On-Demand 3D Spatial Distribution of Magnetic Permeability Based on Fe3 O4 Nanoparticle Liquid Toward Micro-Cavity Detectors.

The change of 3D spatial distribution of magnetic permeability can lead to the generation of introduced electrical signals. However, present studies can only achieve rough regulation by simple shape deformation of magnetic elastomers such as compression, bending, or stretching. Accurate control of the 3D spatial distribution of magnetic permeability is still an open question. In this study, an on-demand 3D spatial distribution of magnetic permeability by controlled flowing of Fe3 O4 nanoparticle liquid (FNL) is demonstrated. The flowing routes of FNL are tuned by a 3D-printed cage with pre-designed hollow structure, thus changing the 3D spatial distribution of magnetic permeability. Then, eight symmetrically distributed coils under cage are used to receive characteristic induction voltage signals. Maxwell numerical simulation reveals the working mechanism of signal generation. Notably, those eight coils can detect FNL flowing status in eight directions, allowing recognition of up to 255 different FNL flowing combinations. By introducing machine learning, the micro-cavity detector based on FNL can distinguish nine kinds of micro-cavity structures with an accuracy of 98.77%. This work provides a new strategy for the adjustment of the 3D spatial distribution of the magnetic permeability and expands the application of FNL in the field of space exploration.

Insulin resistance, coronary artery lesion complexity and adverse cardiovascular outcomes in patients with acute coronary syndrome.

BACKGROUND: Insulin resistance (IR) is linked to both the complexity of coronary artery lesions and the prognosis of acute coronary syndrome (ACS). However, the precise extent of this correlation and its impact on adverse cardiovascular outcomes in ACS patients remain unclear. Therefore, this study aims to investigate the intricate relationship between IR, coronary artery lesion complexity, and the prognosis of ACS through a cohort design analysis. METHOD: A total of 986 patients with ACS who underwent percutaneous coronary intervention (PCI) were included in this analysis. IR was assessed using the triglyceride-glucose (TyG) index, while coronary artery lesion complexity was evaluated using the SYNTAX score. Pearson's correlation coefficients were utilized to analyze the correlations between variables. The association of the TyG index and SYNTAX score with major adverse cardiovascular events (MACEs) in ACS was investigated using the Kaplan-Meier method, restricted cubic splines (RCS), and adjusted Cox regression. Additionally, a novel 2-stage regression method for survival data was employed in mediation analysis to explore the mediating impact of the SYNTAX score on the association between the TyG index and adverse cardiovascular outcomes, including MACEs and unplanned revascularization. RESULTS: During a median follow-up of 30.72 months, 167 cases of MACEs were documented, including 66 all-cause deaths (6.69%), 26 nonfatal myocardial infarctions (MIs) (2.64%), and 99 unplanned revascularizations (10.04%). The incidence of MACEs, all-cause death, and unplanned revascularization increased with elevated TyG index and SYNTAX score. Both the TyG index (non-linear, P = 0.119) and SYNTAX score (non-linear, P = 0.004) displayed a positive dose-response relationship with MACEs, as illustrated by the RCS curve. Following adjustment for multiple factors, both the TyG index and SYNTAX score emerged as significant predictors of MACEs across the total population and various subgroups. Mediation analysis indicated that the SYNTAX score mediated 25.03%, 18.00%, 14.93%, and 11.53% of the correlation between the TyG index and MACEs in different adjusted models, respectively. Similar mediating effects were observed when endpoint was defined as unplanned revascularization. CONCLUSION: Elevated baseline TyG index and SYNTAX score were associated with a higher risk of MACEs in ACS. Furthermore, the SYNTAX score partially mediated the relationship between the TyG index and adverse cardiovascular outcomes.

Tilianin enhances the antitumor effect of sufentanil on non-small cell lung cancer.

