Search Results (388)

Alpha-Synuclein (α-Syn) is a presynaptic neuronal protein implicated in the pathogenesis of Parkinson’s disease (PD) and other synucleinopathies, primarily through its aggregation into insoluble fibrils. The extended α-Syn half-life necessitates treatment durations that are incompatible with efficient high-throughput drug screening, can risk compound stability or cause cellular toxicity. To address this, we inserted a PEST sequence, a motif known to promote rapid protein degradation, at the C-terminus of the SNCA gene using CRISPR/Cas9 to create a novel cell line with reduced α-Syn half-life. This modification accelerates α-Syn turnover, providing a robust model for studying α-Syn dynamics and offering a platform that is applicable to other long-lived proteins. Our results demonstrate a six-fold reduction in α-Syn half-life, enabling the rapid detection of changes in protein levels and facilitating the identification of molecules that modulate α-Syn production and degradation pathways. Using inhibitors of the proteasome, transcription, and translation further validated the model’s utility in examining various mechanisms that impact protein levels. This novel cell line represents a significant advancement for studying α-Syn dynamics and offers promising avenues to develop therapeutics for α-synucleinopathies. Future research should focus on validating this model in diverse experimental settings and exploring its potential in high-throughput screening applications. Full article

This study defines evidence-based minimum internal floor areas required to support long-term residential use across different household types. It addresses the following question: what is the smallest viable floor area that supports sustained occupancy without persistent stress, conflict, or turnover? An integrative review method was employed, drawing from behavioural studies in environmental psychology, international regulatory standards, and real-world market data. The analysis focuses on essential domestic functions including sleep, hygiene, food preparation, storage, social interaction, and work. Quantitative findings from tenancy surveys, post-occupancy research, and market performance data indicate that residential units below 30 square metres for single occupants and 45 square metres for couples are consistently associated with reduced satisfaction and shorter tenancies. Regulatory minimums across diverse jurisdictions tend to converge near these same thresholds. The study proposes technical minimums of 30, 45, and 60 square metres for one-, two-, and three-person households, respectively. These values reflect functional lower bounds rather than ideal or aspirational sizes and are intended to inform performance-based housing standards. Full article

In the realm of recommender systems, the prediction of diverse customer preferences has emerged as a compelling research challenge, particularly for multi-state business organizations operating across various geographical regions. Collaborative filtering, a widely utilized recommendation technique, has demonstrated its efficacy in sectors such as e-commerce, tourism, hotel management, and entertainment-based customer services. In the item-based collaborative filtering approach, users’ evaluations of purchased items are considered uniformly, without assigning weight to the participatory data sources and users’ ratings. This approach results in the ‘relevance problem’ when assessing the generated recommendations. In such scenarios, filtering collaborative patterns based on regional and local characteristics, while emphasizing the significance of branches and user ratings, could enhance the accuracy of recommendations. This paper introduces a turnover-based weighting model utilizing a big data processing framework to mine multi-level collaborative filtering patterns. The proposed weighting model assigns weights to participatory data sources based on the turnover cost of the branches, where turnover refers to the revenue generated through total business transactions conducted by the branch. Furthermore, the proposed big data framework eliminates the forced integration of branch data into a centralized repository and avoids the complexities associated with data movement. To validate the proposed work, experimental studies were conducted using a benchmarking dataset, namely the ‘Movie Lens Dataset’. The proposed approach uncovers multi-level collaborative pattern bases, including global, sub-global, and local levels, with improved predicted ratings compared with results generated by traditional recommender systems. The findings of the proposed approach would be highly beneficial to the strategic management of an interstate business organization, enabling them to leverage regional implications from user preferences. Full article

