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Abstract Mitochondrial dysfunction is a pivotal instigator of neuroinflammation, with mitochondrial DNA (mtDNA) leakage as a critical intermediary. This review delineates the intricate pathways leading to mtDNA release, which include membrane permeabilization, vesicular trafficking, disruption of homeostatic regulation, and abnormalities in mitochondrial dynamics. The escaped mtDNA activates cytosolic DNA sensors, especially cyclic gmp-amp synthase (cGAS) signalling and inflammasome, initiating neuroinflammatory cascades via pathways, exacerbating a spectrum of neurological pathologies. The therapeutic promise of targeting mtDNA leakage is discussed in detail, underscoring the necessity for a multifaceted strategy that encompasses the preservation of mtDNA homeostasis, prevention of membrane leakage, reestablishment of mitochondrial dynamics, and inhibition the activation of cytosolic DNA sensors. Advancing our understanding of the complex interplay between mtDNA leakage and neuroinflammation is imperative for developing precision therapeutic interventions for neurological disorders.

IntroductionSocial impairments and repetitive behaviors are at the core symptoms of autism spectrum disorder (ASD). Intranasal administration of the neuropeptide oxytocin (OXT) is a promising treatment. However, there have been inconsistencies in the effects of OXT on social impairments and repetitive behaviors.MethodsA comprehensive search in PubMed, the Cochrane Library, Embase, and Web of Science was conducted to gather randomized controlled trials (RCTs) on the efficacy of OXT in patients diagnosed with ASD up to 11/06/2024. The core outcomes were social impairments measured by total Social Responsiveness Scale (SRS) scores and repetitive behaviors measured by the Repetitive Behavior Scale (RBS).ResultsThis meta-analysis ultimately included 12 RCTs with 498 ASD patients. In an initial analysis, intranasal OXT showed no significant effect on social impairments. For a high dose of 48 IU per day, a beneficial effect on social impairments was found. According to the dose–response meta-analysis, the results indicated that higher doses of OXT might be more effective for social impairments. Depending on repetitive behaviors, the overall analysis showed no significant effect, while the dose over 48 IU per day revealed significant results and the dose–response meta-analysis suggested that higher doses could be more effective for repetitive behaviors.DiscussionAlthough these findings show no consistent beneficial effects, the results of the dose–response meta-analysis suggest that high doses of intranasal OXT per day may be more effective in ASD.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, identifier CRD42024567213.

In this paper, modal properties of the seated human body were identified from measured transmissibilities to the head, chest, lumbar spine L3, pelvis, hips and thighs with single-axis translational vibration; how they were affected by vibration direction and magnitude was quantitatively compared for the first time. To this end, eight subjects were exposed to fore-aft, lateral and vertical single-axis vibrations with three magnitudes at 0.4, 0.8 and 1.2 m/s 2 r.m.s., respectively. Three and five vibration modes were identified with fore-aft vibration and with vertical vibration in the sagittal plane, respectively, while three modes identified with lateral vibration were in the coronal plane. As the vibration magnitude increased from 0.4 to 1.2 m/s 2 r.m.s., the modal frequencies of the modes at 1.2, 2.2, 2.9 and 6.2 Hz, which contained the pitch, lateral movements, fore-aft movements and vertical movements of the upper body, respectively, were reduced to 1.0, 1.8, 2.3 and 5.8 Hz significantly, and the damping ratios of the modes identified at 0.8, 5.2 and 10.9 Hz were changed. High similarity was observed between the modal shapes identified with different vibration magnitudes.

Relational utility refers to the value of another person for the attainment of one's future goals through social interaction. Nelissen (2014) found that relational utility influences the intensity of guilt feelings. Specifically, people would feel stronger guilt for hurting a person if this person has high relational utility compared to low relational utility. Guilt is thus not only sensitive to how much another person is hurt, but also to one's own future benefits. Previous research suggested that regret, an emotion strongly related to guilt, is typically experienced when one's own benefit is involved. Regret was not measured in Nelissen's research. In the present research, we examined the role of relational utility in experienced guilt and regret and explored whether the effect of relational utility on regret could explain why relational utility has an effect on guilt. Specifically, we attempt to replicate and extend Nelissen's Study 1 by adding a measure of regret. In two experimental studies we did not replicate the effect of relational utility on guilt, and we only found an effect of relational utility on regret in Study 1 (and not in Study 2). Possible reasons for the contradictory findings of the two studies are discussed.

ABSTRACT Helicobacter pylori is a microaerophilic Gram-negative bacterium that resides in the human stomach and is classified as a class I carcinogen for gastric cancer. Numerous studies have demonstrated that H. pylori infection plays a role in regulating the function of host cells, thereby contributing to the malignant transformation of these cells. However, H. pylori infection is a chronic process, and short-term cellular experiments may not provide a comprehensive understanding of the in vivo situation, especially when considering the lower oxygen levels in the human stomach. In this study, we aimed to investigate the mechanisms underlying gastric cell dysfunction after prolonged exposure to H. pylori under hypoxic conditions. We conducted a co-culture experiment using the gastric cell line GES-1 and H. pylori for 30 generations under intermittent hypoxic conditions. By closely monitoring cell proliferation, migration, invasion, autophagy, and apoptosis, we revealed that sustained H. pylori stimulation under hypoxic conditions significantly influences the function of GES-1 cells. This stimulation induces epithelial-mesenchymal transition and contributes to the propensity for malignant transformation of gastric cells. To confirm the in vitro results, we conducted an experiment involving Mongolian gerbils infected with H. pylori for 85 weeks. All the results strongly suggest that the Nod1 receptor signaling pathway plays a crucial role in H. pylori-related apoptosis and autophagy. In summary, continuous stimulation by H. pylori affects the functioning of gastric cells through the Nod1 receptor signaling pathway, increasing the likelihood of cell carcinogenesis. The presence of hypoxic conditions further exacerbates this process.IMPORTANCEDeciphering the collaborative effects of Helicobacter pylori infection on gastric epithelial cell function is key to unraveling the development mechanisms of gastric cancer. Prior research has solely examined the outcomes of short-term H. pylori stimulation on gastric epithelial cells under aerobic conditions, neglecting the bacterium’s nature as a microaerophilic organism that leads to cancer following prolonged stomach colonization. This study mimics a more genuine in vivo infection scenario by repeatedly exposing gastric epithelial cells to H. pylori under hypoxic conditions for up to 30 generations. The results show that chronic exposure to H. pylori in hypoxia substantially increases cell migration, invasion, and epithelial-mesenchymal transition, while suppressing autophagy and apoptosis. This highlights the significance of hypoxic conditions in intensifying the carcinogenic impact of H. pylori infection. By accurately replicating the in vivo gastric environment, this study enhances our comprehension of H. pylori’s pathogenic mechanisms in gastric cancer.

The traditional Chinese herbal prescription Buyang Huanwu decoction (BHD), effectively treats atherosclerosis. However, the mechanism of BHD in atherosclerosis remains unclear. We aimed to determine whether BHD could alleviate atherosclerosis by altering the microbiome-associated metabolic changes in atherosclerotic mice. An atherosclerotic model was established in apolipoprotein E-deficient mice fed high-fat diet, and BHD was administered through gavage for 12 weeks at 8.4 g/kg/d and 16.8 g/kg/d. The atherosclerotic plaque size, composition, serum lipid profile, and inflammatory cytokines, were assessed. Mechanistically, metabolomic and microbiota profiles were analyzed by liquid chromatography-mass spectrometry and 16S rRNA gene sequencing, respectively. Furthermore, intestinal microbiota and atherosclerosis-related metabolic parameters were correlated using Spearman analysis. Atherosclerotic mice treated with BHD exhibited reduced plaque area, aortic lumen occlusion, and lipid accumulation in the aortic root. Nine perturbed serum metabolites were significantly restored along with the relative abundance of microbiota at the family and genus levels but not at the phylum level. Gut microbiome improvement was strongly negatively correlated with improved metabolite levels. BHD treatment effectively slows the progression of atherosclerosis by regulating altered intestinal microbiota and perturbed metabolites.

