Peroxymonosulfate enhanced photocatalytic degradation of organic dye by metal-free TpTt-COF under visible light irradiation.

Recently, the activation of persulfate (PDS) by non-metallic photocatalysts under visible light has attracted significant interest in applications in environmental remediation. This study presents a pioneering investigation into the combined application of the TpTt-COF and PMS for visible light degradation of organic dyes. Synthesized orange TpTt-COF monomers exhibit exceptional crystallinity, a 2D structure, and notable stability in harsh conditions. The broad visible light absorption around a wavelength of 708 nm. The TpTt-COF emerges as a promising candidate for photocatalytic dye degradation. The study addresses high charge recombination in the TpTt-COF, highlighting the crucial role of its electron donor and acceptor for the PMS activation. Comparative analyses against traditional photocatalytic materials, such as the metal-free carbon-based material g-C3N4 and transition metal-containing TiO2, demonstrate TpTt-COF's superior performance, generating diverse free radicals. In simulated experiments, the TpTt-COF's degradation rate surpasses PMS-combined g-C3N4 by 13.9 times. and 1.6 times higher than the TpTt-COF alone. Remarkably, the TpTt-COF maintains high activity under harsh environments. Investigations into the degradation mechanism and the TpTt-COF's reusability reveal its efficiency and stability. Under visible light, TpTt-COF facilitates efficient electron-hole separation. Combining the TpTt-COF with PMS produces various radicals, ensuring effective separation and a synergistic effect. Radical quenching experiments confirm the pivotal role of O2-· radicals, while ·OH and SO4-· radicals intensify the degradation. After five cycles, TpTt-COF maintains an impressive 83.2% degradation efficiency. This study introduces an efficient photocatalytic system mediated by PMS and valuable insights into governing mechanisms for organic pollutant degradation in water environments.

Characterization of tumor microbiome and associations with prognosis in intrahepatic cholangiocarcinoma.

BACKGROUND: The tumor microbiome has been characterized in several malignancies; however, no previous studies have investigated its role in intrahepatic cholangiocarcinoma (ICC). Hence, we explored the tumor microbiome and its association with prognosis in ICC. METHODS: One hundred and twenty-one ICC tumor samples and 89 adjacent normal tissues were profiled by 16S rRNA sequencing. Microbial differences between tumor and adjacent nontumoral liver tissues were assessed. Tumor microbial composition was then evaluated to detect its association with prognosis. Finally, a risk score calculated by the tumor microbiota was accessed by the least absolute shrinkage and selector operator method (Lasso) to predict prognosis of ICC. RESULTS: The tumor microbiome displayed a greater diversity than that in adjacent nontumoral liver tissues. Tumor samples were characterized by a higher abundance of Firmicutes, Actinobacteria, Bacteroidetes, and Acidobacteriota. Higher tumor microbial α diversity was associated with lymph node metastasis and predicted shortened overall survival (OS) and recurrence-free survival (RFS). A total of 11 bacteria were selected to generate the risk score by Lasso. This score showed potential in predicting OS, and was an independent risk factor for OS. CONCLUSION: In conclusion, our study characterized the tumor microbiome and revealed its role in predicting prognosis in ICC.

Delayed care-seeking in international migrant workers with imported malaria in China.

