Effect of PPARγ on oxidative stress in diabetes-related dry eye.

Oxidative stress is closely associated with diabetes and can cause free radical accumulation and eventually lead to ocular surface tissue damage. The purpose of this study was to investigate peroxisome proliferator-activated receptor-γ (PPARγ) expression in the lacrimal gland (LG), meibomian gland, and cornea of diabetes-related dry eye mice and whether the PPARγ agonist rosiglitazone can alleviate the oxidative stress of the ocular surface, thereby improving the condition of diabetes-related dry eye. Quantitative RT-PCR (Q-PCR) showed that the PPARγ, catalase, glutathione peroxidase 3, and heme oxygenase-1 (HO-1) mRNA expression levels in the LG of diabetes-related dry eye mice decreased at 8 and 12 weeks. In addition, the increased levels of oxidative stress were confirmed by western blot. Although the mRNA expression levels of antioxidant enzymes in the cornea and meibomian gland decreased at 8 weeks, some of them recovered by 12 weeks. Rosiglitazone alleviated ocular surface damage and increased corneal sensitivity and tear production in diabetes-related dry eye mice. Moreover, the reactive oxygen species accumulation was reduced and the PPARγ, HO-1, and glutathione peroxidase 3 mRNA expression levels were increased in the LG. The PPARγ, HO-1, translocase of the outer membrane 20, and mitochondrial transcription factor A protein levels were also significantly increased. These results demonstrated that rosiglitazone reduced oxidative stress in the LG of diabetes-related dry eye mice, at least in part, by activating PPARγ to up-regulate antioxidant enzyme expression.

The Relationship of Partial Pressure of Carbon Dioxide (PaCO2) with Disease Severity Indicators Such as BODE and GOLD in Hospitalized COPD Patients.

Purpose: This study aimed to investigate the relationship of partial pressure of carbon dioxide (PaCO2) with BODE and GOLD in stable COPD subjects and to explore the predictive value of PaCO2 for severe COPD (BODE index score ≥5 or GOLD index score ≥3). Patients and Methods. In total, 80 participants with COPD and free from other conditions affecting PaCO2 were recruited. Arterial blood gases, BODE, GOLD, SGRQ, lung function, and other data were collected. The BODE index was calculated, and patients were divided into two groups according to the BODE index and PaCO2 median, respectively. We used Pearson's correlation test and the receiver operating characteristic curves to evaluate the utility of PaCO2. Besides, the univariate and multivariate logistic regression analyses were conducted to verify whether PaCO2 was an independent factor associated with BODE grades. Results: COPD subjects with BODE ≥5 and GOLD ≥3 had significantly higher levels of PaCO2 (p = 0.004, p = 0.001, respectively). In the high PaCO2 group, patients underwent poorer outcomes than the low PaCO2 group. PaCO2 was negatively correlated with forced expiratory volume in 1 second in percent of the predicted value (FEV1%) (r = -0.612, p < 0.001). The performance of PaCO2 levels in predicting BODE ≥5 and GOLD ≥3 was 0.748 and 0.755, respectively. The logistic regression analyses proved that PaCO2 was associated with BODE ≥5 in COPD patients (odds ratio = 1.160, 95% CI: 1.025-1.313, p = 0.019). Conclusions: A higher level of PaCO2 was associated with a higher index for BODE or GOLD in COPD and had the predictive value for severe COPD.

Exploring agreement and feasibility between virtual home visits and in-person home visits for peritoneal dialysis patients-a paired study.

