The growing support for noncanonical amino acids in structure prediction tools such as AlphaFold3 has been largely facilitated by the Chemical Component Dictionary (CCD). However, the limited coverage of modified residues in CCD continues to restrict the application of these models to many biologically and therapeutically relevant peptides. To address this gap, we present HighRes_Builder, a computational method for efficient residue search and automated construction of noncanonical amino acids not currently archived in CCD. We demonstrate the utility of our approach by predicting structures for 3179 noncanonical residues beyond the CCD using AlphaFold3. AlphaFold3 achieved 100% acceptance for both the noncanonical residue monomers and their corresponding 'GGXGG' motifs (where X denotes the noncanonical residue). Of these, 72.44% of the predicted residue monomer structures concurrently satisfy all five geometric criteria (d_N_C1, d_Ck_Ccarb, d_Ccarb_O_mean, ang_Ck_Ccarb_O_mean, and ang_O1_Ccarb_O2). Furthermore, among the generated motif structures, 85.78% exhibited favorable ω values for the embedded noncanonical residues. Furthermore, by integrating HighRes_Builder with structure prediction systems, AlphaFold3 for linear peptides and HighFold3 for cyclic peptides, we successfully model the conformation of the linear peptide drug Relamorelin and the cyclic therapeutic peptides LUNA18 and JNJ-77242113 in complex with their target proteins, elucidating structural determinants of their mechanism of action. This work establishes a scalable and accurate framework for structure prediction of diverse nonstandard peptides, highlighting its potential to accelerate rational design of peptide-based therapeutics.
This article discusses mutual-visibility in graphs through a game-based version of the problem. Two players, Builder and Blocker, alternately select an unmarked vertex on a graph keeping the property that the set of marked vertices forms a mutual-visibility set. The game ends when no such selection is possible. The goal of Builder is to create a largest possible mutual-visibility set, Blocker's goal is the opposite. The central problem here is to determine the number of vertices selected during the game assuming that both players played optimally. Bounds on this number are proved and several general properties of the game derived. Special attention is paid to complete multipartite graphs and Hamming graphs.
The skin serves as the primary physical barrier and plays a critical role in the aesthetic appearance, particularly through its pigmentation and texture. Collagenprash and Collagen builder are developed to support skin integrity by promoting collagen-associated protein expression. This study systematically evaluated these claims through a variety of biochemical and cellular assays. The formulations were assessed for biochemical and cellular antioxidant activity, collagenase inhibition, interleukin-mediated anti-inflammatory activity, melanogenesis inhibition, and proteins associated with collagen expression by using immunofluorescence analysis. The presence of a collagen blend, ascorbic acid, and botanical extracts enhanced the expression of prolyl 4-hydroxylase (P4H) and lysyl hydroxylase, key enzymes involved in post-translational modification of collagen. Upregulation of P4H facilitates hydroxylation of proline residues, a critical step for stabilization of the collagen triple helix, whereas increased lysyl hydroxylase expression promotes hydroxylysine formation and subsequent intermolecular cross-linking. Therefore, these formulations may have the potential to support collagen biosynthesis and maintain skin texture.
Access to safe drinking water, improved sanitation, and basic hygiene is a critical factor of infectious disease risk and child health, particularly in low- and middle-income countries (LMICs). Spatially detailed information on household-level water, sanitation, and hygiene (WASH) conditions is critical for characterizing pathways of infectious disease transmission and exposure; however, such information is not directly available for most locations. We produced a harmonized global dataset of WASH conditions derived from 376 nationally representative household surveys, including the Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and national surveys, covering more than six million households and approximately 291,000 georeferenced clusters across LMICs. Drinking water source, sanitation facility type, and hygiene status were classified as ordered categorical variables reflecting service levels. Household survey data were integrated with 24 environmental and socioeconomic covariates from multiple data sources. Spatial ordinal regression models were fit using R Template Model Builder (RTMB), incorporating cluster-level random effects and spatial random fields represented by the stochastic partial differential equation (SPDE) formulation. The resulting dataset provides high-resolution gridded estimates of WASH service levels and associated probabilities, suitable for geographic distribution pattern analyses, environmental health research, and public health planning.
