Tag: nevin manimala

Eur J Cardiothorac Surg. 2023 Sep 15:ezad319. doi: 10.1093/ejcts/ezad319. Online ahead of print.

ABSTRACT

OBJECTIVES: Sublobar resection, including wedge resection and segmentectomy, is non-inferior to lobectomy in early-stage non-small cell lung cancer (NSCLC) treatment. We aimed to compare the risk of postoperative cognitive dysfunction (POCD) between sublobar resection and lobectomy.

METHODS: We conducted a prospective cohort study. Patients with sublobar resection or lobectomy were divided into sublobar group or lobar group, respectively. Cognition was assessed before and after surgery with Montreal Cognitive Assessment (MoCA) and Minimum Mental State Examination (MMSE) tests. POCD is defined as Z score of MoCA change≤-1.96. Propensity score matching (PSM) was performed to make demographics well-balanced between the two groups.

RESULTS: A total of 335 patients were enrolled. Both the postoperative 1-day POCD rate (sublobar 5.5% vs lobar 18.2%, P < 0.001) and the postoperative 1-month POCD rate (sublobar 7.9% vs lobar 21.8%, P < 0.001) were significantly lower in the sublobar group compared with lobar group, with demographics unbalanced between the two groups. In the 133 demographics-matched pairs obtained by propensity score matching (PSM), both the postoperative 1-day POCD rate (sublobar 5.3% vs lobar 17.3%, P = 0.005) and the postoperative 1-month POCD rate (sublobar 8.3% vs lobar 18.8%, P = 0.018) remained significantly lower in the sublobar group than lobar group. The incidences of postoperative 1-day (P = 0.109) and postoperative 1-month (P = 0.026) MMSE abnormity were also lower in the sublobar group than lobar group but only the latter was with statistical significance after PSM.

CONCLUSIONS: Sublobar resection has an advantage over lobectomy in preventing POCD. Our findings might be a reference for selecting the most suitable type of resection for NSCLC patients.

PMID:37713465 | DOI:10.1093/ejcts/ezad319

PLoS Genet. 2023 Sep 15;19(9):e1010940. doi: 10.1371/journal.pgen.1010940. Online ahead of print.

ABSTRACT

The unknown pathogenicity of a significant number of variants found in cancer-related genes is attributed to limited epidemiological data, resulting in their classification as variant of uncertain significance (VUS). To date, Breast Cancer gene-2 (BRCA2) has the highest number of VUSs, which has necessitated the development of several robust functional assays to determine their functional significance. Here we report the use of a humanized-mouse embryonic stem cell (mESC) line expressing a single copy of the human BRCA2 for a CRISPR-Cas9-based high-throughput functional assay. As a proof-of-principle, we have saturated 11 codons encoded by BRCA2 exons 3, 18, 19 and all possible single-nucleotide variants in exon 13 and multiplexed these variants for their functional categorization. Specifically, we used a pool of 180-mer single-stranded donor DNA to generate all possible combination of variants. Using a high throughput sequencing-based approach, we show a significant drop in the frequency of non-functional variants, whereas functional variants are enriched in the pool of the cells. We further demonstrate the response of these variants to the DNA-damaging agents, cisplatin and olaparib, allowing us to use cellular survival and drug response as parameters for variant classification. Using this approach, we have categorized 599 BRCA2 variants including 93-single nucleotide variants (SNVs) across the 11 codons, of which 28 are reported in ClinVar. We also functionally categorized 252 SNVs from exon 13 into 188 functional and 60 non-functional variants, demonstrating that saturation genome editing (SGE) coupled with drug sensitivity assays can enhance functional annotation of BRCA2 VUS.

PMID:37713444 | DOI:10.1371/journal.pgen.1010940

PLoS Comput Biol. 2023 Sep 15;19(9):e1011460. doi: 10.1371/journal.pcbi.1011460. Online ahead of print.

ABSTRACT

Machine learning has played transformative roles in numerous chemical and biophysical problems such as protein folding where large amount of data exists. Nonetheless, many important problems remain challenging for data-driven machine learning approaches due to the limitation of data scarcity. One approach to overcome data scarcity is to incorporate physical principles such as through molecular modeling and simulation. Here, we focus on the big potassium (BK) channels that play important roles in cardiovascular and neural systems. Many mutants of BK channel are associated with various neurological and cardiovascular diseases, but the molecular effects are unknown. The voltage gating properties of BK channels have been characterized for 473 site-specific mutations experimentally over the last three decades; yet, these functional data by themselves remain far too sparse to derive a predictive model of BK channel voltage gating. Using physics-based modeling, we quantify the energetic effects of all single mutations on both open and closed states of the channel. Together with dynamic properties derived from atomistic simulations, these physical descriptors allow the training of random forest models that could reproduce unseen experimentally measured shifts in gating voltage, ∆V1/2, with a RMSE ~ 32 mV and correlation coefficient of R ~ 0.7. Importantly, the model appears capable of uncovering nontrivial physical principles underlying the gating of the channel, including a central role of hydrophobic gating. The model was further evaluated using four novel mutations of L235 and V236 on the S5 helix, mutations of which are predicted to have opposing effects on V1/2 and suggest a key role of S5 in mediating voltage sensor-pore coupling. The measured ∆V1/2 agree quantitatively with prediction for all four mutations, with a high correlation of R = 0.92 and RMSE = 18 mV. Therefore, the model can capture nontrivial voltage gating properties in regions where few mutations are known. The success of predictive modeling of BK voltage gating demonstrates the potential of combining physics and statistical learning for overcoming data scarcity in nontrivial protein function prediction.

