miR-2940-1 is involved in the circadian regulation of oviposition in Aedes albopictus.

The vast majority of all global species have circadian rhythm cycles that allow them to adapt to natural environments. These regular rhythms are regulated by core clock genes and recent studies have also implicated roles for microRNAs in this regulation. Oviposition is an important circadian behavior in the reproductive cycle of insect vectors of diseases, and little is known about the rhythm or its regulation in mosquitoes. Aedes albopictus is a diurnal mosquito that transmits arboviruses and is the major cause of outbreaks of dengue fever in China. We analyzed the oviposition rhythm patterns of A. albopictus under different light/dark conditions and show that the mosquitoes have an oviposition peak between zeitgeber time 9 (ZT 9) and ZT 12. Furthermore, the antagomir-mediated knockdown of expression of the microRNA miR-2940-1 affected the oviposition rhythm of A. albopictus. These data support the conclusion that miR-2940-1 is involved in the regulation of oviposition rhythm in A. albopictus and provide a foundation for using oviposition rhythms as a new target for vector mosquito control.

Detection of dynamic changes of electrodermal activity to predict the classroom performance of college students.

It is emphasized in the Self-regulated learning (SRL) framework that self-monitoring of learning state is vital for students to keep effective in studying. However, it's still challenging to get an accurate and timely understanding of their learning states during classes. In this study, we propose to use electrodermal activity (EDA) signals which are deemed to be associated with physiological arousal state to predict the college student's classroom performance. Twenty college students were recruited to attend eight lectures in the classroom, during which their EDA signals were recorded simultaneously. For each lecture, the students should complete pre- and after-class tests, and a self-reported scale (SRS) on their learning experience. EDA indices were extracted from both time and frequency domains, and they were furtherly mapped to the student's learning efficiency. As a result, the indices relevant to the dynamic changes of EDA had significant positive correlations with the learning efficiency. Furthermore, compared with only using SRS, a combination with EDA indices had significantly higher accuracy in predicting the learning efficiency. In conclusion, our findings demonstrate that the EDA dynamics are sensitive to the changes in learning efficiency, suggesting a promising approach to predicting the classroom performance of college students.

MetaBCI: An open-source platform for brain-computer interfaces.

BACKGROUND: Recently, brain-computer interfaces (BCIs) have attracted worldwide attention for their great potential in clinical and real-life applications. To implement a complete BCI system, one must set up several links to translate the brain intent into computer commands. However, there is not an open-source software platform that can cover all links of the BCI chain. METHOD: This study developed a one-stop open-source BCI software, namely MetaBCI, to facilitate the construction of a BCI system. MetaBCI is written in Python, and has the functions of stimulus presentation (Brainstim), data loading and processing (Brainda), and online information flow (Brainflow). This paper introduces the detailed information of MetaBCI and presents four typical application cases. RESULTS: The results showed that MetaBCI was an extensible and feature-rich software platform for BCI research and application, which could effectively encode, decode, and feedback brain activities. CONCLUSIONS: MetaBCI can greatly lower the BCI's technical threshold for BCI beginners and can save time and cost to build up a practical BCI system. The source code is available at https://github.com/TBC-TJU/MetaBCI, expecting new contributions from the BCI community.

Almost free of calibration for SSVEP-based brain-computer interfaces.

