Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach.

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.

Integrated Anchored Stapling and Hierarchical Dynamics: MSICDA-Driven CREBBP Bromodomain Inhibition.

Despite recent success in the computational approaches of cyclic peptide design, current studies face challenges in modeling noncanonical amino acids and nonstandard cyclizations due to limited data. To address this challenge, we developed an integrated framework for the tailored design of stapled peptides (SPs) targeting the bromodomain of CREBBP (CREBBP-BrD). We introduce a powerful combination of anchored stapling and hierarchical molecular dynamics to design and optimize SPs by employing the MultiScale integrative conformational dynamics assessment (MSICDA) strategy, which involves an initial virtual screening of over 1.5 million SPs, followed by comprehensive simulations amounting to 154.54 µs across 5418 of instances. The MSICDA method provides a detailed and holistic stability view of peptide-protein interactions, systematically isolated optimized peptides and identified two leading candidates, DA#430 and DA#99409, characterized by their enhanced stability, optimized binding, and high affinity toward the CREBBP-BrD. In cell-free assays, DA#430 and DA#99409 exhibited 2- to 12-fold greater potency than inhibitor SGC-CBP30. Cell studies revealed higher peptide selectivity for cancerous versus normal cells over small molecules. DA#430 combined with (+)-JQ-1 showed promising synergistic effects. Our approach enables the identification of peptides with optimized binding, high affinity, and enhanced stability, leading to more precise and effective cyclic peptide design, thereby establishing MSICDA as a generalizable and transformative tool for uncovering novel targeted drug development in various therapeutic areas.

Spatial profiles of the bacterial microbiota throughout the gastrointestinal tract of dairy goats.

The gastrointestinal tract (GIT) is stationed by a dynamic and complex microbial community with functions in digestion, metabolism, immunomodulation, and reproduction. However, there is relatively little research on the composition and function of microorganisms in different GIT segments in dairy goats. Herein, 80 chyme samples were taken from ten GIT sites of eight Xinong Saanen dairy goats and then analyzed and identified the microbial composition via 16S rRNA V1-V9 amplicon sequencing. A total of 6669 different operational taxonomic units (OTUs) were clustered, and 187 OTUs were shared by ten GIT segments. We observed 264 species belonging to 23 different phyla scattered across ten GITs, with Firmicutes (52.42%) and Bacteroidetes (22.88%) predominating. The results revealed obvious location differences in the composition, diversity, and function of the GIT microbiota. In LEfSe analysis, unidentified_Lachnospiraceae and unidentified_Succinniclassicum were significantly enriched in the four chambers of stomach, with functions in carbohydrate fermentation to compose short-chain fatty acids. Aeriscardovia, Candidatus_Saccharimonas, and Romboutsia were significantly higher in the foregut, playing an important role in synthesizing enzymes, amino acids, and vitamins and immunomodulation. Akkermansia, Bacteroides, and Alistipes were significantly abundant in the hindgut to degrade polysaccharides and oligosaccharides, etc. From rumen to rectum, α-diversity decreased first and then increased, while ß-diversity showed the opposite trend. Metabolism was the major function of the GIT microbiome predicted by PICRUSt2, but with variation in target substrates along the regions. In summary, GIT segments play a decisive role in the composition and functions of microorganisms. KEY POINTS: • The jejunum and ileum were harsh for microorganisms to colonize due to the presence of bile acids, enzymes, faster chyme circulation, etc., exhibiting the lowest α-diversity and the highest ß-diversity. • Variability in microbial profiles between the three foregut segments was greater than four chambers of stomach and hindgut, with a higher abundance of Firmicutes dominating than others. • Dairy goats dominated a higher abundance of Kiritimatiellaeota than cows, which was reported to be associated with fatty acid synthesis.

Polyprenylated acylphloroglucinols from Hypericum sampsonii with cytotoxicity against pancreatic carcinomas.

