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Abstract Currently, even the most effective anti-cancer therapies are often limited by the development of drug resistance and tumor relapse, which is a major challenge facing current cancer research. A deep understanding of the molecular and biochemical bases of drug efficacy that can help predict the clinical drug resistance, coupled with the evolution of systematic genomic and proteomic technologies, have facilitated studies identifying and elucidating the underlying mechanisms. In this review, we focus on several important issues on cancer drug resistance and provide a framework for understanding the common ways by which cancers develop resistance to therapeutic agents. With the increasing arsenal of novel anticancer agents and techniques, there are now unprecedented opportunities to understand and overcome drug resistance. The proteolysis targeting chimera (PROTAC) technology, immunotherapy, nanomedicine, and real-time monitoring of drug response all provide effective approaches for combating drug resistance. In addition to the advancement of therapeutic technologies, the revolution of treatment concept is also of great importance. We can take advantage of the interplay between drug sensitive and resistant subclones for combating cancer. However, there remains a long way to go in the protracted war against cancer drug resistance.

Objectives: The aim of this study was to characterise the first complete genome of Porphyromonas pogonae strain PP01-1 of human origin in China. Methods: The Illumina NovaSeq 6000 (200X coverage) and Nanopore MinION platforms (100× coverage) were used for genome sequencing. A de novo hybrid assembly of short Illumina reads and long MinION reads was performed using Unicycler (v.0.5.0). Genome annotation of PP01-1 was performed using the prokaryotic gene-prediction tool Prokka1.14.6. The genome was further analysed using several bioinformatics tools, including ResFinder, VFDB, VirulenceFinder, Type Strain Genome Server, AntiSMASH, PathogenFinder, MobileElementfinder, CRISPRFinder, and IslandViewer. Results: The assembled circular genome of P. pogonae strain PP01-1 was 2 916 423 bp in length, with a GC content of 41.0%, and no plasmid sequence was detected. A total of 2399 coding sequences were predicted by Prokka. PP01-1 harbours antimicrobial resistance genes blaOXA-347 (β-lactamase resistance), tet(Q) (tetracycline resistance), and floR (chloramphenicol and florfenicol resistance). Conclusions: Here, we are the first to report the complete genome of P. pogonae strain PP01-1 of human origin. In this strain, we first identified blaOXA-347 and tet(Q) in P. pogonae, which will pave the way for further analysis that could identify the potential mechanism of antibiotic resistance and virulence factors in P. pogonae.

Abstract The dense mechanoreceptors in human fingertips enable texture discrimination. Recent advances in flexible electronics have created tactile sensors that effectively replicate slowly adapting (SA) and rapidly adapting (RA) mechanoreceptors. However, the influence of dermatoglyphic structures on tactile signal transmission, such as the effect of fingerprint ridge filtering on friction‐induced vibration frequencies, remains unexplored. A novel multi‐layer flexible sensor with an artificially synthesized skin surface capable of replicating arbitrary fingerprints is developed. This sensor simultaneously detects pressure (SA response) and vibration (RA response), enabling texture recognition. Fingerprint ridge patterns from notable historical figures – Rosa Parks, Richard Nixon, Martin Luther King Jr., and Ronald Reagan – are fabricated on the sensor surface. Vibration frequency responses to assorted fabric textures are measured and compared between fingerprint replicas. Results demonstrate that fingerprint topography substantially impacts skin‐surface vibrational transmission. Specifically, Parks' fingerprint structure conveyed higher frequencies more clearly than those of Nixon, King, or Reagan. This work suggests individual fingerprint ridge morphological variation influences tactile perception and can confer adaptive advantages for fine texture discrimination. The flexible bioinspired sensor provides new insights into human vibrotactile processing by modeling fingerprint‐filtered mechanical signals at the finger‐object interface.

Abstract Geographic Information Systems (GIS)-based technologies are increasingly crucial in the domain of cultural heritage conservation, facilitating the construction of dynamic information management systems and serving as robust platforms for research and display. This review utilizes CiteSpace and Bibliometrix R language to perform a bibliometric analysis of academic literature sourced from the Web of Science (WoS) Core Collection, focusing on the application of GIS in cultural heritage conservation. The analysis covers a broad spectrum of academic articles, identifying research hotspots, patterns of national cooperation, interdisciplinary mobility, knowledge structure, and developmental trends. The findings reveal that this research area is experiencing a phase of steady growth. While three emerging trends have been identified, demonstrating significant theoretical and technical advancements, there remains considerable potential for enhancing in their practical implication within conservation efforts. The study advocates for the integration of digital technologies into the humanities, emphasizing the need for a heritage database equipped with standardized data exchange protocols to support display and analytical functions. This systematic research approach not only illuminates new strategies for the inheritance and innovation in the conservation of cultural heritage, but also paves the way for future explorations in this increasingly vital field.

Aiming at the problem that the change of the inclination angle of the main truss has a great influence on the aerodynamic characteristics of inverted trapezoidal steel trusses，taking a public-rail continuous steel truss as an example, the effect of main truss inclination on the aerodynamic characteristics of inverted trapezoidal steel truss was investigated. A simplified three-dimensional analysis model was established by using computational fluid dynamics (CFD) method for different main truss inclination angles to simulate the wind field of main turss sections with different main truss inclination angles. The differences of static wind aerodynamic coefficient, vortex vibration performance and flow field characteristics of main truss sections with different main truss inclination angles were analyzed. The results show that the lift and moment coefficients are significantly influenced by the change of main truss inclination, the lift coefficient of the steel truss is better when the inclination angle of the main truss is 10°, at this time the steel truss is subjected to smaller vertical wind load, and the moment coefficient of the steel joist is better when the inclination angle of the main truss is 0°, at this time the steel truss is subjected to smaller torsional wind load; the main truss inclination angle has a significant effect on its vortex excitation performance under 0° and 6° wind angle of attack conditions, and the vortex vibration performance is better at the main truss inclination angles of 2.5° and 5°;the deceleration phenomenon of wind velocity inside the steel truss decreases with the increase of main truss inclination, it contributes to internal traffic stabilization; the change of main truss inclination has obvious effect on the distribution of turbulent kinetic energy, the effect of increase of turbulent kinetic energy inside the steel truss decreases with the increase of main truss inclination and the effect of increase of turbulent kinetic energy on the leeward side of the steel truss strengthens. By comprehensively comparing multiple types of aerodynamic properties, the aerodynamic characteristics of steel trusses with main truss inclination angles of 5° are better. The influence of the change of main truss inclination angle on the aerodynamic characteristics and spatial flow field characteristics of inverted trapezoidal steel truss can provide a reference for the subsequent wind-resistant design of steel truss.