PMID:37713443 | DOI:10.1371/journal.pcbi.1011460

J Am Podiatr Med Assoc. 2023 Jul-Aug;113(4):21-077. doi: 10.7547/21-077.

ABSTRACT

BACKGROUND: Bibliometric studies in the field of orthopedics have increased because of the large volume of the available literature that prevents understanding the general status of the related field. This study aimed to identify and analyze the 100 most-cited articles related to flatfoot to reveal their characteristics and research trends.

METHODS: Available literature on the Web of Science database until the end of 2020 were analyzed, and the 100 most-cited articles were determined. The characteristics of articles including publication year, authors, institutions, country, journal, number of pages, number of references, study design, level of evidence, main topic, age group, the specialty of the first author, and availability of funding were extracted and statistically analyzed for any association with the number of citations or citation density.

RESULTS: The average citation number was 63.1 ± 43.8 (range, 30-278). The average citation density was 3.4 ± 1.8 (range, 0.8-12.6). The United States was the leading country with 65 articles, followed by Taiwan and the United Kingdom with five articles from each. Twenty-six papers had Level III evidence and 36 papers had Level IV evidence. Only three studies had Level I evidence and three had Level II evidence. The majority of articles (43 papers) were published in Foot & Ankle International. Citation density was positively correlated with publication year (P < .001) and the number of references (P = .004).

CONCLUSIONS: The available data provide general characteristics of the 100 most influential papers about flatfoot. The vast majority of papers had a low level of evidence, indicating the need for higher quality research.

PMID:37713413 | DOI:10.7547/21-077

PLoS One. 2023 Sep 15;18(9):e0291125. doi: 10.1371/journal.pone.0291125. eCollection 2023.

ABSTRACT

INTRODUCTION: The liver, the most important metabolic organ of the body, performs a wide variety of vital functions. Hepatic cell injury occurs by the activation of reactive oxygen species (ROS) that are generated by carbon tetrachloride (CCl4), xenobiotics, and other toxic substances through cytochrome P450-dependent steps resulting from the covalent bond formation with lipoproteins and nucleic acids. Observing the urgent state of hepatotoxic patients worldwide, different medicinal plants and their properties can be explored to combat such free radical damage to the liver. In vivo and in silico studies were designed and conducted to evaluate the antioxidant and hepatoprotective properties of Gynura procumbens in rats.

MATERIALS AND METHODS: Gynura procumbens leaves were collected and extracted using 70% ethanol. The required chemicals CCl4, standard drug (silymarin), and blood serum analysis kits were stocked. The in vivo tests were performed in 140 healthy Wister albino rats of either sex under well-controlled parameters divided into 14 groups, strictly maintaining Institutional Animal Ethics Committee (IEAC) protocols. For the histopathology study, 10% buffered neutral formalin was used for organ preservation. Later the specimens were studied under a fluorescence microscope. In silico molecular docking and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies were performed, and the results were analyzed statistically.

RESULTS AND DISCUSSION: Gynura procumbens partially negate the deleterious effect of carbon tetrachloride on normal weight gain in rats. The elevated level of serum glutamate pyruvate transaminase (SGPT), serum glutamate oxaloacetate transaminase (SGOT), alkaline phosphatase (ALP), creatinine, LDH, total cholesterol (TC), low-density lipoprotein (LDL), triglycerides (TG), malondialdehyde (MDA), deoxyribonucleic acid (DNA) fragmentation ranges, gamma-glutamyl transferase (γ-GT) in CCl4 treated groups were decreased by both standard drug silymarin and G. procumbens leaf extract. We have found significant & highly significant changes statistically for different doses, here p<0.05 & p<0.01, respectively. On the other hand, G. procumbens and silymarin displayed Statistically significant (p<0.05) and high significant(p<0.01) increased levels of HDL, CAT SOD (here p<0.05 & p<0.01 for different doses) when the treatment groups were compared with the disease control group. Because the therapeutic activity imparted by plants and drugs accelerates the movement of the disturbed pathophysiological state toward the healthy state. In the molecular docking analysis, G. procumbens phytoconstituents performed poorly against transforming growth factor-beta 1 (TGF-β1) compared to the control drug silymarin. In contrast, 26 phytoconstituents scored better than the control bezafibrate against peroxisome proliferator-activated receptor alpha (PPAR-α). The top scoring compounds for both macromolecules were observed to form stable complexes in the molecular dynamics simulations. Flavonoids and phenolic compounds performed better than other constituents in providing hepatoprotective activity. It can, thus, be inferred that the extract of G. procumbens showed good hepatoprotective properties in rats.