Chemical investigation on the 80% EtOH extract of the air dried aerial parts of Hypericum sampsonii resulted in the isolation of two new polycyclic polyprenylated derivatives, hypersampines A and B (1 and 2). The structures of the new compounds were elucidated by spectroscopic data (NMR, IR, and UV) and high resolution mass analysis. The two isolated polyprenylated acylphloroglucinols were tested in vitro for cytotoxic activities against 6 pancreatic cell lines. As a result, compounds 1 and 2 possessed modest cytotoxic activities against all the tested tumor cell lines with IC50 values less than 40 µM.

Reconfigurable Peptide Analogs of Apolipoprotein A-I Reveal Tunable Features of Nanodisc Assembly.

Nanodisc (ND)-forming membrane scaffold proteins or peptides developed from apolipoprotein A-I (apoA-I) have led to considerable promise in structural biology and therapeutic applications. However, the rationale and regularity characteristics in peptide sequence design remain inconclusive. Here, we proposed a consensus-based normalization approach through the reversed engineering of apoA-IΔ1-45 to design reconfigurable apoA-I peptide analogs (APAs) for tunable ND assembly. We present extensive morphological validations and computational simulation analyses on divergent APA-NDs that are generated by our method. Fifteen divergent APAs were generated accordingly to study the assembly machinery of NDs. We show that APA designs exhibit multifactorial influence in terms of varying APA tandem repeats, sequence composition, and lipid-to-APA ratio to form tunable diameters of NDs. There is a strong positive correlation between DMPC-to-APA ratios and ND diameters. Longer APA with more tandem repeats tends to yield higher particle size homogeneity. Our results also suggest proline is a dispensable residue for the APA-ND formation. Interestingly, proline-rich substitution not only provides an inward-bending effect in forming smaller NDs but also induces the cumulative chain flexibility that enables larger ND formation at higher lipid ratios. Additionally, proline-tryptophan residues in APAs play a dominant role in forming larger NDs. Molecular simulation shows that enriched basic and acidic residues in APAs evoke abundant hydrogen-bond and salt bridge networks to reinforce the structural stability of APA-NDs. Together, our findings provide a rational basis for understanding APA design. The proposed model could be extended to other apolipoproteins for desired ND engineering.

[Inhibition of glutaminolysis alleviates myocardial fibrosis induced by angiotensin II].

The present study was aimed to investigate the role and mechanism of glutaminolysis of cardiac fibroblasts (CFs) in hypertension-induced myocardial fibrosis. C57BL/6J mice were administered with a chronic infusion of angiotensin II (Ang II, 1.6 mg/kg per d) with a micro-osmotic pump to induce myocardial fibrosis. Masson staining was used to evaluate myocardial fibrosis. The mice were intraperitoneally injected with BPTES (12.5 mg/kg), a glutaminase 1 (GLS1)-specific inhibitor, to inhibit glutaminolysis simultaneously. Immunohistochemistry and Western blot were used to detect protein expression levels of GLS1, Collagen I and Collagen III in cardiac tissue. Neonatal Sprague-Dawley (SD) rat CFs were treated with 4 mmol/L glutamine (Gln) or BPTES (5 µmol/L) with or without Ang II (0.4 µmol/L) stimulation. The CFs were also treated with 2 mmol/L α-ketoglutarate (α-KG) under the stimulation of Ang II and BPTES. Wound healing test and CCK-8 were used to detect CFs migration and proliferation respectively. RT-qPCR and Western blot were used to detect mRNA and protein expression levels of GLS1, Collagen I and Collagen III. The results showed that blood pressure, heart weight and myocardial fibrosis were increased in Ang II-treated mice, and GLS1 expression in cardiac tissue was also significantly up-regulated. Gln significantly promoted the proliferation, migration, mRNA and protein expression of GLS1, Collagen I and Collagen III in the CFs with or without Ang II stimulation, whereas BPTES significantly decreased the above indices in the CFs. α-KG supplementation reversed the inhibitory effect of BPTES on the CFs under Ang II stimulation. Furthermore, in vivo intraperitoneal injection of BPTES alleviated cardiac fibrosis of Ang II-treated mice. In conclusion, glutaminolysis plays an important role in the process of cardiac fibrosis induced by Ang II. Targeted inhibition of glutaminolysis may be a new strategy for the treatment of myocardial fibrosis.

