The mediating role of trait impulsivity in the relation between cue-induced craving and functional connectivity within the salience network among abstinent patients with methamphetamine use disorder.

Given the widespread use and relapse of methamphetamine (METH), it has caused serious public health burdens globally. However, the neurobiological basis of METH addiction remains poorly understood. Therefore, this study aimed to use magnetic resonance imaging (MRI) to investigate changes in brain networks and their connection to impulsivity and drug craving in abstinent individuals with METH use disorder (MUDs). A total of 110 MUDs and 55 age- and gender-matched healthy controls (HCs) underwent resting-state functional MRI and T1-weighted imaging scans, and completed impulsivity and cue-induced craving measurements. We applied independent component analysis to construct functional brain networks and multivariate analysis of covariance to investigate group differences in network connectivity. Mediation analyses were conducted to explore the relationships among brain-network functional connectivity (FC), impulsivity, and drug craving in the patients. MUDs showed increased connectivity in the salience network (SN) and decreased connectivity in the default mode network compared to HCs. Impulsivity was positively correlated with FC within the SN and played a completely mediating role between METH craving and FC within the SN in MUDs. These findings suggest alterations in functional brain networks underlying METH dependence, with SN potentially acting as a core neural substrate for impulse control disorders.

Alterations in the brain functional network of abstinent male individuals with methamphetamine use disorder.

Methamphetamine is a highly addictive psychostimulant drug that is abused globally and is a serious threat to health worldwide. Unfortunately, the specific mechanism underlying addiction remains unclear. Thus, this study aimed to investigate the characteristics of functional connectivity in the brain network and the factors influencing methamphetamine use disorder in patients using magnetic resonance imaging. We included 96 abstinent male participants with methamphetamine use disorder and 46 age- and sex-matched healthy controls for magnetic resonance imaging. Compared with healthy controls, participants with methamphetamine use disorder had greater impulsivity, fewer small-world attributes of the resting-state network, more nodal topological attributes in the cerebellum, greater functional connectivity strength within the cerebellum and between the cerebellum and brain, and decreased frontoparietal functional connectivity strength. In addition, after controlling for covariates, the partial correlation analysis showed that small-world properties were significantly associated with methamphetamine use frequency, psychological craving, and impulsivity. Furthermore, we revealed that the small-word attribute significantly mediated the effect of methamphetamine use frequency on motor impulsivity in the methamphetamine use disorder group. These findings may further improve our understanding of the neural mechanism of impulse control dysfunction underlying methamphetamine addiction and assist in exploring the neuropathological mechanism underlying methamphetamine use disorder-related dysfunction and rehabilitation.

Manipulation of Electronic Effect and Assembly Architecture to Invoke Oxidation of Ethylbenzene by Hierarchical Co3O4 Wreaths.

A high-performance transition-metal oxide catalyst can be designed by appropriately integrating the concepts of morphology regulation and electronic structure modulation. In this work, hierarchical Co3O4 wreaths (CCW) enriched with oxygen vacancies (Ov) were facilely constructed for the selective oxidation of ethylbenzene (EB) to acetophenone (AP). Under the screened optimal reaction conditions, the CCW catalyst can offer a 79.1% conversion of EB (ri = 0.244 mol gcat-1 h-1) accompanied by a selectivity of 92.3% to AP. The good reaction performance can be attributed to the cooperation of defect engineering and architecture design, which can synergistically facilitate the EB oxidation performance by augmenting the intrinsic reactivity and accessibility of active sites. This work presents a reliable route to construct a high-performance transitional metal oxide catalyst via manipulation of electronic effect and assembly architecture for the selective oxidation of EB and beyond.

Coupled Interface and Oxygen-Defect Engineering in Co3O4/CoMoO4 Heterostructures toward Active Oxidation of Ethylbenzene.

The catalytic oxidation of ethylbenzene (EB) is a promising route to produce acetophenone (AcPO). Unfortunately, it remains a great challenge to achieve the highly efficient oxidation of EB under solvent-free conditions using molecular oxygen as the sole oxidant. In this contribution, we present a facile strategy to construct hierarchical oxygen vacancy-rich Co3O4/CoMoO4 heterostructures (Vö-CCMO), which delivers a high yield value of 74.5% at 83.2% conversion of EB and selectivity of 89.6% to AcPO. Both experimental studies and theoretical calculations substantiate the important role of oxygen-defect engineering triggered by the modified chemistry environment at the interfaces between the biphasic phases, which contributes to the good catalytic performance. This work illustrates a promising paradigm for the exploit of advanced catalysts toward boosting EB oxidation reaction in a more practical way.

