Optimized air quality management based on air quality index prediction and air pollutants identification in representative cities in China.

With the ongoing challenge of air pollution posing serious health and environmental threats, particularly in rapidly industrializing regions, accurate forecasting and effective pollutant identification are crucial for enhancing public health and ecological stability. This study aimed to optimize air quality management through the prediction of the Air Quality Index (AQI) and identification of air pollutants. Our study spans nine representative cities (Hohhot, Yinchuan, Lanzhou, Beijing, Taiyuan, Xi'an, Shanghai, Nanjing, Wuhan) in China, with data collected from January 1, 2015, to November 30, 2021. We proposed a new model for daily AQI prediction, termed VMD-CSA-CNN-LSTM, which employed advanced machine learning techniques, including convolutional neural networks (CNN) and long short-term memory (LSTM) networks, and leveraged the chameleon swarm algorithm (CSA) for hyperparameter optimization, integrated through a variational mode decomposition approach. The model was developed using data from Lanzhou, with a split ratio of 8:1:1 into training, validation, and test sets, achieving an RMSE of 2.25, MAPE of 0.02, adjusted R-squared of 98.91%, and training efficiency of 5.31%. The model was further externally validated in the other eight cities, yielding comparable results, with an adjusted R-squared above 96%, MAPE below 0.1, and RMSE below 7.5. Additionally, we employed a random forest algorithm to identify the primary pollutants contributing to AQI levels. Our results indicated that PM2.5 was the most significant pollutant in Beijing, Taiyuan, and Xi'an, while PM10 was dominant in Hohhot, Yinchuan, and Lanzhou. In Shanghai, Nanjing, and Wuhan, both PM2.5 and PM10 were critical, with ozone also identified as a major air pollutant. This study not only advances the predictive accuracy of AQI models but also aids policymakers by providing a reliable tool for air quality management and strategic planning aimed at pollution reduction. The integration of these advanced computational techniques into environmental monitoring practices offers a promising avenue for enhancing air quality and mitigating pollution-related risks.

The construction of a novel supplementary diagnostic model for patients with indeterminate HIV infection.

INTRODUCTION: The window period, defined as HIV nucleic acid test (NAT) reactivity but Western blot (WB) test inconclusive, is garnering more attention. Improving the detection efficiency of HIV high-risk populations in the window period is critical to reducing the risk of unanticipated transmission. The purpose of this study was to create an additional strategy for distinguishing indeterminate HIV infection cases. METHODS: Based on WB follow-up results, the individuals in this study were divided into persons in the HIV window period and persons without HIV. Plasma was analyzed using quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect differentially expressed proteins (DEPs). The biological implications of these DEPs were investigated using enrichment analysis. Protein-protein interaction (PPI) analysis and LASSO regression were used to identify key proteins. The calibration curve, decision curve, and nomogram were utilized to create the model. RESULTS: Fifty-seven DEPs were screened out, with 33 up-regulated and 24 down-regulated in persons with HIV at window period. The most important Gene Ontology (GO) enrichment items are oxidoreductase activity and heme binding. Oxidoreductases account for half of the 10 main proteins identified from various DEPs. An auxiliary diagnostic model comprised of peroxiredoxin-2 (P32119), band 3 anion transport protein (P02730), and histone H2A type 1 (P0C0S8) was developed. The results of the confusion matrix parameters revealed that this diagnostic approach had strong practicability in distinguishing indeterminate HIV infection cases. CONCLUSIONS: The three DEPs identified and predicted by proteomics are useful for the supplemental identification of persons in the HIV window period.

Knockdown of miR-155 alleviates skin damage in rats with chronic spontaneous urticaria by modulating the JAK/STAT signaling pathway.

