Category: Nevin Manimala

Proc Natl Acad Sci U S A. 2024 Jan 16;121(3):e2309825120. doi: 10.1073/pnas.2309825120. Epub 2024 Jan 8.

ABSTRACT

The impact of sexual selection on the evolution of birds has been widely acknowledged. Although sexual selection has been hypothesized as a driving force in the occurrences of numerous morphological features across theropod evolution, this hypothesis has yet to be comprehensively tested due to challenges in identifying the sex of fossils and by the limited sample size. Confuciusornis sanctus is arguably the best-known early avialan and is represented by thousands of well-preserved specimens from the Early Cretaceous Jehol lagerstätte, which provides us with a chance to decipher the strength of sexual selection on extinct vertebrates. Herein, we present a morphometric study of C. sanctus based on the largest sample size of this taxon collected up to now. Our results indicate that the characteristic elongated paired rectrices is a sexually dimorphic trait and statistically robust inferences of the sexual dimorphism in size, shape, and allometry that have been established, providing the earliest known sexual dimorphism in avian evolution. Our findings suggest that sexual selection, in conjunction with natural selection, does act upon body size and limb length ratio in early birds, thereby promoting a deeper understanding of the role of sexual selection in large-scale phylogenetic evolution.

PMID:38190528 | DOI:10.1073/pnas.2309825120

Proc Natl Acad Sci U S A. 2024 Jan 16;121(3):e2315857121. doi: 10.1073/pnas.2315857121. Epub 2024 Jan 8.

ABSTRACT

Epstein-Barr virus (EBV) infection has long been associated with multiple sclerosis (MS), but the role of EBV in the pathogenesis of MS is not clear. Our hypothesis is that a major fraction of the expanded clones of T lymphocytes in the cerebrospinal fluid (CSF) are specific for autologous EBV-infected B cells. We obtained blood and CSF samples from eight relapsing-remitting patients in the process of diagnosis. We stimulated cells from the blood with autologous EBV-infected lymphoblastoid cell lines (LCL), EBV, varicella zoster virus, influenza, and candida and sorted the responding cells with flow cytometry after 6 d. We sequenced the RNA for T cell receptors (TCR) from CSF, unselected blood cells, and the antigen-specific cells. We used the TCR Vβ CDR3 sequences from the antigen-specific cells to assign antigen specificity to the sequences from the CSF and blood. LCL-specific cells comprised 13.0 ± 4.3% (mean ± SD) of the total reads present in CSF and 13.3 ± 7.5% of the reads present in blood. The next most abundant antigen specificity was flu, which was 4.7 ± 1.7% of the reads in the CSF and 9.3 ± 6.6% in the blood. The prominence of LCL-specific reads was even more marked in the top 1% most abundant CSF clones with statistically significant 47% mean overlap with LCL. We conclude that LCL-specific sequences form a major portion of the TCR repertoire in both CSF and blood and that expanded clones specific for LCL are present in MS CSF. This has important implications for the pathogenesis of MS.

PMID:38190525 | DOI:10.1073/pnas.2315857121

Proc Natl Acad Sci U S A. 2024 Jan 23;121(4):e2309881120. doi: 10.1073/pnas.2309881120. Epub 2024 Jan 8.

ABSTRACT

Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

PMID:38190514 | DOI:10.1073/pnas.2309881120

Med Phys. 2024 Jan 8. doi: 10.1002/mp.16905. Online ahead of print.

ABSTRACT

BACKGROUND: Delta radiomics is a high-throughput computational technique used to describe quantitative changes in serial, time-series imaging by considering the relative change in radiomic features of images extracted at two distinct time points. Recent work has demonstrated a lack of prognostic signal of radiomic features extracted using this technique. We hypothesize that this lack of signal is due to the fundamental assumptions made when extracting features via delta radiomics, and that other methods should be investigated.

PURPOSE: The purpose of this work was to show a proof-of-concept of a new radiomics paradigm for sparse, time-series imaging data, where features are extracted from a spatial-temporal manifold modeling the time evolution between images, and to assess the prognostic value on patients with oropharyngeal cancer (OPC).

