Nevin Manimala

Reprod Health. 2025 May 24;22(1):91. doi: 10.1186/s12978-025-02036-8.

ABSTRACT

BACKGROUND: In December 2020, Argentina passed Law 27.610, legalizing elective abortion up to 14 + 6 weeks and beyond in cases of rape or health risks. This study aims to analyze the sociodemographic characteristics of users who opted or were referred for manual vacuum aspiration (MVA) services at an a ambulatory medical center in Argentina before and after the legal reform, and to assess the safety and effectiveness of outpatient MVA procedures for pregnancies up to 14 + 6 weeks.

METHODS: Observational study using clinical data from patients up to 14 + 6 weeks gestation (n = 1,861) who sought or were referred for outpatient MVA abortion at a public healthcare facility in Rosario, Argentina (2017-2023). We analyze changes in users’ sociodemographic characteristics before and after the legal reform and assess the safety and effectiveness of ambulatory MVA abortion by gestational age (< 13 weeks vs. 13-14 weeks). A logistic regression tested associations between sociodemographic, procedural, and reproductive factors, and receiving MVA after 12 weeks.

RESULTS: Of the 1,861 MVA abortions, 85% (n = 1,590) were provided before 13 weeks’ gestation, and 15% (n = 271) occurred between 13-14 weeks. After the legal reform, more users accessed outpatient MVA services beyond 12 weeks (7% vs. 22%; p < 0.05: before and after the legal change, respectively), including individuals with lower education levels (46% vs. 54%; p < 0.05:), informal employment (34% vs. 47%; p < 0.05), without healthcare insurance (72% vs. 90%; p < 0.05), and nulliparity (18% vs. 30%; p < 0.05). The success rate of ambulatory MVA abortion was 99.9%, with 0.4% (n = 7) adverse events; no statistically significant differences by gestational age groups (< 13 weeks vs. 13-14 weeks). The legal reform was positively associated with accessing MVA abortion after 12 weeks.

CONCLUSIONS: The legal reform improved access to safe ambulatory MVA abortion services up to 14 + 6 weeks’ gestation, particularly for socially disadvantaged users. MVA abortion, both before 13 weeks and at 13-14 weeks, demonstrated a high success rate (99.9%) with minimal adverse events.

PMID:40410790 | DOI:10.1186/s12978-025-02036-8

BMC Endocr Disord. 2025 May 23;25(1):135. doi: 10.1186/s12902-024-01821-z.

ABSTRACT

BACKGROUND: Hyperthyroidism poses challenges, and common treatments like Radioactive Iodine (RAI) have limitations, prompting exploration of adjunctive approaches. This meta-analysis evaluates the combined impact of RAI and Lithium carbonate (LiCO3) on cure rates and thyroid hormone levels.

METHODS: We systematically searched Cochrane Library, PubMed, Scopus, and Web of Science for studies comparing LiCO3 combined with RAI to RAI alone. Pooled results analyzed cure rates and Free T3/T4 changes. A subgroup analysis was conducted based on LiCO3 dosage and treatment duration, while meta-regression was performed to assess covariates such as the patient’s age, RAI dose, and lithium dose. The risk of bias was evaluated using ROB2, ROBINS-1, and NOS, while the statistical analyses were conducted using Revman software 5.4.1.

RESULTS: Analysis of 14 studies involving 2047 patients revealed a significantly increased cure rate with RAI and LiCO3 compared to RAI alone (RR 1.12, 95% CI [1.03,1.23], p = 0.01). Subgroup analysis revealed higher cure rates with short-duration intensified doses of LiCO3, while short-duration diluted doses reduced cure rates. No significant differences were noted in euthyroid and hypothyroid states. Changes in free T3 showed no significant difference between the arms at 7 days and the most common time point. A significant decrease in free T4 favored RAI with LiCO3 at 7 days (MD -4.90, 95% CI [-7.91, -1.89], p = 0.001), and the most common time point (MD -3.83, 95% CI [-7.45, -0.20], p = 0.04). Meta-regression analysis indicated better cure rates in older patients (p < 0.001) and lower total lithium doses (p < 0.001).

CONCLUSION: Treatment with RAI combined with LiCO3 significantly enhanced cure rates, particularly when using short-duration intensified doses of LiCO3. Additionally, LiCO3 effectively reduced T4 levels without altering T3 levels. Future research is needed to validate our findings.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:40410789 | DOI:10.1186/s12902-024-01821-z

Cancer Epidemiol. 2025 May 22;97:102838. doi: 10.1016/j.canep.2025.102838. Online ahead of print.

