Categories
Nevin Manimala Statistics

Furosemide Administration Enhances Diagnostic Confidence in the Evaluation of Ureteral Ectopia in Dogs Using Ultrasound

Vet Radiol Ultrasound. 2026 May;67(3):e70181. doi: 10.1111/vru.70181.

ABSTRACT

Ultrasonography is frequently utilized in patients with urinary incontinence to screen for structural abnormalities such as ectopic ureters (EUs). Furosemide can be administered during an ultrasound for a better assessment of the ureters and their insertions. Furosemide decreases urine specific gravity (USG), and differences in specific gravity allow a better visibility of ureteral jets on ultrasound; however, it is unknown whether furosemide has utility in patients with hyposthenuria or isosthenuria. The aims of this study were to determine if furosemide administration improves the diagnosis of EUs using ultrasound and if there is a USG below which furosemide will not increase ureteral jet visibility. Thirty-one dogs with clinical suspicion for EUs, and seven dogs with polyuria and polydipsia were included. Urinary tract ultrasonography was performed, and a diagnosis of the presence or absence of EUs was made. Urine collected by urocystocentesis was used to measure USG, furosemide was administered, and the exam was repeated. Ultrasound results were compared to cystoscopy or other means of negative diagnosis to determine accuracy. The accuracy of the EU diagnosis following furosemide was not statistically significant. There was a significant increase in the confidence of diagnosis post-furosemide; there was no association between increased confidence and improved accuracy. Ureteral jets were visible following furosemide in dogs with USGs as low as 1.006. On the basis of these findings, furosemide can be helpful to improve confidence of EU diagnosis and can be administered to increase ureteral jet visibility in dogs with hyposthenuria or isosthenuria.

PMID:42170689 | DOI:10.1111/vru.70181

Categories
Nevin Manimala Statistics

Nonlinear Relations Between Resting Heart Rate Measures and Health Risk Behavior in Emerging Adulthood

J Adolesc. 2026 May 22. doi: 10.1002/jad.70175. Online ahead of print.

ABSTRACT

INTRODUCTION: Resting heart rate (HR) measures reflect autonomic processes that could predict health risk behavior (HRB) in emerging adulthood when risky behavior is prominent. However, prior studies and extant theories are inconsistent, such that the relationships between HR measures and HRB could be positive or negative in direction. To reconcile these inconsistencies, we predicted that positive and negative relations between HR measures and HRB propensity exist together in a quadratic function.

METHODS: The current study tested this nonlinear hypothesis in a sample of young adults (N = 89, Mean Age = 21 years, 66% Female) who completed three separate resting baseline periods. ECG was recorded throughout to compute mean HR and high-frequency heart rate variability (HF-HRV) as partial and pure indices of resting vagal activity, respectively. HRB propensity was self-reported on the health/safety and recreational subscales of the Domain-Specific Risk-Taking questionnaire.

RESULTS: Resting HR and HF-HRV each exhibited quadratic associations with HRB propensity that were statistically separate from one another. In all functions, moderate levels of mean HR or HF-HRV were related to a reduced propensity for risk-taking behavior.

CONCLUSIONS: Findings suggest two potential pathways by which heart rate measures might contribute to HRB in emerging adulthood: one through heightened vagal activity, which may signal under-arousal, and the other through reduced vagal activity, which may reflect deficient self-regulation.

PMID:42170687 | DOI:10.1002/jad.70175

Categories
Nevin Manimala Statistics

The impact of social expectation pressure on turnover intention among Generation Z employees: a psychological mechanism analysis based on social comparison theory

Front Psychol. 2026 May 6;17:1689646. doi: 10.3389/fpsyg.2026.1689646. eCollection 2026.

ABSTRACT

INTRODUCTION: In the digital era, Generation Z employees are increasingly influenced by social media driven peer norms. While traditional turnover models focus largely on internal organizational factors, the impact of external digital psychosocial stressors on employee retention remains largely overlooked. Drawing on social comparison theory, this study investigates the relationship between social expectation pressure and turnover intention, with upward social comparison acting as a mediating mechanism.

