Tag: nevin manimala

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-55978-9. Online ahead of print.

ABSTRACT

Floods remain one of the most destructive natural hazards, causing extensive loss of life and infrastructure, largely due to delayed warnings generated by conventional threshold-based monitoring systems. Such systems are inherently reactive and fail to account for evolving hydrological behaviour driven by complex interactions among environmental variables. To address these limitations, this study proposes an unsupervised, explainable anomaly-detection framework for early flood warning using multivariate time-series data from Digital Water Level Recorder (DWLR) sensors. The proposed approach utilises sliding-window temporal modelling and an LSTM autoencoder to learn normal hydrological patterns from water-level, rainfall, temperature, pH, and dissolved-oxygen measurements, without requiring labelled events. Anomalies are identified through reconstruction error and statistically grounded thresholding, enabling proactive detection of abnormal system behaviour. To enhance transparency and trust, Integrated Gradients-based explainability is incorporated to quantify feature- and time-wise contributions to detected anomalies. Experimental results on real-world DWLR data demonstrate that the framework consistently identifies anomalous behaviour several weeks before critical water-level exceedance, providing meaningful early warning signals. Explainability analysis reveals that anomalies often originate from chemical and environmental factors, such as changes in pH and dissolved oxygen, before an observable water-level rise. The proposed framework offers a robust, interpretable, and data-driven solution for smart flood monitoring systems, supporting informed decision-making and improved disaster preparedness.

PMID:42236952 | DOI:10.1038/s41598-026-55978-9

Nat Med. 2026 Jun 3. doi: 10.1038/s41591-026-04381-y. Online ahead of print.

ABSTRACT

The world has made progress in increasing the number of births attended by skilled health personnel (SHP), but maternal and neonatal mortality have not declined proportionately. This may indicate that quality of care has not risen at the same rate as SHP coverage. Several ‘Exemplar’ countries have been previously recognized for outstanding progress in improving maternal and newborn health, and offer a unique opportunity to understand coverage and quality of care provided by SHP. Here we describe quality of care and how it compares with SHP coverage in three Exemplar countries-Nepal, Senegal and Zambia. We developed a conceptual framework, compiled primary and secondary data, and employed latent variable analysis. We combined quality estimates with coverage estimates to quantify the effective coverage of SHP. Results show that effective SHP coverage ranges between 12% and 43% across subnational regions, compared with crude SHP coverage ranging from 30% to 100%, indicating that mothers and newborns are receiving less lifesaving care than coverage statistics portray. The detection of this quality gap in Exemplar settings, which represent some of the highest-performing health systems among low- and middle-income countries, emphasizes the criticality of quality care to reduce maternal and neonatal mortality worldwide.

PMID:42236909 | DOI:10.1038/s41591-026-04381-y

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-56107-2. Online ahead of print.

ABSTRACT

Artificial intelligence is increasingly used in Life Sciences, though the pace and direction of adoption varies widely across countries. To map the Greek landscape, we performed a data‑driven analysis of 916,824 AI-related life-science papers harvested from OpenAlex and PubMed. We tagged each publication with Medical Subject Headings (MeSH) and compared topic frequencies between articles linked to at least one Greek institution and the rest of the world. Greek‑affiliated outputs are disproportionately concentrated under the theme of methodology and algorithm‑development, whereas the global corpus is dominated by disease‑focused, organism‑centered and clinical applications. Statistical contrasts across three MeSH hierarchy levels exposed clear national strengths in machine learning techniques and analytical tools, alongside under‑representation in translational, patient‑centred research. Overall this study combines bibliometric evidence with community perspectives and provides a comprehensive overview of AI activity in Life Sciences in Greece, highlighting potential thematic strengths and gaps.

PMID:42236907 | DOI:10.1038/s41598-026-56107-2

Commun Biol. 2026 Jun 3. doi: 10.1038/s42003-026-10405-7. Online ahead of print.