METHODS: To accomplish this, we developed an algorithm to mathematically describe the relationship between two images acquired at time $t=0$ and $t>0$ . These images serve as boundary conditions of a partial differential equation describing the transition from one image to the other. To solve this equation, we propagate the position and momentum of each voxel according to Fokker-Planck dynamics (i.e., a technique common in statistical mechanics). This transformation is driven by an underlying potential force uniquely determined by the equilibrium image. The solution generates a spatial-temporal manifold (3 spatial dimensions + time) from which we define dynamic radiomic features. First, our approach was numerically verified by stochastically sampling dynamic Gaussian processes of monotonically decreasing noise. The transformation from high to low noise was compared between our Fokker-Planck estimation and simulated ground-truth. To demonstrate feasibility and clinical impact, we applied our approach to ¹⁸ F-FDG-PET images to estimate early metabolic response of patients (n = 57) undergoing definitive (chemo)radiation for OPC. Images were acquired pre-treatment and 2-weeks intra-treatment (after 20 Gy). Dynamic radiomic features capturing changes in texture and morphology were then extracted. Patients were partitioned into two groups based on similar dynamic radiomic feature expression via k-means clustering and compared by Kaplan-Meier analyses with log-rank tests (p < 0.05). These results were compared to conventional delta radiomics to test the added value of our approach.

RESULTS: Numerical results confirmed our technique can recover image noise characteristics given sparse input data as boundary conditions. Our technique was able to model tumor shrinkage and metabolic response. While no delta radiomics features proved prognostic, Kaplan-Meier analyses identified nine significant dynamic radiomic features. The most significant feature was Gray-Level-Size-Zone-Matrix gray-level variance (p = 0.011), which demonstrated prognostic improvement over its corresponding delta radiomic feature (p = 0.722).

CONCLUSIONS: We developed, verified, and demonstrated the prognostic value of a novel, physics-based radiomics approach over conventional delta radiomics via data assimilation of quantitative imaging and differential equations.

PMID:38190505 | DOI:10.1002/mp.16905

Adv Mater. 2024 Jan 8:e2310282. doi: 10.1002/adma.202310282. Online ahead of print.

ABSTRACT

Acquisition of defect-free transition metal dichalcogenides (TMDs) channels with clean heterojunctions has been a critical issue in production of TMD-based functional electronic devices. Conventional approaches have synthesized high quality TMDs and transferred them onto a target substrate, and then applied the typical device fabrication processes. Unfortunately, those processes cause physical defects and chemical contamination in the TMD channels. Here, we propose a novel synthetic process of TMD thin films, named confined interfacial chalcogenization (CIC). In the proposed synthesis, a uniform TMD layer is created at the Au/transition metal (TM) interface by diffusion of chalcogen through the grain boundaries of the Au layer and reaction of chalcogen with the underlying TM. CIC allows for ultraclean heterojunctions with the metals, rapid synthesis of homo- and hetero-structured TMDs, and in-situ TMD channel formation in the last stage of device fabrication. We reveal the mechanism of TMD growth by the TM-accelerated chalcogen diffusion, epitaxial growth of TMD on Au(111), and dependence of the growth rate on material species of chalcogen and TM. We demonstrate a 100% production yield of TMD-based vertical memristors which exhibit excellent statistical concordance in device performance enabled by the ultraclean heterojunctions and superior uniformity in thickness and chemical composition. CIC proposed in this study represents a breakthrough in the synthesis of TMD thin films and also in the TMD-based electronic device fabrication, marking a substantial step towards practical next-generation integrated electronics. This article is protected by copyright. All rights reserved.

PMID:38190458 | DOI:10.1002/adma.202310282

PLoS Genet. 2024 Jan 8;20(1):e1010155. doi: 10.1371/journal.pgen.1010155. Online ahead of print.

ABSTRACT

Introgression is a common evolutionary phenomenon that results in shared genetic material across non-sister taxa. Existing statistical methods such as Patterson’s D statistic can detect introgression by measuring an excess of shared derived alleles between populations. The D statistic is effective to detect genome-wide patterns of introgression but can give spurious inferences of introgression when applied to local regions. We propose a new statistic, D+, that leverages both shared ancestral and derived alleles to infer local introgressed regions. Incorporating both shared derived and ancestral alleles increases the number of informative sites per region, improving our ability to identify local introgression. We use a coalescent framework to derive the expected value of this statistic as a function of different demographic parameters under an instantaneous admixture model and use coalescent simulations to compute the power and precision of D+. While the power of D and D+ is comparable, D+ has better precision than D. We apply D+ to empirical data from the 1000 Genome Project and Heliconius butterflies to infer local targets of introgression in humans and in butterflies.

PMID:38190420 | DOI:10.1371/journal.pgen.1010155

PLOS Glob Public Health. 2024 Jan 8;4(1):e0002328. doi: 10.1371/journal.pgph.0002328. eCollection 2024.

