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Abstract Neuroblastoma (NB) is a challenging pediatric extracranial solid tumor characterized by a poor prognosis and resistance to chemotherapy. Identifying targets to enhance chemotherapy sensitivity in NB is of utmost importance. Increasing evidence implicates long noncoding RNAs (lncRNAs) play important roles in cancer, but their functional roles remain largely unexplored. Here, we analyzed our RNA sequencing data and identified the upregulated lncRNA ZNF674-AS1 in chemotherapy non-responsive NB patients. Elevated ZNF674-AS1 expression is associated with poor prognosis and high-risk NB. Importantly, targeting ZNF674-AS1 expression in NB cells suppressed tumor growth in vivo. Further functional studies have revealed that ZNF674-AS1 constrains cisplatin sensitivity by suppressing pyroptosis and promoting cell proliferation. Moreover, ZNF674-AS1 primarily relies on CA9 to fulfill its functions on cisplatin resistance. High CA9 levels were associated with high-risk NB and predicted poor patient outcomes. Mechanistically, ZNF674-AS1 directly interacted with the RNA binding protein IGF2BP3 to enhance the stability of CA9 mRNA by binding with CA9 transcript, leading to elevated CA9 expression. As a novel regulator of CA9, IGF2BP3 positively upregulated CA9 expression. Together, these results expand our understanding of the cancer-associated function of lncRNAs, highlighting the ZNF674-AS1/IGF2BP3/CA9 axis as a constituting regulatory mode in NB tumor growth and cisplatin resistance. These insights reveal the pivotal role of ZNF674-AS1 inhibition in recovering cisplatin sensitivity, thus providing potential therapeutic targets for NB treatment.

Abstract Decapterus maruadsi is one of the representative offshore fish in the Western Pacific. Since the last century, it has become a commercially valuable marine fishery species in the Western Pacific region. Despite its high economic value, there is still a lack of high-quality reference genome of D. maruadsi in germplasm resource evaluation research. Here we report a chromosome-level reference genome of D. maruadsi based on Nanopore sequencing and Hi-C technologies. The whole genome was assembled through 169 contigs with a total length of 723.69 Mb and a contig N50 length of 24.67 Mb. By chromosome scaffolding, 23 chromosomes with a total length of 713.58 Mb were constructed. In addition, a total of 199.49 Mb repetitive elements, 33,515 protein-coding genes, and 6,431 ncRNAs were annotated in the reference genome. This reference genome of D. maruadsi will provide a solid theoretical basis not only for the subsequent development of genomic resources of D. maruadsi but also for the formulation of policies related to the protection of D. maruadsi.

Abstract Background The relation of adipose tissue depletion with prognostic outcome of variceal bleeding among cirrhotic patients is still inconclusive. The present work explored whether adipose tissue, which was measured based on computed tomography (CT), was valuable for analyzing rebleeding and mortality among patients with variceal bleeding who had undergone endoscopic therapy. Methods The study encompassed cirrhotic patients who underwent endoscopic therapy to prevent variceal rebleeding between January 2016 and October 2022. The L3-level CT images were obtained. Besides, impacts of subcutaneous adipose tissue index (SATI), visceral adipose tissue index (VATI), as well as total adipose tissue index (TATI) on rebleeding and mortality among cirrhotic patients following endoscopic therapy were examined. Results In this work, our median follow-up period was 31 months. Among those adipose tissue indexes, only SATI exhibited an independent relation to higher rebleeding (HR 0.981, 95% CI, 0.971–0.991, p

Abstract Purpose To establish a multivariate linear equation to predict the diameter (outer diameter) of the acetabular prosthesis used in total hip arthroplasty. Methods A cohort of 258 individuals who underwent THA at our medical facility were included in this study. The independent variables encompassed the patients' height, weight, foot length, gender, age, and surgical access. The dependent variable in this study was the diameter of the acetabular prosthesis utilized during the surgical procedure. The entire cohort dataset was randomly partitioned into a training cohort and a validation cohort, with a ratio of 7:3, employing the SPSS 26.0 software. Pearson correlation analysis was conducted to examine the relationships between the patients' height, weight, foot length, gender, age, surgical access, and the diameter of the acetabular prosthesis in the training cohort. Additionally, a multiple linear regression equation was developed using the independent variables from the training cohort and the diameter of the acetabular prosthesis as the dependent variable. This equation aimed to predict the diameter of the acetabular prosthesis based on the patients' characteristics. The accuracy of the equation was evaluated by substituting the data of the validation cohort into the multiple linear equation. The predicted acetabular prosthesis diameters were then compared with the actual diameters used in the operation. Results The correlation analysis conducted on the training cohort revealed that surgical access (r = 0.054) and age (r = −0.120) exhibited no significant correlation with the diameter of the acetabular prosthesis utilized during the intraoperative procedure. Conversely, height (r = 0.687), weight (r = 0.654), foot length (r = 0.687), and sex (r = 0.354) demonstrated a significant correlation with the diameter of the acetabular prosthesis used intraoperatively. Furthermore, a predictive equation, denoted as Y (acetabular prosthesis diameter in mm) = 20.592 + 0.548 × foot length (cm) + 0.083 × height (cm) + 0.077 × weight (kg), was derived. This equation accurately predicted the diameter within one size with an accuracy rate of 64.94% and within two sizes with an accuracy rate of 94.81%. Conclusion Anthropometric data can accurately predict the diameter of acetabular prosthesis during total hip arthroplasty.

High quality mine images can provide guarantee for mine safety production, and improve the performance of subsequent image analysis technologies. Affected by low illuminance environment, mine images suffer low brightness, uneven brightness, color distortion, and serious loss of details. Aiming at the above problems, an illuminance improvement and details enhancement method on coal mine low-light images based on Transformer and adaptive feature fusion was proposed to enhance the brightness and detail of mine low illuminance images. Based on the idea of generative confrontation, a framework of generative adversary agent model was built, and the target image domain was used instead of a single reference image to drive discriminator to supervise the training of generator, so as to achieve adaptive enhancement of low illuminance images; The feature encoder was built based on the feature representation learning theory to decouple the image into illuminance component and reflection component, the method can avoid the interaction between illuminance and color features during image enhancement to solve the color distortion; the CEM-Transformer Encoder was designed to enhance the brightness component, the method can improve the overall image brightness and eliminate the local area brightness unevenness, by capturing the global context and extracting the local area features; In the process of reflection component enhancement, the skip connection combined with CEM-Cross-Transformer Encoder was used to adaptively fuse low-level features with features at the deep CNN layers, which can effectively avoid the loss of detailed features, and ECA-Net was added to the encode network to improve the feature extraction efficiency of the shallow CNN layers. The low illuminance mine image dataset was produced to provide data resources for the low illuminance mine image enhancement task. The experiments show that, compared with five advanced low illuminance image enhancement algorithms, the quality indicators PSNR, SSIM and VIF of the images enhanced by the algorithm are improved by 16.564%, 10.998%, 16.226% and 14.438%, 10.888% and 14.948% on average on the low illuminance mine image dataset and the public dataset. And the algorithm also perform well in subjective visual evaluation. The above results prove that the algorithm can effectively improve the overall image brightness and eliminate the uneven brightness, thus to achieve mine low illuminace image enhancement.

