A novel strategy for designing the magic shotguns for distantly related target pairs.

Due to its promising capacity in improving drug efficacy, polypharmacology has emerged to be a new theme in the drug discovery of complex disease. In the process of novel multi-target drugs (MTDs) discovery, in silico strategies come to be quite essential for the advantage of high throughput and low cost. However, current researchers mostly aim at typical closely related target pairs. Because of the intricate pathogenesis networks of complex diseases, many distantly related targets are found to play crucial role in synergistic treatment. Therefore, an innovational method to develop drugs which could simultaneously target distantly related target pairs is of utmost importance. At the same time, reducing the false discovery rate in the design of MTDs remains to be the daunting technological difficulty. In this research, effective small molecule clustering in the positive dataset, together with a putative negative dataset generation strategy, was adopted in the process of model constructions. Through comprehensive assessment on 10 target pairs with hierarchical similarity-levels, the proposed strategy turned out to reduce the false discovery rate successfully. Constructed model types with much smaller numbers of inhibitor molecules gained considerable yields and showed better false-hit controllability than before. To further evaluate the generalization ability, an in-depth assessment of high-throughput virtual screening on ChEMBL database was conducted. As a result, this novel strategy could hierarchically improve the enrichment factors for each target pair (especially for those distantly related/unrelated target pairs), corresponding to target pair similarity-levels.

IFI16-dependent STING signaling is a crucial regulator of anti-HER2 immune response in HER2+ breast cancer.

Relapse to anti-HER2 monoclonal antibody (mAb) therapies, such as trastuzumab in HER2+ breast cancer (BC), is associated with residual disease progression due to resistance to therapy. Here, we identify interferon-γ inducible protein 16 (IFI16)-dependent STING signaling as a significant determinant of trastuzumab responses in HER2+ BC. We show that down-regulation of immune-regulated genes (IRG) is specifically associated with poor survival of HER2+, but not other BC subtypes. Among IRG, IFI16 is identified as a direct target of EZH2, the underexpression of which leads to deficient STING activation and downstream CXCL10/11 expression in response to trastuzumab treatment. Dual inhibition of EZH2 and histone deacetylase (HDAC) significantly activates IFI16-dependent immune responses to trastuzumab. Notably, a combination of a novel histone methylation inhibitor with an HDAC inhibitor induces complete tumor eradication and long-term T cell memory in a HER2+ BC mouse model. Our findings demonstrate an epigenetic regulatory mechanism suppressing the expression of the IFI16-CXCL10/11 signaling pathway that provides a survival advantage to HER2+ BC to confer resistance to trastuzumab treatment.

Equivalent Response Strategy for Sensing Total Biothiols in Human Serums and Living Cells Using a Hemicyanine-Based Self-Immolative Probe.

Biothiols including cysteine (Cys), homocysteine (Hcy), and glutathione (GSH) are crucial in maintaining the redox balance in the body, and the metabolism and transportation of biothiols rely on the coreaction of diverse proteins and enzymes. The abnormal concentrations and metabolism of biothiols are closely associated with many diseases. However, due to the same active reaction site of the sulfydryl group in biothiols, it is inevitable to bear a confused signal of mutual influence on both nonselective detection and discriminate detection, which presents a serious challenge of accurately sensing or imaging the three biothiols. By assigning an α,ß-unsaturated ketone moiety as a Michael acceptor to trigger thiols to complete the irreversible equivalent domino response processes of nucleophilic addition, olefinic bond migration, and self-immolation, a targeted strategy was rationally pointed out, and herein, a hemicyanine-based probe CyOCy was prepared as a proof of strategy demonstration. The new probe could be equivalently lit up by Cys, Hcy, GSH, and even biothiol combinations (Cys/Hcy, Cys/GSH, Hcy/GSH, or Cys/Hcy/GSH) with unified linear ranges, detection limits, and response times. The probe CyOCy has been successfully used for the accurate quantification of total biothiols in the serum samples of healthy persons and coronary heart disease patients. In addition, the probe has been applied for cell screening, exogenous biothiol imaging, and monitoring drug-induced biothiol fluctuations. The purposive thinking of this work may provide an effective avenue for the accurate sensing of multicomponent samples.

LargeMetabo: an out-of-the-box tool for processing and analyzing large-scale metabolomic data.