Objective. Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) is a promising technology that can achieve high information transfer rate (ITR) with supervised algorithms such as ensemble task-related component analysis (eTRCA) and task-discriminant component analysis (TDCA). However, training individual models requires a tedious and time-consuming calibration process, which hinders the real-life use of SSVEP-BCIs. A recent data augmentation method, called source aliasing matrix estimation (SAME), can generate new EEG samples from a few calibration trials. But SAME does not exploit the information across stimuli as well as only reduces the number of calibration trials per command, so it still has some limitations.Approach. This study proposes an extended version of SAME, called multi-stimulus SAME (msSAME), which exploits the similarity of the aliasing matrix across frequencies to enhance the performance of SSVEP-BCI with insufficient calibration trials. We also propose a semi-supervised approach based on msSAME that can further reduce the number of SSVEP frequencies needed for calibration. We evaluate our method on two public datasets, Benchmark and BETA, and an online experiment.Main results. The results show that msSAME outperforms SAME for both eTRCA and TDCA on the public datasets. Moreover, the semi-supervised msSAME-based method achieves comparable performance to the fully calibrated methods and outperforms the conventional free-calibrated methods. Remarkably, our method only needs 24 s to calibrate 40 targets in the online experiment and achieves an average ITR of 213.8 bits min-1with a peak of 242.6 bits min-1.Significance. This study significantly reduces the calibration effort for individual SSVEP-BCIs, which is beneficial for developing practical plug-and-play SSVEP-BCIs.

[Optimal processing technology of Zhangbang vinegar-processed Olibanum with multi-indicator-response surface methodology and anticoagulant effect evaluation].

This study first optimized the processing technology for Zhangbang vinegar-processed Olibanum and investigated its in vitro anticoagulant activity. A multi-index-response surface methodology was used, with yield, powder yield, and the relative percentage of the content of six non-volatile components [11-keto-boswellic acid(KBA), 3-acetyl-11-keto-boswellic acid(AKBA), ß-elemonic acid, α-boswellic acid(α-BA), ß-boswellic acid(ß-BA), and α-acetyl-boswellic acid(α-BA)] and three volatile components(octyl acetate, incensole, and incensole acetate) as evaluation indicators. Analytical hierarchy process(AHP) combined with coefficient of variation method was used to calculate the weight of each indicator and calculate the comprehensive score(OD). Furthermore, response surface methodology was used to investigate the effects of frying temperature(A), burning time(B), rice vinegar dosage(C), and steaming time(D) on the processing technology of vinegar-processed Olibanum. Vinegar-steamed Olibanum was prepared according to the optimal processing technology for in vitro anticoagulant experiments. The results showed that the weights of octyl acetate, incensole, incensole acetate, KBA, AKBA, ß-elemonic acid, α-BA, ß-BA, α-ABA, yield, and powder yield were 0.358 2, 0.104 5, 0.146 4, 0.032 9, 0.123 7, 0.044 4, 0.022 1, 0.042 2, 0.110 1, 0.012 2, and 0.0032, respectively. The optimal processing technology for Zhangbang vinegar-processed Olibanum was as follows. Olibanum(50 g) with a particle size of 1-5 mm was continuously stir-fried at a low heat of 150-180 ℃ until in a gel-like state, ignited for burning for 15 s, sprayed with 7.5 g of rice vinegar(15%), and steamed for 3 min without fire. Subsequently, the cover was removed, and the product was continuously stir-fried at 150-180 ℃ until in a soft lump shape, removed, cooled, and crushed. The results of the in vitro anticoagulant experiments showed that compared with the blank group, both Olibanum and vinegar-processed Olibanum significantly prolonged the activated partial thromboplastin time(APTT), thrombin time(TT), and prothrombin time(PT) of rat platelet-poor plasma(PPP), and the effect of vinegar-processed Olibanum was significantly better than that of Olibanum(P<0.05). The optimized processing technology for Zhangbang vinegar-processed Olibanum is stable, feasible, and beneficial for the further development and utilization of Olibanum slices. At the same time, using the content of volatile and non-volatile components, yield, and powder yield as indicators, and verifying through pharmacological experiments, the obtained results are more reasonable and credible, and have positive guiding significance for the clinical application of characteristic processed Olibanum products.

Integrative evidence construction for resveratrol treatment of nonalcoholic fatty liver disease: preclinical and clinical meta-analyses.

