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Aiming at the problem of insufficient data in actual production, we propose numerous process parameters for copper matte smelting, and complex relationships between process parameters and quality indicators, which make it difficult to accurately predict the copper matte grade. A method based on data neural generative adversarial network (DN-GAN) data generation and ensemble learning is proposed. First, the DN-GAN network is used to expand the data to solve the problem of insufficient data volume, where the original data are fused with the expanded data to form a new dataset. The tree-structured Parzen estimator (TPE) optimization algorithm is used to optimize the hyperparameters of the basic model in the stacking integration algorithm. Finally, the optimal hyperparameter combination is adopted to predict the grade of copper matte. The experimental results show that the prediction method proposed in this paper has a mean square error (MSE) of 0.093, a mean absolute error (MAE) of 0.236, and a goodness of fit (R2) of 0.979. Thus, the effectiveness of the generated adversarial network and stacked ensemble prediction in this paper has been verified, providing a novel approach for predicting the grade of copper matte. [ABSTRACT FROM AUTHOR]

Electrocatalysis can synthesize kinds of valuable chemicals and plays vital role in developing clean and renewable energy storage and conversion devices. In the traditional electrocatalytic systems, researchers try to synthesize one type of valuable chemical at cathode or anode independently. Recently, electrocatalytic bipolar synthesis of valuable chemicals at both cathode and anode simultaneously becomes popular and attracts much attention. In this minireview, we summarize the latest processes on innovative strategies for electrocatalytic bipolar synthesis of various chemicals. We will discuss the findings according to the categories of the products, including bipolar hydrogen production, bipolar formate production and bipolar hydrogenation. And the associated catalysts optimization, reaction mechanism, and design principles are well introduced. Moreover, the challenges and prospects are highlighted for future developments. This review is timely and will guide others pay more attention to this novel electrocatalytic bipolar synthesis systems. [ABSTRACT FROM AUTHOR]

Background: The relationship between Protein Convertase Subtilisin Kexin Type 9 inhibitor (PCSK9i) and psychiatric adverse events (AEs) remains unclear due to the limitations of clinical trials. In this study, PCSK9i‐related psychiatric AEs were realistically observed and systematically summarized in the real world by data mining the FDA AE Reporting System (FAERS). Method: Total AEs between the third quarter of 2015 and the first quarter of 2023 were obtained from FAERS. Psychiatric AEs were identified using disproportionality analysis and clinical prioritization of signals using a rating scale, followed by univariate logistic regression to explore factors influencing psychiatric AEs. Results: Psychiatric AEs accounted for 6.7% of the total number of PCSK9i reports. Eighteen psychiatric AEs were defined as PCSK9i‐related psychiatric adverse events (ppAEs) (lower 95% CI of both ROR >1 and IC025 > 0). The median age of ppAE reports was 68 years, and female patients accounted for 22.67% of reports, including 41.40% of reports with a serious outcome. Eleven (61.11%) and seven (38.89%) ppAEs were classified as weak and moderate clinical priority, respectively. The median time to onset of ppAEs was 149 and 196 days after treatment with evolocumab and alirocumab, respectively. Patients weighing ≥80 kg were 1.59 times more likely to experience ppAEs. Conclusion: The results of this study facilitate the prioritization of psychiatric AE signals by healthcare professionals with the goal of mitigating the risk of PCSK9i‐related psychiatric AEs. However, as an exploratory study, our findings need to be confirmed in large‐scale prospective studies. [ABSTRACT FROM AUTHOR]

To enhance the precision and reliability of road crack detection, this study introduces an innovative neural network architecture. Strategies were implemented to effectively address the issue of overfitting resulting from the intricacy of the proposed SegCrackNet. Dropout layers, multi-level output fusion, and T-bridge block structures are employed in the network. This optimization allows for a more comprehensive exploitation of contextual information, demonstrating its instrumental role in the efficient detection of subtle variations. Experimental findings clearly demonstrate substantial improvements when compared to other network models. On the Crack500, Crack200, and pavement images datasets, remarkable enhancements in the average Intersection over Union (IoU) scores were observed, with increases of 4.3%, 9.4%, and 3.7%, respectively. [ABSTRACT FROM AUTHOR]

Geospatial data, especially remote sensing (RS) data, are of significant importance for public services and production activities. Expertise is critical in processing raw data, generating geospatial information, and acquiring domain knowledge and other remote sensing applications. However, existing geospatial service platforms are more oriented towards the professional users in the implementation process and final application. Building appropriate geographic applications for non-professionals remains a challenge. In this study, a geospatial data service architecture is designed that links desktop geographic information system (GIS) software and cloud-based platforms to construct an efficient user collaboration platform. Based on the scalability of the platform, four web apps with different themes are developed. Data in the fields of ecology, oceanography, and geology are uploaded to the platform by the users. In this pilot phase, the gap between non-specialized users and experts is successfully bridged, demonstrating the platform's powerful interactivity and visualization. The paper finally evaluates the capability of building spatial data infrastructures (SDI) based on GeoNode and discusses the current limitations. The support for three-dimensional data, the improvement of metadata creation and management, and the fostering of an open geo-community are the next steps. [ABSTRACT FROM AUTHOR]