PMID:37713406 | DOI:10.1371/journal.pone.0291125

PLoS One. 2023 Sep 15;18(9):e0291600. doi: 10.1371/journal.pone.0291600. eCollection 2023.

ABSTRACT

BACKGROUND: The cochlear implant (CI) has proven to be a successful treatment for patients with severe-to-profound sensorineural hearing loss, however outcome variance exists. We sought to evaluate particular mutations discovered in previously established sensory and neural partition genes and compare post-operative CI outcomes.

MATERIALS AND METHODS: Utilizing a prospective cohort study design, blood samples collected from adult patients with non-syndromic hearing loss undergoing CI were tested for 54 genes of interest with high-throughput sequencing. Patients were categorized as having a pathogenic variant in the sensory partition, pathogenic variant in the neural partition, pathogenic variant in both sensory and neural partition, or with no variant identified. Speech perception performance was assessed pre- and 12 months post-operatively. Performance measures were compared to genetic mutation and variant status utilizing a Wilcoxon rank sum test, with P<0.05 considered statistically significant.

RESULTS: Thirty-six cochlear implant patients underwent genetic testing and speech understanding measurements. Of the 54 genes that were interrogated, three patients (8.3%) demonstrated a pathogenic mutation in the neural partition (within TMPRSS3 genes), one patient (2.8%) demonstrated a pathogenic mutation in the sensory partition (within the POU4F3 genes). In addition, 3 patients (8.3%) had an isolated neural partition variance of unknown significance (VUS), 5 patients (13.9%) had an isolated sensory partition VUS, 1 patient (2.8%) had a variant in both neural and sensory partition, and 23 patients (63.9%) had no mutation or variant identified. There was no statistically significant difference in speech perception scores between patients with sensory or neural partition pathogenic mutations or VUS. Variable performance was found within patients with TMPRSS3 gene mutations.

CONCLUSION: The impact of genetic mutations on post-operative outcomes in CI patients was heterogenous. Future research and dissemination of mutations and subsequent CI performance is warranted to elucidate exact mutations within target genes providing the best non-invasive prognostic capability.

PMID:37713394 | DOI:10.1371/journal.pone.0291600

PLOS Digit Health. 2023 Sep 15;2(9):e0000339. doi: 10.1371/journal.pdig.0000339. eCollection 2023 Sep.

ABSTRACT

Timely interventions have a proven benefit for people experiencing psychotic illness. One bottleneck to accessing timely interventions is the referral process to the specialist team for early psychosis (STEP). Many general practitioners lack awareness or confidence in recognising psychotic symptoms or state. Additionally, referrals for people without apparent psychotic symptoms, although beneficial at a population level, lead to excessive workload for STEPs. There is a clear unmet need for accurate stratification of STEPs users and healthy cohorts. Here we propose a new approach to addressing this need via the application of digital behavioural tests. To demonstrate that digital behavioural tests can be used to discriminate between the STEPs users (SU; n = 32) and controls (n = 32, age and sex matched), we compared performance of five different classifiers applied to objective, quantitative and interpretable features derived from the ‘mirror game’ (MG) and trail making task (TMT). The MG is a movement coordination task shown to be a potential socio-motor biomarker of schizophrenia, while TMT is a neuropsychiatric test of cognitive function. All classifiers had AUC in the range of 0.84-0.92. The best of the five classifiers (linear discriminant classifier) achieved an outstanding performance, AUC = 0.92 (95%CI 0.75-1), Sensitivity = 0.75 (95%CI 0.5-1), Specificity = 1 (95%CI 0.75-1), evaluated on 25% hold-out and 1000 folds. Performance of all analysed classifiers is underpinned by the large effect sizes of the differences between the cohorts in terms of the features used for classification what ensures generalisability of the results. We also found that MG and TMT are unsuitable in isolation to successfully differentiate between SU with and without at-risk-mental-state or first episode psychosis with sufficient level of performance. Our findings show that standardised batteries of digital behavioural tests could benefit both clinical and research practice. Including digital behavioural tests into healthcare practice could allow precise phenotyping and stratification of the highly heterogenous population of people referred to STEPs resulting in quicker and more personalised diagnosis. Moreover, the high specificity of digital behavioural tests could facilitate the identification of more homogeneous clinical high-risk populations, benefiting research on prognostic instruments for psychosis. In summary, our study demonstrates that cheap off-the-shelf equipment (laptop computer and a leap motion sensor) can be used to record clinically relevant behavioural data that could be utilised in digital mental health applications.

