Objective: To assess the nutritional supply status of school meals for primary and secondary school students in Henan Province, so as to provide a basis for scientific guidance of school meals. Methods: During 2021-2023, 115 lunch and dinner samples were collected from 25 primary and secondary schools in Zhoukou, Anyang and Luoyang of Henan Province by a direct selection method, and 13 nutrients were determined for each sample. The nutrient supply was evaluated based on Nutrition Guidelines of School Meals and Reference Intake of Dietary Nutrients for Chinese Residents (2023 Edition). Mann-Whitney U test was used to compare the differences of nutritional supply between urban and rural schools. Results: The median values for energy (709.77 kcal,1 kcal=4.18 kJ), fat energy supply ratio (0.27) and carbohydrate energy supply ratio (0.55) in the 66 lunches and dinners from primary school were within the recommended range. The supply of protein (28.39 g) and sodium (1 464.59 mg) was excessive. The median values of zinc (2.62 mg) and dietary fiber (5.19 g) were lower than the reference values. No statistically significant differences were observed in the supply of 13 nutrients between urban and rural primary schools( U = 427.00 -633.00, P > 0.05 ). Among 49 samples from secondary schools, the median value of energy supply (930.02 kcal), carbohydrate energy ratio ( 0.54 ) and fat energy supply ratio(0.25) were within the recommended range; and the median values of protein (38.82 g) and sodium (2 556.80 mg) were higher than the standard; and the median values of calcium (250.32 mg) and vitamin B1 (0.16 mg) were lower than the standard. Additionally, the differences in the level of vitamin B2 ( U =372.00) and zinc ( U =375.00) between the urban and rural secondary schools were statistically significant ( P <0.05). Conclusion Nutrient supply of primary and secondary school meals in three cities of Henan Province is inadequate and imbalanced, and the recipe need to be further optimized and improved.

OBJECTIVE: To observe the effects of antagonistic needling therapy on lower limb spasticity and the muscle morphology of the tibialis anterior and gastrocnemius in patients with stroke. METHODS: A total of 100 patients with post-stroke lower limb spasticity were randomly divided into an antagonistic needling group (50 cases, 1 case dropped out) and a routine acupuncture group (50 cases, 1 case dropped out). Both groups received basic treatment and rehabilitation training. The routine acupuncture group was treated with scalp acupuncture at anterior oblique line of vertex-temporal and vertex lateral line 1, combined with body acupuncture at Jianyu (LI15), Hegu (LI4), Zusanli (ST36), Taichong (LR3), etc. on the affected side, with Quchi (LI11) and Hegu (LI4), Zusanli (ST36) and Fenglong (ST40), Yanglingquan (GB34) and Taichong (LR3) connected to an electroacupuncture device, using disperse wave at 2 Hz of frequency. The antagonistic needling group used the same scalp and upper limb acupoints as the routine acupuncture group, with additional antagonistic needling on the lower limb at Yanglingquan (GB34), Qiuxu (GB40), Jiexi (ST41), and Xuanzhong (GB39) on the affected side, with Quchi (LI11) and Hegu (LI4), Yanglingquan (GB34) and Qiuxu (GB40), Jiexi (ST41), and Xuanzhong (GB39) connected to an electroacupuncture device, using disperse wave at 2 Hz of frequency. Both groups received treatment once daily for 6 consecutive days per course, with a total of 4 courses. The modified Ashworth scale (MAS), Holden functional ambulation classification (FAC), lower limb Fugl-Meyer assessment (FMA), composite spasticity scale (CSS), and musculoskeletal ultrasound parameters (thickness and fiber length of the tibialis anterior and gastrocnemius, and pennation angle of the gastrocnemius on both sides) were evaluated before and after treatment. Clinical efficacy was compared between the two groups. RESULTS: Compared before treatment, the MAS grades and CSS scores were decreased in both groups after treatment (P<0.01), with greater reductions in the antagonistic needling group (P<0.05, P<0.01). FAC grades and FMA scores were increased in both groups after treatment (P<0.01, P<0.05), with greater improvements in the antagonistic needling group (P<0.05). The muscle thickness, fiber length of the tibialis anterior, the muscle thickness, fiber length and pennation angle of the gastrocnemius on the affected side were improved in both groups after treatment (P<0.01), with greater improvements in the antagonistic needling group (P<0.01, P<0.05). On the unaffected side, these parameters were also increased after treatment in both groups (P<0.01, P<0.05), but the antagonistic needling group showed smaller increases than the routine acupuncture group (P<0.01, P<0.05). The total effective rate in the antagonistic needling group was 91.8% (45/49), higher than 81.6% (40/49) in the routine acupuncture group (P<0.05). CONCLUSION Antagonistic needling could effectively reduce spasticity, improve motor function, and enhance muscle structure in patients with post-stroke lower limb spasticity.
Humans ; Male ; Female ; Acupuncture Therapy ; Middle Aged ; Muscle Spasticity/pathology* ; Aged ; Stroke/physiopathology* ; Lower Extremity/physiopathology* ; Acupuncture Points ; Adult ; Muscle, Skeletal/pathology* ; Treatment Outcome

