Analysis of high-throughput omics data is one of the most important approaches for obtaining information regarding interactions between proteins/genes. Time-series omics data are a series of omics data points indexed in time order and normally contain more abundant information about the interactions between biological macromolecules than static omics data. In addition, phosphorylation is a key posttranslational modification (PTM) that is indicative of possible protein function changes in cellular processes. Analysis of time-series phosphoproteomic data should provide more meaningful information about protein interactions. However, although many algorithms, databases, and websites have been developed to analyze omics data, the tools dedicated to discovering molecular interactions from time-series omics data, especially from time-series phosphoproteomic data, are still scarce. Moreover, most reported tools ignore the lag between functional alterations and the corresponding changes in protein synthesis/PTM and are highly dependent on previous knowledge, resulting in high false-positive rates and difficulties in finding newly discovered protein–protein interactions (PPIs). Therefore, in the present study, we developed a new method to discover protein–protein interactions with the delayed comparison and Apriori algorithm (DCAA) to address the aforementioned problems. DCAA is based on the idea that there is a lag between functional alterations and the corresponding changes in protein synthesis/PTM. The Apriori algorithm was used to mine association rules from the relationships between items in a dataset and find PPIs based on time-series phosphoproteomic data. The advantage of DCAA is that it does not rely on previous knowledge and the PPI database. The analysis of actual time-series phosphoproteomic data showed that more than 68% of the protein interactions/regulatory relationships predicted by DCAA were accurate. As an analytical tool for PPIs that does not rely on a priori knowledge, DCAA should be useful to predict PPIs from time-series omics data, and this approach is not limited to phosphoproteomic data.

BackgroundTraditional Chinese medicine has great advantages in improving symptoms of CHF such as chest tightness, shortness of breath, and fatigue. In addition, some traditional Chinese medicines can be used as both medicine and food, which have good effects on the prevention and treatment of CHF patients at home.MethodA comprehensive search across China National Knowledge Infrastructure (CNKI), Wanfang, and Wei Pu (VIP) databases was conducted to retrieve pre-2022 literature related to CHF. After standardization, frequency analysis and Apriori algorithm were used to analyze these data.ResultAmong 626 effective medical records, Fuling, Huangqi, and Danshen are the most commonly used herbs; The medication for chest tightness is closely related to Tinglizi; The medication for palpitations is closely related to Guizhi, Fuzi, Zhigancao, and Wuweizi; The medication of fatigue and poor appetite is closely related to Huangqi and Baizhu; The medication for lower limb edema is closely related to Fuling and Tinglizi; The medication for coughing is closely related to the use of Tinglizi, Wuweizi, Kuxingren, and Sangbaipi; Insomnia is closely related to Suanzaoren and Dazao.ConclusionThe components in traditional Chinese medicine that have anti heart failure effects and reliable evidence can be potential candidates for drug discovery, while dietary therapeutic herbs such as Fuling, Huangqi, Danshen, and Zhigancao can be developed as health products.

Introduction: Multimorbidity has become one of the key issues in the public health sector. This study aimed to explore the urban–rural differences in patterns and associated factors of multimorbidity in China and to provide scientific reference for the development of health management strategies to reduce health inequality between urban and rural areas.Methods: A cross-sectional study, which used a multi-stage random sampling method, was conducted effectively among 3,250 participants in the Shanxi province of China. The chi-square test was used to compare the prevalence of chronic diseases among older adults with different demographic characteristics. The Apriori algorithm and multinomial logistic regression were used to explore the patterns and associated factors of multimorbidity among older adults, respectively.Results: The findings showed that 30.3% of older adults reported multimorbidity, with significantly higher proportions in rural areas. Among urban older adults, 10 binary chronic disease combinations with strong association strength were obtained. In addition, 11 binary chronic disease combinations and three ternary chronic disease combinations with strong association strength were obtained among rural older adults. In rural and urban areas, there is a large gap in patterns and factors associated with multimorbidity.Conclusions: Multimorbidity was prevalent among older adults, which patterns mainly consisted of two or three chronic diseases. The patterns and associated factors of multimorbidity varied from urban to rural regions. Expanding the study of urban–rural differences in multimorbidity will help the country formulate more reasonable public health policies to maximize the benefits of medical services for all.

