Endoscopic retrograde cholangiopancreatography for patients aged ninety and older with choledocholithiasis: A single-center experience in south China

BACKGROUND Endoscopic retrograde cholangiopancreatography(ERCP)serves an essential role in treating biliary diseases,especially in choledocholithiasis.However,due to the limited human lifespan,there remains a paucity of clinical investigations on ERCP treatment in patients over 90 years old.AIM To explore the effectiveness and safety of ERCP in super-older patients aged≥90 years with choledochal stones.METHODS This study retrospectively analyzed data from patients(aged≥65 years)with choledocholithiasis who received ERCP treatment in our hospital from 2011 to 2023.Among them,patients≥90 years old were in the super-older group,and patients aged 65-89 years were in the older group.Baseline data,including gender,number of stones,stone size,gallbladder stones,periampullary diverti-culum,and common bile duct intubation of patients in the two groups,were mat-ched by adopting the 1:1 propensity score matching method.RESULTS After matching,44 patients were included in both the super-older group and the older group.The incidence of stroke in the super-older group was markedly higher than that in the older group[34.1%(15/44)vs 6.8%(3/44),P=0.008].The success rate of the ERCP procedure in the super-older group was 90.9%(40/44),compared to that in the older group[93.2%(41/44),P=1.000].Although endo-scopic papillary balloon dilation was more frequently used in the super-older group than in the older group[61.4%(27/44)vs 18.2%(8/44),P<0.001],there was no significant difference in terms of stone removal rate,the incidence of complications,mortality,recurrence,and length of hospitalization between the two groups(P>0.05).CONCLUSION ERCP is safe and effective in super-older patients≥90 years old with choledocholithiasis.

Endoscopic retrograde cholangiopancreatography,endoscopic papillary balloon dilation,and laparoscopic hepatectomy for intraand extrahepatic bile duct stones

BACKGROUND Intrahepatic and extrahepatic bile duct stones(BDSs)have a high rate of residual stones,a high risk of recurrence,and a high rate of reoperation.It is very important to take timely and effective surgical intervention for patients.AIM To analyze the efficacy,postoperative rehabilitation,and quality of life(QoL)of patients with intra-and extrahepatic BDSs treated with endoscopic retrograde cholangiopancreatography(ERCP)+endoscopic papillary balloon dilation(EPBD)+laparoscopic hepatectomy(LH).METHODS This study selected 114 cases of intra-and extrahepatic BDSs from April 2021 to April 2024,consisting of 55 cases in the control group receiving laparoscopic common bile duct exploration and LH and 59 cases in the observation group treated with ERCP+EPBD+LH.Efficacy,surgical indicators[operation time(OT)and intraoperative blood loss(IBL)],postoperative rehabilitation(time for body temperature to return to normal,time for pain relief,and time for drainage to reduce jaundice),hospital stay,medical expenses,and QoL[Gastrointestinal Quality of Life Index(GIQLI)]were comparatively analyzed.Further,Logistic regression analysis was conducted to analyze factors influencing the QoL of patients with intra-and extrahepatic BDSs.RESULTS The data demonstrated a higher overall effective rate in the observation group compared to the control group(P=0.011),together with notably reduced OT,less IBL,shorter body temperature recovery time,pain relief time,time for drainage to reduce jaundice,and hospital stay(all P<0.05).The postoperative GIQLI of the observation group was more significantly increased compared to the control group(P<0.05).The two groups demonstrated no marked difference in medical expenses(P>0.05).CONCLUSION The above indicates that ERCP+EPBD+LH is effective in treating patients with intra-and extrahepatic BDSs,which is conducive to postoperative rehabilitation and QoL improvement,with promising prospects for clinical promotion.

