Metabolic associated fatty liver disease （MAFLD） is a common chronic liver disease worldwide， and timely and precise intervention can delay disease progression and significantly reduce the risk of serious complications such as liver fibrosis， liver cirrhosis， and liver cancer. Although traditional liver biopsy combined with metabolic markers is the gold standard， it may cause complications such as pain and bleeding as an invasive examination， which has promoted scientific research to shift its focus to the construction of noninvasive assessment systems. In recent years， noninvasive diagnostic technologies based on multi-dimensional detection strategies have been continuously updated， including serological models， imaging techniques， and clinical algorithms. This article systematically reviews the screening methods for MAFLD during the fibrotic stages F1—F3， especially deep learning models based on artificial intelligence， in order to provide ideas for the early screening of MAFLD， as well as a scientific reference for optimizing disease management strategies.

OBJECTIVE: To investigate the current status of long-term quality of life in patients with severe acute pancreatitis (SAP) who have been cured and discharged, and to analyze the influencing factors affecting long-term quality of life in SAP cured patients after discharge. METHODS: A retrospective collection was conducted. Patients who were received standardized treatment before being cured and discharged from the hospital admitted to the first department of critical care medcine of the Second Affiliated Hospital of Anhui Medical University from January 2017 to December 2023 were enrolled. According to the 36-item short form health survey scale (SF-36) score, patients were divided into high score group (high quality of life, the top 50% of patients with total SF-36 score) and low score group (low quality of life, the bottom 50% of patients with total SF-36 score). The gender, age, history of hypertension and diabetes, etiology of pancreatitis, acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), CT severity index (CTSI), laboratory indicators such as C-reactive protein (CRP), procalcitonin (PCT), blood glucose, and triglycerides upon admission, use of vasoactive drugs, non-invasive/high-flow ventilation, invasive ventilation, retroperitoneal puncture and drainage, open pancreatic surgery treatment and secondary infection during hospitalization were collected, as well as the retention of abdominal drainage tubes at discharge from hospital. Distribute follow-up questionnaires or telephone follow-up surveys through WeChat and Question Star programs to investigate the pancreatic secretion function, chronic abdominal pain, and recurrence of pancreatitis of patients after discharge. Multivariable Logistic regression was used to analyze the relevant factors affecting the long-term quality of life of cured patients with SAP. RESULTS: A total of 86 patients were ultimately enrolled. There were 43 patients in both the high and low score groups. Among 86 patients, 20 experienced acute pancreatitis recurrence, with a recurrence rate of 23.26%. Twenty-two (25.58%) experienced chronic abdominal pain after discharge, and 5 patients (5.81%) needed medication to relieve pain. Thirty-three patients (38.37%) had pancreatic exocrine dysfunction after discharge, characterized by abdominal distension, constipation or diarrhea. Twenty-two patients (25.58%) suffered from pancreatic endocrine dysfunction, and were diagnosed with diabetes. Univariate analysis showed that compared with the high score group, the low score group had more patients with hypertension, initial renal dysfunction, initial severe metabolic acidosis, initial serum calcium < 2.0 mmol/L, blood glucose > 11.1 mmol/L and cultured Gram positive bacteria (from blood/body fluid/pancreatic necrotic tissue) during treatment (48.84% vs. 16.28%, 60.47% vs. 32.56%, 18.60% vs. 4.65%, 88.37% vs. 62.79%, 55.81% vs. 30.23%, 34.88% vs. 13.95%), had higher CTSI score (6.60±1.61 vs. 5.77±1.32), lower hemoglobin level at discharge (g/L: 102.30±18.78 vs. 110.72±16.68), and a lower proportion of etiological interventions after discharge (34.88% vs. 67.44%), the differences were statistically significant (all P < 0.05). Multivariate Logistic regression analysis showed that hypertension [odds ratio (OR) = 4.814, 95% confidence interval (95%CI) was 1.196-19.378], initial serum calcium < 2.0 mmol/L (OR = 6.688, 95%CI was 1.321-33.873) and initial blood glucose > 11.1 mmol/L (OR = 6.473, 95%CI was 1.399-29.950) were risk factors for long-term quality of life in cured SAP patients (all P < 0.05), while post discharge prophylactic intervention was a protective factor for long-term quality of life (OR = 0.092, 95%CI was 0.020-0.425, P < 0.01). CONCLUSIONS Cured SAP patients have varying degrees of impaired secretion function and the possibility of recurrence of acute pancreatitis. Hypertension, initial serum calcium < 2.0 mmol/L and blood glucose > 11.1 mmol/L are independent influencing factors for low long-term quality of life in cured SAP patients. Prevention and intervention targeting the etiology of pancreatitis after discharge can improve the long-term quality of life of cured SAP patients.
Humans ; Quality of Life ; Retrospective Studies ; Pancreatitis/therapy* ; Patient Discharge ; Male ; Female ; Middle Aged ; APACHE ; Adult ; Acute Disease ; Aged