Background & Aims: Apolipoprotein A-1 (ApoA-1), the main apolipoprotein of high-density lipoprotein, has been well studied in the area of lipid metabolism and cardiovascular diseases. In this project, we clarify the function and mechanism of ApoA-1 in liver regeneration. Methods: Seventy percent of partial hepatectomy was applied in male ApoA-1 knockout mice and wild-type mice to investigate the effects of ApoA-1 on liver regeneration. D-4F (ApoA-1 mimetic peptide), autophagy activator, and AMPK activator were used to explore the mechanism of ApoA-1 on liver regeneration. Results: We demonstrated that ApoA-1 levels were highly expressed during the early stage of liver regeneration. ApoA-1 deficiency greatly impaired liver regeneration after hepatectomy. Meanwhile, we found that ApoA-1 deficiency inhibited autophagy during liver regeneration. The activation of autophagy protected against ApoA-1 deficiency in inhibiting liver regeneration. Furthermore, ApoA-1 deficiency impaired autophagy through AMPK-ULK1 pathway, and AMPK activation significantly improved liver regeneration. The administration of D-4F could accelerated liver regeneration after hepatectomy. Conclusions: These findings suggested that ApoA-1 played an essential role in liver regeneration through promoting autophagy in hepatocytes via AMPK-ULK1 pathway. Our findings enrich the understanding of the underlying mechanism of liver regeneration and provide a potential therapeutic strategy for liver injury.

Objective To analyze the cost and effectiveness of different HIV screening strategies based on multi-center HIV residual risk study, so as to provide reference for blood centers to adopt appropriate HIV testing strategies. Methods According to the HIV screening and confirmation of blood donors in three blood centers in Anhui Province, the residual risk of different HIV screening strategies was estimated. A decision tree model was established to analyze the cost-effectiveness differences of three different screening strategies under current domestic policies. Results The residual risk of anti-HIV-1 +2 ELISA, HIV Ag/Ab1+2 ELISA and ELISA+NAT were 1.17×10-6,0.84×10-6 and 0.59×10-6, respectively. According to decision tree model analysis, HIV Ag/Ab1+2 ELISA had a cost-effectiveness advantage over anti-HIV 1+2 ELISA when there was no NAT, but the advantage of HIV Ag/Ab1+2 ELISA disappeared when there was one NAT. The cost of HIV reagents, the cost of HIV treatment and the cost of false positive discarding were sensitive factors of the model. Conclusion In this area, one anti-HIV 1+2 ELISA combined with one NAT has a cost-effectiveness advantage. Blood centers need to confirm and evaluate the ELISA reagents used before conducting HIV screening. Under the premise of ensuring sensitivity, reagent cost and reagent false positive rate are the key factors.

Brain networks/graphs have been widely recognized as powerful and efficient tools for identifying neurological disorders. In recent years, various graph neural network models have been developed to automatically extract features from brain networks. However, a key limitation of these models is that the inputs, namely brain networks/graphs, are constructed using predefined statistical metrics (e.g., Pearson correlation) and are not learnable. The lack of learnability restricts the flexibility of these approaches. While statistically-specific brain networks can be highly effective in recognizing certain diseases, their performance may not exhibit robustness when applied to other types of brain disorders. To address this issue, we propose a novel module called Brain Structure Inference (termed BSI), which can be seamlessly integrated with multiple downstream tasks within a unified framework, enabling end-to-end training. It is highly flexible to learn the most beneficial underlying graph structures directly for specific downstream tasks. The proposed method achieves classification accuracies of 74.83% and 79.18% on two publicly available datasets, respectively. This suggests an improvement of at least 3% over the best-performing existing methods for both tasks. In addition to its excellent performance, the proposed method is highly interpretable, and the results are generally consistent with previous findings.

Abstract Background The incidence and mortality rates of patients with chronic lymphocytic leukemia (CLL) in China have recently increased. This study performed a long-term economic evaluation of the first-line treatment strategies ibrutinib (IB) or bendamustine (BE) plus rituximab (RI) for previously untreated older patients with CLL without the del(17p)/TP53 mutation in China. Methods Based on clinical data from large, randomized trials, a Markov model including four disease states (event-free survival, treatment failure, post-treatment failure, and death) was used to estimate the incremental costs per quality adjusted-life year (QALY) gained from the first-line IB strategy versus the BE plus RI strategy over a 10-year period. All costs were adjusted to 2022 values based on the Chinese Consumer Price Index, and all costs and health outcomes were discounted at an annual rate of 5%. Sensitivity analysis was performed to confirm the robustness of base-case results. Results Compared to the first-line BE plus RI strategy, first-line IB treatment achieved 1.17 additional QALYs, but was accompanied by $88,046.78 (estimated in 2022 US dollars) in decremental costs per patient over 10 years. Thus, first-line treatment with IB appeared to have absolute dominance compared to the BE plus RI strategy. Sensitivity analysis confirmed the robustness of these results. Conclusions The first-line treatment with IB is absolutely cost-effective compared to the first-line BE plus RI treatment strategy for 65 or older patients with CLL without the del (17p)/TP53 mutation from the Chinese payer perspective. Therefore, it is strongly recommended that Chinese health authorities select the former strategy for these CLL patients.

Abstract Based on geographical distribution, cultivated Chinese Angelica dahurica has been divided into Angelica dahurica cv. ‘Hangbaizhi’ (HBZ) and Angelica dahurica cv. ‘Qibaizhi’ (QBZ). Long-term geographical isolation has led to significant quality differences between them. The secretory structure in medicinal plants, as a place for accumulating effective constituents and information transmission to the environment, links the environment with the quality of medicinal materials. However, the secretory tract differences between HBZ and QBZ has not been revealed. This study aimed to explore the relationship between the secretory tract and the quality of two kinds of A. dahurica. Root samples were collected at seven development phases. High-Performance Liquid Chromatography (HPLC) and Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI) were used for the content determination and spatial location of coumarins. Paraffin section was used to observe and localize the root secretory tract. Origin, CaseViewer, and HDI software were used for data analysis and image processing. The results showed that compared to QBZ, HBZ, with better quality, has a larger area of root secretory tracts. Hence, the root secretory tract can be included in the quality evaluation indicators of A. dahurica. Additionally, DESI-MSI technology was used for the first time to elucidate the temporal and spatial distribution of coumarin components in A. dahurica root tissues. This study provides a theoretical basis for the quality evaluation and breeding of improved varieties of A. dahurica and references the DESI-MSI technology used to analyze the metabolic differences of various compounds, including coumarin and volatile oil, in different tissue parts of A. dahurica.

