Category: Nevin Manimala

BMC Public Health. 2025 Sep 1;25(1):3003. doi: 10.1186/s12889-025-24194-x.

ABSTRACT

BACKGROUND: Ineffective dissemination of cancer research and information among the public contributes to cancer inequities. Dissemination rarely involves efforts to engage non-research audiences and end-users in developing effective messaging. Efforts to promote equity in clinical trial participation may benefit from marketing strategies traditionally applied in the business sector. Black Americans suffer the highest death rates from most cancers than any other race/ethnicity, yet only 5% of patients enrolled in cancer clinical trials are Black. Our team used a marketing strategy framework to create a culturally responsive public service announcement (PSA) video to increase awareness of clinical trials among Black audiences.

METHODS: We partnered with a marketing recruitment firm and a marketing agency to conduct six focus groups (n = 54) with social support networks of Black cancer survivors and Black community members. Maximum variation sampling was used to recruit a national sample of eligible participants that varied in age, education, geographic region, and gender. Focus groups were conducted over three phases that informed script development, script and storyline testing, and sought feedback on the PSA video post-production. We used the Marketing and Clinical Trials Reference Model to guide marketing strategies, data collection, video content development and production. We used rapid qualitative data analysis techniques to identify themes for each phase to guide PSA development.

RESULTS: Partnered with a film production company, we produced a 2-min PSA video that uses professional actors and storytelling and marketing techniques to describe clinical trials, provide relevant statistics, address barriers to participation expressed by participants, and provide credible resources to seek further information. We also produced 30 s and 60 s versions of the PSA to accommodate different marketing media outlets. Participants felt the videos were engaging and relatable and that the messaging was clear. The videos ignited meaningful discussions about clinical trial participation and motivated participants to share the information learned.

CONCLUSIONS: Using marketing communication strategies is a low-tech, pragmatic approach to effectively produce health information that is meaningful, can be tailored for specific audiences, and disseminated to broader audiences.

PMID:40890722 | DOI:10.1186/s12889-025-24194-x

BMC Med Inform Decis Mak. 2025 Sep 1;25(1):321. doi: 10.1186/s12911-025-03119-z.

ABSTRACT

PURPOSE: Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss, and its prevalence is expected to rise with aging populations. Early prediction of AMD progression is critical for effective management. This systematic review and meta-analysis evaluate the accuracy, sensitivity, and specificity of artificial intelligence (AI) algorithms in in detecting and predicting progression of AMD.

METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review and meta-analysis were conducted from inception to February 7th, 2025. We included five studies that assessed the performance of AI algorithms in predicting AMD progression using multimodal imaging. Data on accuracy, sensitivity, and specificity were extracted, and meta-analysis was performed using Comprehensive Meta-Analysis software version 3.7. Heterogeneity was assessed using the I² statistic.

RESULTS: Of the five studies, AI models demonstrated superior accuracy (mean difference: 0.07, 95% CI: 0.07, 0.07; p < 0.00001) and sensitivity (mean difference: 0.08, 95% CI: 0.08, 0.08; p < 0.00001) compared to retinal specialists. Specificity also showed a minimal but significant advantage for AI (mean difference: 0.01, 95% CI: 0.01, 0.01; p < 0.00001). Importantly, heterogeneity was minimal to absent across all analyses (I² = 0-0.42%), supporting the reliability and consistency of pooled findings.

CONCLUSION: AI algorithms outperform retinal specialists in predicting AMD progression, particularly in accuracy and sensitivity. These findings support the potential of AI in AMD prediction; however, given the limited number of included studies, the results should be interpreted as exploratory and in need of validation through future large-scale, prospective studies.

PMID:40890721 | DOI:10.1186/s12911-025-03119-z

Clin Neuropsychol. 2025 Sep 1:1-14. doi: 10.1080/13854046.2025.2552289. Online ahead of print.

