Co-assembly of cisplatin and dasatinib in hyaluronan nanogel to combat triple negative breast cancer with reduced side effects.

Treatment for triple negative breast cancer (TNBC) remains a huge challenge due to the lack of targeted therapeutics and tumor heterogenicity. Cisplatin (Cis) have demonstrated favorable therapeutic response in TNBC and thus is used together with various kinase inhibitors to fight the heterogenicity of TNBC. The combination of Cis with SRC inhibitor dasatinib (DAS) has shown encouraging anti-TNBC efficacy although the additive toxicity was commonly observed. To overcome the severe side effects of this Cis involved therapy, here we co-encapsulated Cis and DAS into a self-assembled hyaluronan (HA) nanogel (designated as HA/Cis/DAS (HCD) nanogel) to afford the TNBC targeted delivery by using the 4T1 mouse model. The acquired HCD nanogel was around 181 nm in aqueous solution, demonstrating the pharmacological activities of both Cis and DAS. Taking advantages of HA's targeting capability towards CD44 that is overexpressed on many TNBC cells, the HCD could well maintain the anticancer efficacy of the Cis and DAS combination, significantly increase the maximum tolerated dose and relieve the renal toxicity in vivo. The current HCD nanogel provides a potent strategy to improve the therapeutic outcome of Cis and DAS combination and thus representing a new targeted treatment option for TNBC.

Unveiling the link between physical activity levels and dementia risk: Insights from the UK Biobank study.

BACKGROUND: There is limited information on the mixture effect and weights of light physical activity (LPA), moderate physical activity (MPA), and vigorous physical activity (VPA) on dementia risk. METHODS: A prospective cohort study was conducted based on the UK Biobank dataset. We included participants aged at least 45 years old without dementia at baseline between 2006-2010. The weighted quantile sum regression was used to explore the mixture effect and weights of three types of physical activity on dementia risk. RESULTS: This study includes 354,123 participants, with a mean baseline age of 58.0-year-old and 52.4 % of female participants. During a median follow-up time of 12.5 years, 5,136 cases of dementia were observed. The mixture effect of LPA, MPA, and VPA on dementia was statistically significant (ß: -0.0924, 95 % Confidence Interval (CI): (-0.1402, -0.0446), P < 0.001), with VPA (weight: 0.7922) contributing most to a lower dementia risk, followed by MPA (0.1939). For Alzheimer's disease, MPA contributed the most (0.8555); for vascular dementia, VPA contributed the most (0.6271). CONCLUSION: For Alzheimer's disease, MPA was identified as the most influential factor, while VPA stood out as the most impactful for vascular dementia.

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC. SIGNIFICANCE: PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.

Visible Light-Catalyzed Reactions of Polysulfide (DBSPS) with Aryldiazonium.

A visible light-catalyzed radical coupling reaction of polysulfide reagents with aryldiazonium was developed, which gave thiosulfonates under mild conditions. In this reaction, the thiosulfonates were isolated in good yields with a broad tolerance to functional groups. And the synthesis of diaryl monosulfides were achieved through a step-by-step reaction of two molecular aryldiazonium with DBSPS, where the sulfur source was provided by DBSPS. It was worth noting that the reaction of this monosulfides could also be achieved by a one pot two-step process. The described polysulfide reagents were able to produce three new radicals: sulfonyl radicals, sulfur-sulfonyl radicals and sulfur-sulfur-sulfonyl radicals.

Chinese cherry CpMYB44-CpSPDS2 module regulates spermidine content and florescence in tobacco.

