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Abstract Heart failure (HF) is a complex syndrome marked by considerable expenditures and elevated mortality and morbidity rates globally. Shenmai injection (SMI), a form of Traditional Chinese Medicine-based therapy, has demonstrated effectiveness in treating HF. Recent research suggests that Traditional Chinese Medicine (TCM) may induce beneficial changes in microbial-host co-metabolism, potentially providing cardiovascular protection. This study used a rat model of hypertensive heart failure (H-HF) to explore the mechanism of SMI. The possible compounds and key targets of SMI against H-HF were investigated using network pharmacology. The pharmacodynamics of SMI were validated using the H-HF animal model, with analysis of fecal gut microbiota integrating metabolomics and 16S rRNA sequencing. Metorigin metabolite traceability analysis and the MetaboAnalyst platform were utilized to explore the action mechanism. To evaluate changes in serum TMAO levels, targeted metabolomics was performed. Finally, the study looked at the intrinsic relationships among modifications in the intestinal flora, metabolite profile changes, and the targets of SMI compounds to clarify how they might be used to treat H-HF. According to metabolomics and 16S rRNA sequencing, by reestablishing homeostasis in the gut microbiota, SMI affects vital metabolic pathways, such as energy metabolism, amino acid metabolism, and bile acid metabolism. Increased serum TMAO levels were identified to be a risk factor for H-HF, and SMI was able to downregulate the levels of TMAO-related metabolites. Network pharmacology analysis identified 13 active components of SMI targeting 46 proteins, resulting in differential expression changes in 8 metabolites and 24 gut microbes. In conclusion, this study highlights the effectiveness of SMI in alleviating H-HF and its potential to modulate microbial-host co-metabolism. Through a comprehensive discussion of the interconnected relationships among the components, targets, metabolites, and gut microbiota, it provided fresh light on the therapeutic mechanism of SMI on H-HF.

Abstract Background Virtual bracket removal (VBR) facilitates efficient retainer fabrication for fixed orthodontics in a digital workflow. This study is aimed at assessing the influence of the relative bracket base area (RBA), representing the proportion of the labial/buccal surface area intended for removal, on the surface reconstruction accuracy in the VBR technique. Methods 196 teeth from seven resin dental models were included. The maximal bracket base surface area (MBA) was determined by the rectangular area extending to the lateral edges of the tooth labial/buccal surface. On each tooth, diverse RBA percentages (20–100% in 10% increments) of the MBA was removed, respectively. Following removal, the buccal surfaces of the teeth were digitally reconstructed. Subsequently, the root mean square (RMS) values, which represent the surface deviations between the reconstructed and original dentitions was calculated for each tooth. The obtained RMS values were compared within and among groups of different RBAs and compared with the clinically acceptable limit (CAL) of 0.05 mm. Results As the RBA increased, there was a discernible trend of elevated RMS values, both for the overall dentition and each specific tooth type. Among the lower teeth, the molars consistently displayed the highest RMS values in almost all groups, with significantly higher mean/median RMS values compared to the lower incisors (P

In the context of carbon neutrality and carbon peaks, innovations in ecological restoration technology play a key role in carbon adsorption and maintaining ecological balance. Regional governments, tasked with formulating differentiated and rational ecologically sustainable development plans and carbon-neutral strategies tailored to various resource endowment conditions, require timely identification of the mechanisms by which ecological restoration technologies affect the carbon density of ecosystems. Based on data from 31 provinces in China from 2006 to 2021, this study employed the Spatial Durbin Model with both time and space fixed effects to examine the impact of the value of ecological restoration technologies on ecosystem carbon density under varying resource endowments. The empirical results indicate that (1) the value of ecological restoration technology has a significantly positive effect on ecosystem carbon density, particularly in neighbouring areas; (2) energy resource endowment exhibits a significantly inverted U-shaped boundary effect, whereby regions with moderate energy endowment can optimise the positive impact of ecological restoration technology; (3) the heterogeneity analysis, based on levels of regional environmental governance and forest cover, shows that in regions with less investment in environmental infrastructure and lower forest cover, ecosystem carbon density is more sensitive to the value of ecological restoration techniques, making their carbon sink effect more pronounced. This study elucidates the key role of ecological restoration techniques in enhancing carbon storage, promoting the goal of carbon neutrality, and identifying optimal pathways for increasing ecosystem carbon stocks across various regions with differing resource endowments. Moreover, it provides a reference for accelerating the achievement of carbon neutrality targets.