ABSTRACT

Health workers are essential for a functioning healthcare system, and their own health is often not addressed. During the COVID-19 pandemic health workers were at high risk of SARS-CoV-2 infection whilst coping with increased healthcare demand. Here we report the development, implementation, and uptake of an integrated health check combining SARS-CoV-2 testing with screening for other communicable and non-communicable diseases for health workers in Zimbabwe during the COVID-19 pandemic. Health checks were offered to health workers in public and private health facilities from July 2020 to June 2022. Data on the number of health workers accessing the service and yield of screening was collected. Workshops and in-depth interviews were conducted to explore the perceptions and experiences of clients and service providers. 6598 health workers across 48 health facilities accessed the service. Among those reached, 5215 (79%) were women, the median age was 37 (IQR: 29-44) years and the largest proportion were nurses (n = 2092, 32%). 149 (2.3%) healthcare workers tested positive for SARS-CoV-2. Uptake of screening services was almost 100% for all screened conditions except HIV. The most common conditions detected through screening were elevated blood pressure (n = 1249; 19%), elevated HbA1c (n = 428; 7.7%) and common mental disorder (n = 645; 9.8%). Process evaluation showed high acceptability of the service. Key enablers for health workers accessing the service included free and comprehensive service provision, and availability of reliable point-of-care screening methods. Implementation of a comprehensive health check for health workers was feasible, acceptable, and effective, even during a pandemic. Conventional occupational health programmes focus on infectious diseases. In a society where even health workers cannot afford health care, free comprehensive occupational health services may address unmet needs in prevention, diagnosis, and treatment for chronic non-communicable conditions.

PMID:38190397 | DOI:10.1371/journal.pgph.0002328

JMIR Form Res. 2024 Jan 8;8:e46364. doi: 10.2196/46364.

ABSTRACT

BACKGROUND: Prior suicide attempts are a relatively strong risk factor for future suicide attempts. There is growing interest in using longitudinal electronic health record (EHR) data to derive statistical risk prediction models for future suicide attempts and other suicidal behavior outcomes. However, model performance may be inflated by a largely unrecognized form of “data leakage” during model training: diagnostic codes for suicide attempt outcomes may refer to prior attempts that are also included in the model as predictors.

OBJECTIVE: We aimed to develop an automated rule for determining when documented suicide attempt diagnostic codes identify distinct suicide attempt events.

METHODS: From a large health care system’s EHR, we randomly sampled suicide attempt codes for 300 patients with at least one pair of suicide attempt codes documented at least one but no more than 90 days apart. Supervised chart reviewers assigned the clinical settings (ie, emergency department [ED] versus non-ED), methods of suicide attempt, and intercode interval (number of days). The probability (or positive predictive value) that the second suicide attempt code in a given pair of codes referred to a distinct suicide attempt event from its preceding suicide attempt code was calculated by clinical setting, method, and intercode interval.

RESULTS: Of 1015 code pairs reviewed, 835 (82.3%) were nonindependent (ie, the 2 codes referred to the same suicide attempt event). When the second code in a pair was documented in a clinical setting other than the ED, it represented a distinct suicide attempt 3.3% of the time. The more time elapsed between codes, the more likely the second code in a pair referred to a distinct suicide attempt event from its preceding code. Code pairs in which the second suicide attempt code was assigned in an ED at least 5 days after its preceding suicide attempt code had a positive predictive value of 0.90.

CONCLUSIONS: EHR-based suicide risk prediction models that include International Classification of Diseases codes for prior suicide attempts as a predictor may be highly susceptible to bias due to data leakage in model training. We derived a simple rule to distinguish codes that reflect new, independent suicide attempts: suicide attempt codes documented in an ED setting at least 5 days after a preceding suicide attempt code can be confidently treated as new events in EHR-based suicide risk prediction models. This rule has the potential to minimize upward bias in model performance when prior suicide attempts are included as predictors in EHR-based suicide risk prediction models.

PMID:38190236 | DOI:10.2196/46364

JMIR Mhealth Uhealth. 2024 Jan 8;12:e49302. doi: 10.2196/49302.

