Genetics of inflammatory bowel disease: The role of the HLA complex

The human leucocyte antigen （HLA） complex on chromosome 6p21.3 is the most extensively studied genetic region in Inflammatory bowel disease （IBD）. Consistent evidence of linkage to IBD3 （6p21.1-23）, an area which encompasses the HLA complex, has been demonstrated for both Crohn＇s disease and ulcerative colitis, and a number of replicated associations with disease susceptibility and phenotype have recently emerged. However, despite these efforts the HLA susceptibility gene （s） for IBD remain elusive, a consequence of strong linkage disequilibrium, extensive polymorphism and high gene density across this region. This article reviews current knowledge of the role of HLA complex genes in IBD susceptibility and phenotype, and discusses the factors currently limiting the translation of this knowledge to clinical practice.

Smart Devices Based Multisensory Approach for Complex Human Activity Recognition

Sensors based Human Activity Recognition(HAR)have numerous applications in eHeath,sports,fitness assessments,ambient assisted living(AAL),human-computer interaction and many more.The human physical activity can be monitored by using wearable sensors or external devices.The usage of external devices has disadvantages in terms of cost,hardware installation,storage,computational time and lighting conditions dependencies.Therefore,most of the researchers used smart devices like smart phones,smart bands and watches which contain various sensors like accelerometer,gyroscope,GPS etc.,and adequate processing capabilities.For the task of recognition,human activities can be broadly categorized as basic and complex human activities.Recognition of complex activities have received very less attention of researchers due to difficulty of problem by using either smart phones or smart watches.Other reasons include lack of sensor-based labeled dataset having several complex human daily life activities.Some of the researchers have worked on the smart phone’s inertial sensors to perform human activity recognition,whereas a few of them used both pocket and wrist positions.In this research,we have proposed a novel framework which is capable to recognize both basic and complex human activities using builtin-sensors of smart phone and smart watch.We have considered 25 physical activities,including 20 complex ones,using smart device’s built-in sensors.To the best of our knowledge,the existing literature consider only up to 15 activities of daily life.

Automatic Recognition of Construction Worker Activities Using Deep Learning Approaches and Wearable Inertial Sensors

The automated evaluation and analysis of employee behavior in an Industry 4.0-compliant manufacturingfirm are vital for the rapid and accurate diagnosis of work performance,particularly during the training of a new worker.Various techniques for identifying and detecting worker performance in industrial applications are based on computer vision techniques.Despite widespread com-puter vision-based approaches,it is challenging to develop technologies that assist the automated monitoring of worker actions at external working sites where cam-era deployment is problematic.Through the use of wearable inertial sensors,we propose a deep learning method for automatically recognizing the activities of construction workers.The suggested method incorporates a convolutional neural network,residual connection blocks,and multi-branch aggregate transformation modules for high-performance recognition of complicated activities such as con-struction worker tasks.The proposed approach has been evaluated using standard performance measures,such as precision,F1-score,and AUC,using a publicly available benchmark dataset known as VTT-ConIoT,which contains genuine con-struction work activities.In addition,standard deep learning models(CNNs,RNNs,and hybrid models)were developed in different empirical circumstances to compare them to the proposed model.With an average accuracy of 99.71%and an average F1-score of 99.71%,the experimentalfindings revealed that the suggested model could accurately recognize the actions of construction workers.Furthermore,we examined the impact of window size and sensor position on the identification efficiency of the proposed method.

Anti-human leukocyte antigens and anti-major histocompatibility complex class I-related chain A antibody expression in kidney transplantation during a four-year follow-up

