Imageable Brachytherapy with Chelator-Free Radiolabeling Hydrogel.

Brachytherapy stands as an essential clinical approach for combating locally advanced tumors. Here, an injectable brachytherapy hydrogel is developed for the treatment of both local and metastatic tumor. Fe-tannins nanoparticles are efficiently and stably radiolabeled with clinical used therapeutic radionuclides (such as 131I, 90Y, 177Lu, and 225Ac) without a chelator, and then chemically cross-linked with 4-armPEG-SH to form brachytherapy hydrogel. Upon intratumoral administration, magnetic resonance imaging (MRI) signal from ferric ions embedded within the hydrogel directly correlates with the retention dosage of radionuclides, which can real-time monitor radionuclides emitting short-range rays in vivo without penetration limitation during brachytherapy. The hydrogel's design ensures the long-term tumor retention of therapeutic radionuclides, leading to the effective eradication of local tumor. Furthermore, the radiolabeled hydrogel is integrated with an adjuvant to synergize with immune checkpoint blocking therapy, thereby activating potent anti-tumor immune responses and inhibiting metastatic tumor growth. Therefore, this work presents an imageable brachytherapy hydrogel for real-time monitoring therapeutic process, and expands the indications of brachytherapy from treatment of localized tumors to metastatic tumors.

SOX9 Promotes Collagen VI Secretion by Upregulating PCOLCE in Neurofibroma.

Neurofibromatosis type 1 (NF1) is caused by NF1 gene mutations. Patients with NF1 often have complications with tumors, such as neurofibroma. In order to investigate the pathogenesis of human neurofibroma, a systematic comparison of protein expression levels between Schwann cell-like sNF96.2 cells, which originated from malignant peripheral nerve sheath tumors (MPNST), and normal Schwann cells was performed using 4-D label-free proteomic analysis. In addition, the expression levels and localization of dysregulated proteins were confirmed using a Gene Expression Omnibus (GEO) transcriptomic dataset, Western blot analysis, and immunofluorescence labeling. The effects of SRY-box transcription factor 9 (SOX9) in the neurofibroma and surrounding microenvironment were evaluated in vivo using a tumor transplantation model. The present study observed that SOX9 and procollagen C-endopeptidase enhancer (PCOLCE) were significantly altered. NF1 mutation promoted the nuclear translocation and transcriptional activity of SOX9 in neurofibromas. SOX9 increased collagen VI secretions by enhancing the activation of PCOLCE in neurofibroma cells. These findings might provide new perspectives on the pathophysiological significance of SOX9 in neurofibromas and elucidate a novel molecular mechanism underlying neurofibromas.

Genetic Algorithm-Based Receptor Ligand: A Genetic Algorithm-Guided Generative Model to Boost the Novelty and Drug-Likeness of Molecules in a Sampling Chemical Space.

Deep learning-based de novo molecular design has recently gained significant attention. While numerous DL-based generative models have been successfully developed for designing novel compounds, the majority of the generated molecules lack sufficiently novel scaffolds or high drug-like profiles. The aforementioned issues may not be fully captured by commonly used metrics for the assessment of molecular generative models, such as novelty, diversity, and quantitative estimation of the drug-likeness score. To address these limitations, we proposed a genetic algorithm-guided generative model called GARel (genetic algorithm-based receptor-ligand interaction generator), a novel framework for training a DL-based generative model to produce drug-like molecules with novel scaffolds. To efficiently train the GARel model, we utilized dense net to update the parameters based on molecules with novel scaffolds and drug-like features. To demonstrate the capability of the GARel model, we used it to design inhibitors for three targets: AA2AR, EGFR, and SARS-Cov2. The results indicate that GARel-generated molecules feature more diverse and novel scaffolds and possess more desirable physicochemical properties and favorable docking scores. Compared with other generative models, GARel makes significant progress in balancing novelty and drug-likeness, providing a promising direction for the further development of DL-based de novo design methodology with potential impacts on drug discovery.

Effectiveness of Mindfulness-Based Stress Reduction on Mental Health and Psychological Quality of Life among University Students: A GRADE-Assessed Systematic Review.

