Development and validation of a predictive nomogram for the risk of MAFLD in postmenopausal women.

Background and aim: Metabolic-associated fatty liver disease (MAFLD) has gradually become one of the main health concerns regarding liver diseases. Postmenopausal women represent a high-risk group for MAFLD; therefore, it is of great importance to identify and intervene with patients at risk at an early stage. This study established a predictive nomogram model of MAFLD in postmenopausal women and to enhance the clinical utility of the new model, the researchers limited variables to simple clinical and laboratory indicators that are readily obtainable. Methods: Data of 942 postmenopausal women from January 2023 to October 2023 were retrospectively collected and divided into two groups according to the collection time: the training group (676 cases) and the validation group (226 cases). Significant indicators independently related to MAFLD were identified through univariate logistic regression and stepwise regression, and the MAFLD prediction nomogram was established. The C-index and calibration curve were used to quantify the nomogram performance, and the model was evaluated by measuring the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). Results: Of 37 variables, 11 predictors were identified, including occupation (worker), body mass index, waist-to-hip ratio, number of abortions, anxiety, hypertension, hyperlipidemia, diabetes, hyperuricemia, and diet (meat and processed meat). The C-index of the training group predicting the related risk factors was 0.827 (95% confidence interval [CI] 0.794-0.860). The C-index of the validation group was 0.787 (95% CI 0.728-0.846). Calibration curves 1 and 2 (BS1000 times) were close to the diagonal, showing a good agreement between the predicted probability and the actual incidence in the two groups. The AUC of the training group was 0.827, the sensitivity was 0.784, and the specificity was 0.735. The AUC of the validation group was 0.787, the sensitivity was 0.674, and the specificity was 0.772. The DCA curve showed that the nomogram had a good net benefit in predicting MAFLD in postmenopausal women. Conclusions: A predictive nomogram for MAFLD in postmenopausal women was established and verified, which can assist clinicians in evaluating the risk of MAFLD at an early stage.

Associations between semi-quantitative evaluation of intracranial arterial calcification and total cerebral small vessel disease burden score: a retrospective case-control study.

Background and purpose: Arteriosclerotic cerebral small vessel disease (aCSVD) is a cause of cognitive impairment, dementia, and stroke. Developing a better understanding of the risk factor of aCSVD is key to reducing the incidence of these conditions. This study investigated the association between intracranial arterial calcification (IAC) and total cerebral small vessel disease (CSVD) burden score. Materials and methods: This is a retrospective study, the subjects were transient ischemic attack (TIA) or acute ischemic stroke (AIS) patients. The data of 303 inpatients admitted to our study hospital between December 2018 and July 2020 were analyzed. Four imaging markers of CSVD (lacunes, white matter hyperintensities, cerebral microbleeds, and enlarged perivascular spaces) were evaluated by magnetic resonance imaging, and a total CSVD burden score was calculated. The experimental group was divided into four subgroups according to total CSVD burden score (1-4 points). Patients without CSVD (0 points) served as the control group. Head computerized tomography (CT) scans were used to assess ICA, using Babiarz's method. The correlations between IAC and single imaging markers of CSVD were determined using Spearman's rank correlation. Binary logic regression analysis and multivariate ordered logic regression analysis were used to determine the associations between IAC and aCSVD. Results: IAC was positively correlated with total CSVD burden score (r = 0.681), deep white matter hyperintensities (r = 0.539), periventricular white matter hyperintensities (r = 0.570), cerebral microbleeds (r = 0.479), lacunes (r = 0.541), and enlarged perivascular spaces (r = 0.554) (all p < 0.001). After adjusting for the confounding factors of age, diabetes, and hypertension, aCSVD was independently associated with IAC grade 1-2 [odds ratio (OR) = 23.747, 95% confidence interval (CI) = 8.376-67.327] and IAC grade 3-4 (OR = 30.166, 95% CI = 8.295-109.701). aCSVD severity was independently associated with IAC grade 3-4 (OR = 4.697, 95% CI = 1.349-16.346). Conclusion: IAC is associated with the total CSVD burden score and single imaging signs.

Nanoscale chestnut soil pore characteristics changes induced by non-growing season precipitation in a temperate grassland.

