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Abstract Accurate consumption forecasting is of great importance to grasp the energy consumption habits of consumers and promote the stable and efficient operation of integrated energy system (IES). To this end, this paper proposes an interactive multi-scale convolutional module-based short-term multi-energy consumption forecasting method for IES. Firstly, based on multi-scale feature fusion and multi-energy interactive learning, a novel interactive multi-scale convolutional module is proposed to extract and share the coupling information between energy consumption from different scales without increasing network parameters. Then, a short-term multi-energy consumption forecasting method is proposed, where different forecasting network structures are selected in different seasons to make full use of seasonal and coupling characteristics of the energy consumption, thus enhancing prediction performance. Furthermore, a Laplace distribution-based loss function weight optimization method is proposed to dynamically balance the loss magnitude and training speed of joint forecast tasks more robustly. Finally, the effectiveness and superiority of the proposed method are verified by comparative simulation experiments.

Abstract Endometrial cancer (UCEC) is one of three major malignant tumors in women. The HOX gene regulates tumor development. However, the potential roles of HOX in the expression mechanism of multiple cell types and in the development and progression of tumor microenvironment (TME) cell infiltration in UCEC remain unknown. In this study, we utilized both the The Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC) database to analyze transcriptome data of 529 patients with UCEC based on 39 HOX genes, combing clinical information, we discovered HOX gene were a pivotal factor in the development and progression of UCEC and in the formation of TME diversity and complexity. Here, a new scoring system was developed to quantify individual HOX patterns in UCEC. Our study found that patients in the low HOX score group had abundant anti-tumor immune cell infiltration, good tumor differentiation, and better prognoses. In contrast, a high HOX score was associated with blockade of immune checkpoints, which enhances the response to immunotherapy. The Real-Time quantitative PCR (RT-qPCR) and Immunohistochemistry (IHC) exhibited a higher expression of the HOX gene in the tumor patients. We revealed that the significant upregulation of the HOX gene in the epithelial cells can activate signaling pathway associated with tumour invasion and metastasis through single-cell RNA sequencing (scRNA-seq), such as nucleotide metabolic proce and so on. Finally, a risk prognostic model established by the positive relationship between HOX scores and cancer-associated fibroblasts (CAFs) can predict the prognosis of individual patients by scRNA-seq and transcriptome data sets. In sum, HOX gene may serve as a potential biomarker for the diagnosis and prediction of UCEC and to develop more effective therapeutic strategies.

In China, the energy consumption in the building sector has increased tremendously in the past decades. It is important to investigate advanced passive energy-saving technologies for buildings. By applying phase-change materials in walls, the peak cooling/heating load can be significantly reduced. In the present study, a numerical model of one-dimensional heat transfer within a phase-change wall was developed and solved by Matlab, which was successfully validated with published data. Subsequently, the model was used to simulate the thermal performance of a phase-change wall in a hotel building in Shanghai, China. Simulation results demonstrate that the performance of the phase-change wall is optimized when the phase-change material is applied to both sides of the wall. Year-round heat transfer is minimized using layers of paraffin (C16-C28) and capric acid (2 cm), with phase-change temperatures of 43℃ and 16.3℃, respectively. The PCM wall reduces inwardthe inward heat transfer by 26.9% compared with a common wall without phase-change material. The outward heat loss is also reduced by 15.7% during the heating season. This study demonstrates that the PCM wall can effectively reduce indoor heat gain in summerin the summer and heat loss in winterin the winter. The numerical model has proven to be feasible for optimizing construction design.

Crocus sativus (saffron) is a globally autumn-flowering plant, and its stigmas are the most expensive spice and valuable herb medicine. Crocus specialized metabolites, crocins, are biosynthesized in distant species, Gardenia (eudicot) and Crocus (monocot), and the evolution of crocin biosynthesis remains poorly understood. With the chromosome-level Crocus genome assembly, we revealed that two rounds of lineage-specific whole genome triplication occurred, contributing important roles in the production of carotenoids and apocarotenoids. According to the kingdom-wide identification, phylogenetic analysis, and functional assays of carotenoid cleavage dioxygenases (CCDs), we deduced that the duplication, site positive selection, and neofunctionalization of Crocus-specific CCD2 from CCD1 members are responsible for the crocin biosynthesis. In addition, site mutation of CsCCD2 revealed the key amino acids, including I143, L146, R161, E181, T259, and S292 related to the catalytic activity of zeaxanthin cleavage. Our study provides important insights into the origin and evolution of plant specialized metabolites, which are derived by duplication events of biosynthetic genes.

Abstract Background In this study, we investigated the effects of alpine meadow in different phenological periods on ruminal fermentation, serum biochemical indices, and gastrointestinal tract microbes in grazing yak on the Qinghai-Tibetan Plateau. A total of eighteen female freely grazing yaks with an average age of 3 years old and a body weight of 130 ± 19 kg were selected. According to the plant phenological periods, yaks were randomly allocated to one of three treatments: (1) regreen periods group (RP, n = 6); (2) grassy periods group (GP, n = 6); and (3) hay periods group (HP, n = 6). At the end of the experiment, the blood, rumen fluids, and rectal contents were collected to perform further analysis. Results The concentrations of total volatile fatty acid (TVFA), acetate, glucose (GLU), triglyceride (TG), cholesterol (CHO), high density lipoprotein (HDL), and low density lipoprotein (LDL) were higher in the GP group than in the HP group (P

Abstract Cepharanthine is a secondary metabolite isolated from Stephania. It has been reported that it has anti-conronaviruses activities including severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Here, we assemble three Stephania genomes (S. japonica, S. yunnanensis, and S. cepharantha), propose the cepharanthine biosynthetic pathway, and assess the antiviral potential of compounds involved in the pathway. Among the three genomes, S. japonica has a near telomere-to-telomere assembly with one remaining gap, and S. cepharantha and S. yunnanensis have chromosome-level assemblies. Following by biosynthetic gene mining and metabolomics analysis, we identify seven cepharanthine analogs that have broad-spectrum anti-coronavirus activities, including SARS-CoV-2, Guangxi pangolin-CoV (GX_P2V), swine acute diarrhoea syndrome coronavirus (SADS-CoV), and porcine epidemic diarrhea virus (PEDV). We also show that two other genera, Nelumbo and Thalictrum, can produce cepharanthine analogs, and thus have the potential for antiviral compound discovery. Results generated from this study could accelerate broad-spectrum anti-coronavirus drug discovery.

Measuring causal brain network is a significant topic for exploring complex brain functions. While various data-driven algorithms have been proposed, they still have some drawbacks such as ignoring time non-separability, cumbersome parameter settings, and poor robustness. To solve these deficiencies, we developed a novel framework: “time-shift permutation cross-mapping, TPCM,” integrating steps of: (1) delayed improved phase-space reconstruction (DIPSR), (2) rank transformation of embedding vectors’ distances, (3) cross-mapping with a fitting estimation, and (4) causality quantification using multi-delays. Based on the synthetic models and comparison with baseline methods, numerical validation results demonstrate that TPCM significantly improves the robustness for data length with or without noise interference, and achieves the best quantification accuracy in detecting time delay and coupling strength, with the highest determination coefficient ( ${R}^{{2}}={0}.{96}\text {)}$ of fitting verse coupling parameters. The developed TPCM was finally applied to ictal electrocorticogram (ECoG) analysis of patients with drug-resistant epilepsy (DRE). A total of 17 patients with DRE were included into the retrospective study. For 8 patients undergoing successful surgeries, the causal coupling strength ( $0.58~\pm ~0.20$ ) within epileptogenic zone network is significantly higher than those suffering failed surgeries ( $0.38~\pm ~0.16$ ) with ${P}\lt {0}. {001}$ through Mann-Whitney-U-test. Therefore, the epileptic brain network measured by TPCM is a credible biomarker for predicting surgical outcomes. These findings additionally confirm TPCM’s superior performance and promising potential to advance precision medicine for neurological disorders.

