ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

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.

Objective To construct an automatic segmentation model to segment female urine control anatomy on MRI images based on deep learning methods in order to improve the segmentation efficiency and accuracy.Methods A dataset comprising 49 female pelvic floor muscle MRI images[30 women with varying degrees of pelvic organ prolapse(POP)and 19 healthy individuals],obtained from Faculty of Biomedical Engineering and Medical Imaging in Army Medical University,was used for model training and testing.The dataset was split into a training set(17 normal cases and 22 POP cases)and a testing set(4 normal cases and 6 POP cases)in a ratio of 8∶2.The training set was used to train UNet,UNet+++,Dense UNet,and UNet++models separately,and then input into each network.The model achieving the highest testing accuracy was selected as the backbone network.Results Under the training of UNet,UNet+++,Dense UNet,and UNet++,the 4 models achieved average Dice similarity coefficients of 61.82%,57.94%,57.63%,and 62.76%,respectively,for the segmentation of 5 anatomical structures(compressor urethrae,urethra sphincter body,bladder wall,bladder cavity and urethra submucosa).The corresponding Intersection over Union(IoU)score was 49.74%,46.59%,46.07%,and 49.44%,while the accuracy rate was 61.74%,55.03%,59.23%,and 61.91%,respectively for the 4 models.Notably,UNet++consistently outperformed UNet,UNet+++,and Dense UNet across the 3 metrics,indicating that UNet++achieved the highest overall segmentation accuracy.Conclusion In UNet,UNet++,Dense UNet and UNet++for automatic segmentation of 5 female urine control anatomical elements,UNet++achieves the best overall segmentation accuracy.

Background and objective Both of lung cancer incidence and mortality rank first among all cancers in China.Previous lung cancer screening trials were mostly selective screening for high-risk groups such as smokers.Non-smoking women accounted for a considerable proportion of lung cancer cases in Asia.This study aimed to evaluate the outcome of community-based mass screening in Guangzhou and identify the high-risk factors for lung cancer.Methods Residents aged 40-74 years in Guangzhou were screened with low-dose computed tomography(LDCT)for lung cancer and the pulmonary nodules were classified and managed according to China National Lung Cancer Screening Guideline with Low-dose Computed Tomography(2018 version).The detection rate of positive nodules was calculated.Before the LDCT examination,residents were required to complete a"lung cancer risk factors questionnaire".The risk factors of the questionnaire were analyzed by least absolute shrinkage and selection operator(LASSO)penalized Logistic regression analysis.Results A total of 6256 residents were included in this study.1228 positive nodules(19.63％)and 117 lung cancers were confirmed,including 6 cases of Tis,103 cases of stage Ⅰ(accounting for 88.03％of lung cancer).The results of LASSO penalized Logistic regression analysis indicated that age ≥50 yr(OR=1.07,95％CI:1.06-1.07),history of cancer(OR=3.29,95％CI:3.22-3.37),textile industry(OR=1.10,95％CI:1.08-1.13),use coal for cooking in childhood(OR=1.14,95％CI:1.13-1.16)and food al-lergy(OR=1.10,95％CI:1.07-1.13)were risk factors of lung cancer for female in this district.Conclusion This study highlighted that numerous early stages of lung cancer cases were detected by LDCT,which could be applied to screen-ing of lung cancer in women.Besides,age ≥50 yr,personal history of cancer,textile industry and use coal for cooking in childhood are risk factors for women in this district,which suggested that it's high time to raise the awareness of early lung cancer screening in this group.