Abstract The distributed architecture of cloud computing necessitates robust defense mechanisms to secure network-accessible resources against a diverse and dynamic threat landscape. A Network Intrusion Detection System (NIDS) is pivotal in this context, with its efficacy in cloud environments hinging on its adaptability to evolving threat vectors while mitigating false positives. In this paper, we present a novel NIDS algorithm, anchored in the Transformer model and finely tailored for cloud environments. Our algorithm melds the fundamental aspects of network intrusion detection with the sophisticated attention mechanism inherent to the Transformer model, facilitating a more insightful examination of the relationships between input features and diverse intrusion types, thereby bolstering detection accuracy. We provide a detailed design of our approach and have conducted a thorough comparative evaluation. Our experimental results demonstrate that the accuracy of our model is over 93%, which is comparable to that of the CNN-LSTM model, underscoring the effectiveness and viability of our Transformer-based intrusion detection algorithm in bolstering cloud security.

China is facing a serious land resource mismatch problem, which will profoundly affect the acceleration of economic growth and technological innovation. Reform of the industrial land allocation system can solve the mismatch of land resources, and that also has an important impact on the promotion of economic and technological development. This paper selects the data of Chinese A-share listed companies in Shanghai and Shenzhen from 2007 to 2020 as the research sample, constructs a double machine learning model, and empirically investigates the impact of a new industrial land use policy on firms’ green innovation behavior. The study shows that: (1) the new industrial land use policy significantly promotes firms’ substantive and strategic green technological innovation, and the effect on substantive green technological innovation is greater than that on strategic green technological innovation. (2) The enhancement of R&D investment sustainability and the “talent pool” effect are important mechanisms through which the new industrial land use policy influences firms’ substantive and strategic green technological innovation. Meanwhile, the new industrial land use policy is conducive to firms’ green co-innovation. (3) There is heterogeneity in the effect of the new industrial land use policy, which can significantly promote green technological innovation of firms in the eastern region, while it does not play a significant role in the green innovation behavior of firms in the central and western regions. The above research results enrich the research in the field of industrial land and innovation, help to understand more comprehensively the mechanism of new industrial land affecting firms’ green technological innovation, and provide policy insights for strengthening the application of industrial land allocation reform in firms’ green innovation.

Abstract Malignant tumours pose significant challenges in terms of high morbidity and mortality rates, primarily due to the lack of large‐scale applicable screening methods and efficient treatment strategies. However, the development of liquid biopsies, particularly circulating cell‐free DNA (cfDNA), offers promising solutions characterised by their non‐invasiveness and cost‐effectiveness, providing comprehensive tumour information on a global scale. The release of cfDNA is predominantly associated with cell death and turnover, while its elimination occurs through nuclease digestion, renal excretion into the urine and uptake by the liver and spleen. Extensive research into the biological properties of cfDNA has led to the identification of novel applications, including non‐invasive cancer screening, cancer subtype classification, tissue‐of‐origin detection and monitoring of treatment efficacy. Additionally, emerging fields such as methylation‐omics, fragment‐omics and nucleosome‐omics show immense potential as tissue‐ and disease‐specific markers. Therefore, this review aims to comprehensively introduce the latest detection techniques of cfDNA, along with detailed information on its characteristics and applications, providing valuable insights for cancer diagnosis and monitoring, which will assist us in purposefully enhancing relevant features for a more comprehensive application in clinical practice.

Background and objective: Pelvic bone tumors represent a harmful orthopedic condition, encompassing both benign and malignant forms. Addressing the issue of limited accuracy in current machine learning algorithms for bone tumor image segmentation, we have developed an enhanced bone tumor image segmentation algorithm. This algorithm is built upon an improved full convolutional neural network, incorporating both the fully convolutional neural network (FCNN-4s) and a conditional random field (CRF) to achieve more precise segmentation. Methodology: The enhanced fully convolutional neural network (FCNN-4s) was employed to conduct initial segmentation on preprocessed images. Following each convolutional layer, batch normalization layers were introduced to expedite network training convergence and enhance the accuracy of the trained model. Subsequently, a fully connected conditional random field (CRF) was integrated to fine-tune the segmentation results, refining the boundaries of pelvic bone tumors and achieving high-quality segmentation. Results: The experimental outcomes demonstrate a significant enhancement in segmentation accuracy and stability when compared to the conventional convolutional neural network bone tumor image segmentation algorithm. The algorithm achieves an average Dice coefficient of 93.31 %, indicating superior performance in real-time operations. Conclusion: In contrast to the conventional convolutional neural network segmentation algorithm, the algorithm presented in this paper boasts a more intricate structure, proficiently addressing issues of over-segmentation and under-segmentation in pelvic bone tumor segmentation. This segmentation model exhibits superior real-time performance, robust stability, and is capable of achieving heightened segmentation accuracy.

Abstract Cloud computing has gained popularity in recent years, but with its rise comes concerns about data security. Unauthorized access and attacks on cloud-based data, applications, and infrastructure are major challenges that must be addressed. While machine learning algorithms have improved intrusion detection systems in cloud data security, they often fail to consider the entire life cycle of file processing, making it difficult to detect certain issues, especially insider attacks. To address these limitations, this paper proposes a novel approach to analyzing data file processing in multi-cloud environments using process mining. By generating a complete file processing event log from a multi-cloud environment, the proposed approach enables detection from both control flow and performance perspectives, providing a deeper understanding of the underlying file processing in its full life cycle. Through our case study, we demonstrate the power and capabilities of process mining for file security detection and showcase its ability to provide further insights into file security in multi-cloud environments.

Background: The solute carrier (SLC) superfamily, which transports solutes across biological membranes, includes four members (SLC2A1, SLC6A1, SLC9A64, and SLC35A2) that have been linked to epilepsy. This study sought to examine the DNA methylation patterns near the promoters of these genes in temporal lobe epilepsy (TLE), as DNA methylation is a crucial epigenetic modification that can impact gene expression. Methods: The study comprised 38 individuals with TLE and 38 healthy controls. Methylation experiments were performed using peripheral blood, while demethylation experiments were carried out using SH-SY5Y cells with the DNA methylation inhibitor decitabine. Results: A significant difference was observed in the DNA methylation rate of SLC6A1 between TLE patients and controls, with TLE patients showing a lower rate (4.81% vs. 5.77%, p = 0.0000), which remained significant even after Bonferroni correction (p = 0.0000). Based on the hypomethylated SLC6A1 in TLE, a predictive model was established that showed promise in distinguishing and calibrating TLE. In the TLE group, there were differences in DNA methylation rates of SLC6A1 between the young patients and the older controls (4.42% vs. 5.22%, p = 0.0004). A similar trend (p = 0.0436) was noted after adjusting for sex, age at onset, and drug response. In addition, the study found that DNA methylation had a silencing impact on the expression of the SLC6A1 gene in SH-SY5Y cells, which were treated with decitabine at a set dose gradient. Conclusions: The evidence suggests that lower methylation of SLC6A1 may stimulate transcription in TLE, however, further investigation is necessary to confirm the exact mechanism.

Abstract Chronic low-grade inflammation has been identified as a major contributor in the development of atherosclerosis. Nuclear Factor-κappa B (NF-κB) is a critical transcription factors family of the inflammatory pathway. As a major catalytic subunit of the IKK complex, IκB kinase β (IKKβ) drives canonical activation of NF-κB and is implicated in the link between inflammation and atherosclerosis, making it a promising therapeutic target. Various natural product derivatives, extracts, and synthetic, show anti-atherogenic potential by inhibiting IKKβ-mediated inflammation. This review focuses on the latest knowledge and current research landscape surrounding anti-atherosclerotic drugs that inhibit IKKβ. There will be more opportunities to fully understand the complex functions of IKKβ in atherogenesis and develop new effective therapies in the future.

