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Abstract MiRNAs and lncRNAs are two essential noncoding RNAs. Predicting associations between noncoding RNAs and diseases can significantly improve the accuracy of early diagnosis.With the continuous breakthroughs in artificial intelligence, researchers increasingly use deep learning methods to predict associations. Nevertheless, most existing methods face two major issues: low prediction accuracy and the limitation of only being able to predict a single type of noncoding RNA-disease association. To address these challenges, this paper proposes a method called K-Means and multigraph Contrastive Learning for predicting associations among miRNAs, lncRNAs, and diseases (K-MGCMLD). The K-MGCMLD model is divided into four main steps. The first step is the construction of a heterogeneous graph. The second step involves down sampling using the K-means clustering algorithm to balance the positive and negative samples. The third step is to use an encoder with a Graph Convolutional Network (GCN) architecture to extract embedding vectors. Multigraph contrastive learning, including both local and global graph contrastive learning, is used to help the embedding vectors better capture the latent topological features of the graph. The fourth step involves feature reconstruction using the balanced positive and negative samples and the embedding vectors fed into an XGBoost classifier for multi-association classification prediction. Experimental results have shown that AUC value for miRNA-disease association is 0.9542, lncRNA-disease association is 0.9603, and lncRNA-miRNA association is 0.9687. Additionally, this study has conducted case analyses using K-MGCMLD, which has validated the associations of all the top 30 miRNAs predicted to be associated with lung cancer and Alzheimer’s diseases.

Abstract The Optimal electrode configuration of Electroencephalograms (EEG) systems for mild cognitive impairment (MCI) detection and monitoring in non-clinical settings, i.e. number of electrodes and the positions of the electrodes, remains to be explored. In the current study, we explored the optimization of electrode configuration for MCI detection. We used a 32-channel EEG device to record the data of 21 MCI patients and 20 cognitively normal elderly (NC) undergoing working memory (WM) tasks. Based on the differential value (MCI group vs. NC group) from the Power Spectral Density (PSD) value of each electrode in θ and α frequency band during WM coding stage, six different electrode configurations were obtained: (1) four electrodes in the occipital lobe (OCL4); (2) three electrodes in the prefrontal lobe (PRL3); (3) four electrodes in the parietal lobe (PLL4), (4) eight electrodes in occipital combined parietal lobe (OPL8), (5) seven electrodes in occipital combined prefrontal lobe (OPL7); and (6) seven electrodes in parietal combined prefrontal lobe (PPL7). A multi-parameter combination-assisted binary logistic regression model was established to distinguish two groups. Receiver operating characteristic (ROC) curves were used to evaluate the MCI diagnostic power of each electrode configuration. The area under curve (AUC) of the ROC of electrode configurations OCL4, PRL3, PLL4, OPL8, OPL7 and PPL7 were 0.765, 0.683, 0.729, 0.83, 0.788, and 0.769, respectively. And the sensitivity of six electrode configurations were 0.962, 0.794, 0.873, 0.943, 0.859, and 0.938, respectively. Among these six configurations, OCL4, i.e. PO3, PO4, PO8, and PO7, had the highest sensitivity 96.2%, which meant that relying solely on these four electrodes of the occipital lobe had the potential to serve as an objective tool for preliminary screening of MCI. The abnormal brain rhythm characteristics of the frontal, parietal, and occipital lobes in the memory encoding stage of MCI provide a new perspective for MCI-WM impairment, which has the potential to be a novel biomarker for the early detection of pathological age-related cognitive decline. Further, a potential four-electrode configuration may be used for a novel detecting and monitoring EEG system of MCI in non-clinical settings.

