基于HAND的流域洪水淹没快速分析技术

快速分析计算流域洪水淹没,对于防洪具有重要作用,而基于水动力学模型的经典淹没算法在时效性方面存在不足,制约防洪“四预”功能实现和数字孪生流域建设。针对此,本文建立了基于HAND(Height Above Nearest Drainage)的形态淹没模型,用于快速分析流域洪水淹没情况,在乐安河流域上游进行了应用验证。结果表明,模型可在5秒内完成洪水淹没计算,对四场历史洪水和三场设计洪水淹没范围的总体模拟精度平均为0.95,达到水动力学模型的模拟精度;对淹没水深的模拟存在较大误差,平均误差为0.79 m。基于HAND的形态淹没模型可快速绘制全流域洪水淹没范围图,大幅提升影响预报和防洪预演的时效性水平。

子痫前期病人长链非编码RNA H19和长链非编码RNA HAND2-AS1表达水平与胰岛素抵抗的相关性研究

目的检测子痫前期病人胎盘组织、血清长链非编码RNA H19(LncRNA H19)与长链非编码RNAHAND2-AS1(Ln⁃cRNA HAND2-AS1)表达水平,并分析其与病人胰岛素抵抗(IR)的相关性。方法将2021年1—12月在唐山市妇幼保健院建卡的子痫前期孕妇105例作为子痫前期组,根据子痫前期孕妇严重程度分为轻度子痫前期组与重度子痫前期组,另选取同期孕周、年龄相符的健康孕妇97例作为对照组,收集所有孕妇身体质量指数(BMI)、孕周、收缩压、舒张压、空腹胰岛素(FINS)、空腹血糖(FBG)等一般资料,并计算稳态模型的IR指数(HOMA-IR);实时荧光定量PCR(qRT-PCR)法测定孕妇血清、胎盘组织中LncRNA H19,LncRNA HAND2-AS1水平;比较对照组与子痫前期组、轻度子痫前期组与重度子痫前期组间血清、胎盘组织LncRNA H19、LncRNA HAND2-AS1水平;Pearson法分析子痫前期孕妇血清、胎盘组织LncRNA H19、LncRNA HAND2-AS1与HOMA-IR的相关性。结果子痫前期组病人收缩压、舒张压高于对照组(P<0.05),且重度子痫前期病人收缩压、舒张压高于轻度子痫前期病人,孕周低于轻度子痫前期病人(P<0.05);与对照组相比,子痫前期组孕妇24 h尿蛋白、FBG[(5.84±0.97)mmol/L比(4.22±0.70)mmol/L]、FINS[(13.37±2.23)mU/L比(7.52±1.25)mU/L]、HOMI-IR水平(3.47±0.57比1.41±0.23)升高(P<0.05),且重度子痫前期孕妇24 h尿蛋白、FBG[(6.90±1.15)mmol/L比(5.24±0.85)mmol/L]、FINS[(13.97±2.32)mU/L比(13.05±2.17)mU/L]、HOMI-IR水平(4.27±0.71比3.03±0.50)高于轻度子痫前期孕妇(P<0.05);与对照组相比,子痫前期组孕妇血清、胎盘组织Ln⁃cRNA H19(2.52±1.42比1.01±0.15,3.75±0.62比1.02±0.17)与LncRNA HAND2-AS1水平(1.98±0.33比1.01±0.15,2.87±0.47比1.02±0.17)升高(P<0.05),且重度子痫前期孕妇血清、胎盘组织LncRNA H19(2.84±0.47比2.34±0.39,4.28±0.71比3.45±0.57)与LncRNA HAND2-AS1水平(2.59±0.43比1.63±0.27,3.56±0.59比2.49±0.41)高于轻度子痫前期孕妇(P<0.05);子痫前期病人血清与胎盘组织间LncRNA H19水平呈正相关(r=0.55,P<0.05),血清与胎盘组织间LncRNA HAND2-AS1水平呈正相关性(r=0.65,P<0.05)。子痫前期孕妇血清、胎盘组织LncRNA H19水平分别与HOMI-IR呈正相关(r=0.53、0.59,P<0.05);血清、胎盘组织LncRNA HAND2-AS1水平分别与HOMI-IR呈正相关(r=0.60、0.61,P<0.05)。结论子痫前期病人血清、胎盘组织LncRNA H19、LncRNA HAND2-AS1高表达,二者与IR密切相关,可能通过影响IR参与子痫前期发生发展。

