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Abstract Purpose To summarize and analyze the safety and efficacy of a Y-shape Sigma stent loaded with I125 in patients with inoperable malignant main airway obstruction. Methods This study was approved by the Institutional Ethics Committee, and a written informed consent was obtained from each participant. A Y-shape Sigma stent loaded with I125 was placed under vision from rigid bronchoscopy. The primary endpoint was alleviation of symptoms and improvement of Karnofsky Performance Status (KPS) score, and the secondary endpoint was complications and technical success. Results From November 2018 through June 2023, total 33 patients with malignant airway obstruction were palliatively treated by installing Y-shape Sigma stents loaded with I125. The airway lumen was immediately restored and the average airway opening significantly increased to 70 ± 9.4% after the procedure from baseline 30.2 ± 10.5% (p

ObjectiveObservational studies have suggested a potential association between constipation and several cancers. However, the causal relationship between constipation and cancer remains unclear. The purpose of this study is to explore the potential causal relationship between constipation and pan-cancer using Mendelian Randomization (MR) methods.MethodsWe performed a bidirectional MR analysis using publicly available summary data from Genome-Wide Association Studies (GWAS) statistics. The Inverse Variance Weighted (IVW) method was used as the main analysis method. We also used four MR methods: MR-Egger, Weighted Median, MR-PRESSO and MR.RAPS. Simultaneously, MR-Egger regression, Cochran’s Q test and MR-PRESSO Global test were used to estimate the pleiotropy and heterogeneity of SNPs. In addition, we performed “leave-one-out” analyses” to avoid bias caused by horizontal pleiotropy of individual SNPs.ResultsMR analysis revealed a potential causal association between constipation and the risk of colorectal cancer (CRC) [IVW (OR= 1.0021 (1.0003, 1.0039), P= 0.0234)], lung cancer (LC) [IVW (OR=1.0955 (1.0134, 1.1843), P=0.0218)], Oral cavity and pharyngeal cancer (OPC) [IVW (OR=1.4068 (1.0070, 1.9652), P=0.0454)], and Pancreatic cancer (PC) [IVW (OR=1.5580 (1.0659, 2.2773), P=0.0221)]. In addition, we explored causal relationships between constipation and 12 other types of cancers, including gastric cancer, esophageal cancer, skin melanoma and so on. All five methods yielded no evidence of a causal association between constipation and the risk of these cancer types. In the reverse MR analysis, there was no evidence of a causal association between cancer and the risk of constipation for all five methods.ConclusionOur bidirectional MR study suggests a potential relationship between constipation and an increased risk of CRC, LC OPC and PC. The underlying mechanisms behind these associations will need to be explored in future experimental studies.

ObjectiveThe aim of our study was to explore the relationship between changes in neural oscillatory power in the EEG, the severity of depressive-anxiety symptoms, and the risk of suicide in MDD.Methods350 MDD patients’ demographic and clinical data were collected, and their depressive and anxious symptoms were evaluated using HDRS-17 and HAMA-14, along with a suicide risk assessment using the Nurses’ Global Assessment of Suicide Risk (NGASR). EEG data were captured, processed, and analyzed to study brain activity patterns related to MDD. The participants were divided based on suicide risk levels, and statistical analyses, including chi-square, t-tests, Pearson’s correlations were used to explore the associations between brain activity, symptom severity, and suicide risk. Closely related variables were identified and ultimately the optimal model was screened using stepwise regression analysis with a forward strategy, and mediation effects were further used to determine the possible interactions between the variables in the regression model.ResultsThe regression model showed a significant effect of HDRS-17 and alpha power of Medial Occipital Cortex (MOC) on suicide risk, with elevated HDRS-17 increasing suicide risk and elevated alpha power decreasing suicide risk. Mediation effect analyses showed that MOC alpha power partially mediated the effect of depression level on suicide risk, and that an increase in depression severity may lead to a decrease in MOC alpha power, while a decrease in MOC alpha power may lead to an increase in suicide risk.ConclusionThe severity of depression directly increases suicide risk, whereas higher alpha power in the MOC serves as a protective factor, reducing this risk. Notably, MOC alpha power not only directly impacts suicide risk but also mediates the effects of both depression severity and anxiety levels on this risk.LimitationsThe relatively small sample size of this study may limit the representativeness of the overall MDD patient population and the detailed analysis of different subgroups. This study did not delve into the relationship between the severity of cognitive symptoms in MDD patients and suicide risk.