Abstract Endoplasmic reticulum stress (ERS) occurs when misfolded or unfolded proteins accumulate in the endoplasmic reticulum (ER), and it is often observed in tumors, including head and neck squamous cell carcinoma (HNSCC). Relevant studies have demonstrated the prognostic significance of ERS-related long non-coding RNAs (lncRNAs) in various cancers. However, the relationship between ERS and lncRNAs in HNSCC has received limited attention in previous studies. In this study, we aimed to develop an ERS-related lncRNAs prognostic model using correlation analysis, Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) regression analysis based on data from The Cancer Genome Atlas (TCGA) database. The survival and predictive ability of this model were evaluated using Kaplan–Meier analysis and time-dependent receiver operating characteristics (ROC), while nomograms and calibration curves were constructed. Then, functional enrichment analyses, tumor mutation burden (TMB), tumor infiltration of immune cells, single sample Gene Set Enrichment Analysis (ssGSEA), and drug sensitivity analysis were performed. Additionally, we conducted a consensus cluster analysis to compare differences between subtypes of tumors. Finally, we validated the expression of the ERS-related lncRNAs that constructed prognostic risk score model in HNSCC tissues through quantitative real-time PCR (qRT-PCR). We developed a prognostic signature based on seven ERS-related lncRNAs, which showed better predictive performance than other clinicopathological features. The high-risk poor prognosis group had a poorer prognosis in comparison to the low-risk good prognosis. The area under the ROC curve (AUC) predicted by this model for 3-year survival rates of HNSCC patients was 0.805. Enrichment analysis revealed that the differentially expressed genes were primarily enriched in pathways related to immune responses and signal transduction. Low-risk patients had lower TMB, more immune cell infiltrations, and enhanced anti-tumor immunity. Cluster analysis indicated that cluster 3 may have a better prognosis and immunotherapy effect. In addition, the result of qRT-PCR was consistent with our analysis. This prognostic model based on seven ERS-related lncRNAs is a promising tool for risk stratification, survival prediction, and immune cell infiltration status assessment.

Based on the multitarget-directed ligands (MTDLs) strategy, a series of chromone-hydroxypyridinone hybrids were designed, synthesised, and evaluated as potential multimodal anti-AD ligands. Prospective iron-chelating effects and favourable monoamine oxidase B (MAO-B) inhibitory activities were observed for most of the compounds. Pharmacological assays led to the identification of compound 17d, which exhibited favourable iron-chelating potential (pFe3+ = 18.52) and selective hMAO-B inhibitory activity (IC50 = 67.02 ± 4.3 nM, SI = 11). Docking simulation showed that 17d occupied both the substrate and the entrance cavity of MAO-B, and established several key interactions with the pocket residues. Moreover, 17d was determined to cross the blood–brain barrier (BBB), and can significantly ameliorate scopolamine-induced cognitive impairment in AD mice. Despite its undesired pharmacokinetic property, 17d remains a promising multifaceted agent that is worth further investigation.

Crack initiation stress and crack damage stress are two critical indices for assessing the fracture strength of rock mass. However, understanding the stress characteristics of crack initiation and damage under triaxial compression remains still immature. To address this problem, by acoustic monitoring, i.e. ultrasonic wave transmission and acoustic emission (AE), the integrated triaxial compression experiments were carried out on granitic specimens. The crack initiation and damage stresses were determined by wave velocity, wave amplitude and AE methods, respectively. The discrepancy of stresses for crack initiation and damage identified by these methods were examined. Results showed that the confinement affected the peak stress and corresponding strain, and these two parameters increased with increasing confining pressure. The ultrasonic wave velocity and wave amplitude first increased and then remained relatively stable, and finally decreased with increasing axial compressive stress. The number of AE events stayed at a relatively low extent until axial stress approached the peak; after that, the AE accumulative counts skyrocketed to the maximum. It also shows that for a given confinement, the stresses for crack initiation and damage identified by the wave amplitude method were the smallest, followed those by AE method and wave velocity method. Moreover, the stresses for crack initiation and crack damage identified by these methods increased generally with confining pressures. However, the rate of increment of these two crack stresses decreased with increasing confining pressure. In addition, the slight decrease in these two crack stresses ratios was noticed with increasing confining pressure. The findings are helpful to understand the crack stresses of deep rocks, in terms of support of deep underground engineering.

The scaling-dependent behaviors of rocks are significant to the stability and safe operation of the structures built in or on rock masses for practical engineering. Currently, many size effect models are employed to connect laboratory measurements at small scales and engineering applications at large scales. However, limited works consider the strain rate effect. In this study, an fractal-statistical scaling model incorporating strain rate is proposed based on a weakest-link approach, fractal theory and dynamic fracture mechanics. The proposed scaling model consists of 8 model parameters with physical meaning, i.e. rate-dependent parameter, intrinsic material parameter, dynamic strain rate, quasi-static strain rate, quasi-static fracture toughness, micro-crack size, micro-crack intensity and fractal dimension, enabling the proposed scaling model to model the scaling behaviors under different external conditions. Theoretical predictions are consistent with experimental data on red sandstone, proving the reliability and effectiveness of the proposed scaling model. Thus, the scaling behaviors of rocks under dynamic loading conditions can be captured by the proposed fractal-statistical scaling model. The sensitivity analysis indicates that the nominal strength difference becomes more obvious with a higher strain rate, larger fractal dimension, smaller micro-crack size or lower micro-crack intensity. Therefore, the proposed scaling model has the potential to capture the scaling behaviors considering the thermal effect, weathering effect, anisotropic characteristic etc., as the proposed scaling model incorporated model parameters with physical meaning. The findings of this study are of fundamental importance to understand the scaling behaviors of rock under dynamic loading condition, and thus would facilitate the appropriate design of rock engineering.

Abstract Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent imaging methods like ptychography are poised to revolutionize nanoscale materials characterization. However, these advancements are accompanied by significant increase in data and compute needs, which precludes real-time imaging, feedback and decision-making capabilities with conventional approaches. Here, we demonstrate a workflow that leverages artificial intelligence at the edge and high-performance computing to enable real-time inversion on X-ray ptychography data streamed directly from a detector at up to 2 kHz. The proposed AI-enabled workflow eliminates the oversampling constraints, allowing low-dose imaging using orders of magnitude less data than required by traditional methods.

Abstract Background Focal acute pancreatitis is a special type of acute pancreatitis, which diagnosis is based on image showing a focal mass formation in the pancreas. For acute pancreatitis with or without focal inflammatory enlargement, little is known on differences between them. Our purpose was to find differences between focal acute pancreatitis and non-localized acute pancreatitis. Methods We reviewed the medical records of a total of 24 patients diagnosed with focal acute pancreatitis by imaging and clinical diagnosis, and 27 cases of acute pancreatitis which manifest non-localized pancreas inflammation were selected as the control group. The differences of the two groups were compared to describe their clinical characteristics. Results Differences in bloating (4.2% VS 29.6%,P = 0.026), abdominal tenderness (58.3% VS 85.2%,P = 0.032), peripheral blood neutrophil ratio (60.1 ± 23.3VS 75.9 ± 12.6,P = 0.004), serum D-Dimer (0.40(0.25,0.98) VS 1.59(0.49,4.63),P = 0.008), serum GGT (40(25,91) VS120(22,383),P = 0.046), serum amylase(435(241,718) VS 591(394,1333),P = 0.044) and lipase(988(648,1067) VS 1686(525,2675),P = 0.027) between focal acute pancreatitis and non-localized acute pancreatitis groups were statistically significant. However, difference of the severity of two groups was not statistically significant (P = 1.000). Conclusion Compared with non-localized acute pancreatitis, changes in symptoms, signs and laboratory indicators of focal acute pancreatitis are non-obvious, however, there was no significant difference in the severity of two groups, indicating that we should pay more attention to diagnosis of focal acute pancreatitis in clinical practice.

