Bowen Xu

Introduction: Given insulin resistance’s (IR) critical role in metabolic pathophysiology, this study aims to identify optimal coffee consumption patterns by timing and dose to improve population health. Material and methods: Multivariate logistic regression and restricted cubic splines assessed associations between coffee timing, dosage, and IR (measured by estimated glucose disposal rate) from NHANES data (1999–2018). Interaction and subgroup analyses explored variations across population segments. Results: We analysed 21,138 participants, of whom 46.79% were non-consumers. Among consumers, 76% primarily drank coffee in the morning. Morning consumption at the lowest quartile (Q1) showed significant improvement in IR (odds ratio [OR] = 1.37, 95% confidence interval [CI]: 1.16–1.62), although this benefit diminished with higher consumption levels (p < 0.05). While the “all-day” pattern overall showed a non-significant trend toward improved insulin resistance (OR = 1.20, 95% CI: 0.83–1.73), higher consumption within this pattern (Q3: OR = 1.46, 95% CI: 1.13–1.89; Q4: OR = 1.34, 95% CI: 1.11–1.63) proved significantly more beneficial than lower intake. Comparative analysis revealed that morning consumption tended to be more advantageous for low-to-moderate intake (Q1-Q2), whereas all-day distribution showed potential benefits at higher consumption levels (Q3-Q4). The observed benefits were primarily associated with caffeinated coffee, attenuated by sugar addition, and varied across subgroups based on age, sex, and comorbidities. Conclusions: Both morning and all-day coffee intake improve IR. For moderate consumption (1–2 cups/day), morning intake provides optimal improvement in insulin sensitivity. For higher intake (≥ 3 cups/day), distributed consumption is more effective. These findings support chrono-nutrition principles for optimising metabolic health through coffee consumption.

Traditional Chinese medicine is an important part of complementary alternative medicine. Jiedu Qingjin formula (JDQJF) is an effective national invention patent for the treatment of non-small cell lung cancer (NSCLC). We investigated the molecular biological mechanisms based on network pharmacology, molecular docking, and molecular dynamics simulations. Compounds of JDQJF were screened through the TCMSP, ETCM, and literature. Targets were searched by DrugBank and predicted by SwissTargetPrediction. GEO database was applied for screening differentially expressed genes between cancerous tissues and healthy tissues of NSCLC. Subsequently, the protein-protein interaction between JDQJF and NSCLC were obtained by Cytoscape. Visual analyses were carried out to extract candidate genes, then subjected to Metascape for enrichment analyses. Finally, molecular docking was performed by AutoDock, and the best complexes were subjected to molecular dynamics simulation and binding energy calculations by MMPBSA. A total of 273 compounds, 390 targets, 3146 GO terms, and 174 KEGG pathways were obtained. Five potential compounds (quercetin, adenosine, apigenin, heptadecanoic acid, and luteolin) were notably modulated by key targets AKT1, MAPK3, and RAF1. Enrichment results included cell cycle process, growth transduction factor, immune response-activating transduction, and involved PI3K/AKT, MAPK, NF-& kappa;B and VEGF pathway. RAF1-quercetin showed the highest binding affinity (-9.1 kcal/mol), revealed stable interactions during the simulation, and the highest estimated relative binding energy of the RAF1-Heptadecanoic was -184.277 kcal/mol. This study suggested that EMT-related, inflammation-related, immune-related, and angiogenesis-related pathways may be associated with JDQJF, and involved in the advancement of NSCLC, which points out the research direction for subsequent utility mechanism validation.Communicated by Ramaswamy H. Sarma

Cancer continues to pose a severe threat to global health, making pursuing effective treatments more critical than ever. Traditional therapies, although pivotal in managing cancer, encounter considerable challenges, including drug resistance, poor drug solubility, and difficulties targeting tumors, specifically limiting their overall efficacy. Nanomedicine’s application in cancer therapy signals a new epoch, distinguished by the improvement of the specificity, efficacy, and tolerability of cancer treatments. This review explores the mechanisms and advantages of nanoparticle-mediated drug delivery, highlighting passive and active targeting strategies. Furthermore, it explores the transformative potential of nanomedicine in tumor therapeutics, delving into its applications across various treatment modalities, including surgery, chemotherapy, immunotherapy, radiotherapy, photodynamic and photothermal therapy, gene therapy, as well as tumor diagnosis and imaging. Meanwhile, the outlook of nanomedicine in tumor therapeutics is discussed, emphasizing the need for addressing toxicity concerns, improving drug delivery strategies, enhancing carrier stability and controlled release, simplifying nano-design, and exploring novel manufacturing technologies. Overall, integrating nanomedicine in cancer treatment holds immense potential for revolutionizing cancer therapeutics and improving patient outcomes.

