Sarcopenia is a systemic skeletal muscle disease characterized by the gradual decline of muscle mass，strength，and function，and its occurrence and development are related to multiple factors，involving several signaling pathways. Among them，the phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt） signaling pathway，as a key pathway regulating cellular growth，survival，and metabolism，plays an important role in the formation and development of sarcopenia. Its abnormal activation or deactivation may lead to an imbalance in muscle protein metabolism，resulting in muscle atrophy and reduction. Modern medicine is still in the exploratory stage of treatment for sarcopenia. Traditional Chinese medicine （TCM），with its multi-pathway and multi-target characteristics，has shown increasing advantages in the prevention and treatment of sarcopenia. In recent years，various monomers， extracts，and compound formulas of TCM have been proven to effectively prevent and treat sarcopenia by promoting muscle cell protein synthesis，reducing protein degradation，inhibiting cell apoptosis and inflammatory response，and improving mitochondrial function. This paper reviewed the improvement effects of TCM on sarcopenia based on the PI3K/Akt pathway and explored its specific action mechanisms， aiming to provide new insights for the treatment of sarcopenia with TCM.

Chronic post-surgical pain (CPSP) is a common long-term complication following lung surgery. Its high incidence significantly impacts patients’ quality of life and functional recovery, and imposes a substantial socioeconomic burden. This consensus aims to systematically establish a standardized integrated Chinese and Western medicine diagnostic and treatment framework for chronic post-lung surgery pain (CPLSP). Based on the latest domestic and international evidence-based medical research and multidisciplinary clinical experience, the working group comprehensively elaborates on core issues regarding CPLSP, including its definition, epidemiology, pathogenesis, clinical assessment, Western medical treatment, traditional Chinese medicine (TCM) treatment, and integrated strategies. The consensus emphasizes a patient-centered approach, adhering to the principles of multimodality, individualization, and stepwise management, highlighting the synergistic advantages of integrating Chinese and Western medicine throughout the entire perioperative management cycle encompassing "perioperative anti-inflammation, acute analgesia, and chronic rehabilitation." Through systematic literature retrieval and evidence integration, a total of 9 core recommendations were established to provide scientifically sound and clinically practical guidance.

Tuberous sclerosis complex (TSC) is an autosomal dominant genetic disorder primarily caused by pathogenic variants in the TSC1 or TSC2 genes. It is characterized by multisystem hamartomatous lesions and neuropsychiatric manifestations. Here we report a young male patient with TSC involving multiple organs, caused by a heterozygous frameshift mutation in TSC2 (c.2071delC, p.Arg691Alafs^*7). The patient initially presented with classic facial angiofibromas and hypomelanotic macules, and subsequently developed psychiatric and behavioral disturbances with auditory hallucinations. Neuroimaging revealed an intracranial mass lesion, which was confirmed as a subependymal giant cell astrocytoma on postoperative histopathology following surgery performed at an outside institution. After admission, the patient underwent a comprehensive diagnostic workup, and multidisciplinary treatment evaluation revealed extensive multisystem involve-ment, including the nervous system, skin, kidneys, lungs, heart, eyes, pancreas, liver and bones. Combined with relevant literature, this article discusses the molecular mechanisms, clinical phenotypes, and comprehensive management of TSC, in order to provide a reference for the standardized and individualized management of this disease.

Objective: This prospective study evaluated the feasibility of chemical exchange saturation transfer (CEST) MRI for assessing disease activity in thyroid-associated ophthalmopathy (TAO). Materials and Methods: A total of 88 patients with active TAO, 76 with inactive TAO, and 30 healthy controls were enrolled. CEST MRI-derived magnetization transfer ratio (MTR) and MTR asymmetry (MTRasym) at 1 ppm, 2 ppm, and 3.5 ppm were calculated. Clinical data, MTR, and MTRasym values for the extraocular muscles (one representative muscle per eye, yielding two measurements per participant) were compared among the groups. Spearman’s correlation was used to examine associations between imaging parameters and the clinical activity score (CAS) in patients with TAO. Logistic regression analysis was used to identify independent associations between imaging parameters and disease activity in patients with TAO (active vs. inactive). Receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic performance for discriminating active from inactive TAO. Results: Patients with active TAO showed lower MTR values (P < 0.001) and higher MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) (all P < 0.001) compared with those with inactive TAO. MTR was negatively correlated with CAS (r = -0.402; P < 0.001), while MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) were positively correlated with CAS (r = 0.369, 0.350, and 0.349, respectively;all P < 0.001). MTR and MTRasym (1 ppm) were independently associated with TAO activity. The areas under the ROC curve (AUCs) for MTR and MTRasym (1 ppm) in discriminating active from inactive TAO were 0.772 and 0.730, respectively. Combining MTR with MTRasym (1 ppm) significantly improved diagnostic performance compared with either parameter alone, achieving an AUC of 0.805 (P = 0.029 and 0.001). Conclusion MTR and MTRasym (1 ppm) were independently associated with TAO activity. Their combination further enhanced diagnostic performance in distinguishing active from inactive TAO, suggesting their potential as quantitative imaging biomarkers to guide treatment in patients with TAO.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

