ObjectiveTo investigate the clinical application value of thromboelastographic parameters in assessing coagulation function by analyzing the thromboelastographic features of patients with primary liver cancer （PLC）， and to provide a basis for coagulation management and prognostic evaluation in liver cancer patients. MethodsA retrospective analysis was performed for 1 253 PLC patients who were admitted to The First Affiliated Hospital of Xi’an Jiaotong University from May 2015 to December 2022. According to the presence or absence of cirrhosis， the patients were divided into non-cirrhosis group with 262 patients and cirrhosis group with 991 patients， and according to the presence or absence of HBV infection， they were divided into HBV infection group with 1 055 patients and non-HBV infection group with 198 patients. The patients were stratified based on the severity of liver cirrhosis （Child-Pugh class and MELD score） and liver reserve function （indocyanine green retention rate at 15 minutes ［ICGR15］）， and thromboelastography was used to measure thromboelastographic parameters （reaction time ［R］， coagulation formation time ［K］， α-angle， maximum thrombosis amplitude ［MA］， and coagulation composite index ［CI］） and conventional coagulation markers. The t-test was used for comparison of normally distributed continuous data between two groups； a one-way analysis of variance was used for comparison between multiple groups， and the least significant difference t-test was used for further comparison between two groups. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the Kruskal-Wallis H test was used for comparison between multiple groups， and the Bonferroni correction method was used for further comparison between two groups. The chi-square test was used for comparison of categorical data between grouips， and the Spearman test was used for correlation analysis. ResultsAmong the 991 patients in the cirrhosis group， 826 had Child-Pugh class A （5 — 6 points）， and 165 had Child-Pugh class B （7 — 9 points）； 812 had an MELD score of <10， and 179 had an MELD score of ≥10； 679 had an ICGR15 of <10%， and 294 had an ICGR15 of ≥10%. Compared with the patients with Child-Pugh class A， the patients with Child-Pugh class B had a significantly longer K time and significant reductions in α-angle， MA， and CI （all P <0.001）； compared with the MELD score <10 group， the MELD score ≥10 group had a significantly longer K time and significant reductions in α-angle， MA， and CI （all P<0.001）； compared with the ICGR15 <10% group， the ICGR15 ≥10% group had a significantly longer K time and a significant reduction in MA （both P <0.001）. Among the 1 253 patients， MA was strongly positively correlated with fibrinogen and platelet count （r=0.675 and 0.667， both P<0.001）； The MA had a weak correlation with Child-Pugh score， MELD score， and ICGR15 （r=-0.112， -0.250， and -0.117， all P<0.001）， while the K time，α-angle and CI were weakly correlated with the MELD score （r=0.222， -0.184， and -0.183， all P<0.001），R time was negatively correlated with ICGR15 （r=-0.080， P=0.005）. The HBV infection group had significantly higher MA and CI than the non-HBV infection group （P<0.05）. ConclusionThromboelastography can sensitively identify the hypocoagulable state associated with the progression of liver cirrhosis and the hypercoagulable tendency in HBV-related liver cancer， which provides an important reference for individualized anticoagulant therapy in clinical practice.

BACKGROUND:With the continuous progress of science and technology,the introduction of new technologies and methods will bring more possibilities and new breakthroughs for the application of shape memory alloys in the fields of assistive and rehabilitation. OBJECTIVE:To review the application status of shape memory alloys in assistive and rehabilitation equipment,discuss their main methods,techniques and results,summarize and put forward suggestions,hoping that shape memory alloys can be continuously optimized and bring more new changes for the development of assistive and rehabilitation equipment. METHODS:WanFang,PubMed,and Web of Science databases were searched by computer."Shape memory alloys,application progress,orthodontics,orthopedic,prosthesis,rehabilitation,properties,implantation,mechanical properties,nickel-titanium memory alloys,actuation"were used as Chinese search terms."Shape memory alloys,application,orthodontics,orthopedic,prosthetics,rehabilitation,properties,implant,drive,progress,prostheses"were used as English search terms.Finally,91 articles were included for review. RESULTS AND CONCLUSION:(1)Shape memory alloy has the characteristics of corrosion resistance,wear resistance,biocompatibility,fatigue resistance,kink resistance and other properties.Compared with other traditional materials(stainless steel,titanium alloy,cobalt-chromium alloy,etc.),shape memory alloy has lower elastic modulus and no biological toxicity,which is suitable for long-term implantation as an implant prosthesis.Due to its shape memory effect and excellent mechanical properties,it is mainly used as a driving element or as a bridge connecting the device and the human body in artificial limbs,orthoses and rehabilitation equipment.(2)The use of shape memory alloy drive elements can reduce the weight of the device,eliminate noise,easy to operate,easy to carry,better assist joint movement;compared with the use of pneumatic,hydraulic,and electrical drive methods of the device,it has obvious advantages.(3)In addition,shape memory alloy can produce permanent and stable stress during deformation.Compared with stainless steel,titanium alloy and aluminum alloy,shape memory alloy has a higher material recovery rate and does not need to be replaced and adjusted frequently,so it is more practical in the correction of deformity.(4)At present,shape memory alloy is most commonly used in orthosis,and the best clinical application effect is in stapes prosthesis.However,due to the limitations of technology and cost,shape memory alloys are rarely used in artificial limbs and rehabilitation equipment,and there is a lack of large sample size studies on the application effect.(5)Although shape memory alloys have been developed in the field of auxiliary and rehabilitation,there are still many problems:it is difficult to accurately control the shape memory alloys;the cooling speed of shape memory alloy is slow;the deformation speed of shape memory alloy cannot be controlled;there is a lack of comparative research and expert consensus on shape memory alloys with different properties;shape memory alloys are costly and expensive.(6)In the future,attention should be paid to the development of new shape memory alloys,increase comparative research,and use new technologies and methods(such as 4D printing)to solve the existing problems,so as to develop high-performance assistive devices and rehabilitation equipment.