An oxidising and substituting one-pot reaction strategy has been developed to synthesise dihydromyricetin derivatives with the aim of enhancing the inhibitory activity of dihydromyricetin against SARS-CoV-2. Different ω-methoxy-ω-oxeylkyl was introduced in C7-OH site and yielded eight analogs, all of them showed good inhibitory activity against SARS-CoV-2 3CLpro with IC50 values ranging from 0.72 to 2.36 μM. In the Vero E6-cell, compound 3 has a good activity of anti-SARS-CoV-2 virus (Omicron virus BA.5) in the prevention model, with an EC50 of 15.84 μM, and so do compound 10 in the therapeutic model, with an EC50 of 11.52 μM. The results suggest that the introduction of long chain ω-oxeylkyl at C7-OH facilitate the inhibition of viral replication in the therapeutic model, which is consistent with the binding energies predicted from molecular docking conclusions. It implies that dihydromyricetin derivatives have the potential to become effective inhibitors of SARS-CoV-2 Omicron and other viruses.

ABSTRACTFollowing the national dynamic zero-COVID strategy adjustment, the utilization of broad-spectrum nasal neutralizing antibodies may offer an alternative approach to controlling the outbreak of Omicron variants between late 2022 and early 2023 in China. This study involved an investigator-initiated trial (IIT) to assess the pharmacokinetic, safety and efficacy of the F61 nasal spray. A total of 2,008 participants were randomly assigned to receive F61 nasal spray (24 mg/0.8 mL/dose) or normal saline (0.8 mL/dose) and 1336 completed the follow-up in the IIT. Minimal absorption of F61 antibody into the bloodstream was detected in individuals receiving F61 nasal spray for seven consecutive days. No treatment-emergent adverse reactions of grade 3 severity or higher were reported. In the one-dose cohort, the 7-day cumulative SARS-CoV-2 infection rate was 79.0% in the F61 group and 82.6% in the placebo group, whereas, in the multiple-dose (once daily for 7 consecutive days) cohort, the rates were 6.55% in the F61 group and 23.83% in the placebo group. The laboratory-confirmed efficacy of F61 was 3.78% (−3.74%–10.75%) in the one-dose cohort and 72.19% (57.33%–81.87%) in the multiple-dose cohort. In the real-world study, 60,225 volunteers in four different regions were administered the F61 nasal spray based on the subject's wishes, over 90% efficacy rate was observed against different Omicron variants. The F61 nasal spray, with its favourable safety profile, could be a promising prophylactic monoclonal antibody against SARS-CoV-2 VOCs.

IntroductionThe connection between aging and cancer is complex. Previous research has highlighted the association between the aging process of lung adenocarcinoma (LUAD) cells and the immune response, yet there remains a gap in confirming this through single-cell data validation. Here, we aim to develop a novel aging-related prognostic model for LUAD, and verify the alterations in the genome and immune microenvironment linked to cellular senescence.MethodsWe integrated a comprehensive collection of senescence genes from the GenAge and CellAge databases and employed the least absolute shrinkage and selection operator (LASSO) Cox analysis to construct and validate a novel prognostic model for LUAD. This model was then utilized to examine the relationship between aging, tumor somatic mutations, and immune cell infiltration. Additionally, we explored the heterogeneity of senescence and intercellular communication within the LUAD tumor microenvironment (TME) through single-cell transcriptomic data analysis.ResultsBy exploring the expression profiles of 586 cellular senescence-related genes in 428 LUAD patients, we constructed an aging-related genes (ARGs) risk model included 10 ARGs and validated it as an independent prognostic predictor for LUAD patients. Notably, patients with low aging scores (LAS group) exhibited better survival, lower tumor mutation burden (TMB), lower somatic mutation frequency, lower tumor proliferation rate, and an immune activated phenotype compared to patients with high aging scores (HAS group). While the HAS group was enriched in tumor cells and showed a lower infiltration of CD8-CCR7, CD8- CXCL13, CD8-GNLY, FCGR3A NK cells, XCL1 NK cells, plasma cell (PC) and other immune subsets. Furthermore, the SPP1 and TENASCIN pathways, associated with tumor immune escape and tumor progression, were also enriched in the HAS group. Additionally, our study also indicated that senescence levels were heterogeneous in the LUAD tumor microenvironment (TME), especially with tumor cells in the LAS group showing higher age scores compared to those in the HAS group.ConclusionsCollectively, our findings underscore that ARRS through ARGs serves as a robust biomarker for the prognosis in LUAD.

Liposomes have been widely studied as drug carriers for clinical application, and the key issue is how to achieve effective delivery through targeting strategies. Even though certain cell-level targeting or EPR effect designs have been developed, reaching sufficient drug concentration in intracellular regions remains a challenge due to the singularity of functionality. Herein, benefiting from the unique features of tumor from tissue to cell, a dual-thermosensitive and dual-targeting liposome (DTSL) was creatively fabricated through fine microstructure tailoring, which holds intelligent both tissue-regulated active-to-passive binding and membrane-derived homologous-fusion (HF) properties. At the micro level, DTSL can actively capture tumor cells and accompany the enhanced HF effect stimulated by self-constriction, which achieves a synergistic promotion effect targeting tissues to cells. As a result, this first active-then passive targeting process makes drug delivery more accurate and effective, and after dynamic targeting into cells, the nucleus of DTSL undergoes further thermally responsive contraction, fully releasing internal drugs. In vivo experiments showed that liposomes with dual targeting and dual thermosensitive features almost completely inhibited tumor growth. Summarized, these results provide a reference for a rational design and microstructural tailoring of the liposomal co-delivery system of drugs, suggesting that active-to-passive dual-targeting DTSL can function as a new strategy for cancer treatment.

In complex traffic environment, it is still a great challenge for Autonomous Vehicles (AVs) to understand the surrounding drivers’ Lane-Changing Decision (LCD) intention accurately. The LCD intention is affected by Driver’s Psychology (DP) and Driving Style (DS). But few LCD studies considered DP and DS simultaneously. We previously proposed a LCD model, by combing DP and DS, termed as DP&DS-LCD model. Nevertheless, there are some factors not fully considered in this model, including the driver’s Visual Attention (VA) in DP quantification and the influence of driving state on DS. Therefore, an enhanced LCD Model is developed, by integrating the DP under VA (DPVA) and DS Layering (DSL), named as DPVA&DSL-LCD model. In the model, a psychological field model coupling driver’s VA mechanism is established to represent the surrounding vehicles’ influence on the driver. Then, a DSL framework is proposed by adding the influence of driving state on DS. The Gaussian Mixture Model (GMM) clustering and Support Vector Machine (SVM) classifier are respectively adopted in training and recognition phases to identify the current driving style. Finally, integrating the DPVA and DSL, the Light Gradient Boosting Machine (LightGBM) algorithm is used to train the LCD model. In experiments, the open I-80 database from Next Generation Simulation (NGSIM) is adopted to train the DPVA&DSL-LCD. And compared with other three LCD models, the prediction performance of DPVA&DSL-LCD model achieved the best. Therefore, the DPVA&DSL-LCD model is effective and could provide support for the decision-making of AVs by predicting surrounding vehicles’ LCD intention.

Acoustic emission (AE) source localization technology, since the early application to one-dimensional structures, has been extended to a wide range of applications to two-dimensional (2D) structures, including isotropic and anisotropic materials, which are currently the most widely studied and the most mature. With the development of AE source localization technology, more and more significant challenges have arisen for three-dimensional (3D) structures, which are mostly anisotropic and have complex propagation paths. This paper summarizes and discusses the AE source localization methods in different dimensions as well as their applications, including the main methods for 2D AE source localization, such as the triangulation method, beam forming, strain rosette technique, modal AE, artificial neural network, optimization and the time reversal technique, as well as state-of-the-art AE source localization methods in isotropic and anisotropic structures utilizing these methods. Recent advances in AE source localization in complex 3D structures are also reviewed.

