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Pinocembrin is one of the most abundant flavonoids in propolis, and it may also be widely found in a variety of plants. In addition to natural extraction, pinocembrin can be obtained by biosynthesis. Biosynthesis efficiency can be improved by a metabolic engineering strategy and a two-phase pH fermentation strategy. Pinocembrin poses an interest for its remarkable pharmacological activities, such as neuroprotection, anti-oxidation, and anti-inflammation. Studies have shown that pinocembrin works excellently in treating ischemic stroke. Pinocembrin can reduce nerve damage in the ischemic area and reduce mitochondrial dysfunction and the degree of oxidative stress. Given its significant efficacy in cerebral ischemia, pinocembrin has been approved by China Food and Drug Administration (CFDA) as a new treatment drug for ischemic stroke and is currently in progress in phase II clinical trials. Research has shown that pinocembrin can be absorbed rapidly in the body and easily cross the blood–brain barrier. In addition, the absorption/elimination process of pinocembrin occurs rapidly and shows no serious accumulation in the body. Pinocembrin has also been found to play a role in Parkinson’s disease, Alzheimer’s disease, and specific solid tumors, but its mechanisms of action require in-depth studies. In this review, we summarized the latest 10 years of studies on the biosynthesis, pharmacological activities, and pharmacokinetics of pinocembrin, focusing on its effects on certain diseases, aiming to explore its targets, explaining possible mechanisms of action, and finding potential therapeutic applications.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers. Circulating microRNAs (miRNAs) have been suggested as potentially promising markers for early detection of CRC. We aimed to identify and evaluate a panel of miRNAs that might be suitable for CRC early detection. MiRNAs were profiled by TaqMan MicroRNA Array and screened for differential expression in 5 pools of plasma samples of CRC patients (N = 50) and 5 pools of neoplasm-free controls (N = 50). Additional miRNAs were selected from a literature review. Identified candidates were evaluated in independent validation samples with respect to discrimination of CRC patients (N = 80) or advanced adenoma patients (N = 50) and neoplasm-free controls (N = 194). Diagnostic performance of the panel of miRNAs was assessed by multiple logistic regression, using bootstrap analysis to correct for over-optimism. Five miRNAs identified to be differentially expressed from TaqMan MicroRNA Array (miR-29a, -106b, -133a, -342-3p, -532-3p), and seven miRNAs reported to be differentially expressed in the literature (miR-18a, -20a, -21, -92a, -143, -145, -181b) were selected for validation. Nine of the twelve miRNAs (miR-18a, -20a, -21, -29a, -92a, -106b, -133a, -143, -145) were found to be differentially expressed in CRC patients and controls in the validation samples. The optimism-corrected area under the curve was 0.745 (95% confidence interval: 0.708-0.846). None of the selected miRNAs showed significant differential expression between advanced adenoma patients and neoplasm-free controls. The identified panel of miRNAs could be of potential use in the development of a multi-marker blood based test for early detection of CRC. The study underscores the high potential of plasma miRNAs for the improvement of current offers of non-invasive CRC screening.

Non-invasive prenatal testing (NIPT) is a prenatal screening technique that analyzes cell-free fetal DNA in maternal blood plasma, widely used for early detection of fetal chromosomal abnormalities such as trisomy 21, 18, and 13. To optimize personalized testing timing and improve the detection accuracy of chromosomal abnormalities in female fetuses, this study developed a data-driven multifactorial modeling framework. The study population consisted of 1,687 pregnant women from a certain region. Correlation analysis and a nonlinear mixed-effects model (M4) were employed to quantify the relationships among gestational age, body mass index (BMI), and Y-chromosome concentration. The model results showed a positive correlation between gestational age and Y-chromosome concentration, while BMI and height were significantly negatively correlated with Y-chromosome concentration, providing statistical support for subsequent BMI-based stratification. Building on this, the study further predicted the earliest possible gestational week at which fetal DNA concentration reaches the detection threshold for each pregnant woman. A joint optimization model for BMI grouping and testing timing was constructed to determine the optimal testing time for each group, and the interaction between BMI and gestational age was validated using K-means clustering incorporating multiple factors. The model results indicated that the M4 model exhibited the best goodness of fit. As BMI increased, the recommended testing time was postponed from 13.8 weeks to 21.5 weeks. Additionally, to address the issues of limited data and the absence of Y-chromosome signals in female fetuses, this study systematically compared decision tree, random forest, and support vector machine (SVM) models, constructing a multi-feature fusion-based classification system. In the task of classifying chromosomal abnormalities in female fetuses, the SVM model performed the best, with X-chromosome concentration and GC content identified as key discriminatory features. The comprehensive multifactorial model proposed in this study can effectively predict personalized NIPT timing, help reduce the risk of testing failure, enhance the detection performance for chromosomal abnormalities in female fetuses, and thereby provide scientific basis and methodological support for the clinical application of NIPT.

