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Abstract 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.

ObjectiveNumerous studies emphasize the pivotal role of inflammation in metabolic dysfunction-associated steatotic liver disease (MASLD) development. Some link specific systemic immune biomarkers (e.g., systemic immuno-inflammatory index [SII], neutrophil-to-albumin ratio [NPAR] and neutrophil-to-lymphocyte ratio [NLR]) to hepatic steatosis risk. However, the relevance of other markers like systemic immune-inflammation index [SIRI], platelet-to-lymphocyte ratio [PLR] and lymphocyte/monocyte ratio [LMR] in MASLD remains unclear. Limited literature covers all six markers together. This study aims to investigate the association between SII, SIRI, LMR, NLR, PLR, and NPAR and MASLD, assessing their predictive value.MethodsIn this cross-sectional analysis of adults from NHANES (2007–2018), we investigated the relationship between six systemic immune biomarkers, stratified by quartiles: quartile1 (Q1), quartile2 (Q2), quartile3 (Q3) and quartile4 (Q4), and the outcome of MASLD assessed by Fatty Liver Index (FLI) and United States Fatty Liver Index (USFLI). Logistic regression and restricted cubic splines (RCS) were employed to assess the association between systemic immune biomarkers and MASLD risks. Propensity score matching controlled for potential confounders, and receiver operating characteristic (ROC) curve analysis evaluated the biomarkers’ predictive performances for MASLD. Subgroup and interaction analysis were conducted to explore the effects of systemic immune biomarkers on MASLD risks. Multicollinearity was quantified using the variance inflation factor.ResultsIn total, 14,413 participants were included and 6,518 had MASLD. Compared with non-MASLD, participants with MASLD had higher SII, SIRI, NLR, PLR, and NPAR (p 0.05). The prevalence of MASLD increased with the Q4 of SII [OR = 1.47, 95%CI (1.24, 1.74)], SIRI [OR = 1.30, 95%CI (1.09, 1.54)], NLR [OR = 1.25, 95%CI (1.04, 1.49)], PLR [OR = 1.29, 95%CI (1.09, 1.53)] and NPAR [OR = 1.29, 95%CI (1.09, 1.54)] compared to the Q1 after adjusting for the bias caused by potential confounders. However, the propensity score matching analysis only supported an association between the highest SII, SIRI, NLR NPAR and the risk of MASLD. The results of the subgroup analysis showed considerable robustness in the relationship.ConclusionHigher SII, SIRI, NLR and NPAR were positively associated with a heightened risk of MASLD. NPAR showed the superior predictive value, followed by SII, SIRI and NLR. This needs to be validated in additional longitudinal studies and clinical trials.

BackgroundTemporal bone computed tomography (CT) helps diagnose chronic otitis media (COM). However, its interpretation requires training and expertise. Artificial intelligence (AI) can help clinicians evaluate COM through CT scans, but existing models lack transparency and may not fully leverage multidimensional diagnostic information. ObjectiveWe aimed to develop an explainable AI system based on 3D convolutional neural networks (CNNs) for automatic CT-based evaluation of COM. MethodsTemporal bone CT scans were retrospectively obtained from patients operated for COM between December 2015 and July 2021 at 2 independent institutes. A region of interest encompassing the middle ear was automatically segmented, and 3D CNNs were subsequently trained to identify pathological ears and cholesteatoma. An ablation study was performed to refine model architecture. Benchmark tests were conducted against a baseline 2D model and 7 clinical experts. Model performance was measured through cross-validation and external validation. Heat maps, generated using Gradient-Weighted Class Activation Mapping, were used to highlight critical decision-making regions. Finally, the AI system was assessed with a prospective cohort to aid clinicians in preoperative COM assessment. ResultsInternal and external data sets contained 1661 and 108 patients (3153 and 211 eligible ears), respectively. The 3D model exhibited decent performance with mean areas under the receiver operating characteristic curves of 0.96 (SD 0.01) and 0.93 (SD 0.01), and mean accuracies of 0.878 (SD 0.017) and 0.843 (SD 0.015), respectively, for detecting pathological ears on the 2 data sets. Similar outcomes were observed for cholesteatoma identification (mean area under the receiver operating characteristic curve 0.85, SD 0.03 and 0.83, SD 0.05; mean accuracies 0.783, SD 0.04 and 0.813, SD 0.033, respectively). The proposed 3D model achieved a commendable balance between performance and network size relative to alternative models. It significantly outperformed the 2D approach in detecting COM (P≤.05) and exhibited a substantial gain in identifying cholesteatoma (P

Abstract Magnetic nanofluid possesses the characteristic of interfering with the propagation of the magnetic field, endowing it with the sensing property in motion. However, the residual adhesion of magnetic nanofluid as it flows over solid surfaces remains an open question. Liquid marbles allow for quantities of liquids to be encapsulated by hydrophobic particles, ensuring a unique nonstick property for utilization in different applications. In this study, being capsuled by hydrophobic nano‐/microscale powders, a magnetic nanofluid‐based liquid marble (MNLM) with well mechanical stability has been fabricated. A magnetic nanofluid posture detector (MNPD), which consists of an MNLM, a magnetic tube, and coils, has been assembled that can convert mechanical energy to electricity as it freely rolls on the solid surface. Gesture recognition can be achieved when combining five MNPDs with fingers. The fabricated MNPD possesses a good signal recognition capability, which can separately distinguish the bending of each finger. Moreover, a variety of language hand gestures with specific meanings (digits, letters, “OK,” and “I Love You”) can be further recognized through corresponding combinations. The potential of MNPD in the realm of gesture recognition will offer a novel avenue for flexible wearables.

Abstract Triple-negative breast cancer (TNBC) is a highly metastatic and heterogeneous type of breast cancer with poor outcomes. Precise, non-invasive methods for diagnosis, monitoring and prognosis of TNBC are particularly challenging due to a paucity of TNBC biomarkers. Glycans on extracellular vesicles (EVs) hold the promise as valuable biomarkers, but conventional methods for glycan analysis are not feasible in clinical practice. Here, we report that a lectin-based thermophoretic assay (EVLET) streamlines vibrating membrane filtration (VMF) and thermophoretic amplification, allowing for rapid, sensitive, selective and cost-effective EV glycan profiling in TNBC plasma. A pilot cohort study shows that the EV glycan signature reaches 91% accuracy for TNBC detection and 96% accuracy for longitudinal monitoring of TNBC therapeutic response. Moreover, we demonstrate the potential of EV glycan signature for predicting TNBC progression. Our EVLET system lays the foundation for non-invasive cancer management by EV glycans.

Abstract 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. Graphical Abstract The up-regulated lncRNA Anxa10-203 in the trigeminal ganglion of CCI-ION mice interacts with DHX30 to contribute to the excitability of TG neurons and orofacial pain by enhancing Mc1r mRNA stability.