METHODS: A cross-sectional survey was conducted among 542 Generation Z employees working in Chinese e-commerce firms. Validated scales were used to measure social expectation pressure, upward social comparison, and turnover intention. Hierarchical regression, confirmatory factor analysis, Bootstrapping via PROCESS macro, and robustness checks including propensity score matching and multi-group analysis were employed.

RESULTS: Social expectation pressure showed a significant positive association with turnover intention (β = 0.324, p < 0.001). Upward social comparison partially mediated this relationship (indirect effect = 0.178, 95% CI = [0.111, 0.247]), accounting for 55.6% of the total effect. These statistical relationships remained consistent across different organizational contexts.

DISCUSSION: The study broadens turnover research by introducing social expectation pressure as a relevant external psychosocial factor and confirms the mediating role of upward social comparison in the digital workplace. The findings offer theoretical and practical insights for understanding employee withdrawal behavior in social media saturated environments. Furthermore, they underscore the need for organizations to recognize and manage the social and psychological dynamics that shape the career decisions of Generation Z employees, conceptualizing turnover intention as a key manifestation of these broader career choices.

PMID:42170655 | PMC:PMC13188931 | DOI:10.3389/fpsyg.2026.1689646

Categories
Nevin Manimala Statistics

Victim-centered justice through profiling: clustering analysis of parent who suffered abuse

Front Psychol. 2026 May 6;17:1694603. doi: 10.3389/fpsyg.2026.1694603. eCollection 2026.

ABSTRACT

Understanding victimization in the context of parent abuse requires a comprehensive approach that considers the complex interplay of demographic, situational, and psychological factors. This study examines 3,834 administrative records from a victim support system, corresponding to 782 unique cases of parents who suffered violence, to identify distinct victim typologies and inform more effective, victim-centered interventions within the legal system. Drawing on variables such as age, gender, marital status, socioeconomic background, and harm types (physical, psychological, economic, and social), the dataset was analyzed using K-means clustering to uncover latent patterns. A two-cluster solution was selected based on statistical validation, offering both interpretability and strong group separation. Cluster 0, comprising 26.3% of the sample, was characterized by a slightly older average age (mean = 61.3 years) and exhibited a diverse set of vulnerability factors not primarily defined by psychological harm resulting from criminal acts. Members of this cluster showed elevated rates of widowhood (28.6% compared to 17.7% in Cluster 1), suggesting potentially different social support needs. In contrast, Cluster 1, labeled Psychological-Impact Victims, constituted the majority of the sample (73.7%), defined by the presence of psychological harm following criminal incidents, with a lower average age (mean = 58.0 years) and higher rates of separation or divorce (26.9% vs. 19.4%). This binary classification reveals a meaningful distinction in victim experiences of parent who suffered violence. Cluster 0 requires broad social support, while Cluster 1 needs trauma-informed psychological care. These findings emphasize the importance of tailored interventions over uniform approaches.

PMID:42170652 | PMC:PMC13188208 | DOI:10.3389/fpsyg.2026.1694603

Categories
Nevin Manimala Statistics

Dual-Attention BiLSTM for Interpretable Forecasting of Treatment Toxicities

IEEE EMBS Int Conf Biomed Health Inform. 2025 Oct;2025. doi: 10.1109/bhi67747.2025.11269508. Epub 2025 Dec 8.

ABSTRACT

Longitudinal patient-reported outcomes (PROs) provide crucial insights into symptom progression and treatment response in oncology, enabling more personalized and anticipatory care. Deep learning models such as Bidirectional Long Short-Term Memory (Bi-LSTM) networks have recently been applied to forecast symptom trajectories from PRO data. While these models offer improved predictive performance over traditional statistical methods, they often fall short of capturing the evolving clinical relevance of individual symptoms or the varying influence of specific time points in the patient journey and lack clinical interpretability. In this work, we propose an attention-enhanced Bi-LSTM model that incorporates dual attention mechanisms at the item and temporal levels to selectively emphasize the most informative symptom-time interactions. This architecture addresses the limitation of uniform input weighting, enhancing both forecasting accuracy and interpretability. Evaluated on a longitudinal PRO dataset collected at a major cancer center, our model outperforms conventional Bi-LSTM approaches in predicting 12-month symptom severity and offers clinically meaningful insights into symptom evolution. These findings highlight the potential of attention-based temporal modeling to support personalized, timely decision-making in oncology care.

