Development and validation of a nomogram for predicting critical respiratory events during early anesthesia recovery in elderly patients.

BACKGROUND: Elderly patients undergoing recovery from general anesthesia face a heightened risk of critical respiratory events (CREs). Despite this, there is a notable absence of effective predictive tools tailored to this specific demographic. This study aims to develop and validate a predictive model (nomogram) to address this gap. CREs pose significant risks to elderly patients during the recovery phase from general anesthesia, making it an important issue in perioperative care. With the increasing aging population and the complexity of surgical procedures, it is crucial to develop effective predictive tools to improve patient outcomes and ensure patient safety during post-anesthesia care unit (PACU) recovery. METHODS: A total of 324 elderly patients who underwent elective general anesthesia in a grade A tertiary hospital from January 2023 to June 2023 were enrolled. Risk factors were identified using least absolute shrinkage and selection operator (LASSO) regression. A multivariate logistic regression model was constructed and represented as a nomogram. Internal validation of the model was performed using Bootstrapping. This study followed the TRIPOD checklist for reporting. RESULTS: The indicators included in the nomogram were frailty, snoring, patient-controlled intravenous analgesia (PCIA), emergency delirium and cough intensity at extubation. The diagnostic performance of the nomogram model was satisfactory, with AUC values of 0.990 and 0.981 for the training set and internal validation set, respectively. The optimal cutoff value was determined to be 0.22, based on a Youden index of 0.911. The F1-score was 0.927, and the MCC was 0.896. The calibration curve, Brier score (0.046), and HL test demonstrated acceptable consistency between the predicted and actual results. DCA revealed high net benefits of the nomogram prediction across all threshold probabilities. CONCLUSIONS: This study developed and validated a nomogram to identify elderly patients in the PACU who are at higher risk of CREs. The identified predictive factors included frailty condition, snoring syndrome, PCIA, emergency delirium, and cough intensity at extubation. By identifying patients at higher risk of CREs early on, medical professionals can implement targeted strategies to mitigate the occurrence of complications and provide better postoperative care for elderly patients recovering from general anesthesia.

Prediction models for acute kidney injury following liver transplantation: A systematic review and critical appraisal.

OBJECTIVE: This study aims to systematically review and critical evaluation of the risk of bias and the applicability of existing prediction models for acute kidney injury post liver transplantation. DATA SOURCE: A comprehensive literature search up until February 7, 2024, was conducted across nine databases: PubMed, Web of Science, EBSCO CINAHL Plus, Embase, Cochrane Library, CNKI, Wanfang, CBM, and VIP. STUDY DESIGN: Systematic review of observational studies. EXTRACTION METHODS: Literature screening and data extraction were independently conducted by two researchers using a standardized checklist designed for the critical appraisal of prediction modelling studies in systematic reviews. The prediction model risk of bias assessment tool was utilized to assess both the risk of bias and the models' applicability. PRINCIPAL FINDINGS: Thirty studies were included, identifying 34 prediction models. External validation was conducted in seven studies, while internal validation exclusively took place in eight studies. Three models were subjected to both internal and external validation, the area under the curve ranging from 0.610 to 0.921. A meta-analysis of high-frequency predictors identified several statistically significant factors, including recipient body mass index, Model for End-stage Liver Disease score, preoperative albumin levels, international normalized ratio, and surgical-related factors such as cold ischemia time. All studies were demonstrated a high risk of bias, mainly due to the use of unsuitable data sources and inadequate detail in the analysis reporting. CONCLUSIONS: The evaluation with prediction model risk of bias assessment tool indicated a considerable bias risk in current predictive models for acute kidney injury post liver transplantation. IMPLICATIONS FOR CLINICAL PRACTICE: The recognition of high bias in existing models calls for future research to employ rigorous methodologies and robust data sources, aiming to develop and validate more accurate and clinically applicable predictive models for acute kidney injury post liver transplantation.

Clinical Impact of Operating Room Nursing Pathways on Hospitalization Duration and Consciousness Status in Patients Undergoing Emergency Craniocerebral Injury Surgery.