Abstract Robotic fingers with multidirectional tactile perception are of great importance for the robotic exploration of complex unknown space, especially in environments in which visualization is not possible. Unfortunately, most existing tactile sensors for robotic fingers cannot detect multidirectional forces, which greatly limits their potential for further development in navigating complex environments. Here, we demonstrate a soft magnetoelectric finger (SMF) that can achieve self-generated-signal and multidirectional tactile sensing. The SMF is composed of two parts: a ‘finger’ covered with a skin-like flexible sheath containing five liquid metal (LM) coils and a ‘phalangeal bone’ containing a magnet. Due to the changes in magnetic flux through the LM coils caused by external forces, diverse induced voltages are generated and collected in real-time, which can be explained by Maxwell’s numerical simulation. By the analysis of the signals generated by the five LM coils, the SMF can detect forces in varied directions and distinguish 6 different common objects with varied Young’s moduli with an accuracy of 97.46%. These capabilities make the SMF suitable for complex unknown space exploration tasks, as proved by the black box exploration. The SMF can enable the development of self-generated-signal and multidirectional tactile perception for future robots.

Abstract Monitoring the position of orthopedic implants in vivo is paramount for enhancing postoperative rehabilitation. Traditional radiographic methods, although effective, pose inconveniences to patients in terms of specialized equipment requirements and delays in rehabilitation adjustment. Here, a nonradiographic design concept for real‐time and precisely monitoring the position of in vivo orthopedic implants is presented. The monitoring system encompasses an external magnetic field, a three‐dimensional (3D)‐printed superparamagnetic intervertebral body fusion cage (SIBFC), and a magnetometer. The SIBFC with a polyetheretherketone framework and a superparamagnetic Fe3O4 component was integrally fabricated by the high‐temperature selective laser sintering technology. Owing to the superparamagnetic component, the minor migration of SIBFC within the spine would cause the distribution change of the magnetic induction intensities, which can be monitored in real‐time by the magnetometer no matter in the static states or dynamic bending motions. Besides horizontal migration, occurrences of intervertebral subsidence in the vertical plane of the vertebrae can also be effectively distinguished based on the obtained characteristic variations of magnetic induction intensities. This strategy exemplifies the potential of superparamagnetic Fe3O4 particles in equipping 3D‐printed orthopedic implants with wireless monitoring capabilities, holding promise for aiding patients' rehabilitation.

IntroductionUltrasound is instrumental in the early detection of thyroid nodules, which is crucial for appropriate management and favorable outcomes. However, there is a lack of clinical guidelines for the judicious use of thyroid ultrasonography in routine screening. Machine learning (ML) has been increasingly used on big data to predict clinical outcomes. This study aims to leverage the ML approach in assessing the risk of thyroid nodules based on common clinical features.MethodsData were sourced from a Chinese cohort undergoing routine physical examinations including thyroid ultrasonography between 2013 and 2023. Models were established to predict the 3-year risk of thyroid nodules based on patients’ baseline characteristics and laboratory tests. Four ML algorithms, including logistic regression, random forest, extreme gradient boosting, and light gradient boosting machine, were trained and tested using fivefold cross-validation. The importance of each feature was measured by the permutation score. A nomogram was established to facilitate risk assessment in the clinical settings.ResultsThe final dataset comprised 4,386 eligible subjects. Thyroid nodules were detected in 54.8% (n=2,404) individuals within the 3-year observation period. All ML models significantly outperformed the baseline regression model, successfully predicting the occurrence of thyroid nodules in approximately two-thirds of individuals. Age, high-density lipoprotein, fasting blood glucose and creatinine levels exhibited the highest impact on the outcome in these models. The nomogram showed consistency and validity, providing greater net benefits for clinical decision-making than other strategies.ConclusionThis study demonstrates the viability of an ML-based approach in predicting the occurrence of thyroid nodules. The findings highlight the potential of ML models in identifying high-risk individuals for personalized screening, thereby guiding the judicious use of ultrasound in this context.

Abstract 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.

Abstract 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.

Abstract Background The triglyceride–glucose (TyG) index is validated as a reliable biomarker of insulin resistance and an independent predictor of cardiovascular prognosis. However, the prognostic value of the TyG index in patients on dialysis with coronary artery disease (CAD) remained unexplored. This study aimed to determine the association between the TyG index and CAD severity and mortality in these patients. Methods A total of 1061 dialysis patients with CAD were enrolled in this multi-center cohort study from January 2015 to June 2021. The extent and severity of CAD were evaluated using the multivessel disease and Gensini score (GS). Patients were followed up for all-cause death and cardiovascular death. Results The multivariable logistic regression model indicated that the TyG index was significantly associated with multivessel disease (odds ratio [OR] 1.51, 95% confidence interval [CI] 1.18–1.94, P = 0.001), and high GS (OR 1.33, 95% CI 1.10–1.61, P = 0.003). After adjusting for baseline risk factors, the hazards of all-cause death and cardiovascular death were 1.23 (95% CI 1.06–1.43, P = 0.007), and 1.33 (95% CI 1.11–1.59, P = 0.002), independent of CAD severity. Restricted cubic spline analysis identified a dose–response association between the TyG index and both CAD severity and mortality (all P for nonlinearity > 0.05). When modeling the TyG index as a categorical variable, these independent associations remained. Subgroup analyses did not substantially modify the results. Furthermore, incorporating the TyG index into the existing risk prediction model improved the predictive accuracy for all-cause death and cardiovascular death, as evaluated by C-statistic, continuous net reclassification improvement, and integrated discrimination improvement. Conclusions In patients on dialysis with CAD, the TyG index was significantly associated with more severe CAD as well as mortality. These results highlight the clinical importance of the TyG index for assessing CAD severity and risk stratification in patients on dialysis with CAD.

With the awakening of female consciousness, women's participation in sports has gradually gained autonomy and agency. However, Chinese women still face numerous restrictions in combat sports, hindering the development of this industry. Based on years of practice and research experience in the field, we summarize some general and specific issues, such as stigmatization and the constraints of traditional Chinese thinking. These issues need attention and consideration in the pursuit of gender equality in sports in the future.

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.