Non-small cell cancer (NSCLC) is the most common cancer in the world, but its effective therapeutic methods are limited. Tilianin and sufentanil alleviate various human tumors. This research aimed to clarify the functions and mechanisms of Tilianin and sufentanil in NSCLC. The functions of Tilianin and sufentanil on NSCLC cell viability, apoptosis, mitochondrial dysfunction, and immunity in vitro were examined using Cell Counting Kit-8 assay, flow cytometry, reactive oxygen species level analysis, CD8+ T cell percentage analysis, Western blot, and enzyme-linked immunosorbent assay, respectively. The molecular mechanism regulated by Tilianin and sufentanil in NSCLC was assessed using Western blot, and immunofluorescence assays. Meanwhile, the roles of Tilianin and sufentanil in NSCLC tumor growth, apoptosis, and immunity in vivo were determined by establishing a tumor xenograft mouse model, immunohistochemistry, and Western blot assays. When sufentanil concentration was proximity 2 nM, the inhibition rate of NSCLC cell viability was 50%. The IC50 for A549 cells was 2.36 nM, and the IC50 for H1299 cells was 2.18 nM. The IC50 of Tilianin for A549 cells was 38.7 µM, and the IC50 of Tilianin for H1299 cells was 44.6 µM. Functionally, 0.5 nM sufentanil and 10 µM Tilianin reduced NSCLC cell (A549 and H1299) viability in a dose-dependent manner. Also, 0.5 nM sufentanil and 10 µM Tilianin enhanced NSCLC cell apoptosis, yet this impact was strengthened after a combination of Tilianin and Sufentanil. Furthermore, 0.5 nM sufentanil and 10 µM Tilianin repressed NSCLC cell mitochondrial dysfunction and immunity, and these impacts were enhanced after a combination of Tilianin and Sufentanil. Mechanistically, 0.5 nM sufentanil and 10 µM Tilianin repressed the NF-κB pathway in NSCLC cells, while this repression was strengthened after a combination of Tilianin and Sufentanil. In vivo experimental data further clarified that 1 µg/kg sufentanil and 10 mg/kg Tilianin reduced NSCLC growth, immunity, and NF-κB pathway-related protein levels, yet these trends were enhanced after a combination of Tilianin and Sufentanil. Tilianin strengthened the antitumor effect of sufentanil in NSCLC.

Bidirectional modification effects on nonlinear associations of summer temperature and air pollution with first-ever stroke morbidity.

High temperature and air pollution may induce stroke morbidity. However, whether associations between high temperature and air pollution with stroke morbidity are modified by each other is still unclear. Data on 23,578 first-ever stroke patients in Shenzhen, China, during the summers of 2014-2018 were collected. Distributed lag nonlinear models were used to assess the modifying effects of air pollution stratified by the median for the associations between summer temperature and stroke morbidity at 0-3 lag days; modifying effects of temperature stratified by the minimum morbidity temperature on the associations between air pollution and stroke morbidity at the same lags were also estimated. The attributable risks of high temperature and high pollution on stroke morbidity were quantified. Stratified analyses of gender, age, migration type, and complication type were conducted to assess vulnerable population characteristics. Summer high temperature may induce stroke morbidity at high-level PM2.5, PM10, O3, SO2, and NO2 conditions, with attributable fraction (AF) of 2.982% (95% empirical confidence interval [eCI]: 0.943, 4.929), 3.113% (0.948, 5.200), 2.841% (0.943, 4.620), 3.617% (1.539, 5.470), and 2.048% (0.279, 3.637), respectively. High-temperature effects were statistically insignificant at corresponding low-level air pollution conditions. High-level PM2.5, PM10, and O3 may induce stroke morbidity at high-temperature conditions, with AF of 3.664% (0.036, 7.196), 4.129% (0.076, 7.963), and 4.574% (1.009, 7.762), respectively. High-level PM2.5, PM10, and O3 were not associated with stroke morbidity at low-temperature conditions. The effects of high temperature and high pollution on stroke morbidity were statistically significant among immigrants and patients with hypertension, dyslipidemia, or diabetes but insignificant among natives and patients without complications. The associations of summer temperature and air pollution with first-ever stroke morbidity may be enhanced bidirectionally. Publicity on the health risks of combined high temperature and high pollution events should be strengthened to raise protection awareness of relevant vulnerable populations.

LncRNA Anxa10-203 enhances Mc1r mRNA stability to promote neuropathic pain by recruiting DHX30 in the trigeminal ganglion.