OBJECTIVE: The aim of this study was to investigate the role and mechanisms of miR-155 in chronic spontaneous urticaria (CSU). METHODS: The expression level of miR-155 in the skin tissues of patients with CSU and experimental rats were detected by RT-qPCR, followed by the measurement of the histamine release rate in the serum through the histamine release test. Besides, hematoxylin & eosin staining was used to observe the pathological changes of the skin tissues; Corresponding detection kits and flow cytometry to measure the changes of immunoglobulins, inflammatory cytokines and T cell subsets in the serum of rats in each group; and western blot to check the expression level of proteins related to JAK/STAT signaling pathway in the skin tissues. RESULTS: Knockdown of miR-155 reduced the number and duration of pruritus, alleviated the skin damage, and decreased the number of eosinophils in CSU rats. Moreover, knockdown of miR-155 elevated the serum levels of IgG and IgM, decreased the levels of IgA and inflammatory cytokines, and reduced the proportion of CD4 + and CD4 + CD25 + T cells, as well as the CD4+/CD8 + ratio in CSU rats. However, Tyr705 intervention could reverse the effects of knockdown of miR-155 on CSU model rats. Furthermore, we found that knockdown of miR-155 significantly reduced the protein expression of IRF-9, as well as the P-JAK2/JAK2 and P-STAT3/STAT3 ratios in the skin tissues of CSU rats. CONCLUSION: Knockdown of miR-155 can alleviate skin damage and inflammatory responses and relieve autoimmunity in CSU rats by inhibiting the JAK/STAT3 signaling pathway.

Problem-solving model guided by stimulus-organism-response theory: State of mind and coping styles of depressed mothers after cesarean delivery.

BACKGROUND: The use of a problem-solving model guided by stimulus-organism-response (SOR) theory for women with postpartum depression after cesarean delivery may inform nursing interventions for women with postpartum depression. AIM: To explore the state of mind and coping style of women with depression after cesarean delivery guided by SOR theory. METHODS: Eighty postpartum depressed women with cesarean delivery admitted to the hospital between January 2022 and October 2023 were selected and divided into two groups of 40 cases each, according to the random number table method. In the control group, the observation group adopted the problem-solving nursing model under SOR theory. The two groups were consecutively intervened for 12 weeks, and the state of mind, coping styles, and degree of post-partum depression were analyzed at the end of the intervention. RESULTS: The Edinburgh Postnatal Depression Scale and Hamilton Depression Scale-24-item scores of the observation group were lower than in the control group after care, and the level of improvement in the state of mind was higher than that of the control group (P < 0.05). The level of coping with illness in the observation group after care (26.48 ± 3.35) was higher than that in the control group (21.73 ± 3.20), and the level of avoidance (12.04 ± 2.68) and submission (8.14 ± 1.15) was lower than that in the control group (15.75 ± 2.69 and 9.95 ± 1.20), with significant differences (P < 0.05). CONCLUSION: Adopting the problem-solving nursing model using SOR theory for postpartum depressed mothers after cesarean delivery reduced maternal depression, improved their state of mind, and coping level with illness.

Development and validation of machine learning models to predict MDRO colonization or infection on ICU admission by using electronic health record data.

BACKGROUND: Multidrug-resistant organisms (MDRO) pose a significant threat to public health. Intensive Care Units (ICU), characterized by the extensive use of antimicrobial agents and a high prevalence of bacterial resistance, are hotspots for MDRO proliferation. Timely identification of patients at high risk for MDRO can aid in curbing transmission, enhancing patient outcomes, and maintaining the cleanliness of the ICU environment. This study focused on developing a machine learning (ML) model to identify patients at risk of MDRO during the initial phase of their ICU stay. METHODS: Utilizing patient data from the First Medical Center of the People's Liberation Army General Hospital (PLAGH-ICU) and the Medical Information Mart for Intensive Care (MIMIC-IV), the study analyzed variables within 24 h of ICU admission. Machine learning algorithms were applied to these datasets, emphasizing the early detection of MDRO colonization or infection. Model efficacy was evaluated by the area under the receiver operating characteristics curve (AUROC), alongside internal and external validation sets. RESULTS: The study evaluated 3,536 patients in PLAGH-ICU and 34,923 in MIMIC-IV, revealing MDRO prevalence of 11.96% and 8.81%, respectively. Significant differences in ICU and hospital stays, along with mortality rates, were observed between MDRO positive and negative patients. In the temporal validation, the PLAGH-ICU model achieved an AUROC of 0.786 [0.748, 0.825], while the MIMIC-IV model reached 0.744 [0.723, 0.766]. External validation demonstrated reduced model performance across different datasets. Key predictors included biochemical markers and the duration of pre-ICU hospital stay. CONCLUSIONS: The ML models developed in this study demonstrated their capability in early identification of MDRO risks in ICU patients. Continuous refinement and validation in varied clinical contexts remain essential for future applications.