BackgroundHER2-positive molecular breast cancer subtypes are characterized by high aggressiveness and malignancy, and their metastasis and mortality rates are among the highest of all types of breast cancer. The use of anti-HER2-targeted agents in neoadjuvant therapy has significantly improved the prognosis of patients with HER2-positive breast cancer. In this study, we investigated the efficacy and safety of a neoadjuvant Chinese THP regimen (docetaxel, trastuzumab biosimilar TQB211 plus the pertuzumab biosimilar TQB2440 or pertuzumab) for ER/PR-negative and HER2-positive breast cancer in China.MethodAll enrolled patients received the THP regimen (T: docetaxel 75 mg/m2 per cycle; H: trastuzumab biosimilar TQB211 8 mg/kg in the first cycle and 6 mg/kg maintenance dose in cycles 2 to 4; P: pertuzumab biosimilar TQB2440 or pertuzumab 840 mg in the first cycle, maintenance dose 420 mg in cycles 2 to 4) every 3 weeks for 4 cycles. The biosimilar TQB2440 pertuzumab and pertuzumab were randomly assigned to patients. Docetaxel, TQB211, and TQB2440 were all developed by Chiatai Tianqing. The primary endpoint was the complete pathological response (pCR) in the breast, and the secondary endpoint was cardiac safety. ResultsOf the 28 eligible patients, 19 (67.9%) achieved tpCR. The tpCR rate was higher than in the NeoSphere trial (pCR63.2%) and the PEONY study (tpCR52.5%). The adverse events that occurred most frequently were leukopenia and neutropenia, with incidence rates of 82.1% and 75.0%, respectively. Of these, grade 3 leukopenia and neutropenia occupied 46.4% and 35.7%. Other grade 3 or higher adverse events were bone marrow suppression (7.1%), lymphopenia (3.6%), and anemia (3.6%). There were no events of heart failure in patients and no patient died during the neoadjuvant phase. ConclusionDomestic dual-target HP has a more satisfactory efficacy and safety in the neoadjuvant phase of treatment.Clinical trial registrationhttps://clinicaltrials.gov/study/NCT05985187, NCT05985187.

Abstract Bisphenol A (BPA) is a monomer to produce polycarbonate plastics and can be released into the environment through human activities, leading to its accumulation in animals, plants and humans through direct contact or environmental exposure. Epidemiological studies have reported that BPA exposure is associated with metabolic disorders. The pancreas is an important endocrine organ and plays an important role in metabolic disorders. To explore the possible long-term effects of BPA exposure on neonatal health, bioinformatic methods were used to identify differentially expressed genes (DEGs) by comparing the neonatal pancreas after maternal exposure to BPA with the adult pancreas after direct exposure to BPA. Two datasets about BPA exposure and pancreatic abnormality, GSE82175 and GSE126297 in Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) were collected. Control (or BPA-exposed) offspring (maternal exposure) and Control (or BPA-exposed) adults (direct exposure) were defined as Control (or BPA) groups. The results showed that BPA disturbed the normal function of the pancreas in both offspring and adults, with offspring showing higher susceptibility to BPA than adults. Seventeen insulin secretion-related DEGs (Stxbp5l, Fam3d, Mia3, Igf1, Hif1a, Aqp1, Kif5b, Tiam1, Map4k4, Cyp51, Pde1c, Rab3c, Arntl, Clock, Edn3, Kcnb1, and Krt20) in the BPA group were identified, and 15 regulator DEGs (Zfp830, 4931431B13Rik, Egr1, Ddit4l, Cep55, G530011O06Rik, Hspa1b, Hspa1a, Cox6a2, Ibtk, Banf1, Slc35b2, Golt1b, Lrp8, and Pttg1) with opposite expression trends and a regulator gene Cerkl with the similar expression trend in the Control and BPA groups were identified. Hif1α might be an important molecular target for pancreatic cancer caused by BPA exposure, and pregnancy is a critical window of susceptibility to BPA exposure.

Kermesite (Sb2S2O), a needle-like unstable secondary oxysulfide, has made visible advancements in optimizing its triclinic crystal system through twinning discovery. However, research on twinning behavior at micro and nano scales, including its growth mechanisms and impact on kermesite morphologies, remains notably scarce. Our study focuses on kermesite crystal clusters from a private collection in Yunnan, China, confirming the chemical formula as Sb2S1.97O1.03 through EPMA. Single-crystal XRD yielded refined unit cell parameters (a = 8.153(5) Å, b = 10.717(7) Å, c = 5.796(3) Å; α = 102.836(10)°, β = 110.556(8)°, γ = 100.999(12)°), revealing space group P1¯ with Z = 4 and indicating twinning with a ratio of 27.4%. Remarkably, a Transmission Electron Microscope (TEM) provided the first direct observation of twinning in natural kermesite, revealing rotational twins with varying widths and lengths (ranging from 100 nm to several millimeters). Analysis and simulation elucidated that rotational twins, generated by a 180° rotation, align with the mineral’s elongation direction along the [Sb2S2O4]n chains (a-axis), challenging the conventional long-axis direction (b-axis) for crystal growth. This study proposes a symbiotic relationship between kermesite growth and twinning, suggesting that the observed X-shaped growth in crystal clusters results from the collaboration of single crystals (growing along b) and twins (growing along a) in the unit cell. These findings contribute to our understanding of kermesite’s structural complexities and the potential growth and formation mechanism of crystal clusters.

Abstract 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.

Background: The no-/slow-reflow phenomenon following primary percutaneous coronary intervention (PCI) in patients with ST-elevation myocardial infarction (STEMI)is associated with poor prognosis. The early identification of high-risk patients with no-/slow-reflow is critical. This study aimed to evaluate the predictive ability of the Canada Acute Coronary Syndrome (C-ACS) risk score for no-/slow-reflow in these patients. Methods: Patients with STEMI who underwent primary PCI were consecutively enrolled and divided into three groups based on their C-ACS scores: 0, 1, and ≥2. The C-ACS score was computed using the four clinical variables evaluated at admission (one point for each): age ≥75 years, heart rate >100 beats/min, systolic blood pressure 1. No-/slow-reflow was defined as thrombolysis in a myocardial infarction flow grade of 0–2 after primary PCI. The predictive ability of the C-ACS score for no-/slow-reflow was evaluated using a receiver operating characteristic curve. Results: A total of 834 patients were enrolled, of whom 109 (13.1 %) developed no-/slow-reflow. The incidence of no-/slow-reflow increased from the C-ACS 0 group to the C-ACS ≥2 group (6.1 % vs 17.7 % vs 34.3 %, respectively, p

Wilderness plays a crucial role in biodiversity conservation, and its preservation represents a pivotal objective emphasized in the Post-2020 Global Biodiversity Framework (GBF). Nonetheless, wilderness frequently faces threats from the escalating impact of human activities, leading to significant repercussions on diverse ecological processes. Despite the abundance of previous studies on wilderness, there has been a limited focus on the temporal dynamics at the local scale, as well as on identifying the conservation priorities in terms of their ecosystem services. In this study, taking the Lhasa River Basin in the Qinghai-Tibet Plateau of China as an example, the spatio-temporal variations of wilderness were analyzed, and conservation priorities of them were further identified based on ecosystem services. The results revealed a persistent decline in the wilderness from 1990 to 2020, particularly in terms of bare land and grassland. Furthermore, we identified that 33.56% of the remaining wilderness necessitated special attention. These findings offer valuable insights into potential future threats to wilderness and hold critical importance for formulating regional conservation strategies at the local scale.

Abstract 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.

