Objective To investigate the temporal changes in pathological damage and macrophage polarization in liver and spleen tissues of mice infected with Angiostrongylus cantonensis, and to preliminarily unravel the peripheral immune responses during the early stage of A. cantonensis infection. Methods Forty female BALB/c mice at ages of 6 to 8 weeks were randomly divided into four groups, including the control group and 7-, 14-, and 21-day infection groups, with 10 mice in each group. Each mouse in the infection groups was inoculated with 30 third-stage (L3) larvae of A. cantonensis by oral gavage, and five mice were randomly selected from each infection group on days 7, 14, and 21 post-infection, while mice in the control group were given the same volume of physiological saline and five mice were randomly selected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled. The histopathological changes of mouse liver and spleen tissues were observed using hematoxylin and eosin (HE) staining, and the percentage of positive staining area and the co-localization positive rates of the macrophage surface antigens F4/80, CD86, and CD206 were quantified in mouse liver and spleen tissues using immunohistochemical and immunofluorescence staining. In addition, five mice were collected from each infection group on days 7, 14, and 21 post-infection, and five mice were collected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled for detection of macrophage markers CD86 and CD206 and macrophage phenotyping using flow cytometry, and the expression of M1 macrophage markers, including inducible nitric oxide synthase (Nos2), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and M2 markers, including arginase 1 (Arg1), mannose receptor C-type 1 (Mrc1) and chitinase-like protein 3 (Chil3) was quantified in mouse liver and spleen tissues using real-time quantitative PCR (RT-qPCR) assay. Results Proliferative lesions of the hepatocyte were observed in mouse liver tissues and the follicular structures of the mouse spleen white pulp were disrupted 21 days post-infection with A. cantonensis. Immunohistochemical staining showed that there were significant differences in the percentages of F4/80, CD86 and CD206 positive staining areas in the liver and spleen tissues among the four groups of mice (F = 242.40, 197.14, 183.19, 157.65, 242.35 and 146.24; all P values < 0.001), and the percentages of positive staining in the liver and spleen tissues of mice in the 14-day infection group [(4.45 ± 0.51)%, (3.74 ± 0.67)%, (8.32 ± 0.72)%, (16.56 ± 1.14)%, (11.62 ± 0.52)%, and (8.29 ± 0.72)%, respectively] and the 21-day infection group [(3.70 ± 0.11)%, (3.22 ± 0.43)%, (11.53 ± 1.03)%, (12.59 ± 1.05)%, (9.02 ± 0.83)%, and (11.67 ± 1.10)%, respectively] were higher than in the control group [(0.35 ± 0.16)%, (0.40 ± 0.02)%, (0.93 ± 0.05)%, (2.78 ± 0.26)%, (2.33 ± 0.20)%, and (1.85 ± 0.20)%, respectively] (all P values < 0.05). Immunofluorescence staining showed significant differences in the positive rates of F4/80 co-localization with CD86 and CD206 in mouse liver and spleen tissues among the four groups (F = 24.42, 25.28, 54.51 and 130.55; all P values < 0.001). Flow cytometry detected significant differences in the proportions of CD86⁺ and CD206⁺ macrophages in mouse liver and spleen tissues among the four groups (F = 67.98, 18.41, 29.77, 172.80; all P values < 0.001), and the proportions of CD206⁺ macrophages in the liver and spleen of the 21-day infection group were significantly higher than those in the control group [(9.25 ± 2.55)% vs (3.83 ± 0.72)%, and (4.22 ± 0.56)% vs (0.47 ± 0.18)%, respectively] (both P values < 0.05). In addition, RT-qPCR assay quantified significant differences in the relative mRNA expression of M1 macrophage markers (IL-1β, TNF-α and Nos2) and M2 macrophage markers (Arg1, Chil3 and Mrc1) in mouse liver and spleen tissues among the four groups (F = 41.30, 31.82, 199.33, 19.96, 62.01, 119.76, 23.67, 95.90, 72.27, 82.59, 123.41 and 29.75; all P values < 0.05). Conclusions A. cantonensis infection may cause progressive pathological damage in mouse liver and spleen tissues, accompanied by dynamic temporal changes in macrophage polarization. M1 macrophage polarization predominates at the early stage of A. cantonensis infection and shifts towards M2 polarization at the later stages, suggesting that M2 polarization may participate in immune regulation at late stages of A. cantonensis infection by suppressing excessive inflammatory responses and promoting tissue repair.