Background and objective: Bone tumor is a kind of harmful orthopedic disease, there are benign and malignant points. Aiming at the problem that the accuracy of the existing machine learning algorithm for bone tumor image segmentation is not high, a bone tumor image segmentation algorithm based on improved full convolutional neural network which consists fully convolutional neural network (FCNN-4s) and conditional random field (CRF). Methodology: The improved fully convolutional neural network (FCNN-4s) was used to perform coarse segmentation on preprocessed images. Batch normalization layers were added after each convolutional layer to accelerate the convergence speed of network training and improve the accuracy of the trained model. Then, a fully connected conditional random field (CRF) was fused to refine the bone tumor boundary in the coarse segmentation results, achieving the fine segmentation effect. Results: The experimental results show that compared with the traditional convolutional neural network bone tumor image segmentation algorithm, the algorithm has a great improvement in segmentation accuracy and stability, the average Dice can reach 91.56%, the real-time performance is better. Conclusion: Compared with the traditional convolutional neural network segmentation algorithm, the algorithm in this paper has a more refined structure, which can effectively solve the problem of over-segmentation and under-segmentation of bone tumors. The segmentation prediction has better real-time performance, strong stability, and can achieve higher segmentation accuracy.

Using Illumina sequencing technology, we generated complete mitochondrial genomes (mitogenomes) of three constituent species of the aphid genus Hyalopterus Koch, Hyalopterus amygdali (Blanchard), Hyalopterus arundiniformis Ghulamullah, and Hyalopterus pruni (Geoffroy). The sizes of the Hyalopterus mitogenomes range from 15,306 to 15,410 bp, primarily due to variations in the length of non-coding regions. The Hyalopterus mitogenomes consist of 37 coding genes arranged in the order of the ancestral insect mitogenome, a control region, and a repeat region between trnE and trnF. According to the COI-based analysis, one previously reported mitogenome of H. pruni should be assigned to H. arundiniformis. The gene order, nucleotide composition, and codon usage in the Hyalopterus mitogenomes are highly conserved and similar to those of other species of Aphidinae. The tandem repeat units differ in nucleotide composition, length, and copy number across three Hyalopterus species. Within the widespread Eurasian species H. arundiniformis, variation in repeat units among different geographic populations is observed, indicating that the repeat region may provide valuable insights for studying the intraspecific diversification of aphids. Phylogenetic analyses based on 28 complete mitogenomes of Aphidinae supported the monophyly of Aphidinae, Aphidini, Macrosiphini, and two subtribes of Aphidini. Hyalopterus was monophyletic. H. amygdali and H. pruni formed a sister group, while H. arundiniformis was placed basally. Characterization of the mitogenomes of Hyalopterus provides valuable resources for further comparative studies and for advancing our understanding of the aphid mitogenome architecture.

Abstract Background Henoch-Schönlein purpura (HSP) with refractory gastrointestinal (GI) symptoms is always difficult to handle because of its resistance to supportive therapies and glucocorticoid. This study aimed to evaluate the efficacy of hemoperfusion (HP) and intravenous immunoglobulins (IVIG) therapies in this population. Methods Sixty-four HSP patients with refractory GI involvement (R-GI group) and 64 cases with mild GI symptoms (control group) were retrospectively analyzed in our center from March 2016 to October 2019. In R-GI group, 42 cases (subgroup A) were treated with IVIG and steroid, 13 cases (subgroup B) used HP and steroid, 9 cases (subgroup C) executed a combination of IVIG, HP and steroid. Demographic characteristics, clinical features, laboratory indexes and treatment outcomes were recorded. t-test, One-way ANOVA, Mann-Whitney U test, and multivariate logistic regression were used in comparing differences among subgroups and predicting independent risk factors. Results Compared with the control group, R-GI cases experienced higher risk of renal involvement (P = 0.000), more steroid exposure (P = 0.000), six times expenses (P = 0.000) and 2.3 times length of hospitalization (P = 0.000). The independent risk factors of R-GI group were elevated neutrophils (OR 1.250 [95% CI 1.130-1.383]) and the percentage of B lymphocytes (OR 1.100 [95% CI 1.026-1.179]) as well as decreased IgG (OR 0.847 [95% CI 0.732-0.98]). In R-GI group, increased age (OR 1.039 [95% CI 1.016-1.062]) and IgM (OR 5.994 [95% CI 1.403-27.611]) were verified to be risk factors of HSP nephritis. All three subgroups could alleviate the symptoms effectively. Compared with those in subgroup A, patients in subgroup B were elder (P = 0.004), had less relapse (P = 0.002), steroid exposure (P = 0.033) and expenses (P = 0.031), more significant decrease of WBC (P = 0.026) after treatment. Conclusion The HSP with refractory GI involvement had much higher risk of medical burden and renal involvement. Both IVIG and HP therapies could ameliorate refractory GI symptoms efficiently. HP therapy tended to reduce the relapse, costs and steroid exposure in its audiences who were cooperated and with stable hemodynamics, while IVIG had better use in younger children.

IntroductionIn early-stage epithelial ovarian cancer (EOC), how to perform lymphadenectomy to avoid stage migration and achieve reliable targeted excision has not been explored in depth. This study comprehensively considered the stage migration and survival to determine appropriate numbers of examined lymph node (ELN) for early-stage EOC and high-grade serous ovarian cancer (HGSOC).MethodsFrom the Surveillance, Epidemiology, and End Results database, we obtained 10372 EOC cases with stage T1M0 and ELN ≥ 2, including 2849 HGSOC cases. Generalized linear models with multivariable adjustment were used to analyze associations between ELN numbers and lymph node stage migration, survival and positive lymph node (PLN). LOESS regression characterized dynamic trends of above associations followed by Chow test to determine structural breakpoints of ELN numbers. Survival curves were plotted using Kaplan-Meier method.ResultsMore ELNs were associated with more node-positive diseases, more PLNs and better prognosis. ELN structural breakpoints were different in subgroups of early-stage EOC, which for node stage migration or PLN were more than those for improving outcomes. The meaning of ELN structural breakpoint varied with its location and the morphology of LOESS curve. To avoid stage migration, the optimal ELN for early-stage EOC was 29 and the minimal ELN for HGSOC was 24. For better survival, appropriate ELN number were 13 and 8 respectively. More ELNs explained better prognosis only at a certain range.DiscussionNeither too many nor too few numbers of ELN were ideal for early-stage EOC and HGSOC. Excision with appropriate numbers of lymph node draining the affected ovary may be more reasonable than traditional sentinel lymph node resection and systematic lymphadenectomy.

The mirror neuron system (MNS), including the inferior frontal gyrus (IFG), inferior parietal lobule (IPL) and superior temporal sulcus (STS) plays an important role in action representation and imitation and may be dysfunctional in autism spectrum disorder (ASD). However, it's not clear how these three regions respond and interact during the imitation of different basic facial expressions and whether the pattern of responses is influenced by autistic traits. Thus, we conducted a natural facial expression (happiness, angry, sadness and fear) imitation task in 100 healthy male subjects where expression intensity was measured using facial emotion recognition software (FaceReader) and MNS responses were recorded using functional near-infrared spectroscopy (fNIRS). Autistic traits were measured using the Autism Spectrum Quotient questionnaire. Results showed that imitation of happy expressions produced the highest expression intensity but a small deactivation in MNS responses, suggesting a lower processing requirement compared to other expressions. A cosine similarity analysis indicated a distinct pattern of MNS responses during imitation of each facial expression with functional intra-hemispheric connectivity between the left IPL and left STS being significantly higher during happy compared to other expressions, while inter-hemispheric connectivity between the left and right IPL differed between imitation of fearful and sad expressions. Furthermore, functional connectivity changes during imitation of each different expression could reliably predict autistic trait scores. Overall, the results provide evidence for distinct patterns of functional connectivity changes between MNS regions during imitation of different emotions which are also associated with autistic traits.