A novel HLA-DRB4 allele, HLA-DRB4*01:179.

One nucleotide substitution in codon 30 of HLA-DRB4*01:03:01:01 results in a novel allele, HLA-DRB4*01:179.

Screening of key modules and key genes in the prevention of skin cancer development based on gene volcano plot and WGCNA.

BACKGROUND: Skin cancer, a prevalent form of cancer that is on the rise worldwide, requires proactive prevention strategies to reduce the burden of screening, treatment, and mortality. The KEGG research highlighted the significant involvement of red module genes in protein digestion and absorption. These findings provide valuable insights into the underlying molecular mechanisms associated with skin cancer susceptibility, offering potential targets for further research and development of preventive strategies. MATERIALS AND METHODS: Hub genes numbered 130. "limma" in R found 600 DEGs from GSE66359 dataset. DEGs are enriched in BP: chromosome segregation, CC: chromosomal region, and MF: DNA replication origin binding, according to GO analysis. Cell cycle was enriched in DEGs by KEGG and GSEA. Finally, significant genes were COL5A1, CTHRC1, ECM1, FSTL1, KDELR3, and WIPI1. RESULTS: ECM1 and WIPI1 greatly prevented skin cancer. This study created a coexpression network using WGCNA to investigate skin cancer susceptibility modules and cardiovascular disease genes. CONCLUSION: Our study finds a module and many important genes that are essential building blocks in the etiology of skin cancer, which may help us understand the molecular mechanisms of disease prevention.

Direct oral anticoagulants in the treatment of chronic thromboembolic pulmonary hypertension patients: A retrospective cohort study.

INTRODUCTION: Direct oral anticoagulants (DOACs) are increasingly prescribed for life-long anticoagulation in chronic thromboembolic pulmonary hypertension (CTEPH) patients, despite not being recommended in the guidelines. This study aims to evaluate the efficacy and safety of DOACs in CTEPH patients. METHODS: From May 2013 to December 2022, patients who were first diagnosed with CTEPH in Fuwai Hospital and started long-term anticoagulation treatment with warfarin or DOACs were retrospectively included and followed up until (1) death, (2) transition to other kinds of anticoagulants, or (3) discontinuation of anticoagulation. Propensity score matching was used to balance confounding bias of baseline characteristics. All-cause death, major bleeding, clinically relevant nonmajor bleeding and venous thromboembolism (VTE) recurrence were obtained and analysed. RESULTS: After propensity score matching, 115 patients taking warfarin and 206 patients taking DOACs were included in our study and followed up for 5.5 [3.4, 7.1] years. There was no significant difference of survival between the warfarin and the DOAC group (p = 0.77). The exposure adjusted event rate of major bleeding (0.3 %/person-year vs 0.4 %/person-year, p = 0.705) and clinically relevant nonmajor bleeding (3.1 %/person-year vs 3.2 %/person-year, p > 0.999) was similar between two groups. The exposure adjusted rate of VTE recurrence was significantly higher in the DOAC group (1.5 %/person-year vs 0.3 %/person-year, p = 0.030). CONCLUSION: In anticoagulation of CTEPH patients, DOACs have similar survival rate, similar risk of bleeding but higher risk of VTE recurrence than warfarin.

Echocardiography of persistent fifth aortic arch confirmed by computed tomography angiography or surgery in children: a case series.

BACKGROUND: The purpose of this study was to review echocardiography-based diagnosis of persistent fifth aortic arch (PFAA) in children. METHODS: From January 2015 to December 2022, we retrospectively analyzed the echocardiographic findings and the relevant clinical data during follow-up of patients with PFAA who were treated in the Third Affiliated Hospital of Zhengzhou University. The diagnosis was confirmed by computed tomography angiography or surgery. RESULTS: Seven PFAA cases included two Weinberg type A and five Weinberg type B. The anatomical details of PFAA were assessed using a combination of the long-axis view of the left ventricular outflow tract (from the left high parasternal window) and the long-axis view of the aortic arch (from the suprasternal window). In Weinberg type A, the distal fifth and fourth aortic arches were connected to the descending aorta, which was associated with aortic coarctation. In Weinberg type B, the upper arch of the fourth aorta was interrupted, and only the lower arch of the fifth aorta was connected to the descending aorta. Surgical repair of PFAA was indicated in five patients with blood flow disruption, among which four had good postoperative results and one refused surgery. Two patients with unobstructed PFAA blood flow required follow-up rather than surgery. CONCLUSIONS: It is feasible to diagnose PFAA by echocardiography. Combined application of the high parasternal left ventricular outflow tract view and the suprasternal aortic arch view can improve timely detection of different types of PFAA in children.

