Role of MST2/YAP1 signaling pathway in retinal cells apoptosis and diabetic retinopathy.

Diabetic retinopathy (DR) is a main factor affecting vision of patients, and its pathogenesis is not completely clear. The purpose of our study was to investigate correlations between MST2 and DR progression, and to study the possible mechanism of MST2 and its down pathway in high glucose (HG)-mediated RGC-5 apoptosis. The diabetic rat model was established by intraperitoneal injection of streptozotocin (STZ) 60 mg/kg. HE and TUNEL staining were used to evaluate the pathological changes and apoptosis of retinal cells in rats. Western blot, qRT-PCR and immunohistochemistry showed that levels of MST2 were increased in diabetic group (DM) than control. In addition, the differential expression of MST2 is related to HG-induced apoptosis of RGC-5 cells. CCK-8 and Hoechst 33,342 apoptosis experiments showed that MST2 was required in HG-induced apoptosis of RGC-5 cells. Further research revealed that MST2 regulated the protein expression of YAP1 at the level of phosphorylation in HG-induced apoptosis. Simultaneously, we found that Xmu-mp-1 acts as a MST2 inhibitor to alleviate HG-induced apoptosis. In summary, our study indicates that the MST2/YAP1 signaling pathway plays an important role in DR pathogenesis and RGC-5 apoptosis. This discovery provides new opportunities for future drug development targeting this pathway to prevent DR.

Preparation and Mechanical Properties of Flexible Prepreg Resin with High Strength and Low Creep.

In this study, aiming at the problem of low strength and high creep caused by medium-low modulus flexible resin based on the formulation design idea of high-molecular-weight epoxy resin (E12)-reinforced flexible epoxy-terminated urethane resin (EUR), a flexible epoxy prepreg resin with high strength and low bending creep was prepared to be suitable for hot melt processing technology. Flexible EUR was synthesized by grafting flexible polyurethane segments onto the epoxy side chain by urethane bonding. By adjusting the ratio of E12 and EUR, the effects of different ratios of the two components on the mechanical properties and viscoelasticity of the resin were systematically studied with dicyandiamide as the latent curing system. Research has found that when the E12 content is between 20%wt and 40%wt, the resin system has the best coating viscosity at 65 °C to 85 °C. The molecular weight and the content of aromatic heterocyclic groups of the resin determine the strength and creep behavior of the resin. When the content of E12 in the system is less than 50%wt, modulus and strength increase linearly, but after more than 50%wt E12 content, the modulus is almost unchanged and the strength begins to decrease. By increasing the content of E12 in the resin, the creep behavior of the resin is greatly reduced. When the content of E12 increases to 50%wt, the bending creep is the lowest.

Preliminary study on whole genome methylation and transcriptomics in age-related cataracts.

DNA methylation plays an important role in the occurrence and development of age-related cataracts (ARC). This study aims to reveal potential epigenetic biomarkers of ARC by detecting modifications to the DNA methylation patterns of genes shown to be related to ARC by transcriptomics. The MethylationEPIC BeadChip (850 K) was used to analyze the DNA methylation levels in ARC patients and unaffected controls, and the Pearson correlation test was used to perform genome-wide integration analysis of DNA methylation and transcriptome data. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to perform functional analysis of the whole genome, promoter regions (TSS1500/TSS200), and the associated differentially methylated genes (DMG). Pyrosequencing was used to verify the methylation levels of the selected genes. The results showed that, compared with the control group, a total of 52,705 differentially methylated sites were detected in the ARC group, of which 13,858 were hypermethylated and 38,847 were hypomethylated. GO and KEGG analyses identified functions related to the cell membrane, the calcium signaling pathway, and their possible molecular mechanisms. Then, 57 DMGs with negative promoter methylation correlations were screened by association analysis. Pyrosequencing verified that the ARC group had higher methylation levels of C3 and CCKAR and lower methylation levels of NLRP3, LEFTY1, and GPR35 compared with the control group. In summary, our study reveals the whole-genome DNA methylation patterns and gene expression profiles in ARC, and the molecular markers of methylation identified herein may aid in the prevention, diagnosis, treatment, and prognosis of ARC.

