancer stem cells (CSCs) in cancer recurrence and drug resistance, we aimed to identify CSC subpopulations within two MTC cell lines harboring pathogenic variants in the two most common MEN2-associated codons. We analyzed 15 stemness-associated markers, along with well-established thyroid stem cell markers (CD133, CD44, and ALDH1), a novel candidate (DLK1), and multidrug resistance proteins (MRP1 and MRP3). The ability to efflux the fluorescent dye Hoechst 3342 and form spheroids, representing CSC behavior, was also assessed. MZ-CRC-1 cells (p.M918T), displayed higher expression of canonical markers, DLK1 and MRP proteins than TT cells (p.C634W). MZ-CRC-1 cells also formed more spheroids and showed lower dye accumulation (p < 0.0001). Finally, we found that DLK1+ cells (populations of cells expressing DLK1), exhibited significantly higher expression of stemness markers compared to DLK1- cells (populations of cells negative for DLK1). These findings highlight the role of DLK1 in promoting the stemness phenotype and offer new insights into MTC progression and resistance, with potential therapeutic implications.

Complexity is a crucial metric for evaluating urban intersection scenarios. However, existing complexity evaluations are often derived indirectly from the driving risk of autonomous vehicles, leading to subjective and incomplete evaluations. Therefore, this study undertakes a comprehensive evaluation of intersection scenarios from a systems perspective by quantifying the number of vehicles and the characteristics of vehicle interactions within the intersection.Specifically, we propose an objective framework for assessing complexity. In this framework, the number of vehicles serves as the foundation for assessment, while three interaction characteristics—interaction density, interaction disorder, and interaction risk—are modeled as scaling factors of complexity. In particular, by combining logistic and hyperbolic tangent functions, we accurately capture the nonlinear effects of vehicle numbers and interaction characteristics on complexity.The experimental results demonstrate that the evaluation outcomes of the proposed method are highly correlated with the risk and efficiency performance of autonomous vehicles at intersections, thereby validating the method. Additionally, this method is utilized to guide the generation of highly complex urban intersection scenarios, achieving double the generation efficiency compared to the random sampling method.

Although highlands of East Africa lack the geo-ecological landmarks of Rift Valley fever (RVF) disease hotspots to participate in cyclic RVF epidemics, they have recently reported growing numbers of small RVF clusters. Here, we investigated whether RVF cycling occurred among livestock and humans in the central highlands of Kenya during inter-epidemic periods. A 2-year prospective hospital-based study among febrile patients (March 2022 - February 2024) in Murang’a County of Kenya, was followed by a cross-sectional human-animal survey. A total of 1,468 febrile patients were enrolled at two clinics and sera tested for RVF virus RNA and antiviral antibodies. In the cross-sectional study, humans (n=282) and livestock (n=706) from randomly selected households were tested and questionnaire data used to investigate sociodemographic and environmental risk factors by multivariate logistic regression. No human (n=1,750) or livestock (n=706) sera tested positive for RVFV RNA. However, 4.4% livestock and 2.0% humans tested positive for anti-RVFV IgG, including 0.27% febrile patients who showed 4-fold IgG increase and 2.4% young livestock (<12 months old), indicating recent virus exposure. Among humans, odds of RVF exposure increased significantly (P<0.05, 95% CI) in males (aOR:4.77, 2.08–12.4), those consuming raw milk (aOR 5.24,1.13–17.9), milkers (aOR:2.69, 1.23–6.36), and participants residing near quarries (aOR:2.4, 1.08–5.72). In livestock, sheep and goats were less likely to be seropositive (aOR: 0.27, 0.12–0.60) than cattle. The increase in RVF disease activities in the highlands represents widening geographic dispersal of the virus, and greater risk of more widespread RVF epidemics in future.

The paper proposes an approach to solving the inverse epidemiological problem, written in terms of the “mean field” theory. Finding the coefficients of the epidemiological SIR mean field model is reduced to solving an optimization problem, for the solution of which only zero-order methods can be used. The Nelder-Mead method was chosen as such a method. The algorithm for solution of the inverse coefficient problem is proposed. Computational experiments were carried out to compare the obtained solutions with respect to synthetic and real data. The results of computational experiments have shown the efficiency of this approach. Ways to further improve the approach have also been determined.

Potassium is a critical factor for plant growth, particularly in tomato cultivation, where high K levels are essential for achieving high yields and enhancing fruit quality. This study aimed to investigate the effects of varying potassium nitrate (KNO₃) concentrations on two cherry tomato varieties, ‘Tabtim Deang T2021’ (red) and ‘Sweet Boy 1’ (yellow), grown under hydroponic conditions. The plants were subjected to KNO₃ concentrations of 3.0, 1.5, 0.75, 0.50, and 0.37 mM. The findings revealed that a KNO₃ concentration of 1.5 mM was sufficient to support normal plant growth and maintain optimal fruit quality, including pH, total soluble solids, citric acid, and ascorbic acid content, in both cherry tomato varieties. Additionally, the reduction in KNO₃ concentration did not significantly impact the antioxidant activities of the tomato fruits, as measured by 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) and ferric ion reducing antioxidant power (FRAP) assays. Furthermore, low K fertilization resulted in minimal changes to the physical, chemical, and biological characteristics of the cherry tomatoes. The study concludes that decreasing K concentration in the nutrient solutions has a limited effect on the overall quality of cherry tomatoes.

The implementation of waste management strategies informed by supply chain management methodologies may present a viable solution for the effective handling of waste, as exemplified by the waste management challenges observed in Indonesia. The waste management characteristics exhibited by each nation are inherently diverse, as they are influenced by various factors including supply chain management frameworks, the methodologies and technologies employed in waste processing, the cultural practices and behaviours of the populace regarding waste disposal, as well as the unique geographic conditions pertinent to each country. This study seeks to formulate a waste management supply chain framework that incorporates moderating factors influencing the relationship between sustainable macro ergonomic processes and waste management practices. The research methodology employed was purposive convenience sampling, encompassing a total of 224 participants engaged in waste management within the Semarang region of Central Java, Indonesia. The empirical results indicate that H2—TT exerts a statistically significant influence on RPPS (0.02 < 0.05), H3—TP demonstrates a significant impact on RPPS (0.001 < 0.005), H4—MGE displays a significant effect on RPPS (0.00 < 0.05), H5—seasonal floods (BM) reveal a significant effect on RPPS (0.001 > 0.05), and H6—cultural society (CC) manifests no significant impact on RPPS (0.755 > 0.05). The innovative aspect of this study lies in the finding that cultural society has not exerted an influence on waste management, whereas other macro ergonomic factors have shown a significant effect on this domain.

Gastric cancer has become the cancer with the highest incidence rate in the world.Immunotherapy, especially immune point inhibitors targeting programmed cell death 1（PD-1） or its ligand programmed cell death ligand 1 (PD-L1), has become an indispensable part of the clinical treatment of GC. But, only a few of sufferers experience persistent clinical responses during immunotherapy. In this article, we discuss the current mainstream immunotherapy methods for gastric cancer, introduce the mechanisms that lead to immunotherapy resistance, potential biomarkers that can forecast the occurrence of immunotherapy resistance, and measures to improve the efficacy of immunotherapy.

