Bidirectional relationship between late-onset epilepsy (LOE) and dementia: A systematic review and meta-analysis of cohort studies.

OBJECTIVE: To explore the bidirectional relationship of late-onset epilepsy (LOE) with dementia and Alzheimer's disease (AD). METHODS: Using the common electronic databases, including PubMed, Cochrane Library databases and EMBASE, we systematically reviewed published cohort studies that assessed the risk of LOE in individuals comorbid with dementia or AD, and those with dementia or AD comorbid with LOE that had been published up to 31 March 2023. The data extraction process was carried out independently by two authors. The summary adjusted relative ratio (aRR) was calculated by employing Rev Man 5.3 for the inclusion of studies. To investigate the origins of heterogeneity, we conducted both subgroup and sensitivity analyses. In the presence of heterogeneity, a random-effects model was employed. To evaluate potential publication bias, we utilized the funnel plot and conducted Begg's and Egger's tests. RESULTS: We included 20 eligible studies in the final analysis after a rigorous screening process. Pooled results indicated that LOE was association with an increased risk of all-cause dementia (aRR: 1.34, 95% confidence interval [CI]: 1.13-1.59) and AD (aRR: 2.49, 95% CI: 1.16-5.32). In addition, the pooled effect size for LOE associated with baseline AD and all-cause dementia were 3.51 (95% CI: 3.47-3.56) and 2.53 (95% CI: 2.39-2.67), respectively. Both sensitivity and subgroup analyses showed that these positive correlations persisted. According to the results of the Egger's and Begg's tests, as well as visual inspection of funnel plots, none of the studies appeared to be biased by publication. CONCLUSION: The findings suggested that LOE is a potential risk factor for dementia and AD, and vice versa, dementia and AD are both potential risk indicators for LOE. Since there is substantial heterogeneity among the cohorts analyzed and more cohort studies should be conducted to confirm the correlations found in the current study.

DGAMDA: Predicting miRNA-disease association based on dynamic graph attention network.

MiRNA (microRNA)-disease association prediction has essential applications for early disease screening. The process of traditional biological experimental validation is both time-consuming and expensive. However, as artificial intelligence technology continues to advance, computational methods have become efficient tools for predicting miRNA-disease associations. These methods often rely on the combination of multiple sources of association data and require improved feature mining. This study proposes a dynamic graph attention-based association prediction model, DGAMDA, which combines feature mapping and dynamic graph attention mechanisms through feature mining on a single miRNA-disease association network. DGAMDA effectively solves the problems of feature heterogeneity and inadequate feature mining by previous static graph attention mechanisms and achieves high-precision feature mining and association scoring prediction. We conducted a five-fold cross-validation experiment and obtained the mean values of Accuracy, Precision, Recall, and F1-score, which were .8986, .8869, .9115, and .8984, respectively. Our proposed model outperforms other advanced models in terms of experimental results, demonstrating its effectiveness in feature mining and association prediction based on a single association network. In addition, our model can also be used to predict miRNAs associated with unknown diseases.

Study of vision-related resting-state activity in suprasellar tumor patients with postoperative visual damage.

INTRODUCTION: The objective of this study was to investigate changes in vision-related resting-state activity in patients with suprasellar tumors (ST) who experienced vision deterioration after surgery. METHODS: Twelve patients with ST and vision deterioration after surgery were included in the study. Resting-state functional connectivity (FC) was compared before and after surgery using a seed-based analysis with a priori specified regions of interest (ROIs) within the visual areas. The differences between the two groups were identified using a paired t-test. RESULTS: The data showed a decrease in FC within and between the dorsal and ventral pathways, as well as in the third pathway in ST patients. The middle temporal visual cortex (MT+) showed a decreased FC with more regions than other visual ROIs. The data also revealed an increase in FC between the visual ROIs and higher-order cortex. The superior frontal gyrus/BA8 showed an increased FC with more ROIs than other high-order regions, and the hOC4d was involved in an increased FC with more high-order regions than other ROIs. CONCLUSIONS: The study results indicate significant neural reorganization in the vision-related cortex of ST patients with postoperative vision damage. Most subareas within the visual cortex showed remarkable neural dysfunction, and some highe-order cortex may be primarily involved in top-down control of the subareas within the visual cortex. The hot zones may arise in the processing of "top-down" influence.

