ObjectivePancreatic ductal adenocarcinoma (PDAC) exhibits a limited response to current treatments due to its dense fibrotic stroma and highly immunosuppressive tumor microenvironment. In recent years, advancements in cellular immunotherapy, particularly chimeric antigen receptor macrophage (CAR-M) therapy, have offered new hope for pancreatic cancer treatment. Although CAR-M therapy demonstrates dual potential in directly killing tumor cells and remodeling the immune microenvironment, it still faces challenges such as complex in vitro preparation processes and low in vivo targeting and delivery efficiency. Therefore, developing strategies for efficient and targeted in vivo delivery of CAR genes has become crucial for overcoming current therapeutic limitations. This study aims to develop an orally administrable nano-gene delivery system for the targeted delivery of CAR genes to pancreatic tumor sites. MethodsCore nano-gene particles (PNP/pCAR) were constructed by loading plasmid DNA encoding CAR (pCAR) with cationic polypeptides (PNP). Subsequently, PNP/pCAR was surface-modified with β-glucan to prepare the targeted nanoparticles (βGlus-PNP/pCAR). The loading efficiency of PNP for pCAR was quantitatively assessed by gel retardation assay. The particle size, Zeta potential, morphology, and storage stability of PNP/pCAR were characterized using a Malvern particle size analyzer and transmission electron microscopy. At the cellular level, RAW 264.7 macrophages were selected. The cytotoxicity of PNP/pCAR was evaluated using the CCK-8 assay. The cellular uptake efficiency and lysosomal escape ability of the nanoparticles were assessed via flow cytometry and confocal microscopy. Transfection efficiency was quantitatively evaluated by detecting the expression of the reporter gene GFP using flow cytometry. At the in vivo level, an orthotopic pancreatic cancer mouse model was established. Cy7-labeled βGlus-PNP/pCAR nanoparticles were administered orally, and the fluorescence distribution in mice was dynamically monitored at 1, 2, 4, 8, and 16 h post-administration using a small animal in vivo imaging system. Forty-eight hours after oral gavage, the mice were euthanized, and pancreatic tumor tissues were collected for further analysis of intratumoral fluorescence signals using the imaging system. Additionally, βGlus-PNP/pCAR-GFP nanoparticles loaded with the reporter gene (GFP) were administered orally. Forty-eight hours post-administration, pancreatic tumor tissues were harvested to prepare frozen sections, and GFP expression was observed and analyzed under a fluorescence microscope. ResultsThe PNP carrier exhibited a high loading capacity for pCAR. The successfully prepared PNP/pCAR nanoparticles were regular spheres with a hydrodynamic diameter of approximately (120±10) nm and a Zeta potential of about +(6±1) mV. They maintained good structural stability after incubation in PBS buffer for 7 d. Cell experiments demonstrated that PNP/pCAR exhibited no significant cytotoxicity in RAW 264.7 cells while being efficiently internalized and effectively escaping lysosomal degradation. The transfection positive rate of PNP/pCAR-GFP in RAW 264.7 cells reached (25±3)%, surpassing that of Lipofectamine 2000-loaded pCAR-GFP (Lipo/pCAR-GFP), which was (20±1)%.In vivo experiments revealed that, compared to unmodified PNP/pCAR, βGlus-PNP/pCAR exhibited strongerin situ pancreatic tumor targeting ability after oral administration. Furthermore, oral administration of βGlus-PNP/pCAR-GFP resulted in significant GFP protein expression detectable within pancreatic tumor tissues. ConclusionThis study successfully constructed and validated an orally administrable, pancreatic cancer-targeting polypeptide-based nano-gene delivery system. It provides an important technological foundation in delivery systems and experimental basis for the subsequent development of in situ CAR-M-based therapeutic strategies for pancreatic cancer.

