Gastrointestinal (GI) cancers are a leading cause of cancer morbidity and mortality worldwide. Despite advances in treatment, cancer relapse remains a significant challenge, necessitating novel therapeutic strategies. In this study, we engineered nanobody-based chimeric antigen receptor (CAR) natural killer (NK) cells targeting cadherin 17 (CDH17) for the treatment of GI tumors. In addition, to enhance the efficacy of CAR-NK cells, we also incorporated CV1, a CD47-SIRPα axis inhibitor, to evaluate the anti-tumor effect of this combination. We found that CDH17-CAR-NK cells effectively eliminated GI cancers cells in a CDH17-dependent manner. CDH17-CAR-NK cells also exhibit potent in vivo anti-tumor effects in cancer cell-derived xenograft and patient-derived xenograft mouse models. Additionally, the anti-tumor activity of CDH17-CAR-NK cells is synergistically enhanced by CD47-signal regulatory protein α (SIRPα) axis inhibitor CV1, likely through augmented macrophages activation and an increase in M1-phenotype macrophages in the tumor microenvironment. Collectively, our findings suggest that CDH17-targeting CAR-NK cells are a promising strategy for GI cancers. The combination of CDH17-CAR-NK cells with CV1 emerges as a potential combinatorial approach to overcome the limitations of CAR-NK therapy. Further investigations are warranted to speed up the clinical translation of these findings.

Objective To validate the diagnostic performance and risk stratification ability of an AI-based recognition system(PE-AI)for pulmonary embolism(PE)using computed tomography pulmonary angiography(CTPA)so as to analyze its diagnostic value in clinical practice.Methods A total of 416 patients with suspected PE who underwent CTPA from January 1,2023 to December 10,2023 at our hospital were included in this study.Two junior radiologists and PE-AI separately detected and diagnosed emboli in the collected cases by double-blind method,and recorded the diagnosis time respectively.Three senior radiologists reviewing with clinical follow-up results were used as the gold standard in this study.Diagnostic performance was evaluated by using the receiver operating characteristic(ROC)curve analysis and Delong-t test.For positive cases,the pulmonary artery obstruction index(PAOI)calculated by AI and manually were collected respectively and consistency analysis was performed.Results The area under the curve(AUC)of PE-AI,manual and combined diagnosis was 85.6％,90.8％and 95.1％,respectively,which differed significantly(P＜0.05).The reading time of PE-AI[(0.16±0.07)min]was significantly lower than the time of manual[(4.42±1.85)min,P＜0.001]and combined diagnosis[(4.58±1.84)min,P＜0.001].The PAOI measured by PE-AI and manually had high consistency(intraclass correlation efficient,ICC=0.80)in the subgroup analysis of confirmed cases.Conclusion AI can quickly identify pulmonary artery emboli in a short time and assist radiologists to improve diagnostic efficiency.At the same time,through the intelligent detection of PAOI,it is helpful for the risk stratification of patients with PE and optimizing the diagnosis and treatment pathway for pulmonary embolism.

Objective To address the challenges of accurately capturing critical features in small-sample diabetic retinopathy(DR)recognition models in real-world applications,and the overly smooth distribution of true and false feature coefficients,we propose an enhanced small-sample DR recognition method based on an improved capsule network.Methods Firstly,the method enhances image feature representation by removing redundant boundary information and employing discrete wavelet transform based on the Haar wavelet function,thereby high-lighting critical pathological features.Secondly,the convolutional layer of the capsule network is optimized through a multi-branch architecture to extract multi-scale features from retinal images,while incorporating a convolutional block attention module that is subsequently fed into the capsule layer.Finally,the sigmoid function replaces the soft-max function in dynamic routing,thereby improving the model's robustness.Result The enhanced neural network model achieved an accuracy of 98.62%on the Kaggle public dataset following a rigorous selection and preprocessing procedure.Conclusion The enhanced capsule network demonstrated superior precision in identifying diabetic reti-nopathy within small sample sizes compared to other state-of-the-art algorithms currently available.