Flexible user-side resources are of great potential in providing power regulation so as to effectively address the challenges of reverse power flow and overvoltage issues in distribution networks characterized by high photovoltaic (PV) penetration. However, existing distributed algorithms typically implement control signals after the convergence of the algorithms, making it difficult to track frequent and rapid fluctuations in PV power outputs in real time. Given this background, an online-distributed control algorithm for the real-time power regulation of flexible user-side resources is proposed in this paper. The objective of the established control model is to minimize network losses by dynamically adjusting active power outputs of flexible user-side resources and reactive power outputs of PV inverters while respecting branch power flow and voltage magnitude constraints. Furthermore, by deconstructing the centralized problem into a primal–dual one, a distributed control strategy based on the dual ascent method is implemented. With the proposed method, agents can achieve global optimality by exchanging limited information with their neighbors. The simulation results verify the good balance between economic efficiency and voltage control performance of the proposed method.

BackgroundPsoriasis extends beyond its dermatological inflammatory manifestations, encompassing systemic inflammation. Existing studies have indicated a potential risk of cervical cancer among patients with psoriasis, suggesting a potential mechanism of co-morbidity. This study aims to explore the key genes, pathways, and immune cells that may link psoriasis and cervical squamous cell carcinoma (CESC).MethodsThe cervical squamous cell carcinoma dataset (GSE63514) was downloaded from the Gene Expression Omnibus (GEO). Two psoriasis-related datasets (GSE13355 and GSE14905) were merged into one comprehensive dataset after removing batch effects. Differentially expressed genes were identified using Limma and co-expression network analysis (WGCNA), and machine learning random forest algorithm (RF) was used to screen the hub genes. We analyzed relevant gene enrichment pathways using GO and KEGG, and immune cell infiltration in psoriasis and CESC samples using CIBERSORT. The miRNA-mRNA and TFs-mRNA regulatory networks were then constructed using Cytoscape, and the biomarkers for psoriasis and CESC were determined. Potential drug targets were obtained from the cMAP database, and biomarker expression levels in hela and psoriatic cell models were quantified by RT-qPCR.ResultsIn this study, we identified 27 key genes associated with psoriasis and cervical squamous cell carcinoma. NCAPH, UHRF1, CDCA2, CENPN and MELK were identified as hub genes using the Random Forest machine learning algorithm. Chromosome mitotic region segregation, nucleotide binding and DNA methylation are the major enrichment pathways for common DEGs in the mitotic cell cycle. Then we analyzed immune cell infiltration in psoriasis and cervical squamous cell carcinoma samples using CIBERSORT. Meanwhile, we used the cMAP database to identify ten small molecule compounds that interact with the central gene as drug candidates for treatment. By analyzing miRNA-mRNA and TFs-mRNA regulatory networks, we identified three miRNAs and nine transcription factors closely associated with five key genes and validated their expression in external validation datasets and clinical samples. Finally, we examined the diagnostic effects with ROC curves, and performed experimental validation in hela and psoriatic cell models.ConclusionsWe identified five biomarkers, NCAPH, UHRF1, CDCA2, CENPN, and MELK, which may play important roles in the common pathogenesis of psoriasis and cervical squamous cell carcinoma, furthermore predict potential therapeutic agents. These findings open up new perspectives for the diagnosis and treatment of psoriasis and squamous cell carcinoma of the cervix.

Summary: Background: In resectable oesophageal squamous cell carcinoma (ESCC), the efficacy of camrelizumab combined with chemotherapy and apatinib followed by minimally invasive oesophagectomy is not clear. We aimed to fill this knowledge gap. Methods: This investigator-initiated, single-arm, prospective, phase 2 trial was performed at the Second Affiliated Hospital of Zhejiang University, China. Patients (aged 18–75 years) who were histologically or cytologically diagnosed with ESCC were deemed suitable to participate in this trial. Patients received 2–3 cycles of neoadjuvant therapy with camrelizumab, nedaplatin, albumin paclitaxel, and apatinib; each cycle was repeated every 14 days. Surgery occurred 4–6 weeks after the last neoadjuvant treatment cycle. The primary outcome was the pathological complete response (PCR) rate of the tumour and lymph nodes. The changes in the peripheral blood immunoprofile among patients without PCR (ie, non-PCR [NPCR]) and with PCR were assessed by mass cytometry. This study was registered with ClinicalTrials.gov, NCT04666090. Findings: 42 patients were enrolled between November 23, 2020 and December 31, 2022. The disease control rate was 100.0% (95% CI, 91.6–100%), and the objective response rate was 83.3% (95% CI, 68.6–93.0%). Six (14.3%) patients experienced grade 3 adverse events. The most common were white blood cell count decrease (31.0%), alopecia (81.0%), asthenia (38.1%), and reactive cutaneous capillary endothelial proliferation (35.7%). 41 patients received minimally invasive oesophagectomy; all 41patients achieved R0 resection, and 18 (43.9%, 95% CI, 28.5–60.3%) patients achieved PCR. The median follow-up was 23 months and the 2-year survival rate was 85.9%. T-cell subsets in both the PCR and NPCR groups exhibited consistency in response to neoadjuvant therapy. In contrast, some of natural killer (NK) cells (NK-C03, NK-C11), B cells (B-C06) and monocytes (M-C05), exhibited significant differences between the PCR and NPCR groups before neoadjuvant therapy. M-C06 had a significant difference in the PCR group and NPCR group after neoadjuvant therapy. NK-C12 and B-C15 showed significant differences both before and after neoadjuvant therapy. Interpretation: The application of camrelizumab, chemotherapy and apatinib in the neoadjuvant setting for locally advanced ESCC has shown promising antitumour activity and an acceptable safety profile in this single-arm study. In the neoadjuvant setting, NK cell, B cell, and monocyte subsets exhibited greater predictive power for immunotherapy responsiveness than T-cell subsets. Longer follow-up to assess survival outcomes and a phase 3 randomised trial are needed to further evaluate the proposed treatment. Funding: The China Anti-Cancer Association and the “Leading Goose” Research and Development Project of Zhejiang Province.

Wind barriers with different parameters will change the aerodynamic force of the car on the bridge as well as the stability of the vehicle–bridge system, affecting the vehicle’s safety and comfort. A numerical simulation test was conducted on the bridge-deck with three different air permeability wind barriers under three distinct vehicles of varying sizes and wind directions, with a large-span road–rail asymmetric cable-stayed bridge serving as the engineering foundation. The results show that the roll force of the bridge is proportional to the width of the body and inversely related to the height of the train. The roll force of a vehicle is inversely proportional to its height and width. The type of vehicle and the properties of the bridge deck exert minimal influence on the stability of the bridge when a single vehicle is positioned upstream. When a single vehicle is situated downstream, the tri-component force coefficient of the bridge undergoes significant changes, and the vehicle’s impact on the bridge’s stability becomes more pronounced. When the bridge deck’s ventilation rate is at 50%, the drag coefficient of the bridge deck doubles compared to that of a bare bridge deck, and the wind pressure coefficient of the vehicle surface on the bridge approaches zero. In scenarios involving two vehicles, the shielding effect caused by the vehicles positioned upstream and downstream results in a substantial shift in the aerodynamic forces acting on the two vehicles. This increases the wake width of the bridge and generates a visible vortex in the wake.