INTRODUCTION: Virtual home visits may improve chronic disease management. However, whether they are suitable for peritoneal dialysis (PD) patients has not yet been fully investigated. This study aimed to compare the agreement and acceptance of virtual home visits and in-person home visits in PD patients. METHODS: This was a paired, single center, noninferiority trial. Participants received a virtual home visit and an in-person home visit simultaneously. A home visit checklist was built for standardization visits. The content was divided into three parts: domestic habits (57 items), bag exchange procedures (56 items), and exit site care (53 items). Satisfaction questionnaires for both patients and nurses were designed to assess attitudes toward home visits and socioeconomic effects. RESULTS: A total of 30 PD patients were enrolled in a single center. The information collected from virtual home visits and in-person home visits was found to be highly consistent. The perfect agreement was found in 52/57, 49/56, and 44/53 items (Cohen's kappa 0.81-1.00), substantial agreement in 4/57, 7/56, and 8/53 items (Cohen's kappa 0.61-0.80). Patients reported almost identical satisfaction for virtual home visits and in-person home visits (Z = 0.39, p = 0.70). PD nurses reported similar feasibility and patient cooperation for the two visit types (Z = 0.99, p = 0.33; Z = 1.65, p = 0.10, respectively). In addition, virtual home visits were found to be more cost-effective than in-person home visits. CONCLUSIONS: Virtual home visits information collection was similar to in-person home visits in PD. There were no differences in participant satisfaction and feasibility between the two visit types.

Functional connectivity and structural changes of thalamic subregions in episodic migraine.

BACKGROUND: The thalamus plays a crucial role in transmitting nociceptive information to various cortical regions involving migraine-related allodynia and photophobia. Abnormal structural and functional alterations related to the thalamus have been well established. However, it is unknown whether the brain structure and function of the thalamic subregions are differentially affected in this disorder. In this study, we aimed to clarify this issue by comparing the structure and function of 16 thalamic subregions between patients with episodic migraine (EM) and healthy controls (HCs). METHODS: Twenty-seven patients with EM and 30 sex-, age- and education-matched HCs underwent resting-state functional and structural magnetic resonance imaging scans. Functional connectivity (rsFC), grey matter volume (GMV), and diffusion tensor imaging (DTI) parameters of each subregion of the thalamus were calculated and compared between the two groups. Furthermore, correlation analyses between neuroimaging changes and clinical features were performed in this study. RESULTS: First, compared with HCs, patients with EM exhibited decreased rsFC between the anterior-medial-posterior subregions of the thalamus and brain regions mainly involved in the medial system of the pain processing pathway and default mode network (DMN). Second, for the whole thalamus and each of its subregions, there were no significant differences in GMV between patients with EM and HCs (P > 0.05, Bonferroni corrected). Third, there was no significant difference in DTI parameters between the two groups (P > 0.05). Finally, decreased rsFC was closely related to scores on the Hamilton Rating Scale for Anxiety (HAMA) and Big Five Inventory (BFI) scales. CONCLUSION: Selective functional hypoconnectivity in the thalamic subregions provides neuroimaging evidence supporting the important role of thalamocortical pathway dysfunction in episodic migraine, specifically, that it may modulate emotion and different personality traits in migraine patients.

Cellulose accumulation in the secondary cell walls is negatively correlated with the tenderness of new shoots in Camellia sinensis.

Tea, which is usually made from the new shoots of tea plants (Camellia sinensis), is one of the most popular and healthy beverages. The tenderness of new shoots plays a critical role in the production of high-quality tea; however, the factors affecting the tenderness of the new shoots of tea have not been extensively studied. Here, we show that cellulose accumulation is negatively correlated with the tenderness of new shoots, including leaves and stems, by characterizing the cellulose content and visualizing cellulose in the new shoots of two cultivars ("Huangjinya" and "Yujinxiang") via toluidine blue staining. We further found that the number of cells with secondary cell walls (SCWs) and the thickness of SCWs increased with the maturity degree of stems in both cultivars. Because cellulose is the most abundant polymer in SCW, we next identified three cellulose synthase CsCesAs, CsCesA4, 7, and 8A, through homologous alignment with Arabidopsis AtCesAs. Protein sequence analysis revealed that these proteins were closely related based on the phylogenetic analysis. We finally showed that the gene expression of the three CsCesAs was positively correlated with the maturity degree and cellulose content of the new shoots. Thus, our data suggest that cellulose accumulation, especially in the SCWs, is negatively correlated with the tenderness of new shoots in tea plants.

Differential Hydrogen/Deuterium Exchange during Proteoform Separation Enables Characterization of Conformational Differences between Coexisting Protein States.

