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Abstract Background Our previous study revealed that feeding the antimicrobial peptide (AMP) product Scy-hepc significantly enhances the growth of mariculture fish through the activation of the GH-Jak2-STAT5-IGF1 axis. However, the contribution of gut microbiota to this growth enhancement remains unclear. This study aimed to elucidate the potential mechanism involved in intestinal absorption and modulation of gut microbiota in Epinephelus akaara following Scy-hepc feeding. Results The results showed that a 35 day regimen of Scy-hpec markedly promoted the growth of E. akaara compared to groups supplemented with either florfenicol, B. subtilis, or a vector. The growth enhancement is likely attributed to alterations in microbiota colonization in the foregut and midgut, characterized by an increasing abundance of potential probiotics (Rhizobiaceae and Lysobacter) and a decreased abundance of opportunistic pathogens (Psychrobacter and Brevundimonas) as determined by 16S rRNA analysis. Additionally, similar to the effect of florfenicol feeding, Scy-hepc significantly improved host survival rate by over 20% in response to a lethal dose challenge with Edwardsiella tarda. Further investigations demonstrated that Scy-hepc is absorbed by the fish foregut (20–40 min) and midgut (20–30 min) as confirmed by Western blot, ELISA, and Immunofluorescence. The absorption of Scy-hepc affected the swimming, swarming and surfing motility of Vibrio harveyi and Bacillus thuringiensis isolated from E. akaara’s gut. Moreover, Scy-hepc induced the downregulation of 40 assembly genes and the upregulation expression of 5, with the most significant divergence in gene expression between opportunistic pathogens and probiotics concentrated in their motility genes (PomA/B, MotA/B). Conclusions In summary, this study shows that feeding AMP Scy-hepc can promote growth and bolster immunity in E. akaara. These beneficial effects are likely due to the absorption of Scy-hepc in the fish’s foregut and midgut, which modulates the colonization and motility of commensal bacteria, leading to favorable changes in the composition of the foregut and midgut microbiota. Therefore, a profound understanding of the mechanisms by which antimicrobial peptides affect host gut microbiota will contribute to a comprehensive assessment of their advantages and potential application prospects as substitutes for antibiotics in fish health and improving aquaculture practices.

The study of the hydro-chemical characteristics of burnt rock aquifers helps to distinguish the hydraulic connections between different aquifers. Taking Zhangjiamao Coal Mine in Shenfu Mining Area as an example, 29 groups of water samples were collected from weathered bedrock, bedrock, 2−2 coal burned rock and 3−1 coal burned rock aquifers, and the hydro-chemical characteristics and control factors in the study area were analyzed by comprehensive use of statistical analysis, Piper trilinear diagram, Gibbs model and hybrid model, and the source of main ions was determined, based on which the contact relationship of each aquifer was identified. The results indicated that the total dissolved solids (TDS) of the weathered bedrock and the 2−2 coal burnt rock aquifer were close, slightly lower than the TDS of the bedrock aquifer, while the TDS of the 3−1 coal burnt rock aquifer was the highest, showing a trend of gradually increasing TDS with the increase of aquifer depth. The cations in the weathered bedrock and the 2−2 coal burnt rock aquifer were mainly Ca2+, while the cations in the bedrock and 3−1 coal burnt rock aquifer were mainly Na+; the anions in the weathered bedrock, 2−2 coal burnt rock, and 3−1 coal burnt rock aquifers were mainly HCO3−, while the bedrock aquifers were mainly HCO3−, and SO42−. The hydro-chemical types of weathered bedrock, 2−2 coal burnt rock, and 3−1 coal burnt rock aquifers were mainly HCO3−Ca type, HCO3−Ca and HCO3−Ca·Mg type, HCO3−Ca and HCO3−Na·Mg type. The hydro-chemical composition of weathered bedrock and 2−2 coal burnt rock aquifer was mainly controlled by water rock interaction, while the hydro-chemical composition of bedrock and 3−1 coal burnt rock aquifer was mainly influenced by both water rock interaction and concentration. The main ions of 3−1 coal burned rock, bedrock, weathered bedrock and 2−2 coal burned rock aquifer were respectively from the dissolution of silicate rock salt, the dissolution of silicate rock and evaporite rock salt, and the weathering dissolution of silicate rock and carbonate rock salt. At the same time, the reverse cation exchange interaction effect occurred in the groundwater disasters of each aquifer. Multiple indicator results showed that the ion composition of the weathered bedrock and the aquifer of the 2−2 coal fired rock was similar, and there was a strong hydraulic connection. There may be a direct contact relationship locally, which is different from the ion composition of the aquifer of the 3−1 coal fired rock. There is a certain barrier layer between them, and the hydraulic connection between them is weak.

The apolipoprotein E (APOE) ɛ4 allele is a recognized genetic risk factor for Alzheimer’s Disease (AD). Studies have shown that APOE ɛ4 mediates the modulation of intrinsic functional brain networks in cognitively normal individuals and significantly disrupts the whole-brain topological structure in AD patients. However, how APOE ɛ4 regulates brain functional connectivity (FC) and consequently affects the levels of cognitive impairment in AD patients remains unknown. In this study, we systematically analyzed functional magnetic resonance imaging (fMRI) data from two distinct cohorts: an In-house dataset includes 59 AD patients (73.37 ± 6.42 years), and the ADNI dataset includes 117 AD patients (74.91 ± 7.91 years). Experimental comparisons were conducted by grouping AD patients based on both APOE ɛ4 status and cognitive impairment levels of AD. Network-Based Statistic (NBS) method and the Graph Neural Network Explainer (GNN-Explainer) were combined to identify significant FC changes across different comparisons. Importantly, the GNN-Explainer method was introduced as an enhancement over the NBS method to better model complex high-order nonlinear characteristics for discovering FC features that significantly contribute to classification tasks. The results showed that APOE ɛ4 primarily influenced temporal lobe FCs, while it influenced different cognitive impairment levels of AD by adjusting prefrontal-parietal FCs. These findings were validated by p-values < 0.05 from NBS method, and 5-fold cross-validation along with ablation studies from the GNN-Explainer method. In conclusion, our findings provide new insights into the role of APOE ɛ4 in altering FC dynamics during the progression of AD, highlighting potential targets for early intervention.

PurposePrevious observational studies about the link between dietary factors and diabetic microvascular complications (DMCs) is controversial. Thus, we systemically assessed the potential causal relationship between diet and DMCs risk using Mendelian randomization (MR) methods.MethodsWe used genome-wide association studies (GWAS) statistics to estimate the causal effects of 17 dietary patterns on three common DMCs in European. Summary statistics on dietary intakes were obtained from the UK biobank, and data on DMCs [diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic neuropathy (DNP)] were obtained from the FinnGen Consortium. A two-sample MR (TSMR) was conducted to explore the causal relationships of dietary habits with DMCs. In addition, multivariable MR analysis (MVMR) was performed to adjust for traditional risk factors for eating habits, and evaluated the direct or indirect effects of diet on DMCs.ResultsTSMR analysis revealed that salad/raw vegetable intake (odd ratio [OR]: 2.830; 95% confidence interval [CI]: 1.102–7.267; p = 0.0306) and fresh fruit intake (OR: 2.735; 95% CI: 1.622–4.611; p = 0.0002; false discovery rate [FDR] = 0.0082) increased the risk of DR, whereas cheese intake (OR: 0.742; 95% CI: 0.563–0.978; p = 0.0339) and cereal intake (OR: 0.658; 95% CI: 0.444–0.976; p = 0.0374) decreased the risk of DR. Salad/raw vegetable (OR: 6.540; 95% CI: 1.061–40.300; p = 0.0430) and fresh fruit consumption (OR: 3.573; 95% CI: 1.263–10.107; p = 0.0164) are risk factors for DN, while cereal consumption (OR: 0.380; 95% CI: 0.174–0.833; p = 0.0156) is the opposite. And genetically predicted higher pork intake increased the risk of DNP (OR: 160.971; 95% CI: 8.832–2933.974; p = 0.0006; FDR = 0.0153). The MVMR analysis revealed that cheese intake may act as an independent protective factor for DR development. Moreover, fresh fruit intake, salad/raw vegetable intake and pork intake may be independent risk factors for DR, DN and DNP, respectively. Other causal associations between dietary habits and DMCs risk may be mediated by intermediate factors.ConclusionThis causal relationship study supports that specific dietary interventions may reduce the risk of DMCs.