Abstract Purpose The position of the acetabular and femoral components is critical for stability and wear resistance. The aim of this study is to investigate whether the fluoroscopy-guided direct anterior approach in the supine position (S-DAA) is more helpful in improving the position of acetabular and femoral components than the fluoroscopy-guided direct anterior approach in the lateral decubitus position (L-DAA). Methods A retrospective analysis of 76 cases of fluoroscopy-guided direct anterior approach total hip arthroplasty (38 cases in the S-DAA and 38 cases in the L-DAA group) was performed in one hospital from 2019 to 2021. The differences in inclination, anteversion, femoral offset (FO), global offset (GO), and leg length discrepancy (LLD) measurements during and after surgery were analyzed. The postoperative femoral offset (FO), global offset (GO), leg length discrepancy (LLD), and preoperative and postoperative Harris hip score were compared between the two groups. Results In the S-DAA group, there were no significant differences in the mean intraoperative inclination angle anteversion angle, FO, GO, and LLD compared to the postoperative values, whereas in the L-DAA group, there were significant differences between the intraoperative and postoperative measurements (P

Accurate and timely forecasting of traffic on local road networks is crucial for deploying effective dynamic traffic control, advanced route planning, and navigation services. This task is particularly challenging due to complex spatio-temporal dependencies arising from non-Euclidean spatial relations in road networks and non-linear temporal dynamics influenced by changing road conditions. This paper introduces the spatio-temporal network embedding (STNE) model, a novel deep learning framework tailored for learning and forecasting graph-structured traffic data over extended input sequences. Unlike traditional convolutional neural networks (CNNs), the model employs graph convolutional networks (GCNs) to capture the spatial characteristics of local road network topologies. Moreover, the segmentation of very long input traffic data into multiple sub-sequences, based on significant temporal properties such as closeness, periodicity, and trend, is performed. Multi-dimensional long short-term memory neural networks (MDLSTM) are utilized to flexibly access multi-dimensional context. Experimental results demonstrate that the STNE model surpasses state-of-the-art traffic forecasting benchmarks on two large-scale real-world traffic datasets.

Part-time farming is a widespread phenomenon associated with the long-term global trend of urbanization, especially in China since its reform and opening-up in 1978. The shift of agricultural labor to non-agricultural sectors has significantly impacted cultivated land use activities, yet the connection between part-time farming and cultivated land use sustainability (CLS) remains understudied. Here, we construct an index system for assessing CLS that integrates ecological, economic, and social sustainability. Using survey data from seven Chinese villages across three provinces, we analyze the impact pattern and mechanism of part-time farming on CLS. We find the following: (1) The impact of part-time farming on CLS presents an inverted U-shape, peaking negatively at a 45% inflection point; (2) Spatial heterogeneity exists in the effect of part-time farming on CLS; (3) A household’s non-agricultural workforce size and the gender of the household head significantly moderate the link between part-time farming and CLS; (4) CLS strongly hinges on various factors including the household head’s health, other family members’ education levels, commercial insurance, and agricultural skills training. Our findings provide empirical insights into governing part-time farming for sustainable cultivated land use and, eventually, rural human–land system sustainability.

Recycled concrete is a new and environmentally friendly material for future construction. When applying recycled concrete to cold and severe regions, it is necessary to consider the freeze–thaw resistance of recycled concrete. Using an indoor freeze–thaw cycle test system, the rapid freezing method was used to conduct rapid freeze–thaw tests on recycled concrete specimens under set freeze–thaw cycle conditions. Relevant parameters (such as compressive strength, quality loss rate, rebound value) were tested on recycled concrete specimens that completed the set number of freeze–thaw cycles. The influence of various factors (freeze–thaw cycle number, replacement rate of recycled aggregates) on the compressive strength, quality loss rate, and rebound value of recycled concrete was analyzed. The results indicate that with the increase of freeze–thaw cycles and recycled aggregate content, the workability, rebound value, and compressive strength of the specimens decrease, and the quality loss rate increases. The changes in workability of concrete are sharp, with a slump difference of 21 mm between concrete with 100% recycled coarse aggregate and concrete using natural coarse aggregate. The rebound value of the specimen shows a decreasing trend overall, but the rebound value varies for different measuring points on the same specimen. The attenuation of compressive strength is significant. When fully using recycled aggregates to prepare concrete, the compressive strength after 30 freeze–thaw cycles decreases by 49.42% compared to the compressive strength after 0 freeze–thaw cycles. The overall quality loss rate shows a decreasing trend, but the quality loss is not severe.

Abstract This study aimed to understand the changes in the milk and gut microbiota of dairy cows with mastitis, and to further explore the relationship between mastitis and the microbiota. In this study, we extracted microbial DNA from healthy and mastitis cows and performed high-throughput sequencing using the Illumina NovaSeq sequencing platform. OTU clustering was performed to analyze complexity, multi-sample comparisons, differences in community structure between groups, and differential analysis of species composition and abundance. The results showed that there were differences in microbial diversity and community composition in the milk and feces of normal and mastitis cows, where the diversity of microbiota decreased and species abundance increased in the mastitis group. There was a significant difference in the flora composition of the two groups of samples (P

Free bending forming (FBF) is a flexible forming technology that gained significant attention recently because of its broad applications in critical industries such as the automotive, aerospace, and nuclear industries. Thus, this paper aims to present a comprehensive review of FBF technology and its flexibility in manufacturing thin-walled complex-shaped metallic tubes with variable curvatures. First, the historical development and state of the art of FBF technology were reviewed and discussed its importance in tube forming recently. Then, the fundamental principles, theoretical modelling, deformation mechanisms during complex bending, critical process parameters, and forming defects with a discussion of the recent research and technological developments of FBF technology under three-, five- and six-axis processes were explained. After that, the system dies and tools design of the FBF machines and the trajectory control of the bending die were presented. Afterwards, the mechanisms of manufacturing spiral and involute hollow metallic tubes and outstanding solutions for critical issues during tube manufacturing, such as springback, cross-section deformation, over-thinning (even cracking), and wrinkling instability were introduced. Finally, the paper is concluded by providing the discussions on the system, die and tool design methodology, and outlook of the FBF technology.