Background: Craniocerebral injuries carry high disability and mortality rates. In clinical practice, timely determination of the condition and immediate rescue interventions are crucial for patients with emergency craniocerebral injuries. Nurses play a pivotal role in providing proactive nursing services to save patients' lives. Objective: This study aims to examine the practical implications of implementing operating room nursing pathways in the care of patients undergoing emergency craniocerebral injury surgery. Design: A randomized controlled study was conducted. Setting: The study was conducted at the Department of Operating Room at Run Run Shaw Hospital, affiliated with Zhejiang University School of Medicine. Participants: A total of 80 patients undergoing emergency craniocerebral injury surgery in our hospital from August 2020 to August 2022 were included. They were randomly divided into control and observation groups through a lottery, with 40 cases in each. Interventions: The control group received conventional nursing, while the observation group received operating room nursing pathways. Primary Outcome Measures: (1) Surgical preparation time, surgical time, and hospitalization time; (2) Pupil scores; (3) Brain injury grading; and (4) Nursing satisfaction score. Results: The observation group exhibited a significant decrease in surgical preparation time and hospitalization time compared to the control group (P < .05). After the intervention, severe craniocerebral injury pupil scores in the observation group showed improvement compared to the control group (P < .05). The total satisfaction rate in the observation group (92.5%) was higher than that in the control group (80.0%) (P = .012). Conclusions: The application of operating room nursing pathways in patients undergoing emergency craniocerebral injury surgery can lead to a shortened length of stay, substantial improvement in patients' consciousness status, and high satisfaction rates from both patients and their family members. This intervention holds significant clinical value and merits further promotion.

Prediction models for amputation after diabetic foot: systematic review and critical appraisal.

BACKGROUND: Numerous studies have developed or validated prediction models aimed at estimating the likelihood of amputation in diabetic foot (DF) patients. However, the quality and applicability of these models in clinical practice and future research remain uncertain. This study conducts a systematic review and assessment of the risk of bias and applicability of amputation prediction models among individuals with DF. METHODS: A comprehensive search was conducted across multiple databases, including PubMed, Web of Science, EBSCO CINAHL Plus, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang, Chinese Biomedical Literature Database (CBM), and Weipu (VIP) from their inception to December 24, 2023. Two investigators independently screened the literature and extracted data using the checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was employed to evaluate both the risk of bias and applicability. RESULTS: A total of 20 studies were included in this analysis, comprising 17 development studies and three validation studies, encompassing 20 prediction models and 11 classification systems. The incidence of amputation in patients with DF ranged from 5.9 to 58.5%. Machine learning-based methods were employed in more than half of the studies. The reported area under the curve (AUC) varied from 0.560 to 0.939. Independent predictors consistently identified by multivariate models included age, gender, HbA1c, hemoglobin, white blood cell count, low-density lipoprotein cholesterol, diabetes duration, and Wagner's Classification. All studies were found to exhibit a high risk of bias, primarily attributed to inadequate handling of outcome events and missing data, lack of model performance assessment, and overfitting. CONCLUSIONS: The assessment using PROBAST revealed a notable risk of bias in the existing prediction models for amputation in patients with DF. It is imperative for future studies to concentrate on enhancing the robustness of current prediction models or constructing new models with stringent methodologies.

Tumor cells impair immunological synapse formation via central nervous system-enriched metabolite.

Tumors employ various strategies to evade immune surveillance. Central nervous system (CNS) has multiple features to restrain immune response. Whether tumors and CNS share similar programs of immunosuppression is elusive. Here, we analyze multi-omics data of tumors from HER2+ breast cancer patients receiving trastuzumab and anti-PD-L1 antibody and find that CNS-enriched N-acetyltransferase 8-like (NAT8L) and its metabolite N-acetylaspartate (NAA) are overexpressed in resistant tumors. In CNS, NAA is released during brain inflammation. NAT8L attenuates brain inflammation and impairs anti-tumor immunity by inhibiting cytotoxicity of natural killer (NK) cells and CD8+ T cells via NAA. NAA disrupts the formation of immunological synapse by promoting PCAF-induced acetylation of lamin A-K542, which inhibits the integration between lamin A and SUN2 and impairs polarization of lytic granules. We uncover that tumor cells mimic the anti-inflammatory mechanism of CNS to evade anti-tumor immunity and NAT8L is a potential target to enhance efficacy of anti-cancer agents.

Causal associations between modifiable risk factors and isolated REM sleep behavior disorder: a mendelian randomization study.

