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Abstract Background Acute intermittent porphyria (AIP) is a rare genetic metabolic disorder characterized by acute attacks of neurovisceral symptoms. This disease not only poses a threat to patients’ physical and mental well-being, but its frequent acute attacks also have a profound impact on patients’ mental state and overall quality of life (QoL). Objective This study aimed to explore the impact of internet-based health education on the acute attacks, mental health, and QoL of patients with AIP. Methods This study employed a pre-post comparison design, recruiting 52 patients diagnosed with AIP and treated at the Second Hospital of Hebei Medical University between September 2021 and May 2023 as the subjects of investigation. All participants underwent a 12-month internet-based health education intervention. Quantitative assessments of the intervention’s efficacy in reducing acute attacks, enhancing mental health status, and improving QoL among AIP patients were conducted using various instruments, including measures of acute episode frequency and severity, the Depression Anxiety Stress Scales-21 (DASS-21), the Positive and Negative Affect Schedule (PANAS), and the MOS 36-Item Short Form Health Survey (SF-36). Data were collected at two distinct time points: pre- and post-health education interventions, which were then subjected to comparative analysis. Results Compared to pre-health education, the frequency of acute attacks among patients with AIP significantly decreased post-health education intervention (p

Efficient Convolution Operator (ECO) algorithms have achieved impressive performances in visual tracking. However, its feature extraction network of ECO is unconducive for capturing the correlation features of occluded and blurred targets between long-range complex scene frames. More so, its fixed weight fusion strategy does not use the complementary properties of deep and shallow features. In this paper, we propose a new target tracking method, namely ECO++, using deep feature adaptive fusion in a complex scene, in the following two aspects: First, we constructed a new temporal convolution mode and used it to replace the underlying convolution layer in Conformer network to obtain an improved Conformer network. Second, we adaptively fuse the deep features, which output through the improved Conformer network, by combining the Peak to Sidelobe Ratio (PSR), frame smoothness scores and adaptive adjustment weight. Extensive experiments on the OTB-2013, OTB-2015, UAV123, and VOT2019 benchmarks demonstrate that the proposed approach outperforms the state-of-the-art algorithms in tracking accuracy and robustness in complex scenes with occluded, blurred, and fast-moving targets.

Abstract Serine is essential to maintain maximal growth and proliferation of cancer cells by providing adequate intermediate metabolites and energy. Phosphoserine aminotransferase 1 (PSAT1) is a key enzyme in de novo serine synthesis. However, little is known about the mechanisms underlying PSAT1 degradation. We found that acetylation was the switch that regulated the degradation of PSAT1 in lung adenocarcinoma (LUAD). Deacetylation of PSAT1 on Lys51 by histone deacetylase 7 (HDAC7) enhanced the interaction between PSAT1 and the deubiquitinase ubiquitin-specific processing protease 14 (USP14), leading to the deubiquitination and stabilization of PSAT1; while acetylation of PSAT1 promoted its interaction with the E3 ligase ubiquitination factor E4B (UBE4B), leading to proteasomal degradation. Acetylation of PSAT1 on Lys51 regulated serine metabolism and tumor proliferation in LUAD. Thus, acetylation and ubiquitination cooperatively regulated the protein homeostasis of PSAT1. In conclusion, our study reveals a key regulatory mechanism for maintaining PSAT1 protein homeostasis in LUAD.

Abstract Background Annual breast magnetic resonance imaging (MRI) is highly recommended to assist mammography for women at high risk of breast cancer (BC). This study explored the knowledge, attitude, and willingness toward breast MRI screening among women at high risk of BC. Methods This cross-sectional study enrolled women at high risk of BC between August 2022 and January 2023 in Beijing, China. A structural equation model (SEM) was used to analyze the relationships among knowledge, attitude, and willingness. Results A total of 596 questionnaires were collected, and 412 questionnaires (69.13%) were valid. The women’s knowledge and attitude scores were 7.75 ± 2.79 (possible range: 0–12) and 48.53 ± 6.31 (possible range: 13–65). Among the women, 297 (72.09%) were willing to undergo regular breast MRI screening. The SEM showed that knowledge had direct effect on attitude [β = 0.77, 95% CI: (0.57, 0.98), P

ObjectiveTo analyze the whole-genome characteristics of four coxsackievirus B5 (CVB5) strains isolated in Yunnan province, China in 2022. MethodsPrimers were designed to amplify and sequence the whole genome of CVB5 isolates. The whole genome was amplified in segments, and sequenced using the "primer walking" method. Sequence splicing and assembly were performed. Genetic characteristics of the CVB5 strains were analyzed using software such as MEGA 7.0, Simplot 3.5.1, and DNAStar 7.1. ResultsBased on VP1 and whole-genome phylogenetic analysis, all four CVB5 isolates belonged to genotype C. Compared with the prototype strain, multiple amino acid mutations occurred in the VP1 region of the four strains. Phylogenetic analysis of P1, P2, and P3 regions and Simplot recombination analysis showed that the CVB5 isolates in this study may have undergone recombination with multiple enterovirus B strains. ConclusionThe four CVB5 strains isolated from clinical samples of hand, foot and mouth disease (HFMD) patients in Kunming, Yunnan province in 2022 all belonged to genotype C.

Abstract In this study, we dynamically monitored the glomerular filtration rate and other assessment of renal function and markers of injury in various mice models of acute kidney injury. Male C57BL/6 mice were utilized to establish acute kidney injury models of sepsis, ischemia reperfusion, cisplatin, folic acid, aristolochic acid and antibiotic. In addition to the real time glomerular filtration rate, renal LCN-2 and HAVCR-1 mRNA expression levels, and serum creatinine, urea nitrogen and cystatin c levels were also used to evaluate renal function. In addition, the protein levels of LCN-2 and HAVCR-1 in renal, serum and urine were measured. Our results demonstrated that the changes in biomarkers always lagged the real time glomerular filtration rate during the progression and recovery of renal injury. Cystatin-c can reflect renal injury earlier than other markers, but it remains higher in the recovery stage. Perhaps the glomerular filtration rate does not reflect the greater injury caused by vancomycin plus piperacillin.

Abstract Fruit ripening is accompanied by the development of fruit quality traits; however, this process also increases the fruit’s susceptibility to various environmental stresses, including pathogen attacks and other stress factors. Therefore, modulating the fruit ripening process and defense responses is crucial for maintaining fruit quality and extending shelf life. Membrane proteins play intricate roles in mediating signal transduction, ion transport, and many other important biological processes, thus attracting extensive research interest. This review mainly focuses on the functions of membrane proteins in regulating fruit ripening and defense responses against biotic and abiotic factors, addresses their potential as targets for improving fruit quality and resistance to environmental challenges, and further highlights some open questions to be addressed.

Abstract Genes involved in drug absorption, distribution, metabolism, and excretion (ADME) are named ADME genes. However, the comprehensive role of ADME genes in kidney renal clear cell carcinoma (KIRC) remains unclear. Using the clinical and gene expression data of KIRC patients downloaded from The Cancer Genome Atlas (TCGA), ArrayExpress, and the Gene Expression Omnibus (GEO) databases, we cluster patients into two patterns, and the population with a relatively poor prognosis demonstrated higher level of immunosuppressive cell infiltration and higher proportion of glycolytic subtypes. Then, 17 ADME genes combination identified through the least absolute shrinkage and selection operator algorithm (LASSO, 1000 times) was utilized to calculate the ADME score. The ADME score was found to be an independent predictor of prognosis in KIRC and to be tightly associated with the infiltration level of immune cells, metabolic properties, tumor-related signaling pathways, genetic variation, and responses to chemotherapeutics. Our work revealed the characteristics of ADME in KIRC. Assessing the ADME profiles of individual patients can deepen our comprehension of tumor microenvironment (TME) features in KIRC and can aid in developing more personalized and effective therapeutic strategies.