Changes in precipitation patterns during the non-growing season can affect soil moisture storage in temperate grasslands. However, there is a lack of comprehensive understanding regarding how these changes influence microscale soil pore characteristics and nutrient cycling in the context of climate change. Therefore, we carried out a 3-year artificial precipitation experiment during the non-growing season, along with N2 adsorption experiments of soil pore distribution and surveys of soil nutrient content. The aim was to clarify the influence of non-growing season precipitation variations on nanoscale soil pore characteristics and explore the potential correlations of the soil physicochemical properties. The results showed that: (1) The precipitation sheltering treatment during the non-growing season led to a significant 9.80 % increase in soil porosity at the 0-15 cm depth compared to the control. (2) Compared to the control, alterations in non-growing season precipitation (both increase and sheltering treatments) led to a significant increase in soil specific surface area (SSA), with an average increase of 23.2 %. Additionally, soil micropores, mesopores, macropores, and total pore volume (PV) increased by an average of 24.2 %, 14.0 %, 30.1 %, and 23.1 %, respectively. (3) Significant correlations were observed between soil microscale pore characteristics and soil C, soil organic matter (SOM), C: N ratio, and available P (AP). Redundancy analysis showed that soil microscale pore characteristics effectively accounted for the variations in soil nutrients with an explanatory degree of 94.23 %. (4) Influence pathways analysis by structural equation modeling indicated that dramatic variability in non-growing season precipitation promoted increases in mesopore and macropore volume, as well as the transformation of mesopores into macropores, thereby facilitating soil carbon accumulation. Our study suggests that soil microscale pore characteristics, acquired through adsorption experiments, assist in elucidating these potential synergistic mechanisms among physicochemical properties under varying non-growing season precipitation patterns. Given the escalating impacts of climate change, our findings provide novel insights and evidence for the assessment of climate change impacts in temperate arid grassland ecosystems.

Development of a Measurement Device for Micro Gas Flowrate Based on Laminar Flow Element with Micro-Curved Surface.

The laminar flow meter (LFM) boasts several advantages such as no moving parts, a wide range ratio, high measurement accuracy, quick dynamic response, etc., and is a promising technology for micro gas flow measurement. In order to explore the influence of different curvature radii on curved surface gap LFM, three curved structures with different curvature radii were designed. The computational fluid dynamics method is applied to simulate the flow feature of three structures. The simulated velocity cloud and pressure distribution show that the larger the curvature radius, the more stable the flow of gas medium. The relationship between differential pressure and volume flow was obtained through the test within a flow range of 0~540 sccm. Regression analysis revealed that the volume flow measured by the curved surface LFM had a high linear relationship with the differential pressure. Experimental findings indicate that differential pressure of the structure with a curvature radius of 2 mm was greater than that of other two structures (curvature radius of 6 mm and 3 mm) at the same point. This indicates that adding the number of surfaces can effectively increase the pressure loss, so as to obtain a larger range ratio, but will increase the measurement error.

Association between diabetes mellitus and primary biliary cholangitis: a two-sample Mendelian randomization study.

Background: Previous observational studies have demonstrated a link between diabetes mellitus(DM) and primary biliary cholangitis (PBC). Nevertheless, since these relationships might be confused, whether there is any causal connection or in which direction it exists is unclear. Our investigation aimed to identify the causal associations between DM and PBC. Methods: We acquired genome-wide association study (GWAS) datasets for PBC, Type 1 diabetes(T1DM), and Type 2 diabetes(T2DM) from published GWASs. Inverse variance-weighted (IVW), MR-Egger, weighted median (WM), Simple mode, and weighted mode methods were used to determine the causal relationships between DM(T1DM or T2DM) and PBC. Sensitivity analyses were also carried out to ensure the results were robust. To determine the causal relationship between PBC and DM(T1DM or T2DM), we also used reverse MR analysis. Results: T1DM was associated with a higher risk of PBC (OR 1.1525; 95% CI 1.0612-1.2517; p = 0.0007) in the IVW method, but no evidence of a causal effect T2DM on PBC was found (OR 0.9905; 95% CI 0.8446-1.1616; p = 0.9071) in IVW. Results of the reverse MR analysis suggested genetic susceptibility that PBC was associated with an increased risk of T1DM (IVW: OR 1.1991; 95% CI 1.12-1.2838; p = 1.81E-07), but no evidence of a causal effect PBC on T2DM was found (IVW: OR 1.0101; 95% CI 0.9892-1.0315; p = 0.3420). Conclusion: The current study indicated that T1DM increased the risk of developing PBC and vice versa. There was no proof of a causal connection between PBC probability and T2DM. Our results require confirmation through additional replication in larger populations.