ABSTRACT

Objective: To assess the feasibility, accuracy, and reliability of using ChatGPT-4.5 (early-access), a large language model (LLM), for automated scoring of Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) protocols. Performance of ChatGPT-4.5 was compared against human raters on scoring record forms (i.e. word lists, numeric tables, and drawing responses). Method: Thirty-five deidentified BICAMS protocols, including the Symbol Digit Modalities Test (SDMT), California Verbal Learning Test-II (CVLT-II), and Brief Visuospatial Memory Test-Revised (BVMT-R), were independently scored by two trained human raters and ChatGPT-4.5. Scoring with ChatGPT-4.5 involved uploading protocol scans and structured prompts. Scoring discrepancies were resolved by a blinded third rater. Intraclass correlation coefficients (ICCs), paired samples t-tests, and descriptive statistics evaluated interrater reliability, accuracy, and speed. Results: Before public release of ChatGPT-4.5, strong interrater reliability was found between ChatGPT-4.5 and human raters on all total scores (e.g. CVLT-II ICC = 0.992; SDMT ICC = 1.000; BVMT-R ICC = 0.822-853), with minimal scoring discrepancies per test (CVLT = 1.05, SDMT = 0.05, BVMT-R = 1.05-1.19). ChatGPT-4.5 identified scoring errors overlooked by two human raters and completed scoring of each BICAMS protocol in under 9 min. After ChatGPT-4.5 was publicly released, reliability decreased notably (e.g. ICC = -0.046 for BVMT-R Trial 3), and average scoring discrepancies per test increased (e.g. SDMT = 6.79). Conclusions: ChatGPT-4.5 demonstrated comparable accuracy relative to human raters, though performance variability emerged after public release. With adequate computational resources and prompt/model optimization, LLMs may streamline neuropsychological assessment, enhancing clinical efficiency, and reducing human errors.

PMID:40889122 | DOI:10.1080/13854046.2025.2552289

Brief Bioinform. 2025 Aug 31;26(5):bbaf446. doi: 10.1093/bib/bbaf446.

ABSTRACT

The emergence of single-cell RNA sequencing (scRNA-seq) technology has transformed our understanding of cellular diversity, yet it presents notable challenges for cell type annotation due to data’s high dimensionality and sparsity. To tackle these issues, we present scSorterDL, an innovative approach that combines penalized Linear Discriminant Analysis (pLDA), swarm learning, and deep neural networks (DNNs) to improve cell type classification. In scSorterDL, we generate numerous random subsets of the data and apply pLDA models to each subset to capture varied data aspects. The model outputs are then consolidated using a DNN that identifies complex relationships among the pLDA scores, enhancing classification accuracy by considering interactions that simpler methods might overlook. Utilizing GPU computing for both swarm learning and deep learning, scSorterDL adeptly manages large datasets and high-dimensional gene expression data. We tested scSorterDL on 13 real scRNA-seq datasets from diverse species, tissues, and platforms, as well as on 20 pairs of cross-platform datasets. Our method surpassed nine current cell annotation tools in both accuracy and robustness, indicating exceptional performance in both cross-validation and cross-platform contexts. These findings underscore the potential of scSorterDL as an effective and adaptable tool for automated cell type annotation in scRNA-seq research. The code is available on GitHub: https://github.com/kellen8hao/scSorterDL.

PMID:40889117 | DOI:10.1093/bib/bbaf446

Brief Bioinform. 2025 Aug 31;26(5):bbaf445. doi: 10.1093/bib/bbaf445.

ABSTRACT

Enhancing antibody affinity is a critical goal in antibody design, as it improves therapeutic efficacy, specificity, and safety while reducing dosage requirements. Traditional methods, such as single-point mutations or combinatorial mutagenesis, are limited by the impracticality of exhaustively exploring the vast mutational space. To address this challenge, we developed a novel computational pipeline that integrates evolutionary constraints, antibody-antigen-specific statistical potentials, molecular dynamics simulations, metadynamics, and a suite of deep learning models to identify affinity-enhancing mutations. Our deep learning framework includes MicroMutate, which predicts microenvironment-specific amino acid mutations, and graph-based models that evaluate postmutation antigen-antibody-binding probabilities. Using this approach, we screened 12 single-point mutant antibodies targeting the hemagglutinin of the H7N9 avian influenza virus, starting from antibodies with initial affinities in the subnanomolar range, with one showing a 4.62-fold improvement. To demonstrate the generalizability of our method, we applied it to engineer an antibody against death receptor 5 with initial affinities in the subnanomolar range, successfully identifying a mutant with a 2.07-fold increase in affinity. Our work underscores the transformative potential of integrating deep learning and computational methods for rapidly and precisely discovering affinity-enhancing mutations while preserving immunogenicity and expression. This approach offers a powerful and universal platform for advancing antibody therapeutics.

PMID:40889116 | DOI:10.1093/bib/bbaf445

Cancer Cytopathol. 2025 Sep;133(9):e70046. doi: 10.1002/cncy.70046.

ABSTRACT

BACKGROUND: Rapid on-site evaluation (ROSE) of thyroid fine-needle aspiration biopsy (FNAB) improves diagnostic adequacy and facilitates ancillary molecular testing. In this prospective, multireader study, the authors evaluated the feasibility of using whole-slide images (WSIs) for ROSE to determine specimen adequacy and preliminary categorization (according to The Bethesda System for Reporting Thyroid Cytopathology [Bethesda]) of image-guided thyroid FNABs compared with conventional light-microscopic (LM) examination of the same specimens in a referral cancer center.

