Nevin Manimala

PLoS One. 2021 Aug 13;16(8):e0255637. doi: 10.1371/journal.pone.0255637. eCollection 2021.

ABSTRACT

The bandgap of two-dimensional (2D) materials plays an important role in their applications to various devices. For instance, the gapless nature of graphene limits the use of this material to semiconductor device applications, whereas the indirect bandgap of molybdenum disulfide is suitable for electrical and photo-device applications. Therefore, predicting the bandgap rapidly and accurately for a given 2D material structure has great scientific significance in the manufacturing of semiconductor devices. Compared to the extremely high computation cost of conventional first-principles calculations, machine learning (ML) based on statistics may be a promising alternative to predicting bandgaps. Although ML algorithms have been used to predict the properties of materials, they have rarely been used to predict the properties of 2D materials. In this study, we apply four ML algorithms to predict the bandgaps of 2D materials based on the computational 2D materials database (C2DB). Gradient boosted decision trees and random forests are more effective in predicting bandgaps of 2D materials with an R2 >90% and root-mean-square error (RMSE) of ~0.24 eV and 0.27 eV, respectively. By contrast, support vector regression and multi-layer perceptron show that R2 is >70% with RMSE of ~0.41 eV and 0.43 eV, respectively. Finally, when the bandgap calculated without spin-orbit coupling (SOC) is used as a feature, the RMSEs of the four ML models decrease greatly to 0.09 eV, 0.10 eV, 0.17 eV, and 0.12 eV, respectively. The R2 of all the models is >94%. These results show that the properties of 2D materials can be rapidly obtained by ML prediction with high precision.

PMID:34388173 | DOI:10.1371/journal.pone.0255637

PLoS One. 2021 Aug 13;16(8):e0255398. doi: 10.1371/journal.pone.0255398. eCollection 2021.

ABSTRACT

Stable isotope analyses of bone collagen are often used in palaeoecological studies to reveal environmental conditions in the habitats of different herbivore species. However, such studies require valuable reference data, obtained from analyses of modern individuals, in habitats of well-known conditions. In this article, we present the stable carbon and nitrogen isotope composition of bone collagen from modern red deer (N = 242 individuals) dwelling in various habitats (N = 15 study sites) in Europe. We investigated which of the selected climatic and environmental factors affected the δ13C and δ15N values in bone collagen of the studied specimens. Among all analyzed factors, the percent of forest cover influenced the carbon isotopic composition most significantly, and decreasing forest cover caused an increase in δ13C values. The δ15N was positively related to the proportion of open area and (only in the coastal areas) negatively related to the distance to the seashore. Using rigorous statistical methods and a large number of samples, we confirmed that δ13C and δ15N values can be used as a proxy of past habitats of red deer.

PMID:34388162 | DOI:10.1371/journal.pone.0255398

Zh Nevrol Psikhiatr Im S S Korsakova. 2021;121(7. Vyp. 2):94-98. doi: 10.17116/jnevro202112107294.

ABSTRACT

One of the leading symptoms in patients with multiple sclerosis (MS) is cognitive impairment. It often affects aspects of cognition such as learning ability, memory, processing speed, and attention. It has been proven that patients often complain of difficulties in multitasking and choosing the right words. These problems are often underestimated. Various studies show that regular physical activity, mainly aerobic exercise, can potentially improve cognitive function. Positive effects on concentration, memory, and multitasking were described. In March 2019, the Tyumen regional center of MS, together with the clinical Institute of the brain (Yekaterinburg), launched a clinical study of methods for rehabilitation of cognitive disorders in patients with MS. There was a statistically significant improvement in MOCA-test scores, according to SDMT and PASSAT data in the main group of MS patients. Despite a significant improvement in cognitive function, the self-assessment of mental function according to the MSQOL54-MN test in this group of patients did not change. Our preliminary results suggest that a comprehensive and well-controlled training program can improve cognitive abilities in MS patients even after a short course of treatment.

PMID:34387454 | DOI:10.17116/jnevro202112107294

J Ultrasound Med. 2021 Aug 13. doi: 10.1002/jum.15804. Online ahead of print.

ABSTRACT

OBJECTIVE: To explore the clinical value of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of benign and malignant subpleural pulmonary lesions (SPLs).