Background: Psychological distress is a progressive health problem that has been linked to decreased quality of life among university students. This meta-analysis reviews existing randomized controlled trials (RCTs) that have examined the effects of mindfulness-based stress reduction (MBSR) on the relief of psychosomatic stress-related outcomes and quality of life among university students. Methods: The PubMed, EMBASE, Web of Science, PsycINFO (formerly PsychLit), Ovid MEDLINE, ERIC, Scopus, Google Scholar, ProQuest, and Cochrane Library databases were searched in November 2023 to identify the RCTs for analysis. Data on pathology (anxiety, depression, and perceived stress), physical capacity (sleep quality and physical health), and well-being (mindfulness, self-kindness, social function, and subjective well-being) were analyzed. Results: Of the 276 articles retrieved, 29 met the inclusion criteria. Compared with control therapies, the pooled results suggested that MBSR had significant effects, reducing anxiety (SMD = -0.29; 95% CI: -0.49 to -0.09), depression (SMD = -0.32; 95% CI: -0.62 to -0.02), and perceived stress (SMD = -0.41; 95% CI: -0.60 to -0.29) and improving mindfulness (SMD = 0.34; 95% CI: 0.08 to 0.59), self-kindness (SMD = 0.57; 95% CI: 0.30 to 1.12), and physical health (SMD = -0.59; 95% CI: -1.14 to -0.04). No significant differences were observed in sleep quality (SMD = -0.20; 95% CI: -0.06 to 0.20), social function (SMD = -0.71; 95% CI: -2.40 to 0.97), or subjective well-being (SMD = 0.07; 95% CI: -0.18 to 0.32). The quality of the evidence regarding sleep quality and physical health outcomes was low. Conclusions: MBSR therapy appears to be potentially useful in relieving functional emotional disorders. However, additional evidence-based large-sample trials are required to definitively determine the forms of mindfulness-based therapy that may be effective in this context and ensure that the benefits obtained are ongoing. Future studies should investigate more personalized approaches involving interventions that are tailored to various barriers and students' clinical characteristics. To optimize the effects of such interventions, they should be developed and evaluated using various designs such as the multiphase optimization strategy, which allows for the identification and tailoring of the most valuable intervention components.

pH-responsive resveratrol-loaded ZIF-8 nanoparticles modified with tannic acid for promoting colon cancer cell apoptosis.

Resveratrol (Res) is known for its potential in treating various types of cancers, with a particular advantage of causing minimal toxic side effects. However, its clinical application is constrained by challenges such as poor bioavailability, low water solubility, and chemical instability in neutral and alkaline environments. In light of these limitations, we have developed a pH-responsive drug delivery nanoplatform, Res@ZIF-8/TA NPs, which exhibits good biocompatibility and shows promise for in vitro cancer therapy. Benefiting from the mild reaction conditions provided by zeolitic imidazolate frameworks (ZIFs), a "one-pot method" was used for drug synthesis and loading, resulting in a satisfactory loading capacity. Notably, Res@ZIF-8/TA NPs respond to acidic environments, leading to an improved drug release profile with a controlled release effect. Our cell-based experiments indicated that tannic acid (TA) modification enhances the biocompatibility of ZIFs. 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di- phenytetrazoliumromide (MTT assay), Hoechst 33342/PI staining, cell scratch assay, Transwell and Reverse Transcription quantitative PCR (RT-qPCR) assays further demonstrated that Res@ZIF-8/TA NPs inhibited colon cancer cell migration and invasion, and promoted apoptosis of colon cancer cells, suggesting a therapeutic potential and demonstrating anti-cancer properties. In conclusion, the Res@ZIF-8/TA NPs pH-responsive drug delivery systems we developed may offer a promising avenue for cancer therapy. By addressing some of the challenges associated with Res-based treatments, this system could contribute to advancements in cancer therapeutics.

PROTOCOL: Effectiveness of home-based interventions to prevent child neglect: A systematic review.

This is the protocol for a Campbell systematic review. The objectives are as follows. The objectives of the present study are to answer the following questions: (1) What types of home-based interventions are currently being studied to prevent child neglect? (2) How effective are the different home-based interventions for preventing child neglect? (3) What are the causes of heterogeneity among included studies and their impact on study effects?