Abstract Objective Chronic kidney disease (CKD) patients with coronary artery disease (CAD) in the intensive care unit (ICU) have higher in-hospital mortality and poorer prognosis than patients with either single condition. The objective of this study is to develop a novel model that can predict the in-hospital mortality of that kind of patient in the ICU using machine learning methods. Methods Data of CKD patients with CAD were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Boruta algorithm was conducted for the feature selection process. Eight machine learning algorithms, such as logistic regression (LR), random forest (RF), Decision Tree, K-nearest neighbors (KNN), Gradient Boosting Decision Tree Machine (GBDT), Support Vector Machine (SVM), Neural Network (NN), and Extreme Gradient Boosting (XGBoost), were conducted to construct the predictive model for in-hospital mortality and performance was evaluated by average precision (AP) and area under the receiver operating characteristic curve (AUC). Shapley Additive Explanations (SHAP) algorithm was applied to explain the model visually. Moreover, data from the Telehealth Intensive Care Unit Collaborative Research Database (eICU-CRD) were acquired as an external validation set. Results 3590 and 1657 CKD patients with CAD were acquired from MIMIC-IV and eICU-CRD databases, respectively. A total of 78 variables were selected for the machine learning model development process. Comparatively, GBDT had the highest predictive performance according to the results of AUC (0.946) and AP (0.778). The SHAP method reveals the top 20 factors based on the importance ranking. In addition, GBDT had good predictive value and a certain degree of clinical value in the external validation according to the AUC (0.865), AP (0.672), decision curve analysis, and calibration curve. Conclusion Machine learning algorithms, especially GBDT, can be reliable tools for accurately predicting the in-hospital mortality risk for CKD patients with CAD in the ICU. This contributed to providing optimal resource allocation and reducing in-hospital mortality by tailoring precise management and implementation of early interventions.

Livelihoods around nature reserve (NRs), which are highly dependent on the harvest of endangered macrofungi (Cordyceps sinensis, Tricholoma matsutake), challenge biodiversity conservation on the Qinghai-Tibetan Plateau (QTP). Previous studies have attempted to capture the impact of rural livelihood assets through the conceptual framework of a sustainable livelihood and a multinomial logit model to find a possible solution. Although communities around NRs face more severe green traps, they are also regions with limited scientific evidence on this topic. We selected 7 NRs on the southeastern edge of the QTP as the study area, where NRs are densely distributed. Data were collected through a household survey and unstructured interviews with administrators, and we quantitatively analyzed the relationship between livelihood assets and livelihood strategies. K-mean cluster analysis related to income sources was used to identify three distinctive livelihood strategies: livestock, nonfarm, and gathering/livestock strategies. The results indicate that human, natural, and financial assets had significant influences on livelihood strategies and that the choice of livelihood strategy varied by livelihood assets. The multinomial logit model showed that enhancing financial and human assets facilitated the adoption of nonfarm strategies, while nature assets enhanced the propensity toward adopting the gathering/livestock strategy. Hence, this research recommends that policy interventions aimed at both endangered macrofungal conservation and livelihood development should give priority to improving the human assets of households living around NRs to achieve sustainable livelihood development.

Abstract 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.

Abstract Objective Chinese diabetes society has published the new diagnostic criteria for diabetes in China (2020 edition). We aimed to investigate the predictive value of new diabetes-diagnosed criteria for cardiovascular diseases (CVD). Methods A total of 5884 individuals from the China Health and Retirement Longitudinal Study in 2011 and 2018 were enrolled. Baseline characteristics and outcome data were compared. The association between diabetes diagnosed by two criteria and future CVD was identified by Kaplan–Meier curves, Cox regression analyses, and receiver-operating characteristic analyses. Delong’s test was conducted to compare the predictive value for future CVD between diabetes diagnosed by the 2020 edition and diabetes diagnosed by the previous version. Results After multivariate adjustment, both diabetes diagnosed by the 2020 edition and diabetes diagnosed by the previous edition is associated with CVD (HR 1.607, 95% CI 1.221–2.115, P

Individual fish are vulnerable in hydropower reservoirs due to spillway and intake operations. It is essential to understand how reservoir forebay fish ecosystems respond to water levels, intake, and spillway regulation. This study aims to explore the fish entrainment risk of the Dawei Reservoir operation on the Dadu River in Sichuan, China, accounting for both intake and spillway operations under wet, normal, and dry seasonal reservoir water levels. Hydrodynamic variables, reservoir operation scenarios, and two fish species were used as indexes to analyze the fish entrainment risk. The simulation results showed that the fish entrainment risk was low under the Dawei intake operation schemes ranging from 0.84 × 103 to 5.97 × 103 m2. The results also showed that the fish entrainment risk was very high under the Dawei spillway operation in fish entrainment areas ranging from 3.90 × 104 to 2.08 × 105 m2. Based on the simulation results, the lowest fish entrainment risk happened with two intakes open and the reservoir water level at 2,640 m. The highest fish entrainment risk happened with five intakes open and the reservoir water level at 2,670 m. The results indicate that the long-term Dawei Reservoir regulation would not modify the fish entrainment risk at significant levels under the Dawei Reservoir operation schemes. HIGHLIGHTS A model was proposed to determine the fish entrainment risk.; The fish entrainment risk was low during the seasonal operation of intakes.; The maximum and minimum fish entrainment risks were established.; The fish entrainment risk was high under the spillway operation.; The long-term reservoir operation would not significantly affect the fish entrainment risk.;

Abstract Aldolase A (ALDOA) is an enzyme that plays an important role in glycolysis and gluconeogenesis, which is closely related to tumor metabolism. In this study, the overall roles of ALDOA in pan-cancer have been investigated from several aspects using databases and online analysis tools. Using the ONCOMINE database, the expression of ALDOA in various cancers was analyzed. The prognostic role of ALDOA was explored by PrognoScan, GEPIA, and Kaplan–Meier Plotter. The immune-related role of ALDOA and its downstream substrates was decided by TIMER, cBioPortal and String. Our data indicate that ALDOA expression level in lung adenocarcinoma, liver hepatocellular carcinoma, head and neck squamous cell carcinoma is higher than that in normal tissues. Increased expression of ALDOA often indicates a poor prognosis for patients. The correlation between ALDOA and immune infiltration among different tumors is very different. We also investigate the relationship between ALDOA and its upstream/downstream proteins. Our results showed that ALDOA could be used as a biomarker for the tumor prognosis, and could be correlated with the infiltrating levels of macrophages, CD4+ T cells and CD8+ T cells.

