Objective To analyze the acupoint selection law of acupuncture and moxibustion for postherpetic neuralgia(PHN)with R language data mining technology.Methods The clinical research literature on acupuncture and moxibustion treatment of PHN included in CNKI,Wanfang Data,VIP and CBM from January 1,2010 to July 1,2023 was retrieved,and the database was established by Excel 2016.R language was used to statistically analyze the frequency of acupoint usage,meridians,locations,specific acupoints,etc.Through association rule analysis and clustering analysis,the characteristics and law of acupoint selection for acupuncture and moxibustion treatment of PHN were obtained.Results A total of 198 articles were included,including 83 acupoints,with a total frequency of 714 times.The high-frequency acupoints include Ashi acupoint,Jiaji acupoint and Yanglingquan.The commonly used meridians were gallbladder meridian,spleen meridian and large intestine meridiam.The acupoints were mostly in the upper and lower limbs,with the Wushu acupoints,Yuan acupoints and Xiahe acupoints being the most common.The core acupoint was Ashi acupoint,Jiaji acupoint,Hegu,Quchi,and 9 sets of association rules and 5 effective clusters were obtained.Conclusion The most commonly used acupoints for acupuncture and moxibustion treatment of PHN are Ashi acupoint,Jiaji acupoint,Hegu and Quchi,which mainly follow the principle of combining local acupoint selection with distal acupoint selection.

Objective To analyze the acupoint selection law of acupuncture and moxibustion for postherpetic neuralgia(PHN)with R language data mining technology.Methods The clinical research literature on acupuncture and moxibustion treatment of PHN included in CNKI,Wanfang Data,VIP and CBM from January 1,2010 to July 1,2023 was retrieved,and the database was established by Excel 2016.R language was used to statistically analyze the frequency of acupoint usage,meridians,locations,specific acupoints,etc.Through association rule analysis and clustering analysis,the characteristics and law of acupoint selection for acupuncture and moxibustion treatment of PHN were obtained.Results A total of 198 articles were included,including 83 acupoints,with a total frequency of 714 times.The high-frequency acupoints include Ashi acupoint,Jiaji acupoint and Yanglingquan.The commonly used meridians were gallbladder meridian,spleen meridian and large intestine meridiam.The acupoints were mostly in the upper and lower limbs,with the Wushu acupoints,Yuan acupoints and Xiahe acupoints being the most common.The core acupoint was Ashi acupoint,Jiaji acupoint,Hegu,Quchi,and 9 sets of association rules and 5 effective clusters were obtained.Conclusion The most commonly used acupoints for acupuncture and moxibustion treatment of PHN are Ashi acupoint,Jiaji acupoint,Hegu and Quchi,which mainly follow the principle of combining local acupoint selection with distal acupoint selection.

Objective To construct a 3D ResNet deep learning model based on multi-parametric prostate MRI(mpMRI),and to observe its value for automatically identifying the main MR sequences.Methods Totally 1 153 sets pre-biopsy prostate mpMRI data of 1 086 patients who underwent ultrasound-guided prostate biopsy in 3 hospitals were collected and divided into different image datasets,i.e.T2WI,diffusion-weighted imaging(DWI)and apparent diffusion coefficient(ADC)maps with a total of 5 151 images.Then the images were categorized into non-fat-suppressed T2WI(T2WI_nan,n=1 000),fat-suppressed T2WI(T2WI_fs,n=1 188),high b-value DWI(DWI_High,b-value≥500 s/mm2,n=1 045),low b-value DWI(DWI_Low,b-value＜500 s/mm2,n=1 012)or ADC map(n=906),also divided into training set(n=4 122),verification set(n=513)and test set(n=516)at the ratio of 8∶1∶1.After preprocessing and augmentation,a 3D ResNet model for automatically identifying image categories was trained and optimized in the training and verification sets,and its classification efficiency was evaluated in the test set.Results The identifying accuracy,sensitivity,specificity,positive predictive value,negative predictive value,F1 score and Kappa value of the obtained model for automatically identifying categories of images in the test set was 0.995-1.000,0.990-1.000,0.998-1.000,0.990-1.000,0.998-1.000,0.995-1.000 and 0.994-1.000,respectively.Conclusion The obtained 3D ResNet deep learning model could effectively and automatically identify the main sequences of prostate mpMRI.

