Tag: nevin manimala

Sci Rep. 2022 May 4;12(1):7243. doi: 10.1038/s41598-022-11296-4.

ABSTRACT

Knee osteoarthritis (OA) is the most prevalent type of OA, and Toll-like receptor 7 (TLR7) may lead to the pathogenesis of OA. Recently, X-linked TLR7 polymorphism has been confirmed to be associated with arthritis. However, there is a lack of studies on TLR7 gene polymorphism associated with knee OA susceptibility. The current study aimed to determine whether TLR7 gene polymorphism is associated with the risk of knee OA. Genotyping of two polymorphic sites (rs3853839 and rs179010) in the TLR7 gene was performed in 252 OA patients, and 265 healthy controls using the SNaPshot sequencing technique. Data were analyzed statistically by Chi-square tests and logistic regression. Rs3853839-C allele showed frequencies of 28% and 27% in the healthy control and female knee OA groups, respectively. The differences were not statistically significant (P > 0.05). The rs3853839-CG genotype frequency was significantly lower in the female knee OA group as compared to the healthy control group (OR 0.60; 95%CI 0.36-0.99; P = 0.044). In the male hemizygote population, the rs3853839-CC showed significantly lower frequencies in the male knee OA group as compared to the healthy control group (OR 0.35; 95%CI 0.17-0.71; P = 0.0025). Regarding rs179010, there were no differences in the genotype distribution and allele frequencies between OA patients and healthy subjects under any models (P > 0.05). Stratified analysis showed that the frequency of the rs3853839-CG genotypes was lower in high Kellgren-Lawrence grades (KLG) (OR 0.48; 95%CI 0.21-1.08; P = 0.066), and significantly lower in OA patients with effusion synovitis (OR 0.38; 95%CI 0.17-0.88; P = 0.013). TLR7 rs3853839 polymorphism may play a role in the susceptibility of knee OA in the Chinese Han Population and may be associated with OA severity and the risk of effusion synovitis in Knee OA.

PMID:35508687 | DOI:10.1038/s41598-022-11296-4

Risk Anal. 2022 May 4. doi: 10.1111/risa.13937. Online ahead of print.

ABSTRACT

While children are one of the groups at risk in disasters, they can also take an active part in disaster management, provided that the opportunity is given. This research examined the effect of disaster experience, disaster education, country, and city socioeconomic status on children’s perceived risk and preparedness with a survey of 1335 children between 11 and 14 years old, in Nepal and Turkey. The survey used questionnaires and the pictorial representation of illness and self measure (PRISM) tool. Results showed that (1) children’s risk perceptions were in line with their country-specific objective risks; (2) there were differences between the countries in relation to perception of risk for all the hazards except wildfire; (3) socioeconomic status had a statistically significant effect on children’s perceptions of risk and preparedness for earthquakes, wildfires, that is, children who live in wealthier places had higher perceived risk and preparedness; (4) children in both countries showed similar trends in their knowledge of the correct protective actions to take in the event of a hazard occurrence. However, there is still room to enhance children’s knowledge, in terms of safety behaviors, as the children selected many incorrect protective actions. There are important implications in terms of child-centered disaster management which hopefully will make life safer and help to create more resilience to disaster in society as a whole.

PMID:35508707 | DOI:10.1111/risa.13937

J Gastrointest Surg. 2022 May 4. doi: 10.1007/s11605-022-05332-x. Online ahead of print.

ABSTRACT

BACKGROUND: Procedure-specific complications can have devastating consequences. Machine learning-based tools have the potential to outperform traditional statistical modeling in predicting their risk and guiding decision-making. We sought to develop and compare deep neural network (NN) models, a type of machine learning, to logistic regression (LR) for predicting anastomotic leak after colectomy, bile leak after hepatectomy, and pancreatic fistula after pancreaticoduodenectomy (PD).

METHODS: The colectomy, hepatectomy, and PD National Surgical Quality Improvement Program (NSQIP) databases were analyzed. Each dataset was split into training, validation, and testing sets in a 60/20/20 ratio, with fivefold cross-validation. Models were created using NN and LR for each outcome. Models were evaluated primarily with area under the receiver operating characteristic curve (AUROC).