Background: Although gender differences in major depressive disorder (MDD) have been widely reported, there has not been much focus on gender differences in comorbidity. In patients with MDD and comorbid metabolic syndrome (Mets), the goal of this study was to investigate potential gender differences in the prevalence and clinical correlates of concomitant anxiety. Methods: Seven hundred and ninety-four first-episode and drug-naïve patients (FEDN) patients with MDD and comorbid Mets were recruited. For each patient, sociodemographic data, thyroid function indicators, and Mets parameters were acquired. Each participant completed the 14-item Hamilton Assessment Scale for Anxiety (HAMA) and the 17-item Hamilton Assessment Scale for Depression (HAMD). Results: There were no gender differences in the prevalence of anxiety in patients with MDD and comorbid Mets. Female patients with MDD had a shorter duration of illness. Correlation analysis showed that HAMD score, TSH, TgAb, and TPOAb were associated with anxiety prevalence in female patients, whereas anxiety onset in male patients was only associated with TSH, TgAb, and TPOAb levels. In addition, multiple logistic regression analysis showed that TSH and TgAb predicted anxiety in male patients, whereas HAMD score and age of onset significantly predicted anxiety in female patients. Limitations: Cross-sectional design and no control for anxiety-related factors. Conclusions: Our study showed no gender differences in the prevalence of anxiety in patients with MDD and comorbid Mets. HAMD score was associated with anxiety in female patients, whereas TSH, TgAb, and TPOAb were associated with anxiety in male patients. [ABSTRACT FROM AUTHOR]

Background: Although phytoplankton are important primary producers in food webs, they are relatively less studied in large rivers compared to other types of systems. To fill this research gap, we studied phytoplankton taxonomic and functional composition and their relationships with water quality, habitat, climate, and land use across 30 river sections in the middle and lower reaches of the Yangtze River during 2017–2018. Results: Major observed phytoplankton groups were cyanobacteria, bacillariophyta, and chlorophyta. Phytoplankton total abundance, total biomass, and species richness significantly decreased in the dry season compared to the wet season, with the species and functional composition differing significantly between seasons. Phytoplankton species differences between seasons were mainly contributed by Oscillatoria sp., Pseudanabaena sp., and Melosira granulata. The dfferences in phytoplankton functional groups between seasons were mainly contributed by P (including Closterium sp., Melosira sp.), Lo (including Merismopedia sp., Peridinium sp., Ceratium sp., and Gymnodinium sp.), and J (including Pediastrum sp., Tetraedron sp., Crucigenia sp., Scenedesmus sp., and Coelastrum sp.). The variance partitioning showed that water quality (NO3-N, total suspended solids, turbidity) and habitat (water flow, river bank and river channel conditions) were critical factors in shaping phytoplankton patterns, followed by climate and land use. Conclusions: Results indicated that there was significant seasonal variation of phytoplankton in the Yangtze River, with water quality and habitat primarily driving phytoplankton patterns. Our study contributes to the understanding of natural and anthropogenic factors that drive seasonal successional processes of phytoplankton in the Yangtze River. These findings have important implications for environmental management as well as towards the ecological restoration of large rivers. [ABSTRACT FROM AUTHOR]

Context: Alterations of landscapes and riverscapes by humans have fundamentally altered patterns in freshwater biodiversity throughout the world's aquatic systems. Past research has demonstrated precipitous declines in small- and medium-sized streams, with much less attention given to patterns and drivers of fish biodiversity in larger riverine systems. Objectives: By examining alpha and beta diversity of fishes in the middle and lower reaches of the Yangtze River, China, we aimed to address the following question: What is the role of river–lake connectivity, wetland extent, and human stress factors (e.g., urbanization, fishing pressure, navigation, and shoreline modifications) in shaping fish alpha (species richness) and beta (species nestedness and turnover) diversity? Methods: We examined associations among three classifications of fish assemblage data (i.e., all species, nonmigratory species, and migratory species) sampled along gradients of river–lake connectivity (i.e., Dongting and Poyang lakes), wetland extent, and a suite of human stress factors (urbanization, fishing pressure, navigation, shoreline modification). We conducted redundancy analyses and distance-based redundancy analyses to facilitate mechanistic interpretations of the associations between the explanatory variables and fish alpha and beta diversity. Results: Longitudinally from the middle to the lower reaches of the Yangtze River, fish alpha diversity showed marked decreases while fish beta diversity increased. River segments with greater levels of human impact were generally associated with reduced fish species richness, while segments with higher wetland extent and greater river–lake connectivity tended to support greater species richness. River–lake connectivity, wetland extent, and fishing pressure largely influenced total fish beta diversity. Species nestedness was primarily associated with amount of wetlands, and exhibited the strongest associations with nonmigratory fish species. Turnover was primarily associated with river–lake connectivity (mainly Poyang Lake), especially for migratory species. Conclusions: Our analyses demonstrate the roles of river–lake connectivity, wetland extent, and human stress factors in shaping patterns of alpha and beta diversity for migratory and nonmigratory fishes in the middle and lower reaches of the Yangtze River. Fish diversity conservation in this large river ecosystem calls for protecting hydrological connectivity and wetland habitats, along with reducing fishing pressure. Results from this study will help better inform fish conservation efforts in the Yangtze River and have implications towards other large river systems of the world. [ABSTRACT FROM AUTHOR]