Salt bridges contribute disproportionately to protein folding stability and protein-protein interaction energetics, yet systematic tools for engineering novel salt bridges remain limited. There are several approaches that can quantify the energetics of removing salt bridges between proteins, but no existing tools are available for adding salt bridges at protein interfaces. Here, we introduce Salt Bridge Builder (SBB), a software package that identifies candidate mutation sites for adding interprotein salt bridges using residue distance heuristics derived from large-scale structural data. Using the SKEMPI v2 database, we demonstrate that charged-to-uncharged mutations that disrupt interprotein salt bridges result in binding free energy penalties significantly larger than those of comparable mutations that do not, underscoring the stabilizing role of salt bridges at protein interfaces. We benchmark six residue distance metrics for their ability to predict salt bridge formation and show that the side-chain centroid distance (SCCD) provides the optimal balance between the predictive performance and computational efficiency. Based on these findings, we formulate an efficient algorithm that identifies putative salt bridge-forming mutations while avoiding disruption of existing electrostatic interactions. We apply SBB to the kinesin superfamily and identify kinesin-5 as uniquely enriched in potential salt-bridge-building sites at the microtubule interface. Molecular dynamics simulations of engineered kinesin-5 mutants reveal that only a subset of predicted salt bridges exhibits high occupancy, highlighting the role of local microenvironments in stabilizing engineered electrostatic interactions. Principal component analysis of the residue microenvironment distinguishes high-occupancy salt bridges, suggesting a path toward a priori stability prediction. Long-range electrostatic force calculations further show that selected mutations modulate kinesin-5-microtubule attraction. Together, this work establishes residue-distance-based salt bridge engineering as a viable protein-protein engineering strategy and provides a foundation for future extensions of SBB that incorporate microenvironment-aware stability prediction.
Automatic categorization of textual documents into predefined topics is an important natural language processing (NLP) task. This work proposed a strong framework for topic classification, with many independent methods with the goal of potentially achieving the best results for topic classification. The first step in the system is data pre-processing. In this phase, pre-processing takes place, which includes converting file formats, removing stop words to reduce noise, and text normalization. Then, it was possible to vectorize the text for feature extraction using the Term Frequency-Inverse Document Frequency (TF-IDF) method, changing from unstructured documents to structured numerical documents, as well as capturing the importance of terms with respect to all documents. The core classification model is a Bidirectional Gated Recurrent Unit (BiGRU) neural network. This architecture is selected not only because it processes text data in forward and backward directions, but also because it extracts richer contextual information than unidirectional approaches. To enhance the BiGRU architecture, a new approach called the Modified Builder Optimization Algorithm (MBOA) is proposed. The MBOA was a new metaheuristic algorithm developed to optimize the model hyperparameters. The performance of the proposed framework has been tested on two benchmark datasets, including the BBC News dataset and the larger AG News dataset. The proposed MBOA-optimized BiGRU model demonstrated exceptional performance, establishing a new state-of-the-art on both datasets. On the BBC News dataset, the model achieved an accuracy of 98.62%, a precision of 98.71%, a recall of 98.59%, and an F1-Score of 98.65%. Similarly, on the more diverse AG News dataset, it attained an accuracy of 98.23%, a precision of 98.41%, a remarkable recall of 98.82%, and an F1-Score of 98.61%.
The secondary use of clinical data has been widely studied, addressing many challenges in conducting observational studies. However, the complexity of dataset structures and detailed data requirements has led researchers to develop user-friendly query builders, enabling medical researchers to define cohorts more efficiently across the datasets. Although these tools simplify the workflow, their learning curve can sometimes be steep. Motivated by improving the usability to conducted observational studies, we propose a modular conversational assistant framework that would address these limitations. It can be integrated in any web application as an javascript component, improving the system usability. Additionally, the proposed framework would employ deterministic algorithms to reduce computational overhead. The system would enable integration into existing medical information systems through configuration files rather than code modifications. Validation within the OHDSI ecosystem would demonstrate practical applicability for real-world observational research scenarios.