Mutton is one of the most popular meats among the general public due to its high nutritional value. This study evaluated the differences in meat quality among Chaka (CK), Black Tibetan (BT) and Oula (OL) sheep and investigated the metabolic mechanisms affecting meat quality using targeted and untargeted metabolomics and 16S rRNA. The results showed that the meat quality of CK sheep was superior to that of BT and OL sheep in terms of meat color, muscle fiber characteristics and nutritional quality. Pseudobutyrivibrio, Alloprevotella, Methanobrevibacter, unidentified_Christensenellaceae, and unidentified_Bacteroidales were key microbes involved in regulating meat color, muscle fiber characteristics, amino acid and fatty acid content. Protein digestion/absorption, pentose phosphate metabolism, carbon metabolism, and glyoxylate and dicarboxylate metabolism were important metabolic pathways involved in meat quality regulation. Our study is important for the development of sheep breeding strategy and sheep meat industry in Qinghai-Tibetan Plateau.

Abstract Chronic hepatitis B (CHB) remains a major public health concern because of the inefficiency of currently approved therapies in clearing the hepatitis B surface antigen (HBsAg). Antibody‐based regimens have demonstrated potency regarding virus neutralization and HBsAg clearance. However, high dosages or frequent dosing are required for virologic control. In this study, a dual‐domain‐engineered anti‐hepatitis B virus (HBV) therapeutic antibody 73‐DY is developed that exhibits significantly improved efficacy regarding both serum and intrahepatic viral clearance. In HBV‐tolerant mice, administration of a single dose of 73‐DY at 2 mg kg−1 is sufficient to reduce serum HBsAg by over 3 log10 IU mL−1 and suppress HBsAg to < 100 IU mL−1 for two weeks, demonstrating a dose‐lowering advantage of at least tenfold. Furthermore, 10 mg kg−1 of 73‐DY sustainably suppressed serum viral levels to undetectable levels for ≈ 2 weeks. Molecular analyses indicate that the improved efficacy exhibited by 73‐DY is attributable to the synergy between fragment antigen binding (Fab) and fragment crystallizable (Fc) engineering, which conferred sustained viral suppression and robust viral eradication, respectively. Long‐term immunotherapy with reverse chimeric 73‐DY facilitated the restoration of anti‐HBV immune responses. This study provides a foundation for the development of next‐generation antibody‐based CHB therapies.

Abstract Background It is very common for patients with newly diagnosed lung masses to have heart disease. However, papillary fibroelastomas (PFEs) of the tricuspid valve (TV) combined with lung cancer are rarely reported. It is thus unclear whether a two-stage surgery or concomitant surgery is optimal. Case presentation We report the case of a 73-year-old Chinese male who was diagnosed with PFEs on the TV by transthoracic echocardiography (TTE) examination while being evaluated to undergo video-assisted thoracic surgery (VATS) for a right lower lung nodule. We resected both the PFEs and the lung nodule via right minithoracotomy. The surgery was uneventful, and histopathology reports confirmed PFEs of the TV and moderately to poorly differentiated squamous cell carcinoma. The patient recovered uneventfully, and there was no sign of tumor recurrence during 15 months of follow-up. Conclusions We suggest that after careful evaluation, concomitant minimally invasive radical resection of primary lung cancer after cardiac PFE removal is an acceptable and safe treatment strategy and should be performed as soon as possible.

Abstract Background Heart failure (HF) seriously threatens human health worldwide. However, the pathological mechanisms underlying HF are still not fully clear. Results In this study, we performed proteomics and transcriptomics analyses on samples from human HF patients and healthy donors to obtain an overview of the detailed changes in protein and mRNA expression that occur during HF. We found substantial differences in protein expression changes between the atria and ventricles of myocardial tissues from patients with HF. Interestingly, the metabolic state of ventricular tissues was altered in HF samples, and inflammatory pathways were activated in atrial tissues. Through analysis of differentially expressed genes in HF samples, we found that several glutathione S-transferase (GST) family members, especially glutathione S-transferase M2-2 (GSTM2), were decreased in all the ventricular samples. Furthermore, GSTM2 overexpression effectively relieved the progression of cardiac hypertrophy in a transverse aortic constriction (TAC) surgery-induced HF mouse model. Moreover, we found that GSTM2 attenuated DNA damage and extrachromosomal circular DNA (eccDNA) production in cardiomyocytes, thereby ameliorating interferon-I-stimulated macrophage inflammation in heart tissues. Conclusions Our study establishes a proteomic and transcriptomic map of human HF tissues, highlights the functional importance of GSTM2 in HF progression, and provides a novel therapeutic target for HF.

Abstract The composite insulation composed of cross‐linked polyethylene (XLPE) and silicone rubber (SiR) is common in high voltage direct current cable accessory installation. However, the space charge accumulation, especially the interfacial charge accumulation of XLPE/SiR, poses a serious threat to the safe operation of cable accessories, and its charge transport mechanism is still unclear, especially at the micro‐scale. In order to investigate the charge transport mechanism of XLPE/SiR, simultaneous measurement of space charge and relaxation current is performed on XLPE/SiR at various electric fields with different polarities, and the electronic energy levels of XLPE and SiR are determined by quantum chemical calculation (QCC). The results of QCC show that both the hole traps and the electron traps in XLPE are mainly shallow traps. As for SiR, the hole traps are shallow traps, while the electron traps are deep traps. The results of simultaneous measurement show that the interfacial charge accumulation and the composite conductivity of XLPE/SiR are significantly different under different polarities, that is, there is an obvious polarity effect. Based on the results of QCC, the electronic energy levels of XLPE/SiR system are constructed considering the interface between XLPE and SiR, as well as the interfaces between the materials and the electrodes. On this basis, the charge transport mechanism of XLPE/SiR is discussed in detail, and the polarity effect is well explained, which is believed to be related to the differences in the charge injection barrier and the interfacial barrier under different polarities, as well as the electron/hole traps in XLPE and SiR.

Abstract Background Redo heart surgery has become increasingly common but involves additional high surgical risk, especially redo surgery after coronary artery bypass grafting (CABG). Case presentation In this study, we report the case of a 57-year-old Chinese male with left atrium myxoma who had previously undergone CABG. Common surgical methods usually include aortic cross-clamping, administering cold cardioplegia perfusion to protect the myocardium, opening the heart, and then removing the tumor. However, for patients with previous CABG, redo thoracotomy and ascending aortic cross-clamping present a greater risk of damage to the grafted vessels. In this study, we chose a right lateral mini-thoracotomy incision and hypothermia-induced ventricular fibrillation to minimize damage and avoid any adverse effects on the bridge vasculature. The patient recovered uneventfully and was discharged seven days after surgery. Conclusions For patients with previous CABG, minimally invasive right thoracotomy under perfused ventricular fibrillation with hypothermia is safe and reliable and can prevent potential damage to the ascending aorta and graft.