Abstract LLC resonant converter has the features of low noise, high efficiency and power density, which is suitable to be integrated into DC microgrid. Due to severe stresses in the resonant tank, achieving fast and safe transient performance has been challenging for resonant converters. With less switch number and voltage stress, half‐bridge LLC resonant converter with full‐bridge rectifier (H‐F LLC resonant converter) are more suitable for high‐voltage application. To improve the transient response of the converter, this paper proposes a method based fixed center state trajectory for the converter to achieve soft start‐up. To reduce dynamic response time during start‐up, each step of fixed center state‐trajectory is designed optimally for the shortest path with symmetrical current limitation. In addition, the proposed method is also applicable to full‐bridge LLC converters. Moreover, according to the state‐plane analysis, load stepping‐up and stepping‐down transient state trajectories with the shortest path are carried out as well. To minimize the adverse effect of digital delay, fast load transient control based on 3D look‐up table is given based on FPGA‐EP3C25E144I7, which would also significantly reduce the computation requirement of the hardware controllers. The experimental results are verified on a 380V/12V LLC converter prototype at 130 kHz.

Abstract Background Metaplastic breast cancer(MBC) is a specific pathological type of invasive breast cancer. There are few studies related to MBC due to its rarity. This study aimed to analyse the differences in clinicopathological characteristics and prognosis between Metaplastic breast cancer and triple-negative invasive ductal carcinoma (TN-IDC). Methods We retrospectively compared the clinicopathological characteristics of patients diagnosed with MBC and TN-IDC at the Fourth Hospital of Hebei Medical University between 2011 and 2020 in a 1:2 ratio. The log-rank test was used to compare the two groups’ disease-free survival (DFS) and overall survival (OS). For MBCs, we performed univariate and multivariate analyses using the Cox proportional hazards model to determine the characteristics that impacted OS and DFS. Results A total of 81 patients with MBC and 162 patients with TN-IDC were included in this study. At initial diagnosis, MBC patients had larger tumour diameters(P = 0.03) and fewer positive lymph nodes (P = 0.04). Patients with MBC were more likely to have organ metastases after surgery (P = 0.03). Despite receiving the same treatment, MBC patients had worse DFS (HR = 1.66, 95%CI 0.90–3.08, P = 0.11) and OS (HR = 1.98, 95% CI 1.03–3.81, P = 0.04), and OS was statistically significant. Positive lymph nodes at initial diagnosis were associated with worse DFS (HR = 3.98, 95%CI 1.05–15.12, P = 0.04) and OS (HR = 3.70, 95%CI 1.03–13.34, P = 0.04) for patients with MBC. The efficacy of platinum-based agents is insensitive for MBC patients receiving chemotherapy. In addition, patients treated with preoperative chemotherapy had worse DFS compared to patients treated with postoperative chemotherapy (HR = 3.51, 95%CI 1.05–11.75, P = 0.04). Conclusions The clinicopathological characteristics and prognosis of MBC and TN-IDC differ in many ways. Further studies are required to determine suitable treatment guidelines for patients with MBC.

Power transformer plays a very important role in power system, its long-term operation will cause various kinds of faults. Accurate identification and timely elimination of transformer faults are the basis of safe operation of power grid. As one of the most commonly used fault diagnosis methods, dissolved gas analysis (DGA) technology is used to identify fault types through dissolved gas in transformer oil, and its reliability has been proved. In order to analyze these gases and diagnose transformer fault types with the results, many methods have been developed, such as Key Gas Method, Method of Duval, IEC 60599 Method, Method of Dornenburg and Method of Rogers, etc. In some cases, the accuracy of these traditional methods is reduced and cannot be applied for diagnosis, since they have fixed input features and is not flexible for input combination. In order to achieve the propose of solving this defect, this paper introduces a deep belief network-based DGA method to diagnose the faults and states of power transformers with customized input features. For this work, six fault classifications were considered based on the nine characteristics extracted from the gases precipitated from the insulating oil of power transformers. The deep belief network was tested using oil samples collected from power transformers. Experiments have shown that the performance of the network has obtained relatively good accuracy results.

With the proposal of a ''dual carbon strategy '' and the rising share of renewable energy sources, the resulting low-inertia problem has seriously affected the frequency stability of new power systems. This paper proposes a minimum inertial demand estimation of renewable energy considering new power system frequency constraints to enhance the power system inertia situational awareness and clarify the system operation boundary. Firstly, the frequency response model with multi-source renewable energy units and the time-domain mathematical expressions are established, and the frequency constraints and inertial demand of new power systems are given. The minimum inertial demand estimation model is constructed on this basis, which can be solved by the sparrow search algorithm (SSA). Ultimately, the applicability and practicality of the suggested approach are demonstrated and verified in IEEE 39-bus system. The case study results demonstrate the process can accurately calculate the inertial demand of renewable energy side considering system frequency constraints and give guidance for the stable operation of new power systems.

The corrosion behavior of a TA16 titanium alloy during exposure in simulated water environment of small modular reactor (SMR) at 320°C for up to 5000 h was investigated by employing dedicated microstructure characterization. The corrosion weight gain curve of the alloy is found to follow a parabolic law with an exponential parameter of n = 0.738. Oxide scales formed on the alloy surface generally show a two-layer structure composed of a relatively compact inner layer (dense oxide layer) and a discontinuous outer layer (microcrystallites). The dense oxide in the inner layer corresponds to anatase TiO2 while the surface microcrystallite layer is mainly comprised of ilmenite FeTiO3. The number and size of the microcrystallites in the outer layer gradually increase with the exposure time. Fe ions from the corroded loop pipe materials should have participated in forming the outer layer. The compact inner layer is thickened gradually with the test time with its thickness growth curve featured by l = 4.245t0.588, which could better reflect the corrosion behavior of the TA16 alloy.

Reducing sedentary behavior has become a public health priority due to significantly increased prevalence of leisure-time sedentary behaviors among people; promoting physical activity and interrupting sedentary time are among common interventions on sedentary behaviors. The built environment, as one of determinants of sedentary behavior, is increasingly being investigated and relevant studies have indicated that environmental interventions on sedentary behavior may be a more cost-effective and appropriate approach; however, few studies have specified the extent and mechanism of a distinct built environment’s impact on sedentary behavior. In this review, we summarize researches on the association of characteristics of built environment with sedentary behavior, related measurement tools, and environmental interventions on sedentary behaviors to provide references to domestic studies in this field.

Cyclocarya paliurus tea, also known as “sweet tea”, an herbal tea with Cyclocarya paliurus leaves as raw material, is famous for its unique nutritional benefits and flavor. However, due to the unique “bittersweet” of Cyclocarya paliurus tea, it is still unable to fully satisfy consumers’ high-quality taste experience and satisfaction. Therefore, this study aimed to explore metabolites in Cyclocarya paliurus leaves during their growth period, particularly composition and variation of sweet and bitter taste compounds, by combining multi-platform metabolomics analysis with an electronic tongue system and molecular docking simulation technology. The results indicated that there were significant differences in the contents of total phenols, flavonoids, polysaccharides, and saponins in C. paliurus leaves in different growing months. A total of 575 secondary metabolites were identified as potential active metabolites related to sweet/bitter taste using nontargeted metabolomics based on UHPLC-MS/MS analysis. Moreover, molecular docking technology was utilized to study interactions between the candidate metabolites and the sweet receptors T1R2/T1R3 and the bitter receptors T2R4/T2R14. Six key compounds with high sweetness and low bitterness were successfully identified by using computational simulation analysis, including cis-anethole, gluconic acid, beta-D-Sedoheptulose, asparagine, proline, and citrulline, which may serve as candidates for taste modification in Cyclocarya paliurus leaves. These findings provide a new perspective for understanding the sweet and bitter taste characteristics that contribute to the distinctive sensory quality of Cyclocarya paliurus leaves.

