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Abstract Background The identification of spotted leaf 50 (spl50), a novel lesion mimic mutant (LMM) in rice, provides critical insights into the mechanisms underlying programmed cell death (PCD) and innate immunity in plants. Results Based on ethyl methane sulfonate (EMS)-induced mutagenesis, the spl50 mutant mimics hypersensitive responses in the absence of pathogen by displaying spontaneous necrotic lesions after the tillering phase. SPL50, an ARM repeat protein essential for controlling reactive oxygen species (ROS) metabolism and boosting resistance to blast disease, was identified by map-based cloning techniques. This work also demonstrates the detrimental effects of spl50 on photosynthetic efficiency and chloroplast development. The crucial significance of SPL50 in cellular signaling and stress response is shown by its localization to the cytoplasm and constitutive expression in various plant tissues. In light of growing concerns regarding global food security, this study highlights the pivotal role of SPL50 in regulating programmed cell death (PCD) and enhancing the immune response in plants, contributing to strategies for improving crop disease resistance. Conclusions The novel identification of the SPL50 gene in rice, encoding an ARM repeat protein, reveals its pivotal role in regulating PCD and innate immune responses independently of pathogen attack.

Abstract Identification of tumor neoantigens is indispensable for the development of cancer immunotherapies. However, we are still lacking knowledge about the potential neoantigens derived from sequences outside protein-coding regions. Here, we comprehensively characterized the immunopeptidome landscape by integrating multi-omics data in acute myeloid leukemia (AML). Both canonical and non-canonical MHC-associated peptides (MAPs) in AML were identified. We found that the quality and characteristics of ncMAPs are comparable or superior to cMAPs, suggesting ncMAPs are indispensable sources for tumor neoantigens. We further proposed a computational framework to prioritize the neoantigens by integrating additional transcriptome and immunopeptidome in normal tissues. Notably, 6 of prioritized 13 neoantigens were derived from ncMAPs. The expressions of corresponding source genes are highly related to infiltrations of immune cells. Finally, a risk model was developed, which exhibited good performance for clinical prognosis in AML. Our findings expand potential cancer immunotherapy targets and provide in-depth insights into AML treatment, laying a new foundation for precision therapies in AML.

Abstract As machine learning (ML) continues to advance in the field of materials science, the variation in strategies for the same steps of the ML workflow becomes increasingly significant. These details can have a substantial impact on results, yet they have not received the deserved attention. This review aims to explore the various strategies available for each detail within the general workflow of materials ML. Firstly, the general workflow of materials ML will be introduced to help readers gain an understanding of potential details. Subsequently, different strategies of details within each step of the workflow will be presented through state-of-the-art case studies. The potential outcomes associated with choosing different strategies to details will be explored. Following this, suitable strategies for details will be recommended based on distinct application scenarios. Finally, directions for the future development of materials ML concerning details will be proposed. Through these discussions, we aspire to offer a comprehensive understanding of the nuances in details within materials ML. This will serve as valuable reference and guidance for researchers in both materials science and ML.

This paper presents a selective review of statistical computation methods for massive data analysis. A huge amount of statistical methods for massive data computation have been rapidly developed in the past decades. In this work, we focus on three categories of statistical computation methods: (1) distributed computing, (2) subsampling methods, and (3) minibatch gradient techniques. The first class of literature is about distributed computing and focuses on the situation, where the dataset size is too huge to be comfortably handled by one single computer. In this case, a distributed computation system with multiple computers has to be utilized. The second class of literature is about subsampling methods and concerns about the situation, where the blacksample size of dataset is small enough to be placed on one single computer but too large to be easily processed by its memory as a whole. The last class of literature studies those minibatch gradient related optimization techniques, which have been extensively used for optimizing various deep learning models.

Purposes: This study determined the synergy of polymyxin B (POLB) and colistin (COL) with 16 other tested antimicrobial agents in the inhibition of multidrug-resistant Acinetobacter baumannii (MDR-AB). Methods: We used chequerboard assays to determine synergy between the drugs against 50 clinical MDR-AB from a tertiary hospital in the Zhejiang province in 2019, classifying combinations as either antagonistic, independent, additive, or synergistic. The efficacy of hit combinations which showed highest synergistic rate were confirmed using time-kill assays. Results: Both POLB and COL displayed similar bactericidal effects when used in combination with these 16 tested drugs. Antagonism was only observed for a few strains (2%) exposed to a combination of POLB and cefoperazone/sulbactam (CSL). A higher percentage of synergistic combinations with POLB and COL were observed with rifabutin (RFB; 90%/96%), rifampicin (RIF; 60%/78%) and rifapentine (RFP; 56%/76%). Time-kill assays also confirmed the synergistic effect of POLB and rifamycin class combinations. 1/2 MIC rifamycin exposure can achieve bacterial clearance when combined with 1/2 MIC POLB or COL. Conclusion: Nearly no antagonism was observed when combining polymyxins with other drugs by both chequerboard and time-kill assays, suggesting that polymyxins may be effective in combination therapy. The combinations of POLB/COL with RFB, RIF, and RFP displayed neat synergy, with RFB showing the greatest effect.

In the realm of the Internet of Things (IoT), ensuring the security of communication links and evaluating the safety of nodes within these links remains a significant challenge. The continuous threat of anomalous links, harboring malicious switch nodes, poses risks to data transmission between edge nodes and between edge nodes and cloud data centers. To address this critical issue, we propose a novel trust evaluation based secure multi-path routing (TESM) approach for IoT. Leveraging the software-defined networking (SDN) architecture in the data transmission process between edge nodes, TESM incorporates a controller comprising a security verification module, a multi-path routing module, and an anomaly handling module. The security verification module ensures the ongoing security validation of data packets, deriving trust scores for nodes. Subsequently, the multi-path routing module employs multi-objective reinforcement learning to dynamically generate secure multiple paths based on node trust scores. The anomaly handling module is tasked with handling malicious switch nodes and anomalous paths. Our proposed solution is validated through simulation using the Ryu controller and P4 switches in an SDN environment constructed with Mininet. The results affirm that TESM excels in achieving secure data forwarding, malicious node localization, and the secure selection and updating of transmission paths. Notably, TESM introduces a minimal 12.4% additional forwarding delay and a 5.46% throughput loss compared to traditional networks, establishing itself as a lightweight yet robust IoT security defense solution.

The implementation of pretreatment drug-resistance (PDR) surveillance among people living with HIV-1 (PLWH) is a top priority in countries using efavirenz (EFV)/nevirapine (NVP) for first-line ART. In this study, we assessed the prevalence of PDR among PLWH in Shanghai, China during 2017–2021, and to reveal PDR transmission between Shanghai and other regions of China. A total of 5050 PLWH not on ART during 2017–2021 were included. Partial HIV-1 pol sequences were amplified, sequenced, and analysed for drug-resistance mutations (DRMs). Besides, transmission network of PDR variants was inferred using HIV-TRACE. The overall prevalence of PDR was 4.8% (242/5050; 95% CI, 4.2–5.4). Prevalence of NNRTI-associated PDR was 3.9% (95% CI, 3.4–4.5), higher than those of NRTI-associated (0.8%; 95% CI, 0.5–1.1) and PI-associated PDR (0.9%; 95% CI, 0.6–1.2). High prevalence of PDR (especially high-level resistance) to EFV (132/5050, 2.6%) and NVP (137/5050, 2.7%) were found. CRF01_AE (46.0%) was the predominant HIV-1 genotype with any DRMs, followed by CRF55_01B (21.0%), and CRF07_BC (15.1%). Two NRTI-associated (S68G/N/R and T215A/N/S/Y), five NNRTI-associated (V179D/E/T/L, K103N/R/S/T, E138A/G/K, V106M/I/A and Y181C/I) and two PI-associated mutations (M46I/L/V and Q58E) were the most common observed DRMs in PDR patients in Shanghai. The vast majority of S68G occurred in CRF01_AE (45%). M46I/L/V and Q58E showed a relatively high prevalence in CRF01_AE (4.1%) and CRF07_BC (12.6%). Transmission network analyses demonstrated cross-regional transmission links of PDR variants between Shanghai and other regions of China, which was mainly driven by the potential low-level DRM V179D/E. These results provide crucial information for clinical decision making of first-line ART in PLWH with PDR.