Odonata constitute an important invertebrate group that is strongly dependent on water conditions and sensitive to habitat disturbances, rendering them reliable indicators of habitat quality of both aquatic and terrestrial habitats. We studied the compositional and diversity patterns of Odonates in total, and separately for the two suborders (Zygoptera, Anisoptera) in relation to geographic and ecological parameters at the riparian zone of four rivers and one canal within the Axios Delta National Park and the Natura 2000 SAC GR1220002 in northern Greece, using the line transect technique. In total, 6252 individuals belonging to 28 species were identified. The compositional and diversity patterns were significantly different between agricultural and natural sites. Odonata assemblages at croplands were comparatively poorer, dominated by a few, widely distributed, taxonomically proximal species, tolerant to environmental changes, as a result of modifications and consequent alterations of abiotic conditions at croplands, which also led to higher local contribution to β-diversity and species turnover. The absence of several percher, endophytic, and threatened species from agricultural sites led to significantly lower diversity, as a result of environmental filtering due to ecophysiological restrictions. Taxonomic and functional diversity, uniqueness, and Dragonfly Biotic Index (DBI) were significantly higher in riparian forests, due to the sensitivity of damselflies to dehydration, and the avoidance of habitat loss and extreme temperatures by dragonflies, which prefer natural shelters near the ecotone. The newly introduced Conservation Value Index (CVI) revealed 21 conservation hotspots of Odonata (14 at canopy cover sites), widely distributed within the borders of NATURA 2000 SAC GR1220002. Full article

Understanding the biodiversity of aquatic communities and the underlying mechanisms that shape biodiversity patterns and community dynamics is crucial for the effective conservation and management of freshwater ecosystems. However, traditional survey methods often fail to comprehensively capture species diversity, particularly for low-abundance taxa. Moreover, studies integrating both metazoan and fish communities at fine spatial scales remain limited. To address these gaps, we employed a multi-marker eDNA metabarcoding approach, targeting both the 12S and 18S rRNA gene regions, to comprehensively investigate the composition of metazoan and fish communities in the Yujiang River. A total of 12 metazoan orders were detected, encompassing 15 families, 21 genera, and 19 species. For the fish community, 32 species were identified, belonging to 25 genera, 10 families, and 7 orders. Among these, Adula falcatoides and Coptodon zillii were identified as the most prevalent and abundant metazoan and fish species, respectively. Notably, the most prevalent fish species, C. zillii and Oreochromis niloticus, are both recognized as invasive species. The Bray–Curtis distance of metazoa (average: 0.464) was significantly lower than that of fish communities (average: 0.797), suggesting higher community heterogeneity among fish assemblages. Beta-diversity decomposition indicated that variations in the metazoan and fish communities were predominantly driven by species replacement (turnover) (65.4% and 70.9% for metazoa and fish, respectively) rather than nestedness. Mantel tests further revealed that species turnover in metazoan communities was most strongly influenced by water temperature, while fish community turnover was primarily affected by water transparency, likely reflecting the physiological sensitivity of metazoans to thermal gradients and the dependence of fish on visual cues for foraging and habitat selection. In addition, a co-occurrence network of metazoan and fish species was constructed, highlighting potential predator-prey interactions between native species and Corbicula fluminea, which emerged as a potential keystone species. Overall, this study demonstrates the utility of multi-marker eDNA metabarcoding in characterizing aquatic community structures and provides new insights into the spatial dynamics and species interactions within river ecosystems. Full article

In the marine red alga Pyropia yezoensis, filamentous phases of the life cycle, e.g., the conchocelis (sporophyte) and conchosporangium (conchosporophyte), proliferate by tip growth. In this study, we investigated the possible involvement of phosphoinositide turnover and actin polymerization in the spontaneous initiation and tip growth of new branches in isolated single-celled conchocelis cells using pharmacological treatments. Treatment with LY294002 and U73122, specific inhibitors of phosphoinositide-phosphate 3-kinase and phospholipase C, respectively, reduced side-branch formation and inhibited the elongation of branches. In addition, two inhibitors of the actin cytoskeleton, cytochalasin B (CCB) and latrunculin B (LAT-B), had similar effects on tip growth. However, CCB did not alter the branching rate of single-celled conchocelis, whereas LAT-B did. As CCB and LAT-B affect actin polymerization through different mechanisms, this result suggests differences in the contributions of actin polymerization to branch initiation versus tip growth. These findings demonstrate the critical and diverse functional roles played by phosphoinositide turnover and actin polymerization in the regulation of the initiation and maintenance of tip growth in the conchocelis phase of P. yezoensis. Full article