Under the dual goals of achieving carbon peak and carbon neutralization, it is of great practical significance to explore the impact of product information labeling on technological innovation. As an essential element in improving energy performance in consumer products, energy-efficiency labels (EEL) have played a vital role in the government’s portfolio of energy-efficiency improvement, technological progress, and carbon emission mitigation. We estimate the extent of the inductive effects of varying patent types on the relationship between the EEL system and technological innovation in a panel differences-in-differences framework based on the panel data of energy-saving patents and electricity-saving patents from 1998 to 2013 in China. Results indicate that the EEL system helps firms improve the ratio of energy-saving and electricity-saving patents to water-saving patents, and the rate of energy-saving and electricity-saving patents to all patents in the region. In another word, the EEL has a significant directed technological inducing effect. As for the role of the heterogeneity of patent types, the positive effects of the EEL system on invention patents are significantly suppressed in patent-for-utility models. Thus, it is suggested to improve the existing EEL system, gradually expand the product coverage of the EEL system, and increase the protection scope of utility model patents for achieving technological progress and sustainable development of society.

Abstract Background Assessment of immune function is of key importance in recognition of disease or healthy status, which still faces challenge in clinical practice. We conducted a 10-center study to investigate lymphocyte parameters including the number, phenotype and IFN-γ-producing ability, and routine laboratory indicators by using the standard method. Results Although the heterogeneity of lymphocyte parameters was widely found, we have established the normal ranges of these parameters by using pooled data which showed no significant difference among centers. Cluster analysis of 35 parameters found 3 interesting clusters which represented different immunological status. Cluster 1 (parameters: IFN-γ+CD4+ T cell percentage and IFN-γ+CD8+ T cell percentage) represented current lymphocyte function, which was associated with indicators such as body mass index and red blood cell; Cluster 2 (parameters: NK cell number and CD45RA+CD4+ T cell percentage) represented potential of lymphocytes, which was associated with indicators such as albumin and high-density lipoprotein. Cluster 3 (parameters: HLA-DR+CD8+ T cell percentage) represented inflammatory status, which was associated with indicators such as low-density lipoprotein, globulin and age. Correlation analysis found that nutritional indicator albumin is significantly positively correlated with lymphocyte potential. Triglyceride and body mass index were positively correlated with current lymphocyte function rather than lymphocyte potential. The loss of CD8+ T cells was extremely pronounced with increasing age and was one of the most important factors to cause immunosenescence, which may be associated with increased glucose. Conclusions We have established the normal ranges of lymphocyte parameters in different areas. This study elucidates the key indicators used to reflect the current function or potential of lymphocytes, which may provide a valuable clue for how to keep immunity healthy.

In recent years, the power electronic load infiltrates into the microgrid in the form of constant power, and its negative impedance characteristics threaten the stability of the system. To alleviate the instability caused by constant power loads (CPLs) and constant impedance loads (CILs) of the boost power converter in the DC microgrid, an adaptive backstepping control (BSC) method is designed. Firstly, based on the dynamic model of boost converter, an input voltage estimator is designed, which is introduced into backstepping control to improve the robustness to the change of input voltage. In addition, to improve the anti-interference performance of the system and ensure the static error free tracking of the output voltage, an extended nonlinear disturbance observer (ENDO) is used to compensate for the influence caused by mismatched disturbance and model uncertainty, the optimized BSC uses fewer initial parameters to ensure its operation. Finally, the large-signal stability of the proposed control is verified by using Lyapunov stability theory, which ensures the global trajectory tracking of the reference voltage and fast dynamic control. Through MATLAB simulation and hardware in the loop experiment (HIL), the proposed control is compared with BSC+NDO to verify the effectiveness and superiority of the proposed algorithm.

Quantum science and computing represent a vital intersection between science and technology, gaining increasing importance in modern society. There is a pressing need to incorporate these concepts into the K-12 curriculum, equipping new generations with the tools to navigate and thrive in an evolving technological landscape. This study explores the professional learning of K-12 teachers (n = 49) related to quantum concepts and pedagogy. We used open-ended surveys, field notes, workshop artifacts, and interviews to examine teachers’ perceptions of quantum and how they made connections between quantum and their curriculum. Our data reveal that most teachers were excited and interested in teaching quantum but were aware of potential barriers and concerns that might get in the way of teaching quantum. We found that teachers readily identified connections to math and science in their curriculum, but only a few made connections to computing. Enthusiasm for teaching quantum concepts was found in both elementary and secondary educators, suggesting a widespread recognition of its importance in preparing students for a future where quantum technology is a fundamental aspect of their lives and careers.

Abstract Background Macrophages are one of the important cells in immune system. In this article, we aim to explore the regulatory role of miR-455-3p on proliferation and osteoblast differentiation of RAW264.7 cells. Methods Expression levels of genes and proteins in cells were tested via qRT-PCR and western blot. The targeted correlation between miR-455-3p and PTEN was identified by luciferase analysis. MTT assay and flow cytometry were applied to detect the proliferation and apoptosis of cells. Osteoclastogenesis was completed by stimulating RAW 264.7 cells with RANKL. Tartrate-resistant acid phosphatase (TRAP) activity in different groups of cells were assessed. Results Firstly, we determined that up-regulation of miR-455-3p promoted the proliferation and inhibited apoptosis of RAW 264.7 cells. MiR-455-3p deficiency played opposite effect in RAW 264.7 cells. Additionally, osteoclastogenesis-related factors (TRAP, CTSK and NFATc1) expression levels were remarkably up-regulated in miR-455-3p-mimic group of RAW264.7 cells treated with RANKL, but decreased in inhibitor group. Luciferase assay proved that miR-455-3p targeted PTEN. We took a further step and found overexpression of PTEN significantly inhibited the increased proliferation and osteoblast differentiation of RAW264.7 cells induced by miR-455-3p. Conclusions Our findings supported basic to explore the molecular mechanism of proliferation and osteoblast differentiation of RAW264.7 cells.

The role astrocytes play in brain development and function has garnered greater attention as the diversity of roles they are involved in has become apparent. We have previously shown that ethanol-exposed astrocytes alter neuronal neurite outgrowth in an in vitro co-culture system and that ethanol alters the astrocyte-produced extracellular matrix (ECM) in vitro, with similar alterations in vivo. In this study, we utilized the translating ribosome affinity purification (TRAP) procedure in Aldh1l1-EGFP/Rpl10a transgenic mouse primary cortical astrocyte cultures to transcriptionally and translationally profile the astrocyte response to ethanol. We found a large number of differences between the total RNA pool and the translating RNA pool, indicating that the transcriptional state of astrocytes may not always reflect the translational state of astrocytes. In addition, there was a considerable overlap between ethanol-dysregulated genes in the total RNA pool and the translating RNA pool. Comparisons to published datasets indicate the in vitro model used here is most similar to PD1 or PD7 in vivo cortical astrocytes, and the ethanol-regulated genes showed a significant overlap with models of chronic ethanol exposure in astrocytes, a model of third-trimester ethanol exposure in the hippocampus and cerebellum, and an acute model of ethanol exposure in the hippocampus. These findings will further our understanding of the effects of ethanol on astrocyte gene expression and protein translation and how these changes may alter brain development and support the use of in vitro astrocyte cultures as models of neonatal astrocytes.