Experimental observations revealed that the amyloid-β 42 oligomer (AβO) can directly bind to the LilrB2 D1D2(LDD) receptor with nanomolar-affinity, leading to changes in synaptic plasticity and cognitive deficits. However, the dependence of neurotoxicity on the morphology, size, and aggregation stage (SP1, SP2) of AβO, as well as the specific molecular mechanism of AβO–LDD interaction, remain uncertain. To address these uncertainties, we investigated the interaction between the LDD neuroreceptor and AβO with different Aβ42 species (nontoxic species, toxic species, and protofibril) and sizes. Our results showed that the LDD selectively binds AβO species rather than the Aβ42 monomer, accommodating various Aβ42 dimers and trimers as well as SP2 AβO, in a specific pose in the pocket of the LDD receptor (region I). Additionally, protofibrils with exposed β1/β2 regions can also bind to region I of the LDD receptor, as observed experimentally (Cao, et al., Nat. Chem., 2018, 10, 1213; and Aim et al., Nat. Commun., 2021, 12, 3451). More extensively, we identified two additional regions of the LDD receptor, regions II and III, suitable for binding to larger AβO species at the SP1 with different molecular weights and conformations, accounting for the stronger binding strength obtained experimentally. We suggest that the two regions are more competitive than region I in causing toxicity by AβO binding. The detailed and systematic characterization for the complexes generated between the LDD receptor and various AβO species, including the protofibril, offers deep insight into the dependence of neurotoxicity on the AβO size and conformation at the molecular level, and provides novel and specific targets for drug design of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Background: The application of index of biotic integrity (IBI) to evaluate river health can be an essential method for river ecosystem management. However, these types of methods were developed in small, low-order streams, and are therefore, infrequently applied to large rivers. To that end, phytoplankton communities and environmental variables were monitored in 30 sampling segments of the middle and lower reaches of the Yangtze River, China during the wet (July–August) and dry (November–December) seasons in 2017–2018. We developed a phytoplankton-based index of biotic integrity (P-IBI) and used the index to assess the ecological health of the Yangtze River. Relationships among P-IBI, its component metrics, and environmental factors were analyzed across different seasons. Results: Results obtained from the P-IBI indicated that the phytoplankton-based ecological health of the Yangtze River was rated as "good" during both seasons, with an overall better condition in the dry season. During the wet season, there were scattered river segments with P-IBI ratings of "fair" or below. Water quality and land use appeared to shape the patterns of P-IBI. In the wet season, P-IBI negatively correlated with total phosphorus, nitrate, total suspended solids, turbidity, conductivity, and dissolved oxygen. In the dry season, P-IBI positively correlated with total nitrogen, ammonium, and nitrite, and negatively correlated with water temperature. Conclusions: The ecological health of the Yangtze River as reflected by the P-IBI exhibited spatial and temporal variability, with the effect of water quality being greater than that of local land use. This study indicated the importance of considering seasonal effects in detecting large river ecological health. These findings enhanced our understanding of the ecological health and characterized potential benchmarks for management of the Yangtze River. These findings also may be applicable to other large rivers elsewhere. [ABSTRACT FROM AUTHOR]

Fibrous aggregates of beta-amyloid (Aβ) is a hallmark of Alzheimer's disease (AD). Several major strategies of drugs or inhibitors, including neutral molecules, positive or negative ions, and dual-inhibitor, are used to inhibit the misfolding or aggregation of Aβ42, among which a kind of dual-inhibitor composed of a pair of positive and negative ions is emerging as the most powerful candidate. This knowledge lacks the origin of the strong inhibitory effect and synergy mechanisms blocking the development and application of such inhibitors. To this end, we employed 1 : 1 ionic pairs (IP) of oppositely charged benzothiazole molecules (+)BAM1-EG6 (Pos) and (−)BAM1-EG6 (Neg) as well as equimolar neutral BAM1-EG6 (Neu) counterpart at two pH conditions (5.5 and 7.0) to bind Aβ42 targets, Aβ42 monomer (AβM), soluble pentamer (AβP), and pentameric protofibril (AβF) models, respectively, corresponding to the products of three toxic Aβ42 development pathways, lag, exponential and fibrillation phases. Simulated results illustrated the details of the inhibitory mechanisms of IP and Neu for the AβY (Y = M, P, or F) in the three different phases, characterizing the roles of Pos and Neg of IP as well as their charged, hydrophobic groups and linker playing in the synergistic interaction, and elucidated a previously unknown molecular mechanism governing the IP-Aβ42 interaction. Most importantly, we first revealed the origin of the stronger binding of IP inhibitors to Aβ42 than that of the equimolar neutral counterparts, observing a perplexing phenomenon that the physiological condition (pH = 7.0) than the acidic one (pH = 5.5) is more favorable to the enhancement of IP binding, and finally disclosed that solvation is responsible to the enhancement because at pH 7.0, AβP and AβF act as anionic membranes, where solvation plays a critical role in the chemoelectromechanics. The result not only provides a new dimension in dual-inhibitor/drug design and development but also a new perspective for uncovering charged protein disaggregation under IP-like inhibitors. [ABSTRACT FROM AUTHOR]

Background: Nucleic acid is the carrier of genetic information and the keymolecule in life science. It is important to establish a simple and feasible method for nucleic acid quantification in complex biological samples. Methods: Four kinds of hydrogen bond acceptors (choline chloride (ChCl), L-carnitine, tetrabutylammonium chloride (TBAC) and cetyltrimethylammonium bromide (CTAB)) were used to synthesize deep eutectic solvents (DESs) with hexafluoroisopropanol (HFIP). DESs based manganese dioxide (MnO2) nanosheets composites was synthesized and characterized. DNA concentration was determined by a UVVis spectrometer. The mechanism of DNA-DES/MnO2 colorimetric system was further discussed. Results: The composite composed of DES/MnO2 exhibited excellent oxidase-like activity and could oxidize 3,3',5,5' -tetramethylbenzidine (TMB) to produce a clear blue change with an absorbance maximum at 652 nm. When DNA is introduced, the DNA can interact with the DES by hydrogen bonding and electrostatic interactions, thereby inhibiting the color reaction of DES/MnO2 with TMB. After condition optimization, ChCl/HFIP DES in 1:3 molar ratio was used for the colorimetric method of DNA determination. The linear range of DNA was 10–130 µg/mL and exhibited good selectivity. Conclusion: A colorimetric method based on DES/MnO2 was developed to quantify the DNA concentration. The proposed method can be successfully used to quantify DNA in bovine serum samples. [ABSTRACT FROM AUTHOR]

