Tag: nevin manimala

J Am Chem Soc. 2025 Nov 7. doi: 10.1021/jacs.5c11854. Online ahead of print.

ABSTRACT

Herein, we report a ligand-controlled chemodivergent bismuth-catalyzed coupling between arylboronic acids and N-fluorosulfonimide derivatives that enables the selective formation of either C(sp²)-N or C(sp²)-O bonds. Selectivity is achieved by the modulation of the electronic and steric properties of a common ligand framework for bismuth, thus establishing an unusual ligand-controlled chemodivergent platform in main group catalysis. Specifically, the use of an electron-enrich sulfone ligand led to the major formation of sulfonimide with selectivities ranging from 2:1 to more than 20:1. Conversely, a bismuth catalyst supported by an electron-deficient sulfoximine predominantly promoted the sulfonimidate product with ratios ranging between 5:1 and 15:1. To understand the underlying principles that control the selectivity, a comprehensive mechanistic investigation was conducted by combining experimental stoichiometric studies, DFT calculations, and statistical modeling. These studies support a catalytic high-valent bismuth redox cycle, where Bi(V) intermediates dictate product selectivity through either a three- or five-membered reductive elimination-ligand coupling event. By means of statistical modeling, we identified that the charge of the coordinating heteroatom through hypervalency, together with a steric parameter around the bismuth, is the key parameter responsible for the stabilization of the relevant transition states that lead to control over the reductive elimination process.

PMID:41202213 | DOI:10.1021/jacs.5c11854

JMIR Form Res. 2025 Nov 7;9:e71911. doi: 10.2196/71911.

ABSTRACT

BACKGROUND: Older adults undergoing surgeries face increased risks of postoperative neurocognitive disorders, which impair cognitive functions. Analog neurocognitive tests are commonly used, but digital tests offer faster, more accessible assessments.

OBJECTIVE: The primary aim of this study was to evaluate the feasibility of a digital cognitive test battery in older adults undergoing abdominal surgery. Feasibility included estimation of recruitment and retention rates, acceptability, perceived value, and usability of the test. The secondary aim was to explore outcome trajectories of cognition, depression, functional status, and quality of recovery.

METHODS: This nonrandomized feasibility study measured recruitment and retention rates using patient logs and expanded on these findings in semistructured interviews with nurses. Acceptability, perceived value, and usability were explored through interviews with patients and nurses, and the System Usability Scale (SUS). Cognitive functions were assessed with a digital cognitive test battery (Consortium to Establish a Registry for Alzheimer Disease [CERAD] word list learning test, Trail Making Test Parts A and B, Victoria Stroop Test, and Symbol Digit Pairing Test) and the Nursing Delirium Screening scale (NU-DESC), and depression with the Geriatric Depression Scale (GDS-15). Functional status was measured using the World Health Organization Disability Assessment Schedule (WHODAS), and postoperative recovery with the Swedish Quality of Recovery questionnaire (SwQoR-24). Quantitative data were analyzed using descriptive statistics and nonparametric tests and qualitative data with content analysis.

RESULTS: The test battery was feasible, acceptable, and demonstrated excellent usability. The mean SUS score was 87 (SD 17.9; 95% CI 78.9-95.2), and all predefined progression criteria were met. Recruitment spanned over 1.5 years, during which 24 patients were included (mean age of 77, SD 6.5 years; range: 63-90 years; n=13, 54% women). Most patients underwent laparoscopic colorectal cancer surgery. Three patients developed postoperative delirium for 1 day only. No patient developed delayed neurocognitive recovery or mild/major neurocognitive disorder at the postoperative follow-up. Qualitative data showed that both nurses and patients regarded the digital cognitive test battery as important for assessing cognitive function and found it easy to use and understand. Nurses reported that recruitment was challenging, partly because not all patients attended a preoperative in-person consultation before surgery.