BackgroundMajor depressive disorder (MDD) is the leading cause of disability among all mental illnesses with increasing prevalence. The diagnosis of MDD is susceptible to interference by several factors, which has led to a trend of exploring objective biomarkers. Electroencephalography (EEG) is a non-invasive procedure that is being gradually applied to detect and diagnose MDD through some features such as functional connectivity (FC).MethodsIn this research, we analyzed the resting-state EEG of patients with MDD and healthy controls (HCs) in both eyes-open (EO) and eyes-closed (EC) conditions. The phase locking value (PLV) method was utilized to explore the connection and synchronization of neuronal activities spatiotemporally between different brain regions. We compared the PLV between participants with MDD and HCs in five frequency bands (theta, 4–8 Hz; alpha, 8–12 Hz; beta1, 12–16 Hz; beta2, 16–24 Hz; and beta3, 24–40 Hz) and further analyzed the correlation between the PLV of connections with significant differences and the severity of depression (via the scores of 17-item Hamilton Depression Rating Scale, HDRS-17).ResultsDuring the EO period, lower PLVs were found in the right temporal-left midline occipital cortex (RT-LMOC; theta, alpha, beta1, and beta2) and posterior parietal-right temporal cortex (PP-RT; beta1 and beta2) in the MDD group compared with the HC group, while PLVs were higher in the MDD group in LT-LMOC (beta2). During the EC period, for the MDD group, lower theta and beta (beta1, beta2, and beta3) PLVs were found in PP-RT, as well as lower theta, alpha, and beta (beta1, beta2, and beta3) PLVs in RT-LMOC. Additionally, in the left midline frontal cortex-right temporal cortex (LMFC-RT) and posterior parietal cortex-right temporal cortex (PP-RMOC), higher PLVs were observed in beta2. There were no significant correlations between PLVs and HDRS-17 scores when connections with significantly different PLVs (all p > 0.05) were checked.ConclusionOur study confirmed the presence of differences in FC between patients with MDD and healthy individuals. Lower PLVs in the connection of the right temporal-left occipital cortex were mostly observed, whereas an increase in PLVs was observed in patients with MDD in the connections of the left temporal with occipital lobe (EO), the circuits of the frontal-temporal lobe, and the parietal-occipital lobe. The trends in FC involved in this study were not correlated with the level of depression.LimitationsThe study was limited due to the lack of further analysis of confounding factors and follow-up data. Future studies with large-sampled and long-term designs are needed to further explore the distinguishable features of EEG FC in individuals with MDD.

Abstract Background Recent state-of-the-art sequencing technologies enable the investigation of challenging regions in the human genome and expand the scope of variant benchmarking datasets. Herein, we sequence a Chinese Quartet, comprising two monozygotic twin daughters and their biological parents, using four short and long sequencing platforms (Illumina, BGI, PacBio, and Oxford Nanopore Technology). Results The long reads from the monozygotic twin daughters are phased into paternal and maternal haplotypes using the parent–child genetic map and for each haplotype. We also use long reads to generate haplotype-resolved whole-genome assemblies with completeness and continuity exceeding that of GRCh38. Using this Quartet, we comprehensively catalogue the human variant landscape, generating a dataset of 3,962,453 SNVs, 886,648 indels (

Abstract Micro-light-emitting diode displays are generating considerable interest as a promising technology for augmented-reality glasses. However, the fabrication of highly efficient and ultra-small (

BackgroundMajor Depressive Disorder (MDD) is a pervasive mental health issue with significant diagnostic challenges. Electroencephalography (EEG) offers a non-invasive window into the neural dynamics associated with MDD, yet the diagnostic efficacy is contingent upon the appropriate selection of EEG features and brain regions.MethodsIn this study, resting-state EEG signals from both eyes-closed and eyes-open conditions were analyzed. We examined band power across various brain regions, assessed the asymmetry of band power between the hemispheres, and integrated these features with clinical characteristics of MDD into a diagnostic regression model.ResultsRegression analysis found significant predictors of MDD to be beta2 (16–24 Hz) power in the Prefrontal Cortex (PFC) with eyes open (B = 20.092, p = 0.011), beta3 (24–40 Hz) power in the Medial Occipital Cortex (MOC) (B = −12.050, p

