Tag: nevin manimala

Obstet Gynecol. 2025 Sep 11. doi: 10.1097/AOG.0000000000006068. Online ahead of print.

ABSTRACT

Trends in cervical cancer epidemiology and physician workforces have converged to make radical hysterectomy an increasingly rare procedure for gynecologic oncologists practicing in the United States. Using data from the National Cancer Database and the Centers for Disease Control and Prevention’s United States Cancer Statistics and published gynecologic oncology workforce data, we assessed trends in radical hysterectomy performed in the United States from 2004 to 2020. Over this period, the annual rate of radical hysterectomies per gynecologic oncologist declined significantly, by an average of 6.9% per year (95% CI, 6.4-7.5), corresponding to a decrease from 4.5 to 1.5 cases per oncologist per year. The increasing rarity of radical hysterectomy may pose a challenge to those seeking to acquire and maintain competency in this complex operation.

PMID:40934516 | DOI:10.1097/AOG.0000000000006068

JMIR Ment Health. 2025 Sep 11;12:e72038. doi: 10.2196/72038.

ABSTRACT

BACKGROUND: Depression is one of the most prevalent mental health disorders globally, affecting approximately 280 million people and frequently going undiagnosed or misdiagnosed. The growing ubiquity of wearable devices enables continuous monitoring of activity levels, providing a new avenue for data-driven detection and severity assessment of depression. However, existing machine learning models often exhibit lower performance when distinguishing overlapping subtypes of depression and frequently lack explainability, an essential component for clinical acceptance.

OBJECTIVE: This study aimed to develop and evaluate an interpretable machine learning framework for detecting depression and classifying its severity using wearable-actigraphy data, while addressing common challenges such as imbalanced datasets and limited model transparency.

METHODS: We used the Depresjon dataset and applied Adaptive Synthetic Sampling (ADASYN) to mitigate class imbalance. We extracted multiple statistical features (eg, power spectral density mean and autocorrelation) and demographic attributes (eg, age) from the raw activity data. Five machine learning algorithms (logistic regression, support vector machines, random forest, XGBoost, and neural networks) were assessed via accuracy, precision, recall, F1-score, specificity, and Matthew correlation constant. We further used Shapley Additive Explanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) to elucidate prediction drivers.

RESULTS: XGBoost achieved the highest overall accuracy of 84.94% for binary classification and 85.91% for multiclass severity. SHAP and LIME revealed power spectral density mean, age, and autocorrelation as top predictors, highlighting circadian disruptions’ role in depression.

CONCLUSIONS: Our interpretable framework reliably identifies depressed versus nondepressed individuals and differentiates mild from moderate depression. The inclusion of SHAP and LIME provides transparent, clinically meaningful insights, emphasizing the potential of explainable artificial intelligence to enhance early detection and intervention strategies in mental health care.

PMID:40934462 | DOI:10.2196/72038

Chem Biodivers. 2025 Sep 11:e01787. doi: 10.1002/cbdv.202501787. Online ahead of print.

ABSTRACT

Pistacia species are widely used in traditional medicine, particularly for wound healing. This study investigated the fatty acid composition of fruits from four Pistacia species collected from various regions of Algeria. Dried fruits of Pistacia lentiscus L. were extracted using hexane in a Soxhlet apparatus. The extracted lipids were subjected to acid hydrolysis and then converted into their corresponding methyl esters by refluxing with methanolic sulfuric acid prior to analysis. These methylated fatty acids were analyzed by gas chromatography coupled with mass spectrometry. The major fatty acids identified were oleic acid (C18:1n9c), palmitic acid (C16:0), linoleic acid (C18:2n6c), palmitoleic acid (C16:1), and stearic acid (C18:0). Multivariate statistical analysis using R software (version 4.3.3), including principal component analysis and hierarchical clustering, was applied to explore patterns among the fatty acid profiles. Oleic acid was dominant in PL3 (51.18%), linoleic acid in PL1 (21.86%), and palmitoleic acid in PL2 (3.26%). These findings support the ethnomedicinal relevance of Pistacia species and provide the first detailed chemometric profiling of their fruit fatty acid content.

PMID:40934461 | DOI:10.1002/cbdv.202501787

Neurology. 2025 Oct 7;105(7):e214068. doi: 10.1212/WNL.0000000000214068. Epub 2025 Sep 11.

ABSTRACT

BACKGROUND AND OBJECTIVES: Recent trials have shown the efficacy of endovascular thrombectomy (EVT) in patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO) and large infarcts on admission. However, many patients still experience poor outcomes despite treatment. The aim of this study was to investigate whether quantitative ischemic lesion net water uptake (NWU) on noncontrast head CT (NCCT) could identify AIS-LVO patients with large baseline infarcts who may require constant care or die despite successful EVT.