Automated classification of lay health articles using natural language processing: a case study on pregnancy health and postpartum depression.

Objective: Evidence suggests that high-quality health education and effective communication within the framework of social support hold significant potential in preventing postpartum depression. Yet, developing trustworthy and engaging health education and communication materials requires extensive expertise and substantial resources. In light of this, we propose an innovative approach that involves leveraging natural language processing (NLP) to classify publicly accessible lay articles based on their relevance and subject matter to pregnancy and mental health. Materials and methods: We manually reviewed online lay articles from credible and medically validated sources to create a gold standard corpus. This manual review process categorized the articles based on their pertinence to pregnancy and related subtopics. To streamline and expand the classification procedure for relevance and topics, we employed advanced NLP models such as Random Forest, Bidirectional Encoder Representations from Transformers (BERT), and Generative Pre-trained Transformer model (gpt-3.5-turbo). Results: The gold standard corpus included 392 pregnancy-related articles. Our manual review process categorized the reading materials according to lifestyle factors associated with postpartum depression: diet, exercise, mental health, and health literacy. A BERT-based model performed best (F1 = 0.974) in an end-to-end classification of relevance and topics. In a two-step approach, given articles already classified as pregnancy-related, gpt-3.5-turbo performed best (F1 = 0.972) in classifying the above topics. Discussion: Utilizing NLP, we can guide patients to high-quality lay reading materials as cost-effective, readily available health education and communication sources. This approach allows us to scale the information delivery specifically to individuals, enhancing the relevance and impact of the materials provided.

Epigallocatechin gallate delays age-related cataract development via the RASSF2/AKT pathway.

Age-related cataract (ARC) is a common eye disease, the main cause of which is oxidative stress-mediated apoptosis of lens epithelial cells (LECs). Epigallocatechin gallate (EGCG) is the most potent antioxidant in green tea. Our results demonstrated that EGCG could effectively reduce apoptosis of LECs and retard lens clouding in aged mice. By comparing transcriptome sequencing results of three groups of mice (young control, untreated aged, and EGCG-treated) and screening using GO and KEGG analyses, we selected RASSF2 as the effector gene of EGCG for mechanistic exploration. We verified that the differential expression of RASSF2 was associated with the occurrence of ARC in clinical samples and mouse tissues by immunohistochemistry and western blotting, respectively. We showed that high RASSF2 expression plays a crucial role in the oxidative induction of apoptosis in LECs, as revealed by overexpression and interference experiments. Further studies showed that RASSF2 mediates the inhibitory effect of EGCG on apoptosis and ARCogenesis in LECs by regulating AKT (Ser473) phosphorylation. In this study, we found for the first time the retarding effect of EGCG on lens clouding in mice and revealed the mechanism of action of RASSF2/AKT in it, which provides a theoretical basis for the targeted treatment of EGCG.

A scoping review on multimodal deep learning in biomedical images and texts.

Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images and text, has the potential to revolutionize the analysis and interpretation of biomedical data. However, it only caught researchers' attention recently. To this end, there is a critical need to conduct a systematic review on this topic, identify the limitations of current work, and explore future directions. In this scoping review, we aim to provide a comprehensive overview of the current state of the field and identify key concepts, types of studies, and research gaps with a focus on biomedical images and texts joint learning, mainly because these two were the most commonly available data types in MDL research. This study reviewed the current uses of multimodal deep learning on five tasks: (1) Report generation, (2) Visual question answering, (3) Cross-modal retrieval, (4) Computer-aided diagnosis, and (5) Semantic segmentation. Our results highlight the diverse applications and potential of MDL and suggest directions for future research in the field. We hope our review will facilitate the collaboration of natural language processing (NLP) and medical imaging communities and support the next generation of decision-making and computer-assisted diagnostic system development.

A scoping review on multimodal deep learning in biomedical images and texts.