Rationale & Objective: Intradialytic hypotension (IDH) is associated with mortality in adults with kidney failure requiring hemodialysis (HD); however, large-scale pediatric studies are lacking. Moreover, there is no evidence-based consensus definition of IDH in pediatric literature. We aimed to examine the association of commonly used definitions of IDH with mortality in adolescents and young adults. Study Design: This was a retrospective observational cohort study. Setting & Participants: In total, 1,199 adolescents and young adults (N = 320, aged 10-18 years and N = 879, aged 19-21 years) who initiated HD in a large dialysis organization were included. Exposures: This study used different definitions of IDH. Outcome: The study outcome was 2-year all-cause mortality. Analytical Approach: Several definitions of IDH were selected a priori based on a literature review. Patients were classified as having IDH if it was present in at least 30% of HD treatments during the first 90 days after dialysis initiation. Cox proportional hazards regression was used to test whether IDH associated with 2-year all-cause mortality. Results: Over a 2-year follow-up period, 54 (4.5%) patients died. Dependent on its definition, IDH was present in 2.9%-61.1% of patients. After the multivariable adjustment for sociodemographic and clinical characteristics, we found no association of IDH with mortality. Results were consistent across subgroups stratified by age (aged 150 mm Hg). We also examined IDH as occurring in 50% of baseline treatments, and did not find a dose-response association with mortality (P > 0.05). Limitations: Owing to low event rates, our current sample size may have been too small to detect a difference in mortality. Conclusions: Our study found that IDH was not associated with mortality in adolescents and young adults. Plain-Language Summary: Intradialytic hypotension (IDH), or hypotension experienced during dialysis, is common among children and young adults with kidney failure requiring hemodialysis. We examined the association of commonly used definitions of IDH with death in adolescents and young adults with kidney failure receiving hemodialysis. Intradialytic hypotension was present in 2.9%-61.1% of patients, depending on the definition, and over a 2-year follow-up period, 4.5% of the patients died. We found no association of IDH with mortality.

Depression is a global disease that is harmful to people. Traditional identification methods based on various scales are not objective and accurate enough. Electroencephalogram (EEG) contains abundant physiological information, which makes it a new research direction to identify depression state. However, most EEG-based algorithms only extract the original EEG features and ignore the complex spatiotemporal information interactions, which will reduce performance. Thus, a more accurate and objective method for depression identification is urgently needed. In this work, we propose a novel depression identification model: W-GCN-GRU. In our proposed method, we censored six sensitive features based on Spearman’s rank correlation coefficient and assigned different weight coefficients to each sensitive feature by AUC for the weighted fusion of sensitive features. In particular, we use the GCN and GRU cascade networks based on weighted sensitive features as depression recognition models. For the GCN, we creatively took the brain function network based on the correlation coefficient matrix as the adjacency matrix input and the weighted fused sensitive features were used as the node feature matrix input. Our proposed model performed well on our self-collected dataset and the MODMA datasets with a accuracy of 94.72%, outperforming other methods. Our findings showed that feature dimensionality reduction, weighted fusion, and EEG spatial information all had great effects on depression recognition.

Abstract Background Breast cancer brain metastases (BCBM) are the most fatal, with limited survival in all breast cancer distant metastases. These patients are deemed to be incurable. Thus, survival time is their foremost concern. However, there is a lack of accurate prediction models in the clinic. What’s more, primary surgery for BCBM patients is still controversial. Methods The data used for analysis in this study was obtained from the SEER database (2010–2019). We made a COX regression analysis to identify prognostic factors of BCBM patients. Through cross-validation, we constructed XGBoost models to predict survival in patients with BCBM. Meanwhile, a BCBM cohort from our hospital was used to validate our models. We also investigated the prognosis of patients treated with surgery or not, using propensity score matching and K–M survival analysis. Our results were further validated by subgroup COX analysis in patients with different molecular subtypes. Results The XGBoost models we created had high precision and correctness, and they were the most accurate models to predict the survival of BCBM patients (6-month AUC = 0.824, 1-year AUC = 0.813, 2-year AUC = 0.800 and 3-year survival AUC = 0.803). Moreover, the models still exhibited good performance in an externally independent dataset (6-month: AUC = 0.820; 1-year: AUC = 0.732; 2-year: AUC = 0.795; 3-year: AUC = 0.936). Then we used Shiny-Web tool to make our models be easily used from website. Interestingly, we found that the BCBM patients with an annual income of over USD$70,000 had better BCSS (HR = 0.523, 95%CI 0.273–0.999, P

