iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution.

Although sequencing-based high-throughput chromatin interaction data are widely used to uncover genome-wide three-dimensional chromatin architecture, their sparseness and high signal-noise-ratio greatly restrict the precision of the obtained structural elements. To improve data quality, we here present iEnhance (chromatin interaction data resolution enhancement), a multi-scale spatial projection and encoding network, to predict high-resolution chromatin interaction matrices from low-resolution and noisy input data. Specifically, iEnhance projects the input data into matrix spaces to extract multi-scale global and local feature sets, then hierarchically fused these features by attention mechanism. After that, dense channel encoding and residual channel decoding are used to effectively infer robust chromatin interaction maps. iEnhance outperforms state-of-the-art Hi-C resolution enhancement tools in both visual and quantitative evaluation. Comprehensive analysis shows that unlike other tools, iEnhance can recover both short-range structural elements and long-range interaction patterns precisely. More importantly, iEnhance can be transferred to data enhancement of other tissues or cell lines of unknown resolution. Furthermore, iEnhance performs robustly in enhancement of diverse chromatin interaction data including those from single-cell Hi-C and Micro-C experiments.

Identification of gene biomarkers for brain diseases via multi-network topological semantics extraction and graph convolutional network.

BACKGROUND: Brain diseases pose a significant threat to human health, and various network-based methods have been proposed for identifying gene biomarkers associated with these diseases. However, the brain is a complex system, and extracting topological semantics from different brain networks is necessary yet challenging to identify pathogenic genes for brain diseases. RESULTS: In this study, we present a multi-network representation learning framework called M-GBBD for the identification of gene biomarker in brain diseases. Specifically, we collected multi-omics data to construct eleven networks from different perspectives. M-GBBD extracts the spatial distributions of features from these networks and iteratively optimizes them using Kullback-Leibler divergence to fuse the networks into a common semantic space that represents the gene network for the brain. Subsequently, a graph consisting of both gene and large-scale disease proximity networks learns representations through graph convolution techniques and predicts whether a gene is associated which brain diseases while providing associated scores. Experimental results demonstrate that M-GBBD outperforms several baseline methods. Furthermore, our analysis supported by bioinformatics revealed CAMP as a significantly associated gene with Alzheimer's disease identified by M-GBBD. CONCLUSION: Collectively, M-GBBD provides valuable insights into identifying gene biomarkers for brain diseases and serves as a promising framework for brain networks representation learning.

Molecular Structures of Poly(methyl methacrylate) at Different Buried Interfaces Revealed by Sum Frequency Generation Vibrational Spectroscopy.

Silica or calcium fluoride (CaF2) substrate-supported poly(methyl methacrylate) (PMMA) thin films as insulating layers are commonly used in photoelectric/photovoltaic devices to improve the efficiency or stability of these devices. However, a comparative investigation of molecular structures at buried PMMA/silica and PMMA/CaF2 interfaces under thermal stimuli remains unexplored. In this study, we qualitatively and quantitatively revealed different molecular orderings and orientations of PMMA at two interfaces before and after annealing using sum frequency generation (SFG) vibrational spectroscopy. SFG vibrations were carefully assigned by using various deuterated PMMAs. SFG results indicated that, at the buried PMMA/silica interface, the side OCH3 groups were prone to lie down before annealing and tended to stand up after annealing. In contrast, the case was the opposite at the buried PMMA/CaF2 interface. The relative hydrophobicity/hydrophilicity of the two substrates and the developed hydrogen bonds upon annealing at the buried PMMA/silica interface, which is absent at the CaF2 surface, are believed to be the driving forces for different interfacial molecular structures. This study benefits the molecular-level understanding of the interfacial local structural relaxation of polymers at buried interfaces and the rational design of photoelectric/photovoltaic devices from the molecular level.

Comparative efficacy of sodium thiosulfate, bisphosphonates, and cinacalcet for the treatment of vascular calcification in patients with haemodialysis: a systematic review and network meta-analysis.