With the rapid development of sequencing technologies, the detection of alternative polyadenylation (APA) in mammals has become more precise. APA precisely regulates gene expression by altering the length and position of the poly(A) tail, and is involved in various biological processes such as disease occurrence and embryonic development. The research on APA in mammals mainly focuses on the following aspects:(1) identifying APA based on transcriptome data and elucidating their characteristics; (2) investigating the relationship between APA and gene expression regulation to reveal its important role in life regulation;(3) exploring the intrinsic connections between APA and disease occurrence, embryonic development, differentiation, and other life processes to provide new perspectives and methods for disease diagnosis and treatment, as well as uncovering embryonic development regulatory mechanisms. In this review, the classification, mechanisms and functions of APA were elaborated in detail and the methods for APA identifying and APA data resources based on various transcriptome data were systematically summarized. Moreover, we epitomized and provided an outlook on research on APA, emphasizing the role of sequencing technologies in driving studies on APA in mammals. In the future, with the further development of sequencing technology, the regulatory mechanisms of APA in mammals will become clearer.

How to effectively promote osseointegration of dental implants remains a pressing clinical challenge. Low-intensity pulsed ultrasound (LIPUS) has demonstrated remarkable efficacy in accelerating the healing of various bodily tissues, including bone tissue. In recent years, there has been extensive research on its application in promoting osseointegration in the field of dental implantology. Animal studies have shown that LIPUS exhibits significant potential in facilitating osseointegration of dental implants. In vitro experiments have further revealed that LIPUS can enhance the expression of key osteogenic factors, extracellular matrix mineralization, and induce local neurons to secrete αCGRP. Through the regulation of signaling pathways such as bone morphogenetic protein/Smad (Bmp/Smad), mitogen-activated protein kinase (MAPK), and phosphatidylinositol 3-kinase/protein kinase B (PI3k/Akt), LIPUS promotes the proliferation, migration, and osteogenic differentiation of osteogenic-related cells, thereby enhancing osseointegration of dental implants. Additionally, clinical studies have shown that bone mass increases around the implants after LIPUS treatment, with more pronounced growth observed on the buccal bone plate than on the palatal side. Furthermore, there is a lack of research that systematically summarizes the clinical evidence, in vitro and in vivo studies, and mechanisms of action regarding the role of LIPUS in promoting osseointegration of implants. Therefore, the aim of this study is to discuss the mechanisms of effect of LIPUS on osseointegration of implants, with the goal of further enhancing the outcome of implant-supported prosthodontic treatment.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Hepatic encephalopathy is a difficult and critical disease with rapid progression and limited treatment methods in the field of liver disease， and it is urgently needed to make breakthroughs in its pathogenesis. Selection of appropriate prevention and treatment strategies is of great importance in delaying disease progression and reducing the incidence and mortality rates. This article reviews the theory of “turbid toxin pathogenesis” and related prevention and treatment strategies for hepatic encephalopathy in traditional Chinese medicine/Zhuang medicine， proposes a new theory of “turbid toxin pathogenesis”， analyzes the scientific connotations of “turbid”， “toxin”， and the theory of “turbid toxin pathogenesis”， and constructs the “four-step” prevention and treatment strategies for hepatic encephalopathy， thereby establishing the new clinical prevention and treatment regimen for hepatic encephalopathy represented by “four prescriptions and two techniques” and clarifying the effect mechanism and biological basis of core prescriptions and techniques in the prevention and treatment of hepatic encephalopathy， in order to provide a reference for the prevention and treatment of hepatic encephalopathy.

N-acetyl-p-aminophenol （APAP） is an antipyretic analgesic commonly used in clinical practice， and APAP overdose can cause severe liver injury and even death. In recent years， the incidence rate of APAP-induced liver injury （AILI） tends to increase， and it has become the second most common cause of liver transplantation worldwide. Autophagy is a highly conserved catabolic process that removes unwanted cytosolic proteins and organelles through lysosomal degradation to achieve the metabolic needs of cells themselves and the renewal of organelles. A large number of studies have shown that autophagy plays a key role in the pathophysiology of AILI， involving the mechanisms such as APAP protein conjugates， oxidative stress， JNK activation， mitochondrial dysfunction， inflammatory response and apoptosis. This article elaborates on the biological mechanism of autophagy in AILI， in order to provide a theoretical basis for the treatment of AILI and the development of autophagy regulators.

Messenger ribonucleic acid (mRNA) is a promising therapeutic drug with great potential in the fields of immunology, oncology, vaccines and inborn metabolic diseases. However, due to its instability and susceptibility to nuclease degradation, efficient delivery vectors are required. Lipid nanoparticles (LNPs) are recognized as the most mature delivery vectors due to their advantages of easy formulation, high stability, efficient cell uptake and endosomal escape. However, the accumulation of LNPs in the liver severely limits the targeting and treatment of mRNA-LNP technology beyond the liver. To overcome this obstacle, researchers have been focusing on various means to achieve precise delivery of extrahepatic tissues and organs. This article mainly expounds the research progress of LNP-specific delivery mRNA from three aspects: endogenous targeting, active targeting and selection of administration route, in order to provide ideas and directions for the design of new mRNA-LNP delivery systems in the future.