BACKGROUND: Imported malaria cases continue to pose major challenges in China as well as in other countries that have achieved elimination. Early diagnosis and treatment of each imported malaria case is the key to successfully maintaining malaria elimination success. This study aimed to build an easy-to-use predictive nomogram to predict and intervene against delayed care-seeking among international migrant workers with imported malaria. METHODS: A prediction model was built based on cases with imported malaria from 2012 to 2019, in Jiangsu Province, China. Routine surveillance information (e.g. sex, age, symptoms, origin country and length of stay abroad), data on the place of initial care-seeking and the gross domestic product (GDP) of the destination city were extracted. Multivariate logistic regression was performed to identify independent predictors and a nomogram was established to predict the risk of delayed care-seeking. The discrimination and calibration of the nomogram was performed using area under the curve and calibration plots. In addition, four machine learning models were used to make a comparison. RESULTS: Of 2255 patients with imported malaria, 636 (28.2%) sought care within 24 h after symptom onset, and 577 (25.6%) sought care 3 days after symptom onset. Development of symptoms before entry into China, initial care-seeking from superior healthcare facilities and a higher GDP level of the destination city were significantly associated with delayed care-seeking among migrant workers with imported malaria. Based on these independent risk factors, an easy-to-use and intuitive nomogram was established. The calibration curves of the nomogram showed good consistency. CONCLUSIONS: The tool provides public health practitioners with a method for the early detection of delayed care-seeking risk among international migrant workers with imported malaria, which may be of significance in improving post-travel healthcare for labour migrants, reducing the risk of severe malaria, preventing malaria reintroduction and sustaining achievements in malaria elimination.

Death receptor 5 is required for intestinal stem cell activity during intestinal epithelial renewal at homoeostasis.

Intestinal epithelial renewal, which depends on the proliferation and differentiation of intestinal stem cells (ISCs), is essential for epithelial homoeostasis. Understanding the mechanism controlling ISC activity is important. We found that death receptor 5 (DR5) gene deletion (DR5-/-) mice had impaired epithelial absorption and barrier function, resulting in delayed weight gain, which might be related to the general reduction of differentiated epithelial cells. In DR5-/- mice, the expression of ISC marker genes, the number of Olfm4+ ISCs, and the number of Ki67+ and BrdU+ cells in crypt were reduced. Furthermore, DR5 deletion inhibited the expression of lineage differentiation genes driving ISC differentiation into enterocytes, goblet cells, enteroendocrine cells, and Paneth cells. Therefore, DR5 gene loss may inhibit the intestinal epithelial renewal by dampening ISC activity. The ability of crypts from DR5-/- mice to form organoids decreased, and selective DR5 activation by Bioymifi promoted organoid growth and the expression of ISC and intestinal epithelial cell marker genes. Silencing of endogenous DR5 ligand TRAIL in organoids down-regulated the expression of ISC and intestinal epithelial cell marker genes. So, DR5 expressed in intestinal crypts was involved in the regulation of ISC activity. DR5 deletion in vivo or activation in organoids inhibited or enhanced the activity of Wnt, Notch, and BMP signalling through regulating the production of Paneth cell-derived ISC niche factors. DR5 gene deletion caused apoptosis and DNA damage in transit amplifying cells by inhibiting ERK1/2 activity in intestinal crypts. Inhibition of ERK1/2 with PD0325901 dampened the ISC activity and epithelial regeneration. In organoids, when Bioymifi's effect in activating ERK1/2 activity was completely blocked by PD0325901, its role in stimulating ISC activity and promoting epithelial regeneration was also eliminated. In summary, DR5 in intestinal crypts is essential for ISC activity during epithelial renewal under homoeostasis.

Preparation of magnetic polyacrylamide hydrogel with chitosan for immobilization of glutamate decarboxylase to produce γ-aminobutyric acid.

Gamma-aminobutyric acid (GABA) is an vital neurotransmitter, and the reaction to obtain GABA through biocatalysis requires coenzymes, which are therefore limited in the production of GABA. In this study, polyacrylamide hydrogels doped with chitosan and waste toner were synthesized for glutamate decarboxylase (GAD) and coenzyme co-immobilization to realize the production of GABA and the recovery of coenzymes. Enzymatic properties of immobilized GAD were discussed. The immobilized enzymes have significantly improved pH and temperature tolerance compared to free enzymes. In terms of reusability, after 10 repeated reuses of the immobilized GAD, the residual enzyme activity of immobilized GAD still retains 100% of the initial enzyme activity, and the immobilized coenzyme can also be kept at about 32%, with better stability and reusability. And under the control of no exogenous pH, immobilized GAD showed good performance in producing GABA. Therefore, in many ways, the new composite hydrogel provides another way for the utilization of waste toner and promises the possibility of industrial production of GABA.