Characterization of structural differences between coexisting conformational states of protein is difficult with conventional biophysical techniques. Hydrogen/deuterium exchange (HDX) coupled with top-down mass spectrometry (MS) allows different conformers to be deuterated to different extents and distinguished through gas-phase separation based on molecular weight distributions prior to determination of deuteration levels at local sites for each isolated conformer. However, application of this strategy to complex systems is hampered by the interference from conformers with only minor differences in overall deuteration levels. In this work, we performed differential HDX while the different conformers were separated according to their differing charge to size ratios in capillary electrophoresis. Mixtures of holo- and apo-myoglobin (Mb) and disulfide isomers of lysozyme (Lyz) were characterized in a conformer-specific fashion using this strategy, followed by conformation interrogation for the sequentially eluted 2H-labeled species in real-time using top-down MS. Under mildly denaturing conditions that minimize the charge difference, disulfide isomers of Lyz were differentially labeled with 2H during separation based on their disulfide-dependent sizes. The resulting differences in deuteration pattern between these isomers are in line with their difference in covalent structural constraints set by the disulfide patterns. Under physiologically relevant conditions, we identified the segments undergoing conformational changes of Mb in the absence of the heme group by comparing the deuteration patterns of holo- and apo-Mb.

Winogradskyella ouciana sp. nov., isolated from the hadal seawater of the Mariana Trench.

A Gram-staining-negative, strictly aerobic, long-rod shaped with no flagellum and yellow-pigmented bacterium designated strain ZXX205T, was isolated from the hadal seawater at the depth of 7500 m in the Mariana Trench, Pacific Ocean. Phylogenetic analysis based on 16S rRNA gene sequences placed strain ZXX205T within the genus Winogradskyella and strain ZXX205T was most closely related to Winogradskyella flava KCTC 52348T and Winogradskyella echinorum KCTC 22026T with 96.9 % and 96.6 % sequence similarity, respectively. The sequence similarities to all other type strains were 96.3 % or less, and to the type strain Winogradskyella thalassocola LMG 22492T was 94.1 %. Growth occurred in the presence of 0-9.0 % (w/v) NaCl (optimum 3.0 %), at 4-45 °C (optimum 28 °C) and pH 6.0-9.0 (optimum pH 7.5). The sole respiratory quinone was menaquinone 6 (MK-6). The dominant cellular fatty acids (>10 %) of strain ZXX205T were iso-C15 : 0, iso-C15 : 1 G, iso-C16 : 0 3-OH and iso-C16 : 0. The polar lipids profile contained predominantly phosphatidylethanolamine, four glycolipids, four unidentified aminolipids and three unidentified lipids. The genomic DNA G+C content was 35.5 %. The DNA-DNA relatedness (DDH) values between strain ZXX205T and the most closely related species Winogradskyella flava and Winogradskyella echinorum were 21.1 and 20.4 %, respectively. Based on polyphasic taxonomic analysis, strain ZXX205T is considered to represent a novel species in the genus Winogradskyella of the family Flavobacteriaceae, for which the name Winogradskyella ouciana is proposed. The type strain is ZXX205T (=MCCC 1K03851T=JCM 33665T).

A gadolinium(III)-porphyrin based coordination polymer for colorimetric and fluorometric dual mode determination of ferric ions.

A coordination polymer (CP) based nanoprobe is described for colorimetric and fluorometric (dual mode) determination of ferric ion. The method is making use of a nanosized Gd(III)-5,10,15,20-tetrakis(4-carboxyphenyl)porphyrin coordination polymer that was prepared by a single-step hydrothermal procedure. The nanoprobe is monodisperse and has uniform size and good water solubility. It also exhibits strong fluorescence and magnetic resonance response. On exposure to Fe(III), the color of the solution changes from red to brown as the concentration of Fe(III) exceed 5 µM. Similarly, the red fluorescence of the probe (with excitation/emission peaks at 420/675 nm) decreases as concentrations of Fe(III) increase from 0.5 to 100 µM. The limit of detection is 98 nM in the fluorometric mode. The assay was applied to the determination of Fe(III) in fetal bovine serum samples. Graphical abstract Schematic presentation of the synthesis and application of lanthanide-porphyrin based coordination polymer for ferric ion detection in colorimetric and fluorometric dual modes.

