Neuraminidase(NA),a glycoprotein on the surface of the influenza virus,plays a crucial role in viral escape and serves as a stable target for drug candidates.Monoclonal antibodies targeting the NA active site can bind to multiple influenza virus subtypes and inhibit the spread of influenza virus through various mechanisms,such as neutralizing,mediating antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotox-icity.In vivo experiments have shown that human monoclonal antibodies targeting the influenza virus NA can ef-fectively exert preventive and therapeutic effects,rescuing mice infected with lethal doses and reducing viral ti-ters in lungs of mice.This article provides a review of the currently reported human monoclonal antibodies targe-ting NA of Influenza A and Influenza B viruses,providing new ideas and prospects for the subsequent development of anti-influenza drugs.

Objective:To analyze the risk factors for clinically relevant delayed gastric emptying (CR-DGE) following laparoscopic pancreaticoduodenectomy (LPD) and to develop a model to predict the postoperative CR-DGE after LPD using the machine-learning approach with multi-model comparison.Methods:Clinical data of 278 patients with tumors located in the pancreatic head and periampullary region undergoing LPD at People’s Hospital of Zhengzhou University from January 2019 to December 2023 were retrospectively analyzed, including 167 males and 111 females, aged 59 (53, 66) years. According to the occurrence of DGE, patients were divided into the CR-DGE group ( n=94) and the non-CR-DGE group ( n=184). Main clinical characteristics were compared between the groups, including pancreatic duct diameter, intraoperative blood loss and operative time. The perioperative indicators were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Following variable selection, 278 patients were allocated into a training set ( n=222) and a validation set ( n=56) in an 8∶2 ratio. Eight machine learning models were selected to model the training set: random forest, adaptive boosting, light gradient boosting, multilayer perceptron, support vector machine, K-nearest neighbor algorithm, decision tree and complementary set plain bayes. The area under the curve (AUC) of receiver operating characteristic curve of the validation set was utilized to identify the optimal model. The predictive performance of the optimal model was evaluated using calibration plots and decision curve analysis (DCA). The contribution of each feature to the prediction is assessed using Shapley additive explanation (SHAP). Results:Univariate analysis showed statistically significant differences between the CR-DGE and non-CR-DGE groups in terms of age [66(62, 69) years vs. 56(51, 60), years], diabetes [42.6%(40/94) vs. 11.4%(21/184)], level of fibrinogen [3.43(2.74, 4.18) g/L vs. 3.84(3.19, 4.68) g/L], pancreatic duct diameter [2.00(1.50, 2.70) mm vs. 3.40(1.60, 5.00) mm], intraoperative blood loss [300(200, 600) ml vs. 200(150, 300) ml], operative time [472(430, 502) min vs. 430(365, 475) min], clinically relevant postoperative pancreatic fistula [34.0%(32/94) vs. 3.8%(7/184)], abdominal fluid accumulation [46.8%(44/94) vs. 12.5%(23/184)], postoperative hemorrhage [20.2%(19/94) vs. 3.3%(6/184)], abdominal infection [28.7%(27/94) vs. 11.4% (21/184)] and duration of postoperative gastrointestinal decompression [4.00 (2.00, 6.00) d vs. 3.00 (2.00, 5.00) d] (all P<0.05). The eleven variables selected via LASSO were incorporated into each of the eight machine learning models. Results demonstrated that the random forest model achieved the highest performance in the validation set, with an AUC of 0.894 (95% CI: 0.800-0.985), accuracy of 0.820 and sensitivity of 0.606. Calibration plots and DCA confirmed the robustness of the random forest model. SHAP analysis indicated that age, pancreatic duct diameter and preoperative aspartate aminotransferase were important predictors in the random forest model. Conclusion:The random forest model developed in this study demonstrated a good predictive performance for CR-DGE after LPD and may assist in the early identification of high-risk patients in clinical practice.

Neuraminidase(NA),a glycoprotein on the surface of the influenza virus,plays a crucial role in viral escape and serves as a stable target for drug candidates.Monoclonal antibodies targeting the NA active site can bind to multiple influenza virus subtypes and inhibit the spread of influenza virus through various mechanisms,such as neutralizing,mediating antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotox-icity.In vivo experiments have shown that human monoclonal antibodies targeting the influenza virus NA can ef-fectively exert preventive and therapeutic effects,rescuing mice infected with lethal doses and reducing viral ti-ters in lungs of mice.This article provides a review of the currently reported human monoclonal antibodies targe-ting NA of Influenza A and Influenza B viruses,providing new ideas and prospects for the subsequent development of anti-influenza drugs.

