Background: The link between diabetes and dementia risk is not well understood. This study evaluates the factors linking diabetes to dementia onset, providing guidance for preventing dementia in diabetic patients. Methods: This analysis utilized databases such as PubMed, Embase, Web of Science, and the Cochrane Library to review literature from January 31, 2012, to March 5, 2023. Articles were rigorously assessed using specific inclusion and exclusion criteria. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the studies. Data analysis was performed with STATA 15.0. Results: The study analyzed 15 articles, covering 10,103,868 patients, with 8,821,516 diagnosed with diabetes. The meta-analysis reveals a substantial association between diabetes and an increased risk of dementia [RR: 1.59, 95%CI (1.40–1.80), P < 0.01, I²=96.4%]. A diabetes duration of less than five years is linked to a higher dementia risk [RR: 1.29, 95%CI (1.20–1.39), P < 0.01, I²=92.6%]. Additionally, hypoglycemia significantly raises dementia risk [RR: 1.56, 95%CI (1.13–2.16), P < 0.01, I²=51.5%]. Analyses of blood sugar control, glycated hemoglobin, and fasting blood sugar indicated no significant effects on the onset of dementia. Conclusion: Diabetes notably increases dementia risk, particularly where diabetes duration is under five years or hypoglycemia is present. Registration: The research protocol was registered with PROSPERO and assigned the registration number CRD42023394942.

Cardiovascular diseases (CVDs) remain the leading cause of death and disability worldwide, highlighting an urgent need for new treatments. Traditional Chinese Medicine (TCM) offers a rich repository of natural metabolites (flavonoids, alkaloids, saponins, etc.) that act on multiple targets to protect the heart and blood vessels. These compounds have demonstrated multiple cardioprotective effects, including anti-inflammatory, antioxidant, anti-atherosclerotic, and blood pressure–lowering activities. They work by reducing oxidative stress, dampening chronic inflammation, improving blood vessel function, correcting abnormal lipid levels, and mitigating cardiac fibrosis. Recent preclinical studies and clinical trials show that TCM-derived metabolites can improve cardiovascular health. For instance, the multi-herb formula Qili Qiangxin and the alkaloid berberine have improved heart failure symptoms and cardiac function in clinical trials when added to standard therapy. These examples underscore the clinical potential of TCM compounds. However, challenges like poor bioavailability, complex multi-component interactions, and lack of standardization still hinder their widespread use. To address these issues, researchers are exploring advanced drug delivery methods and better quality control with modern analytical tools. If these hurdles are overcome, TCM-derived therapies could be successfully integrated into mainstream cardiovascular care, offering a novel multi-target approach to combat CVDs.

The lethality of liver cancer and the resistance to chemical drugs have forced the search for effective prescriptions of traditional herbs for liver cancer. Animal models that are repeatable, easy to manipulate, and highly mimic the pathophysiological processes of liver cancer are the prerequisite for the successful screening of effective drug candidates. Meanwhile, reliable drug efficacy evaluation indicators and means are also the guarantee of anti-liver cancer drug research and development. Sanleng Jiashen formula, a representative prescription of traditional Chinese medicine containing Sparganium stoloni erum, Buch. -Ham. (Sanleng), Panax ginseng C. A. Mey. (ginseng), Rheum officinale Baill. (rhubarb), and Ligusticum chuanxiong Hort. (Chuanxiong), is prescribed to nourish the liver and clear heat, remove toxins, and promote blood circulation to treat liver cancer. This experimental protocol describes the preparation of lyophilized Sanleng Jiashen formula and the establishment process of in-situ liver cancer in BALB/c-nu mice. Histopathological staining, immunohistochemical detection of cancer markers, in vivo imaging of mice, and chick embryo chorioallantoic membrane test were used to explore the inhibition and anti-angiogenesis effect of Sanleng Jiashen formula on malignant proliferation of liver cancer tissue. The data show that the Sanleng Jiashen formula can effectively resist the malignant proliferation of liver cancer tissue, which is manifested by reduced tumor mass volume, improved pathological damage, and lower levels of the cancer marker ki67. The superior inhibition of angiogenesis also suggests that the Sanleng Jiashen formula may have the potential to treat and prevent the progression and deterioration of liver cancer. The whole experimental scheme shows a comprehensive process of traditional Chinese medicine components in the treatment of mouse liver cancer, which provides a reference for the establishment and optimization of a liver cancer model, as well as the research and development of drugs to prevent and treat liver cancer.

In traditional Chinese medicine, acupuncture is considered free of harmful side effects when properly performed. Pharmacokinetics provides a valuable approach to explore how acupuncture influences drug disposition. Stimulation at specific acupoints, such as Zusanli (ST36), may modulate drug absorption and action. While most studies highlight beneficial outcomes, potential risks also deserve consideration. A systematic review was conducted to evaluate how acupuncture or electroacupuncture at ST36 affects the pharmacokinetics of various drugs. Data on changes in absorption, distribution, metabolism, and excretion, along with pharmacokinetic parameters (e.g., average plasma concentration-time curve [AUC], C _max , T _max ), were extracted and analyzed. Acupuncture at ST36 significantly influenced the pharmacokinetics of several compounds. For instance, it enhanced the absorption and plasma levels of Schisandra chinensis lignans and acetaminophen (APAP), increasing AUC and C _max while shortening T _max . Tissue distribution also shifted, with elevated concentrations observed in certain organs such as the lungs. While aspirin metabolism remained unaffected, ST36 stimulation delayed APAP clearance at higher doses, resulting in prolonged systemic exposure. In the case of triptolide, a bioactive diterpenoid, acupuncture increased its plasma levels and AUC. Some studies reported changes in biomarkers associated with liver function under elevated compound exposure, though no acute adverse effects were noted for commonly used agents. ST36 acupuncture can alter drug pharmacokinetics, potentially impacting drug exposure and clinical response. Awareness of such interactions is important when combining acupuncture with medication. Further studies are warranted to ensure the safe and effective integration of acupuncture into pharmacological treatment strategies.

Background and aim: The Systemic Immunity-inflammation Index (SII) is an emerging metric for assessing an individual’s immunological and inflammatory condition. Studies examining the relationship between SII and body mass index (BMI) are limited. This study aims to clarify the correlation between SII and BMI. Methods: The current study investigated the association between SII and BMI using data from the National Health and Nutrition Examination Survey (NHANES). Information on SII and BMI was obtained from laboratory and demographic data. The analytical approach included techniques such as linear univariate analysis, linear multivariate analysis, and subgroup analysis to explore the intricate relationship between SII and BMI comprehensively. Results: A total of 1568 participants who met the inclusion criteria were included in the study; their average age was 53.6 ± 16.7 years, and they were 40.8% female and 59.2% male. Several baseline indicators showed statistically significant differences across SII groups. Curve fitting revealed an inverted L-shape, non-linear relationship between SII and BMI. Multivariate linear regression analysis revealed that adjusted β values were 1.7 (95% CI: 0.87–2.54, p < 0.001) for T3 and 0.46 (95% CI: −0.36–1.28, p = 0.271) for T2 in comparison to T1. Threshold analysis indicated that SII < 677.842 was associated with a BMI increase β of 0.005 (95% CI: 0.002–0.007, p < 0.001). The stratified analysis demonstrated the positive association between SII and BMI was not influenced by gender, diabetes, or smoking (all p > 0.05). Conclusions: In summary, these findings reveal a robust association between SII and BMI within the examined American population.