Tag: nevin manimala

Phys Rev Lett. 2026 Jul 17;137(3):033201. doi: 10.1103/g865-9mk1.

ABSTRACT

We report high-precision frequency ratio measurements between optical atomic clocks based on ^{27}Al^{+}, ^{171}Yb, and ^{87}Sr. With total fractional uncertainties at or below 3.2×10^{-18}, these measurements meet an important milestone criterion for redefinition of the second in the International System of Units. Discrepancies in ^{87}Sr ratios at approximately 1×10^{-16} and the Al^{+}/Yb ratio at 1.6×10^{-17} in fractional units compared to our previous measurements underscore the importance of repeated, high-precision comparisons by different laboratories. A key upgrade from our previous work is the use of a common ultrastable reference delivered to all clocks via a 3.6-km phase-stabilized fiber link between two institutions, enabling better accuracy and stability in frequency transfer. Derived from a cryogenic single-crystal silicon cavity, this reference improves comparison stability by a factor of 2-3 over previous systems, with an optical lattice clock ratio achieving a fractional instability of 1.3×10^{-16} at 1 s. Identifying individual clock stabilities with a three-corner-hat measurement, we demonstrate the most stable optical lattice and trapped-ion clocks used in a multispecies comparison. By enabling faster comparisons, this stability will improve sensitivity to nonwhite noise processes and other underlying limits of state-of-the-art optical frequency standards.

PMID:42537076 | DOI:10.1103/g865-9mk1

Phys Rev Lett. 2026 Jul 17;137(3):037102. doi: 10.1103/jkn8-h939.

ABSTRACT

We experimentally study a system of N=4 two-dimensional Brownian particles, each confined in a harmonic trap with identical stiffness. The stiffness switches simultaneously between two values at random Poissonian times. This collective switching drives the system into a nonequilibrium stationary state with strong long-range correlations between the positions of the particles. Remarkably, we find that, despite the presence of hydrodynamic interactions between the particles mediated by the surrounding fluid, the statistics of some observables are insensitive to hydrodynamic interactions and are well described by the noninteracting theory. Comparing with exact theoretical predictions for noninteracting particles, we observe excellent agreement between theory and experiments for three such observables, namely, the correlations between particles, extreme value, and order statistics (maxima, minima, and ranked positions) and the full counting statistics (i.e., the distribution of the number of particles in a finite interval [-L,L] around the trap center).

PMID:42537064 | DOI:10.1103/jkn8-h939

Phys Rev Lett. 2026 Jul 17;137(3):031803. doi: 10.1103/6f6r-51br.

ABSTRACT

The time-dependent CP asymmetry in B^{0}→J/ψρ(770)^{0} decays is measured using proton-proton collision data corresponding to an integrated luminosity of 6 fb^{-1}, collected with the LHCb detector at a center-of-mass energy of 13 TeV during the years 2015-2018. The CP-violation parameters for this process are determined to be 2β_{cc[over ¯]d}^{eff}=0.710±0.084±0.051 rad and |λ|=1.019±0.034±0.024, where the first uncertainty is statistical and the second systematic. This constitutes the first observation of time-dependent CP violation in B^{0}→J/ψρ(770)^{0} decays. Assuming approximate SU(3) flavor symmetry, these results are combined with the previous consistent LHCb measurement to set the most stringent constraint on the penguin contribution, Δϕ_{s}, to the CP-violating phase ϕ_{s} in B_{s}^{0}→J/ψϕ(1020) decays, yielding Δϕ_{s}=5.0±4.6 mrad.

PMID:42537061 | DOI:10.1103/6f6r-51br

Niger J Physiol Sci. 2026 Jun 30;41(1):17-27.

ABSTRACT

Hypertension is a prevalent disease globally and its prevalence is rising in sub-Saharan Africa. Urban-rural differences in the prevalence of hypertension are under-reported in Nigeria. Though hypertension is known to be related to obesity, the nature of the relationship is still unclear. This study sought to interrogate these and thus enrolled a total of 1,755 subjects (59% females) from five states in the old Eastern Region of Nigeria. Standard protocols and definitions were used to take measurements and diagnose relevant disease states. Appropriate statistical tools were used for data analysis. The results indicate that prehypertension was found in 40.0% of males and 27.5% of females while hypertension was found in 19.1% of males and 18.6% of females. The prevalence of (pre)hypertension among urban and rural males were similar (19%). However, prehypertension was more prevalent among urban females (29.1% Vs 24.3%); while hypertension was more prevalent among rural females (21.9% Vs 17.1%). SBP was found to be positively and significantly correlated with weight, waist circumference, hip circumference, waist-to-height ratio and body mass index in the general population. When disaggregated based on blood pressure phenotypes, the correlations were found to be consistent mostly among normotensive subjects and among females. Among subjects with (pre)hypertension, the correlations varied in strength and direction depending on sex and measure of adiposity used. The urban-rural difference in the prevalence of hypertension and the relationship between hypertension and obesity are not linear.