BACKGROUND: Up to now, there is no unequivocal intervention to mitigate vascular calcification (VC) in patients with hemodialysis. This network meta-analysis aimed to systematically evaluate the clinical efficacy of sodium thiosulfate, bisphosphonates, and cinacalcet in treating vascular calcification. METHODS: A comprehensive study search was performed using PubMed, Web of Science, the Cochrane Library, EMBASE and China National Knowledge Internet (CNKI) to collect randomized controlled trials (RCTs) of sodium thiosulfate, bisphosphonates, and cinacalcet for vascular calcification among hemodialysis patients. Then, network meta-analysis was conducted using Stata 17.0 software. RESULTS: In total, eleven RCTs including 1083 patients were qualified for this meta-analysis. We found that cinacalcet (SMD - 0.59; 95% CI [-0.95, -0.24]) had significant benefit on vascular calcification compared with conventional therapy, while sodium thiosulfate or bisphosphonates did not show such efficiency. Furthermore, as for ranking the efficacy assessment, cinacalcet possessed the highest surface under the cumulative ranking curve (SUCRA) value (88.5%) of lessening vascular calcification and was superior to sodium thiosulfate (50.4%) and bisphosphonates (55.4%). Thus, above results suggested that cinacalcet might be the most promising drug for vascular calcification treatment in hemodialysis patients. Mechanistically, our findings illustrated that cinacalcet reduced serum calcium (SMD - 1.20; 95% CI [-2.08, - 0.33]) and showed the tendency in maintaining the balance of intact Parathyroid Hormone (iPTH) level. CONCLUSIONS: This network meta-analysis indicated that cinacalcet appear to be more effective than sodium thiosulfate and bisphosphonates in mitigating vascular calcification through decreasing serum calcium and iPTH. And cinacalcet might be a reasonable option for hemodialysis patients with VC in clinical practice. SYSTEMATIC REVIEW REGISTRATION: [ http://www.crd.york.ac.uk/PROSPERO ], identifier [CRD42022379965].

Association of Vascular Calcification with Serum lncRNA H19 and Runx2 mRNA Expression in Patients with Uremia.

Background: The objective of this study was to investigate the relationship between vascular calcification, serum lncRNA H19, and Runt-Related Transcription Factor 2 mRNA expression in patients with uremia. Methods: This study is a retrospective study which recruited 146 patients with uremia on dialysis from December 2021 to November 2022. Participants were divided into the VC and non-VC groups based on their chest X-ray calcification ratings. General and clinical data were collected from all patients. Serum H19, Runx2 mRNA, mineral bone disease effectors, and other blood markers were tested. Univariate analysis was performed to compare the changes in each clinical index between these two groups of patients. A multi-factor logistic regression analysis of risk factors for VC was performed. Receiver operating characteristics analyzed the H19 and Runx2 for their diagnostic values for VC. Pearson's test was used to analyze the correlation between the H19 and Runx2 expression and the factors influencing VC. Results: Patients in the VC group had significantly higher creatinine, serum phosphorus, calcium, BMP-2, FGF-23, OPG, and iPTH levels than those in the non-VC group (P < .05), while their albumin levels were significantly lower than those in the non-VC group (P < .05). The expression of H19 and Runx2 mRNA was significantly upregulated in the serum of VC patients (P < .05). H19 was significantly positively correlated with creatinine, serum phosphorus, calcium, BMP-2, OPG, and iPTH (P < .05). Runx2 mRNA was significantly positively correlated with creatinine, FGF-23, and iPTH (P < .05 ), while there was no significant correlation with other factors(P > .05). Albumin, BMP-2, iPTH, H19, and Runx2 were independent correlative-factors of uremic VC. In addition, the combined H19 and Runx2 test (AUC=0.850; 95% CI: 0.781-0.903) had good diagnostic values for the development of VC. Conclusion: Serum H19 and Runx2 levels are significantly associated with VC-related factors and are independent risk factors for uremic VC, and their levels contribute to the diagnosis of uremic VC.