The Principles of Starch Gelatinization and Retrogradation

The polysaccharides, such as κ-carrageenan, ι-carrageenan, agarose (agar), gellan gum, amylose, curdlan, alginate, and deacetylated rhamsan gum, in water changed into an ice-like structure with hydrogen bonding between polymer and water molecules, and between water-water molecules even at a concentration range of 0.1% - 1.0% (W/V) at room temperature, resulting in gelation. Such dramatic changes from liquid into gels have been understood at the molecular level in principles. In this review, we describe the structure-function relationship of starch on the view point of rheological aspects and discuss gelatinization and retrogradation mechanism including water molecules at molecular level. The starch molecules (amylose and amylopectin) play a dominant role in the center of the tetrahedral cavities occupied by water molecules, and the arrangement is partially similar to a tetrahedral structure in a gelatinization process. The arrangement should lead to a cooperative effect stabilizing extended regions of ice-like water with hydrogen bonding on the surface of the polymer molecules, where hemiacetal oxygen and hydroxyl groups might participate in hydrogen bonding with water molecules. Thus, a more extended ice-like hydrogen bonding within water molecules might be achieved in a retrogradation process. Though many investigations not only include starch gelatinization and retrogradaion, but also the gelling properties of the polysaccharides have been undertaken to elucidate the structure-function relationship, no other researchers have established mechanism at the molecular level. There is reasonable consistency in our investigations.

Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery

BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has not been determined.The prognostic value of red blood cell distribution width(RDW)for CRC patients was controversial.AIM To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery.METHODS Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included.The short-term outcomes,overall survival(OS)and disease-free survival(DFS)were compared among the different groups.Cox analysis was also conducted to identify independent risk factors for OS and DFS.RESULTS There were 4258 CRC patients who underwent radical surgery included in our study.A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group.There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group,respectively.Patients in the higher RDW group had more intraoperative blood loss(P<0.01)and more overall complications(P<0.01)than did those in the lower RDW group.Similarly,patients in the lower hematocrit group had more intraoperative blood loss(P=0.012),longer hospital stay(P=0.016)and overall complications(P<0.01)than did those in the higher hematocrit group.The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis(TNM)stage I(OS,P<0.05;DFS,P=0.001)and stage II(OS,P=0.004;DFS,P=0.01)than the lower RDW group;the lower hematocrit group had worse OS and DFS for TNM stage II(OS,P<0.05;DFS,P=0.001)and stage III(OS,P=0.001;DFS,P=0.001)than did the higher hematocrit group.Preoperative hematocrit was an independent risk factor for OS[P=0.017,hazard ratio(HR)=1.256,95%confidence interval(CI):1.041-1.515]and DFS(P=0.035,HR=1.194,95%CI:1.013-1.408).CONCLUSION A higher preoperative RDW and lower hematocrit were associated with more postoperative complications.However,only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery,while RDW was not.

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

Multi-aspect analysis of ureteral access sheath usage in retrograde intrarenal surgery: A RIRSearch group study

Objective:To evaluate the effect of ureteral access sheath(UAS)use and calibration change on stone-free rate and complications of retrograde intrarenal surgery(RIRS).Methods:Data from 568 patients undergoing RIRS for kidney or upper ureteral stones were retrospectively included.Firstly,patients were compared after 1:1 propensity score matching,according to UAS usage during RIRS(UAS used[+]87 and UAS non-used[−]87 patients).Then all UAS+patients(n=481)were subdivided according to UAS calibration:9.5-11.5 Fr,10-12 Fr,11-13 Fr,and 13-15 Fr.Primary outcomes of the study were the success and complications of RIRS.Results:Stone-free rate of UAS+patients(86.2%)was significantly higher than UAS−patients(70.1%)after propensity score matching(p=0.01).Stone-free rate increased with higher caliber UAS(9.5-11.5 Fr:66.7%;10-12 Fr:87.0%;11-13 Fr:90.6%;13-15 Fr:100%;p<0.001).Postoperative complications of UAS+patients(11.5%)were significantly lower than UAS−patients(27.6%)(p=0.01).Complications(8.7%)with 9.5-11.5 Fr UAS was lower than thicker UAS(17.2%)but was not statistically significant(p=0.09).UAS usage was an independent factor predicting stone-free status or peri-and post-operative complications(odds ratio[OR]3.654,95%confidence interval[CI]1.314-10.162;OR 4.443,95%CI 1.350-14.552;OR 4.107,95%CI 1.366-12.344,respectively).Conclusion:Use of UAS in RIRS may increase stone-free rates,which also increase with higher caliber UAS.UAS usage may reduce complications;however,complications seemingly increase with higher UAS calibration.

Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.

Modeling injection-induced fault slip using long short-term memory networks

Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault.This can be due to subsurface(geo)engineering activities such as fluid injections and geologic disposal of nuclear waste.Such activities are expected to rise in the future making it necessary to assess their short-and long-term safety.Here,a new machine learning(ML)approach to model pore pressure and fault displacements in response to high-pressure fluid injection cycles is developed.The focus is on fault behavior near the injection borehole.To capture the temporal dependencies in the data,long short-term memory(LSTM)networks are utilized.To prevent error accumulation within the forecast window,four critical measures to train a robust LSTM model for predicting fault response are highlighted:(i)setting an appropriate value of LSTM lag,(ii)calibrating the LSTM cell dimension,(iii)learning rate reduction during weight optimization,and(iv)not adopting an independent injection cycle as a validation set.Several numerical experiments were conducted,which demonstrated that the ML model can capture peaks in pressure and associated fault displacement that accompany an increase in fluid injection.The model also captured the decay in pressure and displacement during the injection shut-in period.Further,the ability of an ML model to highlight key changes in fault hydromechanical activation processes was investigated,which shows that ML can be used to monitor risk of fault activation and leakage during high pressure fluid injections.

A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.

Extraction of Tea Polysaccharides and Their Effect on Wheat Starch Retrogradation

Tea Polysaccharides(TPS) has been acknowledged of one of the most important components with various bioactivities in tea.The extraction of TPS from wide tea sources was the previous and determinant work before further studies done.While the extraction procedures of TPS would be different due to the later utilization.In this work,the extraction conditions of TPS were previously optimized by respond surface methodology.A quadric model was obtained as Y = 3.16 + 0.31X1- 0.55X2- 0.47X3- 0.034X1X2+ 0.022X1X3- 0.041X2X3- 0.90X12-0.40X22- 0.73X32.The model was tested and proved through the ANOVA with F-value and p-value.Furthermore,the optimal condition was achieved as extraction temperature of 82℃,extraction time of 106 min and ratio of water to material of 33∶ 1(mL/g),meanwhile the highest yield of TPS showed 3.39% ± 0.08%.The crude TPS was later refined to be of purity of 81.3%.The refined TPS was incorporated with starch as to state the role of TPS in the starch retrogradation of starch-based food.The results showed that TPS-wheat starch mixture has a relatively low degree of retrogradation,which indicated that TPS has a delayed or resistant effect on wheat starch retrogradation.This work may provide a practical evidence for the promising starch-based food incorporated tea.

Physics Guided Deep Learning-Based Model for Short-Term Origin–Destination Demand Prediction in Urban Rail Transit Systems Under Pandemic

Accurate origin–destination(OD)demand prediction is crucial for the efficient operation and management of urban rail transit(URT)systems,particularly during a pandemic.However,this task faces several limitations,including real-time availability,sparsity,and high-dimensionality issues,and the impact of the pandemic.Consequently,this study proposes a unified framework called the physics-guided adaptive graph spatial–temporal attention network(PAG-STAN)for metro OD demand prediction under pandemic conditions.Specifically,PAG-STAN introduces a real-time OD estimation module to estimate real-time complete OD demand matrices.Subsequently,a novel dynamic OD demand matrix compression module is proposed to generate dense real-time OD demand matrices.Thereafter,PAG-STAN leverages various heterogeneous data to learn the evolutionary trend of future OD ridership during the pandemic.Finally,a masked physics-guided loss function(MPG-loss function)incorporates the physical quantity information between the OD demand and inbound flow into the loss function to enhance model interpretability.PAG-STAN demonstrated favorable performance on two real-world metro OD demand datasets under the pandemic and conventional scenarios,highlighting its robustness and sensitivity for metro OD demand prediction.A series of ablation studies were conducted to verify the indispensability of each module in PAG-STAN.