PMID:42537033

JMIR Cardio. 2026 Jul 31;10:e92930. doi: 10.2196/92930.

ABSTRACT

Synthetic data offer significant potential for cardiology research by enabling data sharing, preserving privacy, and supporting machine learning model development. By generating artificial patient records that reflect real-world distributions, synthetic data can accelerate clinical research, improve model performance for rare cardiovascular conditions, and facilitate transnational collaborations that would otherwise be restricted by data-sharing barriers. Despite these advantages, the increasing use of synthetic data raises important ethical, regulatory, and methodological concerns that remain insufficiently addressed. Key challenges include assessing the validity and generalizability of synthetic datasets, understanding their limitations in representing complex and heterogeneous patient populations, and preventing the amplification of existing biases in cardiovascular care. Current regulatory frameworks, including the General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA), do not fully address emerging risks such as reidentification and data leakage, and there is no harmonized guidance to govern the use of synthetic data as stand-alone evidence for medical device evaluation or therapeutic research. In this viewpoint, we argue that responsible integration of synthetic data in cardiology requires, first, clear differentiation between synthetic data as a privacy-preserving distributional substitute and synthetic data as a counterfactual simulation tool, and, second, fit-for-purpose governance frameworks that pair rigorous utility and fidelity testing with explicit, adversary-aware privacy evaluation before synthetic cohorts are accepted as evidence in research or product evaluation. A prerequisite for that governance is conceptual clarity about what synthetic data are being used for. Synthetic data in health care serve 2 fundamentally distinct roles that carry entirely different validity requirements, failure modes, and regulatory implications, yet they are routinely conflated. The first role is as a privacy-preserving distributional substitute: the goal is statistical fidelity to the real data distribution, so that analyses of the synthetic dataset yield results equivalent to those of the original. The second role is as a tool for counterfactual simulation: the goal is to generate data that could not have been observed, such as rare conditions, hypothetical interventions, or extrapolations to new populations. These 2 roles are methodologically distinct. A dataset that accurately reflects real-world distributions may be inadequate for extrapolating findings to underrepresented subgroups. Conversely, a simulator optimized for novel scenario generation may systematically diverge from real-world distributions. This distinction informs every subsequent discussion of validity, bias, and regulation in this viewpoint and our proposed 4 concrete actions for the cardiology research community, including mandatory 3-layer (fidelity, utility, and privacy) validation, systematic subgroup reporting, explicit intended-use scoping, and domain-specific acceptability thresholds for synthetic data-based evidence.

PMID:42537019 | DOI:10.2196/92930

Int J Oral Maxillofac Implants. 2026 Jul 31;0(0):1-25. doi: 10.11607/jomi.11696. Online ahead of print.

ABSTRACT

PURPOSE: Healthy peri-implant soft tissues are essential for implant longevity. Low-level laser therapy (LLLT) has emerged as a promising additional approach for enhancing wound healing after implant surgery, but evidence remains inconsistent. This study evaluates the clinical, radiographic, and inflammatory effects of LLLT on peri-implant soft tissue healing, pain, inflammatory biomarkers, and marginal bone preservation following implant placement.

MATERIALS AND METHODS: This randomized, controlled, single-blinded trial included 272 adults requiring single-tooth implants. Participants were randomized to two equal groups, LLLT (n=136) or control (n=136). The intervention involved daily 810 nm diode laser irradiation for five days post-surgery. Outcomes assessed included pain (VAS), healing clinical indices, oral health-related quality of life (OHIP-14), marginal bone loss (MBL), and peri-implant crevicular fluid biomarkers. Statistical analysis was conducted using SPSS software with mixed-effects models adjusted for baseline imbalances.