ObjectiveTo explore the distribution characteristics of traditional Chinese medicine （TCM） syndrome elements of macroangiopathy in patients with type 2 diabetes mellitus （T2DM） and the key elements of occurrence， development and progression of disease. MethodsA multicenter cross-sectional study was conducted to enroll 445 T2DM patients from five hospitals， and according to the presence or absence of macroangiopathy， the patients were divided into a T2DM group （120 cases） and a diabetic macroangiopathy （DM） group （325 cases）. Patients in DM group were divided into grade Ⅰ， Ⅱ， Ⅲ and Ⅳ according to the peripheral vascular color Doppler ultrasound results and the vascular anomalies classification standard. The general data including gender， age， duration of T2DM and body mass index （BMI） were collected， and the data of four examinations were obtained for syndrome differentiation. According to the diagnostic criteria of TCM syndrome elements， the patients can be divided into 9 patterns including qi deficiency， blood deficiency， yin deficiency， yang deficiency， qi stagnation， blood stasis， excess heat， and excess cold. The general data and distribution of TCM syndrome elements were compared between the two groups. The distribution of TCM syndrome elements in different vascular anomalies grades in the DM group was analyzed. Logistic regression analysis was used to explore the influence of various TCM syndrome elements on the occurrence of macroangiopathy in T2DM. ResultsThere was no significant difference in gender and BMI between groups （P＞0.05）. The age and duration of diabetes in the DM group were older and longer than those in the T2DM group （P＜0.01）. With the increase of age and prolonged course of disease， the severity of diabetic macroangiopathy increases gradually （P＜0.05 or P＜0.01）. There was no significant difference in BMI and course of disease among the different TCM syndrome elements （P＞0.05）. The average age of patients with blood stasis syndrome was the oldest （P＜0.05）. There was significant difference in gender distribution between the excess heat syndrome and yin deficiency syndrome （P＜0.05）. A total of 240 TCM syndrome elements were extracted from the T2DM group， while 731 TCM syndrome elements extracted from the DM group. The top two high-frequency syndrome elements in the two groups were qi deficiency and yin deficiency， with a frequency of larger than 50%. The distribution of phlegm-damp syndrome and blood-stasis syndrome were significantly higher in the DM group than in the T2DM group （P＜0.01）. There were significant differences in the distribution of qi deficiency syndrome， yin deficiency syndrome， phlegm-damp syndrome， blood stasis syndrome， and excess heat syndrome among different grades of vascular anomalies （P＜0.01）； qi deficiency and yin deficiency were both high-frequency TCM syndrome elements in patients at grades 0 to Ⅲ； phlegm-damp syndrome increased in frequency with the progression of the disease from grades 0 to Ⅳ， and the frequency of blood stasis syndrome showed an overall upward trend. The frequency of phlegm-dampness syndrome increased from grades 0 to Ⅳ with the progression of the disease， and the frequency of blood stasis syndrome showed an overall upward trend. Logistic regression analysis showed that phlegm-damp syndrome and blood stasis syndrome were important TCM syndrome elements related to the vascular anomalies degree of macrovascular disease in T2DM （P＜0.05 or P＜0.01）. ConclusionQi deficiency and yin deficiency are the basic TCM syndrome elements throughout the whole process of T2DM and diabetic macrovascular disease. Phlegm-damp and blood stasis are related to the degree of vascular anomalies in diabetic macrovascular disease and are the key TCM syndrome elements in the progression of macroangiopathy in T2DM.

Objective To investigate the clinical efficacy of interesting respiratory rehabilitation training(IRRT)combined with budesonide and montelukast sodium in the treatment of bronchial asthma(BA).Methods This is a pilot clinical research.Children with BA who visited Ma'anshan Shiqiye Hospital of Anhui province from January 2023 to December 2023 in were prospectively recruited as study subjects,and were divided into the IRRT group and the conventional group according to the random number table method.After 8 weeks of continuous intervention,the clinical efficacy,recovery of related symptoms and adverse reactions of BA children were evaluated.The changes in lung function parameters,inflammation indicators and quality of life were compared before and after treatment in the IRRT group and the conventional group,and the changes in lung function parameters,inflammation indicators and quality of life between the IRRT group and the conventional group after treatment were compared.Results A total of 120 BA children were included in the study,with 60 cases in each group.Before treatment,there was no significant difference in baseline data such as age and gender between the two groups(P>0.05).After 8 weeks of treatment,pulmonary function parameters,inflammation indicators,and quality of life were all improved in the IRRT group and the conventional group,(P<0.05),and the improvement in the IRRT group was better than that in the conventional group(P<0.05).In addition,the disappearance time of wheezing,disappearance time of cough,and disappearance time of dyspnea were significantly shorter than those in the conventional group(P<0.05).In terms of safety,no significant serious adverse effects were seen in the IRRT group and the conventional group.Conclusion Adjuvant IRRT therapy can significantly improve children's lung function,reduce the level of inflammatory factors,shorten the course of the disease,improve quality of life,and promote early recovery in children.

