Treatment of Acute Proximal Interphalangeal Joint Palmar Plate Injury by Bone Channel Suture

Objective: Objective: To explore the surgical efect of suture through bone canal in the treatment of reconstruction of acute prox-imal interphalangeal joint metacarpal anchorage. Methods From July 2018 to August 2021, we retrospectively analyzed 9 cases of avulsion of metacarpal plate near interphalangeal joint, including 7 males and 2 females, aged 17-40 years, with an average of 34 years. There were 4 cases of index fnger, 3 cases of middle fnger and 2 cases of ring fnger. Early fexion and extension exercises were performed after opera-tion. The last follow-up included the range of motion of the proximal interphalangeal joint and joint pain. Results All patients were followed up (4-12 months) after operation.According to the TAM method, 7 cases were excellent and 2 cases were good. Conclusion Transosseous su-ture for acute proximal interphalangeal joint metacarpal reconstruction has the advantages of simple operation, safety, frm fxation and rapid postoperative recovery

Compressive hard thresholding pursuit algorithm for sparse signal recovery

Hard Thresholding Pursuit (HTP) is one of the important and efficient algorithms for reconstructing sparse signals. Unfortunately, the hard thresholding operator is independent of the objective function and hence leads to numerical oscillation in the course of iterations. To alleviate this drawback, the hard thresholding operator should be applied to a compressible vector. Motivated by this idea, we propose a new algorithm called Compressive Hard Thresholding Pursuit (CHTP) by introducing a compressive step first to the standard HTP. Convergence analysis and stability of CHTP are established in terms of the restricted isometry property of a sensing matrix. Numerical experiments show that CHTP is competitive with other mainstream algorithms such as the HTP, Orthogonal Matching Pursuit (OMP) and Subspace Pursuit (SP) algorithms both in the sparse signal reconstruction ability and average recovery runtime

De Novo Sequence and Copy Number Variants Are Strongly Associated with Tourette Disorder and Implicate Cell Polarity in Pathogenesis

We previously established the contribution of de novo damaging sequence variants to Tourette disorder (TD) through whole-exome sequencing of 511 trios. Here, we sequence an additional 291 TD trios and analyze the combined set of 802 trios. We observe an overrepresentation of de novo damaging variants in simplex, but not multiplex, families; we identify a high-confidence TD risk gene, CELSR3 (cadherin EGF LAG seven-pass G-type receptor 3); we find that the genes mutated in TD patients are enriched for those related to cell polarity, suggesting a common pathway underlying pathobiology; and we confirm a statistically significant excess of de novo copy number variants in TD. Finally, we identify significant overlap of de novo sequence variants between TD and obsessive-compulsive disorder and de novo copy number variants between TD and autism spectrum disorder, consistent with shared genetic risk

Rare X-linked variants carry predominantly male risk in autism, Tourette syndrome, and ADHD

© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Autism spectrum disorder (ASD), Tourette syndrome (TS), and attention-deficit/hyperactivity disorder (ADHD) display strong male sex bias, due to a combination of genetic and biological factors, as well as selective ascertainment. While the hemizygous nature of chromosome X (Chr X) in males has long been postulated as a key point of “male vulnerability”, rare genetic variation on this chromosome has not been systematically characterized in large-scale whole exome sequencing studies of “idiopathic” ASD, TS, and ADHD. Here, we take advantage of informative recombinations in simplex ASD families to pinpoint risk-enriched regions on Chr X, within which rare maternally-inherited damaging variants carry substantial risk in males with ASD. We then apply a modified transmission disequilibrium test to 13,052 ASD probands and identify a novel high confidence ASD risk gene at exome-wide significance (MAGEC3). Finally, we observe that rare damaging variants within these risk regions carry similar effect sizes in males with TS or ADHD, further clarifying genetic mechanisms underlying male vulnerability in multiple neurodevelopmental disorders that can be exploited for systematic gene discovery.This study was supported by grants from the National Institute of Mental Health to A.J.W. and M.W.S (R01MH115963), A.J.W. (R01NS105746), G.A.H. and J.A.T. (R01MH115958), Alyssa Rosen (R01MH115960), Donald L. Gilbert (R01MH115962), Samuel Kuperman (R01MH115961), Samuel H. Zinner (R01MH115993), Barbara J. Coffey (R01MH115959), B.W. (R25MH06048); from the Tourette Association of America to A.J.W. (Young Investigator Award); from the Human Genetics Institute of New Jersey to G.A.H. and J.A.T.; and the New Jersey Center for Tourette Syndrome and Associated Disorders (NJCTS) to G.A.H. and J.A.T.Peer reviewe

A massive proteogenomic screen identifies thousands of novel human protein coding sequences

<p>Accurate annotation of genes in the human genome is fundamental for biomedical research and genomic data interpretation. The Ensembl, RefSeq, and GENCODE consortiums continuously update the human genome annotations based on new computational and experimental evidence, and new proteins were identified constantly. The Genotype-Tissue Expression (GTEx) project has generated more than 15,000 RNA sequencing dataset from multiple-tissues of more than 800 donors which allows to model almost all transcripts and proteins in the human genome. Using proteins translated from the GTEx transcript model, more than 21 million in-silico trypsin-digested peptides were generated. To identify high-confidence novel proteins with proteomic support, we screened more than 2,000 proteomic projects in the PRIDE database and selected more than 50,000 mass spectrometry (MS) runs from 923 projects. These MS data were used to validate the predicted novel peptides. With a stringent standard, we identified almost 20,000 novel peptides. </p> <p>This dataset include files used in the the above analysis. More details can be found in the GitHub page (https://github.com/ATPs/human_novo_protein_2022). </p&gt