[Detection method of early heart valve diseases based on heart sound features].

Heart valve disease (HVD) is one of the common cardiovascular diseases. Heart sound is an important physiological signal for diagnosing HVDs. This paper proposed a model based on combination of basic component features and envelope autocorrelation features to detect early HVDs. Initially, heart sound signals lasting 5 minutes were denoised by empirical mode decomposition (EMD) algorithm and segmented. Then the basic component features and envelope autocorrelation features of heart sound segments were extracted to construct heart sound feature set. Then the max-relevance and min-redundancy (MRMR) algorithm was utilized to select the optimal mixed feature subset. Finally, decision tree, support vector machine (SVM) and k-nearest neighbor (KNN) classifiers were trained to detect the early HVDs from the normal heart sounds and obtained the best accuracy of 99.9% in clinical database. Normal valve, abnormal semilunar valve and abnormal atrioventricular valve heart sounds were classified and the best accuracy was 99.8%. Moreover, normal valve, single-valve abnormal and multi-valve abnormal heart sounds were classified and the best accuracy was 98.2%. In public database, this method also obtained the good overall accuracy. The result demonstrated this proposed method had important value for the clinical diagnosis of early HVDs.

Genetic Mapping of Behavioral Traits Using the Collaborative Cross Resource.

The complicated interactions between genetic background, environment and lifestyle factors make it difficult to study the genetic basis of complex phenotypes, such as cognition and anxiety levels, in humans. However, environmental and other factors can be tightly controlled in mouse studies. The Collaborative Cross (CC) is a mouse genetic reference population whose common genetic and phenotypic diversity is on par with that of humans. Therefore, we leveraged the power of the CC to assess 52 behavioral measures associated with locomotor activity, anxiety level, learning and memory. This is the first application of the CC in novel object recognition tests, Morris water maze tasks, and fear conditioning tests. We found substantial continuous behavioral variations across the CC strains tested, and mapped six quantitative trait loci (QTLs) which influenced these traits, defining candidate genetic variants underlying these QTLs. Overall, our findings highlight the potential of the CC population in behavioral genetic research, while the identified genomic loci and genes driving the variation of relevant behavioral traits provide a foundation for further studies.

Time-restricted feeding alleviates cardiac dysfunction induced by simulated microgravity via restoring cardiac FGF21 signaling.

Dietary restriction has been well-described to improve health metrics, but whether it could benefit pathophysiological adaptation to extreme environment, for example, microgravity, remains unknown. Here, we investigated the effects of a daily rhythm of fasting and feeding without reducing caloric intake on cardiac function and metabolism against simulated microgravity. Male rats under ad libitum feeding or time-restricted feeding (TRF; food access limited to 8 hours every day) were subjected to hindlimb unloading (HU) to simulate microgravity. HU for 6 weeks led to left ventricular dyssynchrony and declined cardiac function. HU also lowered pyruvate dehydrogenase (PDH) activity and impaired glucose utilization in the heart. All these were largely preserved by TRF. TRF showed no effects on HU-induced loss of cardiac mass, but significantly improved contractile function of cardiomyocytes. Interestingly, TRF raised liver-derived fibroblast growth factor 21 (FGF21) level and enhanced cardiac FGF21 signaling as manifested by upregulation of FGF receptor-1 (FGFR1) expression and its downstream markers in HU rats. In isolated cardiomyocytes, FGF21 treatment improved PDH activity and glucose utilization, consequently enhancing cell contractile function. Finally, both liver-specific knockdown (KD) of FGF21 and cardiac-specific FGFR1 KD abrogated the cardioprotective effects of TRF in HU rats. These data demonstrate that TRF improves cardiac glucose utilization and ameliorates cardiac dysfunction induced by simulated microgravity, at least partially, through restoring cardiac FGF21 signaling, suggesting TRF as a potential countermeasure for cardioprotection in long-term spaceflight.

Short-Term Effect of Percutaneous Coronary Intervention on Heart Rate Variability in Patients with Coronary Artery Disease.