BACKGROUND: Trigeminal nerve injury is one of the most serious complications in oral clinics, and the subsequent chronic orofacial pain is a consumptive disease. Increasing evidence demonstrates long non-coding RNAs (lncRNAs) play an important role in the pathological process of neuropathic pain. This study aims to explore the function and mechanism of LncRNA Anxa10-203 in the development of orofacial neuropathic pain. METHODS: A mouse model of orofacial neuropathic pain was established by chronic constriction injury of the infraorbital nerve (CCI-ION). The Von Frey test was applied to evaluate hypersensitivity of mice. RT-qPCR and/or Western Blot were performed to analyze the expression of Anxa10-203, DHX30, and MC1R. Cellular localization of target genes was verified by immunofluorescence and RNA fluorescence in situ hybridization. RNA pull-down and RNA immunoprecipitation were used to detect the interaction between the target molecules. Electrophysiology was employed to assess the intrinsic excitability of TG neurons (TGNs) in vitro. RESULTS: Anxa10-203 was upregulated in the TG of CCI-ION mice, and knockdown of Anxa10-203 relieved neuropathic pain. Structurally, Anxa10-203 was located in the cytoplasm of TGNs. Mechanistically, Mc1r expression was positively correlated with Anxa10-203 and was identified as the functional target of Anxa10-203. Besides, Anxa10-203 recruited RNA binding protein DHX30 and formed the Anxa10-203/DHX30 complex to enhance the stability of Mc1r mRNA, resulting in the upregulation of MC1R, which contributed to the enhancement of the intrinsic activity of TGNs in vitro and orofacial neuropathic pain in vivo. CONCLUSIONS: LncRNA Anxa10-203 in the TG played an important role in orofacial neuropathic pain and mediated mechanical allodynia in CCI-ION mice by binding with DHX30 to upregulate MC1R expression.

Metabotropic glutamate receptor 5-mediated inhibition of inward-rectifying K+ channel 4.1 contributes to orofacial ectopic mechanical allodynia following inferior alveolar nerve transection in male mice.

Inward-rectifying K+ channel 4.1 (Kir4.1), which regulates the electrophysiological properties of neurons and glia by affecting K+ homeostasis, plays a critical role in neuropathic pain. Metabotropic glutamate receptor 5 (mGluR5) regulates the expression of Kir4.1 in retinal Müller cells. However, the role of Kir4.1 and its expressional regulatory mechanisms underlying orofacial ectopic allodynia remain unclear. This study aimed to investigate the biological roles of Kir4.1 and mGluR5 in the trigeminal ganglion (TG) in orofacial ectopic mechanical allodynia and the role of mGluR5 in Kir4.1 regulation. An animal model of nerve injury was established via inferior alveolar nerve transection (IANX) in male C57BL/6J mice. Behavioral tests indicated that mechanical allodynia in the ipsilateral whisker pad lasted at least 14 days after IANX surgery and was alleviated by the overexpression of Kir4.1 in the TG, as well as intraganglionic injection of an mGluR5 antagonist (MPEP hydrochloride) or a protein kinase C (PKC) inhibitor (chelerythrine chloride); Conditional knockdown of the Kir4.1 gene downregulated mechanical thresholds in the whisker pad. Double immunostaining revealed that Kir4.1 and mGluR5 were co-expressed in satellite glial cells in the TG. IANX downregulated Kir4.1 and upregulated mGluR5 and phosphorylated PKC (p-PKC) in the TG; Inhibition of mGluR5 reversed the changes in Kir4.1 and p-PKC that were induced by IANX; Inhibition of PKC activation reversed the downregulation of Kir4.1 expression caused by IANX (p < .05). In conclusion, activation of mGluR5 in the TG after IANX contributed to orofacial ectopic mechanical allodynia by suppressing Kir4.1 via the PKC signaling pathway.

Association between the triglyceride glucose index and in-hospital and 1-year mortality in patients with chronic kidney disease and coronary artery disease in the intensive care unit.

OBJECTIVE: This study aimed to explore the association between the triglyceride glucose index (TyG) and the risk of in-hospital and one-year mortality in patients with chronic kidney disease (CKD) and cardiovascular disease (CAD) admitted to the intensive care unit (ICU). METHODS: The data for the study were taken from the Medical Information Mart for Intensive Care-IV database which contained over 50,000 ICU admissions from 2008 to 2019. The Boruta algorithm was used for feature selection. The study used univariable and multivariable logistic regression analysis, Cox regression analysis, and 3-knotted multivariate restricted cubic spline regression to evaluate the association between the TyG index and mortality risk. RESULTS: After applying inclusion and exclusion criteria, 639 CKD patients with CAD were included in the study with a median TyG index of 9.1 [8.6,9.5]. The TyG index was nonlinearly associated with in-hospital and one-year mortality risk in populations within the specified range. CONCLUSION: This study shows that TyG is a predictor of one-year mortality and in-hospital mortality in ICU patients with CAD and CKD and inform the development of new interventions to improve outcomes. In the high-risk group, TyG might be a valuable tool for risk categorization and management. Further research is required to confirm these results and identify the mechanisms behind the link between TyG and mortality in CAD and CKD patients.

