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Abstract In the field of spinal pathology, sagittal balance of the spine is usually judged by the spatial structure and morphology of pelvis, which can be represented by pelvic parameters. Pelvic parameters, including pelvic incidence, pelvic tilt and sacral slope, are therefore essential for the diagnosis and treatment of spinal disorders, however, it is a time-consuming and laborious procedure to measure these parameters by traditional methods. In this paper, an automatic measurement framework for pelvic CT images was proposed to calculate three-dimensional (3D) pelvic parameters with the support of deep learning technology. Pelvic images were first preprocessed, and 3D reconstruction was then performed to obtain 3D pelvic model by the Visualization Toolkit. DRINet was trained to segment the femoral head region in the pelvic images, and 3D sphere fitting was performed to locate the femoral heads. In addition, VGG16 was adopted to recognize images containing superior sacral endplate, and the plane growth algorithm was used to fit the plane so that the midpoint and normal vector of the superior sacral endplate could be obtained. Finally, 3D pelvic parameters were automatically calculated, and compared with manual measurements for 15 patients. The proposed framework automatically generated 3D pelvic models, and calculated two-dimensional (2D) and 3D pelvic parameters from continuous CT images. Experiments demonstrated that the framework can greatly speed up the calculation of pelvic parameters, and these parameters are accurate when compared with the manual measurements. In conclusion, the proposed framework demonstrates good performance on automatic pelvimetry measurement by incorporating deep learning technology, and can well replace the traditional methods for pelvic parameter measurement.

PD1/PD-L1 checkpoint inhibitors are at the forefront of cancer immunotherapies. However, the overall response rate remains only 10–30%. Even among initial responders, drug resistance often occurs, which can lead to prolonged use of a futile therapy in the race with the fatal disease. It would be ideal to closely monitor key indicators of patients’ immune responsiveness, such as circulating PD-L1 levels. Traditional PD-L1 detection methods, such as ELISA, are limited in sensitivity and rely on core lab facilities, preventing their use for the regular monitoring. Electrochemical sensors exist as an attractive candidate for point-of-care tool, yet, streamlining multiple processes in a single platform remains a challenge. To overcome this challenge, this work integrated electrochemical sensor arrays into a digital microfluidic device to combine their distinct merits, so that soluble PD-L1 (sPD-L1) molecules can be rapidly detected in a programmed and automated manner. This new platform featured microscale electrochemical sensor arrays modified with electrically conductive 3D matrix, and can detect as low as 1 pg/mL sPD-L1 with high specificity. The sensors also have desired repeatability and can obtain reproducible results on different days. To demonstrate the functionality of the device to process more complex biofluids, we used the device to detect sPD-L1 molecules secreted by human breast cancer cell line in culture media directly and observed 2X increase in signal compared with control experiment. This novel platform holds promise for the close monitoring of sPD-L1 level in human physiological fluids to evaluate the efficacy of PD-1/PD-L1 immunotherapy.

In the context of the in-depth advancement of the power system reform and the increasingly stringent supervision of state-owned assets and state-owned enterprises, it is urgent to clarify the balance between investment demand and investment capacity of the power grid. First, the investment capacity and investment demand estimation models are established respectively, and then a dynamic balance optimization model between investment capacity and investment demand is established. By adjusting the range of adjustable indicators of the investment ability and demand calculation model, the objective is set to be the smallest difference between the investment ability and the investment need, the Quantum Genetic Algorithm is used to solve the problem. And consider future development scenarios to achieve a dynamic balance between investment ability and the investment need. Through the analysis of calculation examples, it is known that the investment capacity of a certain place is 630 million yuan, and the investment demand is 661 million yuan. Combined with the development of related factors affecting the investment in the future, when the relevant factors are at a certain value, the two reach a balance, and the investment scale after the balance is 649 million yuan, which verifies the feasibility of investment optimization of the investment scale, so as to support the investment decision of power grid.

Due to various factors, there is still a lack of effective neuroprotective agents for ischemic stroke in clinical practice. Neuroinflammation and neuronal apoptosis mediated by endoplasmic reticulum stress are some of the important pathological mechanisms in ischemic stroke. Linarin has been reported to have anti-inflammation, antioxidant, and anti-apoptotic effects in myocardial ischemia, osteoarthritis, and kidney disease. Whether it exerts neuroprotective functions in ischemic stroke has not been investigated. The results showed that linarin could reduce the infarct volume in cerebral ischemia animal models, improve the neurological function scores and suppress the expression of inflammatory factors mediating the NF-κB. Meanwhile, it could protect the neurons from OGD/R-induced-apoptosis, which was related to the PERK-eIF2α pathway. Our results suggested linarin could inhibit neuronal inflammation and apoptosis induced by endoplasmic reticulum stress. Furthermore, the neuroprotective effect of linarin may be related to the inhibition of AKR1B1. Our study offers new insight into protecting against ischemia-reperfusion injury by linarin treatment in stroke.

Summary: Stop codon readthrough (SCR) has important biological implications but remains largely uncharacterized. Here, we identify 1,009 SCR events in plants using a proteogenomic strategy. Plant SCR candidates tend to have shorter transcript lengths and fewer exons and splice variants than non-SCR transcripts. Mass spectrometry evidence shows that stop codons involved in SCR events can be recoded as 20 standard amino acids, some of which are also supported by suppressor tRNA analysis. We also observe multiple functional signals in 34 maize extended proteins and characterize the structural and subcellular localization changes in the extended protein of basic transcription factor 3. Furthermore, the SCR events exhibit non-conserved signature, and the extensions likely undergo protein-coding selection. Overall, our study not only characterizes that SCR events are commonly present in plants but also identifies the recoding plasticity of stop codons, which provides important insights into the flexibility of genetic decoding.

Digital rural construction is a key strategic direction to promote China's rural revitalization and alleviate global climate problems. In order to put forward feasible suggestions for the subsequent development and ensure the smooth development of digital village construction, how to reflect the development level of the digital village through scientific and reasonable comprehensive evaluation has become an urgent problem to be solved. This paper establishes a comprehensive evaluation index system through the Delphi method and principal component analysis method, then assigns weights to the evaluation indicators based on the improved CRITIC-G1 method, and then grades the development level of digital villages according to the extension matter element method. Finally, taking Jiangxi Province in China as an example, the overall development level of digital villages in Jiangxi Province is evaluated from the provincial level according to the proposed method. And put forward the corresponding countermeasures and suggestions. Results: Firstly, the development level of digital villages in Jiangxi Province is good, and there is a trend of excellent development level. Secondly, from different aspects of digital rural development, the digitalization of infrastructure, services, economy, and green production in Jiangxi Province is at a good level, and the digitalization of life has reached an excellent level. Thirdly, from the perspective of development trends, the digitization of infrastructure has a progressive trend towards an excellent level of development, while the digitization of services, economy and green production has signs of development regression. According to the analysis results, the relevant countermeasures and suggestions are put forward from four aspects: talent, capital, governance system and development planning. Other regions can evaluate the development level of the digital village according to the evaluation model proposed in this paper so as to analyze the existing problems and put forward targeted solutions to promote the construction of the digital village.