Abstract Background The gut microbiota significantly influences the health and growth of red-spotted grouper (Epinephelus akaara), a well-known commercial marine fish from Fujian Province in southern China. However, variations in survival strategies and seasons can impact the stability of gut microbiota data, rendering it inaccurate in reflecting the state of gut microbiota. Which impedes the effective enhancement of aquaculture health through a nuanced understanding of gut microbiota. Inspired by this, we conducted a comprehensive analysis of the gut microbiota of wild and captive E. akaara in four seasons. Results Seventy-two E. akaara samples were collected from wild and captive populations in Dongshan city, during four different seasons. Four sections of the gut were collected to obtain comprehensive information on the gut microbial composition and sequenced using 16S rRNA next-generation Illumina MiSeq. We observed the highest gut microbial diversity in both captive and wild E. akaara during the winter season, and identified strong correlations with water temperature using Mantel analysis. Compared to wild E. akaara, we found a more complex microbial network in captive E. akaara, as evidenced by increased abundance of Bacillaceae, Moraxellaceae and Enterobacteriaceae. In contrast, Vibrionaceae, Clostridiaceae, Flavobacteriaceae and Rhodobacteraceae were found to be more active in wild E. akaara. However, some core microorganisms, such as Firmicutes and Photobacterium, showed similar distribution patterns in both wild and captive groups. Moreover, we found the common community composition and distribution characteristics of top 10 core microbes from foregut to hindgut in E. akaara. Conclusions Collectively, the study provides relatively more comprehensive description of the gut microbiota in E. akaara, taking into account survival strategies and temporal dimensions, which yields valuable insights into the gut microbiota of E. akaara and provides a valuable reference to its aquaculture.

Abstract Aspect-based sentiment analysis (ABSA) aims to mine the sentiment tendencies expressed by specific aspect terms. The studies of ABSA mainly focus on the attention-based approaches and the graph neural network approaches based on dependency trees. However, the attention-based methods usually face difficulties in capturing long-distance syntactic dependencies. Additionally, existing approaches using graph neural networks have not made sufficient exploit the syntactic dependencies among aspects and opinions. In this paper, we propose a novel Syntactic Dependency Graph Convolutional Network (SD-GCN) model for ABSA. We employ the Biaffine Attention to model the sentence syntactic dependencies and build syntactic dependency graphs from aspects and emotional words. This allows our SD-GCN to learn both the semantic relationships of aspects and the overall semantic meaning. According to these graphs, the long-distance syntactic dependency relationships are captured by GCNs, which facilitates SD-GCN to capture the syntactic dependencies between aspects and viewpoints more comprehensively, and consequently yields enhanced aspect features. We conduct extensive experiments on four aspect-level sentiment datasets. The experimental results show that our SD-GCN outperforms other methodologies. Moreover, ablation experiments and visualization of attention further substantiate the effectiveness of SD-GCN.

Evidence showed that N6-methyladenosine (m6A) modification plays a pivotal role in influencing RNA fate and is strongly associated with cell growth and developmental processes in many species. However, no information regarding m6A modification in Eimeria tenella is currently available. In the present study, we surveyed the transcriptome-wide prevalence of m6A in sporulated oocysts and unsporulated oocysts of E. tenella. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) analysis showed that m6A modification was most abundant in the coding sequences, followed by stop codon. There were 3,903 hypermethylated and 3,178 hypomethylated mRNAs in sporulated oocysts compared with unsporulated oocysts. Further joint analysis suggested that m6A modification of the majority of genes was positively correlated with mRNA expression. The mRNA relative expression and m6A level of the selected genes were confirmed by quantitative reverse transcription PCR (RT-qPCR) and MeRIP-qPCR. GO and KEGG analysis indicated that differentially m6A methylated genes (DMMGs) with significant differences in mRNA expression were closely related to processes such as regulation of gene expression, epigenetic, microtubule, autophagy-other and TOR signaling. Moreover, a total of 96 DMMGs without significant differences in mRNA expression showed significant differences at protein level. GO and pathway enrichment analysis of the 96 genes showed that RNA methylation may be involved in cell biosynthesis and metabolism of E. tenella. We firstly present a map of RNA m6A modification in E. tenella, which provides significant insights into developmental biology of E. tenella.

ObjectivesAdrenal tumors are common, but adrenocortical carcinomas (ACCs) are a rare and challenging form of cancer to diagnose and manage.This study aimed to explore the critical role of mitochondrial quality in maintaining cellular function and the implications of the abnormal expression of mitochondrial metabolism-related proteins observed in ACC patients. We focused on identifying the connection between mitochondrial quality and the development of ACC at molecular and genomic levels.MethodsWe compared mitochondrial quality-related genes (MQRGs) across ACC subtypes using overall survival (OS) and disease-free survival (DFS) as evaluation indicators. Furthermore, a novel MQRG score was developed to predict clinical prognosis and guide immunotherapy responses accurately.ResultsThe majority of MQRGs were upregulated in the ACC samples, correlating to poor prognosis. The MQRG score was confirmed as an independent prognostic factor for ACC, with the high-risk MQRG score group showing a significantly shorter overall survival period.ConclusionsMultilayer alterations in MQRGs are associated with patient prognosis and immune cell infiltration characteristics. This comprehensive analysis of MQRGs can contribute to a deeper understanding of potential differences in ACC patients' tumor microenvironment. This can influence clinical decision-making and advanced prognosis prediction, thereby offering new insights into personalized treatments in ACC.

Abstract Background Previous studies have reported that high fasting plasma glucose (FPG), even that within the normal range, is associated with the risk of type 2 diabetes (T2D). Nevertheless, these findings are limited to specific populations. Thus, studies in the general population are imperative. Methods This study included two cohorts comprising 204 640 individuals who underwent physical examinations at the Rich Healthcare Group present at 32 locations in 11 cities of China from 2010 to 2016 and 15 464 individuals who underwent physical tests at the Murakami Memorial Hospital in Japan. Cox regression, restricted cubic spline (RCS), Kaplan–Meier (KM) curves, and subgroup analysis were used to determine the relationship between FPG and T2D. Receiver operating characteristic (ROC) curves were used to evaluate the predictive power of FPG for T2D. Results The mean age of the 220 104 participants (204 640 Chinese and 15 464 Japanese participants) was 41.8 years (41.7 years for the Chinese and 43.7 years for the Japanese participants). During follow-up, 2611 individuals developed T2D (2238 Chinese and 373 Japanese participants). The RCS demonstrated a J-shaped relationship between FPG and T2D risk, with inflexion points of 4.5 and 5.2 for the Chinese and Japanese populations, respectively. Multivariate-adjusted hazard ratio (HR) was 7.75 for FPG and T2D risk after the inflexion point (7.3 for Chinese and 21.13 for Japanese participants). Conclusions In general Chinese and Japanese populations, the normal baseline FPG range showed a J-shaped relationship with the risk of T2D. Baseline FPG levels help identify individuals at high risk of T2D and may enable early primary prevention to improve their outcomes.

