Nevin Manimala

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/C^CDC20 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

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

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

Acta Paediatr. 2025 Jul 7. doi: 10.1111/apa.70216. Online ahead of print.

ABSTRACT

AIM: Retinopathy of prematurity (ROP) risk factors have been investigated in population-based studies from most global regions. No such studies are available from Sub-Saharan Africa (SSA), where improved neonatal care is increasing the survival of preterm infants at risk of ROP.

METHODS: A population-based study was conducted in infants born in Cape Town, South Africa, from 1 May 2022 to 31 January 2023. The screening criteria were birth weight < 1250 g or gestational age < 32 weeks. The data were extracted from the Retinopathy of Prematurity South African register.

RESULTS: The study included 378 screened infants, 115 (30.4%) of whom developed ROP. In the multiple regression analyses, lower birth weight was an independent ROP risk factor, OR 1.3 95% CI 1.2-1.5, p < 0.001. Surgical necrotising enterocolitis (NEC) was the only other independent ROP risk factor, OR 5.8 95% CI 1.6-21.0, p = 0.007. Infants with birth weight < 1000 g were 39.4% (130/378) of those screened and more likely to develop ROP compared to larger infants, OR 2.4 95% CI 1.5-3.9, p < 0.001.

CONCLUSION: Birth weight remained a significant ROP risk factor, especially for those born weighing less than 1000 g. These infants represented a larger proportion of screened infants compared to previous Sub-Saharan African studies.

PMID:40622745 | DOI:10.1111/apa.70216

J Magn Reson Imaging. 2025 Jul 7. doi: 10.1002/jmri.70034. Online ahead of print.

ABSTRACT

BACKGROUND: Abbreviated breast MRI protocols are advocated for breast screening as they limit acquisition duration and increase resource availability. However, radiologists’ specificity may be slightly lowered when only such short protocols are evaluated. An adaptive approach, where a full protocol is performed only when abnormalities are detected by artificial intelligence (AI)-based models in the abbreviated protocol, might improve and speed up MRI screening. This study explores the potential benefits of such an approach.

PURPOSE: To assess the potential impact of adaptive breast MRI scanning based on AI detection of malignancies.

STUDY TYPE: Mathematical model.

FIELD STRENGTH/SEQUENCE: Breast cancer screening protocols.

ASSESSMENT: Theoretical upper and lower limits on expected protocol duration and recall rate were determined for the adaptive approach, and the influence of the AI model and radiologists’ performance metrics on these limits was assessed, under the assumption that any finding on the abbreviated protocol would, in an ideal follow-up scenario, prompt a second MRI with the full protocol.

STATISTICAL TESTS: Estimated most likely scenario.

RESULTS: Theoretical limits for the proposed adaptive AI-based MRI breast cancer screening showed that the recall rates of the abbreviated and full screening protocols always constrained the recall rate. These abbreviated and full protocols did not fully constrain the expected protocol duration, and an adaptive protocol’s expected duration could thus be shorter than the abbreviated protocol duration. Specificity, either from AI models or radiologists, has the largest effect on the theoretical limits. In the most likely scenario, the adaptive protocol achieved an expected protocol duration reduction of ~47%-60% compared with the full protocol.

DATA CONCLUSION: The proposed adaptive approach may offer a reduction in expected protocol duration compared with the use of the full protocol alone, and a lower recall rate relative to an abbreviated-only approach could be achieved. Optimal performance was observed when AI models emulated radiologists’ decision-making behavior, rather than focusing solely on near-perfect malignancy detection.

EVIDENCE LEVEL: Not applicable.

TECHNICAL EFFICACY: Stage 6.

PMID:40622738 | DOI:10.1002/jmri.70034

JAMA. 2025 Jul 7. doi: 10.1001/jama.2025.9855. Online ahead of print.

ABSTRACT

IMPORTANCE: Recent scientific and policy statements suggest that child health may be worsening in the US.

OBJECTIVE: To determine how US children’s health has been changing from 2007 to 2023 using multiple data collection methods and a comprehensive set of health indicators.

DESIGN, SETTING, AND PARTICIPANTS: Repeated, cross-sectional analyses using mortality statistics from the US and 18 comparator high-income nations from the Organisation for Economic Co-operation and Development (OECD18), 5 nationally representative surveys, and electronic health records from 10 pediatric health systems (PEDSnet). The populations included individuals younger than 20 years old. Unweighted denominator sample size ranges were 1623 to 95 677 across the surveys, 1 026 926 to 2 114 638 for PEDSnet, 81.9 million to 83.2 million in the US, and 118.4 million to 121.1 million in the OECD18 for mortality statistics.

EXPOSURE: Calendar time.

MAIN OUTCOMES AND MEASURES: Rate ratios (RRs) and annual incidence for mortality and prevalence for chronic physical, developmental, and mental health conditions, functional status, and symptoms.