Large-scale metabolomics is a powerful technique that has attracted widespread attention in biomedical studies focused on identifying biomarkers and interpreting the mechanisms of complex diseases. Despite a rapid increase in the number of large-scale metabolomic studies, the analysis of metabolomic data remains a key challenge. Specifically, diverse unwanted variations and batch effects in processing many samples have a substantial impact on identifying true biological markers, and it is a daunting challenge to annotate a plethora of peaks as metabolites in untargeted mass spectrometry-based metabolomics. Therefore, the development of an out-of-the-box tool is urgently needed to realize data integration and to accurately annotate metabolites with enhanced functions. In this study, the LargeMetabo package based on R code was developed for processing and analyzing large-scale metabolomic data. This package is unique because it is capable of (1) integrating multiple analytical experiments to effectively boost the power of statistical analysis; (2) selecting the appropriate biomarker identification method by intelligent assessment for large-scale metabolic data and (3) providing metabolite annotation and enrichment analysis based on an enhanced metabolite database. The LargeMetabo package can facilitate flexibility and reproducibility in large-scale metabolomics. The package is freely available from https://github.com/LargeMetabo/LargeMetabo.

A Bioinformatic Analysis of Gut Microbiota Related with Immune Cell Infiltration in Colorectal Cancer.

OBJECTIVE: The composition of microbiota which correlates with infiltrating immune cells and clinical signatures is not clarified in CRC. METHODS: We applied 4 kinds of bioinformatic tools GSVA (version: 1.42.0), ESTIMATE (version: 1.0.13), CIBERSORT (version: 2.0), and immune-related genes. RESULTS: We found that a total of 8 types of microbiotas appeared in the three immune correlation analyses. Among these microbiotas, significant enrichments in relative abundances associated with immune cell infiltration can be found for the dominant phyla Proteobacteria, Firmicutes, and Actinobacteria. Moreover, there existed correlations between some of the 8 microbiotas and clinical-related indicators. CONCLUSION: We identified some novel microbiotas involved in immune regulation in CRC.

Solid-State Surface-Anchoring Strategy to Prepare Anti-Sintering Supported Metal Cluster Catalysts.

Due to the unique geometric and electronic structures, supported metal clusters with sizes below 3 nm have appealed to great interest in heterogeneous catalysis. However, these supported ultrasmall metal clusters would endure severe particle coalescences under high reaction temperatures. Herein, based on the technology of ball-milling processing, we propose a solid-state "surface-anchoring" strategy to synthesize thermally stabilized Al2O3-supported Ni nanoclusters. Interestingly, when the theoretical Ni loading weight was 1 wt %, highly dispersed Ni species were found where no Ni nanoparticles would be seen after 500 °C calcination. Until the Ni loading weight increased to 5 wt % and the calcination temperature increased to 750 °C, the Ni nanoparticles became significant but still with a size of only about 6.8 nm. With the small Ni nanoparticles, the final 5-Ni-Al2O3-OAm-750 sample worked well as methane dry reforming catalysts with excellent anticoking performance during a 500 h stability test.

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives.

Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning- and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.

Identification and genetic diversity analysis of broomrape in Xinjiang, China.

BACKGROUND: As a holoparasitic weed, broomrape has seriously threatened the production of economically important crops, such as melon, watermelon, processed tomato, and sunflower, in Xinjiang in recent years. However, the distribution and genetic diversity of broomrape populations in Xinjiang are not clear at present, which hinders their prevention and control. The purpose of this study was to identify the main species and the genetic differentiation structure of the broomrape population in Xinjiang. METHODS AND RESULTS: In the present study, 93 samples from different geographic regions of Xinjiang were collected to identify the species based on ITS and plastid rps2 regions, and the samples were also used to analyze the genetic diversity based on ISSR markers. The results showed that broomrape is not monophyletic in Xinjiang and consists of two major clades (Orobanche cf. aegyptiaca and O. cernua) and three subclades (O. cf. aegyptiaca var. tch, O. cf. aegyptiaca var. klz, and O. cernua.var. alt) based on phylogenetic analysis. Furthermore, the results of the genetic diversity analysis indicated that the average polymorphic information content and marker index were high values of 0.58 and 7.38, respectively, showing the efficiency of the ISSR markers in detecting polymorphism among the broomrape population studied. Additionally, the 11 selected primers produced 154 repeatable polymorphic bands, of which 150 were polymorphic. The genetic diversity of the samples was 37.19% within populations and 62.81% among the populations, indicating that the main genetic differentiation occurred among the populations. There was less gene exchange between populations, with a gene flow index (Nm) of 0.2961 (< 1). The UPGMA dendrogram indicated that most populations with similar geographical conditions and hosts were clustered first, and then all samples were separated into two major groups and seven subclusters. CONCLUSION: The broomrapes are mainly O. cf. aegyptiaca and O. cernua in Xinjiang, which were separated into two major groups and seven subclusters based on ISSR markers. Our results provide a theoretical basis for breeding broomrape-resistant varieties.