We used the ray tracing technique based on the IASP91 Earth model to calculate the travel times in order to identify the phases. This technique can calculate the travel times for the seismic phases in the conventional travel time tables. The waveform data received from the stations in the Guangxi area are selected for analysis and discussion. The outcomes of the numerical modeling and its use demonstrate that there is good agreement in terms of the absolute differences between the calculated and theoretical travel times from the ISAP91 tables. The relative residuals are determined directly from the actual arrival times picking during the correlation analysis, and the validity of the travel time method for picking seismic phases by correlation analysis can be demonstrated. [ABSTRACT FROM AUTHOR]

Ferroptosis is a new form of iron-dependent cell death and plays an important role during the occurrence and development of various tumors. Increasingly, evidence shows a convincing interaction between ferroptosis and tumor immunity, which affects cancer patients' prognoses. These two processes cooperatively regulate different developmental stages of tumors and could be considered important tumor therapeutic targets. However, reliable prognostic markers screened based on the combination of ferroptosis and tumor immune status have not been well characterized. Here, we chose the ssGSEA and ESTIMATE algorithms to evaluate the ferroptosis and immune status of a TCGA breast invasive ductal carcinoma (IDC) cohort, which revealed their correlation characteristics as well as patients' prognoses. The WGCNA algorithm was used to identify genes related to both ferroptosis and immunity. Univariate COX, LASSO regression, and multivariate Cox regression models were used to screen prognostic-related genes and construct prognostic risk models. Based on the ferroptosis and immune scores, the cohort was divided into three groups: a high-ferroptosis/low-immune group, a low-ferroptosis/high-immune group, and a mixed group. These three groups exhibited distinctive survival characteristics, as well as unique clinical phenotypes, immune characteristics, and activated signaling pathways. Among them, low-ferroptosis and high-immune statuses were favorable factors for the survival rates of patients. A total of 34 differentially expressed genes related to ferroptosis-immunity were identified among the three groups. After univariate, Lasso regression, and multivariate stepwise screening, two key prognostic genes (GNAI2, PSME1) were identified. Meanwhile, a risk prognosis model was constructed, which can predict the overall survival rate in the validation set. Lastly, we verified the importance of model genes in three independent GEO cohorts. In short, we constructed a prognostic model that assists in patient risk stratification based on ferroptosis-immune-related genes in IDC. This model helps assess patients' prognoses and guide individualized treatment, which also further eelucidatesthe molecular mechanisms of IDC. [ABSTRACT FROM AUTHOR]

System software for interactive human–computer data processing based on the IASP91 Earth model was designed. An interactive data processing system for visualizing earthquake data was designed and implemented via the Intel Fortran platform. The system reads and processes broadband seismic data acquired by field stations, mainly including the reading and import of raw data, pre-processing, identification of seismic phases and inter-correlation traveltimes picking. In the data processing step, shortcomings have been improved and functions have been gradually refined and enhanced, making it easier and faster to process data. It has already processed more than 1000 large seismic events received by the station from 2013 to 2018. The practical application shows that the human–computer interaction system is easy to operate, accurate, fast and flexible, and is an effective tool for processing seismic data. [ABSTRACT FROM AUTHOR]

The paper reports in silico three modified small molecules, two negatively charged E1C and E2C and one neutral TQ, which show more potent inhibitory effect than their parental molecules CQ3, TS0, and ER on the Cu2+ induced Aβ42 aggregation. In the acidic condition, TQ is the most powerful inhibitor, as it not only decreases the helix content of Cu2+‐Aβ42 complex but also increases the oxidizability; E1C/E2C however decreases the helix content of Cu2+‐Aβ42 complex but also with increased oxidizability, indicating that the inhibitory effect of the two charged molecules depends on the multiple factors, at least including the composite mechanism of helix decrease and oxidizability increase. In the basic condition, any of three modified molecules can increase the helix content of the Cu2+‐Aβ42 complex. Anyway, small molecules containing neutral and larger hydrophobic aromatic groups are always more effective in inhibiting Cu2+‐induced Aβ42 aggregation in both basic and acidic conditions. [ABSTRACT FROM AUTHOR]

Leukocyte immunoglobulin-like receptor B2 (LilrB2) is one of discovered cell surface β-amyloid (Aβ) receptors and taken as a promising therapeutic target for the treatment of Alzheimer's disease (AD). Aβ42 oligomer rather than monomer is toxic to neuronal cells and can directly bind to LilrB2, resulting in synaptic loss and cognitive impairment in the development of AD. Therefore, uncovering the mechanism of interaction between Aβ42 oligomer and LilrB2 becomes the first step to obtain a clear drug target and specific binding sites. Herein, a tetracoordinated mechanism for the Aβ oligomer-LilrB2 binding was first put forward by employing Aβ42 dimer mimic-antiparallel copies of Aβ42 core fragment 16KLVFFA21, to bind LilrB2 as models, in which four key residues (F5/F6/L12/F14) in the Aβ42 mimic are bound strongly with LilrB2 residue(s) or accommodated by four hydrophobic cavities in LilrB2 to generate a stable complex. Bi-dentate binding, however, cannot keep the complex Aβ42 mimic-LilrB2 stable. The inhibitor fluspirilene can disturb the binding of four key residues of Aβ42 to LilrB2, justifying the tetracoordinated zipper mechanism on the other hand. [ABSTRACT FROM AUTHOR]