Objective To meet the clinical need for dynamic monitoring on lactate metabolism in septic shock pa-tients,a time-series prediction model based on a long short-term memory(LSTM)network was developed to predict 24-hour lactate clearance rate at admission.Methods A multi-stage retrospective cohort design was adopted to en-roll septic shock patients admitted to the department of critical care medicine of a hospital from January 2018 to Sep-tember 2024.By conducting univariate analysis and LASSO combined feature screening,predictive factors were extracted from multidimensional clinical data.An end-to-end LSTM framework(two-layer 64/32 units,dropout rate=0.3)was constructed.A sliding window strategy(six-hour step size)was adopted for dynamic prediction and compared with traditional logistic model in terms of three dimensions:calibration(Brier score),discrimination(area under the curve[AUC]of time-dependent receiver operating characteristic[ROC]),and clinical practicality(deci-sion curve analysis).Consistency between model prediction result and actual lactate clearance rate was analyzed,and the accuracy of prediction was evaluated.Results A total of 112 septic shock patients were enrolled in the analysis,including 65 males and 47 females,with an average age of(67.35±7.28)years.65 patients were assigned in the lactate good clearance rate group(lactate good clearance rate≥10％)and 47 in the lactate poor clearance rate group(lactate good clearance rate＜10％);78 patients were in the training set and 34 in the validation set.Time-depen-dent AUC analysis revealed that the predictive performance of the LSTM model in the time windows of 6,12,and 24 hours were 0.89(0.85-0.93),0.91(0.88-0.95),and 0.92(0.89-0.96),respectively,superior to the logistic regression model(ΔAUC=0.085,P＜0.01).The core predictive factors included APACHE Ⅱ score(OR=1.38),lactate level at admission(OR=1.65),vasoactive drug dosage(OR=1.42),and 6-hour fluid resuscitation dosage(OR=1.35).The Pearson correlation coefficient between the predicted value of the model and the actual 24-hour lactate clearance rate was 0.83(P＜0.001),with an average absolute error of 8.2％.Decision curve analysis confirmed that when the threshold probability was 15％-60％,the LSTM model could increase clinical net benefits by 27.3％.The validation of each subgroup showed that the model maintained the optimal predictive performance(AUC=0.87)in the lung infection subgroup(n=16).Conclusion The LSTM-based dynamic prediction model for predicting 24-hour lactate clearance rate through integrating early admission indicators demonstrates excellent pre-dictive performance and clinical application value,which can provide important reference for individualized treatment decisions in septic shock patients.

Pain modulation encompasses a complex neurobiological process, in which the lateral habenula (LHb) plays a crucial role in integrating, regulating and modulating pain signals. It is also involved in pain-related memory functions associated with perception, transmission and regulation of pain. Furthermore, the LHb collaborates with structures such as the spinal dorsal horn, forebrain, and amygdala to form an essential neural circuit that contributes to sensitization, development of tolerance, and adaptation processes related to pain. However, there remains limited understanding regarding the specific roles and interactions among different neuron subtypes within the LHb concerning pain regulation. Additionally, further investigation is warranted to explore functional changes and plasticity within both the LHb and its associated neural circuits in chronic pain models. Future research endeavors should utilize advanced neuroimaging techniques alongside optogenetics and gene editing technologies to elucidate intricate neural circuits, cellular architecture, and molecular mechanisms governing LHb function in pain regulation. In conclusion, this paper aims to comprehensively review existing literature on the involvement of the LHb and its neural circuits in modulating pain, thereby enhancing our understanding of their neurobiological mechanisms while providing novel targets for precise therapeutic strategies aimed at alleviating pain.

Pain modulation encompasses a complex neurobiological process, in which the lateral habenula (LHb) plays a crucial role in integrating, regulating and modulating pain signals. It is also involved in pain-related memory functions associated with perception, transmission and regulation of pain. Furthermore, the LHb collaborates with structures such as the spinal dorsal horn, forebrain, and amygdala to form an essential neural circuit that contributes to sensitization, development of tolerance, and adaptation processes related to pain. However, there remains limited understanding regarding the specific roles and interactions among different neuron subtypes within the LHb concerning pain regulation. Additionally, further investigation is warranted to explore functional changes and plasticity within both the LHb and its associated neural circuits in chronic pain models. Future research endeavors should utilize advanced neuroimaging techniques alongside optogenetics and gene editing technologies to elucidate intricate neural circuits, cellular architecture, and molecular mechanisms governing LHb function in pain regulation. In conclusion, this paper aims to comprehensively review existing literature on the involvement of the LHb and its neural circuits in modulating pain, thereby enhancing our understanding of their neurobiological mechanisms while providing novel targets for precise therapeutic strategies aimed at alleviating pain.