Abstract Background Studies have reported that lipid-derived indicators are associated with type 2 diabetes (T2D) in various populations; however, it is unclear which lipid-derived indicators could effectively predict T2D risk. Therefore, this study aimed to explore the association between four lipid-derived indicators and T2D risk. Methods This was a post-hoc analysis from a large cohort that included data from 114,700 Chinese individuals aged 20 years and older from 11 cities and 32 sites. The association between four lipid-derived indicators and T2D risk was determined using Kaplan-Meier (KM) survival curves, Cox regression, and restricted cubic spline analyses. This study used receiver operating characteristic (ROC) curves for assessing the ability of four lipid-derived indicators to accurately predict the development of T2D during follow-up. Results This study included a total of 114,700 participants, with a mean age of 44.15. These individuals were followed up for 3.1 years, of which 2668 participants developed T2D. ROC curve analysis showed that TyG was the most robust predictor of 3-year [aera under the ROC (AUC) = 0.77, 95% CI: 0.768, 0.772] and 5-year T2D risk (AUC = 0.763, 95% CI: 0.760, 0.765). In addition, sensitivity analysis showed an association between TyG and an increased incidence of T2D. Conclusions The results suggest that TyG was a superior for predicting the risk of developing T2D in the general Chinese population.

The cleanliness of transferred graphene is crucial for its application in various fields. The presence of residues of polymethyl methacrylate (PMMA) on the surface of transferred graphene has a negative impact on its transparency, transport, and other critical properties. In this study, we propose an alternative method to reduce such residues by using acetic acid instead of the commonly used acetone. The effects of treating graphene with acetic acid and acetone are comprehensively evaluated through optical microscopy, scanning electron microscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy. The results of this study demonstrate a significant reduction in surface residue when graphene is treated with acetic acid, compared to acetone treatment. Additionally, we applied this method to fabricate graphene-based supercapacitors and compared the results using acetic acid and acetone. This reduction in residue holds great promise for advancing the development of high-quality graphene devices.

Abstract Background The incidence of renal cell carcinoma (RCC) has increased in recent years. Metastatic RCC is common and remains a major cause of mortality. A regulatory role for circular RNAs (circRNAs) in the occurrence and progression of RCC has been identified, but their function, molecular mechanisms, and potential clinical applications remain poorly understood. Methods High‐throughput RNA sequencing was used to explore the differential expression of circRNAs and their related pathways in RCC patients. Transwell and CCK‐8 assays were used to assess the function of hsa_circ_0057105 in RCC cells. The clinical relevance of hsa_circ_0057105 was evaluated in a cohort of RCC patients. The hsa_circ_0057105 regulatory axis was defined using RNA pull‐down, luciferase reporter assays, and fluorescence in situ hybridization assays, and the in vivo effect of hsa_circ_0057105 was validated using animal experiments. Results Single‐sample gene set enrichment analysis and correlation analysis of RNA‐seq data showed that hsa_circ_0057105 was potentially oncogenic and may serve to regulate epithelial‐mesenchymal transition (EMT) activation in RCC. Hsa_circ_0057105 expression was associated with advanced TNM stages and was an independent prognostic factor for poor RCC patient survival. Phenotypic studies show that hsa_circ_0057105 can enhance the migration and invasion abilities of RCC cells. Further, hsa_circ_0057105 was shown to inhibit the expression of miR‐577, a miRNA that regulated the expression of both COL1A1, which induced EMT activation, and VDAC2, which modulated ferroptosis sensitivity. The dual regulatory roles of hsa_circ_0057105 on EMT and ferroptosis sensitivity were verified using rescue experiments. Animal studies confirmed that hsa_circ_0057105 increased the metastatic ability and ferroptosis sensitivity of RCC cells in vivo. Conclusions In RCC, hsa_circ_0057105 regulates COL1A1 and VDAC2 expression through its sponge effect on miR‐577, acting like a ‘double‐edged sword’. These findings provide new insight into the relationship between EMT and ferroptosis in RCC and provide potential biomarkers for RCC surveillance and treatment.

As a special kind of entropy, decision self-information effectively considers the uncertainty information of both the lower and upper approximations. However, it is limited to rough binary relations, which limits its application to complex problems. In addition, parameterized fuzzy β covering, as an extension of the covering-based rough set model, can effectively characterize the similarity between samples. We combine decision self-information with a parameterized fuzzy β neighborhood to propose decision self-information in fuzzy environments, and we study its important properties. On this basis, a three-way multi-attribute group decision-making algorithm is established, and a practical problem is solved. The effectiveness of the proposed method is verified by experimental analysis.

PurposeThis study aimed to identify the effect of different durations of visual target presentation during ciliary-muscle training on children's kinetic visual acuity (KVA), uncorrected distance visual acuity (UDVA), axial length, and accommodative facility.MethodsBased on the ciliary-muscle regulation mechanism, an intervention program involving ciliary-muscle training with different durations of visual target presentation combined with physical education classes was designed. The intervention aimed to determine the effect of different ciliary-muscle training durations on children's visual acuity. A total of 153 children aged 10–11 years from a school in Suzhou (a major city located in southeastern Jiangsu Province, East China) were enrolled as participants in this 32-week intervention study. This study measured the participants' UDVA and KVA before, during (after the 16th week), and after (after the 32nd week) the experimental intervention. The accommodative facility was measured during and after the intervention.ResultsAfter 32 weeks of the intervention, the KVA and UDVA of each experimental group were significantly improved (p < 0.05). A high percentage in the improvement of KVA was observed in the 3-s and 1-s groups (25.53%, 21.74%), and the highest percentage in the improvement of UDVA was observed in the 3-s group (2.96%). Axial length increased significantly in all groups (p < 0.05), and there was a low percentage increase in the 1-s and 3-s groups (0.82%). The accommodative facility was significantly improved in all experimental groups, with a higher improvement percentage in the 3-s and 1-s groups (3.01% and 2.61%, respectively). After dividing the children in each group according to their visual acuity, the KVA of children in the 1-s group was significantly improved, the UDVA of children with myopia was significantly increased, and the accommodative facility of children with mild and moderate myopia was significantly improved. Moreover, the KVA, UDVA, and accommodative facility of children with mild and moderate myopia in the 3-s group were significantly improved. The KVA of children with emmetropia and the accommodative facility of children with mild and moderate myopia in the 5-s group were also significantly increased.ConclusionIn school physical education classes, the 1-s, 3-s, and 5-s ciliary-muscle regulating exercise could effectively improve the kinetic visual acuity, uncorrected distance visual acuity, and accommodative facility of children aged 10–11 years. Among them, the effects of the 1-s and 3-s durations are better than that of the 5-s duration, as it can reduce the growth rate of axial length and achieve better effects among children with mild and moderate myopia.

Battery state of health (SOH) is a significant metric for evaluating battery life and predicting battery safety. Currently, SOH research is largely based on laboratory data, with a dearth of research on electric vehicle (EV) operating data. Due to the difficulty in obtaining complete charge data under EV operating conditions, this study presents a SOH estimation method utilizing deep network adaptation. First, a data-driven approach is employed to extract voltage, current, state of charge (SOC), and incremental capacity (IC) data features. To compensate for the lack of aging information in the EV operation data domain, transfer learning is employed to construct the SOH estimation model. Additionally, to resolve inconsistent data distribution between the source laboratory battery data domain and the target EV operation data domain, an adaptive layer is added to the network, and adaptation of deep network (ADN) is utilized to enhance the model’s performance. Finally, the model is validated using electric bus operational data. Results indicate that this model’s average Mean Absolute Error (MAE) is less than 3.0%, and, compared to support vector machine (SVM) regression and Gaussian Process Regression (GPR) algorithms, the MAE is reduced by 27.7% and 38.4%, respectively.