ObjectivesThe prevention of cognitive impairment in the elderly is one of the public health priority areas. However, the relationship between closed-eye unipedal standing and cognitive impairment remains unclear.MethodsThis study was conducted on a group of elderly individuals from a community, using a prospective cohort study design. Participants were monitored for 7 years and were diagnosed with new-onset cognitive impairment. Logistic regression models and restricted cubic spline (RCS) were used to investigate the relationship between closed-eye unipedal standing and cognitive impairment. Stratified analysis by baseline characteristics were also performed.ResultsAt baseline, 1,652 people aged 65 years or older were enrolled. Ultimately, 880 participants completed the follow-up and 155 (17.61%) of them satisfied the diagnostic criteria for cognitive impairment at follow-up. Compared to the closed-eye unipedal standing low group as the reference, the middle (OR = 0.601, 95% CI: 0.396–0.911) and high (OR = 0.508, 95% CI: 0.329–0.785) groups had significantly lower cognitive impairment risks. RCS analysis indicated a linear relationship (Pnon − linear = 0.177), with a reduced risk of developing cognitive impairment when the duration of closed-eye unipedal standing was exceeded ~2.920 s. Stratified analysis showed that for female, aged 70 years or younger, with 3 or more years of education, without lack of exercise and without falls within 1 year subgroup, the elderly in the high group of closed-eye unipedal standing had significantly reduced cognitive impairment risks.ConclusionAmong the elderly population, closed-eye unipedal standing duration was linearly and negatively associated with the cognitive impairment risk. The closed-eye unipedal standing duration might be a predictive index for cognitive impairment in the elderly.

ObjectivesIn China influenza remains a low activity for continuous 3 years due to COVID-19 controls. We here sought to study the clinical characteristics and risk factors of the influenza infection among children after the mandatory COVID-19 restrictions were lifted.MethodsWe included 1,006 pediatric patients with influenza A virus (IAV) infection, enrolled in one tertiary hospital in Zhenjiang, Jiangsu Province, China, during February to April 2023. Patients were divided into the outpatient (n = 798) and inpatient (n = 208) groups, and their baseline characteristics were compared between two groups to conclude the risk factors for pediatric hospitalization. Separately, pediatric inpatients (n = 208) were further divided into the pneumonia and non-pneumonia groups with comparison of their clinical characteristics, including their laboratory test results and representative radiological features, to derive the key determinants for pneumonia development after hospitalization.ResultsCompared to outpatients, IAV-infected pediatric inpatients exhibited younger age, higher female: male ratio, more co-infection of influenza B virus (IBV) and hematological abnormality. Multivariate regression analysis determined the independent risk factors of hospitalization to be the clinical symptom of abdominal pain (OR = 2.63, [95% CI, 1.05–6.57], p = 0.039), co-infection of IBV (OR = 44.33, [95% CI, 25.10–78.30], p = 0.001), elevated levels of lymphocytes (OR = 2.24, [95% CI,1.65–3.05], p = 0.001) and c-reactive proteins (CRPs) (OR = 1.06, [95% CI, 1.03–1.08], p = 0.001) upon hospital admission. Furthermore, the cough symptom (OR = 17.39, [95% CI, 3.51–86.13], p = 0.001) and hospitalization length (OR = 1.36, [95% CI, 1.12–1.67], p = 0.002) were determined to be risk factors of pneumonia acquirement for pediatric inpatients.ConclusionWhile the abdominal pain, viral co-infection and some hematological abnormality mainly contribute to hospitalization of pediatric patients with IAV infection, the length of hospital stay and clinical sign of coughing upon hospital admission constitute the key determinants for nosocomial pneumonia development.

Abstract Background The precise mechanisms of hormone action responsible for the full course of events modulating folliculogenesis in crocodilian have not been determined, although histological features have been identified. Results The Alligator sinensis ovarian morphological characteristics observed at 1, 15, 30, 60, 90, and 300 days post hatching(dph) revealed that the dynamic changes in germ cells varied in different meiotic and developmental stages, confirming that the processes of folliculogenesis were protracted and asynchronous. The presence of endogenous follicle-stimulating hormone(FSH) mRNA and protein expression within the cerebrum at 1 dph, in parallel with the increase in germ cells within the germ cell nests(Nest) from 1 dph to 15 dph, suggested that endocrine regulation of the pituitary-gonad axis is an early event in oogonia division. Furthermore, the endogenous expression of FSH showed a trend of negative feedback augmentation accompanied by the exhaustion of maternal yolk E2 observed at 15 dph. Such significant elevation of endogenous FSH levels was observed to be related to pivotal events in the transition from mitosis to meiosis, as reflected by the proportion of oogonia during premeiosis interphase, with endogenous FSH levels reaching a peak at the earliest time step of 1 dph. In addition, the simultaneous upregulation of premeiotic marker STRA8 mRNA expression and the increase in endogenous FSH further verified the above speculation. The strongly FSHr-positive label in the oocytes within Pre-previtellogenic follicles was synchronized with the significant elevation of ovarian cAMP detected at 300 dph, which suggested that diplotene arrest maintenance during early vitellogenesis might be FSH dependent. In addition, preferential selection in asynchronous meiotic initiation has been supposed to act on somatic supportive cells and not directly on germ cells via regulation of FSH that in turn affects downstream estrogen levels. This suggestion was verified by the reciprocal stimulating effect of FSH and E2 on the accelerated meiotic marker SYCP3 and by the inhibited cell apoptosis demonstrated in ovarian cell culture in vitro. Conclusion The corresponding results contribute an expansion of the understanding of physiological processes and shed some light on the specific factors responsible for gonadotropin function in the early folliculogenesis of crocodilians.

Abstract Global agricultural trade creates multiple telecoupled flows of nitrogen (N) and phosphorus (P). The flows of physical and virtual nutrients along with trade have discrepant effects on natural resources in different countries. However, existing literature has not quantified or analyzed such effects yet. Here we quantified the physical and virtual N and P flows embedded in the global agricultural trade networks from 1997 to 2016 and elaborated components of the telecoupling framework. The N and P flows both increased continuously and more than 25% of global consumption of nutrients in agricultural products were related to physical nutrient flows, while virtual nutrient flows were equivalent to one-third of the nutrients inputs into global agricultural system. These flows have positive telecoupling effects on saving N and P resources at the global scale. Reducing inefficient trade flows will enhance resource conservation, environmental sustainability in the hyper-globalized world.

Summary: Background: Malaria, a widespread parasitic disease caused by Plasmodium species, remains a significant global health concern. Rapid and accurate detection, as well as species genotyping, are critical for effective malaria control. Methods: We have developed a Flexible, Robust, Equipment-free Microfluidic (FREM) platform, which integrates recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats (CRISPR)-based detection, enabling simultaneous malaria infection screening and Plasmodium species genotyping. The microfluidic chip enabled the parallel detection of multiple Plasmodium species, each amplified by universal RPA primers and genotyped by specific crRNAs. The inclusion of a sucrose solution effectively created spatial separation between the RPA and CRISPR assays within a one-pot system, effectively resolving compatibility issues. Findings: Clinical assessment of DNA extracts from patients with suspected malaria demonstrates the FREM platform's superior sensitivity (98.41%) and specificity (92.86%), yielding consistent results with PCR-sequencing for malaria detection, which achieved a positive predictive agreement of 98.41% and a negative predictive agreement of 92.86%. Additionally, the accuracy of species genotyping was validated through concordance rates of 90.91% between the FREM platform and PCR-sequencing. Interpretation: The FREM platform offers a promising solution for point-of-care malaria screening and Plasmodium species genotyping. It highlights the possibility of improving malaria control efforts and expanding its applicability to address other infectious diseases. Funding: This work was financially supported by International Joint Laboratory on Tropical Diseases Control in Greater Mekong Subregion, National Natural Science Foundation of China, the Natural Science Foundation of Shanghai, Bill & Melinda Gates Foundation and National Research and Development Plan of China.