Formation and Extractive Desulfurization Mechanisms of Aromatic Acid Based Deep Eutectic Solvents: An Experimental and Theoretical Study.

The formation and extractive desulfurization (EDS) mechanisms of aromatic acid based deep eutectic solvents (DESs) were studied experimentally and through quantum chemistry calculations. Hydrogen bonding and van der Waals forces were investigated as the driving forces for the formation of aromatic acid based DESs by means of 1 H NMR and FTIR spectroscopy, and DFT calculations. The driving forces of EDS were also studied. The results showed that van der Waals forces and other weak interactions were the main diving forces for EDS, and the structures of the aromatic acid based DESs did not change after EDS. The interaction energy between the aromatic acid based DESs and thiophene (TH), benzothiophene (BT), and dibenzothiophene (DBT) were calculated by DFT to understand the EDS order: TH

Deducing disulfide patterns of cysteine-rich proteins using signature fragments produced by top-down mass spectrometry.

Direct mapping of protein disulfide patterns using top-down mass spectrometry (MS) is often hampered by inadequate fragmentation at the disulfide-enclosing region, and insufficient structural information provided by the fragments. Here we used electron-transfer/high energy collision dissociation (EThcD) to improve the fragmentation efficiency, and developed strategies that minimize the false positive identification of fragments and deconvolute the signals representing specific modifications made to the disulfide-cleavage-induced fragments. We observed clear correlations between unique modification (attachment or removal of H or SH) patterns and the number of disulfide bonds that enclose the corresponding region. Using the characteristic signature fragments, we in part localized the Cys-bridging sites in disulfide-scrambled lysozymes, and reduced the number of putative disulfide patterns from 104 to 6. The results demonstrated the feasibility of direct analysis of complex disulfide patterns using top-down MS.

Determinants of health care-seeking delay among tuberculosis patients in Shandong Province, China.

BACKGROUND: It is beneficial for tuberculosis patients to seek health care in time. The aim of this study was to understand the situation of initial health care-seeking delay among tuberculosis patients in eastern China, and explore its influencing factors, to provide a basis for formulating related polices and reducing its transmission. METHODS: A cross-sectional survey was conducted in six counties of Shandong Province, China, and we selected study sites by multi-stage random sampling. Subjects were pulmonary tuberculosis patients registered with the county tuberculosis dispensaries at study sites that completed treatment during the period October 2006 to September 30, 2007. RESULTS: For the 819 cases of pulmonary tuberculosis, the median initial health care-seeking delay time was 6 days, and 49.8% of them were initial health care-seeking delayed. The logistic regression analysis showed that marriage (odds ratio = 0.354, 95% confidence interval: 0.193-0.650) and knowledge of the national tuberculosis subsidy policy (odds ratio = 1.753, 95% confidence interval: 1.258-2.441) were associated with initial health care-seeking delay. CONCLUSION: Changing the perception of patients and popularizing the national tuberculosis subsidy policy will do well towards reducing initial health care-seeking delay.

Amination of nitroazoles--a comparative study of structural and energetic properties.

In this work, 3-nitro-1H-1,2,4-triazole (1) and 3,5-dinitro-1H-pyrazole (2) were C-aminated and N-aminated using different amination agents, yielding their respective C-amino and N-amino products. All compounds were fully characterized by NMR (1H, 13C, 15N), IR spectroscopy, differential scanning calorimetry (DSC). X-ray crystallographic measurements were performed and delivered insight into structural characteristics as well as inter- and intramolecular interactions of the products. Their impact sensitivities were measured by using standard BAM fallhammer techniques and their explosive performances were computed using the EXPLO 5.05 program. A comparative study on the influence of those different amino substituents on the structural and energetic properties (such as density, stability, heat of formation, detonation performance) is presented. The results showed that the incorporation of an N-amino group into a nitroazole ring can improve nitrogen content, heat of formation and impact sensitivity, while the introduction of a C-amino group can enhance density, detonation velocity and pressure. The potential of N-amino and C-amino moieties for the design of next generation energetic materials is explored.