Activation of adenosine A2B receptor alleviates myocardial ischemia-reperfusion injury by inhibiting endoplasmic reticulum stress and restoring autophagy flux.

Myocardial ischemia-reperfusion injury (MIRI) poses a significant threat to patients with coronary heart disease. Adenosine A2A receptors have been known as a protective role in MIRI by regulating autophagy, so we assumed that activation of adenosine A2B receptor (A2BAR) might exert a similar effect during MIRI and underlying mechanism be related to proteostasis maintenance as well. In situ hearts were subjected to 30 min of ischemia and 120 min of reperfusion (IR), while invitro cardiomyocytes from neonatal rats experienced 6 h of oxygen-glucose deprivation followed by 12 h of reoxygenation (OGDR). Initially, we observed that post-ischemia-reperfusion induced autophagy flux blockade and ERS both in vivo and in vitro, evident through the increased expression of p62, LC3II, and BIP, which indicated the deteriorated proteostasis. We used a selective A2BAR agonist, Bay 60-6583, to explore the positive effects of A2BAR on cardiomyocytes and found that A2BAR activation rescued damaged cardiac function and morphological changes in the IR group and improved frail cell viability in the OGDR group. The A2BAR agonist also alleviated the blockage of autophagic flux, coupled with augmented ERS in the IR/OGDR group, which was reassured by using an autophagy inhibitor chloroquine (CQ) and ERS inhibitor (4-PBA) in vitro. Additionally, considering cAMP/PKA as a well-known downstream effector of A2BAR, we utilized H89, a selective PKA inhibitor. We observed that the positive efficacy of Bay 60-6583 was inhibited by H89. Collectively, our findings demonstrate that the A2BAR/cAMP/PKA signaling pathway exerts a protective role in MIRI by mitigating impaired autophagic flux and excessive ERS.

Use of consecutive transcutaneous oxygen measurement when assessing the need for revascularization and association with the outcomes of ischemic diabetic ulcers.

This study compared the ankle-brachial index (ABI) with transcutaneous oxygen pressure (TcPO2 ) in assessing peripheral vascular disease (PVD) prevalence in 100 diabetic foot ulcer (DFU) patients. Patients were categorized into vascular or nonvascular reconstruction groups and underwent both ABI and TcPO2 measurements four times over 6 months. Predictive validity for PVD diagnosis was analysed using the area under the receiver-operating characteristic curve (AUC). The study found TcPO2 to be a superior predictor of PVD than ABI. Among the DFU patients, 51 with abnormal TcPO2 values underwent vascular reconstruction. Only TcPO2 values showed significant pretreatment differences between the groups and increased post-reconstruction. These values declined over a 6-month follow-up, whereas ABI values rose. For those with end-stage renal disease (ESRD), TcPO2 values saw a sharp decrease within 3 months. Pre-reconstruction TcPO2 was notably lower in amputation patients versus limb salvage surgery patients. In conclusion, TcPO2 is more effective than ABI for evaluating ischemic limb perfusion and revascularization necessity. It should be prioritized as the primary follow-up tool, especially for ESRD patients.

Early identification of delayed wound healing in complex diabetic foot ulcers treated with a dermal regeneration template: a novel clinical target and its risk factors.

BACKGROUND: The dermal regeneration template (DRT), a tissue-engineered skin substitute composing a permanent dermal matrix and an upper temporary silicone layer that serves as the epidermis, has demonstrated efficacy in treating uncomplicated diabetic foot ulcers (DFUs). Our institution has obtained good outcomes with DRT in patients with more complicated DFUs. Because of its chronicity, the authors are working to identify a clinical target that anticipates delayed healing early in the treatment in addition to determining the risk factors linked to this endpoint to increase prevention. MATERIALS AND METHODS: This retrospective single-center study analyzed patients with DFUs who underwent wound reconstruction using DRT between 2016 and 2021. The patients were categorized into poor or good graft-take groups based on their DRT status on the 21st day after the application. Their relationship with complete healing (CH) rate at day 180 was analyzed. Variables were collected for risk factors for poor graft take at day 21. Independent risk factors were identified after multivariable analysis. The causes of poor graft take were also reported. RESULTS: This study examined 80 patients (38 and 42 patients in the poor and good graft-take groups, respectively). On day 180, the CH rate was 86.3% overall, but the poor graft-take group had a significantly lower CH rate (76.3 vs. 95.2%, P =0.021) than the good graft-take group. Our analysis identified four independent risk factors: transcutaneous oxygen pressure less than 30 mmHg (odds ratio, 154.14), off-loading device usage (0.03), diabetic neuropathy (6.51), and toe wound (0.20). The most frequent cause of poor graft take was infection (44.7%), followed by vascular compromise (21.1%) and hematoma (15.8%). CONCLUSION: Our study introduces the novel concept of poor graft take at day 21 associated with delayed wound healing. Four independent risk factors were identified, which allows physicians to arrange interventions to mitigate their effects or select patients more precisely. DRT represents a viable alternative to address DFUs, even in complicated wounds. A subsequent split-thickness skin graft is not always necessary to achieve CH.