Tea grey blight disease is one of the most destructive diseases that infects tea and is caused by the pathogen Pestalotiopsis theae (Sawada) Steyaert. L-theanine is a unique non-protein amino acid of the tea plant. Different concentrations of L-theanine exhibit significant inhibitory effects on the growth and sporulation ability of the pathogen causing tea grey blight disease. To understand the effect mechanism of L-theanine on P. theae, transcriptome profiling was performed on the pathogenic mycelium treated with three different concentrations of L-theanine: no L-theanine treatment (TH0), 20 mg/mL theanine treatment (TH2), and 40 mg/mL theanine treatment (TH4). The colony growths were significantly lower in the treatment with L-theanine than those without L-theanine. The strain cultured with a high concentration of L-theanine produced no spores or only a few spores. In total, 2344, 3263, and 1158 differentially expressed genes (DEGs) were detected by RNA-sequencing in the three comparisons, Th2 vs. Th0, Th4 vs. Th0, and Th4 vs. Th2, respectively. All DEGs were categorized into 24 distinct clusters. According to GO analysis, low concentrations of L-theanine primarily affected molecular functions, while high concentrations of L-theanine predominantly affected biological processes including external encapsulating structure organization, cell wall organization or biogenesis, and cellular amino acid metabolic process. Based on KEGG, the DEGs of Th2 vs. Th0 were primarily involved in pentose and glucuronate interconversions, histidine metabolism, and tryptophan metabolism. The DEGs of Th4 vs. Th0 were mainly involved in starch and sucrose metabolism, amino sugar, and nucleotide sugar metabolism. This study indicated that L-theanine has a significant impact on the growth and sporulation of the pathogen of tea grey blight disease and mainly affects amino acid metabolism, carbohydrate metabolism, and cellular structure-related biosynthesis processes of pathogenic fungi. This work provides insights into the direct control effect of L-theanine on pathogenic growth and also reveals the molecular mechanisms of inhibition of L-theanine to P. theae.

Random lasers have attracted much attention in recent years owing to their advantages of a simple fabrication process, low processing cost, and material flexibility for any lasing wavelengths. They provide a roadmap for the design of ultra-bright lighting, displays, etc. However, the threshold reduction in random nanolasers remains a challenge in practical applications. In this work, lower-threshold random laser action from monolayer molybdenum disulfide film-encapsulated Au nanoparticles (MoS2/Au NPs) is demonstrated. The observed laser action of the MoS2/Au NPs shows a lower threshold of about 0.564 µJ/mm2, which is about 46.2% lower than the threshold of random lasers based on Au NPs. We proposed that the charge transfer between MoS2 and the gain material is the main reason for the reduction in the random laser threshold. The finite-difference time-domain (FDTD) method was used to calculate the lasing action of these two nanostructures. When charge transfer is taken into account, the theoretically calculated threshold of the MoS2/Au NPs is reduced by 46.8% compared to Au NP samples, which is consistent with the experimental results. This study provides a new mechanism to achieve low-threshold and high-quality random lasers, which has the potential to facilitate the application of random lasers and the development of high-performance optoelectronic devices.

Abstract Accumulation of vimentin is the core event in epithelial–mesenchymal transition (EMT). Post‐translational modifications have been widely reported to play crucial roles in imparting different properties and functions to vimentin. Here, a novel modification of vimentin, acetylated at Lys104 (vimentin‐K104Ac) is identified, which is stable in lung adenocarcinoma (LUAD) cells. Mechanistically, NACHT, LRR, and PYD domain‐containing protein 11 (NLRP11), a regulator of the inflammatory response, bind to vimentin and promote vimentin‐K104Ac expression, which is highly expressed in the early stages of LUAD and frequently appears in vimentin‐positive LUAD tissues. In addition, it is observed that an acetyltransferase, lysine acetyltransferase 7 (KAT7), which binds to NLRP11 and vimentin, directly mediates the acetylation of vimentin at Lys104 and that the cytoplasmic localization of KAT7 can be induced by NLRP11. Malignant promotion mediated by transfection with vimentin‐K104Q is noticeably greater than that mediated by transfection with vimentin‐WT. Further, suppressing the effects of NLRP11 and KAT7 on vimentin noticeably inhibited the malignant behavior of vimentin‐positive LUAD in vivo and in vitro. In summary, these findings have established a relationship between inflammation and EMT, which is reflected via KAT7‐mediated acetylation of vimentin at Lys104 dependent on NLRP11.

Since the first 70 years of reporting cancer chemotherapy, malignant tumors have been the second most common cause of death in children and adults. Currently, the commonly used anti-cancer methods include surgery, chemotherapy, radiotherapy, and immunotherapy. Although these treatment methods could alleviate cancer, they lead to different forms of side effects and have no particularly significant effect on prolonging the patients’ life span. Glycyrrhizic acid (GL), a native Chinese herbal extract, has a wide range of pharmacological effects, such as anti-cancer, anti-inflammatory, antioxidant, and immune regulation. In this review, the anti-cancer effects and mechanisms of GL are summarized in various cancers. The inhibition of GL on chemotherapy-induced side effects, including hepatotoxicity, nephrotoxicity, genotoxicity, neurotoxicity and pulmonary toxicity, is highlighted. Therefore, GL may be a promising and ideal drug for cancer therapy.

Maize (Zea mays L.) stalk rot is a devastating disease worldwide, causing severe yield losses. Although previous studies have focused on the genetic dissection of maize resistance to stalk rot, the mechanisms of resistance remain largely unknown. We used a comparative proteomics approach to identify candidate proteins associated with stalk rot resistance. Statistical analyses revealed 763 proteins differentially accumulated between Fusarium graminearum and mock-inoculated plants. Among them, the antioxidant protein ZmPrx5, which was up-accumulated in diseased plants, was selected for further study. ZmPrx5 transcripts were present in root, stalk, leaf, ear, and reproductive tissues. The expression of ZmPrx5 in three inbred lines increased significantly upon F. graminearum infection. ZmPrx5 was localized in the cytoplasm. Compared to control plants, maize plants overexpressing ZmPrx5 showed increased resistance to F. graminearum infection, and ZmPrx5 mutant plants were more susceptible than wild-type plants. Defense-associated pathways including plant–pathogen interactions, phenylalanine metabolism, and benzoxazinoid and flavonoid biosynthesis were suppressed in ZmPrx5 homozygous mutant plants compared with wild-type plants. We suggest that ZmPrx5 positively regulates resistance against stalk rot in maize, likely through defense-oriented transcriptome reprogramming. These results lay a foundation for further research on the roles of Prx5 subfamily proteins in resistance to plant fungal diseases, and provide a potential genetic resource for breeding disease-resistance maize lines.