Comprehensive analysis of immune-related genes associated with the microenvironment of patients with unexplained infertility.

Background: Disturbances in immunological responses and modulation lead to implantation and pregnancy failure and might be involved in the pathogenesis of infertility. This project aimed to screen and identify immune-related genes as potential biomarkers for treatment. Methods: Gene expression profiles were obtained from Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were screened using GEO 2R to explore potential biomarkers. Protein-protein interaction (PPI) network analysis and functional enrichment analysis were applied to explore possible mechanisms. The deconvolution algorithm [referred to as Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT)] was employed to assess tissue-infiltrating immune cells. Western blot analysis and immunohistochemistry (IHC) were conducted for determination of protein levels. Results: In this research, we identified 24 candidate immune-related DEGs via combined DEGs and functional analysis. We also found that the ratio of M0 macrophages and resting mast cells was higher in infertile group (P<0.05), whereas the amounts of activated natural killer (NK) cells was significantly lower compared with the control group (P<0.05). Furthermore, we evaluated the relationship between immune cells and candidate genes and found that 17 genes were related to M0 macrophages, resting mast cells, or activated NK cells. The genes CD40, PRF1, and EDN3 were chosen based on validation from independent datasets. Finally, our clinical samples confirmed the expression of the 3 genes. Conclusions: The study recognized 3 genes that are signatures and could be potential biomarkers for unexplained infertility. These genes might guide the immunotherapy of these patients and become new treatment targets.

Transformer-based deep learning method for optimizing ADMET properties of lead compounds.

A successful drug needs to exhibit both effective pharmacodynamics (PD) and safe pharmacokinetics (PK). However, the coordinated optimization of PD and PK properties in molecule generation tasks remains a great challenge for most existing methods, especially when they focus on the pursuit of affinity and selectivity for the lead compound. Thus, molecular optimization for PK properties is a critical step in the drug discovery pipeline, in which absorption, distribution, metabolism, excretion and toxicity (ADMET) property predictive models play an increasingly important role by providing an effective method to assess multiple PK properties of compounds. Here, we proposed a Graph Bert-based ADMET prediction model that achieves state-of-the-art performance on the public dataset Therapeutics Data Commons (TDC) by combining molecular graph features and descriptor features, with 11 tasks ranked first and 20 tasks ranked in the top 3. Based on this prediction model, we trained a Transformer model with multiple properties as constraints for learning the structural transformations involved in MMP and the accompanying property changes. The experimental results show that the trained Constraints-Transformer can implement targeted modifications to the starting molecule, while preserving the core scaffold. Moreover, molecular docking and binding mode analysis demonstrate that the optimized molecules still retain the activity and selectivity for biological targets. Therefore, the proposed method accounts for biological activity and ADMET properties simultaneously. Finally, a webserver containing ADMET property prediction and molecular optimization functions is provided, enabling chemists to improve the properties of starting molecules individually.

Investigating the Dynamic Binding Behavior of PMX53 Cooperating with Allosteric Antagonist NDT9513727 to C5a Anaphylatoxin Chemotactic Receptor 1 through Gaussian Accelerated Molecular Dynamics and Free-Energy Perturbation Simulations.