Many genetic loci for wheat plant height (PH) have been reported, and 26 dwarfing genes have been catalogued. To identify major and stable genetic loci for PH, here we thoroughly summarized these functionally or genetic verified dwarfing loci from QTL linkage analysis and genome-wide association study published from 2003 to 2022. A total of 332 QTL, 270 GWAS loci and 83 genes for PH were integrated onto chromosomes according to their locations in the IWGSC RefSeq v2.1 and 65 QTL-rich clusters (QRC) were defined. Candidate genes in each QRC were predicted based on IWGSC Annotation v2.1 and the information on functional validation of homologous genes in other species. A total of 38 candidate genes were predicted for 65 QRC including three GA2ox genes in QRC-4B-IV, QRC-5A-VIII and QRC-6A-II (Rht24) as well as GA 20-oxidase 2 (TaSD1-3A) in QRC-3A-IV. These outcomes lay concrete foundations for map-based cloning of wheat dwarfing genes and application in breeding.

Two-dimensional layered molybdenum trioxide (MoO3) holds significant importance in optoelectronics owing to its unique anisotropic structure and optical properties. Given that changes in structure can profoundly impact physical characteristics, it becomes imperative to explore new properties by means of acquiring different structures. Here, we report the irreversibility of structural evolution and optical properties of molybdenum trioxide under high pressure. The quenched MoO3 possesses a stable high-pressure phase MoO3-II, a narrowed bandgap (reduced by ∼25%) and a strong optical absorption at visible to infrared region compared to the initial low-pressure phase α-MoO3. These findings will facilitate the exploring of high-pressure phase materials under ambient conditions.

To effectively address the mental health risks associated with public health emergencies, it is crucial to actively manage rumors. This study explores the dynamic evolutionary process of rumor diffusion and its collaborative governance in public health emergencies. A game-theoretic model is constructed, involving three main actors: regulators, parties involved in public health emergencies (PIPHE), and whistle-blowers. The behaviors and game outcomes of each party are analyzed, and the effectiveness and feasibility of the model are validated through numerical simulations. The findings of this study reveal that various factors, such as regulatory costs, penalty income, reputation damage for regulators; image loss, reputation enhancement, penalty expenditure for PIPHE; and time costs, social responsibility, and reward income for whistle-blowers, all influence the behavioral choices and game equilibrium of each party. Optimization strategies for rumor governance are proposed in this study, including enhancing the sense of responsibility and capability among regulators, increasing transparency and credibility among PIPHE, and encouraging and protecting the participation of whistle-blowers. This study provides a comprehensive analytical framework for rumor governance in public health emergencies, contributing to improving the governance of public health emergencies and maintaining online public health orders for social sustainability.

ABSTRACT Facial skin is more exposed to the outside environment, and it is usually affected by environmental factors. Characterization of the skin microbiome and metabolome of individuals from different geographic regions will help to understand the factors behind the prevalence of skin disorders and support skincare product development. In the current study, volunteers from northern, southern, and northwestern China were recruited. Facial skin samples were collected for amplicon sequencing and metabolomic liquid chromatography‒mass spectrometry (LC–MS/MS) analyses. We demonstrated significant alterations in the abundances of multiple microorganisms and skin lipid compositions between individuals. People living in the northwest, which has a dry climate and high altitude, showed lower level of total lipids, and lower abundance of Malassezia, but higher levels of ceramides and fatty acids. Malassezia had a positive correlation with eicosanoids and a negative correlation with ceramides. This work highlights the effects of geographic factors on the skin microbial structures and skin lipids. IMPORTANCE Characterization of the skin microbiome and metabolome across geography will help uncover the climate factors behind the prevalence of skin disorders and provide suggestions for skincare products for people living in different geographic regions.

Nonmydriatic retinal fundus images often suffer from quality issues and artifacts due to ocular or systemic comorbidities, leading to potential inaccuracies in clinical diagnoses. In recent times, deep learning methods have been widely employed to improve retinal image quality. However, these methods often require large datasets and lack robustness in clinical settings. Conversely, the inherent stability and adaptability of traditional unsupervised learning methods, coupled with their reduced reliance on extensive data, render them more suitable for real-world clinical applications, particularly in the limited data context of high noise levels or a significant presence of artifacts. However, existing unsupervised learning methods encounter challenges such as sensitivity to noise and outliers, reliance on assumptions like cluster shapes, and difficulties with scalability and interpretability, particularly when utilized for retinal image enhancement. To tackle these challenges, we propose a novel robust PCA (RPCA) method with low-rank sparse decomposition that also integrates affine transformations τi, weighted nuclear norm, and the L2,1 norms, aiming to overcome existing method limitations and to achieve image quality improvement unseen by these methods. We employ the weighted nuclear norm (Lw,∗) to assign weights to singular values to each retinal images and utilize the L2,1 norm to eliminate correlated samples and outliers in the retinal images. Moreover, τi is employed to enhance retinal image alignment, making the new method more robust to variations, outliers, noise, and image blurring. The Alternating Direction Method of Multipliers (ADMM) method is used to optimally determine parameters, including τi, by solving an optimization problem. Each parameter is addressed separately, harnessing the benefits of ADMM. Our method introduces a novel parameter update approach and significantly improves retinal image quality, detecting cataracts, and diabetic retinopathy. Simulation results confirm our method’s superiority over existing state-of-the-art methods across various datasets.

The laying of power cables is a crucial aspect of developing and maintaining modern electrical infrastructure, which is vital for transmitting electricity reliably and efficiently. This review discusses the challenges and advancements in cable laying technologies, emphasizing the critical role of these techniques in meeting the increasing demands for power transmission in the backdrop of the global shift to renewable energy. Three main traditional cable laying methods are explored, including underground, overhead, and submarine, each suited to specific environmental and operational conditions. Then, the cable faults due to the impropriate laying process are discussed. Subsequently, the challenges and advancements encountered in cable laying processes are investigated, especially the difficulties of the cable laying of underground cable, submarine cable, and high-temperature superconductivity cable. This review also considers the impact of technological innovations on improving efficiency in cable laying processes, highlighting the advances driven by digitalization and automation.

It has been shown that there are thresholds of influence on the response of ecosystem services to their drivers, and the range of drivers that provide high levels of ecosystem services can be delineated through thresholds. However, due to the spatial heterogeneity of landscapes in karst regions, the results of ecosystem service threshold studies in non-karst regions may not be applicable to karst regions. This study explores the threshold effects between ecosystem services in karst landscapes and their natural and social drivers. It is shown that there are nonlinear constraints between them, and different critical thresholds exist for different kinds of ecosystem services. The main thresholds for water supply services include the slope (43.64°) and relief amplitude (331.60 m); for water purification services, they include relief amplitude (147.05 m) and distance to urban land (DTUL) (32.30 km); for soil conservation services, they include the normalized difference vegetation index (NDVI) (0.80) and nighttime light intensity (43.58 nW∙cm−2∙sr−1); the main thresholds for biodiversity maintenance services include population density (1481.06 person∙km−2) and distance to urban land (DTUL) (32.80 km). This enables regional ecological conservation planning based on different threshold ranges corresponding to different ecosystem services to meet the different needs of different decision makers.