Abstract Stomach adenocarcinoma (STAD) is a prevalent malignancy that is highly aggressive and heterogeneous. Intratumor heterogeneity (ITH) showed strong link to tumor progression and metastasis. High ITH may promote tumor evolution. An ITH-related signature (IRS) was created using as integrative technique including 10 machine learning methods based on TCGA, GSE15459, GSE26253, GSE62254 and GSE84437 datasets. The relevance of IRS in predicting the advantages of immunotherapy was assessed using a number of prediction scores and three immunotherapy datasets (GSE78220, IMvigor210 and GSE91061). Vitro experiments were performed to verify the biological functions of AKR1B1. The RSF + Enet (alpha = 0.1) projected model was proposed as the ideal IRS because it had the highest average C-index. The IRS demonstrated a strong performance in serving as an independent risk factor for the clinical outcome of STAD patients. It performed exceptionally well in predicting the overall survival rate of STAD patients, as seen by the TCGA cohort’s AUC of 1-, 3-, and 5-year ROC curves, which were 0.689, 0.683, and 0.669, respectively. A low IRS score demonstrated a superior response to immunotherapy, as seen by a lower TIDE score, lower immune escape score, greater TMB score, higher PD1&CTLA4 immunophenoscore, higher response rate, and improved prognosis. Common chemotherapeutic and targeted treatment regimens had lower IC50 values in the group with higher IRS scores. Vitro experiment showed that AKR1B1 was upregulated in STAD and knockdown of AKR1B1 obviously suppressed tumor cell proliferation and migration. The present investigation produced the best IRS for STAD, which may be applied to prognostication, risk stratification, and therapy planning for STAD patients.

Abstract Digital trade, as one of the vanguards of the global technological revolution and industrial transformation, empowers low-carbon economic cooperation on a global scale. This study based on panel data from 2007 to 2021 of 46 countries with varied development levels, constructed a multi-dimensional indicator system from six aspects: trade potential, digital infrastructure, digital innovation, digital skills and security, scale of digital trade, and digital trade environment, aim to measure the development level of digital trade and explore its impact on carbon emissions, followed by a heterogeneity analysis. The research results indicate that there are significant differences in the development levels of digital trade among countries with different economic strengths. Countries with stronger economic power and larger trade scales have a higher level of digital trade development, while less developed regions lag in digital trade. As the level of digital trade development increases, the impact of digital trade on carbon emissions will also change. Overall, digital trade exhibits a pronounced low-carbon effect, while its impact varies among countries with different development levels.

Abstract Temporary neurological dysfunction (TND), a common complication following surgical repair of Type A Aortic Dissection (TAAD), is closely associated with increased mortality and long-term cognitive impairment. Currently, effective treatment options for TND remain elusive. Therefore, we sought to investigate the potential of postoperative relative band power (RBP) in predicting the occurrence of postoperative TND, with the aim of identifying high-risk patients prior to the onset of TND. We conducted a prospective observational study between February and December 2022, involving 165 patients who underwent surgical repair for TAAD at our institution. Bedside Quantitative electroencephalography (QEEG) was utilized to monitor the post-operative brain electrical activity of each participant, recording changes in RBP (RBP Delta, RBP Theta, RBP Beta and RBP Alpha), and analyzing their correlation with TND. Univariate and multivariate analyses were employed to identify independent risk factors for TND. Subsequently, line graphs were generated to estimate the incidence of TND. The primary outcome of interest was the development of TND, while secondary outcomes included intensive care unit (ICU) admission and length of hospital stay. A total of 165 patients were included in the study, among whom 68 (41.2%) experienced TND. To further investigate the independent risk factors for postoperative TND, we conducted both univariate and multivariate logistic regression analyses on all variables. In the univariate regression analysis, we identified age (Odds Ratio [OR], 1.025; 95% CI, 1.002–1.049), age ≥ 60 years (OR, 2.588; 95% CI, 1.250–5.475), hemopericardium (OR, 2.767; 95% CI, 1.150–7.009), cardiopulmonary bypass (CPB) (OR, 1.007; 95% CI, 1.001–1.014), RBP Delta (OR, 1.047; 95% CI, 1.020–1.077), RBP Alpha (OR, 0.853; 95% CI, 0.794–0.907), and Beta (OR, 0.755; 95% CI, 0.649–0.855) as independent risk factors for postoperative TND. Further multivariate regression analyses, we discovered that CPB time ≥ 180 min (OR, 1.021; 95% CI, 1.011–1.032), RBP Delta (OR, 1.168; 95% CI, 1.105–1.245), and RBP Theta (OR, 1.227; 95% CI, 1.135–1.342) emerged as independent risk factors. TND patients had significantly longer ICU stays (p

