Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Objective: To analyze density of stromal tumor-infiltrating lymphocytes (sTIL) and expression of lymphocyte-activation gene-3 (LAG-3) protein in advanced gastric adenocarcinomas, and to investigate the correlation of sTIL and LAG-3 with the prognosis in patients with advanced gastric adenocarcinoma. Methods: The clinicopathological characteristics and follow-up data of 260 patients with advanced gastric adenocarcinoma were collected at Fujian Cancer Hospital, from January 2011 to December 2014. The percentage of sTILs was reported semi-quantitatively using histological section evaluation, the LAG-3 protein was detected using immunohistochemistry, and the expression was correlated with the clinicopathological features and patient outcomes. Results: Among the 260 cases, high density of sTIL was detected in 173 cases (66.5%) while LAG-3 high expression was observed in 160 cases (61.5%). These cases were divided into four groups. Group Ⅰ: 48 cases (18.5%) were sTIL low/LAG-3 low; group Ⅱ: 52 cases (20.0%) were sTIL high/LAG-3 low; group Ⅲ: 39 cases (15.0%) were sTIL low/LAG-3 high; group Ⅳ: 121 cases (46.5%) were sTIL high/LAG-3 high. Kaplan-Meier survival analyses showed that patient prognoses were related to age, tumor size, tumor location, Lauren classification, perineural invasion, vascular invasion, TNM staging, postoperative adjuvant chemotherapy and molecular classification (P<0.05). Meanwhile, higher densities of sTIL and higher expression of LAG-3 were associated with better prognosis. Multivariate survival analysis showed age, tumor size, Lauren classification and postoperative adjuvant chemotherapy were independent prognostic factors for patient survival. The results showed a poor prognosis in low-sTIL/low-LAG-3 patients. Conclusions: Compared with low density of sTIL and low expression of LAG-3, high density of sTIL and high expression of LAG-3 are associated with better outcomes in patients with advanced gastric adenocarcinoma, respectively. Combined detecton of sTIL and LAG-3 may be more useful in gastric cancer than using either alone. Age, tumor size, Lauren classification and postoperative adjuvant chemotherapy are independent prognostic factors for patients with advanced gastric adenocarcinoma.
Adenocarcinoma/pathology* ; Humans ; Immunohistochemistry ; Lymphocytes, Tumor-Infiltrating/metabolism* ; Neoplasm Staging ; Prognosis ; Retrospective Studies ; Stomach Neoplasms/pathology*

Aim Amyotrophic lateral sclerosis (Alii) is a neurodegenerative disease caused by the selective loss of upper and lower motor neurons.Its pathogenesis is complex and not yet fully understood.Accumulating evidences show that energy metabolism defieits and homeostasis imbalance lead to selective degeneration of motor neurons in ALS.Adenosine phosphate-activated protein kinase ( AMPK) and silent information regulator-1 (SIRT1) are known to sense energy metabolism at the cellular level, playing an essential part in regulating the energy homeostasis and autophagy by activating downstream pathways.AMPK activates SIRT1 to activate the deaeetylation and activation of downstream genes involved in energy metabolism such as peroxisome proliferator-aetivated receptor 7 ( PPAR-y) and eoaetivator la ( PGC-la) , thereby increasing the level of mitochondrial biosynthesis.Therefore, the mechanism by which AMPK/SIRT1 participates in the regulation of energy metabolism is highly likely to be a potential target for ALS treatment.Here we first review the important role of energy metabolism defects and mitochondrial abnormalities in the pathogenesis of ALS, and briefly address the therapeutic potential of AMPK/SIRT1/PGC-1 a pathway as a treatment target in ALS, and how targeted regulation of this signaling pathway makes it an effective therapeutic strategy for ALS.

Amana edulis is a traditional Chinese medicinal plant with low propagation coefficient. In recent years, the increasing demands of A. edulis lead to a shortage of its wild resources. In order to analyze the expression of related functional genes in A. edulis, the selection of suitable internal reference genes is crucial to improve the accuracy of experimental results. Eight genes(ACT, TUA, CYP, GAPDH, UBQ, UBI, EF1a, UBC)were chosen as candidate reference genes based on the RNA-Seq. Real-time fluorescence quantitative technique was used to detect the expression level of candidate internal reference genes in different organs(bulb, leaf, flo-wer) and stolons at different development stages of A. edulis. Then GeNorm, NormFinder, BestKeeper softwares and RefFinder website were used for a comprehensive analysis of the expression stability of the candidate genes.The results showed that among the 8 candidate reference genes, the variation range of Ct value of UBC was the smallest, and the expression level was stable, which was suitable for an reference gene. GeNorm and NormFinder software analysis showed that UBC and UBI were the optimal reference genes. BestKeeper analysis showed that CYP and UBC expression were relatively stable. Comprehensive evaluation of RefFinder website showed that UBC and UBI were the most stable genes, and ACT displayed the lowest stability in all software evaluation, indicating UBC and UBI were suitable for reference genes. Additionally, the most stable UBC, UBI and the most unstable ACT were used as internal reference genes to detect the expression of GBSS gene in A. edulis, and expression pattern of GBSS gene was the same under the calibration of UBC and UBI. The expression data of GBSS gene confirmed that UBC and UBI genes were reliable for A. edulis qRT-PCR as internal reference genes. The results would benefit future studies on related gene expression of A. edulis.
Gene Expression Profiling ; Gene Expression Regulation, Plant ; Genes, Plant/genetics* ; Real-Time Polymerase Chain Reaction ; Reference Standards