Objectives: This Mendelian randomization (MR) study identified modifiable risk factors for isolated rapid eye movement sleep behavior disorder (iRBD). Methods: Genome-wide association study (GWAS) datasets for 29 modifiable risk factors for iRBD in discovery and replication stages were used. GWAS data for iRBD cases were obtained from the International RBD Study Group. The inverse variance weighted (IVW) method was primarily employed to explore causality, with supplementary analyses used to verify the robustness of IVW findings. Co-localization analysis further substantiated causal associations identified via MR. Genetic correlations between mental illness and iRBD were identified using trait covariance, linkage disequilibrium score regression, and co-localization analyses. Results: Our study revealed causal associations between sun exposure-related factors and iRBD. Utilizing sun protection (odds ratio [OR] = 0.31 [0.14, 0.69], p = 0.004), ease of sunburn (OR = 0.70 [0.57, 0.87], p = 0.001), childhood sunburn occasions (OR = 0.58 [0.39, 0.87], p = 0.008), and phototoxic dermatitis (OR = 0.78 [0.66, 0.92], p = 0.003) decreased iRBD risk. Conversely, a deep skin color increased risk (OR = 1.42 [1.04, 1.93], p = 0.026). Smoking, alcohol consumption, low education levels, and mental illness were not risk factors for iRBD. Anxiety disorders and iRBD were genetically correlated. Conclusion: Our study does not corroborate previous findings that identified smoking, alcohol use, low education, and mental illness as risk factors for iRBD. Moreover, we found that excessive sun exposure elevates iRBD risk. These findings offer new insights for screening high-risk populations and devising preventive measures.

Deciphering prognostic indicators in AQP4-IgG-seropositive neuromyelitis optica spectrum disorder: An integrative review of demographic and laboratory factors.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a group of inflammatory diseases affecting the central nervous system, characterized by optic neuritis and myelitis. The complex nature of NMOSD and varied patient response necessitates personalized treatment and efficient patient stratification strategies. OBJECTIVE: To provide a comprehensive review of recent advances in clinical and biomarker research related to aquaporin-4 (AQP4)-immunoglobulin G (IgG)-seropositive NMOSD prognosis and identify key areas for future research. METHODS: A comprehensive review and synthesis of recent literature were conducted, focusing on demographic factors and laboratory investigations. RESULTS: Demographic factors, such as age, ethnicity, and sex, influence NMOSD prognosis. Key biomarkers for NMOSD prognosis include homocysteine, antinuclear antibodies, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, thyroid hormone levels, neurofilament light chain levels, and serum glial fibrillary acidic protein might also predict NMOSD attack prognosis. CONCLUSION: Further investigation is required to understand sex-related disparities and biomarker inconsistencies. Identification and understanding of these factors can aid in the development of personalized therapeutic strategies, thereby improving outcomes for NMOSD patients. Future studies should focus on unifying research design for consistent results.

High mobility group box 1 promotes endometriosis under hypoxia by regulating inflammation and autophagy in vitro and in vivo.

BACKGROUND: Endometriosis is a chronic disease. Our previous study identified a positive correlation between high mobility group box 1 (HMGB1) and endometriosis, and HMGB1 and inflammation. However, the precise roles of HMGB1 in endometriosis are not fully elucidated. METHODS: We overexpressed HMGB1 in human endometrial stromal cells (HESCs). The expression of pro-inflammatory cytokines and autophagy-related markers were detected by Western blot and ELISA. We generated HMGB1 deficient mice and established the murine model of endometriosis. The development of endometriosis was evaluated. The expression of cytokines and markers of autophagy in implant lesions and mouse endometrial stromal cells was measured. RESULTS: Overexpression of HMGB1 in HESCs promoted the pro-inflammatory cytokines production and expression of autophagy-related markers. HMGB1 deficient mice had less implant lesions, decreased inflammatory cytokines level and down-regulated autophagy-related markers in implant lesions and mouse endometrial stromal cells. CONCLUSION: HMGB1 promotes endometriosis by regulating inflammation and autophagy.

The gene polymorphisms of eNOS and MTHFR modulates the development of preeclampsia in Han population.