Abstract Significant improvements in long-read sequencing technologies have unlocked complex genomic areas, such as centromeres, in the genome and introduced the centromere annotation problem. Currently, centromeres are annotated in a semi-manual way. Here, we propose HiCAT, a generalizable automatic centromere annotation tool, based on hierarchical tandem repeat mining to facilitate decoding of centromere architecture. We apply HiCAT to simulated datasets, human CHM13-T2T and gapless Arabidopsis thaliana genomes. Our results are generally consistent with previous inferences but also greatly improve annotation continuity and reveal additional fine structures, demonstrating HiCAT’s performance and general applicability.

IntroductionThis study aims to explore the risk factors associated with suicidal behavior and establish predictive models in female patients with mood disorders, specifically using a nomogram of the least absolute shrinkage and selection operator (LASSO) regression.MethodsA cross-sectional survey was conducted among 396 female individuals diagnosed with mood disorders (F30-F39) according to the International Classification of Diseases and Related Health Problems 10th Revision (ICD-10). The study utilized the Chi-Squared Test, t-test, and the Wilcoxon Rank-Sum Test to assess differences in demographic information and clinical characteristics between the two groups. Logistic LASSO Regression Analyses were utilized to identify the risk factors associated with suicidal behavior. A nomogram was constructed to develop a prediction model. The accuracy of the prediction model was evaluated using a Receiver Operating Characteristic (ROC) curve.ResultThe LASSO regression analysis showed that psychotic symptoms at first-episode (β = 0.27), social dysfunction (β = 1.82), and somatic disease (β = 1.03) increased the risk of suicidal behavior. Conversely, BMI (β = −0.03), age of onset (β = −0.02), polarity at onset (β = −1.21), and number of hospitalizations (β = −0.18) decreased the risk of suicidal behavior. The area under ROC curve (AUC) of the nomogram predicting SB was 0.778 (95%CI: 0.730–0.827, p

The advantages of both the length and accuracy of high-fidelity (HiFi) reads enable chromosome-scale haplotype-resolved genome assembly. In this study, we sequenced a cell line named HJ, established from a Chinese Han male individual by using HiFi and Hi-C. We assembled two high-quality haplotypes of the HJ genome (haplotype 1 (H1): 3.1 Gb, haplotype 2 (H2): 2.9 Gb). The continuity (H1: contig N50 = 28.2 Mb, H2: contig N50 = 25.9 Mb) and completeness (BUSCO: H1 = 94.9%, H2 = 93.5%) are substantially better than those of other Chinese genomes, for example, HX1, NH1.0, and YH2.0. By comparing HJ genome with GRCh38, we reported the mutation landscape of HJ and found that 176 and 213 N-gaps were filled in H1 and H2, respectively. In addition, we detected 12.9 Mb and 13.4 Mb novel sequences containing 246 and 135 protein-coding genes in H1 and H2, respectively. Our results demonstrate the advantages of HiFi reads in haplotype-resolved genome assembly and provide two high-quality haplotypes of a potential Chinese genome as a reference for the Chinese Han population.

