Tag: nevin manimala

Sci Rep. 2022 Apr 1;12(1):5516. doi: 10.1038/s41598-022-09396-2.

ABSTRACT

Depression and cardiovascular disease (CVD) are main contributors to the global disease burden and are linked. Pathophysiological pathways through increased blood pressure (BP) are a common focus in studies aiming to explain the relationship. However, studies to date have not differentiated between the predictive effect of depression on the course of BP versus hypertension diagnosis. Hence, we aimed to elucidate this relationship by incorporating these novel aspects in the context of a cohort study. We included initially normotensive participants (n = 3214) from the second (2001-2003), third (2009-2011), and fourth (2016-2018) waves of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). We defined depression based on physician diagnosis, depression treatment and/or SF-36 Mental Health score < 50. The prospective association between depression and BP change was quantified using multivariable censored regression models, and logistic regression for the association between depression and incident hypertension diagnosis. All models used clustered robust standard errors to account for repeat measurements. The age-related increase in systolic BP was slightly lower among people with depression at baseline (β = – 2.08 mmHg/10 years, 95% CI – 4.09 to – 0.07) compared to non-depressed. A similar trend was observed with diastolic BP (β = – 0.88 mmHg/10 years, 95% CI – 2.15 to 0.39), albeit weaker and not statistically significant. Depression predicted the incidence of hypertension diagnosis (OR 1.86, 95% CI 1.33 to 2.60). Our findings do not support the hypothesis that depression leads to CVD by increasing BP. Future research on the role of depression in the pathway to hypertension and CVD is warranted in larger cohorts, taking into account healthcare utilization as well as medication for depression and hypertension.

PMID:35365701 | DOI:10.1038/s41598-022-09396-2

Sci Rep. 2022 Apr 1;12(1):5508. doi: 10.1038/s41598-022-09421-4.

ABSTRACT

Mood disorders, including generalized anxiety disorder, are associated with disruptions in circadian rhythms and are linked to polymorphisms in circadian clock genes. Molecular mechanisms underlying these connections may be direct-via transcriptional activity of clock genes on downstream mood pathways in the brain, or indirect-via clock gene influences on the phase and amplitude of circadian rhythms which, in turn, modulate physiological processes influencing mood. Employing machine learning combined with statistical approaches, we explored clock genotype combinations that predict risk for anxiety symptoms in a deeply phenotyped population. We identified multiple novel circadian genotypes predictive of anxiety, with the PER3(rs17031614)-AG/CRY1(rs2287161)-CG genotype being the strongest predictor of anxiety risk, particularly in males. Molecular chronotyping, using clock gene expression oscillations, revealed that advanced circadian phase and robust circadian amplitudes are associated with high levels of anxiety symptoms. Further analyses revealed that individuals with advanced phases and pronounced circadian misalignment were at higher risk for severe anxiety symptoms. Our results support both direct and indirect influences of clock gene variants on mood: while sex-specific clock genotype combinations predictive of anxiety symptoms suggest direct effects on mood pathways, the mediation of PER3 effects on anxiety via diurnal preference measures and the association of circadian phase with anxiety symptoms provide evidence for indirect effects of the molecular clockwork on mood. Unraveling the complex molecular mechanisms underlying the links between circadian physiology and mood is essential to identifying the core clock genes to target in future functional studies, thereby advancing the development of non-invasive treatments for anxiety-related disorders.

PMID:35365695 | DOI:10.1038/s41598-022-09421-4

Sci Data. 2022 Apr 1;9(1):148. doi: 10.1038/s41597-022-01261-1.

ABSTRACT

Antibiotic resistance is a major threat to public health. The development of chemo-informatic tools to guide medicinal chemistry campaigns in the efficint design of antibacterial libraries is urgently needed. We present AB-DB, an open database of all-atom force-field parameters, molecular dynamics trajectories, quantum-mechanical properties, and curated physico-chemical descriptors of antimicrobial compounds. We considered more than 300 molecules belonging to 25 families that include the most relevant antibiotic classes in clinical use, such as β-lactams and (fluoro)quinolones, as well as inhibitors of key bacterial proteins. We provide traditional descriptors together with properties obtained with Density Functional Theory calculations. Noteworthy, AB-DB contains less conventional descriptors extracted from μs-long molecular dynamics simulations in explicit solvent. In addition, for each compound we make available force-field parameters for the major micro-species at physiological pH. With the rise of multi-drug-resistant pathogens and the consequent need for novel antibiotics, inhibitors, and drug re-purposing strategies, curated databases containing reliable and not straightforward properties facilitate the integration of data mining and statistics into the discovery of new antimicrobials.

