Nevin Manimala

NPJ Digit Med. 2026 May 27. doi: 10.1038/s41746-026-02796-y. Online ahead of print.

ABSTRACT

Gastroesophageal reflux disease (GERD) diagnosis traditionally relies on acid exposure time (AET) obtained from 24-h multichannel intraluminal impedance-pH (MII-pH) monitoring, the gold standard for GERD diagnosis. However, a negative result (AET < 4%) does not always exclude GERD, as the limited 24-h monitoring window may fail to capture reflux events in patients with intermittent or low-frequency reflux. To address this limitation, we proposed a complementary machine learning-based framework targeting exclusively patients with negative MII-pH results (AET < 4%) to identify potential false-negative cases within this cohort, by integrating statistical and waveform-derived features from pH signals to enhance anomaly detection. Using one-class support vector machine and support vector data description models trained on real-world MII-pH datasets, the framework achieved an $F_3$ score of approximately 0.9 and identified potential anomalies undetected by the conventional AET criteria. Explainable AI techniques using Shapley additive explanations showed that features such as kurtosis and peak-to-peak amplitude contributed significantly to the identification of subtle reflux patterns within this cohort. These anomalies may indicate additional candidates for clinical reassessment within the AET-negative cohort. This complementary approach, operating downstream of the conventional MII-pH diagnostic system, could help identify potential false-negative cases among patients with negative MII-pH results, potentially assisting in their proper clinical management.

PMID:42204253 | DOI:10.1038/s41746-026-02796-y

Commun Med (Lond). 2026 May 28. doi: 10.1038/s43856-026-01645-z. Online ahead of print.

ABSTRACT

BACKGROUND: Prostate cancer (PCa) is heterogeneous, making risk stratification essential for clinical care. Although polygenic risk scores (PRSs) with main effects of single-nucleotide polymorphisms (SNPs) can help identify individuals at high risk before biological and clinical onset, a PRS for predicting PCa aggressiveness remains underdeveloped. The KLK3, which encodes prostate-specific antigen (PSA), is linked to PCa aggressiveness. Recent findings on KLK3 SNP-SNP interactions show promise for predicting PCa aggressiveness. The objective of this study is to develop a PRS (PRS-KLK3int) by examining KLK3 SNP-SNP interaction pairs.

METHODS: The PRS-KLK3int was developed based on a discovery set (10,836 PCa patients) and two validation sets with 14,348 and 16,584 patients of European ancestry. A total of 3145 SNP pairs and two published PRSs were evaluated.

RESULTS: This study developed a PRS-KLK3int with 284 SNPs, combining an existing PRS with 270 SNPs and 12 SNP-SNP interaction pairs with 15 SNPs (one overlapped). All these 12 pairs were involved with at least one SNP from KLK3. The PRS-KLK3int outperformed two existing PRSs in predicting PCa aggressiveness (p-values: 3.5×10^-18, 9×10^-14, and 1.7×10^-20 for the three sets). It effectively distinguished high-risk from low-risk groups across all datasets. The top 1% high-risk group had a higher prevalence of PCa aggressiveness than the middle 50% group (45.5% vs. 25.9%, OR = 2.38, p = 2.2×10^-5) in the discovery set, and similar results were observed in validation sets (OR = 2.56, p = 4.3×10^-6; OR = 2.07, p = 2.1×10^-5).

CONCLUSIONS: These findings support PRS-KLK3int as a valuable tool for PCa severity stratification, especially in identifying extremely high-risk PCa patients.

PMID:42204244 | DOI:10.1038/s43856-026-01645-z

Sci Rep. 2026 May 27. doi: 10.1038/s41598-026-54762-z. Online ahead of print.