Mapping structural covariance networks of emotional withdrawal symptoms in males with methamphetamine use disorder during abstinence.

Individuals with methamphetamine use disorder (MUD) often experience anxiety and depressive symptoms during abstinence, which can worsen the likelihood of relapse. Thus, it is essential to understand the neuro-mechanism behind methamphetamine use and its associated emotional withdrawal symptoms in order to develop effective clinical strategies. This study aimed to evaluate associations between emotional withdrawal symptoms and structural covariance networks (SCNs) based on cortical thickness (CTh) across the brain. The CTh measures were obtained from Tl-weighted MRI data from a sample of 48 males with MUD during abstinence and 48 male healthy controls. The severity of anxiety and depressive symptoms was assessed by the Hamilton Anxiety Scale (HAMA) and depression (HAMD) scales. Two important nodes belonging to the brain reward system, the right rostral anterior cingulate cortex (rACC) and medial prefrontal cortex (medPFC), were selected as seeds to conduct SCNs and modulation analysis by emotional symptoms. MUDs showed higher structural covariance between the right rACC and regions in the dorsal attention, right frontoparietal, auditory, visual and limbic networks. They also displayed higher structural covariance between the right medPFC and regions in the limbic network. Moreover, the modulation analysis showed that higher scores on HAMA were associated with increased covariance between the right rACC and the left parahippocampal and isthmus cingulate cortex in the default mode network. These outcomes shed light on the complex neurobiological mechanisms underlying methamphetamine use and its associated emotional withdrawal symptoms and may provide new insights into the development of effective treatments for MUD.

Using machine learning to develop a five-item short form of the children's depression inventory.

BACKGROUND: Many adolescents experience depression that often goes undetected and untreated. Identifying children and adolescents at a high risk of depression in a timely manner is an urgent concern. While the Children's Depression Inventory (CDI) is widely utilized in China, it lacks a localized revision or simplified version. With its 27 items requiring professional administration, the original CDI proves to be a time-consuming method for predicting children and adolescents with high depression risk. Hence, this study aimed to develop a shortened version of the CDI to predict high depression risk, thereby enhancing the efficiency of prediction and intervention. METHODS: Initially, backward elimination is conducted to identify various version of the short-form scales (e.g., three-item and five-item versions). Subsequently, the performance of five machine learning (ML) algorithms on these versions is evaluated using the area under the ROC curve (AUC) to determine the best algorithm. The chosen algorithm is then utilized to model the short-form scales, facilitating the identification of the optimal short-form scale based on predefined evaluation metrics. Following this, evaluation metrics are computed for all potential decision thresholds of the optimal short-form scale, and the threshold value is determined. Finally, the reliability and validity of the optimal short-form scale are assessed using a new sample. RESULTS: The study identified a five-item short-form CDI with a decision threshold of 4 as the most appropriate scale considering all assessment indicators. The scale had 81.48% fewer items than the original version, indicating good predictive performance (AUC = 0.81, Accuracy = 0.83, Recall = 0.76, Precision = 0.71). Based on the test of 315 middle school students, the results showed that the five-item CDI had good measurement indexes (Cronbach's alpha = 0.72, criterion-related validity = 0.77). CONCLUSIONS: This five-item short-form CDI is the first shortened and revised version of the CDI in China based on large local data samples.

NIR-II Imaging and Sandwiched Plasmonic Biosensor for Ultrasensitive Intraoperative Definition of Tumor-Invaded Lymph Nodes.

Radical lymphadenectomy remains the cornerstone of preventing tumor metastasis through the lymphatic system. Current surgical resection of lymph nodes (LNs) based on fluorescence-guided surgery (FGS) suffers from low sensitivity/selectivity with only qualitative information, hampering accurate intraoperative decision-making. Herein, we develop a modularized theranostic system including NIR-II FGS and a sandwiched plasmonic chip (SPC). Intraoperative NIR-II FGS and detection of tumor-positive lymph nodes were performed on the gastric tumor to determine the feasibility of the modularized theranostic system in defining LN metastasis. Under the NIR-II imaging window, the orthotopic tumor and sentinel lymph nodes (SLNs) were successfully excised without ambient light interference in the operating room. Importantly, the SPC biosensor achieved 100% sensitivity and 100% specificity for tumor markers and realized rapid and high-throughput intraoperative SLN detection. We propose the synergetic design of combining the NIR-II FGS and suitable biosensor will substantially improve the efficiency of cancer diagnosis and therapy follow-up.

