Nevin Manimala

PLoS One. 2025 Jul 14;20(7):e0327870. doi: 10.1371/journal.pone.0327870. eCollection 2025.

ABSTRACT

OBJECTIVE: This study examined the association between diagnosis of depressive disorder, the number of bad mental health days per month, and diabetes management behaviors among American Indian/Alaska Native (AI/AN) adults with diabetes.

RESEARCH DESIGN AND METHODS: Data were drawn from the Behavioral Risk Factor Surveillance System (2018-2021), including 2,272 self-identified non-Hispanic AI/AN adults diagnosed with non-gestational diabetes. Key variables included a self-reported prior diagnosis of depressive disorder and the number of bad mental health days in the past month. Outcome variables were seven diabetes management behaviors, such as taking a diabetes management class and performing daily foot checks. Statistical analyses included descriptive statistics, chi-squared tests, ANOVA, and logistic regression models.

RESULTS: Among the participants, 24.8% were diagnosed with depressive disorder, and 19.5% reported at least 14 bad mental health days in the past month. Logistic regression models show that those reporting depressive disorders were significantly less likely to check their feet daily (adjusted odds ratio (AOR) = 0.56, 95% CI: 0.34-0.92). Individuals with at least 14 bad mental health days were significantly less likely to have ever taken a diabetes management class (AOR = 0.59, 95% CI: 0.36-0.99) and check their feet daily (AOR = 0.37, 95% CI: 0.21-0.65) than those reporting no bad mental health days.

CONCLUSIONS: Depressive disorders and frequent bad mental health days were associated with lower odds of diabetes management behaviors among AI/AN adults. These findings suggest that enhancing mental health support within diabetes management programs may help address disparities in diabetes care among AI/AN adults.

PMID:40658702 | DOI:10.1371/journal.pone.0327870

J Vis Exp. 2025 Jun 24;(220). doi: 10.3791/68400.

ABSTRACT

This study aimed to use functional near-infrared spectroscopy (fNIRS) mobile neuroimaging technology to examine changes in prefrontal cortex (PFC) activity before, during, and after yoga asana (physical yoga postures). A total of 27 healthy adults participated in a 23 min yoga asana session using a block design. Before and after the sequence, participants completed two 6 min, task-independent resting states. PFC activity was continuously recorded using the fNIRS instrument, positioned on the frontal area of the skull. The session included a control posture alternating with three active postures. Each active posture was held for 30 s, followed by a 25-30 s control posture interval, and repeated eight times. This block design resulted in 25 control posture intervals and 24 repetitions of each active posture. Analysis included preprocessing of raw fNIRS data to calculate concentrations of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR), motion artifact correction, and statistical evaluation using ANOVA with Bonferroni corrections. Connectivity analyses examined interhemispheric and intrahemispheric correlations in the prefrontal cortex. In conclusion, this study demonstrates the utility of fNIRS in real-world, movement-based contexts and provides neurological insights into the effects of yoga asana.

PMID:40658699 | DOI:10.3791/68400

PLoS One. 2025 Jul 14;20(7):e0327130. doi: 10.1371/journal.pone.0327130. eCollection 2025.

ABSTRACT

BACKGROUND: People living with HIV (PLWH) who use tobacco face significant public health risks compared to non-users, including an average loss of 12.3 years of life expectancy. Tobacco use increases the likelihood of non-communicable diseases (NCDs), such as cardiovascular diseases, hypertension, diabetes mellitus, and non-AIDS-related cancers.

AIM: This study investigated factors associated with tobacco smoking and smokeless tobacco (SLT) use among PLWH in Zambia.

METHODS: Data were obtained from a national cross-sectional survey involving 5,204 PLWH from 193 clinics across Zambia’s 10 provinces. Tobacco smoking, SLT use, behavioral patterns, and clinical characteristics were assessed. Logistic regression was used to determine unadjusted (UOR) and adjusted odds ratios (AOR) at a 95% confidence interval (CI).