The causal relationship between cathepsins and digestive system tumors: a Mendelian randomization study.

Background: Multiple studies have confirmed the significant role of cathepsins in the development and progression of digestive system tumors. However, further investigation is needed to determine the causal relationships. Methods: We conducted a two-sample bidirectional Mendelian randomization (MR) study using pooled data from a genome-wide association study (GWAS) to assess the causal associations between nine cathepsins (cathepsin B, E, F, G, H, L2, O, S, and Z) and six types of digestive system tumors, including hepatocellular carcinoma (HCC), pancreatic cancer (PCa), biliary tract cancer (BTC), colorectal cancer (CRC), gastric carcinoma (GC), and esophageal cancer (EC). We employed the following methods including inverse variance weighting (IVW), MR-Egger, weighted median (WM), Cochran's Q, MR-PRESSO, MR-Egger intercept test and leave-one-out sensitivity analysis. The STROBE-MR checklist for the reporting of MR studies was used in this study. Results: The risk of HCC increased with high levels of cathepsin G (IVW: p = 0.029, odds ratio (OR) = 1.369, 95% confidence interval (CI) = 1.033-1.814). Similarly, BTC was associated with elevated cathepsin B levels (IVW: p = 0.025, OR = 1.693, 95% CI = 1.070-2.681). Conversely, a reduction in PCa risk was associated with increased cathepsin H levels (IVW: p = 0.027, OR = 0.896, 95% CI = 0.812-0.988). Lastly, high levels of cathepsin L2 were found to lower the risk of CRC (IVW: p = 0.034, OR = 0.814, 95% CI = 0.674-0.985). Conclusion: Our findings confirm the causal relationship between cathepsins and digestive system tumors, which can offer valuable insights for the diagnosis and treatment of digestive system tumors.

Identification and functional analysis of the hub Ferroptosis-Related gene EZH2 in diabetic kidney disease.

BACKGROUND: Diabetic kidney disease (DKD) is a common microvascular complication and one of the main causes of death in diabetes. Ferroptosis, an iron-dependent mode of cell death characterized by lipid ROS accumulation, was found to be associated with a number of diseases and has great potential for kidney diseases. It has great value to identify potential ferroptosis-related genes and their biological mechanisms in DKD. METHODS: We obtained the GSE30122 dataset from Gene Expression Omnibus (GEO) database and ferroptosis-related genes from the Ferrdb database. After differential expression analysis, and three machine learning algorithms, the hub ferroptosis-related gene EZH2 was identified. In order to investigate the function of EZH2, Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA) and single cell analysis were conducted. The expression of EZH2 was validated in DKD patients, HK-2 cell models and DKD mouse models. EZH2 knockdown HK-2 cells and HK-2 cells treated with GSK126 were performed to verify whether EZH2 affected ferroptosis in DKD. CHIP assay was used to detect whether EZH2 regulated ferroptosis by suppressing SLC7A11. Molecular docking was performed to explore EZH2 and four traditional Chinese medicine (Sennoside A, Berberine, Umbelliferone, Platycodin D) related to ferroptosis in DKD treatment. RESULTS: According to the GSE30122 dataset in GEO and ferroptosis-related genes from the Ferrb database, we obtained the hub ferroptosis-related gene EZH2 in DKD via diversified machine learning methods. The increasing of EZH2 expression was shown in single cell analysis, DKD patients, DKD mouse models and high glucose induced DKD cell models. Further study showed that EZH2 knockdown and inhibition can alleviate HG-induced ferroptosis in vitro. CHIP assay showed EZH2-mediated epigenetic silencing regulated the expression of SLC7A11. Molecular docking results showed that EZH2 had strong binding stability with Sennoside A, Berberine, Umbelliferone, and Platycodin D. CONCLUSION: Overall, our data shouwed that histone H3K27 methyltransferase EZH2 could regulate the renal tubular epithelial cell ferroptosis by suppressing SLC7A11 in DKD, which may serve as a credible reliable indicator for diagnosing DKD and a potential target for treatment.