Genetic mechanisms underlying local spontaneous brain activity in episodic migraine.

Advances in neuroimaging techniques during the past few decades have captured impaired functional brain activity in migraine disorders, yet the molecular mechanisms accounting for its alterations in migraine remain largely unknown. A total of 27 patients with episodic migraine (EM) and 30 matched healthy controls (HCs) underwent resting-state functional and structural magnetic resonance imaging (MRI) scans. Regional homogeneity (ReHo), low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) of fMRI were compared between the two groups. Based on the Allen Human Brain Atlas and risk genes in migraine, we identified gene expression profiles associated with ReHo alterations in EM. Compared with HCs, patients with EM showed increased ReHo in the left orbital part of the superior frontal gyrus (P < 0.05, cluster-level FWE-corrected). The expression profiles of 16 genes were significantly correlated with ReHo alterations in EM (P < 0.05/5,013, Bonferroni corrected). These genes were mainly enriched for transcription regulation, synaptic transmission, energy metabolism, and migraine disorders. Furthermore, the neural activation was positively correlated with Hamilton Rating Scale for Anxiety (HAMA) scores. To test the stability of our results, we repeated our procedure by using ALFF and fALFF and found these results had a high degree of consistency. Overall, these findings not only demonstrated that regional brain activity was increased in patients with EM, which was associated with emotional regulation but also provided new insights into the genetic mechanisms underlying these changes in migraine.

Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study.

OBJECTIVE: Postoperative delirium (POD) is strongly associated with poor early and long-term prognosis in cardiac surgery patients with cardiopulmonary bypass (CPB). This study aimed to develop dynamic prediction models for POD after cardiac surgery under CPB using machine learning (ML) algorithms. METHODS: From July 2021 to June 2022, clinical data were collected from patients undergoing cardiac surgery under CPB at Nanjing First Hospital. A dataset from the same center (October 2022 to November 2022) was also used for temporal external validation. We used ML and deep learning to build models in the training set, optimized parameters in the test set, and finally validated the best model in the validation set. The SHapley Additive exPlanations (SHAP) method was introduced to explain the best models. RESULTS: Of the 885 patients enrolled, 221 (25.0%) developed POD. 22 (22.0%) of 100 validation cohort patients developed POD. The preoperative and postoperative artificial neural network (ANN) models exhibited optimal performance. The validation results demonstrated satisfactory predictive performance of the ANN model, with area under the receiver operator characteristic curve (AUROC) values of 0.776 and 0.684 for the preoperative and postoperative models, respectively. Based on the ANN algorithm, we constructed dynamic, highly accurate, and interpretable web risk calculators for POD. CONCLUSIONS: We successfully developed online interpretable dynamic ANN models as clinical decision aids to identify patients at high risk of POD before and after cardiac surgery to facilitate early intervention or care.

Machine learning-based risk prediction of hypoxemia for outpatients undergoing sedation colonoscopy: a practical clinical tool.

OBJECTIVES: Hypoxemia as a common complication in colonoscopy under sedation and may result in serious consequences. Unfortunately, a hypoxemia prediction model for outpatient colonoscopy has not been developed. Consequently, the objective of our study was to develop a practical and accurate model to predict the risk of hypoxemia in outpatient colonoscopy under sedation. METHODS: In this study, we included patients who received colonoscopy with anesthesia in Nanjing First Hospital from July to September 2021. Risk factors were selected through the least absolute shrinkage and selection operator (LASSO). Prediction models based on logistic regression (LR), random forest classifier (RFC), extreme gradient boosting (XGBoost), support vector machine (SVM), and stacking classifier (SCLF) model were implemented and assessed by standard metrics such as the area under the receiver operating characteristic curve (AUROC), sensitivity and specificity. Then choose the best model to develop an online tool for clinical use. RESULTS: We ultimately included 839 patients. After LASSO, body mass index (BMI) (coefficient = 0.36), obstructive sleep apnea-hypopnea syndrome (OSAHS) (coefficient = 1.32), basal oxygen saturation (coefficient = -0.14), and remifentanil dosage (coefficient = 0.04) were independent risk factors for hypoxemia. The XGBoost model with an AUROC of 0.913 showed the best performance among the five models. CONCLUSION: Our study selected the XGBoost as the first model especially for colonoscopy, with over 95% accuracy and excellent specificity. The XGBoost includes four variables that can be quickly obtained. Moreover, an online prediction practical tool has been provided, which helps screen high-risk outpatients with hypoxemia swiftly and conveniently.

