Miracle-dz/UniFAR-FTUs huggingface dataset:
A cross-level information transmission network for hierarchical omics data integration and phenotype prediction from a new genotype

Abstract Motivation An unsolved fundamental problem in biology is to predict phenotypes from a new genotype under environmental perturbations. The emergence of multiple omics data provides new opportunities but imposes great challenges in the predictive modeling of genotype-phenotype associations. Firstly, the high-dimensionality of genomics data and the lack of coherent labeled data often make the existing supervised learning techniques less successful. Secondly, it is challenging to integrate heterogeneous omics data from different resources. Finally, few works have explicitly modeled the information transmission from DNA to phenotype, which involves multiple intermediate molecular types. Higher-level features (e.g. gene expression) usually have stronger discriminative and interpretable power than lower-level features (e.g. somatic mutation). Results We propose a novel Cross-LEvel Information Transmission (CLEIT) network framework to address the above issues. CLEIT aims to represent the asymmetrical multi-level organization of the biological system by integrating multiple incoherent omics data and to improve the prediction power of low-level features. CLEIT first learns the latent representation of the high-level domain then uses it as ground-truth embedding to improve the representation learning of the low-level domain in the form of contrastive loss. Besides, CLEIT can leverage the unlabeled heterogeneous omics data to improve the generalizability of the predictive model. We demonstrate the effectiveness and significant performance boost of CLEIT in predicting anti-cancer drug sensitivity from somatic mutations via the assistance of gene expressions when compared with state-of-the-art methods. CLEIT provides a general framework to model information transmissions and integrate multi-modal data in a multi-level system. Availabilityand implementation The source code is freely available at https://github.com/XieResearchGroup/CLEIT. Supplementary information Supplementary data are available at Bioinformatics online.
Nano-ligament combined with sports rehabilitation training on the therapeutic effect after ligament reconstruction

Abstract As for the postoperative treatment effect of joint reconstruction, researchers have recognized the following point of view: surgical treatment alone not only has many complications, but also the recovery of knee joint function in some patients is not ideal. The effect of ligament reconstruction depends not only on the level of operation, but also on the postoperative rehabilitation. In order to study the effect of the new nano ligament combined with sports rehabilitation training on the treatment effect of ligament reconstruction, strict method analysis and control experiment were carried out in this paper.This paper first studies the importance, significance and related research status of link reconstruction at home and abroad, and then studies the proprioception training rehabilitation methods, rood multi sensory stimulation promotion, Mrs lower limb training methods and so on. Based on the theoretical support of these methods, this paper carried out the experimental study on the influence of rehabilitation training on the therapeutic effect of ligament reconstruction and the experimental results. This paper innovated on the traditional rehabilitation training: using more technical experimental results and comparing the experimental results of this paper, setting more control groups than the traditional reference experiments. In order to achieve more in-depth research results.The results showed that at the early stage of recovery, the passive flexion of bilateral knee joints was also slightly limited. After 24 weeks of rehabilitation training, the passive flexibility angle of the injured side of the three patients increased from 84 degrees to 92 degrees, from 148 degrees to 154 degrees, and the maximum increase was 64 degrees. At the early stage of rehabilitation, it gradually decreases with the rehabilitation process, and finally tends to be stable, which shows that the effect of early rehabilitation is very obvious, and it proves that early rehabilitation is more important in the whole rehabilitation training.
Swearing in informal spoken English: 1990s–2010s

Abstract This paper investigates changes in swearing usage in informal speech using large-scale corpus data, comparing the occurrence and social distribution of swear words in two corpora of informal spoken British English: the demographically-sampled part of the Spoken British National Corpus 1994 (BNC1994) and the Spoken British National Corpus 2014 (BNC2014); the compilation of the latter has facilitated large-scale, diachronic analyses of authentic spoken data on a scale which has, until now, not been possible. A form and frequency analysis of a set of 16 ‘pure’ swear word lemma forms is presented. The findings reveal that swearing occurrence is significantly lower in the Spoken BNC2014 but still within a comparable range to previous studies. Furthermore, FUCK is found to overtake BLOODY as the most popular swear word lemma. Finally, the social distribution of swearing across gender and age groups generally supports the findings of previous research: males still swear more than females, and swearing still peaks in the twenties and declines thereafter. However, the distribution of swearing according to socio-economic status is found to be more complex than expected in the 2010s and requires further investigation. This paper also reflects on some of the methodological challenges associated with making comparisons between the two corpora.
Improvement of wound healing by the development of ECM-inspired biomaterial coatings and controlled protein release

