Background/Aims: Chronic constipation is prevalent yet under-diagnosed across Asia, compromising quality of life and burdening healthcare systems. Cultural stigma, varied diets, and limited access to standardized diagnostic tools delay timely care. Methods: The Bali Chronic Constipation Roundtable in November 2024, brought together experts from 11 Asian countries. The group reviewed epidemiological data, analyzed multinational questionnaire on clinical practice pattern, and conducted structured discussions to identify key barriers and propose region-specific recommendations. Results: Chronic constipation prevalence varies across Asia, ranging from 1.8% in India to 16.6% in Japan, with women and the elderly disproportionately affected. Under-reporting persists owing to cultural taboos and widespread self treatment with laxatives and traditional medications. Although the Rome IV criteria remains the global standard, they may not fully reflect Asian symptom profiles, and diagnosis is limited by scarce motility laboratories. First line therapies such as dietary-fiber optimization and osmotic laxatives are widely available, but newer pharmacotherapies (prucalopride, linaclotide, lubiprostone, and elobixibat) remain costly and unevenly accessible. Biofeedback for dyssynergic defecation is underutilized due to limited availability. Experts recommend expanded regional research on to refine diagnostic criteria, coupled with enhanced physician education and public awareness. They advocate accessibility to second-line and novel therapies that incorporate culturally attuned regional guidelines, and improved access to gastrointestinal motility testing. Conclusions The Bali Chronic Constipation Roundtable highlighted Asia’s need for region specific diagnostics and management. Addressing diagnostic and treatment gaps will improve outcomes, while ongoing researcher clinician policy collaboration must standardize guidelines, advance research, and ensure equitable care across Asia.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective : To investigate the prevalence of negative emotions in hospitalized youth patients with type 2 diabetes(T2DM) and its correlation with coping strategies and psychological resilience. Methods : 141 youth T2DM patients who met the research standards were selected. Blood glucose related indicators, blood pressure, body mass index(BMI), diabetes chronic complications screening results and other data were collected. The basic information and disease related information questionnaire, self-rating depression scale(SDS), self-rating anxiety scale(SAS), diabetes distress scale(DDS), medical coping modes questionnaire(MCMQ) and Connor-Davidson resilience scale(CD-RISC) were completed. Results: Among 141 hospitalized youth T2DM patients, 37.6% were combined with depression, 32.6% were combined with anxiety, and 35.5% were combined with diabetic distress(DD). Univariate analysis showed that systolic blood pressure(P<0.01), educational level, and the form of hospitalization expenses(P<0.05) were significantly correlated with depression. Marital status(P<0.01), family residence, blood glucose monitoring methods, and the last fasting blood glucose(P<0.05) were significantly correlated with anxiety. BMI, whether it was first diagnosed or treated(P<0.01), gender, occupation, disease course, weekly blood glucose monitoring frequency, and the presence of chronic complications(P<0.05) were significantly correlated with DD. In multivariate analysis, systolic blood pressure(P<0.01), educational level, and the form of hospitalization expenses were significantly correlated with depression, marital status(P<0.05) was significantly correlated with anxiety; BMI and weekly blood glucose monitoring frequency(P<0.01) were significantly correlated with DD. SDS, SAS, total scores and dimensions of DDS were negatively correlated with the total score and dimensions of CD-RISC(rs=-0.182--0.467, P<0.05 or 0.01), and positively correlated with the yielding coping strategies(rs=0.177-0.271,P<0.05 or 0.01). SAS,total scores and dimensions of DDS were positively correlated with avoiding coping strategies(rs=0.237-0.419,P<0.05 or 0.01). The total and dimensions of CD-RISC were positively correlated with facing coping strategies(rs=0.215-0.349,P<0.05 or 0.01),and negatively correlated with yielding coping strategies(rs=-0.234--0.325,P<0.01). Conclusion More than 30% of hospitalized youth T2DM may experience negative emotions such as depression,anxiety,and DD. The occurrence of negative emotions in such patients may be related to disease management or socio-economic issues such as systolic blood pressure,educational level,hospitalization expenses,marital status,BMI,and frequency of blood glucose monitoring,as well as decreased psychological resilience and negative coping strategies.