Colonoscopy under sedation is an effective technique for the inspection and treatment of alimentary canal diseases, but hypoxemia associated with this process cannot be ignored, since prolonged or severe hypoxemia may result in several serious consequences.We wanted to develop a practical and accurate model to predict the risk of hypoxemia for outpatient colonoscopy under sedation, which could help clinicians make more accurate and objective judgments to prevent patients from being harmed.A total of 839 patients were included in our study and we constructed five machine learning models and selected the best one, which demonstrated satisfactory performance. On this basis, a user-friendly data interface has been developed for convenient application. Clinicians can log in to this interface at any time and it will automatically calculate the patient's risk of hypoxemia when entering patient information.This study offers evidence that machine learning algorithms can accurately predict the risk of hypoxemia for outpatient colonoscopy under sedation and the model we developed is a practical and interpretable tool that could be used as a clinical decision-making aid.

Development and validation of a novel nomogram model to assess the risk of gastric contents in outpatients undergoing elective sedative gastrointestinal endoscopy procedures.

BACKGROUND: Gastric contents may contribute to patients' aspiration during anesthesia. Ultrasound can accurately assess the risk of gastric contents in patients undergoing sedative gastrointestinal endoscopy (GIE) procedures, but its efficiency is limited. Therefore, developing an accurate and efficient model to predict gastric contents in outpatients undergoing elective sedative GIE procedures is greatly desirable. METHODS: This study retrospectively analyzed 1501 patients undergoing sedative GIE procedures. Gastric contents were observed under direct gastroscopic vision and suctioned through the endoscope. High-risk gastric contents were defined as having solid content or liquid volume > 25 ml and pH < 2.5; otherwise, they were considered low-risk gastric contents. Univariate analysis and multivariate analysis were used to select the independent risk factors to predict high-risk gastric contents. Based on the selected independent risk factors, we assigned values to each independent risk factor and established a novel nomogram. The performance of the nomogram was verified in the testing cohort by the metrics of discrimination, calibration, and clinical usefulness. In addition, an online accessible web calculator was constructed. RESULTS: We found BMI, cerebral infarction, cirrhosis, male, age, diabetes, and gastroesophageal reflux disease were risk factors for gastric contents. The AUROCs were 0.911 and 0.864 in the development and testing cohort, respectively. Moreover, the nomogram showed good calibration ability. Decision curve analysis and Clinical impact curve demonstrated that the predictive nomogram was clinically useful. The website of the nomogram was https://medication.shinyapps.io/dynnomapp/. CONCLUSIONS: This study demonstrates that clinical variables can be combined with algorithmic techniques to predict gastric contents in outpatients. Nomogram was constructed from routine variables, and the web calculator had excellent clinical applicability to assess the risk of gastric contents accurately and efficiently in outpatients, assist anesthesiologists in assessment and identify the most appropriate patients for ultrasound.

Iodide intake during pregnancy and lactation stimulates KLF9, BDNF expression in offspring brain with elevated DHA, EPA metabolites.