RESULTS: A total of 197,488 patients were included for colectomy, 25,403 for hepatectomy, and 23,333 for PD. For anastomotic leak, AUROC for NN was 0.676 (95% 0.666-0.687), compared with 0.633 (95% CI 0.620-0.647) for LR. For bile leak, AUROC for NN was 0.750 (95% CI 0.739-0.761), compared with 0.722 (95% CI 0.698-0.746) for LR. For pancreatic fistula, AUROC for NN was 0.746 (95% CI 0.733-0.760), compared with 0.713 (95% CI 0.703-0.723) for LR. Variables related to intra-operative information, such as surgical approach, biliary reconstruction, and pancreatic gland texture were highly important for model predictions.

DISCUSSION: Machine learning showed a marginal advantage over traditional statistical techniques in predicting procedure-specific outcomes. However, models that included intra-operative information performed better than those that did not, suggesting that NSQIP procedure-targeted datasets may be strengthened by including relevant intra-operative information.

PMID:35508684 | DOI:10.1007/s11605-022-05332-x

Sci Rep. 2022 May 4;12(1):7216. doi: 10.1038/s41598-022-10902-9.

ABSTRACT

Infertility is a significant health problem and assisted reproductive technologies to treat infertility. Despite all efforts, the success rate of these methods is still low. Also, each of these methods has side effects and costs. Therefore, accurate prediction of treatment success rate is a clinical challenge. This retrospective study aimed to internally validate and compare various machine learning models for predicting the clinical pregnancy rate (CPR) of infertility treatment. For this purpose, data from 1931 patients consisting of in vitro fertilization (IVF) or intra cytoplasmic sperm injection (ICSI) (733) and intra uterine insemination (IUI) (1196) treatments were included. Also, no egg or sperm donation data were used. The performance of machine learning algorithms to predict clinical pregnancy were expressed in terms of accuracy, recall, F-score, positive predictive value (PPV), brier score (BS), Matthew correlation coefficient (MCC), and receiver operating characteristic. The significance of the features with CPR and AUCs was evaluated by Student’s t test and DeLong’s algorithm. Random forest (RF) model had the highest accuracy in the IVF/ICSI treatment. The sensitivity, F1 score, PPV, and MCC of the RF model were 0.76, 0.73, 0.80, and 0.5, respectively. These values for IUI treatment were 0.84, 0.80, 0.82, and 0.34, respectively. The BS was 0.13 and 0.15 for IVF/ICS and IUI, respectively. In addition, the estimated AUCs of the RF model for IVF/ICS and IUI were 0.73 and 0.7, respectively. Some essential features were obtained based on RF ranking for the two datasets, including age, follicle stimulation hormone, endometrial thickness, and infertility duration. The results showed a strong relationship between clinical pregnancy and a woman’s age. Also, endometrial thickness and the number of follicles decreased with increasing female age in both treatments.

PMID:35508641 | DOI:10.1038/s41598-022-10902-9

Sci Rep. 2022 May 4;12(1):7295. doi: 10.1038/s41598-022-10459-7.

ABSTRACT

Conventional Vector Autoregressive (VAR) modelling methods applied to high dimensional neural time series data result in noisy solutions that are dense or have a large number of spurious coefficients. This reduces the speed and accuracy of auxiliary computations downstream and inflates the time required to compute functional connectivity networks by a factor that is at least inversely proportional to the true network density. As these noisy solutions have distorted coefficients, thresholding them as per some criterion, statistical or otherwise, does not alleviate the problem. Thus obtaining a sparse representation of such data is important since it provides an efficient representation of the data and facilitates its further analysis. We propose a fast Sparse Vector Autoregressive Greedy Search (SVARGS) method that works well for high dimensional data, even when the number of time points is relatively low, by incorporating only statistically significant coefficients. In numerical experiments, our methods show high accuracy in recovering the true sparse model. The relative absence of spurious coefficients permits accurate, stable and fast evaluation of derived quantities such as power spectrum, coherence and Granger causality. Consequently, sparse functional connectivity networks can be computed, in a reasonable time, from data comprising tens of thousands of channels/voxels. This enables a much higher resolution analysis of functional connectivity patterns and community structures in such large networks than is possible using existing time series methods. We apply our method to EEG data where computed network measures and community structures are used to distinguish emotional states as well as to ADHD fMRI data where it is used to distinguish children with ADHD from typically developing children.