RESULTS: Among 272 participants, baseline demographics and comorbidities were comparable (all p>0.23 and p≥0.658, respectively). LLLT significantly reduced pain scores across all follow-ups (0.35-1.21 points lower, partial η²=0.783) and improved healing indices, gingival inflammation, and bleeding scores compared to controls. The LLLT group demonstrated persistently lower peri-implant inflammatory markers (TNF-α) and higher angiogenic response (VEGF). Radiographic evaluation revealed less MBL in the LLLT group with 0.07-0.22 mm less than control after day 7. Additionally, patients reported improved oral-health-related quality of life.

CONCLUSION: LLLT enhances peri-implant wound healing, reduces pain and inflammation, and preserves marginal bone, suggesting its value as a minimally invasive adjunct to implant therapy.

PMID:42537018 | DOI:10.11607/jomi.11696

Int J Oral Maxillofac Implants. 2026 Jul 31;0(0):1-21. doi: 10.11607/jomi.11841. Online ahead of print.

ABSTRACT

PURPOSE: This study compared the effects of local and systemic calcitriol administration on bone regeneration in a xenograft-based rabbit maxillary sinus augmentation model.

MATERIALS AND METHODS: Eighteen New Zealand rabbits were randomly assigned to three groups (n = 6 per group at baseline): control (xenograft only), local calcitriol (xenograft hydrated with 0.1 µg/kg calcitriol per sinus), and systemic calcitriol (single intravenous dose of 0.2 µg/kg). After 10 weeks, histomorphological scoring, RT-qPCR quantification of VEGF and BMP-2, and serum 25(OH)D measurements were performed.

RESULTS: Osteoblast activity was significantly higher in the local calcitriol group than in the control group (p = 0.024). Ossification scores showed a numerical trend toward higher values in the local group but did not reach statistical significance (p = 0.061). VEGF and BMP-2 expression were approximately 17.2-fold and 29.3-fold higher in the local group compared with controls (Bonferroni-corrected p < 0.001 for both); the systemic group showed intermediate expression without reaching corrected significance. Serum 25(OH)D levels showed no significant between-group differences at any time point.

CONCLUSIONS: Local calcitriol delivery was associated with significantly greater osteoblast activity and VEGF and BMP-2 expression, along with a non-significant trend toward higher ossification scores. Local application via routine graft hydration may represent a practical, low-cost strategy to enhance bone regeneration without systemic exposure, warranting confirmation in larger clinical studies.

PMID:42537017 | DOI:10.11607/jomi.11841

J Med Internet Res. 2026 Jul 31;28:e93378. doi: 10.2196/93378.

ABSTRACT

BACKGROUND: Sleep apnea (SA) is a serious sleep disorder, and its diagnostic gold standard, polysomnography, is costly and time-consuming. Electroencephalogram (EEG) signals, due to their direct correlation with neural activity and ease of extraction, represent a promising tool. Despite increasing research on machine learning (ML) and deep learning for EEG-based SA detection, model performance has not been consistently evaluated.

OBJECTIVE: This systematic review evaluated the accuracy of ML in detecting SA from EEG data and provided an evidence base for further clinical application and future research.

METHODS: Following the PRISMA-DTA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 expanded checklists, we systematically searched PubMed, Embase, Web of Science, Cochrane Library (CENTRAL), Scopus, IEEE Xplore, and ClinicalTrials.gov databases from inception to April 2026. Studies evaluating the value of ML algorithms for detecting SA based only on EEG data were included. The Quality Assessment of Diagnostic Accuracy Studies-2 and Prediction Model Risk of Bias Assessment Tool for Artificial Intelligence tools were used to assess the risk of bias in each study. Statistical analysis was performed using the mada and metafor packages in R (version 4.6.0; R Foundation for Statistical Computing) and the Meta-DiSc (version 1.4; Hospital Ramón y Cajal) software. We used GRADE (Grading of Recommendations Assessment, Development and Evaluation) to evaluate the certainty of evidence.

RESULTS: A total of 27 retrospective studies were included. Segment-level analyses showed high diagnostic performance, with a pooled sensitivity of 0.90 (95% CI 0.85-0.94; 95% prediction interval 0.43-0.99) and specificity of 0.92 (95% CI 0.87-0.95; 95% prediction interval 0.46-0.99). The pooled area under the summary receiver operating characteristic curve was 0.95 (95% CI 0.92-0.99). Meta-regression identified EEG channel configuration, region, and validation strategy as significant sources of heterogeneity (P=.004, P=.003, and P=.046, respectively). Multichannel EEG, deep learning approaches, and hold-out validation strategies generally demonstrated better diagnostic performance. Only 2 studies evaluated patient-level diagnostic performance, which was summarized qualitatively.