ObjectiveTraditional Chinese medicine (TCM) has been used for the treatment of chronic liver diseases for a long time, with proven safety and efficacy in clinical settings. Previous studies suggest that the therapeutic mechanism of TCM for hepatitis B cirrhosis may involve the gut microbiota. Nevertheless, the causal relationship between the gut microbiota, which is closely linked to TCM, and cirrhosis remains unknown. This study aims to utilize two-sample Mendelian randomization (MR) to investigate the potential causal relationship between gut microbes and cirrhosis, as well as to elucidate the synergistic mechanisms between botanical drugs and microbiota in treating cirrhosis.MethodsEight databases were systematically searched through May 2022 to identify clinical studies on TCM for hepatitis B cirrhosis. We analyzed the frequency, properties, flavors, and meridians of Chinese medicinals based on TCM theories and utilized the Apriori algorithm to identify the core botanical drugs for cirrhosis treatment. Cross-database comparison elucidated gut microbes sharing therapeutic targets with these core botanical drugs. MR analysis assessed consistency between gut microbiota causally implicated in cirrhosis and microbiota sharing therapeutic targets with key botanicals.ResultsOur findings revealed differences between the Chinese medicinals used for compensated and decompensated cirrhosis, with distinct frequency, dosage, properties, flavors, and meridian based on TCM theory. Angelicae Sinensis Radix, Salviae Miltiorrhizae Radix Et Rhizoma, Poria, Paeoniae Radix Alba, Astragali Radix, Atrctylodis Macrocephalae Rhizoma were the main botanicals. Botanical drugs and gut microbiota target MAPK1, VEGFA, STAT3, AKT1, RELA, JUN, and ESR1 in the treatment of hepatitis B cirrhosis, and their combined use has shown promise for cirrhosis treatment. MR analysis demonstrated a positive correlation between increased ClostridialesvadinBB60 and Ruminococcustorques abundance and heightened cirrhosis risk. In contrast, Eubacteriumruminantium, Lachnospiraceae, Eubacteriumnodatum, RuminococcaceaeNK4A214, Veillonella, and RuminococcaceaeUCG002 associated with reduced cirrhosis risk. Notably, Lachnospiraceae shares key therapeutic targets with core botanicals, which can treat cirrhosis at a causal level.ConclusionWe identified 6 core botanical drugs for managing compensated and decompensated hepatitis B cirrhosis, despite slight prescription differences. The core botanical drugs affected cirrhosis through multiple targets and pathways. The shared biological effects between botanicals and protective gut microbiota offer a potential explanation for the therapeutic benefits of these key herbal components in treating cirrhosis. Elucidating these mechanisms provides crucial insights to inform new drug development and optimize clinical therapy for hepatitis B cirrhosis.

Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder among women of reproductive age that significantly impacts their reproductive health. Acupuncture and its combined therapies may have beneficial effects on the endocrine and metabolic states of women with PCOS. This systematic review and meta-analysis evaluated the treatment effects and potential mechanisms of acupuncture and its combined therapies compared to oral metformin in treating PCOS patients. The evaluation focused on three sets of outcomes: hormonal indicators, metabolic indicators, and body weight indicators. Studies that involved additional therapies beyond the specified interventions or included patients with other diseases were excluded. Additionally, data mining methods were used, including frequency statistics to analyze the frequency of acupuncture points and the meridians involved, and the Apriori algorithm to perform association rule analysis for the most effective interventions. The study included 46 articles (51 studies) involving six interventions: acupuncture combined with metformin, acupuncture treatment, acupuncture with Chinese herbal medicine and metformin, acupuncture with Chinese herbal medicine, acupuncture combined with cupping, and auricular acupuncture combined with metformin showed significant improvements in all evaluated indicators. Data mining revealed the Stomach meridian of foot yangming was the most frequently used, and the most commonly used combination of points included CV4, SP6, and ST36. This study suggests that acupuncture and its combined therapies may benefit PCOS. However, risk of bias and heterogeneity observed were noted. Future high-quality, rigorously designed randomized controlled trials are needed to confirm these findings and provide stronger clinical recommendations for acupuncture in PCOS treatment.