Background Humoral immunity is an important factor for long-term survival of renal allograft. Here we performed a four-year follow-up to explore the clinical significance of monitoring anti-human leukocyte antigens （HLA） and anti-major histocompatibility complex class I-related chain A （MICA） antibody expression after kidney transplantation. Methods We obtained serial serum samples from 84 kidney transplant patients over a four-year period. All patients were followed up at least 6 months after transplantation and had at least two follow-up points. Anti-HLA and anti-MICA antibody titres and serum creatinine （SCr） levels were evaluated at each follow-up. Patients were divided into 4 groups： HLA（＋） MICA（-）, HLA（-）MICA（＋）, HLA（＋）MICA（＋） and HLA（-）MICA（-）. The impact of post-transplant antibody level on kidney allograft function was evaluated. Results Antibodies were detected in 38.1% （32/84） of the renal allograft recipients. HLA, MICA and HLA＋MICA expression was observed in 18.89%, 14.44% and 5.93% of the recipients respectively. The most frequent anti-HLA and anti-MICA specific antibodies identified were All, A24, A29, A32, A33, A80; B7, B13, B37; DR17, DR12, DR18, DR52, DR53, DR1, DR4, DR9, DR51; DQ7, DQ4, DQ8, DQ2, DQ9, DQ5, DQ6 and MICA02, MICA18, MICA19, MICA07, MICA27. As the time after transplantation elapsed, more recipients developed de novo antibody expression. Total 11.91% （10/84） of the recipients had de novo antibody expression during the follow up. The average level of SCr and the percentage of recipients with abnormal allograft function were significantly higher in recipients with anti-HLA and/or anti- MICA antibody expression than those without. The appearance of anti-HLA and anti-MICA antibody expression always preceded the increase in SCr value. Conclusions Anti-HLA and anti-MICA antibody expression has predictive value for early and late allograft dysfunction. The presence of donor specific antibody is detrimental to graft function and graft survival.

Mechanism and Patterns of Control for Complex Systems with Human Participation

Many systems, such as transportation systems, the information super highway and urban systems, lie between natural systems and man made systems. These kinds of systems, which have both the self organization phenomena of natural systems and the organization of man made systems, are called complex systems with human participation (CSHP). The mechanism of control for CSHP is essentially the self organization/organization cooperation. This paper discusses the concept of CSHP and the mechanism and patterns of control for CSHP. Finally, a case study of control for transportation systems, the typical CSHP, is given to properly illustrate the mechanism and the serial pattern of control for CSHP.

HPC-Atlas:Computationally Constructing A Comprehensive Atlas of Human Protein Complexes

A fundamental principle of biology is that proteins tend to form complexes to play important roles in the core functions of cells.For a complete understanding of human cellular functions,it is crucial to have a comprehensive atlas of human protein complexes.Unfortunately,we still lack such a comprehensive atlas of experimentally validated protein complexes,which prevents us from gaining a complete understanding of the compositions and functions of human protein complexes,as well as the underlying biological mechanisms.To fill this gap,we built Human Protein Complexes Atlas(HPC-Atlas),as far as we know,the most accurate and comprehensive atlas of human protein complexes available to date.We integrated two latest protein interaction networks,and developed a novel computational method to identify nearly 9000 protein complexes,including many previously uncharacterized complexes.Compared with the existing methods,our method achieved outstanding performance on both testing and independent datasets.Furthermore,with HPC-Atlas we identified 751 severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)-affected human protein complexes,and 456 multifunctional proteins that contain many potential moonlighting proteins.These results suggest that HPC-Atlas can serve as not only a computing framework to effectively identify biologically meaningful protein complexes by integrating multiple protein data sources,but also a valuable resource for exploring new biological findings.The HPCAtlas webserver is freely available at http://www.yulpan.top/HPC-Atlas.

Targeting Ageing to Decrease Complex Non-Communicable Human Diseases

During the last two centuries, there have been many spectacular advances in medical science, the main consequence of which has been the dramatically reduced burden of infectious diseases. While in the 1800s many people died before reaching adult- hood, nowadays most people survive. Hence average life ex- pectancy in 1800s was around 30-40, which was barely higher than it had been in Greek and Roman times （Finch, 2010）, but nowadays life expectancy in most modernised economies is around 75 - 80. This demographic shift, which has happened in only 200 years, has created a dramatic change in the causes of mortality. The major killers in the modern world are non- communicable diseases （NCDs）： principally cardiovascular disease, cancer and neurodegenerative disorders such as Alz- heimer＇s disease. A major factor that influences susceptibility to all these diseases is age. As we get older, our risk of developing these NCDs increases enormously. For example, the rate of breast cancer in females at age 15-19 is less than 10 per 100,000 population, but this increases to 100 at age 40-44, 275 at age 55--59 and 450 at age 85 ＋ （http：//www.cancerresearchuk.org/ cancer-info/cancerstats/types/breast/incidence/#age）. Ageing has consequently become a major medical, social and economic burden to many countries.

