Abstract: Analysis reproducibility has become one of the main challenges for scientific reporting as it is critical to ensure transparent and comparable results. Metagenomics studies are not exempted from these concerning aspects, and hence bioinformatics pipelines to handle this type of data have evolved rapidly as an attempt to equip the research community with reliable methodologies and procedures. Nonetheless, as these workflows grow in robustness and complexity, inexperienced users find it difficult to understand or customize the pipelines. To address this limitation, we developed an open, interactive and web-based tutorial (TaxoFlow) that guides scholars through the detailed development of a validated and reproducible Nextflow metagenomics profiling pipeline. This workflow integrates software to remove host sequences (Bowtie2), a taxonomic classification (Kraken2), a tool for species abundance re-estimation (Bracken) and different data visualization strategies. As important features, the tutorial emphasizes simplicity, modularity, and containerization, which empowers users with both conceptual understanding and practical implementation skills. Noteworthy, this tutorial provides all the required files, databases, dependencies, software and environment for the user to run without the need of local installation or computational adaptations elsewhere. Finally, by offering a fully reproducible pipeline with a step-by-step developing tutorial, this work aims to lower technical barriers in microbiome bioinformatics and promote best practices in metagenomics data analysis. TaxoFlow is freely available at https://taxoflow.work/.

Abstract: We innovate the Lorentz covariant spacetime curls for the complex Minkowski space, from which the extended Maxwell equations are theoretically derived rigorously. The extended Maxwell equations, which actually arise from the features of the spacetime characterized by the Lorentz transformation, are found to be capable of describing the fields of electromagnetism and weak gravity as distinct solutions in the unified way. The properties of gravitational and electromagnetic fields, such as the interaction force, the energy flux density and the Lagrangian, are obtained homogeneously. The nature that the electric charges with the same sign repel each other and the objects with masses always attract each other, which was previously considered to be the bounty of nature, can now be theoretically derived in this mechanic. Besides, both the electromagnetism and the gravity unfold their mirror descriptions. A unified charge dimension, which will facilitate to the homogeneous description of the two interactions, is proposed. The mechanic is partially examined in a thought experiment.

Abstract: Background: Voice analysis combined with artificial intelligence (AI) is rapidly becoming a vital tool for disease diagnosis and monitoring. A key issue is the identification of vocal biomarkers, that are quantifiable features extracted from voice to assess a person’s health status or predict the likelihood of certain diseases. Currently, the biomarkers are extracted using pitch-asynchronized methods that need improvement. Methods: Based on the timbron theory of voice production, a pitch-synchronous method of vocal biomarker extraction is proposed and demonstrated on standard voice databases, especially the ARCTIC speech databases published by Carnegie Melon University. A complete set of formant parameters and timbre vectors for all US English monophthong vowels are presented. The timbre distances among all US English monophthong vowels are presented, showing the richness and accuracy of information contained in those biomarkers. Results: The methods are then applied on the voice recordings of the Saarbrücken voice database for voice diagnostics. Accurate and reproducible measurements of timbre vectors, jitter, shimmer, and spectral irregularity are generated, showing the usefulness to diagnostics-oriented voice signals. Conclusions: The biomarkers extracted using pitch-synchronous methods might have significant advantages for voice-based diagnostics over the traditional biomarkers. To quantify its effectiveness and accuracy, the pitch-synchronous methods should be tested on large-scale databases for diagnostics tasks to compare with the traditional biomarkers. Furthermore, the method of finding glottal closing instants from voice signals should be tested on voice databases for diagnostics tasks and live voice signals.