Myocardial ischemia in patients with coronary artery disease (CAD) leads to imbalanced autonomic control that increases the risk of morbidity and mortality. To systematically examine how autonomic function responds to percutaneous coronary intervention (PCI) treatment, we analyzed data of 27 CAD patients who had admitted for PCI in this pilot study. For each patient, five-minute resting electrocardiogram (ECG) signals were collected before and after the PCI procedure. The time intervals between ECG collection and PCI were both within 24 h. To assess autonomic function, normal sinus RR intervals were extracted and were analyzed quantitatively using traditional linear time- and frequency-domain measures [i.e., standard deviation of the normal-normal intervals (SDNN), the root mean square of successive differences (RMSSD), powers of low frequency (LF) and high frequency (HF) components, LF/HF] and nonlinear entropy measures [i.e., sample entropy (SampEn), distribution entropy (DistEn), and conditional entropy (CE)], as well as graphical metrics derived from Poincaré plot [i.e., Porta's index (PI), Guzik's index (GI), slope index (SI) and area index (AI)]. Results showed that after PCI, AI and PI decreased significantly (p < 0.002 and 0.015, respectively) with effect sizes of 0.88 and 0.70 as measured by Cohen's d static. These changes were independent of sex. The results suggest that graphical AI and PI metrics derived from Poincaré plot of short-term ECG may be potential for sensing the beneficial effect of PCI on cardiovascular autonomic control. Further studies with bigger sample sizes are warranted to verify these observations.

Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals.

Heart sound signals reflect valuable information about heart condition. Previous studies have suggested that the information contained in single-channel heart sound signals can be used to detect coronary artery disease (CAD). But accuracy based on single-channel heart sound signal is not satisfactory. This paper proposed a method based on multi-domain feature fusion of multi-channel heart sound signals, in which entropy features and cross entropy features are also included. A total of 36 subjects enrolled in the data collection, including 21 CAD patients and 15 non-CAD subjects. For each subject, five-channel heart sound signals were recorded synchronously for 5 min. After data segmentation and quality evaluation, 553 samples were left in the CAD group and 438 samples in the non-CAD group. The time-domain, frequency-domain, entropy, and cross entropy features were extracted. After feature selection, the optimal feature set was fed into the support vector machine for classification. The results showed that from single-channel to multi-channel, the classification accuracy has increased from 78.75% to 86.70%. After adding entropy features and cross entropy features, the classification accuracy continued to increase to 90.92%. The study indicated that the method based on multi-domain feature fusion of multi-channel heart sound signals could provide more information for CAD detection, and entropy features and cross entropy features played an important role in it.

Discrimination of Patients with Varying Degrees of Coronary Artery Stenosis by ECG and PCG Signals Based on Entropy.

Coronary heart disease (CHD) is the leading cause of cardiovascular death. This study aimed to propose an effective method for mining cardiac mechano-electric coupling information and to evaluate its ability to distinguish patients with varying degrees of coronary artery stenosis (VDCAS). Five minutes of electrocardiogram and phonocardiogram signals was collected synchronously from 191 VDCAS patients to construct heartbeat interval (RRI)-systolic time interval (STI), RRI-diastolic time interval (DTI), HR-corrected QT interval (QTcI)-STI, QTcI-DTI, Tpeak-Tend interval (TpeI)-STI, TpeI-DTI, Tpe/QT interval (Tpe/QTI)-STI, and Tpe/QTI-DTI series. Then, the cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), joint distribution entropy (JDistEn), magnitude-squared coherence function, cross power spectral density, and mutual information were applied to evaluate the coupling of the series. Subsequently, support vector machine recursive feature elimination and XGBoost were utilized for feature selection and classification, respectively. Results showed that the joint analysis of XSampEn, XFuzzyEn, and JDistEn had the best ability to distinguish patients with VDCAS. The classification accuracy of severe CHD-mild-to-moderate CHD group, severe CHD-chest pain and normal coronary angiography (CPNCA) group, and mild-to-moderate CHD-CPNCA group were 0.8043, 0.7659, and 0.7500, respectively. The study indicates that the joint analysis of XSampEn, XFuzzyEn, and JDistEn can effectively capture the cardiac mechano-electric coupling information of patients with VDCAS, which can provide valuable information for clinicians to diagnose CHD.