Objective To develop a 3D V-Net deep learning segmentation model based on multi-center data,and to evaluate its value for automatic segmentation of prostate on T2WI and apparent diffusion coefficient(ADC)maps.Methods Totally 2 894 sets of multi-parametric MRI data of 2 673 patients with clinically suspected prostate cancer from 3 medical centers within 1 month before biopsy were retrospectively collected.Finally 5 974 sets axial images were enrolled,including 3 654 sets of T2WI and 2 320 sets of ADC maps.Prostate contours were manually annotated layer by layer on axial T2WI and ADC maps,and the left-to-right,anterior-to-posterior,superior-to-inferior diameters and volume of prostate were measured and taken as reference standards.The images were divided into training set(n=4 780,including 2 907 sets of T2WI and 1 873 sets of ADC map),verification set(n=601,including 384 sets of T2WI and 217 sets of ADC map)and test set(n=593,including 363 sets of T2WI and 230 sets of ADC map)at the ratio of 8:1:1.After preprocessing and augmentation,3D V-Net was used to construct and train the segmentation model based on training and verification sets,and the segmentation performance of the model was evaluated in test set using Dice similarity coefficient(DSC),Jaccard coefficient(JACARD)and volume similarity(VS),respectively.The parameters measured with the model were compared with the reference standards,and the correlations were explored.Results Compared with the corresponding ADC maps,DSC,JACARD and VS of the model for automatic segmentation of prostate on T2WI in test set were all higher(all P＜0.001).The left-to-right,anterior-to-posterior and superior-to-inferior diameters of prostate measured with the model on both T2WI and ADC maps were all larger than the reference standards(all P＜0.001),while no significant difference of the volume was found(both P＞0.05).All parameters measured with the model on T2WI and ADC maps were positively correlated with reference standards(rs=0.794-0.985).Conclusion 3D V-Net deep learning model could automatically segment prostate on T2WI and ADC maps with high accuracy,and its efficiency based on T2WI was better than that based on ADC maps.

Objective:To analyze clinical features, short-term efficacy and side effects of salvage re-irradiation therapy for patients with locally recurrent esophageal cancer after definitive chemoradiotherapy, to investigate the prognostic factors of re-irradiation with precise radiotherapy techniques.Methods:A retrospective analysis was performed on patients with locally recurrent esophageal squamous cell carcinoma after definitive chemoradiotherapy treated in the Fourth Hospital of Hebei Medical University from January 2008 to December 2016. The patients underwent re-irradiation therapy (re-RT) or re-irradiation therapy concurrent chemotherapy (re-CCRT). The main observation index was after-recurrence survival (ARS), which was calculated by Kaplan-Meier method for survival analysis. Univariate analysis was conducted by log-rank test, and multivariate analysis was performed by Cox regression model.Results:A total of 109 patients were included, with a median age of 66 years (43-89 years), and a median follow-up time of 120.8 months (79.0-176.5 months). The objective response rates (ORR) and dysphagia improvement rates (DIR) in all patients were 64.2% and 63.0%, respectively. The median ARS and 1-, 3-, 5-, 8-year survival rates in all patients were 7.8 months and 32.1%, 9.2%, 7.3% and 2.3%, respectively. The median ARS and 1-, 3-, 5-years survival rates were 10.8 months and 45.9%, 13.5%, 10.8% for patients with time to recurrence (TTR) ≥24 months, significantly longer than those of 5.7 months and 25.0%, 6.9%, 5.6% for patients with TTR<24 months ( χ2=7.99, P=0.005). The median ARS in groups with re-irradiation dose of ≤50 Gy,>50-54 Gy, and>54 Gy groups were 5.7, 10.0 and 8.1 months, respectively ( χ2=6.94, P=0.031). The 1-, 3- and 5-year survival rates were 30.4%, 5.1%, and 3.8% for re-RT versus 36.7%, 20.0%, and 16.7% for re-CCRT ( χ2=2.12, P=0.145). Multivariate analysis showed that TTR ( HR=0.607, 95% CI=0.372-0.991, P=0.046) and lesion length ( HR=0.603, 95% CI=0.371-0.982, P=0.042) were the independent factors for ARS. There was no significant difference in ≥2 grade pneumonitis and 2-3 grade radiation esophagitis between the re-RT and re-CCRT groups ( χ2=0.25, P=0.619; χ2=0.51, P=0.808). The morbidity of ≥2 grade myelosuppression in the re-RT group was significantly lower than that in the re-CCRT group (3.7% vs. 36.7%, χ2=18.15, P<0.001). Conclusions:Precise re-irradiation therapy for patients with locally recurrent esophageal cancer after definitive chemoradiotherapy can alleviate dysphagia, but ARS remains poor. Re-irradiation dose range from>50-54 Gy may be suitable for locally relapse patients as salvage treatment. Patients with TTR≥24 months and lesion length ≤5 cm obtain favorable prognosis.