Abstract: Purpose – The purpose of this study is to investigate the heterogeneous valuation effects of adopting global investor-focused ESG standards (e.g., GRI, SASB) versus local stakeholder-centric mandates (e.g., EU CSRD, China CSDS). Specifically, it aims to resolve the strategic trade-off MNEs face between pursuing "global standardization" for capital access and "local alignment" for operational legitimacy in a bifurcated regulatory landscape.Design/methodology/approach – Spanning the critical transition period from 2016 to 2023, this study employs a longitudinal research design utilizing a unique dataset of multinational energy enterprises (MNEs) operating in both the European Union and China. The authors applied a fixed-effects panel regression strategy to isolate long-term performance trends and complemented this with an event study methodology to capture market reactions to the regulatory shocks of 2024. Robustness checks, including winsorization and lagged variable models, were employed to ensure validity.Findings – The empirical results reveal three distinct mechanisms: (1) Signal Dilution: Voluntary adoption of global standards yields statistically insignificant financial returns, suggesting they have become baseline "hygiene factors"; (2) Legitimacy Premium: Strict alignment with local mandates—particularly the EU’s CSRD—generates tangible improvements in Return on Equity (ROE) and positive market reactions in China; and (3) Complexity Penalty: A non-linear, inverted U-shaped relationship exists between disclosure intensity and Tobin’s Q, indicating that adopting multiple conflicting standards triggers information overload and discounts firm value.Originality/value – This study contributes to the literature by integrating Signaling and Legitimacy theories into a unified "Regulatory Portfolio" framework. It is among the first to quantitatively identify the "Complexity Penalty" in ESG reporting and proposes the concept of "Strategic Interoperability"—integrating divergent data streams rather than maximizing disclosure volume—as a superior pathway for value creation. The findings offer actionable insights for managers navigating the shift from voluntary to mandatory regimes.

Abstract: The endocannabinoid system (ECS) is a lipid-based, on-demand signaling network essential for maintaining physiological homeostasis across metabolic, immune, cardiovascular, and neurological domains. Proper ECS function is contingent upon the availability of specific dietary nutrients that serve as biochemical precursors, structural components, enzymatic cofactors, and receptor modulators. This analysis examines hemp seeds as a uniquely complete nutritional substrate for ECS support, organizing their contributions according to the three functional pillars of the ECS: endogenous ligands, cannabinoid receptors, and enzymatic machinery. Hemp seeds provide an optimal omega-6 to omega-3 fatty acid ratio, supplying precursors for both arachidonic acid–derived endocannabinoids and anti-inflammatory omega-3 ethanolamides, thereby supporting balanced endocannabinoid tone. Their inclusion of gamma-linolenic acid enables bypass metabolism that further modulates inflammatory signaling. In addition, hemp seeds deliver complete, highly digestible proteins rich in L-arginine, facilitating nitric oxide–mediated vascular responses that intersect with ECS signaling. Essential micronutrients such as magnesium, zinc, and vitamin E support enzymatic function and protect lipid substrates from oxidative degradation. Finally, bioactive phytochemicals including beta-caryophyllene and phytosterols directly influence cannabinoid receptor activation and membrane dynamics. Collectively, these findings position hemp seeds as a functional food capable of supporting ECS integrity through multiple, convergent biochemical pathways.

Abstract: Lipid nanoparticles (LNPs) are a critical structural element of modern mRNA therapeutics, including COVID‑19 modRNA vaccines. Each formulation is a multicomponent system in which the LNP serves not as a passive carrier but as an active, biointeractive entity whose ionizable lipids engage directly with cellular membranes. Current evidence from cellular, transcriptomic, and proteomic analyses indicates that LNPs, with or without active mRNA cargo, alter transcriptomic programs and protein expression. This suggests that, even during uptake and interaction with the membrane (transfection), the membrane serves as an initial site for inflammatory, detoxifying, and stress responses. Simultaneously, pathways involved in fat metabolism and detoxification are affected, such as the peroxisome proliferator-activated receptor γ (PPARγ) and cytochrome P450 (CYP) enzyme systems. We believe that the phosphatidylinositol (PI) cycle is the initial point for these disorders. This cycle regulates both organelle trafficking and membrane restructuring following endocytic processes, including macropinocytosis. When this cycle is disrupted, membrane restructuring and organelle dysfunction occur, triggering downstream signaling cascades such as nuclear factor kappa-B (NF- κB), mitogen-activated protein kinases (MAPKs), Janus kinase–signal transducer (JAK-STAT) pathways, and mechanistic target of rapamycin (mTOR) complexes. Transfection with LNPs may induce a systemic condition we call lipid-nanoparticle-driven membrane dysfunction (L‑DMD), where transfection results in broader dysregulation of cellular communication, stress response, and energy balance. This hypothesis-driven review offers a mechanistic foundation for understanding the diffuse, often enduring, biological effects observed after exposure to messenger RNA LNP formulations. It highlights a needed perspective at the intracellular level and within systems biology.