Exploring resting-state EEG oscillations in patients with Neuromyelitis Optica Spectrum Disorder.

BACKGROUND AND OBJECTIVE: Quantitative resting-state electroencephalography (rs-EEG) is a convenient method for characterizing the functional impairments and adaptations of the brain that has been shown to be valuable for assessing many neurological and psychiatric disorders, especially in monitoring disease status and assisting neuromodulation treatment. However, it has not yet been explored in patients with neuromyelitis optica spectrum disorder (NMOSD). This study aimed to investigate the rs-EEG features of NMOSD patients and explore the rs-EEG features related to disease characteristics and complications (such as anxiety, depression, and fatigue). METHODS: A total of 32 NMOSD patients and 20 healthy controls (HCs) were recruited; their demographic and disease information were collected, and their anxiety, depression, and fatigue symptoms were evaluated. The rs-EEG power spectra of all the participants were obtained. After excluding the participants with low-quality rs-EEG data during processing, statistical analysis was conducted based on the clinical information and rs-EEG data of 29 patients and 19 HCs. The rs-EEG power (the mean spectral energy (MSE) of absolute power and relative power in all frequency bands, as well as the specific power for all electrode sites) of NMOSD patients and HCs was compared. Furthermore, correlation analyses were performed between rs-EEG power and other variables for NMOSD patients (including the disease characteristics and complications). RESULTS: The distribution of the rs-EEG power spectra in NMOSD patients was similar to that in HCs. The dominant alpha-peaks shifted significantly towards a lower frequency for patients when compared to HCs. The delta and theta power was significantly increased in the NMOSD group compared to that in the HC group. The alpha oscillation power was found to be significantly negatively associated with the degree of anxiety (reflected by the anxiety subscore of hospital anxiety and depression scale (HADS)) and the degree of depression (reflected by the depression subscore of HADS). The gamma oscillation power was revealed to be significantly positively correlated with the fatigue severity scale (FSS) score, while further analysis indicated that the electrode sites of almost the whole brain region showing correlations with fatigue. Regarding the disease variables, no statistically significant rs-EEG features were related to the main disease features in NMOSD patients. CONCLUSION: The results of this study suggest that the rs-EEG power spectra of NMOSD patients show increased slow oscillations and are potential biomarkers of widespread white matter microstructural damage in NMOSD. Moreover, this study revealed the rs-EEG features associated with anxiety, depression, and fatigue in NMOSD patients, which might help in the evaluation of these complications and the development of neuromodulation treatment. Quantitative rs-EEG analysis may play an important role in the management of NMOSD patients, and future studies are warranted to more comprehensively understand its application value.

Tumor-derived KLK8 predicts inferior survival and promotes an immune-suppressive tumor microenvironment in lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is the second most common lung cancer worldwide, leading to millions of deaths annually. Although immunotherapy has expanded the therapeutic choices for LUSC and achieved considerable efficacy in a subset of patients, many patients could not benefit, and resistance was pervasive. Therefore, it is significant to investigate the mechanisms leading to patients' poor response to immunotherapies and explore novel therapeutic targets. Using multiple public LUSC datasets, we found that Kallikrein-8 (KLK8) expression was higher in tumor samples and was correlated with inferior survival. Using a LUSC cohort (n = 190) from our center, we validated the bioinformatic findings about KLK8 and identified high KLK8 expression as an independent risk factor for LUSC. Function enrichment showed that several immune signaling pathways were upregulated in the KLK8 low-expression group and downregulated in the KLK8 high-expression group. For patients with low KLK8 expression, they were with a more active TME, which was both observed in the TCGA database and immune marker immunohistochemistry, and they had extensive positive relations with immune cells with tumor-eliminating functions. This study identified KLK8 as a risk factor in LUSC and illustrated the associations between KLK8 and cancer immunity, suggesting the potentiality of KLK8 as a novel immune target in LUSC.

Multimodal Vigilance Estimation With Modality-Pairwise Contrastive Loss.