To further reform the medical and health care system, regulating multi-level treatment and rationalizing the use of medicine, and securing prescription circulation information, this study explores the evolutionary behavior of three players in terms of information security collaboration under the prescription circulation policy, analyzes the evolutionary paths, and examines the influence of key parameters on evolutionary outcomes by constructing a tripartite evolutionary game model consisting of hospitals, retail pharmacies, and healthcare service platforms. The study shows the following: (1) When the information security costs of prescription circulation increase, the willingness of hospitals to promote information collaboration weakens, the probability of control and regulation by healthcare platforms will be enhanced, and the incentive for retail pharmacies to undertake prescription circulation increases and then decreases. (2) The increased profitability of prescription drug sales can cause a decrease in the likelihood of both parties working together to promote information security. Increasing the collaborative space between hospitals and retail pharmacies is conducive to improving information security in the circulation of prescriptions. (3) A bi-directional constraint relationship exists between the circulation and control subjects. The shorter the technology spillover time from the healthcare service platform is, the higher the probability that hospitals and retail pharmacies will maintain the security of prescription information. (4) In the early stages of prescription circulation, the external regulatory action of the healthcare service platform is essential to improve the coordination of information security. Finally, combined with the tripartite evolutionary game model and simulation analysis results, it offers countermeasures and suggestions for the government to realize the prescription circulation information security collaboration.

Obtaining temperature and humidity profiles with high vertical resolution is essential for describing and predicting atmospheric motion, and, in particular, for understanding the evolution of medium- and small-scale weather processes, making short-range and near-term weather forecasting, and implementing weather modifications (artificial rainfall, artificial rain elimination, etc.). Ground-based microwave radiometers can acquire vertical tropospheric atmospheric data with high temporal and spatial resolution. However, the accuracy of temperature and relative humidity retrieval is still not as accurate as that of radiosonde data, especially in cloudy conditions. Therefore, improving the observation and retrieval accuracy is a major challenge in current research. The focus of this study was to further improve the accuracy of atmospheric temperature and humidity profile retrieval and investigate the specific effects of cloud information (cloud-base height and cloud thickness) on temperature and humidity profile retrieval. The observation data from the ground-based multichannel microwave radiometer (GMR) and the millimeter-wave cloud radar (MWCR) were incorporated into the retrieval process of the atmospheric temperature and relative humidity profiles. The retrieval was performed using the backpropagation neural network (BPNN). The retrieval results were quantified using the mean absolute error (MAE) and root mean square error (RMSE). The statistical results showed that the temperature profiles were less affected by the cloud information compared with the relative humidity profiles. Cloud thickness was the main factor affecting the retrieval of relative humidity profiles, and the retrieval with cloud information was the best retrieval method. Compared with the retrieval profiles without cloud information, the MAE and RMSE values of most of the altitude layers were reduced to different degrees after adding cloud information, and the relative humidity (RH) errors of some altitude layers were reduced by approximately 50%. The maximum reduction in the RMSE and MAE values for the retrieval of temperature profiles with cloud information was about 1.0 °C around 7.75 km, and the maximum reduction in RMSE and MAE values for the relative humidity profiles was about 10%, which was obtained around 2 km.

ABSTRACTThe emergence of antibiotic-resistant bacteria (ARB) caused by the overuse of antibiotics severely threatens human health. Hospital sewage may be a key transmission hub for ARB. However, the complex link between the microbiome and resistomeresistance in hospital sewage remains unclear. In this study, metagenomic assembly and binning methods were used to investigate the microbial community, resistome, and association of antibiotic resistance genes (ARGs) with ARB in sewage from 10 representative sites (outpatient building, surgery building, internal medicine buildings [IMB1-4], staff dormitory, laboratory animal building, tuberculosis building [TBB], and hospital wastewater treatment plant) of a hospital in Shanghai from June 2021 to February 2022. A total of 252 ARG subtypes, belonging to 17 antibiotic classes, were identified. The relative abundance of KPC-2 was higher at IMBs and TBB than at other sites. Of the ARG-carrying contigs, 47.3%-62.6% were associated with mobile genetic elements, and the proportion of plasmid-associated ARGs was significantly higher than that of chromosome-associated ARGs. Although a similar microbiome composition was shared, certain bacteria were enriched at different sites. Potential pathogens Enterococcus B faecium and Klebsiella pneumoniae were primarily enriched in IMB2 and IMB4, respectively. The same ARGs were identified in diverse bacterial hosts (especially pathogenic bacteria), and accordingly, the latter possessed multiple ARGs. Furthermore, gene flow was frequently observed in the sewage of different buildings. The results provide crucial information on the characterization profiles of resistomes in hospital sewage in Shanghai.IMPORTANCEEnvironmental antibiotic resistance genes (ARGs) play a critical role in the emergence and spread of antimicrobial resistance, which poses a global health threat. Wastewater from healthcare facilities serves as a significant reservoir for ARGs. Here, we characterized the microbial community along with the resistome (comprising all antibiotic resistance genes) in wastewater from a specialized hospital for infectious diseases in Shanghai. Potential pathogenic bacteria (e.g., Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterococcus B faecium) were frequently detected in hospital wastewater and carried multiple ARGs. A complex link between microbiome and resistome was observed in the wastewater of this hospital. The monitoring of ARGs and antibiotic-resistant bacteria (ARB) in hospital wastewater might be of great significance for preventing the spread of ARB.

Summary: The typical genomic feature of acute myeloid leukemia (AML) M3 subtype is the fusion event of PML/RARα, and ATRA/ATO-based combination therapy is current standard treatment regimen for M3 subtype. Here, a machine-learning model based on expressions of PML/RARα targets was developed to identify M3 patients by analyzing 1228 AML patients. Our model exhibited high accuracy. To enable more non-M3 AML patients to potentially benefit from ATRA/ATO therapy, M3-like patients were further identified. We found that M3-like patients had strong GMP features, including the expression patterns of M3 subtype marker genes, the proportion of myeloid progenitor cells, and deconvolution of AML constituent cell populations. M3-like patients exhibited distinct genomic features, low immune activity and better clinical survival. The initiative identification of patients similar to M3 subtype may help to identify more patients that would benefit from ATO/ATRA treatment and deepen our understanding of the molecular mechanism of AML pathogenesis.

Flavonoids are bioactive natural polyphenolic compounds with health benefits, including anti-tumor, anti-inflammatory and anti-aging effects. Our previous studies revealed that a flavonoid 4,4′-dimethoxychalcone (DMC) induced ferroptosis via inhibiting ferrochelatase (FECH). However, the effect of DMC on cellular senescence is unknown. In the present study, we found that DMC treatment selectively eliminated senescent cells, and DMC alone or a combination of DMC and quercetin or dasatinib showed high efficiency in the clearance of senescent cells. We identified FECH was highly expressed in senescent cells compared to non-senescent cells. Mechanistically, we found that DMC inhibited FECH and induced ferritinophagy, which led to an increase of labile iron pool, triggering ferroptosis of senescent cells. Importantly, we found that DMC treatment prevented hair loss, improved motor coordination, and reduced the expression of several senescence-associated secretory phenotype factors (IL-6, IL-1β, CXCL-10, and MMP12) in the liver of old mice. Collectively, we revealed that, through the induction of ferroptosis, DMC holds the promise as a new senolytics to prevent age-related pathologies.