Product quality is a key factor affecting consumers’ willingness to buy, providing greater advantages to an enterprise than product price. This paper investigates the impact of two factors, price and quality, on the operational decisions of hybrid competing supply chains. Supply chain I, which consists of a manufacturer and a retailer, is a decentralized structure. Supply chain II, where the manufacturer and retailer are integrated, is a centralized structure. Quality investment and vertical shareholding are introduced into the decentralized supply chain. Models are constructed for three different scenarios, examining whether the manufacturer makes a quality investment and whether the retailer holds shares in the quality investment. By comparing the equilibrium results, solved by the Stackelberg game method, the following conclusions are drawn: (1) Quality investment and shareholding can enhance product quality and price. (2) The retail price in a centralized supply chain is consistently lower than that in a decentralized one, leading to generally higher total profits for centralized supply chain. (3) The total profit of the decentralized supply chain only exceeds that of the centralized ones when the degree of substitution between products is lower than 0.6285 and the quality effort cost factor is within a specific range. While centralized supply chain is generally more advantageous, decentralized supply chain can outperform him under specific conditions.

Abstract Immunogenomic loci remain poorly understood because of their genetic complexity and size. Here, we report the de novo assembly of a cattle genome and provide a detailed annotation of the immunogenomic loci. The assembled genome contains 143 contigs (N50 ~ 74.0 Mb). In contrast to the current reference genome (ARS-UCD1.2), 156 gaps are closed and 467 scaffolds are located in our assembly. Importantly, the immunogenomic regions, including three immunoglobulin (IG) loci, four T-cell receptor (TR) loci, and the major histocompatibility complex (MHC) locus, are seamlessly assembled and precisely annotated. With the characterization of 258 IG genes and 657 TR genes distributed across seven genomic loci, we present a detailed depiction of immune gene diversity in cattle. Moreover, the MHC gene structures are integrally revealed with properly phased haplotypes. Together, our work describes a more complete cattle genome, and provides a comprehensive view of its complex immune-genome.

Abstract Cushing’s disease is a rare neuroendocrine disorder with excessive endogenous cortisol, impaired cognition, and psychiatric symptoms. Evidence from resting-state fMRI revealed the abnormalities of static brain connectivity in patients with Cushing’s disease (CD patients). However, it is unknown whether the CD patients’ dynamic functional connectivity would be abnormal and whether the dynamic features are associated with deficits in cognition and psychopathological symptoms. Here, we evaluated 50 patients with Cushing’s disease and 57 healthy participants by using resting-state fMRI and dynamic functional connectivity (dFNC) approach. We focused on the dynamic features of default mode network (DMN), salience network (SN), and central executive network (CEN) because these are binding sites for the cognitive-affective process, as well as vital in understanding the pathophysiology of psychiatric disorders. The dFNC was further clustered into four states by k-mean clustering. CD patients showed more dwell time in State 1 but less time in State 4. Intriguingly, group differences in dwell time in these two states can explain the cognitive deficits of CD patients. Moreover, the inter-network connections between DMN and SN and the engagement time in State 4 negatively correlated with anxiety and depression but positively correlated with cognitive performance. Finally, the classifier trained by the dynamic features of these networks successfully classified CD patients from healthy participants. Together, our study revealed the dynamic features of CD patients’ brains and found their associations with impaired cognition and emotional symptoms, which may open new avenues for understanding the cognitive and affective deficits induced by Cushing’s disease.

Abstract Background Spindle and kinetochore-associated complex subunit 3 (SKA3) plays an important role in cell proliferation by regulating the separation of chromosomes and their division into daughter cells. Previous studies demonstrated that SKA3 was strongly implicated in tumor development and progression. However, the roles of SKA3 in cholangiocarcinoma (CCA) and the underlying mechanisms remain unclear. Methods Next-generation sequencing (NGS) was performed with paired CCA tissues and normal adjacent tissues (NATs). SKA3 was chose to be the target gene because of its remarkably upregulation and unknown function in cholangiocarcinoma in TCGA datasets, GSE107943 datasets and our sequencing results. RT-PCR and immunohistochemistry staining were used to detect the expression of SKA3 in paired CCA tissues and normal adjacent tissues. The SKA3 knockdown and overexpression cell line were constructed by small interfering RNA and lentivirus vector transfection. The effect of SKA3 on the proliferation of cholangiocarcinoma under hypoxic conditions was detected by experiments in vitro and in vivo. RNA-seq was used to find out the differentially expressed pathways in cholangiocarcinoma proliferation under hypoxia regulated by SKA3. IP/MS analysis and Western blot assays were used to explore the specific mechanism of SKA3 in regulating the expression of HIF-1a under hypoxia. Results SKA3 was up-regulated in NGS, TCGA and GSE107943 databases and was associated with poor prognosis. Functional experiments in vitro and in vivo showed that hypoxia-induced SKA3 promoted cholangiocarcinoma cell proliferation. RNA-sequencing was performed and verified that SKA3 enhanced fatty acid synthesis by up-regulating the expression of key fatty acid synthase, thus promoting cholangiocarcinoma cell proliferation under hypoxic conditions. Further studies indicated that under hypoxic conditions, SKA3 recruited PARP1 to bind to HIF-1a, thus enhancing the poly ADP-ribosylation (PARylation) of HIF-1a. This PARylation enhanced the binding between HIF-1a and USP7, which triggered the deubiquitylation of HIF-1a under hypoxic conditions. Additionally, PARP1 and HIF-1a were upregulated in CCA and promoted CCA cell proliferation. SKA3 promoted CCA cell proliferation and fatty acid synthesis via the PARP1/HIF-1a axis under hypoxic conditions. High SKA3 and HIF-1a expression levels were associated with poor prognosis after surgery. Conclusion Hypoxia-induced SKA3 promoted CCA progression by enhancing fatty acid synthesis via the regulation of PARylation-dependent HIF-1a deubiquitylation. Furthermore, increased SKA3 level enhanced chemotherapy-resistance to gemcitabine-based regimen under hypoxic conditions. SKA3 and HIF-1a could be potential oncogenes and significant biomarkers for the analysis of CCA patient prognosis.

The missing and abnormal data in power transformer operation and monitoring greatly affect the accuracy of fault diagnosis and thus threaten the stable operation of power systems. To conduct outlier detection and improve data quality for safety warning, this paper proposes a transformer operation data preprocessing method based on KNN (K-nearest neighbor) and LOF (local outlier factor) for power transformer operation data classification. Firstly, this paper analyzes the characteristics of transformer operation data. Secondly, the local reachable density of the input data is calculated by LOF algorithm. The local outlier factor score of the data is derived according to the local reachable density, and the abnormal data is output according to the abnormal score. Then, KNN algorithm is utilized to classify the relevant data around the abnormal value and missing value of the transformer. The data are filled or corrected according to the classification results. Thirdly, the elbow method is used to determine the optimal K value and cluster operation data by K-Means algorithm. Finally, the proposed method is applied and verified with real transformer operation data in case study. The results show the method can effectively detect and correct the abnormal and missing data, conduct transformer data cleaning and preprocessing and provide accurate and effective data samples for transformer fault diagnosis.