Background/Objectives: This study aimed to evaluate the impact of image enhancement techniques on the interobserver reliability of tear breakup time (TBUT), tear meniscus height (TMH), corneal fluorescein staining (CFS) scoring, and conjunctivochalasis detection using the Smart Eye Camera (SEC), a portable device for anterior segment examination. Methods: A retrospective analysis was conducted on video recordings captured by SEC from 46 patients with dry eye disease (DED). Three video sets were created: unenhanced (G0), mildly enhanced (G3), and strongly enhanced (G7). Three observers—two DED specialists and one general ophthalmologist—assessed TBUT, TMH, CFS scores, and conjunctivochalasis. Interobserver reliability was evaluated using intraclass correlation coefficients (ICCs) for each image set. Results: Interobserver reliability for CFS scores significantly improved with G3, yielding an ICC of 0.8413. In contrast, G7 improved reliability for TBUT measurements (ICC = 0.7381) but led to a notable decrease in reliability for both CFS scoring (ICC = 0.2259) and conjunctivochalasis detection (ICC = 0.0786). Furthermore, the assessment of TMH demonstrated a progressive decline in accuracy with increasing levels of image enhancement. Conclusions: Image enhancement using SEC improves diagnostic consistency between dry eye specialists and general ophthalmologists, especially for TBUT and CFS assessments. However, excessive enhancement may obscure key diagnostic features, indicating the need for careful optimization of image processing techniques depending on the diagnostic focus.

Mismatch repair (MMR) deficiency can be indicative of Lynch syndrome (LS) and guide treatment with immune checkpoint inhibitors. Colorectal cancers (CRCs) and endometrial cancers (ECs) are routinely screened to identify LS, primarily using immunohistochemistry (IHC) or Microsatellite Instability (MSI) testing, but concordance between methods is variable in ECs. Here, we investigate this variability by using the amplicon sequencing based Newcastle MSI assay (NCL_MSI) to re-analyse 361 ECs from the Ohio OCCPI/OPTEC (n=196) and Manchester PETALS (n=165) trials. NCL_MSI was consistent with Ohio results (94% and 97% concordance with IHC and original MSI assays respectively), and increased concordance in the Manchester cohort from 78% to 86% (MSI) and 84% (IHC). Among discordant Manchester samples, NCL_MSI was significantly associated with MLH1 promoter methylation status (p=0.0028), and had the highest concordance with methylation, 62/69 samples (90%), indicating utility as a screening tool in this tumour type. However, tumours with germline MSH6 defects were only detected efficiently with IHC; 7/8 LS tumours classified as MSS by either MSI assay had isolated MSH6 loss, compared to 4/12 classified as MSI-H by both (p=0.028). Furthermore, reduced MSI signal was observed in tumours with isolated MSH6 loss (p=0.009 Ohio, p=6.2x10-5 Manchester), and in both ECs and CRCs with germline defects although this only reached significance in CRCs (p=0.002). These results provide further evidence that ECs with MSH6 loss in particular, and LS tumours in general, have an attenuated MSI signal, and supports current guidelines specifically recommending IHC for LS detection and immune checkpoint therapy assessment in EC.

Non-melanoma skin cancers (NMSCs), including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), are highly prevalent and a significant cause of morbidity. Image-guided su-perficial radiation therapy (IGSRT) uses integrated high-resolution dermal ultrasound to improve lesion visualization, but it is unknown whether efficacy varies by histology. This large retro-spective cohort study was conducted to determine the effect of tumor histology on freedom from recurrence in 20,069 biopsy-proven NMSC lesions treated with IGSRT, including 9,928 BCC (49.5%), 5,294 SCC (26.4%), 4,648 SCCIS (23.2%), and 199 lesions with ≥2 NMSCs (1.0%). Freedom from recurrence at 2, 4, and 6 years was 99.60%, 99.45%, and 99.45% in BCC; 99.58%, 99.49%, and 99.49% in SCC; and 99.96%, 99.80%, and 99.80% in SCCIS. Freedom from recurrence at 2, 4, and 6 years following IGSRT did not differ significantly comparing BCC vs. non-BCC or SCC vs. non-SCC but were slightly lower among SCCIS vs. non-SCCIS (p = 0.002). There were no significant differences in freedom from recurrence when stratifying lesions by histologic subtype. This study demonstrates that there is no significant effect of histology on freedom from recurrence in IGSRT-treated NMSC except in SSCIS. These findings support IGSRT as a first-line therapeutic option for NMSC regardless of histology.

Subtilisin-like proteins are serine proteases that use two types of catalytic triads: Ser-His-Asp and Ser-Glu-Asp. Here, we investigate the two known families of subtilisin-like proteins, the subtilases (Ser-His-Asp triad) and the serine-carboxyl proteinases (Ser-Glu-Asp triad), and describe local structural arrangements (cores) that govern the catalytic residues in these proteins. We show separation of the cores into conserved structural zones, which can be repeatedly found in different structures, and compare the structural cores in subtilisin-like proteins with those in trypsin-like serine proteases and alpha/beta-hydrolases.

Tomato processing generates a by-product known as tomato pomace (TP), which contains chemically diverse valuable components such as lycopene, phenols, dietary fibre, proteins, and oil. The aim of this study was to characterize bioactive compounds in small-sized tomato pomace and to evaluate the effects of the addition of 10 and 20 % (w/w) of tomato pomace flour (TPF) to durum wheat dough for bread production. Bread containing different amounts of TPF was characterized for physical, chemical, nutritional and sensory characteristics. TPF is an important source of dietary fibre with a total content of approximately 52.3%, of which 5.3% soluble and 47% insoluble. It is also a potential source of natural antioxidants and contains remarkable residual levels of both total carotenoids and polyphenols. TPF addition reduced water loss during baking and significantly affected color parameters and acidity; furthermore, both fortified TPF breads could use the nutrition and health claims on label “High Fibre” according to Regulation (EC) (1924/2006). The sensory "overall" attribute showed similar values in the control and fortified bread samples, suggesting that the overall quality of the bread remained relatively constant, regardless of the percentage of added TPF.

This paper discusses our experience with a computer assisted design for the analysis of an intervention on a digital platform, conducted by the Swedish Tax Agency. The interest was in analyzing the possibilities of estimating the effect of a message (the intervention) on the subsequent tax compliance of taxpayers who had foreign income. The effect size was not expected to be large. However, as the cost of the intervention is very low, even a small effect could be important economically. Due to administrative reasons the number of treated was limited to 500 individuals. Because of the limited sample size and the small expected effect it was imperative to consider an efficient experimental design. The population considered for the experiment consisted of 2,697 individuals. Instead of choosing all except the treated as controls, only 500 were deliberately chosen to examine the efficiency gains of a rerandomization design with real world data. To this end, a simulation study was conducted on the same population as was randomly sampled to be part of the experiment. An important conclusion from this exercise is that regression-based post-stratification on relevant covariates is an equally efficient alternative as rerandomization in this setting. The results are of special interest when experiments are run in organizations where computer assisted designs may be costly.

This research arises from the need to rethink children’s play spaces found in the city through new manufacturing methods of Solid Surface materials such as Krion K-Life 1100 from the Porcelanosa Group, which allow the creation of complex ergonomic shapes. The method consisted of an iterative digital fabrication process, in which a series of molds were developed and adjusted to thermoform the Krion, adapting the design in each iteration according to the results obtained. Parametric digital modeling techniques and in-detph curvature analysis were used to optimize the geometry to meet the technical limitations of the material and the thermoforming process. The results showed that, through precise adjustments in the curvature and thickness of the surface, it is possible to thermoform Krion without defects such as folds or wrinkles, obtaining a complex modular and ergonomic surface suitable for children’s play. In conclusions, Krion is a viable material for the generation of complex double-curved geometries, thus opening up a range of possibilities from the creation of new children’s spaces to parametric facades optimized according to their location.