Towards simulation optimization of subway station considering refined passenger behaviors.

The escalating passenger flow in subway systems presents significant challenges to station facilities during peak hours. Poorly designed station facilities can reduce passenger throughput efficiency and compromise passenger safety. This study conducts on-site investigations to extract refined parameters of passenger behaviors in security check and ticket checking areas. Using Beijing Subway Yizhuang Line Ciqunan Station as a case study, a microscopic simulation model is developed to replicate pedestrian flow within the subway station. By focusing on passenger demand and traffic organization, the layout of station facilities is regulated and optimized. After optimization, the passenger density in the security check and ticket inspection areas during the morning peak period decreased from 1.33 people/m2 to 1.00 people/m2; the longest queue length on the east side decreased from 15 people to 10 people, and the maximum queue length on the west side decreased from 7 people to 3 people. During peak hours, the dispersal time of passenger flow on the west side when entering the station decreased from 31.56 minutes to 30.04 minutes, and on the east side, it decreased from 36.12 minutes to 30.87 minutes. The optimization results effectively improved the efficiency of entering the station during peak hours.

Construction of high-density genetic map based on SLAF-seq and QTL analysis of major traits in sweetpotato [Ipomoea batatas (L.) Lam.].

Sweetpotato, Ipomoea batatas (L.) Lam., is an important worldwide crop used as feed, food, and fuel. However, its polyploidy, high heterozygosity and self-incompatibility makes it difficult to study its genetics and genomics. Longest vine length (LVL), yield per plant (YPP), dry matter content (DMC), starch content (SC), soluble sugar content (SSC), and carotenoid content (CC) are some of the major agronomic traits being used to evaluate sweetpotato. However limited research has actually examined how these traits are inherited. Therefore, after selecting 212 F1 from a Xin24 × Yushu10 crossing as the mapping population, this study applied specific-locus amplified fragment sequencing (SLAF-seq), at an average sequencing depth of 26.73 × (parents) and 52.25 × (progeny), to detect single nucleotide polymorphisms (SNPs). This approach generated an integrated genetic map of length 2441.56 cM and a mean distance of 0.51 cM between adjacent markers, encompassing 15 linkage groups (LGs). Based on the linkage map, 26 quantitative trait loci (QTLs), comprising six QTLs for LVL, six QTLs for YPP, ten QTLs for DMC, one QTL for SC, one QTL for SSC, and two QTLs for CC, were identified. Each of these QTLs explained 6.3-10% of the phenotypic variation. It is expected that the findings will be of benefit for marker-assisted breeding and gene cloning of sweetpotato.

Performance of Nitrogen-Doped Carbon Nanoparticles Carrying FeNiCu as Bifunctional Electrocatalyst for Rechargeable Zinc-Air Battery.

Catalysts for zinc-air batteries (ZABs) must be stable over long-term charging-discharging cycles and exhibit bifunctional catalytic activity. In this study, by doping nitrogen-doped carbon (NC) materials with three metal atoms (Fe, Ni, and Cu), a single-atom-distributed FeNiCu-NC bifunctional catalyst is prepared. The catalyst includes Fe(Ni-doped)-N4 for the oxygen evolution reaction (OER), Fe(Cu-doped)-N4 for the oxygen reduction reaction (ORR), and the NiCu-NC catalytic structure for the oxygen reduction reaction (ORR) in the nitrogen-doped carbon nanoparticles. This single-atom distribution catalyst structure enhances the bifunctional catalytic activity. If a trimetallic single-atom catalyst is designed, it will surpass the typical bimetallic single-atom catcalyst. FeNiCu-NC exhibits outstanding performance as an electrocatalyst, with a half-wave potential (E1/2) of 0.876 V versus RHE, overpotential (Ej = 10) of 253 mV versus RHE at 10 mA cm-2, and a small potential gap (ΔE = 0.61 V). As the anode in a ZAB, FeNiCu-NC can undergo continuous charge-discharged cycles for 575 h without significant attenuation. This study presents a new method for achieving high-performance, low-cost ZABs via trimetallic single-atom doping.