C5a anaphylatoxin chemotactic receptor 1 (C5aR1) is an important target in anti-inflammatory therapeutics. The cyclic peptide antagonist PMX53 binds to the orthosteric site located in the extracellular vestibule of C5aR1, and the non-peptide antagonist NDT9513727 binds to the allosteric site formed by the middle region of TM3 (trans-membrane helix), TM4, and TM5. We catch a sight of the variational binding mode of PMX53 during the Gaussian accelerated molecular dynamic (GaMD) simulations. In the binary complex of C5aR1 and PMX53, the PMX53 takes a dynamic binding mechanism during the simulation. Namely, the side chain of Arg6 of PMX53 extends to TM6-TM7 (pose 1) or swings to TM5 (pose 2), forming a salt bridge with Glu199. Meanwhile, in the ternary complex of C5aR1 with PMX53 and NDT9513727, the side chain of Arg6 of PMX53 swings to TM5 (pose 2) from extending to TM6-TM7 (pose 1) at the beginning of the GaMD simulation. In subsequent simulation, PMX53 stabilizes in the pose 2 binding mode by forming a stable salt bridge with Glu199. The free-energy perturbation (FEP) calculations demonstrate that pose 1 (ΔGbinding = -10.94 kcal/mol) is more stable in the binary complex and pose 2 (ΔGbinding = -7.91 kcal/mol) is unstable because of highly dynamic TM5. NDT9513727 interacts directly with TM4 and TM5 and stabilizes the hydrophobic stack between the extracellular sides of the two helices. Therefore, pose 2 (ΔGbinding = -16.27 kcal/mol) is notably stable than pose 1 (ΔGbinding = -9.78 kcal/mol) in the ternary complex. The identification of a novel binding mode of PMX53 and the detailed structural information of PMX53 interacting with a receptor obtained by GaMD simulations will be helpful in designing potent antagonists of C5aR1.

Accelerating the discovery of anticancer peptides targeting lung and breast cancers with the Wasserstein autoencoder model and PSO algorithm.

In the development of targeted drugs, anticancer peptides (ACPs) have attracted great attention because of their high selectivity, low toxicity and minimal non-specificity. In this work, we report a framework of ACPs generation, which combines Wasserstein autoencoder (WAE) generative model and Particle Swarm Optimization (PSO) forward search algorithm guided by attribute predictive model to generate ACPs with desired properties. It is well known that generative models based on Variational AutoEncoder (VAE) and Generative Adversarial Networks (GAN) are difficult to be used for de novo design due to the problems of posterior collapse and difficult convergence of training. Our WAE-based generative model trains more successfully (lower perplexity and reconstruction loss) than both VAE and GAN-based generative models, and the semantic connections in the latent space of WAE accelerate the process of forward controlled generation of PSO, while VAE fails to capture this feature. Finally, we validated our pipeline on breast cancer targets (HIF-1) and lung cancer targets (VEGR, ErbB2), respectively. By peptide-protein docking, we found candidate compounds with the same binding sites as the peptides carried in the crystal structure but with higher binding affinity and novel structures, which may be potent antagonists that interfere with these target-mediated signaling.

RELATION: A Deep Generative Model for Structure-Based De Novo Drug Design.

Deep learning (DL)-based de novo molecular design has recently gained considerable traction. Many DL-based generative models have been successfully developed to design novel molecules, but most of them are ligand-centric and the role of the 3D geometries of target binding pockets in molecular generation has not been well-exploited. Here, we proposed a new 3D-based generative model called RELATION. In the RELATION model, the BiTL algorithm was specifically designed to extract and transfer the desired geometric features of the protein-ligand complexes to a latent space for generation. The pharmacophore conditioning and docking-based Bayesian sampling were applied to efficiently navigate the vast chemical space for the design of molecules with desired geometric properties and pharmacophore features. As a proof of concept, the RELATION model was used to design inhibitors for two targets, AKT1 and CDK2. The calculation results demonstrated that the RELATION model could efficiently generate novel molecules with favorable binding affinity and pharmacophore features.

Loss of RPS27a expression regulates the cell cycle, apoptosis, and proliferation via the RPL11-MDM2-p53 pathway in lung adenocarcinoma cells.