Extrahepatic cholangiocarcinoma (eCCA) contains perihilar cholangiocarcinoma and distal cholangiocarcinoma both of which can arise at any point of the biliary tree and originate from disparate anatomical sites. Generally, the incidence of eCCA is increasing globally. Though surgical resection is the principal treatment of choice for the early stages of eCCA, optimal survival remains restricted by the high risk of recurrence when most patients are present with unresectable disease or distant metastasis. Furthermore, both intra- and intertumoral heterogeneity make it laborious to determine molecularly targeted therapies. In this review, we mainly focused on current findings in the field of eCCA, mostly including epidemiology, genomic abnormalities, molecular pathogenesis, tumor microenvironment, and other details while a summary of the biological mechanisms driving eCCA may shed light on intricate tumorigenesis and feasible treatment strategies.

Systemic sclerosis (SSc) is a connective tissue disease with high mortality. One of the most common causes of death in potential SSc patients is cardiac arrest. However, the pathogenesis of cardiac death is not very clear. As far as we know, there are few autopsy reports on this subject. Our autopsy report on two fatal cases of heart injury in SSc patients revealed evidence of myocarditis, focal myocardial necrosis, and myocardial fibrosis. Our findings suggest that chronic inflammation of the heart may lead to extensive fibrosis, which could contribute to the high mortality rate observed in SSc patients. Early detection of heart injury in SSc patients using existing technology is necessary to improve patient outcomes. Future research should focus on developing more effective methods for early detection and management of heart involvement in SSc.

Summary: Vigorous-intensity leisure-time physical activity, such as marathon, has become increasingly popular, but its effect on immune functions and health is poorly understood. Here, we performed scRNA-seq analysis of peripheral blood mononuclear cells (PBMCs) after a bout of symptom-limited cardiopulmonary exercise (CPX) test or marathon. Time-series single-cell analysis revealed the detailed series of landscapes of immune cells in response to short and long vigorous-intensity activities. Reduction of effective T cells was observed with the cell migration and motility pathways enriched in circulation following marathon. Baseline values of PBMCs abundance were reached around 1 h after CPX and 24 h following marathon, but longer time was required for expression recovery of cytotoxicity genes. The ratio of effector/naive T cells was found to change uniformly among the participants and could serve as a better indicator for exercise intensity than the CD4+/CD8+ T cell ratio. Moreover, we identified time-dependent monocyte state transitions after marathon.

Runoff processes are the basis for maintaining the safety of river ecosystems. The Yarlung Zangbo River (YZR) faces changes in flow regimes due to the impacts of human activities and climate change, which may threaten its fragile ecosystem. In this study, a new comprehensive system for evaluating runoff variation was constructed to investigate the degree of runoff alternation in the YZR. Based on the data from the primary hydrological stations in the YZR from 1956 to 2000, the assessment indicators of runoff variation were selected by considering the flow, sediment, and water temperature processes. Furthermore, a comprehensive evaluation system for runoff variation was constructed via multiple hydrological analysis methods and vague sets. The results showed that the variation index of the YZR from 2010 to 2013 was 0.15–0.20 compared with the flow regimes of the YZR before 2000, which were within a reasonable range, indicating that the comprehensive runoff conditions of the YZR were not greatly disturbed by human activities such as reservoir construction and river regulation during this period. These results provide a tool for evaluating the runoff change in the YZR and new references for researching runoff variation in other similar watersheds. HIGHLIGHTS Flow, sediment and water temperature were considered to describe river runoff processes.; A comprehensive evaluation system for runoff variation was developed based on vague sets theory.; Historical runoff process data were used to establish a natural baseline for variation evolution.; This method provides a new reference for further research on river regulation and management.;

Abstract Chlorination converts an efficient isoindigo (IID)‐based electron donor material to an effective electron acceptor material, which could pair with different donor materials. The polymer PAZ could work as the donor and achieve moderate power conversion efficiency of 3.56%, but organic solar cells based on the blend of PC71BM and the chlorinated analogue PAZ‐Cl fail. On the contrary, only PAZ‐Cl could be used as the acceptor material matching with typical donor polymers, such as PTB7‐Th, J52 and J52‐2Cl. Simulation based on density functional theory suggests that the main reason for this transform might be attributed to the change in the electrostatic potential of the polymers. This research paves a new way to design novel electron acceptors for organic solar cells.

Objectives and Introduction The purpose of this study was to determine the prevalence and influencing factors of systemic lupus erythematosus (SLE) patients complicated with infection having multi-system involvement and to analyze the influencing factors of early CMV and fungal infection. Methods We conducted a cross-sectional study of hospitalized SLE patients complicated with infection. Participants had an average age of 44.80 ± 17.30, with 152 being female (89.94%). Clinical data and laboratory results were collected from medical records. Receiver operating characteristic (ROC) curves were plotted, and sensitivity and specificity were calculated. Results Univariate analysis showed that systemic lupus erythematosus disease activity index-2000 (SLEDAI-2k), red blood cell, platelets, hemoglobin, lymphocytes, IgG, IgM, C3, C4, albumin and globulin were significantly associated with SLE patients with infection complicated with multi-system involvement. After multivariable analysis, the following variables remained significant: Hemoglobin, CD4 lymphocyte, IgM and SM ( p < 0.05). ROC curve analysis showed the areas under the curve of Hb, CD4 count, and IgM for the differential diagnosis of SLE with infection complicated with multisystem involvement being 0.646, 0.627, and 0.610. Then, the sensitivities of 73.3%, 53.3%, and 73.3% were observed with the specificities of 54.1%, 69.7%, and 48.6%, respectively. Conclusions Our results demonstrated that hemoglobin, CD4 lymphocyte value, IgM and anti SM antibody had significant value in monitoring multi-system involvement in SLE patients complicated with infection. Besides, intrinsic lymphatic count disturbances associated with SLE disease can cause infections by opportunistic pathogens such as fungi.

As remote sensing images have complex backgrounds and varying object sizes, their semantic segmentation is challenging. This study proposes a multiscale cascaded network (MSCNet) for semantic segmentation. The resolutions employed with respect to the input remote sensing images are 1, 1/2, and 1/4, which represent high, medium, and low resolutions. First, 3 backbone networks extract features with different resolutions. Then, using a multiscale attention network, the fused features are input into the dense atrous spatial pyramid pooling network to obtain multiscale information. The proposed MSCNet introduces multiscale feature extraction and attention mechanism modules suitable for remote sensing land-cover classification. Experiments are performed using the Deepglobe, Vaihingen, and Potsdam datasets; the results are compared with those of the existing classical semantic segmentation networks. The findings indicate that the mean intersection over union (mIoU) of the MSCNet is 4.73% higher than that of DeepLabv3+ with the Deepglobe datasets. For the Vaihingen datasets, the mIoU of the MSCNet is 15.3%, and 6.4% higher than those of a segmented network (SegNet), and DeepLabv3+, respectively. For the Potsdam datasets, the mIoU of the MSCNet is higher than those of a fully convolutional network, Res-U-Net, SegNet, and DeepLabv3+ by 11.18%, 5.89%, 4.78%, and 3.03%, respectively.

Atherosclerosis, the main pathological basis of cardiovascular disease, is a chronic inflammatory disease that severely affects the quality of human life. Resveratrol (Res) is a natural polyphenol that is a major component of many herbs and foods. The present study analyzed resveratrol from the perspective of visualization and bibliometric analysis and found that resveratrol is closely related to the inflammatory response in cardiovascular diseases (associated with atherosclerosis). To explore the specific molecular mechanism of resveratrol, network pharmacology and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used, in which HIF-1α signaling may be a key pathway in the treatment of AS. Furthermore, we induced the polarization of macrophage RAW264.7 to M1 type to generate inflammatory response by the combination of lipopolysaccharide (LPS) (200 ng/mL) + interferon-γ (IFN-γ) (2.5 ng/mL). LPS and IFN-γ increased the inflammatory factor levels of IL-1β, TNF-α, and IL-6 in RAW264.7, and the proportion of M1-type macrophages also increased, but the expression of inflammatory factors decreased after resveratrol administration, which confirmed the anti-inflammatory effect of resveratrol in AS. In addition, we found that resveratrol downregulated the protein expression of toll-like receptor 4 (TLR4)/NF-κB/hypoxia inducible factor-1 alpha (HIF-1α). In conclusion, resveratrol has a significant anti-inflammatory effect, alleviates HIF-1α-mediated angiogenesis, and prevents the progression of AS through the TLR4/NF-κB signaling pathway.