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Genomics analyses often rely on command-line tools executed via remote servers, imposing usability barriers for non-technical users and raising privacy concerns. WebAssembly (WASM) enables native-code execution directly in web browsers, eliminating installations and data transfers. We introduce BioChef, a client-side genomic workflow platform that uses WASM. BioChef compiles a genomics toolkit into browser-executable modules and exposes them through a drag-and-drop GUI designed to be intuitive. The system provides real-time validation, flexible input methods (form-based and JSON), intermediate step inspections, and reproducible workflows exportable as bash scripts or configuration files. Performance benchmarks across major browsers (Chromium, Gecko, WebKit) demonstrate rapid initialization (LCP 0.583 s), responsive interactivity (INP 30.5 ms), minimal layout shifts (CLS 0.01), and acceptable overhead (average 181.5 ms initial WASM module load). Although browser execution introduced performance penalties ( ∼ 130 × slower than native), BioChef workflows still significantly outperformed traditional web services such as Galaxy by avoiding network delays and server-side queueing (11.3 × faster in a standard pipeline benchmark). BioChef shows how WebAssembly on the client side can democratize genomic data processing, ensuring privacy, reproducibility and ease of use without external dependencies. To our knowledge, this is the first fully client-side, graphical genomic workflow environment powered by WASM.
Among the key strategies for protecting the environment are education, modifying people's behavior, fostering pro-environmental values, and promoting active citizenship. With this in mind, the present study sought to investigate the effect of an educational intervention based on the Theory of Planned Behavior (TPB) on environmentally responsible behaviors (ERBs) among lower secondary students. This quasi-experimental study was conducted among 100 lower secondary school students in Piranshahr, Iran, selected using a multistage cluster sampling method. Schools were randomly allocated to the intervention or control groups, resulting in 50 students in each group. A demographic form and a researcher-developed questionnaire, grounded in the constructs of the TPB and centered on environmental issues as well as ERBs, served as the data collection instruments. The educational program, also designed according to TPB constructs, focused on three key aspects of ERBs. This program was delivered to intervention group students over three 45-minute sessions, along with a separate 60-minute session for parents and school staff. Data gathering took place at two time points: prior to the educational intervention and again three months later. In the intervention group, following the educational intervention, there was a statistically significant increase in the mean scores of TPB constructs-including attitude, subjective norms, perceived behavioral control, intention, and behavior-as well as in knowledge about the environment and ERBs, compared with the pre-test and the control group (p < 0.05). The educational intervention grounded in the TPB was found to be effective in enhancing ERBs among lower secondary school students. Given that students are the future builders of society, environmental education holds particular importance for this group. Therefore, the intervention developed in this study is proposed as a straightforward, low-cost strategy that can complement existing school programs. The adoption of such interventions has the potential to significantly reinforce ERBs and, over time, lead to better environmental outcomes.
Sexual systems such as dioecy, although rare in angiosperms, seem to enhance intrapopulation genetic diversity due to obligate outcrossing. Empirical studies had strengthened theoretical predictions that genetic diversity in dioecious angiosperms is strongly linked to population demographic structure, phenological patterns, and species life-history traits such as pollination mode and seed dispersal syndrome. As anthropogenic pressures and climate change have disrupted and altered plant reproduction, understanding how ecological and environmental factors modulate genetic diversity in threatened dioecious angiosperms is paramount to inform and to establish effective conservation and management plans. Here, we compiled genetic and ecological data of 66 dioecious angiosperms from articles published until August 2025. To test the effects of pollination mode, seed dispersal syndrome, reproductive mode, growth form, conservation status, endemism, and species distribution range on intrapopulation genetic diversity (i.e., H E), we implemented Generalized Linear Mixed Models fitted with Template Model Builder. Our results revealed that species conservation status and endemism play a significant role in the patterns of H E among dioecious angiosperms, with endemic and/or threatened species showing reduced levels of genetic diversity. Pollination mode also emerged as an important predictor of H E, with abiotically pollinated species exhibiting highest genetic diversity. Pruning not only the knowledge on how ecological and evolutionary processes drive molecular variation in dioecious angiosperms, our study is also an attempt to strengthen conservation efforts to plant species presenting rare sexual system. We stress that dioecious angiosperms should be targeted as priority in conservation agendas worldwide.