Background Triple-negative breast cancer (TNBC) is a molecular subtype of breast cancer with high aggressiveness and poor prognosis. Cancer-associated fibroblasts (CAFs) are major components of the TNBC microenvironment and play an important role in tumor progression and treatment responses. Our goal is to identify specific CAFs subpopulations contributing to TNBC development.Methods Multiomics analyses were applied to identify the CAFs-specific genes related to immunotherapy response. The clinical significance of a CAFs subset with A-kinase anchoring protein 12 (AKAP12) positive was explored in 80 patients with TNBC through double-labeling immunofluorescence assay. Cytometry by time-of-flight and RNA sequencing were performed to elucidate the immune landscape of TNBC microenvironment and functional mechanism of AKAP12+ CAFs.Results Multiomics analyses identified an AKAP12+ CAFs subset associated with the immunotherapy response of TNBC, and a high population of these cells is correlated with poor prognosis in patients with TNBC. Intratumoral AKAP12+ CAFs promote formation of an immunosuppressive tumor microenvironment by spatially mediating macrophage M2 polarization via interleukin-34 (IL-34)/macrophage-colony stimulating factor receptor (CSF1R) signaling in TNBC. Single-cell RNA sequencing analyses revealed that AKAP12+ fibroblasts interact with macrophages through the PI3K/AKT/IL-34 axis. In addition, pharmacological blockade of the IL-34/CSF1R signaling enhances the efficacy of anti-programmed cell death protein-1 antibody in TNBC rodent models.Conclusions AKAP12 is mainly expressed in fibroblasts in TNBC. AKAP12+ CAFs population is negatively associated with the prognosis of patients with TNBC. AKAP12+ CAFs shape the immunosuppressive TNBC microenvironment by releasing IL-34 to promote macrophage M2 polarization. Targeting IL-34 may boost the immunotherapeutic efficacy for TNBC.

BackgroundPrior observational research has indicated a potential link between pediatric asthma and united airways disease (UAD). However, these findings could be subject to confounding factors and reverse causation. Therefore, our study utilizes Mendelian randomization (MR) method to further investigate the causal relationship between pediatric asthma and UAD.MethodsWe conducted a comprehensive two-sample Mendelian randomization (MR) analysis to investigate the association between pediatric asthma and seven groups of UAD, including chronic sinusitis, chronic rhinitis, nasopharyngitis and pharyngitis, chronic diseases of tonsils and adenoids, chronic laryngitis and laryngotracheitis, chronic bronchitis, bronchiectasis, chronic obstructive pulmonary disease (COPD). The present study employed a range of methods for two-sample MR analysis, including inverse variance weighted (IVW), MR-Egger regression, Simple mode, weighted median, and weighted models. The conclusion of the MR analysis primarily relies on the IVW results, while other analytical methods are utilized as supplementary evidence to ensure result robustness in this MR analysis. And sensitivity analyses were conducted, including heterogeneity test, horizontal pleiotropy test, MR-PRESSO test, and leave-one-out analysis to validate the results.ResultsThe results of the MR analysis indicate significant causal effects of pediatric asthma on chronic rhinitis, nasopharyngitis and pharyngitis (IVW: OR = 1.15, 95%CI: 1.05–1.26, p-value = 0.003), chronic diseases of tonsils and adenoids (IVW: OR = 1.07, 95%CI: 1.00–1.15, p-value = 0.038), chronic bronchitis (IVW: OR = 1.51, 95%CI: 1.42–1.62, p-value