Lower body negative pressure protects brain perfusion in aviation gravitational stress induced by push-pull manoeuvre.

KEY POINTS: Rapid alterations of gravitational stress during high-performance aircraft push-pull manoeuvres induce dramatic shifts in volume and pressure within the circulation system, which may result in loss of consciousness due to the rapid and significant reduction in cerebral perfusion. There are still no specific and effective countermeasures so far. We found that lower body negative pressure (LBNP), applied prior to and during -Gz and released at the subsequent transition to +Gz, could effectively counteract gravitational haemodynamic stress induced by a simulated push-pull manoeuvre and improve cerebral diastolic perfusion in human subjects. We developed a LBNP strategy that effectively protects cerebral perfusion at rapid -Gz to +Gz transitions via improving cerebral blood flow and blood pressure during push-pull manoeuvres and highlight the importance of the timing of the intervention. Our findings provide a systemic link of integrated responses between the peripheral and cerebral haemodynamic changes during push-pull manoeuvres. ABSTRACT: The acute negative (-Gz) to positive (+Gz) gravity stress during high-performance aircraft push-pull manoeuvres dramatically reduces transient cerebral perfusion, which may lead to loss of vision or even consciousness. The aim of this study was to explore a specific and effective counteractive strategy. Twenty-three healthy young male volunteers (age 21 ± 1 year) were subjected to tilting-simulated push-pull manoeuvres. Lower body negative pressure (LBNP) of -40 mmHg was applied prior to and during -Gz stress (-0.50 or -0.87 Gz) and released at the subsequent transition to +1.00 Gz stress. Beat-to-beat cerebral and systemic haemodynamics were continuously recorded during the simulated push-pull manoeuvre in LBNP bouts and corresponding control bouts. During the rapid gravitational transition from -Gz to +Gz, the mean cerebral blood flow velocity decreased significantly in control bouts, while it increased in LBNP bouts (control vs. LBNP bouts, -6.6 ± 4.6 vs. 5.1 ± 6.8 cm s-1 for -0.50 Gz, and -7.4 ± 4.8 vs. 3.4 ± 4.6 cm s-1 for -0.87 Gz, P < 0.01), which was attributed mainly to the elevation of diastolic flow. The LBNP bouts showed much smaller reduction of mean arterial blood pressure at the brain level than control bouts (control bouts vs. LBNP bouts, -38 ± 12 vs. -23 ± 10 mmHg for -0.50 to +1.00 Gz, and -62 ± 16 vs. -43 ± 11 mmHg for -0.87 to +1.00 Gz, P < 0.01). LBNP applied at -Gz and released at subsequent +Gz had biphasic counteractive effects against the gravitational responses to the push-pull manoeuvre. These data demonstrate that this LBNP strategy could effectively protect cerebral perfusion with dominant improvement of diastolic flow during push-pull manoeuvres.

Bivariate Entropy Analysis of Electrocardiographic RR-QT Time Series.

QT interval variability (QTV) and heart rate variability (HRV) are both accepted biomarkers for cardiovascular events. QTV characterizes the variations in ventricular depolarization and repolarization. It is a predominant element of HRV. However, QTV is also believed to accept direct inputs from upstream control system. How QTV varies along with HRV is yet to be elucidated. We studied the dynamic relationship of QTV and HRV during different physiological conditions from resting, to cycling, and to recovering. We applied several entropy-based measures to examine their bivariate relationships, including cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), cross conditional entropy (XCE), and joint distribution entropy (JDistEn). Results showed no statistically significant differences in XSampEn, XFuzzyEn, and XCE across different physiological states. Interestingly, JDistEn demonstrated significant decreases during cycling as compared with that during the resting state. Besides, JDistEn also showed a progressively recovering trend from cycling to the first 3 min during recovering, and further to the second 3 min during recovering. It appeared to be fully recovered to its level in the resting state during the second 3 min during the recovering phase. The results suggest that there is certain nonlinear temporal relationship between QTV and HRV, and that the JDistEn could help unravel this nuanced property.