Nowadays, how to estimate vigilance with higher accuracy has become a hot field of research direction. Although the increasing available modalities opens the door for amazing new possibilities to achieve good performance, the uncertain cross-modal interaction still poses a real challenge to the multimodal fusion. In this paper, a cross-modality alignment method has been proposed based on the contrastive learning for extracting shared but not the same information among modalities. The contrastive learning is adopted to minimize the intermodal differences by maximizing the similarity of semantic representation of modalities. Applying our proposed modeling framework, we evaluated our approach on SEED-VIG dataset consisting of EEG and EOG signals. Experiments showed that our study achieved state-of-the-art multimodal vigilance estimation performance both in intra-subject and inter-subject situations, the average of RMSE/CORR were improved to 0.092/0.893 and 0.144/0.887, respectively. In addition, analysis on the frequency bands showed that theta and alpha activities contain valuable information for vigilance estimation, and the correlation between them and PERCLOS can be significantly improved by contrastive learning. We argue that the proposed method in the inter-subject case could offer the possibility of reducing the high-cost of data annotation, and further analysis may provide an idea for the application of multimodal vigilance regression.

Defocused mode in depressed mood and its changes in time-frequency attention-related beta.

Depressed mood has been proposed to possibly possess a unique mode of defocused attention. However, this argument needs to be supported by experimental evidence based on attentional performance. The present study used a perceptual load paradigm, combining factors of perceptual load, distractor-target compatibility, and eccentricity, to investigate the degree of attentional distraction in depressed mood. In addition, the mode of attentional distraction associated with depressed mood was explored with the time-frequency features of electroencephalography (EEG). The behavioral results showed that the high depressed mood (HD) group had significantly higher attentional distraction than the low depressed mood (LD) group. EEG results showed that 1) the beta power (especially beta-2, 18-30 Hz) of the two groups differed in the medio-late part of the attentional distraction, with significantly lower power in the HD group than in the LD group; 2) the results of the correlation between beta-2 power and depression scores revealed a significant negative correlation. These results imply that beta-2 is a potential marker that may be sensitive to depressed mood during attentional processing, which was further supported by the classification results of the support vector machine (SVM) with 80.65% accuracy between the HD and LD groups.

[Water Environment Characteristics and Water Quality Assessment of Typical Lakes in Inner Mongolia].

Lakes on the Inner Mongolia Plateau, located in the ecologically fragile area of the northern border of China, play a very important role in regulating the regional climate and ecological environment and maintaining biodiversity. Owing to the dual influence of natural factors and human factors, the lake water environment in Inner Mongolia is facing challenges. To clarify the overall water quality of lakes in Inner Mongolia, based on the water quality data of typical lakes in Inner Mongolia in autumn 2019(October-November) and summer 2021(July-August), the temporal and spatial variation in water quality was discussed, and the influence of different indexes on lake water quality was analyzed, and the key factors affecting lake water quality were identified. The results showed as follows:① the spatiotemporal distribution of multiple physicochemical indices of typical lakes in Inner Mongolia were different in the two seasons. On the time scale, the concentration of ammonia nitrogen(NH4+-N) and nitrite nitrogen(NO2--N) were lower in autumn than that in summer, whereas dissolved oxygen(DO) was higher in autumn than that in summer. On the spatial scale, the concentrations of total phosphorus(TP), total nitrogen(TN), chemical oxygen demand(COD), and salinity(Sal) and other indicators in the southwest lakes of Inner Mongolia were higher than those of lakes in the northeast, but the DO index showed the opposite trend. ② Dissolved total solids(TDS) was the main characteristic factor of water quality of typical lakes in Inner Mongolia. ③ The spatiotemporal distribution of lake water quality index(WQI) was significantly different. The lake water quality level decreased with the increase in TDS, and the lake water quality was better in autumn than that in summer.

The suitability of isotopic methods in identifying water sources of a shallow-rooted herbaceous plant in a desert steppe.