Predictive value of the stress hyperglycemia ratio in dialysis patients with acute coronary syndrome: insights from a multi-center observational study.

BACKGROUND: Various studies have indicated that stress hyperglycemia ratio (SHR) can reflect true acute hyperglycemic status and is associated with poor outcomes in patients with acute coronary syndrome (ACS). However, data on dialysis patients with ACS are limited. The Global Registry of Acute Coronary Events (GRACE) risk score is a well-validated risk prediction tool for ACS patients, yet it underestimates the risk of major events in patients receiving dialysis. This study aimed to evaluate the association between SHR and adverse cardiovascular events in dialysis patients with ACS and explore the potential incremental prognostic value of incorporating SHR into the GRACE risk score. METHODS: This study enrolled 714 dialysis patients with ACS from January 2015 to June 2021 at 30 tertiary medical centers in China. Patients were stratified into three groups based on the tertiles of SHR. The primary outcome was major adverse cardiovascular events (MACE), and the secondary outcomes were all-cause mortality and cardiovascular mortality. RESULTS: After a median follow-up of 20.9 months, 345 (48.3%) MACE and 280 (39.2%) all-cause mortality occurred, comprising 205 cases of cardiovascular death. When the highest SHR tertile was compared to the second SHR tertile, a significantly increased risk of MACE (adjusted hazard ratio, 1.92; 95% CI, 1.48-2.49), all-cause mortality (adjusted hazard ratio, 2.19; 95% CI, 1.64-2.93), and cardiovascular mortality (adjusted hazard ratio, 2.70; 95% CI, 1.90-3.83) was identified in the multivariable Cox regression model. A similar association was observed in both diabetic and nondiabetic patients. Further restricted cubic spline analysis identified a J-shaped association between the SHR and primary and secondary outcomes, with hazard ratios for MACE and mortality significantly increasing when SHR was > 1.08. Furthermore, adding SHR to the GRACE score led to a significant improvement in its predictive accuracy for MACE and mortality, as measured by the C-statistic, net reclassification improvement, and integrated discrimination improvement, especially for those with diabetes. CONCLUSIONS: In dialysis patients with ACS, SHR was independently associated with increased risks of MACE and mortality. Furthermore, SHR may aid in improving the predictive efficiency of the GRACE score, especially for those with diabetes. These results indicated that SHR might be a valuable tool for risk stratification and management of dialysis patients with ACS.

The triglyceride-glucose index predicts 1-year major adverse cardiovascular events in end-stage renal disease patients with coronary artery disease.

BACKGROUND: The triglyceride-glucose (TyG) index has been suggested as a dependable indicator for predicting major adverse cardiovascular events (MACE) in individuals with cardiovascular conditions. Nevertheless, there is insufficient data on the predictive significance of the TyG index in end-stage renal disease (ESRD) patients with coronary artery disease (CAD). METHODS: This study, conducted at multiple centers in China, included 959 patients diagnosed with dialysis and CAD from January 2015 to June 2021. Based on the TyG index, the participants were categorized into three distinct groups. The study's primary endpoint was the combination of MACE occurring within one year of follow-up, including death from any cause, non-fatal myocardial infarction, and non-fatal stroke. We assessed the association between the TyG index and MACE using Cox proportional hazard models and restricted cubic spline analysis. The TyG index value was evaluated for prediction incrementally using C-statistics, continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI). RESULTS: The three groups showed notable variations in the risk of MACE (16.3% in tertile 1, 23.5% in tertile 2, and 27.2% in tertile 3; log-rank P = 0.003). Following complete adjustment, patients with the highest TyG index exhibited a notably elevated risk of MACE in comparison to those in the lowest tertile (hazard ratio [HR] 1.63, 95% confidence interval [CI] 1.14-2.35, P = 0.007). Likewise, each unit increase in the TyG index correlated with a 1.37-fold higher risk of MACE (HR 1.37, 95% CI 1.13-1.66, P = 0.001). Restricted cubic spline analysis revealed a connection between the TyG index and MACE (P for nonlinearity > 0.05). Furthermore, incorporating the TyG index to the Global Registry of Acute Coronary Events risk score or baseline risk model with fully adjusted factors considerably enhanced the forecast of MACE, as demonstrated by the C-statistic, continuous NRI, and IDI. CONCLUSIONS: The TyG index might serve as a valuable and dependable indicator of MACE risk in individuals with dialysis and CAD, indicating its potential significance in enhancing risk categorization in clinical settings.