BackgroundLittle is known about the role of interleukin (IL) in patients with acute myocardial infarction (MI), especially soluble IL-2 receptor (sIL-2R) and IL-8. We aim to evaluate, in MI patients, the predictive value of serum sIL-2R and IL-8 for future major adverse cardiovascular events (MACEs), and compare them with current biomarkers reflecting myocardial inflammation and injury.MethodsThis was a prospective, single-center cohort study. We measured serum concentrations of IL-1β, sIL-2R, IL-6, IL-8 and IL-10. Levels of current biomarkers for predicting MACEs were measured, including high-sensitivity C reactive protein, cardiac troponin T and N-terminal pro-brain natriuretic peptide. Clinical events were collected during 1-year and a median of 2.2 years (long-term) follow-up.ResultsTwenty-four patients (13.8%, 24/173) experienced MACEs during 1-year follow-up and 40 patients (23.1%, 40/173) during long-term follow-up. Of the five interleukins studied, only sIL-2R and IL-8 were independently associated with endpoints during 1-year or long-term follow-up. Patients with high sIL-2R or IL-8 levels (higher than the cutoff value) had a significantly higher risk of MACEs during 1-year (sIL-2R: HR 7.7, 3.3–18.0, p

Summary: The United Nations (UN) has adopted the 17 Sustainable Development Goals (SDGs), aiming to provide human welfare and conserve the planet, now and into the future. Two of the SDGs directly address biodiversity conservation and sustainable development – SDG 14 (life below water) and SDG 15 (life on land). Although the UN has issued annual reports on SDGs, the reports did not consistently reveal the progress over time, because of inconsistent methods such as estimation based on different indicators across years. Our research examined the dynamics of the same 10 indicators for SDGs 14 and 15 between 2010 and 2020. Results indicate that the overall SDG 14 scores had a small growth between 2010 and 2020, whereas the substantial increase in SDG 15 scores spotlighted the conservation efforts and sustainable use of terrestrial ecosystem services, especially in countries with biodiversity hotspots. Globally, there was more progress in terms of SDG 15 scores during 2015–2020 than during 2010–2015 (before the UN adopted SDGs in 2015). Surprisingly, SDG 14 score had smaller progress during 2015–2020 than during 2010–2015. Special attention should be given to low-income countries lagging in sustainable development performance when implementing the post-2020 global biodiversity framework.

Stroke is a major cause of mortality and morbidity and most acute strokes are ischemic. Evidence-based medicine has demonstrated the effectiveness of constraint-induced movement therapy (CIMT) in the recovery of motor function in patients after ischemic stroke, but the specific treatment mechanism remains unclear. Herein, our integrated transcriptomics and multiple enrichment analysis studies, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) studies show that CIMT conduction broadly curtails immune response, neutrophil chemotaxis, and chemokine-mediated signaling pathway, CCR chemokine receptor binding. Those suggest the potential effect of CIMT on neutrophils in ischemic mice brain parenchyma. Recent studies have found that accumulating granulocytes release extracellular web-like structures composed of DNA and proteins called neutrophil extracellular traps (NETs), which destruct neurological function primarily by disrupting the blood–brain barrier and promoting thrombosis. However, the temporal and spatial distribution of neutrophils and their released NETs in parenchyma and their damaging effects on nerve cells remain unclear. Thus, utilizing immunofluorescence and flow cytometry, our analyses uncovered that NETs erode multiple regions such as primary motor cortex (M1), striatum (Str), nucleus of the vertical limb of the diagonal band (VDB), nucleus of the horizontal limb of the diagonal band (HDB) and medial septal nucleus (MS), and persist in the brain parenchyma for at least 14 days, while CIMT can reduce the content of NETs and chemokines CCL2 and CCL5 in M1. Intriguingly, CIMT failed to further reduce neurological deficits after inhibiting the NET formation by pharmacologic inhibition of peptidylarginine deiminase 4 (PAD4). Collectively, these results demonstrate that CIMT could alleviate cerebral ischemic injury induced locomotor deficits by modulating the activation of neutrophils. These data are expected to provide direct evidence for the expression of NETs in ischemic brain parenchyma and novel insights into the mechanisms of CIMT protecting against ischemic brain injury.

The flow field distribution around the suspended pipeline is closely related to the mechanical characteristics and local scour characteristics of the underwater crossing pipelines. To fully investigate the velocity distribution and wake structure characteristics around the suspended pipeline under oblique flows, a flume model test and a numerical simulation based on the LES (Large Eddy Simulation) method were performed. The results showed that the velocity distribution near the suspended pipeline under oblique flows had obvious three-dimensional characteristics. The influence range of pipeline on velocity is 1 d before to 6 d behind the pipeline (d is pipeline diameter). The smaller the flow angle, the more disordered the velocity distribution is. The larger the flow angle, the greater the variation degree of the velocity at each section at the same section is, as well as the higher the velocity deficit value is. In addition, the larger the angle of pipe flow, the more violent the wake structure changes with the flow velocity, and the stronger the regularity of vortex street shedding. This research provides a theoretical reference for the scour prevention design and safe operation of crossing pipelines. HIGHLIGHT The velocity distribution and wake structure characteristics around the suspended section of the pipeline under oblique flows with different angles were numerically and experimentally investigated.;

Introduction: Our recent work demonstrated that Fufang Yinhua Jiedu granule (FFYH) exhibited a good antiviral activity against influenza A virus (IAV). However, whether the combinations of FFYH with antiviral agents show synergistic action against IAV remains unclear. Methods: In vitro combinations of FFYH and oseltamivir against IAV were evaluated using Madin-Darby canine kidney (MDCK) cell model. In vivo combinations effect against IAV (H1N1, A/FM1/1/33) was performed using Institute of Cancer Research (ICR) mice model. The potential mechanism of FFYH against IAV in vitro and in vivo was investigated by RT-PCR or Western blot. Results: In vitro combinations of FFYH and oseltamivir could synergistically inhibit the replication of IAV and prevent the cell pathogenic effect (CPE) caused by IAV. In in vivo assays, FFYH combined with oseltamivir not only could markedly improve the sick signs, food intake, weight loss, hematology parameters, inflammatory factors and lung pathological changes, but also significantly increased the survival rate and the survival time of the IAV-infected mice. In addition, virus titers in lung tissue and lung index were markedly reduced on day 6 post-infection by combination therapy of oseltamivir combined with FFYH at 0.25 and 0.5 g/kg/d. The studies of mechanism of action indicated that the combination effect of FFYH with oseltamivir against IAV might be achieved through regulating TLR7-MyD88 signaling pathway. Conclusions: The combinations of FFYH and oseltamivir not only exhibited in vitro synergistic antiviral activity on IAV, but also showed better protective effect against lethal IAV infections than oseltamivir or FFYH each on its own. These findings might provide a new option for the treatment of IAV infection in the future.