Abstract Purpose This study aimed to assess the value of an HPV E6/E7 mRNA assay and HPV 16 18/45 genotype assay combined with age stratification for triaging women negative for intraepithelial lesions or malignancy (NILM) cytology. Methods From January 2017 to December 2021, a total of 162,309 eligible women underwent cervical cancer screening at the Affiliated Hospital of Jining Medical University, China. Excluding those with negative HPV E6/E7 mRNA, abnormal and unsatisfactory cytology, and those who failed to undergo colposcopy, 6,845 women were ultimately included in our study. We analysed the triage guidance for different subtypes of HPV in the presence of NILM cytology. Results Among 162,309 women, 19,834 (12.2%) were positive for HPV E6/E7 mRNA. Of the 6,845 women included in the study, 1,941 (28.4%), 561 (8.2%), 55 (0.8%) and 4,288 (62.6%) tested positive for HPV 16, HPV 18/45, HPV16/18/45 or other HR-HPV genotypes, respectively. The proportions of LSIL+ (including LSIL, HSIL and ICC) and HSIL+ (including HSIL and ICC) pathological results in the HPV 16/18/45 + group were 57% and 34.1%, respectively, higher than 36.3% and 11% in the other HR-HPV + group (χ2 = 653.214, P 0.05). The above results were consistent after stratification according to age. Conclusion The rate of histopathological abnormalities was still high for the other HR-HPV subtypes with NILM cytology, although the rate of histopathological abnormalities was much higher for the HPV 16/18/45 positive subtypes. Therefore, colposcopy should be performed in women with HPV E6/E7 mRNA positivity and NILM cytology, regardless of age and HPV genotype.

Abstract Background With the global spread of COVID-19, detecting high-risk countries/regions timely and dynamically is essential; therefore, we sought to develop automatic, quantitative and scalable analysis methods to observe and estimate COVID-19 spread worldwide and further generate reliable and timely decision-making support for public health management using a comprehensive modeling method based on multiple mathematical models. Methods We collected global COVID-19 epidemic data reported from January 23 to September 30, 2020, to observe and estimate its possible spread trends. Countries were divided into three outbreak levels: high, middle, and low. Trends analysis was performed by calculating the growth rate, and then country grouping was implemented using group-based trajectory modeling on the three levels. Individual countries from each group were also chosen to further disclose the outbreak situations using two predicting models: the logistic growth model and the SEIR model. Results All 187 observed countries' trajectory subgroups were identified using two grouping strategies: with and without population consideration. By measuring epidemic trends and predicting the epidemic size and peak of individual countries, our study found that the logistic growth model generally estimated a smaller epidemic size than the SEIR model. According to SEIR modeling, confirmed cases in each country would take an average of 9–12 months to reach the outbreak peak from the day the first case occurred. Additionally, the average number of cases at the peak time will reach approximately 10–20% of the countries’ populations, and the countries with high trends and a high predicted size must pay special attention and implement public health interventions in a timely manner. Conclusions We demonstrated comprehensive observations and predictions of the COVID-19 outbreak in 187 countries using a comprehensive modeling method. The methods proposed in this study can measure COVID-19 development from multiple perspectives and are generalizable to other epidemic diseases. Furthermore, the methods also provide reliable and timely decision-making support for public health management.

Abstract Objective To investigate the infection status of high-risk human papillomavirus (HR-HPV) E6/E7 mRNA in patients with a cytological diagnosis of “atypical squamous cells of undetermined significance” (ASCUS) and to analyze the pathogenic rate of different high-risk HPV subtypes combined with biopsy pathological results to provide a more accurate basis for managing ASCUS patients. Methods A total of 1387 patients with ASCUS and HPV E6/E7 mRNA positivity who were referred for colposcopy were retrospectively analyzed. They were divided into HPV16+, 18/45 + and other HR-HPV + groups premenopausal and postmenopausal groups. The pathological results of the biopsy were divided into the LSIL- group (including normal and low-grade squamous intraepithelial lesions) and the HSIL + group (including high-grade squamous intraepithelial lesions and higher lesions). SPSS was used for the analysis. Results The age group 31–40 years had the highest level of HPV16+, and HPV18/45 + was the highest in the 41–50 years group. The detection rates of HSIL + in the HPV16+, HPV18/45+, HPV 16/18/45 + and Other HR-HPV + groups were 48.4%, 18.8%, 43.9% and 15.0%, respectively. The infection rates of HPV16/18/45 in postmenopausal and premenopausal women were 42.4% and 34.3%, respectively. In the HPV18/45 group, the incidence of HSIL + was 30.0% in postmenopausal women and 15.0% in premenopausal women (P

Cardiogenesis is an extremely complicated process involved with DNA regulatory elements, and trans factors regulate gene expression pattern spatiotemporally. Enhancers, as the well-known DNA elements, activate target gene expression by transcription factors (TFs) occupied to organize dynamic three-dimensional (3D) interactions, which when affected or interrupted might cause heart defects or diseases. In this study, we integrated transcriptome, 3D genome, and regulatome to reorganize the global 3D genome in cardiomyogenesis, showing a gradually decreased trend of both chromatin interactions and topological associating domains (TADs) during cardiomyocyte differentiation. And almost all of the chromatin interactions occurred within the same or between adjacent TADs involved with enhancers, indicating that dynamical rewiring of enhancer-related chromatin interactions in the continuous expansive TADs is closely correlated to cardiogenesis. Moreover, we found stage-specific interactions activate stage-specific expression to be involved within corresponding biological functions, and the stage-specific combined regulations of enhancers and binding TFs form connected networks to control stage-specific expression and biological processes, which promote cardiomyocyte differentiation. Finally, we identified markers based on regulatory networks, which might drive cardiac development. This study demonstrates the power of enhancer interactome combined with active TFs to reveal insights into transcriptional regulatory networks during cardiomyogenesis.

Rice (Oryza sativa L.), a fundamental global staple, nourishes over half of the world’s population. The identification of the ddt1 mutant in rice through EMS mutagenesis of the indica cultivar Shuhui527 revealed a dwarf phenotype, characterized by reduced plant height, smaller grain size, and decreased grain weight. Detailed phenotypic analysis and map-based cloning pinpointed the mutation to a single-base transversion in the LOC_Os03g04680 gene, encoding a cytochrome P450 enzyme, which results in a premature termination of the protein. Functional complementation tests confirmed LOC_Os03g04680 as the DDT1 gene responsible for the observed phenotype. We further demonstrated that the ddt1 mutation leads to significant alterations in gibberellic acid (GA) metabolism and signal transduction, evidenced by the differential expression of key GA-related genes such as OsGA20OX2, OsGA20OX3, and SLR1. The mutant also displayed enhanced drought tolerance, as indicated by higher survival rates, reduced water loss, and rapid stomatal closure under drought conditions. This increased drought resistance was linked to the mutant’s improved antioxidant capacity, with elevated activities of antioxidant enzymes and higher expression levels of related genes. Our findings suggest that DDT1 plays a crucial role in regulating both plant height and drought stress responses. The potential for using gene editing of DDT1 to mitigate the dwarf phenotype while retaining improved drought resistance offers promising avenues for rice improvement.

As one of the most important food crops in the world, rice yield is directly related to national food security. Lodging is one of the most important factors restricting rice production, and the cultivation of rice varieties with lodging resistance is of great significance in rice breeding. The lodging resistance of rice is directly related to the mechanical strength of the stalks. In this paper, we reviewed the cell wall structure, its components, and its genetic regulatory mechanism, which improved the regulatory network of rice stalk mechanical strength. Meanwhile, we analyzed the new progress in genetic breeding and put forward some scientific problems that need to be solved in this field in order to provide theoretical support for the improvement and application of rice breeding.

Aerosol microphysical properties, including aerosol particle size distribution, complex refractive index and concentration properties, are key parameters evaluating the impact of aerosols on climate, meteorology, and human health. High Spectral Resolution Lidar (HSRL) is an efficient tool for probing the vertical optical properties of aerosol particles, including the aerosol backscatter coefficient (β) and extinction coefficient (α), at multiple wavelengths. To swiftly process vast data volumes, address the ill-posedness of retrieval problems, and suit simpler lidar systems, this study proposes an algorithm (modified algorithm) for retrieving microphysical property profiles from the HSRL optical data targeting fine-mode aerosols, building upon a previous algorithm (basic algorithm). The modified algorithm is based on a look-up table (LUT) approach, combined with the k-nearest neighbor (k-NN) and random forest (RF) algorithms, and it optimizes the decision tree generation strategy, incorporating a self-posed scheme. In numerical simulation tests for different lidar configurations, the modified algorithm reduced retrieval errors by 41%, 30%, and 32% compared to the basic algorithm for 3β + 2α, 3β + 1α, and 2β + 1α, respectively, with a remarkable improvement of stability. In two observation scenes of a field campaign, the median relative errors of the effective radius for 3β + 2α were 6% and −3%, and the median absolute errors of single-scattering albedo were 0.012 and 0.005. This method represents a further step toward the use of the LUT approach, with the potential to provide effective and efficient aerosol microphysical retrieval for simpler lidar systems, which could advance our understanding of aerosols’ climatic, meteorological, and health impacts.