TP53INP2 knockdown inhibits inflammatory response and apoptosis after spinal cord injury

Abstract Background Spinal cord injury (SCI) is a traumatic neurological disorder with limited therapeutic options. Tumor protein p53‐inducible nuclear protein 2 (TP53INP2) is involved in the occurrence and development of various diseases, and it may play a role during SCI via affecting inflammation and neuronal apoptosis. This study investigated the associated roles and mechanisms of TP53INP2 in SCI. Methods Mouse and lipopolysaccharide (LPS)‐induced SCI BV‐2 cell models were constructed to explore the role of TP53INP2 in SCI and the associated mechanisms. Histopathological evaluation of spinal cord tissue was detected by hematoxylin and eosin staining. The Basso, Beattie, and Bresnahan score was used to measure the motor function of the mice, while the spinal cord water content was used to assess spinal cord edema. The expression of TP53INP2 was measured using RT‐qPCR. In addition, inflammatory factors in the spinal cord tissue of SCI mice and LPS‐treated BV‐2 cells were measured using enzyme‐linked immunosorbent assay. Apoptosis and related protein expression levels were detected by flow cytometry and western blot analysis, respectively. Results TP53INP2 levels increased in SCI mice and LPS‐treated BV‐2 cells. The results of in vivo and in vitro experiments showed that TP53INP2 knockdown inhibited the inflammatory response and neuronal apoptosis in mouse spinal cord tissue or LPS‐induced BV‐2 cells. Conclusions After spinal cord injury, TP53INP2 was upregulated, and TP53INP2 knockdown inhibited the inflammatory response and apoptosis

A robust training algorithm of discrete-time MIMO RNN and application in fault tolerant control of robotic system

In this paper, a novel robust training algorithm of multi-input multi-output recurrent neural network and its application in the fault tolerant control of a robotic system are investigated. The proposed scheme optimizes the gradient type training on basis of three new adaptive parameters, namely, dead-zone learning rate, hybrid learning rate, and normalization factor. The adaptive dead-zone learning rate is employed to improve the steady state response. The normalization factor is used to maximize the gradient depth in the training, so as to improve the transient response. The hybrid learning rate switches the training between the back-propagation and the real-time recurrent learning mode, such that the training is robust stable. The weight convergence and L 2 stability of the algorithm are proved via Lyapunov function and the Cluett's law, respectively. Based upon the theoretical results, we carry out simulation studies of a two-link robot arm position tracking control system. A computed torque controller is designed to provide a specified closed-loop performance in a fault-free condition, and then the RNN compensator and the robust training algorithm are employed to recover the performance in case that fault occurs. Comparisons are given to demonstrate the advantages of the control method and the proposed training algorithm

Stability of 1-Bit Compressed Sensing in Sparse Data Reconstruction

1-bit compressing sensing (CS) is an important class of sparse optimization problems. This paper focuses on the stability theory for 1-bit CS with quadratic constraint. The model is rebuilt by reformulating sign measurements by linear equality and inequality constraints, and the quadratic constraint with noise is approximated by polytopes to any level of accuracy. A new concept called restricted weak RSP of a transposed sensing matrix with respect to the measurement vector is introduced. Our results show that this concept is a sufficient and necessary condition for the stability of 1-bit CS without noise and is a sufficient condition if the noise is available

Heavy-Ball-Based Hard Thresholding Pursuit for Sparse Phase Retrieval Problems

We introduce a novel iterative algorithm, termed the Heavy-Ball-Based Hard Thresholding Pursuit for sparse phase retrieval problem (SPR-HBHTP), to reconstruct a sparse signal from a small number of magnitude-only measurements. Our algorithm is obtained via a natural combination of the Hard Thresholding Pursuit for sparse phase retrieval (SPR-HTP) and the classical Heavy-Ball (HB) acceleration method. The robustness and convergence for the proposed algorithm were established with the help of the restricted isometry property. Furthermore, we prove that our algorithm can exactly recover a sparse signal with overwhelming probability in finite steps whenever the initialization is in the neighborhood of the underlying sparse signal, provided that the measurement is accurate. Extensive numerical tests show that SPR-HBHTP has a markedly improved recovery performance and runtime compared to existing alternatives, such as the Hard Thresholding Pursuit for sparse phase retrieval problem (SPR-HTP), the SPARse Truncated Amplitude Flow (SPARTA), and Compressive Phase Retrieval with Alternating Minimization (CoPRAM)

Sliding mode-based active disturbance rejection control for vehicle steer-by-wire systems

This study presents a sliding mode-based active disturbance rejection control (SMADRC) scheme for a steer-by-wire (SbW) system in road vehicles. First, a plant model that describes the mechanical dynamics of the SbW system is elaborated, where the viscous friction and the self-aligning torque are regarded as external disturbances. Second, the design of SMADRC is exposited, in which a non-linear extended state observer is utilised to estimate the non-linearities existing in the plant model, and a sliding mode control component is used to cope with the effect of the non-linearities and guarantee the control robustness against system uncertainties and varying road conditions. Finally, experimental results are shown to demonstrate the superiority of the designed SMADRC in comparison with a conventional sliding mode controller and a PD-based active disturbance rejection controller (PDADRC)