Three-Dimensional Histological Electrophoresis for High-Throughput Cancer Margin Detection in Multiple Types of Tumor Specimens.

Accurate identification of tumor margins during cancer surgeries relies on a rapid detection technique that can perform high-throughput detection of multiple suspected tumor lesions at the same time. Unfortunately, the conventional histopathological analysis of frozen tissue sections, which is considered the gold standard, often demonstrates considerable variability, especially in many regions without adequate access to trained pathologists. Therefore, there is a clinical need for a multitumor-suitable complementary tool that can accurately and high-throughput assess tumor margins in every direction within the surgically resected tissue. We herein describe a high-throughput three-dimensional (3D) histological electrophoresis device that uses tumor-specific proteins to identify and contour tumor margins intraoperatively. Testing on seven cell-line xenograft models and human cervical cancer models (representing five types of tissues) demonstrated the high-throughput detection utility of this approach. We anticipate that the 3D histological electrophoresis device will improve the accuracy and efficiency of diagnosing a wide range of cancers.

Effect of nanoparticle-mediated delivery of SFRP4 siRNA for treating Dupuytren disease.

Dupuytren disease (DD) is a progressive fibrous proliferative disease. It invades the palmar aponeurosis and extends to the finger fascia, eventually leading to flexion contracture of the metacarpophalangeal or interphalangeal joint. At present, surgical resection and the local injection of collagenase are the main methods for the treatment of DD, but postoperative complications and high recurrence rates often occur. Bioinformatics analysis showed that the increased expression of SFRP4 protein was closely related to the incidence of DD. Persistent and effective inhibition of SFRP4 expression may be a promising treatment for DD. We prepared SFRP4 siRNA/nanoparticle complexes (si-SFRP4) and negative siRNA/nanoparticle complexes (NC) and applied them in vitro and in vivo. Flow cytometry analysis showed that si-SFRP4 could be successfully transfected into DD cells. MTT and EdU staining assays showed that the OD values and percentage of EdU-positive cells in the si-SFRP4 group were significantly lower than those in the NC group. Scratch tests showed that the wound healing rate of the si-SFRP4 group was lower than that of the NC group, and the difference was statistically significant. The expression of SFRP4 and α-SMA protein in the si-SFRP4 group significantly decreased in both DD cells and xenografts. Compared with the NC group, the xenograft quality of the si-SFRP4 group was significantly reduced. Masson's trichrome staining showed that the collagen and fibrous cells in the si-SFRP4 group were more uniform, slender, parallel and regular. The above experimental results suggest that the proliferation and metabolism of palmar aponeurosis cells and the quality of metacarpal fascia xenografts were both significantly decreased. We speculated that nanoparticle-mediated SFRP4 siRNA can be used as a potential new method for the treatment of DD.

Dye-Triplet-Sensitized Downshifting Nanoprobes with Ratiometric Dual-NIR-IIb Emission for Accurate In Vivo Detection.

Despite the emerging near-infrared-IIb (NIR-IIb, 1500-1700 nm) bioimaging significantly improving the in vivo penetration depth and resolution, quantitative detection with accuracy remains challenging due to its inhomogeneous fluorescence signal attenuation in biological tissue. Here, ratiometric dual-NIR-IIb in vivo detection with excitation wavelengths of 808 and 980 nm is presented using analyte-responsive dye-triplet-sensitized downshifting nanoprobes (DSNPs). NIR cyanine dye IR-808, a recognizer of biomarker hypochlorite (ClO-), is introduced to trigger a triplet energy transfer process from the dye to Er3+ ions of DSNPs under 808 nm excitation, facilitating the formation of an analyte-responsive 1525 nm NIR-IIb assay channel. Meanwhile, DSNPs also enable emitting intrinsic nonanalyte-dependent downshifting fluorescence at the same NIR-IIb window under 980 nm excitation, serving as a self-calibrated signal to alleviate the interference from the probe amount and depth. Due to the two detected emissions sharing identical light propagation and scattering, the ratiometric NIR-IIb signal is demonstrated to ignore the depth of penetration in biotissue. The arthritis lesions are distinguished from normal tissue using ratiometric probes, and the amount of ClO- can be accurately output by the established detection curves.