RESULTS: Among the 5,204 PLWH surveyed, 9.7% were current tobacco smokers (21.9% men, 3.7% women), while 1.4% used smokeless tobacco (1.81% men, 1.26% women). In the multivariable analysis, several factors were identified as predictors of tobacco smoking. Male individuals had significantly higher odds of smoking (AOR: 4.81, 95% CI: 3.36-6.90). In contrast, higher educational attainment was associated with lower odds of smoking (AOR: 0.29, 95% CI: 0.16-0.52). Alcohol consumption was associated with an increased likelihood of smoking (AOR: 4.97, 95% CI: 2.93-8.44). Additionally, overweight or obese individuals were less likely to smoke, with adjusted odds ratios of 0.55 (95% CI: 0.35-0.85) and 0.36 (95% CI: 0.17-0.79), respectively. Non-adherence to antiretroviral therapy (ART) was also associated with higher smoking rates (AOR: 1.75, 95% CI: 1.14-2.67). Similarly, several factors were identified as predictors of smokeless tobacco (SLT) use. Individuals with an annual income exceeding 4,000 ZMW had lower odds of using SLT (AOR: 0.31, 95% CI: 0.14-0.73). In contrast, alcohol users exhibited significantly higher odds of SLT use (AOR: 14.74, 95% CI: 1.99-109.02). Furthermore, non-adherence to ART was associated with an increased likelihood of SLT use (AOR: 3.32, 95% CI: 1.54-7.17).

CONCLUSIONS: Our findings highlight the urgent need for targeted interventions to reduce tobacco use among PLWH in Zambia. Integrating these measures within the existing healthcare framework can maximize impact. Gender-specific programs addressing unique risk factors, alongside economic empowerment initiatives for low-income females, could help curb SLT use. Additionally, reinforcing ART adherence through tobacco cessation counseling within HIV care settings may lower smoking rates. Given the strong association between alcohol consumption and tobacco use, structured behavioral interventions and support programs should also be prioritized. Strengthening collaborations between health authorities and community organizations can further enhance accessibility and outreach. By embedding these strategies within primary care and ART clinics, Zambia can effectively reduce tobacco use among PLWH, ultimately improving overall health outcomes and strengthening HIV management efforts.

PMID:40658694 | DOI:10.1371/journal.pone.0327130

Rev Med Inst Mex Seguro Soc. 2025 Jul 1;63(4):e6168. doi: 10.5281/zenodo.15644313.

ABSTRACT

BACKGROUND: Acute appendicitis is the most common surgical emergency worldwide. Closure of the appendiceal stump is a critical step to prevent postoperative complications.

OBJECTIVE: To compare postoperative outcomes of appendectomy using the Pouchet technique versus other appendiceal stump closure techniques.

MATERIAL AND METHODS: This retrospective study analyzed medical records of patients over 18 years of age who underwent surgery for acute appendicitis at a secondary-level hospital. Postoperative outcomes were assessed based on the presence of infectious complications, operative time, and length of hospital stay, comparing the surgical techniques used: Pouchet, Halsted, Zuckerman, and Parker. Descriptive and inferential statistics were applied, using the chi-square test to estimate differences in postoperative outcomes, with a significance level of ≤ 0.05.

RESULTS: A total of 118 medical records were analyzed, of which 70 corresponded to female patients (59.3%), with a median age of 39 years (interquartile range: 18-92 years). The most commonly used surgical techniques were: Pouchet (74 cases; 62.7%), Halsted (27; 22.8%), Zuckerman (12; 10.1%), and Parker (5; 4.2%). The Pouchet and Halsted techniques showed statistically significant differences compared to other techniques in terms of shorter operative time and hospital stay (p = 0.000 and p = 0.011, respectively). Additionally, the Pouchet and Parker techniques were associated with statistically significant differences in the incidence of infectious complications (p = 0.030).

CONCLUSIONS: The Pouchet technique demonstrated the best postoperative outcomes in terms of operative time, hospital stay duration, and lower incidence of infectious complications.

PMID:40658474 | DOI:10.5281/zenodo.15644313

Bioinformatics. 2025 Jul 14:btaf400. doi: 10.1093/bioinformatics/btaf400. Online ahead of print.

ABSTRACT

MOTIVATION: A critical challenge in observational studies arises from the presence of hidden confounders in high-dimensional data. This leads to biases in causal effect estimation due to both hidden confounding and high-dimensional estimation. Some classical deconfounding methods are inadequate for high-dimensional scenarios and typically require prior information on hidden confounders. We propose a two-step deconfounded and debiased estimation for high-dimensional linear regression with hidden confounding.

RESULTS: First, we reduce hidden confounding via spectral transformation. Second, we correct bias from the weighted ℓ1 penalty, commonly used in high-dimensional estimation, by inverting the Karush-Kuhn-Tucker conditions and solving convex optimization programs. This deconfounding technique by spectral transformation requires no prior knowledge of hidden confounders. This novel debiasing approach improves over recent work by not assuming a sparse precision matrix, making it more suitable for cases with intrinsic covariate correlations. Simulations show that the proposed method corrects both biases and provides more precise coefficient estimates than existing approaches. We also apply the proposed method to a deoxyribonucleic acid methylation dataset from the Alzheimer’s disease (AD) neuroimaging initiative database to investigate the association between cerebrospinal fluid tau protein levels and AD severity.

