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Nevin Manimala Statistics

Preferred Sources For Suicide Prevention And Crisis Services Among Segments Of The US Adult Population

Health Aff (Millwood). 2025 Jul;44(7):869-877. doi: 10.1377/hlthaff.2024.01163.

ABSTRACT

Recent policy initiatives such as the 988 Suicide and Crisis Lifeline aim to increase the use of crisis services. We conducted a probability survey of 5,006 US adults in 2023 and used latent class analysis to identify population segments that vary in crisis help-seeking preferences. We identified five segments: “Seek Help Nowhere,” “Definitely Not 988, Yes Friends And Family-Distressed,” “Seek Help Everywhere,” “Seek Help Most Places, But Not Religious Network,” and “Relatively Indifferent-Not Distressed.” Having serious prior-thirty-day psychological distress was positively associated with membership in the Definitely Not 988 segment and was negatively associated with the Relatively Indifferent segment. Respondents who were not aware of the 988 Lifeline were more likely to be in the Seek Help Nowhere and Definitely Not 988 segments. Political party affiliation was associated with membership in all segments. Communication campaigns that encourage the use of crisis services and help seeking may consider tailoring messages for these different audience segments.

PMID:40623251 | DOI:10.1377/hlthaff.2024.01163

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Nevin Manimala Statistics

Maternal Contact With Child Protective Services Associated With Less Postpartum Care In Wisconsin, 2010-19

Health Aff (Millwood). 2025 Jul;44(7):812-820. doi: 10.1377/hlthaff.2024.01250.

ABSTRACT

Maternal involvement with Child Protective Services (CPS) is common around childbirth, particularly for women with economic and health challenges. Federal and state policies aim to improve health care access and use for CPS-involved families, but evidence is needed to understand how CPS contact relates to health care for new mothers. We used linked population-based administrative data, representing all Medicaid-covered births in Wisconsin during the period 2010-19, to produce estimates of the associations of CPS interventions with maternal receipt of postpartum health care. After we adjusted for factors influencing risk for CPS involvement, women whose births were brought to the attention of CPS were around 13 percentage points less likely to receive postpartum care within twelve weeks after delivery, and this relation was present across different levels of CPS intervention and key population subgroups. These findings highlight the need to consider how child welfare and health care policies and practices can support connections with health care for new mothers and their infants.

PMID:40623250 | DOI:10.1377/hlthaff.2024.01250

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Nevin Manimala Statistics

Convergent validity of a person-dependent definition of a low back pain flare

Pain. 2025 Jul 2. doi: 10.1097/j.pain.0000000000003703. Online ahead of print.

ABSTRACT

Exacerbations of existing low back pain (LBP) or new LBP episodes are colloquially referred to as “flares.” Although the experience of flares is common to many people with LBP, few validated measures enable people to self-report if they are experiencing a flare. This study examined the convergent validity of a person-dependent definition of flares (“a worsening of your low back pain that lasts from hours to weeks”) as compared with (1) LBP intensity, (2) LBP-related pain interference, and (3) analgesic use, in a large, prospective research study of Veterans with LBP. Veterans seeking care for LBP (n = 465) were followed prospectively for up to 1 year. Participants completed up to 36 scheduled surveys and additional patient-initiated surveys (triggered by the onset of new flares) over follow-up. Each survey inquired about current flare status, pain intensity measured on a 0 to 10 numeric rating scale (NRS), LBP-related pain interference, and analgesic use. Linear mixed-effects models estimated the association between current flare status and pain intensity, with and without adjustment for potential confounding factors; secondary analyses examined associations with pain interference and analgesic use. In longitudinal analyses of 11,817 surveys, flare status was significantly associated with a 2.8-NRS point greater pain intensity (P < 0.0001), with and without adjustment for other factors. Statistically significant associations were found between flare status and LBP-related pain interference and analgesic use. New flare periods were associated with impacts on coping, functional limitations, and mood/emotions. These findings support the convergent validity of a person-dependent flare definition.