The flower bud differentiation plays a crucial role in cherry yield and quality. In a preliminary study, we revealed the promotion of spermidine (Spd) in bud differentiation and quality. However, the molecular mechanism underlying Spd regulating cherry bud differentiation remains unclear. To address this research gap, we cloned CpSPDS2, a gene that encodes Spd synthase and is highly expressed in whole flowers and pistils of the Chinese cherry (cv. 'Manaohong'). Furthermore, an overexpression vector with this gene was constructed to transform tobacco plants. The findings demonstrated that transgenic lines exhibited higher Spd content, an earlier flowering time by 6 d, and more lateral buds and flowers than wild-type lines. Additionally, yeast one-hybrid assays and two-luciferase experiments confirmed that the R2R3-MYB transcription factor (CpMYB44) directly binds to and activates the CpSPDS2 promoter transcription. It is indicated that CpMYB44 promotes Spd accumulation via regulating CpSPDS2 expression, thus accelerating the flower growth. This research provides a basis for resolving the molecular mechanism of CpSPDS2 involved in cherry bud differentiation.

A machine learning-based predictive model of causality in orthopaedic medical malpractice cases in China.

PURPOSE: To explore the feasibility and validity of machine learning models in determining causality in medical malpractice cases and to try to increase the scientificity and reliability of identification opinions. METHODS: We collected 13,245 written judgments from PKULAW.COM, a public database. 963 cases were included after the initial screening. 21 medical and ten patient factors were selected as characteristic variables by summarising previous literature and cases. Random Forest, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) were used to establish prediction models of causality for the two data sets, respectively. Finally, the optimal model is obtained by hyperparameter tuning of the six models. RESULTS: We built three real data set models and three virtual data set models by three algorithms, and their confusion matrices differed. XGBoost performed best in the real data set, with a model accuracy of 66%. In the virtual data set, the performance of XGBoost and LightGBM was basically the same, and the model accuracy rate was 80%. The overall accuracy of external verification was 72.7%. CONCLUSIONS: The optimal model of this study is expected to predict the causality accurately.

Analysis of dissolved oxygen influencing factors and concentration prediction using input variable selection technique: A hybrid machine learning approach.

Accurate quantification of dissolved oxygen (DO) is critically important for the protection and management of aquatic ecosystems. Successful applications have utilized mechanistic and data-driven models to simulate DO content in aquatic ecosystems. However, mechanistic models present challenges due to their complex and difficult-to-solve conditions, making them less portable. Additionally, data-driven model predictions are hindered by the challenge of numerous input variables, impacting both the running speed and prediction performance of the model. To address these challenges, water quality data and meteorological data of the Tanjiang River were obtained. The maximum information coefficient (MIC) input variable selection technique was employed to identify primary environmental factors influencing DO changes. Furthermore, coupled with support vector regression (SVR), two models (SVR and MIC-SVR) were employed to estimate the DO concentration of the Tanjiang River, and the optimal model was established. The results indicated a shift in the primary pollution factor from ammonia nitrogen to total phosphorus after recent treatment in the Tanjiang River. In comparison with the SVR model, the root mean square error (RMSE) of the MIC-SVR model was reduced by 4.46%, and the Nash-efficiency coefficient (NSE) was improved by 45.85%. In addition, study of kernel function selection revealed that considering as many kernel functions as possible is necessary for improving the performance of the SVR model. Conclusively, the proposed MIC-SVR model serves as an effective tool to analyze the relationship between DO and environmental factors, identifying the primary causes of low DO, and accurately predict the DO concentration in the Tanjiang River (especially in its middle and lower reaches), thus providing a reference for governmental decision-making on water environmental protection and water resource management.

Improvement of social functioning in patients with first-episode schizophrenia using blonanserin treatment: a prospective, multi-centre, single-arm clinical trial.