Abstract: Drone localization is essential for various purposes such as navigation, autonomous flight, and object tracking. However, this task is challenging when satellite signals are unavailable. This paper addresses vision-only localization of flying drones through op-timal window velocity fusion. Multiple optimal windows are derived from a piecewise linear regression (segment) model of the image-to-real world conversion function. Each window serves as a template to estimate the drone's instantaneous velocity. The multiple velocities obtained from multiple optimal windows are integrated by two fusion rules: one is a weighted average for lateral velocity, and the other is a winner-take-all decision for longitudinal velocity. In the experiments, a drone performed a total of six short-range (about 800 m to 2 km) and high maneuvering flights in rural and urban areas. Four flights in rural areas consist of a forward-backward straight flight, a forward-backward zigzag flight (a snake path), a square path with three banked turns, and a free flight that includes both banked turns and zigzags. Two flights in urban areas are a straight outbound flight and a forward-backward straight flight. The performance was evaluated through the root mean squared error (RMSE) and drift error of the ground-truth trajectory and the rig-id-body rotated vision-only trajectory. The proposed image-based method has been shown to achieve flight errors of a few meters to tens of meters, which corresponds to around 3% of the flight length.

Abstract: Background: Menopause results in complex climacteric symptoms that significantly compromise quality of life in postmenopausal women. Here, we specifically evaluated the dual synergistic effects of Gochujang, a traditional Korean fermented food containing fermentation-enhanced isoflavone aglycones and red pepper-derived capsaicinoids, in alleviating menopause-associated symptoms and metabolic dysregulation. Methods: This was a pioneering 8-week, randomized, double-blind, controlled clinical trial designed to assess the therapeutic effects of different Gochujang preparations (high-Gochujang [HGC] and low-Gochujang [LGC]) in postmenopausal women, against a control group (CG). The primary efficacy endpoint was a change in the total Kupperman Menopausal Index (KMI) score. Secondary outcomes included body composition, metabolic marker levels, and safety evaluations. Results: We observed a comprehensive, statistically significant decrease in the total KMI score in both the HGC and LGC groups, with the CG group exhibiting no significant overall improvement, indicating that Gochujang supplementation significantly alleviated climacteric symptoms. Furthermore, we confirmed the anti-obesity effects of Gochujang: a statistically significant decrease in percent body fat was observed in all three groups. The LGC group exhibited beneficial body composition modulation, exhibiting a significant increase in fat-free mass and a corresponding increase in basal metabolic rate without significant changes in overall weight. Moreover, the intervention was well-tolerated, with no adverse changes observed in blood pressure or vital signs. Conclusion: Gochujang supplementation is a safe and effective non-hormonal nutritional strategy. This study provides clinical evidence that Gochujang is suitable for the concurrent management of climacteric symptoms and favorable modulation of metabolic health in postmenopausal women.