To investigate the effect of different iodide intake during pregnancy and lactation on thyroid function, docosahexaenoic acid (DHA), Eicosapentaenoic acid (EPA) metabolites, the expression of Krüppel-like factor KLF9 (KLF9), brain-derived neurotrophic factor (BDNF) in brain in offspring rats. In both male and female offspring rats, serum FT3, FT4 levels and the expression of KLF9, thyroid hormone receptors (TR)α, TRß and BDNF in the hippocampal region and cerebellum were significantly increased in 5 times higher-than-normal pregnant iodide intake (5 HI) and 10 times higher-than-normal pregnant iodide intake (10 HI) group. The median levels of DHA metabolite (17-HDoHE) and EPA metabolites (15-HEPE, 17,18-EEQ, 9-HEPE and 14,15-DiHETE) were significantly increased in 5 HI and 10 HI group of offspring rats. Serum DHA, EPA metabolites and KLF9 as well as BDNF expression in brain might be potential iodine status biomarkers to reflect brain development in offspring.

Effect of different iodide intake during pregnancy and lactation on thyroid and cardiovascular function in maternal and offspring rats.

OBJECTIVE: We aimed to investigate the impact of different iodide intake during pregnancy and lactation on iodine concentration in urine and serum, fatty acid metabolism, thyroid and cardiovascular function in maternal and offspring rats. METHODS: Pregnant rats were randomly assigned to four groups: normal adult iodide intake (NAI, 7.5 µg/d), normal pregnant iodide intake (NPI, 12.5 µg/d), 5 times (5 HI, 62.5 µg/d) and 10 times higher-than-normal pregnant iodide intake (10 HI, 125 µg/d). The maternal rats were continuously administered potassium iodide until postnatal day 16 (PN16). Thyroid function was measured by enzyme-linked immunosorbent assay (ELISA). The iodine concentration in urine and serum were detected by inductively coupled plasma mass spectrometry (ICP-MS). The messenger ribonucleic acid (mRNA) expressions of Krüppel-like factor 9 (KLF9) and thioredoxin reductase 2 (Txnrd2) were measured using quantitative real-time polymerase chain reaction (RT-qPCR). Characteristic distribution of KLF9 expression and its interaction with TRß was assessed by immunohistochemical and immunofluorescence staining. Serum fatty acids were analyzed by Liquid Chromatography-Mass Spectrometry (LC-MS). Cardiac function and blood pressure were measured by echocardiography and a non-invasive tail-cuff system. RESULTS: High iodide intake (5 HI and 10 HI) during pregnancy and lactation results in increased urinary iodine concentration (UIC), serum total iodine concentration (STIC) and serum non-protein-bound iodine concentration (SNBIC) in both maternal and offspring rats, along with significantly increased FT3 and its target gene expression of KLF9. In maternal rats of both 5 HI and 10 HI groups, systolic blood pressure (SBP) was significantly higher, the increased SBP was significantly correlated with the increased UIC (r = 0.968, p = 0.002; r = 0.844, p = 0.035), KLF9 (r = 0.935, p = 0.006; r = 0.954, p = 0.003) and the decreased Txnrd2 (r = -0.909, p = 0.012; r = -0.912, p = 0.011). In maternal rats of 10 HI group, cardiac hyperfunction with increased LVEF, LVFS and decreased LVESD were observed. The increased LVEF and decreased LVESD were significantly correlated with UIC, STIC and SNBIC (r = 0.976, p = 0.001; r = 0.945, p = 0.005; r = 0.953, p = 0.003; r = -0.917, p = 0.01; r = -0.859, p = 0.028; r = -0.847, p = 0.033), LVEF, LVFS and LVESD were significant correlated with KLF9 (r = 0.950, p = 0.004; r = 0.963, p = 0.002; r = -0.990, p = 0.0002) and Txnrd2 expression (r = -0.979, p = 0.001; r = -0.915, p = 0.01; r = 0.933, p = 0.007), and the decreased LVESD was correlated with decreased epoxyeicosatrienoic acid (EET) metabolites: 5,6-EET, 8,9-DHET and 11,12-DHET (r = 0.999, p = 0.034; r = 1.000, p = 0.017; r = 1.000, p = 0.017). While in offspring rats, no significant change in SBP and cardiac function was found. STIC and SNBIC were much lower than those in maternal rats, and eicosapentaenoic acid (EPA) metabolites (9-HEPE, 15-HEPE and 14,15 DiHETE) were significantly increased. CONCLUSION: In addition to thyroid hormones, STIC, SNBIC, KLF9, Txnrd2, EET and EPA metabolites might be promising biomarkers in high iodide intake-induced thyroid and cardiovascular function.