BackgroundThere is compelling evidence for an association between triglyceride glucose-body mass index (TyG-BMI) and cardiovascular disease (CVD). However, data on the relationship between TyG-BMI and prehypertension (pre-HTN) or hypertension (HTN) remains scant. The aim of this study was to characterize the association between TyG-BMI and pre-HTN or HTN risk, and to assess the ability of TyG-BMI in predicting pre-HTN and HTN in Chinese and Japanese populations.MethodsA total of 214,493 participants were included in this study. The participants were divided into 5 groups based on quintiles of TyG-BMI index at baseline (Q1, Q2, Q3 Q4 and Q5). Logistic regression analysis was then employed to assess the relationship between TyG-BMI quintiles and pre-HTN or HTN. Results were presented as odds ratios (ORs) and 95% confidence intervals (CIs).ResultsOur restricted cubic spline analysis showed that TyG-BMI was linearly correlated with both pre-HTN and HTN. Multivariate logistic regression analysis indicated that TyG-BMI was independently correlated with pre-HTN [ORs and 95% CIs were 1.011 (1.011–1.012), 1.021 (1.02–1.023), 1.012 (1.012–1.012), respectively] and HTN [ORs and 95% CIs were 1.021 (1.02–1.021), 1.031 (1.028–1.033), 1.021 (1.02–1.021), respectively] in Chinese or Japanese individuals or both groups after adjusting for all variates. In addition, subgroup analyses showed that the relationship between TyG-BMI and pre-HTN or HTN was independent of age, sex, BMI, country, smoking and drinking status. Across all study populations, the areas under the TyG-BMI curve predicting pre-HTN and HTN were 0.667 and 0.762, respectively, resulting in cut-off values of 189.7 and 193.7, respectively.ConclusionOur analyses showed that TyG-BMI was independently correlated with both pre-HTN and HTN. Besides, TyG-BMI showed superior predictive power in predicting pre-HTN and HTN compared to TyG or BMI alone.

ObjectivesTo investigate the significance of proton magnetic resonance spectroscopy (1H-MRS) and glutamate chemical exchange saturation transfer (Glu-CEST) techniques in assessing the condition and prognosis of acute bilirubin encephalopathy patients and to understand the mechanism of nerve injury in this disease.Materials and methodsFrom September 2019 to February 2021, 31 neonates with acute bilirubin encephalopathy and 16 healthy neonates were enrolled in this study. All the quantitative results of 1H-MRS, Glu-CEST, and conventional magnetic resonance imaging (MRI) of all neonates were analyzed. The associations between statistically significant indicators of imaging and developmental quotients (DQ) were analyzed.ResultsThe 31 cases were assigned to the mild subgroup (n = 21) and moderate and severe subgroup (n = 10) according to the bilirubin-induced neurologic dysfunction (BIND) scores. The case group had elevated Cho and GABA absolute concentrations compared to the normal control group (all p < 0.05). Compared with the normal control group, the absolute concentration of GABA of the moderate and severe subgroup was significantly larger (p < 0.05). Compared with the normal control group, the Glu-CEST% values in the left basal ganglia, right thalamus, left frontal cortex and bilateral medial geniculate body of the case group was significantly larger (all p < 0.05). The moderate and severe subgroup had higher Glu-CEST% values in the left basal ganglia, right thalamus, and bilateral medial geniculate body than the normal control group (all p < 0.05). A negative association was revealed between the DQ scores and the Glu-CEST% values in the left basal ganglia (r = −0.888, p < 0.05).ConclusionThe combination of 1H-MRS and Glu-CEST techniques can monitor the intracerebral metabolite level of acute bilirubin encephalopathy and evaluate the illness severity.

AimsDepression in bipolar disorder (BD) is often misdiagnosed as unipolar depression (UD), leading to mistreatments and poor clinical outcomes in many bipolar patients. Herein, we report direct comparisons between medication-free patients with BD and those with UD in terms of the microstructure and neurometabolites in eight brain regions.MethodsA total of 20 patients with BD, 30 with UD patients, and 20 matched healthy controls (HCs) underwent 3.0T magnetic resonance imaging with chemical exchange saturation transfer (CEST) for glutamate (Glu; GluCEST) imaging, multivoxel magnetic resonance spectroscopy, and diffusion kurtosis imaging.ResultsCompared with HCs, patients with UD showed significantly lower levels of multiple metabolites, GluCEST% values, and diffusional kurtosis [mean kurtosis (MK)] values in most brain regions. In contrast, patients with BD presented significantly higher levels of Glu in their bilateral ventral prefrontal white matter (VPFWM), higher choline (Cho)-containing compounds in their left VPFWM and anterior cingulate cortex (ACC), and higher GluCEST% values in their bilateral VPFWM and ACC; moreover, reduced MK in these patients was more prominent in the left VPFWM and left thalamus.ConclusionThe findings demonstrated that both patients with UD and BD have abnormal microstructure and metabolic alterations, and the changes are not completely consistent in the prefrontal lobe region. Elevated Glu, Cho, and GluCEST% in the ACC and VPFWM of patients with UD and BD may help in differentiating between these two disorders. Our findings support the significance for the microstructural integrity and brain metabolic changes of the prefrontal lobe region in BD and UD.

AimsThis study adopted the Glutamate Chemical Exchange Saturation Transfer (GluCEST) imaging technique to quantitatively analyze cranial glutamate and discussed the effectiveness of GluCEST values in identifying the pathogenesis of encephalopathy after CO poisoning.MethodsThe routine MRI and functional MRI scans of two cohorts of subjects (CO group, n = 29; Control group, n = 21) were performed. Between-group comparisons were conducted for GluCEST% in regions of interest (ROI), including the basal ganglia, the thalamus, the frontal lobe, the occipital lobe, the genu of corpus callosum, the cingulate gyrus, and the cuneus. Moreover, an age-stratified subgroup analysis was devised, and a correlational analysis was performed for GluCEST% in each ROI, including the time in coma, Simple Mini-Mental State Examination Scale (MMSE) score, Hamilton Anxiety Scale score, and blood COHb%.ResultsAs compared to the healthy control, the CO group led to significantly increasing GluCEST% in the basal ganglia, the occipital lobe, the genu of the corpus callosum, the cingulate gyrus, and the cuneus (p < 0.05). In the subgroup analysis for age, adult patients had higher GluCEST% in the basal ganglia, the thalamus, the occipital lobe, the cingulate gyrus, and the cuneus compared to healthy adults (p < 0.05). In addition, the correlational analysis of CO-poisoned patients revealed a statistical association between the GluCEST% and the MMSE in the thalamus and the genu of the corpus callosum.ConclusionThe GluCEST technique is superior to routine MRI in that it can identify the cerebral biochemical changes sooner after acute CO poisoning, which is significant for our understanding of the role of neurotransmitters in the pathological basis of this disease. Brain injury caused by CO poisoning may be different in adults and children.

AimsCurrently, there are only a few studies concerning brain functional alterations after acute alcohol exposure, and the majority of existing studies attach more importance to the spatial properties of brain function without considering the temporal properties. The current study adopted sliding window to investigate the resting-state brain networks in healthy volunteers after acute alcohol intake and to explore the dynamic changes in network connectivity.Materials and methodsTwenty healthy volunteers were enrolled in this study. Blood-oxygen-level-dependent (BOLD) data prior to drinking were obtained as control, while that 0.5 and 1 h after drinking were obtained as the experimental group. Reoccurring functional connectivity patterns (states) were determined following group independent component analysis (ICA), sliding window analysis and k-means clustering. Between-group comparisons were performed with respect to the functional connectivity states fractional windows, mean dwell time, and the number of transitions.ResultsThree optimal functional connectivity states were identified. The fractional windows and mean dwell time of 0.5 h group and 1 h group increased in state 3, while the fraction window and mean dwell time of 1 h group decreased in state 1. State 1 is characterized by strong inter-network connections between basal ganglia network (BGN) and sensorimotor network (SMN), BGN and cognitive executive network (CEN), and default mode network (DMN) and visual network (VN). However, state 3 is distinguished by relatively weak intra-network connections in SMN, VN, CEN, and DMN. State 3 was thought to be a characteristic connectivity pattern of the drunk brain. State 1 was believed to represent the brain’s main connection pattern when awake. Such dynamic changes in brain network connectivity were consistent with participants’ subjective feelings after drinking.ConclusionThe current study reveals the dynamic change in resting-state brain functional network connectivity before and after acute alcohol intake. It was discovered that there might be relatively independent characteristic functional network connection patterns under intoxication, and the corresponding patterns characterize the clinical manifestations of volunteers. As a valuable imaging biomarker, dynamic functional network connectivity (dFNC) offers a new approach and basis for further explorations on brain network alterations after alcohol consumption and the alcohol-related mechanisms for neurological damage.