Background: Resveratrol, a polyphenol found in various plants, is known for its diverse bioactivities and has been explored in relation to nonalcoholic fatty liver disease (NAFLD). However, no high-quality evidence exists regarding its efficacy. Objective: a meta-analysis was conducted to evaluate the potential efficacy of resveratrol in treating nonalcoholic fatty liver disease by analyzing both preclinical studies and clinical trials. Method: PubMed, Embase and Web of Science were searched for the included literature with the criteria for screening. Quantitative synthesis and meta-analyses were performed by STATA 16.0. Results: Twenty-seven studies were included, and the results indicated that resveratrol effectively improved liver function, reduced fatty liver indicators, and affected other indices in preclinical studies. The effective dosage ranged from 50 mg/kg-200 mg/kg, administered over a period of 4-8 weeks. While there were inconsistencies between clinical trials and preclinical research, both study types revealed that resveratrol significantly reduced tumor necrosis factor-α levels, further supporting its protective effect against nonalcoholic fatty liver disease. Additionally, resveratrol alleviated nonalcoholic fatty liver disease primarily via AMPK/Sirt1 and anti-inflammatory signaling pathways. Conclusion: Current meta-analysis could not consistently verify the efficacy of resveratrol in treating nonalcoholic fatty liver disease, but demonstrated the liver-protective effects on nonalcoholic fatty liver disease. The large-sample scale and single region RCTs were further needed to investigate the efficacy.

A data expansion technique based on training and testing sample to boost the detection of SSVEPs for brain-computer interfaces.

Objective.Currently, steady-state visual evoked potentials (SSVEPs)-based brain-computer interfaces (BCIs) have achieved the highest interaction accuracy and speed among all BCI paradigms. However, its decoding efficacy depends deeply on the number of training samples, and the system performance would have a dramatic drop when the training dataset decreased to a small size. To date, no study has been reported to incorporate the unsupervised learning information from testing trails into the construction of supervised classification model, which is a potential way to mitigate the overfitting effect of limited samples.Approach.This study proposed a novel method for SSVEPs detection, i.e. cyclic shift trials (CSTs), which could combine unsupervised learning information from test trials and supervised learning information from train trials. Furthermore, since SSVEPs are time-locked and phase-locked to the onset of specific flashes, CST could also expand training samples on the basis of its regularity and periodicity. In order to verify the effectiveness of CST, we designed an online SSVEP-BCI system, and tested this system combined CST with two common classification algorithms, i.e. extended canonical correlation analysis and ensemble task-related component analysis.Main results.CST could significantly enhance the signal to noise ratios of SSVEPs and improve the performance of systems especially for the condition of few training samples and short stimulus time. The online information transfer rate could reach up to 236.19 bits min-1using 36 s calibration time of only one training sample for each category.Significance.The proposed CST method can take full advantages of supervised learning information from training samples and unsupervised learning information of testing samples. Furthermore, it is a data expansion technique, which can enhance the SSVEP characteristics and reduce dependence on sample size. Above all, CST is a promising method to improve the performance of SSVEP-based BCI without any additional experimental burden.

[Recognition of high-frequency steady-state visual evoked potential for brain-computer interface].

Coding with high-frequency stimuli could alleviate the visual fatigue of users generated by the brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP). It would improve the comfort and safety of the system and has promising applications. However, most of the current advanced SSVEP decoding algorithms were compared and verified on low-frequency SSVEP datasets, and their recognition performance on high-frequency SSVEPs was still unknown. To address the aforementioned issue, electroencephalogram (EEG) data from 20 subjects were collected utilizing a high-frequency SSVEP paradigm. Then, the state-of-the-art SSVEP algorithms were compared, including 2 canonical correlation analysis algorithms, 3 task-related component analysis algorithms, and 1 task discriminant component analysis algorithm. The results indicated that they all could effectively decode high-frequency SSVEPs. Besides, there were differences in the classification performance and algorithms' speed under different conditions. This paper provides a basis for the selection of algorithms for high-frequency SSVEP-BCI, demonstrating its potential utility in developing user-friendly BCI.

Accurate Complementarity Learning for Graph-Based Multiview Clustering.