Abstract: In the framework of the recently proposed 4G model of final unification, integrating three large atomic gravitational constants corresponding to the electromagnetic, strong, and electroweak interactions, we explore the physical existence of a fundamental electroweak fermion of rest energy 585 GeV. This particle is envisioned as the "zygote" of all elementary fermions and as the weak‐field counterpart to photons and gluons. Using three core assumptions and five defining relations, the model quantitatively reproduces key nuclear and particle physics observables, including the strong coupling constant, nuclear binding energies, neutron lifetime, charge radii, and several dimensionless large numbers. Theoretical string tensions and energies are derived for each atomic interaction (weak, strong, electromagnetic) using experimentally relevant scales (GeV–MeV–eV) rather than the inaccessible Planck scale, thus extending string theory's applicability to testable low‑energy domains. Comparative analysis (Tables 1 and 2) demonstrates close agreement between calculated string energies and known interaction energies, providing a bridge between quantum gravity concepts and measurable nuclear data. String theory’s mathematical consistency requires experimental grounding. Systematically testing different sets of the three atomic gravitational constants (Ge, Gn, Gw) over the next 15 years offers a practical pathway to advance string theory from an abstract mathematical framework to a viable predictive model with experimentally testable interaction-level phenomena. The model predicts astrophysical signatures of the 585 GeV fermion through annihilation and acceleration processes generating TeV–multi‑TeV photons, consistent with Fermi-LAT gamma-ray excesses in the Milky Way halo (0.5–0.8 TeV dark matter mass range, 20 GeV spectral peaks). Our 4G model's charged electroweak fermion at 585 GeV/c² exhibits remarkable numerical proximity to half the supersymmetric Higgsino mass (1.1–1.2) TeV/c², where 2×585 GeV = 1.170 TeV precisely matches both the central Higgsino prediction and the H.E.S.S. cosmic-ray electron spectral break energy. This triple correspondence among independent phenomena, the predicted mass doubling, Higgsino dark matter candidate, and observed electron spectrum transition, reinforces alignment with dark matter, supersymmetry, and high-energy astrophysics theories. The charged fermion may manifest through electron-positron pair production or annihilation processes contributing to the 1.17 TeV spectral characteristics. Such convergence provides compelling experimental search avenues bridging nuclear physics, particle phenomenology, and cosmic-ray astrophysics while demonstrating the model’s ability to unify fundamental constants within an experimentally testable string–gravitational framework.

Abstract: Humans tend to mark their presence and thus their lands by naming charismatic places such as mountains, canyons, rivers, and lakes. Toponyms is the term for marking places with names. In doing so, cultural groups claim the lands and the recognition of their presence through names in their language and behaviors reflecting their culture. When other cultures occupy these lands, they similarly mark them with their own place names, thus replacing earlier names and evidence of occupation. A conflict of toponyms occurs when one cultural group uses their power to maintain a superior attachment to the land. This chapter uses six toponym ethnographic studies to understand the origins of debates between Native American and settler colonial peoples in North American. Research findings from these studies define both the importance of toponyms to cultural groups and possible resolution of heritage conflicts. All studies have been reviewed and approved for public use for place interpretations, visitor education, and culturally appropriate man-agement by funding agencies and participating Native American tribes and pueblos.

Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for enhancing Large Language Models (LLMs) with external knowledge. However, existing ranking methods in RAG pipelines primarily optimize for document-query relevance, neglecting crucial factors for generation quality such as factual consistency and information coverage. We propose a novel multiobjective ranking framework that explicitly models three critical dimensions: relevance, coverage, and faithfulness support. Unlike traditional IR-centric approaches, our method introduces a utilitybased scoring mechanism that evaluates each document’s contribution to reducing hallucinations, improving answer completeness, and maintaining relevance. We formulate the ranking problem as a multi-objective optimization task and employ listwise learning with carefully constructed utility labels derived from existing QA datasets. Extensive experiments on Natural Questions, TriviaQA, and HotpotQA demonstrate that our approach achieves substantial improvements over state-of-the-art baselines, with an average 4.8- point increase (8.6% relative improvement) in Exact Match scores, 10.1% improvement in faithfulness metrics, and 35.7% reduction in hallucination rates compared to RankRAG, all while maintaining computational efficiency comparable to traditional reranking methods.