Abstract Osteoarthritis (OA) is a progressive cartilage degradation disease, concomitant with synovitis, osteophyte formation, and subchondral bone sclerosis. Over 37% of the elderly population is affected by OA, and the number of cases is increasing as the global population ages. Therefore, the objective of this study was to identify and analyze the hub genes of OA combining with comprehensive bioinformatics analysis tools to provide theoretical basis in further OA effective therapies. Two sample sets of GSE46750 contained 12 pairs OA synovial membrane and normal samples harvested from patients as well as GSE98918 including 12 OA and non-OA patients were downloaded from the Gene Expression Omnibus database (GEO) database. Differentially expressed genes (DEGs) were identified using Gene Expression Omnibus 2R (GEO2R), followed by functional enrichment analysis, protein–protein interaction networks construction. The hub genes were identified and evaluated. An OA rat model was constructed, hematoxylin and eosin staining, safranin O/fast green staining, cytokines concentrations of serum were used to verify the model. The hub genes expression level in the knee OA samples were verified using RT-qPCR. The top 20 significantly up-regulated and down-regulated DEGs were screened out from the two datasets, respectively. The top 18 GO terms and 10 KEGG pathways were enriched. Eight hub genes were identified, namely MS4A6A, C1QB, C1QC, CD74, CSF1R, HLA-DPA1, HLA-DRA and ITGB2. Among them, the hub genes were all up-regulated in in vivo OA rat model, compared with healthy controls. The eight hub genes identified (MS4A6A, C1QB, C1QC, CD74, CSF1R, HLA-DPA1, HLA-DRA and ITGB2) were shown to be associated with OA. These genes can serve as disease markers to discriminate OA patients from healthy controls.

Abstract Traumatic brain injury (TBI) is a common disease in neurosurgery with a high fatality and disability rate which imposes a huge burden on society and patient's family. Inhibition of neuroinflammation caused by microglia activation is a reasonable strategy to promote neurological recovery after TBI. Myricetin is a natural flavonoid that has shown good therapeutic effects in a variety of neurological disease models, but its therapeutic effect on TBI is not clear. We demonstrated that intraperitoneal injection of appropriate doses of myricetin significantly improved recovery of neurological function after TBI in Sprague Dawley rats and inhibited excessive inflammatory responses around the lesion site. Myricetin dramatically reduced the expression of toxic microglia markers generated by TBI and LPS, according to the outcomes of in vivo and in vitro tests. In particular, the expression of inducible nitric oxide synthase, cyclooxygenase 2, and some pro-inflammatory cytokines was reduced, which protected learning and memory functions in TBI rats. Through network pharmacological analysis, we found that myricetin may inhibit microglia hyperactivation through the EGFR-AKT/STAT pathway. These findings imply that myricetin is a promising treatment option for the management of neuroinflammation following TBI.

Abstract X-ray ptychography offers high-resolution imaging of large areas at a high computational cost due to the large volume of data provided. To address the cost issue, we propose a physics-informed unsupervised classification algorithm that is performed prior to reconstruction and removes data outside the region of interest (RoI) based on the multimodal features present in the diffraction patterns. The preprocessing time for the proposed method is inconsequential in contrast to the resource-intensive reconstruction process, leading to an impressive reduction in the data workload to a mere 20% of the initial dataset. This capability consequently reduces computational time dramatically while preserving reconstruction quality. Through further segmentation of the diffraction patterns, our proposed approach can also detect features that are smaller than beam size and correctly classify them as within the RoI.