A "One-Step" Strategy for the Global Characterization of Core-Fucosylated Glycoproteome.

Core fucosylation, a special type of N-linked glycosylation, is important in tumor proliferation, invasion, metastatic potential, and therapy resistance. However, the core-fucosylated glycoproteome has not been extensively profiled due to the low abundance and poor ionization efficiency of glycosylated peptides. Here, a "one-step" strategy has been described for protein core-fucosylation characterization in biological samples. Core-fucosylated peptides can be selectively labeled with a glycosylated probe, which is linked with a temperature-sensitive poly(N-isopropylacrylamide) (PNIPAM) polymer, by mutant endoglycosidase (EndoF3-D165A). The labeled probe can be further removed by wild-type endoglycosidase (EndoF3) in a traceless manner for mass spectrometry (MS) analysis. The feasibility and effectiveness of the "one-step" strategy are evaluated in bovine serum albumin (BSA) spiked with standard core-fucosylated peptides, H1299, and Jurkat cell lines. The "one-step" strategy is then employed to characterize core-fucosylated sites in human lung adenocarcinoma, resulting in the identification of 2494 core-fucosylated sites distributed on 1176 glycoproteins. Further data analysis reveals that 196 core-fucosylated sites are significantly upregulated in tumors, which may serve as potential drug development targets or diagnostic biomarkers. Together, this "one-step" strategy has great potential for use in global and in-depth analysis of the core-fucosylated glycoproteome to promote its mechanism research.

Advances in the Application of AI Robots in Critical Care: Scoping Review.

BACKGROUND: In recent epochs, the field of critical medicine has experienced significant advancements due to the integration of artificial intelligence (AI). Specifically, AI robots have evolved from theoretical concepts to being actively implemented in clinical trials and applications. The intensive care unit (ICU), known for its reliance on a vast amount of medical information, presents a promising avenue for the deployment of robotic AI, anticipated to bring substantial improvements to patient care. OBJECTIVE: This review aims to comprehensively summarize the current state of AI robots in the field of critical care by searching for previous studies, developments, and applications of AI robots related to ICU wards. In addition, it seeks to address the ethical challenges arising from their use, including concerns related to safety, patient privacy, responsibility delineation, and cost-benefit analysis. METHODS: Following the scoping review framework proposed by Arksey and O'Malley and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a scoping review to delineate the breadth of research in this field of AI robots in ICU and reported the findings. The literature search was carried out on May 1, 2023, across 3 databases: PubMed, Embase, and the IEEE Xplore Digital Library. Eligible publications were initially screened based on their titles and abstracts. Publications that passed the preliminary screening underwent a comprehensive review. Various research characteristics were extracted, summarized, and analyzed from the final publications. RESULTS: Of the 5908 publications screened, 77 (1.3%) underwent a full review. These studies collectively spanned 21 ICU robotics projects, encompassing their system development and testing, clinical trials, and approval processes. Upon an expert-reviewed classification framework, these were categorized into 5 main types: therapeutic assistance robots, nursing assistance robots, rehabilitation assistance robots, telepresence robots, and logistics and disinfection robots. Most of these are already widely deployed and commercialized in ICUs, although a select few remain under testing. All robotic systems and tools are engineered to deliver more personalized, convenient, and intelligent medical services to patients in the ICU, concurrently aiming to reduce the substantial workload on ICU medical staff and promote therapeutic and care procedures. This review further explored the prevailing challenges, particularly focusing on ethical and safety concerns, proposing viable solutions or methodologies, and illustrating the prospective capabilities and potential of AI-driven robotic technologies in the ICU environment. Ultimately, we foresee a pivotal role for robots in a future scenario of a fully automated continuum from admission to discharge within the ICU. CONCLUSIONS: This review highlights the potential of AI robots to transform ICU care by improving patient treatment, support, and rehabilitation processes. However, it also recognizes the ethical complexities and operational challenges that come with their implementation, offering possible solutions for future development and optimization.

Subthalamic nucleus-language network connectivity predicts dopaminergic modulation of speech function in Parkinson's disease.

