AIM: To explore the effect of dihydroquercetin on visual function in mice with form deprivation myopia based on the NOD-like receptor thermoprotein domain-related protein 3(NLRP3)inflammasome pathway.METHODS: The C57BL/6 mice were randomly divided into control group and form deprivation myopia model group, and the form deprivation myopia model group was constructed by covering the right eye with a translucent eye patch. After successful modeling, the mice in the model group of form deprivation myopia were randomly divided into model group, low-, medium- and high-dose dihydroquercetin groups, and high-dose dihydroquercetin + NLRP3 agonist group. The diopter and axial length of mice in each group were detected. The kit was used to detect the levels of superoxide dismutase(SOD)and malondialdehyde(MDA)in retinal tissue. RT-qPCR was used to detect the mRNA expressions of NLRP3, apoptosis-associated spot-like protein(ASC), Caspase-1, IL-1β and IL-18 in retinal tissues. Western blot was used to detect the expression of NLRP3, ASC, cleaved Caspase-1, IL-1β and IL-18 proteins in retinal tissues. TUNEL staining was used to detect apoptosis in retinal tissue.RESULTS: Compared with the control group, the diopter of the mice in the model group decreased, and axial length increased, and the SOD decreased whereas MDA, NLRP3, ASC, Caspase-1, IL-1β, IL-18 increased, and the rate of apoptosis in retinal tissue increased(all P<0.05). Compared with the model group, the diopter of mice in the low-, medium- and high-dose dihydroquercetin groups increased, axial length shortened, the SOD increased, whereas MDA, NLRP3, ASC, Caspase-1, IL-1β, IL-18 decreased, and the rate of apoptosis in retinal tissue decreased(all P<0.05). Compared with the high-dose dihydroquercetin group, the high-dose dihydroquercetin+NLRP3 agonist group had reduced diopter, increased axial length, decreased SOD levels, elevated MDA, NLRP3, ASC, Caspase-1, IL-1β, and IL-18 levels, as well as increased apoptosis rate in retinal tissue(all P<0.05).CONCLUSION: Dihydroquercetin can improve visual function in mice with form deprivation myopia by inhibiting pyroptosis and oxidative stress responses, which may be related to the suppression of NLRP3 inflammasome. NLRP3 agonists can partially mitigate the effects of high-dose dihydroquercetin on form deprivation myopia in mice.

Objectives: Hypoparathyroidism (HP) is a rare endocrine disorder caused by parathyroid hormone (PTH) defi ciency. The PTH is a candidate gene for familial isolated hypoparathyroidism (FIH). This study aimed to investigate the pathogenicity of two novel rare variants (RVs) ofPTH through in vitro functional study. Methods: Targeted next-generation sequencing was used to identify candidate gene mutations. Clinical data were retrospectively collected. Wild-type (WT) PTH was used as a template for site-directed mutagenesis to create mutant eukaryotic expression plasmids, which were transfected into cells. Treated with or without 4-phenylbu tyric acid (4-PBA), the levels of intact PTH (iPTH) and PTH (1-84) were measured by chemiluminescence, and protein expression was assessed using Western blotting. Results: Two patients carrying PTH mutations (c.154G > A: p.Val52Ile, c.270G > T: p.Leu90Phe) were identified.Patient 1, a 45-year-old male, presented with carpal and pedal numbness, muscle cramps, and low serum calcium (1.29 mmol/L). Patient 2, a 12-year-old female, had muscle twitches, convulsions, low calcium (1.50 mmol/L), and iPTH of 4 pg/mL. The iPTH or PTH (1-84) levels in the medium transfected with mutant Val52Ile and Leu90Phe PTH decreased by 31%–38%, and 51%–96% compared to WT (allP < 0.05), which were not rescued by 4-PBA. No significant changes in intracellular PTH expression were observed. Conclusions In this study, two novel RVs of PTH(Val52Ile and Leu90Phe) were identified that may impair hormone synthesis and secretion. Our study has broadened the mutation spectrum of the PTH and shed light on potential mechanisms underlying FIH.