ObjectiveTo analyze the expression level of triggering receptor expressed on myeloid cells-1 （TREM-1） in serum and ascites of patients with cirrhotic ascites， and to investigate its correlation with clinical features and inflammatory markers and its role in the diagnosis of infection and prognostic evaluation. MethodsA total of 110 patients with cirrhotic ascites who were hospitalized in The Fifth Hospital of Shijiazhuang from January 2019 to December 2020 were enrolled， and according to the presence or absence of intra-abdominal infection， they were divided into infection group with 72 patients and non-infection group with 38 patients. The patients with infection were further divided into improvement group with 38 patients and non-improvement group with 34 patients. Clinical data and laboratory markers were collected from all patients. Serum and ascites samples were collected， and ELISA was used to measure the level of TREM-1. The independent-samples t test was used for comparison of normally distributed continuous data between two groups； the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between multiple groups； the chi-square test was used for comparison of categorical data between two groups. A Spearman correlation analysis was used to investigate the correlation between indicators. A multivariate Logistic regression analysis was used to identify the influencing factors for the prognosis of patients with cirrhotic ascites and infection. The receiver operating characteristic （ROC） curve was used to evaluate the diagnostic and prognostic efficacy of each indicator， and the Delong test was used for comparison of the area under the ROC curve （AUC）. ResultsThe level of TREM-1 in ascites was significantly positively correlated with that in serum （r=0.50， P<0.001）. Compared with the improvement group， the non-improvement group had a significantly higher level of TREM-1 in ascites （Z=-2.391， P=0.017） and serum （Z=-2.544， P=0.011）， and compared with the non-infection group， the infection group had a significantly higher level of TREM-1 in ascites （Z=-3.420， P<0.001）， while there was no significant difference in the level of TREM-1 in serum between the two groups （P>0.05）. The level of TREM-1 in serum and ascites were significantly positively correlated with C-reactive protein （CRP）， procalcitonin （PCT）， white blood cell count， and neutrophil-lymphocyte ratio （r=0.288， 0.344， 0.530， 0.510， 0.534， 0.454， 0.330， and 0.404， all P<0.05）. The ROC curve analysis showed that when PCT， CRP， and serum or ascitic TREM-1 were used in combination for the diagnosis of cirrhotic ascites with infection， the AUCs were 0.715 and 0.740， respectively. The multivariate Logistic regression analysis showed that CRP （odds ratio ［OR］=1.019， 95% confidence interval ［CI］： 1.001‍ ‍—‍ ‍1.038， P=0.043） and serum TREM-1 （OR=1.002， 95%CI： 1.000‍ ‍—‍ ‍1.003， P=0.016） were independent risk factors for the prognosis of patients with cirrhotic ascites and infection， and the combination of these two indicators had an AUC of 0.728 in predicting poor prognosis. ConclusionThe level of TREM-1 is closely associated with the severity of infection and prognosis in patients with cirrhotic ascites， and combined measurement of TREM-1 and CRP/PCT can improve the diagnostic accuracy of infection and provide support for prognostic evaluation.