Short-term and long-term effectiveness of acupuncture and Tuina on knee osteoarthritis: study protocol for a randomized controlled trial.

Background: The effectiveness of acupuncture and tuina in treating knee osteoarthritis (KOA) is still controversial, which limits their clinical application in practice. This study aims to evaluate the short-term and long-term effectiveness of acupuncture and tuina on KOA. Methods/design: This parallel-group, multicenter randomized clinical trial (RCT) will be conducted at the outpatient clinic of five traditional Chinese medicine hospitals in China. Three hundred and thirty participants with KOA will be randomly assigned to acupuncture, tuina, or home-based exercise group with a ratio of 1:1:1. The primary outcome is the proportion of participants achieving a minimal clinically important improvement defined as a ≥ 12% reduction on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain dimension on short term (week 8) and long term (week 26) compared with baseline. Secondary outcomes are knee joint conditions (pain, function, and stiffness), self-efficacy of arthritis, quality of life, and psychological conditions, which will be evaluated by the WOMAC score and the Patient Global Assessment (PGA), and in addition, the respondents index of OMERACT-OARSI, Short Form 12 Health Survey (SF-12), arthritis self-efficacy scale, and European five-dimensional health scale (EQ-5D). Adverse events will be collected by self-reported questionnaires predefined. Clinical trial registration: https://www.chictr.org.cn.

Gout/hyperuricemia reduces the risk of Alzheimer's disease: A meta-analysis based on latest evidence.

OBJECTIVE: Previous studies have found the potential role of gout or hyperuricemia in subsequent development of Alzheimer's disease (AD) but reported inconsistent results. We conducted the current meta-analysis to evaluate whether an association exists between gout/ hyperuricemia and AD. METHODS: We systematically searched PubMed and EMBASE for the published cohort studies that measured the risk of AD in subject with gout/ hyperuricemia up to May 20, 2023. Data extraction was employed by two authors independently. Rev Man 5.3 and Stata 15.0 software were used to calculate the relative ratio (RR) or hazard ratio (HR) for including studies. Subgroup analysis was performed to assess the sources of heterogeneity. A random-effects model was adopted when heterogeneity was present. The funnel plot, Begg's test, and and Egger's test were used to assess publication bias. RESULTS: After rigorous screening, seven eligible studies were included in the final analyses. Pooled results indicated that gout or hyperuricemia decreases the risk of AD (RR: 0.69, 95% CI: 0.64∼0.72), with a high heterogeneity of 93%. Subgroup analyses showed that regional distribution was the source of heterogeneity. Egger's and Begg's tests as well as visual inspection of funnel plot suggested no publication bias in the studies. CONCLUSION: The findings suggested that gout or hyperuricemia might have a protective effect against AD. This negative correlation should be verified by more cohort studies due to the existence of substantial heterogeneity.

Reorganization of the structural connectome during vision recovery in pituitary adenoma patients post-transsphenoidal surgery.