Assessing the risk of malaria local transmission and re-introduction in China from pre-elimination to elimination: A systematic review.

Assessing the risk of malaria local transmission and re-introduction is crucial for the preparation and implementation of an effective elimination campaign and the prevention of malaria re-introduction in China. Therefore, this review aims to evaluate the risk factors for malaria local transmission and re-introduction in China over the period of pre-elimination to elimination. Data were obtained from six databases searched for studies that assessed malaria local transmission risk before malaria elimination and re-introduction risk after the achievement of malaria elimination in China since the launch of the NMEP in 2010, employing the keywords "malaria" AND ("transmission" OR "re-introduction") and their synonyms. A total of 8,124 articles were screened and 53 articles describing 55 malaria risk assessment models in China from 2010 to 2023, including 40 models assessing malaria local transmission risk (72.7%) and 15 models assessing malaria re-introduction risk (27.3%). Factors incorporated in the 55 models were extracted and classified into six categories, including environmental and meteorological factors (39/55, 70.9%), historical epidemiology (35/55, 63.6%), vectorial factors (32/55, 58.2%), socio-demographic information (15/26, 53.8%), factors related to surveillance and response capacity (18/55, 32.7%), and population migration aspects (13/55, 23.6%). Environmental and meteorological factors as well as vectorial factors were most commonly incorporated in models assessing malaria local transmission risk (29/40, 72.5% and 21/40, 52.5%) and re-introduction risk (10/15, 66.7% and 11/15, 73.3%). Factors related to surveillance and response capacity and population migration were also important in malaria re-introduction risk models (9/15, 60%, and 6/15, 40.0%). A total of 18 models (18/55, 32.7%) reported the modeling performance. Only six models were validated internally and five models were validated externally. Of 53 incorporated studies, 45 studies had a quality assessment score of seven and above. Environmental and meteorological factors as well as vectorial factors play a significant role in malaria local transmission and re-introduction risk assessment. The factors related to surveillance and response capacity and population migration are more important in assessing malaria re-introduction risk. The internal and external validation of the existing models needs to be strengthened in future studies.

Cooperative Time-Varying Formation Fuzzy Tracking Control of Multiple Heterogeneous Uncertain Marine Surface Vehicles With Actuator Failures.

This article addresses the cooperative time-varying formation fuzzy tracking control problem for a cluster of heterogeneous multiple marine surface vehicles subject to unknown nonlinearity and actuator failures. The proposed cooperative control scheme consists of two parts: 1) a distributed time-varying formation observer and 2) a decentralized adaptive fuzzy tracking controller. The distributed observer is designed to obtain a predefined time-varying formation pattern under a directed communication topology. Subsequently, based on the states of the distributed observer, a decentralized fuzzy tracking control law is developed using fuzzy-logic systems and the adaptive approach. Lyapunov functions are constructed to guarantee that the controlled marine vehicles attain the desired time-varying formation with asymptotical stability of tracking errors. Finally, simulation results are presented to validate the efficacy of the proposed control methodology.

A Lightweight Recognition Method for Rice Growth Period Based on Improved YOLOv5s.

The identification of the growth and development period of rice is of great significance to achieve high-yield and high-quality rice. However, the acquisition of rice growth period information mainly relies on manual observation, which has problems such as low efficiency and strong subjectivity. In order to solve these problems, a lightweight recognition method is proposed to automatically identify the growth period of rice: Small-YOLOv5, which is based on improved YOLOv5s. Firstly, the new backbone feature extraction network MobileNetV3 was used to replace the YOLOv5s backbone network to reduce the model size and the number of model parameters, thus improving the detection speed of the model. Secondly, in the feature fusion stage of YOLOv5s, we introduced a more lightweight convolution method, GsConv, to replace the standard convolution. The computational cost of GsConv is about 60-70% of the standard convolution, but its contribution to the model learning ability is no less than that of the standard convolution. Based on GsConv, we built a lightweight neck network to reduce the complexity of the network model while maintaining accuracy. To verify the performance of Small-YOLOv5s, we tested it on a self-built dataset of rice growth period. The results show that compared with YOLOv5s (5.0) on the self-built dataset, the number of the model parameter was reduced by 82.4%, GFLOPS decreased by 85.9%, and the volume reduced by 86.0%. The mAP (0.5) value of the improved model was 98.7%, only 0.8% lower than that of the original YOLOv5s model. Compared with the mainstream lightweight model YOLOV5s- MobileNetV3-Small, the number of the model parameter was decreased by 10.0%, the volume reduced by 9.6%, and the mAP (0.5:0.95) improved by 5.0%-reaching 94.7%-and the recall rate improved by 1.5%-reaching 98.9%. Based on experimental comparisons, the effectiveness and superiority of the model have been verified.