AimsAlcohol consumption could lead to a series of health problems and social issues. In the current study, we investigated the resting-state functional brain networks of healthy volunteers before and after drinking through graph-theory analysis, aiming to ascertain the effects of acute alcohol intake on topology and information processing mode of the functional brain networks.Materials and methodsThirty-three healthy volunteers were enrolled in this experiment. Each volunteer accepted alcohol breathalyzer tests followed by resting-state magnetic resonance imaging at three time points: before drinking, 0.5 h after drinking, and 1 h after drinking. The data obtained were grouped based on scanning time into control group, 0.5-h group and 1-h group, and post-drinking data were regrouped according to breath alcohol concentration (BrAC) into relative low BrAC group (A group; 0.5-h data, n = 17; 1-h data, n = 16) and relative high BrAC group (B group; 0.5-h data, n = 16; 1-h data, n = 17). The graph-theory approach was adopted to construct whole-brain functional networks and identify the differences of network topological properties among all the groups.ResultsThe network topology of most groups was altered after drinking, with the B group presenting the most alterations. For global network measures, B group exhibited increased global efficiency, Synchronization, and decreased local efficiency, clustering coefficient, normalized clustering coefficient, characteristic path length, normalized characteristic path length, as compared to control group. Regarding nodal network measures, nodal clustering coefficient and nodal local efficiency of some nodes were lower in B group than control group. These changes suggested that the network integration ability and synchrony improved, while the segregation ability diminished.ConclusionThis study revealed the effects of acute alcohol intake on the topology and information processing mode of resting-state functional brain networks, providing new perceptions and insights into the effects of alcohol on the brain.

Liquid crystal tunable filters (LCTFs) are extensively used in hyperspectral imaging systems to obtain spectral information of target scenes. However, a typical LCTF can only filter linearly polarized light, greatly reducing the transmittance of the system and limiting its application in spectral and polarization imaging. In this paper, a spectropolarimeter using Mach–Zehnder structured LCTFs (MZ-LCTFs) combined with liquid crystal variable retarders (LCVRs) is proposed. The polarized beam splitter (PBS) can make full use of the two polarization components of the incident light to improve the transmittance of the system. Specifically, the results show that the mean pixel intensity (MPI) of spectral images is improved by 93.48% compared to a typical LCTF. Subsequently, the average signal to noise ratio (SNR) of filtered and unfiltered images when simultaneously using polarization S and P channels is increased by 2.59 dB compared to a single channel. In addition, the average Standard Deviations (STDs) of DoLP and DoCP are 0.016 and 0.018, respectively. The proposed method has the potential to be applied to obtain polarization information with high optical efficiency and a full spectrum in a wide band.

This study aims to investigate the effect of high temperature on the mechanical properties of low-slump polypropylene fiber (PPF) concrete, and tests the tensile and compressive properties of 204 groups of low-slump PPF concrete with eight different dosages and four different lengths at normal temperature and after high temperature. The results of the compressive test showed that PPF can significantly improve the mechanical properties of concrete after high temperature when the fiber content is small, and the compressive strength of low collapse polypropylene fiber concrete after high temperature showed a tendency to rise and then fall at the same temperature with an increase of the fiber admixture. When the fiber content was 0.5 kg/m3, the compressive strengths of 3 mm, 9 mm, 15 mm and 19 mm reached their maxima, which were 9.65%, 11.33%, 7.90% and 2.87% higher than that of ordinary concrete, respectively. With an increase in fiber length, the effect of PPF on the compressive strength of concrete is not obvious. PPF at high admixture further increases the pore and air content in concrete, which decreases the compactness of the concrete, thus leading to a decrease in the compressive strength of the concrete. When the temperature was 800 °C and the fiber admixture was 5.0 kg/m3, the compressive strength of PPF concrete with different lengths reduced by 17.83%, 17.27%, 22.59% and 23.92%, respectively, compared to normal concrete. In addition, according to the results, the optimal combinations of strength at room temperature and after high temperature were 3 mm fiber length and 1.0 kg/m3 dosing and 9 mm fiber length and 0.5 kg/m3 dosing, respectively, which increased the compressive and tensile strengths by 17.15% and 25.72% at room temperature and by at least 6% and 20% after high temperature, compared to the concrete without fiber dosing. Moreover, the stress–strain constitutive equations of PPF concrete at normal temperature and after high temperature were established, which can be used for finite element simulation and related mechanical analysis of PPF after high temperature.

ObjectivesTo evaluate the diagnostic and prognostic values of glutamate chemical exchange saturation transfer (GluCEST) magnetic resonance imaging as a quantitative method for pathogenetic research and clinical application of carbon monoxide (CO) poisoning-induced encephalopathy combined with the proton magnetic resonance spectroscopy (1H-MRS) and the related histopathological and behavioral changes.MethodsA total of 63 Sprague–Dawley rats were randomly divided into four groups. Group A (n = 12) was used for animal modeling verification; Group B (n = 15) was used for magnetic resonance molecular imaging, Group C (n = 15) was used for animal behavior experiments, and Group D (n = 21) was used for histopathological examination. All the above quantitative results were analyzed by statistics.ResultsThe peak value of carboxyhemoglobin saturation in the blood after modeling was 7.3-fold higher than before and lasted at least 2.5 h. The GluCEST values of the parietal lobe, hippocampus, and thalamus were significantly higher than the base values in CO poisoning rats (p < 0.05) and the 1H-MRS showed significant differences in the parietal lobe and hippocampus. In the Morris water maze tests, the average latency and distance were significantly prolonged in poisoned rats (p < 0.05), and the cumulative time was shorter and negatively correlated with GluCEST.ConclusionThe GluCEST imaging non-invasively reflects the changes of glutamate in the brain in vivo with higher sensitivity and spatial resolution than 1H-MRS. Our study implies that GluCEST imaging may be used as a new imaging method for providing a pathogenetic and prognostic assessment of CO-associated encephalopathy.

Background. To analyze the effects of the implementation of emergency surgical patterns in patients with rhegmatogenous retinal detachment (RRD) and provide evidence for promoting emergency surgical patterns for RRD. Methods. We reviewed the electronic medical records of 346 patients (348 eyes) who underwent surgical repair of RRD at the Zhongshan Ophthalmic Center in Southern China. A total of 140 patients (140 eyes) in the routine inpatient surgery group were collected at the fundus disease department between January 2019 and December 2019, and 206 patients (208 eyes) in the emergency surgery group were collected at the ophthalmic emergency department between January 2021 and December 2021. Demographics, best-corrected visual acuity (BCVA) expressed as the logarithm of the minimum angle of resolution (logMAR), the status of the macula before surgery, time to presentation, treatment interval, and postoperative BCVA measured at least three months follow-up were compared. Results. The preoperative BCVA (logMAR) of the emergency surgery group and the inpatient surgery group were 1.0 (0.4–1.7) and 1.4 (0.7–1.7), respectively, with significant differences between groups (P0.05). Conclusions. Patients who underwent emergency surgical patterns of RRD had better visual outcomes after surgery than patients with routine inpatient surgery, which might be attributed to a shorter duration, shorter treatment interval, and the preoperative status of the macula in the emergency surgery pattern. Emergency surgical patterns for RRD should be considered to achieve better surgical outcomes in suitable patients.