Modified Distribution Entropy as a Complexity Measure of Heart Rate Variability (HRV) Signal.

The complexity of a heart rate variability (HRV) signal is considered an important nonlinear feature to detect cardiac abnormalities. This work aims at explaining the physiological meaning of a recently developed complexity measurement method, namely, distribution entropy (DistEn), in the context of HRV signal analysis. We thereby propose modified distribution entropy (mDistEn) to remove the physiological discrepancy involved in the computation of DistEn. The proposed method generates a distance matrix that is devoid of over-exerted multi-lag signal changes. Restricted element selection in the distance matrix makes "mDistEn" a computationally inexpensive and physiologically more relevant complexity measure in comparison to DistEn.

Identification of Pulmonary Hypertension Using Entropy Measure Analysis of Heart Sound Signal.

This study introduced entropy measures to analyze the heart sound signals of people with and without pulmonary hypertension (PH). The lead II Electrocardiography (ECG) signal and heart sound signal were simultaneously collected from 104 subjects aged between 22 and 89. Fifty of them were PH patients and 54 were healthy. Eleven heart sound features were extracted and three entropy measures, namely sample entropy (SampEn), fuzzy entropy (FuzzyEn) and fuzzy measure entropy (FuzzyMEn) of the feature sequences were calculated. The Mann-Whitney U test was used to study the feature significance between the patient and health group. To reduce the age confounding factor, nine entropy measures were selected based on correlation analysis. Further, the probability density function (pdf) of a single selected entropy measure of both groups was constructed by kernel density estimation, as well as the joint pdf of any two and multiple selected entropy measures. Therefore, a patient or a healthy subject can be classified using his/her entropy measure probability based on Bayes' decision rule. The results showed that the best identification performance by a single selected measure had sensitivity of 0.720 and specificity of 0.648. The identification performance was improved to 0.680, 0.796 by the joint pdf of two measures and 0.740, 0.870 by the joint pdf of multiple measures. This study showed that entropy measures could be a powerful tool for early screening of PH patients.

Chemical characteristics of haze particles in Xi'an during Chinese Spring Festival: Impact of fireworks burning.

Fireworks burning releases massive fine particles and gaseous pollutants, significantly deteriorating air quality during Chinese Lunar New Year (LNY) period. To investigate the impact of the fireworks burning on the atmospheric aerosol chemistry, 1-hr time resolution of PM2.5 samples in Xi'an during the winter of 2016 including the LNY were collected and detected for inorganic ions, acidity and liquid water content (LWC) of the fine aerosols. PM2.5 during the LNY was 167±87µg/m3, two times higher than the China National Ambient Air Quality Standard (75µg/m3). K+ (28wt.% of the total ion mass) was the most abundant ion in the LNY period, followed by SO42- (25wt.%) and Cl- (18wt.%). In contrast, NO3- (34wt.%) was the most abundant species in the haze periods (hourly PM2.5>75µg/m3), followed by SO42- (29.2wt.%) and NH4+ (16.3wt.%), while SO42 - (35wt.%) was the most abundant species in the clean periods (hourly PM2.5<75µg/m3), followed by NO3- (23.1wt.%) and NH4+ (11wt.%). Being different from the acidic nature in the non-LNY periods, aerosol in the LNY period presented an alkaline nature with a pH value of 7.8±1.3. LWC during the LNY period showed a robust linear correlation with K2SO4 and KCl, suggesting that aerosol hygroscopicity was dominated by inorganic salts derived from fireworks burning. Analysis of correlations between the ratios of NO3-/SO42- and NH4+/SO42- indicated that heterogeneous reaction of HNO3 with NH3 was an important formation pathway of particulate nitrate and ammonium during the LNY period.

Analysis of short-term heart rate and diastolic period variability using a refined fuzzy entropy method.