Isotopic methodologies have gained prominence in investigating the composition of plant water sources; however, concerns regarding their suitability and reliability in diverse environments have emerged in recent years. This study presents a comparative analysis of root, soil, and liquid water (precipitation, dew, and groundwater) samples obtained from a desert steppe using isotope ratio infrared spectrometry (IRIS) and isotope ratio mass spectrometry (IRMS). The objective was to evaluate the applicability of these techniques in discerning the water sources of Stipa breviflora, a shallow-rooted herbaceous plant species. Additionally, we explored the root water uptake characteristics and water use strategy of S. breviflora. Our findings indicate that the IRIS method had more enriched values of D compared to the IRMS method across all samples, while no discernible pattern was observed for 18O. Notably, the differences observed among all samples exceeded the instruments' accuracies. Moreover, an unexpected occurrence was noted, whereby both D and 18O values in the root water were more enriched than in any of the considered water sources, rendering identification of the plant water sources unattainable. By conducting a re-analysis of more refined soil layer samples, we discovered that S. breviflora exhibits the ability to absorb and utilize water sources in close proximity to the soil surface. It further suggested that the shallow-rooted herbaceous plants in desert steppes can exploit small rainfalls, frequently overlooked in their ecological importance. Considering the distinctive soil and plant characteristics of desert steppes, we recommend adopting IRMS methods in conjunction with refined surface soil sampling for isotopic analysis aiming to identify water sources of shallow-rooted herbaceous plants. This study provides novel insights into assessing the suitability of isotopic techniques for analyzing plant water sources, while enhancing our understanding of water use strategies and environmental adaptation mechanisms employed by shallow-rooted herbaceous plants within xerophytic grassland ecosystems.

Recombination of the right cerebral cortex in patients with left side USN after stroke: fNIRS evidence from resting state.

Objective: Unilateral spatial neglect (USN) is an impaired contralesional stimulus detection, response, or action, causing functional disability. After a stroke, the right hemisphere experiences USN more noticeably, severely, and persistently than the left. However, few studies using fNIRS have been reported in cases of USN. This study aimed to confirm weaker RSFC in USN and investigate the potential inherent features in hemodynamic fluctuations that may be associated with USN. Furthermore, these features were combined into a mathematical model for more accurate classification. Methods: A total of 33 stroke patients with right-sided brain damage were chosen, of whom 12 had non-USN after stroke, and 21 had USN after stroke (the USN group). Graph theory was used to evaluate the hemodynamic signals of the brain's right cerebral cortex during rest. Furthermore, a support vector machine model was built to categorize the subjects into two groups based on the chosen network properties. Results: First, mean functional connectivity was lower in the USN group (0.745 ± 0.239) than in the non-USN group (0.843 ± 0.254) (t = -4.300, p < 0.001). Second, compared with the non-USN group, USN patients had a larger clustering coefficient (C) (t = 3.145, p < 0.001), local efficiency (LE) (t = 3.189, p < 0.001), and smaller global efficiency (GE) (t = 3.047, p < 0.001). Notably, there were differences in characteristic path length (L) and small worldness (σ) values between the two groups at certain thresholds, mainly as higher L (t = 3.074, p < 0.001) and lower small worldness (σ) values (t = 2.998, p < 0.001) in USN patients compared with non-USN patients. Finally, the classification accuracy of the SVM model based on AUC aC (t = -2.259, p = 0.031) and AUC aLE (t = -2.063, p = 0.048) was 85%, the sensitivity was 75%, and the specificity was 89%. Conclusion: The functional network architecture of the right cerebral cortex exhibits significant topological alterations in individuals with USN following stroke, and the sensitivity index based on the small-world property AUC may be utilized to identify these patients accurately.

Correction to: Bacomics: a comprehensive cross area originating in the studies of various brain-apparatus conversations.

[This corrects the article DOI: 10.1007/s11571-020-09577-7.].

Stem cell-derived exosomal MicroRNAs: Potential therapies in diabetic kidney disease.

The diabetic kidney disease (DKD) is chronic kidney disease caused by diabetes and one of the most common comorbidities. It is often more difficult to treat end-stage renal disease once it develops because of its complex metabolic disorders, so early prevention and treatment are important. However, currently available DKD therapies are not ideal, and novel therapeutic strategies are urgently needed. The potential of stem cell therapies partly depends on their ability to secrete exosomes. More and more studies have shown that stem cell-derived exosomes take part in the DKD pathophysiological process, which may offer an effective therapy for DKD treatment. Herein, we mainly review potential therapies of stem cell-derived exosomes mainly stem cell-derived exosomal microRNAs in DKD, including their protective effects on mesangial cells, podocytes and renal tubular epithelial cells. Using this secretome as possible therapeutic drugs without potential carcinogenicity should be the focus of further research.