OBJECTIVE: Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images and text, has the potential to revolutionize the analysis and interpretation of biomedical data. However, it only caught researchers' attention recently. To this end, there is a critical need to conduct a systematic review on this topic, identify the limitations of current work, and explore future directions. METHODS: In this scoping review, we aim to provide a comprehensive overview of the current state of the field and identify key concepts, types of studies, and research gaps with a focus on biomedical images and texts joint learning, mainly because these two were the most commonly available data types in MDL research. RESULT: This study reviewed the current uses of multimodal deep learning on five tasks: (1) Report generation, (2) Visual question answering, (3) Cross-modal retrieval, (4) Computer-aided diagnosis, and (5) Semantic segmentation. CONCLUSION: Our results highlight the diverse applications and potential of MDL and suggest directions for future research in the field. We hope our review will facilitate the collaboration of natural language processing (NLP) and medical imaging communities and support the next generation of decision-making and computer-assisted diagnostic system development.

Evaluating large language models on medical evidence summarization.

Recent advances in large language models (LLMs) have demonstrated remarkable successes in zero- and few-shot performance on various downstream tasks, paving the way for applications in high-stakes domains. In this study, we systematically examine the capabilities and limitations of LLMs, specifically GPT-3.5 and ChatGPT, in performing zero-shot medical evidence summarization across six clinical domains. We conduct both automatic and human evaluations, covering several dimensions of summary quality. Our study demonstrates that automatic metrics often do not strongly correlate with the quality of summaries. Furthermore, informed by our human evaluations, we define a terminology of error types for medical evidence summarization. Our findings reveal that LLMs could be susceptible to generating factually inconsistent summaries and making overly convincing or uncertain statements, leading to potential harm due to misinformation. Moreover, we find that models struggle to identify the salient information and are more error-prone when summarizing over longer textual contexts.

Evaluating Large Language Models on Medical Evidence Summarization.

Recent advances in large language models (LLMs) have demonstrated remarkable successes in zero- and few-shot performance on various downstream tasks, paving the way for applications in high-stakes domains. In this study, we systematically examine the capabilities and limitations of LLMs, specifically GPT-3.5 and ChatGPT, in performing zero-shot medical evidence summarization across six clinical domains. We conduct both automatic and human evaluations, covering several dimensions of summary quality. Our study has demonstrated that automatic metrics often do not strongly correlate with the quality of summaries. Furthermore, informed by our human evaluations, we define a terminology of error types for medical evidence summarization. Our findings reveal that LLMs could be susceptible to generating factually inconsistent summaries and making overly convincing or uncertain statements, leading to potential harm due to misinformation. Moreover, we find that models struggle to identify the salient information and are more error-prone when summarizing over longer textual contexts.

An NLP approach to identify SDoH-related circumstance and suicide crisis from death investigation narratives.

OBJECTIVES: Suicide presents a major public health challenge worldwide, affecting people across the lifespan. While previous studies revealed strong associations between Social Determinants of Health (SDoH) and suicide deaths, existing evidence is limited by the reliance on structured data. To resolve this, we aim to adapt a suicide-specific SDoH ontology (Suicide-SDoHO) and use natural language processing (NLP) to effectively identify individual-level SDoH-related social risks from death investigation narratives. MATERIALS AND METHODS: We used the latest National Violent Death Report System (NVDRS), which contains 267 804 victim suicide data from 2003 to 2019. After adapting the Suicide-SDoHO, we developed a transformer-based model to identify SDoH-related circumstances and crises in death investigation narratives. We applied our model retrospectively to annotate narratives whose crisis variables were not coded in NVDRS. The crisis rates were calculated as the percentage of the group's total suicide population with the crisis present. RESULTS: The Suicide-SDoHO contains 57 fine-grained circumstances in a hierarchical structure. Our classifier achieves AUCs of 0.966 and 0.942 for classifying circumstances and crises, respectively. Through the crisis trend analysis, we observed that not everyone is equally affected by SDoH-related social risks. For the economic stability crisis, our result showed a significant increase in crisis rate in 2007-2009, parallel with the Great Recession. CONCLUSIONS: This is the first study curating a Suicide-SDoHO using death investigation narratives. We showcased that our model can effectively classify SDoH-related social risks through NLP approaches. We hope our study will facilitate the understanding of suicide crises and inform effective prevention strategies.