We explored the effects of the endothelial nitric oxide synthase (eNOS) gene -786 T > C and 894 G > T locus polymorphisms and the methylenetetrahydrofolate reductase (MTHFR) gene 1298 A > C and 677 C > T locus polymorphisms on preeclampsia (PE) in pregnant women in Quanzhou area and provide reliable and stable predictors PE. This study included 160 normal pregnant women (normal control group) and 160 women with preeclampsia (PE group). Polymorphisms in eNOS gene and MTHFR were analyzed by the polymerase chain reaction/restriction fragment length polymorphism (PCR/RFLP) technique. eNOS 894 G > T locus and MTHFR 1298 A > C locus had no significant difference between the two groups. In the PE patients, eNOS -786 T allele (OR: 2.07, p = 0.03) and MTHFR 677 C allele (OR: 1.83, p = 0.04) had significantly lower frequency. The nitric oxide (NO) level in patients with eNOS -786 C C was significantly lower than that in those with -786 TT. The homocysteine (Hcy) level in patients with MTHFR 677 TT was significantly higher than that in those with 677 C C. In conclusion, the frequency of the eNOS -786 C C genotype and MTHFR 677 TT genotype are higher in women with PE, which cause lower NO level and higher Hcy level.

Are Physical Sunscreens Safe for Marine Life? A Study on a Coral-Zooxanthellae Symbiotic System.

Limited toxic and ecological studies were focused on physical sunscreen that is considered to have "safer performance", in which nanosize zinc oxide (nZnO) and nanosize titanium dioxide (nTiO2) generally are added as ultraviolet filters. Herein, the common button coral Zoanthus sp. was newly used to assess the toxic effects and underlying mechanisms of physical sunscreen. Results showed that physical sunscreen induced severe growth inhibition effects and largely compelled the symbiotic zooxanthellae, indicating that their symbiotic systems were threatened and, also, that neural and photosynthesis functions were influenced. Zn2+ toxicity and bioaccumulation were identified as the main toxic mechanisms, and nTiO2 particles released from physical sunscreen also displayed limited bioattachment and toxicity. Oxidative stress, determined by increased reactive oxygen species, superoxide dismutase, and malondialdehyde content, was indicated as another important toxic mechanism. Furthermore, when Zoanthus sp. was restored, the inhibited individual coral could be largely recovered after a short (3 d) exposure time; however, a longer exposure time damaged the coral irretrievably, which revealed the latent environmental risks of physical sunscreen. This study investigated the toxic effect of physical sunscreen on Zoanthus sp. in a relatively comprehensive manner, thus providing new insights into the toxic response of sunscreen on marine organisms.

A radiomics-clinical combined nomogram-based on non-enhanced CT for discriminating the risk stratification in GISTs.

PURPOSE: To discriminate the risk stratification in gastrointestinal stromal tumors (GISTs) by preoperatively constructing a model of nonenhanced computed tomography (NECT). METHODS: A total of 111 GISTs patients (77 in the training group and 34 in the validation Group) from two hospitals between 2015 and 2022 were collected retrospectively. One thousand and thirty-seven radiomics features were extracted from non-contract CT images, and the optimal radiomics signature was determined by univariate analysis and LASSO regression. The radiomics model was developed and validated from the ten optimal radiomics features by three methods. Covariates (clinical features, CT findings, and immunohistochemical characteristics) were collected to establish the clinical model, and both the radiomics features and the covariates were used to build the combined model. The effectiveness of the three models was evaluated by the Delong test. RESULTS: The experimental results showed that the clinical models (75.3%, 70.6%), the radiomics models (79.2%, 79.4%) and the combined models (81.8%, 82.4%) all had high accuracy in predicting the pathological risk of GIST in both training and validation groups. The AUC values of the combined models were significantly higher in both the training groups (0.921 vs 0.822, p= 0.032) and the validation groups (0.913 vs 0.792, p= 0.019) than that of the clinical models. According to the calibration curve, the combined model nomogram is clinically useful. CONCLUSIONS: The clinical-radiomics combined model and based on NECT performed well in discriminating the risk stratification in GISTs. As a quantitative technique, radiomics is capable of predicting the malignant potential and guiding treatment preoperatively.

Plasma Soluble Podoplanin as a Biomarker of Hypercoagulability and Cellular Immunity Status in Patients With Non-small Cell Lung Cancer.