基于隐喻与转喻的人体多义词hand的认知研究及其教学启示

人体是人类认知世界的起点,人体词的义项拓展严格遵循隐喻、转喻路径进行生成和演化。为帮助英语学习者更好地理解、记忆多义词,从隐喻映射和转喻映射角度出发,考察人体多义词hand的义项拓展路径及其类别。研究发现,hand的义项派生共有七种映射路径,分别为基本、抽象、人物、形貌、意动、计量、修饰,并探讨如何基于人体词分析其他多义词的义项拓展,尝试为二语词汇学习和教学提供思路。

Hand Cooling Enhances the Proprioceptive Drift during Rubber Hand Illusion

Background: The neural representation of the body is easily altered by integrating multiple sensory signals in the brain. The “Rubber Hand Illusion” (RHI) is one of the most popular experimental paradigms to investigate this phenomenon. During this illusion, ownership of a rubber hand is temporarily induced. It was shown that external and continuous cooling of the palm enhanced the RHI, suggesting an association between altered the autonomic nervous system regulation and altered the sense of ownership of a specific limb. Purpose: To investigate whether artificially cooling the entire hand for a short period affects the magnitude of the illusion. Methods: Participants immersed their entire hand in cool, cold, or warm water for 1 min before the RHI procedure. Results: We found that cooling the entire hand enhanced the proprioceptive drift during the RHI but not the subjective feeling of ownership. In contrast, warming and intense cooling of the entire hand did not affect the RHI strength. Conclusion: Our results suggest that transient and moderate cooling of the entire hand was sufficient in enhancing the illusory disembodiment of one’s own hand.

Comparison between Care Strategies for Patients with Osteoarthritis of the Hands Based on the Use of Joint Protection, Assistive Technology and Exercises

Background: Osteoarthritis (OA) is a disabling disease that can affect 6% to 12% of the adult population and more than a third of people over 65 years of age. Purpose: To assess whether a group of people with hand osteoarthritis (hOA) who received different types of treatment improved their function after two years of follow-up. Method: The entire sample (n = 97) underwent three follow-up assessments regarding anthropometric parameters of the upper limbs and ability to perform functional activities. Subsequently, the sample was divided into two groups for the intervention periods, called the First Period (n = 73) and the Second Period (n = 24);the First Period kept the same protocol with orientations, and the Second Period went to an intervention with orientation strength exercises and use of orthosis. Findings: In the separate analysis of the three questions of the DASH pain module, no differences were found between the assessment moments for groups of guidelines, treatment, or symptoms. Significant effects were observed for F(2, 162) = 3.5, p = 0.033, η2 = 0.04, and interaction for moments and intervention F(2, 162) = 4.3, p = 0.016, η2 = 0.05. Implications: It can be concluded that only guidance treatment does not benefit patients with hand osteoarthritis. In contrast, guidance, exercise, and orthosis treatment can significantly improve the disease.

Tenosynovitis of hand: Causes and complications

Tenosynovitis represents a common clinical condition characterized by inflam-mation of the synovium that encases the tendon sheath.Although tenosynovities may be noted in any tendon in the body,extremities such as hand,and foot remain the sites of high predilection to acquire this condition.The predominant cause of this predilection rests in the intricate tendon arrangements in these extremities that permit fine motor actions.This editorial explores the common causes and the complications associated with this condition to improve the understanding of the readers of this common condition encountered in our everyday clinical practice.

Dynamic Hand Gesture-Based Person Identification Using Leap Motion and Machine Learning Approaches

Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing communities.In Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for communication.However,existing JSL recognition systems have faced significant performance limitations due to inherent complexities.In response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning features.Our system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL gestures.Simultaneously,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second stream.Then,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL gestures.After reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the classification.To assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)dataset.Our results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

Virtual Keyboard:A Real-Time Hand Gesture Recognition-Based Character Input System Using LSTM and Mediapipe Holistic