PMID:42170647 | PMC:PMC13189339 | DOI:10.1109/bhi67747.2025.11269508

Categories
Nevin Manimala Statistics

Weeding out variability: a proof-of-concept for producing uniform F1 hybrid Cannabis sativa L. using single-seed descent

Hortic Res. 2026 Feb 19;13(5):uhag038. doi: 10.1093/hr/uhag038. eCollection 2026 May.

ABSTRACT

Cannabis sativa is a wind-pollinated, predominantly dioecious, and outcrossing crop associated with high levels of genetic variability even within a single cultivar. As such, seed-grown crops are often constrained by variability issues, decreasing production efficiency and product consistency. F1 hybrid seed technology offers great potential to address these limitations by generating genetically uniform populations from a cross of two inbred parental lines. In C. sativa, single-seed descent (SSD) is currently the most viable method to produce these homozygous parental lines necessary for F1 hybrid seed production. This study exemplifies the potential of SSD coupled with chemically induced sex reversion to produce fully homozygous lines and its subsequent application in creating five F1 hybrid accessions. Up to six rounds of SSD were performed in an 18-month period on 16 different lines, highlighting the speed of methodology. Inbreeding through XY males was most successful and offered the greatest advantages of the lines assessed. The F1 hybrid lines were statistically more uniform than the inbred or original lines and more vigorous than the inbred lines, with F1 lines increasing seed yield between 3.9% and 155% when compared to their midparents indicating the potential to exploit heterosis. Chemotype stability was achieved in some F1 hybrid lines, showing that seed-grown cannabinoid crops would be possible in some contexts using F1 hybrid methodology, paving the way for the validation of this breeding technique in field settings and highlighting a path toward commercial hybrid seed systems in C. sativa.

PMID:42170633 | PMC:PMC13188225 | DOI:10.1093/hr/uhag038

Categories
Nevin Manimala Statistics

Development of a High-Sensitivity Screening Tool for Neuropathic Pain Integrating PainDETECT and BS-POP Using Machine Learning

J Pain Res. 2026 May 16;19:594918. doi: 10.2147/JPR.S594918. eCollection 2026.

ABSTRACT

PURPOSE: Accurate identification of neuropathic pain (NeP) remains challenging in routine clinical practice. While PainDETECT is widely used, its sensitivity is limited by its focus on somatic symptoms. This study aimed to develop a high-sensitivity screening tool by integrating PainDETECT with the Brief Scale for Psychiatric Problems in Orthopaedic Patients (BS-POP) using machine learning.

PATIENTS AND METHODS: Neuropathic pain was diagnosed based on comprehensive clinical evaluation including medical history, neurological examination, and imaging findings when available. We analyzed clinical data from 1083 consecutive patients with pain. The study involved two phases: evaluation of conventional tools via statistical modeling and construction of a random forest-based classification model.

RESULTS: The proposed system achieved an overall accuracy of 75.6%. For NeP, the sensitivity was 70.3% and specificity was 86.0%, representing higher sensitivity compared with the conventional PainDETECT cutoff method (17.6%).

CONCLUSION: Integrating psychosocial factors via BS-POP and utilizing machine learning significantly enhances NeP screening performance. This system may support earlier and more appropriate pain management in clinical practice.

PMID:42170614 | PMC:PMC13189191 | DOI:10.2147/JPR.S594918

Categories
Nevin Manimala Statistics

Measurement of the 27Al+ and 87Sr absolute optical frequencies

Metrologia. 2021 Jan;58(1). doi: 10.1088/1681-7575/abd040.