Background: Employee turnover poses a multi-faceted challenge to organizations by undermining productivity, morale, and financial stability while rendering recruitment, onboarding, and training investments wasteful. Traditional machine learning approaches often struggle with class imbalance and lack transparency, limiting actionable insights. This study introduces an Explainable AI (XAI) framework to achieve both high predictive accuracy and interpretability in turnover forecasting. Methods: Two publicly available HR datasets (IBM HR Analytics, Kaggle HR Analytics) were preprocessed with label encoding and MinMax scaling. Class imbalance was addressed via GAN-based synthetic data generation. A three-layer Transformer encoder performed binary classification, and SHapley Additive exPlanations (SHAP) analysis provided both global and local feature attributions. Model performance was evaluated using accuracy, precision, recall, F1 score, and ROC AUC metrics. Results: On the IBM dataset, the Generative Adversarial Network (GAN) Transformer model achieved 92.00% accuracy, 96.67% precision, 87.00% recall, 91.58% F1, and 96.32% ROC AUC. On the Kaggle dataset, it reached 96.95% accuracy, 97.28% precision, 96.60% recall, 96.94% F1, and 99.15% ROC AUC, substantially outperforming classical resampling methods (ROS, SMOTE, ADASYN) and recent literature benchmarks. SHAP explanations highlighted JobSatisfaction, Age, and YearsWithCurrManager as top predictors in IBM and number project, satisfaction level, and time spend company in Kaggle. Conclusion: The proposed GAN Transformer SHAP pipeline delivers state-of-the-art turnover prediction while furnishing transparent, actionable insights for HR decision-makers. Future work should validate generalizability across diverse industries and develop lightweight, real-time implementations. Full article

Understanding the processes that drive microbial community assembly is a fundamental question in ecology, with important implications for predicting community responses to environmental disturbances. River ecosystems are under growing pressure from human disturbances, jeopardizing their ecological functions. Here, we investigated bacterial and protistan communities along the Yujiang River using environmental DNA metabarcoding. Bacterial communities exhibited significantly greater alpha diversity and broader habitat niches compared to protists. Additionally, a negative correlation was found between alpha diversity and niche breadth for both groups. Protistan communities exhibited significantly higher beta diversity (Bray–Curtis distance) than bacterial communities, with species turnover being the principal factor driving the variations in both communities. Null model results indicated that heterogeneous selection primarily structured bacterial communities, while stochastic processes (drift) mainly governed protist communities. Redundancy analysis and Mantel tests showed significant associations between environmental factors (e.g., temperature and pH) and bacterial community composition. Moreover, the longitude of sampling sites was linked to spatial variations in both bacterial and protistan communities. Further analyses, including distance-decay patterns, variation partitioning, and multiple regression on distance matrices, demonstrated that bacterial communities were driven by both environmental and spatial factors, while protist communities exhibited a stronger response to spatial factors. These results enhance our understanding of microbial community assembly in river ecosystems and provide valuable insights for the conservation and sustainable management of freshwater systems. Full article

Understanding the processes that shape biodiversity patterns is an important challenge in ecology. Land-use change is often recognized as a pivotal factor influencing biodiversity at large scales, with habitat heterogeneity being one of the most critical drivers of community composition and diversity. In this study, we evaluate the influence of landscape structure on the functional diversity of bird assemblages in the Upper Magdalena River Valley, Colombia. We used Generalized Linear Models to assess the effects of landscape structure on functional diversity, incorporating landscape metrics such as the number of patches, patch area and shape, and Shannon’s diversity and evenness indices. Additionally, we analyzed the influence of landscape structure on functional beta diversity—including its components of functional turnover and nestedness—using a distance-based redundancy analysis. We also examined the relationship between species traits and landscape metrics through a RLQ and fourth-corner analysis. We found a negative effect of habitat loss and fragmentation on functional diversity. Our results show that bird assemblages exhibit higher diversity in non-fragmented landscapes (>75% forest area; <1% urban cover), retaining greater functional richness and functional evenness (FRic > 0.24; FEve > 0.60). Moreover, non-fragmented landscapes seem to support a higher number of nectarivores and forest specialist species. In contrast, bird functional richness decreased with landscape fragmentation (FRic < 0.07). These findings highlight the importance of forest conservation for maintaining species persistence, ecological processes, and ecosystem services provided by birds. Full article