Relationship between effective blood flow rate and clinical outcomes in maintenance hemodialysis patients: a single-center study.

The association between blood flow rate (BFR) and clinical outcomes in patients undergoing maintenance hemodialysis (MHD) is inconclusive. This retrospective study included 175 patients undergoing MHD treatment between July 2015 and March 2022, divided into two groups based on time-averaged effective blood flow rate (eBFR) median value. We investigated arteriovenous fistula (AVF) outcomes and the association of eBFR with all-cause mortality and new major adverse cardiovascular events (MACE). Mean ± SD and median time-averaged eBFR values were 276 ± 24 and 275 mL/min, respectively. After adjusting for relevant factors including age, sex, vintage, diabetes, CVD, receiving hemodiafiltration (HDF) treatment and spKt/V, Cox models indicated a low time-averaged eBFR (≤ 275 ml/min) was associated with increased risks of all-cause mortality (hazard ratio [HR] 14.18; 95% confidence interval [CI], 3.14-64.1) and new MACE (HR 3.76; 95% CI, 1.91-7.40) in MHD patients. Continuous Cox models demonstrated each 20 ml/min increase in eBFR linked to a 63% decrease in the risk of all-cause mortality (HR: 0.37, 95% CI: 0.23-0.59) and a 38% decrease in the occurrence of new MACE (HR: 0.62, 95% CI: 0.46-0.84). There was no significant difference in AVF outcomes between the two groups. Our study noted higher eBFR (>275 mL/min) is associated with lower risks of both all-cause mortality and new MACE compared with low eBFR (≤275 mL/min). Increased eBFR is not associated with a higher risk of AVF failure.

The role of sacubitril/valsartan in abnormal renal function patients combined with heart failure: a meta-analysis and systematic analysis.

AIMS: This study aimed to investigate the efficacy and safety of sacubitril/valsartan in abnormal renal function (eGFR < 60 ml/min/1.73m2) patients combined with heart failure based on randomized controlled trials (RCTs) and observational studies. METHODS: The Embase, PubMed and the Cochrane Library were searched for relevant studies from inception to December 2023. Dichotomous variables were described as event counts with the odds ratio (OR) and 95% confidence interval (CI) values. Continuous variables were expressed as mean standard deviation (SD) with 95% CIs. RESULTS: A total of 6 RCTs and 8 observational studies were included, involving 17335 eGFR below 60 ml/min/1.73m2 patients combined with heart failure. In terms of efficacy, we analyzed the incidence of cardiovascular events and found that sacubitril/valsartan significantly reduced the risk of cardiovascular death or heart failure hospitalization in chronic kidney disease (CKD) stages 3-5 patients with heart failure (OR: 0.65, 95%CI: 0.54-0.78). Moreover, sacubitril/valsartan prevented the serum creatinine elevation (OR: 0.81, 95%CI: 0.68-0.95), the eGFR decline (OR: 0.83, 95% CI: 0.73-0.95) and the development of end-stage renal disease in this population (OR:0.73, 95%CI:0.60-0.89). As for safety outcomes, we did not find that the rate of hyperkalemia (OR:1.31, 95%CI:0.79-2.17) and hypotension (OR:1.57, 95%CI:0.94-2.62) were increased in sacubitril/valsartan group among CKD stages 3-5 patients with heart failure. CONCLUSIONS: Our meta-analysis proves that sacubitril/valsartan has a favorable effect on cardiac function without obvious risk of adverse events in abnormal renal function patients combined with heart failure, indicating that sacubitril/valsartan has the potential to become perspective treatment for these patients.

How does ultrasound-assisted ionic liquid treatment affect protein? A comprehensive review of their potential mechanisms, safety evaluation, and physicochemical and functional properties.