Abstract Background There is an association between migraine and dementia, however, their causal relationship remains unclear. This study employed bidirectional two-sample Mendelian randomization (MR) to investigate the potential causal relationship between migraine and dementia and its subtypes: Alzheimer’s disease (AD), vascular dementia (VaD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB). Methods Summary-level statistics data were obtained from publicly available genome-wide association studies (GWAS) for both migraine and five types of dementia. Single nucleotide polymorphisms (SNPs) associated with migraine and each dementia subtype were selected. MR analysis was conducted using inverse variance weighting (IVW) and weighted median (WM) methods. Sensitivity analyses included Cochran’s Q test, MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, the intercept of MR-Egger, and leave-one-out analysis. Results Migraine showed a significant causal relationship with AD and VaD, whereas no causal relationship was observed with all-cause dementia, FTD, or DLB. Migraine may be a potential risk factor for AD (odds ratio [OR]: 1.09; 95% confidence interval [CI]: 0.02–0.14; P = 0.007), while VaD may be a potential risk factor for migraine (OR: 1.04; 95% CI: 0.02–0.06; P = 7.760E-5). Sensitivity analyses demonstrated the robustness of our findings. Conclusion Our study suggest that migraine may have potential causal relationships with AD and VaD. Migraine may be a risk factor for AD, and VaD may be a risk factor for migraine. Our study contributes to unraveling the comprehensive genetic associations between migraine and various types of dementia, and our findings will enhance the academic understanding of the comorbidity between migraine and dementia.

Abstract Owing to its versatile roles in almost all aspects of plants, FERONIA (FER), a receptor-like kinase of the Catharanthus roseus receptor-like kinase 1-like (CrRLK1L) subfamily, has received extensive research interests during the past decades. Accumulating evidence has been emerged that FER homologs in horticultural crops also play crucial roles in reproductive biology and responses to environmental stimuli (abiotic and biotic stress factors). Here, we provide a review for the latest advances in the studies on FER homologs in modulating stress responses in horticultural crops, and further analyze the underlying mechanisms maintained by FER. Moreover, we also envisage the missing links in current work and provide a perspective for future studies on this star protein.

To make full use of tobacco waste in cigarette production and enhance resource utilization efficiency, cellulose nanocrystals (CNCs) were prepared by a method of sulfuric acid combined with a deep eutectic solvent. This method was compared with conventional methods, and the CNCs were thoroughly characterized. The results indicated that the yield of CNCs prepared by the sulfuric acid combined with a deep eutectic solvent method exceeded 26 %, with the highest yield reaching 29.5 %, surpassing the yields from two other methods of 12.5 %, 17.2 %, corresponding to sulfuric acid and sulfuric acid-oxalic acid, respectively. Scanning electron microscopy revealed a laminar morphology of CNCs, in which the CNCs maintained a cellulose type I structure with well-preserved crystallinity. In addition, CNCs prepared by the sulfuric acid combined with a deep eutectic solvent method exhibited good thermal stability, with maximum mass loss at temperature of 342.8 °C during third pyrolysis stage, higher than that of sulfuric acid at 316.7 °C and sulfuric acid-oxalic acid at 335.9 °C. Steady-state rheological testing revealed that the viscosity of the CNCs suspension decreased with an increasing shear rate, which is characteristic of pseudoplastic fluid shear thinning behavior. CNCs prepared by the sulfuric acid combined with DES method reduced the amount of sulfuric acid, and the yield was much higher than that of the other two methods. Moreover, the method using sulfuric acid combined with DES method was simple and safe, and the obtained CNCs had high thermal stability and viscosity, which expands the application prospects in biocomposite material fields.

BackgroundThe status of sentinel lymph nodes is crucial for prognosis and treatment decisions in breast cancer patients. This study aimed to evaluate the predictive value of combined methylene blue and indocyanine green for sentinel lymph node metastasis in breast cancer.MethodsThis prospective cohort study enrolled 90 clinically node-negative breast cancer patients. Methylene blue and indocyanine green were injected locally before surgery. Sentinel lymph nodes were grouped based on fluorescence intensity and methylene blue staining. A binary logistic regression model was established using 285 lymph node groups to predict metastatic risk.ResultsA total of 475 lymph nodes were identified, with 33 being metastatic. The metastatic risk reached 70% for partially blue-stained and weakly fluorescent lymph nodes between 1-2 cm. The model revealed associations between lymph node size, dye staining patterns, and metastatic risks (P

BackgroundOnline mental health communities (OMHCs) are an effective and accessible channel to give and receive social support for individuals with mental and emotional issues. However, a key challenge on these platforms is finding suitable partners to interact with given that mechanisms to match users are currently underdeveloped or highly naive. ObjectiveIn this study, we collaborated with one of the world’s largest OMHCs; our contribution is to show the application of agent-based modeling for the design of online community matching algorithms. We developed an agent-based simulation framework and showcased how it can uncover trade-offs in different matching algorithms between people seeking support and volunteer counselors. MethodsWe used a comprehensive data set spanning January 2020 to April 2022 to create a simulation framework based on agent-based modeling that replicates the current matching mechanisms of our research site. After validating the accuracy of this simulated replication, we used this simulation framework as a “sandbox” to test different matching algorithms based on the deferred acceptance algorithm. We compared trade-offs among these different matching algorithms based on various metrics of interest, such as chat ratings and matching success rates. ResultsOur study suggests that various tensions emerge through different algorithmic choices for these communities. For example, our simulation uncovered that increased waiting time for support seekers was an inherent consequence on these sites when intelligent matching was used to find more suitable matches. Our simulation also verified some intuitive effects, such as that the greatest number of support seeker–counselor matches occurred using a “first come, first served” protocol, whereas relatively fewer matches occurred using a “last come, first served” protocol. We also discuss practical findings regarding matching for vulnerable versus overall populations. Results by demographic group revealed disparities—underaged and gender minority groups had lower average chat ratings and higher blocking rates on the site when compared to their majority counterparts, indicating the potential benefits of algorithmically matching them. We found that some protocols, such as a “filter”-based approach that matched vulnerable support seekers only with a counselor of their same demographic, led to improvements for these groups but resulted in lower satisfaction (–12%) among the overall population. However, this trade-off between minority and majority groups was not observed when using “topic” as a matching criterion. Topic-based matching actually outperformed the filter-based protocol among underaged people and led to significant improvements over the status quo among all minority and majority groups—specifically, a 6% average chat rating improvement and a decrease in blocking incidents from 5.86% to 4.26%. ConclusionsAgent-based modeling can reveal significant design considerations in the OMHC context, including trade-offs in various outcome metrics and the potential benefits of algorithmic matching for marginalized communities.

Unsafe hoisting operations have been consistently associated with numerous safety incidents involving tower cranes. Currently, the predominant measures to mitigate these operations center around comprehensive training and education, emphasizing standardized protocols prior to hoisting activities. Despite concerted efforts in this direction, a conspicuous research gap persists in early-warning mechanisms during the construction phase. This paper aims to address this gap by proposing an innovative early-warning methodology, inspired by the principles of digital twin and knowledge graph. We firstly introduce a digital twin framework designed to mirror the real-time operational status of the tower crane. This framework enables the immediate detection of deviations or infractions as they occur. Subsequently, we develop a knowledge graph capable of promptly identifying unsafe hoisting operations by leveraging real-time data obtained from the digital twin. To validate the efficacy of our proposed methodology, we construct a scaled-down replica of a tower crane and establish a tailored digital twin system. The findings of a series of experimental trials prominently underscore the system's capability to generate timely alerts in response to unsafe hoisting operations while maintaining an impressively low rate of false alarms.