METHODS: This retrospective study included AIS-LVO patients with large baseline infarcts (Alberta Stroke Program Early CT Score ≤5) and occlusion of the intracranial internal carotid artery or first (M1) or second (M2) segments of the middle cerebral artery. Patients underwent EVT in 2 centers between 2012 and 2020. NWU was assessed on admission CT images by comparing density measurements of the ischemic core with the matching area of the contralateral hemisphere. The primary end point was a very poor outcome determined by functional neurologic status at 90 days on the modified Rankin Scale (mRS, score 5 or 6). Statistical analyses included group comparisons and evaluation of the predictive accuracy of an NWU ≥11.5% for very poor outcomes.

RESULTS: A total of 103 patients with AIS-LVO were included, of whom 57.3% were female, with a mean age of 72.1 years. Among patients with NWU ≥11.5%, 85% experienced very poor outcomes, compared with 51.8% of patients with an NWU <11.5% (p = 0.007). Patients with very poor outcomes had higher mean NWU compared with those without very poor outcomes (10.3% vs 6.0%, p < 0.001). An NWU threshold of 11.5% showed high specificity (93.0%, 95% CI 81.4-97.6) and positive predictive value (85%, 95% CI 64.0-94.8) for predicting very poor outcomes, which increased after combining it with other clinical and imaging parameters.

DISCUSSION: Elevated ischemic lesion NWU (≥11.5%) on admission NCCT was strongly associated with very poor functional outcomes at 90 days in AIS-LVO patients with large baseline infarcts treated by EVT. NWU assessment may serve as a valuable imaging biomarker for identifying patients who are likely to require constant care or die despite EVT.

PMID:40934458 | DOI:10.1212/WNL.0000000000214068

J Clin Oncol. 2025 Sep 11:JCO2501535. doi: 10.1200/JCO-25-01535. Online ahead of print.

NO ABSTRACT

PMID:40934453 | DOI:10.1200/JCO-25-01535

JCO Oncol Pract. 2025 Sep 11:OP2500475. doi: 10.1200/OP-25-00475. Online ahead of print.

ABSTRACT

PURPOSE: A provider’s participation in a randomized clinical trial (RCT) may influence their use of the trial intervention outside of trial contexts. We explored the association between site-level participation in a trial evaluating a postradical prostatectomy (RP) genomic classifier (GC; Genomics in Michigan Impacting Observation or Radiation [G-MINOR], ClinicalTrials.gov identifier: NCT02783950) and use of post-RP GC after completion of the trial’s enrollment window.

METHODS: The Michigan Urological Surgery Improvement Collaborative (MUSIC) data registry, in which G-MINOR was embedded, was queried for G-MINOR-eligible patients outside of the trial context (nonparticipating sites, chronology). A logistic regression model compared time with a patient’s receipt of post-RP GC testing at G-MINOR participating and nonparticipating sites, before and after the trial’s enrollment window.

RESULTS: A total of 7,144 patients (5,822 at G-MINOR sites, 1,322 non-G-MINOR sites) met study inclusion criteria between October 2015 and October 2020. Post-RCT, GC testing peaked among G-MINOR sites at 0.122 tests per eligible patient-quarter; no testing was observed among nonparticipating sites. Adjusting for patient characteristics, an interaction term between site-level RCT participation and pre-/postenrollment was statistically significant (hazard ratio, 21.9 [95% CI, 3.57 to 134]; P < .001).

CONCLUSION: Site-level participation in the G-MINOR RCT was significantly associated with a differential change in post-RCT GC use, where trial sites showed a greater post-RCT increase compared with nontrial sites. Whether this is caused by trial participation or represents a pre-existing intention to adopt an intervention remains unknown. Implementation and deimplementation considerations should be included in trial design.

PMID:40934443 | DOI:10.1200/OP-25-00475

Lupus. 2025 Sep 11:9612033251379313. doi: 10.1177/09612033251379313. Online ahead of print.

ABSTRACT

ObjectiveTo estimate the prevalence of Systemic Lupus Erythematosus (SLE) in Peru in 2017 and its association with altitude, environmental temperature, and physician density.MethodsThis ecological study was performed using population data from the 2017 Peruvian census. The number of SLE cases for each department was obtained from the National Health Registries using the ICD-10 code M32. Altitude, environmental temperature and physician density were obtained for each department from the National Institute of Statistics and Informatic (Instituto Nacional de Estadística e Informática) registries. The prevalence for each department was calculated adjusting for age and sex. Then a negative binomial regression was performed to estimate the prevalence ratio (PR) and evaluate factors associated with the prevalence of SLE.ResultsThe national prevalence of SLE was 40.2 per 100,000 people. Two age groups had the highest prevalence: 12-17 years and 30-59 years. Females exhibited a higher prevalence than males, particularly in the 30-59 age group (113.9 vs 16.1 per 100,000, respectively). An inverse relationship was observed between the age- and sex-adjusted prevalence in each department and altitude (PR 0.97; 95% CI: 0.94-0.99). On the other hand, there was a direct relationship with physician density (PR: 1.04; 95% CI: 1.01-1.07). No association was found between the adjusted prevalence and environmental temperature or latitude.ConclusionThe prevalence of SLE in Peru aligns with global estimates. The inverse relationship with altitude and the direct association with physician density suggest that environmental and healthcare access factors may influence disease distribution. Further research is needed to explore the underlying mechanisms driving these associations.