Neuraxial opioids, widely used in obstetric and perioperative pain management, often lead to unwanted itch, reducing patient satisfaction. While the μ-opioid receptor has been implicated in opioid-induced itch, the genetic basis for variable itch incidence remains unknown. This study examined 3616 patients receiving epidural opioids, revealing an itch occurrence of 26.55%, with variations among opioid types and gender. Analysis of the OPRM1 gene identified six single-nucleotide polymorphisms, notably rs1799971 (A118G), that correlated with opioid-induced itch. Mouse models with an equivalent A112G mutation showed reduced neuraxial opioid-induced itch and light touch-evoked itch, mirroring human findings. The 118G allele demonstrated an anti-itch effect without impacting analgesia, addiction, or tolerance, offering insights for risk stratification and potential anti-itch pretreatment strategies.
Receptors, Opioid, mu/genetics* ; Pruritus/chemically induced* ; Humans ; Analgesics, Opioid/administration & dosage* ; Female ; Male ; Animals ; Polymorphism, Single Nucleotide/genetics* ; Adult ; Mice ; Middle Aged

OBJECTIVE: To explore the feasibility of incorporating simple bedside indicators into death predictive model for elderly critically ill patients based on interpretability machine learning algorithms, providing a new scheme for clinical disease assessment. METHODS: Elderly critically ill patients aged ≥ 65 years who were hospitalized in the intensive care unit (ICU) of Tacheng People's Hospital of Ili Kazak Autonomous Prefecture from June 2017 to May 2020 were retrospectively selected. Basic parameters including demographic characteristics, basic vital signs and fluid intake and output within 24 hours after admission, as well acute physiology and chronic health evaluation II (APACHE II), Glasgow coma score (GCS) and sequential organ failure assessment (SOFA) were also collected. According to outcomes in hospital, patients were divided into survival group and death group. Four datasets were constructed respectively, namely baseline dataset (B), including age, body temperature, heart rate, pulse oxygen saturation, respiratory rate, mean arterial pressure, urine output volume, infusion volume, and crystal solution volume; B+APACHE II dataset (BA), B+GCS dataset (BG), and B+SOFA dataset (BS). Then three machine learning algorithms, Logistic regression (LR), extreme gradient boosting (XGboost) and gradient boosting decision tree (GBDT) were used to develop the corresponding mortality predictive models within four datasets. The feature importance histogram of each prediction model was drawn by SHapley additive explanation (SHAP) method. The area under curve (AUC), accuracy and F1 score of each model were compared to determine the optimal prediction model and then illuminate the nomogram. RESULTS: A total of 392 patients were collected, including 341 in the survival group and 51 in the death group. There were statistically significant differences in heart rate, pulse oxygen saturation, mean arterial pressure, infusion volume, crystal solution volume, and etiological distribution between the two groups. The top three causes of death were shock, cerebral hemorrhage, and chronic obstructive pulmonary disease. Among the 12 prognostic models trained by three machine learning algorithms, overall performance of prognostic models based on B dataset was behind, whereas the LR model trained by BA dataset achieved the best performance than others with AUC of 0.767 [95% confidence interval (95%CI) was 0.692-0.836], accuracy of 0.875 (95%CI was 0.837-0.903) and F1 score of 0.190. The top 3 variables in this model were crystal solution volume with first 24 hours, heart rate and mean arterial pressure. The nomogram of the model showed that the total score between 150 and 230 were advisable. CONCLUSION The interpretable machine learning model including simple bedside parameters combined with APACHE II score could effectively identify the risk of death in elderly patients with critically illness.
Humans ; Critical Illness ; Machine Learning ; Aged ; Algorithms ; Intensive Care Units ; Retrospective Studies ; APACHE ; Prognosis ; Organ Dysfunction Scores ; Hospital Mortality ; Male ; Female