PMID:37713385 | DOI:10.1371/journal.pdig.0000339

PLoS One. 2023 Sep 15;18(9):e0291139. doi: 10.1371/journal.pone.0291139. eCollection 2023.

ABSTRACT

BACKGROUND: The cancer registry system is an important part of the cancer control program. Improper coding of cancers leads to misclassification and incorrect statistical information about cancer. Therefore, in this study, the main objective of the qualitative analysis was the accuracy in assigning the codes to the pathological reports in the centers responsible for cancer registry.

METHODS: This study was descriptive, retrospective and applied. The data source in this study included 15,659 pathology reports received during the years 2017-2019 in the population-based cancer registry centers of Mazandaran province. Out of 1800 reports, 1765 samples of reports were selected and analysis was done on them by stratified random sampling method. A researcher-made checklist was used to collect data, and the Kappa agreement coefficient and Cohen’s agreement percentage were presented to check the accuracy of the reports. STATA13 was used for data analysis.

RESULTS: 1150 of 1765 pathology reports (65.0%), did not have a topographic, morphological and behavioral codes and 410 (23.2%) had grade codes. The Kappa coefficient in reports with a topography code was 0.916 and with a morphology code it was 0.929, respectively. In behavior coding, the highest agreement is in the category of benign cancers at 65.2% and in grade coding in the category without grade is 100%.

CONCLUSION: The most reports were on carcinoma morphology, and the Kappa coefficient in morphology codes has almost complete reliability. In terms of behavior coding, there was the most agreement in the category of benign cancers. The Kappa coefficient in given behavior codes has low reliability.

PMID:37713374 | DOI:10.1371/journal.pone.0291139

PLoS One. 2023 Sep 15;18(9):e0290838. doi: 10.1371/journal.pone.0290838. eCollection 2023.

ABSTRACT

Climate change is one of the most relevant challenges that the world has to deal with. Studies that aim to understand the behavior of environmental and atmospheric variables and the way they relate to each other can provide helpful insights into how the climate is changing. However, such studies are complex and rarely found in the literature, especially in dealing with data from the Brazilian territory. In this paper, we analyze four environmental and atmospheric variables, namely, wind speed, radiation, temperature, and humidity, measured in 27 Weather Stations (the capital of each of the 26 Brazilian states plus the federal district). We use the detrended fluctuation analysis to evaluate the statistical self-affinity of the time series, as well as the cross-correlation coefficient ρDCCA to quantify the long-range cross-correlation between stations, and a network analysis that considers the top 10% ρDCCA values to represent the cross-correlations between stations better. The methodology used in this paper represents a step forward in the field of hybrid methodologies, combining time series and network analysis that can be applied to other regions, other environmental variables, and also to other fields of research. The application results are of great importance to better understand the behavior of environmental and atmospheric variables in the Brazilian territory and to provide helpful insights about climate change and renewable energy production.

PMID:37713368 | DOI:10.1371/journal.pone.0290838

PLoS One. 2023 Sep 15;18(9):e0290727. doi: 10.1371/journal.pone.0290727. eCollection 2023.

ABSTRACT

Quality control (QC) is a systematic approach to ensuring that products and services meet customer requirements. It is an essential part of manufacturing and industry, as it helps to improve product quality, customer satisfaction, and profitability. Quality practitioners generally apply control charts to monitor the industrial process, among many other statistical process control tools, and to detect changes. New developments in control charting schemes for high-quality monitoring are the need of the hour. In this paper, we have enhanced the performance of the mixed homogeneously weighted moving average (HWMA)-cumulative sum (CUSUM) control chart by using the auxiliary information-based (AIB) regression estimator and named it MHCAIB. The proposed MHCAIB chart provided an unbiased and more efficient estimator of the process location. The various measures of the run length are used to judge the performance of the proposed MHCAIB and to compare it with existing AIB charts like CUSUMAIB, EWMAAIB, MECAIB (mixed AIB EWMA-CUSUM), and HWMAAIB. The Run length (RL) based performance comparisons indicate that the MHCAIB chart performs relatively better in monitoring small to moderate shifts over its competitor’s charts. It is shown that the chart’s performance improves with the increase in correlation between the study variable and the auxiliary variable. An illustrative application of the proposed MHCAIB chart is also provided to show its implementation in practical situations.

PMID:37713367 | DOI:10.1371/journal.pone.0290727