Heart failure (HF) is a chronic condition that progressively worsens and continues to be a major financial burden and public health concern. The “gut-heart” axis provides an innovative perspective and therapeutic strategy for preventing and treating heart failure. Shenfu injection (SFI) is a Traditional Chinese Medicine-based treatment demonstrating potential as a therapeutic strategy for heart failure. However, the precise therapeutic mechanisms of SFI in heart failure are not completely characterized. In this study, HF models were established utilizing subcutaneous multipoint injection of isoproterenol (ISO) at a dosage of 5 mg kg−1·d−1 for 7 days. Serum levels of inflammatory biomarkers were quantified using protein microarrays. Rat feces were analyzed using untargeted metabolomics research and 16S rRNA sequencing. The link between gut microbiota and metabolites was examined using a MetOrigin and Spearman correlation analysis. Our results show that Shenfu injection effectively enhances cardiac function in rats with ISO-induced heart failure by potentially modulating pro-/anti-inflammatory imbalance and reducing serum and urine Trimethylamine-N-oxide (TMAO) levels. Moreover, SFI significantly increases the abundance of Bacteroidota at the phylum level, thereby improving disrupted gut microbiota composition. Additionally, SFI supplementation enriches specific genera known for their capacity to produce short-chain fatty acids. SFI was found to be associated with three key metabolic pathways, as revealed by fecal metabonomics analysis, including the pentose phosphate pathway, pyrimidine metabolism, and purine metabolism. Metabolite tracing analysis revealed that Taurine and hypotaurine metabolism was found to be specific to the microbial community. The biosynthesis of Pyrimidine metabolism, Purine metabolism, beta-alanine metabolism, Naphthalene degradation, Pantothenate, and CoA biosynthesis were identified as co-metabolic pathways between microbes and host. The Spearman correlation analysis was also significantly correlated to differentially expressed metabolites regulated by SFI and the gut microbiota. These results suggest that SFI improves ISO-induced heart failure by modulating co-metabolism and regulating the TMAO-inflammation axis.

Cardiac fibrosis is an important pathological manifestation of various cardiac diseases such as hypertension, coronary heart disease, and cardiomyopathy, and it is also a key link in heart failure. Previous studies have confirmed that exercise can enhance cardiac function and improve cardiac fibrosis, but the molecular target is still unclear. In this review, we introduce the important role of miR-126 in cardiac protection, and find that it can regulate TGF-β/Smad3 signaling pathway, inhibit cardiac fibroblasts transdifferentiation, and reduce the production of collagen fibers. Recent studies have shown that exosomes secreted by cells can play a specific role through intercellular communication through the microRNAs carried by exosomes. Cardiac endothelial progenitor cell-derived exosomes (EPC-Exos) carry miR-126, and exercise training can not only enhance the release of exosomes, but also up-regulate the expression of miR-126. Therefore, through derivation and analysis, it is believed that exercise can inhibit TGF-β/Smad3 signaling pathway by up-regulating the expression of miR-126 in EPC-Exos, thereby weakening the transdifferentiation of cardiac fibroblasts into myofibroblasts. This review summarizes the specific pathways of exercise to improve cardiac fibrosis by regulating exosomes, which provides new ideas for exercise to promote cardiovascular health.

The development and provision of soil spectral library (SSL) could facilitate the application of near infrared (NIR) spectroscopy for economical, accurate, and efficient determination of soil organic matter (SOM). In this work, the performances of partial least squares regression (PLSR) and convolutional neural network (CNN) combined with the datasets of Zhejiang provincial SSL (ZSSL) and the feature subset (FS) were compared for the prediction of SOM at the target field. The FS dataset was chosen from ZSSL based on similarity to the spectral characteristics of the target samples. The results showed that compared with modelling using ZSSL, modelling using FS can greatly improve the prediction accuracy of the PLSR model, but the impact on the performance of the CNN model was limited. The method of mean squared Euclidean distance (MSD) was an effective way for determining the optimal spiking sample size for the PLSR model only using the spectral data of the spiking subset and the prediction set. The PLSR model combined with the FS dataset and the spiking subset determined by MSD achieved the optimal prediction results among all developed models, which is an accurate and easy-to-implement solution for the SOM determination based on ZSSL.

Centrifugal pumps are a crucial part of nuclear power plants, and their dependable and safe operation is crucial to the security of the entire facility. Cavitation will cause the centrifugal pump to violently vibration with the large number of vacuoles generated, which not only affect the hydraulic performance of the centrifugal pump but also cause structural damage to the impeller, seriously affecting the operational safety of nuclear power plants. A closed cavitation test bench of a centrifugal pump is constructed, and a method for precisely identifying the cavitation state is proposed based on Complementary Ensemble Empirical Mode Decomposition (CEEMD) and Deep Residual Shrinkage Network (DRSN). First, we compared the cavitation sensitivity of pressure fluctuation, vibration, and liquid-borne noise and decomposed the liquid-borne noise by CEEMD to capture cavitation characteristics. The decomposition results are sent into a 12-layer deep residual shrinkage network (DRSN) for cavitation identification training. The results demonstrate that the liquid-borne noise signal is the most cavitation-sensitive signal, and the accuracy of CEEMD-DRSN to identify cavitation at different stages of centrifugal pumps arrives at 94.61%