ObjectivePancreatic ductal adenocarcinoma (PDAC) exhibits a limited response to current treatments due to its dense fibrotic stroma and highly immunosuppressive tumor microenvironment. In recent years, advancements in cellular immunotherapy, particularly chimeric antigen receptor macrophage (CAR-M) therapy, have offered new hope for pancreatic cancer treatment. Although CAR-M therapy demonstrates dual potential in directly killing tumor cells and remodeling the immune microenvironment, it still faces challenges such as complex in vitro preparation processes and low in vivo targeting and delivery efficiency. Therefore, developing strategies for efficient and targeted in vivo delivery of CAR genes has become crucial for overcoming current therapeutic limitations. This study aims to develop an orally administrable nano-gene delivery system for the targeted delivery of CAR genes to pancreatic tumor sites. MethodsCore nano-gene particles (PNP/pCAR) were constructed by loading plasmid DNA encoding CAR (pCAR) with cationic polypeptides (PNP). Subsequently, PNP/pCAR was surface-modified with β-glucan to prepare the targeted nanoparticles (βGlus-PNP/pCAR). The loading efficiency of PNP for pCAR was quantitatively assessed by gel retardation assay. The particle size, Zeta potential, morphology, and storage stability of PNP/pCAR were characterized using a Malvern particle size analyzer and transmission electron microscopy. At the cellular level, RAW 264.7 macrophages were selected. The cytotoxicity of PNP/pCAR was evaluated using the CCK-8 assay. The cellular uptake efficiency and lysosomal escape ability of the nanoparticles were assessed via flow cytometry and confocal microscopy. Transfection efficiency was quantitatively evaluated by detecting the expression of the reporter gene GFP using flow cytometry. At the in vivo level, an orthotopic pancreatic cancer mouse model was established. Cy7-labeled βGlus-PNP/pCAR nanoparticles were administered orally, and the fluorescence distribution in mice was dynamically monitored at 1, 2, 4, 8, and 16 h post-administration using a small animal in vivo imaging system. Forty-eight hours after oral gavage, the mice were euthanized, and pancreatic tumor tissues were collected for further analysis of intratumoral fluorescence signals using the imaging system. Additionally, βGlus-PNP/pCAR-GFP nanoparticles loaded with the reporter gene (GFP) were administered orally. Forty-eight hours post-administration, pancreatic tumor tissues were harvested to prepare frozen sections, and GFP expression was observed and analyzed under a fluorescence microscope. ResultsThe PNP carrier exhibited a high loading capacity for pCAR. The successfully prepared PNP/pCAR nanoparticles were regular spheres with a hydrodynamic diameter of approximately (120±10) nm and a Zeta potential of about +(6±1) mV. They maintained good structural stability after incubation in PBS buffer for 7 d. Cell experiments demonstrated that PNP/pCAR exhibited no significant cytotoxicity in RAW 264.7 cells while being efficiently internalized and effectively escaping lysosomal degradation. The transfection positive rate of PNP/pCAR-GFP in RAW 264.7 cells reached (25±3)%, surpassing that of Lipofectamine 2000-loaded pCAR-GFP (Lipo/pCAR-GFP), which was (20±1)%.In vivo experiments revealed that, compared to unmodified PNP/pCAR, βGlus-PNP/pCAR exhibited strongerin situ pancreatic tumor targeting ability after oral administration. Furthermore, oral administration of βGlus-PNP/pCAR-GFP resulted in significant GFP protein expression detectable within pancreatic tumor tissues. ConclusionThis study successfully constructed and validated an orally administrable, pancreatic cancer-targeting polypeptide-based nano-gene delivery system. It provides an important technological foundation in delivery systems and experimental basis for the subsequent development of in situ CAR-M-based therapeutic strategies for pancreatic cancer.

Objective To investigate the role and regulatory mechanism of LINC00657 in the progression of cervical cancer. Methods Bioinformatics analysis predicted potential binding sites between LINC00657 and miR-30a-5p and between miR-30a-5p and Skp2. These sites were verified by using RNA immunoprecipitation and dual-luciferase reporter experiments. LINC00657, miR-30a-5p, and Skp2 mRNA expression levels in cervical cancer tissues and cell lines were assessed by utilizing RT-qPCR. Western blot analysis was employed to examine the protein levels of Skp2 in cells and subcutaneous xenograft tumor models in nude mice. Immunohistochemistry was applied to analyze Skp2 expression in animal tissues. The cellular processes of cervical cancer cell lines were evaluated through CCK-8, scratch, and Transwell assays. Results LINC00657 and Skp2 presented binding sites for miR-30a-5p. In cervical cancer, LINC00657 and Skp2 showed high expression levels (P<0.05), whereas miR-30a-5p displayed low expression (P<0.05). Functional experiments demonstrated that linc00657 upregulates Skp2 expression, a process that is dependent on its sequestration of miR-30a-5p. Conclusion LINC00657 promoted the malignant progression of cervical cancer by upregulating Skp2 expression through specifically sequestering miR-30a-5p, thereby relieving its inhibitory effect on the target gene Skp2.