Aims: Carbon monoxide poisoning is a common condition that can cause severe neurological sequelae. Previous studies have revealed that functional connectivity in carbon monoxide poisoning is abnormal under the assumption that it is resting during scanning and have focused on studying delayed encephalopathy in carbon monoxide poisoning. However, studies of functional connectivity dynamics in the acute phase of carbon monoxide poisoning may provide a more insightful perspective for understanding the neural mechanisms underlying carbon monoxide poisoning. To our knowledge, this is the first study that explores abnormal brain network dynamics in the acute phase of carbon monoxide poisoning.Methods: Combining the sliding window method and k-means algorithm, we identified four recurrent dynamic functional cognitive impairment states from resting-state functional magnetic resonance imaging data from 29 patients in the acute phase of carbon monoxide poisoning and 29 healthy controls. We calculated between-group differences in the temporal properties and intensity of dFC states, and we also performed subgroup analyses to separately explore the brain network dynamics characteristics of adult vs. child carbon monoxide poisoning groups. Finally, these differences were correlated with patients’ cognitive performance in the acute phase of carbon monoxide poisoning and coma duration.Results: We identified four morphological patterns of brain functional network connectivity. During the acute phase of carbon monoxide poisoning, patients spent more time in State 2, which is characterized by positive correlation between SMN and CEN, and negative correlation between DMN and SMN. In addition, the fractional window and mean dwell time of State 2 were positively correlated with coma duration. The subgroup analysis results demonstrated that the acute phase of childhood carbon monoxide poisoning had greater dFNC time variability than adult carbon monoxide poisoning.Conclusion: Our findings reveal that patients in the acute phase of carbon monoxide poisoning exhibit dynamic functional abnormalities. Furthermore, children have greater dFNC instability following carbon monoxide poisoning than adults. This advances our understanding of the pathophysiological mechanisms underlying acute carbon monoxide poisoning.

Background and Objective: The abnormal T1-weighted imaging of MRI can be used to characterize neonatal acute bilirubin encephalopathy (ABE) in newborns, but has limited use in evaluating the severity and prognosis of ABE. This study aims to assess the value of diffusion kurtosis imaging (DKI) in detecting ABE and understanding its pathogenesis.Method: Seventy-six newborns with hyperbilirubinemia were grouped into three groups (mild group, moderate group, and severe group) based on serum bilirubin levels. All the patients underwent conventional MRI and DKI serial, as well as 40 healthy full-term infants (control group). The regions of interest (ROIs) were the bilateral globus pallidus, dorsal thalamus, frontal lobe, auditory radiation, superior temporal gyrus, substantia nigra, hippocampus, putamen, and inferior olivary nucleus. The values of mean diffusivity (MD), axial kurtosis (AK), radial kurtosis (RK), and mean kurtosis (MK), and fractional anisotropy (FA), radial diffusivity (RD), and axis diffusivity (AD) of the ROIs were evaluated. All newborns were followed up and evaluated using the Denver Development Screening Test (DDST). According to the follow-up results, the patients were divided into the normal group, the suspicious abnormal group, and the abnormal group.Result: Compared with the control group, significant differences were observed with the increased MK of dorsal thalamus, AD of globus pallidus in the moderate group, and increased RD, MK, AK, and RK value of globus pallidus, dorsal thalamus, auditory radiation, superior temporal gyrus, and hippocampus in the severe group. The peak value of total serum bilirubin was moderately correlated with the MK of globus pallidus, dorsal thalamus, and auditory radiation and was positively correlated with the other kurtosis value. Out of 76 patients, 40 finished the DDST, and only 9 patients showed an abnormality. Compared with the normal group, the AK value of inferior olivary nucleus showed significant differences (p < 0.05) in the suspicious abnormal group, and the MK of globus pallidus, temporal gyrus, and auditory radiation; RK of globus pallidus, dorsal thalamus, and auditory radiation; and MD of globus pallidus showed significant differences (p < 0.05) in the abnormal group.Conclusion: DKI can reflect the subtle structural changes of neonatal ABE, and MK is a sensitive indicator to indicate the severity of brain damage.

Most existing AMBTC (absolute moment block truncation coding)-based reversible data hiding (RDH) schemes cannot be decoded by traditional AMBTC decoders, because they change the coding structure of the AMBTC compressed code stream, which is unidentified for decoders. Even if some AMBTC-based RDH methods can be decoded by traditional AMBTC decoders, but the obtained payload is low. To this end, in this paper, a high-capacity and decodable AMBTC-based RDH scheme is presented. It is well observed that an m × n-sized bitmap has 2m×n combinations of `1' and `0'. However, all the bitmaps of an image occupy only a small part of all the combinations, and a large part are not used in this image. Motivated by this observation, we propose a one-to-many map between the used and unused combinations, in which one used bitmap can be mapped to multiple unused combinations, achieving high payloads (e.g., log2 25 bits for one bitmap of Lena), and more importantly, completely reserving the coding structure of the AMBTC-compressed code. Unlike existing decodable AMBTC-based RDH methods only capable of achieving a fixed payload for one test image, our method can adjust adaptively payloads according to the required visual quality by introducing a predefined threshold. The experimental results also demonstrate that our proposed scheme can largely increase the payload on the basis of maintaining good visual quality.

Digital microfluidic biochips (DMFBs) are increasingly important and are used for point-of-care, drug discovery, clinical diagnosis, immunoassays, etc. Pin-constrained DMFBs are an important part of digital microfluidic biochips, and they have gained increasing attention from researchers. However, many previous works have focused on the problem of electrode addressing and aimed to minimize the number of control pins in pin-constrained DMFBs. Although the number of control pins can be effectively redistributed through broadcast addressing technology, the chip reliability will be reduced if the signals are shared arbitrarily. Arbitrary signal sharing can lead to a large number of actuations for many idle electrodes, and as a result, a trapping charge or decreasing contact angle problem could occur for some electrodes, reducing the reliability of the chip. To address this problem, the appropriate electrode matching object should be carefully selected, and the influence of these factors on chip reliability should be fully considered. For this purpose, we aimed to fully consider electrode addressing and the reliability of the chip in improving the reliability of DMFBs. This paper proposed a pin addressing method based on a support vector machine (SVM) with the reliability constraint algorithm, which can fully consider the electrode addressing method and the reliability of the chip together. The proposed method achieved an average maximum number of electrode actuations that was 53.8% and 18.2% smaller than those of the baseline algorithm and the graph-based algorithm, respectively. The simulation experiment results showed that the proposed method can efficiently solve reliability problems during the DMFB design process.

Multi-label learning has become a hot topic in recent years, attracting scholars’ attention, including applying the rough set model in multi-label learning. Exciting works that apply the rough set model into multi-label learning usually adapt the rough sets model’s purpose for a single decision table to a multi-decision table with a conservative strategy. However, multi-label learning enforces the rough set model which wants to be applied considering multiple target concepts, and there is label correlation among labels naturally. For that proposal, this paper proposes a rough set model that has multiple target concepts and considers the similarity relationships among target concepts to capture label correlation among labels. The properties of the proposed model are also investigated. The rough set model that has multiple target concepts can handle the data set that has multiple decisions, and it has inherent advantages when applied to multi-label learning. Moreover, we consider how to compute the approximations of GMTRSs under a static and dynamic situation when a target concept is added or removed and derive the corresponding algorithms, respectively. The efficiency and validity of the designed algorithms are verified by experiments.