RESULTS: From 2007 to 2022, infants (<1 year old) were 1.78 (95% CI, 1.78-1.79) and 1- to 19-year-old individuals were 1.80 (95% CI, 1.80-1.80) times more likely to die in the US than in the OECD18. The 2 causes of death with the largest net difference between the US and OECD18 were prematurity (RR, 2.22 [95% CI, 2.20-2.24]) and sudden unexpected infant death (RR, 2.39 [95% CI, 2.35-2.43]) for infants 12 months or younger, and firearm-related incidents (RR, 15.34 [95% CI, 14.89-15.80]) and motor vehicle crashes (RR, 2.45 [95% CI, 2.42-2.48]) for 1- to 19-year-old individuals. From 2011 to 2023, the prevalence of 3- to 17-year-old individuals with a chronic condition rose from 39.9% to 45.7% (RR, 1.15 [95% CI, 1.14-1.15]) within PEDSnet, and from 25.8% to 31.0% (RR, 1.20 [95% CI, 1.20-1.20]) within the general population. Rates of obesity, early onset of menstruation, trouble sleeping, limitations in activity, physical symptoms, depressive symptoms, and loneliness all increased during the study period.

CONCLUSIONS AND RELEVANCE: The health of US children has worsened across a wide range of health indicator domains over the past 17 years. The broad scope of this deterioration highlights the need to identify and address the root causes of this fundamental decline in the nation’s health.

PMID:40622733 | DOI:10.1001/jama.2025.9855

J Obstet Gynaecol. 2025 Dec;45(1):2528093. doi: 10.1080/01443615.2025.2528093. Epub 2025 Jul 7.

ABSTRACT

BACKGROUND: This study aimed to analyse the clinical characteristics of mifepristone-associated congenital and foetal cardiac adverse events using data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS).

METHODS: A retrospective pharmacovigilance analysis was conducted using FAERS data from Q1 2016 to Q4 2022. Disproportionality analysis was performed using the Bayesian Information Component (IC) to detect potential associations between mifepristone and congenital or foetal cardiac adverse events.

RESULTS: A total of 1,130 reports involving mifepristone were identified, of which 18 (1.59%) were related to congenital or foetal cardiac events. Most reports originated from the United States. The most frequently reported events were foetal arrhythmia and foetal heart rate disorder. Notably, foetal arrhythmia showed the strongest signal (IC = 3.13, CI₀₂₅ = 1.37). No disproportional signals were detected for structural cardiac malformations. A partial assessment of the Bradford Hill criteria suggested a possible association with functional cardiac anomalies.

CONCLUSION: This study did not identify an association between mifepristone exposure and structural congenital heart defects. However, a positive signal for transient foetal heart rhythm abnormalities was observed. Clinicians should remain vigilant for foetal heart rate irregularities following maternal mifepristone use and consider enhanced cardiac monitoring during labour and delivery to enable early detection and management.

PMID:40622732 | DOI:10.1080/01443615.2025.2528093

JAMA Netw Open. 2025 Jul 1;8(7):e2519106. doi: 10.1001/jamanetworkopen.2025.19106.

NO ABSTRACT

PMID:40622718 | DOI:10.1001/jamanetworkopen.2025.19106

JAMA Netw Open. 2025 Jul 1;8(7):e2518895. doi: 10.1001/jamanetworkopen.2025.18895.

ABSTRACT

IMPORTANCE: Uptake of human papillomavirus (HPV) vaccination varies by characteristics, exposing some children to higher HPV cancer risks than others.

OBJECTIVE: To examine whether the effectiveness of a multilevel intervention on HPV vaccination differed by race and ethnicity, rurality, and Area Deprivation Index (ADI) in children ages 11 to 12 years.

DESIGN, SETTING, AND PARTICIPANTS: A stepped-wedge cluster randomized trial was conducted from April 2018 to August 2022 among children at 6 Mayo Clinic primary care practices in Minnesota to improve HPV vaccination. This secondary analysis was performed from March to June 2024.

INTERVENTION: A multilevel intervention that included parent reminder/recall letters, which alerted parents of children due or past due for vaccination, and health care professional audit/feedback reports, which alerted health care professionals of their own vaccination rates.

MAIN OUTCOME AND MEASURE: Vaccine initiation (first dose of the 2-dose HPV vaccine) and vaccine completion (second dose) were the primary study outcomes. In this secondary analysis, the effect of the intervention on HPV vaccine initiation and completion by race and ethnicity, rurality, and ADI quartiles (Qs) was assessed.