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE: To observe the clinical efficacy and safety of automatic pressure-controlled pressure cupping in patients with lumbar disc herniation, and compare it with traditional cupping. METHODS: A total of 100 patients diagnosed with lumbar disc herniation from January 2022 to August 2024 were selected and divided into two groups:the automatic pressure-controlled pressure cupping group (controlled pressure cupping group) and the traditional cupping group (control group), 50 cases in each group. In the controlled pressure cupping group, there were 18 males and 32 females, with an age of (51.98±12.69) years;in the control group, there were 16 males and 34 females, with an age of (51.32±12.05) years. The visual analogue scale(VAS), comfort score, and lumbar range of motion were observed before treatment and after the 1st, 3rd, and 7th treatments to evaluate the efficacy and safety. RESULTS: All patients completed the treatment intervention, with complete follow-up data collected. No adverse reactions or complications occurred during treatment and follow-up. After the 3rd treatment, the VAS score of the controlled pressure cupping group was (2.38±0.49), which was lower than that of the control group (2.94±0.68), with a statistically significant difference (P<0.001). In the controlled pressure cupping group, the VAS scores after the 1st, 3rd, and 7th treatments were significantly better than those before treatment (P=0.026);in the control group, the VAS scores after the 3rd and 7th treatments were better than those before treatment, but the difference was not statistically significant(P=0.182). Repeated-measures analysis of variance (ANOVA) on VAS scores at different time points in both groups showed that there were statistically significant differences in inter-group, time, and interaction effects (P<0.05). After the 1st treatment, in the controlled pressure cupping group, 0 patients felt comfortable, 42 patients (84%) felt mild discomfort, and 8 patients (16%) felt moderate discomfort;in the control group, 0 patients felt comfortable, 28 patients (56%) felt mild discomfort, and 22 patients(44%) felt moderate discomfort;the difference between the two groups was statistically significant(P=0.005). After the 3rd treatment, in the controlled pressure cupping group, 30 patients(60%) felt comfortable, 20 patients (40%) felt mild discomfort, and 0 patients felt moderate discomfort; in the control group, 9 patients (18%) felt comfortable, 41 patients (82%) felt mild discomfort, and 0 patients felt moderate discomfort;the difference between the two groups was statistically significant(P<0.001). There was no statistically significant difference in comfort between the two groups after the 7th treatment(P>0.001). There was no statistically significant difference in lumbar range of motion between the two groups before and after treatment(P>0.05);compared with before treatment, the lumbar range of motion of both groups after treatment was significantly improved, with statistically significant differences (P<0.001). CONCLUSION Automatic pressure-controlled pressure cupping can effectively relieve symptoms in patients with lumbar disc herniation, with excellent safety.
Humans ; Female ; Male ; Intervertebral Disc Displacement/physiopathology* ; Middle Aged ; Adult ; Lumbar Vertebrae/physiopathology* ; Cupping Therapy/methods* ; Pressure ; Aged ; Treatment Outcome

OBJECTIVES: To analyze the potential causal relationship between gut microbiota and food allergy (FA) using two-sample Mendelian randomization (MR) methods. METHODS: Data from genome-wide association studies on gut microbiota and FA were utilized. MR analysis was conducted employing inverse variance weighting, MR-Egger regression, and weighted median methods to assess the causal relationship between gut microbiota and FA. Cochrane's Q test was used to evaluate heterogeneity of instrumental variables, MR-PRESSO analysis was conducted to test for outliers and pleiotropy, and MR-Egger regression was employed to assess horizontal pleiotropy. The "leave-one-out" method was used to evaluate the impact of removing individual single nucleotide polymorphisms on the causal relationship. RESULTS: Inverse variance weighting analysis revealed that the phylum Verrucomicrobia, family Verrucomicrobiaceae, order Verrucomicrobiales, genus Ruminococcaceae UCG013, and genus Akkermansia were negatively associated with FA (P<0.05). Sensitivity analyses confirmed the reliability of the findings, indicating no heterogeneity or pleiotropy present. CONCLUSIONS There is a causal relationship between gut microbiota and FA, with Verrucomicrobia, Verrucomicrobiaceae, Verrucomicrobiales, Ruminococcaceae UCG013, and Akkermansia potentially reducing the risk of developing FA. These findings provide potential targets for the treatment and prevention of FA; however, further research is needed to explore the specific mechanisms by which the microbiota influence FA.