In real scenarios, graph-based multiview clustering has clearly shown popularity owing to the high efficiency in fusing the information from multiple views. Practically, the multiview graphs offer both consistent and inconsistent cues as they usually come from heterogeneous sources. Previous methods illustrated the importance of leveraging the multiview consistency and inconsistency for accurate modeling. However, when fusing the graphs, the inconsistent parts are generally ignored and hence the valued view-specific attributes are lost. To solve this problem, we propose an accurate complementarity learning (ACL) model for graph-based multiview clustering. ACL clearly distinguishes the consistent, complementary, and noise and corruption terms from the initial multiview graphs. In contrast to existing models that overlooked the complementary information, we argue that the view-specific characteristics extracted from the complementary terms are beneficial for affinity learning. In addition, ACL exploits only the positive parts of the complementary information for preserving the evidence on the positive sample relationship, and ignores the negative cues to avoid the vanishing of effective affinity strengths. This way, the learned affinity matrix is able to properly balance the consistent and complementary information. To solve the ACL model, we introduce an efficient alternating optimization algorithm with a varying penalty parameter. Experiments on synthetic and real-world databases clearly demonstrated the superiority of ACL.

[Research on phase modulation to enhance the feature of high-frequency steady-state asymmetric visual evoked potentials].

High-frequency steady-state asymmetric visual evoked potential (SSaVEP) provides a new paradigm for designing comfortable and practical brain-computer interface (BCI) systems. However, due to the weak amplitude and strong noise of high-frequency signals, it is of great significance to study how to enhance their signal features. In this study, a 30 Hz high-frequency visual stimulus was used, and the peripheral visual field was equally divided into eight annular sectors. Eight kinds of annular sector pairs were selected based on the mapping relationship of visual space onto the primary visual cortex (V1), and three phases (in-phase[0º, 0º], anti-phase [0º, 180º], and anti-phase [180º, 0º]) were designed for each annular sector pair to explore response intensity and signal-to-noise ratio under phase modulation. A total of 8 healthy subjects were recruited in the experiment. The results showed that three annular sector pairs exhibited significant differences in SSaVEP features under phase modulation at 30 Hz high-frequency stimulation. And the spatial feature analysis showed that the two types of features of the annular sector pair in the lower visual field were significantly higher than those in the upper visual field. This study further used the filter bank and ensemble task-related component analysis to calculate the classification accuracy of annular sector pairs under three-phase modulations, and the average accuracy was up to 91.5%, which proved that the phase-modulated SSaVEP features could be used to encode high- frequency SSaVEP. In summary, the results of this study provide new ideas for enhancing the features of high-frequency SSaVEP signals and expanding the instruction set of the traditional steady state visual evoked potential paradigm.

A novel visual brain-computer interfaces paradigm based on evoked related potentials evoked by weak and small number of stimuli.

Introduction: Traditional visual Brain-Computer Interfaces (v-BCIs) usually use large-size stimuli to attract more attention from users and then elicit more distinct and robust EEG responses, which would cause visual fatigue and limit the length of use of the system. On the contrary, small-size stimuli always need multiple and repeated stimulus to code more instructions and increase separability among each code. These common v-BCIs paradigms can cause problems such as redundant coding, long calibration time, and visual fatigue. Methods: To address these problems, this study presented a novel v-BCI paradigm using weak and small number of stimuli, and realized a nine-instruction v-BCI system that controlled by only three tiny stimuli. Each of these stimuli were located between instructions, occupied area with eccentricities subtended 0.4°, and flashed in the row-column paradigm. The weak stimuli around each instruction would evoke specific evoked related potentials (ERPs), and a template-matching method based on discriminative spatial pattern (DSP) was employed to recognize these ERPs containing the intention of users. Nine subjects participated in the offline and online experiments using this novel paradigm. Results: The average accuracy of the offline experiment was 93.46% and the online average information transfer rate (ITR) was 120.95 bits/min. Notably, the highest online ITR achieved 177.5 bits/min. Discussion: These results demonstrate the feasibility of using a weak and small number of stimuli to implement a friendly v-BCI. Furthermore, the proposed novel paradigm achieved higher ITR than traditional ones using ERPs as the controlled signal, which showed its superior performance and may have great potential of being widely used in various fields.