Plastics offer many advantages and are widely used in various fields. Nevertheless, most plastics derived from petroleum are slow to degrade due to their stable polymer structure, posing serious threats to organisms and ecosystems. Thus, developing environmentally friendly and biodegradable plastics is imperative. In this study, biodegradable cellulose/multi-walled carbon nanotube (MCNT) hybrid gels and films with improved ultraviolet-shielding properties were successfully prepared using cotton textile waste as a resource. It was proven that MCNTs can be dispersed evenly in cellulose without any chemical or physical pretreatment. It was found that the contents of MCNTs had obvious effects on the structures and properties of hybrid films. Particularly, the averaged transmittance of cellulose/MCNT composite films in the range of 320–400 nm (T320–400) and 290–320 nm (T290–320) can be as low as 19.91% and 16.09%, when the content of MCNTs was 4.0%, much lower than those of pure cellulose films (T320–400: 84.12% and T290–320: 80.03%). Meanwhile, the water contact angles of the cellulose/MCNT films were increased by increasing the content of MCNTs. Most importantly, the mechanical performance of cellulose/MCNT films could be controlled by the additives of glycerol and MCNTs. The tensile strength of the cellulose/MCNT films was able to reach as high as 20.58 MPa, while the elongation at break was about 31.35%. To summarize, transparent cellulose/MCNT composites with enhanced ultraviolet-shielding properties can be manufactured successfully from low-cost cotton textile waste, which is beneficial not only in terms of environmental protection, but also the utilization of natural resources.

Abstract Certain chemotherapeutics can induce tumor cells’ immunogenic cell death (ICD), release tumor antigens, and thereby trigger personalized antitumor immune responses. Co-delivery of adjuvants using nanocarriers could amplify the ICD-induced tumor-specific immunity achieving a synergistic chemo-immunotherapeutic effect. However, complicated preparation, low drug loading efficiency, and potential carrier-associated toxicity are the major challenges that limited its clinical applications. Herein, a carrier-free core–shell nanoparticle (MPLA-CpG-sMMP9-DOX, MCMD NPs) was constructed by facile self-assembly of spherical nucleic acids (SNA) with two adjuvants of CpG ODN and monophosphoryl lipid A (MPLA) as a core and doxorubicin (DOX) radially around the dual-adjuvants SNA as a shell. The results demonstrated that MCMD NPs could enhance drugs accumulation in tumors, and release DOX upon enzymatic degradation of matrix metalloproteinase-9 (MMP-9) peptide in the tumor microenvironment (TME), which enhanced the direct-killing effect of DOX on tumor cells. The core of MPLA-CpG SNA efficiently boosted the ICD-induced antitumor immune response to further attack tumor cells. Thus, MCMD NPs achieved a synergistic therapeutic effect of chemo-immunotherapy with reduced off-target toxicity. This study provided an efficient strategy for the development of a carrier-free nano-delivery system for enhanced cancer chemo-immunotherapy.

Abstract A novel magnetic-targeted pH-responsive intelligent drug carrier based on hollow mesoporous structured NiFe2O4 nanospheres was designed and developed for potential anticancer treatment in the present study. The hollow mesoporous NiFe2O4 nanospheres were fabricated through a template-free solvothermal approach and the possible formation mechanism of this structure was proposed. The products were investigated comprehensively for their morphology, microstructure, composition and magnetic properties using a wide series of characterization methods. The NiFe2O4 nanospheres were demonstrated to possess a well-defined spherical morphology, homogeneous particle size distribution, large hollow cavities and abundant mesopores, unique superparamagnetic behavior, high saturation magnetization as well as good biocompatibility. Due to these desirable physicochemical properties, the hollow mesoporous NiFe2O4 nanospheres were expected to be employed as a potential vehicle for loading and delivering anticancer drug of doxorubicin hydrochloride (DOX). Drug release behavior was evidenced to be controllable and pH-responsive with effective DOX release of 73.1% and 58.8% in acidic conditions (pH 4.0 and 5.5), whereas insufficient drug release of 44.7% at a neutral atmosphere (pH 7.4) within 48 h. More importantly, the DOX-loaded NiFe2O4 nanospheres displayed significant anti-proliferation and apoptosis effects on human breast cancer cells (MCF-7), which further indicated the promising potential application of constructed drug delivery nanocarriers in the field of cancer therapy.

We identified a novel circovirus (human-associated circovirus 2 [HuCV2]) from the blood of 2 intravenous drug users in China who were infected with HIV-1, hepatitis C virus, or both. HuCV2 is most closely related to porcine circovirus 3. Our findings underscore the risk for HuCV2 and other emerging viruses among this population.

This study designed a novel multi-drugs co-delivery system of ciprofloxacin-curcumin-N-acetylcysteine based on hybrid nanocrystals technology for dry powder inhalations (DPIs). The particle size of PVP k-30 stabilized curcumin nanosuspensions and Poloxamer 188 stabilized ciprofloxacin - N-acetylcysteine (NAC) hybrid nanocrystals was 219.2±4.6 nm and 346.3±7.3 nm, respectively (n=3). The curcumin nanosuspensions was solidified with ciprofloxacin - N-acetylcysteine (NAC) hybrid nanocrystals accompanied by the L-leucine to improve the dispersion of the DPIs. The dispersion, uniformity and fluidity of the spray-dried ciprofloxacin - N-acetylcysteine - curcumin (CPFX/NAC/Cur) nanosuspensions superior to the freeze-dried DPIs. The ciprofloxacin and curcumin of the CPFX/NAC/Cur DPIs obtained by spray-drying with mannitol was amorphous form, and thereby the dispersibility and solubility would be further improved. The four components complex DPIs delivery system designed in this study could give full play to the effects of each component, and then produce synergistic results. Therefore, this multi-drugs ciprofloxacin-curcumin-N-acetylcysteine co-delivery system based on hybrid nanocrystals has the potential to be used in the clinical treatment of pulmonary infections to improve the treatment effect and quality of life of patients.

Microgrids are a promising solution for decentralized energy generation and distribution, offering reliability, efficiency, and resilience. These small-scale power systems can operate independently or connect to the main grid, providing greater reliability and resilience. However, integrating renewable energy into microgrids presents challenges due to their unpredictable nature and fluctuating load of electricity. Energy management strategies play a crucial role in optimizing the operation of microgrids, aiming to balance electricity supply and demand, maximize renewable energy utilization, and minimize operational costs. Various approaches have been proposed for energy management in microgrids, including optimization algorithms, machine learning techniques, and intelligent control systems. This study proposes an optimized and efficient strategy for microgrids operating in both independent and grid-connected modes, focusing on microgrids that utilize a combination of solar and green energy sources. The proposed approach, based on the Promoted Remora Optimization (PRO) algorithm, aims to meet load power requirements at the lowest possible cost while ensuring constant DC bus voltage and safeguarding batteries against overcharging and depletion. The CRO method effectively optimized the charging process, maintaining a consistent level of charge and achieving a final SoC of 33.37 %–33.60 %. It also demonstrated high system efficiency, with an average of 87.99 %, and a range of 87.80 %–88.03 %. The optimizer efficiency ranged from 83.12 % to 86.52 %, with an average of 86.46 %. The CRO method also achieved reasonable operating costs, with a cost per power of $0.1687/kW to $0.1699/kW and a daily cost of $1,379,595 to $1,479,998. Overall, the CRO method showed promise in optimizing the charging process in terms of efficiency and cost-effectiveness. Comparative analysis with existing literature is conducted to evaluate the effectiveness of the proposed approach, demonstrating its superior results compared to other energy management strategies for microgrids. This study contributes to the field of microgrid energy management by providing a novel approach based on the PRO algorithm and demonstrating its effectiveness through comparative analysis.