Objective To validate the diagnostic performance and risk stratification ability of an AI-based recognition system(PE-AI)for pulmonary embolism(PE)using computed tomography pulmonary angiography(CTPA)so as to analyze its diagnostic value in clinical practice.Methods A total of 416 patients with suspected PE who underwent CTPA from January 1,2023 to December 10,2023 at our hospital were included in this study.Two junior radiologists and PE-AI separately detected and diagnosed emboli in the collected cases by double-blind method,and recorded the diagnosis time respectively.Three senior radiologists reviewing with clinical follow-up results were used as the gold standard in this study.Diagnostic performance was evaluated by using the receiver operating characteristic(ROC)curve analysis and Delong-t test.For positive cases,the pulmonary artery obstruction index(PAOI)calculated by AI and manually were collected respectively and consistency analysis was performed.Results The area under the curve(AUC)of PE-AI,manual and combined diagnosis was 85.6％,90.8％and 95.1％,respectively,which differed significantly(P＜0.05).The reading time of PE-AI[(0.16±0.07)min]was significantly lower than the time of manual[(4.42±1.85)min,P＜0.001]and combined diagnosis[(4.58±1.84)min,P＜0.001].The PAOI measured by PE-AI and manually had high consistency(intraclass correlation efficient,ICC=0.80)in the subgroup analysis of confirmed cases.Conclusion AI can quickly identify pulmonary artery emboli in a short time and assist radiologists to improve diagnostic efficiency.At the same time,through the intelligent detection of PAOI,it is helpful for the risk stratification of patients with PE and optimizing the diagnosis and treatment pathway for pulmonary embolism.

Objective To address the challenges of accurately capturing critical features in small-sample diabetic retinopathy(DR)recognition models in real-world applications,and the overly smooth distribution of true and false feature coefficients,we propose an enhanced small-sample DR recognition method based on an improved capsule network.Methods Firstly,the method enhances image feature representation by removing redundant boundary information and employing discrete wavelet transform based on the Haar wavelet function,thereby high-lighting critical pathological features.Secondly,the convolutional layer of the capsule network is optimized through a multi-branch architecture to extract multi-scale features from retinal images,while incorporating a convolutional block attention module that is subsequently fed into the capsule layer.Finally,the sigmoid function replaces the soft-max function in dynamic routing,thereby improving the model's robustness.Result The enhanced neural network model achieved an accuracy of 98.62%on the Kaggle public dataset following a rigorous selection and preprocessing procedure.Conclusion The enhanced capsule network demonstrated superior precision in identifying diabetic reti-nopathy within small sample sizes compared to other state-of-the-art algorithms currently available.

ObjectiveBy starting with the combination of Os Draconis， Bupleuri Radix， and Ostreae Concha， the role of mineral medicine Os Draconis in the combination of the Bupleuri Radix-containing tri-herbal medicines was preliminarily explored from the perspective of supramolecular system formation. Method① The appearance and Tyndall phenomenon of single decoction of Os Draconis， Bupleuri Radix， and Ostreae Concha， as well as co-decoction of Bupleuri Radix-Os Draconis， Bupleuri Radix-Os Draconis-Ostreae Concha， and Bupleuri Radix-Ostreae Concha were observed， and the average particle size， dispersion coefficient， and Zeta potential of suspension particles in each decoction were determined. The micromorphology of supramolecular structures was observed by scanning electron microscope （SEM）. ② The pH of different compatibility systems， liquid viscosity coefficient， liquid surface tension， freeze-dried powder yield rate， and other physical properties were determined， and the interaction of different compatibility systems was detected by infrared absorption spectroscopy （FTIR） and UV-visible spectrophotometry （UV-Vis）. ③ The composition and content difference of different compatible systems were determined by high-performance liquid chromatography （HPLC） and ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry （UPLC-Q-TOF-MS）. ResultCompared with the single decoction， the co-decoction had more obvious turbidity and Tyndall phenomenon. The particles in the co-decoction suspension were smaller and more evenly distributed， and the Zeta potential was reduced， indicating a more stable system. Under SEM， Bupleuri Radix was irregularly lamellar， and Bupleuri Radix-Os Draconis and Bupleuri Radix-Os Draconis-Ostreae Concha were mainly spherical nanoparticles. Bupleuri Radix-Ostreae Concha was irregularly lamellar， with a small number of spherical nanoparticles. The pH of the single decoction of Bupleuri Radix and co-decoction increased， and the viscosity coefficient increased. The liquid surface tension decreased. The freeze-dried powder yield rate of the Bupleuri Radix-Os Draconis co-decoction was the highest， followed by Bupleuri Radix-Ostreae Concha decoction and Bupleuri Radix-Os Draconis-Ostreae Concha decoction， and the yield rate of Bupleuri Radix single decoction was the lowest. The main change of FTIR was the stretching vibration of -OH， and the co-decoction moved to the low-frequency direction obviously. UV-Vis showed that the maximum absorption occurred at 295.8 nm for all groups， and the absorption intensity was different （Bupleuri Radix-Os Draconis>Bupleuri Radix-Os Draconis-Ostreae Concha>Bupleuri Radix-Ostreae Concha>Bupleuri Radix）. The components of Bupleuri Radix were used as the indexes， and the content of methanol extract determined by HPLC was higher than that of water extract， and the components of Bupleuri Radix single decoction were mainly saikosaponin a （SSa） and saikosaponin c （SSc）， which were slightly higher after co-decoction compatibility. UPLC-Q-TOF-MS could identify 37 compounds in both single decoction and co-decoction. ConclusionThe combination of Bupleuri Radix， Os Draconis， and Ostreae Concha can form a smaller， more uniform， and stable nano-sized supramolecular system， which is conducive to the dissolution of the main components of Bupleuri Radix， and the Os Draconis contributes the most in this process.