Dynamic prediction of hypoxemia risk at different time points based on preoperative and intraoperative features: machine learning applications in outpatients undergoing esophagogastroduodenoscopy.

BACKGROUND: Hypoxemia often occurs in outpatients undergoing anesthesia-assisted esophagogastroduodenoscopy (EGD). However, there is a scarcity in tools to predict the hypoxemia risk. We aimed to solve this problem by developing and validating machine learning (ML) models based on preoperative and intraoperative features. METHODS: All data were retrospectively collected from June 2021 to February 2022. The most appropriate predictive features were selected by the least absolute shrinkage and selection operator, which were incorporated and modelled by 4 ML algorithms. The area under the precision-recall curve (AUPRC) was used as the main evaluation metric to select the best models, and the selected models were compared with the STOP-BANG score. Their predictive performance was visually interpreted by SHapley Additive exPlanations. The primary endpoint of this study was hypoxemia during the procedure, defined as at least one reading of pulse oximetry < 90% without probes misplacement from the anesthesia induction beginning to the end of EGD, while the secondary endpoint was hypoxemia during induction, from the induction beginning to the start of endoscopic intubation. RESULTS: Of 1160 patients in the derivation cohort, 112 patients (9.6%) developed intraoperative hypoxemia, of which 102 (8.8%) occurred during the induction period. In temporal and external validation, no matter whether based on preoperative variables or still based on preoperative plus intraoperative variables, our models showed excellent predictive performance for the two endpoints, significantly better than STOP-BANG score. In the model interpretation section, preoperative variables (airway assessment indicators, pulse oximeter oxygen saturation and BMI) and intraoperative variables (the induced propofol dose) made the highest contribution to the predictions.To our knowledge, our ML models were the first to predict hypoxemia risk, which achieved excellent overall predictive ability integrating various clinical indicators. These models have the potential to become an effective tool for adjusting sedation strategies flexibly and reducing the workload of anesthesiologists.KEY MESSAGESThis study is the first model employing ML methods based on preoperative and preoperative plus intraoperative variables for predicting the risk of hypoxemia during induction and the whole EGD procedure respectively.Our four models achieved satisfactory predictive performance and outperformed STOP-BANG score in terms of AUPRC in the temporal and external validation cohorts respectively.We found that the relevant variables of airway assessment should be fully taken into account when analyzing the risk factor of hypoxemia, and the effect of patients' age on their hypoxemia risk should be considered in conjunction with the propofol dose.

An interpretable artificial neural network model for predicting hypoxemia via an online tool in adult (18-64) patients during esophagogastroduodenoscopy.

Background: The hypoxemia risk in adult (18-64) patients treated with esophagogastroduodenoscopy (EGD) under sedation often poses a dilemma for anesthesiologists. We aimed to establish an artificial neural network (ANN) model to solve this problem, and introduce the Shapley additive explanations (SHAP) algorithm to further improve the interpretability. Methods: The relevant data of patients underwent routine anesthesia-assisted EGD were collected. Elastic network was used to filter the optimal features. Airway-ANN and Basic-ANN models were established based on all collected indicators and remaining variables excluding airway assessment indicators, respectively. The performance of Basic-ANN, Airway-ANN and STOP-BANG was evaluated by the area under the precision-recall curve (AUPRC) on temporal validation set. The SHAP was used for revealing the predictive behavior of our best model. Results: 999 patients were eventually included. The AUPRC value of Airway-ANN model was significantly higher than Basic-ANN model in the temporal validation set (0.532 vs 0.429, P < 0.05). And the performance of both two ANN models was significantly better than that of STOP-BANG score (both P < 0.05). The Airway-ANN model was deployed to the cloud (http://njfh-yxb.com.cn:2022/airway_ann). Conclusion: Our online interpretable Airway-ANN model achieved satisfying ability in identifying the hypoxemia risk in adult (18-64) patients undergoing EGD.