Obstructive Sleep Apnea (OSA), a sleep disorder with high prevalence, is normally accompanied by affective, autonomic, and cognitive abnormalities, and is deemed to be linked to functional brain alterations. To investigate alterations in brain functional connectivity properties in patients with OSA, a comparative analysis of global and local topological properties of brain networks was conducted between patients with OSA and healthy controls (HCs), utilizing functional near-infrared spectroscopy (fNIRS) imaging. A total of 148 patients with OSA and 150 healthy individuals were involved. Firstly, quantitative alterations in blood oxygen concentration, changes in functional connectivity, and variations in graph theory-based network topological characteristics were assessed. Then, with Mann–Whitney statistics, this study compared whether there are significant differences in the above characteristics between patients with OSA and HCs. Lastly, the study further examined the correlation between the altered characteristics and the apnea hypopnea index (AHI) using linear regression. Results revealed a higher mean and standard deviation of hemoglobin concentration in the superior temporal gyrus among patients with OSA compared to HCs. Resting-state functional connectivity (RSFC) exhibited a slight increase between the superior temporal gyrus and other specific areas in patients with OSA. Notably, neither patients with OSA nor HCs demonstrated significant small-world network properties. Patients with OSA displayed an elevated clustering coefficient (p < 0.05) and local efficiency (p < 0.05). Additionally, patients with OSA exhibited a tendency towards increased nodal betweenness centrality (p < 0.05) and degree centrality (p < 0.05) in the right supramarginal gyrus, as well as a trend towards higher betweenness centrality (p < 0.05) in the right precentral gyrus. The results of multiple linear regressions indicate that the influence of the AHI on RSFC between the right precentral gyrus and right superior temporal gyrus (p < 0.05), as well as between the right precentral gyrus and right supramarginal gyrus (p < 0.05), are statistically significant. These findings suggest that OSA may compromise functional brain connectivity and network topological properties in affected individuals, serving as a potential neurological mechanism underlying the observed abnormalities in brain function associated with OSA.

Abstract Background Pancreatic cancer (PAC), a malignancy that is fatal and commonly diagnosed at a late stage. Despite considerable advancements in cancer treatment, the survival rate of PAC remains largely consistent for the past 60 years. The traditional Chinese medicine formula Pulsatilla Decoction (PD) has been clinically used to treat inflammatory diseases for millennia and recently as a supplementary anti-cancer treatment in China. However, the bioactive ingredients and mechanisms underlying its anti-cancer effect remains unclear. Methods The composition and quality control of PD were verified through analysis by high performance liquid chromatography. Cell viability was determined using Cell Counting Kit-8 assay. The cell cycle distribution was analyzed through PI staining and flow cytometry analysis, while apoptotic cells were measured by double staining with Annexin V-FITC and PI. We used immunoblotting to examine protein expressions. The in vivo effects of β-peltatin and podophyllotoxin were evaluated on a subcutaneously-xenografted BxPC-3 cell nude mice model. Results The current study demonstrated that PD markedly inhibited PAC cell proliferation and triggered their apoptosis. Four herbal PD formula was then disassembled into 15 combinations of herbal ingredients and a cytotoxicity assay showed that the Pulsatillae chinensis exerted the predominant anti-PAC effect. Further investigation indicated that β-peltatin was potently cytotoxic with IC50 of ~ 2 nM. β-peltatin initially arrested PAC cells at G2/M phase, followed by apoptosis induction. Animal study confirmed that β-peltatin significantly suppressed the growth of subcutaneously-implanted BxPC-3 cell xenografts. Importantly, compared to podophyllotoxin that is the parental isomer of β-peltatin but clinically obsoleted due to its severe toxicity, β-peltatin exhibited stronger anti-PAC effect and lower toxicity in mice. Conclusions Our results demonstrate that Pulsatillae chinensis and particularly its bioactive ingredient β-peltatin suppress PAC by triggering cell cycle arrest at G2/M phase and apoptosis.

The accuracy of carbon emission data is essential for various disciplines to maintain reasonable expectations and certainty regarding the carbon emission rights trading market. However, the management of carbon emission data quality faces many challenges, especially due to the harmful behavior of enterprises that falsify such data, which seriously disrupts the order and credibility of the carbon market. Currently, few studies focus on the behavior and mechanism of corporate carbon emission data fraud, which requires an in-depth stakeholder analysis to obtain theoretical and empirical support for the formulation of effective regulatory policies. To investigate the influence of government regulation and media monitoring on addressing enterprise carbon emission data falsification, as well as to analyze the game behaviors and equilibrium outcomes among the government, media, and enterprises under different policy combinations and market environments, this study develops an evolutionary game model incorporating the government, media, and enterprises as three key stakeholders. Furthermore, numerical simulations are conducted for empirical validation. The key findings of this research highlight the significant impact of government regulation and media monitoring on deterring enterprise carbon emission data falsification, thus effectively reducing falsification motives and behaviors and enhancing the quality of carbon emission data. Additionally, the game between the government, media, and enterprises reveals the existence of multiple evolutionary stable strategies. Of these, the optimal strategy is the comprehensive implementation of all three elements: government regulation, media monitoring, and corporate integrity disclosure. This paper comprehensively examines the influence of government regulation and media monitoring on enterprise carbon emission data falsification and addresses the gaps in existing research. Moreover, it provides theoretical guidance and policy recommendations for establishing a high-quality carbon market.

The senescence of adipose stem cells (ASCs) impairs healthy adipose tissue remodeling, causing metabolic maladaptation to energy surplus. The intrinsic molecular pathways and potential therapy targets for ASC senescence are largely unclear. Here, we showed that visceral ASCs were prone to senescence that was caused by reactive oxygen species (ROS) overload, especially mitochondrial ROS. These senescent ASCs failed to sustain efficient glucose influx, pentose phosphate pathway (PPP) and redox homeostasis. We showed that CD90 silence restricted the glucose uptake by ASCs and thus disrupted their PPP and anti-oxidant system, resulting in ASC senescence. Notably, fibroblast growth factor 21 (FGF21) treatment significantly reduced the senescent phenotypes of ASCs by augmenting CD90 protein via glycosylation, which promoted glucose influx via the AKT-GLUT4 axis and therefore mitigated ROS overload. For diet-induced obese mice, chronic administration of low-dose FGF21 relieved their visceral white adipose tissue (VAT) dysfunction and systemic metabolic disorders. In particular, VAT homeostasis was restored in FGF21-treated obese mice, where ASC repertoire was markedly recovered, accompanied by CD90 elevation and anti-senescent phenotypes in these ASCs. Collectively, we reveal a molecular mechanism of ASC senescence by which CD90 downregulation interferes glucose influx into PPP and redox homeostasis. And we propose a FGF21-based strategy for healthy VAT remodeling, which targets CD90 glycosylation to correct ASC senescence and therefore combat obesity-related metabolic dysfunction.

KCNQ2 epileptic encephalopathy is relatively common in early-onset neonatal epileptic encephalopathy and seizure severity varied widely, categorized as drug-sensitive epilepsy and drug-resistant epilepsy. However, in clinical practice, anti-seizure medicines need to be gradually adjusted based on seizure control which undoubtedly increases the economic burden of patients, so further positive anti-seizure regimens depend on whether seizure severity can be predicted in advance. In this paper, we proposed a reliable assessment to differentiate between drug-sensitive epilepsy and drug-resistant epilepsy caused by KCNQ2 pathogenic variants. Based on the electroencephalogram (EEG) and electrooculogram (EOG) signals, twenty-four classical temporal and spectral domain features were extracted and Gradient Boosting Decision Tree (GBDT) was employed to distinguish between patients with drug-sensitive epilepsy and drug-resistant epilepsy. In addition, we also systematically investigated the impact of channel combination and feature combination based on the forward stepwise selection strategy. By employing selected channels and features, the classification accuracy can reach 81.25% with a sensitivity of 57.14% and specificity of 100%. Compared with the state-of-the-art techniques, including the functional network, effective network, and common spatial patterns, the improvement of accuracy ranges from 37.5% to 56.25%, indicating the superiority of our proposed method. Overall, the proposed method may provide a promising tool to distinguish different seizure outcomes of KCNQ2 epileptic encephalopathy.