Objective:To investigate the clinicopathological characteristics of early-onset colorectal cancer.Methods:The retrospective and descriptive study was conducted. The clincopatholo-gical data of 59 206 patients with colorectal cancer in the Surveillance, Epidemiology, and End Results Program of the United States of America From January 1,2010 to December 31,2019 were collected. There were 33 213 males, 25 993 males, aged (50±7)years. Observation indicators: (1) demographic and oncological characteristics of colorectal cancer patients; (2) comparison of clinico-pathological characteristics between early-onset and late-onset colorectal cancer. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison among groups was conducted using the Kruskal-Wallis H test. Count data were described as absolute numbers, and comparison among groups was conducted using the chi-square test. Comparison of ordinal data was conducted using the non-parameter H test. Patients with early-onset colorectal cancer were segmented by age, and missing data for categorical variables is set as unknown. Results:(1) Demographic and oncological characteristics of colorectal cancer patients. Of 59 206 patients, there were 23 104 cases with early-onset colorectal cancer and 36 102 cases with late-onset colorectal cancer, and cases aged 13-29 years, cases aged 30-34 years, cases aged 35-39 years, cases aged 40-44 years, cases aged 45-49 years, cases aged 55-59 years were 1 041, 1 740, 3 288, 6 050, 10 985, 15 303,20 799, respectively. (2) Comparison of clinicopathological charac-teristics between early-onset and late-onset colorectal cancer. ① There were significant differences in gender, tumor location, degree of tumor differentiation, tumor histological type, tumor TNM staging, tumor T staging, tumor N staging, tumor M staging, preoperative carcinoembryonic antigen (CEA), perineural invasion, cancer nodule, tumor diameter between patients with early-onset and late-onset colorectal cancer ( P<0.01). Results of further analysis showed that cases with tumor located in ileocecal region, ascending colon, colon liver region, transverse colon were 2 329, 2 139, 579, 1 303 in the 6 350 patients with early-onset right colon cancer. The above indicators were 4 563, 3 945, 902, 1 951 in the 11 361 patients with late-onset right colon cancer. There was a significant difference in the above indicators between the two groups of patients ( χ2=114.27, P<0.01). Cases with tumor located in splenic region of the colon, descending colon, sigmoid colon, rectum sigmoid junction were 553, 1 354, 6 404, 2 431 in the 10 742 patients with early-onset left colon cancer. The above indicators were 865, 1 798, 9 668, 3 610 in the 15 941 patients with late-onset left colon cancer. There was a significant difference in the above indicators between the two groups of patients ( χ2=35.60, P<0.01). ②Of 23 104 patients with early-onset colorectal cancer, cases aged 13-29 years, cases aged 30-34 years, cases aged 35-39 years, cases aged 40-44 years, cases aged 45-49 years were 1 041, 1 740, 3 288, 6 050, 10 985, respectively. There were significant differences in gender, degree of tumor differentiation, tumor histological type, tumor TNM staging, tumor T staging, tumor N staging, pre-operative CEA, perineural invasion, cancer nodule, tumor diameter among patients of different age groups ( P<0.01). Results of further analysis showed that cases with tumor located in ileocecal region, ascending colon, colon liver region, and transverse colon were 91, 117, 45, 69 in the 6 350 early-onset right colorectal cancer patients aged 13-29 years. The above indicators were 165, 136, 47, 115, 304, 313, 93,201, 614, 535, 151, 330, 1 155, 1 038, 243, 588 in early-onset right colorectal cancer patients aged 30-34, 35-39, 40-44, 45-49 years, respectively. There was a significant difference in the above indicators among the five groups of patients ( H=36.63, P<0.01). Cases with tumor located in splenic region of the colon, descending colon, sigmoid colon, rectum sigmoid junction were 32, 83, 260, 95 in the 10 742 early-onset left colorectal cancer patients aged 13-29 years. The above indica-tors were 53, 112, 452, 171, 95, 230, 867, 342, 149, 337, 1 702, 665, 224, 592, 3 123, 1 158 in the 10 742 early-onset left colorectal cancer patients aged 30-34, 35-39, 40-44, 45-49 years, respectively. There was a significant difference in the above indicators among the five groups of patients ( H=47.84, P<0.01). Conclusions:Compared with late-onset colorectal cancer, early-onset colorectal cancer are more likely to occur in the left colon and rectum, with poorly differentiated and undifferentiated tumors, histological type of mucinous adenocarcinoma, TNM staging of stage Ⅲ and Ⅳ, higher proportion of nerve infiltration and cancer nodules, and larger tumor diameter. There are significant differences in clinicopathological characteristics of tumors among patients with early-onset colorectal cancer of different age groups.