Machine learning to predict occult metastatic lymph nodes along the recurrent laryngeal nerves in thoracic esophageal squamous cell carcinoma.

PURPOSE: Esophageal squamous cell carcinoma (ESCC) metastasizes in an unpredictable fashion to adjacent lymph nodes, including those along the recurrent laryngeal nerves (RLNs). This study is to apply machine learning (ML) for prediction of RLN node metastasis in ESCC. METHODS: The dataset contained 3352 surgically treated ESCC patients whose RLN lymph nodes were removed and pathologically evaluated. Using their baseline and pathological features, ML models were established to predict RLN node metastasis on each side with or without the node status of the contralateral side. Models were trained to achieve at least 90% negative predictive value (NPV) in fivefold cross-validation. The importance of each feature was measured by the permutation score. RESULTS: Tumor metastases were found in 17.0% RLN lymph nodes on the right and 10.8% on the left. In both tasks, the performance of each model was comparable, with a mean area under the curve ranging from 0.731 to 0.739 (without contralateral RLN node status) and from 0.744 to 0.748 (with contralateral status). All models showed approximately 90% NPV scores, suggesting proper generalizability. The pathology status of chest paraesophgeal nodes and tumor depth had the highest impacts on the risk of RLN node metastasis in both models. CONCLUSION: This study demonstrated the feasibility of ML in predicting RLN node metastasis in ESCC. These models may potentially be used intraoperatively to spare RLN node dissection in low-risk patients, thereby minimizing adverse events associated with RLN injuries.

Deep learning in automatic detection of dysphonia: Comparing acoustic features and developing a generalizable framework.

BACKGROUND: Auditory-perceptual assessment of voice is a subjective procedure. Artificial intelligence with deep learning (DL) may improve the consistency and accessibility of this task. It is unclear how a DL model performs on different acoustic features. AIMS: To develop a generalizable DL framework for identifying dysphonia using a multidimensional acoustic feature. METHODS & PROCEDURES: Recordings of sustained phonations of /a/ and /i/ were retrospectively collected from a clinical database. Subjects contained 238 dysphonic and 223 vocally healthy speakers of Chinese Mandarin. All audio clips were split into multiple 1.5-s segments and normalized to the same loudness level. Mel frequency cepstral coefficients and mel-spectrogram were extracted from these standardized segments. Each set of features was used in a convolutional neural network (CNN) to perform a binary classification task. The best feature was obtained through a five-fold cross-validation on a random selection of 80% data. The resultant DL framework was tested on the remaining 20% data and a public German voice database. The performance of the DL framework was compared with those of two baseline machine-learning models. OUTCOMES & RESULTS: The mel-spectrogram yielded the best model performance, with a mean area under the receiver operating characteristic curve of 0.972 and an accuracy of 92% in classifying audio segments. The resultant DL framework significantly outperformed both baseline models in detecting dysphonic subjects on both test sets. The best outcomes were achieved when classifications were made based on all segments of both vowels, with 95% accuracy, 92% recall, 98% precision and 98% specificity on the Chinese test set, and 92%, 95%, 90% and 89%, respectively, on the German set. CONCLUSIONS & IMPLICATIONS: This study demonstrates the feasibility of DL for automatic detection of dysphonia. The mel-spectrogram is a preferred acoustic feature for the task. This framework may be used for vocal health screening and facilitate automatic perceptual evaluation of voice in the era of big data. WHAT THIS PAPER ADDS: What is already known on this subject Auditory-perceptual assessment is the current gold standard in clinical evaluation of voice quality, but its value may be limited by the rater's reliability and accessibility. DL is a new method of artificial intelligence that can overcome these disadvantages and promote automatic voice assessment. This study explored the feasibility of a DL approach for automatic detection of dysphonia, along with a quantitative comparison of two common sets of acoustic features. What this study adds to existing knowledge A CNN model is excellent at decoding multidimensional acoustic features, outperforming the baseline parameter-based models in identifying dysphonic voices. The first 13 mel-frequency cepstral coefficients (MFCCs) are sufficient for this task. The mel-spectrogram results in greater performance, indicating the acoustic features are presented in a more favourable way than the MFCCs to the CNN model. What are the potential or actual clinical implications of this work? DL is a feasible method for the detection of dysphonia. The current DL framework may be used for remote vocal health screening or documenting voice recovery after treatment. In future, DL models may potentially be used to perform auditory-perceptual tasks in an automatic, efficient, reliable and low-cost manner.