ABSTRACT

Obesity results from an imbalance between energy intake and expenditure and is regulated by hypothalamic neuropeptide systems. The neurosecretory proteins GL (NPGL) and GM (NPGM) are expressed in the hypothalamus and promote feeding in gain-of-function studies; however, their endogenous physiological roles remain unclear. Here, we show that mice lacking both NPGL and NPGM display a lean phenotype driven by reduced food intake and increased energy expenditure. This anti-obesity phenotype is associated with increased expression of anorexigenic pro-opiomelanocortin in the hypothalamus and enhanced thermogenic activity in brown adipose tissue, marked by elevated uncoupling protein 1. Consistent with these findings, suppression of NPGL/NPGM signaling reduces feeding and alters sympathetic nerve activity. In addition, genome-wide association analysis identifies an obesity-associated variant near the human NPGM locus, suggesting relevance to human energy balance. Together, these findings identify NPGL and NPGM as endogenous regulators of energy homeostasis with potential relevance to obesity.

PMID:42236905 | DOI:10.1038/s42003-026-10405-7

Sci Rep. 2026 Jun 3;16(1):17188. doi: 10.1038/s41598-026-56246-6.

ABSTRACT

Second-generation antihistamines-cetirizine, fexofenadine, and loratadine-require simultaneous determination methods for pharmaceutical quality control including cleaning validation and cross-contamination monitoring in multi-product manufacturing facilities, yet their severely overlapping UV spectra preclude direct spectrophotometric quantification. This study developed a novel, sustainable UV-spectrophotometric method employing spectral residual augmented classical least squares (SRACLS) chemometrics to mathematically resolve spectral overlap and enable simultaneous quantification. Calibration (25 mixtures, partial factorial design) and validation sets (20 mixtures, central composite design) spanned 4-12 µg/mL concentration ranges. Comparative evaluation revealed that SRACLS demonstrated superior performance versus concentration residual augmented classical least squares (CRACLS), achieving 40-70% lower prediction errors (RRMSEP: 1.745, 2.605, 1.736 versus 3.011, 3.960, 2.674) and tighter residual distributions (± 3-5 versus ± 5-6 units). Subsequently, ICH Q2(R2) validation confirmed excellent analytical performance: recoveries 98.06-101.95% across the full working range, intra-day precision ≤ 1.522% RSD, inter-day precision ≤ 1.986% RSD, LOD values of 0.379-0.560 µg/mL, LOQ values of 1.149-1.697 µg/mL, and robust selectivity against pharmaceutical excipients and environmental co-contaminants (96.05-103.38% recovery). Application to commercial tablets yielded results statistically equivalent to reported HPLC methods (t-test, F-test: p > 0.05), whereas analysis of tap water samples spiked at concentrations relevant to pharmaceutical manufacturing facility effluents following salting-out assisted liquid-liquid extraction achieved 95.43-103.85% recovery. Moreover, comprehensive sustainability assessment demonstrated excellent performance: MoGAPI 76, CaFRI 85, AGSA 70.83, BAGI 77.5, CACI 66, and AMRI 68, attributed to eliminated organic solvent consumption, minimal energy usage, low waste generation, and high throughput (> 30 samples/hour). Overall, this work represents the first SRACLS application to antihistamine analysis, providing a practical green alternative to chromatographic methods for pharmaceutical quality control and manufacturing effluent monitoring applications.

PMID:42236886 | DOI:10.1038/s41598-026-56246-6

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-56154-9. Online ahead of print.