ABSTRACT

Given the growing concern about how school-based bullying undermines students’ academic success and emotional well-being, especially in high-stakes assessment environments, the study investigated the relationships between bullying frequency, psychological safety during assessments, counselling-based accommodations, and academic performance among senior high school (SHS) students in Ghana, with a focus on gender and regional variations. Guided by Edmondson’s (1999) theory of psychological safety, the research employed a quantitative correlational design involving 585 students from 12 public SHSs across Greater Accra, Central, and Ashanti regions. Multivariate statistical techniques were used to test three hypotheses related to direct, indirect, and interaction effects. Findings indicated that psychological safety significantly mediated the relationship between bullying and academic performance (indirect effect = – 0.775, 95% CI [- 1.23, – 0.43]), while the direct effect of bullying on performance became non-significant when psychological safety was controlled (B = 0.02, p = 0.921). Students who perceived higher psychological safety scored significantly higher in academic performance (B = 3.10, p < .001, η² = 0.049). Counselling-based accommodations were found to moderate the negative impact of bullying on psychological safety (interaction term B = 0.22, p = 0.029, η² = 0.008), suggesting that students with access to counselling reported greater resilience against bullying-induced threats to their assessment environments. Gender moderated the bullying performance link (B = – 0.88, p = 0.010), with female students more adversely affected. MANOVA results showed significant multivariate effects for gender (Wilks’ Λ = 0.934, p < 0.001, partial η² = 0.039) and region (Wilks’ Λ = 0.882, p < 0.001, partial η² = 0.043), and a smaller but significant interaction effect (Wilks’ Λ = 0.972, p = 0.012). The study advocates for gender-sensitive, regionally tailored interventions and suggests that the Ministry of Education institutionalize counselling-based accommodations during high-stakes assessments.

PMID:42204225 | DOI:10.1038/s41598-026-54762-z

Sci Rep. 2026 May 27. doi: 10.1038/s41598-026-54514-z. Online ahead of print.

ABSTRACT

Premature ovarian insufficiency (POI) is a reproductive endocrine disorder characterized by amenorrhea, hypergonadotropism, and hypoestrogenism before age 40. This study investigated the association of serum Chemerin, follicle stimulating hormone, lipid profile and cardiometabolic indices with the POI. In this case-control study, 38 women with POI and 38 controls were assessed for anthropometric parameters, serum Chemerin, FSH, lipid profile and cardiometabolic indices. Associations were examined using multivariable logistic regression models. Discriminative performance was evaluated using receiver operating characteristic (ROC) analysis and a combined multivariable model. POI was significantly associated with educational years, physical activity, total cholesterol (TC), triglyceride (TG) and serum Chemerin levels (P < 0.05). ROC analysis showed moderate discriminative ability for Chemerin, TC, and TG, with optimal cut-offs of 25.14 ng/L for serum Chemerin, 196.0 mg/dL for TC, and 114.5 mg/dL for TG, respectively. The combined multivariable model demonstrated excellent discrimination (AUC = 0.929; 95% CI 0.876-0.981), achieving 94.7% sensitivity and 76.3% specificity. Serum Chemerin showed moderate diagnostic value, while several individual variables also demonstrated moderate discriminative ability. However, the combined multivariable model showed substantially stronger discriminatory performance, indicating that integrating multiple variables improves the ability to identify POI compared with individual variables alone.

PMID:42204224 | DOI:10.1038/s41598-026-54514-z

Sci Rep. 2026 May 27. doi: 10.1038/s41598-026-52684-4. Online ahead of print.

ABSTRACT

The determination of the extent and margins of precancerous or cancerous lesions is still a problem in oncological surgeries today. This is more so with the ‘holy grail’ goal of optimal excision requiring total lesion removal and maximal neighboring tissue conservation especially for an important organ like the cervix. Although frozen section is the gold standard method available for aiding intraoperative diagnosis and surgery decision management, in dysplasia of the cervix where precancer cases are treated, it is not applicable due to various reasons, mainly to avoid over treatment. Still an optimal surgery is highly advocated and currently applying LUGOL dye to cervix is the accepted technique although not always accurate. Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy can complement visual inspection after LUGOL application, and several efforts have shown its potential in this regard. Research efforts on the subject, however, have not explored the use of ATR-FTIR spectroscopy for determining the extent of precancer on fresh cervical biopsies. This work therefore sets out to investigate ATR-FTIR spectroscopy for estimating the extent of precancer on fresh cervical samples using discriminatory features from the fingerprint region, as well as entropy and bound water related markers. Our results show that posterior probabilities were statistically different for precancer and healthy sampling points, with an area under the receiver operating characteristic curve value of 0.678 ± 0.094. At a cut-off probability of 0.550, sensitivity and specificity were 70% and 59%, respectively. These results show that ATR-FTIR spectroscopy on fresh tissue can aid spatially resolved determination of the extent of precancer, and that bound water and entropy related spectral biomarkers can provide additional diagnostic information for the ultimate goal of aiding intraoperative decision management.