CNS infiltration (CNS+) leads to serious complications in AML. Cytogenetic and Molecular profile is essential in risk stratification, treatment decisions and envisage prognosis. We utilize the NGS data and cytogenetics as a screening tool, for determining the incidences and specific CNS+ risks, in patients eligible for intrathecal chemotherapy. 52 mutations database per NGS was used for the analysis. 435 newly diagnosed patients underwent frontline induction chemotherapy. 259 (59.5%) patients received LP. The most common molecular mutation in the CNS+ patients were MPN1 (48.3%), FLT3 (22.5%), TET2 (25.8%), RAS / KRAS (25.7%), DMNT3 (19.3%), ASXL1 and (16.1%). Of which 31 patients had confirmed CNS+ disease due to the presence of characteristic markers. CNS+ patients have significantly higher bone marrow blast% (76 vs. 53) (p= 0.0202). WBC count ≥ 100x109/L (OR: 5.614 [2.313-13.626] p=0.0001) in the multivariable analysis, and LDH ≥2ULN (OR: 5.512 [2.176-13.965]; p= 0.0003) in the univariate analysis, revealed higher risk for CNS+. Patients exhibited significantly higher NPM1 mutations (48.4% vs 24.6%, p=0.0053) and 11q23 chromosomal abnormality (12.9% vs 2.19%, p= 0.0139). However, FLT3 by NGS did not predict CNS+ (P=0.1226). CNS+ did not contribute significantly toward CIR (p=0.066), and has no bearing on OS (p=0.9063). Patients presented with either neurological symptoms or accompanied by hyperleukocytosis, elevated LDH, NPM1 positivity or 11q23 abnormality are highly suggestive of CNS+. Therefore, LP is needed to rule-out CNS disease at presentation. NGS did not consistently predict CNS+. A large prospective trial is needed to confirm the results.

Bovine respiratory disease (BRD) inflicts significant losses in cattle farming worldwide and is caused by the co-occurrence of various infectious agents which is often compounded by envi-ronmental factors. It is well known that microorganisms of the Mollicutes class are responsible for respiratory disorders in cattle, including BRD. This review highlights the current role of these microorganisms, in particular Mycoplasma bovis and Mycoplasma dispar, in the aetiology of this disease complex, which has recently shifted towards a primary or predominant cause of the disease.

MGMT promotor hypermethylation is the most important biomarker for predicting temozolomide sensitivity in aggressive glioblastoma (GBM), a disease with a poor prognosis. An MGMT status prediction without biopsy is mandatory for tailored therapy because methylated MGMT patients have better prognosis. To this end, this paper proposes the radiogenomic model for predicting the status of MGMT Promoter methylation in glioblastoma patients based on the multi-modal MRI data and the EfficientNet deep learning architecture. Perhaps using sophisticated machine learning-based non-invasive methods of genetic prognosis may decrease risky biopsies. The Magnetic Resonance Imaging (MRI) sequences in the BraTS21 competition dataset include T1-weighted and contrast-enhanced images, T2-weighted images, and Fluid Attenuated Inversion Recovery (FLAIR) images. Image preprocessing consisted of normalization, scaling, and data augmentation Fourier transformations for cross-modal alignment. The EfficientNet-b0 model was initially pre-trained on ImageNet and then fine-tuned to the binary classification of methylation and unmethylated MGMT. The models were evaluated based on AUC-ROC, accuracy, and the F1 score. The model’s capability of accurately identifying MGMT methylation status was moderate, with an AUC-ROC score of 0.62393 at its best. These differences influenced validation findings: overfit and resulted in accuracy variations for the small or unbalanced datasets. Applying multimodal MRI data elevated feature extraction, proving that deep learning models have radiogenic predictive power. Therefore, this study demonstrates that ALC and DL models can noninvasively estimate MGMT promoter methylation status. They also suffer from problems of overfitting or generalization, which will require some optimization. It might be safer than biopsies and can enhance approaches to glioblastoma treatment.

In Military, Medical, Space, Professional equipments design there is a need to be able to prove that the devices can last a certain length of time with a certain confidence level. Or that reliability must be used in design to inform the design direction, either through component selection, component testing and sort or in amelioration techniques (like redundancy, FEC - Forward Error Correction and so on). A higher level of reliability became a compulsory demand in modern DC-DC converters. Since the latest version MIL-HDBK-217F Notice 2 released in 1995, newer failure rate prediction standards had appeared on the electronic systems reliability market. These are introduced to compensate for the lack of the newest component technology in the above-mentioned standard. When it comes to reliability many studies have shown that the output capacitor bank is demonstrated to be the most critical component. In this work, the failure rate of an output capacitor bank and MOSFET transistor pair used within a high current low voltage buck converter is calculated both by the latest prediction standard SN 29500 and by with the previous standard MIL-HDBK, providing a comparison between the two which is a helpful tool for the output capacitor selection in the early stage design. Both simulation and experimental workbench set-up for the converter was used to detect the temperatures of the components. The SN 29500 standard is particularly useful for components used in harsh environments, providing up-to-date failure rate data and stress models. The components’ environmental conditions were defined by a standard PoL buck converter used for both calculation methodologies. Results are compared by taking account of the influence of the component’s temperature and application of specific parameters such as reference conditions and operating conditions.

This case report describes the innovative treatment of a 73-year-old woman with a Solitary Fibrous Tumor (SFT) using Selective Internal Radiation Therapy (SIRT) with Yttrium-90 resin microspheres. SFTs are rare tumors that pose significant treatment challenges, particularly in cases of recurrence or when the disease has metastasized. Systemic therapies often have limited effectiveness. In this case, the patient initially presented with a pelvic mass that was surgically resected, but she later developed metastatic disease in the liver. After experiencing severe side effects from targeted therapy with sunitinib, SIRT was chosen as an alternative treatment. Remarkably, the patient achieved substantial tumor reduction and symptom relief following this novel intervention. To our knowledge and following extensive literature search, this is the first documented instance of treating SFT with SIRT. It provides new insights into its potential as a therapeutic strategy, especially for cases where conventional treatments are inadequate or cause intolerable side effects. The success of SIRT, in this case, highlights its potential as a less invasive, locally targeted treatment option and may offer new hope for patients with similar conditions.

Cervical cancer (CC) remains a critical global health concern, ranking as the fourth leading cause of cancer-related mortality among women, with an estimated 604,000 new cases and 342,000 deaths in 2020. The primary etiological factor for CC is infection with high-risk strains of the Human papillomavirus (HPV), which often goes unrecognized due to the immune system's ability to clear the virus. Emerging evidence suggests that the vaginal microbiome (VMB) plays a pivotal role in modulating the immune response, influencing oncogenesis, and impacting HPV clearance. This review discusses the dynamics of the VMB, emphasizing its diversity and how various factors, such as hormonal fluctuations and ethnicity, shape its composition. A balanced VMB, characterized by a predominance of Lactobacillus species, is crucial for maintaining local immune defenses and preventing dysbiosis, which can lead to chronic inflammation and increase the risk of CC. Conversely, dysbiotic conditions with reduced Lactobacillus and increased anaerobic bacteria have been correlated with HPV persistence and disease progression. The potential of probiotics to restore a healthy VMB and enhance immune responses offers a promising avenue for CC prevention and management. Further research into the VMB's role in HPV pathogenesis is essential for developing targeted therapeutic strategies to mitigate CC risk.