Abstract We built up a risk stratification model to divide acute type A aortic dissection (aTAAD) patients into low- and high-risk groups, further, to evaluate the risk factors for postoperative mortality. A total of 1364 patients from 2010 to 2020 in our center were retrospectively analyzed. More than twenty clinical variables were related with postoperative mortality. The postoperative mortality of the high-risk patients was doubled than the low-risk ones (21.8% vs 10.1%). The increased operation time, combined coronary artery bypass graft, cerebral complications, re-intubation, continuous renal replacement therapy and surgical infection were risk factors of postoperative mortality in low-risk patients. In addition, postoperative lower limbs or visceral malperfusion were risk factors, axillary artery cannulation and moderate hypothermia were protective factors in high-risk patients. A scoring system for quick decision-making is needed to select appropriate surgical strategy in aTAAD patients. For low-risk patients, different surgical treatments can be performed with similar clinical prognosis. Limited arch treatment and appropriate cannulation approach are crucial in high-risk aTAAD patients.

Abstract Stress fibers are actomyosin bundles that regulate cellular mechanosensation and force transduction. Interacting with the extracellular matrix through focal adhesion complexes, stress fibers are highly dynamic structures regulated by myosin motors and crosslinking proteins. Under external mechanical stimuli such as tensile forces, the stress fiber remodels its architecture to adapt to external cues, displaying properties of viscoelastic materials. How the structural remodeling of stress fibers is related to the generation of contractile force is not well understood. In this work, we simulate mechanochemical dynamics and force generation of stress fibers using the molecular simulation platform MEDYAN. We model stress fiber as two connecting bipolar bundles attached at the ends to focal adhesion complexes. The simulated stress fibers generate contractile force that is regulated by myosin motors and $$\alpha$$ α -actinin crosslinkers. We find that stress fibers enhance contractility by reducing the distance between actin filaments to increase crosslinker binding, and this structural remodeling ability depends on the crosslinker turnover rate. Under tensile pulling force, the stress fiber shows an instantaneous increase of the contractile forces followed by a slow relaxation into a new steady state. While the new steady state contractility after pulling depends only on the overlap between actin bundles, the short-term contractility enhancement is sensitive to the tensile pulling distance. We further show that this mechanical response is also sensitive to the crosslinker turnover rate. Our results provide new insights into the stress fiber mechanics that have significant implications for understanding cellular adaptation to mechanical signaling.

Abstract Bladder cancer (BC) is the most common malignant tumour of the urinary system and one of the leading causes of cancer-related death. Cuproptosis is a novel form of programmed cell death, and its mechanism in tumours remains unclear. This study aimed to establish the prognostic signatures of cuproptosis-related lncRNAs and determine their clinical prognostic value. RNA sequencing data from The Cancer Genome Atlas were used to detect the expression levels of cuproptosis-related genes in BC. Cuproptosis-related lncRNAs linked to survival were identified using co-expression and univariate Cox regression. Furthermore, consensus cluster analysis divided the lncRNAs into two subtypes. Subsequently, we established a signature model consisting of seven cuproptosis-related lncRNAs (AC073534.2, AC021321.1, HYI-AS1, PPP1R26-AS1, AC010328.1, AC012568.1 and MIR4435-2Hg) using least absolute shrinkage and selection operator regression. Survival analysis based on risk score showed that the overall survival and progression-free survival of patients in the high-risk group were worse than those in the low-risk group. Multivariate Cox analysis demonstrated the independent prognostic potential of this signature model for patients with BC. Moreover, age and clinical stage were also significantly correlated with prognosis. The constructed nomogram plots revealed good predictive power for the prognosis of patients with BC and were validated using calibration plots. Additionally, enrichment analysis, Single sample gene set enrichment analysis and immune infiltration abundance analysis revealed significant differences in immune infiltration between the two risk groups, with high levels of immune cell subset infiltrations observed in the high-risk group accompanied by various immune pathway activation. Moreover, almost all the immune checkpoint genes showed high expression levels in the high-risk group. Moreover, TIDE analysis suggested that the high-risk group was more responsive to immunotherapy. Finally, eight drugs with low IC50 values were screened, which may prove to be beneficial for patients in the high-risk group.