PMID:40623243 | DOI:10.1097/j.pain.0000000000003703

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Nevin Manimala Statistics

Mental Healthcare Utilization Among US Healthcare Workers During the COVID-19 Pandemic: Evidence from the 2020-2021 National Health Interview Survey

J Healthc Manag. 2025 Jul-Aug 01;70(4):269-287. doi: 10.1097/JHM-D-24-00002. Epub 2025 Jul 4.

ABSTRACT

GOAL: Despite the well-documented mental health impact of the COVID-19 pandemic on healthcare workers (HCWs), the literature holds limited research on their use of mental healthcare. This study assessed the prevalence and correlates of mental healthcare utilization among US HCWs, which can be used as baseline measurements to guide the evaluation of interventions and guide the development of those interventions.

METHODS: We used the 2020-2021 US National Health Interview Survey and restricted our analytic sample to respondents who worked in healthcare settings and reported daily, weekly, or monthly mental health symptoms (unweighted n = 1,412). Our outcome variables were: (1) receiving anxiolytic or antidepressant prescriptions, (2) receiving psychotherapy, and (3) not utilizing either treatment. We conducted multivariable logistic regression models to identify factors associated with each outcome. Based on Andersen’s behavioral model, we included predisposing factors (e.g., gender, healthcare role), enabling factors (e.g., social support, telehealth use), need factors (e.g., frequency of depressive or anxiety symptoms), and year.

PRINCIPAL FINDINGS: We found that 32.1% of HCWs received prescriptions, 22.3% received psychotherapy, and 59.0% were not currently using mental healthcare. Overall, some predisposing, enabling, and need factors were associated with all three outcome variables for mental healthcare utilization among HCWs. For instance, when examining the odds of not reporting current use of mental healthcare services, odds were higher among HCWs who were non-Hispanic Black/African American (odds ratio [OR] = 1.90, 95% confidence interval [CI] [1.16-3.12]), or Hispanic (OR = 2.68, 95% CI [1.63-4.39]) compared to those who were non-Hispanic White. Higher odds were also observed among HCWs who reported rarely or never received adequate social support (OR = 1.94, 95% CI [1.04-3.62]) as compared to those who reported always receiving adequate social support, those who were male (OR = 1.47, 95% CI [1.00-2.16]), and those without a usual source of care (OR = 2.08, 95% CI [1.12-3.88]). Inversely, lower odds were observed among HCWs who reported themselves as not heterosexual (OR = 0.58, 95% CI [0.34-0.99]) and those who had used telehealth appointments (OR = 0.32, 95% CI [0.24-0.44]). Lower odds were also observed among HCWs with more frequent anxiety symptoms: monthly (OR = 0.42, 95% CI [0.20-0.88]), weekly (OR = 0.36, 95% CI [0.18-0.73]), or daily frequency (OR = 0.27, 95% CI [0.14-0.55]), compared to never or few times a year. A similar pattern was observed among HCWs with more frequent depressive symptoms: monthly (OR = 0.33, 95% CI [0.22-0.49]), weekly (OR = 0.15, 95% CI [0.09-0.24]), or daily (OR = 0.11, 95% CI [0.05-0.21]), compared to never or few times a year. No differences in any outcome variable by type of HCW (diagnosing vs. nondiagnosing roles) were observed.

PRACTICAL APPLICATIONS: Our findings reveal a potential pattern of underutilization of mental health services among HCWs with mental health symptoms. To inform intervention design and delivery, additional research is needed to identify barriers to mental healthcare and preferences for their modalities that are specific to HCWs.

PMID:40623224 | DOI:10.1097/JHM-D-24-00002

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Nevin Manimala Statistics

ChatGPT performance in answering medical residency questions in nephrology: a pilot study in Brazil

J Bras Nefrol. 2025 Oct-Dec;47(4):e20240254. doi: 10.1590/2175-8239-JBN-2024-0254en.

ABSTRACT

OBJECTIVE: This study evaluated the performance of ChatGPT 4 and 3.5 versions in answering nephrology questions from medical residency exams in Brazil.