Abstract Introduction As proteins that promote immune cell differentiation, chemokines have attracted great interest regarding their role in anti-tumor immune responses within the cancer environment. However, the exact role of CXCL10, a chemokine, in bladder cancer (BLCA) is still not fully elucidated. Method In the present study, we employed bioinformatics approaches to examine the expression pattern, prognostic value, and immune infiltration of CXCL10 in BLCA. Furthermore, we focused on examining the impact of CXCL10 on immune therapy in BLCA. Additionally, we validated the expression of CXCL10 in various BLCA cell lines using PCR techniques. Results We observed an upregulation of CXCL10 in BLCA tissues as well as in different cell lines. Additionally, upregulation of CXCL10 indicates a better prognosis for BLCA patients. ESTIMATE and CIBERSORT algorithms suggest that CXCL10 is closely associated with the immune microenvironment of BLCA. Through multiple immune therapy cohorts, we also identified that CXCL10 has shown promising predictive value for assessing the efficacy of immune therapy in in BLCA. Conclusion Our study indicates that CXCL10 has the potential to serve as a favorable prognostic factor and is strongly associated with immune infiltration in BLCA. Graphical Abstract

Abstract Objective To retrospectively analyze the risk factors for postoperative delirium (POD) after orthopedic surgery in elderly patients and establish an individualized nomogram to predict the risk of POD. Methods The data of 1011 patients who underwent orthopedic surgery from January 2019 to January 2022 were retrospectively analyzed. Univariate and multivariate logistic analyses were used to screen for independent risk factors. Stepwise regression was conducted to screen risk factors to construct a nomogram to predict the risk of POD after orthopedic surgery in elderly individuals, and nomogram validation analyses were performed. Results The logistic regression results showed that age (≥ 75 years old vs.

Background: Since the inception of the term “Biomimetics” in 1991, the concept of utilizing natural solutions or deriving inspiration from nature to address contemporary engineering challenges has gained significant attention within the scientific community. Organisms, in order to thrive in harsh environments, have evolved a wide range of micro/nanostructured surfaces, which serve as a rich source of inspiration for the development of artificial micro/nano-structured surfaces. These natural adaptations provide valuable insights and novel pathways for fabricating such surfaces. Aim: To conclude recent advances in micro/nano-structured surfaces from four aspects: biomimetic micro-structured surfaces of plants and animals, properties and applications of biomimetic surfaces, methods of preparations, and their limitation. Key Scientific Concepts:: Artificial micro/nano-structured surfaces inspired by animals and plants are classified and demonstrated according to their living environment. The performances, principles and preparation techniques of natural superhydrophobic surfaces, slippery liquid-infused porous surfaces (SLIPS), anisotropic surfaces, etc. are described in detail. Moreover, the pros and cons of each preparation measures are compared and the challenges developing large-scale, cost-effective surface microstructure preparation processes are pointed out. In the end, the development trends of artificial micro/nano-structured surface are forecasted.

Abstract Electroencephalography (EEG) microstate analysis is a neuroimaging analytical method that has received considerable attention in recent years and is widely used for analysing EEG signals. EEG is easily influenced by internal and external factors, which can affect the repeatability and stability of EEG microstate analysis. However, there have been few reports and publicly available datasets on the repeatability of EEG microstate analysis. In the current study, a 39-year-old healthy male underwent a total of 60 simultaneous electroencephalography and electrocardiogram measurements over a period of three months. After the EEG recording was completed, magnetic resonance imaging (MRI) was also conducted. To date, this EEG dataset has the highest number of repeated measurements for one individual. The dataset can be used to assess the stability and repeatability of EEG microstates and other analytical methods, to decode resting EEG states among subjects with open eyes, and to explore the stability and repeatability of cortical spatiotemporal dynamics through source analysis with individual MRI.

Enhanced mortality, relapse rates, and increased prevalence of Clostridioides difficile infection (CDI) emphasize the need for better therapies and management approaches. Modulating host immune response to ameliorate CDI-associated immunopathology may provide new advantages to currently inadequate antibiotic therapies. Here, we identified progranulin (PGRN) as an important immune target upregulated in response to CDI. PGRN-deficient mice displayed dramatically higher mortality and aggravated epithelial barrier disruption compared with wild type (WT) mice after CDI despite equivalent levels of bacterial burden or toxin in the large intestine. Mechanistically, PGRN protection was mediated by IL-22 production from CD4+ T helper cells, as demonstrated by a decrease in colonic IL-22-producing CD4+ T helper cells in the intestine of PGRN-deficient mice upon CDI and a boost of IL-22-producing CD4+ T helper cells activated by PGRN ex vivo. Clinical evidence suggests that CDI patients had significantly higher serum levels of PGRN compared with healthy controls, which was significantly and positively correlated with IL-22. Our findings thus indicate a critical role for PGRN-promoted CD4+ T cell IL-22 production in shaping gut immunity and reestablishing the intestinal barrier during CDI. As an alternative to pathogen-targeted therapy, this study may provide a new host-directed therapeutic strategy to attenuate severe, refractory CDI.

ABSTRACT: An attenuated vaccine against the Mycoplasma gallisepticum ts-11 strain has become an effective prevention and control method against MG infection. However, the ts-11 strain is usually difficult to distinguish from the non-ts-11 strain (including field isolates and other vaccine strains (F and 6/85)). Therefore, it is critical to establish a rapid and effective method to distinguish ts-11 strains from non-ts-11 strains. The gene sequences of the ts-11 strain (CP044225.1) and the non-ts-11 strain (including the wild-type (CP006916.3), 6/85 (CP044224.1), and F strains (NC_017503.1) were used to construct a conserved region containing a single point mutation in the potC gene in the ts-11 strain, after which a primer–probe combination method was designed. The primer–probe method was able to accurately and efficiently identify the ts-11 and non-ts-11 strains with minimum detection limits of 2.43 copies/μL and 1.65 copies/μL, respectively. Moreover, it could simultaneously distinguish the ts-11 strain from a non-ts-11 strain, and amplifications of avian influenza virus, infectious bronchitis virus, Newcastle disease virus, fowl adenovirus, infectious laryngotracheitis virus, infectious bursal disease virus, chicken anemia virus, Marek's disease virus, Mycoplasma synoviae, and Ornithobacter rhinotracheale were negative. The detection of clinical samples revealed that the established dual-probe fluorescence quantitative PCR method could be used to screen for mixed and single infections of the ts-11 strain and non-ts-11 strains effectively, with lower variation coefficients for intra- and interbatch repetition. The established cycleave dual-probe fluorescence quantitative PCR method showed good specificity, sensitivity, and repeatability and provides powerful technical support for the rapid and efficient differential diagnosis of the MG ts-11 strain from non-ts-11 strains.

AbstractAs an autoimmune disease of the colon, the incidence of ulcerative colitis (UC) remains high. Carbon dots (CDs), a new type of nanomaterials, display excellent biological activity and are expected to inspire a new treatment for UC. A green method was used to carbonise rhei radix rhizoma (RRR) and extract CDs to study their anti-ulcer activity. The RRR-based carbon dots (RRR-CDs) were characterised by electron microscopy, optical techniques, and other techniques. The results indicated RRR-CDs have abundant chemical groups, excellent solubility and tiny size (1.374 nm–4.533 nm), which may be conducive to the exertion of inherent activity. Using a classic dextran sodium sulphate (DSS)-induced UC mouse model, for the first time, it was demonstrated RRR-CDs have significant anti-ulcerative activity in improving DAI score (from 2.8 to 1.6), colon length (4.15 to 6.08), and histopathology in mice. The underlying mechanisms of anti-ulcerative activity may be related to haemostatic, antioxidant, and anti-inflammatory activities to protect the mucosal barrier. RRR-CDs have symptomatic and potential mechanisms of treatment and are expected to become a candidate drug for the treatment of UC. This not only further expands the basis for the biological activity of CDs, but provides a potential treatment plan for solving thorny diseases in clinical practice.

