Objective To explore the effect of Linc00460 on the aerobic glycolysis of breast cancer (BC) cells through sponge adsorption of miR-320a. Methods The qRT-PCR method was used to detect Linc00460 and miR-320a expression levels in normal breast epithelial cell line MCF-10A and five BC cell lines. The effect of interfering Linc00460 on miR-320a expression was detected by qRT-PCR. The double luciferase reporter gene experiment was used to analyze the targeting relationship between miR-320a and Linc00460. In addition, the si-Linc00460 and miR-320a inhibitor were co-transfected into MDA-MB-231 cells, and the expression level of miR-320a in the cells was detected by qRT-PCR; cell proliferation ability was measured by the MTT method; glucose uptake rate was detected by 2-NBDG method; the content of lactic acid in the cell supernatant was detected by colorimetric method; the key enzymes of glycolysis was detected by the enzyme activity kit; and the expression levels of the key proteins in the glycolysis pathway were detected by Western blot. Results Linc00460 was highly expressed in five BC cell lines, while miR-320a was lowly expressed as compared with MCF-10A cells. The expression of miR-320a in MDA-MB-231 cells significantly increased after interfering with Linc00460. The double luciferase reporter gene experiment confirmed that miR-320a and Linc00460 could target binding. Interfering with the expression of Linc00460 could inhibit MDA-MB-231 cells proliferation (all P=0.000), reduce the rate of cellular glucose uptake and the content of lactic acid in the cell supernatant (all P=0.000), inhibit the activities of PFK, PK, and LDH enzymes (all P=0.000), and downregulate the protein expression levels of PFKM, GLUT1, and LDHA (all P=0.000). Meanwhile, inhibition of miR-320a could reverse the inhibitory effect of si-Linc00460 on the proliferation and glycolysis of MDA-MB-231 cells (all P=0.000 or 0.001). Conclusion Linc00460 might adsorb miR-320a, consequently leading to upregulation of PFKM expression, thereby promoting aerobic glycolysis in BC cells.

Objective To investigate the association between recurrent low back pain(RLBP)and postoperative weight gain(PWG)after recurrent low back pain(TLIF)at three-month follow-up.Methods We analyzed 254 patients at three-month after TLIF from September 2020 to September 2022.Data such as age,gender,height and weight before surgery,smoking status,Pfirrmann grade of preoperative intervertebral disc degeneration,visual analogue scale(VAS)before surgery and 7 days,1 month and 2 months after surgery were collected.RLBP was defined for patients with low back pain with VAS score ≤3 on the 7th,1st and 2nd month after surgery,but ≥4 on the 3rd month after surgery.Three months after surgery,PWG was divided into 4 groups:＜0 kg group,0～＜5 kg group,5～＜10 kg group,and ≥10 kg group.Multivariate Logistic regression analysis of odds ratio(ORs).Results The prevalence of persistent RLBP was 18.5％(n=47).Compared to patients with a PWG of＜0 kg,patients with a PWG of 5 kg to＜10 kg and ≥ 10 kg had a higher prevalence of RLBP(OR=2.48 and 4.19,respectively);the difference was statistically significant(P＜0.05).However,no significant difference was found for patients with a PWG of 0 kg to＜5 kg.In addition,Logistic regression analysis also showed female,higher preoperative body mass index(BMI)and higher preoperative Pfirrmann grade were other three independent risk factors of RLBP.Conclusion PWG in TLIF patients is one of the independent risk factors for RLBP.Postoperative weight intervention for patients can reduce the incidence of RLBP and improve patient satisfaction with the surgery.

Objective:To study a deep learning-based dual-modality fundus camera which was used to study retinal blood oxygen saturation and vascular morphology changes in eyes with branch retinal vein occlusion (BRVO).Methods:A prospective study. From May to October 2020, 31 patients (31 eyes) of BRVO (BRVO group) and 20 healthy volunteers (20 eyes) with matched gender and age (control group) were included in the study. Among 31 patients (31 eyes) in BRVO group, 20 patients (20 eyes) received one intravitreal injection of anti-vascular endothelial growth factor drugs before, and 11 patients (11 eyes) did not receive any treatment. They were divided into treatment group and untreated group accordingly. Retinal images were collected with a dual-modality fundus camera; arterial and vein segments were segmented in the macular region of interest (MROI) using deep learning; the optical density ratio was used to calculate retinal blood oxygen saturation (SO 2) on the affected and non-involved sides of the eyes in the control group and patients in the BRVO group, and calculated the diameter, curvature, fractal dimension and density of arteriovenous in MROI. Quantitative data were compared between groups using one-way analysis of variance. Results:There was a statistically significant difference in arterial SO 2 (SO 2 -A) in the MROI between the affected eyes, the fellow eyes in the BRVO group and the control group ( F=4.925, P<0.001), but there was no difference in the venous SO 2 (SO 2-V) ( F=0.607, P=0.178). Compared with the control group, the SO 2-A in the MROI of the affected side and the non-involved side of the untreated group was increased, and the difference was statistically significant ( F=4.925, P=0.012); there was no significant difference in SO 2-V ( F=0.607, P=0.550). There was no significant difference in SO 2-A and SO 2-V in the MROI between the affected side, the non-involved side in the treatment group and the control group ( F=0.159, 1.701; P=0.854, 0.197). There was no significant difference in SO 2-A and SO 2-V in MROI between the affected side of the treatment group, the untreated group and the control group ( F=2.553, 0.265; P=0.088, 0.546). The ophthalmic artery diameter, arterial curvature, arterial fractal dimension, vein fractal dimension, arterial density, and vein density were compared in the untreated group, the treatment group, and the control group, and the differences were statistically significant ( F=3.527, 3.322, 7.251, 26.128, 4.782, 5.612; P=0.047, 0.044, 0.002, <0.001, 0.013, 0.006); there was no significant difference in vein diameter and vein curvature ( F=2.132, 1.199; P=0.143, 0.321). Conclusion:Arterial SO 2 in BRVO patients is higher than that in healthy eyes, it decreases after anti-anti-vascular endothelial growth factor drugs treatment, SO 2-V is unchanged.

