Esophageal cancer is a prevalent malignant tumor of the digestive tract in China, and radical surgery remains the cornerstone of its comprehensive treatment. However, multifactorial challenges such as postoperative gastrointestinal tract reconstruction, traumatic stress, and tumor-related metabolic disturbances render esophageal cancer patients highly susceptible to malnutrition. Perioperative nutritional support therapy plays a crucial role in enhancing surgical safety, improving clinical outcomes, and elevating patients' quality of life by regulating metabolic homeostasis, preserving organ function, and optimizing the immune microenvironment. This article reviews the mechanisms underlying malnutrition in esophageal cancer, methods for nutritional status assessment, and precision intervention pathways based on multi-omics evaluations. The aim is to strengthen clinicians' awareness of standardized perioperative nutritional management for esophageal cancer patients and promote its clinical implementation, thereby facilitating postoperative recovery and improving long-term quality of life.

ObjectiveTo investigate the intervention effects of modified Linggui Zhugan Tang （LGZGT） on patients with obstructive sleep apnea-hypopnea syndrome （OSAHS） of the spleen deficiency and dampness obstruction with blood stasis type， reveal its possible mechanisms， and provide a theoretical basis for the clinical treatment of OSAHS with traditional Chinese medicine （TCM）. MethodsEighty OSAHS patients with spleen deficiency and dampness obstruction with blood stasis were randomly assigned to a control group and an observation group （1∶1） using a random number table， with 40 patients in each group. The control group received standard basic treatment combined with oral Doxofylline tablets， while the observation group received standard basic treatment combined with modified LGZGT. Serum levels of macrophage migration inhibitory factor （MIF）， microRNA-223 （miR-223）， and interleukin-18 （IL-18） were measured by enzyme-linked immunosorbent assay （ELISA）， and the mRNA expression levels of MIF， miR-223， and IL-18 were measured by real-time quantitative polymerase chain reaction （Real-time PCR）. After two months of treatment， the total clinical efficacy， apnea-hypopnea index （AHI）， lowest nocturnal oxygen saturation （LSpO₂）， body mass index （BMI）， TCM syndrome scores， and expression levels of MIF， miR-223， and IL-18 before and after treatment were compared between the two groups. Correlations between MIF， miR-223， IL-18 and AHI and LSpO₂ were also analyzed. ResultsCompared with the control group， the observation group showed a significantly higher total clinical effective rate （P<0.01， Z=-3.49）. Within the control group， no significant changes were observed in AHI， LSpO₂， BMI， TCM syndrome scores， or MIF， miR-223， IL-18 levels and their mRNAs after treatment. In the observation group， AHI， BMI， TCM syndrome scores， and MIF and IL-18 levels and their mRNAs decreased significantly， while LSpO₂ increased significantly （P<0.01）. After treatment， compared with the control group， the observation group exhibited significantly lower AHI， BMI， TCM syndrome scores， and MIF and IL-18 levels and their mRNAs， and significantly higher LSpO₂ （P<0.01）. Correlation analysis showed that MIF and IL-18 were positively correlated with AHI （P<0.01） and negatively correlated with LSpO₂ （P<0.01）， whereas miR-223 was negatively correlated with AHI （P<0.01） and positively correlated with LSpO₂ （P<0.01）. ConclusionModified LGZGT may improve OSAHS of the spleen deficiency and dampness obstruction with blood stasis type by reducing airway inflammatory factors， alleviating airway inflammation， relieving airway edema and stenosis， and improving airway obstruction.