Objective:To compare the differences in breastfeeding rates and the incidence of clinical complications in very/extremely low birth weight infants with and without the use of donor milk banks.Methods:Before and after the establishment of the donor milk bank,a total of 279 very/extremely low birth weight infants who were hospitalized in neonatal intensive care unit in a tertiary hospital in Beijing were selected.In the study,136 infants who did not receive donated breast-feeding were included in con-trol group and 143 infants who received donated breast-feeding were included in observation group.The clinical data of mothers and their infants were collected.The mother's information included gestational age,maternal comorbidities,and mode of delivery.Infant information includes gender,weight,gesta-tional age,duration of breastfeeding,total enteral feeding time,hospitalization time and incidence of complications(feeding intolerance,necrotizing enterocolitis,retinopathy of prematurity).Results:The maternal ages were(33.5±4.2)years in the observation group and(32.5±3.9)years in the con-trol group.Cesareans were performed in 95 cases(70.4％)and 81 cases(66.9％),respectively.The gestational ages of preterm infants were(29.2±2.1)weeks and(29.1±2.2)weeks,with birth weights of(1 140.5±247.1)g and(1 169.4±228.6)g,respectively.Newborn boys accounted for 72 cases(50.3％)in the observation group and 63 cases(46.3％)in the control group.No statistically significant differences were found in baseline characteristics between the two groups(all P＞0.05).After the use of donor milk banks,the rate of exclusive breastfeeding in very/low birth weight infants increased from 3.1％to 10.5％(x2=5.778,P=0.016)during hospitalization,the time to full enteral feeding was shortened from 13dto10d(Z=-4.567,P＜0.001),the first breastfeeding time was shortened from the third day of admission to the first day of admission(Z=-11.812,P＜0.001),the first breastfeeding of mother's own milk was extended from the third day of admission to the fourth day of admission(Z=-4.652,P＜0.001),and the incidence of feeding intolerance during hospitalization was reduced from 34.0％to 10.0％(x2=17.015,P＜0.001).There were no significant differences in the incidence of necrotizing enterocolitis,late-onset sepsis,retinopathy of prematurity and total length of hospital stay(P＞0.05).Conclusion:The use of donor milk bank can improve the breastfeeding rate,shorten the time to first breastfeeding,and reduce the incidence of feeding intolerance in very/extremely low birth weight infants,which provides a reference for the clinical treatment of very/extremely low birth weight infants.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective To propose a decision tree-based optimization algorithm to shorten the time spent and to improve the decision-making efficiency for medical device fault diagnosis.Methods Firstly,a binarized fault state space for medical equipment was constructed;secondly,the binarized fault state space was simplified with logical functions;finally,a greedy algorithm was applied to iterative judgment to build a decision tree for medical device fault diagnosis.The algorithm proposed was compared with the greedy algorithm,Gini coefficient method and random forest algorithm in terms of the result accuracy and time cost and the influences of fault probability distribution and time-consuming differences for the algorithms.A case study on gastric lavage machine fault diagnosis was conducted to demonstrate the algorithm.Results The algorithm proposed behaved better than the greedy algorithm,Gini coefficient method and random forest algorithm in lowered time cost and result accuracy.However,the algorithm showed a decrease in accuracy for the logarithmic distribution of the detection method's time consumption,and it was not sensitive to the changes in the failure rate distribution.The gastric lavage machine case study demonstrated that the algorithm was functionally similar to an experienced engineer.Conclusion The proposed algorithm with overall perspective effectively enhances fault judgment efficiency and facilitates rapid diagnostic decision-making in medical equipment maintenance.[Chinese Medical Equipment Journal,2025,46(5):78-83]