METHODS: The authors evaluated 98 ultrasound-guided thyroid FNAB cases. Smears were stained with Papanicolaou and Diff-Quik and were scanned at ×20 magnification using a Leica Aperio CS2 scanner. Five cytopathologists evaluated specimen adequacy and Bethesda categorization using WSI followed by LM assessment after a 2-week washout. Intraobserver and interobserver agreements were calculated using Cohen and Fleiss kappa (κ) statistics. Scan time, interpretation time, and the need for ×40 magnification or z stacking were recorded.

RESULTS: In total, 463 slides were scanned, with mean scan time of 5.48 minutes. WSI quality was acceptable in most cases. Z stacking and ×40 magnification were requested in 23% and 14% of reviews, respectively. Intrareader agreement between WSI and LM examination was excellent (κ = 0.86-0.95). Inter-reader agreement was moderate for both WSI (κ = 0.48) and LM examination (κ = 0.56). Concordance was highest for Bethesda categories I and VI and lowest for categories III-V. Interpretation with WSI took significantly longer than with LM examination (p < .0001).

CONCLUSIONS: WSI is a feasible alternative to LM examination for ROSE of thyroid FNABs, with high intrareader agreement and comparable inter-reader agreement. The limited need for high magnification and z stacking supports its practical utility.

PMID:40889104 | DOI:10.1002/cncy.70046

Ophthalmol Ther. 2025 Sep 1. doi: 10.1007/s40123-025-01226-8. Online ahead of print.

ABSTRACT

INTRODUCTION: This study investigated the long-term natural history of peripapillary pachychoroid syndrome (PPS), analyzing both morphological and functional outcomes.

METHODS: This retrospective study included 24 eyes from 14 participants diagnosed with PPS. No interventions were administered. Baseline and follow-up assessments comprised best-corrected visual acuity (BCVA), measured on the LogMAR scale, inner nasal (IN) and outer nasal (ON) macular thickness measured using the ETDRS (Early Treatment Diabetic Retinopathy Study) subfields. To account for repeated measures and the hierarchical structure of eyes nested within participants, and to appropriately handle incomplete longitudinal data, linear mixed-effects models were utilized for all statistical analyses.

RESULTS: The mean age was 74 ± 7 years, and 71% of patients had bilateral PPS. All patients had peripapillary atrophy at baseline. The mean baseline BCVA was 0.05 and showed only small variations over time. ON macular thickness showed a significant decrease at 2 years (Δ = – 36.9 µm, p = 0.034), whereas IN macular thickness decreased significantly at both 2 years (Δ = – 40.75 µm, p = 0.023) and 3 years (Δ = – 39.97 µm, p = 0.042). One-quarter of participants developed a serous pigment epithelium detachment with subretinal fluid, suggesting an overlapping PPS/CSC (central serous chorioretinopathy) phenotype.

CONCLUSIONS: Peripapillary atrophy appears to be an important anatomical predisposition for PPS. Waxing and waning of intraretinal fluid were observed during the natural course of PPS, with a significant reduction at 2 years. Most patients remained asymptomatic and maintained stable BCVA throughout long-term follow-up, indicating a generally favorable prognosis in the absence of intervention.

PMID:40889090 | DOI:10.1007/s40123-025-01226-8

CNS Drugs. 2025 Sep 1. doi: 10.1007/s40263-025-01215-2. Online ahead of print.

ABSTRACT

OBJECTIVE: To characterize multinational trends and patterns of opioid analgesic prescribing by sex and age.

DESIGN, SETTING, AND PARTICIPANTS: We studied opioid analgesic prescribing from 2001 to 2019 with common protocol using population-based databases from eighteen countries and one special administrative region.

MAIN OUTCOME MEASURES: We measured opioid prescribing by geographical region, sex and age, estimating annual prevalent, incident, and nonincident opioid prescribing per 100 population with a 95% confidence interval (CI) and meta-analyzed the multinational and regional opioid prescribing with a random-effects model. Time trends were reported through average annual absolute changes, estimated using linear mixed models. We further explored the effect of sex and age on prevalent opioid prescribing in the multivariable analysis.