BackgroundGallbladder neuroendocrine carcinoma (GB-NEC) is an extremely rare cancer with a poor prognosis in the clinic. Although surgical resection remains the primary and preferred therapeutics, many patients are in a late stage and lose the opportunity for surgery. However, due to the extremely low morbidity, the specific treatment guidelines for GB-NEC have not been established.Case presentationA 52-year-old woman was admitted to our hospital with the chief complaint of “almost 1 month after palliative surgery for metastatic gallbladder carcinoma.” According to the results of pathological findings and imaging manifestations, the patient was diagnosed with GB-NEC with a clinical stage of pT3N1M1 (IVB). The patient then received tislelizumab plus EP chemotherapy (etoposide 100 mg + cisplatin 30 mg, d1–3) every 3 weeks for 8 cycles from 12 November, 2021, followed by maintenance therapy (tislelizumab alone) every 3 weeks until now. The tumor response was evaluated as complete remission since 13 February, 2023. As of the last follow-up, the patient remains alive, with no complaints of discomfort.ConclusionsGallbladder NEC has no specific symptoms, and the diagnosis is based on pathological and immunohistochemical results. The therapeutic course and efficacy of the case in this study indicates that the application of PD-1 inhibitor might be a feasible therapeutic option for GB-NEC. However, this potential strategy needs validation by further clinical studies in the future.

The purpose of this study is to investigate the flow field characteristics of the road-rail same-story asymmetric bridge deck and the influence of the asymmetric arrangement of the bridge deck on the flow field of the main girders. Numerical simulation tests were conducted on this bridge to analyze the distribution characteristics of the flow field near the main girder, as well as the aerodynamic characteristics of the railway bridge deck and highway bridge deck under different wind speeds and directions. The results indicate that the wind speed has less influence on the flow field distribution and aerodynamic characteristics of the road-rail same-story asymmetric bridge deck, but the incoming flow direction has a significant impact on its flow field characteristics. Compared to the railway bridge deck, during the reattachment position of the airflow, the highway bridge deck moves toward the windward side, and the volume of the separation bubble has been reduced, thus improving the effect on the negative pressure area of the railway bridge deck. The road-rail same-story asymmetric bridge deck has different aerodynamic interference characteristics for different wind speeds and different wind directions.

Functional vascularization is crucial for maintaining the long-term patency of tissue-engineered trachea and repairing defective trachea. Herein, we report the construction and evaluation of a novel cell-free tissue-engineered tracheal scaffold that effectively promotes vascularization of the graft. Our findings demonstrated that exosomes derived from endothelial progenitor cells (EPC-Exos) enhance the proliferation, migration, and tube formation of endothelial cells. Taking advantage of the angiogenic properties of EPC-Exos, we utilized methacrylate gelatin (GelMA) as a carrier for endothelial progenitor cell exosomes and encapsulated them within a 3D-printed polycaprolactone (PCL) scaffold to fabricate a composite tracheal scaffold. The results demonstrated the excellent angiogenic potential of the methacrylate gelatin/vascular endothelial progenitor cell exosome/polycaprolactone tracheal scaffold. Furthermore, in vivo reconstruction of tracheal defects revealed the capacity of this composite tracheal stent to remodel vasculature. In conclusion, we have successfully developed a novel tracheal stent composed of methacrylate gelatin/vascular endothelial progenitor exosome/polycaprolactone, which effectively promotes angiogenesis for tracheal repair, thereby offering significant prospects for clinical and translational medicine.

Sequencing-based genetic association analysis is typically performed by first generating genotype calls from sequence data and then performing association tests on the called genotypes. Standard approaches require accurate genotype calling (GC), which can be achieved either with high sequencing depth (typically available in a small number of individuals) or via computationally intensive multi-sample linkage disequilibrium (LD)-aware methods. We propose a computationally efficient two-stage combination approach for association analysis, in which single-nucleotide polymorphisms (SNPs) are screened in the first stage via a rapid maximum likelihood (ML)-based method on sequence data directly (without first calling genotypes), and then the selected SNPs are evaluated in the second stage by performing association tests on genotypes from multi-sample LD-aware calling. Extensive simulation- and real data-based studies show that the proposed two-stage approaches can save 80% of the computational costs and still obtain more than 90% of the power of the classical method to genotype all markers at various depths d≥2.

The excellent insulation performance of roof insulators is crucial to the reliability of operating trains. The complex environment encountered by trains may cause roof insulator insulation failure, thus affecting the normal operation of the train. The field operation experience shows that during the operation of Hainan CRHAF-A trains, partial arcs are generated frequently on the roof insulators and even flashover accidents occur. In addition, the insulation failure probability of the insulators in the coastal environment is higher than that in other areas, and pollution is an important factor leading to lower insulation performance. Therefore, the pollution accumulation characteristics of roof insulators are investigated and analyzed in this paper. The accumulated pollution simulation model is built based on the operating environment of the train, and the electric field, flow field, and pressure field around the roof insulators are simulated. This has important engineering application and economic value for the study of insulator anti-pollution.

Background: Deep learning methods are increasingly applied in the medical field; however, their lack of interpretability remains a challenge. Captum is a tool that can be used to interpret neural network models by computing feature importance weights. Although Captum is an interpretable model, it is rarely used to study medical problems, and there is a scarcity of data regarding MRI anatomical measurements for patients with prostate cancer after undergoing Robotic-Assisted Radical Prostatectomy (RARP). Consequently, predictive models for continence that use multiple types of anatomical MRI measurements are limited. Methods: We explored the energy efficiency of deep learning models for predicting continence by analyzing MRI measurements. We analyzed and compared various statistical models and provided reference examples for the clinical application of interpretable deep-learning models. Patients who underwent RARP at our institution between July 2019 and December 2020 were included in this study. A series of clinical MRI anatomical measurements from these patients was used to discover continence features, and their impact on continence was primarily evaluated using a series of statistical methods and computational models. Results: Age and six other anatomical measurements were identified as the top seven features of continence by the proposed model UINet7 with an accuracy of 0.97, and the first four of these features were also found by primary statistical analysis. Conclusions: This study fills the gaps in the in-depth investigation of continence features after RARP due to the limitations of clinical data and applicable models. We provide a pioneering example of the application of deep-learning models to clinical problems. The interpretability analysis of deep learning models has the potential for clinical applications.

Objectives: Copper (Cu) and mercury (Hg) are major pollutants worldwide, but the gastrointestinal damage caused by copper and mercury exposure is unclear. We are committed to scientific research on the harm and transformation of copper and mercury exposure to the rectal microbial population of female mice. Methods: Kunming mice (n = 24) were randomly divided into four equal groups, i.e., 1) Rectal Colon Control (RCK) group, 0 mg/kg of Cu and Hg), 2) Rectal Copper (RCu group), 5 mg/kg weight of Cu), 3) Rectal Mercury (RHg) group, 2 mg/kg weight of Hg) and 4) Rectal copper-mercury (RCH) group, 2.5 and 1 mg/kg weight of Cu and Hg. On the 90th day, the rectal and intestinal tissues were analyzed for pathophysiology, and quantitative analysis by PCR, then a library was prepared, and sequencing was carried out. Results: The rectal tissue of the RCu and RCH group had histopathological and physiological damage, including low weight, low pH value, increased thickness of the outer muscle layer, smooth muscle tissue, widening of the submucosal layer, reduction of goblet cells, blunt intestinal villi and severe aging of the central mammary duct. In addition, Sequencing results of 16S rRNA genes compared with RCK showed that the abundance of the Treponema, Coprococcus, and Dehalobacterium in RCu was more significant than the RCK. Still, the bacillus, Jeotgalicoccus, Salinicoccus, Staphylococcus, and Ignatzschineria was just the opposite. The abundance of Butyricimonas, Streptococcus, Dehalobacterium, Coprococcus, Oscillospira, and Helicobacter in RHg was more significant than in the RCK. Still, Corynebacterium, Bacillus, Jeotgalicoccus, Salinicoccus, Staphylococcus, Lactococcus, and Ignatzschineria were the opposite. We found some similar exciting things. The abundance of the Dehalobacterium, Coprococcus, and Oscillospira was significantly more significant than the RCK. Still, the Corynebacterium, Salinicoccus, Jeotgalicoccus, Staphylococcus, Lactococcus, Sutterella, and Ignatzschineria were the opposite. In addition, the Staphylococcus in RCu was increased than in the RCH, and the Streptococcus in RCu was increased than in the RCH. Conclusion: The results of the present study furnish a source for a more precise validation of the risk of digestive tract diseases driven by Cu and Hg.