Podoplanin (PDPN) is known to play a role in thrombosis, metastasis of tumor cells, the epithelial-mesenchymal transition (EMT), and immune response. The present study aim to evaluate the clinical significance of soluble PDPN (sPDPN) in hypercoagulability and cellular immune status in patients with non-small cell lung cancer (NSCLC). Enzyme-linked immunosorbent assay (ELISA) was used to determine plasma sPDPN levels, and T-lymphocyte distribution was determined using flow cytometry. The levels of sPDPN were markedly higher in the NSCLC group than control group, and sPDPN was higher in patients with advanced-stage and with distant metastases. The high-sPDPN group had lower absolute numbers of CD3+, CD4+, and CD4+/CD8+ ratio than low-sPDPN group. Correlation analysis indicated that sPDPN was positively linked to platelet (r = 0.50, P < .001), D-dimer (r = 0.52, P < .001), and fibrinogen (r = 0.37, P < .001); and inversely correlated with CD3+ (r = -0.37, P < .001), CD4+ (r = -0.44, P < .001), and CD4+/CD8+ (r = -0.37, P < .001). Multivariate logistic regression analysis indicated that sPDPN (odds ratio [OR] = 2.293; 95% CI, 1.559-3.373) and tumor stage (OR = 15.857; 95% CI, 1.484-169.401) were separate risk indicators for hypercoagulability. The receiver operating characteristic curves (ROC) indicated that sPDPN had high diagnostic values for hypercoagulability in NSCLC patients. In conclusion, plasma sPDPN was not only linked to hypercoagulability, but it may also be an indicator of the body's cellular immune status in NSCLC patients.

Development and Psychometric Properties of a Scale Measuring Barriers to Perioperative Hypothermia Prevention for Anesthesiologists and Nurses.

PURPOSE: To develop a scale that measures barriers to perioperative hypothermia prevention (BPHP) as perceived by anesthesiologists and nurses. DESIGN: A methodological and prospective psychometric study. METHODS: Based on the theoretical domains framework, the item pool was created through a literature review, qualitative interviews, and expert consultation. The scale was pretested with a sample of 154 key stakeholders in perioperative temperature management and then field tested with 416 anesthesiologists and nurses working at three hospitals in Southeast China. Item analysis, and reliability and validity analysis were performed. FINDINGS: The average content validity index was 0.94. According to exploratory factor analysis, seven factors were obtained that could explain 70.283% of the total variance. Confirmatory factor analysis showed excellent or acceptable goodness-of-fit indices. The reliability analysis demonstrated that the scale had high internal consistency and temporal stability, with Cronbach's α, split-half coefficient and test-retest values of 0.926, 0.878 and 0.835, respectively. CONCLUSIONS: The BPHP scale meets the psychometric criteria for reliability and validity and promises to be a useful quality measure for IPH management during the perioperative period. Further investigations on educational or resource needs and the development of an optimal perioperative hypothermia prevention protocol to narrow the gap between research evidence and clinical practice should be performed.

Tumor Cell-Intrinsic CD96 Mediates Chemoresistance and Cancer Stemness by Regulating Mitochondrial Fatty Acid ß-Oxidation.

Targeting CD96 that originates in immune cells has shown potential for cancer therapy. However, the role of intrinsic CD96 in solid tumor cells remains unknown. Here, it is found that CD96 is frequently expressed in tumor cells from clinical breast cancer samples and is correlated with poor long-term prognosis in these patients. The CD96+ cancer cell subpopulations exhibit features of both breast cancer stem cells and chemoresistance. In vivo inhibition of cancer cell-intrinsic CD96 enhances the chemotherapeutic response in a patient-derived tumor xenograft model. Mechanistically, CD96 enhances mitochondrial fatty acid ß-oxidation via the CD155-CD96-Src-Stat3-Opa1 pathway, which subsequently promotes chemoresistance in breast cancer stem cells. A previously unknown role is identified for tumor cell-intrinsic CD96 and an attractive target in improving the chemotherapeutic response.

VLA-4 suppression by senescence signals regulates meningeal immunity and leptomeningeal metastasis.