Abstract Implant design has evolved from biochemically inert substrates, minimizing cell and protein interaction, towards sophisticated bioactive substrates, modulating the host response and supporting the regeneration of the injured tissue. Important aspects to consider are the control of cell adhesion, the discrimination of bacteria and non-local cells from the desired tissue cell type, and the stimulation of implant integration and wound healing. Here, the extracellular matrix acts as a role model providing us with inspiration for sophisticated designs. Within this scope, small bioactive peptides have proven to be miscellaneously deployable for the mediation of surface, cell and matrix interactions. Combinations of adhesion ligands, proteoglycans, and modulatory proteins should guide multiple aspects of the regeneration process and cooperativity between the different extracellular matrix components, which bears the chance to maximize the therapeutic efficiency and simultaneously lower the doses. Hence, efforts to include multiple of these factors in biomaterial design are well worth. In the following, multifunctional implant coatings based on bioactive peptides are reviewed and concepts to implement strong surface anchoring for stable cell adhesion and a dynamic delivery of modulator proteins are discussed.
Radiomic Score as a Potential Imaging Biomarker for Predicting Survival in Patients With Cervical Cancer

Objectives Accurate prediction of prognosis will help adjust or optimize the treatment of cervical cancer and benefit the patients. We aimed to investigate the incremental value of radiomics when added to the FIGO stage in predicting overall survival (OS) in patients with cervical cancer. Methods This retrospective study included 106 patients with cervical cancer (FIGO stage IB1–IVa) between October 2017 and May 2019. Patients were randomly divided into a training cohort (n = 74) and validation cohort (n = 32). All patients underwent contrast-enhanced computed tomography (CT) prior to treatment. The ITK-SNAP software was used to delineate the region of interest on pre-treatment standard-of-care CT scans. We extracted 792 two-dimensional radiomic features by the Analysis Kit (AK) software. Pearson correlation coefficient analysis and Relief were used to detect the most discriminatory features. The radiomic signature (i.e., Radscore) was constructed via Adaboost with Leave-one-out cross-validation. Prognostic models were built by Cox regression model using Akaike information criterion (AIC) as the stopping rule. A nomogram was established to individually predict the OS of patients. Patients were then stratified into high- and low-risk groups according to the Youden index. Kaplan–Meier curves were used to compare the survival difference between the high- and low-risk groups. Results Six textural features were identified, including one gray-level co-occurrence matrix feature and five gray-level run-length matrix features. Only the FIGO stage and Radscore were independent risk factors associated with OS (p < 0.05). The C-index of the FIGO stage in the training and validation cohorts was 0.703 (95% CI: 0.572–0.834) and 0.700 (95% CI: 0.526–0.874), respectively. Correspondingly, the C-index of Radscore was 0.794 (95% CI: 0.707–0.880) and 0.754 (95% CI: 0.623–0.885). The incorporation of the FIGO stage and Radscore achieved better performance, with a C-index of 0.830 (95% CI: 0.738–0.922) and 0.772 (95% CI: 0.615–0.929), respectively. The nomogram based on the FIGO stage and Radscore could individually predict the OS probability with good discrimination and calibration. The high-risk patients had shorter OS compared with the low-risk patients (p < 0.05). Conclusion Radiomics has the potential for noninvasive risk stratification and may improve the prediction of OS in patients with cervical cancer when added to the FIGO stage.
Non-structural Proteins of Severe Fever With Thrombocytopenia Syndrome Virus Suppress RNA Synthesis in a Transcriptionally Active cDNA-Derived Viral RNA Synthesis System