The hypocenter parameters of an earthquake may give us an insight into the Earth's structure and tectonic processes. Among the hypocenter parameters, the focal depth is normally more difficult to estimate than the earthquake location (latitude and longitude). We propose to use the pPKIKP-PKIKP arrival time intervals for estimating the focal depth. We analyze the sensitivity of the pPKIKP-PKIKP arrival time interval to the earthquake depth. We measure the pPKIKP-PKIKP arrival time interval on seismograms (the vertical component), and invert the time interval data set using the simulated annealing inversion algorithm. We illustrate the inversion approach on two teleseismic earthquakes which have shallow and deep focal depths, and demonstrate that the approach is indeed appropriate to the shallow and deep event. We can obtain a reliable estimate on focal depth, even though the seismic station is sparse or in a remote part of the epicenter. [ABSTRACT FROM AUTHOR]

Pyroptosis is recently identified as an inflammatory form of programmed cell death. However, the roles of pyroptosis-related genes (PS genes) in major depressive disorder (MDD) remain unclear. This study developed a novel diagnostic model for MDD based on PS genes and explored the pathological mechanisms associated with pyroptosis. First, we obtained 23 PS genes that were differentially expressed between healthy controls and MDD cases from GSE98793 dataset. There were obvious variation in immune cell infiltration profiles and immune-related pathway enrichment between healthy controls and MDD cases. Then, a novel diagnostic model consisting of eight PS genes (GPER1 , GZMA, HMGB1 , IL1RN , NLRC4 , NLRP3 , UTS2 , and CAPN1) for MDD was constructed by random forest (RF) and least absolute shrinkage and selection operator (LASSO) analyses. ROC analysis revealed that our model has good diagnostic performance, AUC = 0.795 (95% CI 0.721–0.868). Subsequently, the consensus clustering method based on 23 differentially expressed PS genes was constructed to divide all MDD cases into two distinct pyroptosis subtypes (cluster A and B) with different immune and biological characteristics. Principal component analysis (PCA) algorithm was performed to calculate the pyroptosis scores ("PS-scores") for each sample to quantify the pyroptosis regulation subtypes. The MDD patients in cluster B had higher "PS-scores" than those in cluster A. Furthermore, we also found that MDD patients in cluster B showed lower expression levels of 11 interferon (IFN)-α isoforms. In conclusion, pyroptosis may play an important role in MDD and can provide new insights into the diagnosis and underlying mechanisms of MDD. [ABSTRACT FROM AUTHOR]

Pyroptosis is recently identified as an inflammatory form of programmed cell death. However, the roles of pyroptosis-related genes (PS genes) in major depression disease (MDD) remain unclear. This study developed a novel diagnostic model for MDD based on PS genes and explored the pathological mechanisms associated with pyroptosis. First, we obtained 23 PS genes that were differentially expressed between healthy controls and MDD cases from GSE98793 dataset. There were obvious variation in immune cell infiltration profiles and immune-related pathway enrichment between healthy controls and MDD cases. Then, a novel diagnostic model consisting of eight PS genes (GPER1 , GZMA, HMGB1 , IL1RN , NLRC4 , NLRP3 , UTS2 , and CAPN1) for MDD was constructed by random forest (RF) and least absolute shrinkage and selection operator (LASSO) analyses. ROC analysis revealed that our model has good diagnostic performance, AUC = 0.795 (95% CI 0.721–0.868). Subsequently, the consensus clustering method based on 23 differentially expressed PS genes was constructed to divide all MDD cases into two distinct pyroptosis subtypes (cluster A and B) with different immune and biological characteristics. Principal component analysis (PCA) algorithm was performed to calculate the pyroptosis scores ("PS-scores") for each sample to quantify the pyroptosis regulation subtypes. The MDD patients in cluster B had higher "PS-scores" than those in cluster A. Furthermore, we also found that MDD patients in cluster B showed lower expression levels of 11 interferon (IFN)-α isoforms. In conclusion, pyroptosis may play an important role in MDD and can provide new insights into the diagnosis and underlying mechanisms of MDD. [ABSTRACT FROM AUTHOR]

There is increasing appreciation for the roles of the gut-liver axis in liver and gall diseases. Specific gut microbes are associated with susceptibility to gallstone diseases, while the relationship between intestinal flora and liver metabolism in the formation of gallstones remains unclear. In this study, an experimental group of model mice was given a lithogenic diet, and a control group was given a normal diet. Both groups were fed for 8 weeks. Integrating 16S rRNA gene sequencing and non-targeted metabolomics to explore the impact of the lithogenic diet on intestinal flora and liver metabolism, Spearman correlation analysis reveals the network of relationships between the intestine and liver. Our findings showed that the gut microbiome and liver metabolome compositions of the test group were significantly changed compared with those of the normal group. Through our research, biomarkers of gallstones were identified at the phylum (5), class (5), order (5), family (7), and genus levels. We predicted the function of the differential flora. We analyzed the liver metabolism of mice with gallstones paired with their flora, and the results showed that there were 138 different metabolites between the two groups. The metabolic pathways enriched by these differential metabolites are highly consistent with the functions of the disordered flora. We focused on an analysis of the relationship between deoxycholic acid, asymmetric dimethylarginine, glucosamine, tauroursodeoxycholic acid, and the disordered flora. This provides a basis for the establishment of the intestine-liver axis in gallstone disease. This research provides a theoretical basis for the research and development of probiotics and prebiotics. [ABSTRACT FROM AUTHOR]