Modulation of rhythmic visual stimulation on left-right attentional asymmetry.

The rhythmic visual stimulation (RVS)-induced oscillatory brain responses, namely steady-state visual evoked potentials (SSVEPs), have been widely used as a biomarker in studies of neural processing based on the assumption that they would not affect cognition. However, recent studies have suggested that the generation of SSVEPs might be attributed to neural entrainment and thus could impact brain functions. But their neural and behavioral effects are yet to be explored. No study has reported the SSVEP influence on functional cerebral asymmetry (FCA). We propose a novel lateralized visual discrimination paradigm to test the SSVEP effects on visuospatial selective attention by FCA analyses. Thirty-eight participants covertly shifted their attention to a target triangle appearing in either the lower-left or -right visual field (LVF or RVF), and judged its orientation. Meanwhile, participants were exposed to a series of task-independent RVSs at different frequencies, including 0 (no RVS), 10, 15, and 40-Hz. As a result, it showed that target discrimination accuracy and reaction time (RT) varied significantly across RVS frequency. Furthermore, attentional asymmetries differed for the 40-Hz condition relative to the 10-Hz condition as indexed by enhanced RT bias to the right visual field, and larger Pd EEG component for attentional suppression. Our results demonstrated that RVSs had frequency-specific effects on left-right attentional asymmetries in both behavior and neural activities. These findings provided new insights into the functional role of SSVEP on FCAs.

Data Augmentation of SSVEPs Using Source Aliasing Matrix Estimation for Brain-Computer Interfaces.

OBJECTIVE: Currently, ensemble task-related component analysis (eTRCA) and task discriminative component analysis (TDCA) are the state-of-the-art algorithms for steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). However, training the BCIs requires multiple calibration trials. With insufficient calibration data, the accuracy of the BCI will degrade, or even become invalid with only one calibration trial. However, collecting a large amount of electroencephalography (EEG) data for calibration is a time-consuming and laborious process, which hinders the practical use of eTRCA and TDCA. METHODS: This study proposed a novel method, namely Source Aliasing Matrix Estimation (SAME), to augment the calibration data for SSVEP-BCIs. SAME could generate artificial EEG trials with the featured SSVEPs. Its effectiveness was evaluated using two public datasets (i.e., Benchmark, BETA). RESULTS: When combined with SAME, both eTRCA and TDCA had significantly improved performance with a limited number of calibration data. Specifically, SAME increased the average accuracy of eTRCA and TDCA by about 12% and 3%, respectively, with as few as two calibration trials. Notably, SAME enabled eTRCA and TDCA to work well with a single calibration trial, achieving an average accuracy >90% for the Benchmark dataset and >70% for the BETA dataset with 1-second EEG. CONCLUSION: SAME is an effective method for SSVEP-BCIs to augment the calibration data, thereby significantly enhancing the performance of eTRCA and TDCA. SIGNIFICANCE: We propose a new data-augmentation method that is compatible with the state-of-the-art algorithms of SSVEP-based BCIs. It can significantly reduce the efforts required to calibrate SSVEP-BCIs, which is promising for the development of practical BCIs.

[Advances in brain-computer interface based on high-frequency steady-state visual evoked potential].

Steady-state visual evoked potential (SSVEP) has been widely used in the research of brain-computer interface (BCI) system in recent years. The advantages of SSVEP-BCI system include high classification accuracy, fast information transform rate and strong anti-interference ability. Most of the traditional researches induce SSVEP responses in low and middle frequency bands as control signals. However, SSVEP in this frequency band may cause visual fatigue and even induce epilepsy in subjects. In contrast, high-frequency SSVEP-BCI provides a more comfortable and natural interaction despite its lower amplitude and weaker response. Therefore, it has been widely concerned by researchers in recent years. This paper summarized and analyzed the related research of high-frequency SSVEP-BCI in the past ten years from the aspects of paradigm and algorithm. Finally, the application prospect and development direction of high-frequency SSVEP were discussed and prospected.