Algorithms ; Crystallography, X-Ray ; Disulfides ; chemistry ; Models, Molecular ; Protein Conformation ; Proteins ; chemistry

Objective To investigate the prevalence of thyroid nodules and thyroid dysfunction in southern mountainouss areas of Ningxia.Methods A cross-sectional study was conducted among a representative sample of 10 639 adults in Jingyuan county with a population proportionate sampling method.High-resolution ultrasound was used to examine the thyroid and fasting blood specimens were collected in the morning for measurement of TSH,FT4,FT3.Chi-square test and spearman rank correlation analysis were used for statistical analysis.Results The prevalence of thyroid nodules was 29.08％,the sex-and age-adjusted rate was 27.17％.The prevalence of thyroid nodules was higher in women than in men (32.68％ vs.24.88％,x2=76.029 2,P＜0.001) and age was positively associated with thyroid nodules (r=0.272,P＜0.001).The rate of thyroid dysfunetion,subclinical hypothyroidism,subclinical hyperthyroidism,hypothyroidism,hyperthyroidism were 17.39％,13.00％,0.42％,0.96％,3.01％,respectively.The prevalence of thyroid nodules was higher in abnormal TSH group than in normal TSH group (39.44％ vs.27.24％,x2=95.624 0,P＜0.001).The level of THS,FT3,FT4 in thyroid nodules group differed fromn control group (Z=-9.144,P＜0.001;Z=-6.140,P＜0.001;Z=-1.997,P=0.046).Conclusion The prevalence of thyroid nodules and thyroid dysfunction were higher in southern mountainous areas of Ningxia.The relationship between thyroid nodules and thyroid function needs further research.We should pay attention to the early screening and diagnosis of thyroid nodules in mountainous areas.

Objective To investigate the influence of hypothyroidism on pregnancy outcome and fetus in pregnant women.Methods A total of 4 286 pregnant women,who received prenatal examination in our hospital from January 2013 to October 2015,were selected as study subjects.The incidence of hypothyroidism and the influence on pregnancy outcomes and fetus were investigated.Results In 4 286 pregnant women surveyed,209 hypothyroidism cases were detected (4.9％),including 85 clinical hypothyroidism cases and 124 subclinical hypothyroidism cases.In health group,the premature delivery rate was 1.0％,significantly lower than that in clinical hypothyroidism group (10.6％) and in subclinical hypothyroidism group (6.5％),the differences were significant (χ2=38.884,P＜0.001;χ2=17.722,P＜0.001).In healthy group,the incidence of anemia was 3.8％,significantly lower than that in clinical hypothyroidism group (18.8％) and in subclinical hypothyroidism group (9.7％),the differences were significant (χ2=30.949,P＜0.001;χ2=23.275,P＜0.001).In health group,the incidence of low birth weight was 1.1％,significantly lower than that in clinical hypothyroidism group (14.1％) and in subclinical hypothyroidism group (4.8％),the differences were significant (χ2=50.593,P＜0.001;χ2=15.637,P＜0.001).In health group,the fetal distress incidence was 1.9％,significantly lower than that in clinical hypothyroidism group (10.6％) and in subclinical hypothyroidism group (5.6％),the differences were significant (χ 2=19.257,P＜0.001;χ2=12.357,P＜0.001).In health group,the fetal Apgar score (9.69 ± 0.32) was significantly higher than those in clinical hypothyroidism group (9.25 ± 0.45) and in subclinical hypothyroidism group (9.28 ± 0.44),the differences were significant (t=8.823,P＜0.001;t=15.175,P＜0.001).Conclusion Hypothyroidism during pregnancy has adverse influences on pregnancy outcome and fetus,and it is necessary to strengthen the hypothyroidism detection in pregnant women for the early treatment.