Tailored Skincare and Wellness Solutions for HIV-Positive Individuals: Addressing Skin Conditions, Joint Pains, and Memory Loss. Research Topic This research aims to explore tailored skincare and wellness solutions for HIV-positive individuals, specifically focusing on addressing skin conditions, joint pains, and memory loss. The research question revolves around developing innovative and effective medical approaches to improve the quality of life for this population. Research Importance The topic is crucial as it addresses the unique challenges faced by HIV-positive individuals, highlighting the need for tailored healthcare solutions. By understanding and addressing the physical symptoms associated with HIV, such as skin conditions, joint pains, and memory loss, the research contributes to enhancing the overall well-being and quality of life of individuals living with HIV. Research Method The research encompasses a comprehensive analysis of existing literature, including studies on dermatological problems, musculoskeletal issues, and cognitive impairments in HIV-positive individuals. Additionally, the development of a proposed skincare and serum line, RadientResilience, is based on a careful consideration of pharmacological effects and the unique skin conditions of this population. Research Findings The research findings emphasize the prevalence of dermatological conditions as a significant marker for HIV in affected populations. Furthermore, the study highlights the importance of thorough clinical assessment and the potential use of specific compounds and ingredients to alleviate joint discomfort in HIV-positive individuals. Research Conclusions The interpretations and conclusions drawn from the research underscore the need for tailored medical approaches to address the unique healthcare needs of HIV-positive individuals. The proposed skincare and serum line, RadientResilience, represents an innovative and empowering solution providing effective care for this targeted audience. Research Implications The research has implications for the development of specialized skincare and wellness products tailored to address the specific needs of HIV-positive individuals. Potential challenges in developing and implementing tailored skincare and wellness solutions for HIV-positive people include stigma and discrimination, as well as logistical and financial constraints. As Bouabida, Chaves, and Anane (2023) noted, “Stigma and discrimination are major barriers to HIV care engagement and adherence” (Challenges and barriers to HIV care engagement and care cascade: viewpoint, para. 3). Additionally, the authors highlight that “logistical and financial constraints can limit access to necessary healthcare services” (para. 5). Logistical and financial constraints can limit access to necessary healthcare services for individuals living with HIV by creating barriers such as transportation challenges, limited availability of healthcare professionals, and financial strain related to medical expenses.

The article describes the use of deep neural networks to detect small floating objects located in the own vessel’s path. The research aimed to evaluate the performance of deep neural networks by classifying sea surface images and assigning the level of threat resulting from the detection of objects floating on the water, such as fishing nets, plastic debris or buoys. Such a solution could function as a decision support system capable of detecting and informing the watch officer or helmsman about possible threats and reducing the risk of overlooking them at a critical moment. Several neural network structures were compared to find the most efficient solution, taking into account the speed and efficiency of network training and its performance during testing. Additional time measurements have been made to test real-time capabilities of the system. The research results confirm that it is possible to create a practical lightweight detection system with Convolutional Neural Networks that calculates safety level in real time.

Anxiety-based cognitive distortions pertaining to somatic perception (ABCD-SPs)—primarily catastrophizing, fear avoidance, and kinesiophobia—have been repeatedly linked to worsening chronic, non-cancer pain (CNCP) outcomes of increased disability, amplified pain, ineffective opioid use, and opioid misuse. Several studies have suggested that treating ABCD-SPs can improve pain outcomes, yet identification and targeting of ABCD-SPs are not part of the standard medical pain assessment and treatment plan. Utilizing a narrative review of proposed mechanisms, published patient perspectives, and study correlations connecting these cognitive distortions with CNCP outcomes, an approach for better practice in the delivery of standard medical CNCP care can be deduced and formulated into a Belief and Behavior Action Plan (BBAP) for medical clinicians treating CNCP to implement into initial and maintenance care planning. These recommendations require relatively few resources to implement and have the potential to disseminate more effective CNCP treatment on a large scale now and in the future with the new frontier of cognitive computing in medicine.

Chronic Hepatitis B Virus (HBV) infection remains a significant public health concern, particularly in Africa, where the burden is substantial. HBV is an enveloped virus, classified into ten phylogenetically distinct genotypes (A – J). Tests to determine HBV genotypes are based on full-genome sequencing or reverse hybridization. In practice, both approaches have limitations. Whereas diagnostic sequencing, generally using the Sanger approach, tends to focus only on the S-gene and yields little or no information on intra-patient HBV genetic diversity, reverse hybridization detects only known genotype-specific mutations. To resolve these limitations, we developed an Oxford Nanopore Technology (ONT)-based HBV diagnostic sequencing protocol suitable for clinical virology that yields both complete genome sequences and extensive intra-patient HBV diversity data. Specifically, the protocol involves tiling-based PCR amplification of HBV sequences, library preparation using the ONT Rapid Barcoding Kit, ONT GridION sequencing, genotyping using Genome Detective software, recombination analysis using jpHMM and RDP5 software, and drug resistance profiling using Geno2pheno software. We prove the utility of our protocol by efficiently generating and characterizing high-quality near full-length HBV genomes from 148 residual diagnostic samples from HBV-infected patients in the Western Cape province of South Africa, providing valuable insights into the genetic diversity and epidemiology of HBV in this region of the world.

The assessment methods for estimating the behavior of the complex mechanics of reinforced concrete (RC) structural elements were primarily based on experimental investigation, followed by collective evaluation of experimental databases from the available literature. There is still a lot of uncertainty in relation to the strength and deformability criteria that have been derived from tests due to the differences in the experimental test setups of the individual research studies that are being fed into the databases used to derive predictive models. This research work focuses on structural elements that exhibit pronounced strength degradation with plastic deformation and brittle failure characteristics. The study’s focus is on evaluating existing models that predict the shear strength of RC columns, which take into account important factors including the structural element’s ductility and axial load, as well as the contributions of specific resistance mechanisms like that of concrete, transverse, and longitudinal reinforcement. Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. Three ML models, LINREG, POLYREG-HYT, and XGBoost-HYT-CV, were used to develop different predictive models that were able to compute the shear strength of RC columns. According to the numerical findings, POLYREG-HYT and XGBoost-HYT-CV derived models outperformed other ML models in predicting the shear strength of rectangular RC columns with the correlation coefficient having a value R greater than 99% and minimal errors. It was also found that the newly proposed predictive model derived a 2-fold improvement in terms of the correlation coefficient compared to best available equation in the international literature.

Extended-spectrum beta-lactamase (ESBL) -producing and multidrug resistant Enterobacterales pose a major threat to both human and animal health. This study assessed the prevalence of ESBL-producing Escherichia coli (ESBL-Ec) and Klebsiella spp. (ESBL-K) in cattle farms in Ouagadougou, Burkina Faso, using a One Health approach. From May 2021 to September 2022, cattle faeces, farmers’ stools, their drinking water and farm soil samples were collected from semi-intensive and traditional farms. ESBL-selective medium was used to obtain resistant isolates, which were further characterized using biochemical tests. An-timicrobial susceptibility testing was performed using the Kirby-Bauer disc dif-fusion method. ESBL-Ec and/or ESBL-K were detected in 188 of 322 samples (58.0%). The prevalence of ESBL-Ec isolates was 42.2% (136/322) and ESBL-K isolates 24.5% (79/322). Notably, 156 of the 188 ESBL isolates (83.0%) exhibited multidrug resistance. The highest resistance rates were observed against tetracy-cline and cotrimoxazole. Importantly, no isolates showed resistance to mero-penem, which was used to test for carbapenem resistance. This study highlights the presence of ESBL-Ec and ESBL-K among humans, animals and the envi-ronment of the cattle farms. Good hygiene and biosafety practices are essential to limit the potential spread of multidrug resistant bacteria between different inter-faces on farms.