BACKGROUND: Heart rate variability (HRV) has been widely used in the non-invasive evaluation of cardiovascular function. Recent studies have also attached great importance to the cardiac diastolic period variability (DPV) examination. Short-term variability measurement (e.g., 5 min) has drawn increasing attention in clinical practice, since it is able to provide almost immediate measurement results and enables the real-time monitoring of cardiovascular function. However, it is still a contemporary challenge to robustly estimate the HRV and DPV parameters based on short-term recordings. METHODS: In this study, a refined fuzzy entropy (rFuzzyEn) was developed by substituting a piecewise fuzzy membership function for the Gaussian function in conventional fuzzy entropy (FuzzyEn) measure. Its stability and robustness against additive noise compared with sample entropy (SampEn) and FuzzyEn, were examined by two well-accepted simulation models-the [Formula: see text] noise and the Logistic attractor. The rFuzzyEn was further applied to evaluate clinical short-term (5 min) HRV and DPV of the patients with coronary artery stenosis and healthy volunteers. RESULTS: Simulation results showed smaller fluctuations in the rFuzzyEn than in SampEn and FuzzyEn values when the data length was decreasing. Besides, rFuzzyEn could distinguish the simulation models with different amount of additive noise even when the percentage of additive noise reached 60%, but neither SampEn nor FuzzyEn showed comparable performance. Clinical HRV analysis did not indicate any significant differences between the patients with coronary artery disease and the healthy volunteers in all the three mentioned entropy measures (all p > 0.20). But clinical DPV analysis showed that the patient group had a significantly higher rFuzzyEn (p < 0.01) than the healthy group. However, no or less significant difference was observed between the two groups in either SampEn (p = 0.14) or FuzzyEn (p = 0.05). CONCLUSIONS: Our proposed rFuzzyEn outperformed conventional SampEn and FuzzyEn in terms of both stability and robustness against additive noise, particularly when the data set was relatively short. Analysis of DPV using rFuzzyEn may provide more valuable information to assess the cardiovascular states than the other entropy measures and has a potential for clinical application.

[Transmembrane transport behavior of in vitro HepG2 cells of ananas and its effect on lipids and glucose distribution].

Pineapple (Ananas comosus) leaves contain mainly phenolic components with antioxidant and hypolipidemic effects. One of the principle components is p-coumaric acid. In this study, the transport behavior of p-coumaric acid, was observed after the administration of pineapple leaf phenols in vitro. Simultaneously, the effect of the phenols on glucose, total cholesterol and triglycerides transportation and metabolism in HepG2 cells was also observed. The results showed that the phenols had good transport characteristics. 5 min after the administration, p-coumaric acid of the phenols could be detected, and the content of p-coumaric acid reached the peak concentration after 60 min of the administration. p-coumaric acid of phenols have time-and dose-dependent manner. While promoting glucose transporter (GLUT4) and low density lipoprotein receptor (LDLR) expression, the phenols decreased intracellular lipid content. This reduction of intracellular lipid content was highly correlated with the promotion of lipoprotein lipase (LPL) and hepatic triglyceride lipase (HTGL) expression, while the reduction of intracellular glucose levels was correlated with glycogen synthesis in the cells.

Decabromodiphenyl ether exposure reduces dabrafenib sensitivity of papillary thyroid carcinoma harboring BRAFV600E mutation through the EGFR-CRAF-MAPK pathway: An in vitro study.

Decabromodiphenyl ether (BDE209) has been demonstrated to be associated with thyroid dysfunction and thyroid carcinoma risk as a widely used brominated flame retardants. Although dabrafenib has been confirmed to be a promising therapeutic agent for papillary thyroid carcinoma (PTC) harboring BRAFV600E mutation, the rapid acquired dabrafenib resistance has brought a great challenge to clinical improvement and the underpinning mechanisms remain poorly defined. By treating PTC-derived and normal follicular epithelial cell lines with BDE209, we assessed its impact on the MAPK pathway's activation and evaluated the resultant effects on cell viability and signaling pathways, utilizing methods such as Western blot, IF staining, and RNA-seq bioinformatic analysis. Our findings reveal that BDE209 exacerbates MAPK activation, undermining dabrafenib's inhibitory effects by triggering the EGFR pathway, thereby highlighting BDE209's potential to diminish the pharmacological efficacy of dabrafenib in treating BRAF-mutated PTC. This research underscores the importance of considering environmental factors like BDE209 exposure in the effective management of thyroid carcinoma treatment strategies.