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

BackgroundHeart failure (HF) is characterized by reduced ventricular filling or ejection function due to organic or non-organic cardiovascular diseases. Danhong injection (DHI) is a medicinal material used clinically to treat HF for many years in China. Although prior research has shown that Danhong injection can improve cardiac function and structure, the biological mechanism has yet to be determined.MethodsSerum metabolic analysis was conducted via ultra-high-performance liquid chromatography-quadrupole time-of-flight/mass spectrometry (UHPLC-QE/MS) to explore underlying protective mechanisms of DHI in the transverse aortic constriction (TAC)-induced heart failure. Multivariate statistical techniques were used in the research, such as unsupervised principal component analysis (PCA) and orthogonal projection to latent structures discriminant analysis (OPLS-DA). MetaboAnalyst and Kyoto Encyclopedia of Genes and Genomes (KEGG) were employed to pinpoint pertinent metabolic pathways.ResultsAfter DHI treatment, cardiac morphology and function as well as the metabolism in model rats were improved. We identified 17 differential metabolites and six metabolic pathways. Two biomarkers, PC(18:3(6Z,9Z,12Z)/24:0) and L-Phenylalanine, were identified for the first time as strong indicators for the significant effect of DHI.ConclusionThis study revealed that DHI could regulate potential biomarkers and correlated metabolic pathway, which highlighted therapeutic potential of DHI in managing HF.

ABSTRACT Importance Recurrent respiratory tract infection (RRTI) is common in children. Inappropriate RRTI treatment will lead to asthma and other diseases, thereby seriously affecting the growth and physical health of children. Immune function modulation can prevent and alleviate childhood RRTI. Yupingfeng (YPF), a patented traditional Chinese medicine (TCM), has immunomodulatory effects and is widely used in China to treat children with RRTI. Objective To evaluate the safety and efficacy of YPF monotherapy in treating children with RRTI. Methods This multicenter, randomized, double‐blind, double‐simulation, noninferiority clinical trial was conducted from January 2015 to August 2017, with an 8‐week treatment period and 52‐week follow‐up after the drug withdrawal. Children aged 2–6 years with RRTI meeting the inclusion and exclusion criteria were enrolled in 13 hospitals in China and divided randomly into three groups (2:2:1 ratio) to receive YPF, pidotimod, or placebo. The primary outcome was the proportion of RRTI returning to normal standard level during the follow‐up. The secondary outcomes were reduction in the number of RRTI recurrences, effect on clinical symptoms (in accord with TCM practice), effect per symptom, and safety. The trial was registered at the Chinese Clinical Trials Registry (www.chictr.org.cn) under the unique identifier ChiCTR‐IPR‐15006847. Results Three hundred and fifty‐one children were enrolled and randomly assigned to 3 groups; 124, 125, and 61 children in the YPF, pidotimod, and placebo groups, respectively, had completed the trial. During the follow‐up, the proportion of RRTI returning to normal standard level was 73.13%, 67.15%, and 38.81% with YPF, pidotimod, and placebo, respectively (P

Abstract Background In recent years, gene expression-based analysis has been used for disease biomarker discovery, providing ways for better diagnosis, leading to improvement of clinical treatment efficacy. This study aimed to explore the role of miR-16-5p and ANLN in breast cancer (BC). Methods Cohort datasets of BC were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) and analyzed by bioinformatics tools. qRT-PCR and western blotting were applied to validate ANLN and its protein expression. A dual-luciferase reporter assay was used to prove the regulatory relationship of miR-16-5p and ANLN. Finally, MTT, wound healing, Transwell invasion and flow cytometry analyses of the cell cycle and apoptosis were performed to assess cell proliferation, migration, invasion, cell cycle and apoptosis, respectively. Results A total of 195 differentially expressed genes (DEGs) and 50 overlapping microRNAs (miRNAs) were identified. Among these DEGs and miRNAs, ANLN, associated with poor overall survival in BC, overlapped in the GSE29431, GSE42568, TCGA and GEPIA2 databases. Moreover, ANLN was highly expressed, while miR-16-5p was lower in BC cells than in breast epithelial cells. Then, we confirmed that ANLN was directly targeted by miR-16-5p in BC cells. Over-expression of miR-16-5p and knock-down of ANLN remarkably inhibited cell proliferation and migration as well as cell invasion, arrested the cells in G2/M phase and induced apoptosis in BC cells. Conclusions These findings suggest that miR-16-5p restrains proliferation, migration and invasion while affecting cell cycle and promotes apoptosis by regulating ANLN, thereby providing novel candidate biomarkers for the diagnosis and treatment of BC.