Speech impediments are a prominent yet understudied symptom of Parkinson's disease (PD). While the subthalamic nucleus (STN) is an established clinical target for treating motor symptoms, these interventions can lead to further worsening of speech. The interplay between dopaminergic medication, STN circuitry, and their downstream effects on speech in PD is not yet fully understood. Here, we investigate the effect of dopaminergic medication on STN circuitry and probe its association with speech and cognitive functions in PD patients. We found that changes in intrinsic functional connectivity of the STN were associated with alterations in speech functions in PD. Interestingly, this relationship was characterized by altered functional connectivity of the dorsolateral and ventromedial subdivisions of the STN with the language network. Crucially, medication-induced changes in functional connectivity between the STN's dorsolateral subdivision and key regions in the language network, including the left inferior frontal cortex and the left superior temporal gyrus, correlated with alterations on a standardized neuropsychological test requiring oral responses. This relation was not observed in the written version of the same test. Furthermore, changes in functional connectivity between STN and language regions predicted the medication's downstream effects on speech-related cognitive performance. These findings reveal a previously unidentified brain mechanism through which dopaminergic medication influences speech function in PD. Our study sheds light into the subcortical-cortical circuit mechanisms underlying impaired speech control in PD. The insights gained here could inform treatment strategies aimed at mitigating speech deficits in PD and enhancing the quality of life for affected individuals.

The relationship between screen time and gross motor movement: A cross-sectional study of pre-school aged left-behind children in China.

OBJECTIVE: To investigate the level of screen time and gross motor movement level and the correlation between them in left-behind children aged 3 to 6 years old in China. METHODS: A randomized whole-group sampling method was used to study 817 left-behind children aged 3-6 years in 15 kindergartens in Xiangcheng city, Henan province. The third version of the Test of Gross Motor Development (TGMD-3) was used to test the children's gross motor movement level, and the screen time questionnaire was used to test the children's screen time level. The relationship between the two and the indicators was explored using Pearson's two-sided correlation and multilevel regression. RESULTS: The average daily screen time of left-behind children aged 3-6 years old increased with age, and the reporting rate of >2 h/d ranged from 22.43% to 33.73%; gross motor movement of left-behind children aged 3-6 years old increased with age, with significant differences between age (p<0.05). There was a low to moderate negative correlation (r = -0.133 to -0.354, p<0.05) between screen time and gross motor movement in children aged 3-6 years, and multiple regression analysis showed that screen time was predictive of gross motor movement in children (p<0.05), with an explanation rate of 21.4%. CONCLUSION: There is a correlation between screen time and gross motor movement development in children aged 3-6 years old left behind, and the gross motor movement ability of children aged 3-6 years old can be developed by reducing screen time and increasing physical activity.

Ferrocene-Based Antioxidant Self-Healing Hydrogel via the Biginelli Reaction for Wound Healing.

The development of antioxidant wound dressings to remove excessive free radicals around wounds is essential for wound healing. In this study, we developed an efficient strategy to prepare antioxidant self-healing hydrogels as wound dressings by combining multicomponent reactions (MCRs) and postpolymerization modification. A polymer containing ferrocene and phenylboronic acid groups was developed via the Biginelli reaction, followed by efficient modification. This polymer is antioxidant due to its ferrocene moieties and can rapidly cross-link poly(vinyl alcohol) to realize an antioxidant self-healing hydrogel through dynamic borate ester linkages. This hydrogel has low cytotoxicity and is biocompatible. In in vivo experiments, this hydrogel is superior to existing clinical dressings in promoting wound healing. This study demonstrates the value of the Biginelli reaction in exploring biomaterials, potentially offering insights into the design of other multifunctional polymers and related materials using different MCRs.

Effects of silencing NLRP3 gene on proliferation of psoriasis-like HaCaT cells and expressions of cytokines.