METHODS: Among 959 patients with SPLs who were scheduled to undergo ultrasound-guided puncture in our department between January 2019 and June 2019, 506 patients were included and their B-mode ultrasound and CEUS features, including the lesion’s location, size, margin, echo, perfusion pattern of ultrasound contrast agent, degree of enhancement, homogeneity, vascular signs, and necrosis, were retrospectively investigated. All malignant cases were diagnosed by pathology, while benign cases were diagnosed by two respiratory physicians after comprehensive analysis of pathology, etiology, imaging, and clinical symptoms. Statistical differences in these features between the benign and malignant groups were then analyzed.

RESULTS: There were 506 cases in this study, including 219 benign cases and 287 malignant cases. Among them, 351 were males and 155 were females, with an average age of 59 ± 16 years. There were statistically significant differences between benign and malignant groups in the perfusion pattern, the degree of enhancement, and vascular signs. The features of the malignant group included local-to-whole perfusion pattern, hypo-enhancement, and curly hair sign, while those of the benign group included a centrifugal perfusion pattern, iso-enhancement and hyper-enhancement, and dendritic sign. There was no statistically significant difference between the two groups in homogeneity and necrosis.

CONCLUSIONS: CEUS enhancement mode is different between benign and malignant SPLs, which can provide supplementary information for the differential diagnosis of SPLs in the existing imaging diagnosis.

PMID:34387377 | DOI:10.1002/jum.15804

J Comput Chem. 2021 Aug 13. doi: 10.1002/jcc.26734. Online ahead of print.

ABSTRACT

AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem. 2018, 39, 1922). This release features a number of new capabilities: rare-event molecular dynamics simulations to enhance reaction discovery, extension of the original search algorithm to study van der Waals complexes, use of chemical knowledge, a new search algorithm based on bond-order time series analysis, statistics of the chemical reaction networks, a web application to submit jobs, and other features. The source code, manual, installation instructions and the website link are available at: https://rxnkin.usc.es/index.php/AutoMeKin.

PMID:34387374 | DOI:10.1002/jcc.26734

Med Phys. 2021 Aug 13. doi: 10.1002/mp.15161. Online ahead of print.

ABSTRACT

PURPOSE: Convolutional neural network (CNN)-based denoising is an effective method for reducing complex computed tomography (CT) noise. However, the image blur induced by denoising processes is a major concern. The main source of image blur is the pixel-level loss (e.g., mean-squared-error (MSE) and mean-absolute-error (MAE)) used to train a CNN denoiser. To reduce the image blur, feature-level loss is utilized to train a CNN denoiser. A CNN denoiser trained using VGG loss can preserve the small structures, edges, and texture of the image. However, VGG loss, derived from an ImageNet-pretrained image classifier, is not optimal for training a CNN denoiser for CT images. ImageNet contains natural RGB images, so the features extracted by the ImageNet-pretrained model cannot represent the characteristics of CT images that are highly correlated with diagnosis. Furthermore, a CNN denoiser trained with VGG loss causes bias in CT number. Therefore, we propose to use a binary classification network trained using CT images as a feature extractor and newly define the feature-level loss as observer loss.

METHODS: As obtaining labeled CT images for training classification network is difficult, we create labels by inserting simulated lesions. We conduct two separate classification tasks, signal-known-exactly (SKE) and signal-known-statistically (SKS), and define the corresponding feature-level losses as SKE loss and SKS loss, respectively. We use SKE loss and SKS loss to train CNN denoiser.

RESULTS: Compared to pixel-level losses, a CNN denoiser trained using observer loss (i.e., SKE loss and SKS loss) is effective in preserving structure, edge, and texture. Observer loss also resolves the bias in CT number, which is a problem of VGG loss. Comparing observer losses using SKE and SKS tasks, SKS yields images having a more similar noise structure to reference images.

CONCLUSIONS: Using observer loss for training CNN denoiser is effective to preserve structure, edge, and texture in denoised images and prevent the CT number bias. In particular, when using SKS loss, denoised images having a similar noise structure to reference images are generated.

PMID:34387360 | DOI:10.1002/mp.15161

Syst Biol. 2021 Aug 13:syab067. doi: 10.1093/sysbio/syab067. Online ahead of print.