PMID:35508638 | DOI:10.1038/s41598-022-10459-7

Nat Commun. 2022 May 4;13(1):2454. doi: 10.1038/s41467-022-30102-3.

ABSTRACT

Liver gene therapy with adeno-associated viral (AAV) vectors delivering clotting factor transgenes into hepatocytes has shown multiyear therapeutic benefit in adults with hemophilia. However, the mostly episomal nature of AAV vectors challenges their application to young pediatric patients. We developed lentiviral vectors, which integrate in the host cell genome, that achieve efficient liver gene transfer in mice, dogs and non-human primates, by intravenous delivery. Here we first compare engineered coagulation factor VIII transgenes and show that codon-usage optimization improved expression 10-20-fold in hemophilia A mice and that inclusion of an unstructured XTEN peptide, known to increase the half-life of the payload protein, provided an additional >10-fold increase in overall factor VIII output in mice and non-human primates. Stable nearly life-long normal and above-normal factor VIII activity was achieved in hemophilia A mouse models. Overall, we show long-term factor VIII activity and restoration of hemostasis, by lentiviral gene therapy to hemophilia A mice and normal-range factor VIII activity in non-human primate, paving the way for potential clinical application.

PMID:35508619 | DOI:10.1038/s41467-022-30102-3

J Card Surg. 2022 May 4. doi: 10.1111/jocs.16500. Online ahead of print.

ABSTRACT

OBJECTIVE: The prevalence of coronary artery fistula (CAF) based on coronary angiography has been reported. However, with the popularity of coronary computerized tomography angiography (CTA), CAFs have been found more and more by chance. The purpose of this study was to determine the prevalence and types of CAFs detected by coronary CTA, and to explore the differences in the size of fistulas, the number of complicated aneurysms, and fistulas among different types.

MATERIALS AND METHODS: From January 2016 to December 2020, 96,037 patients underwent coronary CTA in our hospital. The prevalence of CAF was retrospectively evaluated, The origin, course, and drainage site of CAF and coexisting abnormalities were analysed. The conventional treatments and follow-up DSCT images were also evaluated. Analyze the difference between the coronary-pulmonary artery fistula (CPAFs) group (380) and the coronary-cameral fistula (CCF) group (99).

RESULTS: Among 96,037 patients, 482 (0.5%) patients (male 232 and 250 female) had CAF. The types of CAF detected. The pulmonary artery was the most common site of drainage (380/482, 78.8%). Of the 99 CCFs, coronary to the left ventricle is the most common pattern in CCF (34/482, 7.0%). Single origins are more common in CAF (n = 361, 74.9%), multiple origins are more common in CPAFs than in CCF. There were statistically significant differences in the stoma diameter (2.4 ± 1.1 mm vs. 5.4 ± 4.3 mm p < .05), aneurysm complicated (85 cases [85/380] vs. 50 cases [50/99]), the size of aneurysm (8.8 ± 5.7 mm vs. 19.1 ± 11.6 mm, p < .05), and single fistula (261 [261/380] vs. 96 [96/99], p < .05). Most of the 380 CPAFs patients received conservative treatment (350/380, 92.1%), While the 59 CCF patients (59/93, 63.4%) were treated.

CONCLUSIONS: Different from previous reports, the prevalence of CAF in coronary CTA is 0.5%, the incidence of CPAFs is the highest, and the incidence of the left ventricular fistula is higher in CCF. Compared with CPAFs, CCF fistulas were more likely to be associated with a larger diameter of draining, larger aneurysms, single fistula pattern. Coronary artery CTA is a useful and noninvasive imaging method to detect CAF, which is of great significance for the detection of small fistulas and the surgical guidance of complex CAF.