Proteins are essential to human health with enormous food applications. Despite their advantages, plant and animal proteins often exhibit limited molecular flexibility and poor solubility due to hydrogen bonds, hydrophobic interactions, and ionic interactions within their molecular structures. Thus, there is an urgent need to modify the rigid structure of proteins to enhance their stability and functional properties. Ultrasound-assisted ionic liquid (UA-IL) treatment for developing compound modification and producing proteins with excellent functional properties has received interest. However, no review specifically addresses the interactions between UA-ILs and proteins. Hence, this review focused on recent research advancements concerning the effects and potential reaction mechanisms of UA-ILs on the physicochemical properties (including particle size; primary, secondary, and tertiary structure; and surface morphology) as well as the functionality (such as solubility, emulsifying properties, and foaming ability) of proteins. Moreover, the safety evaluation of modified proteins was also discussed from various perspectives, such as acute and chronic toxicity, genotoxicity, cytotoxicity, and environmental and microbial toxicity. This review demonstrated that UA-IL treatment-induced protein structural changes significantly impact the functional characteristics of proteins. This treatment approach efficiently promotes protein structure stretching and spatial rearrangement through cavitation, thermal effects, and ionic interactions. As a result, the functional properties of modified proteins exhibited an obvious enhancement, thereby bringing more opportunities to utilize modified protein products in the food industry. Potential future directions for protein modification using UA-ILs were also proposed.

PDA-PRGCN: identification of Piwi-interacting RNA-disease associations through subgraph projection and residual scaling-based feature augmentation.

BACKGROUND: Emerging evidences show that Piwi-interacting RNAs (piRNAs) play a pivotal role in numerous complex human diseases. Identifying potential piRNA-disease associations (PDAs) is crucial for understanding disease pathogenesis at molecular level. Compared to the biological wet experiments, the computational methods provide a cost-effective strategy. However, few computational methods have been developed so far. RESULTS: Here, we proposed an end-to-end model, referred to as PDA-PRGCN (PDA prediction using subgraph Projection and Residual scaling-based feature augmentation through Graph Convolutional Network). Specifically, starting with the known piRNA-disease associations represented as a graph, we applied subgraph projection to construct piRNA-piRNA and disease-disease subgraphs for the first time, followed by a residual scaling-based feature augmentation algorithm for node initial representation. Then, we adopted graph convolutional network (GCN) to learn and identify potential PDAs as a link prediction task on the constructed heterogeneous graph. Comprehensive experiments, including the performance comparison of individual components in PDA-PRGCN, indicated the significant improvement of integrating subgraph projection, node feature augmentation and dual-loss mechanism into GCN for PDA prediction. Compared with state-of-the-art approaches, PDA-PRGCN gave more accurate and robust predictions. Finally, the case studies further corroborated that PDA-PRGCN can reliably detect PDAs. CONCLUSION: PDA-PRGCN provides a powerful method for PDA prediction, which can also serve as a screening tool for studies of complex diseases.

A comprehensive analysis of copy number variations in diverse apple populations.

BACKGROUND: As an important source of genetic variation, copy number variation (CNV) can alter the dosage of DNA segments, which in turn may affect gene expression level and phenotype. However, our knowledge of CNV in apple is still limited. Here, we obtained high-confidence CNVs and investigated their functional impact based on genome resequencing data of two apple populations, cultivars and wild relatives. RESULTS: In this study, we identified 914,610 CNVs comprising 14,839 CNV regions (CNVRs) from 346 apple accessions, including 289 cultivars and 57 wild relatives. CNVRs summed to 71.19 Mb, accounting for 10.03% of the apple genome. Under the low linkage disequilibrium (LD) with nearby SNPs, they could also accurately reflect the population structure of apple independent of SNPs. Furthermore, A total of 3,621 genes were covered by CNVRs and functionally involved in biological processes such as defense response, reproduction and metabolic processes. In addition, the population differentiation index ([Formula: see text]) analysis between cultivars and wild relatives revealed 127 CN-differentiated genes, which may contribute to trait differences in these two populations. CONCLUSIONS: This study was based on identification of CNVs from 346 diverse apple accessions, which to our knowledge was the largest dataset for CNV analysis in apple. Our work presented the first comprehensive CNV map and provided valuable resources for understanding genomic variations in apple.