Background: Short-chain enoyl-CoA hydratase (ECHS1) is a multifunctional mitochondrial matrix enzyme involved in the second step of mitochondrial fatty acid β-oxidation. Mitochondrial diseases resulting from ECHS1 mutations are often characterised by encephalopathy, deafness, epilepsy, optic atrophy, cardiomyopathy, dystonia, and lactic acidosis. In this study, we report two novel heterogeneous variants, c.414 + 5G > A (in intron 3) and c.310C > G (in CDS), of ECHS1 in an infant with mitochondrial encephalopathy.Case Presentation: The two novel variants, c.414 + 5G > A (Chr10:135183403) in intron 3 and c.310C > G (Chr10:135183512) in CDS, were identified by next generation sequencing (NGS). A minigene assay was used to analyse the function of the c.414 + 5G > A variant. ECHS1 enzyme activity was measured by spectrophotometry in the patient-derived myoblasts. The 2-year old patient presented with mitochondrial encephalopathy since birth. Clinical features were encephalopathy, epilepsy, and hindered psychomotor and language development. Serum lactate and blood ammonia levels were elevated, and brain magnetic resonance imaging showed abnormal signals in the bilateral frontal, parietal, and occipital cortices and brainstem and basal ganglia. We found two novel heterogeneous variants in ECHS1 in this patient. Minigene assay revealed the c.414 + 5G > A variant as the cause of intronic cryptic splice site activation and 39 bp deletion in mature mRNA. In silico analysis predicted that c.310C > G might change glutamine (Q) to glutamic acid (E) in the 104th amino acid sequence (p.Q104E). To investigate the impact of these two variants on protein function, we constructed a 3D model of human ECHS1 and showed that the variants might alter the highly conserved region in close proximity to the active site, which might hinder, or even halt, enzymatic activity. The experimental assay showed that ECHS1 enzyme activity in the patient-derived myoblasts decreased compared to that in control.Conclusions: Our findings are the first to report a mitochondrial encephalopathy infant carrying two novel ECHS1 variants, c.414 + 5G > A and c.310C > G, which might be deleterious variants, function as pathogenicity markers for mitochondrial encephalopathy, and facilitate disease diagnosis. [ABSTRACT FROM AUTHOR]

The increased prevalence of obesity has been a major medical and public health problem in the past decades. In obese status, insulin resistance and sustained oxidative stress damage might give rise to behavioral deficits. The anti-obesity and anti-oxidant effects of allicin have been previously reported in peripheral tissues. In the present study, the functions and mechanisms of allicin involved in the prevention of high-fat diet (HFD)-induced depressive-like behaviors were investigated to better understand the pharmacological activities of allicin. Obese mice (five weeks of age) were treated with allicin (50, 100, and 200 mg/kg) by gavage for 15 weeks and behavioral test (sucrose preference, open field, and tail suspension) were performed. Furthermore, markers of oxidative stress, mitochondrial function, autophagy, and insulin resistance were measured in the hippocampal tissue. Finally, the levels of NADPH oxidase (NOX2, NOX4) and the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway were evaluated in the hippocampus. The body weight, metabolic disorders, and depressive-like behaviors in obese mice were ameliorated by allicin. The depressive-like behaviors presented in the obese mice were accompanied by remarkably excessive reactive oxygen species (ROS) production and oxidative stress, damaged mitochondrial function, imbalanced autophagy, and enhanced insulin resistance in the hippocampus. We found that allicin improved the above undesirable effects in the obese mice. Furthermore, allicin significantly decreased NOX2 and NOX4 levels and activated the Nrf2 pathway. Allicin attenuated depressive-like behaviors triggered by long-term HFD consumption by inhibiting ROS production and oxidative stress, improving mitochondrial function, regulating autophagy, and reducing insulin resistance in the hippocampus via optimization of NOX/Nrf2 imbalance. [ABSTRACT FROM AUTHOR]

Aim: We investigated the effects of pentamethylquercetin (PMQ) on the tumor growth in monosodium glutamate (MSG)-induced obese mice. Materials and Methods: At the age of 5 weeks, control and MSG mice were, respectively, divided into five groups (n = 10): Vehicle group; PMQ 5, 10, 20 mg/kg; and metformin (MET) 300 mg/kg groups. All mice were administrated PMQ and MET by gastric gavage from 5- to 24-week age. 22-week-old mice were injection with H22 hepatic ascitic tumor cells. After 2 weeks, animals were anesthetized and blood, tumor, and liver tissues were harvested. Results: Compared with control mice, MSG mice showed obviously metabolic disorders and larger tumor weight and volume than those of control mice. PMQ and MET administration reduced body weight, improved glucose and lipid metabolism, and insulin resistance and inhibited tumor growth in MSG mice. However, PMQ and MET had a litter effect on the tumor growth and metabolic indexes in the control mice. Furthermore, there is significant positive correlation between improved insulin resistance and inhibited tumor growth by chronic PMQ and MET treatment. Further experiments showed PMQ and MET treatment upregulated mRNA expressions of sirtuin 6 (sirt6) both in tumor and liver tissues. Conclusion: Our results demonstrated PMQ decreased tumor growth in the MSG mice and the potential mechanisms might be attributed to upregulated mRNA expressions of sirt6. [ABSTRACT FROM AUTHOR]