We aimed to explore the effects of silencing NOD-like receptor protein 3 (NLRP3) on proliferation of psoriasis-like HaCaT cells and expressions of cytokines. HaCaT cells were treated with human keratinocyte growth factor (KGF) and were divided into KGF group, negative control group, NLRP3-RNAi group and control group. Cells proliferation was detected by CCK8, cell clone formation rate was detected by clone formation assay, distribution of cells cycle was detected by flow cytometry, expressions of cyclin B1 (Cyclin B1), cyclin-dependent kinase 2 (CDK2), Ki67 and proliferating cell nuclear antigen (PCNA) proteins were detected by Western blot, and levels of interleukin (IL)-17, IL-23, IL-6 and tumor necrosis factor α (TNF-α) were detected by enzyme-linked immunosorbent assay. Compared with control group, expressions of NLRP3 mRNA and protein, proliferation rate and clonal formation rate were increased in KGF group, percentage of cells in G0/G1 phase was decreased, percentage of cells in S phase was increased, expressions of Cyclin B1, CDK2, Ki67 and PCNA proteins were increased, and levels of IL-17, IL-23, IL-6 and TNF-α were increased. Compared with negative control group, expressions of NLRP3 mRNA and protein, proliferation rate and clonal formation rate were decreased in NLRP3-RNAi group, percentage of cells in G0/G1 phase was increased, percentage of cells in S phase was decreased, expressions of Cyclin B1, CDK2, Ki67 and PCNA proteins were decreased, and levels of IL-17, IL-23, IL-6 and TNF-α were decreased. Silencing NLRP3 gene can inhibit the proliferation of psoriasis-like HaCaT cells, arrest cell cycle, inhibit the expressions of cell proliferation-related proteins and reduce levels of pro-inflammatory factors.

[Determination of 21 organophosphate esters and their metabolites in drinking water by automatic solid phase extraction-liquid chromatography-tandem mass spectrometry].

OBJECTIVE: To establish a method for simultaneous determination of 21 organophosphate esters(OPEs) and their metabolites in drinking water by automatic solid phase extraction-liquid chromatography-tandem mass spectrometry. METHODS: The drinking water was purified by automatic solid phase extraction with HLB column, eluted by methanol, determined by liquid chromatography tandem mass spectrometry with ACQUITY UPLC BEH(100 mm×2.1mm, 1.7 µm) column, and quantified by internal standard method. RESULTS: The optimized method could simultaneously detect 21 organophosphate esters and their metabolites in drinking water. The detection limit was 0.01-0.24 ng/L, the quantitation limit was 0.03-0.77 ng/L. The recovery range was 57.6%-121.2% and the relative standard deviation is 1.2%-11.1% when the concentration was 0.8-20 ng/L. Senventeen tap water and 30 packaged drinking water collected by the supermarket were measured. The ΣOPEs range was 16.8-177 ng/L, and the Σdi-OPEs range was 0.328-16.3ng/L, indicating the exposure risk of organophosphates and their metabolites in water. CONCLUSION: The pretreatment of the method is simple, automatic and sensitive, and is suitable for simultaneous high-throughput determination of organophosphate esters and their metabolites in large quantities of drinking water.

Comparison of the activation level in the sensorimotor cortex between motor point and proximal nerve bundle electrical stimulation.

Objective.Neuromuscular electrical stimulation (NMES) is widely used for motor function rehabilitation in stroke survivors. Compared with the conventional motor point (MP) stimulation, the stimulation at the proximal segment of the peripheral nerve (PN) bundles has been demonstrated to have multiple advantages. However, it is not known yet whether the PN stimulation can increase the cortical activation level, which is crucial for motor function rehabilitation.Approach.The current stimuli were delivered transcutaneously at the muscle belly of the finger flexors and the proximal segment of the median and ulnar nerves, respectively for the MP and PN stimulation. The stimulation intensity was determined to elicit the same contraction levels between the two stimulation methods in 18 healthy individuals and a stroke patient. The functional near-infrared spectroscopy and the electromyogram were recorded to compare the activation pattern of the sensorimotor regions and the target muscles.Main Results.For the healthy subjects, the PN stimulation induced significantly increased concentration of the oxygenated hemoglobin in the contralateral sensorimotor areas, and enhanced the functional connectivity between brain regions compared with the MP stimulation. Meanwhile, the compound action potentials had a smaller amplitude and the H-reflex became stronger under the PN stimulation, indicating that more sensory axons were activated in the PN stimulation. For the stroke patient, the PN stimulation can elicit finger forces and induce activation of both the contralateral and ipsilateral motor cortex.Conclusions. Compared with the MP stimulation, the PN stimulation can induce more cortical activation in the contralateral sensorimotor areas possibly via involving more activities in the central pathway.Significance.This study demonstrated the potential of the PN stimulation to facilitate functional recovery via increasing the cortical activation level, which may help to improve the outcome of the NMES-based rehabilitation for motor function recovery after stroke.