EEG-based emergency braking intention detection during simulated driving.

BACKGROUND: Current research related to electroencephalogram (EEG)-based driver's emergency braking intention detection focuses on recognizing emergency braking from normal driving, with little attention to differentiating emergency braking from normal braking. Moreover, the classification algorithms used are mainly traditional machine learning methods, and the inputs to the algorithms are manually extracted features. METHODS: To this end, a novel EEG-based driver's emergency braking intention detection strategy is proposed in this paper. The experiment was conducted on a simulated driving platform with three different scenarios: normal driving, normal braking and emergency braking. We compared and analyzed the EEG feature maps of the two braking modes, and explored the use of traditional methods, Riemannian geometry-based methods, and deep learning-based methods to predict the emergency braking intention, all using the raw EEG signals rather than manually extracted features as input. RESULTS: We recruited 10 subjects for the experiment and used the area under the receiver operating characteristic curve (AUC) and F1 score as evaluation metrics. The results showed that both the Riemannian geometry-based method and the deep learning-based method outperform the traditional method. At 200 ms before the start of real braking, the AUC and F1 score of the deep learning-based EEGNet algorithm were 0.94 and 0.65 for emergency braking vs. normal driving, and 0.91 and 0.85 for emergency braking vs. normal braking, respectively. The EEG feature maps also showed a significant difference between emergency braking and normal braking. Overall, based on EEG signals, it was feasible to detect emergency braking from normal driving and normal braking. CONCLUSIONS: The study provides a user-centered framework for human-vehicle co-driving. If the driver's intention to brake in an emergency can be accurately identified, the vehicle's automatic braking system can be activated hundreds of milliseconds earlier than the driver's real braking action, potentially avoiding some serious collisions.

Predicting the risk of malaria re-introduction in countries certified malaria-free: a systematic review.

BACKGROUND: Predicting the risk of malaria in countries certified malaria-free is crucial for the prevention of re-introduction. This review aimed to identify and describe existing prediction models for malaria re-introduction risk in eliminated settings. METHODS: A systematic literature search following the PRISMA guidelines was carried out. Studies that developed or validated a malaria risk prediction model in eliminated settings were included. At least two authors independently extracted data using a pre-defined checklist developed by experts in the field. The risk of bias was assessed using both the prediction model risk of bias assessment tool (PROBAST) and the adapted Newcastle-Ottawa Scale (aNOS). RESULTS: A total 10,075 references were screened and 10 articles describing 11 malaria re-introduction risk prediction models in 6 countries certified malaria free. Three-fifths of the included prediction models were developed for the European region. Identified parameters predicting malaria re-introduction risk included environmental and meteorological, vectorial, population migration, and surveillance and response related factors. Substantial heterogeneity in predictors was observed among the models. All studies were rated at a high risk of bias by PROBAST, mostly because of a lack of internal and external validation of the models. Some studies were rated at a low risk of bias by the aNOS scale. CONCLUSIONS: Malaria re-introduction risk remains substantial in many countries that have eliminated malaria. Multiple factors were identified which could predict malaria risk in eliminated settings. Although the population movement is well acknowledged as a risk factor associated with the malaria re-introduction risk in eliminated settings, it is not frequently incorporated in the risk prediction models. This review indicated that the proposed models were generally poorly validated. Therefore, future emphasis should be first placed on the validation of existing models.