Genome-wide identification and expression pattern analysis of the GRF transcription factor family in Astragalus mongholicus.

BACKGROUND: Astragalus membranaceus is a plant of the Astragalus genus, which is used as a traditional Chinese herbal medicine with extremely high medicinal and edible value. Astragalus mongholicus, as one of the representative medicinal materials with the same origin of medicine and food, has a rising market demand for its raw materials, but the quality is different in different production areas. Growth-regulating factors (GRF) are transcription factors unique to plants that play important roles in plant growth and development. Up to now, there is no report about GRF in A. mongholicus. METHODS AND RESULTS: This study conducted a genome-wide analysis of the AmGRF gene family, identifying a total of nine AmGRF genes that were classified into subfamily V based on phylogenetic relationships. In the promoter region of the AmGRF gene, we successfully predicted cis-elements that respond to abiotic stress, growth, development, and hormone production in plants. Based on transcriptomic data and real-time quantitative polymerase chain reaction (qPCR) validation, the results showed that AmGRFs were expressed in the roots, stems, and leaves, with overall higher expression in leaves, higher expression of AmGRF1 and AmGRF8 in roots, and high expression levels of AmGRF1 and AmGRF9 in stems. CONCLUSIONS: The results of this study provide a theoretical basis for the further exploration of the functions of AmGRFs in plant growth and development.

The influence of resourcefulness on the family functioning of young- and middle-aged lymphoma patients in China: a cross-sectional study.

BACKGROUND: Lymphoma has become 1 of the 10 most common cancers with increased prevalence in young- and middle-aged adults in China. This poses a tremendous burden on patients and their families and brings great challenges to maintaining the balance of family functioning in young- and middle-aged patients. OBJECTIVE: This cross-sectional study aimed to analyse the influence of resourcefulness on the family functioning of Chinese young- and middle-aged lymphoma patients. METHODS: A total of 172 Chinese young- and middle-aged patients with lymphoma were recruited from the oncology departments of two tertiary hospitals in Zhengzhou, Henan, China. They were invited to complete a survey that included a demographic questionnaire, the Resourcefulness Scale and the Chinese Version Family Adaptability and Cohesion Scale II. Multiple linear regression was used to analyse the related factors for family functioning. RESULTS: The multiple regression analysis revealed that the main influencing factors of family cohesion were resourcefulness (ß = 0.338, 95% CI (0.072, 0.173)), spouse caregiver (ß = 0.376, 95% CI (1.938, 10.395)), and cancer stage (ß = -0.274, 95% CI (-3.219, -1.047)). Resourcefulness (ß = 0.438, 95% CI (0.096, 0.181)), spouse caregiver (ß = 0.340, 95% CI (1.348, 8.363)), and family per capita monthly income (ß = 0.157, 95% CI (0.066, 2.243)) were the influencing factors of family adaptability. CONCLUSIONS: Healthcare professionals and family scholars should value young- and middle-aged lymphoma patients' family functioning throughout the cancer treatment process, and family interventions should be designed by healthcare providers based on patients' resourcefulness. Moreover, healthcare providers need to pay attention to the risk factors of patients' family cohesion and adaptability, such as low family per capita monthly income, and consider employing corresponding measures to help them.

The relationship between social frailty and loneliness in community-dwelling older adults: a cross-sectional study.