PurposeApproximately half of ST-segment elevation myocardial infarction (STEMI) patients who undergo revascularization present with coronary microvascular dysfunction. Dual antiplatelet therapy, consisting of aspirin and a P2Y12 inhibitor (e.g., clopidogrel or ticagrelor), is recommended to reduce rates of cardiovascular events after STEMI. The present study performed a pooled analysis of randomized controlled trials (RCTs) to compare effects of ticagrelor and clopidogrel on coronary microcirculation dysfunction in STEMI patients who underwent the primary percutaneous coronary intervention.MethodsThe PubMed, Embase, Cochrane Library, and Web of Science databases were searched for eligible RCTs up to September 2022, with no language restriction. Coronary microcirculation indicators included the corrected thrombolysis in myocardial infarction (TIMI) frame count (cTFC), myocardial blush grade (MBG), TIMI myocardial perfusion grade (TMPG), coronary flow reserve (CFR), and index of microcirculatory resistance (IMR).ResultsSeven RCTs that included a total of 957 patients (476 who were treated with ticagrelor and 481 who were treated with clopidogrel) were included. Compared with clopidogrel, ticagrelor better accelerated microcirculation blood flow [cTFC = −2.40, 95% confidence interval (CI): −3.38 to −1.41, p

Abstract Extensive research have been devoted to the exploration of multifunctional theranostic agents for cancer, but the poor tumor specificity and unsatisfactory treatment efficacy are some of the critical obstacles for their clinical translations. Herein, ferrocene‐carbon dot‐crosslinked nanoparticles (Fc‐CD NPs) were designed and fabricated for achieving highly specific and photothermal‐augmented chemodynamic therapy (CDT). The Fc‐CD NPs were found not only to inherit the immanent fluorescence, photoacoustic, and photothermal properties of carbon dots (CDs), but also be endowed with CDT that could occur selectively in tumor microenvironment (TME) due to the presence of Fc for triggering Fenton reaction. Moreover, the enlarged particle size of Fc‐CD NPs facilitated their effective accumulation at tumor sites, thus realizing great improvement for antitumor treatment outcomes. Once docking at tumor and being exposed to 660 nm laser irradiation, significantly amplified CDT effect of Fc‐CD NPs was observed due to heat‐accelerating generation of reactive oxygen species (ROS). More interestingly, since the produced ROS could in turn alleviate the thermal‐resistance of photothermal therapy (PTT), the therapeutic efficiency of integrated PTT and CDT was synergized to the maximum extent. This study on the one hand provides a facile approach to fabricate CDs‐based multifunctional theranostic nanoplatform with enhanced tumor accumulation and specificity, on the other hand emphasizes the merits of synergizing mutually beneficial therapeutic modalities for more efficient cancer therapy.

Abstract 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

Abstract The purpose of this study was to assess the feasibility of machine learning (ML) in predicting the risk of end-stage kidney disease (ESKD) from patients with chronic kidney disease (CKD). Data were obtained from a longitudinal CKD cohort. Predictor variables included patients’ baseline characteristics and routine blood test results. The outcome of interest was the presence or absence of ESKD by the end of 5 years. Missing data were imputed using multiple imputation. Five ML algorithms, including logistic regression, naïve Bayes, random forest, decision tree, and K-nearest neighbors were trained and tested using fivefold cross-validation. The performance of each model was compared to that of the Kidney Failure Risk Equation (KFRE). The dataset contained 748 CKD patients recruited between April 2006 and March 2008, with the follow-up time of 6.3 ± 2.3 years. ESKD was observed in 70 patients (9.4%). Three ML models, including the logistic regression, naïve Bayes and random forest, showed equivalent predictability and greater sensitivity compared to the KFRE. The KFRE had the highest accuracy, specificity, and precision. This study showed the feasibility of ML in evaluating the prognosis of CKD based on easily accessible features. Three ML models with adequate performance and sensitivity scores suggest a potential use for patient screenings. Future studies include external validation and improving the models with additional predictor variables.

Abstract Manufacturing abrasion‐resistant superhydrophobic matters is challenging due to the fragile feature of the introduced micro‐/nanoscale surface roughness. Besides the long‐term durability, large scale at meter level, and 3D complex structures are of great importance for the superhydrophobic objects used across diverse industries. Here it is shown that abrasion‐resistant, half‐a‐meter scaled superhydrophobic objects can be one‐step realized by the selective laser sintering (SLS) 3D printing technology using hydrophobic‐fumed‐silica (HFS)/polymer composite grains. The HFS grains serve as the hydrophobic guests while the sintered polymeric network provides the mechanical strength, leading to low‐adhesion, intrinsic superhydrophobic objects with desired 3D structures. It is found that as‐printed structures remained anti‐wetting capabilities even after undergoing different abrasion tests, including knife cutting test, rude file grinding test, 1000 cycles of sandpaper friction test, tape test and quicksand impacting test, illustrating their abrasion‐resistant superhydrophobic stability. This strategy is applied to manufacture a shell of the unmanned aerial vehicle and an abrasion‐resistant superhydrophobic shoe, showing the industrial customization of large‐scale superhydrophobic objects. The findings thus provide insight for designing intrinsic superhydrophobic objects via the SLS 3D printing strategy that might find use in drag‐reduce, anti‐fouling, or other industrial fields in harsh operating environments.

Background: Accurate motion tracking in head-mounted displays (HMDs) has been widely used in immersive VR interaction technologies. However, tracking the head motion of users at all times is not always desirable. During a session of HMD usage, users may make scene-irrelevant head rotations, such as adjusting the head position to avoid neck pain or responding to distractions from the physical world. To the best of our knowledge, this is the first study that addresses the problem of scene-irrelevant head movements. Methods: We trained a classifier to detect scene-irrelevant motions using temporal eyehead-coordinated information sequences. To investigate the usefulness of the detection results, we propose a technique to suspend motion tracking in HMDs where scene-irrelevant motions are detected. Results: /Conclusions Experimental results demonstrate that the scene-relevancy of movements can be detected using eye-head coordination information, and that ignoring scene-irrelevant head motions in HMDs improves user continuity without increasing sickness or breaking immersion.

Thimerosal has been widely used as a preservative in drug and vaccine products for decades. Due to the strong propensity to modify thiols in proteins, conformational changes could occur due to covalent bond formation between ethylmercury (a degradant of thimerosal) and thiols. Such a conformational change could lead to partial or even complete loss of desirable protein function. This study aims to investigate the effects of thimerosal on the capsid stability and antigenicity of recombinant human papillomavirus (HPV) 18 virus-like particles (VLPs). Dramatic destabilization of the recombinant viral capsid upon thimerosal treatment was observed. Such a negative effect on the thermal stability of VLPs preserved with thimerosal was shown to be dependent on the thimerosal concentration. Two highly neutralizing antibodies, 13H12 and 3C3, were found to be the most sensitive to thimerosal treatment. The kinetics of antigenicity loss, when monitored with 13H12 or 3C3 as probes, yielded two distinctly different sets of kinetic parameters, while the data from both monoclonal antibodies (mAbs) followed a biphasic exponential decay model. The potential effect of thimerosal on protein function, particularly for thiol-containing proteinaceous active components, needs to be comprehensively characterized during formulation development when a preservative is necessary.