Lung microbiota and potential treatment of respiratory diseases.

The unique microbiome found in the lungs has been studied and shown to be associated with both pulmonary homeostasis and lung diseases. The lung microbiome has the potential to produce metabolites that modulate host-microbe interactions. Specifically, short-chain fatty acids (SCFAs) produced by certain strains of the lung microbiota have been shown to regulate immune function and maintain gut mucosal health. In response, this review described the distribution and composition of the microbiota in lung diseases and discussed the impact of the lung microbiota on health and lung disease. In addition, the review further elaborated on the mechanism of microbial metabolites in microbial-host interaction and their application in the treatment of lung diseases. A better understanding of the interaction between the microbiota, metabolites, and host will provide potential strategies for the development of novel methods for the treatment of pulmonary microbial induced lung diseases.

Depletion of CUL4B in macrophages ameliorates diabetic kidney disease via miR-194-5p/ITGA9 axis.

Diabetic kidney disease (DKD) is the most prevalent chronic kidney disease. Macrophage infiltration in the kidney is critical for the progression of DKD. However, the underlying mechanism is far from clear. Cullin 4B (CUL4B) is the scaffold protein in CUL4B-RING E3 ligase complexes. Previous studies have shown that depletion of CUL4B in macrophages aggravates lipopolysaccharide-induced peritonitis and septic shock. In this study, using two mouse models for DKD, we demonstrate that myeloid deficiency of CUL4B alleviates diabetes-induced renal injury and fibrosis. In vivo and in vitro analyses reveal that loss of CUL4B suppresses migration, adhesion, and renal infiltration of macrophages. Mechanistically, we show that high glucose upregulates CUL4B in macrophages. CUL4B represses expression of miR-194-5p, which leads to elevated integrin α9 (ITGA9), promoting migration and adhesion. Our study suggests the CUL4B/miR-194-5p/ITGA9 axis as an important regulator for macrophage infiltration in diabetic kidneys.

Association of BRAF Variants With Disease Characteristics, Prognosis, and Targeted Therapy Response in Intrahepatic Cholangiocarcinoma.

Importance: BRAF variants are associated with tumor progression; however, the prevalence of BRAF variant subtypes and their association with disease characteristics, prognosis, and targeted therapy response in patients with intrahepatic cholangiocarcinoma (ICC) are largely unknown. Objective: To explore the association of BRAF variant subtypes with disease characteristics, prognosis, and targeted therapy response in patients with ICC. Design, Setting, and Participants: In this cohort study, 1175 patients who underwent curative resection for ICC from January 1, 2009, through December 31, 2017, were evaluated at a single hospital in China. Whole-exome sequencing, targeted sequencing, and Sanger sequencing were performed to identify BRAF variants. The Kaplan-Meier method and log-rank test were used to compare overall survival (OS) and disease-free survival (DFS). Univariate and multivariate analyses were performed using Cox proportional hazards regression. Associations between BRAF variants and targeted therapy response were tested in 6 BRAF-variant, patient-derived organoid lines and in 3 of the patient donors of those lines. Data were analyzed from June 1, 2021, to March 15, 2022. Interventions: Hepatectomy in patients with ICC. Main Outcomes and Measures: The association of BRAF variant subtypes with OS and DFS. Results: Of 1175 patients with ICC, the mean (SD) age was 59.4 (10.4) years and 701 (59.7%) were men. A total of 20 different subtypes of BRAF somatic variance affecting 49 patients (4.2%) were identified; V600E was the most frequent allele in this cohort, accounting for 27% of the identified BRAF variants, followed by K601E (14%), D594G (12%), and N581S (6%). Compared with patients with non-V600E BRAF variants, patients with BRAF V600E variants were more likely to have large tumor size (10 of 13 [77%] vs 12 of 36 [33%]; P = .007), multiple tumors (7 of 13 [54%] vs 8 of 36 [22%]; P = .04), and more vascular/bile duct invasion (7 of 13 [54%] vs 8 of 36 [22%]; P = .04). Multivariate analysis revealed that BRAF V600E variants, but not overall BRAF variants or non-V600E BRAF variants, were associated with poor OS (hazard ratio [HR], 1.87; 95% CI, 1.05-3.33; P = .03) and DFS (HR, 1.66; 95% CI, 1.03-2.97; P = .04). There were also broad differences among organoids with different BRAF variant subtypes in sensitivity to BRAF or MEK inhibitors. Conclusions and Relevance: The findings of this cohort study suggest that there are broad differences among organoids with different BRAF variant subtypes in sensitivity to BRAF or MEK inhibitors. Identifying and classifying BRAF variants may be able to help guide precise treatment for patients with ICC.