This study investigated the performance of thermophilic–mesophilic (T-M) and mesophilic–thermophilic (M-T) two-phase sludge anaerobic digestion at different inoculation proportions after a change in digestion temperature. After temperature change, the pH, total ammonia nitrogen (TAN), free ammonia nitrogen (FAN), solubility chemical oxygen demand (SCOD), and total alkalinity (TA) levels of two-phase digesters were between thermophilic control digesters and mesophilic control digesters. However, the volatile fatty acid (VFA) levels of two-phase digesters were higher than those of thermophilic or mesophilic control digesters. The bacteria communities of M-T two-phase digesters were more diverse than those of T-M. After a change in digestion temperature, the bacterial community was dominated by Coprothermobacter. After a change of digestion temperature, the relative abundance (RA) of Methanobacterium, Methanosaeta, and Methanospirillum of M-T two-phase digesters was higher than that of T-M two-phase digesters. In comparison, the RA of Methanosarcina of T-M two-phase digesters was higher than that of M-T two-phase digesters. The ultimate methane yields of thermophilic control digesters were greater than those of mesophilic control digesters. Nevertheless, the ultimate methane yield levels of M-T two-phase digesters were greater than those of T-M two-phase digesters. The ultimate methane yields of all two-phase digesters presented an earlier increase and later decrease trend with the increasing inoculation proportion. Optimal methane production condition was achieved when 15% of sludge (T-M15) was inoculated under mesophilic–thermophilic conditions, which promoted 123.6% (based on mesophilic control) or 27.4% (based on thermophilic control). An optimal inoculation proportion (about 15%) balanced the number and activity of methanogens of high-solid sludge anaerobic digestion.

Escherichia coli O157:H7 ( E. coli O157:H7) can induce severe diseases in animals and humans that result in significant public health problems. Therefore, the development of rapid and visual detection methods to diagnose E. coli O157:H7 infections and monitor its prevalence is critical for the prevention and control purposes. A colorimetric loop-mediated isothermal amplification (LAMP) assay was utilized to detect E. coli O157:H7. A DNA extraction kit and Flinders Technology Associates (FTA) cards were used to extract nucleic acid in conjunction with colorimetric LAMP detection. The method developed effectively distinguished E. coli O157:H7 from other pathogens with a detection limit of 25 CFU/mL in spiked stool samples. In addition, the nucleic acid of these samples was easily extracted and transported with an FTA card at room temperature. The entire detection process was completed within 35 min using simple constant-temperature equipment. The colorimetric LAMP method with FTA card-based nucleic acid purification was shown to rapidly detect E. coli O157:H7 with sensitivity and specificity. This visual method is expected to be widely used to control E. coli O157:H7 infections, particularly in resource-limited settings.

ObjectiveThis study aimed to compare the efficacy of contralaterally controlled functional electrical stimulation (CCFES) vs. neuromuscular electrical stimulation (NMES) for motor recovery of the lower extremity in patients with subacute stroke.Materials and methodsSeventy patients within 6 months post-stroke were randomly assigned to the CCFES group (n = 35) and the NMES group (n = 35). Both groups underwent routine rehabilitation plus 20-min electrical stimulation (CCFES or NMES) on ankle dorsiflexion muscles per day, 5 days a week, for 3 weeks. Ankle AROM (dorsiflexion), Fugl-Meyer assessment-lower extremity (FMA-LE), Barthel Index (BI), Functional Ambulation Category scale (FAC), 10-meter walking test, and surface electromyography (sEMG) were assessed at the baseline and at the end of the intervention.ResultTen patients did not complete the study (five in CCFES and five in NMES), so only 60 patients were analyzed in the end. After the 3-week intervention, FMA-LE, BI, Ankle AROM (dorsiflexion), and FAC increased in both groups (p < 0.05). Patients in the CCFES group showed significantly greater improvements only in the measurement of Fugl-Meyer assessment-lower extremity compared with the NMES group after treatment (p < 0.05). The improvement in sEMG response of tibialis anterior by CCFES was greater than NMES (p < 0.05).ConclusionContralateral controlled functional electrical stimulation can effectively improve the motor function of the lower limbs better than conventional neuromuscular electrical stimulation in subacute patients after stroke, but the effect on improving the ability to walk, such as walking speed, was not good.Clinical trial registrationhttp://www.chictr.org.cn/, identifier: ChiCTR2100045423.

Microglia are considered the main phagocytic cells in the central nervous system, remodeling neural circuits by pruning synapses during development. Microglial phagocytosis is also a crucial process in maintaining adult brain homeostasis and clearing potential toxic factors, which are recognized to be associated with neurodegenerative and neuroinflammatory disorders. For example, microglia can engulf amyloid-β plaques, myelin debris, apoptotic cells, and extracellular harmful substances by expressing a variety of specific receptors on the cell surface or by reprogramming intracellular glucose and lipid metabolism processes. Furthermore, physical exercise has been implicated to be one of the non-pharmaceutical treatments for various nervous system diseases, which is closely related to neuroplasticity and microglia functions including proliferation, activation, and phagocytosis. This review focuses on the central regulatory mechanisms related to microglia phagocytosis and the potential role of exercise training in this process.

Tea (Camellia sinensis) is an important crop that is mainly used in the food industry. This study using the metabolome and microbiome investigates the resistance factors of wild tea plant resources against tea gray blight disease, which is caused by Pestalotiopsis theae (Sawada) Steyaert. According to the interaction analysis of tea leaves and pathogenic fungus, the resistance of wild tea plant resource “R1” (Resistance 1) to tea gray blight disease was significantly higher than that of wild tea plant resource “S1” (Susceptibility 1). The difference between “R1” and “S1” in the metabolome was obvious. There were 145 metabolites that significantly changed. The phenolic acids and flavonoids were the major increased categories in “R1,” and it included 4-O-glucosyl-sinapate and petunidin-3-o-(6”-o-p-coumaroyl) rutinoside. Six metabolic pathways were significantly enriched, including aminoacyl-tRNA biosynthesis, flavone, and flavonol biosynthesis. In terms of bacteria, there was no significant difference between “S1” and “R1” in the principal component analysis (PCA). Pseudomonas was the major bacterial genus in “S1” and “R1.” In addition, each of the two resources had its own predominant genus: Cellvibirio was a predominant bacterial genus in “S1” and Candidatus_competibacter was a predominant bacterial genus in “R1.” In terms of fungi, the fungal diversity and the abundance of the two tea plant resource samples could be distinguished clearly. The fungal component of “S1” was more abundant than that of “R1” at the genus level. Toxicocladosporium was the predominant fungal genus of “S1,” and Filobasidium was the predominant fungal genus of “R1.” The relative abundance of unclassified-norank-norank-Chloroplast and Penicillium were significantly different between “S1” and “R1.” Penicillium was identified as a potential biomarker. They correlated with some metabolites enriched in “S1” or “R1,” such as L-arginine and quercetin-3-o-(2”-o-rhamnosyl) rutinoside-7-o-glucoside. Overall, phenolic acids, flavonoids, and Penicillium could be functional metabolites or microorganisms that contributed to improving the resistance of wild tea plant resources to tea gray blight disease.

Abstract Background Benign paroxysmal positional vertigo (BPPV) is one of the most common peripheral vestibular disorders leading to balance difficulties and increased fall risks. This study aims to investigate the walking stability of BPPV patients in clinical settings and propose a machine-learning-based classification method for determining the severity of gait disturbances of BPPV. Methods Twenty-seven BPPV outpatients and twenty-seven healthy subjects completed level walking trials at self-preferred speed in clinical settings while wearing two accelerometers on the head and lower trunk, respectively. Temporo-spatial variables and six walking stability related variables [root mean square (RMS), harmonic ratio (HR), gait variability, step/stride regularity, and gait symmetry] derived from the acceleration signals were analyzed. A support vector machine model (SVM) based on the gait variables of BPPV patients were developed to differentiate patients from healthy controls and classify the handicapping effects of dizziness imposed by BPPV. Results The results showed that BPPV patients employed a conservative gait and significantly reduced walking stability compared to the healthy controls. Significant different mediolateral HR at the lower trunk and anteroposterior step regularity at the head were found in BPPV patients among mild, moderate, and severe DHI (dizziness handicap inventory) subgroups. SVM classification achieved promising accuracies with area under the curve (AUC) of 0.78, 0.83, 0.85 and 0.96 respectively for differentiating patients from healthy controls and classifying the three stages of DHI subgroups. Study results suggest that the proposed gait analysis that is based on the coupling of wearable accelerometers and machine learning provides an objective approach for assessing gait disturbances and handicapping effects of dizziness imposed by BPPV.