This study identified the types and pathogen carrying status of fleas on the surface of sheep in some areas of southern Xinjiang,and analyzed the genetic evolution differences with respect to related pathogens.The aim was to provide a reference for the local prevention and control of fleas and insect borne infectious diseases.A total of 1 586 fleas were collected from agricultural and pas-toral areas of Tumushuke City and Hotan Prefecture.Flea species were identified on the basis of morphology and the Pulex irritans mi-tochondrial COII gene.Flea DNA was extracted,and PCR was conducted to amplify the Bartonella gltA gene;Arsenophonus,Ana-plasma,Ehrlichia,and Wolbachia 16S rRNA genes;RickettsiaOmpA,17kDa,16S rRNA genes,and Yersinia pestis 16S rDNA gene.The amplified products were sequenced,and the homology of the genes of the three detected pathogens(gltA gene of Bartonella,16S rRNA gene of Wolbachia,and Anaplasma phagocytophilum)with respect to known corresponding genes of the same pathogen in Gen-Bank was analyzed.Phylogenetic trees were constructed with the adjacency method in MEGA 11.0.According to morphological and mo-lecular biology identification results,all fleas collected in this study were Pulex irritans.PCR indicated that the target gene fragments had been added to the mitochondrial COII,BartonellagltA,Wolbachia,and autophagosomal 16S rRNA genes of human fleas,all of which were consistent with the expected fragment sizes.Target bands were not amplified from Ehrlichia,Arsenophonus,spotted fever group Rickettsia,and Yersinia pestis.According to homology and genetic evolution analysis of human flea mitochondrial COII and the corresponding genes of the above-described pathogens,the COX2 gene(ON455234.1)of human fleas in Tumushuke city and Iran ob-tained in this study showed the highest homology(99.84%).The COII gene(NC_063709.1)of human fleas in Hetan City and Hunan region showed the highest homology(100%).Our findings further confirmed that the flea species was Pulex irritans.The PCR amplifi-cation results indicated that the collected Pulex irritans carried multiple pathogens,among which Bartonella and Wolbachia had the highest infection rates,and the infection rate with Anaplasma phagocytophilum was relatively low.This study is the first to discover flea species on the surface of sheep in some areas of southern Xinjiang.Our findings preliminarily confirmed that Bartonella,Wolba-chia,and Anaplasma phagocytophilum are the main Pulex irritans pathogens.

Objective To achieve efficient compression of on-board radiotherapy projection images using dynamic video encoding algorithms.Methods The on-board radiotherapy imaging system primarily provides 2D X-ray projection images for patient positioning verification and 3D tomographic image reconstruction.Since multiple projection images acquired continuously exhibit strong spatiotemporal correlations,their similarities could be used to eliminate redundant information,thereby improving the image compression ratio.During image compression,the image sets obtained at different times were arranged into an image sequence which was input into a video encoder and output as a video file.During image decompression,the video file was input into a video decoder and output as an image sequence,and the images in the sequence were then assigned back to their original image sets.Three current dynamic video encoding algorithms(AVC,HEVC,and AV1)and the classic static image coding algorithm(JPEG 2000)were tested on a database of 2D projection images.The performance of various compression algorithms was evaluated using indicators such as compression ratio(CR),peak signal-to-noise ratio(PSNR),and structural similarity(SSIM).Moreover,visual comparison of projection images before and after compression was evaluated by clinical radiation oncologists.Results Dynamic video encoding algorithms achieved higher CR than the static image coding algorithm.The average CR of the 3 dynamic video encoding algorithms was as followed:CRAVC=11.50,CRHEVC=30.74,and CRAV1=27.10,while the average CR of the static image coding algorithm(JPEG 2000)was 5.28.For abdominal projection images,well-defined contours and textural details were preserved even when the CR reached 42.37.For head-neck projection images,although mild contour blurring emerged at a CR of 20.71,subsequent evaluation by clinical radiation oncologists confirmed that the reconstructed CBCT images still satisfied clinical requirements.Conclusion These dynamic video encoding algorithms effectively utilize the strong correlation information between multiple projection images,reduce the storage of redundant information,and greatly improve the image CR.

Objective To explore the changes in neural activity in patients with type 2 diabetes mellitus(T2DM)and their corre-lation with executive function,and to analyze the neural mechanisms underlying the decline in executive function in T2DM patients.Methods Thirty-one T2DM patients(T2DM group)and thirty-two healthy controls(HC)(HC group)matched for body mass index(BMI)underwent resting-state functional magnetic resonance imaging(rs-fMRI)scans and N-back task tests were included.Differ-ences in the amplitude of low-frequency fluctuation(ALFF),regional homogeneity(ReHo),and seed-based functional connectivity(FC)between the two groups were compared,and partial correlation analyses were performed between the difference results and N-back task performance.Results The T2DM group showed prolonged reaction time(RT)in the 1-back and 2-back tasks.T2DM patients exhibited increased ALFF in the bilateral caudate nucleus,left medial superior frontal gyrus,and right postcentral gyrus,as well as elevated ReHo in the right putamen.FC analysis revealed significant alterations in FC between the caudate nucleus,putamen,and multiple brain regions in T2DM patients,with some of these FC changes significantly correlated with RT and accuracy(ACC)in the N-back task.Conclusion The decline in executive function in T2DM patients may be associated with abnormal neural activity in brain regions such as the striatum,salience network,and frontoparietal control network.FC further decreases under increased cognitive load.These findings provide evidence for the study of the neural mechanisms of executive function impairment in T2DM patients.