Objective:To analyze the risk factors for clinically relevant delayed gastric emptying (CR-DGE) following laparoscopic pancreaticoduodenectomy (LPD) and to develop a model to predict the postoperative CR-DGE after LPD using the machine-learning approach with multi-model comparison.Methods:Clinical data of 278 patients with tumors located in the pancreatic head and periampullary region undergoing LPD at People’s Hospital of Zhengzhou University from January 2019 to December 2023 were retrospectively analyzed, including 167 males and 111 females, aged 59 (53, 66) years. According to the occurrence of DGE, patients were divided into the CR-DGE group ( n=94) and the non-CR-DGE group ( n=184). Main clinical characteristics were compared between the groups, including pancreatic duct diameter, intraoperative blood loss and operative time. The perioperative indicators were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Following variable selection, 278 patients were allocated into a training set ( n=222) and a validation set ( n=56) in an 8∶2 ratio. Eight machine learning models were selected to model the training set: random forest, adaptive boosting, light gradient boosting, multilayer perceptron, support vector machine, K-nearest neighbor algorithm, decision tree and complementary set plain bayes. The area under the curve (AUC) of receiver operating characteristic curve of the validation set was utilized to identify the optimal model. The predictive performance of the optimal model was evaluated using calibration plots and decision curve analysis (DCA). The contribution of each feature to the prediction is assessed using Shapley additive explanation (SHAP). Results:Univariate analysis showed statistically significant differences between the CR-DGE and non-CR-DGE groups in terms of age [66(62, 69) years vs. 56(51, 60), years], diabetes [42.6%(40/94) vs. 11.4%(21/184)], level of fibrinogen [3.43(2.74, 4.18) g/L vs. 3.84(3.19, 4.68) g/L], pancreatic duct diameter [2.00(1.50, 2.70) mm vs. 3.40(1.60, 5.00) mm], intraoperative blood loss [300(200, 600) ml vs. 200(150, 300) ml], operative time [472(430, 502) min vs. 430(365, 475) min], clinically relevant postoperative pancreatic fistula [34.0%(32/94) vs. 3.8%(7/184)], abdominal fluid accumulation [46.8%(44/94) vs. 12.5%(23/184)], postoperative hemorrhage [20.2%(19/94) vs. 3.3%(6/184)], abdominal infection [28.7%(27/94) vs. 11.4% (21/184)] and duration of postoperative gastrointestinal decompression [4.00 (2.00, 6.00) d vs. 3.00 (2.00, 5.00) d] (all P<0.05). The eleven variables selected via LASSO were incorporated into each of the eight machine learning models. Results demonstrated that the random forest model achieved the highest performance in the validation set, with an AUC of 0.894 (95% CI: 0.800-0.985), accuracy of 0.820 and sensitivity of 0.606. Calibration plots and DCA confirmed the robustness of the random forest model. SHAP analysis indicated that age, pancreatic duct diameter and preoperative aspartate aminotransferase were important predictors in the random forest model. Conclusion:The random forest model developed in this study demonstrated a good predictive performance for CR-DGE after LPD and may assist in the early identification of high-risk patients in clinical practice.

Objective To discuss the feasibility and safety of simultaneous bilateral adrenal vein sampling(AVS)using two 4F-MPA1 catheters via right elbow vein access.Methods A total of 51 consecutive patients with primary aldosteronism,who received simultaneous bilateral AVS using two 4F-MPA1 catheters(one of the two catheters was shaped into pig tail figure)via right elbow vein access at Xiangyang Municipal Central Hospital between October 2021 and October 2022,were enrolled in this study.The used catheter,the success rate of simultaneous bilateral AVS,and the incidence of complications rate were calculated.Results The 4F-MPA1 catheter was used for all of the right AVS,while a specially shaped 4F-MPA1 catheter was used for the main trunk vein AVS of the left adrenal gland and the central vein AVS of the left adrenal gland.The success rate of simultaneous bilateral AVS was 92.2%(47/51).Adrenal hematoma occurred in one patient(1.96%).Conclusion The technique of simultaneous bilateral AVS using two 4F-MPA1 catheters via right elbow vein access is simple to operate,less traumatic,and clinically safe and feasible.However,due to the small sample used in this study,the clinical value of this technique still needs further investigation and verification.

Objective To evaluate the incidental irradiation to the axillary levels Ⅰ,Ⅱ and Ⅲduring the whole breast radiotherapy after breast conserving surgery(BCS)without axillary lymph node dissection(ALND)in breast cancer(BC)patients.Methods A retrospective analysis was performed on the consecutive 42 cases of T1-2N0M0stage BC patients with sentinel lymphnode biopsy(SLNB)and BCS but without ALND.The axillary lymph nodes of Ⅰ,Ⅱ and Ⅲ were delineated according to RTOG atlas guideline.Three radiotherapy plans including conventional tangential field(CTF),three-dimensional conformal radiotherapy(3D-CRT)and forward-planned intensity-modulated radiotherapy(IMRT)for whole breast irradiation were devised for each case.The Prescription dose was 50 Gy per 25 fractions.Doses to axillary levels(Ⅰ-Ⅲ)were evaluated.Results The mean doses delivered to axillary by the three techniques(CTF,3D-CRT and IMRT)were(40.1 ±6.8),(35.4 ±8.3),(32.9 ±7.0)Gy for level Ⅰ(F＝10.269,P＜0.05),(33.2 ±7.1),(30.6 ±6.7),(30.4 ±7.0)Gy for level Ⅱ(P＞0.05)and(9.6 ±6.8),(6.4 ±4.5),(5.2 ±3.7)Gy for level Ⅲ(F ＝8.377,P ＜0.05),respectively.V50(volume receiving 50 Gy)for the three techniques were 21.3％,27.6％,9.6％for level Ⅰ(F＝13.161,P＜0.05),12.9％,15.9％,8.3％for level Ⅱ(F＝2.750,P＜0.05)and 0.4％,0.1％and 0％for level Ⅲ(P＞0.05),respectively.Conclusions The doses coverage to axillary levelsⅠ-Ⅲwere all limited in the three techniques.Therefore,it is necessary to assess the risk of axillary lymph node metastasis adequately to develop individualized radiotherapy plans.