Summary: The protein kinase ATR is essential for replication stress responses in all eukaryotes. Ribonucleotide reductase (RNR) catalyzes the formation of deoxyribonucleotide (dNTP), the universal building block for DNA replication and repair. However, the relationship between ATR and RNR is not well understood. Here, we show that ATR promotes the protein stability of RNR in Arabidopsis. Through an activation tagging-based genetic screen, we found that overexpression of TSO2, a small subunit of RNR, partially suppresses the hypersensitivity of the atr mutant to replication stress. Biochemically, TSO2 interacts with PRL1, a central subunit of the Cullin4-based E3 ubiquitin ligase CRL4PRL1, which polyubiquitinates TSO2 and promotes its degradation. ATR inhibits CRL4PRL1 to attenuate TSO2 degradation. Our work provides an important insight into the replication stress responses and a post-translational regulatory mechanism for RNR. Given the evolutionary conservation of the proteins involved, the ATR-PRL1-RNR module may act across eukaryotes.

Abstract Formation of functional and perfusable vascular network is critical to ensure the long‐term survival and functionality of the engineered tissue tracheae after transplantation. However, the greatest challenge in tracheal‐replacement therapy is the promotion of tissue regeneration by rapid graft vascularization. Traditional prevascularization methods for tracheal grafts typically utilize omentum or muscle flap wrapping, which requires a second operation; vascularized segment tracheal orthotopic transplantation in one step remains difficult. This study proposes a method to construct a tissue‐engineered tracheal graft, which directly forms the microvascular network after orthotopic transplantation in vivo. The focus of this study was the preparation of a hybrid tracheal graft that is non‐immunogenic, has good biomechanical properties, supports cell proliferation, and quickly vascularizes. The results showed that vacuum‐assisted decellularized trachea‐polycaprolactone hybrid scaffold could match most of the above requirements as closely as possible. Furthermore, endothelial progenitor cells (EPCs) were extracted and used as vascularized seed cells and seeded on the surfaces of hybrid grafts before and during the tracheal orthotopic transplantation. The results showed that the microvascularized tracheal grafts formed maintained the survival of the recipient, showing a satisfactory therapeutic outcome. This is the first study to utilize EPCs for microvascular construction of long‐segment trachea in one‐step; the approach represents a promising method for microvascular tracheal reconstruction.

Abstract Traditional lithium‐ion batteries cannot meet the ever‐increasing energy demands due to the unsatisfied graphite anode with sluggish electrochemical kinetics. Recently, the perovskite material family as anode attracts growing attention due to their advantages on specific capacity, rate capability, lifetime, and safety. Herein, a double perovskite La2MnNiO6 synthesized by solid‐state reaction method as a high‐performance anode material for LIBs is reported. La2MnNiO6 with an average operating potential of

Five artemisinin bivalent ligands molecules 4a–4e were designed, synthesized, and confirmed by 1H NMR, 13C NMR, and low-resolution mass spectrometry, and the bioactivities of the target compounds were investigated against four human tumor cell lines in vitro, including BGC-823, HepG-2, MCF-7, and HCT-116. The results showed 4a, 4d, and 4e exhibited significantly tumor cell inhibitory activity compared with the artemisinin and dihydroartemisinin; compound 4e has good biological activity inhibiting BGC-823 with an IC50 value of 8.30 μmol/L. Then, the good correlations with biological results were validated by molecular docking through the established bivalent ligands multi-target model, which showed that 4e could bind well with the antitumor protein MMP-9.

Planting energy sorghum to remove soil cadmium (Cd) has been selected as an effective phytoremediation method in subtropical farmland in China in recent years. Nevertheless, the effects of energy sorghum species and cropping systems on Cd removal by energy sorghum are still not fully understood. In the present work, biomass sorghum (BS) and sweet sorghum (SS) were planted for screening varieties and comparing the applicability of cropping systems to remove Cd from contaminated soils through batch field experiments. The results indicated that BS had a higher plant height (4.70–75.63%), lower water content in the shoot (4.78–13.49%), greater dry biomass yield (13.21–125.16%), and stronger Cd removal (average 45.71%) compared with SS. Significant differences (p < 0.05) were observed in the agronomic traits and Cd accumulation of energy sorghums with genetic regulation of varieties. Pearson correlation coefficients analysis and the structural equation model (SEM) showed that plant height was the crucial agronomic parameter affecting the dry biomass yield, and Cd concentration in the stem was the key factor for evaluating the Cd extraction ability of energy sorghums, which indirectly determined the removal of Cd by energy sorghum together. Furthermore, the regeneration cropping system was the most suitable because of the adaptation to climatic conditions of energy sorghums in subtropical regions of China, and its Cd removal efficiency increased by more than 49% compared with double cropping and single cropping systems, respectively. Our study provides valuable information for the phytoremediation of Cd-contaminated soil in Chinese subtropical farmland.

Sarcopenia has become a significant obstacle to healthy aging in older adults. Flavonoids may contribute to treating sarcopenia, and attenuate the age-related loss of skeletal muscle mass, muscle strength, and physical function, however, their benefits in sarcopenic individuals remain unclear. This systematic review aimed to evaluate the effect of flavonoids on muscle mass, muscle strength, and physical performance in adults with sarcopenia based on randomized controlled trials (RCTs). This review was conducted in conformity with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the risk of bias was assessed using the Cochrane risk of bias tool. The article search was conducted using PubMed, Scopus, Embase, Cochrane, Web of Science databases, and Google Scholar for the period until June 2023. RCTs that assessed the effects of flavonoids/flavonoids combined with other supplementation/flavonoid-rich supplementations on skeletal muscle mass, muscle strength, and physical performance in adults diagnosed with sarcopenia before intervention were included. From the 309 articles found, a total of 6 RCTs met the inclusion criteria. RCTs evaluated the main outcomes of tea catechins, epicatechin, and isoflavones intervention. Skeletal muscle mass significantly increased in three studies, muscle strength significantly elevated in two studies, and physical performance significantly improved in two studies. The majority of studies (five in six) found at least one of the main outcomes is elevated by flavonoids intervention. Flavonoids may have a great potential to treat sarcopenia.