METHODS: A total of 411 multiple-choice questions, with and without images, were analyzed, organized into four main themes: chronic kidney disease (CKD), hydroelectrolytic and acid-base disorders (HABD), tubulointerstitial diseases (TID), and glomerular diseases (GD). Questions with images were answered only by ChatGPT-4. Statistical analysis was performed using the chi-square test.

RESULTS: ChatGPT-4 achieved an overall accuracy of 79.80%, while ChatGPT-3.5 achieved 56.29%, with a statistically significant difference (p < 0.001). In the main themes, ChatGPT-4 performed better in HABD (79.11% vs. 55.17%), TID (88.23% vs. 52.23%), CKD (75.51% vs. 61.95%), and DG (79.31% vs. 55.29%), all with p < 0.001. ChatGPT-4 presented an accuracy of 81.49% in questions without images and 54.54% in questions with images, with an accuracy of 60% for electrocardiogram analysis. This study is limited by the small number of image-based questions and the use of outdated examination items, reducing its ability to assess visual diagnostic skills and current clinical relevance. Furthermore, addressing only 4 areas of Nephrology may not fully represent the breadth of nephrology practice.

CONCLUSION: ChatGPT-3.5 was found to have limitations in nephrology reasoning compared to ChatGPT-4, evidencing gaps in knowledge. The study suggests that further exploration is needed in other nephrology themes to improve the use of these AI tools.

PMID:40623208 | DOI:10.1590/2175-8239-JBN-2024-0254en

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Nevin Manimala Statistics

Genome report: Genome sequence of the hibiscus mealybug, Nipaecoccus viridis (Newstead), an invasive pest of citrus

G3 (Bethesda). 2025 Jul 7:jkaf154. doi: 10.1093/g3journal/jkaf154. Online ahead of print.

ABSTRACT

Mealybugs are frequently known for being pest insects to both ornamental and large-scale agricultural crops. Yet despite their agricultural importance, the genomic resources for this group remain quite limited. One such species is the hibiscus mealybug, Nipaecoccus viridis (Newstead) (Hemiptera: Coccomorpha: Pseudococcidae). This invasive mealybug species has recently expanded throughout Florida and has spread across the state. Genomic resources would provide a new means to better understand the invasive nature of this insect, and thus, we present the de novo genome assembly for Nipaecoccus viridis. Our genome assembly is 289 Mb, in which 91.2% of this sequence assembled into 5 chromosomal scaffolds. We report 15,370 genes to be present within our genome. We found that repetitive elements in the genome accounted for 32.40% of the sequence. These statistics follow similar trends to other previously sequenced pseudococcid species.

PMID:40623205 | DOI:10.1093/g3journal/jkaf154

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Nevin Manimala Statistics

Confinement of ions within graphene oxide membranes enables neuromorphic artificial gustation

Proc Natl Acad Sci U S A. 2025 Jul 15;122(28):e2413060122. doi: 10.1073/pnas.2413060122. Epub 2025 Jul 7.

ABSTRACT

Introducing neuromorphic computing paradigms into taste-sensing technology will bring unprecedented opportunities for developing new hardware architectures with perceptual intelligence. Constructing the biomimetic gustatory system, however, remains a challenge due to the scarcity of suitable components operating under wet conditions. Here, we report that ion confinement within the layered graphene oxide membranes can be used to develop a memristive device capable of implementing both synaptic function and chemical sensing. The continuum model and ion dynamics characterizations demonstrate that interfacial adsorption-desorption slows down ion transport and leads to memristive behavior. Based on this nanofluidic device, we built an artificial gustatory system in the physiological environment, which can efficiently classify different flavors according to the reservoir computing algorithm. Our results suggest a paradigm for in-sensor computing in liquid.

PMID:40623193 | DOI:10.1073/pnas.2413060122

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Nevin Manimala Statistics

DNA2 protein destruction dictates DNA hyperexcision, cGAS-STING activation, and innate immune response in CDK12-deregulated cancers

Proc Natl Acad Sci U S A. 2025 Jul 15;122(28):e2413732122. doi: 10.1073/pnas.2413732122. Epub 2025 Jul 7.