Gene therapy involves introducing genetic material into cells to treat or prevent disease and offers highly targeted and potentially curative approaches for both inherited and acquired conditions. The skin is an especially suitable organ for gene therapy due to its accessibility, ease of sampling, rapid cell turnover, and the possibility for localized treatment with minimal systemic exposure. Gene therapy is being actively explored across a range of dermatological conditions, including recessive dystrophic epidermolysis bullosa, ichthyosis, psoriasis, chronic wounds, and melanoma, with therapeutic strategies encompassing viral vectors, non-viral delivery systems, gene editing technologies, RNA-based treatments, and cell-based approaches. These diverse methods aim to correct genetic defects, modulate immune responses, promote tissue repair, or selectively target malignant cells. This review examines the advancements and potential of gene therapies in addressing complex skin diseases, providing hope for improved patient outcomes and long-term care. Full article

Leaf litter traits among tree species exert a direct influence on spatiotemporal nutrient turnover and an indirect influence by shifting the decomposition dynamics of leaf litter mixtures including other sympatric species. Cycas micronesica and Serianthes nelsonii are two Mariana Island tree species that are endangered, and developing a greater understanding of the influence of these trees on biogeochemistry may improve information-based conservation decisions. The objectives of this study were to quantify the influence of mixing the leaf litter of these species with 12 sympatric forest plants to determine the additive and nonadditive influences on decomposition. The C. micronesica litter was collectively antagonistic when litter mixtures were incubated in a mesocosm study and a field litterbag study, and the response was similar among the included species. The S. nelsonii litter was collectively synergistic among the same mixed species, and the response was dissimilar among the included species. The contributions of these two threatened tree species to spatiotemporal diversity in biogeochemistry are dissimilar and considerable. These findings indicate that species recovery efforts for these two species are of paramount importance for maintaining Mariana Island ecological integrity and native biodiversity by sustaining their contributions to ecosystem services. Full article

Amid declining fish diversity and human pressures in freshwater ecosystems, robust basin-scale assessments are vital for effective fisheries management. This study collated nearly four decades of fishery yields from the Pearl and Yangtze Rivers to identify conservation priorities in the Pearl River Basin. It introduced a novel cumulative effect indicator based on zeta diversity—a biodiversity pattern metric—integrated with cumulative effects analysis for management decision-making. The research employed a multi-site generalized dissimilarity model to examine the non-linear relationships between fish species composition (ζ_n) and human pressures, environmental factors, and geospatial variations across elevation gradients. The cumulative effect indicator, reflecting responses to anthropogenic stress when assessing ζ₂ (related to β diversity), helped evaluate basins for conservation or restoration needs based on their unique or homogenized biotic communities. The results suggest that ζ diversity in low-elevation sub-basins has a stronger filtering effect on ζ by human pressures than in mid- to high-elevation sub-basins, where community aggregation is more random. The impact varied with diversity aspects (nestedness vs. turnover) and zeta order. A negative correlation between cumulative effects and community uniqueness validated the novel cumulative effect indicator’s effectiveness for guiding restoration in the Pearl River Delta, potential fishing bans, and karst conservation. This approach offers a theoretical basis for prioritizing areas for freshwater fish diversity conservation and fishing restrictions in the Pearl River Basin. Full article