ABSTRACT

Water scarcity in arid and semi-arid regions calls for irrigation strategies that adapt to real-time field conditions. This pilot study presents a low-cost fuzzy logic-based irrigation controller for vineyards in Malekan County (East Azerbaijan, Iran). The controller uses three environmental inputs (soil moisture, air temperature, and a solar-radiation index derived from light intensity (LDR)) and applies a rule-based fuzzy inference system to determine irrigation duration (with pump activation derived from the duration). A rainfall-gating rule is also used to prevent unnecessary irrigation during rainfall events. The system was implemented on an Arduino Uno using off-the-shelf sensors and evaluated through MATLAB surface analysis and a field pilot conducted from March to August 2024. In addition, an adjacent-plot pilot comparison against conventional irrigation was performed to examine seasonal water use and plot-level grape performance indicators (cluster weight, °Brix, acidity, and rotten cluster rate). The proposed controller was associated with a 34.6% reduction in irrigation water use (520 → 340 m³/ha) and descriptive improvements in cluster weight, °Brix, and rotten cluster incidence. These pilot results demonstrate the technical feasibility and operational reliability of the fuzzy logic-based controller under real-world semi-arid vineyard conditions, alongside promising descriptive improvements in water-use efficiency and key grape performance indicators. However, as this was a single-season, unreplicated adjacent-plot pilot study, the observed differences in yield and quality parameters should be interpreted as exploratory. Larger-scale, multi-season field trials are therefore required to statistically validate these preliminary findings and confirm their generalizability.

PMID:42236880 | DOI:10.1038/s41598-026-56154-9

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-55603-9. Online ahead of print.

ABSTRACT

To investigate the air disinfection efficacy of a novel high-oxygen membrane air sterilizer in hospital ward environments. Natural bacteria were used as indicator microorganisms, and air disinfection experiments were conducted under both unoccupied and occupied ward conditions to compare the actual disinfection performance between a high-oxygen membrane air sterilizer and a plasma air sterilizer. The relationship between disinfection efficacy and factors such as ward volume, temperature, humidity, initial bacterial load, and personnel movement was analyzed. Under unoccupied conditions, the natural bacterial extinction rate of the high-oxygen membrane air disinfecting machine was 88.4%, significantly higher than the 82.5% of the plasma air disinfecting machine (P = 0.019). However, under occupied conditions, there was no statistically significant difference in extinction rates between the two devices (80.0% vs. 78.7%, P = 0.165). Additionally, the disinfection efficacy of the high-oxygen membrane air disinfecting machine was not statistically affected by ward volume, temperature, humidity, initial bacterial concentration, or personnel activity (all P > 0.05) within the present experimental settings. Although high-oxygen membrane air disinfection technology demonstrates statistically superior disinfection performance in unoccupied environments, the observed efficacy does not currently support its use as a standalone intervention for reducing the airborne infection transmission. Further research in diverse clinical environments is needed to fully assess its potential.

PMID:42236873 | DOI:10.1038/s41598-026-55603-9

Aesthetic Plast Surg. 2026 Jun 3. doi: 10.1007/s00266-026-05966-1. Online ahead of print.

ABSTRACT

BACKGROUND: Post-operative pain after breast augmentation remains unpredictable, and regional anesthesia alone is seldom described. We evaluated an opioid-free protocol combining pectoral nerves (PECS I-II) and parasternal blocks with intravenous sedation.

METHODS: Between January 2020 and December 2024, 627 women (mean age 35 y) underwent bilateral primary augmentation under ultrasound-guided fascial-plane blocks plus sedation. VAS pain scores were recorded at predefined intervals up to 72 h. Descriptive statistics, cubic modelling of pain trajectories and Kruskal-Wallis tests compared implant planes; cumulative pain was expressed as the 0-72 h area under the curve (AUC).

RESULTS: Mean VAS was < 2 in all groups by 72 h. Pain peaked at 16 h, highest with dual-plane placement (mean 7.0) and lower with submuscular and pre-pectoral placements (both ≈ 5.5; p < 0.001). Inter-group differences persisted to 48 h but disappeared by 72 h (p = 0.115). AUC confirmed the greatest pain burden for dual-plane (292 VAS·h) versus submuscular (238) and pre-pectoral (200). Implant volume showed only a weak overall correlation with pain (ρ = 0.20) and none within individual planes. No patient required rescue opioids; most resumed normal activities within four days, and no major complications occurred.

CONCLUSIONS: Ultrasound-guided PECS I-II and parasternal blocks with sedation provide safe, effective, opioid-free analgesia for aesthetic breast augmentation. Early pain is determined mainly by the implant plane, not by implant size, and should be considered in surgical planning and postoperative care.

LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

PMID:42236868 | DOI:10.1007/s00266-026-05966-1

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-55879-x. Online ahead of print.

ABSTRACT

We investigated whether inflammatory markers would be significant prognostic factors for survival in patients with non-small-cell lung cancer (NSCLC). This was a retrospective cohort study including 748 consecutive Chinese NSCLC patients. The relationships of inflammatory markers with clinicopathologic characteristics and prognosis were analyzed by chi-squared test and Cox regression. Restricted cubic splines (RCS) with 4 knots were used to flexibly model non-linear relationships between markers and overall survival (OS). Survival was estimated using Kaplan-Meier curves. In multivariate analysis, the systemic inflammation response index (SIRI) and albumin-to-globulin ratio (AGR) were independently associated with OS (HR: 1.506, 95% CI: 1.224-1.852; HR: 0.749, 95% CI: 0.608-0.923). RCS showed a non-linear association for SIRI (P for non-linear = 0.004) and a linear association for AGR (P for non-linear = 0.258). We constructed a 3-tier SIRI-AGR score: Score 1 (low risk: SIRI ≤ 0.91 and AGR > 1.19), Score 2 (intermediate: either SIRI > 0.91 or AGR ≤ 1.19, but not both), Score 3 (high risk: SIRI > 0.91 and AGR ≤ 1.19). Patients with Score 3 had significantly shorter OS (HR: 1.974; 95% CI: 1.486-2.622). Time-dependent ROC showed stable predictive performance with AUC ≈ 0.70 throughout follow-up. The SIRI-AGR score is an independent, convenient, and low-cost prognostic factor for NSCLC. It can serve as a useful indicator for risk stratification and clinical decision-making.

PMID:42236852 | DOI:10.1038/s41598-026-55879-x

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-55290-6. Online ahead of print.

ABSTRACT

Electrolyte abnormalities commonly complicate heart failure management, yet their prognostic significance and optimal monitoring strategies remain incompletely characterized. We examined the prevalence, temporal patterns, and clinical outcomes associated with electrolyte abnormalities in hospitalized heart failure patients. Retrospective cohort study of 30,678 heart failure patients (80,408 admissions) from the MIMIC-IV database (2008-2022). Clinically significant electrolyte abnormalities (CSEA) were defined as patients whose potassium remained consistently < 3.5 or > 5.0 mEq/L, or whose sodium remained consistently < 135 or > 145 mEq/L throughout all measurements during hospitalization. Primary outcomes were 30-day all-cause readmission and mortality. We developed a clinical risk score incorporating electrolyte abnormalities and examined temporal electrolyte patterns. CSEA occurred in 950 patients (3.1%) in the full cohort, of whom 713 (2.3%) survived to discharge and constituted the primary analysis cohort for post-discharge outcomes. Patients with abnormalities had paradoxically lower 30-day readmission (3.9% vs 15.3%; adjusted HR 0.29, 95% CI 0.21-0.40) but substantially higher mortality (15.4% vs 7.0%; adjusted HR 1.93, 95% CI 1.57-2.38), reflecting competing mortality risk. Individual electrolyte abnormalities were independently associated with mortality: hypokalemia HR 1.45 (1.28-1.65), hyperkalemia HR 1.67 (1.48-1.89), hyponatremia HR 1.34 (1.19-1.51). Temporal analysis revealed biphasic patterns-initial correction followed by recurrence-identified the highest-risk subset (composite event rates 27.6% for potassium, 28.5% for sodium). A five-variable risk score (electrolyte abnormality, age ≥ 75, chronic kidney disease, multiple admissions, coronary artery disease) achieved C-statistic 0.593. CSEA are independently associated with mortality in heart failure patients despite paradoxically lower readmission rates due to competing risks. Biphasic electrolyte patterns identify particularly high-risk patients. Simple risk stratification using routinely collected electrolyte data may enhance post-discharge risk prediction and inform targeted monitoring strategies.

PMID:42236834 | DOI:10.1038/s41598-026-55290-6