Renewable energy is connected to the distribution network in the form of distributed generation, and its output is random and fluctuating. The high penetration of renewable energy will weaken the security and economy of the electric distribution network. In view of the uncertainty of renewable power output, Monte Carlo simulation method and simultaneous backward reduction method are used to scenario generation and reduction of wind power and photovoltaic, so as to represent their randomness. On this basis, a two-stage optimization strategy for Volt/Var coordination in distribution network is proposed. In the first stage, a network reconfiguration model with the goal of minimizing the power loss of the system is established, and the particle swarm optimization algorithm is used to solve it. In the second stage, a Volt/Var optimization model with the goal of minimizing the node voltage offset and the system power loss is established, and the multi-objective model is solved by combining the network topology obtained in the first stage with the reactive power adjustment device and voltage regulating equipment such as switching capacitor, static var compensator and on-line tap changer. The distribution network’s Volt/Var is optimized using the non-dominated sorted genetic algorithm-II. The optimization results of the first stage are regarded as the conditions of the second stage. Lastly, the IEEE 33-node extension system is used to validate the effectiveness of the suggested strategy.

With the proposal of “double carbon strategy” and new power system construction, the increasing proportion of renewable energy sources and the wide access of power line sub-devices, the inertia support capacity of the power grid is gradually weakened and shows low inertia characteristics, which seriously threatens the system operation safety and frequency stability. In order to comprehensively grasp the operation status of the new power system and ensure its frequency stability, this paper proposes a renewable energy virtual control theory based on the established frequency response model of new power systems considering multiple inertial resources. Secondly, the inertial safety region (ISR) of the new power system considering the virtual inertia and frequency regulation capability of renewable energy is proposed to determine the frequency stability boundary, and its estimation method and procedure are introduced in detail. Finally, a case study and analysis are conducted in the New England system with actual operational data to verify the feasibility and effectiveness of the proposed method. The simulation results show that the method can effectively identify the ISR of the new power system and analyze the mechanism of the influence of renewable energy on ISR, and relevant conclusions are drawn from the simulation results.

Cu–Al2O3–TiB2 is an important high-performance dual-phase dispersion strengthened copper alloy. The problem of serious coarseness and agglomeration of TiB2 and Al2O3 particles is a bottleneck that restricts the preparation of high-performance Cu–Al2O3–TiB2 alloys by traditional liquid-phase in-situ reaction method. In this paper, an idea of combining the split cavity melting of complex reactants and efficient solidification of melt was proposed, and a new liquid phase in-situ reaction technology for dual-phase strengthened metal matrix composites was invented. Compared with the traditional liquid phase in-situ reaction method, the strengthening particles in the Cu-0.75Al2O3-0.75TiB2 (wt.%, nominal composition) prepared by the new liquid phase in-situ reaction technology were more uniform, and the tensile strength and hardness were significantly improved. Large-deformation cold rolling can improve distribution of particles. With the increase of deformation, the main deformation mode of the composite changed from matrix plastic deformation to matrix-particle shear deformation, with the main fracture mechanism changing from particle-matrix interface fracture to particle shear fracture. The new liquid phase in-situ reaction technology effectively solved the problem of particle coarsening and agglomeration in Cu–Al2O3–TiB2 composites. The new liquid phase in-situ reaction technology combined with large deformation is a new process with high efficiency and short flow for preparing dual-phase dispersion strengthened copper alloys.

Abstract Modern scanning microscopes can image materials with up to sub-atomic spatial and sub-picosecond time resolutions, but these capabilities come with large volumes of data, which can be difficult to store and analyze. We report the Fast Autonomous Scanning Toolkit (FAST) that addresses this challenge by combining a neural network, route optimization, and efficient hardware controls to enable a self-driving experiment that actively identifies and measures a sparse but representative data subset in lieu of the full dataset. FAST requires no prior information about the sample, is computationally efficient, and uses generic hardware controls with minimal experiment-specific wrapping. We test FAST in simulations and a dark-field X-ray microscopy experiment of a WSe2 film. Our studies show that a FAST scan of

Abstract The immense potential of lead-free dielectric capacitors in advanced electronic components and cutting-edge pulsed power systems has driven enormous investigations and evolutions heretofore. One of the significant challenges in lead-free dielectric ceramics for energy-storage applications is to optimize their comprehensive characteristics synergistically. Herein, guided by phase-field simulations along with rational composition-structure design, we conceive and fabricate lead-free Bi0.5Na0.5TiO3-Bi0.5K0.5TiO3-Sr(Sc0.5Nb0.5)O3 ternary solid-solution ceramics to establish an equitable system considering energy-storage performance, working temperature performance, and structural evolution. A giant W rec of 9.22 J cm−3 and an ultra-high ƞ ~ 96.3% are realized in the BNKT-20SSN ceramic by the adopted repeated rolling processing method. The state-of-the-art temperature (W rec ≈ 8.46 ± 0.35 J cm−3, ƞ ≈ 96.4 ± 1.4%, 25–160 °C) and frequency stability performances at 500 kV cm−1 are simultaneously achieved. This work demonstrates remarkable advances in the overall energy storage performance of lead-free bulk ceramics and inspires further attempts to achieve high-temperature energy storage properties.

Abstract Background The Qinghai-Tibet Plateau is the “sensitive area” of climate change, and also the “driver” and “amplifier” of global change. The response and feedback of its carbon dynamics to climate change will significantly affect the content of greenhouse gases in the atmosphere. However, due to the unique geographical environment characteristics of the Qinghai-Tibet Plateau, there is still much controversy about its carbon source and sink estimation results. This study designed a new algorithm based on machine learning to improve the accuracy of carbon source and sink estimation by integrating multiple scale carbon input (net primary productivity, NPP) and output (soil heterotrophic respiration, Rh) information from remote sensing and ground observations. Then, we compared spatial patterns of NPP and Rh derived from the fusion of multiple scale data with other widely used products and tried to quantify the differences and uncertainties of carbon sink simulation at a regional scale. Results Our results indicate that although global warming has potentially increased the Rh of the Qinghai-Tibet Plateau, it will also increase its NPP, and its current performance is a net carbon sink area (carbon sink amount is 22.3 Tg C/year). Comparative analysis with other data products shows that CASA, GLOPEM, and MODIS products based on remote sensing underestimate the carbon input of the Qinghai-Tibet Plateau (30–70%), which is the main reason for the severe underestimation of the carbon sink level of the Qinghai-Tibet Plateau (even considered as a carbon source). Conclusions The estimation of the carbon sink in the Qinghai-Tibet Plateau is of great significance for ensuring its ecological barrier function. It can deepen the community’s understanding of the response to climate change in sensitive areas of the plateau. This study can provide an essential basis for assessing the uncertainty of carbon sources and sinks in the Qinghai-Tibet Plateau, and also provide a scientific reference for helping China achieve “carbon neutrality” by 2060.