BackgroundIn the past few decades, liver disease has gradually become one of the major causes of death and illness worldwide. Hepatitis is one of the most common liver diseases in China. There have been intermittent and epidemic outbreaks of hepatitis worldwide, with a tendency toward cyclical recurrences. This periodicity poses challenges to epidemic prevention and control. ObjectiveIn this study, we aimed to investigate the relationship between the periodic characteristics of the hepatitis epidemic and local meteorological elements in Guangdong, China, which is a representative province with the largest population and gross domestic product in China. MethodsTime series data sets from January 2013 to December 2020 for 4 notifiable infectious diseases caused by hepatitis viruses (ie, hepatitis A, B, C, and E viruses) and monthly data of meteorological elements (ie, temperature, precipitation, and humidity) were used in this study. Power spectrum analysis was conducted on time series data, and correlation and regression analyses were performed to assess the relationship between the epidemics and meteorological elements. ResultsThe 4 hepatitis epidemics showed clear periodic phenomena in the 8-year data set in connection with meteorological elements. Based on the correlation analysis, temperature demonstrated the strongest correlation with hepatitis A, B, and C epidemics, while humidity was most significantly associated with the hepatitis E epidemic. Regression analysis revealed a positive and significant coefficient between temperature and hepatitis A, B, and C epidemics in Guangdong, while humidity had a strong and significant association with the hepatitis E epidemic, and its relationship with temperature was relatively weak. ConclusionsThese findings provide a better understanding of the mechanisms underlying different hepatitis epidemics and their connection to meteorological factors. This understanding can help guide local governments in predicting and preparing for future epidemics based on weather patterns and potentially aid in the development of effective prevention measures and policies.

Background Hepatocellular carcinoma (HCC) is a primary malignant tumor of the liver, and pyroptosis has been identified as a novel cellular program that plays a role in numerous diseases including cancer. However, the functional role of pyroptosis in HCC remains unclear. The purpose of this study is to explore the relationship between the two found hub genes and provide targets for clinical treatment. Methods The Cancer Genome Atlas (TCGA) database was used to collect the gene data and clinically-related information of patients with HCC. After the differentially expressed genes (DEGs) were identified, they were intersected with the genes related to pyroptosis, and a risk prediction model was established to predict the overall survival (OS). Subsequently, drug sensitivity analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) was used to analyze the biological characteristics of the DEGs. Different immune cell infiltration and related pathways were analyzed, and hub genes were identified by protein-protein interaction (PPI). Finally, the expression of hub genes was verified by real-time quantitative PCR (qRT-PCR) and immunohistochemistry. Results We conducted a comprehensive bioinformatics analysis to investigate the molecular mechanisms of pyroptosis in hepatocellular carcinoma (HCC). A total of 8,958 differentially expressed genes were identified, and 37 differentially expressed genes were associated with pyroptosis through intersection. Moreover, we developed an OS model with excellent predictive ability and discovered the differences in biological function, drug sensitivity, and immune microenvironment between high-risk and low-risk groups. Through enrichment analysis, we found that the differentially expressed genes are related to various biological processes. Then, 10 hub genes were identified from protein-protein interaction networks. Finally, midkine (MDK) was screened from the 10 hub genes and further verified by PCR and immunohistochemistry, which revealed its high expression in HCC. Conclusion We have developed a reliable and consistent predictive model based on the identification of potential hub genes, which can be used to accurately forecast the prognosis of patients, thus providing direction for further clinical research and treatment.

In order to promote marine technology innovation and marine industry development of Shandong Province, this paper summarized the development status of marine technology innovation platform of Shandong, analyzed the problems, and proposed corresponding countermeasures and suggestions. The results showed that the construction of marine technology innovation platform system was continually being improved, new breakthroughs had been made in variety and quantity, and high-quality development of marine industry had been promoted. However, there were still some problems, such as low overall development level, unbalance of regional and industrial layout, lack of provincial platforms and advanced platforms, and weak role of enterprise innovation force. In the future, Shandong should focus on top-level design, enhance enterprise technological innovation, innovate process management, improve the regulatory system, strengthen policy support and promote collaborative innovation in the development of marine technology innovation platform.