Can early precut reduce post-endoscopic retrograde cholangiopancreatography pancreatitis in patients with difficult bile duct cannulation?

BACKGROUND Endoscopic retrograde cholangiopancreatography(ERCP)is associated with a variety of adverse events(AEs).One of the most important AEs is post-ERCP pancreatitis(PEP),which is most common in cases of difficult biliary cannulation.Although the precut technique has been reported as a PEP risk factor,recent studies indicate that early precut could reduce PEP,and that precut itself is not a risk factor.AIM To evaluate the safety of the precut technique,especially in terms of PEP.METHODS We conducted a retrospective study,spanning the period from November 2011 through December 2021.It included 1556 patients,aged≥20 years,who underwent their initial ERCP attempt for biliary disease with a naïve papilla at the Kawasaki University General Medical Center.We compared the PEP risk between the early precut and the delayed precut group.RESULTS The PEP incidence rate did not significantly differ between the precut and nonprecut groups.However,the PEP incidence was significantly lower in the early precut group than the delayed precut group(3.5%vs 10.5%;P=0.02).The PEP incidence in the delayed precut group without pancreatic stent insertion(17.3%)was significantly higher compared to other cases(P<0.01).CONCLUSION Our findings indicate that early precut may reduce PEP incidence.If the precut decision is delayed,a pancreatic stent should be inserted to prevent PEP.

The outcomes and safety of patients undergoing endoscopic retrograde cholangiopancreatography combining a single-use cholangioscope and a single-use duodenoscope:A multicenter retrospective international study

Background: Duodenoscope-related multidrug-resistant organism(MDRO) infections raise concerns. Disposable duodenoscopes have been recently introduced in the market and approved by regulatory agencies with the aim to reduce the risk of endoscopic retrograde cholangiopancreatography(ERCP) associated infections. The aim of this study was to evaluate the outcome of procedures performed with single-use duodenoscopes in patients with clinical indications to single-operator cholangiopancreatoscopy. Methods: This is a multicenter international, retrospective study combining all patients who underwent complex biliopancreatic interventions using the combination of a single-use duodenoscope and a single-use cholangioscope. The primary outcome was technical success defined as ERCP completion for the intended clinical indication. Secondary outcomes were procedural duration, rate of cross-over to reusable duodenoscope, operator-reported satisfaction score(1 to 10) on performance rating of the single-use duodenoscope, and adverse event(AE) rate. Results: A total of 66 patients(26, 39.4% female) were included in the study. ERCP was categorized according to ASGE ERCP grading system as 47(71.2%) grade 3 and 19(28.8%) grade 4. The technical success rate was 98.5%(65/66). Procedural duration was 64(interquartile range 15-189) min, cross-over rate to reusable duodenoscope was 1/66(1.5%). The satisfaction score of the single-use duodenoscope classified by the operators was 8.6 ± 1.3 points. Four patients(6.1%) experienced AEs not directly related to the single-use duodenoscope, namely 2 post-ERCP pancreatitis(PEP), 1 cholangitis and 1 bleeding.Conclusions: Single-use duodenoscope is effective, reliable and safe even in technically challenging procedures with a non-inferiority to reusable duodenoscope, making these devices a viable alternative to standard reusable equipment.