Hidden Genetic Regulation of Human Complex Traits via Brain Isoforms

Alternative splicing exists in most multi-exonic genes,and exploring these complex alternative splicing events and their resultant isoform expressions is essential.However,it has become conventional that RNA sequencing results have often been summarized into gene-level expression counts mainly due to the multiple ambiguous mapping of reads at highly similar regions.Transcript-level quantification and interpretation are often overlooked,and biological interpretations are often deduced based on combined transcript information at the gene level.Here,for the most variable tissue of alternative splicing,the brain,we estimate isoform expressions in 1,191 samples collected by the Genotype-Tissue Expression(GTEx)Consortium using a powerful method that we previously developed.We perform genome-wide association scans on the isoform ratios per gene and identify isoform-ratio quantitative trait loci(irQTL),which could not be detected by studying gene-level expressions alone.By analyzing the genetic architecture of the irQTL,we show that isoform ratios regulate edu-cational attainment via multiple tissues including the frontal cortex(BA9),cortex,cervical spinal cord,and hippocampus.These tissues are also associated with different neuro-related traits,including Alzheimer’s or dementia,mood swings,sleep duration,alcohol intake,intelligence,anxiety or depression,etc.Mendelian randomization(MR)analysis revealed 1,139 pairs of isoforms and neuro-related traits with plausible causal relationships,showing much stronger causal effects than on general diseases measured in the UK Biobank(UKB).Our results highlight essential transcript-level biomarkers in the human brain for neuro-related complex traits and diseases,which could be missed by merely investigating overall gene expressions.

PASSIVE CONTROL OF HUMAN BODY COMPLEX SINGULAR SYSTEMS

Due to the complexity of interaction among constituents inside the whole system, it is difficult to establish accurate mathematics models to describe and analyze the complex systems exactly. There are few attempts concerning on the moving process of endocrine disruptor in human bodies, which have been the polluted material worldwide related to the reproduction, existence and development of human being. Focusing on such two challenging issues, a multi-compartment model of endocrine disruptor Benzene moving in the human body complex system is established in this paper. Furthermore, passivity of this model is described systematically. A feedback controller for this descriptor biological complex system is used under the station of strict passivity, and an example of the controller is given for a particular instantiation of the model.

Relationship between HLA-DRB1 and DQ alleles and the genetic susceptibility to type 1 diabetes

Objective To study the relationship between human leukocyte antigen (HLA) DRB1 and DQ alleles and the genetic susceptibility of type 1 diabetes in North Chinese children Methods Polymerase chain reaction (PCR) techniques were used to amplify the second exon of DRB1 and DQ alleles, after which sequence specific olignucleotide probe (SSOP) dot blot hybridization techniques were used to analyze the amplified products Results DRB1*0301, DQA1*0301, DQB1*0201 alleles and DRB1*0301 DQA1*0501 DQB1*0201 haplotype were significantly increased in patients, while DQA1*0103 and DQB1*0601 alleles were significantly increased in controls The distribution of DR4 and DR9 haplotypes in patients and controls were not significantly different, but DR3/DR4 and DR4/DR9 heterozygotes were significantly increased in patients Conclusions DRB1*0301, DQA1*0301 and DQB1*0201 confer susceptibility while DQA1*0103 and DQB1*0601 confer protection to type 1 diabetes DRB1*0301 DQA1*0501 DQB1*0201 haplotype offers a predisposition to type 1 diabetes in North Chinese Although the distribution of DR4 and DR9 in patients and controls had no significant difference, DR3/DR4 and DR3/DR9 heterozygotes were significantly increased in patients, showing that the susceptive effects of DR3 and DR4 or DR4 and DR9 haplotypes could be added up

Overcoming Debye length limitations:Three-dimensional wrinkled graphene field-effect transistor for ultra-sensitive adenosine triphosphate detection

Adenosine triphosphate(ATP)is closely related to the pathogenesis of certain diseases,so the detection of trace ATP is of great significance to disease diagnosis and drug development.Graphene field-effect transistors(GFETs)have been proven to be a promising platform for the rapid and accurate detection of small molecules,while the Debye shielding limits the sensitive detection in real samples.Here,a three-dimensional wrinkled graphene field-effect transistor(3D WG-FET)biosensor for ultra-sensitive detection of ATP is demonstrated.The lowest detection limit of 3D WG-FET for analyzing ATP is down to 3.01 aM,which is much lower than the reported results.In addition,the 3D WG-FET biosensor shows a good linear electrical response to ATP concentrations in a broad range of detection from 10 aM to 10 pM.Meanwhile,we achieved ultra-sensitive(LOD:10 aM)and quantitative(range from 10 aM to 100 fM)measurements of ATP in human serum.The 3D WG-FET also exhibits high specificity.This work may provide a novel approach to improve the sensitivity for the detection of ATP in complex biological matrix,showing a broad application value for early clinical diagnosis and food health monitoring.