OBJECTIVE To explore the improvement effect and potential mechanism of modified Yanghe decoction on bone destruction in rats with breast cancer bone metastasis based on the receptor-interacting serine/threonine-protein kinase 1 （RIPK1）/RIPK3 pathway. METHODS The rat model of breast cancer bone metastasis was established by injecting a suspension of breast cancer cells into the bone marrow cavity. The rats with successful modeling were randomly divided into a model group （intragastric administration of equal volume of normal saline）， modified Yanghe decoction low-， medium-， and high-dose groups （intragastric administration of corresponding decoction at 1.30， 2.60 and 5.20 g/kg， calculated by the dosage of crude drug）， high-dose modified Yanghe decoction+si-RIPK1 group （intragastric administration of corresponding decoction at 5.20 g/kg， calculated by the dosage of crude drug； simultaneous injection of small interfering RNA for RIPK1 via the tail vein）， and high-dose modified Yanghe decoction+si-NC group （intragastric administration of corresponding decoction at 5.20 g/kg， calculated by the dosage of crude drug； simultaneous injection of small interfering RNA for negative control via the tail vein）， with 12 rats in each group. Another 12 healthy rats were selected as the control group and were given the same volume of normal saline intragastrically， once a day， for 14 consecutive days. Body weight was measured before administration and at the end of the last administration. The mechanical pain threshold and thermal pain threshold were measured， and the bone destruction， pathological changes and osteoclast formation of the tibia were observed. The positive expression of receptor activator of nuclear factor-κB （RANK） and receptor activator of nuclear factor-κB ligand （RANKL） in the tibial tissue， as well as the phosphorylation levels of RIPK1， RIPK3 and mixed lineage kinase domain-like protein （MLKL） were detected. RESULTS Compared with the control group， the tumor cells of tibia tissues in rats of the model group showed significant proliferation and diffuse infiltration into the bone marrow cavity. Extensive areas of tumor necrosis of cells， severe bone destruction， thinning of the bone cortex， and damage to the bone trabeculae were observed. The body weight （before administration and at the end of the last administration）， mechanical pain threshold， thermal pain threshold， and the phosphorylation levels of RIPK1， RIPK3 and MLKL were decreased significantly； the tumor volume， the proportion of bone destruction area， the number of osteoclasts， and the positive expressions of RANK and RANKL were increased/up-regulated significantly （P＜0.05）. Compared with the model group， the above pathological changes in the tibial tissues of rats in modified Yanghe decoction low-， medium- and high-dose groups were all alleviated， and all quantitative indicators showed dose-dependent improvement （P＜0.05）. After silencing RIPK1， the aforementioned beneficial effects of high-dose modified Yanghe decoction were significantly weakened （P＜0.05）.CONCLUSIONSModified Yanghe decoction can alleviate bone destruction in rats with breast cancer bone metastasis. The above effect is related to the activation of the RIPK1/RIPK3 pathway.

There are practical and cost-effective opportunities for the prevention and early intervention of periodontal disease, a common oral condition. Depression and anxiety represent major global mental health challenges, and they are characterized by high prevalence rates and an elevated suicide risk. Their clinical management is complicated by extended treatment timelines and substantial healthcare costs. Accumulating evidence demonstrates a statistically significant bidirectional association between periodontal disease and depression/anxiety disorders. However, established clinical pathways integrating these conditions remain lacking. This review presents a comprehensive analysis of current research examining the relationship between periodontal disease and mood disorders, specifically depression and anxiety. This study explored the bidirectional mechanisms within the microbiota-oral-brain axis, which includes both periodontal disease inducing neuroinflammation through pro-inflammatory factors, such as interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) activating the TLR-4/NF-κB signaling pathway, and depression and anxiety leading to “glucocorticoid resistance” through hypothalamic-pituitary-adrenal (HPA) axis dysregulation, thus causing dual immune dysfunction that exacerbates periodontal tissue destruction, as well as the mechanisms by which biological, psychological, and social factors contribute to the bidirectional association between periodontal disease and depression/anxiety. We propose implementing bidirectional referral protocols between dental and psychiatric services in clinical practice, incorporating mental health screening tools, such as Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7(GAD-7), for patients with moderate-to-severe periodontal disease, and incorporating periodontal examination into routine assessment during psychiatric services. This multidisciplinary approach aims to break the vicious circle between these conditions and provide clinicians with pragmatic intervention strategies.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