Pituitary adenomas (PAs) can exert pressure on the optic apparatus, leading to visual impairment. A subset of patients may observe a swift improvement in their vision following surgery. Nevertheless, the alterations in the structural connectome during the early postoperative period remain largely unexplored. The research employed probabilistic tractography, graph theoretical analysis, and statistical methods on preoperative and postoperative structural magnetic resonance imaging and diffusion tensor images from 13 PA patients. Postoperative analysis revealed an increase in global and local efficiency, signifying improved network capacity for parallel information transfer and fault tolerance, respectively. Enhanced clustering coefficient and reduced shortest path length were also observed, suggesting a more regular network organization and shortened communication steps within the brain network. Furthermore, alterations in node graphical properties were detected, implying a restructuring of the network's control points, possibly contributing to more efficient visual processing. These findings propose that rapid vision recovery post-surgery may be associated with significant reorganization of the brain's structural connectome, enhancing the efficiency and adaptability of the network, thereby facilitating improved visual processing.

Generative Adversarial Matrix Completion Network based on Multi-Source Data Fusion for miRNA-Disease Associations Prediction.

Numerous biological studies have shown that considering disease-associated micro RNAs (miRNAs) as potential biomarkers or therapeutic targets offers new avenues for the diagnosis of complex diseases. Computational methods have gradually been introduced to reveal disease-related miRNAs. Considering that previous models have not fused sufficiently diverse similarities, that their inappropriate fusion methods may lead to poor quality of the comprehensive similarity network and that their results are often limited by insufficiently known associations, we propose a computational model called Generative Adversarial Matrix Completion Network based on Multi-source Data Fusion (GAMCNMDF) for miRNA-disease association prediction. We create a diverse network connecting miRNAs and diseases, which is then represented using a matrix. The main task of GAMCNMDF is to complete the matrix and obtain the predicted results. The main innovations of GAMCNMDF are reflected in two aspects: GAMCNMDF integrates diverse data sources and employs a nonlinear fusion approach to update the similarity networks of miRNAs and diseases. Also, some additional information is provided to GAMCNMDF in the form of a 'hint' so that GAMCNMDF can work successfully even when complete data are not available. Compared with other methods, the outcomes of 10-fold cross-validation on two distinct databases validate the superior performance of GAMCNMDF with statistically significant results. It is worth mentioning that we apply GAMCNMDF in the identification of underlying small molecule-related miRNAs, yielding outstanding performance results in this specific domain. In addition, two case studies about two important neoplasms show that GAMCNMDF is a promising prediction method.

Leukocyte transcriptome of Cushing's disease are associated with nerve impairment and psychiatric disorders.

INTRODUCTION: The hypothalamus-pituitary-adrenal (HPA) axis and its end product cortisol is a major response mechanism to stress and plays a critical role in many psychiatric disorders. Cushing's disease (CD) serves as a valuable in vivo "hyperexpression" model to elucidate the effect of cortisol on brain function and mental disorders. Changes in brain macroscale properties measured by magnetic resonance imaging (MRI) have been detailed demonstrated, but the biological and molecular mechanisms underlying these changes remain poorly understood. MATERIAL AND METHODS: Here we included 25 CD patients and matched 18 healthy controls for assessment, and performed transcriptome sequencing of peripheral blood leukocytes. Weighted gene co-expression network analysis (WGCNA) was performed to construct a co-expression network of the relationships between genes and we identified a significant module and hub gene types associated with neuropsychological phenotype and psychiatric disorder identified in enrichment analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis preliminarily explored the biological functions of these modules. RESULTS: The WGCNA and enrichment analysis indicated that module 3 of blood leukocytes was enriched in broadly expressed genes and was associated with neuropsychological phenotypes and mental diseases enrichment. GO and KEGG enrichment analysis of module 3 identified enrichment in many biological pathways associated with psychiatric disorders. CONCLUSION: Leukocyte transcriptome of Cushing's disease is enriched in broadly expressed genes and is associated with nerve impairment and psychiatric disorders, which may reflect some changes in the affected brain.

USP33 enhances cell survival and stemness by deubiquitinating CTNNB1 in BXPC-3 and SW1990 cells.