Kaempferol (KFL), the major constituent of various fruits and vegetables, could attenuate oxidaitve stress and inflammation. The aims of the present study were to explore the ameliorative abilities of KFL on the depressive-like behaviors in a chronic social defeat stress (CSDS) mouse model, and to determine the potential mechanisms on oxidative stress, neuroinflammation, and AKT/β-catenin signaling pathway. Three behavioral tests, sucrose preference test (SPT), social interaction test (SIT), and tail suspension test (TST), were used to evaluate the antidepressive effects of KFL in CSDS mice. Activity levels of antioxidant enzyme, superoxide dismutase (SOD), glutathione peroxidase (GPx), catalase (CAT), glutathione s-transferase (GST), and concentrations of malonaldehyde (MDA) and protein carbonylation in the prefrontal cortex were assessed by commercial kits, respectively. Elisa was used to detect the levels of interleukin-1β (IL-1β) and tumor necrosis factor α (TNF-α). Q-PCR was used to determine the mRNA level of CD-11b. Furthermore, activity level of AKT/β-catenin signaling in the prefrontal cortex of CSDS mice was investigated by western blot. In addition, LY294002, a PI3-K inhibitor, was used to investigate the role of AKT/β-catenin signaling in the antidepressant effects of KFL. Social defeat stress reduced the bodyweights, sucrose consumptions, social interaction times, and the tail suspension mobility times in mice. CSDS mice were also exhibited remarkablely increased levels in oxidative stress markers, inflammatory mediators, and decreased activity of AKT/β-catenin cascade in the prefrontal cortex, which were reversed by treatment with KFL. Interestingly, LY294002 appeared to partly inhibit the overall KFL-mediated protective effects in the CSDS mice. These results confirmed that KFL exerted antidepressive effects, which might be mediated, at least in part, by enhanced antioxidant abilities and anti-inflammation effects via up-regulation AKT/β-catenin cascade activity in the prefrontal cortex of CSDS mice. Thus, KFL might be a promising, effective, and safe food medicine for depression treatment. [ABSTRACT FROM AUTHOR]

Allicin, one of the main biologically active compounds derived from garlic, was previously reported to possess multiple pharmacological activities. Whether allicin protected against chronic social defeat stress (CSDS) induced depressive-like behaviors remained unknown. Thus, our present study for the first time investigated the potential antidepressant effects and the mechanisms of allicin on the CSDS mice model. Thirty minutes before social defeat stress, allicin (2, 10, 50 mg/kg) was treated by intraperitoneal injection. The duration times of CSDS model establishment and allicin intervene were 10 days. Subsequently, the force swimming test (FST), social interaction test (SIT), and sucrose preference test (SPT) were applied for behavioral assessments. The levels of inflammation mediators were determined by commercial ELISA kits. The concentration of iron was tested, and relative protein expressions were measured by western blot. Oxidative stress and apoptosis markers were also detected by commercial kits and western blot. The behavioral defects induced by social defeat stress were obviously improved by allicin. Microglia activation, as well as inflammatory cytokines elevation in the hippocampus of CSDS also down-regulated by administration of allicin. Furthermore, content of iron and protein expressions of key components in iron metabolism were remarkably aberrant changed in the CSDS mice hippocampus, meanwhile, allicin ameliorated this phenomenon. Allicin decreased the production of reactive oxygen species (ROS), malondialdehyde (MDA), and protein carbonyl, and the protein expression of NOX4, as well as up-regulated the activities of superoxide dismutase (SOD) and Nrf2/HO-1 pathway. In addition, allicin attenuated the enhanced neuronal apoptosis. Finally, allicin supplementation inhibited the Nucleotide-binding oligomerization domain containing 3 (NLRP3) inflammasome hyperactivity, and the expressions of inflammasome components, such as ACS, caspase-1, and IL-1β in the hippocampus of CSDS mice. Allicin attenuated depressive-like behaviors of CSDS mice through reducing neuroinflammation, ameliorating iron abnromal accumulation, balacing oxidative stress, and attenuation neuronal apoptosis in the hippocampus via suppression of NLRP3 inflammasome. [ABSTRACT FROM AUTHOR]

Objective: Depression imposes a huge health problem in the world. Recent studies report that berberine has neuroprotective effects. This study was investigated to evaluate the effects of berberine on depression and the potential underlying mechanisms. Methods: This experimental study included 48 mice, 8 CD1 mice and 40 C57 mice. Experiments were performed in the Laboratory Animal Center of China Three Gorges University, between May 2016 and February 2017. Chronic social defeat stress (CSDS) was used to build the depressive-like behaviors model. Three behavior tests, quantitative polymerase chain reaction, and Western blot were used to assay the changes in vivo. Results: We found that, in mice model induced by CSDS, berberine treatment increased mobility times in forced swim test and tail suspension test and reduced corticosterone level in serum. Furthermore, berberine increased traveled distance, frequencies in enter the central square, and duration time on the center square in the open field test as well. Further experiments showed that berberine treatment upregulated neuronal PAS domain protein 4 (NPAS4) and brain-derived neurotrophic factor (BDNF) protein/mRNA expressions in hippocampus tissue of CSDS mice. Conclusion: The present results suggested that berberine possessed properties in antidepressive-like behaviors, which might be partly attributed to upregulation of NPAS4 and BDNF expressions in hippocampus. Abbreviations used: CSDS: Chronic social defeat stress; BDNF: Brain-derived neurotrophic factor; NPAS4: Neuronal PAS domain protein 4; FST: Force swim test; TST: Tail suspension test; OFT: Open field test. [ABSTRACT FROM AUTHOR]