Objectives: This clinical trial primarily aimed to investigate the effects of blonanserin on social functioning in patients with first-episode schizophrenia. Methods: In this prospective, multi-centre, single-arm clinical trial study, blonanserin (flexible oral dose ranging from 8mg to 24mg per day) was given 26 weeks. Outcome measures included the Personal and Social Performance (PSP) scale for evaluating social functioning, the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery (MCCB) for measuring neurocognitive performance, and the Positive and Negative Syndrome Scale (PANSS) for assessing symptom severity. The primary endpoint was social function improvement evaluated by PSP scale at the end of blonanserin treatment. And the secondary endpoint was to validate the efficacy and neurocognitive effects of blonanserin. Adverse drug reactions (ADRs) were also recorded and analysed. Results: A total of 96 patients with first-episode schizophrenia were recruited and proceeded to analysis. Fifty-one participants (53.1%) completed the PSP scale measurements at baseline and week 26. Following 26 weeks of blonanserin treatment, all outcome measurements demonstrated significant improvement during the follow-up period. Notably, PSP scores exhibited a continuous increase up to 68.1% ± 103.7% at the end of the treatment (46.6 ± 14.6 at baseline, 69.4 ± 17.4 at week 26, p<0.001), indicating positive effects on social functioning that were already noticeable by week 8. Conclusion: Blonanserin treatment exhibited favourable effects on social functioning in individuals with first-episode schizophrenia. The results suggest that blonanserin was effective treatment options for patients with schizophrenia encountering functional impairments.

Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis.

Background: The immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment of OA using multi-omics data. Methods: The discovery dataset integrated the GSE89408 and GSE143514 datasets to identify biomarkers that were significantly associated with the OA immune microenvironment through multiple machine learning methods and weighted gene co-expression network analysis (WGCNA). The identified signature genes were confirmed using two independent validation datasets. We also performed a two-sample mendelian randomization (MR) study to generate causal relationships between biomarkers and OA using OA genome-wide association study (GWAS) summary data (cases n = 24,955, controls n = 378,169). Inverse-variance weighting (IVW) method was used as the main method of causal estimates. Sensitivity analyses were performed to assess the robustness and reliability of the IVW results. Results: Three signature genes (FCER1G, HLA-DMB, and HHLA-DPA1) associated with the OA immune microenvironment were identified as having good diagnostic performances, which can be used as biomarkers. MR results showed increased levels of FCER1G (OR = 1.118, 95% CI 1.031-1.212, P = 0.041), HLA-DMB (OR = 1.057, 95% CI 1.045 -1.069, P = 1.11E-21) and HLA-DPA1 (OR = 1.030, 95% CI 1.005-1.056, P = 0.017) were causally and positively associated with the risk of developing OA. Conclusion: The present study identified the 3 potential immune-related biomarkers for OA, providing new perspectives for the prevention and treatment of OA. The MR study provides genetic support for the causal effects of the 3 biomarkers with OA and may provide new insights into the molecular mechanisms leading to the development of OA.

Interferon-γ+ Th1 activates intrahepatic resident memory T cells to promote HBsAg loss by inducing M1 macrophage polarization.

The immune mechanism underlying hepatitis B surface antigen (HBsAg) loss, particularly type I inflammatory response, during pegylated interferon-α (PEG-IFN) therapy remains unclear. In this study, we aimed to elucidate such immune mechanisms. Overall, 82 patients with chronic hepatitis B (CHB), including 41 with HBsAg loss (cured group) and 41 uncured patients, received nucleos(t)ide analogue and PEG-IFN treatments. Blood samples from all patients, liver tissues from 14 patients with CHB, and hepatic perfusate from 8 liver donors were collected for immune analysis. Jurkat, THP-1 and HepG2.2.15 cell lines were used in cell experiments. The proportion of IFN-γ+ Th1 cells was higher in the cured group than in the uncured group, which was linearly correlated with HBsAg decline and alanine aminotransferase (ALT) levels during treatment. However, CD8+ T cells were weakly associated with HBsAg loss. Serum and intrahepatic levels of Th1 cell-associated chemokines (C-X-C motif chemokine ligand [CXCL] 9, CXCL10, CXCL11, IFN-γ) were significantly lower in the cured patients than in patients with a higher HBsAg quantification during therapy. Serum from cured patients induced more M1 (CD68+CD86+ macrophage) cells than that from uncured patients. Patients with chronic HBV infection had significantly lower proportions of CD86+ M1 and CD206+ M2 macrophages in their livers than healthy controls. M1 polarization of intrahepatic Kupffer cells promoted HBsAg loss by upregulating the effector function of tissue-resident memory T cells with increased ALT levels. IFN-γ+ Th1 activates intrahepatic resident memory T cells to promote HBsAg loss by inducing M1 macrophage polarization.