ObjectiveNeuroinflammation plays a crucial role in both the onset and progression of ischemic stroke, exerting a significant impact on the recovery of the central nervous system. Excessive neuroinflammation can lead to secondary neuronal damage, further exacerbating brain injury and impairing functional recovery. As a result, effectively modulating and reducing neuroinflammation in the brain has become a key therapeutic strategy for improving outcomes in ischemic stroke patients. Among various approaches, targeting immune regulation to control inflammation has gained increasing attention. This study aims to investigate the role of in vitro induced regulatory T cells (Treg cells) in suppressing neuroinflammation after ischemic stroke, as well as their potential therapeutic effects. By exploring the mechanisms through which Tregs exert their immunomodulatory functions, this research is expected to provide new insights into stroke treatment strategies. MethodsNaive CD4⁺ T cells were isolated from mouse spleens using a negative selection method to ensure high purity, and then they were induced in vitro to differentiate into Treg cells by adding specific cytokines. The anti-inflammatory effects and therapeutic potential of Treg cells transplantation in a mouse model of ischemic stroke was evaluated. In the middle cerebral artery occlusion (MCAO) model, after Treg cells transplantation, their ability to successfully migrate to the infarcted brain region and their impact on neuroinflammation levels were examined. To further investigate the role of Treg cells in stroke recovery, the changes in cytokine expression and their effects on immune cell interactions was analyzed. Additionally, infarct size and behavioral scores were measured to assess the neuroprotective effects of Treg cells. By integrating multiple indicators, the comprehensive evaluation of potential benefits of Treg cells in the treatment of ischemic stroke was performed. ResultsTreg cells significantly regulated the expression levels of both pro-inflammatory and anti-inflammatory cytokines in vitro and in vivo, effectively balancing the immune response and suppressing excessive inflammation. Additionally, Treg cells inhibited the activation and activity of inflammatory cells, thereby reducing neuroinflammation. In the MCAO mouse model, Treg cells were observed to accumulate in the infarcted brain region, where they significantly reduced the infarct size, demonstrating their neuroprotective effects. Furthermore, Treg cell therapy notably improved behavioral scores, suggesting its role in promoting functional recovery, and increased the survival rate of ischemic stroke mice, highlighting its potential as a promising therapeutic strategy for stroke treatment. ConclusionIn vitro induced Treg cells can effectively suppress neuroinflammation caused by ischemic stroke, demonstrating promising clinical application potential. By regulating the balance between pro-inflammatory and anti-inflammatory cytokines, Treg cells can inhibit immune responses in the nervous system, thereby reducing neuronal damage. Additionally, they can modulate the immune microenvironment, suppress the activation of inflammatory cells, and promote tissue repair. The therapeutic effects of Treg cells also include enhancing post-stroke recovery, improving behavioral outcomes, and increasing the survival rate of ischemic stroke mice. With their ability to suppress neuroinflammation, Treg cell therapy provides a novel and effective strategy for the treatment of ischemic stroke, offering broad application prospects in clinical immunotherapy and regenerative medicine.

ObjectiveTo investigate the accuracy of multiple discriminant analysis （MDA） versus fibrosis-4 （FIB-4） in assessing liver fibrosis degree in patients with HBV infection， as well as the possibility of MDA as an indicator for disease progression. MethodsA total of 263 patients with HBV infection who underwent liver biopsy in The First Affiliated Hospital of Guangxi Medical University from April 2010 to April 2024 were included， and their clinical data were collected. According to the results of pathological examination， they were divided into non-significant fibrosis group （F<2） with 126 patients and significant fibrosis group （F≥2） with 137 patients. The correlation of MDA and FIB-4 with liver fibrosis degree was analyzed， and MDA and FIB-4 were compared in terms of their accuracy in assessing significant liver fibrosis. A total of 62 patients completed follow-up， and according to the presence or absence of progression to liver cirrhosis at the last follow-up visit， they were divided into progressive group with 21 patients and non-progressive group with 41 patients； the efficacy of MDA and FIB-4 in diagnosing disease progression was analyzed and compared. The independent-samples t test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups； the Kruskal-Wallis H test was used for comparison between multiple groups， and the Bonferroni method was used for further comparison between two groups. The chi-square test was used for comparison of categorical data. The Spearman’s correlation coefficient was used for correlation analysis. The Wilcoxon signed rank sum test was used for the analysis of baseline data and data at the end of follow-up， and the binary Logistic regression analysis was used to investigate the influencing factors for progression to liver cirrhosis. The receiver operating characteristic （ROC） curve was used to investigate the diagnostic efficacy of indicators， the Z-test was used for comparison of the area under the ROC curve （AUC）， and the paired chi-square test was used for comparison of the sensitivity， specificity， and accuracy of the two indicators. ResultsThe correlation coefficient between FIB-4 and liver fibrosis degree was 0.378， while the correlation coefficient between MDA and liver fibrosis degree was -0.325 （both P<0.001）. FIB-4 had an AUC of 0.688， a sensitivity of 64.96%， a specificity of 68.87%， a positive predictive value of 67.42%， a negative predictive value of 63.36%， an accuracy of 65.40%， and a cut-off value of 1.01， while MDA had an AUC of 0.653， a sensitivity of 52.55%， a specificity of 78.57%， a positive predictive value of 72.73%， a negative predictive value of 60.37%， an accuracy of 65.02%， and a cut-off value of 0.29， suggesting that compared with FIB-4， MDA had a lower sensitivity （P=0.004） and a higher specificity （P=0.001）. The progressive group had a significantly higher age than the non-progressive group at baseline （t=2.611， P=0.011）. For the progressive group， there was an increase in FIB-4 and a reduction in MDA from baseline to the end of follow-up （both P<0.001）， while the non-progressive group showed no significant changes （both P>0.05）. The multivariate Logistic regression analysis showed that aspartate aminotransferase （odds ratio ［OR］=0.940， 95% confidence interval ［CI］： 0.885‍ ‍—‍ ‍0.998， P<0.05） and MDA （OR=0.445， 95%CI： 0.279‍ ‍—‍ ‍0.710， P<0.001） were independent influencing factors for disease progression. MDA had an AUC of 0.893 and an optimal cut-off value of -0.01 in diagnosing the disease progression of liver cirrhosis. ConclusionMDA has a comparable accuracy to FIB-4 in the diagnosis of significant liver fibrosis， and MDA<-0.01 has a high accuracy in diagnosing the progression of liver fibrosis to liver cirrhosis， which can help to reduce the need for liver biopsy in clinical practice.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

This paper reported a patient with early-onset Alzheimer's disease （AD） who had previously responded poorly to anti-dementia medications while showed improvement in cognitive functioning after treatment with occupational therapy and computerized cognitive remediation therapy （CCRT） for 50 minutes three times per week. This case report provided an in-depth evaluation of occupational therapy combined with CCRT for early-onset AD in an effort to inform cognitive rehabilitation of patients with AD. ［Funded by Chengdu Medical Scientific Research Project （number， 2023635）］