This survey delves into cross layer energy-efficient solutions and cutting-edge security measures for Internet of Things (IoT) networks. The conventional security techniques are considered inadequate, leading to the suggestion of AI-powered intrusion detection systems and novel strategies such as blockchain integration. In this paper, we provide a comprehensive review and analysis of secure and energy efficient cross-layer framework for IoT.We highlight the significance of developing IoT security for robust and sustainable connected systems. We discuss multi-layered security approaches and ways to enhance energy efficiency of resource-constrained devices in IoT networks. Finally, we identify open research issues and future research directions in the emerging field ofcross-layer design for secure and energy efficient IoT networks. We expect this study will stimulate further research endeavors to build a secure and energy-efficient framework for next-generation IoT systems.

Traditionally, professionals in the tourism sector have been encouraged to segment their market based on socio-demographic variables. However, the multifaceted nature of tourist activity calls for consideration of psychological factors to effectively shape marketing strategies. This study aims to provide insights for tourism industry practitioners by investigating the roles of tourists’ personalities and travel motivations in shaping their activities, and commitment to sustainability in Cumbria, home to UNESCO World Heritage Sites like The Lake District National Park, and Hadrian's Wall. Data was collected using quantitative methods to identify correlations between personality traits, travel motivations, and tourist activities. Additionally, a qualitative focus group with SME representatives from Cumbria provided insights into their understanding of the model. The findings provide significant insights into how the relationship between personality traits, travel motivations and tourist activities benefit tourism SMEs. By comprehending tourist behaviour, SMEs can tailor their offerings to appeal to the right audience, mitigating the adverse effects of overtourism, and therefore do more than allude to the concept of sustainability. Using these insights, SMEs could make informed decisions and create more effective marketing strategies, fostering sustainable practices that benefit both their customers and the long-term viability of their businesses and the destination.

As a long lifeline system of buried structures, Utility tunnel (UT) is vulnerable to earthquake invading. For utility tunnels with inverted siphon arrangement crossing the river, the seismic response is more complex due to the basin effect of acceleration in the topography and the influence of fluctuating hydrodynamic pressure. Based on a UT project in Haikou, this paper studied seismic response of cast-in-place UT considering the coupled model of water-soil-tunnel structure on ABAQUS software. Herein, the dynamic fluctuation of hydrodynamic pressure is simulated using acoustic-solid interaction model. A viscoelastic artificial boundary was used to simulate the soil boundary effect, and seismic loads were equivalent to nodal forces. Considering seismic invading direction and varying water elevation, the paper investigates the dynamic response characteristics and damage mechanisms of river-crossing utility tunnels. The study shows that basin effects cause the different acceleration amplifying of the soil around the UT in different sections, and the greater damage to the tunnels in bidirectional seismic excitation, which the damage concentrated at the junction of the transition between the horizontal section and the vertical section; Bending moments and axial forces are the dominant mechanical behaviors along the axial direction; and the river water level change influences the internal distribution of the tunnels, showing a certain amount of energy dissipation and seismic damping effects. For the aseismic design of cross-river cast-in-place utility tunnels, bidirectional seismic calculations should be performed, and the influence of river hydrodynamic pressure should not be neglected.

Owing to recent advancements in nanotechnology, magnetic iron oxide nanoparticles (MNPs), particularly magnetite (Fe3O4) and maghemite (γ-Fe2O3), are currently widely employed in the field of medicine. These MNPs, characterized by their large specific surface area, potential for diverse functionalization, and magnetic properties, have found application in various medical domains, including tumor imaging (MRI), radiolabelling, internal radiotherapy, hyperthermia, gene therapy, drug delivery, and theranostics. However, ensuring the non-toxicity of MNPs when employed in medical practices is paramount. Thus, ongoing research endeavors are essential to comprehensively understand and address potential toxicological implications associated with their usage. This review aims to present the latest research and findings on assessing the potential toxicity of magnetic nanoparticles. It meticulously delineates the primary mechanisms of MNPs toxicity at the cellular level, encompassing oxidative stress, genotoxic effects, disruption of the cytoskeleton, cell membrane perturbation, alterations in the cell cycle, dysregulation of gene expression, inflammatory response, disturbance in ion homeostasis, and interference with cell migration and mobility. Furthermore, the review expounds upon the potential impact of MNPs on various organs and systems, including the brain and nervous system, heart and circulatory system, liver, spleen, lymph nodes, skin, urinary, and reproductive systems.

The main goal of this research is to create biocompatible hydrogels using gelatin and a double cross-linking technique involving both covalent and ionic bonds to immobilize propolis. Covalent bonds are formed through Schiff base cross-links between protein-free amino groups (NH2) from the lysine residue and aldehyde groups (CHO) produced by oxidizing sodium alginate with NaIO4, while the ionic bonds are achieved using Mg2+ ions. Hydrogel films were obtained by varying the molar ratios -CHO/NH2 under different pH conditions (3.5 and 5.5). The presence of aldehyde groups in the oxidized sodium alginate (OSA) was confirmed using FTIR and NMR spectroscopy. The oxidation degree was monitored over 48 hours, and the influence of temperature was examined. Results showed that higher -CHO/-NH2 molar ratios led to increased conversion index values of NH2 groups, and a decrease in swelling degree values was observed in mediums with pH of 5.5 and 7.4. The encapsulation and release efficiency of propolis decreased with the increase of the hydrogel cross-linking degree. UV irradiation enhanced the antioxidant activity of both free and encapsulated propolis. These findings offer valuable insights into designing biocompatible hydrogels for propolis immobilization, with potential for controlled release in biomedical and pharmaceutical fields.

Background: Wideband tympanometry (WBT) has the potential to distinguish various mechanical middle ear and inner ear pathologies noninvasively. This study investigated the diagnostic value of WBT in the diagnosis of enlarged vestibular aqueduct (EVA). Methods: The absorbance and resonance frequency (RF) of patients with EVA (40 ears, 25 patients) and matched population controls (39 ears, 28 subjects) were compared, alongside receiver operating characteristic (ROC) analysis. Correlations between VA width and RF were also examined. Results: Patients with EVA had higher absorbance at low frequencies (226–917 Hz) and lower absorbance at high frequencies (2,520–4,896 Hz) compared to controls. The RF of the EVA group was significantly lower versus controls (751 [391–1,165] vs. 933 [628–1,346] Hz). ROC analysis revealed area under the curve values of 0.771 and 0.801 respectively, for absorbance and RF. RF had a sensitivity, specificity, positive predictive value, and negative predictive value of 74.4%, 82.5%, 76.7%, and 80.6%, respectively, for diagnosing EVA. In the EVA group, the VA midpoint width (r = −0.334) and VA petrous width (r = −0.402) both significantly correlated with RF. Conclusion: Our findings support the utility of WBT for diagnosing EVA, with RF as the optimal index used.