In the context of the modernization of traditional Chinese medicine （TCM）， the inheritance of the experiences of famous doctors faces significant challenges due to its complex nonlinear characteristics and dynamic evolution. There are still issues in the current inheritance system， such as the homogenization of talent cultivation models， lack of standardized mentoring practices， and monotonous evaluation method， which hinder the systematic inheritance and innovative development of famous doctors' experiences. Based on a systematic review of the current state of artificial intelligence （AI）-assisted inheritance of famous doctors' experiences， this study explores innovative pathways for deep integration of modern information technologies with famous doctors' experiences from key dimensions， including data authenticity assurance， interdisciplinary collaboration mechanisms， and the establishment of dynamic inheritance standards. It proposes a paradigm shift in the inheritance of TCM famous doctors' experiences in the AI era， aiming to build a new TCM inheritance system of "digital intelligence empowerment and cross-disciplinary innovation"， providing theoretical support and practical pathways for the inheritance of famous doctors' experiences in TCM.

OBJECTIVE: To explore the genetic variants and phenotypic characteristics of patients with Neurofibromatosis type I (NF1). METHODS: Twenty two NF1 patients who presented at Enze Medical (Center) Group in Taizhou between 2018 and 2024 were selected as the study subjects. Clinical phenotype and family history were collected for the patients. Whole exome sequencing (WES) was carried out for the 22 probands to screen the variants of NF1 gene. Candidate variants were verified by Sanger sequencing of their family members. This study was approved by the Medical Ethics Committee of the Hospital (Ethics No.: K20230902). RESULTS: The 22 probands were diagnosed between the age of 5 months to 47 years old, and have all shown cafe au lait spots on their skin. Seventeen patients exhibited the phenotype at birth, and 11 had various degrees of neurofibromatosis. Among them, probands 1 and 13 underwent surgical resection of the tumor but had recurred, while proband 12 had amputation due to the huge size and serious impact of the neurofibroma and had no recurrence. Five patients had various degrees of scoliosis. In total 22 germline mutations and one somatic mutation were identified among the 22 families, with 5 variants unreported previously, including 1 nonsense mutation c.1603C>T (Q535*), 3 frameshift mutations [c.7268_7269delCA (Thr2423fs), c.2293del (Arg765Alafs*26), and c.5433_5438delinsGC (Phe1812ArgfsTer50)], and 1 deletion involving exons 41-44 of the NF1 gene and adjacent introns. Proband 13 was found to harbor germline mutation c.6796C>T (Gln2266Ter) and somatic mutation c.1019_1020del (Ser340Cysfs Ter12) in the peripheral blood and tumor tissue, respectively. Among the 22 NF1 probands, 6 had received treatment due to severe illness. Proband 1 had tumor resection in the right upper limb, but was found to have malignant lung tumor and died during follow-up. Proband 12 had multiple recurrence of neurofibroma in the left ring finger. Proband 4 underwent spinal correction surgery due to severe scoliosis. Proband 11 had died due to a central nervous system disease. Among the 22 germline mutations, 6 had led to the occurrence of truncated proteins, which may have a more severe impact on the phenotype. CONCLUSION This study investigated the genetic variants and clinical phenotypes of 22 NF1 families and identified 5 novel variants of the NF1 gene, which has expanded the genotypic and phenotypic spectra of the NF1. Preliminary studies have identified an association between truncated mutations, young age, and severe phenotypes, which may provide important clues for prognosis evaluation. For the clinical diagnosis and treatment of NF1, it is necessary to consider the phenotypic characteristics and genetic testing in combination with genetic counseling and long-term follow-up.
Humans ; Neurofibromatosis 1/pathology* ; Male ; Female ; Pedigree ; Adult ; Child ; Child, Preschool ; Middle Aged ; Adolescent ; Infant ; Young Adult ; Neurofibromin 1/genetics* ; Phenotype ; Asian People/genetics* ; Mutation ; Exome Sequencing ; East Asian People

ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

ObjectiveTo investigate the influencing factors and independent risk factors for lower extremity deep vein thrombosis （DVT） in patients with acute necrotizing pancreatitis （ANP）， to analyze the effectiveness of three commonly used risk assessment models for thrombosis （Caprini score， Padua score， and Wells score）， and to provide a reference for clinical identification of high-risk individuals and optimization of prevention and treatment strategies. MethodsA retrospective analysis was performed for the clinical data of 320 patients with ANP who were admitted to Luzhou People’s Hospital and The Affiliated Hospital of Southwest Medical University from April 2013 to April 2024， and according to the presence or absence of DVT during hospitalization， the patients were divided into thrombosis group with 25 patients and control group with 295 patients. After propensity score matching， the two groups were compared in terms of past history and various examination results during hospitalization. The risk factors for lower extremity DVT in ANP patients during hospitalization were analyzed through univariate and multivariate Logistic regression， and a DVT risk prediction model was established based on independent influencing factors. The receiver operating characteristic （ROC） curve was used to assess the performance of models， and the DeLong test was used for comparison of the area under the ROC curve （AUC）， sensitivity， and specificity. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups； the chi-square test was used for comparison of categorical data between groups. ResultsAfter matching， the patients were divided into thrombosis group with 24 patients and control group with 112 patients. The clinical characteristics analysis showed that compared with the control group， the thrombosis group had significantly higher degree of pancreatic necrosis， D-dimer level， Bedside Index for Severity in Acute Pancreatitis （BISAP） score， and proportion of patients undergoing dialysis （all P<0.05）. The multivariable Logistic regression analysis showed that BISAP score， degree of pancreatic necrosis， and D-dimer level were independent risk factors for lower extremity DVT in ANP patients during hospitalization （all P<0.05）. The BISAP-Caprini score model had an AUC of 0.832 （95% confidence interval： 0.722 — 0.942， P<0.001） in predicting the risk of lower extremity DVT， with a Youden index of 1.661， an optimal cut-off value of 0.26， a sensitivity of 75.0%， and a specificity of 91.1%. ConclusionD-dimer， BISAP score， and the degree of pancreatic necrosis are independent risk factors for lower extremity DVT in patients with ANP during hospitalization， and the BISAP-Caprini score model can effectively predict the risk of DVT in ANP patients.

OBJECTIVE To provide a scientific basis for the quality evaluation and clinical application of Qingwen hufei granules. METHODS Fourteen batches of Qingwen hufei granules were used as samples to establish high-performance liquid chromatography （HPLC） fingerprints using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 Edition）. The chromatographic peaks were identified and the similarity was evaluated. Cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were used to conduct chemical pattern recognition analysis on the 14 batches of samples. Meanwhile， the contents of neochlorogenic acid （NGA）， chlorogenic acid （CHA）， cryptochlorogenic acid （CGA）， forsythoside A （FTA）， 3，5-O-dicaffeoylquinic acid （3，5-O- DA）， 4，5-O-dicaffeoylquinic acid （4，5-O-DA）， and angoroside C （AGC） in the samples were determined by HPLC. RESULTS The methodological investigation results of both the fingerprint and the content determination complied with the relevant requirements. Fourteen common peaks were indicated in the HPLC fingerprints of the 14 batches of samples， and 7 of them were identified [NGA （peak 2）， CHA （peak 3）， CGA （peak 5）， FTA （peak 11）， 3，5-O-DA （peak 12）， 4，5-O-DA （peak 13）， and AGC （peak 14）]； the similarity of each sample was greater than 0.94. The results of CA and PCA showed that the samples could be classified into 3 categories； the results of OPLS-DA indicated that peak 4 （unknown）， peak 11 （FTA）， peak 8 （unknown）， peak 9 （unknown）， and peak 1 （unknown） were the differential components. The content ranges of NGA， CHA， CGA， 3，5-O-DA， FTA， 4，5-O-DA and AGC in the 14 batches of samples were 0.210 4-0.458 7， 0.269 1-0.506 3， 0.228 1-0.461 1， 0.443 9-1.044 6， 0.066 7-0.155 7， 0.062 8-0.143 8， and 0.057 4-0.105 7 mg/g， respectively. CONCLUSIONS The HPLC fingerprint and multi-component content determination methods established in this study are efficient and reliable， and can be used for the quality evaluation of Qingwen hufei granules.