Molecular-Level Insight of CP52/NBR Damping Composites through a Combination of Molecular Dynamics Simulation and Experimental Method.

To enhance the damping properties of nitrile butadiene rubber (NBR), the elastomer used was blended with chlorinated paraffin 52 (CP52) to prepare NBR/CP52 composites. The results showed that CP52 could significantly enhance the damping properties of NBR and shift the glass transition temperature (Tg) to lower temperatures. Molecular dynamics models of the CP52/NBR system were established, and the damping properties of the CP52-reinforced NBR were investigated using molecular dynamics (MD) simulations. Through the combination of MD simulations and the experimental results, the essential mechanism of the enhanced damping properties of the NBR was methodically expatiated and was ascribed to the Cl-CP-H····NC-NBR (type I) and CP-Cl····H-NBR-CN (type II) analogous hydrogen bonds formed between NBR and CP52. The higher the CP52 content, the higher the analogous hydrogen bond concentration, and the better the damping properties of the CP52/NBR composites. The experimental results were very consistent with the MD simulation results, meaning that the combination method can provide a new means to optimize the design of damping materials and broaden the application range of small polar molecules in the damping modification of polar rubber materials.

Preparation and research of epoxy modified by carboxyl-terminated polybutylene adipate at room temperature.

In this study, carboxyl-terminated polybutylene adipate (CTPBA) was used to modify epoxy resin, and the modified epoxy resin was cured by a room temperature rapid curing agent (T-31). The effects of CTPBA modification on bonding properties and mechanical properties of epoxy resin adhesive at room temperature were carefully studied. Epoxy-terminated prepolymer was synthesized by pre-polymerization and its structure was characterized. Compared with the addition method of direct blending, the bonding properties and mechanical properties of pre-polymerized epoxy resin adhesive were significantly better. Compared with unmodified epoxy resin, CTPBA modification significantly improved the bonding strength. Furthermore, with the increase of CTPBA content, the shear strength of the material increased first and then decreased, and reached the maximum when the addition amount was 40 phr. This shows that the tensile strength of the material decreased with the increase of CTPBA content, and the elongation at break increased with the increase of CTPBA content. Dynamic mechanical analyzer (DMA) test results showed that the addition of CTPBA reduced the glass transition temperature, but broadened the damping temperature range. TG analysis showed that the thermal stability of the modified epoxy resin was good, and compared with pure epoxy resin, the initial temperature of thermal weight loss and the maximum thermal decomposition rate decreased, but the overall thermal stability was not significantly different. In summary, CTPBA modification of epoxy resin is expected to improve the comprehensive mechanical properties at room temperature.

High MST2 expression regulates lens epithelial cell apoptosis in age-related cataracts through YAP1 targeting GLUT1.

Age-related cataract (ARC) is a severe visual impairment disease and its pathogenesis remains unclear. This study investigated the relevance of MST2/YAP1/GLUT1 in ARC development in vivo and in vitro, and explored the role and possible mechanisms of this pathway in oxidative damage-mediated apoptosis of lens epithelial cells (LECs). Western blot analysis and immunohistochemistry showed that MST2 and phosphorylated (p)-YAP (Ser127) protein levels were increased, and YAP1 and GLUT1 protein levels were decreased in LECs of ARC patients and aged mice. Additionally, differential expression of MST2 and YAP1 was associated with H2O2-induced apoptosis of human lens epithelial B3 (HLE-B3) cells. CCK-8 and Hoechst 33,342 apoptosis assays showed that MST2 and YAP1 were involved in H2O2-induced apoptosis of LECs. Subsequent experiments showed that, during MST2-mediated H2O2-induced apoptosis, p-YAP (Ser127) levels were elevated and immunofluorescence revealed nucleoplasmic translocation and inhibition of YAP1 protein expression. Furthermore, GLUT1 was in turn synergistically transcriptionally regulated by YAP1-TEAD1 in dual luciferase reporter assays. In conclusion, our study indicates that the MST2/YAP1/GLUT1 pathway plays a major role in the pathogenesis of ARC and LECs apoptosis, providing a new direction for future development of targeted inhibitors that block this signaling pathway to prevent, delay, or even cure ARC.