Underwater sonar is the primary remote sensing and imaging modality within turbid environments with poor visibility. The two-dimensional (2-D) images of a target near the air–sea interface (or resting on a hard seabed), acquired by forward-scan sonar (FSS), are generally corrupted by the ghost and sometimes mirror components, formed by the multipath propagation of transmitted acoustic beams. In the processing of the 2-D FSS views to generate an accurate three-dimensional (3-D) object model, the corrupted regions have to be discarded. The sonar tilt angle and distance from the sea surface are two important parameters for the accurate localization of the ghost and mirror components. We propose a unified optimization technique for improving both the measurements of these two parameters from inexpensive sensors and the accuracy of a 3-D object model using 2-D FSS images at known poses. The solution is obtained by the recursive updating of sonar parameters and 3-D object model. Utilizing the 3-D object model, we can enhance the original images and generate synthetic views for arbitrary sonar poses. We demonstrate the performance of our method in experiments with the synthetic and real images of three targets: two dominantly convex coral rocks and a highly concave toy wood table.

The fabrication of highly efficient yet stable noble-metal-free bifunctional electrocatalysts that can simultaneously catalyse both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) remains challenging. Herein, we employ the heterostructure coupling strategy, showcasing an aerosol-assisted chemical vapour deposition (AACVD) aided synthetic approach for the in-situ growth of cobalt molybdenum sulphide nanocomposites on carbon paper (CoMoS@CP) as a bifunctional electrocatalyst. The AACVD allows the rational incorporation of Co in the Mo–S binary structure, which modulates the morphology of CoMoS@CP, resulting in enhanced HER activity (ŋ10 = 171 mV in acidic and ŋ10 = 177 mV in alkaline conditions). Furthermore, the CoS2 species in the CoMoS@CP ternary structure extends the OER capability, yielding an ŋ100 of 455 mV in 1 M KOH. Lastly, we found that the synergistic effect of the Co–Mo–S interface elevates the bifunctional performance beyond binary counterparts, achieving a low cell voltage (1.70 V at 10 mA cm−2) in overall water splitting test and outstanding catalytic stability (∼90 % performance retention after 50-/30-h continuous operation at 10 and 100 mA cm−2, respectively). This work has opened up a new methodology for the controllable synthesis of self-supported transition metal-based electrocatalysts for applications in overall water splitting.

Abstract Targeting cancer‐specific metabolic processes is a promising therapeutic strategy. Here, this work uses a compound library that directly inhibits metabolic enzymes to screen the potential metabolic targets in lung adenocarcinoma (LUAD). SHIN1, the specific inhibitor of serine hydroxymethyltransferase 1/2 (SHMT1/2), has a highly specific inhibitory effect on LUAD cells, and this effect depends mainly on the overexpression of SHMT2. This work clarifies that mitogen‐activated protein kinase 1 (MAPK1)‐mediated phosphorylation at Ser90 is the key mechanism underlying SHMT2 upregulation in LUAD and that this phosphorylation stabilizes SHMT2 by reducing STIP1 homology and U‐box containing protein 1 (STUB1)‐mediated ubiquitination and degradation. SHMT2‐Ser90 dephosphorylation decreases S‐adenosylmethionine levels in LUAD cells, resulting in reduced N6‐methyladenosine (m6A) levels in global RNAs without affecting total protein or DNA methylation. Methylated RNA immunoprecipitation sequencing (MeRIP‐Seq) and RNA sequencing (RNA‐Seq) analyses further demonstrate that SHMT2‐Ser90 dephosphorylation accelerates the RNA degradation of oncogenic genes by reducing m6A modification, leading to the inhibition of tumorigenesis. Overall, this study elucidates a new regulatory mechanism of SHMT2 during oncogenesis and provides a theoretical basis for targeting SHMT2 as a therapeutic target in LUAD.

Abstract Background To accelerate the clinical translation of tumor‐infiltrating lymphocytes (TILs) biomarkers for guiding chemotherapy de‐escalation in early‐stage triple‐negative breast cancer (TNBC), cost‐effectiveness evidence is essential but has not been investigated. We intend to evaluate the cost‐effectiveness of using TILs to guiding chemotherapy de‐escalation in patients with early‐stage TNBC from the perspective of the Chinese health service system. Methods The hybrid decision‐tree‐Markov model was designed to compare the cost‐effectiveness of cytotoxic chemotherapy guided by whether TILs assay was performed in 50‐year‐old female patients with early‐stage TNBC over a lifetime horizon. In Strategy (1), if TILs testing was performed, patients with TILs values exceeding 30% could be spared from chemotherapy. In Strategy (2), where no TILs testing was performed, all patients were administered chemotherapy following China's clinical practices. Based on the algorithm built by Guyot, the individual patient data were reconstructed from the published Kaplan–Meier curves, and the survival functions were calculated by parametric methods. Cost estimates were valued in Chinese yuan (as per rates in 2022). Results In 50‐year‐old female patients with early‐stage TNBC, Strategy (1), which employs TILs testing to guide cytotoxic chemotherapy yielded an additional 0.47 quality‐adjusted life years (QALYs) and saved 40,976 yuan, with an incremental cost‐effectiveness ratio (ICER) of −87,182.98 yuan per QALY gained compared with Strategy (2). This indicates that compared with Strategy (2), Strategy (1) is the dominant scheme. The results were sensitive to utility parameters, discount rates, and treatment costs after relapse. At a willingness‐to‐pay threshold of 85,700 yuan (based on GDP per capita) per QALY, the probability of TILs being cost‐effective was almost 100%. Conclusions The application of biomarkers (TILs) to guide decisions for chemotherapy de‐escalation is a cost‐effective strategy for early‐stage TNBC patients and deserves to be widely promoted in clinical practice.

Abstract Background Echovirus 30 is prone to cause hand-foot-and-mouth disease in infants and children. However, molecular epidemiologic information on the spread of E30 in southwestern China remains limited. In this study, we determined and analyzed the whole genomic sequences of E30 strains isolated from the stools of patients with hand-foot-and-mouth disease in Yunnan Province, China, in 2019. Methods E30 isolates were obtained from fecal samples of HFMD patients. The whole genomes were sequenced by segmented PCR and analyzed for phylogeny, mutation and recombination. MEGA and DNAStar were used to align the present isolates with the reference strains. The VP1 sequence of the isolates were analyzed for selection pressure using datamonkey server. Results The complete genome sequences of four E30 were obtained from this virus isolation. Significant homologous recombination signals in the P2-3’UTR region were found in all four isolates with other serotypes. Phylogenetic analysis showed that the four E30 isolates belonged to lineage H. Comparison of the VP1 sequences of these four isolates with other E30 reference strains using three selection pressure analysis models FUBAR, FEL, and MEME, revealed a positive selection site at 133rd position. Conclusions This study extends the whole genome sequence of E30 in GenBank, in which mutations and recombinations have driven the evolution of E30 and further improved and enriched the genetic characteristics of E30, providing fundamental data for the prevention and control of diseases caused by E30. Furthermore, we demonstrated the value of continuous and extensive surveillance of enterovirus serotypes other than the major HFMD-causing viruses.

Objectives: We examined the association of nasopharyngeal (NP) pneumococcal co-colonization (>1 pneumococcal serotype) and pneumococcal density in young Peruvian children enrolled in a prospective cohort study. Methods: NP swabs collected monthly from children aged

In this study, indigo carmine (IC)-calcium carbonate lakes with different crystalline forms of calcium carbonate were prepared through co-precipitation methods, and the properties of these lakes and their formation mechanisms were investigated. The results showed that amorphous calcium carbonate (ACC) exhibited the smallest particle size and the largest specific surface area, resulting in the highest adsorption efficiency. Vaterite, calcite, and aragonite followed after ACC in decreasing order of adsorption efficiency. Kinetic analysis and isothermal analysis revealed the occurrence of chemisorption and multilayer adsorption during formation of the lakes. The FTIR and Raman spectra suggested participation of sulfonic acid groups in chemisorption. Appearance of IC significantly altered TGA curves by changing weight loss rate before decomposition of calcium carbonate. EDS analysis revealed the adsorption of IC predominantly happened on the surface of calcium carbonate particles rather than the interior.