Abstract: A model of nanoparticles has been designed to resemble partly self-similar ferroelastic star-like domain textures. Numerical computations have been used to find the equilibrium configurations of magnetisation in such systems. As expected from symmetry, the self-similar initial states give room to other types of domain structure as a function of the star parameters. When relaxed without external field the self-similar pattern mostly turns to a massive vortex in the center with radially oriented domains in the peripheral arms of the star. In contrast to that a random initial state ends up in a configuration of a triple valve with one input and two outputs or vice versa in analogy to logical gates. A treatment with an in-plane magnetic field always leads to the valve configuration. The triple-valve states turn out stable and the vortex ones metastable. The results may be useful in the design of magnetic based logic devices.

Abstract: Multimodal Large Language Models (MLLMs) have emerged as a powerful paradigm in artificial intelligence, enabling systems to process and reason over data from multiple modalities, such as text, images, video, and audio. By combining the strengths of different data types, MLLMs offer the potential to tackle more complex and nuanced tasks than traditional unimodal models. This paper provides a comprehensive survey of the current state of MLLMs, examining their architecture, training strategies, applications, and the challenges that remain in scaling and deploying these models. We begin by reviewing the core components of MLLMs, including the integration of modality-specific encoders and the development of joint multimodal representations. The training strategies that support the learning of multimodal interactions, such as contrastive learning, early and late fusion, and self-supervised pretraining, are discussed in detail. Furthermore, we explore a wide range of applications where MLLMs have demonstrated success, including visual-language understanding tasks like image captioning and visual question answering, multimodal sentiment analysis, and human-robot interaction. Despite their impressive capabilities, MLLMs face a number of significant challenges, such as issues with cross-modal alignment, missing modalities, computational inefficiency, and the presence of bias in multimodal datasets. The ethical concerns associated with fairness, interpretability, and accountability are also highlighted. We conclude by exploring future research directions that could help address these challenges and advance the field, including improvements in cross-modal fusion, multimodal pretraining paradigms, model efficiency, and bias mitigation strategies. As MLLMs continue to evolve, they are poised to play a transformative role in various industries, from healthcare and education to robotics and entertainment, by enabling machines to understand and interact with the world in a more human-like and contextually aware manner. This survey aims to provide a comprehensive overview of the current landscape of MLLMs, offering insights into both their potential and the hurdles that remain for their widespread adoption.

Abstract: Fascia has traditionally been described as a passive connective tissue mainly composed of Collagen types I and III. Recent research, however, has revealed its structural and functional complexity, suggesting the possible presence of additional collagen types. This study aimed to quantify the presence and distribution of Collagen types I, III, VI, and XII in human superficial and deep fascia to improve understanding of fascial extracellular matrix composition. Superficial and deep fascia samples were collected from 19 adult patients (ages 20–83 years; thigh and lower back). Histology, Azan Mallory staining, hydroxyproline quantification, Western blotting, and immunohistochemistry were performed. Results indicated that deep fascia contained significantly more total collagen than superficial fascia (0.55 ± 0.17 µg/mg vs. 0.36 ± 0.14 µg/mg, p

Abstract: In this paper, for any real number $\lambdaup$, we transform the complete max-plus semiring $\mathbb{R}_\infty$ into a commutative, complete, additively idempotent semiring $\mathbb{R}_\infty^\lambdaup$, called the lower $\lambdaup$-truncation~of~$\mathbb{R}_\infty$. It is obtained by removing from $\mathbb{R}_\infty$ all real numbers smaller than $\lambdaup$, inheriting the addition operation, shifting the original products by $-\lambdaup$, and appropriately modifying the residuum operation. The purpose of lower truncations is to transfer the iterative procedures for computing the greatest presimulations and prebisimulations between max-plus automata, in cases where they cannot be completed in a finite number of iterations over $\mathbb{R}_\infty$, to $\mathbb{R}_\infty^\lambdaup$, where they could terminate in a finite number of iterations. For instance, we prove that this necessarily happens when working with max-plus automata with integer weights. We also show how presimulations and prebisimulations computed over $\mathbb{R}_\infty^\lambdaup$ can be transformed into presimulations and prebisimulations between the original automata over $\mathbb{R}_\infty$. Although they do not play a significant role from the standpoint of computing presimulations and prebisimulations, for theoretical reasons we also introduce two types of upper truncations of the complete max-plus semiring $\mathbb{R}_\infty$.