Hydroelectric power is one of the most essential renewable energy sources in the world. In addition to generating electricity, hydropower offers other benefits such as flood control, irrigation assistance, and clean drinking water. In this study, we examine the evolution of hydropower in the context of energy transition with a forecasting analysis. We analyze time series data of hydropower generation from 1965 to 2023 and apply Innovation Diffusion Models as well as other models such as Prophet and ARIMA for comparison. The models are evaluated for different geographical regions, namely the North, South, and Central American countries, the European countries, and the Middle East with Asian countries, to determine their effectiveness in predicting trends in hydropower generation. The models' accuracy is assessed using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). Through this analysis, we find that, on average, the GGM model outperforms the Prophet and ARIMA models, and is more accurate than the Bass Model. This analysis underscores the critical role of precise forecasting in energy planning and suggests further research to validate these results and explore other factors influencing the development of hydroelectric generation.

The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions. Key themes include the challenges in accurately modeling lignin’s complex structure, the development of efficient screening methodologies for ionic liquids to enhance lignin dissolution and valorization processes, and the integration of machine learning with quantum calculations. These computational advances will drive progress in IL-based lignin valorization by providing deeper molecular-level insights and facilitating the rapid screening of novel IL-lignin systems.

This study aimed to test the effect of toxic leadership on exit intentions and whether burnout syndrome mediates this relationship. This study's sample consists of 309 participants who work in organizations based in Portugal and Angola. The results indicate that toxic leadership positively and significantly affects burnout syndrome and exit intentions. As for burnout, only the disengagement dimension positively and significantly affects turnover intentions. Disengagement partially mediates the relationship between toxic leadership and exit intentions for participants working in Portugal and a total mediation effect for participants working in Angola. Organizations should be concerned about the leadership style adopted by their leaders, because if there is a toxic leader, this will lead to burnout syndrome in their subordinates and cause them to leave the organization, since turnover intentions are the best predictor of voluntary departure from the organization.

Corner joints and edge banding play crucial roles in the strength, durability, and aesthetics of furniture made from particleboards. This review highlights the importance of edge banding on corner joints in enhancing the overall quality of panel furniture. The choice of joint type, materials, and construction techniques can significantly influence the overall appearance and design of the furniture. The quality and design of corner joints directly affect the durability and longevity of furniture. Strong and well-designed corner joints ensure that furniture can withstand various forces and loads without failure or deformation. In addition, corner joints contribute to the aesthetics of furniture by providing seamless and visually appealing connections between different elements. Edge banding plays a crucial role in influencing the strength of corner joints in the furniture. Different edge-banding materials have varying levels of resistance to impact, scratches, and abrasion, which protect furniture surfaces. Overall, edge banding not only enhances the visual appeal of furniture, but also ensures its durability and longevity, both in the service of its purpose and during disassembly and/or transport due to the remodeling of the living space or its relocation. The findings aim to unify the knowledge and set parameters for further research on the quality of corner joints and edge bands in particleboard furniture.

The study investigates methods to enhance the reliability of NO2 monitoring using low-cost electrochemical sensors to measure gaseous pollutants in air by addressing the impacts of temperature and relative humidity. The temperature within a plastic container was controlled using an internal mica heater, an external hot air blower or cooling packs, while relative humidity was adjusted using glycerin solutions. Findings indicated that the Auxiliary Electrode (AE) signal is susceptible to temperature and moderately affected by relative humidity. In contrast, the Working Electrode (WE) signal is less affected by temperature and relative humidity; however, adjustments are still required to determine gas concentrations accurately. Tests involving on/off cycles showed that the AE signal experiences exponential decay before stabilizing, requiring the exclusion of initial readings during monitoring activities. Additionally, calibration experiments in zero air allowed the determination of the compensation factor nT across different temperatures and humidity levels. These results highlight the importance of compensating for temperature and humidity effects to improve the accuracy and reliability of NO2 measurements using low-cost electrochemical sensors. This refinement makes the calibration applicable across a broader range of environmental conditions. However, the experiments also show a lack of repeatability of the zero calibration.

We propose a universal approach for modeling complex integrated photonic resonators based on the scattering matrix method. By dividing devices into basic elements including directional couplers and connecting waveguides, our approach can be used to model integrated photonic resonators with both unidirectional and bidirectional light propagation, with the simulated spectral response showing good agreement with experimental results. A simplified form of our approach, which divides devices into several independent submodules such as microring resonators and Sagnac interferometers, is also introduced to streamline the calculation of spectral transfer functions. Finally, we discuss the deviations introduced by approximations in our modeling, along with strategies for improving modeling accuracy. Our approach is universal across different integrated platforms, providing a useful tool for designing and optimizing integrated photonic devices with complex configurations.

In a V2V communication environment, the control of electric vehicle platoons faces issues such as random communication delays, packet loss, and external disturbances, which affect sustainable transportation systems. In order to solve these problems and promote the development of sustainable transportation, a longitudinal control algorithm for the platoon based on robust Unscented Kalman Filter (UKF) and Model Predictive Control (MPC) is designed. First, a longitudinal kinematic model of the vehicle platoon is constructed, and discrete state-space equations are established. The robust UKF algorithm is derived by enhancing the UKF algorithm with Huber-M estimation. This enhanced algorithm is then used to estimate the state information of the leading vehicle. Based on the vehicle state information obtained from the robust UKF estimation, feedback correction and compensation are added to the MPC algorithm to design the robust UKF-MPC longitudinal controller. Finally, the effectiveness of the proposed controller is verified through CarSim/Simulink joint simulation. The simulation results show that in the presence of communication delay and data loss, the robust UKF-MPC controller outperforms the MPC and UKF-MPC controllers in terms of MSE and IAE metrics for vehicle spacing error and acceleration tracking error, and exhibits stronger robustness and stability.

This paper definitively settles the longstanding conjecture regarding odd perfect numbers. A perfect number is one whose sum of divisors equals itself doubled. While Euclid's method for constructing even perfect numbers is well-known, the existence of odd ones has remained elusive. By employing elementary techniques and analyzing the properties of the divisor sum function, we conclusively prove that no odd perfect numbers exist.

Papillary tumors of the pineal region (PTPR) are extremely rare malignancies usually treated with surgery and adjuvant tumor bed radiotherapy (RT). We present the case of a 69-year-old man diagnosed with PTPR after presenting with two weeks of confusion and ataxia. Imaging the head with computed tomography (CT) and magnetic resonance imaging (MRI) showed hydrocephalus and a 2 cm pineal region mass. We review the presenting symptoms, investigations, and differential diagnosis for patients with pineal region masses. The pathological features, including immunohistochemistry, are described with exemplative images. We report how the patient’s hydrocephalus was managed with medications and neurosurgical interventions, as well as the curative treatment of his tumor with surgery and postoperative tumor bed RT with 54 Gray (Gy) in 30 fractions. We also review the PTPR literature, including prognostic features and the evidence for treatment modalities. Few publications outline adjuvant radiotherapy planning treatment volumes, which are reported here. The patient was followed with a brain MRI every three months and is asymptomatic with no evidence of recurrent disease 18 months after surgery. PTPR has very high local recurrence rates following treatment and further research is needed to find more effective interventions and improve patient outcomes.