Abstract Background CDC42 is a member of Rho GTPase family, acting as a molecular switch to regulate cytoskeleton organization and junction maturation of epithelium in organ development. Tooth root pattern is a highly complicated and dynamic process that dependens on interaction of epithelium and mesenchyme. However, there is a lack of understanding of the role of CDC42 during tooth root elongation. Methods The dynamic expression of CDC42 was traced during tooth development through immunofluorescence staining. Then we constructed a model of lentivirus or inhibitor mediated Cdc42 knockdown in Herwig’s epithelial root sheath (HERS) cells and dental papilla cells (DPCs), respectively. Long-term influence of CDC42 abnormality was assessed via renal capsule transplantation and in situ injection of alveolar socket. Results CDC42 displayed a dynamic spatiotemporal pattern, with abundant expression in HERS cells and apical DPCs in developing root. Lentivirus-mediated Cdc42 knockdown in HERS cells didn’t disrupt cell junctions as well as epithelium-mesenchyme transition. However, inhibition of CDC42 in DPCs undermined cell proliferation, migration and odontogenic differentiation. Wnt/β-catenin signaling as the downstream target of CDC42 modulated DPCs’ odontogenic differentiation. The transplantation and in situ injection experiments verified that loss of CDC42 impeded root extension via inhibiting the proliferation and differentiation of DPCs. Conclusions We innovatively revealed that CDC42 was responsible for guiding root elongation in a mesenchyme-specific manner. Furthermore, CDC42-mediated canonical Wnt signaling regulated odontogenic differentiation of DPCs during root formation.

Low-earth orbit satellites have the advantages of wide bandwidth, low latency, and large coverage, making them very suitable as a supplement to ground cellular networks.Low-earth orbit satellites can meet the requirements of smart high-speed railway full line coverage and seamless connection, which helps to build an integrated communication network between ground and space.Considered the shortcomings of the current railway mobile communication network, the application and key technologies of low earth orbit satellites in smart high-speed railway were studied.Firstly, the communication requirements of smart high-speed railway were analyzed, and then the development status of railway satellite communication at home and abroad were introduced.Finally, the key technologies and challenges of low earth orbit satellite application in the field of smart high-speed rail were discussed from the aspects of propagation characteristics, physical layer parameters, beam handover, and resource management.

Purpose: The purpose of this study was to clarify the effect of ZC3H13 on the growth of papillary thyroid carcinoma (PTC). Methods: Firstly, we used qRT-PCR and Western blot to compare the difference in the expression of ZC3H13 between normal thyroid epithelial cells and PTC cell lines. Then, ZC3H13 overexpression/knockout thyroid cancer cells were constructed by lentivirus transfection, and the effects of overexpression of ZC3H13 on the proliferation, migration and invasion of PTC cells were detected by CCK8 and transwell experiments. Lastly, MeRIP-qPCR, RIP and o Actinomycin D were used to verify that ZC3H13 regulated the expression of downstream target gene IQGAP1 through m6A modification. Results: ZC3H13 expression was decreased in PTC cell lines BCPAP, KTC-1, k1, HTH83, and TPC-1. Proliferation, invasion, and migration of PTC cells were inhibited by overexpressed ZC3H13 but increased by knockdown of ZC3H13. IQGAP1 expression was suppressed by ZC3H13 overexpression but enhanced by ZC3H13 knockdown. In ZC3H13-overexpressed PTC cells, the m6A level of IQGAP1 mRNA was increased, and the IQGAP1 mRNA expression was decreased with the increasing time of Actinomycin D treatment. YTHDF2 enriched more IQGAP1 mRNA than IgG and knockdown of YTHDF2 reversed the effect of ZC3H13 overexpression on IQGAP1 mRNA stability. The xenograft tumor experiment in nude mice confirmed that the overexpression of ZC3H13 inhibited tumor growth, while overexpression of IQGAP1 could reverse the inhibitory effect of ZC3H13 overexpression on tumor growth. Conclusion: ZC3H13 mediates IQGAP1 mRNA degradation by promoting m6A modification of IQGAP1 mRNA, this provides a prospective therapeutic target for PTC.

Abstract Background This study analyzed the clinical features and biomarkers of alcohol-associated liver disease (ALD) to investigate the diagnostic value of age, bilirubin, international normalized ratio (INR), and creatinine (ABIC) score to triglyceride (TG) ratio (ABIC/TG) in ALD-associated primary liver carcinoma (PLC). Materials and methods Data were collected from 410 participants with ALD, and the epidemiological and clinical records of 266 participants were analyzed. Participants were divided into ALD-without-PLC and ALD-associated-PLC groups. Relationships between clinical characteristics, biomarkers and ALD-associated PLC were estimated. Serum lipid levels and liver function were compared between ALD patients without PLC and patients with ALD-associated PLC. Scoring systems were calculated to investigate ALD severity. The robustness of the relationship was analyzed by the receiver operating characteristic (ROC) curve. Results Age and dyslipidemia were more strongly associated with ALD-associated PLC than with ALD-without PLC, with AORs of 2.39 and 0.25, respectively, with P less than 0.05. Drinking time and average daily intake, ABIC score, and ABIC/TG ratio were significantly higher in the ALD-associated-PLC group than in the ALD-without-PLC group. The AUC for the ABIC/TG ratio predicting the incidence of PLC was 0.80 (P

Abstract The neutron capture cross section of $$ ^{181} $$ 181 Ta is relevant to s-process of nuclear astrophysics, extraterrestrial samples analysis in planetary geology and new generation nuclear energy system design. The $$^{181}$$ 181 Ta( $$n,\gamma $$ n , γ ) cross section had been measured between 1 eV and 800 keV at the back-streaming white neutron facility (Back-n) of China spallation neutron source(CSNS) using the time-of-flight (TOF) technique and $$\hbox {C}_{6}\,\hbox {D}_{6}$$ C 6 D 6 liquid scintillator detectors. The experimental results are compared with the data of several evaluated libraries and previous experiments in the resolved and unresolved resonance region. Resonance parameters are extracted using the R-Matrix code SAMMY in the 1–700 eV region. The astrophysical Maxwell average cross section(MACS) from kT = 5 to 100 keV is calculated over a sufficiently wide range of neutron energies. For the characteristic thermal energy of an astrophysical site, at kT = 30keV the MACS value of $$^{181}$$ 181 Ta is 834 ± 75 mb, which shows an obvious discrepancy with the Karlsruhe Astrophysical Database of Nucleosynthesis in Stars (KADoNiS) recommended value 766 ± 15 mb. The new measurements strongly constrain the MACS of $$^{181}$$ 181 Ta( $$n,\gamma $$ n , γ ) reaction in the stellar s-process temperatures.

Abstract Covering array generation (CAG) is the key research problem in combinatorial testing and is an NP‐complete problem. With the increasing complexity of software under test and the need for higher interaction covering strength t, the techniques for constructing high‐strength covering arrays are expected. This paper presents a hybrid heuristic memetic algorithm named QSSMA for high‐strength CAG problem. The sub‐optimal solution acceptance rate is introduced to generate multiple test cases after each iteration to improve the efficiency of constructing high‐covering strength test suites. The QSSMA method could successfully build high‐strength test suites for some instances where t up to 15 within one day cutoff time and report five new best test suite size records. Extensive experiments demonstrate that QSSMA is a competitive method compared to state‐of‐the‐art methods.