ABSTRACT

BACKGROUND: Puerto Rico, a United States (U.S.) territory with 99 % of its inhabitants identifying as Hispanic/Latino, has one of the most rapid aging populations in the world. We quantified the incidence and mortality of cancer among 85 + year-old residents of Puerto Rico, and compared these rates with Hispanic/Latino populations in the U.S.

METHODS: We accessed cancer incidence and mortality rates (2005-2021) from the United States Cancer Statistics and North American Association of Centralized Cancer Registries datafiles. Cancers were restricted to males and females of age 85 + . In addition to analyzing Puerto Rico data, we also analyzed incidence and mortality rates in nine U.S. states with large Hispanic/Latino populations. We calculated annual percentage changes (APCs), Mortality-Incidence Ratios (MIRs), and Standardized Incidence and Mortality Ratios (SIRs, SMRs) for all cancers and specific sites.

RESULTS: In 2021, Puerto Rico’s population aged 85 + was 108,041. Since 2001, cancer incidence and mortality rates for both males and females aged 85 + in Puerto Rico declined. Puerto Rico’s decline in male cancer incidence (APC = -3.1 %) and mortality (APC = -3.3 %) exceeded the respective decline in incidence (APC = -0.08 %) and mortality (APC = -0.9 %) in Hispanic/Latino male populations in the U.S. However, in 2021, the MIR in 85 + females in Puerto Rico (0.73) and males (0.94) were higher than most comparable state MIRs. While stable in most other U.S. Hispanic/Latino populations, between 2005 and 2021 in Puerto Rico, the proportion of staged cancers diagnosed at advanced stages increased 12 %.

CONCLUSIONS: While significant progress has been made in reducing cancer incidence and mortality among Puerto Rico’s oldest residents, challenges persist. Policies improving healthcare access could help reduce the burden of cancer incidence and mortality among Puerto Rico’s aging population. Data revealing disaggregated ethnicity and nationality beyond Hispanic/Latino could further inform targeted efforts to advance cancer equity across the U.S.

PMID:40408793 | DOI:10.1016/j.canep.2025.102838

J Chromatogr A. 2025 May 15;1756:466059. doi: 10.1016/j.chroma.2025.466059. Online ahead of print.

ABSTRACT

In this work, a reversed-phase high-performance liquid chromatographic method was developed for the characterization of dynamic changes in phenolic compounds during roasting of coffee beans. To optimize the gradient profile and tandem mass spectrometric detection conditions in multiple reaction monitoring mode, a new approach was developed, combining three statistical criteria, i.e., interquartile range of gradient retention times, probability of mass spectrometric time-window overlapping at 95 % statistical significance level, and the gradient time range. The summary criterion “gradient score” was evaluated at different weights of all statistical criteria and optimal conditions were proposed using a heatmap diagram approach. The results of the quantitative analysis of phenolic compounds using the developed gradient method, combined with the isocratic determination of chlorogenic acids and gas chromatographic analysis of volatile phenolic compounds, were used for comprehensive evaluation of the phenolic profile in coffee during the roasting process. Thus, the quantitative analysis revealed a progressive decline in the concentration of chlorogenic acids and hydroxycinnamic acids as roasting progresses, attributed to thermal degradation and chemical transformations. In contrast, the levels of hydroxybenzoic acids, phenolic aldehydes, alkylphenols, and volatile phenols consistently increase. These findings highlight the complex interplay of degradation and synthesis reactions during coffee roasting, contributing to the formation of new phenolic compounds with potential impacts on the coffee brew’s flavor, aroma, and antioxidant properties.

PMID:40408785 | DOI:10.1016/j.chroma.2025.466059

Physiother Theory Pract. 2025 May 23:1-13. doi: 10.1080/09593985.2025.2508364. Online ahead of print.

ABSTRACT

BACKGROUND: Grip strength and hand function are critical for upper extremity performance. Although scapular stability is essential for upper extremity functioning, the effects of scapular taping on hand function and grip strength remain unknown.

PURPOSE: Investigating the immediate effects of scapular taping techniques on grip strength and hand function in healthy individuals.

