TSSFinder is a valuable new tool for the annotation of genomes. TSSFinder source code and docker container can be downloaded from http//tssfinder.github.io. Alternatively, TSSFinder is also available as a web service at http//sucest-fun.org/wsapp/tssfinder/.With the development of high-throughput sequencing technology, biological sequence data reflecting life information becomes increasingly accessible. Particularly on the background of the COVID-19 pandemic, biological sequence data play an important role in detecting diseases, analyzing the mechanism and discovering specific drugs. click here In recent years, pretraining models that have emerged in natural language processing have attracted widespread attention in many research fields not only to decrease training cost but also to improve performance on downstream tasks. Pretraining models are used for embedding biological sequence and extracting feature from large biological sequence corpus to comprehensively understand the biological sequence data. In this survey, we provide a broad review on pretraining models for biological sequence data. Moreover, we first introduce biological sequences and corresponding datasets, including brief description and accessible link. Subsequently, we systematically summarize popular pretraining models for biological sequences based on four categories CNN, word2vec, LSTM and Transformer. Then, we present some applications with proposed pretraining models on downstream tasks to explain the role of pretraining models. Next, we provide a novel pretraining scheme for protein sequences and a multitask benchmark for protein pretraining models. Finally, we discuss the challenges and future directions in pretraining models for biological sequences.

This cross-sectional study examined accuracy of traditional Medical Symptom Validity Test (MSVT) validity indicators, including immediate recognition (IR), delayed recognition (DR), and consistency (CNS), as well as a novel indicator derived from the mean performance on IR, DR, and CNS across verbal, visual, and combined learning and memory impairment bands.

A sample of 180 adult outpatients was divided into valid (n = 150) and invalid (n = 30) groups based on results of four independent criterion performance validity tests. Verbal and visual learning and recall were classified as indicative of no impairment, mild impairment, or severe impairment based on performance on the Rey Auditory Verbal Learning Test and Brief Visuospatial Memory Test-Revised, respectively.

In general, individual MSVT subtests were able to accurately classify performance as valid or invalid, even in the context of severe learning and memory deficits. However, as verbal and visual memory impairment increased, optimal MSVT cut-scores diverged from manual-specified cutoffs such that DR and CNS required cut-scores to be lowered to maintain adequate specificity. By contrast, the newly proposed scoring algorithm generally showed more robust psychometric properties across the memory impairment bands.

The mean performance index, a novel scoring algorithm using the mean of the three primary MSVT subtests, may be a more robust validity indicator than the individual MSVT subtests in the context of bona fide memory impairment.

The mean performance index, a novel scoring algorithm using the mean of the three primary MSVT subtests, may be a more robust validity indicator than the individual MSVT subtests in the context of bona fide memory impairment.High blood pressure is one of the most important risk factors for ischaemic heart disease, stroke, other cardiovascular diseases, chronic kidney disease and dementia. Mean blood pressure and the prevalence of raised blood pressure have declined substantially in high-income regions since at least the 1970s. By contrast, blood pressure has risen in East, South and Southeast Asia, Oceania and sub-Saharan Africa. Given these trends, the prevalence of hypertension is now higher in low-income and middle-income countries than in high-income countries. In 2015, an estimated 8.5 million deaths were attributable to systolic blood pressure >115 mmHg, 88% of which were in low-income and middle-income countries. Measures such as increasing the availability and affordability of fresh fruits and vegetables, lowering the sodium content of packaged and prepared food and staples such as bread, and improving the availability of dietary salt substitutes can help lower blood pressure in the entire population. The use and effectiveness of hypertension treatment vary substantially across countries. Factors influencing this variation include a country’s financial resources, the extent of health insurance and health facilities, how frequently people interact with physicians and non-physician health personnel, whether a clear and widely adopted clinical guideline exists and the availability of medicines. Scaling up treatment coverage and improving its community effectiveness can substantially reduce the health burden of hypertension.In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements they also embody algorithms that implement the brain’s ability to learn from experience and cope with new challenges. Importantly, they exhibit structural dynamics that depend on activity, excitatory input and inhibitory input (synaptic plasticity or ‘extrinsic’ dynamics) and dynamics independent of activity (‘intrinsic’ dynamics), both of which are subject to neuromodulatory influences and reinforcers such as dopamine. Here we succinctly review extrinsic and intrinsic dynamics, compare these with parallels in machine learning where they exist, describe the importance of intrinsic dynamics for memory management and adaptation, and speculate on how disruption of extrinsic and intrinsic dynamics may give rise to mental disorders. Throughout, we also highlight algorithmic features of spine dynamics that may be relevant to future artificial intelligence developments.The self-assembly of proteins into sophisticated multicomponent assemblies is a hallmark of all living systems and has spawned extensive efforts in the construction of novel synthetic protein architectures with emergent functional properties. Protein assemblies in nature are formed via selective association of multiple protein surfaces through intricate noncovalent protein-protein interactions, a challenging task to accurately replicate in the de novo design of multiprotein systems. In this protocol, we describe the application of metal-coordinating hydroxamate (HA) motifs to direct the metal-mediated assembly of polyhedral protein architectures and 3D crystalline protein-metal-organic frameworks (protein-MOFs). This strategy has been implemented using an asymmetric cytochrome cb562 monomer through selective, concurrent association of Fe3+ and Zn2+ ions to form polyhedral cages. Furthermore, the use of ditopic HA linkers as bridging ligands with metal-binding protein nodes has allowed the construction of crystalline 3D protein-MOF lattices.