Somatomotor-visual resting state functional connectivity increases after 2 years in the UK Biobank longitudinal cohort.

Purpose: Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been observed in children, in which high connectivity among all brain regions changes to a more modular structure with maturation. We examine FC changes in older adults after 2 years of aging in the UK Biobank (UKB) longitudinal cohort. Approach: We process fMRI connectivity data using the Power264 atlas and then test whether the average internetwork FC changes in the 2722-subject longitudinal cohort are statistically significant using a Bonferroni-corrected t-test. We also compare the ability of Power264 and UKB-provided, independent component analysis (ICA)-based FC to determine which of a longitudinal scan pair is older. Finally, we investigate cross-sectional FC changes as well as differences due to differing scanner tasks in the UKB, Philadelphia Neurodevelopmental Cohort, and Alzheimer's Disease Neuroimaging Initiative datasets. Results: We find a 6.8% average increase in somatomotor network (SMT)-visual network (VIS) connectivity from younger to older scans (corrected p<10-15) that occurs in male, female, older subject (>65 years old), and younger subject (<55 years old) groups. Among all internetwork connections, the average SMT-VIS connectivity is the best predictor of relative scan age. Using the full FC and a training set of 2000 subjects, one is able to predict which scan is older 82.5% of the time using either the full Power264 FC or the UKB-provided ICA-based FC. Conclusions: We conclude that SMT-VIS connectivity increases with age in the UKB longitudinal cohort and that resting state FC increases with age in the UKB cross-sectional cohort.

NK-cell-elicited gasdermin-D-dependent hepatocyte pyroptosis induces neutrophil extracellular traps that facilitate HBV-related acute-on-chronic liver failure-pyroptosis.

BACKGROUND AND AIMS: HBV infection is a major etiology of acute-on-chronic liver failure (ACLF). At present, the pattern and regulation of hepatocyte death during HBV-ACLF progression are still undefined. Evaluating the mode of cell death and its inducers will provide new insights for developing therapeutic strategies targeting cell death. In this study, we aimed to elucidate whether and how immune landscapes trigger hepatocyte death and lead to the progression of HBV-related ACLF. APPROACH AND RESULTS: We identified that pyroptosis represented the main cell death pattern in the liver of patients with HBV-related ACLF. Deficiency of MHC-I in HBV-reactivated hepatocytes activated cytotoxic NK cells, which in turn operated in a perforin/granzyme-dependent manner to trigger GSDMD/caspase-8-dependent pyroptosis of hepatocytes. Neutrophils selectively accumulated in the pyroptotic liver, and HMGB1 derived from the pyroptotic liver constituted an important factor triggering the generation of pathogenic extracellular traps in neutrophils (NETs). Clinically, elevated plasma levels of myeloperoxidase-DNA complexes were a promising prognostic biomarker for HBV-related ACLF. More importantly, targeting GSDMD pyroptosis-HMGB1 release in the liver abrogates NETs that intercept the development of HBV-related ACLF. CONCLUSIONS: Studying the mechanisms that selectively modulate GSDMD-dependent pyroptosis, as well as its immune landscapes, will provide a novel strategy for restoring the liver function of patients with HBV-related ACLF.

Effect of anatomical liver resection on early postoperative recurrence in patients with hepatocellular carcinoma assessed based on a nomogram: a single-center study in China.