Abstract Electron ptychography provides new opportunities to resolve atomic structures with deep sub-angstrom spatial resolution and to study electron-beam sensitive materials with high dose efficiency. In practice, obtaining accurate ptychography images requires simultaneously optimizing multiple parameters that are often selected based on trial-and-error, resulting in low-throughput experiments and preventing wider adoption. Here, we develop an automatic parameter selection framework to circumvent this problem using Bayesian optimization with Gaussian processes. With minimal prior knowledge, the workflow efficiently produces ptychographic reconstructions that are superior to those processed by experienced experts. The method also facilitates better experimental designs by exploring optimized experimental parameters from simulated data.

Abstract In this paper, a piecewise sine waveguide (PWSWG) is proposed as the slow-wave structure (SWS) to develop high-power terahertz (THz) traveling wave tubes (TWTs). The PWSWG is an improvement over the rectangular waveguide wherein its two E-planes simultaneously oscillate up and down along the longitudinal direction. The oscillation curve in the H-plane is a piecewise sine curve formed by inserting line segments into the peaks and troughs of the sine curve. The simulation analysis and experimental verification show that the PWSWG offers the advantages of large interaction impedance and excellent electromagnetic transmission performance. Furthermore, the calculation results of beam–wave interaction show that the TWT based on PWSWG SWS can generate a radiated power of 253.1 W at the typical frequency of 220 GHz, corresponding to a gain of 37.04 dB and an interaction efficiency of 6.92%. Compared with the conventional SWG TWTs, the PWSWG TWT has higher interaction efficiency and shorter saturation tube length. In conclusion, the PWSWG proposed in this paper can be considered a suitable SWS for high-power THz radiation sources.

Abstract Throughout the world, esophageal cancer patients had a greater suicidal risk compared with ordinary people. Thus, we aimed to affirm suicide rates, standardized mortality rates, and underlying suicide-related risk factors of esophageal cancer patients. Patients suffering esophageal cancer were chosen from the Surveillance, Epidemiology, and End Results repository in 1975–2016. Suicide rates as well as standardized mortality rates in the patients were measured. Univariable and multivariable Cox regression had been adopted for establishing the latent suicide risk factors among patients suffering esophageal cancer. On multivariable Cox regression, gender (male vs. female, HR: 6.37), age of diagnosis (70–105 vs. 0–55, HR: 2.69), marital status, race (white race vs. black race, HR: 6.64; American Indian/Alaska Native, Asian/Pacific Islander vs. black race, HR: 8.60), histologic Grade (Grade III vs. Grade I, HR: 2.36), no surgery performed (no/unknown vs. yes, HR: 2.01), no chemotherapy performed were independent risk factors related to suicide in patients suffering esophageal cancer. Male sex, the older age, unmarried state, non-black race, histologic Grade III, no surgery performed, no chemotherapy performed were strongly related to suicide in patients suffering esophageal cancer.