The rough set model has two symmetry approximations called upper approximation and lower approximation, which correspond to a concept’s intension and extension, respectively. Multi-label learning enforces the rough set model, which wants to be applied considering the correlations among labels, while the target concept should not be limited to only one. This paper proposes a multi-target model considering label correlation (Neighborhood Multi-Target Rough Sets, NMTRS) and proposes an attribute reduction approach based on NMTRS. First, some definitions of NMTRS are introduced. Second, some properties of NMTRS are discussed. Third, some discussion about the attribute significance measure is given. Fourth, the attribute reduction approaches based on NMTRS are proposed. Finally, the efficiency and validity of the designed algorithms are verified by experiments. The experiments show that our algorithm shows considerable performance when compared to state-of-the-art approaches.

Introduction Diabetic retinopathy (DR) is the main cause of adult visual impairment worldwide. Severe non-proliferative DR (sNPDR) is an important clinical intervention stage. Currently, panretinal photocoagulation (PRP) is the standard treatment for sNPDR. However, PRP alone cannot completely prevent NPDR progression. One explanation might be that PRP does not remove the detrimental vitreous that plays an important role in DR progression. Microinvasive pars plana vitrectomy (PPV) was shown to be a safe and effective method to treat late-stage proliferative DR (PDR) by completely removing the pathological vitreous. However, whether PPV is effective in controlling sNPDR remains unknown. In this trial, we aim to compare the effectiveness of microinvasive PPV with that of PRP for sNPDR progression control.Methods and analysis This single centre, parallel group, randomised controlled trial aims to evaluate the clinical efficacy of microinvasive PPV in preventing the progression of sNPDR compared with PRP. A total of 272 adults diagnosed with sNPDR will be randomised 1:1 to the microinvasive PPV and PRP groups. The primary outcome is the disease progression rate, calculated as the rate of sNPDR progressed to PDR from baseline to 12 months after treatment. The secondary outcomes include the change in best-corrected visual acuity, re-treatment rate, diabetic macular oedema occurrence, change in central retinal thickness, change in the visual field, cataract occurrence and change in the quality of life.Ethics and dissemination The Ethics Committee of Zhongshan Ophthalmic Center approved this study (2019KYPJ108). The results will be presented at scientific meetings and submitted for publication to peer-reviewed journals.Trial registration number NCT04103671.

Eimeria tenella encodes a genome of approximately 8000 genes. To date, however, very few data are available regarding E. tenella rhoptry kinase family proteins. In the present study, the gene fragment encoding the mature peptide of the rhoptry kinase family protein 17 of E. tenella (EtROP17) was amplified by PCR and expressed in E. coli. Then, we generated polyclonal antibodies that recognize EtROP17 and investigated the expression of EtROP17 in the merozoite stage of E. tenella by immunofluorescent staining and Western blot analysis. Meanwhile, the protective efficacy of rEtROP17 against E. tenella was evaluated in chickens. Sequencing analysis showed that a single base difference at sequence position 1901 was observed between the SD-01 strain and the Houghton strain. EtROP17 was expressed in the merozoite stage of E. tenella. The results of the animal challenge experiments demonstrated that vaccination with rEtROP17 significantly reduced cecal lesions and oocyst outputs compared with the challenged control group. Our findings indicate that EtROP17 could serve as a potential candidate for developing a new vaccine against E. tenella.

Gene function prediction is used to assign biological or biochemical functions to genes, which continues to be a challenging problem in modern biology. Genes may exhibit many functions simultaneously, and these functions are organized into a hierarchy, such as a directed acyclic graph (DAG) for Gene Ontology (GO). Because of these characteristics, gene function prediction can be seen as a typical hierarchical multi-label classification (HMC) task. A novel HMC method based on neural networks is proposed in this article for predicting gene function based on GO. The proposed method belongs to a local approach by transferring the HMC task to a set of subtasks. There are three strategies implemented in this method to improve its performance. First, to tackle the imbalanced data set problem when building the training data set for each class, negative instances selecting policy and SMOTE approach are used to preprocess each imbalanced training data set. Second, a particular multi-layer perceptron (MLP) is designed for each node in GO. Third, a post processing method based on the Bayesian network is used to guarantee that the results are consistent with the hierarchy constraint. The experimental results indicate that the proposed HMC-MLPN method is a promising method for gene function prediction based on a comparison with two other state-of-the-art methods.

Surface subsidence caused by coal mining has a great impact on the geological and ecological environments and causes damage to houses, roads, and industrial buildings. In order to understand the subsidence pattern in the mountainous mining regions, three mining faces of the Zhangjiamao mining area in the north of Shaanxi province, northwestern China are taken as case study. Firstly, the small baseline subset (SBAS) technology is used to process 12 images obtained in the mining area to investigate the subsidence data from December 2019 to April 2020. The boundary of surface deformation of the mining area interpreted by the SBAS-InSAR technology is inconsistent with the theoretical boundary suggested by coal mine subsidence theories. Especially, there are some areas in which the real subsidence are larger than estimated area. This discrepancy must be corrected as steep slopes near the theoretical boundary may increase the likelihood of landslides. Our research indicates that: (1) The accumulated displacement and the maximum deformation rate reached −120.759 mm and −270.012 mm/yr in the study area, and the subsidence boundary of the three mining faces is revealed; (2) the combination of the predicted boundary and slope stability analysis can effectively identify the landslide region at the edge of subsidence boundary; (3) the field surveys have proved the effectiveness of this method. The mining area subsidence revealed by our research helps to further understand the impact of land subsidence caused by mining in the mountainous areas and provides a practical method to predict subsidence boundaries and the likelihood for landslides.

Abstract Background Age-related macular degeneration (AMD) causes the dysfunction of the retinal pigment epithelial (RPE) cells. In this study, we examined the effects of riluzole, a sustained activator of the TRAAK potassium channel, on human RPE (ARPE-19) cells in an oxidant-induced cell-injury model and elucidate the mechanism of riluzole on RPE cell apoptosis. Methods The follow four groups of ARPE-19 cells were treated with riluzole and/or tert-butyl hydroperoxide (t-BHP) for 24.0 h: control, t-BHP, riluzole, and t-BHP + riluzole. Cell apoptosis was measured by flow cytometry, and Western blotting was performed to analyze the expression of the weakly inward rectifying potassium (TRAAK) channel. Finally, the mitochondrial membrane potential (Δψm) was detected by flow cytometry, and cytochrome C (Cyt-c) release was assessed by Western blotting. Results The viability of the cells in the cotreated group was significantly higher (85.6 ± 3.1%) than that in the t-BHP group (66.2 ± 2.5%). In addition, the cells in the cotreated group had a higher effect on increasing the expression of TRAAK than the t-BHP group. The results also showed that Cyt-c translocation significantly decreased and Δψm increased in the cotreated group. Conclusions These results demonstrate that riluzole protects RPE cells from apoptosis. The protection mechanism of riluzole could be from stabilizing mitochondrial Δψm and preventing the release of Cyt-c. Changes in TRAAK expression might also contribute to the protection of RPE cells.