PMID:42204206 | DOI:10.1038/s41598-026-52684-4

Sci Rep. 2026 May 27. doi: 10.1038/s41598-026-46257-8. Online ahead of print.

ABSTRACT

Engineering optical resilience against atmospheric turbulence is essential for robust free-space photonic technologies. Here, we demonstrate that dual partially coherent Bessel-Vortex beams-with engineered topological charge pairing-exhibit unprecedented control over turbulence-induced scintillation beyond what is achievable with single beams or partial coherence alone. Using a spatial light modulator, we generate single and dual partially coherent Bessel-Vortex beams and propagate them through a laboratory turbulence chamber calibrated to Kolmogorov statistics ([Formula: see text]) over a 0.15 m path, corresponding to a 1 km atmospheric propagation with equivalent turbulence strength [Formula: see text]. A key technical innovation of this work is the simultaneous encoding of both the Bessel-Vortex phase profile and the Kolmogorov-distributed random phase onto a single hologram displayed on the SLM-enabling real-time generation of partially coherent structured beams without additional optical components. We find that dual-beam configurations with co-signed topological charges show monotonically increasing resilience with charge difference, whereas counter-signed pairs display a pronounced non-monotonic response with minimal resistance at Δm = 8. Most strikingly, beams with equal-magnitude opposite charges (|m₁| = |m₂|) exhibit monotonic degradation in resilience up to order 14-a behavior absent in single-vortex systems. These results establish dual topological charge pairing as a previously unexplored design parameter for turbulence-resilient optical systems, with direct implications for free-space optical communication, quantum information transfer, and high-precision optical manipulation.

PMID:42204203 | DOI:10.1038/s41598-026-46257-8

Sci Rep. 2026 May 27;16(1):16437. doi: 10.1038/s41598-026-53181-4.

ABSTRACT

Overactive bladder (OAB) is a common chronic condition that can have a significant impact on quality of life (HRQL). We aimed to assess the prevalence of OAB bother and its related quality of life among medical students in Egypt. A cross-sectional study among medical students in Egypt. An online questionnaire was shared via online platforms to collect the intended participants. We used the Overactive Bladder Symptoms and Health-Related Quality of Life Short Form (OAB-q SF). We assessed the difference between participants in their baseline characteristics using the Mann-Whitney U and Kruskal-Wallis Tests. We performed a multiple linear regression to assess the potential risk factors. 1003 participants completed the questionnaire. The median transformed OAB bother score was 10[3.33, 23.33], while the median transformed score of HRQL was 93.8[80, 98.46]. The prevalence was about 15%, while about 51.65% reported a decline in HRQL. A statistically significant association between OAB bother and academic phase, energy drink, or satisfaction with social life was reported. We found no association between OAB bother and caffeinated drinks or smoking. Finally, neither age, gender, nor BMI had an association with OAB bother. A low prevalence of OAB among medical students was found. Consumption of Energy drinks was found to be a risk factor, while caffeinated drinks had no effect. OAB was found to be higher in the academic phase than in the clinical one. Several studies should be conducted to further assess the risk factors of overactive bladder.Clinicaltrials.gov registration: NCT07044778, June 2025.

PMID:42204195 | DOI:10.1038/s41598-026-53181-4

Sci Rep. 2026 May 27. doi: 10.1038/s41598-026-54820-6. Online ahead of print.