METHODS: Fifty-nine participants (22.15 ± 1.35 years) received Kinesio Taping (KT), Rigid Taping (RT), and Sham Taping in random order with a three-day washout. Grip strength (gross grip, 2-point, 3-point, lateral pinch) and, hand function (Purdue Pegboard Test (PPT), Moberg Pickup Test (MPT), and Minnesota Hand Dexterity Test (MHDT) were conducted immediately after interventions.

RESULTS: RT statistically significantly increased 2-point, and 3-point pinch strength compared to the sham taping (p = .006, d = 0.19, p = .031, d = 0.30). No statistically significant differences were observed in remaining outcomes (p > .05). There were no statistically significant differences between KT-RT or KT-Sham in any of the outcome measures (p > .05, d < 0.2). A moderate negative correlation was detected between 3-point and lateral pinch strength and the PPT Both Hands sub-score (r=-0.372, p = .044; r=-0.351, p = .006). A weak negative correlation was found between gross grip strength and the MPT Eyes Open sub-score (r=-0.294, p = .024).

CONCLUSION: This study demonstrates the effect of scapular taping on enhancing fine grip strength and offers a potential approach to improving distal performance of the upper extremity. Further research involving diverse populations, and long-term follow-up is needed to validate these findings and determine their potential implications for clinical practice.

PMID:40408781 | DOI:10.1080/09593985.2025.2508364

J Med Internet Res. 2025 May 23;27:e72229. doi: 10.2196/72229.

ABSTRACT

BACKGROUND: Differentiating bipolar disorder (BD) from unipolar depression (UD) is essential, as these conditions differ greatly in their progression and treatment approaches. Digital phenotyping, which involves using data from smartphones or other digital devices to assess mental health, has emerged as a promising tool for distinguishing between these two disorders.

OBJECTIVE: This systematic review aimed to achieve two goals: (1) to summarize the existing literature on the use of digital phenotyping to directly distinguish between UD and BD and (2) to review studies that use digital phenotyping to classify UD, BD, and healthy control (HC) individuals. Furthermore, the review sought to identify gaps in the current research and propose directions for future studies.

METHODS: We systematically searched the Scopus, IEEE Xplore, PubMed, Embase, Web of Science, and PsycINFO databases up to March 20, 2025. Studies were included if they used portable or wearable digital tools to directly distinguish between UD and BD, or to classify UD, BD, and HC. Original studies published in English, including both journal and conference papers, were included, while reviews, narrative reviews, systematic reviews, and meta-analyses were excluded. Articles were excluded if the diagnosis was not made through a professional medical evaluation or if they relied on electronic health records or clinical data. For each included study, the following information was extracted: demographic characteristics, diagnostic criteria or psychiatric assessments, details of the technological tools and data types, duration of data collection, data preprocessing methods, selected variables or features, machine learning algorithms or statistical tests, validation, and main findings.

RESULTS: We included 21 studies, of which 11 (52%) focused on directly distinguishing between UD and BD, while 10 (48%) classified UD, BD, and HC. The studies were categorized into 4 groups based on the type of digital tool used: 6 (29%) used smartphone apps, 3 (14%) used wearable devices, 11 (52%) analyzed audiovisual recordings, and 1 (5%) used multimodal technologies. Features such as activity levels from smartphone apps or wearable devices emerged as potential markers for directly distinguishing UD and BD. Patients with BD generally exhibited lower activity levels than those with UD. They also tended to show higher activity in the morning and lower in the evening, while patients with UD showed the opposite pattern. Moreover, speech modalities or the integration of multiple modalities achieved better classification performance across UD, BD, and HC groups, although the specific contributing features remained unclear.

CONCLUSIONS: Digital phenotyping shows potential in distinguishing BD from UD, but challenges like data privacy, security concerns, and equitable access must be addressed. Further research should focus on overcoming these challenges and refining digital phenotyping methodologies to ensure broader applicability in clinical settings.

TRIAL REGISTRATION: PROSPERO CRD42024624202; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024624202.

PMID:40408762 | DOI:10.2196/72229

Phys Rev Lett. 2025 May 2;134(17):177301. doi: 10.1103/PhysRevLett.134.177301.