Introduction: We aimed to investigate risk factors for early postoperative recurrence in patients with hepatocellular carcinoma (HCC) and determine the effect of surgical methods on early recurrence to facilitate predicting the risk of early postoperative recurrence in such patients and the selection of appropriate treatment methods. Methods: We retrospectively analyzed clinical data concerning 428 patients with HCC who had undergone radical surgery at Mianyang Central Hospital between January 2015 and August 2022. Relevant routine preoperative auxiliary examinations and regular postoperative telephone or outpatient follow-ups were performed to identify early postoperative recurrence. Risk factors were screened, and predictive models were constructed, including patients' preoperative ancillary tests, intra- and postoperative complications, and pathology tests in relation to early recurrence. The risk of recurrence was estimated for each patient based on a prediction model, and patients were categorized into low- and high-risk recurrence groups. The effect of anatomical liver resection (AR) on early postoperative recurrence in patients with HCC in the two groups was assessed using survival analysis. Results: In total, 353 study patients were included. Multifactorial logistic regression analysis findings suggested that tumor diameter (≥5/<5 cm, odds ratio [OR] 2.357, 95% confidence interval [CI] 1.368-4.059; P = 0.002), alpha fetoprotein (≥400/<400 ng/L, OR 2.525, 95% CI 1.334-4.780; P = 0.004), tumor number (≥2/<2, OR 2.213, 95% CI 1.147-4.270; P = 0.018), microvascular invasion (positive/negative, OR 3.230, 95% CI 1.880-5.551; P < 0.001), vascular invasion (positive/negative, OR 4.472, 95% CI 1.395-14.332; P = 0.012), and alkaline phosphatase level (>125/≤125 U/L, OR 2.202, 95% CI 1.162-4.173; P = 0.016) were risk factors for early recurrence following radical HCC surgery. Model validation and evaluation showed that the area under the curve was 0.813. Hosmer-Lemeshow test results (X 2 = 1.225, P = 0.996 > 0.05), results from bootstrap self-replicated sampling of 1,000 samples, and decision curve analysis showed that the model also discriminated well, with potentially good clinical utility. Using this model, patients were stratified into low- and high-risk recurrence groups. One-year disease-free survival was compared between the two groups with different surgical approaches. Both groups benefited from AR in terms of prevention of early postoperative recurrence, with AR benefits being more pronounced and intraoperative bleeding less likely in the high-risk recurrence group. Discussion: With appropriate surgical techniques and with tumors being realistically amenable to R0 resection, AR is a potentially useful surgical procedure for preventing early recurrence after radical surgery in patients with HCC.

Lysyl Oxidase Promotes the Formation of Vasculogenic Mimicry in Gastric Cancer through PDGF-PDGFR Pathway.

Objective: Vasculogenic mimicry (VM) generates an important supplementary form of blood supply in cancer, which many factors regulate. However, the effect of lysyl oxidase (LOX) on VM formation is unclear. In this study, gastric cancer tissues and cells were used to investigate the role of LOX in the formation of VM. Materials and Methods: The samples were collected from 49 patients with a final diagnosis of gastric cancer. According to metastasis (including lymph node metastases and distant metastases), gastric cancer samples were divided into metastasis and non-metastasis groups. Based on the degree of invasion, gastric cancer specimens were divided into T1 + T2 and T3 + T4 groups. The relative expression of LOX was detected using Western blot. The formation of VM was measured by double staining with CD34 and Periodic acid-Schiff (PAS) in gastric cancer tissue slices, and the correlation between LOX and VM was analyzed with Pearson's correlation analysis. Gastric cancer cell line BGC-803 was treated with LOX, ß-aminopropionitrile (BAPN, an inhibitor of LOX), and AG1295 or AG1296 (inhibitors of the platelet-derived growth factor receptor). The formation of VM was then measured using PAS staining. The expression of platelet-derived growth factor receptor (PDGFR)α and PDGFRß in gastric cancer cells was detected by Western blot. Results: In gastric cancer samples, the level of LOX was higher in the metastasis group than in the non-metastasis group (P < 0.05) and in the T3 + T4 group than in the T1 + T2 group (P < 0.05). VM formation was greater in the T3+T4 group than in the T1+T2 group (P < 0.05) and in the metastasis group than in the non-metastasis group (P < 0.05). The expression level of LOX was positively correlated with VM formation (P < 0.01). In gastric cancer cells, LOX concentration was positively correlated with the degree of VM, and BAPN concentration was negatively correlated with the degree of VM (P <0.05). PDGFR levels in the T3+T4 and metastasis groups were relatively higher (P <0.01) and positively correlated with LOX levels in gastric cancer specimens (P < 0.01). The relative expression of PDGFRα and PDGFRß in gastric cancer cells was up-regulated with increasing LOX and downregulated with increasing BAPN (P < 0.05). With inhibition of PDGFRα and PDGFRß using AG1295 or AG1296, VM formation in gastric cancer cells decreased (P <0.05), but the number of VM structures increased while LOX was added (P < 0.05). Conclusion: LOX partially promotes the formation of VM in gastric cancer through the PDGF-PDGFR signaling pathway.