ABSTRACT

We perform absolute measurement of the 27Al+ single-ion and 87Sr neutral lattice clock frequencies at the National Institute of Standards and Technology and JILA at the University of Colorado against a global ensemble of primary frequency standards. Over an eight month period multiple measurements yielded the mean optical atomic transition frequencies ν A l + = 1 121 015 393 207 859.50 ( 0.36 ) Hz and ν Sr = 429 228 004 229 873.19 ( 0.15 ) Hz , where the stated uncertainties are dominated by statistical noise and gaps in the observation interval (‘dead-time’ uncertainty).

PMID:42170611 | PMC:PMC13188837 | DOI:10.1088/1681-7575/abd040

Categories
Nevin Manimala Statistics

Association Between Furosemide and Risk of Parkinson’s Disease in a Nested Case-Control Study

Basic Clin Pharmacol Toxicol. 2026 Jun;138(6):e70249. doi: 10.1111/bcpt.70249.

ABSTRACT

A French signal detection study identified an association between sulfonamide diuretics use, particularly furosemide, and lower Parkinson’s disease (PD) risk. Our aim was to confirm this association in a Finnish nationwide nested case-control study (FINPARK), primarily in an indication-restricted case-control study of persons with heart or renal failure. Altogether 19 568 PD cases diagnosed in 1999-2015 and 130 156 age, sex and region-matched controls were included. The case-control study restricted to those with heart or renal failure included 1222 PD cases and 4766 matched controls. Furosemide use was identified from Prescription Register (1995-2015). The main analysis considered exposure at least 3 years before the matching date (3-year lag). Additional analyses with no lag, 5- and 8-year lags were conducted. Furosemide was not associated with PD risk (adjusted OR, 95% CI 1.00, 0.87-1.15 for user-non-user comparison with 3-year lag). A statistically significant borderline association between higher exposure levels and lower PD risk was observed in comparing risk across categories of cumulative furosemide exposure (adjusted OR, 95% CI 0.80, 0.64-1.00 with 3-year lag). Our nationwide indication-restricted case-control study of persons with PD found no robust evidence on the association between furosemide use and PD risk. However, there was suggestive evidence of reduced risk for participants in the highest exposure category.

PMID:42168783 | DOI:10.1111/bcpt.70249

Categories
Nevin Manimala Statistics

Statistical analyses of morphological variations of three Larroussius (Diptera: Psychodidae) sister species collected in leishmaniasis endemic foci of Adana in Turkiye

Med Vet Entomol. 2026 May 21. doi: 10.1111/mve.70086. Online ahead of print.

ABSTRACT

Sand flies are arthropod vectors responsible for transmitting Leishmania parasites to humans. Among them, Phlebotomus (P.) major, P. syriacus and P. neglectus are closely related sister species that play an important role in disease transmission in Türkiye. This study aimed to statistically analyse the morphological measurements of these three species and to identify reliable diagnostic characters. Seven morphometric traits were measured in both female and male specimens. Statistical analyses, including analysis of variance (ANOVA), discriminant function analysis (DFA) and principal component analysis (PCA), were performed to determine significant variables contributing to species differentiation. A total of 1729 sand flies were collected, comprising P. tobbi (44.58%), P. papatasi (21.26%), P. similis (20.30%), P. neglectus (8.50%), P. major (2.88%), P. syriacus (2.19%) and Sergentomyia (S.) fallax (0.27%). The female-to-male ratio was 1.42. ANOVA revealed significant interspecific differences (p < 0.001) in antennal, pharyngeal and genital characters. In females, P. neglectus exhibited shorter antennal segments A3 and A4 + A5, P. syriacus had the shortest pharynx (PHX), and P. major showed the longest epipharynx (EPI). In males, P. major had the longest coxite (CX), whereas P. neglectus displayed the shortest second style segment (S2) (p < 0.05). DFA confirmed clear species separation, with antennal and pharyngeal traits primarily driving differentiation in females, and genital characters being most informative in males. PCA explained 78.37% and 90.24% of the total morphometric variation in females and males, respectively, highlighting sex-specific patterns of morphological variation. Overall, these statistically supported morphometric differences provide robust diagnostic features that can complement molecular approaches, improving species identification and enhancing taxonomic resolution in sand fly vector studies.

PMID:42168762 | DOI:10.1111/mve.70086