AVAILABILITY: The code for the proposed method is available on GitHub (https://github.com/Li-Zhaoy/Dec-Deb.git) and archived on Zenodo (DOI: 10.5281/zenodo.15478745).

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:40658470 | DOI:10.1093/bioinformatics/btaf400

Eur J Cardiothorac Surg. 2025 Jul 14:ezaf232. doi: 10.1093/ejcts/ezaf232. Online ahead of print.

ABSTRACT

OBJECTIVES: We evaluated intimal damage at the histological level resulting from various clamp techniques in human pulmonary artery specimens obtained after lobectomy.

METHODS: We prospectively analysed patients who underwent anatomical lung resection at two centres between April 2021 and March 2025. The double-loop technique (DLT), DeBakey vascular clamp (3rd and 4th notches), Fogarty vascular clamp (2nd notch), endovascular clips (gold and silver), and vessel loop technique (VLT) were evaluated. Pulmonary artery specimens with an external diameter ≥10 mm were included. We measured the burst pressure and evaluated the intimal damage in the human pulmonary artery by using the modified Zhang’s score (MZS; 0 – 5).

RESULTS: Thirty-six patients were enrolled, and 70 pulmonary artery samples were obtained. DeBakey 3rd exerted a significantly higher burst pressure than did DLT (P = 0.022). No significant difference was found between DLT and VLT (P = 0.453). A burst pressure ≥30 mmHg was achieved in all DLT cases. None of the samples clamped with DLT and VLT exhibited MZS 3 – 5. The rate of MZS ≥2 with DeBakey 3rd, Fogarty 2nd, gold and silver clips, and VLT was statistically comparable to that for DLT, whereas DeBakey 4th resulted in significantly higher MZS values than did DLT (P = 0.029).

CONCLUSIONS: The DLT is a feasible and safe for thoracoscopic clamping. Additionally, DLT, VLT, and gold clip are appropriate for clamping the peripheral pulmonary artery. For DeBakey vascular clamp, notch selection should be carefully tailored to the vessel diameter.

PMID:40658467 | DOI:10.1093/ejcts/ezaf232

Bioinformatics. 2025 Jul 14:btaf399. doi: 10.1093/bioinformatics/btaf399. Online ahead of print.

ABSTRACT

MOTIVATION: High-throughput sequencing of single-cell data can be used to rigorously evaluate cell specification and enable intricate variations between groups or conditions to be identified. Many popular existing methods for differential expression target differences in aggregate measurement (mean, median, sum) and limit their approaches to detect only global differential changes.

RESULTS: We present a robust method for differential expression of single-cell data using a kernel-based score test, cytoKernel. CytoKernel is specifically designed to assess the differential expression of single-cell RNA sequencing and high-dimensional flow or mass cytometry data using the full probability distribution pattern. cytoKernel is based on kernel embeddings which employs the probability distributions of the single-cell data, by calculating the pairwise divergence/distance between distributions of subjects. It can detect both patterns involving changes in the aggregate, as well as more elusive variations that are often overlooked due to the multimodal characteristics of single-cell data. We performed extensive benchmarks across both simulated and real data sets from mass cytometry data and single-cell RNA sequencing. The cytoKernel procedure effectively controls the False Discovery Rate (FDR) and shows favourable performance compared to existing methods. The method is able to identify more differential patterns than existing approaches. We apply cytoKernel to assess gene expression and protein marker expression differences from cell subpopulations in various publicly available single-cell RNAseq and mass cytometry data sets.

AVAILABILITY AND IMPLEMENTATION: The methods described in this paper are implemented in the open-source R package cytoKernel, which is freely available from Bioconductor at http://bioconductor.org/packages/cytoKernel.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:40658464 | DOI:10.1093/bioinformatics/btaf399

Bioinformatics. 2025 Jul 14:btaf397. doi: 10.1093/bioinformatics/btaf397. Online ahead of print.

ABSTRACT

MOTIVATION: DNA methylation plays important roles in various cellular physiological processes in bacteria. Nanopore sequencing has shown the ability to identify different types of DNA methylation from individual bacteria directly. However, existing methods for identifying bacterial methylomes showed inconsistent performances in different methylation motifs in bacteria and didn’t fully utilize the different scale information contained in nanopore signals.