Reconstruction of Buccal-penetrating Defects Using the Double-folded Lateral Arm Free Flap.

The reconstruction of buccal-penetrating defects remains challenging. The present study aims to explore the application value of the lateral arm free flap (LAFF) on the reconstruction of buccal-penetrating defects with the hope of providing a better option for clinical practice. Nineteen patients with this kind of issue posed by either tumor resections or deformities in the craniofacial regions were recruited in this study, and LAFF was employed to reconstruct these defects by double folding and individually designing the flap. All the flaps prepared for these subjects in our study survived, and the postoperative assessment of these subjects receiving LAFF revealed that this approach to managing buccal-penetrating defects is able to achieve satisfactory results in terms of appearance and functional recovery. Therefore, our study suggests that LAFF is 1 of the promising flaps to reconstruct the buccal-penetrating defects.

The triglyceride glucose index is associated with future cardiovascular disease nonlinearly in middle-aged and elderly Chinese adults.

OBJECTIVE: We aimed to investigate the association between triglyceride glucose index and cardiovascular disease (CVD) development in the Chinese middle-aged and elderly population using the China Health and Retirement Longitudinal Study dataset 2011-2018. METHODS: Basic characteristics of participants, including sociodemographic information, and health conditions, were acquired. Logistic regression analyses and restricted cubic spline regression analyses were conducted to investigate the association between the triglyceride glucose index and future CVD risks. Subgroup analyses were performed to evaluate potential interaction. RESULTS: Seven hundred fifty-three of 6114 (12.3%) participants have developed CVD in 2018 over an approximately 7-year follow-up. The logistic regression analysis exhibited that compared to the lowest triglyceride glucose index group, the multivariable OR for future CVD was 0.985 (95%CI 0.811-1.198) in the T2 triglyceride glucose index group and 1.288 (95%CI 1.068-1.555) in the T3 TyG index (P for trend 0.006). The restricted cubic spline regression analysis showed the nonlinear association between triglyceride glucose index and CVD incidence; the cut-off values were 8.07 and 8.57, respectively, after total adjustment. Gender, fast blood glucose, and triglycerides interacted with triglyceride glucose index and CVD except for BMI. CONCLUSION: The triglyceride glucose index was nonlinearly related to the risk of future cardiovascular disease in the middle-aged and elderly Chinese population.

Triglyceride glucose index exacerbates the risk of future cardiovascular disease due to diabetes: evidence from the China Health and Retirement Longitudinal Survey (CHARLS).

OBJECTIVE: We aimed to investigate the effect of the triglyceride glucose (TyG) index on the association between diabetes and cardiovascular disease (CVD). METHODS: Data from 6,114 individuals were extracted and analyzed from the China Health and Retirement Longitudinal Survey (CHARLS) from 2011 to 2018. Logistic regression analyses were conducted to assess the relationship between diabetes and CVD across the various TyG index groups. The statistical method of subgroup analysis was used to determine the correlation between diabetes and CVD for each TyG index group by sex, history of hypertension and dyslipidemia, smoking, and drinking. RESULTS: Diabetes was positively associated with CVD risk after adjustment in 2011(odds ratio (OR) 1.475, 95% CI 1.243-1.752, P < 0.001). There was a gradient increase in the OR for new-onset CVD in 2018 due to diabetes at baseline across the value of the TyG index based on a fully adjusted model (P for trend < 0.05). The ORs of diabetes at baseline for CVD in 2018 were 1.657 (95% CI 0.928-2.983, P = 0.098), 1.834(95% CI 1.064-3.188, P = 0.037) and 2.234(95% CI 1.349-3.673, P = 0.006) for T1, T2 and T3 of the TyG index respectively. The gradient of increasing risk of CVD still existed among those with hypertension and nondrinkers in the subgroup analysis. CONCLUSION: Elevated TyG index strengthens the correlation between diabetes mellitus and CVD in middle-aged and elderly Chinese adults.