Oxidative stress, which damages cellular components and causes mitochondrial dysfunction, occurs in a variety of human diseases, including neurological disorders. The clearance of damaged mitochondria via mitophagy maintains the normal function of mitochondria and facilitates cell survival. Astaxanthin is an antioxidant known to have neuroprotective effects, but the underlying mechanisms remain unclear. This study demonstrated that astaxanthin inhibited H2O2-induced apoptosis in SH-SY5Y cells by ameliorating mitochondrial damage and enhancing cell survival. H2O2 treatment significantly reduced the levels of activated Akt and mTOR and induced mitophagy, while pretreatment with astaxanthin prevented H2O2-induced inhibition of Akt and mTOR and attenuated H2O2-induced mitophagy. Moreover, the inhibition of Akt attenuated the protective effect of astaxanthin against H2O2-induced cytotoxicity. Taken together, astaxanthin might inhibit H2O2-induced apoptosis by protecting mitochondrial function and reducing mitophagy. The results also indicate that the Akt/mTOR signaling pathway was critical for the protection of astaxanthin against H2O2-induced cytotoxicity. The results from the present study suggest that astaxanthin can reduce neuronal oxidative injury and may have the potential to be used for preventing neurotoxicity associated with neurodegenerative diseases.

Metformin is the first-line drug to treatment of type 2 diabetes mellitus. Recently, clinical and preclinical studies have been investigated the therapeutic effect of metformin in hair disorders. Metformin can improve hyperandrogenemia-induced hirsutism by reducing circulating insulin concentrations and inhibiting androgen levels. In addition, it has therapeutic effects on telogen alopecia and cicatricial alopecia by promoting scalp hair regeneration throughactivation of multiple mechanisms such as AMP-activated protein kinase pathway. This review aims to presentclinical applications and the potential therapeutic mechanisms of metformin in the treatment of hair diseases.

Understanding the response of soil moisture of different vegetation types to rainfall in karst regions in winter is significant for implementing various ecological restoration projects. However, at present, the related research is mainly focused on non-winter seasons, and only few research exist on winter seasons. Therefore, in this study, four types of vegetation – grassland, arable land, shrubland, and forestland – were selected as sample plots in the Guanling County of southwestern Guizhou, China. The magnitude, time, and speed responses of soil moisture of the vegetation types to rainfall were calculated using the time-series data of soil moisture of different vegetation types. The results showed that the response of soil moisture differed between different vegetation types in winter and non-winter seasons in karst areas. Among the four vegetation types, soil moisture response magnitude to rainfall in grassland and arable land had a similar distribution pattern along different soil depths, whereas in scrubland and forestland, it decreased gradually along the soil depth. In addition, compared with other vegetation types, for grassland soil moisture, the response magnitude, response duration, and response speed to rainfall are the largest, longest, and fastest, respectively. Our study used quantitative indices to illustrate the response of soil moisture to rainfall for different vegetation types under a humid climate in a mid-subtropical zone on sloped, pure limestone land. The results of this study provide a scientific basis for the implementation of ecological restoration projects in karst areas. HIGHLIGHTS Grassland, arable land, shrubland, and forestland were studied in karst regions during winter.; Grassland rainfall response magnitude, duration, and speed were largest, longest, and fastest, respectively.; Soil moisture increment of arable land significantly changed.; Water holding capacity of shrubland and forestland was relatively poor.; Grassland and arable land had relatively small interception effects.;

Background Low attenuation area ratio (LAA%) and pectoral major parameters are in elderly patients with COPD related to pulmonary ventilation function, but there are few studies at home and abroad. Objective To analyze the correlation of LAA% and pectoral major parameters with impaired pulmonary ventilation function in elderly patients with COPD, and to explore the predictive value of LAA% and PMcsa in the severity of airflow restriction, in order to provide clinical basis for the early detection and diagnosis of COPD. Methods A total of 270 elderly patients with stable COPD who underwent chest CT and lung function examination in North Jiangsu People's Hospital affiliated to Yangzhou University from December 2019 to June 2021 were selected and divided into GOLDⅠgroup (FEVl%pred≥80%, n=47) , GOLD Ⅱgroup (50%≤FEVl%pred

Abstract The 2050 carbon‐neutral vision spawns a novel energy structure revolution, and the construction of the future energy structure is based on equipment innovation. Insulating material, as the core of electrical power equipment and electrified transportation asset, faces unprecedented challenges and opportunities. The goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first discussed. The engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are investigated. Insulating materials, including intelligent insulating material, high thermal conductivity insulating material, high energy storage density insulating material, extreme environment resistant insulating material, and environmental‐friendly insulating material, are categorised with their scientific issues, opportunities and challenges under the goal of carbon neutrality being discussed. In the context of carbon neutrality, not only improves the understanding of the insulation problems from a macro level, that is, electrical power equipment and electrified transportation asset, but also offers opportunities, remaining issues and challenges from the insulating material level. It is hoped that this paper envisions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality rules. The authors also hope that this paper can be helpful in future development and research of novel insulating materials, which promote the realisation of the carbon‐neutral vision.

Summary: High-field functional magnetic resonance imaging generates in vivo retinotopic maps, but quantifying them remains challenging. Here, we present a pipeline based on conformal geometry and Teichmüller theory for the quantitative characterization of human retinotopic maps. We describe steps for cortical surface parameterization and surface-spline-based smoothing. We then detail Beltrami coefficient-based mapping, which provides a quantitative and re-constructible description of the retinotopic maps. This framework has been successfully used to analyze the Human Connectome Project’s V1 retinotopic maps.For complete details on the use and execution of this protocol, please refer to Ta et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Summary: Adipose-derived stem cells (ASCs) drive healthy visceral adipose tissue (VAT) expansion via adipocyte hyperplasia. Obesity induces ASC senescence that causes VAT dysfunction and metabolic disorders. It is challenging to restrain this process by biological intervention, as mechanisms of controlling VAT ASC senescence remain unclear. We demonstrate that a population of CX3CR1hi macrophages is maintained in mouse VAT during short-term energy surplus, which sustains ASCs by restraining their senescence, driving adaptive VAT expansion and metabolic health. Long-term overnutrition induces diminishment of CX3CR1hi macrophages in mouse VAT accompanied by ASC senescence and exhaustion, while transferring CX3CR1hi macrophages restores ASC reservoir and triggers VAT beiging to alleviate the metabolic maladaptation. Mechanistically, visceral ASCs attract macrophages via MCP-1 and shape their CX3CR1hi phenotype via exosomes; these macrophages relieve ASC senescence by promoting the arginase1-eIF5A hypusination axis. These findings identify VAT CX3CR1hi macrophages as ASC supporters and unravel their therapeutic potential for metabolic maladaptation to obesity.