CONCLUSIONS: The digital, self-administered cognitive test battery was found to be feasible, acceptable, and usable in older adults undergoing abdominal surgery. However, recruitment challenges and a small, homogeneous sample limit generalizability and warrant careful consideration in a larger-scale study.

PMID:41202209 | DOI:10.2196/71911

JMIR Form Res. 2025 Nov 7;9:e72468. doi: 10.2196/72468.

ABSTRACT

BACKGROUND: Osteoporosis-related fractures significantly impact older adults, often leading to disability and even premature death. While pharmacological and nonpharmacological interventions are widely recommended for managing osteoporosis, adherence to these interventions remains low. To address this challenge, we developed the Healthy Bone digital platform (desktop, mobile app, and smart TV internet-based) for use in clinical settings to improve disease management and treatment adherence. It integrates a multimedia health-related behavioral change program with a patient monitoring and management system.

OBJECTIVE: This study aimed to evaluate the usability and user experience of the desktop version of the Healthy Bone digital platform prototype from the patients’ perspective. The findings will provide valuable insights into optimizing the digital platform and enhancing its functionality.

METHODS: A mixed-methods study was conducted. During usability testing, patients completed tasks simulating real-world use of the platform while using a Think-Aloud approach. After each task, participants filled out an After Scenario Questionnaire to assess task satisfaction. Subsequently, participants completed the System Usability Scale (SUS) and the eHealth Usability Benchmarking Instrument (HUBBI) to measure usability quantitatively. Following this, semistructured interviews were conducted to explore participants’ experiences with the platform in greater depth. Descriptive statistics were used for quantitative analysis. Qualitative data analysis involved a combined deductive and inductive approach, ensuring a comprehensive evaluation of the platform’s usability and user experience. Deductive content analysis was guided by an ontology of eHealth usability components, while thematic analysis adhered to Braun and Clarke’s method to identify emerging themes.

RESULTS: Seven participants evaluated the digital platform, reporting high usability with a mean overall SUS score of 87.1 (SD 13.3). Similarly, good usability was reported across all categories of the HUBBI, except for the guidance and support category, which presented moderate levels of usability (mean 3.3, SD 1.1). Patients reported high levels of task satisfaction and identified 24 unique usability issues, predominantly related to the basic system performance, interface design, and navigation and structure categories of the eHealth usability ontology. Overall, patients had positive perceptions and acceptability of the digital platform, highlighting its simplicity, accessibility, utility, and potential to empower those with osteoporosis. Barriers to usage included limited skills, lack of suitable equipment, and time, while facilitators included motivation for behavior change, health benefits, and the decrease of potential inequalities.

CONCLUSIONS: This study provided valuable insights into the usability and user experience of the desktop version of the Healthy Bone digital platform prototype. These findings will play a key role in optimizing the platform to ensure it is effectively tailored to the needs of the target population. This platform adds an understanding of how various information and communication technology tools can support and benefit large numbers of osteoporosis patients in society.

PMID:41202207 | DOI:10.2196/72468

JCO Clin Cancer Inform. 2025 Nov;9:e2500122. doi: 10.1200/CCI-25-00122. Epub 2025 Nov 7.

ABSTRACT

PURPOSE: We developed and validated a dual-purpose, open-access Rural-Urban Commuting Area (RUCA) tool to standardize geographic coding for cancer disparities research, addressing National Institutes of Health (NIH) Helping to End Addiction Long-term (HEAL) Initiative Common Data Element requirements while supporting institutional catchment area analyses.

METHODS: This web-based tool¹⁶ integrates US Department of Agriculture RUCA codes with census tract data and electronic health record systems, meeting NIH HEAL Initiative Findable, Accessible, Interoperable, and Reusable (FAIR) data ecosystem requirements. We implemented the tool using Wake Forest Cancer Center’s 2023 registry data (n = 21,219) and conducted systematic comparison with county-level Rural-Urban Continuum Code (RUCC) classifications using 18,714 cancer cases across 336 ZIP codes, focusing on breast, colon, and lung cancers to demonstrate enhanced geographic granularity.