HMG-CoA reductase is an enzyme that regulates the initial stage of cholesterol synthesis and its inhibitors are widely used in the treatment of cardiovascular diseases. Methods: We have created a set of quantitative structure-activity relationship (QSAR) models for human HMG-CoA reductase inhibitors using nested cross-validation as the primary validation method. To develop the QSAR models, we employed various machine learning regression algorithms, feature selection methods, and fingerprints or descriptor datasets. Results: We built and evaluated a total of 300 models, selecting 21 that demonstrated good performance (coefficient of determination, R2 ≥ 0.70 or concordance correlation coefficient, CCC ≥ 0.85). Six of these top-performing models met both performance criteria and were used to construct five ensemble models. We identified the descriptors most important in explaining HMG-CoA inhibition for each of the six best-performing models. We used the top models to search through over 220,000 chemical compounds from a large database (ZINC 15) for potential new inhibitors. Only a small fraction (237 out of approximately 220,000 compounds) had reliable predictions with mean pIC50 values ≥8 (IC50 values ≤10 nM). Our svm-based ensemble model predicted IC50 values <10 nM for roughly 0.08% of the screened compounds. We have also illustrated the potential applications of these QSAR models in understanding the cholesterol-lowering activities of herbal extracts, such as those reported for an extract prepared from the Iris × germanica rhizome. Conclusions: Our QSAR models can accurately predict human HMG-CoA reductase inhibitors, having the potential to accelerate the discovery of novel cholesterol-lowering agents and may also be applied to understand the mechanisms underlying the reported cholesterol-lowering activities of herbal extracts.

Globally, life expectancy has been increasing, with South Korea reaching an average of 85.6 years. Therethrough, ‘being healthy’ is essential for a high quality of life, and interest in health and disease prevention grew significantly after the COVID-19 pandemic. The pandemic boosted digital health technology adoption, and emphasizing the need for tailored health strategies based on age group. KIHASA conducted the study of digital confidence and health management methods involving the use of digital devices, and it examines differences in digital device use and confidence between 359 young adults (20–39Y) and 641 middle-aged adults (40–69Y). Respondents were asked about their use of digital health tools, such as wearable devices and mobile apps and confidence in using digital systems and managing health via digital tools was assessed using a five-point Likert scale. We an-alyzed the results, and it indicated that while young adults have lower rates of using digital devices for health care, they exhibit higher confidence in using such devices. In contrast, middle-aged adults, despite having lower confidence, report higher usage of digital devices for health care purposes. This study explored differences in digital confidence and health care usage between age group.

Achieving the energy and climate goals of sustainable development, declared by the UN as an imperative and relevant for the upcoming Society 5.0 with its human-centricity of technological development, requires ensuring a “seamless” Fourth Energy Transition, preserving, but at the same time modifying the role of fossil fuels in economic development. In this regard, the pur-pose of this Review is to analyze the structure of publications in the field of technological plat-form for the energy of the future (Energy 5.0), with digital human-centric modernization and investment of the fossil fuel extraction in the context of the Fourth Energy Transition. To achieve this goal, this Review presents a comprehensive overview of research in the field of determining the prospects of fossil fuels within the Energy 5.0, characterized not only by the dominance of renewable energy sources and the imperative of zero CO2 emissions, but also by the introduc-tion of human-centric technologies of Industry 5.0 (Industrial Internet of Everything, collabora-tive artificial intelligence, digital triples, etc.). It was concluded that further research in such are-as of Energy 5.0 development as the human-centric vector of modernization of fossil fuel extrac-tion and investment, achieving energy and climate goals of sustainable development, reducing CO2 emissions in the minerals extractive sector itself, and developing CO2 capture and utiliza-tion technologies are important and promising for “seamless” Fourth Energy Transition.

Hydrogen sulfide (H₂S) is a highly toxic and corrosive gas commonly found in industrial emissions and natural gas processing, posing serious risks to human health and environmental safety even at low concentrations. Early detection of H₂S is therefore critical for preventing accidents and ensuring compliance with safety regulations. This study presents the development of porous ZnO/SnO₂ heterostructure gas sensors tailored for ultrasensitive detection of H₂S at sub-ppb levels. Utilizing a screen-printing method, we fabricated five different sensor compositions, ranging from pure SnO₂ to pure ZnO, and characterized their structural and morphological properties through X-ray diffraction (XRD) and scanning electron microscopy (SEM). Among these, sensor SnO₂/ZnO with composition weight ratio of 3:4 demonstrated highest response at 325 °C, achieving a low detection limit of 0.14 ppb. The sensor was evaluated for detecting H₂S concentrations ranging from 5 ppb to 500 ppb under dry, humid and N₂ conditions. The relative concentration error was carefully calculated based on analytical sensitivity, confirming the sensor's precision in measuring gas concentrations. Our findings underscore the significant advantages of heterostructure formation in enhancing gas sensitivity, offering promising applications in environmental monitoring and industrial safety. This research paves the way for the advancement of highly effective gas sensors capable of operating under diverse conditions with high accuracy.

This article is a continuation of our previous research on the catalytic capability of chiral copper complex based on commercially available (S)-2-aminomethylpyrrolidine and 3,5-di-tert-butylsalicylaldehyde with various counter-anions in the asymmetric Henry reaction. Our findings indicate that depending on the type of base used, chiral nitroalcohols with yields up to 97% and ee values up to 78%, as well as β-nitrostyrenes with yields up to 82% can be produced. Additionally, it has been found that the outcome of the reaction and the catalytic properties of copper(II) complexes (S)-Cu1 and (S)-Cu2 are influenced by the structure of the aldehyde used.

Designing novel biologically active compounds with anti-inflammatory properties based on condensed quinazolines is a significant area of interest in modern medicinal chemistry. In the present study, we describe the development of promising new bioactive molecules through the bioisosteric replacement of a carbon atom with a sulfur atom in anti-inflammatory agents, specifically 3-methyl-2-oxo-2H-[1,2,4]triazino[2,3-c]quinazolin-6-yl)butanoate. Design and synthetic studies have led to the series of previously unknown substituted 2-[((3-R-2-oxo-2H-[1,2,4]triazino[2,3-c]quinazolin-6-yl)methyl)thio]carboxylic acids and their esters. These compounds were synthesized by reacting 6-chloroalkyl-3-R-2H-[1,2,4]triazino[2,3-c]quinazolin-2-ones with mercaptoalkyl carboxylic acids and their functional derivatives. The purity and structure of the obtained compounds were confirmed using a set of physicochemical methods, including elemental analysis, HPLC-MS, and 1H NMR spectroscopy. Molecular modeling, predicted toxicity, drug-likeness and pharmacokinetics data were used to select compounds for evaluation of their effects on acute aseptic inflammation (carrageenan-induced paw edema test) and on markers of the inflammatory process. The compound 2-((1-(3-methyl-2-oxo-2H-[1,2,4]triazino[2,3-c]quinazolin-6-yl)ethyl)thio)acetic acid (compound 2.5) was identified as the most active anti-inflammatory agent, demonstrating significant inhibition of both paw edema development and the generation of pro-inflammatory cytokines and mediators. Results from docking studies and analysis of "structure-affinity" correlations revealed that these compounds are promising candidates for further modification and detailed investigation of their anti-inflammatory activity

Many measles endemic countries with suboptimal coverage levels still rely on vaccination campaigns to fill immunity gaps and boost control efforts. Depending on local epidemiological patterns, national or targeted campaigns are implemented, following which post-campaign coverage surveys (PCCSs) are conducted to evaluate their performance, particularly in terms of reaching previously unvaccinated children. Due to limited resources, PCCS surveys are designed to be representative at coarse spatial scales, often masking important heterogeneities in coverage that could enhance the identification of areas of poor performance for follow up via routine immunization strategies. Here, we undertake geospatial analyses of the 2021 measles PCCS in Nigeria to map indicators of coverage measuring the individual and combined performance of the campaign and routine immunization (RI) at 1x1 km resolution and the ward and district levels in 13 states. Using additional geospatial data sets, we also produced estimates of numbers of unvaccinated children during the campaign and numbers of measles-containing vaccine (MCV) zero-dose children before and after the campaign at these levels and within health facility catchment areas. Our study revealed that although the campaign reduced the numbers of MCV zero-dose children in all the districts, areas of suboptimal campaign and RI performance with considerable numbers of zero-dose children remained. Our analyses further identified wards and health facility catchment areas with higher numbers of unvaccinated children within these areas. Our outputs provide a robust evidence base to plan and implement follow-up RI strategies and to guide future campaigns at flexible and operationally relevant spatial scales.