Diets(饮食) rich in fat are a major(主要) cause(原因) of metabolic disease(疾病), and nutritional(营养) food has been widely(广泛) used(使用) to counteract the metabolic disorders such(这样) as obesity(肥胖) and fatty(脂肪) liver(肝). The present study investigated the effects of oleuropein-enriched extract(提取物) from Jasminum grandiflorum L. flowers (OLE-JGF) in high-fat diet(饮食) (HFD)-fed mice and oleic acid(酸) (OA)-treated AML-12 cells. Treatment(治疗) of HFD-fed mice with 0.6% OLE-JGF for 8 weeks significantly reduced body and liver(肝) weights, as well as attenuating lipid dysmetabolism and hepatic steatosis. OLE-JGF administration(政府当局) prominently suppressed the mRNA expressions(表达) of monocyte chemoattractant protein(蛋白)-1 (MCP-1) and cluster of differentiation 68 (CD68), and it also downregulated acetyl-CoA carboxylase (ACC) and fatty(脂肪) acid(酸) synthase (FAS) as well as sterol-regulatory-element(元素)-binding protein(蛋白) (SREBP-1c) in the liver(肝). Meanwhile, mitochondrial DNA and uncoupling protein(蛋白) 2 (UCP2) were upregulated along with the increased expression(表达) of mitochondrial biogenic promoters including liver(肝) kinase B1 (LKB1), peroxisome proliferator–activated receptor-γ coactivator-1α (PGC-1α), nuclear(核) factor(因子)-erythroid-derived 2-like 2 (Nrf2), and mitochondrial transcription factor(因子) A (Tfam), but did not change AMP-activated protein(蛋白) kinase (AMPK) in liver(肝). The lipid droplets were decreased significantly after treatment(治疗) with 80 μM oleuropein for 24 h in OA-induced AML-12 cells. Furthermore, oleuropein significantly inhibited ACC mRNA expression(表达) and upregulated LKB1, PGC-1α, and Tfam mRNA levels, as well as increasing the binding level of LKB1 to PGC-1α promoter in OA-induced cells. These findings indicate(表明) that OLE-JGF reduces hepatic lipid deposition in HFD-fed mice, as well as the fact that OA-induced liver(肝) cells may be partly(部分) attributed to upregulation of the LKB1-PGC-1α axis, which mediates hepatic lipogenesis and mitochondrial biogenesis. Our study provides a scientific(科学) basis(基础) for the benefits and potential(潜在) use(使用) of the J. grandiflorum flower as a food supplement(补充) for the prevention(预防) and treatment(治疗) of metabolic disease(疾病).

To overcome the limitations of long-term prediction of PM2.5 concentration, a multi-factor information flow causality analysis method is used to screen suitable meteorological and air pollutant-related factors and concatenate them with a PM2.5 sequence as the dataset. A modal decomposition algorithm is used as a module to be integrated into the autoformer (transformer improved with autocorrelation mechanism) model to improve it, and the modal autoformer (empirical modal decomposition combined with autoformer) is proposed. The constructed model decomposes the sequence into several components by using the modal decomposition module and uses the self-correlation mechanism and decomposition structure to decompose and extract features of different components at the time-feature level. Based on the matching method, the model is adjusted for different component features to improve the long-term prediction effect. The model is applied to three cities in Henan Province, Zhengzhou, Luoyang, and Zhumadian, as examples for experiments, and gated neural unit (GRU), informer, autoformer, and modal GRU (empirical modal decomposition combined with GRU model) are constructed for comparative verification. The results show that the modal autoformer can better cope with the complex characteristics of long-term prediction of the PM2.5 time series, has strong spatial adaptability and that its various indicators are optimal for the three cities, with R2 values being all above 0.96, where the highest is 0.987 in Zhengzhou; MAPE (Mean absolute percentage error) values all being less than 10, where the best is 7.602 in Zhumadian; and MAE (Mean absolute error) values all being less than 4. The prediction effect is stable enough, showing its feasibility and adaptability in long-term prediction.

The Isothermal Relaxation Current (IRC) method, as a non-destructive condition evaluation method based on insulation dielectric response, has been applied in the maintenance of power cables. However, the relaxation current is usually conducted through the outer shield of the high-voltage wire, which will introduce the extra depolarization current into the test circuit, affecting the accuracy of the test results. Furthermore, most IRC cable measurements are single-phase, which means depolarization currents are measured for each cable separately. In order to improve the measurement accuracy and efficiency of the IRC test, this paper proposes an improved IRC measurement method based on an isolated circuit, which discharges the interference current from the high-voltage insulated wire back to the earth and reduces the measurement error of depolarization current. At the same time, a three-phase IRC simultaneous test system is designed, and the control software is developed. Furthermore, by verifying the accuracy of the test system, the independence of the single-phase circuit and the consistency of the three-phase circuit is achieved. The effect of depolarization time and temperature on the relaxation current is then explored to determine the suitable parameter of the IRC test. Finally, the IRC system is used to evaluate the aging state of 10 kV cables with various aging conditions in the air and water for the longest 12 months. Critical parameters such as aging factor and time constants are compared to investigate the aging characteristics of tested cables with various aging conditions in the air and water. The proposed method and research conclusions can provide helpful references for the non-destructive condition evaluation for high-voltage cable insulation.

Wheat coleoptile is a sheath-like structure that helps to deliver the first leaf from embryo to the soil surface. Here, a RIL population consisting of 245 lines derived from Zhou 8425B × Chinese Spring cross was genotyped by the high-density Illumina iSelect 90K assay for coleoptile length (CL) QTL mapping. Three QTL for CL were mapped on chromosomes 2BL, 4BS and 4DS. Of them, two major QTL QCL.qau-4BS and QCL.qau-4DS were detected, which could explain 9.1%–22.2% of the phenotypic variances across environments on Rht-B1 and Rht-D1 loci, respectively. Several studies have reported that Rht-B1b may reduce the length of wheat CL but no study has been carried out at molecular level. In order to verify that the Rht-B1 gene is the functional gene for the 4B QTL, an overexpression line Rht-B1b-OE and a CRISPR/SpCas9 line Rht-B1b-KO were studied. The results showed that Rht-B1b overexpression could reduce the CL, while loss-of-function of Rht-B1b would increase the CL relative to that of the null transgenic plants (TNL). To dissect the underlying regulatory mechanism of Rht-B1b on CL, comparative RNA-Seq was conducted between Rht-B1b-OE and TNL. Transcriptome profiles revealed a few key pathways involving the function of Rht-B1b in coleoptile development, including phytohormones, circadian rhythm and starch and sucrose metabolism. Our findings may facilitate wheat breeding for longer coleoptiles to improve seedling early vigor for better penetration through the soil crust in arid regions.

Objective:BOLA2B is a recently discovered protein-coding gene. Here, pan-cancer analysis was conducted to determine the expression patterns of BOLA2B and its impact on immune response, gene mutation, and possible molecular biological mechanisms in different tumors, together with investigating its potential usefulness for cancer prognosis.Methods: Data on BOLA2B expression and mutations were downloaded from TCGA and GTEx databases. Clinical survival data from TCGA were used to analyze the prognostic value of BOLA2B. TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.Results: BOLA2B was found to be highly expressed at both mRNA and protein levels in multiple tumors, where it was associated with worse overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in all cancers apart from ovarian cancer. BOLA2B was also found to be positively correlated with copy number variation (CNV), and mutations in TP53, TTN, and MUC16 were found to influence BOLA2B expression. Post-transcriptional modifications, including m5C, m1A, and m6A, were observed to regulate BOLA2B expression in all cancers. Functional analysis showed that BOLA2B was enriched in pathways associated with iron–sulfur cluster formation, mTOR-mediated autophagy, and cell cycle inhibition. Decreased BOLA2B expression induced the proliferation of breast cancer cells and G2/M cell cycle arrest.Conclusion:BOLA2B was found to be highly expressed in malignant tumors and could be used as a biomarker of poor prognosis in multiple cancers. Further investigation into BOLA2B’s role and molecular functions in cancer would provide new insights for cancer diagnosis and treatment.