RESULTS: A total of 6232 children aged 11 to 12 years (3285 [52.7%] male; 3481 [55.9%] aged 11 years and 2751 [44.1%] aged 12 years) were included in the analysis. Of the study participants, 304 (4.9%) were Asian, 561 (9.0%) Black, 146 (2.3%) Hispanic, 4501 (72.2%) White, and 720 (11.6%) other, including American Indian or Alaskan Native, Native Hawaiian or Pacific Islander, Other Pacific Islander, Samoan, unable to provide, unknown, chose not to disclose, or other unspecified. A total of 5434 participants (87.2%) were urban residents, and 2794 (44.8%) resided in ADI Q2 areas. With usual care, HPV vaccine initiation and completion rates were significantly lower with each increasing ADI quartile (initiation: Cochran-Armitage test for trend [SE], -0.02 [0.01]; P < .001; completion: Cochran-Armitage test for trend [SE], -0.05 [0.01]; P < .001) but did not differ by children’s race and ethnicity or rurality. With the intervention, vaccine initiation increased significantly for most children (range of rates, 9.2% [95% CI, 5.2%-13.3%] to 24.0% [95% CI, 7.5%-40.6%]) except those with Black race, in rural settings, and in ADI Q4 (highest area deprivation); vaccine completion increased significantly for most children (range of rates, 19.4% [95% CI, 5.5%-33.3%] to 31.2% [95% CI, 12.1%-50.3%]) except for those in ADI Q4.

CONCLUSIONS AND RELEVANCE: In this secondary analysis of a cluster randomized trial, a multilevel intervention was associated with increased HPV vaccination for most children but had limited effect for those residing in areas of highest deprivation. Future research should explore other intervention strategies that would effectively promote HPV vaccination among families in socioeconomically disadvantaged areas to reduce HPV vaccination disparities.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03501992.

PMID:40622715 | DOI:10.1001/jamanetworkopen.2025.18895

JAMA Netw Open. 2025 Jul 1;8(7):e2519236. doi: 10.1001/jamanetworkopen.2025.19236.

ABSTRACT

IMPORTANCE: Etiologic heterogeneity in breast carcinogenesis needs to be well characterized for targeted prevention. Associations between menopausal hormonal therapy (MHT) and oral contraceptive (OC) use and breast cancer intrinsic-like subtypes are not well understood.

OBJECTIVE: To examine whether exogenous hormone use is differentially associated with breast cancer subtypes and to evaluate heterogeneity by intrinsic-like subtypes.

DESIGN, SETTING, AND PARTICIPANTS: This study pooled data from 31 nested and population-based case-control studies involved in the Breast Cancer Association Consortium. The study population included individuals with breast cancer and control participants from 13 case-control studies nested in prospective cohorts (recruited between 1982 and 2011) and 18 population-based case-control studies (recruited between 1990 and 2013). Data analysis was performed in June 2024.

EXPOSURE: MHT use (estrogen-progestin therapy [EPT] or estrogen-only therapy [ET]) in postmenopausal women and OC use in premenopausal women (never, past use, or current use).

MAIN OUTCOMES AND MEASURES: Breast cancer intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-ERBB2 [formerly HER2 or HER2/neu]-like, ERBB2 enriched-like, or triple-negative) were determined by immunohistochemistry of tumor sections. Polytomous logistic regression was performed to estimate the association between exogenous hormones and risk of breast cancer by intrinsic-like subtypes. Analyses by subtypes were stratified by body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]; healthy weight, 18.5-<25; overweight, 25-<30; or obesity, ≥30).

RESULTS: This study included 42 269 individuals with breast cancer (11 901 [28.2%] premenopausal and 30 368 [71.8%] postmenopausal; 23 353 [55.2%] had a known intrinsic-like subtype) and 71 072 control participants. The mean (SD) age of all participants was 57.9 (10.9) years. In postmenopausal women, associations between current MHT use (EPT or ET) and breast cancer differed by subtype. Current EPT users with healthy weight were more likely to be diagnosed with luminal A-like (odds ratio [OR], 2.51 [95% CI, 2.26-2.80]) or luminal B-ERBB2-like (OR, 1.95 [95% CI, 1.61-2.37]) subtypes. These associations were attenuated but remained for individuals with overweight (OR, 1.40 [95% CI, 1.02-1.92]) or obesity (OR, 1.68 [95% CI, 1.01-2.78]). EPT use increased the odds of being diagnosed with luminal B-like tumors solely in women with healthy weight (OR, 1.47 [95% CI, 1.17-1.86]). Current ET use was positively associated with luminal A-like disease in women with healthy weight only (OR, 1.16 [95% CI, 1.01-1.32]), showing inverse associations with higher BMI (obesity: OR, 0.65 [95% CI, 0.50-0.85]). In premenopausal women, recent OC use was associated with luminal B-ERBB2-like (OR, 1.50 [95% CI, 1.09-2.08]), ERBB2 enriched-like (OR, 2.33 [95% CI, 1.55-3.51]), and triple-negative (OR, 1.75 [95% CI, 1.33-2.29]; P < .04 for heterogeneity) tumors.

CONCLUSIONS AND RELEVANCE: In this study, clear differences were observed in associations between current EPT use and luminal-like breast cancer subtypes and other subtypes. EPT users with healthy weight were more likely to be diagnosed with luminal-like breast cancer compared with nonusers. Subtype heterogeneity was less apparent in associations of OC and ET use. Future studies on contemporary formulations, patterns of use, and routes of administration of exogenous hormone usage are warranted.

PMID:40622713 | DOI:10.1001/jamanetworkopen.2025.19236