Background. Alleviating mild cognitive impairment (MCI) is crucial to delay the progression of Alzheimer’s disease (AD). Jia-Wei-Kai-Xin-San (JWKXS) is applied for treating AD with MCI. However, the mechanism of JWKXS in the treatment of MCI is unclear. Thus, this study aimed to investigate the effect and mechanism of JWKXS in SAMP8 mice models of MCI. Methods. MCI models were established to examine learning and memory ability and explore the pathomechanisms in brain of SAMP8 mice at 4, 6, and 8 months. The mice were treated for 8 weeks and the effects of JWKXS on MCI were characterized through Morris water maze and HE/Nissl’s/immunohistochemical staining. Its mechanism was predicted by the combination of UPLC-Q-TOF/MS and system pharmacology analysis, further verified with SAMP8 mice, BV2 microglial cells, and PC12 cells. Results. It was found that 4-month-old SAMP8 mice exhibited MCI. Two months of JWKXS treatment improved the learning and memory ability, alleviated the hippocampal tissue and neuron damage. Through network pharmacology, four key signaling pathways were found to be involved in treatment of MCI by JWKXS, including TLR4/NF-κB pathway, NLRP3 inflammasome activation, and intrinsic and extrinsic apoptosis. In vitro and in vivo experiments demonstrated that JWKXS attenuated neuroinflammation by inhibiting microglia activation, suppressing TLR4/NF-κB and NLRP3 inflammasome pathways, and blocking the extrinsic and intrinsic apoptotic pathways leading to neuronal apoptosis suppression in the hippocampus. Conclusion. JWKXS treatment improved the learning and memory ability and conferred neuroprotective effects against MCI by inducing anti-inflammation and antiapoptosis. Limitations. The small sample size and short duration of the intervention limit in-depth investigation of the mechanisms. Future Prospects. This provides a direction for further clarification of the anti-AD mechanism, and provides certain data support for the formulation to move toward clinical practice.

Potatoes are the fourth major food crop in the world. Higher levels of glycoside alkaloids (GAs) lead to detrimental effects on the edibility and processing qualities. GAs are largely influenced by light; however, the mechanisms of this regulation by light are not well understood. By analyzing the bioinformatics of the phytochrome genes (PHYs) in potatoes, its expression level, the content of GAs and the correlation between them under different lights, this study aims to reveal the specific mechanism of light-regulated GAs accumulation and provide a theoretical basis for improved potato processing. Results based on high-performance liquid chromatography and imaging mass microscopy showed that red light induced a significant increase in α-chaconine and α-solanine accumulation compared to white light, but there was almost no accumulation in the dark within 12 days. Meanwhile, a bioinformatic analysis of PHY gene family members was performed, and the results showed that the five StPHYs were distributed on chromosomes 1, 2, 5, 7 and 10, with amino acid counts ranging from 704 to 1130. StPHYs genes have abundant light-responsive elements. Also, the expression patterns of StPHYs were dramatically induced by red light. Additionally, a correlation analysis showed that the GAs accumulation was significantly correlated with StPHYs expression. This research is useful for comprehending the metabolism of GAs regulated by light and monitoring food safety in potatoes.

The Deeplabv3+ network for semantic segmentation of remote sensing images has drawbacks like inaccurate edge segmentation and intra-class inconsistency in large-scale segmentation. The attention mechanism is a good solution to this problem. This paper integrates the dual attention mechanism module including spatial attention mechanism and channel attention mechanism (ISNet) into the network. Furthermore, the ISNet is added to both the encoder part and decoder part in the network. The newly proposed network is called DISNet. It can enhance target features and suppress background features, having the potential to improve semantic segmentation accuracy. The experimental results indicate that the Mean Intersection over Union (mIoU) of the Deepglobe dataset, GID dataset, and ISPRS test project (Vaihingen) dataset is respectively 64.22, 62.83, and 78.59%. Those results are 5.68, 4.80, and 6.20% higher than that of Deeplabv3+. The proposed network can effectively improve the accuracy of remote sensing land cover classification.

Introduction: Brain metastases (BM) severely affect the prognosis and quality of life of patients with NSCLC. Recently, molecularly targeted agents were found to have promising activity against BM in patients with NSCLC whose primary tumors carry “druggable” mutations. Nevertheless, it remains critical to identify specific pathogenic alterations that drive NSCLC-BM and that can provide novel and more effective therapeutic targets. Methods: To identify potentially targetable pathogenic alterations in NSCLC-BM, we profiled somatic copy number alterations (SCNAs) in 51 matched pairs of primary NSCLC and BM samples from 33 patients with lung adenocarcinoma and 18 patients with lung squamous cell carcinoma. In addition, we performed multiregion copy number profiling on 15 BM samples and whole-exome sequencing on 40 of 51 NSCLC-BM pairs. Results: BM consistently had a higher burden of SCNAs compared with the matched primary tumors, and SCNAs were typically homogeneously distributed within BM, suggesting BM do not undergo extensive evolution once formed. By comparing focal SCNAs in matched NSCLC-BM pairs, we identified putative BM-driving alterations affecting multiple cancer genes, including several potentially targetable alterations in genes such as CDK12, DDR2, ERBB2, and NTRK1, which we validated in an independent cohort of 84 BM samples. Finally, we identified putative pathogenic alterations in multiple cancer genes, including genes involved in epigenome editing and 3D genome organization, such as EP300, CTCF, and STAG2, which we validated by targeted sequencing of an independent cohort of 115 BM samples. Conclusions: Our study represents the most comprehensive genomic characterization of NSCLC-BM available to date, paving the way to functional studies aimed at assessing the potential of the identified pathogenic alterations as clinical biomarkers and targets.

Non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) as a newly developed technique involves stimulating the cutaneous receptive field formed by the auricular branch of the vagus nerve in the outer ear, with resulting activation of vagal connections to central and peripheral nervous systems. Increasing evidence indicates that maladaptive neural plasticity may underlie the pathology of several pediatric neurodevelopmental and psychiatric disorders, such as autism spectrum disorder, attention deficit hyperactivity disorder, disruptive behavioral disorder and stress-related disorder. Vagal stimulation may therefore provide a useful intervention for treating maladaptive neural plasticity. In the current review we summarize the current literature primarily on therapeutic use in adults and discuss the prospects of applying taVNS as a therapeutic intervention in specific pediatric neurodevelopmental and other psychiatric disorders. Furthermore, we also briefly discuss factors that would help optimize taVNS protocols in future clinical applications. We conclude from these initial findings that taVNS may be a promising alternative treatment for pediatric disorders which do not respond to other interventions.

High-resolution images exhibit wide field of vision, high background complexity, special angle of view, rotation, and small objects, thus making automatic object detection a challenging problem. Recently, this problem has been studied by many researchers through the application of deep learning methods, and good detection results have been achieved. However, most of the current networks for object detection on remote sensing images are designed manually, which is not necessarily the optimal structure. Therefore, DARTS-FPN, a network based on differentiable architecture search, has been constructed to improve the accuracy of object detection on high resolution images. The DARTS algorithm is first used to search the remote sensing images data set. The neural architecture search technique of NAS-FPN is then integrated into this network and merged with RetinaNet, a single-stage rotating network for object detection. Experiments are conducted on the DOTA data set to evaluate the performance of DARTS-FPN. Compared with existing classical networks, DARTS-FPN achieves 55.86%, 45.06%, 5.78%, and 2.19% higher mean average precision than the SSD, YOLOv2, R2CNN, and DM algorithms, respectively.