Abstract: Background/Objectives: Nutritional status and the gut microbiome play key roles in supporting treatment tolerance and recovery among patients with colon cancer receiving chemotherapy. This pilot study examined (1) changes in diet quality and fecal microbiome profiles during 6-month chemotherapy and (2) associations between diet quality and microbiome diversity and composition over time. Methods: A longitudinal study of 48 adults with stage II–III colon cancer receiving 5-Fluouracil (FU)–based chemotherapy assessed diet quality and the gut microbiome at baseline and 6 months post-chemotherapy initiation. Diet quality was measured using 3-day dietary recalls to compute Healthy Eating Index (HEI) scores. Stool samples collected at both timepoints underwent 16S rRNA sequencing to quantify Shannon diversity and taxonomic composition. Pre–post differences were examined using paired tests, and associations between HEI and microbiome indicators were evaluated with multivariable linear regressions adjusting for demographic and clinical covariates. Results: Diet quality declined during chemotherapy (HEI 62.4→54.2, p=0.015). Shannon diversity also decreased (1.20→1.05, p=0.011). Microbiome composition shifted, with declines in Short-Chain Fatty Acids (the result of fiber fermentation)-producing taxa (Agathobacter, Bifidobacterium, and Prevotella), and increases in Bacteroides and Proteobacteria. Higher baseline HEI was linked to greater microbial diversity, higher levels of beneficial Firmicutes, and lower Proteobacteria. Changes in HEI were significantly aligned with changes in fecal microbiome profiles. Conclusions: Chemotherapy worsens diet quality and gut microbial health. Higher baseline diet quality appeared protective against microbial disruption, supporting a bidirectional diet–microbiome relationship. Early nutritional and microbiome-supportive strategies may help preserve gut resilience during chemotherapy.

Abstract:

Sexual health is a fundamental component of quality of life that is frequently compromised in cancer patients. In melanoma care, these issues remain under addressed despite increasing survivorship. This scoping review aimed to map the current literature on sexual health concerns in melanoma patients. Following PRISMA-ScR guidelines, five databases were searched (2010–2025). Ten studies met the inclusion criteria, including cross-sectional, qualitative, and systematic reviews. Sexual dysfunction affected up to 52% of melanoma patients, with higher prevalence in men (68.9%) than women (41.3%). Contributing factors included visible scarring, hormonal imbalances (e.g., testosterone deficiency in 69% of men receiving immunotherapy), body image concerns, anxiety, and depression. Women were more affected by body image and recurrence anxiety, while men experienced higher rates of treatment-induced hypogonadism. Sexual health concerns are highly prevalent yet systematically overlooked in melanoma care. Gaps remain in longitudinal data, cultural considerations, and evidence-based interventions. Routine screening and integrated psychosocial support are critical to improving patient-centered survivorship care.