Leptomeningeal metastasis is associated with dismal prognosis and has few treatment options. However, very little is known about the immune response to leptomeningeal metastasis. Here, by establishing an immunocompetent mouse model of breast cancer leptomeningeal metastasis, we found that tumor-specific CD8+ T cells were generated in deep cervical lymph nodes (dCLNs) and played an important role in controlling leptomeningeal metastasis. Mechanistically, T cells in dCLNs displayed a senescence phenotype and their recruitment was impaired in mice bearing cancer cells that preferentially colonized in leptomeningeal space. Upregulation of p53 suppressed the transcription of VLA-4 in senescent dCLN T cells and consequently inhibited their migration to the leptomeningeal compartment. Clinically, CD8+ T cells from the cerebrospinal fluid of patients with leptomeningeal metastasis exhibited senescence and VLA-4 downregulation. Collectively, our findings demonstrated that CD8+ T cell immunosenescence drives leptomeningeal metastasis.

CD16+ fibroblasts foster a trastuzumab-refractory microenvironment that is reversed by VAV2 inhibition.

The leukocyte Fcγ receptor (FcγR)-mediated response is important for the efficacy of therapeutic antibodies; however, little is known about the role of FcγRs in other cell types. Here we identify a subset of fibroblasts in human breast cancer that express CD16 (FcγRIII). An abundance of these cells in HER2+ breast cancer patients is associated with poor prognosis and response to trastuzumab. Functionally, upon trastuzumab stimulation, CD16+ fibroblasts reduce drug delivery by enhancing extracellular matrix stiffness. Interaction between trastuzumab and CD16 activates the intracellular SYK-VAV2-RhoA-ROCK-MLC2-MRTF-A pathway, leading to elevated contractile force and matrix production. Targeting of a Rho family guanine nucleotide exchange factor, VAV2, which is indispensable for the function of CD16 in fibroblasts rather than leukocytes, reverses desmoplasia provoked by CD16+ fibroblasts. Collectively, our study reveals a role for the fibroblast FcγR in drug resistance, and suggests that VAV2 is an attractive target to augment the effects of antibody treatments.

Main Features of Business English Translation and Teaching Model Optimization Based on the Logistic Model.

With the continuous development of global trade in recent years, business English has received more and more attention as a medium of communication. Business English is a branch of English, and in order to meet the practical needs in business, business English is involved in various business disciplines from foreign trade to international logistics, to economics, foreign trade correspondence, law, and so on, which need to be translated in a more targeted manner. Therefore, there are many professional tutorials for business English in the market to guide trade personnel in business English translation. Many scholars have also conducted comprehensive studies on business English translation, some starting from its stylistic features and some focusing on translation skills, but fewer scholars have conducted studies on business English translation through models, and there is still a lack of theoretical basis for how to effectively improve the translation of business English. Therefore, in order to reduce the friction between different cultures in trade, promote business English better, and provide convenience for foreign traders, this study will implement the basic principles of "faithfulness, elegance" in English translation, with the aim of improving the practicality and effectiveness of business English, mainly from the main features of business English translation, and then, in the process of analysis, we mainly use the logistic model to analyze the characteristics of business English translation, including timeliness, professionalism, uniqueness, and diversity. The final analysis results show that the influence of professionalism and diversity on the effect of business English translation is more obvious, and we need to carry out a special teaching mode for these two points. The final analysis shows that professionalism and diversity have a significant impact on the effectiveness of business English translation, and special teaching models are needed to optimize these two points.

Negative air ions through the action of antioxidation, anti-inflammation, anti-apoptosis and angiogenesis ameliorate lipopolysaccharide induced acute lung injury and promote diabetic wound healing in rat.