Ubiquitin-specific protease 33 (USP33) has been implicated in various cancers, but its biological function and mechanism of action remain unknown in pancreatic cancer (PCa) as a deubiquitinating enzyme. Herein, we report that USP33 silencing inhibits PCa cell survival and self-renewal. USPs highly expressed in spherical PCa cells were screened by comparing the levels of ubiquitin-specific proteases in spherical PCa cells and adherent PCa cells. After silencing USP, the effect of USP on the proliferation of PCa cells was detected by CCK-8 and colony formation assay, and the effect of USP on cell stemness was detected by tumor sphere formation assay, flow analysis, and western blot analysis. The interaction of USP with CTNNB1 and the effect of USP on the ubiquitination of CTNNB1 were verified by coimmunoprecipitation assay. After replenishing CTNNB1, cell proliferation and cell stemness were examined. USP33 is upregulated in spheric BXPC-3, PCNA-1, and SW1990, compared with adherent BXPC-3, PCNA-1, and SW1990. USP33 interacts with CTNNB1, and stabilizes CTNNB1 by suppressing its degradation. Furthermore, cell proliferation, colony-forming, and self-renewal abilities of PCa cells in vitro, and the expression of stem cell markers EpCAM and CD44, C-myc, Nanog, and SOX2, were suppressed when USP33 was knocked down, which was reversed when CTNNB1 was ectopically expressed in PCa cells. Thus, USP33 promotes PCa cell proliferation and self-renewal by inhibiting the degradation of CTNNB1. USP33 inhibition may be a new treatment option for PCa patients.

Multidisciplinary Strategies With Real-Time Fluorescence Images and Negative Pressure Wound Therapy to Manage Organ/Space Surgical Site Infection in Transplanted Kidneys.

BACKGROUND: Surgical site infection (SSI) after kidney transplantation can severely compromise graft function and prolong hospital stay. Organ/space SSI (osSSI) is a severe type of SSI associated with a significantly higher mortality rate. AIMS AND OBJECTIVES: This study aims to provide new strategies of managing (osSSI) after kidney transplant and other high-risk wound infections. METHOD: This is a single-center, retrospective study that analyzed the treatment outcomes of 4 patients who developed osSSI after kidney transplant at Shuang-Ho Hospital. The management strategy included real-time fluorescence imaging with MolecuLight, negative-pressure wound therapy (NPWT) with Si-Mesh, and incisional NPWT (iNPWT). RESULT: The average length of hospital stay was 18 days (range, 12-23 days). During hospitalization, all patients obtained high-quality debridement under real-time fluorescence image confirmation. The average duration of NPWT was 11.8 days (range, 7-17 days) and iNPWT was 7 days. All transplanted kidneys were preserved with normal function after 6 months of follow-up. CONCLUSIONS: Our strategies with real-time fluorescence imaging provide a novel and effective method that can be used in adjunct with the standard of care for managing osSSI after kidney transplantation. More studies are warranted to validate the efficacy of our approach.

Feasibility Study on the Classification of Persimmon Trees' Components Based on Hyperspectral LiDAR.

Intelligent management of trees is essential for precise production management in orchards. Extracting components' information from individual fruit trees is critical for analyzing and understanding their general growth. This study proposes a method to classify persimmon tree components based on hyperspectral LiDAR data. We extracted nine spectral feature parameters from the colorful point cloud data and performed preliminary classification using random forest, support vector machine, and backpropagation neural network methods. However, the misclassification of edge points with spectral information reduced the accuracy of the classification. To address this, we introduced a reprogramming strategy by fusing spatial constraints with spectral information, which increased the overall classification accuracy by 6.55%. We completed a 3D reconstruction of classification results in spatial coordinates. The proposed method is sensitive to edge points and shows excellent performance for classifying persimmon tree components.

Adenosine 2 receptor regulates autophagy and apoptosis to alleviate ischemia reperfusion injury in type 2 diabetes via IRE-1 signaling.