ABSTRACT

Using time-reversible Markov models is a very common practice in phylogenetic analysis, because although we expect many of their assumptions to be violated by empirical data, they provide high computational efficiency. However, these models lack the ability to infer the root placement of the estimated phylogeny. In order to compensate for the inability of these models to root the tree, many researchers use external information such as using outgroup taxa or additional assumptions such as molecular-clocks. In this study, we investigate the utility of non-reversible models to root empirical phylogenies and introduce a new bootstrap measure, the rootstrap, which provides information on the statistical support for any given root position. Availability and implementation: rootstrap support is implemented in IQ-TREE 2 and a tutorial is available at the iqtree webpage http://www.iqtree.org/doc/Rootstrap. In addition, a python script is available at https://github.com/suhanaser/Rootstrap.

PMID:34387349 | DOI:10.1093/sysbio/syab067

Hum Mol Genet. 2021 Aug 13:ddab229. doi: 10.1093/hmg/ddab229. Online ahead of print.

ABSTRACT

Alzheimer’s disease (ad) adversely affects the health, quality of life and independence of patients. There is a critical need to identify novel blood gene biomarkers for ad risk assessment. We performed a transcriptome-wide association study to identify biomarker candidates for ad risk. We leveraged two sets of gene expression prediction models of blood developed using different reference panels and modelling strategies. By applying the prediction models to a meta-GWAS including 71 880 (proxy) cases and 383 378 (proxy) controls, we identified significant associations of genetically determined expression of 108 genes in blood with ad risk. Of these, 15 genes were differentially expressed between ad patients and controls with concordant directions in measured expression data. With evidence from the analyses based on both genetic instruments and directly measured expression levels, this study identifies 15 genes with strong support as biomarkers in blood for ad risk, which may enhance ad risk assessment and mechanism-focused studies.

PMID:34387340 | DOI:10.1093/hmg/ddab229

Phys Chem Chem Phys. 2021 Aug 13. doi: 10.1039/d1cp02800f. Online ahead of print.

ABSTRACT

The kinetic behavior of vapor adsorption on a solid surface in an isobaric-isothermal system is investigated by means of molecular dynamics simulations combined with theoretical studies through a statistical rate theory approach. The molecular insights into the formation and evolution of clusters in the adsorbate are presented. Results show that the argon vapor is adsorbed on the silicon surface as different types of clusters. In the initial stage of adsorption, the empty adsorption sites on the surface decrease, and the adsorbed single-molecule-cluster grows rapidly and dominates the interface. The increasing rate of the adsorbed cluster and the declining rate of the empty adsorption site are dependent on the pressure ratio. For a large pressure ratio, the single-molecule-clusters are aggregated to incubate large clusters, and the fraction of a single-molecule-cluster is decreased with time. When the adsorption isotherm is determined, the chemical potential of the adsorbed cluster is expressed from the zeta isotherm model. Then the adsorption kinetics are analyzed through the statistical rate theory. The molecular exchange rate and the instantaneous driving force are calculated. The higher pressure ratio induces the larger chemical potential difference and accelerates the net adsorption rate. The adsorption kinetics derived from MD simulations are in close agreement with the theoretical analysis of the statistical rate theory.

PMID:34387292 | DOI:10.1039/d1cp02800f

J ECT. 2021 Aug 12. doi: 10.1097/YCT.0000000000000800. Online ahead of print.

ABSTRACT

OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has led to reported change in electroconvulsive therapy (ECT) services worldwide. However, minimal data have been published demonstrating tangible changes across multiple ECT centers. This article aimed to examine changes in ECT patients and ECT service delivery during the pandemic.

METHODS: We retrospectively assessed data collected on ECT patients within the Clinical Alliance and Research in Electroconvulsive Therapy and Related Treatments (CARE) Network during a 3-month period starting at the first COVID-19 restrictions in 2020 and compared data with predicted values based on the corresponding 3-month period in 2019. Mixed-effects repeated-measures analyses examined differences in the predicted and actual number of acute ECT courses started and the total number of acute ECT treatments given in 2020. Sociodemographic, clinical, treatment factors, and ECT service delivery factors were compared for 2020 and 2019.

RESULTS: Four Australian and 1 Singaporean site participated in the study. There were no significant differences between the predicted and actual number of acute ECT courses and total number of acute ECT treatments administered in 2020. During 2020, there were statistically significant increases in the proportion of patients requiring ECT under substitute consent and receiving ECT for urgent reasons compared with 2019.

CONCLUSIONS: This multisite empirical study is among the first that supports anecdotal reports of changes in the triaging and delivery of ECT during COVID-19. Results suggest that ECT was prioritized for the most severely ill patients. Further data assessing the impacts of COVID-19 on ECT are needed.

PMID:34387286 | DOI:10.1097/YCT.0000000000000800