Dihydroartemisinin synergistically enhances the cytotoxic effects of oxaliplatin in colon cancer by targeting the PHB2-RCHY1 mediated signaling pathway.

Dihydroartemisinin (DHA) has recently attracted increasing attention for its low toxicity and high antitumor activity. DHA has been reported to have synergistic anticancer effects with a variety of drugs in the clinic; however, the molecular mechanism by which DHA inhibits tumorigenesis and improves oxaliplatin cytotoxicity in colon cancer cells is still not well understood. In this study, we found that DHA can inhibit cell proliferation and colony formation in a dose-dependent manner. Prohibitin 2 (PHB2) is a potential target by which DHA exerts its antitumor and cytotoxic effects. The function and molecular mechanism of PHB2 in colon cancer tumorigenesis were fully studied to determine the regulatory mechanism between DHA and PHB2. We found that PHB2, a mitochondrial inner membrane scaffold protein, has a higher expression level in colon cancer tissues than in adjacent nontumor tissues and is mainly localized in mitochondria. Overexpression of PHB2 can promote cell proliferation and colony formation in vitro and accelerate tumor growth in vivo. We also found that the expression level of PHB2 was inversely related to the cytotoxicity of DHA and oxaliplatin in colon cancer cells. The molecular mechanism of PHB2 in tumorigenesis and cancer therapy was further studied. The results showed that 20 µM DHA can downregulate PHB2 expression in a ubiquitylation-dependent manner and subsequently block PHB2-induced RCHY1 upregulation and p53 and p21 downregulation. In this process, RCHY1 is necessary for PHB2 to play a tumor-promoting role. Thus, PHB2 and RCHY1 are effective targets for colon cancer therapy, and DHA has synergistic anticancer effects with oxaliplatin via promoting PHB2 degradation in colon cancer cells.

Problematic internet gaming and non-suicidal self-injury in Chinese adolescents: Moderating and mediating roles of anxiety.

INTRODUCTION: Despite consistent reports of the association between problematic internet gaming (PIG) and non-suicidal self-injury (NSSI), an increase in PIG does not necessarily lead to increased NSSI. This apparent paradox indicates the presence of other mediators and moderators in the PIG-NSSI association. This study aimed to investigate the role of anxiety as a potential moderating and mediating factor of the PIG-NSSI association in Chinese adolescents. METHODS: A cross-sectional study was conducted among 10,479 Chinese adolescents (50.5% male; age range, 9-18 years). Standardized self-report questionnaires were used to assess the severity of PIG, anxiety, and NSSI. Spearman correlation and multiple linear regression were applied to examine the relationships among PIG, anxiety, and NSSI. Both moderating and mediating effects of anxiety were assessed using Hayes' methods. RESULTS: PIG, anxiety symptoms, and NSSI significantly correlated with one another. Anxiety significantly moderated the relationship between PIG and NSSI [B = 0.002, standard error (SE) = 0.000, p < 0.001], and it partially mediated the PIG-NSSI association [B = 0.017, SE = 0.001, 95% confidence interval (CI) 0.014-0.021]. Social concern and concentration were the two dimensions of anxiety that exerted the strongest mediation effect (B = 0.017, SE = 0.002, 95% CI 0.014-0.020). CONCLUSIONS: Adolescents with PIG and high anxiety are likely to suffer more severe NSSI and may benefit from interventions to reduce anxiety symptoms.

Intracranial Rosai-Dorfman disease: a case report and review of the literature.

RDD involving the central nervous system is rarely reported. To better understand the disease and explore the treatments, we reported this case and review the literature.

Development and validation of a nomogram model for prediction of stroke-associated pneumonia associated with intracerebral hemorrhage.

