Objective: : The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). Methods: : A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. Results: : The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. Conclusion : High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

Objective: : The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). Methods: : A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. Results: : The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. Conclusion : High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

Objective: : The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). Methods: : A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. Results: : The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. Conclusion : High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

Objective: : The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). Methods: : A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. Results: : The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. Conclusion : High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

As an emerging discipline that combines traditional diagnostic methods with modern scientific technology,micro syndrome differentiation has good prospects for development,but there are some controversies in the research process.Based on ancient and modern literature,this article reviewed the origin and flow of research on micro syndrome differentiation,and summarized the problems to be improved in the process of research on micro syndrome differentiation from three aspects:application of disease type,guiding ideology and micro indicators.Based on this,the article further expounded the new thinking on"near-micro"syndrome differentiation from three aspects:connotation,scope of application,and links to traditional identification and micro-identification,and pointed out that the modern medical detection basis should be incorporated into the field of TCM syndrome differentiation,and at the same time,it should be based on the overall thinking mode of TCM,which would provide a new idea for the development of modern TCM diagnosis technology.

BACKGROUND:Irreducible femoral neck fracture was difficult to obtain anatomic reduction.As a new type of internal fixation,the femoral neck system is still blank for the treatment of non-anatomical reduced femoral neck fractures. OBJECTIVE:To explore the biomechanical stability of femoral neck system internal fixation under nonanatomical reduction in the treatment of femoral neck fractures based on finite element analysis. METHODS:CT data of the hip joint of a healthy female adult were obtained.Anatomical reduction of femoral neck fracture models with Pauwels angles of 30°,50°,and 70° were established using Mimics 21.0,Geomagic Wrap 2021,and SolidWorks 2020.The fracture proximal ends of the three anatomical reduction models were shifted upward by 2 mm along the fracture line,and three positive buttress models with different Pauwels angles were obtained.In the same way,three negative buttress models were acquired by shifting downward by 2 mm.SolidWorks 2020 was used to make the femoral neck system internal fixation,and the nine femoral neck fracture models were assembled with the femoral neck system.Then Ansys 19.0 was used for finite element analysis.The displacement distribution and maximum displacement,stress distribution and maximum stress of the femur and femoral neck system were recorded under 2100 N stress. RESULTS AND CONCLUSION:(1)When Pauwels angles were 30°,50°,and 70°,the maximum stresses of the femoral neck system appeared to be concentrated at the junction of the sliding hip screw and anti-rotation screw.The maximum femur stresses appeared to be concentrated in the medial cortex of the femur.The maximum displacement was concentrated at the upper of the femoral head and femoral neck system.(2)When Pauwels angles were 30° and 50°,the maximum displacement and maximum stress of the femoral neck system and femur were:negative buttress>anatomical reduction>positive buttress.(3)When Pauwels angle was 70°,the maximum displacement and maximum stress of the femoral neck system were:negative buttress>anatomical reduction>positive buttress;the maximum displacement and maximum stress of the femur were:negative buttress>positive buttress>anatomical reduction.(4)With the increase of Pauwels angle,the biomechanical advantage of the positive buttress was weakening.However,it was better than a negative buttress.When Pauwels angle was 30°,positive buttress was more stable than anatomical reduction.When Pauwels angle was 50°,the biomechanical difference between positive buttress and anatomical reduction became smaller.When Pauwels angle was 70°,the stability of anatomical reduction was slightly better than positive buttress.(5)If it was difficult to achieve anatomical reduction of femoral neck fracture during operation,but the positive buttress had been displaced within 2 mm,the femoral neck system could be used to offer stable mechanical fixation.It is necessary to avoid negative buttress reduction.

Objective To investigate the effects of Aikeqing(AKQ),a compound of Chinese medicine,on drug-metabolizing activity and on the pharmacokinetic parameters of HIV-1 protease inhibitors lopinavir(LPV)and ritonavir(RTV)in Kaletra tablets.Methods Human liver microsomes were co-incubated with mixed probes and AKQ.HPLC-MS was employed to measure the content of probe.Half-inhibitory concentration(IC50)of AKQ on different subtypes of cytochrome P450 enzymes involved in drug metabolism of liver microsomes was calculated.The P450 subtype,whose activity was significantly inhibited by AKQ was then identified.HPLC-MS analytical method for simultaneous determination of LPV and RTV in rat plasma was established.SD rats were orally given AKQ or vehicle once a day for 7 consecutive days.After half an hour of the last gavage of AKQ,the rats were given Kaletra by intragastric administration.Then,the blood concentration of LPV and RTV were measured and the effect of AKQ on pharmacokinetic parameters of LPV and RTV were analyzed.Results The methanol extract of AKQ at the concentrations of 0～500 μg·mL-1 showed inhibitory effects on the metabolic activity of CYP2D6,CYP2C8、CYP2E1,CYP2C19,CYP1A2,CYP2B6,CYP2C9 and CYP3A4,with IC50 values of 7.7,75.3,144.0,99.5,43.5,104.5,49.3 and 204.9 μg·mL-1,respectively.An HPLC-MS/MS method was established for simultaneous quantification of LPV and RTV in blood samples.LPV and RTV showed linear relationships in the ranges of 30～10 000 ng·mL-1 and 3～1 000 ng·mL-1,respectively.The lowest limits of quantification were 30 ng·mL-1 and 3 ng·mL-1.Intra-day and inter-day precision were all less than 5%,and the accuracy of LPV and RTV was in the range of 96.3%～109%.The extraction recovery rates were not less than 88.7%,the matrix effects were 93.8%～105.0%,and the plasma samples were stable.Compared with Kaletra group,there was no significant changes in non-compartmental model parameters including AUC0-t,AUC0-∞,MRT0-t,t1/2z,tmax,Vz/F,Clz/F and Cmax of LPV in AKQ+Kaletra group(P＞0.05).But MRT0-∞ was found to be obviously affected by AKQ(P＜0.05).All pharmacokinetic parameters of RTV showed no significant change in AKQ+Kaletra group(P＞0.05).Conclusion Aikeqing exhibited varying degrees of inhibitory effects on 8 human drug-metabolizing cytochromes P450,especially CYP2D6.A human-equivalent dose of Aikeqing does not affect the pharmacokinetic parameters of lopinavir and ritonavir in rats.