Mixed-solvent molecular dynamics (MSMD) has become a useful simulation strategy for mapping protein interaction hotspots, exploring cryptic or allosteric pockets, and characterizing ligandable surface regions. However, practical MSMD studies still require labor-intensive system preparation, probe bookkeeping, format conversion, and trajectory post-processing across multiple software environments. Here, we present the Mixed-Solvent MD Suite, a modular software platform that automates these operational steps rather than proposing a new physical sampling formalism. The Suite includes (1) a fully web-based Mixed Solvent MD System Builder for protein and probe setup, concentration-controlled solvation (% w/v or mol/L), and automated generation of GROMACS and AMBER compatible input files, and (2) a local Probe GridMap Builder for grid-based probe occupancy analysis of MD trajectories using the AMBER cpptraj backend. Case studies on five benchmark proteins show that the platform reproducibly constructs MSMD systems, supports transferable analysis workflows across simulation outputs, and qualitatively recovers known ligandable regions in representative targets. Overall, the Mixed-Solvent MD Suite lowers technical barriers for MSMD studies and provides an extensible foundation for future benchmarked hotspot analysis and cryptic-site discovery workflows.
This study investigates the role of conceptual metaphors in constructing China's national image within Chinese-English press conference interpreting. Drawing on Critical Metaphor Analysis and the online corpus tool Wmatrix, the research identifies and examines metaphorical patterns in the interpreted diplomatic discourse. Six types of conceptual metaphors relating to "China" emerge in the interpreting data, with the human and journey metaphors occurring most frequently, followed by building, ecology, war, and entertainment metaphors. These metaphors correspond to six cognitive frames whose linguistic realizations generally construct a favorable national image. The image schemata profile China as a traveler on a journey of struggle, a contributor to the international community, a builder of global causes, a guardian of the global environment, a fighter in challenging endeavors, and a performer on the world stage. Influenced by individual and social resources, three interpreting strategies are deployed, revealing an overall aim to render the national image more relatable, vivid, and warm while emphasizing China's importance in the international community. These findings extend critical metaphor research on press conference interpreting by illuminating how metaphorical framing contributes to image construction. They also offer practical insights for interpreter training, demonstrating that strategic metaphor choices can enhance the communicative effectiveness of diplomatic discourse while maintaining fidelity to institutional positions.
Cytokines are immunomodulatory proteins that play central roles in regulating immune responses and represent attractive targets for cancer therapy. However, as single agents, cytokines have shown limited clinical benefit due to systemic toxicities and a short in vivo half-life. Our group has focused on engineering fusion cytokines (fusokines) that couple two cytokines into a single biologic to reprogram immune cell responses by enforcing non-canonical receptor engagement and signaling. A chimeric IL-6/IL-1β fusokine was engineered to test the hypothesis that enforced co-engagement of IL-6 and IL-1β signaling pathways would confer a gain-of-function phenotype in T cells and promote robust anti-tumor immunity. Here, we describe the immunomodulatory properties of IL6/1 fusokine and a method to deliver this fusokine to produce inhibition of ovarian tumor growth in a pre-clinical mouse model. Lentiviral vectors encoding murine or human IL6/1 were designed using Vector Builder and expressed in either HEK293, CHO or ID8-F3 (p53-/-) cells depending on the downstream experiment to be conducted. IL6/1 expression was validated by ELISA and flow cytometry. Effects of human IL6/1 (hIL6/1) on T cell function (proliferation, memory phenotype, activation induced apoptosis) were monitored by flow cytometry. For in vivo studies, ID8-F3 murine ovarian cancer cells expressing mouse IL6/1 (mIL6/1) were administered intraperitoneally (I.P.) as a cell-based therapy to C57BL/6 female mice bearing established ID8-F3 luciferase tumors. Tumor progression was monitored by bioluminescence (BLI) imaging, and overall survival was evaluated. hIL6/1 significantly enhanced T cell survival and selectively promoted activation and expansion of CD45RO+ memory T cells. mIL6/1 expressing ID8-F3 cells (ID8IL6/1) demonstrated stable transduction and sustained cytokine secretion. In vivo, ID8IL6/1 cell therapy significantly reduced tumor growth and improved overall survival compared to control groups, with 2 of 8 mice achieving complete tumor clearance. These findings indicate that IL6/1 fusokine enhances T cell survival and proliferation while promoting memory responses. Engineered cancer cells (ID8-F3) expressing mIL6/1 fusokine induced a strong anti-tumor response when delivered as a therapeutic vaccine in ovarian cancer mouse model.