Abstract Cathepsin A (CTSA) is a lysosomal protease that regulates galactoside metabolism. The previous study has shown CTSA is abnormally expressed in various types of cancer. However, rarely the previous study has addressed the role of CTSA in hepatocellular carcinoma (HCC) and its prognostic value. To study the clinical value and potential function of CTSA in HCC, datasets from the Cancer Genome Atlas (TCGA) database and a 136 HCC patient cohort were analyzed. CTSA expression was found to be significantly higher in HCC patients compared with normal liver tissues, which was supported by immunohistochemistry (IHC) validation. Both gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that CTSA co-expressed genes were involved in ATP hydrolysis coupled proton transport, carbohydrate metabolic process, lysosome organization, oxidative phosphorylation, other glycan degradation, etc. Survival analysis showed a significant reduction both in overall survival (OS) and recurrence-free survival (RFS) of patients with high CTSA expression from both the TCGA HCC cohort and 136 patients with the HCC cohort. Furthermore, CTSA overexpression has diagnostic value in distinguishing between HCC and normal liver tissue [Area under curve (AUC) = 0.864]. Moreover, Gene set enrichment analysis (GSEA) showed that CTSA expression correlated with the oxidative phosphorylation, proteasome, and lysosome, etc. in HCC tissues. These findings demonstrate that CTSA may as a potential diagnostic and prognostic biomarker in HCC.

Abstract The prognostic factors and optimal treatment for the elderly patient with glioblastoma (GBM) were poorly understood. This study extracted 4975 elderly patients (≥ 65 years old) with histologically confirmed GBM from Surveillance, Epidemiology and End Results (SEER) database. Firstly, Cumulative incidence function and cox proportional model were utilized to illustrate the interference of non-GBM related mortality in our cohort. Then, the Fine-Gray competing risk model was applied to determine the prognostic factors for GBM related mortality. Age ≥ 75 years old, white race, size > 5.4 cm, frontal lobe tumor, and overlapping lesion were independently associated with more GBM related death, while Gross total resection (GTR) (HR 0.87, 95%CI 0.80–0.94, P = 0.010), radiotherapy (HR 0.64, 95%CI 0.55–0.74, P

Abstract We aimed to analyse clinical characteristics and identify risk factors predicting all-cause mortality in older patients with severe coronavirus disease 2019 (COVID-19). A total of 281 older patients with severe COVID-19 were categorized into two age groups (60–79 years and ≥ 80 years). Epidemiological, clinical, and laboratory data, and outcome were obtained. Patients aged ≥ 80 years had higher mortality (63.6%) than those aged 60–79 years (33.5%). Anorexia and comorbidities including hypertension, diabetes and COPD, higher levels of lactate dehydrogenase (LDH), osmotic pressure, C-reactive protein, D-dimer, high-sensitivity troponin I and procalcitonin, and higher SOFA scores were more common in patients aged > 80 years than those aged 60–79 years and also more common and higher in non-survivors than survivors. LDH, osmotic pressure, C-reactive protein, D-dimer, high-sensitivity troponin I, and procalcitonin were positively correlated with age and sequential organ failure assessment (SOFA), whereas CD8+ and lymphocyte counts were negatively correlated with age and SOFA. Anorexia, comorbidities including hypertension, diabetes, and chronic obstructive pulmonary disease (COPD), LDH, osmotic pressure, and SOFA were significantly associated with 28-day all-cause mortality. LDH, osmotic pressure and SOFA were valuable for predicting 28-day all-cause mortality, whereas the area under the receiver operating characteristic curve of LDH was the largest, with sensitivity of 86.0% and specificity of 80.8%. Therefore, patients with severe COVID-19 aged ≥ 80 years had worse condition and higher mortality than did those aged 60–79 years, and anorexia and comorbidities including hypertension, diabetes, COPD, elevated plasma osmotic pressure, LDH, and high SOFA were independent risk factors associated with 28-day all-cause mortality in older patients with severe COVID-19. LDH may have the highest predictive value for 28-day all-cause mortality in all examined factors.

A new class of metal-organic frameworks (MOFs) has been synthesized by ligand-functionalization strategy. Systematic studies of their adsorption properties were performed at low and high pressure. Importantly, when fluorine was introduced into the framework via the functionalization, both the framework stabilities and adsorption capacities towards H2/CO2 were enhanced significantly. This consequence can be well interpreted by theoretical studies of these MOFs structures. In addition, one of these MOFs TKL-107 was used to fabricate mixed matrix membranes, which exhibit great potential for the application of CO2 separation. [ABSTRACT FROM AUTHOR]