Objective To apply real-time transperineal ultrasound ( TPUS) to monitor the intra-fractional prostate motion,collect and analyze the data of the prostate motion,aiming to provide evidence for the optimization of the target area and plan of radiotherapy for prostate cancer. Methods TPUS is a non-invasive monitoring technique that utilizes an automatic scanning ultrasound probe to dynamically monitor and correct the motion of organs during radiotherapy. In this study, TPUS was utilized to collect 1588 intra-fractional data of 70 patients with prostate cancer. Prior to each cycle of radiotherapy,CBCT was adopted to correct the errors between intra-factional data by using VMAT. During radiotherapy, real-time ( once per second) ultrasound images were acquired to monitor the 3D motion of the prostate on the x (left+,right-),y (cranial+, caudal-), and z ( abdominal+, dorsal-) axes, emphasizing the analysis of 4D motion of the prostate. Results All patients successfully completed the treatment and data collection. The median time of effective monitoring per faction was 179 seconds (132-286 seconds). During 95% of the monitoring time,the distance of prostate motion was 2. 22 mm in the left direction,2. 17 mm in the right,2. 08 mm in the cranial, 1. 98 mm in the caudal,2. 44 mm in the abdominal and 2. 97 mm in the dorsal direction,respectively. In the x,y and z axes,the percentage of time in which the distance of prostate motion less than 1 mm among the total time was 83. 07%,85. 46% and 78. 27%,respectively,whereas 97. 70%,97. 87% and 96. 45% for＜3 mm, respectively. Conclusions TPUS is a non-invasive real-time monitoring technique,which can detect the 4D motion of the prostate during radiotherapy. By using VMAT,the range of prostate motion is relatively small, and the motion range is less than 3 mm in each direction within 95% of the time.

Objective To investigate the relationship of complements C3 and C4 with essential hypertension and its risk factors, homocysteine (HCY) and blood lipids.Methods We selected 20 healthy subjects for physical checkup as control group and 45 patients with hypertension as hypertension group.According to The Guidelines for Prevention and Treatment of Dyslipidemia in Chinese Adults, the hypertension group was divided into lipid regulating therapy group and non-lipid regulating therapy group.We determined the levels of complements C3 and C4, HCY, total cholesterol, low density lipoprotein and apolipoprotein.Pearson linear correlation regression analysis was used to analyze the correlation of the complements with HCY and blood lipid indexes.Results Complements C3 and C4 were significantly higher in the hypertension group than in the control group (P<0.05).HCY was also significantly higher than that in control group (P<0.05).The Pearson linear correlation analysis showed that in the hypertension group Complement C3 was positively correlated with cholesterol, low density lipoprotein and apolipoprotein B (P<0.05).Complements C3 and C4 were not related to HCY (P=0.073, P=0.699).Compared with the non-lipid regulating therapy group, C4, cholesterol, low density lipoprotein and apolipoprotein B were significantly decreased in the lipid regulating therapy group (P<0.05).The Pearson linear correlation analysis showed that in the lipid regulating therapy group complements C3 and C4 were not related to low density lipoprotein (P>0.05) or to homocysteine (P=0.074, P=0.894).Conclusion Complements C3 and C4 are closely related to essential hypertension.Activation of the complement system is one of the important risk factors for hypertension.The lipid regulating therapy can significantly alleviate immune damage in patients with essential hypertension.Hyperhomocysteinemia is an independent risk factor for essential hypertension.

Objective To analyze the correlation of vertebral osteophyte and lumbar disc degeneration in the elderly people and explore the possible mechanism of osteophyte formation. Methods X-ray and MRI data of 120 elderly people with backache or leg pain were retrospectively analyzed. Osteophyte was classified into four grades by X-ray according to the method proposed by Nathan. Discs with osteophyte were defined as occurring when osteophyte of grade II or greater were present. Lumbar disc degeneration was classified into five grades by MRI according to the method proposed by Pfirrmann. The obtained parameters were statistically treated and analyzed. Results Osteophyte and age were positively correlated at every lumbar disc level (P < 0.05). The proportion of osteophyte in L3/4 (76.7%) and L4/5 (70.08%) were more severe than that in L1/2 (31.7%) and L2/3 (46.7%). Osteophyte and lumbar disc degeneration were positively correlated at every lumbar disc level (P < 0.01). Conclusion Osteophyte becomes more severe with the increasing of lumbar disc degeneration. The vertebral stress after lumbar disc degeneration may be the main cause of osteophyte.