ABSTRACT

Fake news detection is an essential task for media and news organizations to maintain the trust and reliability of the published content. Due to the rapid growth of online users and the spread of misinformation through malicious sources, the fake news circulates quickly across digital platforms. Hence, developing an accurate and efficient fake news detection model is crucial for social welfare. Although many studies have been conducted, achieving high accuracy remains challenging task, especially when dealing with rare and infrequent words. Traditional embedding models such as Word2Vec and FastText perform only word-level vectorization, while transformer-based models like BERT handle subword token more effectively. However, selecting the most suitable subword pieces for vector representation raises challenges. The research introduces a character-based embedding approach to generate fine-grained vector representations by analysing each character. A hybrid CharBERT-Optimized CNN and attention-based stacked Bi-LSTM with cost-sensitive learning (COASBC) model is proposed to classify fake news. In addition, a federated learning (FL) framework is integrated to enable distributed training across multiple news sources for improving generalization of model without sharing raw data. It reduces centralized computational cost, enhances data security and scalability of the model. Furthermore, statistical analysis and complexity analysis are conducted to evaluate the efficiency and computational feasibility of the proposed model. The generalization ability of the model is also analysed using Truth Seeker dataset 2023 that contains short-text tweets. Experimental evaluation using the LIAR, Fake and Real News datasets, FakeNewsNet, and WELFake Dataset demonstrates that the proposed Federated COASBC model achieves superior accuracy, precision, and reliability compared to existing state-of-the-art fake news detection methods and it maintains high computational efficiency.

PMID:42204192 | DOI:10.1038/s41598-026-54820-6

Sci Rep. 2026 May 27. doi: 10.1038/s41598-026-53535-y. Online ahead of print.

ABSTRACT

Classical heat conduction and thermoelastic theories are often inadequate for describing transport processes in modern micro and nano-scale materials, as they assume instantaneous propagation and neglect memory and nonlocal effects. This limitation becomes particularly important in applications such as semiconductor devices and porous structures subjected to rapid thermal and chemical loading. To address this issue, the present study develops a generalized thermo-elasto-diffusion model for porous medium by incorporating fractional-order heat conduction and Klein-Gordon-type nonlocal dynamics. The model extends the classical Lord-Shulman framework through a set of fractional-order modified models derived using an analogy with viscoelastic behavior, allowing both memory effects and spatial interactions to be captured through intrinsic time and length scales. Analytical solutions are obtained in the Laplace domain and numerically inverted using Zakian’s algorithm to evaluate the transient response of displacement, temperature, chemical potential, and stress fields. The results show that fractional-order parameters and nonlocal effects significantly influence wave propagation and heat transfer, especially near boundaries and in regions with strong microstructural interactions. Overall, the proposed framework provides a more realistic and physically consistent description of coupled thermo-mechanical processes, offering useful insights for the design and analysis of advanced porous and semiconductor materials under extreme conditions.

PMID:42204191 | DOI:10.1038/s41598-026-53535-y

Sci Rep. 2026 May 28. doi: 10.1038/s41598-026-50447-9. Online ahead of print.

ABSTRACT

The triglyceride-glucose (TyG) index has recently gained attention as a cost-effective and easily calculable surrogate marker reflecting insulin resistance-related metabolic risk. Given the close interplay between thyroid hormones, lipid metabolism, glucose regulation, and inflammation, evaluating the association between thyroid dysfunction and the TyG index remains clinically relevant. This study aimed to investigate variation in the TyG index across different thyroid function states-overt hypothyroidism (OH), subclinical hypothyroidism (SCH), euthyroidism (EH), and healthy controls-and to assess its associations with lipid parameters and inflammatory markers, including the CRP/albumin ratio. In this cross-sectional observational study, 222 adults were categorized according to thyroid status based on TSH and free T4 levels. The TyG index was calculated using fasting glucose and triglyceride values. Associations with lipid and inflammatory markers were evaluated, and receiver operating characteristic (ROC) analysis was performed to assess the ability of the TyG index to discriminate individuals with elevated TyG-defined metabolic risk. No statistically significant differences in TyG index levels were observed across thyroid function groups (p = 0.152). However, the TyG index showed significant positive correlations with triglyceride levels (r = 0.419, p < 0.001), CRP/albumin ratio (r = 0.342, p < 0.001), and LDL-C (r = 0.204, p = 0.009). ROC analysis demonstrated moderate discriminatory performance (AUC = 0.731; 95% CI: 0.652-0.809), identifying individuals with higher TyG levels associated with increased metabolic risk. Although TyG index levels did not differ significantly across thyroid function states, their associations with lipid and inflammatory markers suggest that the TyG index reflects metabolic and inflammatory risk profiles independent of thyroid status, rather than serving as a direct diagnostic measure of insulin resistance.

PMID:42204188 | DOI:10.1038/s41598-026-50447-9