Abstract Glioma is the most common malignant primary brain tumour in adults. Despite improvements in neurosurgery and radiotherapy, the prognosis of glioma patients remains poor. One of the main limitations is that there are no proper clinical therapeutic targets for glioma. Therefore, it is crucial to find one or more effective targets. Signal transducer and activator of transcription 3 (STAT3) is a member of the STAT family of genes. Abnormal expression of STAT3 is involved in the process of cell proliferation, migration, invasion, immunosuppression, angiogenesis, dryness maintenance, and resistance to radiotherapy and chemotherapy in glioma. Therefore, STAT3 has been considered an ideal therapeutic target in glioma. Noncoding RNAs (ncRNAs) are a group of genes with limited or no protein-coding capacity that can regulate gene expression at the epigenetic, transcriptional and posttranscriptional level. In this review, we summarized the ncRNAs that are correlated with the ectopic expression of STAT3 in glioma.

Abstract Cholangiocarcinoma (CCA) is a group of malignancies emerging in the biliary tree and is associated with a poor patient prognosis. Although the anatomical location is the only worldwide accepted classification basis, it still has bias. The current study integrates the whole-genome expression data from several big cohorts in the literature, to screen and provide a comprehensive bioinformatic analysis, in order to better classify molecular subtypes and explore an underlying cluster mechanism related to anatomy and geographical regions. Differentially expressed protein-coding genes (DEGs) were identified for CCA as well as subtypes. Biological function enrichment analysis—Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis—was applied and identified different DEGs enriched signaling pathways in CCA subtypes. A co-expression network was presented by Weighted gene co-expression network analysis package and modules related to specific phenotypes were identified. Combined with DEGs, hub genes in the given module were demonstrated through protein–protein interaction network analysis. Finally, DEGs which significantly related to patient overall survival and disease-free survival time were selected, including ARHGAP21, SCP2, UBIAD1, TJP2, RAP1A and HDAC9.

Leaf color is one of the most important features for plants used for landscape and ornamental purposes. However, the regulatory mechanism of yellow leaf coloration still remains elusive in many plant species. To understand the complex genetic mechanism of yellow-leaf Forsythia, we first compared the pigment content and leaf anatomical structure of yellow-leaf and green-leaf accessions derived from a hybrid population. The physiological and cytological analyses demonstrated that yellow-leaf progenies were chlorophyll deficient with defected chloroplast structure. With comparative transcriptome analysis, we identified a number of candidate genes differentially expressed between yellow-leaf and green-leaf Forsythia plants. Among these genes, we further screened out two candidates, ChlH (magnesium chelatase Subunit H) and POLGAMMA2 (POLYMERASE GAMMA 2), with consistent relative-expression pattern between different colored plants. To verify the gene function, we performed virus-induced gene silencing assays and observed yellow-leaf phenotype with total chlorophyll content reduced by approximately 66 and 83% in ChlH-silenced and POLGAMMA2-silenced plants, respectively. We also observed defected chloroplast structure in both ChlH-silenced and POLGAMMA2-silenced Forsythia. Transient over-expression of ChlH and POLGAMMA2 led to increased chlorophyll content and restored thylakoid architecture in yellow-leaf Forsythia. With transcriptome sequencing, we detected a number of genes related to chlorophyll biosynthesis and chloroplast development that were responsive to the silencing of ChlH and POLGAMMA2. To summarize, ChlH and POLGAMMA2 are two key genes that possibly related to yellow-leaf coloration in Forsythia through modulating chlorophyll synthesis and chloroplast ultrastructure. Our study provided insights into the molecular aspects of yellow-leaf Forsythia and expanded the knowledge of foliage color regulation in woody ornamental plants.

Abstract Background Aerobic rice production (AP) may be a solution to the looming water crisis by utilising less water compared to traditional flooded culture. As such, development of genotypes with narrow root cone angle (RCA) is considered a key AP adaptation trait as it could lead to deeper rooting and ensure water uptake at depth. Quantitative trait loci (QTL) and genes associated with rooting angle have been identified in rice, but usually in conventional transplanted systems or in upland and drought conditions. This study aimed to identify QTL associated with RCA in AP systems using a recombinant inbred line population derived from IRAT109. Results Four experiments conducted in glasshouse and aerobic field conditions revealed significant genotypic variation existed for RCA in the population. Single and multiple QTL models identified the presence of eight QTL distributed in chromosomes 1, 2, 3, 4, and 11. Combined, these QTL explained 36.7–51.2% of the genotypic variance in RCA present in the population. Two QTL, qRCA1.1 and qRCA1.3, were novel and may be new targets for improvement of RCA. Genotypes with higher number of favourable QTL alleles tended to have narrower RCA. qRCA4 was shown to be a major and stable QTL explaining up to 24.3% of the genotypic variation, and the presence of the target allele resulted in as much as 8.6° narrower RCA. Several genes related to abiotic stress stimulus response were found in the qRCA4 region. Conclusion Stable and novel genomic regions associated with RCA have been identified. Genotypes which had combinations of these QTL, resulted in a narrower RCA phenotype. Allele mining, gene cloning, and physiological dissection should aid in understanding the molecular function and mechanisms underlying RCA and these QTL. Ultimately, our work provides an opportunity for breeding programs to develop genotypes with narrow RCA and deep roots for improved adaptation in an AP system for sustainable rice production.

Abstract The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. Identification of effective therapeutics is a crucial tool to treat those infected with SARS-CoV-2 and limit the spread of this novel disease globally. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an “omics” repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and publicly available SARS-CoV-2 infected cell lines to identify novel therapeutics. We identified a shortlist of 20 candidate drugs: 8 are already under trial for the treatment of COVID-19, the remaining 12 have antiviral properties and 6 have antiviral efficacy against coronaviruses specifically, in vitro. All candidate drugs are either FDA approved or are under investigation. Our candidate drug findings are discordant with (i.e., reverse) SARS-CoV-2 transcriptome signatures generated in vitro, and a subset are also identified in transcriptome signatures generated from COVID-19 patient samples, like the MEK inhibitor selumetinib. Overall, our findings provide additional support for drugs that are already being explored as therapeutic agents for the treatment of COVID-19 and identify promising novel targets that are worthy of further investigation.

Based on the rainfall data from the automatic weather stations, the conventional data accessed by MICAPS4 and NCEP reanalysis data, we have conducted a comparative analysis of two local heavy rainstorm events on the eastern foot of Helan Mountain in Ningxia occurred respectively on 21 August 2016 and 22 July 2018 in terms of their precipitation characteristics, circulation background and other conditions, with focus on the diagnostic analysis of the moist potential vortex field in the two events. The results indicate that both events can be divided into two stages. In both cases, the first stage are warm-area precipitation, showing the feature such as small range, short time and high intensity. Comparing with the first stage, their second stage of precipitation present larger range and less rain intensity. The severe precipitation during the two events both occurred in the pseudo-equivalent potential temperature (θse) isoline areas, and both of them are distributed along the main axis of the low-level jet. The period of severe precipitation is consistent with the occurrence time of θse maximum. Rainstorm zones are basically located near the center of negative potential vortex (PV), and the trigger and development of rainstorm is consistent with the movement of the negative PV center, whose strengthening, weakening and moving direction can guide the prediction of local heavy rainstorm. The positive large value areas of barotropic term (MPV1) of moist potential vorticity above 500 hPa troposphere are corresponding with the negative large value areas of MPV1 below 700 hPa, and the vertical superposition of positive and negative MPV1 center area is conducive to the occurrence and development of rainstorm. It is found in the vertical section that there are negative extreme areas of baroclinic term (MPV2) of moist potential vorticity at 600 hPa in the two events. The intensity, duration and variation of negative MPV2 extreme areas in the lower and middle troposphere can be used as indicators for the prediction of local heavy rainstorm.