Background: Studies have reported that depression is associated with increased level of oxidative stress and accompanied with decreased Kelch-like erythroid cell-derived protein with CNC homology-associated protein 1-nuclear factor (erythroid-derived 2)-like 2 (Keap1-Nrf2) signaling pathway. Berberine has been shown to possess properties on protection against neurodegenerative diseases, but its effects on chronic unpredictable mild stress (CUMS) induced depressive such as behaviors and Keap1-Nrf2 signaling pathway are unknown. Objective: This study was designed to evaluate the effect of berberine on CUMS induced depression animal model and investigate the underlying mechanisms. Materials and Methods: We established CUMS depressant rats model and treated CUMS rats with berberine. Sucrose preference test, forced swim test , and tail suspension test were used to measure behavioral changes. We used quantitative polymerase chain reaction and western blot to test the levels of cytokines in the hippocampus. Results: We found that CUMS rats displayed obvious depressive-like behaviors. Moreover, berberine treatment prevented depressive behaviors in CUMS rats accompanied with suppression of oxidative stress markers. Further experiments showed that berberine treatment up-regulated the expression of Keap1-Nrf2 antioxidant signaling pathway and its downstream neuroprotective factors. Conclusion: The present results suggested that treatment of berberine significantly ameliorated depressive-like behaviors in CUMS rats and enhanced Keap1-Nrf2 antioxidant signaling pathways in hippocampus. Abbreviations used: MDD: Major depressive disorder; CUMS: Chronic unpredictable mild stress; FST: Forced swim test; TST: Tail suspension test; Keap1: Kelch-like erythroid cell-derived protein with CNC homology-associated protein 1; Nrf2: nuclear factor (erythroid-derived 2)-like 2; ARE: Antioxidant response elements; SOD: Superoxide Dismutase; MDA: Malonic dialdehyde; IMI: Imipramine. [ABSTRACT FROM AUTHOR]

Genetic improvements have significantly contributed to wheat production. Five wheat cultivars--widely grown in north China in the 1950s, 1990s, or 2010s--were grown in field experiments conducted in the 2014-2015 and 2015-2016 growing seasons. This study evaluated the genetic progress in wheat grain yield and its related traits in north China and explored how breeding and selection have influenced grain numbers and weights within spikelets in the past 60 years. The results showed that the significant increases in grain yield in the past 60 years were mainly due to increases in grain number per spike and grain weight, while spike number per m2 has not changed significantly. Improvements in thousand grain weight (TGW) from the 1950s to 2010s have occurred at four grain positions (G1 to G4). The relative contribution of G4 to TGW increased over time, but was much less than the contributions of G1, G2, and G3. Indeed, the average grain weight at G4 was much less than that of 1000 grains. The increase in grain number per spike since the 1950s was mainly due to an increase in grain number at G1, G2 and G3, with the relative contribution of grain position to grain number being G1 > G2 > G3 > G4. Dwarfing genes increased grain number per spike and grain number at G3 and G4, but not TGW. In future, yields could be boosted by enhancing grain weight at G4 and grain number at G3 and G4, while maintaining those at G1 and G2. [ABSTRACT FROM AUTHOR]

Background: Mitofusin 2 (Mfn2) is outer membrane protein, as the inhibitor of Ras protein. This study aimed to investigate the effect of Mfn2 on cell proliferation, and cell-cycle in Hela cervical carcinoma cell lines. Methods: After treated with Adv-mfn2 or Adv-control for 48 h and 60 h, the RNA and protein of Mfn2 in Hela cells were detected by qRT-PCR and western blot. The immunofluorescence assay was performed to observe the expression and sub-location of Mfn2 in Hela cells. The flow cytometry was performed to detect the cell cycle of Hela cells, while western blots were performed to observe the Ras-NF-κB signal pathway. Then, the xenografted cervix carcinoma mouse model was used to confirm the effect of Mfn2 in Hela cells in vivo and the expression of Ras-NF-κB signaling pathway in vivo. Results: In immunofluorescence detection, Mfn2 was located in cytoplasmic, not in the nucleus. In addition, Mfn2 inhibited cell proliferation of Hela cells through reducing PCNA protein expression. Mfn2 induced arrest in G0/G1 phase of the cell cycle in Hela cells. Meanwhile, Mfn2 reduced Cyclin D1 protein expression. Moreover, Mfn2 decreased the Ras signal pathway proteins such as Myc, NF-κB p65, STAT3 in a dose-dependent manner. Then, the in vivo experiment also confirmed that Mfn2 could inhibit the tumor growth, and depress the Cyclin D1, Ras, Myc, NF-κB p65, Erk1/2 and mTOR protein expression. Conclusions: Mfn2 could significantly inhibit cell proliferation in Hela cells. It might be acted as an potential anti-cancer target through inducing cell cycle arrest in human cervical carcinoma cells. [ABSTRACT FROM AUTHOR]