In the digital age,non-touch communication technologies are reshaping human-device interactions and raising security concerns.A major challenge in current technology is the misinterpretation of gestures by sensors and cameras,often caused by environmental factors.This issue has spurred the need for advanced data processing methods to achieve more accurate gesture recognition and predictions.Our study presents a novel virtual keyboard allowing character input via distinct hand gestures,focusing on two key aspects:hand gesture recognition and character input mechanisms.We developed a novel model with LSTM and fully connected layers for enhanced sequential data processing and hand gesture recognition.We also integrated CNN,max-pooling,and dropout layers for improved spatial feature extraction.This model architecture processes both temporal and spatial aspects of hand gestures,using LSTM to extract complex patterns from frame sequences for a comprehensive understanding of input data.Our unique dataset,essential for training the model,includes 1,662 landmarks from dynamic hand gestures,33 postures,and 468 face landmarks,all captured in real-time using advanced pose estimation.The model demonstrated high accuracy,achieving 98.52%in hand gesture recognition and over 97%in character input across different scenarios.Its excellent performance in real-time testing underlines its practicality and effectiveness,marking a significant advancement in enhancing human-device interactions in the digital age.

Epidemiology of Hand Injuries That Presented to the Emergency Department of a Tertiary Care Facility in Suburban Mumbai, India: A Study Including 489 Patients

Background: Hand injuries are very common and responsible for a significant number of emergency department (ED) visits, most of which are not to hand specialists [1]. The functionality and outcome of hand injuries can vary significantly depending on the mechanism and pattern of injuries, which is why it is imperative for emergency physicians to recognize the complexities, and the potential repercussion of missed injuries in such cases. Objective: The aim of this study is to provide epidemiological information on hand injuries and their patterns. The objective is 1) to assess whether most hand injuries are superficial (simple), or involve underlying deeper structures (complex) and 2) to assess whether most hand injuries presented to the emergency department were managed by the emergency physician or plastic/orthopaedic surgeon. Methods: This retrospective single-centre observational study conducted at an emergency department in a tertiary care hospital in Mumbai, India collected data from hand trauma patients using a standardized documentation form. Demographic data, trauma-related data, and disposition plans were analysed. Results: A total of 489 cases sustained hand injuries over a period of one year. The patients were predominantly males in the 20 - 30 year age group and injuries were mainly sustained over the right hand. Most of the injuries were sustained at home (42%). The most common mechanism (34%) was sharp object injury (including needle-stick and other sharps in hospital), followed by blunt injury (30%). Among grievous hand injuries, door jamb was a mechanism noted in 11% of patients, accounting for 50% of all crush injuries. Lacerations were the most common pattern (24.7%) noticed, followed closely by fractures (23.3%). Digits II - IV were injured most commonly (54%), followed by carpals (14%) and the thumb (10%). Nearly 80% of the hand injuries were managed by emergency physicians alone, with 61% of cases involving superficial structures. Though 14% of the cases required plastic surgery intervention, the initial evaluation of all these patients was performed by the emergency physician. Conclusions: Our study highlights the burden of hand injuries on the emergency physician, as well as the odds of missed injuries, directly indicating the necessity of a thorough anatomical knowledge of the structures of the hand, and in turn, a proper physical examination. A dedicated registry for hand trauma would help quantify the mechanism and pattern of injuries, and formulate preventive strategies.

Expression and clinical significance of pattern recognition receptor-associated genes in hand, foot and mouth disease

Objective:To explore which pattern recognition receptors(PRRs)play a key role in the development of hand,foot,and mouth disease(HFMD)by analyzing PRR-associated genes.Methods:We conducted a comparative analysis of PRR-associated gene expression in human peripheral blood mononuclear cells(PBMCs)infected with enterovirus 71(EV-A71)which were derived from patients with HFMD of different severities and at different stages.A total of 30 PRR-associated genes were identified as significantly upregulated both over time and across different EV-A71 isolates.Subsequently,ELISA was employed to quantify the expression of the six most prominent genes among these 30 identified genes,specifically,BST2,IRF7,IFI16,TRIM21,MX1,and DDX58.Results:Compared with those at the recovery stage,the expression levels of BST2(P=0.027),IFI16(P=0.016),MX1(P=0.046)and DDX58(P=0.008)in the acute stage of infection were significantly upregulated,while no significant difference in the expression levels of IRF7(P=0.495)and TRIM21(P=0.071)was found between different stages of the disease.The expression levels of BST2,IRF7,IFI16 and MX1 were significantly higher in children infected with single pathogen than those infected with mixed pathogens,and BST2,IRF7,IFI16 and MX1 expression levels were significantly lower in coxsackie B virus(COXB)positive patients than the negative patients.Expression levels of one or more of BST2,IRF7,IFI16,TRIM21,MX1 and DDX58 genes were correlated with PCT levels,various white blood cell counts,and serum antibody levels that reflect disease course of HFMD.Aspartate aminotransferase was correlated with BST2,MX1 and DDX58 expression levels.Conclusions:PRR-associated genes likely initiate the immune response in patients at the acute stage of HFMD.