BACKGROUND: Social frailty (SF) is associated with multiple adverse health outcomes, yet there has been an inadequate focus on social frailty. The convoy model portrays the social networks through the perspective of the life course, thus providing a framework to explain the occurrence of social frailty. This study aimd to figure out the prevalence of social frailty and loneliness among community-dwelling older adults and to explore their correlations based on convoy model. METHODS: This was a cross-sectional study, and 295 older adults from 10 communities of Zhengzhou in Henan Province participated in the study. Social frailty and loneliness were assessed separately with the Social Frailty Scale and University of California at Los Angeles-Loneliness Scale. The scores of social frailty of the older adults in different characteristic communities were compared by independent sample t-test and single factor analysis of variance. The influencing factors of social frailty were analysed by multiple stepwise linear regression and the structural equation model. The correlation between social frailty and loneliness was analysed by Pearson correlation analysis. RESULTS: The total scores of social frailty and loneliness of the older adults in the community were (2.09 ± 1.53) and (43.19 ± 8.91), respectively. There was a moderate positive correlation between social frailty and loneliness (r = 0.621, P < 0.01). The results of multiple stepwise linear regression analysis showed that age, living styles, balance of payments, and loneliness were the main influencing factors of the social frailty of older adults in the community (F = 27.180, P < 0.001). The structural equation model of social frailty fitted well (χ2 = 47.292, df = 26, χ2/df = 1.819, P = 0.007; RMSEA = 0.053, 95%CI (0.028, 0.076), P = 0.359; GFI = 0.971; AGFI = 0.939; NFI = 0.904; IFI = 0.955; TLI = 0.918; CFI = 0.953; SRMR = 0.0466). CONCLUSIONS: The convoy model had certain applicability in explanation of the relationship between loneliness and social frailty among older adults in community. The incidence of social frailty among the older adults in the community was high, and loneliness was at a medium level. It is necessary to strengthen the intervention of social frailty and loneliness of the older adults in the community, improve the quality of life of the older adults, and promote the development of healthy aging.

Existing psychological supportive care interventions for cervical cancer patients: a systematic review and meta-analysis.

Cervical cancer patients commonly experience psychological supportive care needs, necessitating diverse interventions to enhance psychological well-being and alleviate physical symptoms. This systematic review, covering English-published articles from January 1999 to April 2023, assessed the impact of psychological supportive care interventions on anxiety and depression. Twenty-Six studies, including 11,638 patients, were analyzed, comprising randomized controlled trials; quasi-experimental, and pre-post-test designs from PubMed; Science Direct; Wiley online library; Google Scholar; Cochrane Library; and JSTOR. The extraction of data was done by two independent authors and a third independent author checked the data extraction. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 2020 statement was adopted. The population, intervention, comparator, and outcomes (PICO) search strategy was applied. Effective Public Health Practice Project (EPHPP) tool was used to assess the quality of selected articles. Various interventions, such as psychological nursing, exercise, counselling, psycho-curative approaches, peer and family education, psychotherapy, and medication, were identified. Two studies incorporated homework sessions, predominantly administered by nursing staff. Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS) were commonly used instruments. Statistical analysis revealed a significant difference in anxiety and depression scores between treatment and control groups (p < 0.005) post-intervention across all studies. A subsequent meta-analysis of eight homogeneous studies, utilizing a random-effects model, showed a moderate-to-high overall effect size (1.35, 95% CI: 0.75 to 1.94), indicating a statistically significant positive impact. Various studies exhibited variability in effect sizes ranging from low to high. While the meta-analysis included 936 participants, the forest plot visually represents individual study effect sizes and the combined effect size. Preliminary evidence supports the positive impact of psychological supportive care interventions on cervical cancer outcomes, urging further research, especially exploring long-term effects and employing rigorous study designs.

A simple and sensitive LC-MS/MS method for the determination of loganic acid in rat plasma and its pharmacokinetic analysis.

Loganic acid is an iridoid compound extracted from Gentianaceae plant Gentiana macrophylla Pall. It can effectively inhibit inflammation and tumor migration and has antioxidant activity. In this paper, we establish a simple, fast, sensitive and validated LC-MS method with the purpose of quantification of loganic acid in rat plasma with gliclazide as an internal standard (IS). Methanol was used to precipitate the protein in the plasma sample, and a C18 column (2.1 × 50 mm, 1.7 µm) was used for the separation of the target compound. Meanwhile, 0.1% formic acid water-methanol was employed as the mobile phase. Multiple reaction monitoring detection mode was adopted in detection with m/z 375.1 > 213.2 for loganic acid and m/z 322.1 > 169.9 for the IS, respectively, in negative ion scan mode. The linear range of calibration curve was 5.77-11,540.00 ng/ml, and the lower limit of detedtion was 2.89 ng/ml. The inter-day and intra-day precision and accuracy were <15% for lower limit of quantitation, low, middle and high quality control samples. This method was successfully used for the pharmacokinetic study of loganic acid in rat plasma at a dose range of 50-150 mg/kg for oral administration and 2 mg/kg for intravenous administration. The pharmacokinetic results showed that the oral bioavailability of loganic acid was low (2.71-5.58%).