Multiple primary lung cancer: Updates of clinical management and genomic features.

In recent decades, multiple primary lung cancer (MPLC) has been increasingly prevalent in clinical practice. However, many details about MPLC have not been completely settled, such as understanding the driving force, clinical management, pathological mechanisms, and genomic architectures of this disease. From the perspective of diagnosis and treatment, distinguishing MPLC from lung cancer intrapulmonary metastasis (IPM) has been a clinical hotpot for years. Besides, compared to patients with single lung lesion, the treatment for MPLC patients is more individualized, and non-operative therapies, such as ablation and stereotactic ablative radiotherapy (SABR), are prevailing. The emergence of next-generation sequencing has fueled a wave of research about the molecular features of MPLC and advanced the NCCN guidelines. In this review, we generalized the latest updates on MPLC from definition, etiology and epidemiology, clinical management, and genomic updates. We summarized the different perspectives and aimed to offer novel insights into the management of MPLC.

Micro-aeration assisted with electrogenic respiration enhanced the microbial catabolism and ammonification of aromatic amines in industrial wastewater.

Improvement of refractory nitrogen-containing organics biodegradation is crucial to meet discharged nitrogen standards and guarantee aquatic ecology safety. Although electrostimulation accelerates organic nitrogen pollutants amination, it remains uncertain how to strengthen ammonification of the amination products. This study demonstrated that ammonification was remarkably facilitated under micro-aerobic conditions through the degradation of aniline, an amination product of nitrobenzene, using an electrogenic respiration system. The microbial catabolism and ammonification were significantly enhanced by exposing the bioanode to air. Based on 16S rRNA gene sequencing and GeoChip analysis, our results indicated that aerobic aniline degraders and electroactive bacteria were enriched in suspension and inner electrode biofilm, respectively. The suspension community had a significantly higher relative abundance of catechol dioxygenase genes contributing to aerobic aniline biodegradation and reactive oxygen species (ROS) scavenger genes to protect from oxygen toxicity. The inner biofilm community contained obviously higher cytochrome c genes responsible for extracellular electron transfer. Additionally, network analysis indicated the aniline degraders were positively associated with electroactive bacteria and could be the potential hosts for genes encoding for dioxygenase and cytochrome, respectively. This study provides a feasible strategy to enhance nitrogen-containing organics ammonification and offers new insights into the microbial interaction mechanisms of micro-aeration assisted with electrogenic respiration.

A Novel In-Home Sleep Monitoring System Based on Fully Integrated Multichannel Front-End Chip and Its Multilevel Analyses.

OBJECTIVE: A novel in-home sleep monitoring system with an 8-channel biopotential acquisition front-end chip is presented and validated via multilevel data analyses and comparision with advanced polysomnography. METHODS AND PROCEDURES: The chip includes a cascaded low-noise programmable gain amplifier (PGA) and 24-bit [Formula: see text]-[Formula: see text] analog-to-digital converter (ADC). The PGA is based on three op-amp structure while the ADC adopts cascade of integrator feedforward and feedback (CIFF-B) architecture. An innovative chopper-modulated input-scaling-down technique enhances the dynamic range. The proposed system and commercial polysomnography were used for in-home sleep monitoring of 20 healthy participants. The consistency and significance of the two groups' data were analyzed. RESULTS: Fabricated in 180 nm BCD technology, the input-referred noise, input impedance, common-mode rejection ratio, and dynamic range of the acquisition front-end chip were [Formula: see text]Vpp, 1.25 GN), 113.9 dB, and 119.8 dB. The kappa coefficients between the sleep stage labels of the three scorers were 0.80, 0.76, and 0.79. The consistency of the slowing index, multiscale entropy, and percentile features between the two devices reached 0.958, 0.885, and 0.834. The macro sleep architecture characteristics of the two devices were not significantly different (all p [Formula: see text] 0.05). CONCLUSION: The proposed chip was applied to develop an in-home sleep monitoring system with significantly reduced size, power, and cost. Multilevel analyses demonstrated that this system collects stable and accurate in-home sleep data. CLINICAL IMPACT: The proposed system can be applied for long-term in-home sleep monitoring outside of laboratory environments and sleep disorders screening that with low cost.