Long noncoding RNAs HAND2-AS1 ultrasound microbubbles suppress hepatocellular carcinoma progression by regulating the miR-873-5p/tissue inhibitor of matrix metalloproteinase-2 axis

BACKGROUND Increasing data indicated that long noncoding RNAs(lncRNAs)were directly or indirectly involved in the occurrence and development of tumors,including hepatocellular carcinoma(HCC).Recent studies had found that the expression of lncRNA HAND2-AS1 was downregulated in HCC tissues,but its role in HCC progression is unclear.Ultrasound targeted microbubble destruction mediated gene transfection is a new method to overexpress genes.AIM To study the role of ultrasound microbubbles(UTMBs)mediated HAND2-AS1 in the progression of HCC,in order to provide a new reference for the treatment of HCC.METHODS In vitro,we transfected HAND2-AS1 siRNA into HepG2 cells by UTMBs,and detected cell proliferation,apoptosis,invasion and epithelial-mesenchymal transition(EMT)by cell counting kit-8 assay,flow cytometry,Transwell invasion assay and Western blotting,respectively.In addition,we transfected miR-837-5p mimic into UTMBs treated cells and observed the changes of cell behavior.Next,the UTMBs treated HepG2 cells were transfected together with miR-837-5p mimic and tissue inhibitor of matrix metalloproteinase-2(TIMP2)overexpression vector,and we detected cell proliferation,apoptosis,invasion and EMT.In vivo,we established a mouse model of subcutaneous transplantation of HepG2 cells and observed the effect of HAND2-AS1 silencing on tumor formation ability.RESULTS We found that UTMBs carrying HAND2-AS1 restricted cell proliferation,invasion,and EMT,encouraged apoptosis,and HAND2-AS1 silencing eliminated the effect of UTMBs.Additionally,miR-873-5p targets the gene HAND2-AS1,which also targets the 3’UTR of TIMP2.And miR-873-5p mimic counteracted the impact of HAND2-AS1.Further,miR-873-5p mimic solely or in combination with pcDNA-TIMP2 had been transformed into HepG2 cells exposed to UTMBs.We discovered that TIMP2 reversed the effect of miR-873-5p mimic caused by the blocked signalling cascade for matrix metalloproteinase(MMP)2/MMP9.In vivo results showed that HAND2-AS1 silencing significantly inhibited tumor formation in mice.CONCLUSION LncRNA HAND2-AS1 promotes TIMP2 expression by targeting miR-873-5p to inhibit HepG2 cell growth and delay HCC progression.

Design and Implementation of Hand Gesture Detection System Using HM Model for Sign Language Recognition Development

Gesture detection is the primary and most significant step for sign language detection and sign language is the communication medium for people with speaking and hearing disabilities. This paper presents a novel method for dynamic hand gesture detection using Hidden Markov Models (HMMs) where we detect different English alphabet letters by tracing hand movements. The process involves skin color-based segmentation for hand isolation in video frames, followed by morphological operations to enhance image trajectories. Our system employs hand tracking and trajectory smoothing techniques, such as the Kalman filter, to monitor hand movements and refine gesture paths. Quantized sequences are then analyzed using the Baum-Welch Re-estimation Algorithm, an HMM-based approach. A maximum likelihood classifier is used to identify the most probable letter from the test sequences. Our method demonstrates significant improvements over traditional recognition techniques in real-time, automatic hand gesture recognition, particularly in its ability to distinguish complex gestures. The experimental results confirm the effectiveness of our approach in enhancing gesture-based sign language detection to alleviate the barrier between the deaf and hard-of-hearing community and general people.