A high-speed hybrid brain-computer interface with more than 200 targets.

Objective. Brain-computer interfaces (BCIs) have recently made significant strides in expanding their instruction set, which has attracted wide attention from researchers. The number of targets and commands is a key indicator of how well BCIs can decode the brain's intentions. No studies have reported a BCI system with over 200 targets.Approach. This study developed the first high-speed BCI system with up to 216 targets that were encoded by a combination of electroencephalography features, including P300, motion visual evoked potential (mVEP), and steady-state visual evoked potential (SSVEP). Specifically, the hybrid BCI paradigm used the time-frequency division multiple access strategy to elaborately tag targets with P300 and mVEP of different time windows, along with SSVEP of different frequencies. The hybrid features were then decoded by task-discriminant component analysis and linear discriminant analysis. Ten subjects participated in the offline and online cued-guided spelling experiments. Other ten subjects took part in online free-spelling experiments.Main results.The offline results showed that the mVEP and P300 components were prominent in the central, parietal, and occipital regions, while the most distinct SSVEP feature was in the occipital region. The online cued-guided spelling and free-spelling results showed that the proposed BCI system achieved an average accuracy of 85.37% ± 7.49% and 86.00% ± 5.98% for the 216-target classification, resulting in an average information transfer rate (ITR) of 302.83 ± 39.20 bits min-1and 204.47 ± 37.56 bits min-1, respectively. Notably, the peak ITR could reach up to 367.83 bits min-1.Significance.This study developed the first high-speed BCI system with more than 200 targets, which holds promise for extending BCI's application scenarios.

Targeting cancer stem cells and signalling pathways through phytochemicals: A promising approach against colorectal cancer.

BACKGROUND: Cancer stem cells (CSCs) are strongly associated with high tumourigenicity, chemotherapy or radiotherapy resistance, and metastasis and recurrence, particularly in colorectal cancer (CRC). Therefore, targeting CSCs may be a promising approach. Recently, discovery and research on phytochemicals that effectively target colorectal CSCs have been gaining popularity because of their broad safety profile and multi-target and multi-pathway modes of action. PURPOSE: This review aimed to elucidate and summarise the effects and mechanisms of phytochemicals with potential anti-CSC agents that could contribute to the better management of CRC. METHODS: We reviewed PubMed, EMBASE, Web of Science, Ovid, ScienceDirect and China National Knowledge Infrastructure databases from the original publication date to March 2022 to review the mechanisms by which phytochemicals inhibit CRC progression by targeting CSCs and their key signalling pathways. Phytochemicals were classified and summarised based on the mechanisms of action. RESULTS: We observed that phytochemicals could affect the biological properties of colorectal CSCs. Phytochemicals significantly inhibit self-renewal, migration, invasion, colony formation, and chemoresistance and induce apoptosis and differentiation of CSCs by regulating the Wnt/ß-catenin pathway (e.g., diallyl trisulfide and genistein), the phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin pathway (e.g., caffeic acid and piperlongumine), the neurogenic locus notch homolog protein pathway (e.g., honokiol, quercetin, and α-mangostin), the Janus kinase-signal transducer and activator of transcription pathway (e.g., curcumin, morin, and ursolic acid), and other key signalling pathways. It is worth noting that several phytochemicals, such as resveratrol, silibinin, evodiamine, and thymoquinone, highlight multi-target and multi-pathway effects in restraining the malignant biological behaviour of CSCs. CONCLUSIONS: This review demonstrates the potential of targeted therapies for colorectal CSCs using phytochemicals. Phytochemicals could serve as novel therapeutic agents for CRC and aid in drug development.

Phytochemicals and mitochondria: Therapeutic allies against gastric cancer.