PMID:40934430 | DOI:10.1177/09612033251379313

Phytopathology. 2025 Aug;115(8V):1051-1056. doi: 10.1094/Phyto-67-1051.

ABSTRACT

Powdery mildew development on the slow-mildewing wheat cultivar Knox was compared to that on the susceptible cultivar Vermillion over a period of 4 yr in the field at Lafayette, Indiana. Cultivars received three levels of nitrogen fertilizer to determine if high levels of N affected the expression of slow-mildewing in Knox wheat. Knox’s resistance was evident under conditions favoring moderate to severe disease on Vermillion. Under low nitrogen fertility or unfavorable weather there was little difference in level of mildew on the two cultivars; under more favorable conditions disease severity increased greatly on Vermillion but increased little on Knox. The area under the disease progress curve had a lower error variance than statistics associated with the logit transformation of severity data and hence was a superior measurement of slow-mildewing. Slow-mildewing remains effective under the highest rates of nitrogen fertilization likely to be applied to wheat. In breeding for slow-mildewing, high rates of N provide optimal conditions for recognition of this resistance.

PMID:40934422 | DOI:10.1094/Phyto-67-1051

Phytopathology. 2025 Aug;115(8V):1377-1383. doi: 10.1094/Phyto-68-1377.

ABSTRACT

Significant increases in growth and yield of potato plants were achieved by treating seedpieces with suspensions of two Pseudomonas spp. at ∼10⁹ colony-forming units (cfu)/ml prior to planting. The pseudomonads were selected from over 100 strains that were isolated from the surface of potato tubers and also exhibited antibiosis against Erwinia carotovora var. carotovora in vitro. The isolates were identified as strains of Pseudomonas fluorescens and P. putida. These strains survived for at least 1 mo on treated seedpieces planted in loamy sand field soil at populations of ∼10⁹ cfu/0.785 cm². Also, they colonized developing potato roots and were the predominant bacteria in the rhizospheres up to 2 mo after planting. Bacterization of seedpieces planted in field soils in the greenhouse resulted in up to 100% increase in fresh weight of shoot and root systems in a 4-wk period. Statistically significant increases in yield ranged from 14 to 33% in five of nine field plots in California and Idaho. The pseudomonads had no effect on plant growth or tuber yield when seedpieces were planted in peat soil, or in soil that was relatively dry. Both Pseudomonas spp. were compatible with fungicides that were commonly used to treat seedpieces, except for manganese ethylenebisdithio-carbamate zinc salt (mancozeb). The mechanism by which these bacteria enhance plant growth and tuber yield may be associated with changes in the composition of rhizosphere bacterial flora.

PMID:40934416 | DOI:10.1094/Phyto-68-1377

J Sci Food Agric. 2025 Sep 11. doi: 10.1002/jsfa.70181. Online ahead of print.

ABSTRACT

BACKGROUND: Three-dimensional (3D) food printing enables precise customization and intricate shapes of food materials. The influence of printer control parameters on the printing performance of millet-based dough is still underexplored.

OBJECTIVE: This study investigates the effect of different printer control parameters on the millet dough printing performance, which is evaluated using height ratio, mass flow rate, and bending angle to enhance printing precision.

METHODOLOGY: The already optimized best printable formulation, of 40 g composite flour, 30 g shortening, 22 g jaggery, and 25 g water. The printer control parameters included nozzle diameter (ND) at 1.2, 1.6, and 2 mm; printing speed (PS) at 20, 25, and 30 mm/s; layer height (LH) at 35, 50, and 65% of ND; infill density (ID) at 40%, 60%, and 80%. Response surface methodology (RSM) and Artificial neural networks (ANN) were used for predictive modeling and comparing its statistical measures. Multi-objective optimization was performed through response surface methodology with desirability function (RSMDF) and Artificial neural networks with genetic algorithm (ANNGA). The best-performing printer control parameters were determined by validating the optimized conditions.

RESULTS: The ID and ND strongly influenced the height ratio. LH and ND significantly affect the mass flow rate. ID and LH were the significant parameters affecting the bending angle. While comparing the statistical measures for predictive modeling, the ANN exhibited lower root-mean-square error (RMSE) values (0.0013 for height ratio, 0.0336 for mass flow rate, and 0.202 for bending angle) and higher coefficient of determination (R²) values (0.97, 0.99, and 0.98, respectively) as compared to RSM. These results indicate that ANN has slightly better prediction capabilities than RSM. Based on the prediction capability performance of multi-objective optimization techniques, the ANNGA performs marginally better in predicting height ratio and mass flow rate with lower prediction errors (0.006 and 0.063, respectively) and higher accuracy (99.993 and 99.936, respectively) than the RSMDF model.

CONCLUSION: The optimal condition predicted by ANNGA was as follows: 2 mm of ND, 27.75 mm/s PS, 64.98% LH, and 67.80% ID were obtained for maximum height ratio (5.633), mass flow rate (5.633 g/min), and minimum bending angle (1°). © 2025 Society of Chemical Industry.

PMID:40934366 | DOI:10.1002/jsfa.70181