Electrical status epilepticus during sleep (ESES) is an epileptic encephalopathy in children with complex clinical manifestations. It is accompanied by specific electroencephalography (EEG) patterns of continuous spike and slow-waves. Quantifying such EEG patterns is critical to the diagnosis of ESES. While most of the existing automatic ESES quantification systems ignore the morphological variations of the signal as well as the individual variability among subjects. To address these issues, this paper presents a hybrid expert system that dedicates to mimicking the decision-making process of clinicians in ESES quantification by taking the morphological variations, individual variability, and medical knowledge into consideration. The proposed hybrid system not only offers a general scheme that could propel a semi-auto morphology analysis-based expert decision model to a fully automated ESES quantification with biogeography-based optimization (BBO), but also proposes a more precise individualized quantification system to involve the personalized characteristics by adopting an individualized parameters-selection framework. The feasibility and reliability of the proposed method are evaluated on a clinical dataset collected from twenty subjects at Children’s Hospital of Fudan University, Shanghai, China. The estimation error for the individualized quantitative descriptor ESES is 0-4.32% and the average estimation error is 0.95% for all subjects. Experimental results show the presented system outperforms existing works and the individualized system significantly improves the performance of ESES quantification. The favorable results indicate that the proposed hybrid expert system for automatic ESES quantification is promising to support the diagnosis of ESES.

Abstract Background Heart rate (HR) is an important vital sign for evaluating the physiological condition of a newborn infant. Recently, for measuring HR, novel RGB camera-based non-contact techniques have demonstrated their specific superiority compared with other techniques, such as dopplers and thermal cameras. However, they still suffered poor robustness in infants’ HR measurements due to frequent body movement. Methods This paper introduces a framework to improve the robustness of infants’ HR measurements by solving motion artifact problems. Our solution is based on the following steps: morphology-based filtering, region-of-interest (ROI) dividing, Eulerian video magnification and majority voting. In particular, ROI dividing improves ROI information utilization. The majority voting scheme improves the statistical robustness by choosing the HR with the highest probability. Additionally, we determined the dividing parameter that leads to the most accurate HR measurements. In order to examine the performance of the proposed method, we collected 4 hours of videos and recorded the corresponding electrocardiogram (ECG) of 9 hospitalized neonates under two different conditions—rest still and visible movements. Results Experimental results indicate a promising performance: the mean absolute error during rest still and visible movements are 3.39 beats per minute (BPM) and 4.34 BPM, respectively, which improves at least 2.00 and 1.88 BPM compared with previous works. The Bland-Altman plots also show the remarkable consistency of our results and the HR derived from the ground-truth ECG. Conclusions To the best of our knowledge, this is the first study aimed at improving the robustness of neonatal HR measurement under motion artifacts using an RGB camera. The preliminary results have shown the promising prospects of the proposed method, which hopefully reduce neonatal mortality in hospitals.

Abstract Background Whether adjuvant chemotherapy (AC) after concurrent chemoradiotherapy (CCRT) could provide benefit to esophageal squamous cell carcinoma (ESCC) patients is controversial. Therefore, we decided to investigate the potential benefit of AC after CCRT for ESCC and to identify biomarkers predictive of a clinical benefit. Methods We retrospectively analysed the clinical data of ESCC patients with clinical stage II–IVa who underwent CCRT. Then, we compared patients who received CCRT and AC (CCRT + AC group) with those who received CCRT alone (CCRT group). Propensity score analysis, subgroup analysis and an additional Cox regression model were conducted to analyse the predictive factors. The overall survival (OS) and progression-free survival (PFS) rates were taken as the endpoints. Results From January 2013 to December 2017, 244 patients were recruited (n = 131 for CCRT + AC; n = 113 for CCRT alone) for the analysis. After propensity score matching was performed (1:1 and 99 patients for each group) with consideration of the basic clinical characteristics, no significant differences were found in OS (HR = 1.024; 95% CI 0.737–1.423; P = 0.886) or PFS (HR = 0.809; 95% CI 0.582–1.126; P = 0.197) between the two groups. The good short-term response subgroup showed a better PFS and favoured CCRT + AC treatment (HR = 0.542; 95% CI 0.336–0.876; P = 0.008), the independent predictive role of which was confirmed in additional multivariate Cox regression analysis. Conclusions Although AC did not significantly improve PFS and OS for all ESCC patients after CCRT, the short-term response to CCRT might help identify a subgroup that will benefit, which needs further prospective research to confirm.

As a stem variety of lettuce, the fleshy stem is the main product organ of stem lettuce. The molecular mechanism of fleshy stem expansion in stem lettuce is a complex biological process. In the study, the material accumulation, gene expression, and morphogenesis during fleshy stem expansion process were analyzed by the comparative analysis of metabolome, transcriptome and the anatomical studies. The anatomical studies showed that the occurrence and activity of vascular cambium mainly led to the development of fleshy stems; and the volume of pith cells gradually increased and arranged tightly during the expansion process. A total of 822 differential metabolites and 9,383 differentially expressed genes (DEGs) were identified by the metabolomics and transcriptomics analyses, respectively. These changes significantly enriched in sugar synthesis, glycolysis, and plant hormone anabolism. The expression profiles of genes in the sugar metabolic pathway gradually increased in fleshy stem expansion process. But the sucrose content was the highest in the early stage of fleshy stem expansion, other sugars such as fructose and glucose content increased during fleshy stem expansion process. Plant hormones, including IAA, GA, CTK, and JA, depicted important roles at different stem expansion stages. A total of 1,805 DEGs were identified as transcription factors, such as MYB, bHLH, and bZIP, indicating that these transcription factor families might regulate the fleshy stems expansion in lettuce. In addition, the expression patterns identified by qRT-PCR were consistent with the expression abundance identified by the transcriptome data. The important genes and metabolites identified in the lettuce fleshy stem expansion process will provide important information for the further molecular mechanism study of lettuce fleshy stem growth and development.

BackgroundS-Detect is a computer-assisted, artificial intelligence-based system of image analysis that has been integrated into the software of ultrasound (US) equipment and has the capacity to independently differentiate between benign and malignant focal breast lesions. Since the revision and upgrade in both the breast imaging-reporting and data system (BI-RADS) US lexicon and the S-Detect software in 2013, evidence that supports improved accuracy and specificity of radiologists’ assessment of breast lesions has accumulated. However, such assessment using S-Detect technology to distinguish malignant from breast lesions with a diameter no greater than 2 cm requires further investigation.MethodsThe US images of focal breast lesions from 295 patients in our hospital from January 2019 to June 2022 were collected. The BI-RADS data were evaluated by the embedded program and as manually modified prior to the determination of a pathological diagnosis. The receiver operator characteristic (ROC) curves were constructed to compare the diagnostic accuracy between the assessments of the conventional US images, the S-Detect classification, and the combination of the two.ResultsThere were 326 lesions identified in 295 patients, of which pathological confirmation demonstrated that 239 were benign and 87 were malignant. The sensitivity, specificity, and accuracy of the conventional imaging group were 75.86%, 93.31%, and 88.65%. The sensitivity, specificity, and accuracy of the S-Detect classification group were 87.36%, 88.28%, and 88.04%, respectively. The assessment of the amended combination of S-Detect with US image analysis (Co-Detect group) was improved with a sensitivity, specificity, and accuracy of 90.80%, 94.56%, and 93.56%, respectively. The diagnostic accuracy of the conventional US group, the S-Detect group, and the Co-Detect group using area under curves was 0.85, 0.88 and 0.93, respectively. The Co-Detect group had a better diagnostic efficiency compared with the conventional US group (Z = 3.882, p = 0.0001) and the S-Detect group (Z = 3.861, p = 0.0001). There was no significant difference in distinguishing benign from malignant small breast lesions when comparing conventional US and S-Detect techniques.ConclusionsThe addition of S-Detect technology to conventional US imaging provided a novel and feasible method to differentiate benign from malignant small breast nodules.