PURPOSE: This study aimed to determine the effect and mechanism of action of adenosine 2 receptor (A2R) activation on myocardial ischemia reperfusion injury (MIRI) under diabetic conditions. METHODS: MIRI type 2 diabetic rats and H9C2 cardiomyocytes were treated with A2R agonist and then subjected to hypoxia for 6 h and reoxygenation for 18 h. Myocardial damage, and infarct size were determined by cardiac ultrasound. Indicators of cardiomyocyte injury, creatine kinase-MB and cardiac troponin I were detected by Enzyme Linked Immunosorbent Assay. Endoplasmic reticulum stress (ERS) was determined through measuring the expression levels of ERS related genes GRP78, p-IRE1/IRE1, and p-JNKJNK. The mechanism of A2R cardio protection in MIRI through regulating ERS induced autophagy was determined by investigating the ER resident protein IRE-1. The ER-stress inducer Tunicamycin, and the IRE-1 inhibitor STF in combination with the A2R agonist NECA were used, and the cellular responses were assessed through autophagy proteins expression Beclin-1, p62, LC3 and apoptosis. RESULTS: NECA improved left ventricular function post MIRI, limited myocardial infarct size, reduced myocardial damage, decreased cardiomyocytes apoptosis, and attenuated ERS induced autophagy through regulating the IRE-XBP1s-CHOP pathway. These actions resulted into overall protection of the myocardium against MIRI. CONCLUSION: In summary, A2R activation by NECA prior to ischemia attenuates apoptosis, reduces ERS induced autophagy and restores left ventricular function. This protective effect occurs through regulating the IRE1-XBPs-CHOP related mechanisms. NECA is thus a potential target for the treatment of MIRI in patient with type 2 diabetes.

Auxiliary signal-guided knowledge encoder-decoder for medical report generation.

Medical reports have significant clinical value to radiologists and specialists, especially during a pandemic like COVID. However, beyond the common difficulties faced in the natural image captioning, medical report generation specifically requires the model to describe a medical image with a fine-grained and semantic-coherence paragraph that should satisfy both medical commonsense and logic. Previous works generally extract the global image features and attempt to generate a paragraph that is similar to referenced reports; however, this approach has two limitations. Firstly, the regions of primary interest to radiologists are usually located in a small area of the global image, meaning that the remainder parts of the image could be considered as irrelevant noise in the training procedure. Secondly, there are many similar sentences used in each medical report to describe the normal regions of the image, which causes serious data bias. This deviation is likely to teach models to generate these inessential sentences on a regular basis. To address these problems, we propose an Auxiliary Signal-Guided Knowledge Encoder-Decoder (ASGK) to mimic radiologists' working patterns. Specifically, the auxiliary patches are explored to expand the widely used visual patch features before fed to the Transformer encoder, while the external linguistic signals help the decoder better master prior knowledge during the pre-training process. Our approach performs well on common benchmarks, including CX-CHR, IU X-Ray, and COVID-19 CT Report dataset (COV-CTR), demonstrating combining auxiliary signals with transformer architecture can bring a significant improvement in terms of medical report generation. The experimental results confirm that auxiliary signals driven Transformer-based models are with solid capabilities to outperform previous approaches on both medical terminology classification and paragraph generation metrics.

MSHGANMDA: Meta-Subgraphs Heterogeneous Graph Attention Network for miRNA-Disease Association Prediction.

MicroRNAs (miRNAs) influence several biological processes involved in human disease. Biological experiments for verifying the association between miRNA and disease are always costly in terms of both money and time. Although numerous biological experiments have identified multi-types of associations between miRNAs and diseases, existing computational methods are unable to sufficiently mine the knowledge in these associations to predict unknown associations. In this study, we innovatively propose a heterogeneous graph attention network model based on meta-subgraphs (MSHGANMDA) to predict the potential miRNA-disease associations. Firstly, we define five types of meta-subgraph from the known miRNA-disease associations. Then, we use meta-subgraph attention and meta-subgraph semantic attention to extract features of miRNA-disease pairs within and between these five meta-subgraphs, respectively. Finally, we apply a fully-connected layer (FCL) to predict the scores of unknown miRNA-disease associations and cross-entropy loss to train our model end-to-end. To evaluate the effectiveness of MSHGANMDA, we apply five-fold cross-validation to calculate the mean values of evaluation metrics Accuracy, Precision, Recall, and F1-score as 0.8595, 0.8601, 0.8596, and 0.8595, respectively. Experiments show that our model, which primarily utilizes multi-types of miRNA-disease association data, gets the greatest ROC-AUC value of 0.934 when compared to other state-of-the-art approaches. Furthermore, through case studies, we further confirm the effectiveness of MSHGANMDA in predicting unknown diseases.

SGAEMDA: Predicting miRNA-Disease Associations Based on Stacked Graph Autoencoder.