RESULTS: We propose a deep-learning method, called Nanoident, for de novo detection of DNA methylation types and methylated base positions in bacteria using Nanopore sequencing. For each targeted motif sequence, Nanoident utilizes five different features, including statistical features extracted from both the nanopore raw signals and the basecalling results of the motif. All the five features are processed by a multi-scale neural network in Nanoident, which extracts information from different receptive fields of the features. The LOOCV (Leave-One-Out Cross Validation) on the dataset containing 7 bacteria samples with 46 methylation motifs shows that, Nanoident achieves ∼10% improvement in accuracy than the previous method. Furthermore, Nanoident achieves ∼13% improvement in accuracy in an independent dataset, which contains 12 methylation motifs. Additionally, we optimize the pipeline for de novo methylation motif enrichment, enabling the discovery of novel methylation motifs.

AVAILABILITY AND IMPLEMENTATION: The source code of Nanoident is freely available at https://github.com/cz-csu/Nanoident and https://doi.org/10.6084/m9.figshare.29252264.

SUPPLEMENTARY INFORMATION: data are available at Bioinformatics online.

PMID:40658463 | DOI:10.1093/bioinformatics/btaf397

Nucl Med Commun. 2025 Jul 4. doi: 10.1097/MNM.0000000000002020. Online ahead of print.

ABSTRACT

INTRODUCTION: Sjögren’s syndrome is a chronic autoimmune disease characterized by lymphocytic infiltration and destruction of exocrine glands. Sjögren’s syndrome characteristically involves salivary glands with the presence of xerostomia in the majority (>93%) of patients. The severity of xerostomia can vary from mild to severe and debilitating. Labial histopathology and antinuclear antibodies (ANA) are commonly used in the diagnosis of Sjögren’s syndrome but do not correlate well with disease severity. Tests available for objective assessment of disease severity include sialometry and salivary gland scintigraphy (SGS). This study aims to correlate the severity of xerostomia with semiquantitative parameters on SGS.

MATERIALS AND METHODS: On the basis of clinical symptoms, the severity of xerostomia was graded into mild, moderate, and severe. Semiquantitative parameters (maximum uptake and excretion fractions) for all salivary glands were calculated on SGS. Spearman’s correlation coefficients were calculated to assess correlation with clinical disease severity.

RESULTS: One-hundred thirteen patients (94 females and 19 males) with a median age of 39 years (range: 4-85 years) were included. Of these, 74 had mild, 28 had moderate, while only 11 had severe disease. There was a statistically significant difference between the mean values of maximum uptake and excretion fractions across the three severity groups (P < 0.05).

CONCLUSION: Semiquantitative parameters on SGS show a reduction with an increase in the severity of xerostomia. In addition, maximum uptake and excretion fractions correlated well with the severity of xerostomia of Sjögren’s syndrome, whereas ANA levels showed no significant correlation with disease severity. SGS can serve as an objective parameter of clinical severity of xerostomia, which is otherwise difficult to determine clinically.

PMID:40658462 | DOI:10.1097/MNM.0000000000002020

Stat Med. 2025 Jul;44(15-17):e10258. doi: 10.1002/sim.10258.

ABSTRACT

Multivariate (average) equivalence testing is widely used to assess whether the means of two conditions of interest are “equivalent” for different outcomes simultaneously. In pharmacological research for example, many regulatory agencies require the generic product and its brand-name counterpart to have equivalent means both for the AUC and C_max pharmacokinetics parameters. The multivariate Two One-Sided Tests (TOST) procedure is typically used in this context by checking if, outcome by outcome, the marginal $100\left(1–2\alpha \right)\%$ confidence intervals for the difference in means between the two conditions of interest lie within predefined lower and upper equivalence limits. This procedure, already known to be conservative in the univariate case, leads to a rapid power loss when the number of outcomes increases, especially when one or more outcome variances are relatively large. In this work, we propose a finite-sample adjustment for this procedure, the multivariate $\alpha$ -TOST, that consists in a correction of $\alpha$ , the significance level, taking the (arbitrary) dependence between the outcomes of interest into account and making it uniformly more powerful than the conventional multivariate TOST. We present an iterative algorithm allowing to efficiently define ${\alpha }^{*}$ , the corrected significance level, a task that proves challenging in the multivariate setting due to the inter-relationship between ${\alpha }^{*}$ and the sets of values belonging to the null hypothesis space and defining the test size. We study the operating characteristics of the multivariate $\alpha$ -TOST both theoretically and via an extensive simulation study considering cases relevant for real-world analyses-that is, relatively small sample sizes, unknown and possibly heterogeneous variances as well as different correlation structures-and show the superior finite-sample properties of the multivariate $\alpha$ -TOST compared to its conventional counterpart. We finally re-visit a case study on ticlopidine hydrochloride and compare both methods when simultaneously assessing bioequivalence for multiple pharmacokinetic parameters.

PMID:40658428 | DOI:10.1002/sim.10258