Objective To meet the clinical need for dynamic monitoring on lactate metabolism in septic shock pa-tients,a time-series prediction model based on a long short-term memory(LSTM)network was developed to predict 24-hour lactate clearance rate at admission.Methods A multi-stage retrospective cohort design was adopted to en-roll septic shock patients admitted to the department of critical care medicine of a hospital from January 2018 to Sep-tember 2024.By conducting univariate analysis and LASSO combined feature screening,predictive factors were extracted from multidimensional clinical data.An end-to-end LSTM framework(two-layer 64/32 units,dropout rate=0.3)was constructed.A sliding window strategy(six-hour step size)was adopted for dynamic prediction and compared with traditional logistic model in terms of three dimensions:calibration(Brier score),discrimination(area under the curve[AUC]of time-dependent receiver operating characteristic[ROC]),and clinical practicality(deci-sion curve analysis).Consistency between model prediction result and actual lactate clearance rate was analyzed,and the accuracy of prediction was evaluated.Results A total of 112 septic shock patients were enrolled in the analysis,including 65 males and 47 females,with an average age of(67.35±7.28)years.65 patients were assigned in the lactate good clearance rate group(lactate good clearance rate≥10％)and 47 in the lactate poor clearance rate group(lactate good clearance rate＜10％);78 patients were in the training set and 34 in the validation set.Time-depen-dent AUC analysis revealed that the predictive performance of the LSTM model in the time windows of 6,12,and 24 hours were 0.89(0.85-0.93),0.91(0.88-0.95),and 0.92(0.89-0.96),respectively,superior to the logistic regression model(ΔAUC=0.085,P＜0.01).The core predictive factors included APACHE Ⅱ score(OR=1.38),lactate level at admission(OR=1.65),vasoactive drug dosage(OR=1.42),and 6-hour fluid resuscitation dosage(OR=1.35).The Pearson correlation coefficient between the predicted value of the model and the actual 24-hour lactate clearance rate was 0.83(P＜0.001),with an average absolute error of 8.2％.Decision curve analysis confirmed that when the threshold probability was 15％-60％,the LSTM model could increase clinical net benefits by 27.3％.The validation of each subgroup showed that the model maintained the optimal predictive performance(AUC=0.87)in the lung infection subgroup(n=16).Conclusion The LSTM-based dynamic prediction model for predicting 24-hour lactate clearance rate through integrating early admission indicators demonstrates excellent pre-dictive performance and clinical application value,which can provide important reference for individualized treatment decisions in septic shock patients.

Objective To investigate the liver histopathological features of chronic hepatitis B(CHB)patients with normal alanine aminotransferase(ALT)and their correlation with serological markers.Methods Clinical data were collected from 137 patients with normal ALT who were treated in Wuxi Fifth People's Hospital from April 2018 to June 2021,and the differences in liver histopathology and serological markers were analyzed,as well as the correlation between liver histopathology and serological markers.The chi-square test was used for comparison of categorical data between groups,and the Kruskal-Wallis H test was used for comparison of data between multiple groups.A Spearman rank correlation test was performed,and logistic regression was used to perform the multivariate analysis.Results In the ALT≤20 U/L,20—29 U/L,and 30—40 U/L groups,the patients with significant inflammatory necrosis(≥G2)accounted for 57.4%,53.4%,and 75%,respectively,and the patients with significant fibrosis(≥S2)accounted for 63.8%,62.1%,and 75%,respectively.There was a significant difference in the degree of inflammatory necrosis between the patients with positive or negative HBeAg,the patients with different levels of serum HBV DNA,and the patients with different levels of serum HBV RNA(χ2=10.008,6.911,and 7.946,all P<0.05),and there was a significant difference in fibrosis stage between the patients with positive or negative HBeAg and the patients with different levels of serum HBV RNA(χ2=7.996 and 10.874,both P<0.05).The degree of liver inflammation and fibrosis stage were not significantly correlated with serum HBV DNA(rs=0.024,P=0.785;rs=0.039,P=0.652),while they were significantly correlated with serum HBV RNA(rs=0.222,P=0.009;rs=0.187,P=0.029).The multivariate analysis showed that in CHB patients,positive HBeAg was an independent risk factor for inflammatory necrosis(odds ratio[OR]=-0.302,95%confidence interval[CI]:-1.160 to 0.386,P=0.002)and fibrosis(OR=-0.387,95%CI:-1.160 to 0.386,P=0.011).Conclusion There are varying degrees of inflammatory necrosis and fibrosis in the liver of CHB patients with normal ALT,and positive HBeAg is independent risk factor for significant inflammatory necrosis and fibrosis in liver tissue of these patients.