RESULTS: Over 248 million individuals were included. Pooled multinational opioid prescribing prevalence was 9.0% amongst included countries/regions. Opioid prescribing prevalence in 2015 ranged from 2.7% in Japan to 19.7% in Iceland. Average annual absolute changes in opioid prescribing prevalence per year ranged from – 1.53% (95% CI – 2.06, – 1.00; United States Medicaid) to + 1.24% (95% CI 1.02, 1.46; South Korea). Pooled multinational incident opioid prescribing (4.9%; 95% CI 4.1, 5.9) was higher than pooled multinational nonincident opioid prescribing (3.7%; 95% CI 2.9, 4.8). The female sex and older age were associated with higher opioid prescribing. Main limitations of this study include the absence of data from study duration or individuals not covered by the data sources and the lack of information on medication adherence and indication.

CONCLUSIONS: Opioid prescribing remains unbalanced across geographical regions; however, results suggest a tendency to convergence across countries/regions. Differences in opioid prescribing by sex and age were identified.

PMID:40889082 | DOI:10.1007/s40263-025-01215-2

AIDS Behav. 2025 Sep 1. doi: 10.1007/s10461-025-04822-8. Online ahead of print.

ABSTRACT

Female sex workers (FSW) are a key population who experience a disproportionately high burden of HIV and sexually transmitted infections (STIs). A growing body of evidence suggests that financial incentives can reduce risky sexual behavior and reduce HIV/STI incidence, however few studies have examined a lottery-based incentive mechanism or been conducted with FSW. We examined the effect of a lottery intervention on combined HIV/HSV2 incidence among FSW. The RESPECT II trial was an unmasked, two-arm, parallel group randomized controlled trial conducted in Dar es Salaam, Tanzania (AEA RCT registry: AEARCTR-0002677). Individuals who were ≥ 18 years of age, HIV-negative, not currently pregnant, exchanged sex for money in the past six months, and living in Dar es Salaam were eligible. Participants were randomized in a 1:1 ratio to the basic test group (control) which included testing and counseling for HIV and biweekly text messages with information on safe sex practices, or to the lottery group, which provided the basic test group intervention plus entry into a weekly lottery with a 100,000 TZS (~ $50 USD) reward offered to ten randomly selected participants, conditional on negative test results for syphilis and trichomonas. The primary outcome was combined HIV/HSV2 incidence after 36 months. Between August 2018-February 2019, 2,489 individuals screened for eligibility and 2,206 were enrolled in the trial and randomized. Participants were followed for up to 36 months; 1089 (49.4%) were lost to follow-up at endline and 1,117 were included in the primary intent to treat analysis (609 lottery, 508 control). At 36 months, there was no effect of the lottery intervention on the incidence of combined HIV/HSV2 (unadjusted RD: – 0.006, 95% CI – 0.05, 0.04; adjusted RD – 0.001, 95% CI – 0.05, 0.05). However, the results may have been affected by disruption from the COVID-19 pandemic, and unexpectedly high study attrition levels made it impossible to statistically rule out possible moderate-sized effects.

PMID:40889079 | DOI:10.1007/s10461-025-04822-8

Matern Child Health J. 2025 Sep 1. doi: 10.1007/s10995-025-04174-8. Online ahead of print.

ABSTRACT

OBJECTIVES: This study uses 2022 National Vital Statistics System natality data to identify characteristics associated with infertility treatment among nulliparous individuals 35 years or older, comparing pregnancy and birth outcomes between no infertility treatment and assisted reproductive technology (ART) or fertility-enhancing drugs or intrauterine insemination (IUI).

METHODS: The likelihood of infertility treatment was estimated after controlling for maternal age, education, race and ethnicity, insurance status, Women, Infants and Children (WIC) support, pre-pregnancy body mass index (BMI), chronic hypertension, diabetes, and smoking during pregnancy. Maternal outcomes (gestational diabetes, hypertensive disorders of pregnancy, cesarean birth, maternal morbidity) and neonatal outcomes (preterm birth, low birth weight, neonatal intensive care, and congenital anomalies) were compared for singleton and multifetal births separately.

RESULTS: Among 173,399 births, 13.6% had infertility treatment (10.9% ART, 2.4% IUI). As compared to people who identified as white or Asian, infertility treatment was over one-third less likely for non-Hispanic Black and Hispanic individuals and 2.4 times more likely for those with a graduate degree as compared to those with less than high school. Infertility treatment was associated with significantly higher rates of all adverse maternal and neonatal outcomes, and among multifetal births, ART was associated with a higher rate of maternal morbidity and more frequent gestational diabetes.

CONCLUSIONS FOR PRACTICE: Disparities in infertility treatment exist. ART was associated with modest but significantly worse outcomes, particularly for singleton births. Continued monitoring of infertility treatment selection and birth outcomes is needed for informed clinical and public policy decisions.

PMID:40889057 | DOI:10.1007/s10995-025-04174-8