RESULTS: Among 21,219 patients with cancer, 19.51% (n = 4,140) resided in rural areas, with 4.81% (n = 1,022) in the most rural census tracts (RUCA codes 7-10). Comparative analysis revealed 9.4% disagreement between RUCA and RUCC classifications, affecting 1,765 patients. Twenty-eight ZIP codes classified as rural by RUCA were located within metropolitan counties according to RUCC, encompassing 109 patients with cancer who would be misclassified using county-level measures. As a separate use case, integration with NIH HEAL Initiative standardized rurality data collection across 15 research studies.

CONCLUSION: The RUCA tool addresses critical gaps in geographic data standardization by providing census tract-level precision that county-level classifications miss. This dual-application framework aligns institutional catchment analyses with national standardization efforts, identifying 109 patients with cancer who would be misclassified as urban residents using traditional county-level approaches, thereby enhancing targeted interventions for rural cancer care access.

PMID:41202192 | DOI:10.1200/CCI-25-00122

JCO Clin Cancer Inform. 2025 Nov;9:e2500086. doi: 10.1200/CCI-25-00086. Epub 2025 Nov 7.

ABSTRACT

PURPOSE: Partial nephrectomy has been advocated as the preferred surgical approach for small kidney tumors over total nephrectomy. However, partial nephrectomy is associated with increased perioperative risk. Estimating renal function after nephrectomy can facilitate personalized patient counseling, guide surgical approach, and identify patients who could benefit from perioperative interventions. Existing prediction models have several limitations including the lack of external validation or a user-friendly tool or application, and most have used traditional statistical methods.

METHODS: We used data from two academic medical institutions and machine learning (ML) methods to develop and externally validate renal function after nephrectomy-machine learning (RFAN-ML), a model to estimate long-term renal function after partial or total nephrectomy. Boruta feature selection was used to select four routinely available clinical features, specifically age, BMI, preoperative renal function, and nephrectomy type. In the training set of 1,932 patients, we compared six ML regression models representing a set of both ensemble and nonensemble ML algorithms and optimized for root mean squared error (RMSE). This model was evaluated in a test set of 1,995 patients, and the best performing model was selected as RFAN-ML.

RESULTS: We compared RFAN-ML with existing renal function prediction benchmarks and found that RFAN-ML outperformed or had competitive performance with benchmarks on RMSE (16.6 [95% CI, 15.6 to 17.5]), R², and mean absolute error.

CONCLUSION: We developed and externally validated RFAN-ML, a ML model to predict renal function after nephrectomy, and have deployed our model online. RFAN-ML has the potential to improve the care and outcomes in patients with kidney tumors by informing personalized patient counseling and guiding surgical planning.

PMID:41202191 | DOI:10.1200/CCI-25-00086

PLoS One. 2025 Nov 7;20(11):e0336111. doi: 10.1371/journal.pone.0336111. eCollection 2025.

ABSTRACT

The trans-theoretical model of behavior change (TTM) is widely used to assess an individual’s readiness to perform the new behavior and categorizes the behavior change into five stages: “pre-contemplation, contemplation, preparation, action, and maintenance.” This study focuses on assessing smoking cessation counseling practices (SCC) among Jordanian healthcare providers (HCPs) across various settings using the TTM. A cross-sectional study was conducted among HCPs (i.e., pharmacists, nurses, physicians, and dentists) working in private and public healthcare settings, using an online self-administered questionnaire. A total of 443 HCPs were included. One-third of HCPs reported asking patients if they smoked at their “first visit only.” Only 24.2% advised every patient to stop smoking, while 17.6% went beyond to assist smokers to make quit attempts, and (16.5%), assessed the willingness of the patients to quit and arrange follow-up quit attempts (10.6%). Only 28.4% of HCPs received training on SCC techniques. The majority of HCPs had a moderate level of confidence in performing SCC practices. HCPs in the private sector were more likely to be active in SCC practices than those in the public sector. Dentists and physicians were more involved in SCC practices than nurses and pharmacists. The study found a significant relationship between HCPs’ stage of change, self-efficacy, and performing SCC practices. This study affords a better understanding of the HCPs’ SCC practices. HCPs are found not to fully perform the “5 As” guidelines in their practices. Future efforts should focus on training and developing education programs that encourage HCPs to perform SCC practice.