This study aimed to elucidate responses of the bacterial structure and diversity of the rhizosphere in flowering broomcorn millet after rehydration following drought stress. In this study, the broomcorn millet varieties ‘Hequ red millet’ (A1) and ‘Yanshu No.10′ (A2), known for their different drought tolerance levels, were selected as experimental materials. The plants were subjected to rehydration after drought stress at the flowering stage, while normal watering (A1CK and A2CK) served as the control. Soil samples were collected at 10 days (A11, A21, A1CK1, and A2CK1) and 20 days (A12, A22, A1CK2, and A2CK2) after rehydration. High-throughput sequencing technology was employed to investigate the variations in bacterial community structure, diversity, and metabolic functions in the rhizosphere of the broomcorn millet at different time points following rehydration. The findings indicated that the operational taxonomic units (OTUs) of bacteria in the rhizosphere of broomcorn millet were notably influenced by the duration of treatment, with a significant decrease in OTUs observed after 20 days of rehydration. However, bacterial Alpha diversity was not significantly impacted by rehydration following drought stress. The bacterial community in the rhizosphere of broomcorn millet was mainly composed of Actinobacteria and Proteobacteria. After rewatering for 10 to 20 days after drought stress, the abundance of Sphingomonas and Aeromicrobium in the rhizosphere soil of the two varieties of broomcorn millet decreased gradually. Compared with Yanshu No.10, the abundance of Pseudarthrobacter in the rhizosphere of Hequ red millet gradually increased. A Beta diversity analysis revealed variations in the dissimilarities of the bacterial community which corresponded to different rehydration durations. The relative abundance of bacterial metabolic functions in the rhizosphere of broomcorn millet was lower after 20 days of rehydration, compared to measurements after 10 days of rehydration. This observation might be attributed to the exchange of materials between broomcorn millet and microorganisms during the initial rehydration stage to repair the effects of drought, as well as to the enrichment of numerous microorganisms to sustain the stability of the community structure. This study helps to comprehend the alterations to the bacterial structure and diversity in the rhizosphere of broomcorn millet following drought stress and rehydration. It sheds light on the growth status of broomcorn millet and its rhizosphere microorganisms under real environmental influences, thereby enhancing research on the drought tolerance mechanisms of broomcorn millet.

In order to clarify the effect of different fertilizers on foxtail millet quality under low nitrogen conditions, we used JGNo.21 and LZGNo.2 as experimental materials and set up five treatments, including non-fertilization, nitrogen, phosphorus, compound, and organic fertilizers, to study the regulation of different fertilizer types on agronomic traits, nutrient fractions, and pasting characteristics of foxtail millet under low nitrogen conditions. Compared with the control, all of the fertilizers improved the agronomic traits of JGNo.21 to a certain extent. Nitrogen and compound fertilizer treatments reduced the starch content of JGNo.21; the starch content was reduced by 0.55% and 0.07% under nitrogen and compound fertilizers treatments. Phosphorus and organic fertilizers increased starch content, and starch content increased by 0.50% and 0.56% under phosphorus and organic fertilizer treatments. The effect of each fertilizer treatment on protein content was completely opposite to that of starch; different fertilizer treatments reduced the fat content of JGNo.21 and increased the fiber content. Among them, nitrogen and phosphorus fertilizers increased the yellow pigment content; the yellow pigment content increased by 1.21% and 2.64% under nitrogen and phosphorus fertilizer treatments. Organic and compound fertilizers reduced the content of yellow pigment; the yellow pigment content was reduced by 3.36% and 2.79% under organic and compound fertilizer treatments. Nitrogen and organic fertilizers increased the fat content of LZGNo.2; the fat content increased by 2.62% and 1.98% under nitrogen, organic fertilizer treatment. Compound and phosphorus fertilizer decreased the fat content; the fat content decreased by 2.16% and 2.90% under compound and phosphorus fertilizer treatment. Different fertilizer treatments reduced the cellulose and yellow pigment content of LZGNo.2. The content of essential, non-essential, and total amino acids of JGNo.21 was increased under compound and nitrogen fertilizer treatments and decreased under organic and phosphorus fertilizer treatments. The content of essential, non-essential, and total amino acids of LZGNo.2 was significantly higher under compound, nitrogen, and organic fertilizer treatments compared with control and significantly decreased under phosphorus fertilizer treatments. Nitrogen and compound fertilizer treatments significantly reduced the values of peak viscosity, trough viscosity, breakdown viscosity, final viscosity, setback viscosity, and pasting time of each index of JGNo.21; phosphorus and organic fertilizer treatments improved the values of each index. In contrast, the pasting viscosity of LZGNo.2 increased under phosphorus fertilizer treatment and decreased under nitrogen fertilizer treatment. Reasonable fertilization can improve the quality of foxtail millet, which provides a scientific theoretical basis for improving the quality of foxtail millet.

Diarrhea of college students (DCS) is a prevalent issue among college students, affecting their daily lives and academic performance. This study aims to explore the potential effect of Bifidobacterium breve BB05 supplements on the DCS. Initially, fifty healthy and fifty diarrheal students were recruited in the observational experiment and allocated into control and diarrhea groups, respectively. Subsequently, one hundred diarrheal students were newly recruited in the intervention experiment and randomly allocated into placebo and probiotic groups, both treated for 2 weeks. Questionnaires (BSS, HAMA-14, and HDRS-17) were performed to assess the students’ diarrheal states and mental health at baseline and post-treatment. Fecal samples underwent 16S rRNA sequencing and Enzyme-Linked Immunosorbent Assay to evaluate gut microbiota and fecal metabolite alternations. Results indicated that B. breve BB05 supplementation significantly enriched (p < 0.05) the reduced gut microbial diversity caused by diarrhea. Diarrhea resulted in notable alterations in gut microbiota composition, as exhibited by elevated Collinsella and Streptococcus, alongside substantially decreased Bifidobacterium, Bacteroides, and Prevotella, while B. breve BB05 supplementation partially restored the compromised gut microbiota at both the phylum and genus levels, particularly by increasing Bifidobacterium and Roseburia (p < 0.05). Importantly, questionnaire results suggested that B. breve BB05 administration achieved superior efficacy in relieving diarrhea symptoms and the associated anxiety and depression in college students. An increased fecal concentration of 5-hydroxytryptamine (5-HT) was also observed in the probiotic group, while Acetylcholine (ACH), Epinephrine (EPI), and Noradrenaline/Norepinephrine (NANE) reduced, revealing the potential of B. breve BB05 in alleviating anxiety and depression via modulating the microbiota–gut–brain axis. Furthermore, correlation analysis suggested that the altered microbiota and fecal neurotransmitters were closely associated with the mental symptoms. These results endorse B. breve BB05 intervention as a promising and innovative approach to alleviate both diarrhea and mental health conditions among college students.

For mobile robots, the high-precision integrated calibration and structural robustness of multi-sensor systems are important prerequisites for ensuring healthy operations in the later stage. Currently, there is no well-established validation method for the calibration accuracy and structural robustness of multi-sensor systems, especially for dynamic traveling situations. This paper presents a novel validation method for the calibration accuracy and structural robustness of a multi-sensor mobile robot. The method employs a ground–object–air cooperation mechanism, termed the “ground surface simulation field (GSSF)—mobile robot -photoelectric transmitter station (PTS)”. Firstly, a static high-precision GSSF is established with the true north datum as a unified reference. Secondly, a rotatable synchronous tracking system (PTS) is assembled to conduct real-time pose measurements for a mobile vehicle. The relationship between each sensor and the vehicle body is utilized to measure the dynamic pose of each sensor. Finally, the calibration accuracy and structural robustness of the sensors are dynamically evaluated. In this context, epipolar line alignment is employed to assess the accuracy of the evaluation of relative orientation calibration of binocular cameras. Point cloud projection and superposition are utilized to realize the evaluation of absolute calibration accuracy and structural robustness of individual sensors, including the navigation camera (Navcam), hazard avoidance camera (Hazcam), multispectral camera, time-of-flight depth camera (TOF), and light detection and ranging (LiDAR), with respect to the vehicle body. The experimental results demonstrate that the proposed method offers a reliable means of dynamic validation for the testing phase of a mobile robot.