Transcriptome and single-cell transcriptomics reveal prognostic value and potential mechanism of anoikis in skin cutaneous melanoma.

BACKGROUND: Skin cutaneous melanoma (SKCM) is a highly lethal cancer, ranking among the top four deadliest cancers. This underscores the urgent need for novel biomarkers for SKCM diagnosis and prognosis. Anoikis plays a vital role in cancer growth and metastasis, and this study aims to investigate its prognostic value and mechanism of action in SKCM. METHODS: Utilizing consensus clustering, the SKCM samples were categorized into two distinct clusters A and B based on anoikis-related genes (ANRGs), with the B group exhibiting lower disease-specific survival (DSS). Gene set enrichment between distinct clusters was examined using Gene Set Variation Analysis (GSVA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. RESULTS: We created a predictive model based on three anoikis-related differently expressed genes (DEGs), specifically, FASLG, IGF1, and PIK3R2. Moreover, the mechanism of these prognostic genes within the model was investigated at the cellular level using the single-cell sequencing dataset GSE115978. This analysis revealed that the FASLG gene was highly expressed on cluster 1 of Exhausted CD8( +) T (Tex) cells. CONCLUSIONS: In conclusion, we have established a novel classification system for SKCM based on anoikis, which carries substantial clinical implications for SKCM patients. Notably, the elevated expression of the FASLG gene on cluster 1 of Tex cells could significantly impact SKCM prognosis through anoikis, thus offering a promising target for the development of immunotherapy for SKCM.

Effects of yoga on clinical symptoms, quality of life and social functioning in patients with schizophrenia: A systematic review and meta-analysis.

BACKGROUND: Yoga is gradually being explored as a potential complementary intervention in addition to psychiatric drugs for schizophrenia. However, there are conflicts on the efficacy of yoga for schizophrenia. This meta-analysis was aimed to evaluate the association of yoga intervention with reductions on clinical symptoms and improvements in quality of life (QoL) as well as social functioning among schizophrenia. METHOD: Systematic literature search was undertaken to identify all RCTs that compared yoga with active or passive controls for patients with schizophrenia from inception to July 2023. The outcomes were measurements of positive symptoms, negative symptoms, QoL and social functioning. Random-effects models were performed to calculate the effect sizes in the standardized mean differences reporting as Hedges' s g statistic. RESULTS: 19 studies enrolling 1274 participants with schizophrenia were included. Yoga had a medium effect on positive symptoms in the short term (Hedges's g = 0.31) and small effect in the long term (Hedges's g = 0.18). Medium significant effects were also found on negative symptoms in both the short term (Hedges's g = 0.44) and the long term (Hedges's g = 0.35). Yoga had a significant impact on improving both total QoL (Hedges's g = 0.34) and social functioning (Hedges's g = 0.45) with medium effect sizes. CONCLUSIONS: Yoga was associated with significant reductions on negative and positive symptoms, and significant improvements in QoL as well as social functioning in patients with schizophrenia. Future research should explore the long-term efficacy of yoga for schizophrenia, encompassing more diverse populations.

Molecular characterization and evolutionary relationships of DOFs in four cherry species and functional analysis in sweet cherry.