Objective: To investigate the anatomical features of the safe zone for sacral lateral mass screw placement and find the safe trajectory, so as to provide reference for clinical application. Methods: The three-dimensional computed tomography scan materials of sacrococcygeal vertebrae in 60 patients admitted to the Liaocheng People's Hospital of Shandong Province were analyzed by Mimics software to establish three-dimensional models. There were 33 males and 27 females, aged 25-78 years, with an average age of 45.7 years. After the safe zone was separated from sacral lateral mass model, a maximum cylinder was placed into the safe zone according to its anatomical feature. The cylinder was established as safe trajectory. Anatomical data were measured, including the length and diameter of screw trajectory, the distance between the entry point and the middle jaw, and adjacent upper and lower foramen, as well as the intersection angle between the screw direction and sagittal plane, between the screw direction and the adjacent upper end plate. Results: The restriction factor of screw size on S₁, S₂ lateral mass was transverse diameter, while the restriction factor on S₃, S₄ was the distance between adjacent intervertebral foramen. The maximal length of screw from S₁ to S₄ was 30 mm, 35 mm, 30 mm, 14 mm respectively, while the maximal diameter was 12 mm, 9 mm, 5 mm, 5 mm respectively. The best entry point of S₁ mass screw was lateral to the zygopophysis. The best entry point of S₂-S₄ mass screw was located at the midpoint of a line connecting the lateral edge of adjacent posterior sacral foramen approximately about 2 cm from median sacral crest. The leaning angles of screw was increased successively, and the sagittal plane was slightly inclined. There were significant differences between male and female groups in the leaning angle in S₂ [male: (35.8±1.2)°, female: (37.9±3.7)°] and the distance between entry point and median sacral crest [male: (20.5±1.0)mm, female: (19.1±1.4)mm](P<0.05), while there was no significant difference in other parameters (P>0.05). Conclusions Cylindrical bony channel which is feasible for screw placement can be found in the lateral mass of sacrum. Individualized measurement can provide reference for application of lateral mass screw.

Background Arsenic, cobalt, barium, and other individual metal exposure have been confirmed to be associated with the incidence of kidney stones. However, there are few studies on the association between mixed metal exposure and kidney stones, especially in occupational groups. Objective To investigate the association between mixed metal exposure and kidney stones in an occupational population from a metal smelting plant. Methods A questionnaire survey was conducted to collect sociodemographic characteristics, medical history, and lifestyle information of 1158 mixed metal-exposed workers in a metal smelting plant in Guangdong Province from July 2021 to January 2022. Midstream morning urine samples were collected from the workers, the concentrations of 18 metals including lithium, vanadium, chromium, manganese, cobalt, nickel, copper, zinc, arsenic, selenium, strontium, molybdenum, cadmium, cesium, barium, tungsten, titanium, and lead were measured by inductively coupled plasma mass spectrometry, and the urinary mercury levels were measured by cold atomic absorption spectroscopy. Based on predetermined inclusion criteria, a total of 919 mixed metal-exposed workers were included in the study, including 117 workers in the kidney stone group and 802 workers in the non-kidney stone group. With a detection rate of urinary metals greater than 80% as entry criterion, 16 eligible metals were finally included for further analysis. Parametric or non-parametric methods were used to compare the differences between continuous or categorical variables of the non-kidney stone group and the kidney stone group. Logistic regression models were constructed to explore the association between individual metal exposures and kidney stones. Weighted quantile sum (WQS) regression models were used to evaluate the association between mixed metal exposure and kidney stones, as well as the weights of each metal on kidney stones. Then Bayesian kernel machine regression (BKMR) models were used to explore the overall effect of mixed metal exposure on renal calculi and the potential interactions between metals. Results We found that there were significant differences in sex, age, length of service, and body mass Index (BMI) between the non-kidney stone group and the kidney stone group (P<0.05). The urinary concentrations of molybdenum and barium in the kidney stone group were higher than those in the non-kidney stone group, and the differences were statistically significant (P<0.05). The logistic regression models demonstrated that urinary cobalt, arsenic, molybdenum, and barium were positively correlated with the risk of kidney stones (P_trend<0.05). The WQS regression models showed that the mixed exposure to vanadium, cobalt, arsenic, molybdenum, and barium was positively associated with the risk of kidney stones (P<0.05). Among them, molybdenum, arsenic, and barium accounted for 0.391, 0.337, and 0.154, respectively. The BKMR results revealed a positive association between metal mixture exposure and the risk of kidney stones (P<0.05). When other metals were fixed at the 25th, 50th, or 75th percentile, arsenic, molybdenum, cobalt, and barium exhibited significant positive effects on the risk of kidney stones (P<0.05), while vanadium showed a significant negative effect (P<0.05). The interaction analysis demonstrated interactions between barium and cobalt, as well as between vanadium and cobalt (P<0.05). Conclusion In the occupational population of this smelter, occupational mixed metal exposure could increase the risk of kidney stones, and the main metals are molybdenum, arsenic, barium, and cobalt.