Objective To systematically evaluate the efficacy and safety of proximal gastrectomy (PG) versus total gastrectomy (TG) for the treatment of Siewert type Ⅱ/Ⅲ adenocarcinoma of the esophagogastric junction (AEG). Methods PubMed, The Cochrane Library, Web of Science, EMbase, CNKI, Wanfang, and VIP databases were searched for literature comparing the efficacy and safety of PG and TG for the treatment of Siewert type Ⅱ/Ⅲ AEG. The search period was from database inception to March 2023. Meta-analysis was performed using Review Manager 5.4 software. Results A total of 23 articles were included, including 16 retrospective cohort studies, 5 prospective cohort studies, and 2 randomized controlled trials. The total sample size was 2 826 patients, with 1 389 patients undergoing PG and 1 437 patients undergoing TG. Meta-analysis results showed that compared with TG, PG had less intraoperative blood loss [MD=−19.85, 95%CI (−37.20, −2.51), P=0.02] and shorter postoperative hospital stay [MD=−1.23, 95%CI (−2.38, −0.08), P=0.04]. TG had a greater number of lymph nodes dissected [MD=−6.20, 95%CI (−7.68, −4.71), P<0.001] and a lower incidence of reflux esophagitis [MD=3.02, 95%CI (1.24, 7.34), P=0.01]. There were no statistically significant differences between the two surgical approaches in terms of operative time, postoperative survival rate (1-year, 3-year, 5-year), and postoperative overall complications (P>0.05). Conclusion PG has advantages in terms of intraoperative blood loss and postoperative hospital stay, while TG has advantages in terms of the number of lymph nodes dissected and the incidence of reflux esophagitis. There is no significant difference in long-term survival between the two surgical approaches.

Chemotherapy is an important treatment for tumors， but most patients experience varying degrees of chemotherapy- induced myelosuppression. Four properties theory of traditional Chinese medicine （TCM） has unique advantages in improving chemotherapy-induced myelosuppression. The monomers from TCM with different properties and flavors， such as cold-natured （e.g. Scutellaria baicalensis， Rhus chinensis）， cool-natured （e.g. Ligustrum lucidum， Ophiopogon japonicus）， warm-natured （e.g. Panax ginseng， Epimedium brevicornu， Curcuma longa， Angelica sinensis）， hot-natured （e.g. Cinnamomum cassia， Aconitum carmichaeli）， and neutral-natured （e. g. donkey-hide gelatin， Lycium barbarum， Rhodiola rosea， fungi）， can exert anti- myelosuppressive effects by reducing damage to hematopoietic stem/progenitor cells， improving the bone marrow hematopoietic microenvironment， inhibiting the oxidative stress response， regulating signaling pathways， so as to ultimately repaire inflammatory damage and improve hematopoietic function， thereby playing an anti-myelosuppressive role.

Microbial-derived metabolites are important mediators of host-microbial interactions. In recent years, the role of intestinal microbial metabolites in colorectal cancer has attracted considerable attention. These metabolites, which can be derived from bacterial metabolism of dietary substrates, modification of host molecules such as bile acids, or directly from bacteria, strongly influence the progression of colitis-associated cancer (CAC) by regulating inflammation and immune response. Here, we review how microbiome metabolites short-chain fatty acids (SCFAs), secondary bile acids, polyamines, microbial tryptophan metabolites, and polyphenols are involved in the tumorigenesis and development of CAC through inflammation and immunity. Given the heated debate on the metabolites of microbiota in maintaining gut homeostasis, serving as tumor molecular markers, and affecting the efficacy of immune checkpoint inhibitors in recent years, strategies for the prevention and treatment of CAC by targeting intestinal microbial metabolites are also discussed in this review.
Humans ; Gastrointestinal Microbiome/physiology* ; Animals ; Carcinogenesis/metabolism* ; Colitis-Associated Neoplasms/microbiology* ; Fatty Acids, Volatile/metabolism* ; Bile Acids and Salts/metabolism* ; Colitis/microbiology*