Negative air ions (NAIs) being bioactive and negative charged molecules may confer antioxidant and anti-inflammatory activity. We assessed the effect of NAIs on two inflammatory diseases in animal models including lipopolysaccharide (LPS) induced acute lung injury (ALI) and wound healing in diabetic rats. We used intra-tracheal infusion of LPS to induce ALI and made a full-thickness cutaneous wound in streptozotocin-induced diabetic female Wistar rats. We evaluated NAIs effects on reactive oxygen species amount, leukocyte infiltration, wound healing rate, western blot, and immunohistochemistry in the lungs of ALI and skin sections of wounds. Our data found NAIs exposed saline displayed higher antioxidant activity vs. non-exposed saline. NAIs exposure did not significantly affect arterial blood pressure and respiratory frequency in control and LPS treated groups. LPS increased leukocyte infiltration, caspase 3/Poly-ADP-ribose-polymerase-mediated apoptosis formation and decreased Beclin-1/LC3-II-mediated autophagy in lungs. NAIs exposure conferred pulmonary protection by depressed leukocyte infiltration and caspase 3/Poly-ADP-ribose-polymerase mediated apoptosis and enhanced LC3-II-mediated autophagy in LPS induced ALI. NAIs treatment resulted in a significantly accelerated wound closure rate, decreased erythrocyte accumulation and leukocyte infiltration mediated oxidative stress and inflammation, and upregulated expression of skin collagen, vascular endothelial growth factor receptor-2 (VEGFR-2) and factor transforming growth factor-beta 1 (TGF-ß1) vs non-treated group. Based on these results, it is suggested that NAIs conferred a protection through the upregulating LC3-II-dependent autophagy mechanism and downregulating leukocyte infiltration mediated inflammation and caspase 3/Poly-ADP-ribose-polymerase signaling in the LPS-treated ALI and promoted diabetic wound healing through the enhancing skin collagen synthesis, VEGFR-2 and TGF-ß1 pathways.

Construction of machine learning tools to predict threatened miscarriage in the first trimester based on AEA, progesterone and ß-hCG in China: a multicentre, observational, case-control study.

BACKGROUND: Endocannabinoid anandamide (AEA), progesterone (P4) and ß-human chorionic gonadotrophin (ß-hCG) are associated with the threatened miscarriage in the early stage. However, no study has investigated whether combing these three hormones could predict threatened miscarriage. Thus, we aim to establish machine learning models utilizing these three hormones to predict threatened miscarriage risk. METHODS: This is a multicentre, observational, case-control study involving 215 pregnant women. We recruited 119 normal pregnant women and 96 threatened miscarriage pregnant women including 58 women with ongoing pregnancy and 38 women with inevitable miscarriage. P4 and ß-hCG levels were detected by chemiluminescence immunoassay assay. The level of AEA was tested by ultra-high-performance liquid chromatography-tandem mass spectrometry. Six predictive machine learning models were established and evaluated by the confusion matrix, area under the receiver operating characteristic (ROC) curve (AUC), accuracy and precision. RESULTS: The median concentration of AEA was significantly lower in the healthy pregnant women group than that in the threatened miscarriage group, while the median concentration of P4 was significantly higher in the normal pregnancy group than that in the threatened miscarriage group. Only the median level of P4 was significantly lower in the inevitable miscarriage group than that in the ongoing pregnancy group. Moreover, AEA is strongly positively correlated with threatened miscarriage, while P4 is negatively correlated with both threatened miscarriage and inevitable miscarriage. Interestingly, AEA and P4 are negatively correlated with each other. Among six models, logistic regression (LR), support vector machine (SVM) and multilayer perceptron (MLP) models obtained the AUC values of 0.75, 0.70 and 0.70, respectively; and their accuracy and precision were all above 0.60. Among these three models, the LR model showed the highest accuracy (0.65) and precision (0.70) to predict threatened miscarriage. CONCLUSIONS: The LR model showed the highest overall predictive power, thus machine learning combined with the level of AEA, P4 and ß-hCG might be a new approach to predict the threatened miscarriage risk in the near feature.

DYF-5/MAK-dependent phosphorylation promotes ciliary tubulin unloading.

Cilia are microtubule-based organelles that power cell motility and regulate sensation and signaling, and abnormal ciliary structure and function cause various ciliopathies. Cilium formation and maintenance requires intraflagellar transport (IFT), during which the kinesin-2 family motor proteins ferry IFT particles carrying axonemal precursors such as tubulins into cilia. Tubulin dimers are loaded to IFT machinery through an interaction between tubulin and the IFT-74/81 module; however, little is known of how tubulins are unloaded when arriving at the ciliary tip. Here, we show that the ciliary kinase DYF-5/MAK phosphorylates multiple sites within the tubulin-binding module of IFT-74, reducing the tubulin-binding affinity of IFT-74/81 approximately sixfold. Ablation or constitutive activation of IFT-74 phosphorylation abnormally elongates or shortens sensory cilia in Caenorhabditis elegans neurons. We propose that DYF-5/MAK-dependent phosphorylation plays a fundamental role in ciliogenesis by regulating tubulin unloading.