Introduction. Brain metastases (BMs) are common in non‐small‐cell lung cancer (NSCLC), which leads to a poor prognosis. As the two most effective strategies available, the use of combination of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR‐TKIs) and radiotherapy (RT) is still controversial. This protocol proposes a methodology for carrying out a systematic review and meta‐analysis that is aimed at (1) focusing on the efficacy and safety role of EGFR‐TKIs combined with RT for BMs from NSCLC and (2) displaying the difference in efficacy of EGFR‐TKIs owing to the sites and number of BMs, different types of RT, EGFR mutation status, and the subtypes of EGFR mutations by subgroup analysis. Methods and Analysis. Electronic databases including PubMed, Embase, CENTRAL, Web of Science, CBM, CNKI, Wanfang database, and VIP database will be searched from their inception until May 2022. Only randomized controlled trials evaluating the clinical efficacy and safety of EGFR‐TKIs combined with RT on BMs of NSCLC will be included. Two reviewers will select the articles, assess the risk of bias, and extract data independently and in duplicate. The RoB 2 tool will be used to assess the quality of included studies. The meta‐analysis of data synthesis will be performed with Stata 16. Publication bias will be assessed with the funnel plot method and the Egger test. Quality of the evidence will be evaluated by the GRADE system. Discussion. The approval of an ethical committee is not required. All the included trials will comply with the current ethical standards and the Declaration of Helsinki. Given the ongoing controversies regarding the optimal sequencing of the available and expanding treatment options for EGFR‐TKIs in NSCLC with BMs, a synthesis of available, high‐quality clinical research evidence is essential to advance our understanding in the treatment of this complex and common disease. This systematic review will evaluate available evidence, will try to provide optimized advice in the applications of EGFR‐TKIs, and will be published in a high‐quality journal. This study is registered with PROSPERO registration number CRD42021291509.

Background. Kanglaite injection (KLTi) has shown good clinical efficacy in the treatment of pancreatic ductal adenocarcinoma (PDAC). While previous studies have demonstrated the antitumor effects of the oil compounds in KLTi, it is unclear whether the unsaponifiable matter (USM) also has antitumor effects. This study used network pharmacology, molecular docking, and database verification methods to investigate the molecular biological mechanisms of USM. Methods. Compounds of USM were obtained from GC‐MS, and targets from DrugBank. Next, the GEO database was searched for differentially expressed genes in cancerous tissues and healthy tissues of PDAC to identify targets. Subsequently, the protein‐protein interaction of USM and PDAC targets was constructed by BisoGenet to extract candidate genes. The candidate genes were enriched using GO and KEGG by Metascape, and the gene‐pathway network was constructed to screen the key genes. Molecular docking and molecular dynamic simulations of core compound targets were finally performed and to explore the diagnostic, survival, and prognosis value of targets. Results. A total of 10 active compounds and 36 drug targets were screened for USM, 919 genes associated with PDAC, and 139 USM candidate genes against PDAC were excavated. The enrichment predicted USM by acting on RELA, NFKB1, IKBKG, JUN, MAPK1, TP53, and AKT1. Molecular docking and dynamic simulations confirmed the screened core targets had good affinity and stability with the corresponding compounds. In diagnostic ROC validation, the above targets have certain accuracy for diagnosing PDAC, and the combined diagnosis is more advantageous. As the most diagnostic value of RELA, it is equally significant in predicting disease‐specific survival and progression‐free interval. Conclusions. USM in KLTi plays an anti‐PDAC role by intervening in the cell cycle, inducing apoptosis, and downregulating the NF‐κB, MAPK, and PI3K‐Akt pathways. It might participate in the pancreatic cancer pathway, and core target groups have diagnostic, survival, and prognosis value biomarker significance.