Function approximation has gained significant attention in reinforcement learning research as it effectively addresses problems with large-scale, continuous state, and action space.Although the function approximation algorithm based on gradient descent method is one of the most widely used methods in reinforcement learning, it requires careful tuning of the step size parameter as an inappropriate value can lead to slow convergence, unstable convergence, or even divergence.To address these issues, an improvement was made around the temporal-difference (TD) algorithm based on function approximation.The weight update method was enhanced using both the least squares method and gradient descent, resulting in the proposed weights gradient descent (WGD) method.The least squares were used to calculate the weights, combining the ideas of TD and gradient descent to find the error between the weights.And this error was used to directly update the weights.By this method, the weights were updated in a new manner, effectively reducing the consumption of computing resources by the algorithm enhancing other gradient descent-based function approximation algorithms.The WGD method is widely applicable in various gradient descent-based reinforcement learning algorithms.The results show that WGD method can adjust parameters within a wider space, effectively reducing the possibility of algorithm divergence.Additionally, it achieves better performance while improving the convergence speed of the algorithm.

Abstract Numerical simulations have revolutionized material design. However, although simulations excel at mapping an input material to its output property, their direct application to inverse design has traditionally been limited by their high computing cost and lack of differentiability. Here, taking the example of the inverse design of a porous matrix featuring targeted sorption isotherm, we introduce a computational inverse design framework that addresses these challenges, by programming differentiable simulation on TensorFlow platform that leverages automated end-to-end differentiation. Thanks to its differentiability, the simulation is used to directly train a deep generative model, which outputs an optimal porous matrix based on an arbitrary input sorption isotherm curve. Importantly, this inverse design pipeline leverages the power of tensor processing units (TPU)—an emerging family of dedicated chips, which, although they are specialized in deep learning, are flexible enough for intensive scientific simulations. This approach holds promise to accelerate inverse materials design.

IntroductionIn the context of generative AI intervention in news production, this study primarily focuses on the impact of AI-generated content (AIGC) labeling cues on users’ perceptions of automated news based on nudge theory.MethodsA 2 (authorship disclosure nudge cues: with vs. without AIGC label) × 2 (automated news type: descriptive vs. evaluative news) within-subject experiment was carried out. Thirty-two participants were recruited to read automated news, evaluate the perceived content trustworthiness, and record with an EEG device.ResultsThe results demonstrated that disclosure of AIGC labeling significantly reduced the trustworthiness perception of both fact-based descriptive and opinion-based evaluative news. In EEG, the delta PSD, theta PSD, alpha PSD, and beta PSD with disclosure of AIGC labeling were significantly higher than those without AIGC labeling. Meanwhile, in descriptive news conditions, TAR with AIGC labeling was higher than without AIGC labeling.DiscussionThese results suggested that AIGC labeling significantly improves the degree of attention concentration in reading and deepens the degree of cognitive processing. Users are nudged by AIGC labeling to shift their limited attention and cognitive resources to re-evaluate the information quality to obtain more prudent judgment results. This helps to supplement the theoretical perspective on transparent disclosure nudging in the Internet content governance research field, and it can offer practical guidance to use content labeling to regulate the media industry landscape in the face of AI’s pervasive presence.

AbstractTo detect the value of serum interleukin-17 (IL-17), tumour necrosis factor-α (TNF-α), and Dickkopf-1 (DKK-1) in rheumatoid arthritis (RA) at different disease stages. 141 RA patients were randomly obtained and diagnosed in a large tertiary first-class hospital in Jiangxi Province from November 2021 to January 2022. RA was divided into 38 low activity and remission phase (low remission patients), 72 moderate activity patients, 41 high activity patients, according to the disease activity score 28 (DAS28) of RA and 70 healthy controls. IL-17 and TNF-α in serum detected by flow cytometry; DKK-1by ELISA; rheumatoid factor (RF) and C-reactive protein (CRP) by rate scattering turbidimetry; erythrocyte sedimentation rate (ESR) by Widmanstat method; anti-cyclic citrullinated polypeptide antibody (Anti-CCP) by chemiluminescence. The changes among the groups were statistically analysed and evaluated their diagnostic value. ①Anti-CCP, CRP, and ESR levels in the moderate-to-high activity group were higher than controls, while IL-17, TNF-α, and DKK-1levels higher than low remission group, moderate activity group and controls (p

Powdery mildew severely affects several important crops and cash plants. Disruption of mildew resistance locus O (MLO) genes elevates resistance against powdery mildew in several plants. However, whether rubber tree (Heveae brasiliensis) MLO proteins are linked to susceptibility remains unknown, owing to technical limitations in the genetic manipulation of this woody plant. A previous study showed that the H. brasiliensis MLO-like protein HbMLO12 demonstrates high amino acid sequence similarity with the known Arabidopsis MLO protein AtMLO12. In this study, we investigated whether HbMLO12 regulates susceptibility to powdery mildew. H. brasiliensis leaves take up exogenously synthesized double-stranded RNAs (dsRNAs), and foliar application of dsRNA homologous to HbMLO12 gene specifically induces HbMLO12 silencing in H. brasiliensis leaf tissues. Notably, HbMLO12 silencing inhibited fungal infection and elevated the immune response during interaction with the rubber tree powdery mildew fungus. Furthermore, the heterologous expression of HbMLO12 suppressed bacterial flg22– and fungal chitin–induced immune responses and enhanced bacterial infection in Arabidopsis. Our study provides evidence that HbMLO12 contributes to susceptibility to powdery mildew. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

A novel, highly efficient terahertz fully polarized transmission line is designed by two-dimensional tellurium photonic crystals consisting of square lattice rod arrays with a complete photonic bandgap. The TE and TM photonic bandgaps of the tellurium photonic crystals, which are computed by plane wave expansion, happen to coincide, and the complete photonic bandgap covers from 2.894 to 3.025 THz. The function of the designed waveguide is simulated by the finite element method, and the transmission characteristics are optimized by accurately adjusting its structural parameters. The transmission efficiency of the waveguide for TE mode achieves a peak value of −0.34 dB at a central frequency of 2.950 THz and keeps above −3 dB from 2.82 THz to 3.02 THz, obtaining a broad relative bandwidth of about 6.84 percent. The operating bandwidth of the tellurium photonic crystals’ waveguide for TM mode is narrower than that of TE mode, whose relative bandwidth is about 4.39 percent or around 2.936 THz above −5 dB. The designed terahertz photonic crystals’ waveguide can transmit both TE and TM waves, and not only can it be used as a high-efficiency transmission line, but it also provides a promising approach for implementing fully polarized THz devices for future 6G communication systems.

Cotton Verticillium wilt is mainly caused by the fungus Verticillium dahliae, which threatens the production of cotton. Its pathogen can survive in the soil for several years in the form of microsclerotia, making it a destructive soil-borne disease. The accurate, sensitive, and rapid detection of V. dahliae from complex soil samples is of great significance for the early warning and management of cotton Verticillium wilt. In this study, we combined the loop-mediated isothermal amplification (LAMP) with CRISPR/Cas12a technology to develop an accurate, sensitive, and rapid detection method for V. dahliae. Initially, LAMP primers and CRISPR RNA (crRNA) were designed based on a specific DNA sequence of V. dahliae, which was validated using several closely related Verticillium spp. The lower detection limit of the LAMP-CRISPR/Cas12a combined with the fluorescent visualization detection system is approximately ~10 fg/μL genomic DNA per reaction. When combined with crude DNA-extraction methods, it is possible to detect as few as two microsclerotia per gram of soil, with the total detection process taking less than 90 min. Furthermore, to improve the method’s user and field friendliness, the field detection results were visualized using lateral flow strips (LFS). The LAMP-CRISPR/Cas12a-LFS system has a lower detection limit of ~1 fg/μL genomic DNA of the V. dahliae, and when combined with the field crude DNA-extraction method, it can detect as few as six microsclerotia per gram of soil, with the total detection process taking less than 2 h. In summary, this study expands the application of LAMP-CRISPR/Cas12a nucleic acid detection in V. dahliae and will contribute to the development of field-deployable diagnostic productions.