This study aims to establish a method for counting the viral particles in adenovirus vector-based vaccines. Nano-flow cytometry was employed to analyze the viral particles in adenovirus-based vector vaccines at the single-particle level. Monodisperse silica nanoparticles with a refractive index close to that of the virus were selected as the particle size standard to calculate the viral particle size, which was then compared with the results obtained from transmission electron microscopy (TEM) to determine the gating strategy. Subsequently, a particle count standard was employed to calculate the viral particle concentration. The established method demonstrated good linearity, accuracy, precision, and specificity. The results of determined viral particle concentration showed a good correlation with the infectious titer. Compared with the conventional OD₂₆₀ method, nano-flow cytometry can directly measure the viral particle concentration and indicate whether the sample has been disassembled according to changes in viral particle concentration and size, thus more accurately reflecting the actual infectious potency of the sample. The novel quantification method established in this study is capable of indicating the efficacy of adenovirus vector-based vaccines and provides effective technical support for the quality control of such products.
Adenoviridae/genetics* ; Genetic Vectors ; Flow Cytometry/methods* ; Virion/isolation & purification* ; Particle Size ; Nanoparticles ; Viral Vaccines

L-phosphinothricin (L-PPT) is an efficient broad-spectrum herbicide. To realize the multi-enzyme catalytic preparation of L-PPT, we constructed an engineered strain Escherichia coli YM-1 for efficient expression of D-amino acid transaminase, which could catalyze the generation of the intermediate 2-oxo-4-[(hydroxymethylphosphonyl)] butyric acid (PPO) from D-phosphinothricin (D-PPT). In addition, E. coli pLS was constructed to co-express glutamate dehydrogenase and glucose dehydrogenase, which not only catalyzed the generation of L-PPT from PPO but also regenerated the coenzyme nicotinamide adenine dinucleotide phosphate (NADPH). A fed-batch fermentation process was then established for E. coli YM-1 and pLS, and the apparent activities of D-amino acid transaminase and glutamate dehydrogenase were increased by 22.68% and 100.82%, respectively, compared with those in shake flasks. The process parameters were optimized for the catalytic preparation of L-PPT by whole-cell cascade of E. coli YM-1 and pLS with D, L-PPT as the substrate. After reaction for 8 h, 91.36% conversion of D-PPT was achieved, and the enantiomeric excess of L-PPT reached 90.22%. The findings underpin the industrial production of L-PPT.
Escherichia coli/enzymology* ; Aminobutyrates/metabolism* ; Glutamate Dehydrogenase/biosynthesis* ; Glucose 1-Dehydrogenase/biosynthesis* ; Herbicides/metabolism* ; Multienzyme Complexes/metabolism* ; Transaminases/metabolism* ; Phosphinic Acids/metabolism*

Surgery-based multidisciplinary comprehensive treatment is the preferred treatment strategy for local advanced esophageal cancer. Neoadjuvant chemotherapy and neoadjuvant chemoradiotherapy have been recommended by the Chinese Society of Clinical Oncology (CSCO) guideline. With the advent of immunotherapy, neoadjuvant immunotherapy combined with chemotherapy has received much attention, and the first phase Ⅲ study has also confirmed that neoadjuvant immunotherapy combined chemotherapy is a promising treatment option. This article will review the recent advances and hot spots of neoadjuvant immunotherapy combined with chemotherapy.

Objective To investigate the status quo of pain catastrophizing(PC)in the patients with di-abetic peripheral neuropathic pain(DPNP),and to analyze the influencing factors to provide reference for for-mulating clinical preventive intervention strategies.Methods A total of 206 patients with DPNP admitted and treated in the People's Hospital of Guangxi Zhuang Autonomous Region were selected as the research sub-jects by convenience sampling method.The general data questionnaire,Numerical Rating Scale(NRS),Pain Catastrophizing scale(PCS),Perceived Social Support Scale(PSSS)and diabetes distress scale(DDS)were used to conduct the investigation.Results The incidence rate of PC in 206 cases of DPNP patients was 44.66％(92/206),and the total score of PCS was(30.10±5.16)points.The results of multiple linear regres-sion analysis showed that the gender,duration of diabetes(≥10 years),multiple drug use,number of compli-cations(＞5),NRS score,PSSS score and scores of DDS dimensions were the main influencing factors of PC(all P＜0.05),which could explain 92.3％of the total variation of PC.Conclusion The PC incidence rate in the patients with DPNP is high.Clinical healthcare workers should pay attention to the evaluation of PC in these patients,and formulate the scientific and effective targeted intervention measures according to the main influen-cing factors to help the patients to reduce the pain burden in order to reduce the level of PC.