Object:To explore the role of personalized nutritional intervention based on nutritional assessment in long-term continuous nursing of elderly postoperative colorectal cancer patients.Methods:Elderly patients with colorectal cancer who received radical surgery in a tertiary hospital in Beijing were screened from January 2021 to January 2022 and a total of 100 patients at nutritional risk (defined as with a Nutritional Risk Screening 2002 [NRS 2002] score ≥ 3) were included in the study. Patients were stratified by age and then divided into control and intervention groups with 50 cases in each. The control group received regular health guidance and follow-up visits at postoperative outpatient clinics while the intervention group received personalized nutritional intervention based on nutritional assessment additionally. The intervention period was 12 months. Nutritional indicators including body mass index (BMI), upper arm circumference, grip strength and hemoglobin, as well as albumin and quality of life (QoL), are compared between the two groups.Results:Compared with the control group, the intervention group showed significantly better results of BMI [(18.46±0.53) vs (16.9±0.77)], upper arm circumference [(25.09±1.41)cm vs (23.49±1.45)cm], grip strength [(28.34±8.00)kg vs (23.97±7.19)kg], HGB [(135.10±9.27)g/L vs (106.40±8.73)g/L] and ALB [(41.62±3.41)g/L vs (28.62±2.38)g/L, all P < 0.01]. The intervention group also had significantly higher scores in physical [(20.96±2.03) vs (15.66±0.82)], emotional [(21.48±1.64) vs (15.76±1.00)], social [(23.44±1.67) vs (15.96±0.99)], and functional [(20.74±1.74) vs (5.46±0.97)] domains of QoL (all P<0.01). Conclusion:In elderly patients with colorectal cancer after radical resection, personalized nutritional intervention based on nutritional assessment can effectively control nutritional indicators, help reduce the incidence of malnutrition, improve postoperative quality of life, and inform the establishment of standardized process in nutrition management.

Matching is a standard method for selecting research objects regarding the observational research, which controls confounding factors and improves statistical efficiency. However, its role in controlling confounding is not consistent in different observational studies. Matching can eliminate the confounding bias of matching variables in cohort studies, but checking on itself cannot eliminate confounding bias in case-control studies. In matched case-control studies, researchers may not accurately judge whether the variable is a confounder. Sometimes the variables that are not confounders are mistakenly matched. In that case, it will result in overmatching, which will lead to the decline of statistical efficiency or the introduction of unavoidable bias or increase of workload. If the real confounding factors are omitted, it will cause confounding bias. Therefore, researchers should consider what kind of matching variable selection criteria should be formulated. A directed acyclic graph is a visual graphic language that can show the complicated causality among different epidemiological research designs. This article analyzes the role of Matching in different observational research designs from the perspective of the directed acyclic graph, formulates the selection criteria for matching variables in matched case-control studies, and provides some reference suggestions for future epidemiological research design.

Objective:To recognize virus electron microscopic (EM) images automatically with deep learning techniques and to select an appropriate network for virus EM image classification.Methods:Multiple classic convolutional neural networks, such as AlexNet, VGG, ResNet, DenseNet, SqueezeNet, MobileNet, and ShuffleNet, were used to classify the seven classes of virus electron microscope images by increasing the network depth increasing the network depth and adjusting the learning rate, adjusting the learning rate, batch size and other parameters.Results:Overall, DenseNet169 achieved the best performance with 91.9% accuracy, 90.1% sensitivity and 98.6% specificity. In particular, the model performed best in parvovirus recognition. The precision, sensitivity, specificity, and F1 of papilloma virus, herpes virus, pox virus and rotavirus, were above 90%, even close to 100%, but the precision of adenoviruses and the sensitivity of polyomaviruses were not satisfied, leading to corresponding low F1 value. At the same time, Lightweight network ShuffleNet outperformed AlexNet and VGG deep networks with fewer parameters and fewer FLOPs and could achieve comparable result to ResNet with about 15 times fewer parameters and 90 times fewer FLOPs; Compared with DenseNet, Shufflenet sacrificed recognition performance in the acceptable range to achieve about 10 times fewer parameters and 80 times fewer FLOPs.Conclusions:Deep networks DenseNet169 could realize automatic recognition of virus electron microscopic images with the optimal performance and lightweight networks shuffleNet_v2_x0_5 could achieve suboptimal performcane with fewer parameters and FLOPs. In practical applications, tradeoffs can be made between deep networks and lightweight networks based on specific conditions.