In the contemporary tramp shipping industry, route optimization and scheduling are directly linked to enhancements in operations, economics, and the environment, making them key factors for the effective management of maritime transportation. To enhance effective ship-to-cargo matching and the refinement of maritime transportation itineraries, this paper introduces a time efficiency and carbon dioxide emission multi-objective optimization algorithm named ETE-SRSP (efficiency–time–emission multi-optimization algorithm). ETE-SRSP incorporates several factors, including the initial positions of ships, time windows for loading and unloading operations, and varying sailing speeds. Within the ETE-SRSP framework, pioneering an approach that integrates ballast and laden sailing velocities as decisional parameters, it employs a multi-objective optimization technique to investigate the intricate interplay between temporal efficiency and carbon dioxide emissions. Additionally, the model’s proficiency in mitigating emissions and managing costs is clearly demonstrated through the optimization of these objectives, thereby offering a robust framework for decision support. The experimental results show that the optimal sailing speeds derived from the ETE-SRSP, under typical time-weight scenarios, can achieve an optimal balance between emission reduction and cost control. In summary, this study underscores the optimization strategy’s potential to effectively address the maritime sector’s need for economic growth and ecological conservation, showcasing its practical value in the industry.

Infrared (IR) imaging-based detection systems are of vital significance in the domains of early warning and security, necessitating a high level of precision and efficiency in infrared small moving target detection. IR targets often appear dim and small relative to the background and are easily buried by noise and difficult to detect. A novel high-speed spatial–temporal saliency model (HS-STSM) based on a guided filter (GF) is proposed, which innovatively introduces GF into IR target detection to extract the local anisotropy saliency in the spatial domain, and substantially suppresses the background region as well as the bright clutter false alarms present in the background. Moreover, the proposed model extracts the motion saliency of the target in the temporal domain through vectorization of IR image sequences. Additionally, the proposed model significantly improves the detection efficiency through a vectorized filtering process and effectively suppresses edge components in the background by integrating a prior weight. Experiments conducted on five real infrared image sequences demonstrate the superior performance of the model compared to existing algorithms in terms of the detection rate, noise suppression, real-time processing, and robustness to the background.

Materials discovery lays the foundation for many technological advancements. The prediction and discovery of new materials are not simple tasks. Here, we outline some basic principles of solid-state chemistry, which might help to advance both, and discuss pitfalls and challenges in materials discovery. Using the recent work of Szymanski et al. [Nature 624, 86 (2023)], which reported the autonomous discovery of 43 novel materials, as an example, we discuss problems that can arise in unsupervised materials discovery and hope that by addressing these, autonomous materials discovery can be brought closer to reality. We discuss all 43 synthetic products and point out four common shortfalls in the analysis. These errors unfortunately lead to the conclusion that no new materials have been discovered in that work. We conclude that there are two important points of improvement that require future work from the community, as follows. (i) Automated Rietveld analysis of powder x-ray diffraction data is not yet reliable. Future improvement of such, and the development of a reliable artificial-intelligence-based tool for Rietveld fitting, would be very helpful, not only for autonomous materials discovery but also for the community in general. (ii) We find that disorder in materials is often neglected in predictions. The predicted compounds investigated herein have all their elemental components located on distinct crystallographic positions but in reality, elements can share crystallographic sites, resulting in higher-symmetry space groups and—very often—known alloys or solid solutions. This error might be related to the difficulty of modeling disorder in a computationally economical way and needs to be addressed both by computational and experimental material scientists. We find that two thirds of the claimed successful materials in Szymanski et al. are likely to be known compositionally disordered versions of the predicted ordered compounds. We highlight important issues in materials discovery, computational chemistry, and autonomous interpretation of x-ray diffraction. We discuss concepts of materials discovery from an experimentalist point of view, which we hope will be helpful for the community to further advance this important new aspect of our field.

This study prepared a novel β-carotene colorant lake using calcium carbonate (CaCO3) and investigated the lake formation process and its basic characteristics. Kinetic adsorption analysis confirmed that medium pH (9.3) and medium temperature (40 °C) were more suitable for lake preparation, while desorption occurred, possibly due to crystalline transformation of CaCO3. The isothermal analysis and model fitting results suggested that the β-carotene and CaCO3 particles combined via a monolayer adsorption process driven by physical force. Electrostatic attraction likely participated in the process due to the net negative surface charges of β-carotene dispersion and positively charged groups on the CaCO3 particle surfaces. Ethanol, ultrasonic treatment, and drying method significantly influenced the immobilization efficiency (IE) of β-carotene in the lake and light stability of the lake, without affecting its crystal form. The thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) curves confirmed absorption of β-carotene onto CaCO3. Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) analyses indicated no obvious chemical bonds between β-carotene and CaCO3. Energy-dispersive spectroscopy (EDS) confirmed the presence of β-carotene on surfaces but not in the interior of the CaCO3 particles. The adsorption of β-carotene by calcium carbonate was further confirmed to be a physical adsorption on surface.

Having emerged as strategic focal points in industrial transformation and technological innovation, intelligent machine tools are pivotal in the field of intelligent manufacturing. Accurately forecasting emerging technologies within this domain is crucial for guiding intelligent manufacturing’s evolution and fostering rapid innovation. However, prevailing research methodologies exhibit limitations, often concentrating on popular topics at the expense of lesser-known yet significant areas, thereby impacting the accurate identification of research priorities. The complex, systemic, and interdisciplinary nature of intelligent machine tool technology challenges traditional research approaches, particularly in assessing technological maturity and intricate interactions. To overcome these challenges, we propose a novel framework that leverages technological communities for a comprehensive analysis. This approach clusters data into specific topics which are reflective of the technology system, facilitating detailed investigations within each area. By refining community analysis methods and integrating structural and interactive community features, our framework significantly improves the precision of emerging technology predictions. Our research not only validates the framework but also projects key emerging technologies in intelligent machine tools, offering valuable insights for business leaders and scholars alike.

Water-based coatings are gradually replacing traditional oil-based coatings for environmentally friendly applications, which creates a new paradigm in corrosion control of metallic components. In this work, water-based ZrO2–SiO2 sol-gel coatings were prepared for corrosion protection of carbon steel. The effects of the sol-gel ZrO2 to SiO2 ratio, coating thickness, corrosion inhibitor content and surface hydrophobicity on the coating physicochemical and anti-corrosion properties were investigated. The results showed that, compared to the pure silica coating, coating with 1/9 wt% ZrO2 in SiO2 matrix and coating thickness of 25 μm provided about 7 times higher corrosion resistance (impedance modulus 1.38 × 108 Ω cm2). A smart-releasing corrosion inhibitor containing Ce3+ ions (0.91 wt%) loaded into the layered structure of bentonite showed ability to delay the corrosion of substrate by 9 orders of magnitude by trapping Cl− ions from the environment and releasing Ce3+ ions at the cracked substrate surface. By applying a hydrophobic top layer, the water contact angle increased from 89° to 115°, which further increased the impedance modulus of the coating from 2.42 × 109 to 3.60 × 109 Ω cm2. The optimized coating passed salt spray standard corrosion test for 720 h (on scribed coating) due to the cathodic protection by corrosion inhibitor and shielding effects of a top hydrophobic layer. This work provides an enhanced strategy of dual-functional anti-corrosion coatings with surface water repellency and internal smart-releasing corrosion inhibitor for steel against environmental corrosion and damages with efficient self-healing functionality.