BACKGROUND: Depletion of certain ribosomal proteins induces p53 activation, which is mediated mainly by ribosomal protein L5 (RPL5) and/or ribosomal protein L11 (RPL11). Therefore, RPL5 and RPL11 may link RPs and p53 activation. Thus, this study aimed to explore whether RPs interact with RPL11 and regulate p53 activation in lung adenocarcinoma (LUAD) cells. METHODS: The endogenous RPL11-binding proteins in A549 cells were pulled down through immunoprecipitation and identified with a proteomics approach. Docking analysis and GST-fusion protein assays were used to analyze the interaction of ribosomal protein S27a (RPS27a) and RPL11. Co-immunoprecipitation and in vitro ubiquitination assays were used to detect the effects of knockdown of RPS27a on the interaction between RPS27a and RPL11, and on p53 accumulation. Cell cycle, apoptosis, cell invasion and migration, cell viability and colony-formation assays were performed in the presence of knockdown of RPS27a. The RPS27a mRNA expression in LUAD was analyzed on the basis of the TCGA dataset, and RPS27a expression was detected through immunohistochemistry in LUAD samples. Finally, RPS27a and p53 expression was analyzed through immunohistochemistry in A549 cell xenografts with knockdown of RPS27a. RESULTS: RPS27a was identified as a novel RPL11 binding protein. GST pull-down assays revealed that RPS27a directly bound RPL11. Knockdown of RPS27a weakened the interaction between RPS27a and RPL11, but enhanced the binding of RPL11 and murine double minute 2 (MDM2), thereby inhibiting the ubiquitination and degradation of p53 by MDM2. Knockdown of RPS27a stabilized p53 in an RPL11-dependent manner and induced cell viability inhibition, cell cycle arrest and apoptosis in a p53-dependent manner in A549 cells. The expression of RPS27a was upregulated in LUAD and correlated with LUAD progression and poorer prognosis. Overexpression of RPS27a correlated with upregulation of p53, MDM2 and RPL11 in LUAD clinical specimens. Knockdown of RPS27a increased p53 activation, thus, suppressing the formation of A549 cell xenografts in nude mice. CONCLUSIONS: RPS27a interacts with RPL11, and RPS27a knockdown enhanced the binding of RPL11 and MDM2, thereby inhibiting MDM2-mediated p53 ubiquitination and degradation; in addition, RPS27a as important roles in LUAD progression and prognosis, and may be a therapeutic target for patients with LUAD.

Comparison of life quality in older adults living in traditional family versus nursing home: a systematic review and meta-analysis.

To assess and compare the QoL of the older people dwelling in traditional family versus nursing home/institution. A comprehensive literature search was performed on 10 January 2018 to identify studies that investigated the QoL of older adults dwelling in family versus nursing home settings. Analyses were run using random-effects meta-analyses. A total of six cross-sectional studies with 1623 people were included. The quality of included studies was moderate. Meta-analysis showed that compared with nursing home support, the family support could significantly improve the physical health (6 studies, SMD = 0.50, 95%CI: 0.32-0.68, p < 0.05), mental status (6 studies, SMD = 0.45, 95%CI: 0.26-0.65, p < 0.05), and social relationship (5 studies, SMD = 0.51, 95%CI: 0.19-0.83, p < 0.05). Traditional family support model demonstrated a significant improvement in the physical health, psychological status and social relationships among older adults. The conclusions were driven by cross-sectional studies, Larger, adequately powered RCTs are required to confirm our finding.

Mechanism of Fuzheng Kang'ai Formula Regulating Tumor Microenvironment in Non-Small Cell Lung Cancer.

OBJECTIVE: To study the mechanism of Chinese herbal medicine Fuzheng Kang'ai Formula (, FZKA) on tumor microenvironment (TME). METHODS: CIBERSORTx was used for analysis of TME. Traditional Chinese Medicine Systems Pharmacology and Analysis Platform was applied to identify compounds-targets network and the Cancer Genome Atlas (TCGA) was employed to identify the differential expression genes (DEGs) between tumor and paracancerous tissues in lung adenocarcinoma (LUAD) from TCGA-LUAD. Additionally, DEGs with prognosis in LUAD was calculated by univariable and multivariate Cox regression. The core targets of FZKA were analyzed in lung adenocarcinoma TME. Protein-protein interaction database was employed to predict down-stream of target. Quantitative reverse transcription polymerase chain reaction was employed for biological experiment in A549, H1299 and PC9 cell lines. RESULTS: The active and resting mast cells were significantly associated with prognosis of LUAD (P<0.05). Of the targets, CCNA2 as an important target of FZKA (hazard ratio=1.41, 95% confidential interval: 1.01-2.01, P<0.05) was a prognostic target and significantly associated with mast cells. CCNA2 was positively correlated with mast cell activation and negatively correlated with mast cell resting state. BCL1L2, ACTL6A and ITGAV were down-stream of CCNA2, which were validated by qRT-PCR in A549 cell. CONCLUSION: FZKA could directly bind to CCNA2 and inhibit tumor growth by regulating CCNA2 downstream genes and TME of NSCLC closely related to CCNA2.