Intelligent Fusion of Multi-Source Senses Information for Identifying the Nature of Five Flavors in Chinese Medicine: A Comprehensive Study of Five Classifications.

Objective: To develop a classification model for the five flavors of Chinese medicine using advanced multi-source intelligent sensory information fusion technology. The primary aim is to investigate the feasibility of applying this model to classify and identify the flavors of various Chinese medicines effectively. Methods: We selected 122 representative Chinese medicines, each exhibiting a single distinct flavor (sour, pungent, salty, sweet, bitter), along with 14 common foods. Utilizing the nature and flavors of these decoction pieces specified in Chinese Pharmacopeia (ChP)2020 and the inherent attributes of food components, we obtained valuable data from various sensors, including the PEN3 electronic nose, ASTREE electronic tongue, and SA402B electronic tongue. We then collected single-source data matrices from these sample sensors and a multi-source data matrix that combined the data from all sensors. Using discriminant analysis (DA), principal component analysis-discriminant analysis (PCA-DA), and K-nearest neighbor algorithm (KNN) three kinds of chemometric methods were used to establish five flavors and five-category discrimination models. The results were comprehensively evaluated with the highest correct rate of the model of leave-one-out cross-validation as the index. Results: Upon leave-one-out cross-validation, the correct judgment rate of the five flavors, five-category two-source fusion DA discrimination model (83.8%; ASTREE + SA402B) was significantly higher than the correct judgment rate of the single-source optimal DA and KNN model (73.5%; ASTREE). Following full-sample modeling, the correct judgment rate of the five flavors, five-category three-source fusion DA discrimination model (94.9%; PEN3+ASTREE+SA402B) rose substantially. This was higher than the correct judgment rate of the single-source optimal DA model (77.9%; ASTREE) and slightly higher than the two-source optimal correct judgment rate (89.7%; PEN3 + ASTREE). Conclusions: Compared to single-source identification, multi-source intelligent senses information fusion (MISIF) significantly improved accuracy, providing a new outlook for identifying flavor in Chinese medicine.

Phenotypic heterogeneity of mycosis fungoides cells leads to the difficulties in determining tumour origin.

Mycosis fungoides (MF) is a low-grade malignant cutaneous T-cell lymphoma that originates from memory T cells. It typically follows a unique and relatively indolent disease course. MF is used to be characterized by a tissue-resident memory T cell (TRM) phenotype, although recent molecular research has revealed its complexity, casting doubt on the cell of origin and the TRM-MF paradigm. Recent clonal heterogeneity studies suggest that MF may originate from immature early precursor T cells. During development, the tumour microenvironment (TME) influences tumour cell phenotype. The exact origin and development trajectory of MF remains elusive. Clarifying the origin of MF cells is vital for accurate diagnosis and effective treatment.

Major influencing factors identification and probabilistic health risk assessment of soil potentially toxic elements pollution in coal and metal mines across China: A systematic review.

Deposition of potentially toxic elements (PTEs) in soils due to different types of mining activities has been an increasingly important concern worldwide. Quantitative differences of soil PTEs contamination and related health risk among typical mines remain unclear. Herein, data from 110 coal mines and 168 metal mines across China were analyzed based on 265 published literatures to evaluate pollution characteristics, spatial distribution, and probabilistic health risks of soil PTEs. The results showed that PTE levels in soil from both mine types significantly exceeded background values. The geoaccumulation index (Igeo) revealed metal-mine soil pollution levels exceeded those of coal mines, with average Igeo values for Cd, Hg, As, Pb, Cu, and Zn being 3.02-15.60 times higher. Spearman correlation and redundancy analysis identified natural and anthropogenic factors affecting soil PTE contamination in both mine types. Mining activities posed a significant carcinogenic risk, with metal-mine soils showing a total carcinogenic risk an order of magnitude higher than in coal-mine soils. This study provides policymakers a quantitative foundation for developing differentiated strategies for sustainable remediation and risk-based management of PTEs in typical mining soils.

De novo transcriptional analysis of the response to starvation stress in the white ridgetail prawn, Exopalaemon carinicauda.