Global initiatives such as the Paris Agreement and Agenda 2030 have united nations around common sustainability goals, prompting critical discussions about the true nature of sustainability. A significant concern highlighted by the United Nations is greenwashing—a practice where companies or organisations mislead the public about the environmental benefits of their products or services. Tactics employed in greenwashing include using unclear or misleading labels like “green” and “eco-friendly” or emphasising a single aspect of the product’s lifecycle that appears sustainable while ignoring others. Environmental Product Declarations (EPDs) have gained prominence in response to these challenges, particularly in New Zealand, where government climate declaration regulations have fuelled their demand. This study aims to comprehensively analyse existing EPDs for construction products by identifying and evaluating EPD programs, categorising product types, assessing the completeness of Life Cycle Assessment (LCA) information modules, and verifying the accuracy of declared impact values. The research methodology involves a systematic literature review, drawing data from reputable databases, including Scopus, Elsevier, Taylor & Francis, MDPI, and Emerald Insight, with data analysis conducted using ATLAS.ti 9 software. Examining the current state of EPDs in New Zealand’s construction sector, this study aims to highlight best practices, identify areas for improvement, and provide a foundation for enhancing the transparency and reliability of environmental impact assessments. The findings will contribute to ongoing efforts to combat greenwashing and promote genuine sustainability in construction projects, ultimately supporting the development of more environmentally responsible building practices.

The transformation of Bangladesh from a Digital Bangladesh to a Digital Bangladesh is an ambitious initiative aimed at leveraging digital technologies to drive economic growth, enhance public service delivery, and improve the quality of life for all citizens. This paper explores the strategic roadmap for achieving this vision, focusing on key priorities such as expanding digital infrastructure, promoting digital literacy and skills, fostering innovation and entrepreneurship, enhancing cybersecurity, and strengthening governance and regulatory frameworks. The transformation journey involves significant challenges and opportunities, requiring robust stakeholder engagement, comprehensive policies, and effective monitoring and evaluation mechanisms. Emerging technologies such as artificial intelligence, blockchain, the Internet of Things, and big data analytics present substantial prospects for innovation and efficiency across various sectors. Promoting digital inclusion, bridging the digital divide, and ensuring accessibility and inclusivity are crucial for ensuring that the benefits of digital transformation are widespread. Moreover, enhancing cybersecurity and data privacy is vital for protecting digital systems and maintaining public trust. The paper also highlights the importance of fostering innovation and entrepreneurship, enhancing public service delivery, and strengthening governance frameworks to support the Digital Bangladesh vision. By addressing these strategic priorities and leveraging the collective efforts of government, private sector, academia, and civil society, Bangladesh aims to create a dynamic and resilient digital economy that drives sustainable growth and development. The successful implementation of the Digital Bangladesh vision will position the nation to thrive in the global digital landscape, ensuring a digitally empowered society that benefits all citizens.

In the study at hand a systemic investigation regarding the tribochemical effects of crankcase soot is presented. Sooted oils were generated via an engine dynamometer test. Both conventional as well as advanced oil condition monitoring methods indicated a mild degradation of additives. The wear volume was greatly increased with the sooted oils in model tribometer tests, despite the high residual zinc dialkyl dithiophosphate (ZDDP) antiwear (AW) levels. Once the soot was removed via ultracentrifugation, the wear volume returned to levels comparable to the fresh oil. Surface investigations revealed that ZDDP tribofilms could not form in the sooted oils, as only a thin sulfide layer was present on the metal surfaces. Meanwhile, typical tribofilms were observable with centrifuged oils. The results indicated that a tribocorrosive mechanism is most likely responsible for the elevated wear in the sooted oils, where only the iron sulfide base layer of ZDDP films is formed, which then is rapidly removed by the soot particles in an abrasive manner.

ECM stiffness significantly influences ADSC differentiation, with YAP, a major transcription factor in the Hippo signaling pathway, playing a pivotal role. This study investigates how ECM stiffness affects ADSC differentiation and its relationship with YAP signaling. Different hydrogel concentrations were used to simulate varying ECM stiffness, and their effects on ADSC differentiation were analyzed through material properties, adipocyte-specific gene expression, lipid droplet staining, YAP localization, and protein levels. Results showed that increasing hydrogel stiffness enhanced adipocyte differentiation in a gradient manner. Inhibition of YAP signaling further increased lipid droplet accumulation, suggesting ECM stiffness affects adipogenesis by modulating YAP signaling and its cytoplasmic phosphorylation. This study reveals the molecular mechanism of ECM stiffness-dependent lipid deposition, highlighting YAP's regulatory role in adipogenesis. These findings provide insights into cell differentiation regulation and have implications for tissue engineering and obesity treatment strategies.

This article critically examines the contrasting perspectives of Charles Darwin and Alexander von Humboldt on evolution and the interconnectedness of nature, arguing that Darwin's emphasis on competition has contributed to contemporary ecological crises. While Darwin's theory of natural selection revolutionized biological sciences by focusing on individual competition and the "survival of the fittest," it reflects the competitive and anthropocentric values of Victorian England. In contrast, Humboldt's holistic vision, articulated in his work Kosmos, emphasizes the intricate interdependencies within ecosystems, anticipating modern ecological principles. By exploring the cultural contexts that shaped their theories, this article contends that the widespread adoption of Darwin's competitive framework has fostered exploitative attitudes toward nature, legitimizing environmental degradation and contributing to the current ecological crisis. Embracing Humboldt's interconnected perspective is posited as essential for addressing ecological catastrophes by promoting sustainable practices and fostering a more harmonious relationship with the natural world.

To help limit further climate change, science must be robust and the best available, because it provides insight and understanding, of our impacts and reparations. Although strong standards are part of science, human frailties and facets of society also contribute. Initially, science aided industrialisation of forests, and conservation-oriented science followed. Some early data and methods suit both purposes, but there are different needs, dimensions and scales to consider. Science struggles to blend these frontiers and societal features, such that peer review cannot be the only quality control. Examples are reviewed in depth under two main headings: sustainability and benchmarks. The main arena is a target for industry and conservation: mixed-forests in Tasmania, Australia. Common flaws leading to faulty conclusions were: mis-representing and not noticing earlier studies, inadequately accounting for spatial dimensions and time, and inappropriate benchmarks or error margins when making comparisons. Example results after refinements are: carbon stocks are not sustained within several cycles of first logging primary forest, succession to rainforest may not reduce carbon more than logging cycles, and the proclaimed highest-carbon site is a common peak. Recognizing the carbon legacy and industrial use together through time is necessary for consideration of alternatives and consequent climate-change mitigation.