Background Colorectal cancer (CRC) is the fourth most deadly malignancy throughout the world. Extensive studies have shown that Krüppel-like factors (KLFs) play essential roles in cancer development. However, the function of KLF13 in CRC is unclear. Methods The Cancer Genome Atlas database was applied to analyze the expression of KLF13 in CRC and normal tissues. Lentivirus system was used to overexpress and to knock down KLF13. RT-qPCR and Western blot assays were performed to detect mRNA and protein expression. CCK-8, colony formation, cell cycle analysis and EdU staining were used to assess the in vitro function of KLF13 in CRC cells. Xenografter tumor growth was used to evaluate the in vivo effect of KLF13 in CRC. Cholesterol content was measured by indicated kit. Transcription activity was analyzed by luciferase activity measurement. ChIP-qPCR assay was performed to assess the interaction of KLF13 to HMGCS1 promoter. Results KLF13 was downregulated in CRC tissues based on the TCGA database and our RT-qPCR and Western blot results. Comparing with normal colorectal cells NCM460, the CRC cells HT-26, HCT116 and SW480 had reduced KLF13 expression. Functional experiments showed that KLF13 knockdown enhanced the proliferation and colony formation in HT-29 and HCT116 cells. Opposite results were observed in KLF13 overexpressed cells. Furthermore, KLF13 overexpression resulted in cell cycle arrest at G0/G1 phase, reduced EdU incorporation and suppressed tumor growth of HCT116 cells in nude mice. Mechanistically, KLF13 transcriptionally inhibited HMGCS1 and the cholesterol biosynthesis. Knockdown of HMGCS1 suppressed cholesterol biosynthesis and the proliferation of CRC cells with silenced KLF13. Furthermore, cholesterol biosynthesis inhibitor significantly retarded the colony growth in both cells. Conclusions Our study reveals that KLF13 acts as a tumor suppressor in CRC through negatively regulating HMGCS1-mediated cholesterol biosynthesis.

Background Kruppel-like factor 4 (KLF4) is a zinc finger-containing transcription factor predominantly expressed in terminally differentiated epithelial tissues. Many studies have shown that KLF4 has various mechanisms in different tumours; however, the prognostic role of KLF4 remains unclear. Methods and results We searched the relevant literature that evaluated the prognostic value of KLF4 in different cancers, and the original survival data were obtained from the text, tables or Kaplan–Meier curves for both comparative groups. Thirty studies were included in this meta-analysis, and a total of 10 malignant tumours were involved. The expression of KLF4 was not associated with the prognosis for overall survival (hazard ratio(HR)0.86, 95% confidence interval (CI): 0.65–1.13, P  = 0.28), disease-free survival/recurrence-free survival/metastasis-free survival (HR 0.87, 95% CI: 0.52–1.44, P  = 0.58) or disease-specific survival (HR 1.13, 95% CI: 0.44–2.87, P  = 0.8). Conclusion This study showed that the expression of KLF4 was not related to the prognosis of the tumours that were included in the study.

Purpose Aims to compare the prognostic performance of the number of positive lymph nodes (PLNN), lymph node ratio (LNR) and log odds of metastatic lymph nodes (LODDS) and establish a prognostic nomogram to predict overall survival (OS) rate for patients with endometrial carcinosarcoma (ECS). Methods Patients were retrospectively obtained from Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. The prognostic value of PLNN, LNR and LODDS were assessed. A prediction model for OS was established based on univariate and multivariate analysis of clinical and demographic characteristics of ECS patients. The clinical practical usefulness of the prediction model was valued by decision curve analysis (DCA) through quantifying its net benefits. Results The OS prediction accuracy of LODDS for ECS is better than that of PLNN and LNR. Five factors, age, tumor size, 2009 FIGO, LODDS and peritoneal cytology, were independent prognostic factors of OS. The C-index of the nomogram was 0.743 in the training cohort. The AUCs were 0.740, 0.682 and 0.660 for predicting 1-, 3- and 5-year OS, respectively. The calibration plots and DCA showed good clinical applicability of the nomogram, which is better than 2009 FIGO staging system. These results were verified in the validation cohort. A risk classification system was built that could classify ECS patients into three risk groups. The Kaplan-Meier curves showed that OS in the different groups was accurately differentiated by the risk classification system and performed much better than FIGO 2009. Conclusion Our results indicated that LODDS was an independent prognostic indicator for ECS patients, with better predictive efficiency than PLNN and LNR. A novel prognostic nomogram for predicting the OS rate of ECS patients was established based on the population in the SEER database. Our nomogram based on LODDS has a more accurate and convenient value for predicting the OS of ECS patients than the FIGO staging system alone.

Colorectal cancer (CRC) is the third most common type of cancer in the Western world and the second most frequent cause of cancer‐related death. Although diagnostic tools and therapeutic strategies were improved in the last decades, early detection is one of the most important factors for the prognosis of a patient. Additionally, the decision about the applied therapy is still based solely on clinical and pathological information. Therefore, the discovery of new biomarkers to facilitate early diagnosis enabling a more personalized treatment is strongly desirable. Aberrant expression of microRNAs (miRNAs) might be of potential use as diagnostic and prognostic biomarkers for CRC. Their ability to influence carcinogenesis and tumor progression has been observed in many cancer types including CRC. This chapter covers the current knowledge about miRNA expression signatures in blood plasma/serum and tumor tissues as well as their potential use as early detection markers or as prognostic and predictive biomarkers in CRC. In general, some miRNAs have shown to be promising biomarkers. Circulating miR‐141 expression was shown to be an independent prognostic marker for advanced CRC. In tumor tissue, the expressions of miR‐21, miR‐143, and miR‐145 were intensively studied and could be correlated with survival and therapy response. Although there is still need for further investigations and enlarged validation studies, expression analyses of a single or a set of multiple miRNAs are on the brink of utilization as routine clinical applications. Especially due to their high stability in fresh as well as formalin‐fixed and paraffin‐embedded (FFPE) tumor tissues, miRNAs can be helpful indicators toward the aim of an individually tailored cancer therapy.