Abstract Our aim was to assess microstructural alterations in the cerebrums of paediatric patients with congenital sensorineural hearing loss (SNHL) using diffusion kurtosis imaging (DKI). Seventy-two paediatric SNHL patients and 38 age-matched healthy volunteers were examined via DKI using a 3.0 T magnetic resonance (MR) imager. Fractional anisotropy (FA) and mean kurtosis (MK) values were computed for 12 cerebral regions in both the controls and the SNHL patients. Compared with patients below age 3, patients in the older age group were found to have more significant differences in MK than in FA, and these appeared in more major areas of the brain. In contrast, in 1- to 3-year-old children, a few major brain areas exhibited differences in FA, but none exhibited appreciable differences in MK. There were significant decreases in the FA or MK values (P

Digital microfluidic biochips (DMFBs) are attractive instruments for obtaining modern molecular biology and chemical measurements. Due to the increasingly complex measurements carried out on a DMFB, such chips are more prone to failure. To compensate for the shortcomings of the module-based DMFB, this paper proposes a routing-based fault repair method. The routing-based synthesis methodology ensures a much higher chip utilization factor by removing the virtual modules on the chip, as well as removing the extra electrodes needed as guard cells. In this paper, the routing problem is identified as a dynamic path-planning problem and mixed path design problem under certain constraints, and an improved Dijkstra and improved particle swarm optimization (ID-IPSO) algorithm is proposed. By introducing a cost function into the Dijkstra algorithm, the path-planning problem under dynamic obstacles is solved, and the problem of mixed path design is solved by redefining the position and velocity vectors of the particle swarm optimization. The ID-IPSO routing-based fault repair method is applied to a multibody fluid detection experiment. The proposed design method has a stronger optimization ability than the greedy algorithm. The algorithm is applied to 8×9, 8×8, and 7×8 fault-free chips. The proposed ID-IPSO routing-based chip design method saves 13.9%, 14.3%, and 14.5% of the experiment completion time compared with the greedy algorithm. Compared with a modular fault repair method based on the genetic algorithm, the ID-IPSO routing-based fault repair method has greater advantages and can save 39.3% of the completion time on average in the completion of complex experiments. When the ratio of faulty electrodes is less than 12% and 23%, the modular and ID-IPSO routing-based fault repair methods, respectively, can guarantee a 100% failure repair rate. The utilization rate of the electrodes is 18% higher than that of the modular method, and the average electrode usage time is 17%. Therefore, the ID-IPSO routing-based fault repair method can accommodate more faulty electrodes for the same fault repair rate; the experiment completion time is shorter, the average number of electrodes is lower, and the security performance is better.

Obesity and type 2 diabetes are the most common metabolic diseases globally. They are associated with inflammation, oxidative stress, autophagy, and insulin resistance. Sitagliptin, a dipeptidyl-peptidase 4 inhibitor, has been reported to show multiple biological activities beyond the antidiabetic property. This study was aimed at investigating the effect of sitagliptin on hepatic steatosis, insulin resistance, inflammation, and autophagy and exploring the underlying molecular mechanism. In the current study, ob/ob mice, a mouse model of genetic obesity and diabetes, were administered via gavage with sitagliptin 50 mg/kg daily for 4 weeks. Changes in glycolipid metabolism, inflammatory responses, and autophagy in the liver were evaluated. Body weight gain, lipid metabolic disorder, and hepatic steatosis as well as systemic and hepatic insulin sensitivity in ob/ob mice were significantly attenuated after sitagliptin treatment. Furthermore, sitagliptin decreased inflammatory responses by regulating macrophage M1/M2 polarization and inhibiting the activities of NF-κB and JNK. Moreover, sitagliptin increased the levels of phosphorylation of AMPK and decreased those of mTOR. This study indicates that sitagliptin significantly ameliorates the development of hepatic steatosis and insulin resistance in ob/ob mice by inhibiting inflammatory responses and activating autophagy via AMPK/mTOR signaling pathway.

Based on the generalized Lorenz Mie theory (GLMT), the scattering cross section of mineral aerosol within the Gaussian beam is investigated, and an appropriate modeling of the scattering cross sections for the real mineral aerosols including the feldspar, quartz, and red clay is proposed. In this modeling, the spheroid shape is applied to represent the real nonspherical mineral aerosol, and these nonspherical particles are randomly distributed within the Gaussian beam region. Meanwhile, the Monte Carlo statistical estimate method is used to determine the distributed positions of these random nonspherical particles. Moreover, a method for the nonspherical particles is proposed to represent the scattering cross section of the real mineral aerosols. In addition, the T matrix method is also used to calculate the scattering cross sections of the spheroid particles in order to compare the scattering properties between the plane wave and the Gaussian wave. Simulation results indicate that fairly reasonable results of the scattering cross sections for the mineral aerosols can be obtained with this proposed method, and it can provide a reliable and efficient approach to reproduce the scattering cross sections of the real randomly distributed mineral aerosols illuminated by the Gaussian beam.

Although conventional structural MRI provides vital information in the evaluation of congenital sensorineural hearing loss (SNHL), it is relatively insensitive to white matter microstructure. Our objective was to evaluate possible changes in microstructure of the auditory pathway in children with congenital sensorineural hearing loss (SNHL), and the possible distinction between good and poor outcome of cochlear implantation (CI) patients by using diffusion tensor imaging (DTI). Twenty-four patients with congenital SNHL and 20 healthy controls underwent conventional MRI and DTI examination using a 1.5T MR scanner. The DTI metrics of fractional anisotropy (FA) and mean diffusivity (MD) of six regions of interest (ROIs) positioned along the auditory pathway-the trapezoid body, superior olivary nucleus, inferior colliculus, medial geniculate body, auditory radiation and white matter of Heschl's gyrus-was measured in all subjects. Among the 24 patients, 8 patients with a categorie of auditory performance (CAP) score over 6 were classified into the good outcome group, and 16 patients with a CAP score below 6 were classified into the poor outcome group. A significant decrease was observed in FA values while MD values remained unchanged at the six ROIs of SNHL patients compared with healthy controls. Compared to good outcome subjects, poor outcome subjects displayed decreased FA values at all of the ROIs. No changes were observed in MD values. Correlation analyses only revealed strong correlations between FA values and CAP scores, and strong correlations between CAP scores and age at implant were also found. No correlations of FA values with age at implant were observed. Our results show that preoperative DTI can be used to evaluate microstructural alterations in the auditory pathway that are not detectable by conventional MR imaging, and may play an important role in evaluating the outcome of CI. Early cochlear implantation might be more effectively to restore hearing in SNHL patients.

Gene function prediction is a complicated and challenging hierarchical multi-label classification (HMC) task, in which genes may have many functions at the same time and these functions are organized in a hierarchy. This paper proposed a novel HMC algorithm for solving this problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph (DAG) and is more difficult to tackle. In the proposed algorithm, the HMC task is firstly changed into a set of binary classification tasks. Then, two measures are implemented in the algorithm to enhance the HMC performance by considering the hierarchy structure during the learning procedures. Firstly, negative instances selecting policy associated with the SMOTE approach are proposed to alleviate the imbalanced data set problem. Secondly, a nodes interaction method is introduced to combine the results of binary classifiers. It can guarantee that the predictions are consistent with the hierarchy constraint. The experiments on eight benchmark yeast data sets annotated by the Gene Ontology show the promising performance of the proposed algorithm compared with other state-of-the-art algorithms.

In order to research the effect of different layout forms of steel plate on the axial compression behavior of a steel plate-concrete composite shear wall, this paper presents the experimental results and analysis of the axial compression behavior of a composite shear wall, with different layout forms of steel plate. A total of three tests were carried out, composed of two composite walls with built-in steel plate, and one composite wall with two skins of steel plate. The gross dimensions of the three specimens were 1206 mm × 2006 mm × 300 mm. Experimental results show that the composite wall with two skins of steel plate has an optimal ability of elastic-plastic deformation, and the maximum axial compressive bearing capacity among the three specimens. Using the energy method, the critical local buckling stresses of steel plate were calculated, and compared with the yield stresses. According to different confined actions of concrete, concrete constitutive models were proposed, and the axial compressive strengths of confined concrete were calculated. Considering the local buckling of steel plate and confined concrete, the calculation formula of the axial compression of the composite wall was put forward, and the calculated results were in good agreement with the test results. Therefore, the different layout forms of steel plate have a great influence on its buckling, and on the concrete inhibition effect, which can affect the axial compressive bearing capacity of the composite wall.