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the tick-borne SFTS bunyavirus (SFTSV) resulting in a high fatality rate up to 30%. SFTSV is a negative-strand RNA virus containing three single-stranded RNA genome segments designated as L, M, and S, which respectively, encode the RNA-dependent RNA polymerase (RdRp), glycoproteins Gn and Gc, and nucleoprotein (N) and non-structural proteins (NSs). NSs can form inclusion bodies (IBs) in infected and transfected cells. A previous study has provided a clue that SFTSV NSs may be involved in virus-like or viral RNA synthesis; however, the details remain unclear. Our work described here reveals that SFTSV NSs can downregulate virus-like RNA synthesis in a dose-dependent manner within a cDNA-derived viral RNA synthesis system, i.e., minigenome (−) and minigenome (+) systems based on transfection, superinfection, and luciferase reporter activity determination; meanwhile, NSs also show a weak inhibitory effect on virus replication. By using co-immunoprecipitation (Co-IP) and RT-PCR combined with site-directed mutagenesis, we found that NSs suppress virus-like RNA or virus replication through interacting with N but not with RdRp, and the negative regulatory effect correlates closely with the IB structure it formed but is not associated with its role of antagonizing host innate immune responses. When the cytoplasmic structure of IB formed by SFTSV NSs was deprived, the inhibitory effect of NSs on virus-like RNA synthesis would weaken and even disappear. Similarly, we also evaluated other bandavirus NSs that cannot form IB in neither infected nor transfected cells, and the results showed that the NSs of Heartland bandavirus (HRTV) did not show a significant inhibitory effect on virus-like RNA synthesis within a minigenome system. Our findings provide experimental evidence that SFTSV NSs participate in regulating virus-like or viral RNA synthesis and the negative effect may be due to the NSs–N interaction.
Comparative Study of Acute Lung Injury in COVID-19 and Non-COVID-19 Patients

Background: Amid the coronavirus disease 2019 (COVID-19) pandemic, we analyzed clinical characteristics of acute lung injury (ALI) in COVID-19 patients and reported their similarity and dissimilarity to those of non-COVID-19 patients in the intensive care unit (ICU). Methods: We reported on 90 COVID-19 and 130 non-COVID-19 ALI patients in the ICUs of multiple centers. Demographic data, medical histories, laboratory findings, and radiological images were analyzed and compared between the two cohorts and within each cohort between survivors and non-survivors. For ALI survivors, clinical characteristics before and after treatment were also compared. Findings: Aberrations in blood parameters, such as leukocytosis, neutrophilia, and thrombocytopenia, were observed in both cohorts. More characteristic abnormalities, including significantly higher red cell distribution width (RDW), C-reactive proteins, and lactic dehydrogenase (LDH) but lower troponin (TnT) and procalcitonin, were observed in the COVID-19 cohort than in the non-COVID-19 cohort, whereas D-dimer levels showed a similar elevation in both cohorts. The COVID-19 cohort also showed more diversified CT patterns where severe features such as consolidations and crazy paving patterns were more frequently observed. Multivariate analysis indicated that age, fever symptom, prothrombin time, procalcitonin, partial pressure of carbon dioxide, oxygenated hemoglobin, and crazy paving patterns in CT scans were independent risk factors associated with COVID-19. Interpretation: Comparison of ALI characteristics between COVID-19 and non-COVID-19 patients in the ICU setting provided insight into the pathogenesis of ALI induced by different risk factors, suggesting distinct treatment plans.
CX3CR1 But Not CCR2 Expression Is Required for the Development of Autoimmune Peripheral Neuropathy in Mice