BACKGROUND: Mitochondria are the energy factories of cells with the ability to modulate the cell cycle, cellular differentiation, signal transduction, growth, and apoptosis. Existing drugs targeting mitochondria in cancer treatment have disadvantages of drug resistance and side effects. Phytochemicals, which are widely found in plants, are bioactive compounds that could facilitate the development of new drugs for gastric cancer. Studies have shown that some phytochemicals can suppress the development of gastric cancer. METHODS: We searched for data from PubMed, China National Knowledge Infrastructure, Web of Science, and Embase databases from initial establishment to December 2021 to review the mechanism by which phytochemicals suppress gastric cancer cell growth by modulating mitochondrial function. Phytochemicals were classified and summarized by their mechanisms of action. RESULTS: Phytochemicals can interfere with mitochondria through several mechanisms to reach the goal of promoting apoptosis in gastric cancer cells. Some phytochemicals, e.g., daidzein and tetrandrine promoted cytochrome c spillover into the cytoplasm by modulating the members of the B-cell lymphoma-2 protein family and induced apoptotic body activity by activating the caspase protein family. Phytochemicals (e.g., celastrol and shikonin) could promote the accumulation of reactive oxygen species and reduce the mitochondrial membrane potential. Several phytochemicals (e.g., berberine and oleanolic acid) activated mitochondrial apoptotic submission via the phosphatidylinositol-3-kinase/Akt signaling pathway, thereby triggering apoptosis in gastric cancer cells. Several well-known phytochemicals that target mitochondria, including berberine, ginsenoside, and baicalein, showed the advantages of multiple targets, high efficacy, and fewer side effects. CONCLUSIONS: Phytochemicals could target the mitochondria in the treatment of gastric cancer, providing potential directions and evidence for clinical translation. Drug discovery focused on phytochemicals has great potential to break barriers in cancer treatment.

[Analysis of traditional Chinese medicine syndromes in patients with coronavirus disease 2019 in plateau areas].

OBJECTIVE: To analyze the distribution characteristics of traditional Chinese medicine (TCM) syndromes in patients with coronavirus disease 2019 (COVID-19) in plateau areas, and to provide theoretical basis for further clinical treatment of patients with COVID-19. METHODS: From August 9 to August 24, 2022, patients with COVID-19 admitted to the Third People's Hospital of Tibet Autonomous Region (designated hospital for COVID-19) were included, and their baseline characteristics (age, gender, source), clinical classification and distribution of TCM syndrome types were collected and analyzed. Data analysis was performed using SPSS 26.0 statistical software. RESULTS: A total of 161 COVID-19 patients were enrolled with ethnic distribution: 124 (77.02%) Tibetans, 35 (21.74%) Han, and 2 (1.24%) Hui, 68 males and 93 females. The male-to-female ratio was 0.73:1. Aged 1 to 94 years, the average age was (39.06±23.64) years old, of which 4 patients were under 1 year old (excluded because the information was missing). A total of 157 patients were enrolled, and 124 patients (78.9%) were under 60 years old, including 120 cases of common type, 4 cases of severe type, 0 cases of critical type, 7 cases over 80 years old, 1 case over 90 years old, and 32 cases under 18 years old. The clinical manifestations of the patient are mainly cough, expectoration, fever, aversion to cold, dry throat, headache, fatigue, running nose, dry mouth, bitter mouth, etc. Most of the tongue is pale, red, and white greasy moss or thin white coating. In TCM, the most common syndrome was cold-dampness blocking lung syndrome (99 cases, 63.06%), followed by cold-dampness stagnant lung syndrome (22 cases, 14.01%), damp-heat accumulating lung syndrome (22 cases, 14.01%), and humidity stagnant lung syndrome (11 cases, 7.01%). Syndromes of epidemic (2 cases, 1.27%), epidemic toxins blocking the lung pattern (1 cases, 0.64%), toxins with dryness intense heat in both qi and ying phases pattern (0 cases) accounted for less than 2%, and the distribution of various syndrome types in COVID-19 patients was uneven (χ 2 = 0.48, P < 0.05). CONCLUSIONS: The most common TCM syndromes of COVID-19 patients in Lhasa are cold-dampness blocking lung syndrome, followed by cold-dampness stagnant lung syndrome, damp-heat accumulating lung syndrome, and humidity stagnant lung syndrome.