Reduced irrigation in combination with biochar application can improve stomatal anatomy, water relations and intrinsic water use efficiency (WUEi), thus having a positive effect on the alleviation of salinity and drought stresses. A split-root pot experiment was executed to explore the effects of two biochar applications (WSP: wheat straw biochar; SWP: soft wood biochar) in combination with three irrigation strategies (FI: full irrigation; DI: deficit irrigation, PRD: partial root-zone drying irrigation) on stomatal anatomy, water relations and WUEi of cotton plants under normal soil (S0, EC=0.36 dS m-1) and saline soil (S1, EC=16.55 dS m-1). The results revealed that both salinity and drought stresses negatively affected plant water relations and reduced stomatal conductance, carbon isotope discrimination (Δ13C), stomatal size (SS) and hydraulic conductance (Kl) while increased leaf abscisic acid (ABA) concentration ([ABA]leaf). However, biochar amendment under salt stress significantly decreased [ABA]leaf while improved leaf water relations, increased Kl, stomatal density (SD), SS, Δ13C and maximum stomatal conductance (gsmax). Meanwhile, compared with FI and DI, PRD plants had greater SD, gsmax, and WUEi but lowered stomatal conductance (gs). Among all treatments, the combined application of WSP and PRD significantly increased SD and gsmax, improved leaf water relations, Kl and [ABA]leaf and WUEi. It is concluded that the altered stomatal features caused by the biochar and irrigation treatments are associated with changes in [ABA]leaf and Kl, and have a major role in affecting plant hydraulic integrity and water use efficiency of cotton exposed to salinity stress.

As Internet of Things (IoT) applications continue to proliferate, traditional cloud computing is increasingly unable to meet the low-latency demands of these applications. The IoT fog architecture solves this limitation by introducing fog servers in the fog layer that are closer to the IoT devices. However, this architecture lacks authentication mechanisms for information sources, security verification for information transmission, and reasonable allocation of fog nodes. To ensure the secure transmission of end-to-end information in the IoT fog architecture, an attribute identification based security control and forwarding method for IoT fog data (AISCF) is proposed. AISCF applies attribute signatures to the IoT fog architecture and uses software defined network (SDN) to control and forward fog layer data flows. Firstly, IoT devices add attribute identifiers to the data they send based on attribute features. The ingress switch then performs fine-grained access control on the data based on these attribute identifiers. Secondly, SDN uses attribute features as flow table matching items to achieve fine-grained control and forwarding of fog layer data flows based on attribute identifiers. Lastly, the egress switch dynamically samples data flows and verifies the attribute signatures of the sampled data packets at the controller end. Experimental validation has demonstrated that AISCF can effectively detect attacks such as data tampering and forged matching items. Moreover, AISCF imposes minimal overhead on network throughput, CPU utilization and packet forwarding latency, and has practicality in IoT fog architecture.

BackgroundGlycogen storage diseases (GSDs) are a group of heterogeneous inherited metabolic disorders with an incidence of 4%–5%. There are 19 types of GSDs, making diagnosis one of the greatest challenges.MethodsThe proband and his parents were referred to our hospital for genetic diagnosis. Ultrasound screening suggested hepatomegaly. A novel insertion variant NM_000292 c.1155_1156insT (p. 386N>*) in PHKA2 gene was identified using trio whole exome sequencing (Trio-WES), which resulted in the codon of amino acid 386 from asparagine to termination (p. 386N>*). The 3D mutant protein structure was predicted using AlphaFold, and the results showed that the truncated PHKA2 protein contained 385 of the 1,235 amino acids of the mature protein.ConclusionWe describe a previously unreported case of a GSDs IXa type Chinese boy caused by a novel PHKA2 variant. This clinical case contributes to the understanding of the characteristics of GSDs type IXa and expands the variants spectrum of genes related to GSDs type IXa. Our findings demonstrated the significance of genetic testing in the diagnosis of GSDs.

Vegetation in China has experienced significant improvements under the combined effects of human activities and climate change. However, when exploring the effects of climate change on vegetation dynamics, existing studies mainly focus on two meteorological factors (temperature and precipitation) and rarely consider aerosol optical depth (AOD) and photosynthetically active radiation (PAR). Therefore, in this study, we further explored the potential dependence of leaf area index (LAI) on temperature (Tem), precipitation (Pre), AOD, and PAR, based on the analysis of the spatiotemporal variations of LAI in different vegetation types in China. Results showed that the LAI increased significantly from 2001 to 2020, with an overall growth rate of 0.0202/yr; the response of LAI for different vegetation types to each influencing factor varied greatly, and the deciduous broadleaf forests were more sensitive to climate change. Quantitative analysis based on the GeoDetector method showed that the most important driving force of LAI change is Pre (0.596); while Tem (0.394) and AOD (0.325) showed similar effects; by contrast, PAR (0.279) had the lowest driving force on LAI. Among them, the change of Pre is the dominant factor affecting LAI for most vegetation types. From the perspective of regional research, we found that the increase of LAI in the South was greater than that in North China, while human activities (urbanization) were unfavorable to the increase of LAI, such as the Yangtze River Delta where the LAI decreased significantly. This study contributes to a better understanding of the response of different vegetation types to climate and atmospheric changes in China over the past 20 years and provides a scientific reference for developing and implementing ecological restoration measures and promoting sustainable development. Overall, China is 'turning green', and air quality is improving.

Summary: Long non-coding RNAs (lncRNAs) play widespread roles in various processes. However, there is still limited understanding of the precise mechanisms through which they regulate early stage cardiomyocyte differentiation. In this study, we identified a specific lncRNA called LHX1-DT, which is transcribed from a bidirectional promoter of LIM Homeobox 1 (LHX1) gene. Our findings demonstrated that LHX1-DT is nuclear-localized and transiently elevated expression along with LHX1 during early differentiation of cardiomyocytes. The phenotype was rescued by overexpression of LHX1 into the LHX1-DT−/− hESCs, indicating LHX1 is the downstream of LHX1-DT. Mechanistically, we discovered that LHX1-DT physically interacted with RNA/histone-binding protein PHF6 during mesoderm commitment and efficiently replaced conventional histone H2A with a histone variant H2A.Z at the promoter region of LHX1. In summary, our work uncovers a novel lncRNA, LHX1-DT, which plays a vital role in mediating the exchange of histone variants H2A.Z and H2A at the promoter region of LHX1.

Abstract Background Ambient air pollutants can be hazardous to human health, especially for vulnerable children. The impact of ambient air pollutant exposure before and during intensive care unit (ICU) stays on the development of ventilator-associated pneumonia (VAP) in critically ill children has not been established. We aimed to determine the correlations between short-term exposures to ambient fine particulate matter (PM2.5) and VAP in pediatric cardiac surgery patients in the ICU, and explore the effect of delayed exposure. Methods The medical record of 1755 child patients requiring artificial ventilation in the ICU between December 2013 to December 2020, were analyzed. The daily average concentrations of particulate matters (PM2.5 and PM10), sulfur dioxide (SO2), and ozone (O3) were calculated from public data. Interactions between these pollutants and VAP were simulated with the distributed lag non-linear model. Results Three hundred forty-eight cases (19.829%) of VAP were identified in this study, while the average concentrations of PM2.5, PM10, O3 and SO2 were 58, 118, 98 and 26 μg/m3, respectively. Exposure to increased levels of PM2.5 two days prior (lag 2-day) to VAP diagnosis is significantly correlated with an enhanced risk for VAP development. Even a slight increase of 10 μg/m3 in PM2.5 can translate to a 5.4% increase in VAP incidence (95% CI: 1.4%-9.5%) while the VAP incidence increased to 11.1% (95%CI: 4.5–19.5%) when PM2.5 concentration is well below the National Ambient Air Quality standard (NAAQS) of 50 μg/m3. The association was more pronounced in those aged below 3-months, with low body mass index or suffered from pulmonary arterial hypertension. Conclusion Short-term PM2.5 exposure is a significant risk for development of VAP in pediatric patients. This risk is present even with PM2.5 levels below the NAAQS. Ambient PM2.5 may represent a previously unrecognized risk factor for pneumonia and the current environmental pollution standards need to be reevaluated to consider susceptible populations. Trial registration The trial was registered with the National Clinical Trial Center: The correlation between ambient air pollution and the complications in ICU underwent cardiac surgery. Trial registration number: ChiCTR2000030507. Date of registration: March 5, 2020. URL of trial registry record: http://www.chictr.org.cn/index.aspx .