Background and AimsResearch on the effect of the coronavirus disease 2019 (COVID-19) pandemic on psychosocial function in patients with pediatric-onset inflammatory bowel disease (PIBD) is limited. This study aimed to evaluate the psychological status of patients with PIBD before and during the pandemic, and the relationship between mental health and disease activity.MethodsThis study was a retrospective cohort study. Statistical analyses were performed to assess the relationship between demographic, clinical data and psychological data (questionnaires) of PIBD patients before and during the epidemic. The anxiety and depression emotional status of the guardians during the pandemic were evaluated.ResultsIn the PIBD follow-up cohort, 42 patients(male 61.9%) were included. Female with PIBD had lower pediatric quality of life inventory(PedsQL) scores (P = 0.007) and higher spence children's anxiety scale(SCAS) scores (P = 0.038) than male. The pandemic did not have a substantial impact on PedsQL, pittsburgh sleep quality index(PSQI), SCAS, or children's depression inventory(CDI) in patients with PIBD. The self-rating anxiety scale(SAS) score, anxiety rate, self-rating depression scale(SDS) score, and depression rate of PIBD guardians were significantly higher than those of healthy controls (SAS, P = 0.008; SDS, P = 0.001).ConclusionsFemale children with PIBD were more vulnerable to decreased QOL and increased anxiety than male children. The anxiety and depression status of PIBD guardians were significantly higher than those of healthy controls during the COVID-19 pandemic. But the COVID-19 pandemic did not significantly affect quality of life(QOL), sleep, anxiety, or depressive mood of patients with PIBD in our study.

BackgroundThe reemergence of the monkeypox epidemic has aroused great concern internationally. Concurrently, the COVID-19 epidemic is still ongoing. It is essential to understand the temporal dynamics of the monkeypox epidemic in 2022 and its relationship with the dynamics of the COVID-19 epidemic. In this study, we aimed to explore the temporal dynamic characteristics of the human monkeypox epidemic in 2022 and its relationship with those of the COVID-19 epidemic.MethodsWe used publicly available data of cumulative monkeypox cases and COVID-19 in 2022 and COVID-19 at the beginning of 2020 for model validation and further analyses. The time series data were fitted with a descriptive model using the sigmoid function. Two important indices (logistic growth rate and semi-saturation period) could be obtained from the model to evaluate the temporal characteristics of the epidemic.ResultsAs for the monkeypox epidemic, the growth rate of infection and semi-saturation period showed a negative correlation (r = 0.47, p = 0.034). The growth rate also showed a significant relationship with the locations of the country in which it occurs [latitude (r = –0.45, p = 0.038)]. The development of the monkeypox epidemic did not show significant correlation compared with the that of COVID-19 in 2020 and 2022. When comparing the COVID-19 epidemic with that of monkeypox, a significantly longer semi-saturation period was observed for monkeypox, while a significant larger growth rate was found in COVID-19 in 2020.ConclusionsThis novel study investigates the temporal dynamics of the human monkeypox epidemic and its relationship with the ongoing COVID-19 epidemic, which could provide more appropriate guidance for local governments to plan and implement further fit-for-purpose epidemic prevention policies.

Tyrian purple, mainly composed of 6, 6′-dibromoindigo, is a precious dye extracted from sea snails. In this study, we found Tyrian purple can be selectively produced by a bacterial strain GS-2 when fed with 6-bromotryptophan in the presence of tryptophan. This GS-2 strain was then identified as Providencia rettgeri based on bacterial genome sequencing analysis. An indole degradation gene cluster for indole metabolism was identified from this GS-2 strain. The heterologous expression of the indole degradation gene cluster in Escherichia coli BL21 (DE3) and in vitro enzymatic reaction demonstrated that the indole biodegradation gene cluster may contribute to selectively biosynthesizing Tyrian purple. To further explore the underlying mechanism of the selectivity, we explored the intermediates in this indole biodegradation pathway using liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (LC-ESI-QTOF-MS/MS), which indicated that the indole biodegradation pathway in Providencia rettgeri is the catechol pathway. Interestingly, the monooxygenase GS-C co-expressed with its corresponding reductase GS-D in the cluster has better activity for the biosynthesis of Tyrian purple compared with the previously reported monooxygenase from Methylophaga aminisulfidivorans (MaFMO) or Streptomyces cattleya cytochrome P450 enzyme (CYP102G4). This is the first study to show the existence of an indole biodegradation pathway in Providencia rettgeri, and the indole biodegradation gene cluster can contribute to the selective production of Tyrian purple.