Abstract Consumer wearables and sensors are a rich source of data about patients’ daily disease and symptom burden, particularly in the case of movement disorders like Parkinson’s disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia, and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC = 0.87), as well as tremor- (best AUPR = 0.75), dyskinesia- (best AUPR = 0.48) and bradykinesia-severity (best AUPR = 0.95).

Infectious diseases contribute significantly to the global disease burden. Sensitive and accurate screening methods are some of the most effective means of identifying sources of infection and controlling infectivity. Conventional detecting strategies such as quantitative polymerase chain reaction (qPCR), DNA sequencing, and mass spectrometry typically require bulky equipment and well-trained personnel. Therefore, mass screening of a large population using conventional strategies during pandemic periods often requires additional manpower, resources, and time, which cannot be guaranteed in resource-limited settings. Recently, emerging microfluidic technologies have shown the potential to replace conventional methods in performing point-of-care detection because they are automated, miniaturized, and integrated. By exploiting the spatial separation of detection sites, microfluidic platforms can enable the multiplex detection of infectious diseases to reduce the possibility of misdiagnosis and incomplete diagnosis of infectious diseases with similar symptoms. This review presents the recent advances in microfluidic platforms used for multiplex detection of infectious diseases, including microfluidic immunosensors and microfluidic nucleic acid sensors. As representative microfluidic platforms, lateral flow immunoassay (LFIA) platforms, polymer-based chips, paper-based devices, and droplet-based devices will be discussed in detail. In addition, the current challenges, commercialization, and prospects are proposed to promote the application of microfluidic platforms in infectious disease detection.

Abstract Background Alternative splicing (AS) plays critical roles in generating protein diversity and complexity. Dysregulation of AS underlies the initiation and progression of tumors. Machine learning approaches have emerged as efficient tools to identify promising biomarkers. It is meaningful to explore pivotal AS events (ASEs) to deepen understanding and improve prognostic assessments of lung adenocarcinoma (LUAD) via machine learning algorithms. Method RNA sequencing data and AS data were extracted from The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database. Using several machine learning methods, we identified 24 pairs of LUAD-related ASEs implicated in splicing switches and a random forest-based classifiers for identifying lymph node metastasis (LNM) consisting of 12 ASEs. Furthermore, we identified key prognosis-related ASEs and established a 16-ASE-based prognostic model to predict overall survival for LUAD patients using Cox regression model, random survival forest analysis, and forward selection model. Bioinformatics analyses were also applied to identify underlying mechanisms and associated upstream splicing factors (SFs). Results Each pair of ASEs was spliced from the same parent gene, and exhibited perfect inverse intrapair correlation (correlation coefficient = − 1). The 12-ASE-based classifier showed robust ability to evaluate LNM status of LUAD patients with the area under the receiver operating characteristic (ROC) curve (AUC) more than 0.7 in fivefold cross-validation. The prognostic model performed well at 1, 3, 5, and 10 years in both the training cohort and internal test cohort. Univariate and multivariate Cox regression indicated the prognostic model could be used as an independent prognostic factor for patients with LUAD. Further analysis revealed correlations between the prognostic model and American Joint Committee on Cancer stage, T stage, N stage, and living status. The splicing network constructed of survival-related SFs and ASEs depicts regulatory relationships between them. Conclusion In summary, our study provides insight into LUAD researches and managements based on these AS biomarkers.

Abstract Abnormal DNA methylation persists throughout carcinogenesis and cancer development. Hence, gene promoter methylation may act as a prognostic tool and provide new potential therapeutic targets for patients with lung adenocarcinoma (LUAD). In this study, to explore prognostic methylation signature, data regarding DNA methylation and RNA‐seq, and clinical data of patients with LUAD from the Cancer Genome Atlas database (TCGA) were downloaded. After data preprocessing, the methylation data were divided into training (N = 405) and test sets (N = 62). Then, patients in the training set were assigned to five subgroups based on their different methylation levels using the consensus clustering method. We comprehensively analyzed the survival information, methylation levels, and clinical variables, including American Joint Committee on Cancer (AJCC) stage, tumor‐node‐metastasis (TNM) staging, age, smoking history, and gender of these five groups. Subsequently, we identified a 16‐CpG prognostic signature and constructed a prognostic model, which was verified in the test set. Further analyses showed stable prognostic performance in the stratified cohorts. In conclusion, the new predictive DNA methylation signature proposed in this study may be used as an independent biomarker to assess the overall survival of LUAD patients and provide bioinformatics information for development of targeted therapy.

Abstract Background Bronchoscopy is applied broadly in the diagnosis and treatment of pulmonary diseases. Over the past few decades, an increasing number of studies about bronchoscopy have been published. However, little is known about their qualities and characteristics. Methods All of the databases in Web of Science (including the Web of Science Core Collection, BIOSIS Citation Index, KCI-Korean Journal Database, MEDLINE, Russian Science Citation Index, and SciELO Citation Index) were utilized to identify articles published from 1990 to 2020. The top 100 most cited articles about bronchoscopy were selected for degree centrality analysis and analyses regarding publication time, total citation number, the citation density, time-related flux, first author, published journal, geographic origin, and research theme. Results The selected articles were published mainly in the 2000s and 1990s. Citations per article ranged from 731 to 196. The leading country was the USA, followed by the United Kingdom. The most frequently studied themes were bronchoalveolar lavage (BAL) fluid and biopsy. The degree centrality analysis connoted that “BAL, inflammation, diagnosis” had a high degree of centrality in the 1990s, while “diagnosis, BAL, biopsy, prospective” took centre stage in the 2000s. Conclusions The time, area, and theme distribution of the 100 most cited articles on bronchoscopy have been thoroughly analyzed. It is noticeable that researches based on BAL and endobronchial or transbronchial biopsies currently plays a major role.

Aperiodic structure imaging suffers limitations when utilizing Fourier analysis. The authors report an algorithm that quantitatively overcomes these limitations based on nonconvex optimization, demonstrated by studying aperiodic structures via the phase sensitive interference in STM images.

Amentoflavone (AMF) is a kind of biflavonoids existing in Ginkgo biloba leaves. It has many biological activities, such as antioxidant, anti-inflammatory, anti-bacterial, antiviral, hypoglycemic, anti-tumor and inducing apoptosis. However, its solubility and bioavailability are poor and there are a few studies on it in vivo. In this study, to improve its solubility and bioavailability, the nanomicelles were prepared with TPGS and soluplus as carriers for the first time. The particle size, Zeta potential, encapsulation efficiency, drug loading, stability, cytotoxicity, cellular uptake, and metabolites in rats were studied. Cytotoxicity, cellular uptake, and metabolites in rats of AMF-loaded TPGS/soluplus mixed micelles were compared with those of AMF. As a result, AMF-loaded TPGS/soluplus mixed micelles with a particle size of 67.33 ± 2.01 nm and Zeta potential of −0.84133 ± 0.041405 mV were successfully prepared. The encapsulation efficiency and drug loading of the mixed nanomicelles were 99.18 ± 0.76% and 2.47 ± 0.01%, respectively. The physical and chemical properties of the mixed micelles were stable within 60 d, and the cytotoxicity of the mixed micelles was much greater than that of AMF monomers. Thirty-four kinds of metabolites of AMF were identified in rats. The metabolites were mainly distributed in rat feces. No metabolites were detected in bile and plasma. 14 kinds of metabolites of the mixed micelles in rats were detected, including 11 in feces, 6 in urine, and 3 in plasma, which indicated that the bioavailability of AMF has been improved. And the toxicity to cancer cells was enhanced, which laid a foundation for the development of new drugs.

