The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM) occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC) assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers.
BackgroundThe core domains of social anxiety disorder (SAD), generalized anxiety disorder (GAD), panic disorder (PD) with and without agoraphobia (GA), and specific phobia (SP) are cognitive and physical symptoms that are related to the experience of fear and anxiety. It remains unclear whether these highly comorbid conditions that constitute the anxiety disorder subgroups of the Diagnostic and Statistical Manual for Mental Disorders – Fifth Edition (DSM-5) represent distinct disorders or alternative presentations of a single underlying pathology.MethodsA systematic search of voxel-based morphometry (VBM) studies of SAD, GAD, PD, GA, and SP was performed with an effect-size signed differential mapping (ES-SDM) meta-analysis to estimate the clusters of significant gray matter differences between patients and controls.ResultsTwenty-four studies were eligible for inclusion in the meta-analysis. Reductions in the right anterior cingulate gyrus and the left inferior frontal gyrus gray matter volumes (GMVs) were noted in patients with anxiety disorders when potential confounders, such as comorbid major depressive disorder (MDD), age, and antidepressant use were controlled for. We also demonstrated increased GMVs in the right dorsolateral prefrontal cortex (DLPFC) in comorbid depression-anxiety (CDA), drug-naïve and adult patients. Furthermore, we identified a reduced left middle temporal gyrus and right precentral gyrus in anxiety patients without comorbid MDD.ConclusionOur findings indicate that a reduced volume of the right ventral anterior cingulate gyrus and left inferior frontal gyrus is common in anxiety disorders and is independent of comorbid depression, medication use, and age. This generic effect supports the notion that the four types of anxiety disorders have a clear degree of overlap that may reflect shared etiological mechanisms. The results are consistent with neuroanatomical DLPFC models of physiological responses, such as worry and fear, and the importance of the ventral anterior cingulate (ACC)/medial prefrontal cortex (mPFC) in mediating anxiety symptoms.
BackgroundSeveral task-based functional MRI (fMRI) studies have highlighted abnormal activation in specific regions involving the low-level perceptual (auditory, visual, and somato-motor) network in posttraumatic stress disorder (PTSD) patients. However, little is known about whether the functional connectivity of the low-level perceptual and higher-order cognitive (attention, central-execution, and default-mode) networks change in medication-naïve PTSD patients during the resting state.MethodsWe investigated the resting state networks (RSNs) using independent component analysis (ICA) in 18 chronic Wenchuan earthquake-related PTSD patients versus 20 healthy survivors (HSs).ResultsCompared to the HSs, PTSD patients displayed both increased and decreased functional connectivity within the salience network (SN), central executive network (CEN), default mode network (DMN), somato-motor network (SMN), auditory network (AN), and visual network (VN). Furthermore, strengthened connectivity involving the inferior temporal gyrus (ITG) and supplementary motor area (SMA) was negatively correlated with clinical severity in PTSD patients.LimitationsGiven the absence of a healthy control group that never experienced the earthquake, our results cannot be used to compare alterations between the PTSD patients, physically healthy trauma survivors, and healthy controls. In addition, the breathing and heart rates were not monitored in our small sample size of subjects. In future studies, specific task paradigms should be used to reveal perceptual impairments.ConclusionsThese findings suggest that PTSD patients have widespread deficits in both the low-level perceptual and higher-order cognitive networks. Decreased connectivity within the low-level perceptual networks was related to clinical symptoms, which may be associated with traumatic reminders causing attentional bias to negative emotion in response to threatening stimuli and resulting in emotional dysregulation.
Next-generation sequencing (NGS) technology has rapidly advanced and generated the massive data volumes. To align and map the NGS data, biologists often randomly select a number of aligners without concerning their suitable feature, high performance, and high accuracy as well as sequence variations and polymorphisms existing on reference genome. This study aims to systematically evaluate and compare the capability of multiple aligners for NGS data analysis. To explore this capability, we firstly performed alignment algorithms comparison and classification. We further used long-read and short-read datasets from both real-life and in silico NGS data for comparative analysis and evaluation of these aligners focusing on three criteria, namely, application-specific alignment feature, computational performance, and alignment accuracy. Our study demonstrated the overall evaluation and comparison of multiple aligners for NGS data analysis. This serves as an important guiding resource for biologists to gain further insight into suitable selection of aligners for specific and broad applications.
A series of ferrocene‐based well‐defined amphiphilic graft copolymers, consisting of hydrophilic poly[poly(ethylene glycol) methyl ether acrylate] (PPEGMEA) backbone and hydrophobic poly(2‐acryloyloxyethyl ferrocenecarboxylate) (PAEFC) side chains were synthesized by successive single‐electron‐transfer living radical polymerization (SET‐LRP) and atom transfer radical polymerization (ATRP). The backbone was prepared by SET‐LRP of PEGMEA macromonomer, and it was then treated with lithium di‐isopropylamide and 2‐bromopropionyl bromide at −78 °C to give PPEGMEA‐Br macroinitiator. The targeted well‐defined graft copolymers with narrow molecular weight distributions (Mw/Mn ≤ 1.32) were synthesized via ATRP of AEFC initiated by PPEGMEA‐Br macroinitiator, and the molecular weights of the backbone and side chains were both controllable. The electro‐chemical behaviors of graft copolymers were studied by cyclic voltammetry, and it was found that graft copolymers were more difficult to be oxidized, and the reversibility of electrode process became less with raising the content of PAEFC segment. The effects of the preparation method, the length of hydrophobic PAEFC segment, and the initial water content on self‐assembly behavior of PPEGMEA‐g‐PAEFC graft copolymers in aqueous media were investigated by transmission electron microscopy. The morphologies of micelles could transform from cylinders to spheres or rods with changing the preparation condition and the length of side chains. © 2011 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2012
Aims To investigate the mental workload level of nurses aiding the most affected area during the Coronavirus disease 2019 (COVID‐19) pandemic and explore the subtypes of nurses regarding their mental workload. Design Cross‐sectional study. Methods A sample of 446 frontline nurses participated from March 8 to 19, 2020. A latent profile analysis was performed to identify clusters based on the six subscales of the Chinese version of the National Aeronautics and Space Administration Task Load Index . The differences among the classes and the variables including sociodemographic characteristics, psychological capital and coping style were explored. Results The level of mental workload indicates that the nurses had high self‐evaluations of their performance while under extremely intensive task loads. The following three latent subtypes were identified: ‘low workload & low self‐evaluation’ (8.6%); ‘medium workload & medium self‐evaluation’ (35.3%) and ‘high workload & high self‐evaluation’ (56.1%) ( Classes 1 , 2 , and 3 , respectively). Nurses with shared accommodations, fewer years of practice, junior professional titles, lower incomes, nonmanagement working positions, lower psychological capital levels and negative coping styles had a higher likelihood of belonging to Class 1 . In contrast, senior nurses with higher psychological capital and positive coping styles were more likely to belong to Classes 2 and 3 . Conclusion The characteristics of the ‘low workload & low self‐evaluation’ subtype suggest that attention should be paid to the work pressure and psychological well‐being of junior nurses. Further research on regular training program of public health emergency especially for novices is needed. Personnel management during public health events should be focused on the allocation between novice and senior frontline nurses. Impact This study addresses the level of mental workload of frontline nurses who aid in the most severe area of the COVID‐19 pandemic in China and delineates the characteristics of the subtypes of these nurses.
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