Stolon is an important organ for reproduction and regeneration of Amana edulis. Previous analysis of transcriptome showed that MYB was one of the most active transcription factor families during the development of A. edulis stolon. In order to study the possible role of MYB transcription factors in stolon development, the authors screened out an up-regulated MYB gene named AeMYB4 was by analyzing the expression profile of MYB transcription factors. In the present study, sequence analysis demonstrated that AeMYB4 contained an open reading frame of 756 bp encoding 251 amino acids, and domain analysis revealed that the predicted amino acids sequence contained two highly conserved SANT domains and binding sites for cold stress factor CBF. By multiple sequence alignment and phylogenetic analysis, it is indicated that AeMYB4 clustered with AtMYB15 from Arabidopsis thaliana, belonging to subgroup S2 of R2 R3-MYB. And most of the transcription factors in this subfamily are related to low temperature stress. The GFP-AeMYB4 fusion protein expression vector for subcellular localization was constructed and transferred into Agrobacterium tumefaciens to infect the leaves of Nicotiana benthamiana, and the results showed the protein was located in the nucleus. To investigate the transcriptional activation, the constructed pGBKT7-AeMYB4 fusion expression vector was transferred into Y2 H Gold yeast cells, which proved that AeMYB4 was a transcription activator with strong transcriptional activity. Real-time quantitative PCR was used to detect the expression of AeMYB4 gene in three different development stages of stolon and in leaves, flowers, and bulbs of A. edulis, which indicated that AeMYB4 transcription factor was tissue-specific in expression, mainly in the stolon development stage, and that the expression was the most active in the middle stage of stolon development, suggesting that AeMYB4 gene may play an important role in stolon development. This study contributes to the further research on the function of AeMYB4 transcription factor in stolon development of A. edulis.
Amino Acid Sequence ; Arabidopsis/metabolism* ; Cloning, Molecular ; Gene Expression Regulation, Plant ; Humans ; Phylogeny ; Plant Proteins/metabolism*

ObjectiveTo investigate the efficacy and mechanism of tetramethylpyrazine derivative T-006 on learning and memory function of APP/PS1/Tau transgenic （3×Tg） mice. MethodsEight-month-old 3×Tg mice and their wild-type （WT） littermates were divided into WT group， WT+T-006 （10 mg/kg） group， 3×Tg group， low-dose T-006 group （1 mg/kg）， medium-dose T-006 group （3 mg/kg）， high-dose T-006 group （10 mg/kg）， donepezil group （1.3 mg/kg） and memantine group （5 mg/kg）. Within 4 months， T-006 and donepezil were continuously administered once a day and memantine twice a day. Behavioral tests including novel object recognition， step-down avoidance and morris water maze were performed to evaluate learning and memory function of mice. Immunohistochemistry was used to observe the deposition of amyloid plaques in the hippocampus of mice. Western blotting was employed to detect the protein expression of APP， BACE-1， PSD95， synapsin I， synapsin Ⅱ， synaptophysin， BDNF， CREB and p-CREB. ResultsT-006 treatment reduced the numbers of errors in the step-down avoidance test （P< 0.05）， significantly reduced the APP expression and increased the expression of PSD95， synaptophysin， synapsin I and BDNF （P<0.05）. ConclusionT-006 improves the learning and memory function of 3×Tg mice and reduces the APP expression， which may be explained by the increase of synaptic associated protein expression.

BACKGROUND: Psoriasis is a chronic inflammatory skin disease, affecting about 0.6% of the Chinese population. Many patients are not well controlled by conventional treatments, thus there is need for new treatment regimens. In this study, we assessed the efficacy and safety of secukinumab in Chinese patients with moderate to severe plaque psoriasis. METHODS: This study was a 52-week, multicentre, randomized, double-blind, placebo-controlled, parallel-group, Phase 3 trial. A sub-population of study participants (≥18 years) of Chinese ethnicity were randomized to receive subcutaneous injections of 300 or 150 mg secukinumab, or placebo. The co-primary endpoints were psoriasis area severity index (PASI) 75 and Investigator's Global Assessment (IGA) 0/1 at Week 12. RESULTS: A total of 441 Chinese patients were enrolled in this study. Co-primary outcomes were achieved; 300 and 150 mg secukinumab were superior to placebo as shown in the proportion of patients that achieved PASI 75 (97.7% and 87.2% vs. 3.7%, respectively; P < 0.001), and IGA 0/1 (82.3% and 69.7% vs. 2.7%; P < 0.001) at Week 12. Treatment efficacy was maintained until Week 52. There was no increase in overall adverse events with secukinumab relative to placebo throughout the 52-week period. CONCLUSION: Secukinumab is highly effective and well tolerated in Chinese patients with moderate to severe plaque psoriasis. TRIAL REGISTRATION ClinicalTrials.gov, NCT03066609; https://clinicaltrials.gov/ct2/show/record/NCT03066609.
Antibodies, Monoclonal/therapeutic use* ; Antibodies, Monoclonal, Humanized ; China ; Double-Blind Method ; Humans ; Psoriasis/drug therapy* ; Severity of Illness Index ; Treatment Outcome

Aged ; Cognitive Dysfunction/epidemiology* ; Cross-Sectional Studies ; Geriatric Assessment ; Humans ; Independent Living ; Sarcopenia/epidemiology*