BackgroundUnderstanding the burdens and trends of non-alcoholic fatty liver disease (NAFLD) is necessary for developing effective intervention strategies. In this study, Global Burden of Disease (GBD) 2019 study data were extracted and analyzed to elucidate trends of NAFLD.MethodsThe prevalence, incidence, disability-adjusted life year (DALY), and death rates of NAFLD in geographic populations worldwide from 1990 to 2019 were extracted from the GBD 2019 study data. The global temporal trend of NAFLD from 1990 to 2019 was evaluated using estimated annual percentage changes (EAPCs) and age-standardized rates.ResultsGlobally, between 1999 and 2019, the age-standardized prevalence rate of NAFLD increased, with EAPCs of 0.77 [95% CI (0.69, 0.85)], whereas the DALY and Death rates decreased, with EAPCs of –0.82 [95% CI (–0.92, –0.71)], and –0.67 [95% CI (–0.76, –0.58)], respectively. Geographically, the age-standardized prevalence rate showed the most serious upward trend in high-income North America with an EAPC of 0.98 [95% CI (0.95, 1.02)], and the age-standardized incidence rate showed an upward trend in Central Asia with an EAPC of 3.17 [95% CI (2.2, 2.49)]. The most significant upward trend of DALY and death rates appeared in Eastern Europe, with EAPCs of 4.06 [95% CI (3.31, 4.82)], and 3.36 [95% CI (2.77, 3.96)], respectively. At the country level, the age-standardized rates showed an upward trend in Armenia, Belarus, and Republic of Korea. Regarding age groups, the percentage change of prevalence was the highest in the 40 to 44 group [0.29 (0.26, 0.34)] from 1990 to 2019; the percentage change of incidence was the highest in the 85 to 89 group [0.46 (0.12, 0.71)] from 1990 to 2019; the percentage change of DALY was the highest in the 80 to 84 group [0.25 (0.11, 0.39)] from 1990 to 2019; and the percentage change of death rate was the highest in the 15 to 19 group [0.36 (0.17, 0.60)] from 1990 to 2019. The percentage change of prevalence of liver cancer due to NASH was the highest in the group of 85 to 89, whereas those of incidence, DALY, and death were the highest in the group above 95 from 1990 to 2019. Regarding the sociodemographic index (SDI), the highest age-standardized prevalence, incidence, and Death rates of NAFLD occurred in middle-SDI countries, and the highest DALY rates of NAFLD occurred in low-SDI countries.ConclusionGlobal NAFLD burdens have increased since 1990. Our findings provide a reference for policymakers to reduce the burden of NAFLD, especially in middle and low-SDI countries.

BackgroundCoronary microvascular dysfunction (CMD) is a pathophysiological feature of diabetic heart disease. However, whether sodium-glucose cotransporter 2 (SGLT2) inhibitors protect the cardiovascular system by alleviating CMD is not known.ObjectiveWe observed the protective effects of empagliflozin (EMPA) on diabetic CMD.Materials and methodsThe mice were randomly divided into a db/db group and a db/db + EMPA group, and db/m mice served as controls. At 8 weeks of age, the db/db + EMPA group was given empagliflozin 10 mg/(kg⋅d) by gavage for 8 weeks. Body weight, fasting blood glucose and blood pressure were dynamically observed. Cardiac systolic and diastolic function and coronary flow reserve (CFR) were detected using echocardiography. The coronary microvascular structure and distribution of cardiac pericytes were observed using immunofluorescence staining. Picrosirius red staining was performed to evaluate cardiac fibrosis.ResultsEmpagliflozin lowered the increased fasting blood glucose levels of the db/db group. The left ventricular ejection fraction, left ventricular fractional shortening, E/A ratio and E/e′ ratio were not significantly different between the three groups. CFR was decreased in the db/db group, but EMPA significantly improved CFR. In contrast to the sparse and abnormal expansion of coronary microvessels observed in the db/db group, the number of coronary microvessels was increased, and the capillary diameter was decreased in the db/db + EMPA group. The number and microvascular coverage of cardiac pericytes were reduced in the db/db mice but were improved by EMPA. The cardiac fibrosis was increased in db/db group and may alleviate by EMPA.ConclusionEmpagliflozin inhibited CMD and reduced cardiac pericyte loss in diabetic mice.

Background Peripheral artery disease (PAD) affects >10 million people in the United States. PAD is associated with poor outcomes, including premature death. Machine learning (ML) has been increasingly used on big data to predict clinical outcomes. This study aims to develop ML models to predict in‐hospital mortality in patients hospitalized for PAD based on a national database. Methods and Results Inpatient hospitalization data were obtained from the 2016 to 2019 National Inpatient Sample. A total of 150 921 inpatients were identified with a primary diagnosis of PAD and PAD‐related procedures using codes of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD‐10‐CM) and International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD‐10‐PCS). Four ML models, including logistic regression, random forest, light gradient boosting, and extreme gradient boosting models, were trained to predict the risk of in‐hospital death based on a selection of variables, including patient characteristics, comorbidities, procedures, and hospital‐related factors. In‐hospital mortality occurred in 1.8% of patients. The performance of the 4 models was comparable, with the area under the receiver operating characteristic curve ranging from 0.83 to 0.85, sensitivity of 77% to 82%, and specificity of 72% to 75%. These results suggest adequate predictability for clinical decision‐making. In all 4 models, the total number of diagnoses and procedures, age, endovascular revascularization procedure, congestive heart failure, diabetes, and diabetes with complications were critical predictors of in‐hospital mortality. Conclusions This study demonstrates the feasibility of ML in predicting in‐hospital mortality in patients with a primary PAD diagnosis. Findings highlight the potential of ML models in identifying high‐risk patients for poor outcomes and guiding personalized intervention.

Abstract Near-infrared (NIR), particularly NIR-containing dual-/multi-mode afterglow, is very attractive in many fields of application, but it is still a great challenge to achieve such property of materials. Herein, we report a facile method to prepare green and NIR dual-mode afterglow of carbon dots (CDs) through in situ embedding o-CDs (being prepared from o-phenylenediamine) into cyanuric acid (CA) matrix (named o-CDs@CA). Further studies reveal that the green and NIR afterglows of o-CDs@CA originate from thermal activated delayed fluorescence (TADF) and room temperature phosphorescence (RTP) of o-CDs, respectively. In addition, the formation of covalent bonds between o-CDs and CA, and the presence of multiple fixation and rigid effects to the triplet states of o-CDs are confirmed to be critical for activating the observed dual-mode afterglow. Due to the shorter lifetime and insensitiveness to human vision of the NIR RTP of o-CDs@CA, it is completely covered by the green TADF during directly observing. The NIR RTP signal, however, can be readily captured if an optical filter (cut-off wavelength of 600 nm) being used. By utilizing these unique features, the applications of o-CDs@CA in anti-counterfeiting and information encryption have been demonstrated with great confidentiality. Finally, the as-developed method was confirmed to be applicable to many other kinds of CDs for achieving or enhancing their afterglow performances.