PMID:41202117 | DOI:10.1371/journal.pone.0336111

PLoS One. 2025 Nov 7;20(11):e0335445. doi: 10.1371/journal.pone.0335445. eCollection 2025.

ABSTRACT

The coral microbiome can strongly influence coral health, development, and resilience. While larval settlement is fundamental for coral restoration efforts using assisted larval propagation, post-settlement survival remains a major challenge. The study of lab-bred Orbicella faveolata settlers (LBOFS) microbiome has been proposed due to its potential role in coral adaptation processes. However, there is limited information about LBOFS bacterial communities and comparisons between different growth conditions and life-cycle stages have not been conducted. Using 16S rRNA high-throughput sequencing, we analyzed the structure and composition of LBOFS-associated bacteria and compared them to those from outplanted LBOFS and wild settlers. We also compared the microbiomes of settlers to adult colonies. The LBOFS bacterial community was composed of 4224 ASVs with the Orders Kiloniellales, Rhodobacterales, Cytophagales, Cyanobacteriales, and Flavobacteriales being the most abundant across the samples, with a rare biosphere consisting of 44.6% relative abundance. A Principal Coordinates Analysis and a PERMANOVA indicated significantly different bacterial community structures based on settler growth conditions and life-cycle stage. Linear discriminant analysis Effect Size analysis identified specific taxa whose differential abundances contributed to the observed differences. For settler growth conditions, the differences were mainly due to the Order Cyanobacteriales for LBOFS, SAR202 clade for outplanted settlers, and Microtrichales for wild samples. Statistical analysis of functional prediction showed significant differences only in nitrogen fixation for LBOFS. For life-cycle stage, LEfSe revealed that the Orders Cytophagales and Cyanobacteriales exhibited the highest differential abundances in adults and settlers, respectively. Functional prediction revealed that nitrogen fixation and oxygenic photoautotrophy were more enriched in settlers, whereas nitrate reduction and anaerobic chemoheterotrophy were more enriched in adults. This study highlighted the bacterial taxa and predicted metabolic processes that could potentially contribute to coral settler functioning, providing a valuable baseline for future research to enhance their survival rates using probiotics.

PMID:41202107 | DOI:10.1371/journal.pone.0335445

PLoS One. 2025 Nov 7;20(11):e0336255. doi: 10.1371/journal.pone.0336255. eCollection 2025.

ABSTRACT

BACKGROUND: Adverse pregnancy outcomes continue to pose a significant global public health challenge, especially in low- and middle-income countries. Although preconception care (PCC) interventions are advised to address this problem, their adoption remains inadequate, supported by scarce evidence particularly in conflict-impacted areas such as Tigray, Ethiopia, where rates of poor outcomes like neural tube defects are notably higher than in other regions. This study investigates the experience of pregnant women regarding the use of PCC in the Tigray, northern Ethiopia.

METHODS: A community-based cross-sectional study was conducted from July 31 to August 16, 2024, involving 764 pregnant women in their first or second trimester. Participants were consecutively enrolled from clusters until the predetermined sample size was achieved. Data were collected through interviewer-administered questionnaires in accordance with World Health Organization, and Centers for Disease Control and Prevention, and national guidelines. PCC uptake was measured as the receipt of any service component (screening, counseling, or management) during healthcare consultations. We used SPSS version 27.0 to analyze PCC uptake and its associated factors. Descriptive and binary logistic regression statistics were used in the analysis. Finally, data was presented using text, tables, and figures as appropriate.