Summary: The dysregulation of glutamine metabolism provides survival advantages for tumors by supplementing tricarboxylic acid cycle. Glutamate dehydrogenase 1 (GLUD1) is one of the key enzymes in glutamine catabolism. Here, we found that enhanced protein stability was the key factor for the upregulation of GLUD1 in lung adenocarcinoma. We discovered that GLUD1 showed a high protein expression in lung adenocarcinoma cells or tissues. We elucidated that STIP1 homology and U-box-containing protein 1 (STUB1) was the key E3 ligase responsible for ubiquitin-mediated proteasomal degradation of GLUD1. We further showed that lysine 503 (K503) was the main ubiquitination site of GLUD1, inhibiting the ubiquitination at this site promoted the proliferation and tumor growth of lung adenocarcinoma cells. Taken together, this study clarifies the molecular mechanism of GLUD1 in maintaining protein homeostasis in lung adenocarcinoma, which provides a theoretical basis for the development of anti-cancer drugs targeting GLUD1.

Coxsackievirus B1 (CVB1) is one of the significant pathogens causing viral myocarditis, hand, foot, and mouth disease (HFMD), and aseptic meningitis, and it has been associated with type 1 diabetes (T1DM). No effective antiviral drugs against CVB1 infection or preventive vaccines are available. Due to the success of two inactivated vaccines against enterovirus 71 and poliovirus, an inactivated Vero cell-based CVB1 vaccine could be developed. In this study, we isolated a high-growth CVB1 virus strain KM7 in Vero cells and developed a Vero-adapted vaccine candidate strain KM7-X29 via three rounds of plaque purification and serial passages. The KM7-X29 strain was grouped into the GII sub-genotype, which belonged to the Chinese epidemic strain and grew to a titer of more than 107 CCID50/ml in Vero cells. The inactivated CVB1 vaccine produced by the KM7-X29 strain induced an effective neutralizing antibody response in BALB/c mice, and maternal antibodies were able to provide a 100% protective effect against lethal challenges with a CVB1 strain in suckling BALB/c mice. Thus, the KM7-X29 strain might be used as a new candidate coxsackievirus B1 vaccine strain. The neonatal murine model of CVB1 infection will contribute to the development of the CVB1 vaccine.

Introduction: Numerous studies have demonstrated that the stems of D. officinale have the effect of lowering blood glucose, but the leaves of D. officinale have seldom been investigated. In this study, we mainly studied the hypoglycemic effect and mechanism of D. officinale leaves.Methods: Initially in vivo, male C57BL/6 mice were administered either standard feed (10 kcal% fat) or high-fat feed (60 kcal% fat) along with either normal drinking water or drinking water containing 5 g/L water extract of D. officinale leaves (EDL) for 16 weeks, and changes in body weight, food intake, blood glucose, etc., were monitored weekly. Next in vitro, C2C12 myofiber precursor cells which were induced to differentiate into myofibroblasts and cultured with EDL to detect the expression of insulin signaling pathway related proteins. HEPA cells were also cultured with EDL to detect the expression of hepatic gluconeogenesis or hepatic glycogen synthesis related proteins. Eventually after separating the components from EDL by ethanol and 3 kDa ultrafiltration centrifuge tube, we conducted animal experiments using the ethanol-soluble fraction of EDL (ESFE), ethanol-insoluble fraction of EDL (EIFE), ESFE with a molecular weight of >3 kDa (>3 kDa ESFE), and ESFE with a molecular weight of 3 kDa ESFE displayed the effect of lowering blood glucose. In summary, the effect of EDL in lowering blood glucose may bethanole achieved by activating the insulin signaling pathway to increase insulin sensitivity, and the main functional substance was contained within the >3 kDa ESFE.Discussion: The findings of this study represent a reference point for further exploration of the hypoglycemic effects of D. officinale leaves and may assist in both the identification of new molecular mechanisms to improve insulin sensitivity and the isolation of monomeric substances that lower blood glucose. Furthermore, the obtained results may provide a theoretical basis for the development of hypoglycemic drugs with D. officinale leaves as the main component.

The flowering stage is a critical period for water sensitivity and quality formation of broomcorn millets. However, the effects and mechanisms of drought stress on the quality formation of broomcorn millets are not clear. We used the drought-resistant variety Hequ red millet (H) and the drought-sensitive variety Yanshu No. 10 (Y) were used as materials for drought stress treatment during the flowering stage, metabolomics and physiological methods were used to study the differences in protein, starch, amino acids, medium and medium-long chain fatty acids, and their response characteristics to drought in broomcorn millet. The results showed that different genotypes of broomcorn millets exhibited different response mechanisms in the face of drought stress. In Hequ red millet, drought stress significantly increased the contents of amylopectin (2.57%), pyridoxine (31.89%), and anthocyanin, and significantly decreased the contents of water-soluble protein (5.82%), glutelin (10.07%), thiamine (14.95%) and nicotinamide (23.01%). In Yanshu No. 10, drought significantly decreased amylose by 6.05%, and significantly increased riboflavin and nicotinamide contents by 21.11% and 32.59%. Correlation analysis showed that total starch and amylose were highly significantly positively correlated with methyl palmitate; negatively correlated with amylopectin, vitamins, proteins, free amino acids, and medium-long chain fatty acids; and amylopectin was significantly positively correlated with water-soluble protein, riboflavin, and pyridoxine. Water-soluble protein and glutelin were significantly positively correlated with most free amino acids, medium-long chain fatty acids, and nicotinamide. Thiamine showed significant positive correlation with nicotinamide and significant negative correlation with pyridoxine. Riboflavin was significantly positively correlated with nicotinamide, pyridoxine, and water-soluble protein, and pyridoxine was significantly positively correlated with water-soluble protein. Hequ red millet transforms into amylopectin by consuming water-soluble protein and glutelin, and improves drought resistance by accumulating pyridoxine, and changes its physicochemical properties by decreasing the content of amylose and protein and elevating the content of amylopectin. Yanshu No. 10 resisted drought by catabolizing lipids to produce fatty acids and by consuming amylose for conversion into other metabolites. The present study helps to understand the response of the nutritional quality of millets to drought stress at the flowering stage and provides a theoretical basis for the selection and breeding of superior varieties of millets and drought resistance research.

BackgroundAnoikis is a programmed cell death process that was proven to be associated with cancer. Uroepithelial carcinoma of the bladder (BLCA) is a malignant disease of the urinary tract and has a strong metastatic potential. To determine whether anoikis-associated genes can predict the prognosis of BLCA accurately, we evaluated the prognostic value of anoikis-associated genes in BLCA and constructed the best model to predict prognosis.MethodThe BLCA transcriptome data were downloaded from TCGA and GEO databases, and genes with differential expression were selected and then clustered using non-negative matrix factorization (NMF). The genes with the most correlation with anoikis were screened and identified using univariate Cox regression, lasso regression, and multivariate Cox regression. The GEO dataset was used for external validation. Nomograms were created based on risk characteristics in combination with clinical variants and the performance of the model was validated with receiver operating characteristic (ROC) curves. The immunotherapeutic significance of this risk score was assessed using the immune phenomenon score (IPS). IC50 values of predictive chemotherapeutic agents were calculated. Finally, we used RT-qPCR to determine the mRNA expression of four genes, CALR, FASN, CASP6, and RAD9A.ResultWe screened 406 tumor samples and 19 normal tissue samples from the TCGA database. Based on anoikis-associated genes, we classified patients into two subtypes (C1 and C2) using NMF method. Subsequently, nine core genes were screened by multiple methods after analysis, which were used to construct risk profiles. The design of nomograms based on risk profiles and clinical variables, ROC, and calibration curves confirmed that the model could well have the ability to predict the survival of BLCA patients at 1, 3, and 5 years. By predicting the IC50 values of chemotherapeutic drugs, it was learned that the high-risk group (HRG) was more susceptible to paclitaxel, gemcitabine, and cisplatin, and the low-risk group (LRG) was more susceptible to veriparib and afatinib.ConclusionIn summary, the risk score of anoikis-associated genes can be applied as a predictor to predict the prognosis of BLCA in clinical practice.