Abstract:

Zirconium oxide (ZrO₂) ceramics are widely used in thermal barrier coatings and high temperature structural parts due to their excellent high temperature performance and thermal insulation characteristics. However, its high temperature phase transition, thermal expansion coefficient mismatch and thermal conductivity increase limit its further application. In order to improve the comprehensive properties of ZrO₂ ceramics, the effects of different CeO₂ doping levels (0-20 wt.%) on the microstructure, mechanical properties, tribological behavior and thermophysical properties of ZrO₂ ceramics were systematically investigated. The sample was prepared by a simple and efficient method of ball milling combined with pressure-free sintering, which has simple process and low cost, and was conducive to achieving the uniformity of composition and controllable microstructure. The results showed that 15 wt.% CeO₂ was the optimal doping concentration. At this time, the density of the material was the highest, and the hardness was 310 HV₁, which was 27.64% higher than that of the undoped sample. The friction coefficient and wear rate were reduced to 0.205 and 1.81×10⁻³ mm³/N·m, respectively, showing the optimal wear resistance. At 1200 °C, the thermal expansion coefficient decreased by 72.21%, and the thermal conductivity decreased to 0.612 W/(m·K). The improved performance was mainly attributed to the solid solution enhancement of Ce⁴⁺, grain refinement and phonon scattering effect of enhanced oxygen vacancy. This study provided an important basis for optimizing the comprehensive properties of ZrO₂ ceramics by component design.

Abstract:

The avian immunosuppressive and neoplastic diseases are great threats to the poultry industry causing huge economic losses worldwide. Most recently, the emerging hypervirulent variants of Marek’s disease virus (HV-MDV), partially co-infected with avian leukosis virus (ALV) and/or reticuloendotheliosis virus (REV), have been identified as the key driver of tumour outbreaks in vaccinated chicken flocks, but the role of chicken infectious anaemia virus (CIAV) remains unclear. Herein, we have investigated the prevalence and co-infection of CIAV in 72 clinical tumour-bearing flocks collected from central China during 2020-2023, which has shown a CIAV positivity rate of 59.7% (43/72). Notably, the incidence of CIAV mono-infection increased significantly from 0% (0/30) in 2020-2021 to 26.2% (11/42) in 2022-2023, whereas CIAV+MDV co-infection decreased from 66.7% (20/30) to 28.6% (12/42). A total of 20 viral genomes of epidemic CIAV isolates from diverse sources were obtained, and the phylogenetic analysis including 91 reference isolates were clustered into four major lineages (A–D), with a clade C further subdivided into subclades C1 and C2. Clade C1 consisted predominantly of Asian isolates, with 88.5% (46/52) of the isolates originated from mainland China. Among the 20 new isolates, 17 were clustered in subclade C1, two in C2, and one in B. The VP1 gene phylogeny showed a topology largely consistent with that of the whole-genome analysis. Moreover, all newly characterized isolates contained glutamine (Q) at VP1 residue 394, a molecular marker associated with high pathogenicity. Collectively, our data suggest that prevalent HV-MDV variants together with CIAV co-infections are the primary drivers of the ongoing tumour outbreaks in Chinese poultry flocks. Furthermore, the increased pathogenicity observed in CIAV mono-infections, likely resulting from an independently evolving lineage among circulating Chinese strains, will pose a significant challenge for future control of disease.

Abstract: Background: Climate change is a known risk factor for poor mental health outcomes. While there is a growing body of research on mental health in Uganda, there is still limited evidence on the relationship between mental health and climate change. Therefore, this study assessed the trends of mental disorders, and the relationship between mental disorders and climate factors among residents of Kampala district. Methods: Ecological and cross-sectional study designs were used, employing quantitative data collection approaches. The data was sourced from secondary sources; mental disorders data were extracted from patient registers/files at Butabika National Referral Mental Hospital, and that on climate (temperature, relative humidity and rainfall) from Uganda National Meteorological Authority. Descriptive analysis, Spearman correlation and time series analysis was performed. Results: The proportion of mental disorders ranged from 3.5% to 47.3%. Relative humidity showed a weak negative correlation with mental health disorders (rho = -0.3620 P = 0.00458). Conclusion: The study revealed a rising trend of mental disorders among residents of Kampala. However, meteorological factors do not sufficiently explain this. Future research should focus on longitudinal studies to explore these complex inter-actions further. Policy and planning efforts should prioritize strengthening mental health services to accommodate the growing urban demand.