Covalent post-assembly modification of π-conjugated supramolecular polymers delivers structurally robust light-harvesting nanoscale objects.

A two-component stapling strategy is used to covalently tether a new class of water-soluble supramolecular polymers built from bay-functionalized perylene bisimide (PBI) units. By leveraging a novel combined strategy where excitonic coupling and fluorescence data are exploited as spectroscopic reporters, structural design principles are established to form light-harvesting superstructures whose ground-state electronic properties are not sensitive to solvation environments. Moreover, we interrogate the structural properties of stapled superstructures by capitalizing on the drastic changes in fluorescence quantum yields against parent supramolecular assemblies. In essence, our work shows that the combination of excitonic coupling measurements and photoluminescence experiments delineates a more accurate understanding of the design principles required to limit the degree of structural defects and magnify short- and long-range electronic couplings between redox-active units in this new class of solvated nanoscale objects. These results highlight that the fragile conformation of non-covalent assemblies, which are regulated by weak secondary interactions, can be preserved by post-assembly modification of preformed supramolecular polymers. These synthetic and spectroscopic principles can in turn be codified as experimental handles to parameterize the optoelectronic properties of light-harvesting nanoscale objects.

Convolutional Neural Network with a Topographic Representation Module for EEG-Based Brain-Computer Interfaces.

Convolutional neural networks (CNNs) have shown great potential in the field of brain-computer interfaces (BCIs) due to their ability to directly process raw electroencephalogram (EEG) signals without artificial feature extraction. Some CNNs have achieved better classification accuracy than that of traditional methods. Raw EEG signals are usually represented as a two-dimensional (2-D) matrix composed of channels and time points, ignoring the spatial topological information of electrodes. Our goal is to make a CNN that takes raw EEG signals as inputs have the ability to learn spatial topological features and improve its classification performance while basically maintaining its original structure. We propose an EEG topographic representation module (TRM). This module consists of (1) a mapping block from raw EEG signals to a 3-D topographic map and (2) a convolution block from the topographic map to an output with the same size as the input. According to the size of the convolutional kernel used in the convolution block, we design two types of TRMs, namely TRM-(5,5) and TRM-(3,3). We embed the two TRM types into three widely used CNNs (ShallowConvNet, DeepConvNet and EEGNet) and test them on two publicly available datasets (the Emergency Braking During Simulated Driving Dataset (EBDSDD) and the High Gamma Dataset (HGD)). Results show that the classification accuracies of all three CNNs are improved on both datasets after using the TRMs. With TRM-(5,5), the average classification accuracies of DeepConvNet, EEGNet and ShallowConvNet are improved by 6.54%, 1.72% and 2.07% on the EBDSDD and by 6.05%, 3.02% and 5.14% on the HGD, respectively; with TRM-(3,3), they are improved by 7.76%, 1.71% and 2.17% on the EBDSDD and by 7.61%, 5.06% and 6.28% on the HGD, respectively. We improve the classification performance of three CNNs on both datasets through the use of TRMs, indicating that they have the capability to mine spatial topological EEG information. More importantly, since the output of a TRM has the same size as the input, CNNs with raw EEG signals as inputs can use this module without changing their original structures.

Chronic GPER activation prompted the proliferation of ileal stem cell in ovariectomized mice depending on Paneth cell-derived Wnt3.