Clonal reproduction is one of the most distinctive characteristics of plants and is common and diverse in aquatic macrophytes. The balance between sexual and asexual reproduction is affected by various conditions, especially adverse environments. However, we know little about clonal diversity of aquatic plants under suboptimal conditions, such as at high altitudes, and having this information would help us understand how environmental gradients influence patterns of clonal and genetic variation in freshwater species. The microsatellite data of four aquatic taxa in our previous studies were revisited to estimate clonal and genetic diversity on the Qinghai-Tibetan Plateau. Clonal diversity among different genetic groups was compared. Local environmental features were surveyed. Beta regressions were used to identify the environmental factors that significantly explained clonal diversity for relative taxon. The level of clonal diversity from high to low was Stuckenia filiformis > Hippuris vulgaris > Myriophyllum species > Ranunculus section Batrachium species. A positive correlation between clonal and genetic diversity was identified for all taxa, except H. vulgaris. Clonal diversity was affected by climate in S. filiformis and by the local environment in H. vulgaris. For Myriophyllum spp., low elevation and high sediment nutrition were significant for sexual recruitment. The environmental effects on clonal diversity were not significant in R. sect. Batrachium spp. Clonal diversity of aquatic plants is moderate to high and varies greatly in highlands. The effects of breeding systems and environmental factors on the patterns of clonal variation were identified. Elevational gradients, climates and local conditions play different roles in clonal diversity among relative taxon. Our results highlight the importance of sexual recruitment in alpine aquatic plant populations and the influence of environmental factors on the genetic patterns in freshwater species at local and regional scales.

Summary: The hierarchical organization of the visual system preserves topology, which is often lost in the “raw” human retinotopic maps derived from BOLD fMRI recordings. Here, we present the protocol for generating topology-preserving and smooth retinotopic maps from human retinotopy fMRI data. We describe data pre-processing, 3D surface flattening, and selection of the region of interest (ROI), followed by smoothing of the retinotopic maps within the ROI. This approach can be applied to visual cortical areas V1, V2, and V3 simultaneously.For complete details on the use and execution of this protocol, please refer to Tu et al. (2021). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

The metallic 1T phase layered WS2 was feasible to electrocatalytic hydrogen evolution reaction (HER) compared with its 2H phase. Duo to the intrinsically stabile nature of 2H phase WS2, it is challenging to construct metallic WS2 on flexible polymeric substrate. Herein, a two-step method is proposed for constructing electrospun porous poly (vinylidene fluoride) fibers embedded with metallic WS2 an electrocatalyst. The hybrid catalysts exhibit excellent HER performance, and thanks to distinguished mechanical properties, the flexible electrocatalysts maintain their initial catalytic performance after mechanical twisting. It has been demonstrated by experimentation and COMSOL multiphysics simulations that the identity of catalytic activity not only benefits by the synergistic effect of metallic WS2, but also in favor of the three-dimensional (3D) hierarchical architectures ensuring efficacious and substantial geometric interface for catalyzing the HER. These findings expedite an unique approach to create phase-controlled flexible electrode which facilitates the blueprint of clean energy generation.

Brain networks have attracted increasing attention due to the potential to better characterize brain dynamics and abnormalities in neurological and psychiatric conditions. Recent years have witnessed enormous successes in deep learning. Many AI algorithms, especially graph learning methods, have been proposed to analyze brain networks. An important issue for existing graph learning methods is that those models are not typically easy to interpret. In this study, we proposed an interpretable graph learning model for brain network regression analysis. We applied this new framework on the subjects from Human Connectome Project (HCP) for predicting multiple Adult Self-Report (ASR) scores. We also use one of the ASR scores as the example to demonstrate how to identify sex differences in the regression process using our model. In comparison with other state-of-the-art methods, our results clearly demonstrate the superiority of our new model in effectiveness, fairness, and transparency.

Background: With the acceleration of urbanization, the demand for people to return to forests and their desire for nature is also increasing annually. However, whether the visual behaviors and aesthetic preferences of users vary with background attributes when viewing forest landscapes remains to be further explored. This information will help forest landscape planners and managers to create a forest landscape space suitable for different groups of people. Purpose: This study mainly discusses whether people’s professional background will affect their visual behavior, satisfaction preference and re-viewing intention of a landscape and discusses the relationship among them. Main results: (1) Under the background of an in-forest landscape, the visual behavior of users in different layouts presents great similarity. (2) Satisfaction preference for landscapes is not significantly influenced by the user’s background, but there is a significant linear relationship between satisfaction preference and re-viewing intention (Adj. R2 = 0.412 − 0.697, sig. = 0.000). (3) The spatial cognition that affects users’ visual behavior and satisfaction preference in a scene will change with the landscape layout and users’ professional background. Therefore, we suggest that landscape planners and managers should consider not only the spatial layout of the landscape itself but also the user’s own attributes (whether they have professional knowledge of the landscape) when optimizing the visual behavior and satisfaction preference of in-forest landscape space. This will ensure that users have a high sense of identity and attachment to the scene in a targeted way, thus arousing a greater “desire” to re-view the scene. In addition, our results can identify a more satisfactory course for tour routes according to the user’s professional background, thus enhancing the rate of tourists who decide to “visit again”.

As a core task of computer vision perception, 3D scene understanding has received widespread attention. However, the current research mainly focuses on the semantic understanding task at the level of entity objects and often neglects the semantic relationships between objects in the scene. This paper proposes a 3D scene graph prediction model based on deep learning methods for scanned point cloud data of indoor scenes to predict the semantic graph about the class of entity objects and their relationships. The model uses a multi-scale pyramidal feature extraction network, MP-DGCNN, to fuse features with the learned category-related unbiased meta-embedding vectors, and the relationship inference of the scene graph uses an ENA-GNN network incorporating node and edge cross-attention; in addition, considering the long-tail distribution effect, a category grouping re-weighting scheme is used in the embedded prior knowledge and loss function. For the 3D scene graph prediction task, experiments on the indoor point cloud 3DSSG dataset show that the model proposed in this paper performs well compared with the latest baseline model, and the prediction effectiveness and accuracy are substantially improved.

Abstract Form‐wound windings in electric machines designed for electric aircraft propulsion face reliability challenges due to the severe operating environment, such as high temperature and low pressure. This study proposes a forewarning method for insulation condition monitoring of form‐wound windings based on partial discharge (PD) and deep learning neural network. Three PD features are extracted from the PD profile, which provides information about physics‐of‐failure and reflects the degree of insulation degradation. An algorithm fusion extracted from auto‐encoder and long short‐term recurrent neural network is proposed to synthesize one failure precursor from these three features and make multi‐time‐step prediction through historical data to provide forewarning. An electrical and thermal accelerated ageing test is performed on the form‐wound windings at 0.2 atm to simulate working environment of electric aircraft. The proposed method is validated on the accelerated ageing dataset and shows better prediction accuracy than some existing time‐series prediction methods, indicating the advantages of the proposed method. Moreover, an on‐line hardware setup using a deep learning processor is recommended to implement the forewarning method. The proposed approach has the potential to be widely applied to other insulation systems and contribute to work on condition monitoring.