High Moesin Expression Is a Predictor of Poor Prognosis of Breast Cancer: Evidence From a Systematic Review With Meta-Analysis.

Owing to metastases and drug resistance, the prognosis of breast cancer is still dismal. Therefore, it is necessary to find new prognostic markers to improve the efficacy of breast cancer treatment. Literature shows a controversy between moesin (MSN) expression and prognosis in breast cancer. Here, we aimed to conduct a systematic review and meta-analysis to evaluate the prognostic relationship between MSN and breast cancer. Literature retrieval was conducted in the following databases: PubMed, Web of Science, Embase, and Cochrane. Two reviewers independently performed the screening of studies and data extraction. The Gene Expression Omnibus (GEO) database including both breast cancer gene expression and follow-up datasets was selected to verify literature results. The R software was employed for the meta-analysis. A total of 9 articles with 3,039 patients and 16 datasets with 2,916 patients were ultimately included. Results indicated that there was a significant relationship between MSN and lymph node metastases (P < 0.05), and high MSN expression was associated with poor outcome of breast cancer patients (HR = 1.99; 95% CI 1.73-2.24). In summary, there is available evidence to support that high MSN expression has valuable importance for the poor prognosis in breast cancer patients. SYSTEMATIC REVIEW REGISTRATION: https://inplasy.com/inplasy-2020-8-0039/.

Transformer-Based Generative Model Accelerating the Development of Novel BRAF Inhibitors.

The de novo drug design based on SMILES format is a typical sequence-processing problem. Previous methods based on recurrent neural network (RNN) exhibit limitation in capturing long-range dependency, resulting in a high invalid percentage in generated molecules. Recent studies have shown the potential of Transformer architecture to increase the capacity of handling sequence data. In this work, the encoder module in the Transformer is used to build a generative model. First, we train a Transformer-encoder-based generative model to learn the grammatical rules of known drug molecules and a predictive model to predict the activity of the molecules. Subsequently, transfer learning and reinforcement learning were used to fine-tune and optimize the generative model, respectively, to design new molecules with desirable activity. Compared with previous RNN-based methods, our method has improved the percentage of generating chemically valid molecules (from 95.6 to 98.2%), the structural diversity of the generated molecules, and the feasibility of molecular synthesis. The pipeline is validated by designing inhibitors against the human BRAF protein. Molecular docking and binding mode analysis showed that our method can generate small molecules with higher activity than those carrying ligands in the crystal structure and have similar interaction sites with these ligands, which can provide new ideas and suggestions for pharmaceutical chemists.

Prognosis biomarker and potential therapeutic target CRIP2 associated with radiosensitivity in NSCLC cells.

Radiotherapy plays a major role in non-small cell lung cancer (NSCLC) treatment. The curative efficacy of advanced NSCLC is unsatisfactory because of its radioresistance to conventional radiotherapy. The biomarkers which can be used to diagnose radiosensitivity or predict for prognosis are beneficial in promoting curative effects. In this study, NSCLC cell lines with acquired radioresistance to X-rays were obtained through fractionated irradiation. The differentially expressed proteins (DEPs) between the self-established radioresistant NSCLC cell line A549-R11 and control (A549-CK) were measured by proteomic analysis. Among the detected DEPs, CRIP2, ARHGDIB, and PADI3 were validated to be up-regulated in radioresistant cells, in mRNA and protein levels. Further analysis of bioinformatics deciphered that CRIP2, as a potential biomarker for diagnosis and a key biomarker for prediction of prognosis, may impact the X-ray radiosensitivity of NSCLC by regulating the occurrence of apoptosis and cell cycle arrest; as such, it may serve as a potent therapeutic target to facilitate NSCLC radiotherapy. CRIP2 and other DEPs may shed new light on the recognition of complex factors associated with radiation-responsiveness and finally be beneficial in the advancement of personalized therapies and precision medical treatment.

Comparative efficacies of different immunotherapy regimens in recurrent implantation failure: A systematic review and network meta-analysis.