Menopausal women often face long-term estrogen treatment. G protein-coupled estrogen receptor (GPER) expressed in intestinal crypt was activated by estrogen therapy, but it was unclear whether chronic GPER activation during menopause had an effect on intestinal stem cells (ISCs). We tested the effect of chronic GPER activation on ISCs of ovariectomized (OVX) mice by injection of the selective GPER agonist G-1 for 28 days, or G-1 stimulation of organoids derived from crypts of OVX mice. G-1 up-regulated crypt depth, the number of Ki67+, bromodeoxyuridine+ cells and Olfm4+ ISCs, and the expression of ISCs marker genes (Lgr5, Olfm4 and Axin2). G-1 administration promoted organoid growth, increased the number of EdU+ cells per organoid and protein expression of Cyclin D1 and cyclin B1 in organoids. After G-1 treatment in vivo or in vitro, Paneth cell-derived Wnt3, Wnt3 effector ß-catenin and Wnt target genes c-Myc and Cyclin D1 increased in ileum or organoids. Once blocking the secretion of Wnt3 from Paneth cells, the effects of G-1 on organoids growth, ISCs marker genes and Wnt/ß-catenin signaling were abolished. G-1 did not affect the number of Paneth cells in ex vivo organoids, while activated Mmp7/cryptdin program in Paneth cells, promoted their maturation, and increased the expression of lysozyme protein. G-1 pretreatment in OVX mice inhibited radiation-induced ISCs proliferation injury and enhanced the resistance of mice to intestinal injury. In conclusion, chronic GPER activation prompted the Wnt3 synthesis in Paneth cells, thus increased the proliferation of ISCs via activation of Wnt3/ß-catenin signaling in OVX mice.

Efficacy and Safety of Aspirin for Prevention of Hepatocellular Carcinoma: An Updated Meta-analysis.

Background and Aims: Previous meta-analyses have shown that aspirin use may reduce the risk of hepatocellular carcinoma (HCC). However, the optimal dose, frequency, and duration of aspirin use or the safety and efficacy of aspirin in target populations for HCC prevention remain unclear. The study aim was to investigate the efficacy and safety of aspirin for prevention of HCC. Methods: Publications were retrieved by a comprehensive literature research of several databases. Based on a random-effects model, hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) were used to assess the pooled risk. The dose-response relationship between aspirin use and HCC risk was assessed with a restricted cubic spline model. Results: Twenty-two studies were included in the meta-analysis. Aspirin use was associated with a reduced risk of HCC (HR=0.64, 95% CI: 0.56-0.75). The effect was robust across sex and age; however, women and the non-elderly had the greatest benefit from aspirin use. The preventive effect was well reproduced in those with comorbidities. Daily use and long-term use of aspirin appeared to offer greater benefits. Aspirin 100 mg/d was associated with maximum reduction of HCC risk. Aspirin use did slightly increase the risk of bleeding (HR=1.14, 95% CI: 1.02-1.27). Conclusions: Our meta-analysis confirmed that use of aspirin significantly reduced the incident risk of HCC. Regular and long-term aspirin use offers a greater advantage. Aspirin use was associated with an increased risk of bleeding. We recommend 100 mg/d aspirin as a feasible dose for further research on primary prevention of HCC in a broad at-risk population.

Effects of Low Mental Energy from Long Periods of Work on Brain-Computer Interfaces.