To study the mechanism of the biomolecular response in Exopalaemon carinicauda to starvation stress, we subjected muscle tissue RNA samples from four stress points, including 0 d(control group), 10 d, 20 d, and 30 d, to starvation stress on white ridgetail prawn with a body weight of 1.41 + 0.42 g, aquaculture water temperature of 23-25 °C, salinity of 26, dissolved oxygen ≥5 mg/L, and pH 8-8.5, Then performed de novo transcriptome assembly and gene expression analysis using BGISEQ-500 with a tag-based digital gene expression (DGE) system. By de novo assembling at the four times, we obtained 28,167, 21,115, 24,497, and 27,080 reads, respectively. The results showed that the stress at 10 d led to no significant difference in the expressed genes, while the stress at 20 d and 30 d showed a significant increase (or decrease) in the expression of 97 (276) and 143 (410) genes, respectively, which were involved in 8 different metabolic pathways. In addition, we detected 2647 unigene transcription factors. Eleven upregulated and sixteen downregulated genes from the different starvation stress groups were choose to verify the reliability of the transcriptome data, and the results showed that the expression trends of these genes were consistent with the results shown by the transcriptome. The analysis of the experimental data and our discussion of the response mechanism of white ridgetail prawn under starvation stress provides a foundation for further screening of the key genes of starvation stress and may help to elucidate their functions.

Absolute Ranging with Time Delay Interferometry for Space-Borne Gravitational Wave Detection.

In future space-borne gravitational wave (GW) detectors, time delay interferometry (TDI) will be utilized to reduce the overwhelming noise, including the laser frequency noise and the clock noise etc., by time shifting and recombining the data streams in post-processing. The successful operation of TDI relies on absolute inter-satellite ranging with meter-level precision. In this work, we numerically and experimentally demonstrate a strategy for inter-satellite distance measurement. The distances can be coarsely determined using the technique of arm-locking ranging with a large non-ambiguity range, and subsequently TDI can be used for precise distance measurement (TDI ranging) by finding the minimum value of the power of the residual noises. The measurement principle is introduced. We carry out the numerical simulations, and the results show millimeter-level precision. Further, we perform the experimental verifications based on the fiber link, and the distances can be measured with better than 0.05 m uncertainty, which can well satisfy the requirement of time delay interferometry.

Synthesis, characterization and in vitro antiproliferative effects of isosteviol derivatives.

Nineteen isosteviol derivatives were designed and synthesized by C-16, C-19 and D-ring modifications of isosteviol. These compounds were screened for their cytotoxic activities against Hela and A549 cells in vitro. Among them, the inhibitory effect of compounds 3b and 16 on Hela cells was comparable to that of the positive control gefitinib, and the compounds 3b (IC50=7.84 ± 0.84 µM) and 7a (IC50=6.89 ± 0.33 µM) exhibited significant cytotoxicity superior to gefitinib (IC50=11.02 ± 3.27 µM) against A549 cells.

Bone-Differentiation-Associated Circ-Spen Regulates Death of Mouse Bone Marrow Mesenchymal Stem Cells by Inhibiting Apoptosis and Promoting Autophagy.

The role of estrogen receptor ß (ERß) in bone health is closely associated with its function in vivo, and ERß-/- mice have been widely utilized to explore the related influences. In this study, ERß-/- female mice were established to investigate the differential expression of circular RNAs (circRNAs) by RNA-Sequencing (RNA-Seq). Among these circRNAs, mmu_circ_0011379 (named Circ-Spen) exhibited high expression in ERß-/- female mice. However, the precise mechanism by which Circ-Spen regulates bone health remained unclear. This study identified Circ-Spen as a positive regulator of mouse bone marrow mesenchymal stem cell (mBMSC) viability. The expression of Circ-Spen was markedly increased in ERß-/- mice femurs tested by RT-qPCR. Moreover, Circ-Spen exhibited an enhanced expression during the bone formation process of mBMSCs. Qualitative experiments also demonstrated that Circ-Spen possessed a circular structure and was localized within the nucleus of mBMSCs. Functionally, it inhibited apoptosis via caspase-3, BCL-2, and BAX, while also promoting autophagy through BECN1 and P62 in mBMSCs tested by MTT assays, transmission electron microscopy (TEM), and Western blotting. These findings reveal the potential of targeting Circ-Spen as a promising therapeutic strategy for rejuvenating senescent mBMSCs and enhancing the efficiency of mBMSC transplantation, which lays the foundation for advancements in the field of bone therapy.