Case-based learning is a proven pedagogical strategy in medical laboratory science (MLS) education, fostering critical thinking, data interpretation, and clinical reasoning skills. This article describes an innovative "artificial intelligence (AI)-first, student-corrected" assignment model that leverages generative artificial intelligence (AI) as a drafting tool while positioning students as expert validators of clinical information. Students use AI to generate initial case studies based on current course material, then critically appraise and correct inaccuracies in laboratory analytes, reference ranges, diagnostic pathways, and clinical reasoning. A structured rubric guides revision across four domains: patient background, laboratory data integration, evidence-based case questions, and diagnostic conclusions. Importantly, students also create paired videos to demonstrate comprehensive knowledge as well as patient-professional communication skills. Following implementation, MLS students who had completed both the traditional and AI-enhanced versions of the assignment were surveyed. Of the 17 students who responded, 15 (88%) preferred this AI-enhanced approach over traditional case writing, citing improved engagement, reduced writer's block, enhanced error detection skills, and increased confidence with emerging AI tool usage. By transforming students from passive case consumers into active builders of clinical understanding, this model strengthens essential MLS competencies, including critical appraisal, data verification, and AI literacy, all while preparing learners for a future where AI-assisted tools are embedded throughout laboratory medicine. This pedagogical innovation demonstrates how educators can harness AI's efficiency while preserving and amplifying the cognitive and professional benefits of case-based learning.
Low interfacial tension (IFT) between fracturing fluids and reservoir fluids is essential for enhancing gas recovery and mitigating formation damage in shale gas systems. However, conventional surfactants used in hydraulic fracturing pose environmental and sustainability concerns, necessitating the development of greener alternatives. This study evaluates the potential of the bio-derived surfactant D-limonene in reducing methane-water interfacial tension under both ambient and high-pressure high-temperature (HPHT) conditions representative of shale reservoirs. A systematic relationship between IFT and solvation free energy (ΔGₛₒₗᵥ) was observed across all investigated conditions. Increasing temperature significantly reduced IFT, with reductions of up to ~ 80% under ambient conditions (18-90 °C), whereas the reduction was less pronounced under HPHT conditions (~ 7 mN/m). Pressure exhibited a comparatively minor influence, with IFT increasing by approximately 8% between 70 and 120 MPa. Increasing D-limonene concentration consistently lowered IFT, although higher concentrations were required under HPHT conditions to achieve comparable reductions. All calculations were performed using classical molecular dynamics simulations. Molecular interactions among methane, water, and D-limonene were described using the Optimized Potentials for Liquid Simulations (OPLS) force field. Molecular topologies were generated using the Automated Topology Builder, and simulations were conducted using GROMACS®. Systems were equilibrated under constant number of particles, volume, and temperature (NVT) and constant number of particles, pressure, and temperature (NPT) ensembles. The solvation free energy (ΔGₛₒₗᵥ) was computed using thermodynamic integration (TI), where the ensemble-averaged energy derivatives ⟨∂V/∂λ⟩ were evaluated across 21 λ-coupling states and numerically integrated using the trapezoidal rule. Interfacial tension was subsequently determined via its thermodynamic correlation with ΔGₛₒₗᵥ.