Abstract The inherent intermittency of solar power due to diurnal and seasonal cycles has usually resulted in the need for alternative generation sources thereby increasing system operation costs. However, when solar power is spread over a large geographical area with significant time differences, the intermittency can be significantly reduced and also the electricity market balancing cost. The aim of this article is to address the fundamental scientific question on how the intermittency of solar power generation is affected by aggregation, which is of great interest in the wider power and energy community and would have profound impacts on the solar energy integration into the energy supply and Net-Zero Implementation. This article goes beyond the typical regional analysis by investigating solar power intermittency at 5 aggregation levels from a global perspective based on global 7 year hourly meteorological re-analysis data with a fine spatial resolution of $${0.25}^{\circ }\times {0.25}^{\circ } (\sim 28 \; \mathrm{km} \times 28 \; \mathrm{km})$$ 0.25 ∘ × 0.25 ∘ ( ∼ 28 km × 28 km ) . In the proposed assessment framework, a coefficient of variation (CV) is used to quantify solar power intermittency and hence characterize the potential benefits of wide area solar power aggregation. A duration curve is used to characterize the intermittency in terms of power availability and a probability density function is further employed to investigate the dispersion and scaling behavior of CV at different aggregation levels. The findings indicate that the CV of solar power generation of ‘Inner Mongolia’ in China drops from 129.65 to 105.65% in the level of ‘Asia’ (by 24% decrease), to 56.11% in ‘Asia-North_America’ (by 73.54% decrease) and to the smallest 43.50% in ‘Global’ (by 86.15% decrease), nearly 3.5 times of that in ‘Asia’; (b) the availability of solar power generation increases from 52.17% in Germany, to 73.30% in ‘Europe_EU_plus’, to 77.82% in ‘Europe’, to 98.59% in ‘Europe-North_America’ (80.60% in ‘Europe-Africa’, 96.90% in ‘Europe-Asia’), to 100% in ‘Global’. Finally, conclusions and recommendations are provided to support a Net-Zero strategy.

Hydrogen production by electrolysis is considered an essential means of consuming renewable energy in the future. However, the current assessment of the potential of renewable energy electrolysis for hydrogen production is relatively simple, and the perspective is not comprehensive. Here, we established a Combined Wind and Solar Electrolytic Hydrogen system, considering the influence of regional wind-solar-load characteristics and transmission costs to evaluate the hydrogen production potential of 31 provincial-level regions in China in 2050. The results show that in 2050, the levelized cost of hydrogen (LCOH) in China’s provincial regions will still be higher than 10 ¥/kg, which is not cost-competitive compared to the current hydrogen production from fossil fuels. It is more cost-effective to deploy wind turbines than photovoltaic in areas with similar wind and solar resources or rich in wind resources. Wind-solar differences impact LCOH, equipment capacity configuration, and transmission cost composition, while load fluctuation significantly impacts LCOH and electricity storage configuration. In addition, the sensitivity analysis of 11 technical and economic parameters showed differences in the response performance of LCOH changes to different parameters, and the electrolyzer conversion efficiency had the most severe impact. The analysis of subsidy policy shows that for most regions (except Chongqing and Xizang), subsidizing the unit investment cost of wind turbines can minimize LCOH. Nevertheless, from the perspective of comprehensive subsidy effect, subsidy cost, and hydrogen energy development, it is more cost-effective to take subsidies for electrolysis equipment with the popularization of hydrogen.

Background: With a high incidence and dismal survival rate, hepatocellular carcinoma (HCC) tops the list of the world’s most frequent malignant tumors. Immunotherapy is a new approach to cancer treatment, and its effect on prolonging overall survival (OS) varies from patient to patient. For a more effective prognosis and treatment of HCC, we are committed to identifying immune infiltration-related long non-coding RNAs (IIRLs) with prognostic value in hepatocellular carcinoma.Methods: In our study, we calculated immune scores of 369 hepatocellular carcinoma samples from the Cancer Genome Atlas (TCGA) database by using an estimation algorithm, and obtained long non-coding RNAs (lncRNAs) associated with immune infiltration by using Weighted Gene Co-expression Network analysis (WGCNA). For training cohort, univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis were used to determine prognostic IIRLs, we established a prognostic IIRLs signature. By testing cohort and entire cohort, we confirmed that the signature is practical. The prognosis of people with different clinicopathological stages and risk scores were predicted by the nomogram we constructed. In addition, Immune cell infiltration analysis and prediction of therapeutic drugs were performed.Results: 93 IIRLs were obtained by WGCNA. Furthermore, the prognostic value of these IIRLs were evaluated by using univariate Cox, Lasso and multivariate Cox analysis. Four IIRLs were used to create a signature with a prognosis. Time-related receiver operating characteristic (ROC) curve revealed that this model had an acceptable prognostic value for HCC patients. By using univariate and multivariate Cox regression analysis, this risk score has been shown to be an independent prognostic factor for HCC. The nomogram we made showed good predictions. Except for that, the treatment with immune checkpoint inhibitors (ICI) was likely to be more effective for low-risk patients.Conclusion: Based on four IIRLs, a prognostic signature was created in this research showed good accuracy in predicting OS. This study also provided valuable references for Immunotherapy of hepatocellular carcinoma.

Abstract In vivo, multiple biophysical cues provided by highly ordered connective tissues of the extracellular matrix regulate skeletal muscle cells to align in parallel with one another. However, in routine in vitro cell culture environments, these key factors are often missing, which leads to changes in cell behavior. Here, we present a simple strategy for using optical media discs with nanogrooves and other polymer-based substrates nanomolded from the discs to directly culture muscle cells to study their response to the effect of biophysical cues such as nanotopography and substrate stiffness. We extend the range of study of biophysical cues for myoblasts by showing that they can sense ripple sizes as small as a 100 nm width and a 20 nm depth for myotube alignment, which has not been reported previously. The results revealed that nanotopography and substrate stiffness regulated myoblast proliferation and morphology independently, with nanotopographical cues showing a higher effect. These biophysical cues also worked synergistically, and their individual effects on cells were additive; i.e., by comparing cells grown on different polymer-based substrates (with and without nanogrooves), the cell proliferation rate could be reduced by as much as ~29%, and the elongation rate could be increased as much as ~116%. Moreover, during myogenesis, muscle cells actively responded to nanotopography and consistently showed increases in fusion and maturation indices of ~28% and ~21%, respectively. Finally, under electrical stimulation, the contraction amplitude of well-aligned myotubes was found to be almost 3 times greater than that for the cells on a smooth surface, regardless of the substrate stiffness.