BACKGROUND: We aimed to establish risk factors for stroke-associated pneumonia (SAP) following intracerebral hemorrhage (ICH) and develop an efficient and convenient model to predict SAP in patients with ICH. METHODS: Our study involved 1333 patients consecutively diagnosed with ICH and admitted to the Neurology Department of the First Affiliated Hospital of Wenzhou Medical University. The 1333 patients were randomly divided (3:1) into the derivation cohort (n = 1000) and validation Cohort (n = 333). Variables were screened from demographics, lifestyle-related factors, comorbidities, clinical symptoms, neuroimaging features, and laboratory tests. In the derivation cohort, we developed a prediction model with multivariable logistic regression analysis. In the validation cohort, we assessed the model performance and compared it to previously reported models. The area under the receiver operating characteristic curve (AUROC), GiViTI calibration belt, net reclassification index (NRI), integrated discrimination index (IDI) and decision curve analysis (DCA) were used to assess the prediction ability and the clinical decision-making ability. RESULTS: The incidence of SAP was 19.9% and 19.8% in the derivation (n = 1000) and validation (n = 333) cohorts, respectively. We developed a nomogram prediction model including age (Odds Ratio [OR] 1.037, 95% confidence interval [CI] 1.020-1.054), male sex (OR 1.824, 95% CI 1.206-2.757), multilobar involvement (OR 1.851, 95% CI 1.160-2.954), extension into ventricles (OR 2.164, 95% CI 1.456-3.215), dysphagia (OR 3.626, 95% CI 2.297-5.725), disturbance of consciousness (OR 2.113, 95% CI 1.327-3.362) and total muscle strength of the worse side (OR 0.93, 95% CI 0.876-0.987). Compared with previous models, our model was well calibrated and showed significantly higher AUROC, better reclassification ability (improved NRI and IDI) and a positive net benefit for predicted probability thresholds between 10% and 73% in DCA. CONCLUSIONS: We developed a simple, valid, and clinically useful model to predict SAP following ICH, with better predictive performance than previous models. It might be a promising tool to assess the individual risk of developing SAP for patients with ICH and optimize decision-making.

GATA-binding protein 4 promotes neuroinflammation and cognitive impairment in Aß1-42 fibril-infused rats through small nucleolar RNA host gene 1/miR-361-3p axis.

Aging with dysregulated metabolic and immune homeostasis stimulates pyroptosis, neuroinflammation, and cellular senescence, thus contributing to etiopathogenesis of Alzheimer's disease. GATA-binding protein 4 (GATA4) functions as a transcriptional factor in response to DNA damage, and is associated with neuroinflammation and cellular senescence. The role of GATA4 in Alzheimer's disease was investigated. GATA4 was elevated in hippocampus of Aß1-42 fibril-infused rats. Injection with shRNA targeting GATA4 reduced escape latency with increase of time in target quadrant and number of platform crossings in Aß1-42 fibril-infused rats. Moreover, knockdown of GATA4 ameliorated morphological changes of hippocampus and reduced amyloid plaque deposition in Aß1-42 fibril-infused rats. Silence of GATA4 repressed neuroinflammation and apoptosis in Aß1-42 fibril-infused rats. Loss of GATA4 in Aß1-42 fibril-infused rats reduced the expression of specificity protein 1 (Sp1) to downregulate long noncoding RNA small nucleolar RNA host gene 1 (SNHG1) and upregulated miR-361-3p. Loss of SNHG1 ameliorated learning and memory impairments in Aß1-42 fibril-infused rats. Overexpression of Sp1 attenuated GATA4 silence-induced decrease of escape latency, increase of time in target quadrant, and number of platform crossings in Aß1-42 fibril-infused rats. In conclusion, silence of GATA4 ameliorated cognitive dysfunction and inhibited hippocampal inflammation and cell apoptosis through regulation of Sp1/SNHG1/miR-361-3p.

Ultrabright Renal-Clearable Cyanine-Protein Nanoprobes for High-Quality NIR-II Angiography and Lymphography.

The renal-clearable aspect of imaging agent with minimum toxicity issues and side effects is essential for clinical translation, yet clinical near-infrared-I/II (NIR-I/II) fluorophores with timely renal-clearance pathways are very limited. Herein, we rationally develop the cyanine-protein composite strategy through covalent bonding of ß-lactoglobulin (ß-LG) and chloride-cyanine dye to produce a brilliant and stable NIR-I/II fluorophore (e.g., ß-LG@IR-780). The ß-LG acts as a protecting shell with small molecular weight (18.4 kDa) and ultrasmall size (<5 nm), thus endowing the ß-LG@IR-780 with excellent biocompatibility and renal excretion. Our ß-LG@IR-780 probe enables noninvasive and precise NIR-II visualization of the physiological and pathological conditions of the vascular and lymphatic drainage system, facilitating intraoperative imaging-guided surgery and postoperative noninvasive monitoring. The minimum accumulation of our probes in the main organs improves the overall biosafety. This study provides a facile methodology for new-generation NIR-II fluorophores and largely improves the brightness and pharmacokinetics of small molecular dyes.