MicroRNA (miRNA)-disease association (MDA) prediction is critical for disease prevention, diagnosis, and treatment. Traditional MDA wet experiments, on the other hand, are inefficient and costly.Therefore, we proposed a multi-layer collaborative unsupervised training base model called SGAEMDA (Stacked Graph Autoencoder-Based Prediction of Potential miRNA-Disease Associations). First, from the original miRNA and disease data, we defined two types of initial features: similarity features and association features. Second, stacked graph autoencoder is then used to learn unsupervised low-dimensional representations of meaningful higher-order similarity features, and we concatenate the association features with the learned low-dimensional representations to obtain the final miRNA-disease pair features. Finally, we used a multilayer perceptron (MLP) to predict scores for unknown miRNA-disease associations. SGAEMDA achieved a mean area under the ROC curve of 0.9585 and 0.9516 in 5-fold and 10-fold cross-validation, which is significantly higher than the other baseline methods. Furthermore, case studies have shown that SGAEMDA can accurately predict candidate miRNAs for brain, breast, colon, and kidney neoplasms.

A novel gut-restricted RIPK1 inhibitor, SZ-15, ameliorates DSS-induced ulcerative colitis.

As a key mediator of cell death and inflammation, receptor-interacting protein kinase 1 (RIPK1) responds to a broad set of inflammatory and pro-death stimuli in human diseases. Inhibitors targeting RIPK1 are being investigated for the treatment of a wide range of human diseases, including ulcerative colitis. In the present study, we designed, synthesized, and investigated the anti-necroptosis and RIPK1-inhibition effects of SZ-15-a symmetrical high-molecular-weight (>500 Da) compound. SZ-15 effectively inhibited necroptosis in U937 and HT-29 cells at concentrations of 1 nM and 10 nM, respectively, and SZ-15 at a concentration of 10 nM almost completely blocked RIPK1, RIPK3, and mixed-lineage kinase domain-like (MLKL) protein phosphorylation induced by necrosis inducers. SZ-15 suppressed the pro-necroptosis function of RIPK1 by downregulating the mRNA expression of pro-inflammatory cytokines, including tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6. The activities of SZ-15 were effectively restricted to the gut: The percent recovery of the parent form of SZ-15 in mouse feces was 85.75%. Nevertheless, SZ-15 was effectively absorbed and detected in colon tissues after 1 h at a concentration of 3335 ± 868 ng/g, indicating that membrane permeability was maintained. SZ-15 alleviated dextran sulfate sodium (DSS)-induced ulcerative colitis in vivo by decreasing TNF-α, IL-1ß, IL-22, and IL-6 mRNA expression in colonic tissues. Our preclinical study describes a novel gut-restricted RIPK1 inhibitor that shows great potential for use in the clinical treatment of ulcerative colitis.

Preclinical characterization of a Fab-like CD3/CLDN18.2 XFab® bispecific antibody against solid tumors.

The claudin 18.2(CLDN18.2) antigen is highly expressed in gastric mucosa epithelial cells and frequently expressed in malignant tumors. Positive clinical outcomes have popularized claudin 18.2 as a novel cellular and antibody therapeutic. Here, we designed a bispecific antibody-ZWB67 using the XFab® platform, aimed at redirecting CD3+ effector T cells to CLDN18.2+ target cells or tissues. Physicochemical characterization, binding properties, T cell stimulatory activity, and T cell-dependent cellular cytotoxicity of ZWB67 were evaluated in dosage intervals using antigens of CD3 and target cells expressing CLDN18.2 or CD3. Then, the anti-tumor activity was assessed in humanized CD3EDG mice bearing MC-38-hCLDN18.2 tumors. Our data demonstrate that ZWB67 specifically binds to the human CD3e antigen (KD = 1.04E-08 M) and binds more strongly to CLDN18.2+ cells than to CD3+ cells (4.3- to 9.2-fold difference). ZWB67 showed good activity in the luciferase reporter system and exhibited dose-dependent activation, cytotoxicity of T cells, and cytokine release when co-cultured with CLDN18.2+ cells and CD3+ T cells. ZWB67 also exhibited high in vivo efficacy in the MC-38-hCLDN18.2 xenograft mouse model. In conclusion, the novel anti-CLDN18.2 × anti-CD3 bispecific antibody exhibited low affinity for anti-CD3, highly specific binding, potent cytotoxicity, and anti-tumor activity. These data provide a basis for future preclinical and clinical development of this therapeutic strategy.