ABSTRACT

Transfer learning (TL) is a well-established machine learning technique to boost the generalization performance on a specific (target) task using information gained from a related (source) task, and it crucially depends on the ability of a network to learn useful features. Leveraging recent analytical progress in the proportional regime of deep learning theory (i.e., the limit where the size of the training set P and the size of the hidden layers N are taken to infinity keeping their ratio α=P/N finite), in this Letter we develop a novel single-instance Franz-Parisi formalism that yields an effective theory for TL in fully connected neural networks. Unlike the (lazy-training) infinite-width limit, where TL is ineffective, we demonstrate that in the proportional limit TL occurs due to a renormalized source-target kernel that quantifies their relatedness and determines whether TL is beneficial for generalization.

PMID:40408730 | DOI:10.1103/PhysRevLett.134.177301

Phys Rev Lett. 2025 May 2;134(17):178201. doi: 10.1103/PhysRevLett.134.178201.

ABSTRACT

Understanding how a fluid turns into an amorphous solid is a fundamental challenge in statistical physics, during which no apparent structural ordering appears. In the athermal limit, the two states are connected by a well-defined jamming transition, near which the solid is marginally stable. A recent mechanical response screening theory proposes an additional transition above jamming, called a plastic-to-elastic transition here, separating anomalous and quasielastic mechanical behavior. Through numerical inflation simulations in two dimensions, we show that the onsets of long-range radial and angular correlations of particle displacements decouple, occurring, respectively, at the jamming and plastic-to-elastic transitions. The latter is characterized by a power-law diverging correlation angle and a power-law spectrum of the displacements along a circle. This work establishes two-step transitions on the mechanical properties during “decompression melting” of an athermal overjammed amorphous solid, reminiscent of the two-step structural melting of a crystal in two dimensions. In contradistinction with the latter, the plastic-to-elastic transition exists also in three dimensions.

PMID:40408728 | DOI:10.1103/PhysRevLett.134.178201

Phys Rev Lett. 2025 May 9;134(18):180405. doi: 10.1103/PhysRevLett.134.180405.

ABSTRACT

The eigenstate thermalization hypothesis (ETH) has been highly influential in explaining thermodynamic behavior of closed quantum systems. As of yet, it is unclear whether and how the ETH applies to non-Hermitian systems. Here, we introduce a framework that extends the ETH to non-Hermitian systems, within which expectation values of local operators reproduce statistical and scaling predictions known from Hermitian ETH. We illustrate the validity of the framework on non-Hermitian random-matrix and Sachdev-Ye-Kitaev models. Further, we show numerically how the static ETH predictions become imprinted onto the dynamics of local observables. Finally, we present a prescription for observing both ETH-obeying and ETH-violating regimes in an optical-lattice experiment that implements a disordered interacting Hatano-Nelson model. Our results generalize the celebrated ETH to the non-Hermitian setting, and they show how it affects the system dynamics, and how the salient signatures can be observed in present-day cold-atom experiments.

PMID:40408674 | DOI:10.1103/PhysRevLett.134.180405

PLoS One. 2025 May 23;20(5):e0321008. doi: 10.1371/journal.pone.0321008. eCollection 2025.

ABSTRACT

Accurate monthly runoff forecasting is vital for water management, flood control, hydropower, and irrigation. In glacierized catchments affected by climate change, runoff is influenced by complex hydrological processes, making precise forecasting even more challenging. To address this, the study focuses on the Lotschental catchment in Switzerland, conducting a comprehensive comparison between deep learning and ensemble-based models. Given the significant autocorrelation in runoff time series data, which may hinder the evaluation of prediction models, a novel statistical method is employed to assess the effectiveness of forecasting models in detecting turning points in the runoff data. The performance of Extreme Gradient Boosting (XGBoost) was compared with long short-term memory (LSTM) and random forest (RF) models for one-month-ahead runoff forecasting. The study used 20 years of runoff data (2002-2021), with 70% (2002-2015) dedicated for training and calibration, and the remaining data (2016-2021) for testing. The findings for the testing phase results show that the XGBoost model achieves the best accuracy, with R² of 0.904, RMSE of 1.554 m³/sec, an NSE of 0.797, and Willmott index (d) of 0.972, outperforming both the LSTM and RF models. The study also found that the XGBoost model estimated turning points more accurately, obtaining forecasting improvements of up to 22% to 34% compared to LSTM and RF models. Overall, the study’s findings are essential for global water resource management, providing insights that can inform sustainable practices to support societies impacted by climate change.

PMID:40408639 | DOI:10.1371/journal.pone.0321008