pancreatic cancer is a common malignant tumor of digestive system, with poor prognosis. About 80% of patients have lost the opportunity of surgical resection when diagnosed. In different treatment schemes, radioactive seed 125I implantation can improve the quality of life of patients with unresectable pancreatic cancer and is expected to improve their survival rate. This article reviews the clinical applications of 125I particle implantation therapy combined with chemotherapy, cryotherapy, intracavitary irradiation, stent placement, radiofrequency ablation, nanoknife, and bypass surgery, in order to better promote its clinical application. However, it is necessary to establish unified dosage standards and regulatory guidelines to make them safer and more widely serve clinical practice.

Objective:To perform adenovirus detection and genetic evolutionary analysis on specimens from a fever outbreak in Kunming city.Methods:Pharyngeal swabs from typical febrile patients were collected and tested for nucleic acids of 30 common respiratory pathogens using TaqMan Array Card technology. The full-length sequences of three important genes of adenovirus, Penton base, Hexon and Fiber, were amplified, sequenced and typed using Nanopore high-throughput sequencing. A phylogenetic tree was constructed. Molecular variations and genetic evolution of the three genes were analyzed.Results:Five specimens were collected and all of them tested positive for adenovirus and Haemophilus influenzae. The sequences of the full-length coding regions of the Penton base, Hexon and Fiber genes were obtained by Nanopore sequencing. The homology of the three gene sequences in the five specimens was 100.0%, 99.9%-100.0% and 100.0% in nucleotide sequences, and 100.0% in amino acid sequences. The three genes in the specimens had the highest homology with those of the reference strain of human adenovirus type 3 (HAdV3, accession number: AY599834) in nucleotide sequences, which was 98.6%, 98.7% and 98.9%, respectively. Results of the phylogenetic analysis of the three genes were basically consistent. These Kunming strains were clustered into an independent clade with the reference HAdV3 strain and had a distant relationship with the strains isolated in foreign countries and Taiwan, China in the early years. They were closely related to the domestic and foreign strains in recent years and highly homologous to the 2019 Japanese strain (accession: LC703523) and the Guangzhou strain (accession: MZ540961). Compared with the reference strain, these Kunming strains had five amino acid variations in Penton base, 10 in Hexon and 11 in Fiber. Conclusions:All of the adenovirus strains isolated in this outbreak belong to P3H3F3 type based on the full-length sequences of Penton base, Hexon and Fiber genes. They share high homology with the domestic and foreign HAdV3 strains, including the reference strain. Compared with the reference strain, several amino acid mutations are identified in these Kunming strains, and most of them are in the high variability region or functional regions. M7L in the Hexon protein is an unique amino acid mutation site of Kunming strains.