Abstract Wearing masks has been a recommended protective measure due to the risks of coronavirus disease 2019 (COVID‐19) even in its coming endemic phase. Therefore, deploying a “smart mask” to monitor human physiological signals is highly beneficial for personal and public health. This work presents a smart mask integrating an ultrathin nanocomposite sponge structure‐based soundwave sensor (≈400 µm), which allows the high sensitivity in a wide‐bandwidth dynamic pressure range, i.e., capable of detecting various respiratory sounds of breathing, speaking, and coughing. Thirty‐one subjects test the smart mask in recording their respiratory activities. Machine/deep learning methods, i.e., support vector machine and convolutional neural networks, are used to recognize these activities, which show average macro‐recalls of ≈95% in both individual and generalized models. With rich high‐frequency (≈4000 Hz) information recorded, the two‐/tri‐phase coughs can be mapped while speaking words can be identified, demonstrating that the smart mask can be applicable as a daily wearable Internet of Things (IoT) device for respiratory disease identification, voice interaction tool, etc. in the future. This work bridges the technological gap between ultra‐lightweight but high‐frequency response sensor material fabrication, signal transduction and processing, and machining/deep learning to demonstrate a wearable device for potential applications in continual health monitoring in daily life.

De-carbonization actions, represented by the electrification of end-use energy sources, have been strongly promoted, while space heating in residential buildings is an important aspect. In this paper, Jinan and Qingdao in northern China are selected to explore the challenges that electrification of heating will bring. The electricity demand for heating of different types of buildings is simulated, with the assumption that all heating loads are provided by electric heat pumps. Then the comparison of heating electricity demand with current electricity consumption in various social sectors has been analyzed to investigate the impact of the newly added electrical load on the power grid. The annual dynamic power supply under the currently installed wind turbines and photovoltaic modules is calculated to explore the interrelationship between the power supply potential of the available renewable energy and the heating electricity demand. The results show that the implementation of heating electrification will bring a strong impact on the existing grid, with photovoltaic generation almost negligible during the heating period and wind generation severely affected by intermittency. In the future, the deployment of installed renewable energy needs to continue to be promoted, while the layout of energy storage facilities needs to be strengthened.

To study the relationship between genetic variants and phenotypes, association testing is adopted; however, most association studies are conducted by genotype-based testing. Testing methods based on next-generation sequencing (NGS) data without genotype calling demonstrate an advantage over testing methods based on genotypes in the scenarios when genotype estimation is not accurate. Our objective was to develop NGS data-based methods for association studies to fill the gap in the literature. Single-variant testing methods based on NGS data have been proposed, including our previously proposed single-variant NGS data-based testing method, i.e., UNC combo method. The NGS data-based group testing method has been proposed by us using a linear model framework which can handle continuous responses. In this paper, we extend our linear model-based framework to a generalized linear model-based framework so that the methods can handle other types of responses especially binary responses which is a common problem in association studies. To evaluate the performance of various estimators and compare them we performed simulation studies. We found that all methods have Type I errors controlled, and our NGS data-based methods have better performance than genotype-based methods for other types of responses, including binary responses (logistics regression) and count responses (Poisson regression), especially when sequencing depth is low. We have extended our previous linear model (LM) framework to a generalized linear model (GLM) framework and derived NGS data-based methods for a group of genetic variables. Compared with our previously proposed LM-based methods, the new GLM-based methods can handle more complex responses (for example, binary responses and count responses) in addition to continuous responses. Our methods have filled the literature gap and shown advantage over their corresponding genotype-based methods in the literature.

Safe and effective vaccines against SARS-CoV-2 for children are urgently needed. Here we aimed to assess the safety and immunogenicity of an inactivated COVID-19 vaccine candidate, WIBP-CorV, in participants aged 3-17 years. A randomized, double-blind, placebo-controlled, phase 1/2 clinical trial was conducted in Henan Province, China, in healthy children aged 3-17 years. 240 participants in phase 1 trial and 576 participants in phase 2 trial were randomly assigned to vaccine or control with an age de-escalation in three cohorts (3-5, 6-12 and 13-17 years) and dose-escalation in three groups (2.5, 5.0 and 10.0μg/dose), and received 3 intramuscular injections at day 0, 28, and 56. WIBP-CorV showed a promising safety profile with approximately 17% adverse reactions within 30 days after injection and no grade 3 or worse adverse events. The most common adverse reaction was injection site pain, followed by fever, which were mild and self-limiting. The geometric mean titers of neutralizing antibody ranged from 102.2 to 1065.5 in vaccinated participants at 28 days after the third vaccination, and maintained at a range of 14.3 to 218.2 at day 180 after the third vaccination. WIBP-CorV elicited significantly higher titers of neutralizing antibody in the cohort aged 3-5 years than the other two cohorts. There were no detectable antibody responses in all alum-only groups. Taken together, our data demonstrate that WIBP-CorV is safe and well tolerated at all tested doses in participants aged 3-17 years, and elicited robust humoral responses against SARS-CoV-2 lasted for at least 6 months after the third vaccination. This study is ongoing and is registered with www.chictr.org.cn, ChiCTR2000031809.

This study aims to investigate the effect of heat stress on the physiological metabolism of young laying hens and whether N-acetyl-l-cysteine (NAC) can effectively alleviate heat stress. 120 Hy-Line Brown laying hens aged 12 weeks were randomly divided into four groups: the control group (fed on basal diet under thermal neutral condition), HS group (fed on basal diet under heat stress condition), CN group (fed on the basic meal supplemented with 1,000 mg NAC per kg under thermal neutral condition), and HS+N group (fed on the basic meal was supplemented with 1000 mg NAC per kg under heat stress condition). The HS and HS+N groups were exposed to 36 ± 1°C for 10 h/day. The effects of NAC on the changes of serum concentrations of T3, T4, and CORT and hypothalamic gene and protein expressions induced by heat stress were measured. Results showed that heat stress upregulated the contents of T3, T4, and CORT, while NAC reduced the contents of T3, T4, and CORT. In addition, NAC downregulated AgRP expression, while upregulated the expression of POMC. Moreover, the expressions of AMPKα1, LKB1, and CPT1 were inhibited by NAC, while the expressions of AKT1, ACC, GPAT, and PPARα were increased after NAC treatment, and HMGR did not change significantly. Western blot and comprehensive immunofluorescence section of AMPK in the hypothalamus showed that NAC attenuated the activity of AMPK. In conclusion, NAC can enhance the resistance of laying hens to heat stress by alleviating the metabolic disorders of serum T3, T4, and CORT induced by heat stress, inhibiting the activation of the AMPK pathway and regulating the expression of appetite-related genes in the hypothalamus.

Deep learning has become widely used in image analysis. Transfer learning can make use of information from other datasets for the analysis of the chosen dataset. When there is a small number of images at hand, transfer learning using pre-trained models with coefficients already estimated from other datasets is recommended. This is in contrast to deep learning, where most model parameters are re-estimated. Deep transfer learning uses pre-trained models with fixed weight parameters in the lower layers; thus, deep learning can be viewed as a two-stage approach: (1) feature extraction from a lower neural network layer and (2) estimation of a neural network using the extracted features as inputs. Since deep transfer learning is feature extraction, we can extend the two-stage approach to a more general two-stage framework: (1) feature extraction using multiple methods and (2) machine learning methods taking extracted features as inputs. We evaluate the performance of methods with different Stage 1 and Stage 2 approaches in predicting the phenotype leaf numbers based on a multi-view plant imaging dataset. This paper contains an evaluation of different two-stage machine learning methods for multi-view image data in plant image phenotyping.