The ceremonial inauguration of the Medical Faculty at Lviv University on September 9, 1894, by Emperor Franz Joseph, signified the culmination of a decades-long endeavor to reestablish medical education in Lviv. The institution was initially established in 1784 under the auspices of Emperor Joseph II. However, it was subsequently dissolved in 1805 and subsequently reinstated in 1817, albeit without a medical faculty. This study provides an analysis of the faculty's complete restoration as a result of international and interdisciplinary collaboration within the political, academic, and architectural spheres in the 19th century within the Habsburg Empire. Utilizing archival collections from Ukraine, Austria, and Poland, along with university repositories and current publications, this study performs a contextual and actor-focused analysis. Stakeholders are categorized into three sectors: governmental, academic, and technical. These categories are used to examine their respective roles and interactions. The reestablishment of the university was driven by the sustained advocacy of Lviv's academic community, with support from the Galician Governorship, and it was officially authorized by the Viennese Ministry of Education through an Imperial Decree in 1891. Academic contributions from prominent scholars in Lviv, including Henryk Kadyi, and in Cracow, such as Ludwik Teichmann and Napoleon Cybulski, exerted a significant influence on the curriculum and spatial organization of the faculty. The supervision of the construction process was overseen by architect Josef Braunseis and builder Ivan Levynsky, who engaged in close consultation with academic experts. International suppliers furnished essential materials and equipment. The medical faculty was officially established in 1894, with the inaugural academic year commencing in 1894/95. The restoration of the Medical Faculty in Lviv serves as a prime example of a trans-regional, interdisciplinary Habsburg endeavor, integrating political vision, scientific leadership, and architectural innovation.
Youth unemployment in emerging economies threatens sustainable development, yet universities remain underutilized as entrepreneurial ecosystem builders. This study addresses a critical gap in understanding how psychological mechanisms shape entrepreneurial attitudes, essential for SDG 8 (Decent Work) and SDG 4 (Quality Education). We examine whether entrepreneurial creativity mediates the intrinsic motivation-entrepreneurial attitude relationship, and whether perceived family support moderates this pathway, a moderated mediation model rarely tested in collectivist, emerging-market contexts. A cross-sectional survey of 600 first-year students from public and private universities in northern Peru (Trujillo, Piura, Chiclayo) was conducted using validated instruments with a 5-point Likert scale. The moderated mediation model was analyzed using Hayes' PROCESS Model 14 with 5,000 bootstrap resamples and bias-corrected 95% confidence intervals. The measurement model was evaluated through confirmatory factor analysis (CFA) with configural, metric, and scalar invariance testing by university type and gender. Creativity fully mediated the motivation→attitude relationship (indirect effect: β = .25, 95% CI [.19, .32]), while the direct effect was nonsignificant (β = .05, p = .214), indicating motivation operates exclusively through creativity development. Family support significantly moderated the creativity→attitude pathway (interaction: β = .11, p < .001), with amplified effects at higher support levels (+1SD: β = .65 vs. -1SD: β = .39). The Johnson-Neyman threshold identified a critical family support value of 2.3 on the 1-7 scale. The model explained 51% of variance in entrepreneurial attitude (R 2 = .51), with superior predictive validity compared to the base model (Q 2 = .32 vs .26). In collectivist contexts such as Peru, intrinsic motivation is associated with entrepreneurial attitude through entrepreneurial creativity, consistent with a conditional indirect-effect interpretation rather than a causal one. Universities may benefit from piloting creativity-enhancing pedagogies integrated with family engagement programs to build sustainable entrepreneurial ecosystems, particularly in regions with strong familial values.
The use of surgical navigation using holograms provided by mixed reality glasses is already a reality in other fields of orthopaedics as the shoulder or knee. Due to this, this study aimed to develop and evaluate a mixed reality-based system for navigation in derotational radius osteotomies, focusing on its accuracy and reproducibility. To this end, a holographic computing software based on C++ language and code integrable in MRTK 2 (Microsoft, Redmond, USA) was generated to be implemented in Microsoft Hololens 2. Using the 3D Builder software, positioners and trackers, recognisable by mixed reality glasses, were designed and patented, allowing us to know the changes in spatial relationship between two trackers. A total of 41 radius biomodels were used. A hand surgery consultant and an orthopaedics resident each performed ten rotational osteotomies using freehand technique and ten with the navigation system. Afterwards, a CT scan was performed, measuring the variation achieved. The error was defined as the difference between the planned and obtained orientation in both techniques and analyzed statistically. Under these conditions, the median error of the navigated system was 1º [0-2.25°], compared to 11º [7-19.5°] with the freehand technique (p<0.05). Error did not significantly increase with greater osteotomy magnitudes. The navigated system demonstrated higher accuracy and reproducibility. No significant inter-surgeon differences were observed in either technique. In conclusion, surgical navigation based on holographic computerization improves the accuracy of radius rotational osteotomies. Due to its reproducibility and simplicity, it represents a potential technique for future surgical navigation.