Background and purpose: With the progressive increase in the prevalence of type 2 diabetes mellitus (T2DM), diabetic nephropathy (DN) – one of the most common chronic microvascular complications – has evolved into a significant cause of death worldwide among end-stage renal disease patients. Academic researchers have for decades focused on the development of DN and recently found that free fatty acids (FFAs) constituted an independent risk factor for vascular complications in T2DM patients. It is therefore critical to determine whether the metabolic profile of FFAs is related to DN. Methods: This study comprised 611 research subjects in Dalian, a city in northeast China: 52 DN patients, 115 T2DM patients, and 444 healthy controls. We determined 15 forms of serum FFAs, including arachidonic acid (AA, C20:4), docosahexaenoic acid (DHA, C22:6), erucic acid (C22:1), nervonic acid (NA, C24:1), estimated total omega-3s, total omega-6s, the omega-3/omega-6 ratio, and total FFA content by liquid chromatography–mass spectrometry (LC-MS). Results: The levels of NA (mean = 45.27, range = 0.84–76.57) and DHA (mean = 324.58, range = 205.38–450.03) in DN patients were slightly lower than those in T2DM patients or healthy controls. The serum omega-3 polyunsaturated fatty acid (PUFA) DHA (C22:6) was significantly negatively correlated with microalbuminuria (MAU), the albumin/creatinine ratio (ACR), body mass index (BMI), fasting plasma glucose (FPG), and glycosylated hemoglobin (HbA1c). The serum monounsaturated fatty acid (MUFA) NA (C24:1) was significantly negatively correlated with BMI, FPG, and HbA1c. After adjustment of variables, multiple logistic regression analysis revealed significant odds ratios (ORs) [with confidence intervals (CIs)] for DHA (0.991, 0.985–0.997; p = 0.002) and NA (0.978, 0.958–0.999; p = 0.037). Conclusion: In this study, we ascertained that the contents of NA and DHA in patients with DN were relatively low, and that DHA was negatively correlated with MAU and the ACR. However, large-scale, population-based studies focusing on the role of NA and DHA in the pathogenesis of DN are still required in the future.

A thermophoretic aptasensor can be used to profile cancer-associated proteins of extracellular vesicles (EVs) in patients’ plasma. Here, the authors use this technique to develop an EV-signature able to discriminate metastatic breast cancer, monitor treatment response, and predict patients’ progression-free survival.

Mesothelin (MSLN) is a glycoprotein with various expression degrees in different tumors including mesothelioma, ovarian cancer, pancreatic cancer, etc. MSLN is considered to play an important role in cell survival, proliferation, and tumor progression. Although the expression of MSLN in tumors makes it a potential therapeutic target, its mechanism of action is still unclear, especially its correlation with immune cells infiltration in the tumor microenvironment has not been investigated. In this study, we detected the overexpression of MSLN in ovarian cancer using database analysis and tissue-array staining. We further evaluated the diagnostic value of MSLN and found it was associated with poor overall survival in ovarian cancer. In addition, the high expression of MSLN was significantly related to the immune-related genes and chemoresistant genes. We confirmed the overexpression of MSLN in the chemoresistant ovarian cancer cell lines. Our research suggests that MSLN participates in a variety of pathways related to the suppression of immune activation and promotion of chemoresistance, leading to a poor prognosis in ovarian cancer.

Background: Thyroid cancer has become increasingly prevalent and threatens human health. Few studies have explored the incidence of thyroid cancer in Asia and its relationship with social-progress factors. Methods: We analyzed Global Burden of Disease (GBD) Study 2019 data specific to thyroid cancer. Incidence, prevalence, mortality, and disability-adjusted life year (DALY) rates were used to evaluate the burden of thyroid cancer. Results: The age-standardized incidence, prevalence, and DALY rates per 100,000 population were 1.34% (95% UI, 2.44–3.07), 2.79% (95% UI, 18.82–23.77) and 16.49% (95% UI, 14.6–18), respectively, for all of Asia in 2019. In 2019, the DALY rate of thyroid cancer in the High-income Asia-Pacific region was the highest and mortality due to thyroid cancer in the High-income Asia-Pacific region was also the highest. The growth trend of DALYs in the High-income Asia-Pacific region was much steeper than those in other Asian regions. In all Asian regions and in the High-income Asia-Pacific region, the incidence, prevalence, mortality and DALY rates of thyroid cancer in female patients were drastically higher than those in male patients. Among Asian patients with thyroid cancer, the DALY rate was higher in men aged 80–89 years than in women. The DALY rate gradually increased with age. In the High-income Asia-Pacific region, the mortality rate of patients with thyroid cancer decreased with age. The prevalence was highest in those aged 40–79 years. Conclusion: The disease burden of thyroid cancer in the High-income Asia-Pacific region was significantly higher than those in other regions, which may be due to overdiagnosis. The increasing incidence of thyroid cancer seems to indicate that thyroid cancer is still a public health problem in Asia. Therefore, some health policy adjustments will be meaningful.

In China, rapid urbanization in recent decades has led to increasingly serious ecological and environmental problems, threatening sustainable development. Thus, a clear understanding of the relationship between urbanization and eco-environment is the basis for achieving regional sustainable development. However, despite the current global explosion of research interests on this topic, few studies have focused on ecologically fragile areas. To fill this gap, taking Aba Autonomous Prefecture in the eastern Qinghai-Tibet Plateau as a case study, we explored the relationship between urbanization and eco-environment from 2001 to 2018 using a coupled coordination degree model. The results show that the urbanization level and eco-environmental quality in Aba Prefecture achieved stable and continuous improvements from 0.202 to 0.428 and 0.372 to 0.422, respectively. Moreover, the coupling degree between them ranged from 0.524 to 0.652, indicating that the study area had transformed from uncoordinated development in the initial stage to transformation development in the final stage. Additionally, over the 18 years, the coordinated state of urbanization and eco-environment improved, with the coordinated level increasing from reluctant to moderate coordination after 2011. Lastly, we confirmed that urbanization in Aba Prefecture had an overall positive effect on the local eco-environment, although it gradually decreased as urbanization progressed. These findings have important implications for political decision-makers to achieve high-quality development in ecologically fragile areas.