Organoids are three-dimensional (3D) cellular structures formed through the differentiation and self-organization of pluripotent stem cells or tissue-derived cells, showing considerable potential in the research on disease mechanism, personalized medicine, and developmental biology. However, the development of organoids is limited by the complex composition, batch-to-batch variations, and immunogenicity of basement-membrane matrix in the current culture system, which hinders the clinical translation and in vivo applications of organoids. Hydrogels are highly hydrated 3D polymer network materials, with modifiable mechanical and biochemical properties by engineering, representing an ideal alternative to basement-membrane matrix. This article reviews the research progress in engineered hydrogels with defined composition currently used in organoid culture. We introduce the structural characteristics and engineering design considerations of hydrogels, emphasize the latest research progress and specific application cases, and discuss the future development of these engineered hydrogels, provide valuable insights for the further advancement and optimization of engineered hydrogels for organoid.
Hydrogels/chemistry* ; Organoids/cytology* ; Tissue Engineering/methods* ; Humans ; Animals ; Pluripotent Stem Cells/cytology* ; Cell Culture Techniques, Three Dimensional/methods* ; Tissue Scaffolds

Objective:To screen differentially expressed genes (DEGs) associated with liver cancer by bioinformatics analysis method, and to investigate the mechanism of the minichromosome maintenance protein 2 ( MCM2) and replication factor C subunit 4 ( RFC4) genes in liver cancer in vitro. Methods:Gene expression profiling data of 80 and 36 hepatocellular carcinoma tissues and 307 and 13 cirrhotic tissues were obtained from the GSE25097 and GSE98620 datasets of the gene expression analysis (GEO) database, respectively. Gene expression profiling data of 374 liver cancer tissues and 50 normal liver tissues were downloaded from the cancer genome atlas (TCGA) database. Limma and DESeqs R software were used to process the gene expression profiling data, construct protein-protein interaction networks, and analysis the relevance of these genes to survival. Weighted gene co-expression network analysis was performed to screen out the core genes. Liver cancer SMMC7721 cells were transfected with MCM2 blank plasmid (MCM2 control group), MCM2 overexpression plasmid [MCM2 WT1 group, MCM2 WT2 (2-fold WT1) group], RFC4 blank plasmid (RFC4 control group), and RFC4 overexpression plasmid [RFC4 WT1 group, RFC4 WT2 (2-fold WT1) group], respectively. The expression of MCM2 and RFC4 in liver cancer cell lines and their transfection levels were detected by real-time fluorescence quantitative reverse transcription PCR and Western blotting. The effects of MCM2 and RFC4 on the proliferation of hepatocellular carcinoma cells were detected by MTT assay and cell cloning assay, respectively. The effects of MCM2 and RFC4 on the migration of liver cancer cells were determined by the scratch assay. The effects of MCM2 and RFC4 on liver cancer cell invasion were detected by Transwell assay.Results:By bioinformatic analysis, 9 HCC DEGs were selected, including ubiquitin conjugating enzyme E2 T ( UBE2T), aurora kinase A ( AURKA), targeting protein for Xklp2 ( TPX2), MCM2, RFC4, ribonucleoside-diphosphate reductase subunit M2 ( RRM2), serine peptidase inhibitory factor Kazal type 1 ( SPINK1), collagen type XV alpha 1 chain ( COL15A1) and C-C motif chemokine 25 ( CCL25). Among the six genes associated with clinical stages, the MCM2 and RFC4 genes were found to be strongly associated with prognosis in liver cancer. The relative protein expression of MCM2 and RFC4 in HepG2 cells (1.83±0.07, 1.44±0.09) and SMMC7721 cells (1.74±0.05, 1.43±0.08) was higher than that in MIHA cells (1.00±0.02, 1.00±0.03), and all the differences were statistically significant (all P<0.05). The relative gene expression of MCM2 and RFC4 in HepG2 cells (14.30±0.12, 5.10±0.18) and SMMC7721 cells (10.60±0.11, 7.60±0.07) was higher than that in MIHA cells (1.00±0.05, 1.00±0.03), and all the differences were statistically significant (all P<0.05). Compared with the MCM2 control group, the absorbance values [(0.28±0.01 and 0.21±0.01) vs 0.18±0.03], the number of clonal cells [(717±12 and 782±29) cells vs (389±17) cells], the percentage migration [(0.43±0.02 and 0.68±0.01) vs 0.15±0.06], and the number of cellular invasions [(933±21 and 821±11) cells vs (409±16) cells] were higher in the MCM2 WT1 and MCM2 WT2 groups, and the differences were all statistically significant (all P<0.05). Compared with the RFC4 control group, the absorbance values [(0.30±0.02 and 0.21±0.01) vs 0.17±0.02], the number of cloned cells [(571±11 and 728±9) cells vs (373±23) cells], the percentage migration [(0.75±0.11 and 0.67±0.04) vs 0.34±0.07], and the number of cell invasion [(835±26 and 818±18) cells vs (629±12) cells] were higher in the RFC4 WT1 and the RFC4 WT2 groups, and the differences were statistically significant (all P<0.05). Conclusions:MCM2 and R FC4 genes play a role in promoting tumorigenesis and growth in hepatocellular carcinoma.