Musculoskeletal (MSK) disorders remain a major global cause of disability, with diagnostic complexity arising from their heterogeneous presentation and multifactorial pathophysiology. Recent advances across imaging modalities, molecular biomarkers, artificial intelligence applications, and point-of-care technologies are fundamentally reshaping musculoskeletal diagnostics. This review offers a novel synthesis by unifying recent innovations across multiple diagnostic imaging modalities, such as CT, MRI, and ultrasound, with emerging biochemical, genetic, and digital technologies. While existing reviews typically focus on advances within a single modality or for specific MSK conditions, this paper integrates a broad spectrum of developments to highlight how use of multimodal diagnostic strategies in combination can improve disease detection, stratification, and clinical decision-making in real-world settings. Technological developments in imaging, including photon-counting detector computed tomography, quantitative magnetic resonance imaging, and four-dimensional computed tomography, have enhanced the ability to visualize structural and dynamic musculoskeletal abnormalities with greater precision. Molecular imaging and biochemical markers such as CTX-II (C-terminal cross-linked telopeptides of type II collagen) and PINP (procollagen type I N-propeptide) provide early, objective indicators of tissue degeneration and bone turnover, while genetic and epigenetic profiling can elucidate individual patterns of susceptibility. Point-of-care ultrasound and portable diagnostic devices have expanded real-time imaging and functional assessment capabilities across diverse clinical settings. Artificial intelligence and machine learning algorithms now automate image interpretation, predict clinical outcomes, and enhance clinical decision support, complementing conventional clinical evaluations. Wearable sensors and mobile health technologies extend continuous monitoring beyond traditional healthcare environments, generating real-world data critical for dynamic disease management. However, standardization of diagnostic protocols, rigorous validation of novel methodologies, and thoughtful integration of multimodal data remain essential for translating technological advances into improved patient outcomes. Despite these advances, several key limitations constrain widespread clinical adoption. Imaging modalities lack standardized acquisition protocols and reference values, making cross-site comparison and clinical interpretation difficult. AI-driven diagnostic tools often suffer from limited external validation and transparency (“black-box” models), impacting clinicians’ trust and hindering regulatory approval. Molecular markers like CTX-II and PINP, though promising, show variability due to diurnal fluctuations and comorbid conditions, complicating their use in routine monitoring. Integration of multimodal data, especially across imaging, omics, and wearable devices, remains technically and logistically complex, requiring robust data infrastructure and informatics expertise not yet widely available in MSK clinical practice. Furthermore, reimbursement models have not caught up with many of these innovations, limiting access in resource-constrained healthcare settings. As these fields converge, musculoskeletal diagnostics methods are poised to evolve into a more precise, personalized, and patient-centered discipline, driving meaningful improvements in musculoskeletal health worldwide. Full article

Food waste significantly impacts the restaurant industry’s financial viability and environmental sustainability. This study explores training practices used to minimize food waste and identifies obstacles encountered in implementing these practices. Semi-structured interviews with 10 chefs from diverse restaurants in a mid-South U.S. state were conducted. Two themes emerged from the qualitative analysis. The results revealed that the predominant training methods were verbal instruction, mentoring, and hands-on coaching, emphasizing real-time feedback and individualized guidance. Training for front-of-house staff primarily included reducing unnecessary table items, whereas back-of-house employees focused on portion control and repurposing ingredients. Mentoring emerged as critical, especially for new employees with limited culinary experience, ensuring that they develop critical thinking skills and resourcefulness in minimizing waste. Chefs identified significant barriers, including staff cooperation, knowledge gaps, employee turnover, and resource limitations. Overcoming these challenges necessitates stronger managerial commitment, standardized guidelines, and incentive-based reinforcement. This study concludes that cultivating an organizational culture that embeds sustainability into training practices is essential. Practical strategies such as mentoring and continuous reinforcement can mitigate food waste, enhance operational efficiency, and promote a sustainable food system. Future research should quantify training impacts on waste reduction and examine consumer-side factors influencing restaurant food waste. Full article

Endemic plant species, with their restricted distribution, are vulnerable to extinction due to human activities and environmental change. Monitoring their ecological characteristics and habitat relationships is crucial for conservation. This study examined plant communities to prioritize populations for conserving the Korean endemic species, Taihyun’s abelia (Zabelia tyaihyonii (Nakai) Hisauti & H.Hara), and to identify threats and strategies for its protection. Vegetation surveys were conducted, classifying communities and analyzing species composition differences. Habitat quality and zeta diversity, assessed using the InVEST model, identified three community types: Quercus dentata–Thuja orientalis (Com. 1), Fraxinus rhynchophylla–Buxus koreana (Com. 2), and Quercus dentata–Carex humilis var. nana (Com. 3). Community classification was supported by a multi-response permutation procedure (p < 0.001) and non-metric multidimensional scaling (R² = 0.643). Species richness and soil calcium influenced species composition, and habitat quality was moderate (0.5562 ± 0.0294). Com. 1 and Com. 3 showed minimal zeta diversity decline, indicating strong habitat connectivity. However, fluctuations at zeta orders 8–12 suggested localized disturbances. Species turnover instability was linked to urbanization and disturbance. This study, using a diverse set of analytical tools, was able to pinpoint key features of habitat quality and composition associated with Z. tyaihyonii and the anthropogenic factors that will lead to its decline. Our work provides a road map for the conservation of other rare and endemic Korean plant species with similar conservation issues. Full article