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Nevin Manimala Statistics

Deletion of neurosecretory proteins GL and GM drives dual anti-obesity effects via appetite suppression and enhanced energy expenditure

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

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Nevin Manimala Statistics

Spectral residual augmented classical least squares for simultaneous green determination of cetirizine, fexofenadine and loratadine by UV spectrophotometry in pharmaceuticals and environmental samples

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

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Nevin Manimala Statistics

Development and field evaluation of a low-cost fuzzy logic irrigation controller for vineyards in semi-arid regions

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

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Nevin Manimala Statistics

Evaluation of disinfection efficiency of new high oxygen membrane air disinfecting machine in hospital ward environment

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

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Nevin Manimala Statistics

Regional Anesthesia as Primary Strategy in Aesthetic Breast Augmentation Surgery: Clinical Outcomes in 627 Sedated Patients Undergoing Pectoral Nerves (PECS I-II) and Parasternal Blocks

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

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Nevin Manimala Statistics

The predictive value of systemic inflammation response index and albumin-to-globulin ratio for prognosis in non-small cell lung cancer

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

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Nevin Manimala Statistics

Electrolyte abnormalities and clinical outcomes in heart failure patients: a retrospective cohort study using MIMIC-IV database

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

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Nevin Manimala Statistics

Early detection and community-based surveillance of Aedes albopictus in the Razmian region of Qazvin Province, Iran

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-55779-0. Online ahead of print.

ABSTRACT

Aedes albopictus, the Asian tiger mosquito, is a globally recognized invasive species and a significant vector for arboviruses such as Dengue, Zika, and Chikungunya. While reported in various Northern provinces of Iran, evidence of its detection in Qazvin Province, remained unconfirmed prior to this study. The objective of this research was to conduct early detection and community-based surveillance for invasive Aedes species within this high-risk area. A comprehensive entomological surveillance system was implemented across Qazvin Province (2022-2024), integrating monitoring at Points of Entry, community‑based reporting, and targeted investigations around confirmed dengue cases. Field activities were conducted from April to November each year. Data collection included ovitrap monitoring, larval habitat inspections, and adult mosquito sampling using standardized WHO‑recommended procedures, followed by morphological identification under laboratory conditions. All surveillance information was systematically recorded, validated, and analyzed using descriptive statistics. The presence of Ae. albopictus was confirmed in Razmian. A total of 1,602 mosquito specimens representing eight species from four genera were collected, including 561 eggs, 15 larvae, and 3 adult Ae. albopictus detected across four locations. All positive detections originated from community‑triggered investigations, while ovitraps and routine surveillance at Points of Entry yielded no Aedes specimens. This demonstrates the high sensitivity of community‑based reporting for early detection of low‑density invasive mosquito populations. This study reports the first confirmed detection of Ae. albopictus in Qazvin Province. The findings highlight the essential contribution of community reporting in complementing traditional entomological surveillance and emphasize the need for sustained, people‑centered surveillance strategies to mitigate the risk of future arboviral transmission.

PMID:42236832 | DOI:10.1038/s41598-026-55779-0

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Nevin Manimala Statistics

Intercomparison case study of data-driven reconstructions of a cloud-obscured Saharan dust plume in Europe

Sci Rep. 2026 Jun 3;16(1):17165. doi: 10.1038/s41598-026-55422-y.

ABSTRACT

On 15 March 2022 an intense, but partially cloud-obscured, Saharan dust plume was transported towards Europe by an atmospheric river. Ten-year statistics of dust plumes co-occurring with cloud cover over Europe highlights that regionally up to 100% of dust plumes are obscured by clouds, which poses challenges for reconstructing dust plumes from satellite images. The European dust case on 15 March 2022 is used to investigate whether data-driven machine-learning techniques for restoring the spatial extent of dust plumes in SEVIRI satellite images can be alleviated by exploiting the rich ground-based data sets in Europe. Satellite images were paired with different combinations of ground-based observation data, stemming from ground-based remote sensing, weather reports and measurements of particulate matter, using a k-nearest neighbours approach. Combining ceilometer and photometer data with satellite images added the most value for restoring the dust plume extent and are recommended for future reconstructions of cloud-obscured dust plumes.

PMID:42236821 | DOI:10.1038/s41598-026-55422-y

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Nevin Manimala Statistics

Quantitative measurement of agonistic behaviors of intra- and interspecifics of Gryllus bimaculatus and Acheta domesticus by using DeepLabCut

Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-55331-0. Online ahead of print.

ABSTRACT

Animal social behavior, such as agonistic behavior, has been extensively studied for a long time since it is one of the key factors that influence the survivability and reproductive success in many animals, including crickets. Gryllus bimaculatus, a field cricket, and Acheta domesticus, a house cricket, are two cricket species whose social behaviors have been extensively studied. However, the interspecific behaviors of these crickets had not been assessed and comprehensively compared to their behaviors when encountering their conspecifics. Moreover, most of the behavior studies in crickets still rely on traditional observational methods, which are labor-intensive and prone to observer bias. Fortunately, due to the advancement in machine learning, a markerless pose estimation method has revolutionized behavioral analysis in animal studies by enabling precise, automated tracking of body parts without the need for physical markers, reducing stress and allowing for naturalistic behavior in animals. Therefore, the study aimed to demonstrate a comprehensive methodology in analyzing the intra- and interspecies social behaviors of G. bimaculatus and A. domesticus by DeepLabCut (DLC), a deep learning-based pose estimation tool. Based on the results, the trained model that was used in the current study showed a relatively high accuracy after undergoing several rounds of training, as indicated by the relatively high value of average likelihood (0.94) and low value of average low likelihood percentage (3.85%) of each detected body part in every tested cricket. Meanwhile, GLMM analysis revealed no significant differences between the proposed method and manual scoring in both calculated aggressive-related behavior endpoints. Moreover, the system achieved high sensitivity with an average of 0.8, with acceptable precision with an average of 0.7 for both behaviors, demonstrating that the automated approach provides accurate and reliable quantification of aggressive interactions in paired crickets. Next, in terms of the cricket’s social behaviors, males of G. bimaculatus displayed aggressive behaviors as indicated by statistically high overt physical combat count, which were followed by high locomotion and movement complexity, while a slightly higher posterior-oriented interaction count was observed in the male × female group of this species. Meanwhile, although overt physical combat behaviors still could be observed in males of A. domesticus, this cricket in other gender combinations did not display noticeable aggressive behaviors compared to G. bimaculatus. On the other hand, aggressive behaviors were still shown by both males and females during interspecific tests, though in a relatively lesser magnitude compared to intraspecific G. bimaculatus. Taken together, the present study highlighted the effectiveness of DLC for markerless pose estimation of crickets, emphasizing the potential of this methodology as an alternative to provide novel quantitative insights into the dynamics of their social interactions, and thus, paving the way for large-scale, reproducible research on animal social interactions that could advance our understanding of animal behaviors.

PMID:42236810 | DOI:10.1038/s41598-026-55331-0