In the field of ocean energy detection, Autonomous Underwater Vehicles (AUVs) offer significant advantages in terms of manpower, resource, and energy efficiency. However, the unpredictable nature of the ocean environment, particularly the real-time changes in ocean currents, poses navigational risks for AUVs. Therefore, effective path planning in dynamic environments is crucial for AUVs to perform specific tasks. This paper addresses the static path planning problem and proposes a model called the noise net double DQN network with prioritized experience replay (N-DDQNP). The N-DDQNP model combines a noise network and a prioritized experience replay mechanism to address the limited exploration and slow convergence speed issues of the DQN algorithm, which are caused by the greedy strategy and uniform sampling mechanism. The proposed approach involves constructing a double DQN network with a priority experience replay and an exploration mechanism using the noise network. Second, a compound reward function is formulated to take into account ocean current, distance, and safety factors, ensuring prompt feedback during the training process. Regarding the ocean current, the reward function is designed based on the angle between the current direction and the AUV’s heading direction, considering its impact on the AUV’s speed. As for the distance factor, the reward is determined by the Euclidean distance between the current position and the target point. Furthermore, the safety factor considers whether the AUV may collide with obstacles. By incorporating these three factors, the compound reward function is established. To evaluate the performance of the N-DDQNP model, experiments were conducted using real ocean data in various complex ocean environments. The results demonstrate that the path planning time of the N-DDQNP model outperforms other algorithms in different ocean current scenarios and obstacle environments. Furthermore, a user console-AUV connection has been established using spice cloud desktop technology. The cloud desktop architecture enables intuitive observation of the AUV’s navigation posture and the surrounding marine environment, facilitating safer and more efficient underwater exploration and marine resource detection tasks.

The face inversion effect (FIE) is a behavioral marker of face-specific processing that the recognition of inverted faces is disproportionately disrupted than that of inverted non-face objects. One hypothesis is that while upright faces are represented by face-specific mechanism, inverted faces are processed as objects. However, evidence from neuroimaging studies is inconclusive, possibly because the face system, such as the fusiform face area, is interacted with the object system, and therefore the observation from the face system may indirectly reflect influences from the object system. Here we examined the FIE in an artificial face system, visual geometry group network-face (VGG-Face), a deep convolutional neural network (DCNN) specialized for identifying faces. In line with neuroimaging studies on humans, a stronger FIE was found in VGG-Face than that in DCNN pretrained for processing objects. Critically, further classification error analysis revealed that in VGG-Face, inverted faces were miscategorized as objects behaviorally, and the analysis on internal representations revealed that VGG-Face represented inverted faces in a similar fashion as objects. In short, our study supported the hypothesis that inverted faces are represented as objects in a pure face system.

Cardiac fibrosis is a key pathological link of various cardiovascular diseases to heart failure. It is of great significance to deeply understand the development process of cardiac fibrosis and the cellular and molecular mechanisms involved. Macrophages play a special role in promoting heart development, maintaining myocardial cell homeostasis and heart function. They are involved in the whole process from inflammatory to cardiac fibrosis. This article summarizes the relationship between inflammation and fibrosis, discusses the bidirectional regulation of cardiac fibrosis by macrophages and analyses the functional heterogeneity of macrophages from different sources. It is believed that CCR2– cardiac resident macrophages can promote cardiac function, but the recruitment and infiltration of CCR2+ cardiac non-resident macrophages aggravate cardiac dysfunction and heart remodeling. After heart injury, damage associated molecular patterns (DAMPs) are released in large quantities, and the inflammatory signal mediated by macrophage chemoattractant protein-1 (MCP-1) promotes the infiltration of CCR2+ monocytes and transforms into macrophages in the heart. These CCR2+ non-resident macrophages not only replace part of the CCR2– resident macrophage subpopulation in the heart, but also cause cardiac homeostasis and hypofunction, and release a large number of mediators that promote fibroblast activation to cause cardiac fibrosis. This article reveals the cell biology mechanism of resident and non-resident macrophages in regulating cardiac fibrosis. It is believed that inhibiting the infiltration of cardiac non-resident macrophages and promoting the proliferation and activation of cardiac resident macrophages are the key to improving cardiac fibrosis and improving cardiac function.