OBJECTIVE: To explore the predictive value of acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), quick sequential organ failure assessment (qSOFA) and modified early warning score (MEWS) in evaluating the prognosis of patients in intensive care unit (ICU) of secondary hospitals, and to provide guidance for clinical application. METHODS: The clinical data of adult critical patients admitted to the ICU of Wanzhou District First People's Hospital from October 2022 to April 2023 were retrospectively analyzed. According to the clinical outcome of ICU, the patients were divided into improvement group and death group. The general information, blood routine, heart, liver and kidney function indicators, coagulation indicators, blood gas analysis, APACHE II score, SOFA score, qSOFA score, MEWS score at the time of admission to the ICU, the number of cases of invasive mechanical ventilation (IMV) and continuous blood purification (CBP) were compared between the two groups. Univariate analysis was performed, and multivariate Logistic regression analysis was used to analyze the related factors of death. Receiver operator characteristic curve (ROC curve) was used to analyze the predictive value of the four scores in ICU patients. RESULTS: A total of 126 patients were included, of which 45 patients died in the ICU and 81 patients improved and transferred out. Univariate analysis of death-related critically ill patients showed that procalcitonin (PCT), serum creatinine (SCr), blood urea nitrogen (BUN), albumin (ALB), prothrombin time (PT), activated partial prothrombin time (APTT), D-dimer, pH value, HCO₃^-, blood lactic acid (Lac), number of patients treated with IMV and CBP, APACHE II score, SOFA score, qSOFA score and MEWS score were significantly different between the two groups (all P < 0.05). Multivariate Logistic regression analysis showed that the APACHE II score [odds ratio (OR) = 1.115, 95% confidence interval (95%CI) was 1.025-1.213, P = 0.011], SOFA score (OR = 1.204, 95%CI was 1.037-1.398, P = 0.015), MEWS score (OR = 1.464, 95%CI was 1.102-1.946, P = 0.009), and APTT (OR = 1.081, 95%CI was 1.015-1.152, P = 0.016) were independent risk factors affecting the mortality of critically ill patients in the ICU. ROC curve analysis showed that APACHE II, SOFA, qSOFA, and MEWS scores could predict the prognosis of critically ill ICU patients, among which SOFA score had the strongest predictive effect, and the area under the curve (AUC) was 0.808. There was a statistically significant difference in the time required for the four scores (F = 117.333, P < 0.001), among which the MEWS scoring required the shortest time [(1.03±0.39) minutes], and the APACHE II scoring required the longest time [(2.81±1.04) minutes]. CONCLUSIONS APACHE II, SOFA, qSOFA, and MEWS scores can be used to assess the severity of critically ill patients and predict in-hospital mortality. The SOFA score is superior to other scores in predicting severity. The MEWS is preferred because its assessment time is shortest. Early warning score can help secondary hospitals to detect potentially critical patients early and provide help for clinical rapid urgent emergency decision-making.
Adult ; Humans ; Sepsis/diagnosis* ; ROC Curve ; Retrospective Studies ; Critical Illness ; Early Warning Score ; Organ Dysfunction Scores ; Intensive Care Units ; Prognosis ; Hospitals