ABSTRACT

CDK12 primarily functions as a transcription regulatory cyclin-dependent kinase (CDK) that controls mRNA elongation, splicing, and polyadenylation. The CDK12 gene is implicated in human cancers since it is frequently mutated and/or deleted in prostate and ovarian cancer but paradoxically amplified in breast cancer. Here, we demonstrate that CDK12 promotes serine-933 phosphorylation of DNA2, a nuclease/helicase critical for replication fork stress regulation, and the phosphorylation subsequently facilitates DNA2 polyubiquitination and degradation mediated by the APC/CCDC20 E3 ubiquitin ligase. CDK12 inactivation induces but amplification suppresses genome-wide expression of interferon response and antigen processing and presentation machinery genes in ovarian and breast cancer cells, respectively. Besides causing aberrant DNA2 stabilization, replication stress, genomic instability, and cytosolic double-stranded DNA (dsDNA) accumulation, CDK12 loss also triggers cGAS-STING activation and innate immune response, which can be reversed by forced expression of replication protein A (RPA) subunits or DNA2 depletion. Our findings identify DNA2 as a phosphorylation substrate of CDK12, connecting CDK12 to cell cycle regulation. These data also reveal DNA2 protein destruction as a critical mechanism that dictates genomic instability, cGAS-STING signaling activation, and innate immune response in CDK12-deregulated cancers.

PMID:40623188 | DOI:10.1073/pnas.2413732122

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Nevin Manimala Statistics

Wavelet-based coarse graining for percolation criticality from a single system size

Chaos. 2025 Jul 1;35(7):073112. doi: 10.1063/5.0276783.

ABSTRACT

Scaling analysis is a fundamental tool for estimating critical points and exponents of phase transitions in complex systems, typically relying on numerical simulations at multiple system sizes or scales. However, real-world systems often exist at a single system size, making such analysis challenging. Here, we propose a wavelet-based method to extract scaling behavior from a single system size. Considering two-dimensional random and explosive site percolation, we perform wavelet-based coarse graining and compute high-frequency coefficients across multiple effective system sizes, each of which corresponds to the size of the transformed system at a coarser resolution. In these coarser systems, wavelet energy is defined as the squared coefficients that capture cluster boundaries. We finally demonstrate that average wavelet energies follow a scaling law, enabling accurate estimation of the critical points and exponents, which are consistent with those obtained from traditional susceptibility-based scaling analysis. This suggests that average wavelet energy serves as a susceptibility-like observable in percolation systems. Our findings highlight that wavelet-based analysis provides a new perspective on percolation criticality, allowing the identification of scaling properties from a single system size. Furthermore, this approach is potentially applicable to real-world systems such as brain activity patterns, bacterial colonies, or social networks, where collecting data at multiple sizes is impractical or costly.

PMID:40623173 | DOI:10.1063/5.0276783

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Nevin Manimala Statistics

Rainfall forecast in Brazil using machine learning

Chaos. 2025 Jul 1;35(7):073116. doi: 10.1063/5.0259222.

ABSTRACT

Rainfall forecasting through machine learning can play a crucial role in several areas, such as agriculture, energy, infrastructure, and public safety. The machine learning models have the ability to anticipate climate patterns and extreme events, allowing plantation planning, water resource management, and forecasting energy demands, as well as adopting preventive measures against natural disasters. In this work, we explore three machine learning models (random forest, long short-term memory, and bidirectional long short-term memory) to predict the amount of precipitation in five Brazilian regions (South, Southeast, Central-West, Northeast, and North). We use three-variable reanalysis climate data: local temperature, Atlantic Ocean temperature, and total precipitation. The models are trained by means of the local and Atlantic Ocean temperatures as input features and the total precipitation as a label. Our results indicate that all models perform satisfactorily in their predictions. We verify that the random forest exhibits average absolute errors less than the errors related to the recurrent neural network models. Our results show the effectiveness of machine learning models in predicting rainfall patterns.

PMID:40623172 | DOI:10.1063/5.0259222