Short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function

BACKGROUND Hepatectomy is the first choice for treating liver cancer.However,inflammatory factors,released in response to pain stimulation,may suppress perioperative immune function and affect the prognosis of patients undergoing hepatectomies.AIM To determine the short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function.METHODS Clinical data from patients with liver cancer admitted to Suzhou Ninth People’s Hospital from January 2020 to December 2023 were retrospectively analyzed.Thirty-five patients underwent laparoscopic hepatectomy for liver cancer(liver cancer resection group)and 35 patients underwent medical image-guided microwave ablation(liver cancer ablation group).The short-term efficacy,complications,liver function,and immune function indices before and after treatment were compared between the two groups.RESULTS One month after treatment,19 patients experienced complete remission(CR),8 patients experienced partial remission(PR),6 patients experienced stable disease(SD),and 2 patients experienced disease progression(PD)in the liver cancer resection group.In the liver cancer ablation group,21 patients experienced CR,9 patients experienced PR,3 patients experienced SD,and 2 patients experienced PD.No significant differences in efficacy and complications were detected between the liver cancer ablation and liver cancer resection groups(P>0.05).After treatment,total bilirubin(41.24±7.35 vs 49.18±8.64μmol/L,P<0.001),alanine aminotransferase(30.85±6.23 vs 42.32±7.56 U/L,P<0.001),CD4+(43.95±5.72 vs 35.27±5.56,P<0.001),CD8+(20.38±3.91 vs 22.75±4.62,P<0.001),and CD4+/CD8+(2.16±0.39 vs 1.55±0.32,P<0.001)were significantly different between the liver cancer ablation and liver cancer resection groups.CONCLUSION The short-term efficacy and safety of microwave ablation and laparoscopic surgery for the treatment of liver cancer are similar,but liver function recovers quickly after microwave ablation,and microwave ablation may enhance immune function.

Splenic subcapsular hematoma following endoscopic retrograde cholangiopancreatography:A case report and review of literature

BACKGROUND Splenic injury following endoscopic retrograde cholangiopancreatography(ERCP)is a rare complication.The literature contains around 30 articles reporting various degrees of splenic injuries resulting from ERCP since the first report of splenic rupture after ERCP in 1989.CASE SUMMARY This report describes a case of splenic hematoma and stent displacement in a 69-year-old male patient who developed these conditions 7 days after undergoing ERCP and stenting.The patient had bile duct stenosis caused by a malignant tumor that was obstructing the bile duct.The diagnosis was confirmed by epigastric computed tomography and magnetic resonance cholangiopancreatography.The patient was successfully treated with percutaneous transhepatic cholangial drainage,endoscopic pyloric stent placement,and conservative management.The causes of splenic injury following ERCP are discussed.CONCLUSION ERCP has the potential to cause splenic injury.If a patient experiences symptoms such as abdominal pain,decreased blood pressure,and altered hematology after the procedure,it's important to be thoroughly investigated for postoperative bleeding and splenic injury.

Analysis of the efficacy and safety of endoscopic retrograde cholangiopancreatography for the treatment of pediatric pancreatobiliary diseases

BACKGROUND Traditional surgical procedures are highly invasive and risky for children with pancreatic and biliary diseases.Endoscopic retrograde cholangiopancreatography(ERCP)has been used mostly in adults because it is a safe and effective surgical procedure.Its application in children will contribute to the treatment and prog-nosis of children with pancreatic and biliary diseases.AIM To analyze the efficacy and safety of ERCP for the treatment of pediatric pancre-atobiliary diseases.METHODS A retrospective study was performed using the medical records of 101 pediatric patients who received treatment for pancreatobiliary diseases at Children’s Hospital Capital Institute of Pediatrics from April 2022 to April 2024.The patients were divided into an observation group(n=52,treated with ERCP)and a control group(n=49,treated with traditional surgical methods).Diagnostic and therapeutic outcomes of ERCP were statistically analyzed.Treatment efficacy,time to resume eating,and hospital stay duration were compared between the two groups.Indicators of liver function were monitored preoperatively and one week postoperatively.Dynamic changes in C-reactive protein(CRP)and serum amylase levels were assessed preoperatively and at 6 and 24 hours postoper-atively.Postoperative complications were also compared.Logistic multivariate regression was used to analyze the independent effect of ERCP on outcomes.RESULTS For the observation group,36 and 16 patients were diagnosed with biliary and pancreatic diseases,respectively.Compared with the control group,the observa-tion group exhibited a higher overall effective rate(P<0.05),shorter times to resume eating,shorter hospital stays(P<0.05),and significantly improved postoperative liver function(P<0.05).CRP and serum amylase levels were significantly increased in both groups at 6 and 24 hours postoperatively(P<0.05),but were significantly lower in the observation group(P<0.05).The observation group also had a lower incidence of complications(P<0.05).ERCP was an independent factor affecting treatment efficacy,length of hospital stay,total bilirubin,aspartate aminotransferase,and alanine aminotransferase,CRP,serum amylase,and the occurrence of complications in children with pancreaticobiliary diseases(P<0.05).CONCLUSION ERCP effectively enhances the treatment efficacy of pediatric pancreatobiliary diseases,with a reduced inflam-matory response,faster postoperative recovery,and fewer complications.ERCP is a safe and effective diagnostic and therapeutic method for pediatric pancreatobiliary diseases.