Developing new therapeutic agents for cancer immunotherapy is highly demanding due to the low response ratio of PD-1/PD-L1 blockade in cancer patients. Here, we discovered that the novel immune checkpoint VISTA is highly expressed on a variety of tumor-infiltrating immune cells, especially myeloid derived suppressor cells (MDSCs) and CD8⁺ T cells. Then, peptide C1 with binding affinity to VISTA was developed by phage displayed bio-panning technique, and its mutant peptide VS3 was obtained by molecular docking based mutation. Peptide VS3 could bind VISTA with high affinity and block its interaction with ligand PSGL-1 under acidic condition, and elicit anti-tumor activity in vivo. The peptide DVS3-Pal was further designed by d-amino acid substitution and fatty acid modification, which exhibited strong proteolytic stability and significant anti-tumor activity through enhancing CD8⁺ T cell function and decreasing MDSCs infiltration. This is the first study to develop peptides to block VISTA/PSGL-1 interaction, which could act as promising candidates for cancer immunotherapy.

Objective    To explore the relationship between metformin use and the risk and prognosis of esophageal cancer in patients with diabetes. Methods    The PubMed, Web of Science, EMbase, VIP, WanFang and CNKI databases were searched by computer to identify relevant studies from inception to August 21, 2021. Newcastle-Ottawa scale (NOS) was used to evaluate research quality. The STATA 12.0 software was used to conduct the statistical analysis. Results    A total of 14 studies involving 5 605 218 participants were included finally. NOS of all researches were≥6 points. The pooled results indicated that metformin use could decrease the risk of esophageal cancer in diabetics (OR=0.84, 95%CI 0.71-1.00, P=0.045), and could also prolong the overall survival of diabetics with esophageal cancer (HR=0.89, 95%CI 0.80-0.99, P=0.025). Conclusion    Metformin use can not only decrease the risk of esophageal cancer in patients with diabetes, but also improve the prognosis of diabetics with esophageal cancer significantly. However, more prospective high-quality studies are still needed to verify the conclusion.

AIM: To investigate the effects of age, gender, duration of medication and combined medication on the steady-state blood concentration of tacrolimus in patients with autoimmune diseases, and to establish the reference range of steady-state blood concentration of tacrolimus in combination with liver and kidney function, so as to provide theoretical basis for clinical individual medication. METHODS: A total of 107 patients with autoimmune diseases treated with tacrolimus in the department of rheumatology and immunology of our hospital from August 2017 to June 2021 were included. Their gender, age, dose, drug combination, blood concentration, and liver and kidney function were statistically analyzed by SPSS 22.0 statistical software. RESULTS: In the treatment of autoimmune diseases with tacrolimus, there was statistical significance in the blood concentration of different genders (P<0.05), but there was no statistical significance in the blood concentration of different ages (P>0.05) and a statistically significant difference in the dosage of tacrolimus (P<0.05), the duration of medication did not affect the effective dose, target blood concentration, liver and kidney functions. There was a weak correlation between tacrolimus dose and blood concentration (r=0.115, P=0.047). When the blood concentration of tacrolimus ranged from 4.20 to 9.48 ng/mL, the levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT) and urea increased significantly. When tacrolimus blood concentration ranged from 0.08 to 4.20 ng/mL, there was no significant difference in serum creatinine, AST, ALT, albumin, total bilirubin (TBIL), direct bilirubin (DBIL), indirect bilirubin (IBIL). CONCLUSION: Tacrolimus is used for the treatment of autoimmune diseases, and the blood concentration varies greatly among individuals. To avoid the risk of potential damage to liver and kidney function. It is recommended that clinicians control the blood concentration at 0.08-4.20 ng/mL, and adjust the dose and optimize the dose according to the patient's gender, age, and clinical efficacy.