Objective To develop an erythrocyte-based delivery system for butyrylcholinesterase(BChE)that is capable of prophylaxis against organophosphorus nerve agents.Methods Recombinant BChE was produced and analyzed for oligomerization via polyacrylamide gel electrophoresis(PAGE)and Western blotting.A modified hypotonic preswelling method was employed to prepare BChE-loaded erythrocytes.The drug loading capacity and encapsulation efficiency were quantified using enzyme-linked immunosorbent assay(ELISA).Catalytic activity was assessed in vitro with an activity detection kit.The system was characterized via scanning electron microscopy(SEM),flow cytometry and a hematology analyzer.Results Recombinant BChE predominantly existed as dimers(85％dimer,15％monomer).The optimized volume ratio of erythrocytes to hypotonic solution was determined as 1:7.Compared with native and empty erythrocytes,BChE-loaded erythrocytes exhibited significantly higher catalytic activity(P＜0.001).The mean corpuscular volume of BChE-loaded erythrocytes increased(P＜0.001),while the mean content of corpuscular hemoglobin and hemoglobin in erythrocytes per 100 mL decreased(P＜0.001).SEM revealed no morphological differences(biconcave disc shape).Hypotonic preswelling moderately increased erythrocyte apoptosis(P＜0.001),but no statistical difference was observed between BChE-loaded and hypotonic-treated erythrocytes(P＞0.05).CD47 expression remained unchanged compared to native erythrocytes(P＞0.05).Conclusion The modified hypotonic preswelling method can generate BChE-loaded erythrocytes that retain the characteristics of native erythrocytes while conferring catalytic activity,offering a novel strategy for clinical intervention against organophosphorus poisoning.

Objective: To assess the exposure levels of lead, cadmium, mercury, arsenic and aluminum in the diets of residents in Henan Province, so as to provide the basis for strengthening food safety supervision. Methods: Six sampling points were selected using stratified random sampling method in Henan Province, including Hebi City, Xiangfu District of Kaifeng City, Jianxi District of Luoyang City, Yuzhou City, Baofeng County and Tanghe County. Food samples were collected and processed into mixed samples of 12 major food categories. The levels of lead, cadmium, mercury, arsenic and aluminum in the samples were measured using inductively coupled plasma mass spectrometry (ICP-MS). Dietary consumption information in Henan Province was collected. The dietary exposure risks of lead, cadmium, mercury, arsenic and aluminum were analyzed using the point estimation method and distribution point estimation method, based on the health guidance values of the Joint FAO/WHO Expert Committee on Food Additives and the margin of exposure (MOE) as the assessment criteria. Results: The dietary exposure level of lead among residents in Henan Province was 41.89 μg/d, which was equivalent to 18.62% of its provisional tolerable weekly intake (PTWI), with cereals and vegetables being the main sources; the MOE values of lead among residents aged 2 to <7 years and 7 to <13 years were both less than 1. The dietary exposure level of cadmium was 10.79 μg/d, which was equivalent to 20.55% of the provisional monthly tolerable intake, with cereals and vegetables being the main sources. The dietary exposure level of total mercury was 0.45 μg/d, which was equivalent to 1.25% of its PTWI, with cereals, vegetables, and water and beverage categories being the main sources; the dietary exposure level of methylmercury was 0.04 μg/d, which was equivalent to 0.28% of its PTWI, and it was entirely derived from aquatic products. The dietary exposure level of total arsenic was 26.65 μg/d, which was equivalent to 0.89% of the daily allowable intake, with cereals and vegetables being the main sources; the dietary exposure level of inorganic arsenic was 8.41 μg/d, which was equivalent to 6.23% of its PTWI, with an MOE value of 22.47. The dietary exposure level of aluminum was 8.27 mg/d, which was equivalent to 45.94% of its PTWI, with cereals and tubers being the main sources; the P90 and P97.5 of dietary aluminum exposure among residents aged 2 to <7 years and 7 to <13 years were both greater than PTWI. Conclusion The overall dietary exposure risks of lead, cadmium, mercury, arsenic and aluminum among residents in Henan Province are relatively low.