Transformer-based correction scheme for short-term bus load prediction in holidays

To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios.

Adaptive Successive POI Recommendation via Trajectory Sequences Processing and Long Short-Term Preference Learning

Point-of-interest(POI)recommendations in location-based social networks(LBSNs)have developed rapidly by incorporating feature information and deep learning methods.However,most studies have failed to accurately reflect different users’preferences,in particular,the short-term preferences of inactive users.To better learn user preferences,in this study,we propose a long-short-term-preference-based adaptive successive POI recommendation(LSTP-ASR)method by combining trajectory sequence processing,long short-term preference learning,and spatiotemporal context.First,the check-in trajectory sequences are adaptively divided into recent and historical sequences according to a dynamic time window.Subsequently,an adaptive filling strategy is used to expand the recent check-in sequences of users with inactive check-in behavior using those of similar active users.We further propose an adaptive learning model to accurately extract long short-term preferences of users to establish an efficient successive POI recommendation system.A spatiotemporal-context-based recurrent neural network and temporal-context-based long short-term memory network are used to model the users’recent and historical checkin trajectory sequences,respectively.Extensive experiments on the Foursquare and Gowalla datasets reveal that the proposed method outperforms several other baseline methods in terms of three evaluation metrics.More specifically,LSTP-ASR outperforms the previously best baseline method(RTPM)with a 17.15%and 20.62%average improvement on the Foursquare and Gowalla datasets in terms of the Fβmetric,respectively.

Endoscopic retrograde appendicitis treatment for periappendiceal abscess: A case report

BACKGROUND Acute appendicitis is the most common abdominal emergency.At present,the main treatments for periappendiceal abscess include antibiotics and surgery.However,the complications and mortality of emergency surgery are high.The preferred therapy is conservative treatment with antibiotics first,ultrasound-guided puncture drainage or surgical treatment is followed when necessary.Endoscopic retrograde appendicitis therapy(ERAT)for acute uncomplicated appendicitis have been proved clinically effective,but it is rarely used in periap-pendiceal abscess.CASE SUMMARY We report a patient admitted to hospital because of“right lower abdominal pain for six days”.The computerized tomography(CT)of patient showed that appendicitis with fecaliths and abscess in the pelvis.The patient was treated by CT-guided puncture and drainage of abdominal abscess combined with ERAT to remove appendiceal fecaliths,irrigation and stent placement.CONCLUSION The patient did not receive surgery because of impoverished family.Abdominal pain did not recur during the follow-up period.This case confirms the value of ERAT in the treatment of periappendiceal abscess.

An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction

With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service quality.Traffic volume is an influential parameter for planning and operating traffic structures.This study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning process.The fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal relationships.Firstly,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition model.The second aspect involves predicting traffic volume using the long short-term memory algorithm.Next,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent optimization.Finally,the fusion of the obtained results leads to a final traffic volume prediction.The experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and R-squared.The achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the competing.These findings highlight the accuracy of traffic pattern prediction.Consequently,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.