Objective To develop models for predicting response to chemotherapy combined with immunotherapy in patients with esophageal squamous carcinoma with various machine learning algorithms,and then select the optimal model.Methods A retrospective study was performed for 174 patients with esophageal squamous cell carcinoma undergoing chemotherapy combined with immunotherapy admitted in Department of Thoracic Surgery of the First Affiliated Hospital of Army Medical University from January 2022 to December 2023.The CT scans and clinical information were collected before treatment.They were randomly divided into a training set(n=122)and a testing set(n=52)in a ratio of 7∶3.CT radiomic features were extracted and selected,and then 5 machine-learning algorithms were employed to establish the prediction models,including radiomics model and clinical-radiomics model.Five-fold cross-validation was conducted on the training set,and the performance of the prediction models was evaluated on the testing set using receiver operating characteristic(ROC)curve and the F1 score.The best-performing model was further explained using local interpretable model-agnostic explanations(LIME)algorithm.Results Among the 174 patients,115(66.1%)achieved clinical remission.From the clinical information and CT images,1 clinical features and 10 radiomic features were identified.The area under of ROC curve(AUC)for the radiomics and clinical-radiomics models was 0.750(95%CI:0.616～0.883),and 0.766(95%CI:0.637～0.895),respectively.The F1 score of the optimal clinical-radiomics model was 0.829.LIME algorithm indicated that this best model demonstrated reliability in predicting individual samples.Conclusion The clinical-radiomics prediction model based on machine learning algorithm performs well,and can provide a reference for doctors'clinical decision-making by predicting the response to chemotherapy combined with immunotherapy in patients with esophageal squamous cell carcinoma.

Time-of-flight secondary ion mass spectrometer(TOF-SIMS)is a highly sensitive surface analysis instrument with high spatial resolution.Traditional TOF-SIMS instruments for sample targets use high field extraction methods.Although the ion collection efficiency is high,it is prone to issues such as low-energy ion beam defocusing,sample morphology sensitivity,and organic molecule ion dissociation.This study aimed to develope an efficient low-field ion extraction system suitable for TOF-SIMS with a continuous beam source.The SIMION simulation software was used to construct a model of the secondary ion optical extraction system.The key factors affecting the extraction efficiency were studied,and the structural parameters of the extraction cone were optimized.Using an indium target as the sample,an experimental test of the performance of the ion extraction system was carried out on the TOF-SIMS instrument.The influences of the voltages of the ion extraction cone and the single lens on the ion extraction efficiency were consistent with the simulation results.By adopting the technology of deflection and coaxial dynamic compensation,the imaging field of view of the ion extraction system was increased to 500 μm×500 μm.The energy window of the ion extraction system reached 10 eV,and the large imaging depth of field of 400 μm was achieved.In the test of a 5 mg/L cholesterol thin film sample,the signal-to-noise ratio of the characteristic peak[M-OH]+reached 4453.The results showed that this low-field secondary ion extraction system effectively improved the performance of the continuous beam TOF-SIMS instrument.

Objective To investigate the comparative neuroprotective effects of human umbilical cord mesenchymal stem cells(hUC-MSCs-Exos)administered via different routes on hypoxic ischemic brain damage(HIBD)in neonatal mice.Methods Healthy one-week-old SPF-grade BALB/c mice were randomly divided into 4 groups:sham operation group(n=6),model group(n=6),exosome group 1(n=8),exosome group 2(n=8).HIBD was induced using the Rice-Vannucci method.Exosome group 1 and Exosome group 2 were intraperitoneal injection/intranasal drip of phosphate buffer(PBS)100 μl containing 10 μl exosomes within 24 h after successful modeling,respectively.Sham operation and model groups were intraperitoneal injection of PBS 100 μl.On the 7th day after the intervention,neuromotor function was assessed using the horizontal grid test and pole climbing test.On the 2nd day after the evaluation,all mice were killed and their brains were removed by decapitation.HE staining was used to observe the pathological injury of brain tissue,toluidine blue staining was used to observe the survival of neurons in cerebral cortex,and TUNEL staining was used to observe the apoptosis of cerebral cortex cells.Results Compared with sham operation group,model group,exosome group 1 and exosome group 2 exhibited increased hind limb drops in horizontal grid test and climbing scores(P<0.05).No significant difference was found in model group,exosome group 1 and exosome group 2 in these measures(P<0.05).Significant pathology was observed in model group,exosome group 1 and exosome group 2 compared to sham operation group(P<0.05),with significantly reduced damage in exosome group 1 and exosome group 2 compared to model group(P<0.05).Compared with sham operation group,Nissl body count was lower in model group and exosome group 1 and exosome group 2,with a higher count in exosome group 2 compared to exosome group 1(P<0.05).Compared with sham operation group,apoptotic cells were higher in model group and exosome group 1 and exosome group 2,with a significant reduction in exosome group 1 and exosome group 2 compared to model group,and the lowest in exosome group 2(P<0.05).Conclusions hUC-MSCs-Exos can improve the neuronal motor function,promote neuron repair and inhibit apoptosis in HIBD mice.Intranasal administration of hUC-MSCs-Exos is more effective than intraperitoneal administration for reducing neuronal apoptosis in HIBP neonatal mice,offering a convenient and rapid method suitable for clinical application.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.