Humans ; Mendelian Randomization Analysis ; Gastrointestinal Microbiome ; Food Hypersensitivity/microbiology* ; Genome-Wide Association Study ; Polymorphism, Single Nucleotide

OBJECTIVE: To explore and verify the effect and potential mechanism of Brucea javanica Seed Oil Emulsion Injection (YDZI) and Shengmai Injection (SMI) on peripheral microcirculation dysfunction in treatment of gastric cancer (GC). METHODS: The potential mechanisms of YDZI and SMI were explored through network pharmacology and verified by cellular and clinical experiments. Human microvascular endothelial cells (HMECs) were cultured for quantitative real-time polymerase chain reaction, Western blot analysis, and human umbilical vein endothelial cells (HUVECs) were cultured for tube formation assay. Twenty healthy volunteers and 97 patients with GC were enrolled. Patients were divided into surgical resection, surgical resection with chemotherapy, and surgical resection with chemotherapy combining YDZI and SMI groups. Forearm skin blood perfusion was measured and recorded by laser speckle contrast imaging coupled with post-occlusive reactive hyperemia. Cutaneous vascular conductance and microvascular reactivity parameters were calculated and compared across the groups. RESULTS: After network pharmacology analysis, 4 ingredients, 82 active compounds, and 92 related genes in YDZI and SMI were screened out. β-Sitosterol, an active ingredient and intersection compound of YDZI and SMI, upregulated the expression of vascular endothelial growth factor A (VEGFA) and prostaglandin-endoperoxide synthase 2 (PTGS2, P<0.01), downregulated the expression of caspase 9 (CASP9) and estrogen receptor 1 (ESR1, P<0.01) in HMECs under oxaliplatin stimulation, and promoted tube formation through VEGFA. Chemotherapy significantly impaired the microvascular reactivity in GC patients, whereas YDZI and SMI ameliorated this injury (P<0.05 or P<0.01). CONCLUSIONS YDZI and SMI ameliorated peripheral microvascular reactivity in GC patients. β-Sitosterol may improve peripheral microcirculation by regulating VEGFA, PTGS2, ESR1, and CASP9.
Humans ; Microcirculation/drug effects* ; Drugs, Chinese Herbal/administration & dosage* ; Stomach Neoplasms/physiopathology* ; Emulsions ; Male ; Plant Oils/administration & dosage* ; Brucea/chemistry* ; Middle Aged ; Female ; Drug Combinations ; Human Umbilical Vein Endothelial Cells/metabolism* ; Seeds/chemistry* ; Injections ; Vascular Endothelial Growth Factor A/metabolism* ; Aged ; Network Pharmacology

AIM To investigate the effects of Qifu Yixin Granules on cardiac inflammation in a rat model of heart failure.METHODS The rats were induced into chronic heart failure(CHF)models by 6-week intraperitoneal injection of doxorubicin followed by the random assignment of the successful rat models into the model group,the captopril group(22.5 mg/kg),and the low-dose,medium-dose,and high-dose Qifu Yixin Granules groups(2.84,5.67,11.34 g/kg),in contrast to the normal rats of the blank group.The rats had their body weight monitored;their cardiac function assessed by echocardiography;their serum levels of NT-proBNP,TNF-α,IL-6,IL-1 and CRP measured by ELISA;their cardiac morphological alterations observed by HE and Masson staining;their cardiac protein expressions of TLR4,MyD88 and NF-κB detected by immunohistochemistry and Western blot;and their cardiac mRNA expressions of TLR4,MyD88 and NF-κB measured by RT-qPCR.RESULTS Compared to the blank group,the model group exhibited significantly reduced body weight,LVEF and LVFS(P＜0.01),alongside significantly elevated LVEDD,LVESD,and serum concentrations of NT-proBNP,TNF-α,IL-6,IL-1 and CRP(P＜0.01).Additionally,the model group displayed greater myocardial inflammatory cell aggregation,increased collagen deposition(P＜0.01);and upregulated myocardial protein and mRNA expressions of TLR4,MyD88 and NF-κB(P＜0.01).Compared to the model group,the groups intervened with captopril or medium/high dose Qifu Yixin Granules demonstrated significantly increased body weight,LVEF and LVFS(P＜0.05,P＜0.01);significantly reduced LVEDD,LVESD,and serum levels of the aforementioned indicators(P＜0.05,P＜0.01);mitigated inflammation and collagen deposition(P＜0.05,P＜0.01);and downregulated myocardial protein and mRNA expressions of TLR4,MyD88 and NF-κB(P＜0.05,P＜0.01).CONCLUSION Qifu Yixin Granules attenuate cardiac inflammation and improve cardiac function in doxorubicin-induced CHF rats;this therapeutic effect is mediated by inhibiting the activation of the TLR4/MyD88/NF-κB signaling pathway.

Myxedema coma is a rare condition, typically arising from long-standing, untreated hypothyroidism and triggered by factors such as infection, hypothermia, or severe illness. This report details a successfully treated case of myxedema coma with cardiac attest, accompanied by a literature review, to enhance clinical awareness and improve the diagnosis and management of this critical condition.