Objective To investigate the population distribution of non-alcoholic fatty liver disease before and after renaming and the association between the types of metabolic risk factors(MRF)for metabolic dysfunction-associated steatotic liver disease(MASLD)and advanced liver fibrosis.Methods This study was conducted among 515 patients who were admitted to The Affiliated Hospital of Xuzhou Medical University and Wuxi Fifth People's Hospital from January 2019 to January 2022 and had hepatocyte steatosis≥5%by liver biopsy.Among these patients,2 patients did not meet the diagnostic criteria for nonalcoholic fatty liver disease(NAFLD)and metabolic associated fatty liver disease(MAFLD),respectively,and were classified as steatotic liver disease(SLD)with other specific causes,and the other 513 patients were divided into MASLD group with 275 patients,comorbid group with 216 patients(MASLD comorbid with other liver diseases),and cryptogenic SLD group with 22 patients.The above groups were compared in terms of clinical features,laboratory markers,and advanced liver fibrosis.The MASLD patients with different types of MRF were compared in terms of clinical features,laboratory markers,and advanced liver fibrosis,and the risk factors for advanced liver fibrosis in patients with MASLD were analyzed.The Kruskal-Wallis H test was used for comparison of continuous data with skewed distribution between multiple groups and further comparison between two groups;the chi-square test was used for comparison of categorical data between multiple groups,and Bonferroni correction was used for further comparison between two groups.The logistic regression analysis was used to identify the risk factors for liver fibrosis.Results Among the 515 patients with SLD,297 patients(57.7%)met the diagnostic criteria for NAFLD,among whom 22 were classified as cryptogenic SLD and 275 met the diagnostic criteria for MASLD,and 467(90.7%)were diagnosed with MAFLD.There were significant differences between the three groups in sex,body mass index(BMI),gamma-glutamyl transpeptidase,triglyceride,cholesterol,low-density lipoprotein cholesterol,high-density lipoprotein cholesterol,fasting plasma glucose,NAFLD fibrosis score(NFS),fibrosis-4(FIB-4),and F3-4(all P＜0.05).Compared with the MASLD group and the cryptogenic SLD group,the comorbid group had the highest proportion of patients with advanced liver fibrosis(P＜0.001).With the increase in the type of MRF,the patients tended to have an older age,a significantly higher proportion of female patients,a higher possibility of hypertension and diabetes,and higher levels of metabolic parameters including BMI,blood lipids,and blood glucose(all P＜0.05).With the increase in the types of MRF in MASLD patients,they tended to have significantly higher noninvasive fibrosis scores(NFS and FIB-4)and a significantly higher proportion of patients with advanced liver fibrosis(P＜0.05).The multivariate logistic regression analysis showed that age≥50 years(odds ratio[OR]=2.622,95%confidence interval[CI]:1.091-6.300,P=0.031)and the increase in the type of MRF(OR=1.876,95%CI:1.194-2.947,P=0.006)were independent risk factors for MASLD with severe liver fibrosis.Conclusion The new definition of MASLD is based on the positive identification of MRF,and the reclassified population of MASLD is smaller than that of MAFLD,with little difference from that of NAFLD.In addition,age≥50 years and the increase in the type of MRF are independent risk factors for MASLD with advanced liver fibrosis.

Objective To investigate the characteristics of human papillomavirus (HPV) prevalence and genotype distribution of 18 535 cases in Yuncheng . Methods A sample of 18535 residents who underwent HPV testing in our hospital from August 2020 to September 2023 were enrolled, and HPV genotyping was done to all samples. Then the rate of HPV infection, age distribution, genotype distribution, and multiple infections were statistically analyzed. Results Of the 18,535 subjects included, a total of 4,639 tested positive for HPV, demonstrating a positive rate of 25.03%. The positive rate of HPV infection varied among different age groups (χ²=29.587, P<0.05), with higher rates found in <25 years old group (29.61%) and >60 years old group (25.89%). Overall, 23 genotypes, covering 5315 viruses, were detected. There were 5 low-risk genotypes with the highest percentage of HPV42 (9.29%), and there were 18 high-risk genotypes with HPV52, HPV58, HPV66 and HPV53, subtypes as the most frequent subtypes, accounting for 13.64%, 8.97%, 7.41% and 7.04%, respectively. The type of HPV infection was predominantly single infections, with an overall single infection rate of 21.62% (4008/18535), which accounted for 86.40% (4 008/4 639) of all positive cases, and a multiple genotype infections rate of 3.40% (631/18535). The 25-34 year old group accounted for the largest proportion of single infections (25.12%), while the <25 year old group accounted for the largest proportion of multiple genotype infections (30.74%). Conclusion The prevalence rate of HPV infection in Yuncheng is 25.03%, with a higher positive rate in the <25 years age group and the >60 years age group. A total of 23 HPV genotypes are detected, of which the main genotypes are HPV42, HPV58, HPV66 and HPV53, and the type of infection is dominated by single infections.