Arabidopsis thaliana is an important and long-established model species for plant molecular biology, genetics, epigenetics, and genomics. However, the latest version of reference genome still contains a significant number of missing segments. Here, we reported a high-quality and almost complete Col-0 genome assembly with two gaps (named Col-XJTU) by combining the Oxford Nanopore Technologies ultra-long reads, Pacific Biosciences high-fidelity long reads, and Hi-C data. The total genome assembly size is 133,725,193 bp, introducing 14.6 Mb of novel sequences compared to the TAIR10.1 reference genome. All five chromosomes of the Col-XJTU assembly are highly accurate with consensus quality (QV) scores > 60 (ranging from 62 to 68), which are higher than those of the TAIR10.1 reference (ranging from 45 to 52). We completely resolved chromosome (Chr) 3 and Chr5 in a telomere-to-telomere manner. Chr4 was completely resolved except the nucleolar organizing regions, which comprise long repetitive DNA fragments. The Chr1 centromere (CEN1), reportedly around 9 Mb in length, is particularly challenging to assemble due to the presence of tens of thousands of CEN180 satellite repeats. Using the cutting-edge sequencing data and novel computational approaches, we assembled a 3.8-Mb-long CEN1 and a 3.5-Mb-long CEN2. We also investigated the structure and epigenetics of centromeres. Four clusters of CEN180 monomers were detected, and the centromere-specific histone H3-like protein (CENH3) exhibited a strong preference for CEN180 Cluster 3. Moreover, we observed hypomethylation patterns in CENH3-enriched regions. We believe that this high-quality genome assembly, Col-XJTU, would serve as a valuable reference to better understand the global pattern of centromeric polymorphisms, as well as the genetic and epigenetic features in plants.

Current decoding algorithms based on a one-dimensional (1D) convolutional neural network (CNN) have shown effectiveness in the automatic recognition of emotional tasks using physiological signals. However, these recognition models usually take a single modal of physiological signal as input, and the inter-correlates between different modalities of physiological signals are completely ignored, which could be an important source of information for emotion recognition. Therefore, a complete end-to-end multi-input deep convolutional neural network (MI-DCNN) structure was designed in this study. The newly designed 1D-CNN structure can take full advantage of multi-modal physiological signals and automatically complete the process from feature extraction to emotion classification simultaneously. To evaluate the effectiveness of the proposed model, we designed an emotion elicitation experiment and collected a total of 52 participants' physiological signals including electrocardiography (ECG), electrodermal activity (EDA), and respiratory activity (RSP) while watching emotion elicitation videos. Subsequently, traditional machine learning methods were applied as baseline comparisons; for arousal, the baseline accuracy and f1-score of our dataset were 62.9 ± 0.9% and 0.628 ± 0.01, respectively; for valence, the baseline accuracy and f1-score of our dataset were 60.3 ± 0.8% and 0.600 ± 0.01, respectively. Differences between the MI-DCNN and single-input DCNN were also compared, and the proposed method was verified on two public datasets (DEAP and DREAMER) as well as our dataset. The computing results in our dataset showed a significant improvement in both tasks compared to traditional machine learning methods (t-test, arousal: p = 9.7E-03 < 0.01, valence: 6.5E-03 < 0.01), which demonstrated the strength of introducing a multi-input convolutional neural network for emotion recognition based on multi-modal physiological signals.

BackgroundBreast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced.MethodsA total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs.ResultsThe results reveal that the SIR (1.01; 95% CI, 0.99–1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05–1.11, p

BackgroundBone is the most common metastatic site of patients with advanced breast cancer and the survival time is their primary concern; however, we lack accurate predictive models in clinical practice. In addition to this, primary surgery for breast cancer patients with bone metastases is still controversial.MethodThe data used for analysis in this study were obtained from the SEER database (2010–2019). We made a COX regression analysis to identify prognostic factors of patients with bone metastatic breast cancer (BMBC). Through cross-validation, we constructed an XGBoost model to predicting survival in patients with BMBC. We also investigated the prognosis of patients treated with neoadjuvant chemotherapy plus surgical and chemotherapy alone using propensity score matching and K–M survival analysis.ResultsOur validation results showed that the model has high sensitivity, specificity, and correctness, and it is the most accurate one to predict the survival of patients with BMBC (1-year AUC = 0.818, 3-year AUC = 0.798, and 5-year survival AUC = 0.791). The sensitivity of the 1-year model was higher (0.79), while the specificity of the 5-year model was higher (0.86). Interestingly, we found that if the time from diagnosis to therapy was ≥1 month, patients with BMBC had even better survival than those who started treatment immediately (HR = 0.920, 95%CI 0.869–0.974, P < 0.01). The BMBC patients with an income of more than USD$70,000 had better OS (HR = 0.814, 95%CI 0.745–0.890, P < 0.001) and BCSS (HR = 0.808 95%CI 0.735–0.889, P < 0.001) than who with income of < USD$50,000. We also found that compared with chemotherapy alone, neoadjuvant chemotherapy plus surgical treatment significantly improved OS and BCSS in all molecular subtypes of patients with BMBC, while only the patients with bone metastases only, bone and liver metastases, bone and lung metastases could benefit from neoadjuvant chemotherapy plus surgical treatment.ConclusionWe constructed an AI model to provide a quantitative method to predict the survival of patients with BMBC, and our validation results indicate that this model should be highly reproducible in a similar patient population. We also identified potential prognostic factors for patients with BMBC and suggested that primary surgery followed by neoadjuvant chemotherapy might increase survival in a selected subgroup of patients.