Own race faces tend to be recognized more accurately than those of other less familiar races, however, findings to date have been inconclusive. The present study aimed to determine whether Chinese exhibit different recognition accuracy and eye gaze patterns for Asian (own-race) and White (other-race) facial expressions (neutral, happiness, sadness, anger, disgust, fear). A total of 89 healthy Chinese adults viewed Asian and White facial expressions while undergoing eye-tracking and were subsequently required to identify expressions and rate their intensity and effect on arousal. Results revealed that subjects recognized sad expressions in Asian faces better than in White ones. On the other hand, recognition accuracy was higher for White neutral, happy, fearful, and disgusted expressions although this may have been due to subjects more often misclassifying these Asian expressions as sadness. Moreover, subjects viewed the eyes of emotional expressions longer in Asian compared to White faces and the nose of sad ones, especially during the late phase of presentation, whereas pupil sizes, indicative of cognitive load and arousal, were smaller. Eye-gaze patterns were not, however, associated with recognition accuracy. Overall, findings demonstrate an own-race bias in Chinese for identifying sad expressions and more generally across emotional expressions in terms of viewing the eye region of emotional faces for longer and with reduced pupil size. Interestingly, subjects were significantly more likely to miss-identify Asian faces as sad resulting in an apparent other-race bias for recognizing neutral, happy, fearful, and disgusted expressions.

Abstract NLRP3 inflammasome activation in macrophages fuels sterile inflammation, which has been tied with metabolic reprogramming characterized by high glycolysis and low oxidative phosphorylation. The key enzymes in glycolysis and glycolysis‐related products can regulate and activate NLRP3 inflammasome. In turn, NLRP3 inflammasome is considered to affect glycolysis, as well. However, the exact mechanism remains ambiguous. On the basis of these findings, the focus of this review is mainly on the developments in our understanding of interaction between NLRP3 inflammasome activation and glycolysis in macrophages, and small molecule compounds that influence the activation of NLRP3 inflammasomes by regulating glycolysis in macrophages. The application of this interaction in the treatment of diseases is also discussed. This paper may yield valuable clues for development of novel therapeutic agent for NLRP3 inflammasome‐related diseases.

Endometrioid endometrial carcinomas (EECs) are the most common histological subtype of uterine cancer. Late-stage disease is an adverse prognosticator for EEC. The purpose of this study was to analyze EEC exome mutation data to identify late-stage-specific statistically significantly mutated genes (SMGs), which represent candidate driver genes potentially associated with disease progression. We exome sequenced 15 late-stage (stage III or IV) non-ultramutated EECs and paired non-tumor DNAs; somatic variants were called using Strelka, Shimmer, SomaticSniper and MuTect. Additionally, somatic mutation calls were extracted from The Cancer Genome Atlas (TCGA) data for 66 late-stage and 270 early-stage (stage I or II) non-ultramutated EECs. MutSigCV (v1.4) was used to annotate SMGs in the two late-stage cohorts and to derive p-values for all mutated genes in the early-stage cohort. To test whether late-stage SMGs are statistically significantly mutated in early-stage tumors, q-values for late-stage SMGs were re-calculated from the MutSigCV (v1.4) early-stage p-values, adjusting for the number of late-stage SMGs tested. We identified 14 SMGs in the combined late-stage EEC cohorts. When the 14 late-stage SMGs were examined in the TCGA early-stage data, only Krüppel-like factor 3 (KLF3) and Paired box 6 (PAX6) failed to reach significance as early-stage SMGs, despite the inclusion of enough early-stage cases to ensure adequate statistical power. Within TCGA, nonsynonymous mutations in KLF3 and PAX6 were, respectively, exclusive or nearly exclusive to the microsatellite instability (MSI)-hypermutated molecular subgroup and were dominated by insertions-deletions at homopolymer tracts. In conclusion, our findings are hypothesis-generating and suggest that KLF3 and PAX6, which encode transcription factors, are MSI target genes and late-stage-specific SMGs in EEC.

Background & Aims: Distal cholangiocarcinoma (dCCA) are a group of epithelial cell malignancies that occurs at the distal common bile duct, and account for approximately 40% of all cholangiocarcinoma cases. dCCA remains a highly lethal disease as it typically features remarkable cellular heterogeneity. A comprehensive exploration of cellular diversity and the tumor microenvironment is essential to depict the mechanisms driving dCCA progression. Methods: Single-cell RNA sequencing was used here to dissect the heterogeneity landscape and tumor microenvironment composition of human dCCAs. Seven human dCCAs and adjacent normal bile duct samples were included in the current study for single-cell RNA sequencing and subsequent validation approaches. Additionally, the results of the analyses were compared with bulk transcriptomic datasets from extrahepatic cholangiocarcinoma and single-cell RNA data from intrahepatic cholangiocarcinoma. Results: We sequenced a total of 49,717 single cells derived from human dCCAs and adjacent tissues, identifying 11 distinct cell types. Malignant cells displayed remarkable inter- and intra-tumor heterogeneity with 5 distinct subsets were defined in tumor samples. The malignant cells displayed variable degree of aneuploidy, which can be classified into low- and high-copy number variation groups based on either amplification or deletion of chr17q12 - chr17q21.2. Additionally, we identified 4 distinct T lymphocytes subsets, of which cytotoxic CD8+ T cells predominated as effectors in tumor tissues, whereas tumor infiltrating FOXP3+ CD4+ regulatory T cells exhibited highly immunosuppressive characteristics. Conclusion: Our single-cell transcriptomic dataset depicts the inter- and intra-tumor heterogeneity of human dCCAs at the expression level.

As a new and useful decision tool, interval-valued q-rung orthopair fuzzy set (IVq-ROFS), has strong ability to address uncertain or imprecision information in practical decision-making processes. This paper develops a new interval-valued q-rung orthopair fuzzy QUALIFLEX decision analysis method with Dombi operators for handling the group decision-making problems with IVq-ROFSs data. We also conduct a case study on the health management of hypertensive patients for demonstrating the feasibility and superiority of the developed method. The main contributions of this paper are as follows: (1) we first propose interval-valued q-rung orthopair fuzzy Dombi operational laws and investigate their desirable properties; (2) using the developed Dombi operational laws, we develop an interval-valued q-rung orthopair fuzzy Dombi weighted average (IVq-ROFDWA) operator, and we prove that the IVq-ROFDWA operator satisfies the properties of idempotency, commutativity, boundedness, and monotonicity; (3) we introduce the concept of interval-valued q-rung orthopair fuzzy ideal group opinions with the help of IVq-ROFDWA operator and propose a new weight-determining method for identifying the weights of experts; (4) we develop a new interval-valued q-rung orthopair fuzzy distance measure. With the help of the developed distance measure, we calculate interval-valued q-rung orthopair fuzzy concordance/discordance index under each permutation, and then a new interval-valued q-rung orthopair fuzzy QUALIFLEX decision analysis method is developed for addressing the complex multiattribute group decision-making problems with IVq-ROFSs.

Objectives. We aimed to investigate the effects of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor on blood lipid levels in patients with high and very-high cardiovascular risk. Design. 14 trials (n = 52,586 patients) comparing treatment with or without PCSK9 inhibitors were retrieved from PubMed and Embase updated to 1st Jun 2021. The data quality of included studies was assessed by two independent researchers using the Cochrane systematic review method. All-cause mortality, cardiovascular mortality, and changes in serum low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG), apolipoprotein B (ApoB), lipoprotein (a) (LP (a)), non-high-density lipoprotein cholesterol (non-HDL-C), high-density lipoprotein cholesterol (HDL-C), and apolipoprotein A1 (ApoA1) from baseline were analyzed using Rev Man 5.1.0 software. Results. Compared with treatments without PCSK9 inhibitor, addition of PCSK9 inhibitors (evolocumab and alirocumab) had obvious decreasing effects on the levels of LDL-C [MD = −46.86, 95% CI (−54.99 to −38.72), P