BackgroundChronic kidney disease (CKD) patients have a high prevalence of coronary artery disease and a high risk of cardiovascular events. The present study assessed the value of the CHA2DS2-VASc score for predicting mortality among hospitalized acute coronary syndrome (ACS) patients with CKD.MethodsThis was a retrospective cohort study that included CKD patients who were hospitalized for ACS from January 2015 to May 2020. The CHA2DS2-VASc score for each eligible patient was determined. Patients were stratified into two groups according to CHA2DS2-VASc score:

ObjectiveOur study aims to investigate the role of the ABO blood group in the development and severity of coronary artery disease (CAD) in end-stage renal disease (ESRD) patients with dialysis.MethodsA total of 408 ESRD patients with dialysis between January 2010 and December 2020 were enrolled including 204 patients diagnosed with CAD undergoing coronary angiography for the first time, and baseline characteristics as well as Gensini score (GS) were collected. Logistic regression analysis and linear regression analysis were performed to evaluate the relation of ABO blood types to the risk and severity of CAD, respectively.ResultsBlood group O frequency was significantly low in dialysis ESRD patients with CAD (25 vs. 38.24%) compared with the non-CAD patients and multivariable logistic regression showed blood group O was negatively associated with the risk of CAD [adjusted odds ratio (OR) = 0.33, 95% CI = 0.19–0.60, p < 0.001] as well as the GS tertiles (adjusted OR = 0.23, 95% CI = 0.11–0.49, p < 0.001) compared with A blood group. Blood group A, B, and AB were positively associated with the high Gensini tertile compared with O blood group (adjusted OR = 4.26, 95% CI = 2.03–8.93, p < 0.001; adjusted OR = 2.39, 95% CI = 1.11–5.13, p < 0.05; adjusted OR = 4.33, 95% CI = 1.40–13.35, P < 0.05). Similarly, multivariable linear regression results revealed O blood type was negatively associated with the GS (β = −26.129, 95% CI = −40.094 to −12.164, p < 0.001).ConclusionThis case-control study demonstrated that blood group O was a potential independent protective factor for the risk and severity of CAD in ESRD patients with dialysis.

Introduction. Radiotherapy for patients with head and neck cancers raises their risk of aspiration pneumonia-related death. We aimed to develop and validate a model to predict radiation-associated aspiration pneumonia (RAP) among patients with dysphagia after radiotherapy for nasopharyngeal carcinoma (NPC). Materials and Methods. A total of 453 dysphagic patients with NPC were retrospectively recruited from Sun Yat-Sen Memorial Hospital from January 2012 to January 2018. Patients were randomly divided into training cohort (n=302) and internal validation cohort (n=151) at a ratio of 2 : 1. The concordance index (C-index) and calibration curve were used to evaluate the accuracy and discriminative ability of this model. Moreover, decision curve analysis was performed to evaluate the net clinical benefit. The results were externally validated in 203 dysphagic patients from the First People’s Hospital of Foshan. Results. Derived from multivariable analysis of the training cohort, four independent factors were introduced to predict RAP, including Kubota water drinking test grades, the maximum radiation dose of lymph node gross tumor volume (Dmax of the GTVnd), neutrophil count, and erythrocyte sedimentation rate (ESR). The nomogram showed favorable calibration and discrimination regarding the training cohort, with a C-index of 0.749 (95% confidence interval (CI), 0.681 to 0.817), which was confirmed by the internal validation cohort (C-index 0.743; 95% CI, 0.669 to 0.818) and the external validation cohort (C-index 0.722; 95% CI, 0.606 to 0.838). Conclusions. Our study established and validated a simple nomogram for RAP among patients with dysphagia after radiotherapy for NPC.

Considering the constraint of cost in conserving biodiversity, conservation resources need to be primarily allocated to keystone species. The structure and interaction of strength of the food web determine the stability of the network, and the keystone species is key node for the stable food web. In this research, starting with constructing a diet proportion food web structure model on the shore of Xingkai Lake quantitatively based on carbon and nitrogen stable isotopes. We calculated the feeding ratio between species and used it as the link weight, combined with the complex network centrality theory. Afterwards, we identified the keystone species in the diet proportion food web by calculating the degree centrality, closeness centrality, betweenness centrality and PageRank centrality of each node in the network. We have found that the link weight is the key factor affecting the identification of keystone species. Besides, Chinese white prawn has been identified as the keystone species in the typical food web of the shore of Xingkai Lake shown from the perspective of the food web structure and the results of the four centrality indices. This article is of great significance to identify the keystone species in the food web from a holistic perspective quantitatively, further clarify the conservation goals, and reduce conservation costs under the impact of the global COVID-19 epidemic, so as to conserve biodiversity accurately and effectively.

Background: Some evidence indicates a potential beneficial effect of omega-6 polyunsaturated fatty acids (n-6 PUFAs) on type 2 diabetes mellitus (T2DM); however, the findings to date remains inconclusive and little is known about whether sex modifies these associations. Therefore, this study aimed to investigate potential sex-specific differences in this associations among Chinese adults.Methods: We conducted a cross-sectional study in an area of Dalian city, China; Chinese men and women who attended the Department of Clinical Nutrition and Metabolism between January and December 2020 were invited to participate in this study. All participants were assessed for basic demographic characteristics, fasting blood glucose, HbA1c, and other serum biomarkers and serum phospholipid FAs.Results: In total, 575 Chinese adult participants (270 men and 305 women) were included in the analysis. Hypertension and dyslipidaemia were more common among men than women, but there were no significant differences between the sexes in fatty acid composition, except for eicosadienoic acid (EA; 20:2n-6) and total monounsaturated fatty acids (MUFA). The age-adjusted OR for having T2DM in the highest quartile of arachidonic acid (20:4n-6) level was 0.47 (95% CI, 0.22, 0.98) in men, and this association remained consistently significant in the fully adjusted multivariate models. In contrast, no significant associations between n-6 PUFAs and T2DM risk were observed in women, regardless of model adjustment.Conclusions: In conclusion, these results demonstrate a notable sex-specific differences in the associations between n-6 PUFAs and T2DM. Higher n-6 PUFA status may be protective against the risk of T2DM in men.

Symmetry breaking and chiral amplification are fundamental principles in chemistry and biology but the control of initial chiral bias remains a great challenge. Here the authors show that chiral microvortices can lead to a selection of initial chiral bias of supramolecular systems composed of achiral molecules.

Vocal fold paralysis (VFP) refers to neurological causes of reduced or absent movement of one or both vocal folds. Bilateral VFP (BVFP) is characterized by inspiratory dyspnea due to narrowing of the airway at the glottic level with both vocal folds assuming a paramedian position. The primary objective of intervention for BVFP is to relieve patients’ dyspnea. Common clinical options for management include tracheostomy, arytenoidectomy and cordotomy. Other options that have been used with varying success include reinnervation techniques and botulinum toxin (Botox) injections into the vocal fold adductors. More recently, research has focused on neuromodulation, laryngeal pacing, gene therapy, and stem cell therapy. These newer approaches have the potential advantage of avoiding damage to the voicing mechanism of the larynx with an added goal of restoring some physiologic movement of the affected vocal folds. However, clinical data are scarce for these new treatment options (i.e., reinnervation and pacing), so more investigative work is needed. These areas of research are expected to provide dramatic improvements in the treatment of BVFP.