Alarming changes in the global burden of mental disorders in children and adolescents from 1990 to 2019: a systematic analysis for the Global Burden of Disease study.

Mental disorders account for a large and increasing health burden worldwide, as shown in the Global Burden of Diseases (GBD) Study 2010. Unpacking how this burden in children and adolescents varies with sex, geographical regions, and ethnicities and how it has changed in the last 3 decades are important to improve the existing public health policies and prevention strategies. The study was conducted using GBD 2019 database. The burden of children and adolescents' (< 20 years old) mental disorders was displayed as prevalence, incidence, disability-adjusted life-years (DALYs), years of life lost, and years lived with disability globally between 1990 and 2019. The number of DALYs in children and adolescents diagnosed with mental disorders was 21.5 million (95% CI: 15.2-29.6 million) in 2019. From 1990 to 2019, the age-standardized rates of DALYs of mental disorders increased from 803.8 per 100,000 (95% CI: 567.7-1104.3 per 100,000) to 833.2 per 100,000 (95% CI: 589.0-1146.1 per 100,000) population. Over the past 30 years, there had been a huge increase in the number of individuals suffering from anxiety disorders, major depressive disorders, and conduct disorders including an alarming increase in the rate of eating disorders such as 24.3% in bulimia nervosa and 17.0% in anorexia nervosa. Globally, 8.8% of children and adolescents have been diagnosed with varieties of mental illnesses, accounting for a heavy disease burden on public health. Besides, the worldwide increasing rates of anxiety disorders, major depressive disorders, and eating disorders have brought considerable challenges to public health undertakings, for which further prevention and treatment countermeasures are urgently needed.

Molecular Identification of Tumor-Derived Extracellular Vesicles Using Thermophoresis-Mediated DNA Computation.

Molecular profiling of tumor-derived extracellular vesicles (tEVs) holds great promise for non-invasive cancer diagnosis. However, sensitive and accurate identification of tEVs is challenged by the heterogeneity of EV phenotypes which reflect different cell origins. Here we present a DNA computation device mediated by thermophoresis for detection of tEVs. The strategy leverages the aptamer-based logic gate using multiple protein biomarkers on single EVs as the input and thermophoretic accumulation to amplify the output signals for highly sensitive and specific profiling of tEVs. Employing this platform, we demonstrate a high accuracy of 97% for discrimination of breast cancer (BC) patients and healthy donors in a clinical cohort (n = 30). Furthermore, molecular phenotyping assessed by tEVs is in concordance with the results from tissue biopsy in BC patients. The thermophoresis-mediated molecular computation on EVs thus provides new opportunities for accurate detection and classification of cancers.

NEK7 promotes gastric cancer progression as a cell proliferation regulator.

BACKGROUND: Gastric cancer is one of the most common malignant tumors of the digestive system. However, its targeted therapy develops at a slow pace. Thus, exploring the mechanisms of the malignant behavior of gastric cancer cells is crucial to exploit its treatment. Mammalian never-in-mitosis A (NIMA)-related kinases (NEKs) are considered to play a significant role in cancer cell proliferation. However, no study has reported on NIMA family proteins in gastric cancer. METHODS: Bioinformatics analysis was employed to clarify the expression patterns of NEK1-NEK11 and their effects on prognosis. The effects of NEK7 on immune infiltration and NEK7 related pathways were also analyzed. At the cell level, 5-ethynyl-2-deoxyuridine, cell cycle, and Cell Counting Kit-8 assays were utilized to clarify the effect of NEK7 on gastric cancer cell proliferation. A mouse subcutaneous model revealed the regulating effect of NEK7 on gastric cancer cell proliferation in vivo. RESULTS: Bioinformatics analysis revealed that NEK7 is upregulated in gastric cancer and is related to poor prognosis. NEK7 is also related to T-stage, which is closely associated with cell proliferation. Further analysis showed that NEK7 was correlated with infiltration of multiple immune cells as well as gastric cancer-related pathways. Cell experiments indicated the promoting effect of NEK7 on cell proliferation, while the absence of NEK7 could lead to inhibition of gastric cancer proliferation and G1/S arrest. CONCLUSION: NEK7 exerts a regulatory effect on cell proliferation and is closely related to tumor immune infiltration.

