A combination of the "disease-syndrome-symptom" approach was used to study the syndrome characterization and features of dampness-heat obstruction syndrome in papain-induced knee osteoarthritis(KOA) model rats during the disease process. Forty-eight male SD rats were randomly divided into sham and model groups. The KOA model was established by injecting a mixture of papain and L-cysteine into the joint cavity on days 1, 3, and 5. During the 8 weeks following model establishment, the rats were assessed weekly for the plantar mechanical pain threshold, knee joint diameter, local skin temperature of the knee joint, weight-bearing difference between the two hind feet, and the modified Lequesne MG score of the knee joint. Samples were collected at 1, 2, 4, 6, and 8 weeks after model establishment to observe the gross lesions in cartilage and synovium. Histopathological changes in joint tissues were examined using hematoxylin-eosin, Masson's trichrome, and Senna red O-solid green staining. ELISA and immunohistochemical analysis were performed to detect the levels of interleukin(IL)-1β, IL-6, tumor necrosis factor(TNF)-α, prostaglandin E2(PGE2), and the expression of aquaporins(AQP) 1 and 3 in serum and synovium. The results showed that the ink score of articular cartilage in the model group significantly increased from 4 to 8 weeks, the cartilage Mankin's score and the percentage of Masson-positive area in cartilage increased significantly from 1 to 8 weeks. The percentage of red-stained area for cartilage proteoglycans decreased significantly from 1 to 8 weeks. The synovitis score from 1 to 6 weeks and the percentage of blue-stained collagen fibers in the synovium from 1 to 8 weeks increased significantly, with statistically significant differences compared to the sham group. The mechanical pain threshold in the model group significantly decreased from 1 to 8 weeks, the knee joint diameter significantly increased from 1 to 6 weeks, and the local skin temperature of the knee joint, the weight-bearing difference between the two hind feet, and the modified Lequesne MG score from 1 to 5 weeks significantly increased, all with statistically significant differences compared to the sham group. The levels of IL-1β, IL-6, TNF-α, and PGE2 in serum and synovium of the model group significantly increased from 1 to 6 weeks. Serum TNF-α and PGE2, and synovial IL-1β, also significantly increased at 8 weeks. The levels of cartilage AQP1 and AQP3 significantly increased from 1 to 4 weeks, while synovial AQP1 and AQP3 increased significantly from 1 to 6 weeks, with all differences statistically significant compared to the sham group. In conclusion, papain-induced KOA rats exhibited pathological changes, including articular cartilage degeneration and synovial inflammation, within 1 week of induction. The KOA rats showed characteristics of dampness-heat obstruction syndrome, such as joint pain, swelling, elevated skin temperature, and decreased function, as well as increased inflammatory factors and AQP1、AQP3 in serum and joint tissues within 5 to 6 weeks of disease onset. These results provide an experimental model for studying the syndromes of KOA with dampness-heat obstruction syndrome.
Animals ; Male ; Rats, Sprague-Dawley ; Rats ; Osteoarthritis, Knee/physiopathology* ; Disease Models, Animal ; Humans ; Interleukin-1beta/metabolism* ; Interleukin-6/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Knee Joint/pathology*

To investigate the effects of Biyan Jiedu Capsules on the proliferation and apoptosis of nasopharyngeal carcinoma cells and their molecular mechanism, nasopharyngeal carcinoma cells CNE1 and CNE2 were used. They were divided into control group(30% blank serum medium), low-(10% drug-containing serum + 20% blank serum medium), medium-(20% drug-containing serum + 10% blank serum medium), and high-(30% drug-containing serum medium) concentration group of Biyan Jiedu Capsules according to in vitro experiment. After 24 h of intervention, the effects of Biyan Jiedu Capsules on the proliferation of CNE1 and CNE2 were detected by CCK-8 assay, clonal formation experiment, and EdU staining. The effect of Biyan Jiedu Capsules on apoptosis of CNE1 and CNE2 was detected by flow cytometry. Western blot was used to detect the effect of Biyan Jiedu Capsules on the expression of X-linked apoptosis inhibitor protein(XIAP), survivin, proliferating cell nuclear antigen(PCNA), and PI3K/Akt pathway-related proteins in CNE1 and CNE2. The results showed that compared with the control group, the survival rate of CNE1 and CNE2 in the medium and high concentration groups of Biyan Jiedu Capsules could be decreased in a concentration-dependent way(P<0.05, P<0.01). At the same time, EdU staining and clonal formation experiments showed that the proliferation of CNE1 and CNE2 was significantly inhibited in the medium and high concentration groups of Biyan Jiedu Capsules(P<0.05, P<0.01). Flow cytometry showed that the apoptosis rate of CNE1 and CNE2 was significantly increased in all concentration groups of Biyan Jiedu Capsules(P<0.01), and the apoptosis rate was concentration-dependent. Western blot showed that the expressions of XIAP, survivin, PCNA, p-PI3K, and p-Akt in all concentration groups of Biyan Jiedu Capsules were significantly down-regulated(P<0.05, P<0.01). In conclusion, Biyan Jiedu Capsules can inhibit the proliferation and induce apoptosis of nasopharyngeal carcinoma cells possibly by down-regulating the PI3K/Akt signaling pathway.
Humans ; Apoptosis/drug effects* ; Cell Proliferation/drug effects* ; Nasopharyngeal Carcinoma ; Nasopharyngeal Neoplasms/physiopathology* ; Proto-Oncogene Proteins c-akt/genetics* ; Cell Line, Tumor ; Drugs, Chinese Herbal/pharmacology* ; Phosphatidylinositol 3-Kinases/genetics* ; Signal Transduction/drug effects* ; Capsules ; Carcinoma/drug therapy*