RNA sequencing and bioinformatics analysis of human lens epithelial cells in age-related cataract.

BACKGROUND: Age-related cataract (ARC) is the main cause of blindness in older individuals but its specific pathogenic mechanism is unclear. This study aimed to identify differentially expressed genes (DEGs) associated with ARC and to improve our understanding of the disease mechanism. METHODS: Anterior capsule samples of the human lens were collected from ARC patients and healthy controls and used for RNA sequencing to detect DEGs. Identified DEGs underwent bioinformatics analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Subsequently, reverse transcription quantitative RT-qPCR was used to validate the different expression levels of selected genes. RESULTS: A total of 698 up-regulated DEGs and 414 down-regulated DEGs were identified in ARC patients compared with controls by transcriptome analysis. Through GO and KEGG bioinformatics analysis, the functions of significantly DEGs and their possible molecular mechanisms were determined. Sequencing results were verified by RT-qPCR as being accurate and reliable. CONCLUSIONS: This study identified several genes associated with ARC, which improves our knowledge of the disease mechanism.

Maintaining manganese in tumor to activate cGAS-STING pathway evokes a robust abscopal anti-tumor effect.

Radiotherapy (RT)-induced DNA damage leaked into cytosol can elicit host antitumor immune response. However, such response rate is unpromising due to limited cyclic GMP-AMP synthase (cGAS) recognition of cytosolic DNA, which could be digested inherently by host DNases. Here we show that synchronizing Mn2+ delivery with accumulated cytosolic DNA after RT can promote the activation of cGAS-STING pathway, thereby enhancing RT-induced antitumor immunity. Intratumoral Mn2+ injection immediately after RT cannot enhance RT, while intratumoral Mn2+ injection 24 h after RT can. Direct-injected Mn2+ can be metabolized out from tumor in minutes while RT-induced DNA damage need cells mitotic progression for up to 24 h to accumulate into cytosol. Alginate can maintain Mn2+ in tumor for up to 24 h due to it can chelate divalent cations. When the release profile of Mn2+ is controlled by alginate (Alg) and synchronized with the accumulation of RT-induced DNA damage, over 90% inhibition rate can be obtained even in the unirradiated tumor, and survival time is significantly extended. This synchronizing strategy provides a simple and novel approach to effectively activate cGAS-STING pathway in tumor and promote RT-induced immunity.

Circular RNA hsa_circ_0001588 promotes the malignant progression of lung adenocarcinoma by modulating miR-524-3p/NACC1 signaling.

AIMS: Previous studies have demonstrated that circular RNAs play significant roles in several tumors, including lung adenocarcinoma; however, specific biological functions and molecular mechanisms underlying this process remain unclear. MATERIALS AND METHODS: Here, we conducted real-time quantitative PCR (qRT-PCR) to measure hsa_circ_0001588 expression levels in 60 paired lung adenocarcinoma tissues and cell lines. Furthermore, the association between hsa_circ_0001588 and clinical features of lung adenocarcinoma was analyzed. Functional experiments were conducted to assess the influence of hsa_circ_0001588 on proliferation, migration, and invasion in lung adenocarcinoma cells. We detected possible downstream targets of hsa_circ_0001588 using bioinformatics analysis. Luciferase reporter assays, qRT-PCR, and western blotting assays were performed to verify the molecular mechanism underlying hsa_circ_0001588 functions. KEY FINDINGS: We found that hsa_circ_0001588 was prominently upregulated in lung adenocarcinoma tissues and cell lines; elevated expression of hsa_circ_0001588 was positively correlated with poor clinicopathological features of lung adenocarcinoma. Functional experiments revealed that hsa_circ_0001588 acts as an oncogene to promote the proliferation, migration, and invasion of lung adenocarcinoma in vitro. Mechanistically, hsa_circ_0001588 promoted the proliferation, migration, and metastasis of lung adenocarcinoma by binding to miR-524-3p to promote nucleus accumbens-associated protein 1(NACC1) expression. SIGNIFICANCE: Together, our results revealed that hsa_circ_0001588 upregulated the expression of NACC1 by combining with miR-524-3p to promote the proliferation, migration, and invasion of lung adenocarcinoma cells, suggesting that hsa_circ_0001588 may be an underlying therapeutic target for lung adenocarcinoma.