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective To propose a decision tree-based optimization algorithm to shorten the time spent and to improve the decision-making efficiency for medical device fault diagnosis.Methods Firstly,a binarized fault state space for medical equipment was constructed;secondly,the binarized fault state space was simplified with logical functions;finally,a greedy algorithm was applied to iterative judgment to build a decision tree for medical device fault diagnosis.The algorithm proposed was compared with the greedy algorithm,Gini coefficient method and random forest algorithm in terms of the result accuracy and time cost and the influences of fault probability distribution and time-consuming differences for the algorithms.A case study on gastric lavage machine fault diagnosis was conducted to demonstrate the algorithm.Results The algorithm proposed behaved better than the greedy algorithm,Gini coefficient method and random forest algorithm in lowered time cost and result accuracy.However,the algorithm showed a decrease in accuracy for the logarithmic distribution of the detection method's time consumption,and it was not sensitive to the changes in the failure rate distribution.The gastric lavage machine case study demonstrated that the algorithm was functionally similar to an experienced engineer.Conclusion The proposed algorithm with overall perspective effectively enhances fault judgment efficiency and facilitates rapid diagnostic decision-making in medical equipment maintenance.[Chinese Medical Equipment Journal,2025,46(5):78-83]

Aim To identify the chemical components of Angelica sinensis(AS)and explore the mechanism of AS in activating blood circulation.Methods UP-LC-Q-TOF-MS was used to identify the chemical com-ponents of AS.The changes of syndrome and patholog-ical section of heart in rats were observed.Hemody-namics and proteomics were measured.Results A to-tal of 270 compounds were identified from AS.It showed that rats of Angelica sinensis group were greatly improved such as arched back,shrugged fur,huddled up and less mobile,purplish paws and tails,whitish ear margins and nasolabial lips,reduced drinking and feed-ing,and slow response to external stimuli;mildly disor-dered myocardial fibre arrangement,myofibre arrange-ment was tighter than that of model group,myocardial fibres were narrower and close to normal,and mild oe-dema,exudation,and inflammatory cell infiltration could be seen in the surrounding area;SAP was signif-icantly lower and LVSP was significantly higher in An-gelica sinensis group(P＜0.05).Proteomics showed that 62 differential proteins were screened in Angelica sinensis group compared to model,GO function were concentrated in the extracellular matrix,cytoskeletal proteins binding and protein hydrolysis negatively regu-lated.KEGG pathway were enriched in signalling path-ways such as complement and coagulation cascades,cellular focal adhesion,leukocyte transendothelial mi-gration and chemokine signalling pathways.Conclu-sions AS probably through the expression of proteins,which modulate the signalling pathways of the comple-ment and coagulation cascade reactions and the con-traction of vascular smooth muscle.

Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

Objectives: Hypoparathyroidism (HP) is a rare endocrine disorder caused by parathyroid hormone (PTH) defi ciency. The PTH is a candidate gene for familial isolated hypoparathyroidism (FIH). This study aimed to investigate the pathogenicity of two novel rare variants (RVs) ofPTH through in vitro functional study. Methods: Targeted next-generation sequencing was used to identify candidate gene mutations. Clinical data were retrospectively collected. Wild-type (WT) PTH was used as a template for site-directed mutagenesis to create mutant eukaryotic expression plasmids, which were transfected into cells. Treated with or without 4-phenylbu tyric acid (4-PBA), the levels of intact PTH (iPTH) and PTH (1-84) were measured by chemiluminescence, and protein expression was assessed using Western blotting. Results: Two patients carrying PTH mutations (c.154G > A: p.Val52Ile, c.270G > T: p.Leu90Phe) were identified.Patient 1, a 45-year-old male, presented with carpal and pedal numbness, muscle cramps, and low serum calcium (1.29 mmol/L). Patient 2, a 12-year-old female, had muscle twitches, convulsions, low calcium (1.50 mmol/L), and iPTH of 4 pg/mL. The iPTH or PTH (1-84) levels in the medium transfected with mutant Val52Ile and Leu90Phe PTH decreased by 31%–38%, and 51%–96% compared to WT (allP < 0.05), which were not rescued by 4-PBA. No significant changes in intracellular PTH expression were observed. Conclusions In this study, two novel RVs of PTH(Val52Ile and Leu90Phe) were identified that may impair hormone synthesis and secretion. Our study has broadened the mutation spectrum of the PTH and shed light on potential mechanisms underlying FIH.