Objective This study conducted molecular biological identification of the viruses carried by Culex pipiens pallens specimens collected in Shunyi District, Beijing in 2023, and observed the changes in the infection rate of the viruses carried by Cx. pipiens pallens at different collection times. Methods Cx. pipiens pallens were collected using carbon dioxide mosquito traps. The mosquito samples were ground in batches and analyzed by molecular biology technologies. The virus infection rate at different collection times was analyzed statistically. Results 17 strains of Culex pipiens pallens densovirus(CppDNV)were identified from Cx. pipiens pallens samples collected in Shunyi District, Beijing, in 2023. The nucleotide sequence analysis of the virus genome coding region showed that CppDNV was a single-stranded DNA virus with a total length of 3 335 nt, encoding 2 non-structural proteins(NS1, NS2)and 1 capsid protein(VP). The nucleotide(amino acid)sequence lengths of the three proteins were 2 376 nt(791 aa),1 092 nt(363 aa)and 1 071 nt(356 aa), respectively. Phylogenetic analysis showed that CppDNV was located in genus Brevihamaparvovirus. Statistical analysis showed no significant difference in infection rates across collection times(χ2=4.429, P=0.194). Conclusions CppDNV was identified in Cx. pipiens pallens in Beijing, and it was stably maintained in this natural population.

OBJECTIVE To optimize the prescription pre-review system in our hospital and evaluate its application effects. METHODS Aiming at the problems of imperfect rule base and high false positive rate in the early operation of the system， optimization measures were taken， including improving the content of the rule base， adjusting the interception level and prompt mode， refining the working model of prescription review pharmacists， and strengthening clinical communication. A retrospective cohort study was conducted， with prescription data from June to December 2023 （before optimization） as the control group and June to December 2024 （after optimization） as the observation group. Through inter group comparative analysis， the actual effect of optimizing the prescription pre-approval system was evaluated. RESULTS The prescription qualified rate increased from （82.51± 4.04）% before optimization to （90.98±1.55）% after optimization； the false positive rate decreased from （20.87±1.64）% before optimization to （7.41±2.04）% after optimization. The monthly range of prescription qualified rate narrowed from 10.24% to 4.11%， and the coefficient of variation decreased from 4.92% to 1.73%. The monthly range of false positive rate slightly increased from 4.40% to 5.34%， the coefficient of variation rose from 8.32% to 26.18%. CONCLUSIONS Through multi-dimensional optimizations of the prescription pre-review system in our hospital， its prescription review efficiency has been significantly enhanced， the quality of prescriptions has steadily improved， and the accuracy of reviews has notably improved.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLs), are essential in establishing and maintaining brain circuits. Autophagy is a conserved process that keeps the quality of organelles and proteostasis. The role of autophagy in oligodendrocyte lineage cells remains unclear. The present study shows that autophagy is required to maintain the number of OPCs/OLs and myelin integrity during brain aging. Inactivation of autophagy in oligodendrocyte lineage cells increases the number of OPCs/OLs in the developing brain while exaggerating the loss of OPCs/OLs with brain aging. Inactivation of autophagy in oligodendrocyte lineage cells impairs the turnover of myelin basic protein (MBP). It causes MBP to accumulate in the cytoplasm as multimeric aggregates and fails to be incorporated into integral myelin, which is associated with attenuated endocytic recycling. Inactivation of autophagy in oligodendrocyte lineage cells impairs myelin integrity and causes demyelination. Thus, this study shows autophagy is required to maintain myelin quality during aging by controlling the turnover of myelin components.
Animals ; Autophagy/physiology* ; Oligodendroglia/metabolism* ; Myelin Sheath/physiology* ; Aging/pathology* ; Myelin Basic Protein/metabolism* ; Cell Lineage/physiology* ; Mice ; Oligodendrocyte Precursor Cells ; Mice, Inbred C57BL ; Brain/cytology* ; Cells, Cultured ; Cell Count

The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans ; Malocclusion, Angle Class III/classification* ; Orthodontics, Corrective/methods* ; Consensus ; Child

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Image 1.