Uncertainty expressions are used in accounting contexts to describe business information. Due to the widespread use of uncertainty expressions, accounting scholars have critically assessed their potential impacts in financial reporting, as well as in the context of judgement and decision-making behaviour. In line with this topic, this paper outlines several fundamental issues related to uncertainty expressions and grounds these research paradigms and empirical findings in the context of the behavioural-psychology literature. In this study, we propose a solution to reduce potential impacts of uncertainty expressions in accounting. We advocate the Verbal-Numerical (V-N) Scale strategy for the communication of objective accounting information. We also recommend the V-N Disclosure strategy for the communication of subjective accounting information by associating a mathematical strategy. Practical limitations and implications for future accounting research on uncertainty expressions are also discussed.

As a consequence of long-term coevolution and natural selection, the leaves of mulberry (Morus alba) trees have become the best food source for silkworms (Bombyx mori). Nevertheless, the molecular and genomic basis of defense response remains largely unexplored. In the present study, we assessed changes in the transcriptome changes of mulberry in response to silkworm larval feeding at 0, 3, and 6 h. A total of 4709 (up = 2971, down = 1738) and 3009 (up = 1868, down = 1141) unigenes were identified after 3 and 6 h of silkworm infestation, respectively. MapMan enrichment analysis results show structural traits such as leaf surface wax, cell wall thickness and lignification form the first physical barrier to feeding by the silkworms. Cluster analysis revealed six unique temporal patterns of transcriptome changes. We predicted that mulberry promoted rapid changes in signaling and other regulatory processes to deal with mechanical damage, photosynthesis impairment, and other injury caused by herbivores within 3–6 h. LRR-RK coding genes (THE1, FER) was predicted participated in perception of cell wall perturbation in mulberry responding to silkworm feeding. Ca2+ signal sensors (CMLs), ROS (OST1, SOS3), RBOHD/F, CDPKs, and ABA were part of the regulatory network after silkworm feeding. Jasmonic acid (JA) signal transduction was predicted to act in silkworm feeding response, 10 JA signaling genes (such as OPR3, JAR1, and JAZ1) and 21 JA synthesis genes (such as LOX2, AOS, and ACX1) were upregulated after silkworm feeding for 3 h. Besides, genes of “alpha-Linolenic acid metabolism” and “phenylpropanoid biosynthesis” were activated in 3 h to reprogram secondary metabolism. Collectively, these findings provided valuable insights into silkworm herbivory-induced regulatory and metabolic processes in mulberry, which might help improve the coevolution of silkworm and mulberry.

Significant advances have been made in the morphological observations of the dorsal gland (DG), an oval organ/tissue which lies on both sides of the dorsal midline of the crocodilian. In the current study, RNA sequencing (RNA-seq) was used to identify the changing patterns of Alligator sinesis DGs at different timepoints from the 31st embryonic day (E31) to the newly hatched 1st day (NH1). A comprehensive transcriptional changes of differentially expression gene (DEGs) involved in the melanogenesis, cholesterol metabolism, and cell apoptosis pathways suggested that the DG might serves as a functional secretory gland in formation, transport and deposition of pigment, and lipids secretion via lysosomal exocytosis. Furthermore, the remarkable immunohistochemical staining of proliferating cell nuclear antigen (PCNA) and B-cell lymphoma 2 (Bcl-2)-positive signals in the basilar cells, in parallel with the immuno-reactive TdT-mediated dUTP nick-End labeling(TUNEL) within suprabasal cells, provided direct molecular evidence supporting for the speculation that DG serves as a holocrine secretion mode. Finally, subsequent phylogenetic and immunohistochemical analysis for the PITX2, the identified DEGs in the RNA-seq, was helpful to further elucidate the transcriptional regulatory mechanism of candidate genes. In conclusion, the current results are of considerable importance in enriching our understanding of the intrinsic relationship between the skin derivatives and lifestyles of newborn Alligator sinesis.

In this work, an Au modified Bi2O3-TiO2 (Au/Bi2O3-TiO2) hybrid is developed as a simple and effective photocatalyst for the production of H2O2. The modification of Bi2O3 improves the charge separation of photocatalyst and significantly enhances the photocatalytic activity of Au/TiO2 for H2O2 production. In-situ electron spin resonance studies shows stepwise single-electron oxygen reduction reaction (ORR) on the Au/Bi2O3-TiO2 photocatalyst for the production of H2O2. This work demonstrates the importance of heterojunction structure photocatalyst for improved performance of TiO2 in order to produce concentrated H2O2.

Blockchain is considered a breakthrough technology in the construction industry, with the potential to improve the trust environment and workflow of construction stakeholders. Although recent research offers hints regarding possible contributing elements to blockchain adoption in the construction industry, no specific study has addressed this topic. This knowledge gap hinders the adoption and promotion of blockchain in construction organizations. This study aimed to identify the determinants of blockchain adoption in the construction industry and verify the influence of the combination of various factors on adoption intention. Based on the technology–organization–environment framework, a conceptual model of blockchain adoption in the construction industry was constructed. Data were collected through the distribution of questionnaires, and 244 professionals in the construction field participated in this study. To evaluate the model hypotheses, we used a two-stage partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) combination. The PLS-SEM revealed that factors such as compatibility, top management support, relative advantage, regulatory support, cost, competitive pressure, organizational readiness, and firm size significantly influence blockchain adoption. The fsQCA indicated that six causal conditions achieve high adoption intention. This is one of the first empirical studies on blockchain adoption in the construction industry, which can aid organizations, policymakers, and project participants in making informed decisions regarding the adoption of blockchain.

The grey wolf optimization (GWO) algorithm is widely utilized in many global optimization applications. In this paper, a dynamic opposite learning-assisted grey wolf optimizer (DOLGWO) was proposed to improve the search ability. Herein, a dynamic opposite learning (DOL) strategy is adopted, which has an asymmetric search space and can adjust with a random opposite point to enhance the exploitation and exploration capabilities. To validate the performance of DOLGWO algorithm, 23 benchmark functions from CEC2014 were adopted in the numerical experiments. A total of 10 popular algorithms, including GWO, TLBO, PIO, Jaya, CFPSO, CFWPSO, ETLBO, CTLBO, NTLBO and DOLJaya were used to make comparisons with DOLGWO algorithm. Results indicate that the new model has strong robustness and adaptability, and has the significant advantage of converging to the global optimum, which demonstrates that the DOL strategy greatly improves the performance of original GWO algorithm.