Analysis of Hand Hygiene Knowledge,Compliance,and Influencing Factors Among Psychiatric Healthcare Workers

Objective:To evaluate the knowledge,compliance,and influencing factors of hand hygiene among psychiatric healthcare workers.Methods:68 healthcare workers who worked in the Department of Psychiatry between September 2023 and May 2024 were selected to assess their knowledge of hand hygiene and compliance by questionnaire as well as to analyze their influencing factors.Results:Knowledge of hand hygiene among healthcare workers was less than 90%,and doctors’knowledge was lower than that of nurses(P<0.05).The healthcare workers’compliance with hand hygiene was lower than 80%,and the adherence of doctors was lower than that of nurses(P<0.05).Analysis of influencing factors reveals that skepticism about the effectiveness of rapid disinfectants/hand washing,skin irritation from disinfectants/cleaning agents,and busy work schedules with time constraints are the main factors affecting healthcare workers’compliance with hand hygiene,with P<0.05 compared with the same group.Conclusion:Psychiatric healthcare workers’knowledge of hand hygiene as well as compliance with it is low,and there are various factors affecting it,so targeted training is required to strengthen their hand hygiene implementation.

Commodity Value Theory-Invisible Hands Seen

Through the revelation of“commodity value”,the“invisible hand”described by Adam Smith is now clearly visible.It is precisely“commodity value”that guides people to seek benefits for themselves and for others,adding enormous wealth to society.

Application of PDCA Cycle in Hand Hygiene Management of Psychiatric Medical Staff

Objective:To study the application effect of the plan-do-check-act(PDCA)cycle management in the hand hygiene management of psychiatric medical staff.Methods:One hundred and twenty medical staff from a psychiatric hospital from May 2023 to December 2023 were selected and divided into two groups.The control group(May 2023 to August 2023)applied the conventional management model,and the observation group(September 2023 to December 2023)applied the PDCA cycle management.The hand hygiene compliance,hand hygiene knowledge,and hygiene qualifications were compared,including the amount of hand sanitizer used.Results:The proportion of medical staff’s hand hygiene compliance and hand hygiene knowledge mastery scores in the observation group were higher than those in the control group(P<0.05);the hand hygiene passing rate in the observation group was higher than that of the control group(P<0.05);the daily amount of hand sanitizer per patient bed and the amount of hand sanitizer used was higher than that of the control group(P<0.05).Conclusion:The PDCA cycle management model for psychiatric medical staff promoted the improvement of hand hygiene compliance and increased their hand hygiene qualifications.It is suitable for further popularization and application in future clinical practice.

Transmission Dynamics and Optimal Control Strategies of a Hand-Foot-Mouth Disease Model with Treatment and Vaccination Interventions

In this article, the transmission dynamics of a Hand-Foot-Mouth disease model with treatment and vaccination interventions are studied. We calculated the basic reproduction number and proved the global stability of disease-free equilibrium when R0 R0 > 1. Meanwhile, we obtained the optimal control strategies minimizing the cost of intervention and minimizing the infected person. We also give some numerical simulations to verify our theoretical results.