A kind of novel two-dimensional magnetic nanocomposites were successfully fabricated via the immobilization of Fe3O4 nanoparticles onto the surface of graphitic carbon nitrogen (g-C3N4) nanosheets by a facile liquid exfoliated method and subsequent solvothermal reaction. The structural, morphological, compositional, thermal and magnetic characteristics of the as-prepared samples were systematically assessed by employing a wide spectrum of characterization techniques. Subsequently, the as-constructed Fe3O4/g-C3N4 composites were exploited to fabricate a stable magnetorheological (MR) suspension, and the rheological performances and sedimentation stability of the designed MR fluid were evaluated through a rotational rheometer and a visual observation method, respectively. The experimental results revealed that the established MR fluid demonstrated an obvious enhancement in sedimentation stability in comparison with that of another a kind of suspension containing carbonyl iron particles. The higher sedimentation stability realized in this MR smart system can be associated primarily with the dispersed Fe3O4/g-C3N4 composite particles with ultrathin sheet-like nanostructure and the reduced density mismatch.

Abstract High expression of CD38 in tissues is a characteristic of aging, resulting in a decline in nicotinamide adenine dinucleotide (NAD) and increasing cellular reactive oxygen species (ROS). However, whether CD38 increases susceptibility to ferroptosis remains largely unexplored. Our previous study showed that CD38 overexpression decreased dihydrofolate reductase (DHFR). In the present study, we confirmed that high expression of CD38 increased ROS levels and induced DHFR degradation, which was prevented by nicotinamide mononucleotide (NMN) replenishment. We further revealed that ROS-mediated sulfonation on Cys7 of DHFR induced its degradation via the autophagy and non-canonical proteasome pathways. Mutation of Cys7 to alanine abolished ROS-induced DHFR degradation. Moreover, oxidative degradation of DHFR was responsible for the increased ferroptosis susceptibility of cells in which CD38 was highly expressed. We also found that CD38 expression was higher in bone-marrow-derived macrophages (BMDMs) from aged mice than those from young mice, while the DHFR level was lower. Consequently, we demonstrated that BMDMs from aged mice were more susceptible to ferroptosis that can be reverted by NMN replenishment, suggesting that CD38 high expression rendered cells more susceptible to ferroptosis. Taken together, these results indicated that CD38-mediated NAD+ decline promoted DHFR oxidative degradation, thus resulting in increased cellular susceptibility to ferroptosis and suggesting that NMN replenishment may protect macrophages from ferroptosis in aged mice.

IntroductionPyrotinib is a novel irreversible pan-HER tyrosine kinase inhibitor (TKI). However, real-world data of pyrotinib-containing therapy in human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC) and developing brain metastases (BMs) are limited, and the genomic profile of this subpopulation is almost undefined.Methods and materialsPatients with BM of HER2-positive MBC (n = 35) treated with pyrotinib-containing therapy were enrolled in this analysis. Progression-free survival (PFS), overall survival (OS), objective response rate (ORR), disease control rate (DCR), and toxicity profiles were evaluated. Hazard ratios (HRs) and 95% confidence intervals (CIs) for disease progression were estimated using the Cox proportional hazards models. Targeted next-generation sequencing of 618 cancer-relevant genes was performed on plasma and primary breast tumors from patients with BM and without BM.ResultsThe median PFS time was 8.00 (95% CI, 5.98–10.017) months, and the median OS time was 23 (95% CI, 10.412–35.588) months. The ORR was 45.7%, and the DCR was 74.3%. In the Cox multivariate analysis, prior exposure to brain radiotherapy (HR = 3.268), received pyrotinib as third- or higher-line treatment (HR = 4.949), subtentorial brain metastasis (HR = 6.222), and both supratentorial and subtentorial brain metastases (HR = 5.863) were independently associated with increased risk of progression. The frequent grade 3–4 adverse event was increased direct bilirubin (14.3%), and two patients suffered from grade 3–4 diarrhea. In the exploratory genomic analysis, altered frequencies of FGFR3, CD276, CDC73, and EPHX1 were higher in the BM group. The consistency of mutated profiles of plasma and primary lesion in the BM group was significantly lower (30.4% vs. 65.5%; p = 0.0038).ConclusionsPyrotinib-containing therapy shows favorable effectiveness and tolerable safety in patients with BM of HER2-positive MBC, particularly in a population that is brain radiotherapy-naïve, received pyrotinib as first- or second-line treatment, and developed supratentorial brain metastasis. In the exploratory genomic analysis, patients with BM showed distinct genomic features from patients without BM.

Peanut (Arachis hypogea L.) bacterial wilt (BW) is a devastating disease caused by Ralstonia solanacearum that results in severe yield and quality losses. Plant defensins are short cysteine-rich peptides with antimicrobial activity. The role of defensin genes (AhDef) in peanut is unclear. A genome-wide investigation of AhDef genes was undertaken, and 12 identified AhDef genes were classified into two groups containing the gamma-thionin domain formed by four disulfide pairs: Cys1-Cys8, Cys2-Cys5, Cys3-Cys6, and Cys4-Cys7. In silico analysis revealed that AhDef genes showed highly conserved architectural features and contained cis-elements associated with phytohormone signaling and defense responses. A highly resistant cultivar, H108 (R) and a susceptible accession, H107 (S) were tested by R. solanacearum inoculation. H108 (R) showed fewer symptoms than H107 (S) owing to inhibition of bacterial reproduction and spread in the vascular bundles of roots and stems. In a transcriptomic expression profile, AhDef genes, particularly AhDef1.6 and AhDef2.2, were up-regulated in H108 (R) compared with H107 (S) under R. solanacearum infection and phytohormone treatment. Subcellular localization showed that the AhDef1.6 and AhDef2.2 proteins were both expressed specifically on the plasma membrane. Overexpression of protein fusion AhDef2.2-YFP in Nicotiana benthamiana and peanut leaves increased resistance to R. solanacearum, suggesting its role in response to BW infection. AhDef2.2 may be valuable for peanut resistance breeding.

Extreme environmental and climate problems have been ravaging the world, causing serious economic losses and hindering human development, so that carbon neutrality has become a global undertaking related to the survival of human civilization. To ensure climate change mitigation and carbon emission reduction, this paper finds that green finance as an important and efficient tool has become a legislative priority for many countries and have been embedded in the path to achieve carbon neutrality. On the basis of in-depth analysis of the evolution and development of global green finance, this paper reviews and summarizes the development of green finance in China through literature analysis and horizontal comparison, and explores concrete recommendations and feasible tools that can be tailored to China’s carbon neutrality goal and stage of development. It is concluded that China needs to improve the green finance operation mechanism and flexible policy framework, to formulate a more accurate timetable and roadmap, to strengthen the modernization of the governance system and governance capacity and to promote the global green finance cooperation.

Abstract Chemotherapeutics that can trigger immunogenic cell death (ICD) and release tumor-specific antigens are effective on treating a variety of cancers. The codelivery of chemotherapeutics with adjuvants is a promising strategy to achieve synergistic therapeutic effect. However, low drug loading and complicated preparation of current delivery systems lead to carrier-associated toxicity and immunogenicity. Herein, we developed a facile approach to construct liposomal spherical nucleic acids (SNA) by the self-assembly of 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE)-doxorubicin conjugate and DOPE-matrix metalloproteinases-9 (MMP-9) responsive peptide-CpG conjugate (DOPE-MMP-CpG). Liposomal SNAs efficiently co-delivered DOX and CpG into tumors and released the two drugs upon biological stimuli of MMP-9 enzyme in tumor microenvironment (TME) and high concentration of endogenous glutathione in tumor cells. We demonstrated that liposomal SNA enhanced activation of dendritic cells (DCs), promoted expansion of CD8+ and CD4+ T cells in both tumors and spleen, inhibited tumor growth, and extended animal survival. This work provided a simple strategy of delivering chemotherapeutics and adjuvants to tumors with synergistic therapeutic effect and reduced side effect. Graphical Abstract

The disease of SARS-CoV-2 has caused considerable morbidity and mortality globally. Spike proteins on the surface of SARS-CoV-2 allow it to bind with human cells, leading to infection. Fullerenes and their derivatives are promising SARS-CoV-2 inhibitors and drug-delivery vehicles. In this study, Gaussian accelerated molecular dynamics simulations and the Markov state model were employed to delve into the inhibitory mechanism of Fullerene–linear-polyglycerol-b-amine sulfate (F–LGPS) on spike proteins. During the study, it was discovered that fullerene derivatives can operate at the interface of the receptor-binding domain (RBD) and the N-terminal domain (NTD), keeping structural domains in a downward conformation. It was also observed that F-LGPS demonstrated superior inhibitory effects on the XBB variant in comparison to the wild-type variant. This study yielded invaluable insights for the potential development of efficient therapeutics targeting the spike protein of SARS-CoV-2.