The DOF (DNA binding with one finger) has multiple functions in plants. However, it has received little attention in the research field of cherries. In this study, the evolutionary relationship and molecular characterization of DOF in four cherry species were analyzed, revealing its expression pattern in sweet cherry. There are 23 members in Prunus avium cv. 'Tieton', 88 in Prunus cerasus, 53 in Cerasus × yedoensis, and 27 in Cerasus serrulata. Most of these genes are intron-less or non-intron, with a conserved C2-C2 domain. Due to heterozygosity and chromosomal ploidy, whole-genome duplication (WGD) events occur to varying degrees, and DOF genes are contracted during evolution. Furthermore, these genes are affected by purifying selection pressure. Under low-temperature treatment, the expression of PavDOF2 and PavDOF18 were significantly up-regulated, while that of PavDOF16 is significantly down-regulated. The expression of PavDOF9, PavDOF12, PavDOF14, PavDOF16, PavDOF17, PavDOF18, and PavDOF19 exhibits an increasing trend during flower development and varies during sweet cherry fruit development. PavDOF1, PavDOF8, PavDOF9, and PavDOF15 are localized in the nucleus but is not transcriptionally active. The findings systemically demonstrate the molecular characteristics of DOF in different cherry varieties, providing a basis for further research on the functions of these genes.

Structurally diverse cucurbitane-type triterpenoids from the tubers of Hemsleya chinensis with cytotoxic activity.

Ten previously undescribed cucurbitane-type triterpenoids, namely hemslyencins A-F (1-6) and hemslyencosides A-D (7-10), together with twenty previously reported compounds (11-30), were isolated from the tubers of Hemsleya chinensis. Their structures were elucidated by unambiguous spectroscopic data (UV, IR, HR-ESI-MS, 1D and 2D NMR data). Hemslyencins A and B (1 and 2) possessing unique 9, 11-seco-ring system with a six-membered lactone moiety, were the first examples among of the cucurbitane-type triterpenoids, and hemslyencins C and D (3 and 4) and hemslyencoside D (10) are the infrequent pentacyclic cucurbitane triterpenes featuring a 6/6/6/5/6 fused system. The cytotoxic activities of all isolated compounds were evaluated against MCF-7, HCT-116, HeLa, and HepG2 cancer cells, and their structure-activity relationships (SARs) was discussed as well. Compounds 17, 25, and 26 showed significant cytotoxic effects with IC50 values ranging from 1.31 to 9.89 µM, among which compound 25 induced both apoptosis and cell cycle arrest at G2/M phase in a dose dependent manner against MCF-7 cells.

CLCLSA: Cross-omics linked embedding with contrastive learning and self attention for integration with incomplete multi-omics data.

Integration of heterogeneous and high-dimensional multi-omics data is becoming increasingly important in understanding etiology of complex genetic diseases. Each omics technique only provides a limited view of the underlying biological process and integrating heterogeneous omics layers simultaneously would lead to a more comprehensive and detailed understanding of diseases and phenotypes. However, one obstacle faced when performing multi-omics data integration is the existence of unpaired multi-omics data due to instrument sensitivity and cost. Studies may fail if certain aspects of the subjects are missing or incomplete. In this paper, we propose a deep learning method for multi-omics integration with incomplete data by Cross-omics Linked unified embedding with Contrastive Learning and Self Attention (CLCLSA). Utilizing complete multi-omics data as supervision, the model employs cross-omics autoencoders to learn the feature representation across different types of biological data. The multi-omics contrastive learning is employed, which maximizes the mutual information between different types of omics. In addition, the feature-level self-attention and omics-level self-attention are employed to dynamically identify the most informative features for multi-omics data integration. Finally, a Softmax classifier is employed to perform multi-omics data classification. Extensive experiments were conducted on four public multi-omics datasets. The experimental results indicate that our proposed CLCLSA produces promising results in multi-omics data classification using both complete and incomplete multi-omics data.