Aiming at the problems of slow teaching resource sharing rate, long platform response time, and low student learning efficiency in traditional ideological and political learning platforms, a research on the construction of intelligent media ideological and political learning platforms based on artificial intelligence technology is proposed. We build an artificial intelligence open source development platform framework based on the cloud platform and use the Ceph method to optimize the storage of artificial intelligence training platform data. Under this framework, we design the business process and business module service architecture of the intelligent media ideological and political learning platform. Based on the K-means algorithm, the intelligent media ideological and political learning platform resource management module is designed, the teaching resource database is constructed, and the teaching resource sharing model component module is designed to realize the construction of the intelligent media ideological and political learning platform. The experimental results show that the sharing rate of ideological, political, and educational learning resources on the platform is relatively fast. The response time of the platform is 0.08 s when the amount of ideological and political teaching resources is 16000 MB. Students who are interested and very interested in the teaching account for 89% of the total.

The deformation and vibration of wind turbine blades in turbulent environment cannot be ignored; therefore, in order to better ensure the safety of wind turbine blades, the study of air-elastic response of wind turbine blades under turbulent wind is indispensable. In this paper, the NREL 5MW wind turbine blades are modeled with accurate 3D lay-up design, firstly, based on the joint simulation of commercial software STAR CCM+ and ABAQUS, the two-way fluid-solid coupling technology, the wind turbine under uniform wind condition is simulated, and the results from thrust, torque, structural deformation and force perspective and FAST are compared with good accuracy and consistency below the rated wind speed. Secondly, the aerodynamic performance, flow field distribution and structural response of turbulent winds with different turbulence strengths at 10 m/s were studied. The results show that the turbulence intensity has a greater impact on the amplitude of the wind turbine blade, and the stress distribution of the blade is more concentrated, which in turns affects the stability and safety of the wind turbine blade and is not conducive to the normal operation of the wind turbine.

Working memory is a fundamental cognitive ability that allows the maintenance and manipulation of information for a brief period of time. Previous studies found a set of brain regions activated during working memory tasks, such as the prefrontal and parietal cortex. However, little is known about the variability of neural activation in working memory. Here, we used functional magnetic resonance imaging to quantify individual, hemispheric, and sex differences of working memory activation in a large cohort of healthy adults (N = 477). We delineated subject-specific activated regions in each individual, including the frontal pole, middle frontal gyrus, frontal eye field, superior parietal lobule, insular, precuneus, and anterior cingulate cortex. A functional probabilistic atlas was created to quantify individual variability in working memory regions. More than 90% of the participants activated all seven regions in both hemispheres, but the intersection of regions across participants was markedly less (50%), indicating significant individual differences in working memory activations. Moreover, we found hemispheric and sex differences in activation location, extent, and magnitude. Most activation regions were larger in the right than in the left hemisphere, but the magnitude of activation did not follow a similar pattern. Men showed more extensive and stronger activations than women. Taken together, our functional probabilistic atlas quantified variabilities of neural activation in working memory, providing a robust spatial reference for standardization of functional localization.