MDM2 phosphorylation mediates H2O2-induced lens epithelial cells apoptosis and age-related cataract.

Lens epithelial cells (LECs) apoptosis induced by oxidative stress is a major factor in age-related-cataract (ARC) pathogenesis, but there are still many blind nodes in this progress. This study aimed to investigate the effects of MDM2 phosphorylation in ARC and H2O2-induced lens epithelial cells apoptosis. Our results confirmed that the levels of p-MDM2 (Ser166) and p-MDM2 (Ser186) in the anterior lens capsules of human cataracts were reduced compared to that in normal capsules. Similarly, in naturally aging cataract mice, the level of MDM2 phosphorylation also decreased. Oxidative stress-induced apoptosis model was constructed by cultivating HLE-B3 cells with 200 µM H2O2. It was confirmed that MDM2 could regulate lens epithelial cell apoptosis, and MDM2 inhibitors could partly inhibited AKT's role in suppressing apoptosis induced by H2O2. Besides, we examed the decreased level of p-AKT(Ser473) in apoptosis of lens epithelial cells and ARC. Our study revealed that MDM2 phosphorylation mediated H2O2-induced lens epithelial cells apoptosis and ARC, which could provide new ideas for the clinical treatment of ARC.

Using HPLC to analyze (S)-oxiracetam and four related substances in the bulk drug of (S)-oxiracetam.

(S)-oxiracetam is undergoing clinical trials as an active ingredient in the racemic oxiracetam. Here, we report a specific analytical method for analyzing (S)-oxiracetam and four related impurities in the bulk drug of (S)-oxiracetam by using high-performance liquid chromatography (HPLC) system. The chromatographic system included a Capcell pak NH2 analytical column, a mobile phase containing acetonitrile-water (95:5, v/v; pH adjusted to 2.0 with trifluoroacetic acid) at a flow rate of 1.0 mL/min, column temperature at 35 ℃ and the UV detection wavelength is set at 210 nm. This analytical method has shown effective and specific analysis for (S)-oxiracetam and four related substances. Moreover, the molecular weight and chemical structure preliminarily speculated of related substances were characterized by mass spectrometry. The methodology was verified by HPLC and results collected of the method validation included the system suitability, specificity sensitivity, linearity and accuracy, good linear correlation coefficient R2 was more than 0.9991. The analytical method developed and verified in the study, as far as we know, is the most exhaustive HPLC determination report which could be applied for the quality control and stability monitor purposes of the bulk drug of (S)-oxiracetam in the routine pharmaceutical analysis.

Hydrogel-Based Controlled Drug Delivery for Cancer Treatment: A Review.

As an emerging drug carrier, hydrogels have been widely used for tumor drug delivery. A hydrogel drug carrier can cause less severe side effects than systemic chemotherapy and can achieve sustained delivery of a drug at tumor sites. In addition, hydrogels have excellent biocompatibility and biodegradability and lower toxicity than nanoparticle carriers. Smart hydrogels can respond to stimuli in the environment (e.g., heat, pH, light, and ultrasound), enabling in situ gelation and controlled drug release, which greatly enhance the convenience and efficiency of drug delivery. Here, we summarize the different sizes of hydrogels used for cancer treatment and their related delivery routes, discuss the design strategies for stimuli-responsive hydrogels, and review the research concerning smart hydrogels reported in the past few years.