The dynamic immune response to various diseases and therapies has been considered a promising indicator of disease status and therapeutic effectiveness. For instance, the human peripheral blood mononuclear cell (PBMC), as a major player in the immune system, is an important index to indicate a patient’s immune function. Therefore, establishing a simple yet sensitive tool that can frequently assess the immune system during the course of disease and treatment is of great importance. This study introduced an integrated system that includes an electrochemical impedance spectroscope (EIS)-based biosensor in a digital microfluidic (DMF) device, to quantify the PBMC abundance with minimally trained hands. Moreover, we exploited the unique droplet manipulation feature of the DMF platform and conducted a dynamic cell capture assay, which enhanced the detection signal by 2.4-fold. This integrated system was able to detect as few as 104 PBMCs per mL, presenting suitable sensitivity to quantify PBMCs. This integrated system is easy-to-operate and sensitive, and therefore holds great potential as a powerful tool to profile immune-mediated therapeutic responses in a timely manner, which can be further evolved as a point-of-care diagnostic device to conduct near-patient tests from blood samples.

Functional magnetic resonance imaging (fMRI) is a neuroimaging tool which has been applied extensively to explore the pathophysiological mechanisms of neurological disorders. Spatial neglect is considered to be the failure to attend or respond to stimuli on the side of the space or body opposite a cerebral lesion. In this review, we summarize and analyze fMRI studies focused specifically on spatial neglect. Evidence from fMRI studies have highlighted the role of dorsal and ventral attention networks in the pathophysiological mechanisms of spatial neglect, and also support the concept of interhemispheric rivalry as an explanatory model. fMRI studies have shown that several rehabilitation methods can induce activity changes in brain regions implicated in the control of spatial attention. Future investigations with large study cohorts and appropriate subgroup analyses should be conducted to confirm the possibility that fMRI might offer an objective standard for predicting spatial neglect and tracking the response of brain activity to clinical treatment, as well as provide biomarkers to guide rehabilitation for patients with SN.

Extracellular vesicles (EVs) have gained considerable attention as vital circulating biomarkers since their structure and composition resemble the originating cells. The investigation of EVs’ biochemical and biophysical properties is of great importance to map them to their parental cells and to better understand their functionalities. In this study, a novel frequency-dependent impedance measurement system has been developed to characterize EVs based on their unique dielectric properties. The system is composed of an insulator-based dielectrophoretic (iDEP) device to entrap and immobilize a cluster of vesicles followed by utilizing electrical impedance spectroscopy (EIS) to measure their impedance at a wide frequency spectrum, aiming to analyze both their membrane and cytosolic charge-dependent contents. The EIS was initially utilized to detect nano-size vesicles with different biochemical compositions, including liposomes synthesized with different lipid compositions, as well as EVs and lipoproteins with similar biophysical properties but dissimilar biochemical properties. Moreover, EVs derived from the same parental cells but treated with different culture conditions were characterized to investigate the correlation of impedance changes with biochemical properties and functionality in terms of pro-inflammatory responses. The system also showed the ability to discriminate between EVs derived from different cellular origins as well as among size-sorted EVs harbored from the same cellular origin. This proof-of-concept approach is the first step towards utilizing EIS as a label-free, non-invasive, and rapid sensor for detection and characterization of pathogenic EVs and other nanovesicles in the future.

Background The highest rate of cancer-related deaths worldwide is from lung adenocarcinoma (LUAD) annually. Metabolism was associated with tumorigenesis and cancer development. Metabolic-related genes may be important biomarkers and metabolic therapeutic targets for LUAD. Materials and Methods In this study, the gleaned cohort included LUAD RNA-SEQ data from the Cancer Genome Atlas (TCGA) and corresponding clinical data (n = 445). The training cohort was utilized to model construction, and data from the Gene Expression Omnibus (GEO, GSE30219 cohort, n = 83; GEO, GSE72094, n = 393) were regarded as a testing cohort and utilized for validation. First, we used a lasso-penalized Cox regression analysis to build a new metabolic-related signature for predicting the prognosis of LUAD patients. Next, we verified the metabolic gene model by survival analysis, C-index, receiver operating characteristic (ROC) analysis. Univariate and multivariate Cox regression analyses were utilized to verify the gene signature as an independent prognostic factor. Finally, we constructed a nomogram and performed gene set enrichment analysis to facilitate subsequent clinical applications and molecular mechanism analysis. Result Patients with higher risk scores showed significantly associated with poorer survival. We also verified the signature can work as an independent prognostic factor for LUAD survival. The nomogram showed better clinical application performance for LUAD patient prognostic prediction. Finally, KEGG and GO pathways enrichment analyses suggested several especially enriched pathways, which may be helpful for us investigative the underlying mechanisms.

Job shop scheduling problem (JSP) is one of the most difficult optimization problems in manufacturing industry, and flexible job shop scheduling problem (FJSP) is an extension of the classical JSP, which further challenges the algorithm performance. In FJSP, a machine should be selected for each process from a given set, which introduces another decision element within the job path, making FJSP be more difficult than traditional JSP. In this paper, a variant of grasshopper optimization algorithm (GOA) named dynamic opposite learning assisted GOA (DOLGOA) is proposed to solve FJSP. The recently proposed dynamic opposite learning (DOL) strategy adopts the asymmetric search space to improve the exploitation ability of the algorithm and increase the possibility of finding the global optimum. Various popular benchmarks from CEC 2014 and FJSP are used to evaluate the performance of DOLGOA. Numerical results with comparisons of other classic algorithms show that DOLGOA gets obvious improvement for solving global optimization problems and is well-performed when solving FJSP.

In this work, Au-modified F-TiO2 is developed as a simple and efficient photocatalyst for H2O2 production under ultraviolet light. The Au/F-TiO2 photocatalyst avoids the necessity of adding fluoride into the reaction medium for enhancing H2O2 synthesis, as in a pure TiO2 reaction system. The F− modification inhibits the H2O2 decomposition through the formation of the ≡Ti–F complex. Au is an active cocatalyst for photocatalytic H2O2 production. We compared the activity of TiO2 with F− modification and without F− modification in the presence of Au, and found that the H2O2 production rate over Au/F-TiO2 reaches four times that of Au/TiO2. In situ electron spin resonance studies have shown that H2O2 is produced by stepwise single-electron oxygen reduction on the Au/F-TiO2 photocatalyst.

Bacterial biofilm-related diseases cause serious hazard to public health and bring great challenge to the traditional antibiotic treatment. Photothermal therapy (PTT) has been recognized as a promising alternative solution. However, the therapeutic efficacy of PTT is often compromised by the collateral damage to normal tissues due to the lack of bacteria-targeting capability. Here, a Staphylococcus aureus (S. aureus)-targeted PTT nanoagent is prepared based on antibody (anti-protein A IgG), polydopamine (PDA), and PEG-SH (thiolated poly (ethylene glycol)) functionalized MoS2 nanosheets (MoS2@PDA-PEG/IgG NSs, MPPI NSs). The PDA was used as bio-nano interface to facilitate the covalent conjugation of antibody and PEG-SH onto the surface of MoS2 NSs via facile catechol chemistry. Targeted PTT of MPPI NSs shows excellent inactivation efficiency of larger than 4 log (>99.99%) to S. aureus both in biofilms (in vitro) and in infected tissues (in vivo) without causing damage to normal mammalian cells. By contrast, non-targeted PTT of MoS2@PDA-PEG NSs (MPP NSs) only kills S. aureus by