lncRNA HAND2-AS1通过调节miR-21表达对子宫内膜异位症患者子宫内膜基质细胞迁移和侵袭的抑制作用

目的:探讨子宫内膜异位症(EMT)患者子宫内膜组织中长链非编码RNAs(lncRNAs)HAND2-AS1对异位子宫内膜(EC)组织中子宫内膜基质细胞(ESCs)增殖、迁移和侵袭能力的影响,并阐明其可能机制。方法:收集30例EMT患者(EMT组)的EC组织和30例健康育龄女性(对照组)的子宫内膜组织,分离子宫内膜组织获取ESCs。采用脂质体转染法转染EMT患者EC组织的ESCs,并将ESCs分为pcDNA组(转染pcDNA空质粒)、HAND2-AS1组(转染HAND2-AS1过表达质粒)、mimic NC组(转染mimic NC)、miR-21 mimic组(转染miR-21 mimic)、pcDNA+mimic NC组(联合转染pcDNA和mimic NC)、HAND2-AS1+mimic NC组(联合转染HAND2-AS1过表达质粒和mimic NC)、pcDNA+miR-21 mimic组(联合转染pcDNA空质粒和miR-21 mimic)和HAND2-AS1+miR-21 mimic组(联合转染HAND2-AS1过表达质粒和miR-21 mimic),另设未转染的细胞为空白对照组。采用实时荧光定量PCR(RT-qPCR)法检测2组研究对象子宫内膜组织和ESCs中HAND2-AS1 mRNA和miR-21表达水平,采用Pearson相关系数分析其相关性。采用生物信息学软件Starbase预测lncRNA HAND2-AS1与miR-21的靶向作用关系,荧光素酶基因报告实验进行验证。CCK-8法检测各组ESCs增殖活性,Transwell小室实验检测ESCs的迁移和侵袭数。结果:2组研究对象年龄、体质量指数(BMI)和血清中卵泡刺激素(FSH)、黄体生成素(LH)及催乳素(PRL)水平比较差异均无统计学意义(P<0.05)。与对照组比较,EMT组患者血清中雌二醇(E2)水平升高(P<0.05),EMT组患者EC组织中HAND2-AS1 mRNA表达水平降低(P<0.05),miR-21表达水平升高(P<0.05);与对照组比较,EMT组ESCs中HAND2-AS1 mRNA表达水平降低(P<0.05),miR-21表达水平明显升高(P<0.01)。Pearson相关系数分析,对照组研究对象HAND2-AS1与miR-21表达水平无明显相关性(r=0.34,P>0.05),EMT组患者ES组织中和ESCs中HAND2-AS1与miR-21表达水平呈负相关关系(r=-0.57,P<0.05)。RT-qPCR法检测,与空白对照组比较,HAND2-AS1组ESCs中HAND2-AS1 mRNA表达水平明显升高(P<0.01),miR-21 mimic组ESCs中miR-21表达水平明显升高(P<0.01),HAND2-AS1+mimic NC组ESCs中miR-21表达水平降低(P<0.05),pcDNA+miR-21 mimic组ESCs中miR-21表达水平明显升高(P<0.01);与pcDNA+miR-21 mimic组比较,HAND2-AS1+miR-21 mimic组ESCs中miR-21表达水平降低(P<0.05)。lncRNA HAND2-AS1与miR-21存在潜在结合位点;双荧光素酶基因报告实验,与mimic NC组比较,miR-21 mimic组HAND2-AS1-WT中荧光素酶活性明显降低(P<0.01)。与空白对照组比较,HAND2-AS1+mimic NC组ESCs增殖活性、迁移和侵袭数均明显降低(P<0.05或P<0.01),pcDNA+miR-21 mimic组ESCs增殖活性、迁移和侵袭数升高(P<0.05);与pcDNA+miR-21 mimic组比较,HAND2-AS1+miR-21 mimic组ESCs增殖活性、迁移和侵袭数均降低(P<0.05)。结论:HAND2-AS1在EMT患者EC组织和ESCs中表达明显降低,其可通过靶向抑制miR-21表达下调EC组织中ESCs的增殖、迁移和侵袭,从而参与EMT的发生发展。

A Novel SE-CNN Attention Architecture for sEMG-Based Hand Gesture Recognition

In this article,to reduce the complexity and improve the generalization ability of current gesture recognition systems,we propose a novel SE-CNN attention architecture for sEMG-based hand gesture recognition.The proposed algorithm introduces a temporal squeeze-and-excite block into a simple CNN architecture and then utilizes it to recalibrate the weights of the feature outputs from the convolutional layer.By enhancing important features while suppressing useless ones,the model realizes gesture recognition efficiently.The last procedure of the proposed algorithm is utilizing a simple attention mechanism to enhance the learned representations of sEMG signals to performmulti-channel sEMG-based gesture recognition tasks.To evaluate the effectiveness and accuracy of the proposed algorithm,we conduct experiments involving multi-gesture datasets Ninapro DB4 and Ninapro DB5 for both inter-session validation and subject-wise cross-validation.After a series of comparisons with the previous models,the proposed algorithm effectively increases the robustness with improved gesture recognition performance and generalization ability.

室间隔缺损与HAND2基因罕见变异的关联分析

目的对室间隔缺损(ventricular septal defect,VSD)与HAND2基因启动子区罕见变异的关联性进行分析,并对相关分子机制进行初步探索。方法收集349例VSD组患儿和345例健康对照组儿童血液样本,通过聚合酶链反应扩增目的片段并进行测序,确定HAND2基因启动子区的罕见变异位点。使用双荧光素酶检测进行变异位点功能分析,并通过电泳迁移率变动分析进行分子机制研究,同时使用TRANSFAC和JASPAR数据库预测转录因子。结果通过测序发现3个变异位点(g.173530852A>G、g.173531173A>G和g.173531213C>G)只出现在10例VSD患儿的HAND2基因启动子上,其中4例患儿仅有1个变异位点。双荧光素酶检测显示g.173531213C>G降低了HAND2基因启动子转录活性。电泳迁移率变动分析和转录因子预测提示g.173531213C>G产生了1个转录因子结合位点。结论HAND2基因启动子区的罕见变异g.173531213C>G可能通过影响转录因子的结合,进而参与VSD的发生发展。