Supramolecular Dimer as High-Performance pH Probe: Study on the Fluorescence Properties of Halogenated Ligands in Rigid Schiff Base Complex.

The development of high-performance fluorescence probes has been an active area of research. In the present work, two new pH sensors Zn-3,5-Cl-saldmpn and Zn-3,5-Br-saldmpn based on a halogenated Schiff ligand (3,5-Cl-saldmpn = N, N'-(3,3'-dipropyhnethylamine) bis (3,5-chlorosalicylidene)) with linearity and a high signal-to-noise ratio were developed. Analyses revealed an exponential intensification in their fluorescence emission and a discernible chromatic shift upon pH increase from 5.0 to 7.0. The sensors could retain over 95% of their initial signal amplitude after 20 operational cycles, demonstrating excellent stability and reversibility. To elucidate their unique fluorescence response, a non-halogenated analog was introduced for comparison. The structural and optical characterization suggested that the introduction of halogen atoms can create additional interaction pathways between adjacent molecules and enhance the strength of the interaction, which not only improves the signal-to-noise ratio but also forms a long-range interaction process in the formation of the aggregation state, thus enhancing the response range. Meanwhile, the above proposed mechanism was also verified by theoretical calculations.

Digital transformation and carbon intensity reduction in transportation industry: Empirical evidence from a global perspective.

Digital transformation has become an inevitable trend in industrial development, but research on its environmental benefits has not been conducted in-depth. This paper focuses on the impact and mechanisms of the digital transformation of the transportation industry on its carbon intensity. Empirical tests are conducted based on the panel data of 43 economies from 2000 to 2014. The results show that the digital transformation of the transportation industry reduces its carbon intensity, but only the digital transformation that relies on domestic digital sources is significant. Second, technological progress, upgrading the industry's internal structure and improving energy consumption are the main channels through which the digital transformation of the transportation industry reduces its carbon intensity. Third, in terms of subdividing industries, the digital transformation of basic transportation has a more significant effect on reducing carbon intensity. For segmentation digitization, the carbon intensity reduction from digital infrastructure is more significant. This paper serves as a reference for countries to formulate development policies for the transportation industry and implement the Paris Agreement.

Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning.

Vaccination offers health, economic, and social benefits. However, three major issues-vaccine quality, demand forecasting, and trust among stakeholders-persist in the vaccine supply chain (VSC), leading to inefficiencies. The COVID-19 pandemic has exacerbated weaknesses in the VSC, while presenting opportunities to apply digital technologies to manage it. For the first time, this study establishes an intelligent VSC management system that provides decision support for VSC management during the COVID-19 pandemic. The system combines blockchain, internet of things (IoT), and machine learning that effectively address the three issues in the VSC. The transparency of blockchain ensures trust among stakeholders. The real-time monitoring of vaccine status by the IoT ensures vaccine quality. Machine learning predicts vaccine demand and conducts sentiment analysis on vaccine reviews to help companies improve vaccine quality. The present study also reveals the implications for the management of supply chains, businesses, and government.

Multiple Roles of SIRT2 in Regulating Physiological and Pathological Signal Transduction.

Sirtuin 2 (SIRT2), as a member of the sirtuin family, has representative features of evolutionarily highly conserved nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase activity. In addition, SIRT2, as the only sirtuin protein colocalized with tubulin in the cytoplasm, has its own functions and characteristics. In recent years, studies have increasingly shown that SIRT2 can participate in the regulation of gene expression and regulate signal transduction in the metabolic pathway mainly through its post-translational modification of target genes; thus, SIRT2 has become a key centre in the metabolic pathway and participates in the pathological process of metabolic disorder-related diseases. In this paper, it is discussed that SIRT2 can regulate all aspects of gene expression, including epigenetic modification, replication, transcription and translation, and post-translational modification, which enables SIRT2 to participate in energy metabolism in life activities, and it is clarified that SIRT2 is involved in metabolic process-specific signal transduction mechanisms. Therefore, SIRT2 can be involved in metabolic disorder-related inflammation and oxidative stress, thereby triggering the occurrence of metabolic disorder-related diseases, such as neurodegenerative diseases, tumours, diabetes, and cardiovascular diseases. Currently, although the role of SIRT2 in some diseases is still controversial, given the multiple roles of SIRT2 in regulating physiological and pathological signal transduction, SIRT2 has become a key target for disease treatment. It is believed that with increasing research, the clinical application of SIRT2 will be promoted.