The urban road network is a large and complex system characterized by significant heterogeneity arising from different spatial structures and traffic demands. To facilitate effective management and control, it is necessary to partition the road network into homogeneous sub-areas. In this regard, we aim to propose a hybrid method for partitioning sub-areas with intra-area homogeneity, inter-area heterogeneity, and similar sizes, called CSDRA. It is specifically designed for bidirectional road networks with segment weights that encompass traffic flow, speed, or roadside facility evaluation. Based on community detection and spectral clustering, this proposed method comprises four main modules: initial partition, partitioning of large sub-areas, reassignment of small sub-areas, and boundary adjustment. In the preliminary partitioning work, we also design a road network reconstruction method which further helps to enhance the intra-area homogeneity and inter-area heterogeneity of partitioning results. Furthermore, to align with the requirement for comparable work units in practical traffic management and control, we control the similarity in the size of sub-areas by enforcing upper and lower bound constraints on the size of the sub-areas. We verify the outperformance of the proposed method by an experiment on the partitioning of an urban road network in Guangzhou, China, where we employ sidewalk barrier-free score data as segment weights. The results demonstrate the effectiveness of both the road network reconstruction method and the CSDRA proposed in this paper, as they significantly improve the partitioning outcomes compared with other methods using different evaluation indicators corresponding to the partitioning objectives. Finally, we investigate the influence of constraint parameters on the evaluation indicator. Our findings indicate that appropriately configuring these constraint parameters can effectively minimize sub-region size variations while having minimal impact on other aspects.

In this day and age, livestream shopping is developing by leaps and bounds in China. It has been proved that livestream shopping is efficient in attracting customers and boosting the sales of products. However, very little research has been carried out on user stickiness, which plays a valuable role in business success. In light of the stimulus–organism–response framework (S–O–R), a multiple-mediation model (identification and gratification as mediators) was established to examine the effect of interactivity affordance (S) on the user stickiness (R) of a sample of 489 Chinese livestream viewers. Structural equation modeling with bootstrapping estimation was performed to examine the mediating roles of identification (O-cognitive) and gratification (O-affective). The modeling results revealed that the relationship between interactivity affordance and user stickiness was partially mediated by identification combined with utilitarian gratification and fully mediated by identification combined with hedonic gratification. The findings stress the importance of categorizing gratifications. In addition, these findings offer new perspectives for understanding the effects of IT affordance on user stickiness.

Bovine viral diarrhea virus (BVDV) is the causative agent of bovine viral diarrhea-mucosal disease, which significantly affects the production performance of cattle, causing serious economic losses to the cattle industries worldwide. Up to now, some mechanisms involved in host–BVDV interaction are still not fully understood. The discovery of long non-coding RNAs (lncRNAs) has provided a new perspective on gene regulation in diverse biological contexts, particularly in viral infection and host immune responses. However, little is known about the profiles and functions of lncRNAs in host cells in response to BVDV infection. Here, we utilized Illumina sequencing to explore lncRNAs profiles in cytopathic (CP) biotype BVDV-infected MDBK cells to further reveal the potential roles of lncRNAs in BVDV infection and host–BVDV interaction with integrated analysis of lncRNAs and mRNA expression profiles. A total of 1747 significantly differentially expressed genes, DEGs (156 lncRNAs and 1591 mRNAs) were obtained via RNA-seq in BVDV-infected MDBK cells compared to mock-infected cells. Next, these DE lncRNAs and mRNAs were subjected to construct lncRNAs-mRNAs co-expression network followed by the prediction of potential functions of the DE lncRNAs. Co-expression network analysis elucidated that DE lncRNAs were significant enrichment in NOD-like receptor, TNF, NF-ĸB, ErbB, Ras, apoptosis, and fatty acid biosynthesis pathways, indicating that DE lncRNAs play important roles in host–BVDV interactions. Our data give an overview of changes in transcriptome and potential roles of lncRNAs, providing molecular biology basis for further exploring the mechanisms of host–BVDV interaction.

Hormone receptor-positive HER2-positive (HR+/HER2+) metastatic breast cancer (MBC) is a unique subtype of breast cancer. Most current guidelines recommend that combination regimens based on anti-HER2 therapy should be used as first-line treatment for HER2+ MBC, irrespective of HR status. Endocrine therapy can be applied as maintenance therapy for patients who are intolerant to chemotherapy or post-chemotherapy. Increasing evidence suggests that complex molecular crosstalk between HR and HER2 pathways may affect the sensitivity to both HER2-targeted and endocrine therapy in patients with HR+/HER2+ breast cancer. Recent research and clinical trials have revealed that a combination of endocrine therapy and anti-HER2 approaches without chemotherapy provides along-term disease control for some patients, but the challenge lies in how to accurately identify the subsets of patients who can benefit from such a de-chemotherapy treatment strategy. In this review, we aim to summarize the results of preclinical and clinical studies in HR+/HER2+ MBC and discuss the possibility of sparing chemotherapy in this subgroup of patients.

BackgroundVentilator-associated pneumonia (VAP) is the most common healthcare-associated infection (HAI) in patients with mechanical ventilation. VAP is largely preventable, and a comprehensive unit-based safety program (CUSP) has effectively reduced HAI. In this study, we aim to comprehensively investigate the effect of implementing the CUSP in patients requiring mechanical ventilation.MethodsIn this uncontrolled before-and-after trial conducted in two intensive care unit (ICU) settings in China, patients requiring invasive mechanical ventilation were enrolled. Patients were divided into two groups based on the implementation of CUSP. The primary outcome was the incidence of VAP. The secondary outcomes were the time from intubation to VAP, days of antibiotic use for VAP treatments, rate of other infection, length of stay (LOS) in ICU, hospital LOS, and safety culture score. Joinpoint regression analysis was used to test the changes in trends of VAP rate for statistical significance. Propensity score matching (1:1 matching) was used to reduce the potential bias between CUSP and no CUSP groups. Univariate and multivariate logistic/linear regression analyses were performed to evaluate the association between the use of CUSP and clinical outcomes. This study was registered at the Chinese Clinical Trial Registry (chictr.org.cn), registration number: ChiCTR1900025391.ResultsA total of 1,004 patients from the transplant ICU (TICU) and 1,001 patients from the surgical ICU (SICU) were enrolled in the study from January 2016 to March 2022. Before propensity score matching, the incidences of VAP decreased from 35.1/1,000 ventilator days in the no CUSP group to 12.3/1,000 ventilator days in the CUSP group in the TICU setting (adjusted odds ratio [OR], 0.30; 95% confidence interval [CI], 0.15–0.59). The results of the joinpoint regression analysis confirmed that the implementation of CUSP significantly decreased the incidences of VAP. After propensity score matching in TICU setting, the CUSP group reported a lower incidence of VAP (30.4 vs. 9.7‰, P = 0.003; adjusted OR = 0.26, 95% CI: 0.10–0.76), lower wound infection (3.4 vs. 0.9%, P = 0.048; adjusted OR = 0.73, 95% CI: 0.50–0.95), shorter ICU LOS [3.5(2.3–5.3) vs. 2.5(2.0–4.5) days; P = 0.003, adjusted estimate = −0.34, 95% CI: −0.92 to −0.14], and higher safety culture score (149.40 ± 11.74 vs. 153.37 ± 9.74; P = 0.002). Similar results were also observed in the SICU setting between the no CUSP and CUSP group.ConclusionsThe implementation of CSUP for patients receiving mechanical ventilation could significantly reduce the incidences of VAP, and other infections, prolong the time until the VAP occurrence, reduces the days of antibiotic use for VAP, shorten the ICU and hospital LOS, and enhance the awareness of safety culture.