One hallmark of Guillain-Barre syndrome (GBS), a prototypic autoimmune peripheral neuropathy (APN) is infiltration of leukocytes (macrophages and T cells) into peripheral nerves, where chemokines and their receptors play major roles. In this study, we aimed to understand the potential contribution of chemokine receptors CCR2 and CX3CR1 in APN by using a well-established mouse model, B7.2 transgenic (L31) mice, which possesses a predisposed inflammatory background. We crossbred respectively CCR2KO and CX3CR1KO mice with L31 mice. The disease was initiated by partial ligation on one of the sciatic nerves. APN pathology and neurological function were evaluated on the other non-ligated sciatic nerve/limb. Our results revealed that L31/CX3CR1KO but not L31/CCR2KO mice were resistant to APN. CX3CR1 is needed for maintaining circulating monocyte and CD8+ T cell survival. While migration of a significant number of activated CD8+ T cells to peripheral nerves is essential in autoimmune response in nerve, recruitment of monocytes into PNS seems optional. Disease onset is independent of CCR2 mediated blood-derived macrophage recruitment, which can be replaced by compensatory proliferation of resident macrophages in peripheral nerve. CX3CR1 could also contribute to APN via its critical involvement in maintaining nerve macrophage phagocytic ability. We conclude that blockade of CX3CR1 signaling may represent an interesting anti-inflammatory strategy to improve therapeutic management for GBS patients.
Defect Engineering in Metal‒Organic Frameworks as Futuristic Options for Purification of Pollutants in an Aqueous Environment

Clean water scarcity is becoming an increasingly important worldwide issue. The water treatment industry is demanding the development of novel effective materials. Defect engineering in nanoparticles is among the most revolutionary of technologies. Because of their high surface area, structural diversity, and tailorable ability, Metal‒Organic Frameworks (MOFs) can be used for a variety of purposes including separation, storage, sensing, drug delivery, and many other issues. The application in wastewater treatment associated with water stable MOF‒based materials has been an emerging research topic in recent decades. Defect engineering is a sophisticated technique used to manufacture defects and to change the geometric framework of target compounds. Since MOFs have a series of designable structures and active sites, tailoring properties in MOFs by defect engineering is a novel concept. Defect engineering can excavate hidden active sites in MOFs, which can lead to better performance in many fields. Therefore, this technology will open new opportunities in water purification processes. However, there has been little effort to comprehensively discuss this topic. In this review, we provide an overview of the development of defect engineered MOFs for water purification processes. Furthermore, we discuss the potential applications of defect engineered materials.
Selective Catalytic Reduction System Ammonia Injection Control Based on Deep Deterministic Policy Reinforcement Learning

The control of flue gas emission in thermal power plants has been a topic of concern. Selective catalytic reduction technology has been widely used as an effective flue gas treatment technology. However, precisely controlling the amount of ammonia injected remains a challenge. Too much ammonia not only causes secondary pollution but also corrodes the reactor equipment, while too little ammonia does not effectively reduce the NOx content. In recent years, deep reinforcement learning has achieved better results than traditional methods in decision making and control, which provides new methods for better control of selective catalytic reduction systems. The purpose of this research is to design an intelligent controller using reinforcement learning technology, which can accurately control ammonia injection, and achieve higher denitrification effect and less secondary pollution. To train the deep reinforcement learning controller, a high-precision virtual denitration environment is first constructed. In order to make the virtual environment more realistic, this virtual environment was designed as a special structure with two decoders and a unique approach was used in fitting the virtual environment. A deep deterministic policy agent is used as an intelligent controller to control the amount of injected ammonia. To make the intelligent controller more stable, the actor-critic framework and the experience pool approach were adopted. The results show that the intelligent controller can control the emissions of nitrogen oxides and ammonia at the outlet of the reactor after training in virtual environment.
Cardiac Fibrosis: Cellular Effectors, Molecular Pathways, and Exosomal Roles