Tetrastigma hemsleyanum Diels et Gilg (Sanyeqing, SYQ) is a perennial climbing liana and an endemic plant to southern China. Its tuberous roots (TRs) are used in traditional Chinese medicine for treating some diseases such as high fever, pneumonia, asthma, hepatitis, and cancers. However, the mechanisms underlying the development of TR and the content of flavonoids and phenylpropanoids (FPs) are not well-understood. In this study, we performed a transcriptomic analysis of 12 fully developed TR (FD-TR) samples harvested in four seasons [spring (Sp), summer (Su), autumn (Au), and winter (Wi)] using the RNA-Sequencing (RNA-Seq). We obtained a total of 78.54 Gb raw data and 65,578 unigenes. Then, the unigenes were annotated by using six databases such as non-redundant protein database (NR), Pfam, eggNOG, SWISSProt, Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene ontology (GO). The transcriptomic profiling showed closer relationships between the samples obtained in Su and Au than those obtained in Sp and Wi based on the results of both total unigenes and differentially expressed genes (DEGs). Three pathways, including the biosynthesis of FPs, metabolism of starch and sucrose, and signaling of phytohormones, were highly enriched, suggesting a gene-level seasonal variation. Based on the numbers of DEGs, brassinosteroid (BR) signal transduction factors appeared to play a key role in modulating the development of TRs while most of the auxin signaling genes were mainly activated in Wi and Sp FD-TRs. Most genes in the biosynthesis and biodegradation of starch and biodegradation of cellulose were activated in Wi FD-TRs. As determined by the high performance liquid chromatography (HPLC) and aluminum nitrate colorimetric method, the contents of total flavonoids and most detected FP components increased from Sp to Au but decreased in Wi. Enhanced expression levels of some genes in the biosynthetic pathways of FPs were detected in Su and Au samples, which corroborated well with metabolite content. Our findings provide the first transcriptomic and biochemical data on a seasonal variation in the composition of medically important metabolites in SYQ FD-TRs.

The increasingly popular application of AI runs the risk of amplifying social bias, such as classifying non-white faces as animals. Recent research has largely attributed this bias to the training data implemented. However, the underlying mechanism is poorly understood; therefore, strategies to rectify the bias are unresolved. Here, we examined a typical deep convolutional neural network (DCNN), VGG-Face, which was trained with a face dataset consisting of more white faces than black and Asian faces. The transfer learning result showed significantly better performance in identifying white faces, similar to the well-known social bias in humans, the other-race effect (ORE). To test whether the effect resulted from the imbalance of face images, we retrained the VGG-Face with a dataset containing more Asian faces, and found a reverse ORE that the newly-trained VGG-Face preferred Asian faces over white faces in identification accuracy. Additionally, when the number of Asian faces and white faces were matched in the dataset, the DCNN did not show any bias. To further examine how imbalanced image input led to the ORE, we performed a representational similarity analysis on VGG-Face's activation. We found that when the dataset contained more white faces, the representation of white faces was more distinct, indexed by smaller in-group similarity and larger representational Euclidean distance. That is, white faces were scattered more sparsely in the representational face space of the VGG-Face than the other faces. Importantly, the distinctiveness of faces was positively correlated with identification accuracy, which explained the ORE observed in the VGG-Face. In summary, our study revealed the mechanism underlying the ORE in DCNNs, which provides a novel approach to studying AI ethics. In addition, the face multidimensional representation theory discovered in humans was also applicable to DCNNs, advocating for future studies to apply more cognitive theories to understand DCNNs' behavior.

The rapid transmission of measles poses a great challenge for measles elimination. Thus, rapid testing is required to screen the health status in the population during measles outbreaks. A pseudotype-based virus neutralisation assay was used to measure neutralising antibody titres in serum samples collected from healthcare workers in Sheffield during the measles outbreak in 2016. Vesicular stomatitis virus (VSV) pseudotypes bearing the haemagglutinin and fusion glycoproteins of measles virus (MeV) and carrying a luciferase marker gene were prepared; the neutralising antibody titre was defined as the dilution resulting in 90% reduction in luciferase activity. Spearman’s correlation coefficients between IgG titres and neutralising antibody levels ranged from 0.40 to 0.55 (p < 0.05) or from 0.71 to 0.79 (p < 0.0001) when the IgG titres were obtained using different testing kits. In addition, the currently used vaccine was observed to cross-neutralise most circulating MeV genotypes. However, the percentage of individuals being “well-protected” was lower than 95%, the target rate of vaccination coverage to eliminate measles. These results demonstrate that the level of clinical protection against measles in individuals could be inferred by IgG titre, as long as a precise correlation has been established between IgG testing and neutralisation assay; moreover, maintaining a high vaccination coverage rate is still necessary for measles elimination.