Changes in the microbial community are considered important factors affecting the yield and quality of ginseng cultivated in farmland, while the characteristics of the change in the microbial community of the soil before and after cultivation of ginseng in farmland are not well understood. Here, we aimed to fill this research gap by comparing the differences in soil nutrients and microbial communities between continuously cultivated ginseng soils for 1-, 2-, 3- and 5-year-old ginseng soils and corresponding uncultivated ginseng soils. The soil properties (pH, total soil organic carbon (TOC) content and total nitrogen (TN) content) of aged ginseng soil (3- and 5-year-old) were significantly reduced compared with those of the control soil after ginseng was cultivated in farmland. With the exception of 2-year-old ginseng, soil bacterial richness and diversity were higher in different ages of cultivated ginseng soils than in the control soil, while fungal diversity decreased in aged ginseng soil and increased in young ginseng soil (1- and 2-year-old). Ascomycota and Basidiomycota showed a consistent increasing/decreasing trend in cultivated ginseng soils of all ages compared to the control. In addition, ginseng cultivation resulted in a substantial decrease in the complexity of soil bacterial networks but a slight decrease in the complexity of fungal networks. The results from the linear discriminant size effect (LEfSe) analysis showed that beneficial microorganisms were biomarkers of the young ginseng soil, including Nitrosospira, Cephalotrichum and Humicola, while harmful microorganisms were biomarkers of aged ginseng, such as Plectosphaerella, Cladosporium and Alternaria. PICRUSt2 analysis revealed that the increase in the incidence of ginseng disease with continuous cultivation time may be related to the decreases in amino acid synthesis and physiological metabolism and the increase in fungal saprophytes. Soil pH was the most common and best predictor of bacterial and fungal community structure, followed by TOC and ammonium nitrogen (NH4+-N) contents. Meanwhile, the decreased of soil pH, TOC and AK may be the driving factors for the growth of ginseng soil pathogens. Overall, this study revealed the changing ginseng rhizosphere soil microbial community at different continuous cultivation times, provided a theoretical basis for ginseng cultivation, and promoted the development of medicinal plants such as ginseng.

ABSTRACT HIV-1 CRF07_BC originated among injection drug users (IDUs) in China. After diffusing into men who have sex with men (MSM), CRF07_BC has shown a rapid expansion in this group; however, the mechanism remains unclear. Here, we identified a new K28E32 variant of CRF07_BC that was characterized by five specific mutations (E28K, K32E, E248V, K249Q, and T338S) in reverse transcriptase. This variant was mainly prevalent among MSM, and was overrepresented in transmission clusters, suggesting that it could have driven the rapid expansion of CRF07_BC in MSM, though founder effects cannot be ruled out. It was descended from an evolutionary intermediate accumulating four specific mutations and formed an independent phylogenetic node with an estimated origin time in 2003. The K28E32 variant was demonstrated to have significantly higher in vitro HIV-1 replication ability than the wild type. Mutations E28K and K32E play a critical role in the improvement of in vitro HIV-1 replication ability, reflected by improved reverse transcription activity. The results could allow public health officials to use this marker (especially E28K and K32E mutations in the reverse transcriptase (RT) coding region) to target prevention measures prioritizing MSM population and persons infected with this variant for test and treat initiatives. IMPORTANCE HIV-1 has very high mutation rate that is correlated with the survival and adaption of the virus. The variants with higher transmissibility may be more selective advantage than the strains with higher virulence. Several HIV-1 variants were previously demonstrated to be correlated with higher viral load and lower CD4 T cell count. Here, we first identified a new variant (the K28E32 variant) of HIV-1 CRF07_BC, described its origin and evolutionary dynamics, and demonstrated its higher in vitro HIV-1 replication ability than the wild type. We demonstrated that five RT mutations (especially E28K and K32E) significantly improve in vitro HIV-1 replication ability. The appearance of the new K28E32 variant was associated with the rapidly increasing prevalence of CRF07_BC among MSM.

BackgroundTumors are characterized by extracellular matrix (ECM) remodeling and stiffening. The ECM has been recognized as an important determinant of breast cancer progression and prognosis. Recent studies have revealed a strong link between ECM remodeling and immune cell infiltration in a variety of tumor types. However, the landscape and specific regulatory mechanisms between ECM and immune microenvironment in breast cancer have not been fully understood.MethodsUsing genomic data and clinical information of breast cancer patients obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we conducted an extensive multi-omics analysis to explore the heterogeneity and prognostic significance of the ECM microenvironment. Masson and Sirius red staining were applied to quantify the contents of collagen in the ECM microenvironment. Tissue immunofluorescence (IF) staining was applied to identify T helper (Th) cells.ResultsWe classified breast cancer patients into two ECM-clusters and three gene-clusters by consensus clustering. Significant heterogeneity in prognosis and immune cell infiltration have been found in these distinct clusters. Specifically, in the ECM-cluster with better prognosis, the expression levels of Th2 and regulatory T (Treg) cells were reduced, while the Th1, Th17 and T follicular helper (Tfh) cells-associated activities were significantly enhanced. The correlations between ECM characteristics and Th cells infiltration were then validated by clinical tissue samples from our hospital. The ECM-associated prognostic model was then constructed by 10 core prognostic genes and stratified breast cancer patients into two risk groups. Kaplan-Meier analysis showed that the overall survival (OS) of breast cancer patients in the high-risk group was significantly worse than that of the low-risk group. The risk scores for breast cancer patients obtained from our prognostic model were further confirmed to be associated with immune cell infiltration, tumor mutation burden (TMB) and stem cell indexes. Finally, the half-maximal inhibitory concentration (IC50) values of antitumor agents for patients in different risk groups were calculated to provide references for therapy targeting distinct ECM characteristics.ConclusionOur findings identify a novel strategy for breast cancer subtyping based on the ECM characterization and reveal the regulatory roles of Th cells in ECM remodeling. Targeting ECM remodeling and Th cells hold potential to be a therapeutic alternative for breast cancer in the future.

Particle matter (PM) mass concentrations have an important influence on human and environmental health. Lidar plays an important role in the monitoring of PM concentrations. However, the accuracy of PM concentrations retrieved via lidar depends on the performance of the conversion model from the aerosol extinction coefficient (EC) to PM concentration. Therefore, surface PM concentrations, aerosol EC and five meteorological factors are used to build the conversion model that can also be applicable to lidar for retrieving PM concentrations. In this study, the traditional linear model (LM), random forest (RF) and artificial neural network (ANN) algorithms are used to estimate the mass concentrations of PM with aerodynamic diameters < 1 µm (PM1), 2.5 µm (PM2.5) and 10 µm (PM10). The influence of meteorological factors on the conversion model is analyzed. The results show that the meteorological parameters play a non-ignorable role in the model of PM retrieval based on EC, especially when retrieving PM10. Moreover, the performance of three models is investigated by comparing with the surface measurements. The results indicate that the RF and ANN models are more suitable to estimate PM than the LM model. The diurnal variations in mean relative error (MRE) from the three models are then analyzed. There is a diurnal pattern in MRE values, meaning that the maximum values occur in the afternoon and the minimum values occur at night. In addition, there are subtle differences in performance between two machine learning (ML) models. After analysis, it is found that for PM10, the RF method is superior to the ANN when the EC value is small, while the ANN method is superior to the RF when the EC value is relatively high, and the EC threshold is set to 0.6 km−1. For PM1 and PM2.5 estimation, the ANN is the most appropriate model. Finally, accurate diurnal variations in PM1 and PM2.5 based on the ANN model and PM10 based on the combined model of RF and ANN (named RA) are investigated. The results exhibit that the daily maximum values of PM1, PM2.5 and PM10 in the Wuhan area all occur at approximately 08:00–10:00 local time (LT), which is mainly due to the impact of commuter vehicle emissions and the impact of secondary photochemistry response aggravated by sufficient illumination and temperature rises after sunrise. These research results provide an important basis for particulate matter monitoring.