For patients with recurrent implantation failure (RIF), immune system imbalances have become the focus of research. The effects of different classes of immunotherapies on improving pregnancy outcomes have not been fully established. This network meta-analysis was performed to assess the impact of popular immunotherapies in women with RIF. We systematically searched the Cochrane Central Register of Controlled Trials, PubMed, Embase, and Web of Science databases as well as clinical trial registration websites. Randomized controlled trials comparing immunotherapeutic outcomes were included. We performed the random-effects network meta-analysis to compare efficacy measures. A total of 21 trials involving 2277 participants and 8 immunotherapies were eligible for this study. Patients that had been administered with PBMCs, G-CSF, PRP, and sirolimus exhibited higher CPR than those administered with the placebo (2.63, 1.71-4.06; 2.03, 1.35-3.05; 1.98, 1.02-3.84; 2.55, 1.36-4.79; and 3.95, 1.33-11.72, respectively). For IR, only PBMCs and G-CSF were significantly more effective than the placebo (2.92, 1.39-6.12; 2.66, 1.16-6.06, respectively). In terms of LBR, PBMCs (2.96, 1.67-5.27) and sirolimus (3.55, 1.18-10.64) were effective. However, r-hLIF (0.25, 0.10-0.62) had a reduced risk of LBR. No therapeutic regimen was found to have significantly decreased MR, but PBMCs exhibited the lowest rank among all interventions (0.28, 0.06-1.44). To improve clinical pregnancy while reducing miscarriage outcomes, PBMCs might be a beneficent therapeutic option for RIF in the future.

Insights into the molecular mechanism of positive cooperativity between partial agonist MK-8666 and full allosteric agonist AP8 of hGPR40 by Gaussian accelerated molecular dynamics (GaMD) simulations.

Activation of human free fatty acid receptor 1 (FFAR1, also called hGPR40) enhances insulin secretion in a glucose-dependent manner. Hence, the development of selective agonist targeting hGPR40 has been proposed as a therapeutic strategy of type 2 diabetes mellitus. Some agonists targeting hGPR40 were reported. The radioligand-binding studies and the crystal structures reveal that there are multiple sites on GPR40, and there exists positive binding cooperativity between the partial agonist MK-8666 and full allosteric agonist (AgoPAM) AP8. In this work, we carried out long-time Gaussian accelerated molecular dynamics (GaMD) simulations on hGPR40 to shed light on the mechanism of the cooperativity between the two agonists at different sites. Our results reveal that the induced-fit conformational coupling is bidirectional between the two sites. The movements and rotations of TM3, TM4, TM5 and TM6 due to their inherent flexibility are crucial in coupling the conformational changes of the two agonists binding sites. These helices adopt similar conformational states upon alternative ligand or both ligands binding. The Leu1384.57, Leu1865.42 and Leu1905.46 play roles in coordinating the rearrangements of residues in the two pockets, which makes the movements of residues in the two sites like gear movements. These results provide detailed information at the atomic level about the conformational coupling between different sites of GPR40, and also provide the structural information for further design of new agonists of GPR40. In addition, these results suggest that it is necessary by considering the effect of other site bound in structure-based ligands discovery.

LncRNA H19 Upregulation Participates in the Response of Glioma Cells to Radiation.

Previous studies have indicated that radiation resistance of glioma is one of the leading causes of radiotherapy failure. Mounting evidence suggests that long non-coding RNA (lncRNA) plays an important role in regulating radiosensitivity of cancer cells via implicating in various cell processes. However, the underlying mechanisms remain unclear and need further study, especially at the molecular level. We found that the expression level of lncRNA H19 was elevated by radiation, and then, the modulation of H19 affected the resistant of glioma cells to X-rays. Dual-luciferase reporter analyses showed that H19 was transcriptionally activated by CREB1 in glioma cells after irradiation. In addition, both flow cytometry and 5-ethynyl-2'-deoxyuridine (EdU) assay suggested that H19 was involved in the cell cycle arrest, apoptosis, and DNA synthesis to modulate the radiation response of glioma cells and influenced their radioresistance. Therefore, H19 might play a crucial role in enhancing the radioresistance of glioma.