Objective To propose a classification method for ultrasound images of pedicle screw canals based on radiomics analysis,and to evaluate the integrity of the screw canal.Methods With thoracolumbar spine specimens from 4 fresh cadavers,50 pedicle screw canals were pre-established and ultrasound images of the canals were acquired.A total of 2 000 images(1 000 intact and 1 000 damaged canal samples)were selected.The dataset was randomly divided in a 4∶1 ratio using 5-fold cross-validation to form training and testing sets(consisting of 1 600 and 400 samples,respectively).Firstly,the optimal radius of the region of interest was identified using the Otsu's thresholding method,followed by feature extraction using pyradiomics.Principal component analysis and the least absolute shrinkage and selection operator algorithm were employed for dimensionality reduction and feature selection,respectively.Subsequently,3 machine learning models(support vector machine[SVM],logistic regression,and random forest)and 3 deep learning models(visual geometry group[VGG],ResNet,and Transformer)were used to classify the ultrasound images.The performance of each model was evaluated using accuracy.Results With a region of interest radius of 230 pixels,the SVM model achieved the highest classification accuracy of 96.25%.The accuracy of the VGG model was only 51.29%,while the accuracies of the logistic regression,random forest,ResNet,and Transformer models were 85.50%,80.75%,80.17%,and 75.18%,respectively.Conclusion For ultrasound images of pedicle screw canals,the machine learning model performs better than the deep learning model as a whole,and the SVM model has the best classification performance,which can be used to assist physicians in diagnosis.

Objective:To develop a nomogram predictive model on the basis of identification of the risk factors associated with failure in repositioning the dislocation of the subaxial cervical spine with locked facets by skull traction.Methods:A retrospective study was conducted of the clinical data of the patients who had been treated for dislocation of the subaxial cervical spine with locked facets at Department of Orthopaedic Trauma, The Hospital Affiliated to Guizhou Medical University and Department of Spine Surgery, The People's Hospital of Guizhou Province from January 2014 to December 2022. The clinical data from The Hospital Affiliated to Guizhou Medical University were used as a training set (156 cases) and those from The People's Hospital of Guizhou Province as an external validation set (54 cases). Univariate analysis and multi-variate logistic regression analysis of the training set were conducted to screen out independent risk factors associated with the failure in repositioning the dislocation of the subaxial cervical spine with locked facets by skull traction. A nomogram predictive model was thus constructed and assessed by the receiver operating characteristic (ROC) curve, calibration curve, and decision curve. Internal validation of the training set and external validation set was used to evaluate and validate the model.Results:The multivariate logistic regression analysis revealed that cervical Ⅰ grade dislocation ( P=0.002), cervical Ⅱ grade dislocation ( P=0.007), low segment affected ( P=0.042), unilateral facet locked ( P=0.027), and the ASIA grading of spinal cord injury ( P=0.008) were the independent risk factors associated with the failure in repositioning the dislocation of the subaxial cervical spine with locked facets by skull traction, based on which the nomogram model with a C-index of 0.88 was constructed to predict the failure in repositioning the dislocation of the subaxial cervical spine with locked facets by skull traction. Analysis of the ROC curve of the training set showed an area under the curve (AUC) of 0.88, indicating good accuracy of the nomogram model. Analysis of the calibration curve showed high consistency between the probability of the nomogram model predicting the failure in repositioning the dislocation of the subaxial cervical spine with locked facets by skull traction and the actual probability of traction reposition failure. Analysis of the decision curve showed that application of the nomogram model led to good benefits when the net benefit threshold for the failure in repositioning the dislocation of the subaxial cervical spine with locked facets by skull traction was 0.03 to 0.84. Analysis of the ROC curve of external validation set showed an AUC of 0.79, indicating good accuracy of the nomogram model. The training set showed a C-index of 0.87 after 1,000 internal verifications by the Bootstrap method, indicating good discrimination of the nomogram model. Conclusions:Cervical Ⅰ grade dislocation, cervical Ⅱ grade dislocation, low segment affected, unilateral facet locked, and incomplete spinal cord injury are independent risk factors associated with failure in repositioning the dislocation of the subaxial cervical spine with locked facets by skull traction. A nomogram model has been successfully constructed which can predict the failure in repositioning the dislocation of the subaxial cervical spine with locked facets by skull traction. Validation and evaluation of the nomogram model have demonstrated its good predictive value.

This paper presents two cases of renal allograft parapelvic cysts treated with ureteroscopy involving internal incision and drainage using a holmium laser. The procedure also involved cyst puncture and injection of methylthioninium chloride, with ultrasound monitoring to determine the incision location based on the 'flame sign.' The surgeries were uneventful, and follow-up ultrasounds conducted 2 to 3 months later revealed a reduction in cyst size. This technique introduces a novel approach for treating parapelvic cysts in renal allografts.