Clock genes regulate mating activity rhythms in the vector mosquitoes, Aedes albopictus and Culex quinquefasciatus.

BACKGROUND: Endogenous circadian rhythms result from genetically-encoded molecular clocks, whose components and downstream output factors cooperate to generate cyclic changes in activity. Mating is an important activity of mosquitoes, however, the key aspects of mating rhythm patterns and their regulatory mechanisms in two vector mosquito species, Aedes albopictus and Culex quinquefasciatus, remain unclear. METHODOLOGY/PRINCIPAL FINDINGS: We determined and compared the diel mating activity rhythms of these two mosquito species and discovered that Ae. albopictus had mating peaks in the light/dark transition periods (ZT0-3 and ZT9-12), while Cx. quinquefasciatus only had a mating peak at ZT12-15. Knockouts of the clock (clk) orthologous genes (Aalclk and Cxqclk) resulted in phase delay or phase reversal of the mating peaks in Ae. albopictus and Cx. quinquefasciatus, respectively. In addition, the temporal expression pattern of the desaturase orthologous genes, desat1, in both mosquito species was also different in respective wild-type strains and showed phase changes similar to the mating rhythms in clk mutant strains. Inhibition of desat1 expression resulted in decreased mating activity in male mosquitoes of both species but not females. In addition, desat1 regulated cuticular hydrocarbons' synthesis in both species. Silencing desat1 in male Ae. albopictus resulted in decreases of nonadecane and tricosane, which promoted mating, with concomitant increases of heptacosane, which inhibited mating. Silencing desat1 in male Cx. quinquefasciatus also resulted in decreases of tricosane, which promoted mating. CONCLUSIONS/SIGNIFICANCE: These results suggest that Aalclk and Cxqclk have significant roles in the mating activity rhythms in both Ae. albopictus and Cx. quinquefasciatus by regulating the temporal expression of the desat1 gene under LD cycles, which affects sex pheromone synthesis and mating. This work provides insights into the molecular regulatory mechanism of distinct mating rhythm of Ae. albopictus and Cx. quinquefasciatus and may provide a basis for the control of these two important vector mosquitoes.

[Mechanism of Euodiae Fructus stir-fried with water decoction of Coptidis Rhizoma in treatment of chronic colitis based on UPLC-Q-TOF-MS, network pharmacology and experimental verification].

To elucidate the mechanism of Euodiae Fructus stir-fried with water decoction of Coptidis Rhizoma in the treatment of chronic colitis, this study employed ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS), network pharmacology, and experimental verification to predict the involved targets and signaling pathways. The chronic colitis mouse model was constructed to verify the core targets. A total of 48 compounds in the herbal medicine were identified by UPLC-Q-TOF-MS. SwissTargetPrediction was used to screen the potential active components and drug targets. GeneCards, OMIM, PharmGKB, and TDD were used to search for the disease targets. A total of 31 active ingredients, 453 targets of the herbal medicine, and 3 960 targets of chronic colitis were obtained. The common targets shared by the herbal medicine and chronic colitis were introduced into STRING to construct the protein-protein interaction(PPI) network, and CytoNCA plug-in was used to screen the key targets. A total of 90 key targets were obtained, and the key active components included isorhamnetin, quercetin, limonin, and oxyberberine. GO annotation and KEGG pathway enrichment for the key targets were carried out via DAVID. The targets were mainly involved in the positive regulation of protein phosphorylation, positive regulation of nitric oxide biosynthetic process, and negative regulation of apoptotic process. The medicine may treat chronic colitis through PI3 K-Akt, VEGF, HIF-1, and TNF signaling pathways. A mouse model of chronic colitis was established and then treated with Euodiae Fructus stir-fried with the water decoction of Coptidis Rhizoma. The experimental results demonstrated that the medicine can alleviate the pathological damage of colon, significantly reduce the levels of IL-1ß, IL-6, and TNF-α, inhibit the activation of PI3 K/Akt pathway, and down-regulate the expression of VEGFA in the treatment of chronic colitis.