OBJECTIVES: To evaluate and integrate evidence on the management of sleep disorders in children with attention deficit hyperactivity disorder (ADHD). METHODS: Literature was retrieved based on the 6S model, and evidence related to sleep disorder management in children with ADHD was extracted from the included references. RESULTS: A total of 17 studies were included, from which 16 pieces of evidence were extracted. Of these, 6 were classified as Level 1 evidence and 10 as Level 5. The evidence covered screening, assessment, non-pharmacological interventions, pharmacological interventions, follow-up, and multidisciplinary collaboration. CONCLUSIONS This study integrated evidence on the management of sleep disorders in children with ADHD using an evidence-based approach, providing an evidence-based foundation for managing sleep disorders in this population.
Humans ; Attention Deficit Disorder with Hyperactivity/complications* ; Sleep Wake Disorders/etiology* ; Child ; Evidence-Based Medicine

BACKGROUND: Early control of low-density lipoprotein cholesterol (LDL-C) is crucial for reducing the progress of cardiovascular disease. However, its additional role to the risk of primary osteoporosis in men with coronary heart disease was inconclusive. Our study aims to determine the association of LDL-C and its trajectories for osteoporosis risk in the middle-aged and aged men of China. METHODS: The retrospective cohort study of 1546 men aged 69.74 ± 11.30 years conducted in Beijing, China from 2015 to 2022. And the incidence of primary osteoporosis was annually recorded. LDL-C trajectories were further identified by latent class growth model using repeated measurements of LDL-C. The association of baseline LDL-C for osteoporosis was estimated using hazard ratio (HR) with 95% CI in Cox proportional hazard model, while mean level and trajectories of LDL-C for osteoporosis were evaluated using odds ratio (OR) with 95% CI in logistic regression model. RESULTS: During the median 6.2-year follow-up period, 70 men developed primary osteoporosis. The higher level of baseline LDL-C (HR = 1.539, 95% CI: 1.012-2.342) and mean LDL-C (OR = 2.190, 95% CI: 1.443-3.324) were associated with higher risk of osteoporosis in men with coronary heart disease after adjusted for covariates. Compared with those in the LDL-C trajectory of low-stable decrease, participants with medium-fluctuant trajectory, whose longitudinal LDL-C started with a medium LDL-C level and appeared an increase and then decrease, were negatively associated with osteoporosis risk (OR = 2.451, 95% CI: 1.152-5.216). And participants with initially high LDL-C level and then a rapid decrease demonstrated a tendency towards reduced risk (OR = 0.718, 95% CI: 0.212-2.437). CONCLUSIONS Elevated LDL-C level and its long-term fluctuation may increase the risk of primary osteoporosis in men. Early controlling a stable level of LDL-C is also essential for bone health.

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

Objective The volume and cortical thickness of gray matter in patients with multiple sclerosis (MS) and neuromyelitis optica (NMO) were compared and analyzed by voxel⁃based morphometry (VBM) and surface⁃based morphometry (SBM), and the differences in the structural changes of gray matter in the two diseases were discussed. Methods A total of 21 MS patients, 16 NMO patients and 19 healthy controls were scanned by routine MRI sequence. The data were processed and analyzed by VBM and SBM method based on the statistical parameter tool SPM12 of Matlab2014a platform and the small tool CAT12 under SPM12. Results Compared with the normal control group (NC), after Gaussian random field (GRF) correction, the gray matter volume in MS group was significantly reduced in left superior occipital, left cuneus, left calcarine, left precuneus, left postcentral, left central paracentral lobule, right cuneus, left middle frontal, left superior frontal and left superior medial frontal (P<0. 05). After family wise error (FWE) correction, the thickness of left paracentral, left superiorfrontal and left precuneus cortex in MS group was significantly reduced (P<0. 05). Compared with the NC group, after GRF correction, the gray matter volume in the left postcentral, left precentral, left inferior parietal, right precentral and right middle frontal in NMO group was significantly increased (P<0. 05). In NMO group, the volume of gray matter in left middle occipital, left superior occipital, left inferior temporal, right middle occipital, left superior frontal orbital, right middle cingulum, left anterior cingulum, right angular and left precuneus were significantly decreased (P<0. 05). Brain regions showed no significant differences in cortical thickness between NMO groups after FWE correction. Compared with the NMO group, after GRF correction, the gray matter volume in the right fusiform and right middle frontal in MS group was increased significantly(P<0. 05). In MS group, the gray matter volume of left thalamus, left pallidum, left precentral, left middle frontal, left middle temporal, right pallidum, left inferior parietal and right superior parietal were significantly decreased (P<0. 05). After FWE correction, the thickness of left inferiorparietal, left superiorparietal, left supramarginal, left paracentral, left superiorfrontal and left precuneus cortex in MS group decreased significantly (P<0. 05). Conclusion The atrophy of brain gray matter structure in MS patients mainly involves the left parietal region, while NMO patients are not sensitive to the change of brain gray matter structure. The significant difference in brain gray matter volume between MS patients and NMO patients is mainly located in the deep cerebral nucleus mass.

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.