Objective To analyze the epidemiological characteristics of newly reported advanced schistosomiasis cases in Sichuan Province, so as to provide the evidence for analyzing the causes and formulating targeted control measures of newly reported advanced schistosomiasis cases. Methods Individual case investigation forms for advanced schistosomiasis cases were collected from the Sichuan Provincial Epidemic Annual Report System from 2011 to 2022, and patients’ demographics, previous medical history and liver parenchymal grading were retrieved. All advanced schistosomiasis cases’ medical records were reviewed, and the subtypes of schistosomiasis-endemic villages where the cases’ household registration were, floating population, survival and death and time of death were collected. Results A total of 321 newly reported advanced schistosomiasis cases were found in Sichuan Province from 2011 to 2022, with a male to female ratio of 0.99 to 1. There were 274 cases at ages of over 50 years (85.4%), with the highest proportion seen at ages of 60 to 69 years (87 cases, 27.1%), and splenomegaly was the most common type (180 cases, 56.1%), with no dwarfism type detected. The highest number of cases was reported in 2011 (78 cases), followed by in 2022 (74 cases), and the highest number of cases were reported in Meishan City (199 cases, 62.0%), Dongpo District (131 cases, 40.8%), and hilly subtype areas (136 cases, 42.4%). As of the end of 2022, there were 111 deaths due to advanced schistosomiasis, with the highest number of deaths seen in 2018 (25 deaths), and the highest mortality was seen among patients with the ascites type (41.2%). There were 47 (37.3%), 40 (59.5%) and 4 (23.5%) cases with grade III liver parenchyma among patients with splenomegaly, ascites, and colonic proliferation types, respectively, and there was a significant difference in the grading of III liver parenchyma among three types of patients (H = 12.092, P < 0.05), with more severe liver parenchyma injuries seen among patients with the ascites type than among those with splenomegaly and colonic proliferation type (Z = 24.262 and 44.738, both P_adjusted values < 0.05). Conclusions There have been newly reported advanced schistosomiasis cases in Sichuan Province during recent years, and patients with the ascites type should be given a high priority among advanced schistosomiasis cases in Sichuan Province. Intensified clue surveys are needed for early identification and treatment of advanced schistosomiasis cases, so as to increase the survival rate and improve the quality of life.

Many studies have found a correlation between suicidal behavior (SB) and anhedonia, the main symptom of depression, in terms of both psychological and neurophysiological findings. The purpose of this review is to find the relationship between the two neuroimaging mechanisms, and to provide help for the future study of how the brain imaging changes can promote the mechanism of SB in depression patients with anhedonia symptoms. This review also emphasizes the necessity of intervention for the symptoms of anhedonia when preventing depression from committing suicide. The latest research results were reviewed about anhedonia in depression and magnetic resonance imaging of SB.The results showed that the default network, insula, lateral orbitofrontal gyrus, anterior cingulate gyrus, ventral striatum gyrus, ventral lateral and dorsolateral prefrontal gyrus, thalamus and habenula nucleus were dysfunction in depression with state anhedonia symptoms, affecting SB in terms of mood, execution, reward and aversion processing, especially the low lethal SB.

The first rate-limiting enzyme of the serine synthesis pathway (SSP), phosphoglycerate dehydrogenase (PHGDH), is hyperactive in multiple tumors, which leads to the activation of SSP and promotes tumorigenesis. However, only a few inhibitors of PHGDH have been discovered to date, especially the covalent inhibitors of PHGDH. Here, we identified withangulatin A (WA), a natural small molecule, as a novel covalent inhibitor of PHGDH. Affinity-based protein profiling identified that WA could directly bind to PHGDH and inactivate the enzyme activity of PHGDH. Biolayer interferometry and LC-MS/MS analysis further demonstrated the selective covalent binding of WA to the cysteine 295 residue (Cys295) of PHGDH. With the covalent modification of Cys295, WA blocked the substrate-binding domain (SBD) of PHGDH and exerted an allosteric effect to induce PHGDH inactivation. Further studies revealed that with the inhibition of PHGDH mediated by WA, the glutathione synthesis was decreased and intracellular levels of reactive oxygen species (ROS) were elevated, leading to the inhibition of tumor proliferation. This study indicates WA as a novel PHGDH covalent inhibitor, which identifies Cys295 as a novel allosteric regulatory site of PHGDH and holds great potential in developing anti-tumor agents for targeting PHGDH.