PMID:35508600 | DOI:10.1111/jocs.16500

Sci Rep. 2022 May 4;12(1):7285. doi: 10.1038/s41598-022-11215-7.

ABSTRACT

The usability of a Web Based Library System (WBLS) is an important quality attribute that must be met in order for the intended users to be satisfied. These usability quality attributes are available in two forms: general to web systems and domain-specific. It must be evaluated through some evaluation method such as checklist. Many evaluation checklists have been proposed, although they mostly facilitate the evaluation of WBLS’s general usability aspects, but they lack in covering domain-specific usability aspects of WBLS. There is a need to define domain specific usability aspects to maximize the usability for such systems. The purpose of this research is to develop and validates a usability evaluation checklist that supports the evaluation of general as well as specific usability aspects of WBLS. To accomplish this, a control experiment was conducted in the first phase with undergraduate students to develop a usability evaluation checklist that includes both general and specific usability aspects. Another controlled experiment will be used in the second phase to evaluate the effectiveness and efficiency of the proposed checklist with the existing checklist as “Academic Library Website Evaluation Checklist”. The manual and statistical result shows that, the proposed usability evaluation checklist is effective with maximum coverage of general and specific usability aspects. Furthermore, the proposed checklist is equally efficient while identifying the usability errors in WBLS. The proposed checklist is beneficial for the academia as well as industry to evaluate the usability of WBLS to an optimal level.

PMID:35508578 | DOI:10.1038/s41598-022-11215-7

Sci Rep. 2022 May 4;12(1):7299. doi: 10.1038/s41598-022-10711-0.

ABSTRACT

Nitrification, a key pathway of nitrogen (N) loss from agricultural soils, is performed by ammonia-oxidizing bacteria (AOB) and archaea (AOA). We examined the seasonal dynamics (2 years) of ammonia oxidizer gene abundances across a gradient of soil carbon (C) and N in a semi-arid soil after 8 years of tillage and crop residue treatments. AOB was more dominant than AOA in the surface soil, as AOA were undetected in 96% of samples. Seasonal variation in AOB abundance was related to substrate availability; AOB gene copy numbers increased at the end of the growing season (during summer fallow) following higher concentrations in dissolved organic matter soil water. This suggests increased co-location between AOB and substrate resources in pores still filled with water as the soils dried. AOB was however not statistically related to soil ammonium concentrations, soil water content, rainfall or temperature. Organic matter inputs enhanced AOB abundance independent of seasonal variation. AOB abundance was greatest in autumn and immediately preceding the start of the growing season, and coincided with elevated soil nitrate concentrations. The growth of the AOB population is likely to contribute to increased risk of N loss through leaching and/or denitrification at the start of the crop growing season following summer fallow.

PMID:35508560 | DOI:10.1038/s41598-022-10711-0

Sci Rep. 2022 May 4;12(1):7308. doi: 10.1038/s41598-022-11184-x.

ABSTRACT

Children born very preterm are at significant risk of neurodevelopmental impairment. This study sought to identify differences in cognitive function in children born very preterm compared to term-born controls and investigate alteration in white matter microstructure and functional connectivity (FC) based on tract-based spatial statistics (TBSS) and resting-state functional MRI, respectively. At 6 years of age, 36 children born very preterm (< 32 weeks’ gestation) without major neurological disabilities and 26 term-born controls were tested using the Wechsler Intelligence Scale for Children, 4th edition, and Child Behavior Checklist. Whole-brain deterministic tractography and FC measurements were performed in both groups. The very preterm group had significantly lower intelligence scores than the term-born controls. The TBSS revealed no significant differences between the two groups, whereas FC was significantly increased between the frontoparietal network and the language network and was significantly decreased between the right salience network nodes in the very preterm group. The altered FC patterns between specific regions of the higher-order networks may reflect underlying deficits in the functional network architecture associated with cognitive function. Further studies are needed to demonstrate a direct connection between FC in these regions and cognitive function.

PMID:35508563 | DOI:10.1038/s41598-022-11184-x