BackgroundTillage practices can substantially affect soil properties depending on crop stage. The interaction between tillage and crop growth on arbuscular mycorrhizal fungi (AMF) communities remains unclear. We investigated the interactions between four tillage treatments (CT: conventional tillage, RT: reduced tillage, NT: no tillage with mulch, and SS: subsoiling with mulch), maintained for 25 years, and two wheat growth stages (elongation stage and grain filling stage) on AMF diversity and community composition.ResultsThe AMF community composition strongly changed during wheat growth, mainly because of changes in the relative abundance of dominant genera Claroideoglomus, Funneliformi, Rhizophagu, Entrophospora, and Glomus. Co-occurrence network analysis revealed that the grain filling stage had a more complex network than the elongation stage. Redundancy analysis results showed that keystone genera respond mainly to changes in soil organic carbon during elongation stage, whereas the total nitrogen content affected the keystone genera during grain filling. Compared with CT, the treatments with mulch, i.e., NT and SS, significantly changed the AMF community composition. The change of AMF communities under different tillage practices depended on wheat biomass and soil nutrients. NT significantly increased the relative abundances of Glomus and Septoglomus, while RT significantly increased the relative abundance of Claroideoglomus.ConclusionOur findings indicate that the relative abundance of dominant genera changed during wheat growth stages. Proper tillage practices (e.g., NT and SS) benefit the long-term sustainable development of the Loess Plateau cropping systems.

A new Cu-1.5Ni-0.7Co-0.7Si-0.3Fe-0.1Mg alloy with low cobalt content was designed. Multi-stage thermo-mechanical treatment (MTT) was used to produce the high-performance alloy with hardness of 286 HV, yield strength of 858 MPa, tensile strength of 910 MPa and electrical conductivity of 45.4 % IACS. The addition of 0.3 wt% Fe element dissolved in (Ni,Co)2Si resulted in the formation of the orthorhombic δ-(Ni,Co,Fe)2Si. During MTT, the δ-(Ni,Co,Fe)2Si, (Ni,Co)2Si, β-Ni3Si, and Fe2Si precipitated successively near the deformation microstructure. Transmission electron microscope observations indicated that the δ-(Ni,Co,Fe)2Si precipitates showed disc-like and rod-like shapes at different orientations, respectively. A new resource-saving, high-strength and medium-conductivity Cu-Ni-Co-Si-Fe-Mg alloy was prepared by replacing an equal amount of Co element with 0.3 wt% Fe element, reducing the amount of scarce metal Co in the alloy.

ABSTRACTMetabolic maladaptation in dairy cows after calving can lead to long-term elevation of ketones, such as β-hydroxybutyrate (BHB), representing the condition known as hyperketonemia, which greatly influences the health and production performance of cows during the lactation period. Although the gut microbiota is known to alter in dairy cows with hyperketonemia, the association of microbial metabolites with development of hyperketonemia remains unknown. In this study, we performed a multi-omics analysis to investigate the associations between fecal microbial community, fecal/plasma metabolites, and serum markers in hyperketonemic dairy cows during the transition period. Dynamic changes in the abundance of the phyla Verrucomicrobiota and Proteobacteria were detected in the gut microbiota of dairy cows, representing an adaptation to enhanced lipolysis and abnormal glucose metabolism after calving. Random forest and univariate analyses indicated that Frisingicoccus is a key bacterial genus in the gut of cows during the development of hyperketonemia, and its abundance was positively correlated with circulating branched-chain amino acid levels and the ketogenesis pathway. Taurodeoxycholic acid, belonging to the microbial metabolite, was strongly correlated with an increase in blood BHB level, and the levels of other secondary bile acid in the feces and plasma were altered in dairy cows prior to the diagnosis of hyperketonemia, which link the gut microbiota and hyperketonemia. Our results suggest that alterations in the gut microbiota and its metabolites contribute to excessive lipolysis and insulin insensitivity during the development of hyperketonemia, providing fundamental knowledge about manipulation of gut microbiome to improve metabolic adaptability in transition dairy cows.IMPORTANCEAccumulating evidence is pointing to an important association between gut microbiota-derived metabolites and metabolic disorders in humans and animals; however, this association in dairy cows from late gestation to early lactation is poorly understood. To address this gap, we integrated longitudinal gut microbial (feces) and metabolic (feces and plasma) profiles to characterize the phenotypic differences between healthy and hyperketonemic dairy cows from late gestation to early lactation. Our results demonstrate that cows underwent excessive lipid mobilization and insulin insensitivity before hyperketonemia was evident. The bile acids are functional readouts that link gut microbiota and host phenotypes in the development of hyperketonemia. Thus, this work provides new insight into the mechanisms involved in metabolic adaptation during the transition period to adjust to the high energy and metabolic demands after calving and during lactation, which can offer new strategies for livestock management involving intervention of the gut microbiome to facilitate metabolic adaptation.

Summary: C1orf112/FIRRM is a recently identified DNA damage repair factor that regulates RAD51 in homologous recombination through interacting with the anti-recombinase FIGNL1. Here, we describe steps for purifying C1orf112/FIRRM, FIGNL1, miBRCA2, and RAD51 proteins from Escherichia coli or Saccharomyces cerevisiae cells. We then detail procedures for reconstituting the disassembly of RAD51 filament by C1orf112/FIRRM-FIGNL1 in vitro and the antagonistic effect between C1orf112/FIRRM-FIGNL1 and miBRCA2 on RAD51 filament stabilization.For complete details on the use and execution of this protocol, please refer to Zhou et al. (2023).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Communication among the brain, gut and microbiota in the gut is known to affect the susceptibility to stress, but the mechanisms involved are unclear. Here we demonstrated that stress resistance in mice was associated with more abundant Lactobacillus and Akkermansia in the gut, but less abundant Bacteroides, Alloprevotella, Helicobacter, Lachnoclostridium, Blautia, Roseburia, Colidextibacter and Lachnospiraceae NK4A136. Stress-sensitive animals showed higher permeability and stronger immune responses in their colon, as well as higher levels of pro-inflammatory cytokines in serum. Their hippocampus also showed more extensive microglial activation, abnormal interactions between microglia and neurons, and lower synaptic plasticity. Transplanting fecal microbiota from stress-sensitive mice into naïve ones perturbed microglia-neuron interactions and impaired synaptic plasticity in the hippocampus, translating to more depression-like behavior after stress exposure. Conversely, transplanting fecal microbiota from stress-resistant mice into naïve ones protected microglia from activation and preserved synaptic plasticity in the hippocampus, leading to less depression-like behavior after stress exposure. These results suggested that gut microbiota may influence resilience to chronic psychological stress by regulating microglia-neuron interactions in the hippocampus.

Abstract Introduction The objective of this study was to investigate changes in vision‐related resting‐state activity in patients with suprasellar tumors (ST) who experienced vision deterioration after surgery. Methods Twelve patients with ST and vision deterioration after surgery were included in the study. Resting‐state functional connectivity (FC) was compared before and after surgery using a seed‐based analysis with a priori specified regions of interest (ROIs) within the visual areas. The differences between the two groups were identified using a paired t‐test. Results The data showed a decrease in FC within and between the dorsal and ventral pathways, as well as in the third pathway in ST patients. The middle temporal visual cortex (MT+) showed a decreased FC with more regions than other visual ROIs. The data also revealed an increase in FC between the visual ROIs and higher‐order cortex. The superior frontal gyrus/BA8 showed an increased FC with more ROIs than other high‐order regions, and the hOC4d was involved in an increased FC with more high‐order regions than other ROIs. Conclusions The study results indicate significant neural reorganization in the vision‐related cortex of ST patients with postoperative vision damage. Most subareas within the visual cortex showed remarkable neural dysfunction, and some highe‐order cortex may be primarily involved in top‐down control of the subareas within the visual cortex. The hot zones may arise in the processing of “top‐down” influence.