Objective To explore the protective effect in a model of nicotinamide riboside(NR)against carbonyl cyanide m-chlorophenylhydrazone(CCCP)-induced oxidative stress in R28 cells.Methods 4 μmol/L CCCP was used to induce oxidative stress in R28 cells,and 400 nmol/L NR was used to intervene.The cell viability was quantified by CCK-8 assay.The apoptosis was detected by Annexin-V/PI double staining and flow cytometry.Western blotting was used to examine the levels of Cytochrome C,Caspase-3,and Caspase-9 to evaluate the apoptosis.Tetramethylrhodamine ethyl ester was used to detect the mitochondrial membrane potential(MMP),MitoSOX was used to detect the mitochondrial reactive oxygen species(mtROS)levels,and adenosine triphosphate(ATP)assay kit was used to assess ATP generation ability to evaluate mitochondrial function.Results After CCCP treatment of R28 cells,the cell viability decreased,the apoptotic protein levels and apoptosis rates increased,the MMP decreased,and the mtROS generation increased(P＜0.05).After NR pretreatment,the cell viability increased,the apoptotic protein levels and apoptosis rates decreased,the MMP increased,and the mtROS generation decreased(P＜0.05).Conclusion:NR enhances the cell viability,reduces the expression of apoptotic proteins,and ultimately reduces the apoptosis of retinal ganglion cell by inhibiting oxidative stress response and protecting mitochondrial function.

Objective:To construct and validate a machine learning model for preoperative prediction of perineural invasion (PNI) status in intrahepatic cholangiocarcinoma (ICC).Methods:Clincial data of 329 patients, including 245 admitted to Zhengzhou University People's Hospital from January 2018 to June 2023 and 84 admitted to the Affiliated Cancer Hospital of Zhengzhou University from January 2013 to January 2020 were retrospectively analyzed. Patients were divided into a training set ( n=231) and a validation set ( n=98). Clinicopathological data including age, gender, hepatitis B virus (HBV) infection status were collected. Predictive variables were determined using least absolute shrinkage and selection operator (LASSO) regression analysis. Six machine learning algorithms including random forest (RF), logistic regression, and linear kernel-based support vector machine were selected to construct the preoperative prediction model for PNI in ICC. Performance metrics of the model were calculated using a confusion matrix, and the final model was selected. The model performance was evaluated in the validation set. Calibration curves were plotted to evaluate the final model, and a Pareto chart was used to visualize the importance of predictive variables. Results:LASSO regression identified nine predictive variables included in the prediction model, including carbohydrate antigen 19-9 (CA19-9), HBV infection status, alkaline phosphatase, alanine aminotransferase, prothrombin time, total bilirubin, albumin, neutrophil times gamma-glutamyl transferase to lymphocyte ratio, and tumor burden score. Among the trained six models, the area under the curve (AUC) of the RF model was 0.909, with a sensitivity of 0.842 and an accuracy of 0.870. Compared with the AUC of the RF model, the AUCs of the other 5 models were lower (all P<0.05). The AUC of the RF model for predicting PNI in ICC in validation set was 0.736. Calibration curves showed good fit of the RF model's prediction of PNI in ICC in both training and validation sets. The Pareto chart showed that CA19-9 was the most important predictive variable in the model, followed by HBV infection status. Conclusion:The machine learning model based on the RF algorithm has a high accuracy in preoperative prediction of PNI status in ICC.