Brain-computer interfaces (BCIs) provide novel hands-free interaction strategies. However, the performance of BCIs is affected by the user's mental energy to some extent. In this study, we aimed to analyze the combined effects of decreased mental energy and lack of sleep on BCI performance and how to reduce these effects. We defined the low-mental-energy (LME) condition as a combined condition of decreased mental energy and lack of sleep. We used a long period of work (>=18 h) to induce the LME condition, and then P300- and SSVEP-based BCI tasks were conducted in LME or normal conditions. Ten subjects were recruited in this study. Each subject participated in the LME- and normal-condition experiments within one week. For the P300-based BCI, we used two decoding algorithms: stepwise linear discriminant (SWLDA) and least square regression (LSR). For the SSVEP-based BCI, we used two decoding algorithms: canonical correlation analysis (CCA) and filter bank canonical correlation analysis (FBCCA). Accuracy and information transfer rate (ITR) were used as performance metrics. The experimental results showed that for the P300-based BCI, the average accuracy was reduced by approximately 35% (with a SWLDA classifier) and approximately 40% (with a LSR classifier); the average ITR was reduced by approximately 6 bits/min (with a SWLDA classifier) and approximately 7 bits/min (with an LSR classifier). For the SSVEP-based BCI, the average accuracy was reduced by approximately 40% (with a CCA classifier) and approximately 40% (with a FBCCA classifier); the average ITR was reduced by approximately 20 bits/min (with a CCA classifier) and approximately 19 bits/min (with a FBCCA classifier). Additionally, the amplitude and signal-to-noise ratio of the evoked electroencephalogram signals were lower in the LME condition, while the degree of fatigue and the task load of each subject were higher. Further experiments suggested that increasing stimulus size, flash duration, and flash number could improve BCI performance in LME conditions to some extent. Our experiments showed that the LME condition reduced BCI performance, the effects of LME on BCI did not rely on specific BCI types and specific decoding algorithms, and optimizing BCI parameters (e.g., stimulus size) can reduce these effects.

Advances and trends in microbial production of polyhydroxyalkanoates and their building blocks.

With the rapid development of synthetic biology, a variety of biopolymers can be obtained by recombinant microorganisms. Polyhydroxyalkanoates (PHA) is one of the most popular one with promising material properties, such as biodegradability and biocompatibility against the petrol-based plastics. This study reviews the recent studies focusing on the microbial synthesis of PHA, including chassis engineering, pathways engineering for various substrates utilization and PHA monomer synthesis, and PHA synthase modification. In particular, advances in metabolic engineering of dominant workhorses, for example Halomonas, Ralstonia eutropha, Escherichia coli and Pseudomonas, with outstanding PHA accumulation capability, were summarized and discussed, providing a full landscape of diverse PHA biosynthesis. Meanwhile, we also introduced the recent efforts focusing on structural analysis and mutagenesis of PHA synthase, which significantly determines the polymerization activity of varied monomer structures and PHA molecular weight. Besides, perspectives and solutions were thus proposed for achieving scale-up PHA of low cost with customized material property in the coming future.

Carbon 60 Dissolved in Grapeseed Oil Inhibits Dextran Sodium Sulfate-Induced Experimental Colitis.

Introduction: Carbon 60 (C60) and its derivatives have various biological applications. In our laboratory, we have demonstrated that C60 dissolved in grape seed oil (C60-Oil) has antioxidant and anti-inflammatory properties; however, the effectiveness of this formulation to treat diseases of the intestinal tract and specifically ulcerative colitis has not been studied. In this study, we intend to explore the effects of C60-Oil against experimental ulcerative colitis induced by Dextran Sulfate Sodium (DSS) in rats and a human colorectal cell line, HT-29. Methods: The rats were randomly distributed into three groups: a negative control group with no induced damage and two other groups were treated with DSS to induce UC for seven days: one as untreated control and the other group treated with C60-Oil 3 mg/kg/day. We quantified the clinical manifestations of the disease, body weight, colon weight, microscopic damage score, and colonic content of IL-6, TNF-alpha, IL-1B, and IL-10. As part of the cell studies, HT-29 cells were pretreated with C60-Oil at different concentrations (0.1, 1, 5, 10, 50, 30 µg/mL) and then stimulated with DSS (10 µg/mL). We measured the levels of IL-8 and NO secreted in the medium and the intracellular levels of ROS. Results: Oral treatment with C60-Oil significantly prevented the change in body weight, reduced most of the clinical signs of the disease, colon weight, microscopic damage score, and considerably improved the profile of cytokines analyzed. The pretreatment of HT-29 cells also protected the cells from the action of DSS as it reduced the levels of IL-8, NO, and ROS. Conclusion: According to our results, we can suggest C60-Oil, as a formulation with pharmacological potential for treating ulcerative colitis.