PMID:35365662 | DOI:10.1038/s41597-022-01261-1

Sci Data. 2022 Apr 1;9(1):145. doi: 10.1038/s41597-022-01175-y.

ABSTRACT

During the second half of 2020, many European governments responded to the resurging transmission of SARS-CoV-2 with wide-ranging non-pharmaceutical interventions (NPIs). These efforts were often highly targeted at the regional level and included fine-grained NPIs. This paper describes a new dataset designed for the accurate recording of NPIs in Europe’s second wave to allow precise modelling of NPI effectiveness. The dataset includes interventions from 114 regions in 7 European countries during the period from the 1st August 2020 to the 9th January 2021. The paper includes NPI definitions tailored to the second wave following an exploratory data collection. Each entry has been extensively validated by semi-independent double entry, comparison with existing datasets, and, when necessary, discussion with local epidemiologists. The dataset has considerable potential for use in disentangling the effectiveness of NPIs and comparing the impact of interventions across different phases of the pandemic.

PMID:35365668 | DOI:10.1038/s41597-022-01175-y

Nat Commun. 2022 Apr 1;13(1):1733. doi: 10.1038/s41467-022-29391-5.

ABSTRACT

The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R_S), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and R_S are irreconcilable. When we estimate GPP based on R_S measurements and some assumptions about R_S:GPP ratios, we found the resulted global GPP values (bootstrap mean [Formula: see text] Pg C yr^-1) are significantly higher than most GPP estimates reported in the literature ([Formula: see text] Pg C yr^-1). Similarly, historical GPP estimates imply a soil respiration flux (Rs_GPP, bootstrap mean of [Formula: see text] Pg C yr^-1) statistically inconsistent with most published R_S values ([Formula: see text] Pg C yr^-1), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R_S:GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.

PMID:35365658 | DOI:10.1038/s41467-022-29391-5

Nat Commun. 2022 Apr 1;13(1):1738. doi: 10.1038/s41467-022-29463-6.

ABSTRACT

A hallmark of topological superconductivity is the non-Abelian statistics of Majorana bound states (MBS), its chargeless zero-energy emergent quasiparticles. The resulting fractionalization of a single electron, stored nonlocally as a two spatially-separated MBS, provides a powerful platform for implementing fault-tolerant topological quantum computing. However, despite intensive efforts, experimental support for MBS remains indirect and does not probe their non-Abelian statistics. Here we propose how to overcome this obstacle in mini-gate controlled planar Josephson junctions (JJs) and demonstrate non-Abelian statistics through MBS fusion, detected by charge sensing using a quantum point contact, based on dynamical simulations. The feasibility of preparing, manipulating, and fusing MBS in two-dimensional (2D) systems is supported in our experiments which demonstrate the gate control of topological transition and superconducting properties with five mini gates in InAs/Al-based JJs. While we focus on this well-established platform, where the topological superconductivity was already experimentally detected, our proposal to identify elusive non-Abelian statistics motivates also further MBS studies in other gate-controlled 2D systems.

PMID:35365644 | DOI:10.1038/s41467-022-29463-6

Blood Cancer J. 2022 Apr 1;12(4):53. doi: 10.1038/s41408-022-00648-y.

ABSTRACT

The objective of this study is to examine the association between neighborhood socioeconomic status (nSES) and baseline allostatic load (AL) and clinical trial endpoints in patients enrolled in the E1A11 therapeutic trial in multiple myeloma (MM). Study endpoints were symptom burden (pain, fatigue, and bother) at baseline and 5.5 months, non-completion of induction therapy, overall survival (OS) and progression-free survival (PFS). Multivariable logistic and Cox regression examined associations between nSES, AL and patient outcomes. A 1-unit increase in baseline AL was associated with greater odds of high fatigue at baseline (adjusted OR [95% CI] = 1.21 [1.08-1.36]) and a worse OS (adjusted hazard ratio, [95% CI] = 1.21 [1.06-1.37]). High nSES was associated with worse baseline bother (middle OR = 4.22 [1.11-16.09] and high 4.49 [1.16-17.43]) compared to low nSES. There was no association between AL or nSES and symptom burden at 5.5 months, non-completion of induction therapy or PFS. Additionally, there was no association between nSES and OS. AL may have utility as a predictive marker for OS among patients with MM and may allow individualization of treatment. Future studies should standardize and validate AL patients with MM.

PMID:35365604 | DOI:10.1038/s41408-022-00648-y

BDJ Open. 2022 Apr 1;8(1):9. doi: 10.1038/s41405-022-00101-z.