ABSTRACT

BACKGROUND: The World Health Organization has called for addressing the growing burden of noncommunicable diseases (NCDs) by promoting healthy lifestyles among the population. Regarding patient health, primary care professionals (PCPs) are the first line of care who can positively influence patients’ behavior and lifestyle habits. However, a significant percentage of PCPs do not lead a healthy lifestyle. Therefore, addressing their health behaviors may be the key to substantially increasing health promotion advice in general practice. The Mediterranean diet has been extensively studied, and there is strong evidence of it being a dietary pattern for the prevention of NCDs, in addition to its significant environmental, sociocultural, and local economics benefits.

OBJECTIVE: This study focused only on the dietary aspect of the PCPs’ lifestyle. The primary objective was to evaluate the effect of using the Electronic 12-Hour Dietary Recall (e-12HR) smartphone app to improve diet, specifically to promote adherence to the Mediterranean diet (AMD), among PCPs. The secondary objectives were to establish the usability of the e-12HR app and to determine AMD among PCPs.

METHODS: An individual-level randomized, controlled, and single-blind clinical trial was conducted with 2 parallel groups: a control group (CG), using the nonfeedback version of the e-12HR app, and an intervention group (IG), using the feedback version of the e-12HR app. The level of human involvement was fully automated through the use of the app. There was a 28-day follow-up period. Participants were PCPs (medicine or nursing) recruited offline at one of the selected primary care centers (Andalusia, Spain, Southern Europe), of both sexes, over 18 years old, possessing a smartphone, and having smartphone literacy.

RESULTS: The study response rate was 73% (71 of 97 PCPs), with 27 (38%) women and 44 (62%) men: 40 (56%) PCPs in the CG and 31 (44%) in the IG. At baseline, AMD was medium (mean Mediterranean Diet Serving Score [MDSS] index 9.45, range 0-24), with 47 (66%) PCPs with a medium/high MDSS index. There were significant statistical improvements (CG vs IG, in favor of the IG) at week 4 (no significant statistical differences at baseline): +25.6% for the MDSS index (P=.002) and +213.1% for the percentage with a medium/high MDSS index (P=.001). In relation to specific food groups, there were significant statistical improvements for fruits (+33.8%, P=.02), vegetables (+352%, P=.001), nuts (+184%, P=.02), and legumes (+75.1%, P=.03). The responses to the usability rating questionnaire were satisfactory.

CONCLUSIONS: The results support recommending the use of the e-12HR app as a tool to contribute to improving diet and preventing NCDs among PCPs, while positively influencing patient dietary behavior and preventing diet-related NCDs among patients.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05532137; https://clinicaltrials.gov/study/NCT05532137.

PMID:38190226 | DOI:10.2196/49302

Anesthesiology. 2024 Jan 8. doi: 10.1097/ALN.0000000000004894. Online ahead of print.

ABSTRACT

INTRODUCTION: Severe traumatic brain injury (TBI) is a leading cause of morbidity and mortality among young people around the world. Prehospital care focusses on the prevention and treatment of secondary brain injury and commonly includes tracheal intubation after induction of general anesthesia. The choice of induction agent in this setting is controversial. We therefore investigated the association between the chosen induction medication etomidate versus S(+)-ketamine , and the 30-day mortality in patients with severe TBI who received prehospital airway management in the Netherlands.

METHODS: We conducted a retrospective analysis of the prospectively collected observational data of the BRAIN-PROTECT cohort study. Patients with suspected severe TBI, who were transported to a participating trauma center and who received etomidate or S(+)-ketamine for prehospital induction of anesthesia for advanced airway management were included. Statistical analyses were performed with multivariable logistic regression and Inverse Probability of Treatment Weighting analysis.

RESULTS: In total, 1457 patients were eligible for analysis. No significant association between the administered induction medication and 30-day mortality was observed in unadjusted analyses (etomidate 32.9% mortality versus S(+)-ketamine 33.8% mortality, p= 0.716, OR 1.04, 95% CI 0.83 to 1.32, p= 0.711) as well as after adjustment for potential confounders (OR 1.08, 95% CI 0.67 to 1.73, p= 0.765; risk difference 0.017, 95% CI -0.051 to 0.084, p= 0.686). Likewise, in planned subgroup analyses for patients with confirmed TBI and patients with isolated TBI, no significant differences were found. Consistent results were found after multiple imputation of missing data.

CONCLUSIONS: We found no evidence for an association between the use of etomidate or S(+)-ketamine as an anesthetic agent for intubation in patients with TBI and mortality after 30 days in the prehospital setting, suggesting that the choice of induction agent may not influence patient mortality rate in this population.

PMID:38190220 | DOI:10.1097/ALN.0000000000004894