Cardiac fibrosis, a common pathophysiologic process in most heart diseases, refers to an excess of extracellular matrix (ECM) deposition by cardiac fibroblasts (CFs), which can lead to cardiac dysfunction and heart failure subsequently. Not only CFs but also several other cell types including macrophages and endothelial cells participate in the process of cardiac fibrosis via different molecular pathways. Exosomes, ranging in 30–150 nm of size, have been confirmed to play an essential role in cellular communications by their bioactive contents, which are currently a hot area to explore pathobiology and therapeutic strategy in multiple pathophysiologic processes including cardiac fibrosis. Cardioprotective factors such as RNAs and proteins packaged in exosomes make them an excellent cell-free system to improve cardiac function without significant immune response. Emerging evidence indicates that targeting selective molecules in cell-derived exosomes could be appealing therapeutic treatments in cardiac fibrosis. In this review, we summarize the current understandings of cellular effectors, molecular pathways, and exosomal roles in cardiac fibrosis.
Engineering Functional Vasculature in Decellularized Lungs Depends on Comprehensive Endothelial Cell Tropism

Tissue engineering using decellularized whole lungs as matrix scaffolds began as a promise for creating autologous transplantable lungs for patients with end-stage lung disease and can also be used to study strategies for lung regeneration. Vascularization remains a critical component for all solid organ bioengineering, yet there has been limited success in generating functional re-endothelialization of most pulmonary vascular segments. We evaluated recellularization of the blood vessel conduits of acellular mouse scaffolds with highly proliferating, rat pulmonary microvascular endothelial progenitor cells (RMEPCs), pulmonary arterial endothelial cells (PAECs) or microvascular endothelial cells (MVECs). After 8 days of pulsatile perfusion, histological analysis showed that PAECs and MVECs possessed selective tropism for larger vessels or microvasculature, respectively. In contrast, RMEPCs lacked site preference and repopulated all vascular segments. RMEPC-derived endothelium exhibited thrombomodulin activity, expression of junctional genes, ability to synthesize endothelial signaling molecules, and formation of a restrictive barrier. The RMEPC phenotype described here could be useful for identifying endothelial progenitors suitable for efficient vascular organ and tissue engineering, regeneration and repair.
Non-medical Use of Prescription Stimulants Among College Students: Non-oral Routes of Administration, Risk Factors, Motivations, and Pathways

Introduction: Non-medical use (NMU) of prescription stimulant medications is a continuing public health concern. Stimulant medications prescribed for attention-deficit/hyperactivity disorder (ADHD) are widely available on college campuses, and, as a consequence, college students may have multiple opportunities to engage in prescription stimulant NMU. This online self-report survey examined prescription stimulant NMU among college students, including: (1) patterns of non-oral route of administration (ROA); (2) motivations for non-oral ROAs; and (3) retrospectively recalled pathways of initiation. Method: The survey sample was created from a pool of 3,379 respondents, who were matched to a sampling frame constructed from the 18–26-year-old, college student sample of the 2016 American Community Survey (ACS). About 14% (n = 486) from the overall pool were identified as college students with self-reported prescription stimulant NMU, all of whom completed the survey. The survey covered user characteristics, prescription and illicit substance use, age of first NMU, motivations for NMU, sources of procurement, and ROAs used. Results: Among 486 students reporting prescription stimulant NMU, 43% had a lifetime diagnosis of ADHD. More than 90% reported polysubstance use, with 55% using illicit substances other than marijuana. Slightly more than 2 in 5 (43.3%) reported using illicit substances prior to prescription stimulant NMU, 24.6% used both at the same age, and 32.0% engaged in NMU of prescription stimulants prior to using illicit substances. Prescription stimulant NMU preceded prescription opioid NMU 45% of the time. More than a quarter of those engaged in prescription stimulant NMU (27.9%) initiated prescription stimulants alone or at the same age as other drugs. Most prescription stimulant NMU was oral, however 23.0% reported any non-oral use: snorting (20.4%), smoking (6.0%)and/or injection (3.5%). Non-oral use was associated with being male, obtaining medication from a dealer, use to get high, and/or a substance use disorder diagnosis. Conclusions: Prescription stimulant NMU often occurs in the larger context of other substance use among college students. Injection, an under-researched route for prescription stimulants, was associated with male gender, history of substance use and higher likelihood of illicit substance use. Nearly a quarter of college student survey respondents reported use with non-oral routes, which is associated with other high-risk behaviors. Efforts to reduce non-oral prescription stimulant NMU in college students are warranted.