Background/Aims: microRNAs are of vital importance in neural development. As a brain-specific miRNA, miR-132 has been well studied in mature neurons. However, its role in neural stem cells (NSCs) remains unclear. In this study, we investigated the role of miR-132 in regulating NSCs proliferation, differentiation and neuronal maturation. Methods: NSCs were obtained from fetal mice spinal cord. Proliferation, cell cycle, cell apoptosis, cell motility were measured through CCK-8, BrdU, AnnexinV-FITC/PI and migration assay respectively. The expression of synaptic proteins and ERK1/2 pathway were detected by western blot. The inactivation of Notch pathway was checked using qPCR. The neurite outgrowth was recorded using Image J software and Neuron J software. Dendritic length was further analyzed through sholl analysis. Fate determination of NSCs, developmental synapse formation was assessed by immunostaining. Results: miR-132 negatively regulated NSCs proliferation by affecting the cell cycle and promoting apoptosis. Inactivated Notch-Hes1pathway was observed in miR-132 overexpression cells. miR-132 was significantly increased in differentiating NSCs following activation of ERK1/2 pathway. miR-132 could impair neuronal differentiation but promote glial cell differentiation by regulating Mecp2 expression. miR-132 was implicated in neurite outgrowth but slightly inhibited postsynaptic PSD-95 expression. The differentiated neurons exhibited normal electrophysiological characteristics, and already interacted with other neurons to form synaptic-like structures. Conclusion: miR-132 was demonstrated as a negative regulator for NSCs self-renewal, neuronal differentiation but promoted glial cell differentiation and neurite outgrowth.

Background/Aims: Serine/threonine kinase 35 (STK35) may be associated with Parkinson disease and human colorectal cancer, but there have been no reports on the expression levels or roles of STK35 in osteosarcoma. Methods: STK35 mRNA expression was determined in osteosarcoma and bone cyst tissues by real-time PCR. Cell proliferation and apoptosis were assessed by Cell Counting Kit-8 (CCK-8) assay and flow cytometry analysis, respectively. Results: STK35 was up-regulated in osteosarcoma tissues as indicated by analyzing publicly available expression data (GEO dataset E-MEXP-3628) and real-time PCR analysis on our own cohort. We subsequently investigated the effects of STK35 knockdown on two osteosarcoma cell lines, MG63 and U2OS. STK35 knockdown inhibited the growth of osteosarcoma cells in vitro and in xenograft tumors. Meanwhile, STK35 knockdown enhanced apoptosis. Expression of the active forms and the activity of two major executioner caspases, caspase 3 and caspase 7, were also increased in osteosarcoma cells with STK35 silenced. Additionally, Gene Set Enrichment Analysis (GSEA) identified that the JAK/STAT signaling pathway was positively correlated with STK35 expression. The mRNA expression of STK35 was repressed by STAT3 small interfering RNA (siRNA), but not by siRNA of STAT4, STAT5A or STAT6. A luciferase reporter assay further demonstrated that STAT3 transcriptionally regulated STK35 expression. A chromatin immunoprecipitation (ChIP) assay confirmed the direct recruitment of STAT3 to the STK35 promoter. The promotion effects of STAT3 knockdown on cell apoptosis were partially abolished by STK35 overexpression. Furthermore, STK35 mRNA expression was positively correlated with STAT3 mRNA expression in osteosarcoma tissues by Pearson correlation analysis. Conclusions: These results collectively reveal that STAT3 regulates the transcription of STK35 in osteosarcoma. STK35 may exert an oncogenic role in osteosarcoma.

Multiple studies have revealed that adolescent AIDS orphans have more psychosocial problems than healthy adolescents. However, little is known about whether and how the brain structures of adolescent AIDS orphans differ from those of healthy adolescents. Here, we used magnetic resonance imaging to compare adolescent AIDS orphans reared in institutions (N = 20) with a sex- and age-matched group of healthy adolescents reared in families (N = 20) in China using a voxel-based morphometry analysis. First, we found that both total gray- and white-matter volumes did not differ between groups. Second, after correcting for age, sex, and total gray-matter volume, the AIDS orphan group demonstrated smaller hippocampal volumes, larger anterior cingulate cortex (ACC) volumes, and no differences in the amygdala. Third, a whole-brain analysis identified higher gray-matter volume of the ACC in the AIDS orphan group than in the control group. The preliminary findings of this study highlight the need for future research to confirm the sensitivity of the hippocampus and ACC to early adversity.