Thermophoretic Detection of Exosomal microRNAs by Nanoflares.

Exosomal microRNAs (miRNAs) are reliable and noninvasive biomarkers for the early diagnosis of cancer. Yet, accurate and feasible detection of exosomal miRNAs is often hampered by the low abundance of miRNAs in exosomes and the requirement for RNA extraction in large sample volumes. Here we show a thermophoretic sensor implemented with nanoflares for in situ detection of exosomal miRNAs, without resorting to either RNA extraction or target amplification. Thermophoretic accumulation of nanoflare-treated exosomes leads to an amplified fluorescence signal upon the binding of exosomal miRNAs to nanoflares, allowing for direct and quantitative measurement of exosomal miRNAs down to 0.36 fM in 0.5 µL serum samples. One of the best markers, exosomal miR-375, showed an accuracy of 85% for detection of estrogen receptor-positive breast cancer at early stages (stages I, II). This work provides a feasible tool to improve the diagnosis of cancer.

Disulfide bond-based self-crosslinked carbon-dots for turn-on fluorescence imaging of GSH in living cells.

Herein, we report a turn-on fluorimetric nanoprobe for intracellular glutathione (GSH) imaging. The principle of this probe is designed on the basis of the selective reduction between GSH and disulfide bond-based self-crosslinked red emissive carbon dots (abbreviated as SCCDs). The nanoprobe (i.e., SCCDs) was facilely fabricated from thiol-modified carbon dots (CDs) through oxidation in the presence of H2O2, and its fluorescence was greatly reduced due to the effect of aggregation induced quenching (AIQ). However, in the presence of GSH, the SCCDs were separated into many single CDs. As a result, the fluorescence of the nanoprobe was recovered in a GSH concentration-dependent manner, which is the basis for the quantitative analysis of GSH. The nanoprobe shows excellent specificity and a linear range from 0 to 0.15 mM towards GSH with a limit of detection (LOD) of 5.7 µM. Finally, the nanoprobe was demonstrated to have extremely low cytotoxicity, and was successfully applied for monitoring the GSH level in living cells. This work would provide a promising probe for the research of GSH in cytobiology.

Deep Learning in Automated Region Proposal and Diagnosis of Chronic Otitis Media Based on Computed Tomography.

OBJECTIVES: The purpose of this study was to develop a deep-learning framework for the diagnosis of chronic otitis media (COM) based on temporal bone computed tomography (CT) scans. DESIGN: A total of 562 COM patients with 672 temporal bone CT scans of both ears were included. The final dataset consisted of 1147 ears, and each of them was assigned with a ground truth label from one of the 3 conditions: normal, chronic suppurative otitis media, and cholesteatoma. A random selection of 85% dataset (n = 975) was used for training and validation. The framework contained two deep-learning networks with distinct functions: a region proposal network for extracting regions of interest from 2-dimensional CT slices; and a classification network for diagnosis of COM based on the extracted regions. The performance of this framework was evaluated on the remaining 15% dataset (n = 172) and compared with that of 6 clinical experts who read the same CT images only. The panel included 2 otologists, 3 otolaryngologists, and 1 radiologist. RESULTS: The area under the receiver operating characteristic curve of the artificial intelligence model in classifying COM versus normal was 0.92, with sensitivity (83.3%) and specificity (91.4%) exceeding the averages of clinical experts (81.1% and 88.8%, respectively). In a 3-class classification task, this network had higher overall accuracy (76.7% versus 73.8%), higher recall rates in identifying chronic suppurative otitis media (75% versus 70%) and cholesteatoma (76% versus 53%) cases, and superior consistency in duplicated cases (100% versus 81%) compared with clinical experts. CONCLUSIONS: This article presented a deep-learning framework that automatically extracted the region of interest from two-dimensional temporal bone CT slices and made diagnosis of COM. The performance of this model was comparable and, in some cases, superior to that of clinical experts. These results implied a promising prospect for clinical application of artificial intelligence in the diagnosis of COM based on CT images.