RESULTS: In this study, the overall uptake of PCC services was 7.2%. All participants in the current pregnancy were exposed to at least one risk factor for adverse pregnancy outcomes. Factors such as women’s decision-making power, having information about PCC, HIV screening during the current pregnancy, and perceived susceptibility to preconception risks showed a statistically significant positive association with the uptake of PCC services.

CONCLUSION: The uptake of PCC services was very low. Addressing the low uptake of PCC services requires a multifaceted strategy, including public health campaigns via media and social forums, strengthened health extension programs, and the integration of a reproductive life plan tool to improve health-seeking behavior among women.

PMID:41202106 | DOI:10.1371/journal.pone.0336255

PLoS Comput Biol. 2025 Nov 7;21(11):e1013691. doi: 10.1371/journal.pcbi.1013691. Online ahead of print.

ABSTRACT

Understanding microbial interactions is fundamental for exploring population dynamics, particularly in microbial communities where interactions affect stability and host health. Generalized Lotka-Volterra (gLV) models have been widely used to investigate system dynamics but depend on absolute abundance data, which are often unavailable in microbiome studies. To address this limitation, we introduce an iterative Lotka-Volterra (iLV) model, a novel framework tailored for compositional data that leverages relative abundances and iterative refinements for parameter estimation. The iLV model features two key innovations: an adaptation of the gLV framework to compositional constraints and an iterative optimization strategy combining linear approximations with nonlinear refinements to enhance parameter estimation accuracy. Using simulations and real-world datasets, we demonstrate that iLV surpasses existing methodologies, such as the compositional LV (cLV) and the generalized LV (gLV) model, in recovering interaction coefficients and predicting species trajectories under varying noise levels and temporal resolutions. Applications to the lynx-hare predator-prey, Stylonychia pustula-P. caudatum mixed culture, and cheese microbial systems revealed consistency between predicted and observed relative abundances showcasing its accuracy and robustness. In summary, the iLV model bridges theoretical gLV models and practical compositional data analysis, offering a robust framework to infer microbial interactions and predict community dynamics using relative abundance data, with significant potential for advancing microbial research.

PMID:41202104 | DOI:10.1371/journal.pcbi.1013691

Environ Sci Technol. 2025 Nov 7. doi: 10.1021/acs.est.5c06700. Online ahead of print.

ABSTRACT

Estuaries and adjacent waters are highly productive ecosystems, but are increasingly stressed by urbanization and climate change. Understanding long-term shifts in fish communities is critical for sustainable management, yet remains limited by scarce historical data. Here, we applied quality-controlled sedimentary DNA (sedDNA) metabarcoding, combining contamination prevention, stringent data filtering, and statistical calibration, to reconstruct ca. 100 years of fish diversity dynamics in the Pearl River Estuary (PRE) area, southern China. The monitored sedDNA data sets revealed that changes in fish communities in the PRE can be categorized into four distinct historical phases: the 1930s-1950s, 1950s-1970s, 1970s-1990s, and 1990s-2020s. Taxonomic and functional richness peaked around the 1970s but declined sharply thereafter. Small-bodied and omnivorous species gradually gave way to larger-bodied and warm-water species, reflecting a shift in trophic and habitat preferences over time. Invasive species, such as Oreochromis niloticus and Coptodon zillii, became increasingly dominant, whereas indigenous species markedly declined. Multivariate analyses showed that urbanization primarily affected taxonomic diversity, while climate drivers shaped functional traits and community structure, with invasive species acting as key mediators of ecological disruption. Overall, these results offer new insights into the century-scale fish diversity dynamics under compounded urbanization and climatic pressures, and highlight sedDNA as a powerful tool for reconstructing historical biomonitoring records.

PMID:41202103 | DOI:10.1021/acs.est.5c06700