ABSTRACT

OBJECTIVES: Understanding of lifelong control of disease processes associated with caries and its management is an essential part of dental education. This study evaluated the dental students’ knowledge of caries diagnosis and management using the International Caries Classification and Management System (ICCMS).

METHODS: A survey was conducted among undergraduate dental students at two dental schools, attending the sixth (centre 1) and seventh semester (centre 2), respectively. Medical histories, clinical images and radiographs of 12 patients were compiled as anonymous cases. For each case, a specific lesion was to be assessed. In addition, the students should determine the patient’s caries risk and select a treatment option. An expert report (consensus decision) was used as the reference standard. For statistical analysis, kappa statistics and binomial tests were used.

RESULTS: A total of 46 students participated in this study. The percentage of agreement of responses to the reference was: centre 1: 40.7-51.3%, centre 2: 57.9-67.9%. The corresponding Kappa values were: centre 1: 0.073-0.175, centre 2: 0.315-0.432. Overall, students tended to underestimate the codes compared to the reference standard (p < 0.001).

CONCLUSION: Introducing systematic content about caries diagnosis and management such as ICDAS and ICCMS in the learning objectives of undergraduate dental students can be proposed. However, in order to improve diagnosis and enable a more reliable choice of treatment options, attention should also be given to the way they are didactically taught.

PMID:35365612 | DOI:10.1038/s41405-022-00101-z

Wound Repair Regen. 2022 Apr 1. doi: 10.1111/wrr.13005. Online ahead of print.

ABSTRACT

The objective of this study was to develop a pilot physician driven patient pyoderma gangrenosum (PG) registry to summarise patient baseline demographics, PG-related medical history, treatments, and outcomes for patients with pyoderma gangrenosum. Standardised patient information was collected prospectively during clinical encounters between December 2019 and July 2021 at a single academic institution. Eligibility criteria for the study was a diagnosis of pyoderma gangrenosum determined by a PARACELSUS score of at least 10 for ulcerative patients. Main outcome measures included demographic data, PG related history and comorbidities, past and current treatments, healing outcomes, hospitalisations and recurrences of PG. The Pyoderma Gangrenosum Study (PYGAS) Registry currently includes 52 patients with 56 target lesions of four distinct PG subtypes (41 ulcerative, 12 peristomal, 2 vegetative and 1 bullous). For the 38 patients with 41 total ulcerative PG lesions, referrals to our institution most commonly came from dermatologists (42.1%). The median follow-up time in our initial registry was 5.5 months (95% CI = 4.1-11.5 months), with average time between follow-up visits at 1.1 months. These ulcers were most commonly treated with first-line systemic immunosuppressants (70.6%), such as corticosteroids or cyclosporine. Additional use of systemic immunomodulators at baseline visit was statistically significantly associated with healing (P = 0.048). This pilot study suggests that use of systemic immunomodulators has an impact on healing of PG patients. Wound care regimens are variable, and assessing their impact on treatment outcomes could be challenging. Standardisation of both wound care regimens and data collection in prospective clinical studies is necessary to assess their impact in PG treatment outcomes.

PMID:35363927 | DOI:10.1111/wrr.13005

Cogn Sci. 2022 Apr;46(4):e13121. doi: 10.1111/cogs.13121.

ABSTRACT

The extraction of cooccurrences between two events, A and B, is a central learning mechanism shared by all species capable of associative learning. Formally, the cooccurrence of events A and B appearing in a sequence is measured by the transitional probability (TP) between these events, and it corresponds to the probability of the second stimulus given the first (i.e., p(B|A)). In the present study, nonhuman primates (Guinea baboons, Papio papio) were exposed to a serial version of the XOR (i.e., exclusive-OR), in which they had to process sequences of three stimuli: A, B, and C. In this manipulation, first-order TPs (i.e., AB and BC) were uninformative due to their transitional probabilities being equal to .5 (i.e., p(B|A) = p(C|B) = .5), while second-order TPs were fully predictive of the upcoming stimulus (i.e., p(C|AB) = 1). In Experiment 1, we found that baboons were able to learn second-order TPs, while no learning occurred on first-order TPs. In Experiment 2, this pattern of results was replicated, and a final test ruled out an alternative interpretation in terms of proximity to the reward. These results indicate that a nonhuman primate species can learn a nonlinearly separable problem such as the XOR. They also provide fine-grained empirical data to test models of statistical learning on the interaction between the learning of different orders of TPs. Recent bioinspired models of associative learning are also introduced as promising alternatives to the modeling of statistical learning mechanisms.

PMID:35363923 | DOI:10.1111/cogs.13121