CONCLUSIONS: To our knowledge, this is the first systematic review and meta-analysis specifically focused on the diagnostic accuracy of EEG-based ML models in the detection of SA. This meta-analysis indicates that ML models based on EEG demonstrate good diagnostic accuracy in detecting SA at the segment level and show promise as tools for SA screening and clinical decision support. However, most current studies are retrospective segment-level analyses, which may overestimate the practical value of this technology in real-world clinical settings. To reliably integrate EEG-based ML models into clinical diagnostic workflows, further prospective studies incorporating full-night monitoring and patient-level validation are needed.

PMID:42537009 | DOI:10.2196/93378

J Med Entomol. 2026 Jul 1;63(4):tjag127. doi: 10.1093/jme/tjag127.

ABSTRACT

Tunga penetrans (Linnaeus, 1758) (Siphonaptera: Tungidae) is an ectoparasitic flea whose adult females cause tungiasis by embedding into the host’s skin. Environmental, social and financial challenges in tungiasis endemic areas have left this disease neglected and lacking locally available control measures. One possible approach for controlling T. penetrans targets its off-host stages; however, surveillance tools for adult fleas are still lacking. Moreover, host-seeking cues and behaviour of adult T. penetrans remain largely unknown. In this study, we show that visual cues are attractive to adult T. penetrans. Newly emerged T. penetrans responded to light stimuli across a broad spectrum, ranging from 375 nm to 690 nm. Within this range, significantly stronger attraction was observed at 430 nm over 375 nm, at 490 nm over 610 nm, and at 610 nm over 690 nm. Attraction did not differ significantly between 430 nm and 490 nm or between 535 nm and 490 nm. Overall, wavelengths between 430-535 nm induced stronger attraction in both sexes under constant electrical current conditions. In contrast, although host odor and body temperature attracted more than half of the tested adult fleas on average, the observed responses were not statistically significant. These findings suggest that visual cues in this spectral range could serve as promising attractants for capturing adult fleas. Incorporating these insights into trap strategies could support improved monitoring, surveillance, and potentially contribute to control efforts.

PMID:42537008 | DOI:10.1093/jme/tjag127

Arch Clin Neuropsychol. 2026 Jul 31;41(6):acag057. doi: 10.1093/arclin/acag057.

ABSTRACT

OBJECTIVE: This cross-sectional study investigated the prevalence of adult Attention Deficit/Hyperactivity Disorder (ADHD) evaluations in an outpatient neuropsychology clinic and the sensitivity and specificity of neuropsychological assessments in differentiating ADHD with comorbid psychiatric conditions from psychiatric-related cognitive deficits.

METHOD: Logistic regression analyses were run on neuropsychological testing results extracted from medical records to evaluate each test’s ability to predict ADHD diagnosis. Receiver Operating Characteristic curves were plotted, and an Area Under the Curve (AUC) >0.7 was considered acceptable.

RESULTS: Sixty-seven of 252 reviewed charts were included (n = 30 with ADHD, n = 37 without ADHD). Overall, 54% of individuals presenting to the clinic were referred for ADHD, and 58% of those diagnosed with ADHD had a comorbid psychiatric disorder. No cognitive testing was predictive of ADHD diagnosis (AUC range: 0.503-0.636). The Generalized Anxiety Disorder-7 was the strongest predictive scale of ADHD (AUC = 0.800; χ2(28) = 8.216, p = .004, Nagelkerke R2 = 0.333). Adults who endorsed higher levels of anxiety were 28% more likely to be diagnosed with ADHD (OR = 1.28, 95%CI [0.05, 0.45]). Subtests of ADHD scales performed worse, but still within the adequate range (AUC range: 0.703-0.751). Sample demographics were notable for over-representation of women (n = 46, 69%), and they skewed White (n = 43, 64%) and highly educated (M years of education = 15.79, SD = 1.94), which may limit generalizability.

CONCLUSIONS: Cognitive testing profiles and screeners of current inattention and hyperactivity were indiscriminate between individuals with ADHD and comorbid psychiatric conditions versus psychiatric conditions alone. Current anxiety was the strongest predictor of adult ADHD diagnosis.

PMID:42537007 | DOI:10.1093/arclin/acag057