Alpha rhythms in the human electroencephalogram (EEG), oscillating at 8-13 Hz, are located in parieto-occipital cortex and are strongest when awake people close their eyes. It has been suggested that alpha rhythms were related to attention-related functions and mental disorders (e.g., Attention-deficit/hyperactivity disorder (ADHD)). However, many studies have shown inconsistent results on the difference in alpha oscillation between ADHD and control groups. Hence it is essential to verify this difference. In this study, a dataset of EEG recording (128 channel EGI) from 87 healthy controls (HC) and 162 ADHD (141 persisters and 21 remitters) adults in a resting state with their eyes closed was used to address this question and a three-gauss model (summation of baseline and alpha components) was conducted to fit the data. To our surprise, the power of alpha components was not a significant difference among the three groups. Instead, the baseline power of remission and HC group in the alpha band is significantly stronger than that of persister groups. Our results suggest that ADHD recovery may have compensatory mechanisms and many abnormalities in EEG may be due to the influence of behavior rather than the difference in brain signals.

BackgroundEpidemics of infectious diseases have a great negative impact on people's daily life. How it changes over time and what kind of laws it obeys are important questions that researchers are always interested in. Among the characteristics of infectious diseases, the phenomenon of recrudescence is undoubtedly of great concern. Understanding the mechanisms of the outbreak cycle of infectious diseases could be conducive for public health policies to the government.MethodIn this study, we collected time-series data for nine class C notifiable infectious diseases from 2009 to 2021 using public datasets from the National Health Commission of China. Oscillatory power of each infectious disease was captured using the method of the power spectrum analysis.ResultsWe found that all the nine class C diseases have strong oscillations, which could be divided into three categories according to their oscillatory frequencies each year. Then, we calculated the oscillation power and the average number of infected cases of all nine diseases in the first 6 years (2009–2015) and the next 6 years (2015–2021) since the update of the surveillance system. The change of oscillation power is positively correlated to the change in the number of infected cases. Moreover, the diseases that break out in summer are more selective than those in winter.ConclusionOur results enable us to better understand the oscillation characteristics of class C infectious diseases and provide guidance and suggestions for the government's prevention and control policies.

The fungal decay of fresh fruits and vegetables annually generates substantial global economic losses. The utilization of conventional synthetic fungicides is damaging to the environment and human health. Recently, the biological control of post-harvest fruit and vegetable diseases via antagonistic microorganisms has become an attractive possible substitution for synthetic fungicides. Numerous studies have confirmed the potential of volatile organic compounds (VOCs) for post-harvest disease management. Moreover, VOC emission is a predominant antifungal mechanism of antagonistic microorganisms. As such, it is of great significance to discuss and explore the antifungal mechanisms of microbial VOCs for commercial application. This review summarizes the main sources of microbial VOCs in the post-harvest treatment and control of fruit and vegetable diseases. Recent advances in the elucidation of antifungal VOC mechanisms are emphasized, and the applications of VOCs produced from antagonistic microorganisms are described. Finally, the current prospects and challenges associated with microbial VOCs are considered.

Background: Occult breast cancer (OBC) is an uncommon malignant tumor and the prognosis and treatment of OBC remain controversial. Currently, there exists no accurate prognostic clinical model for OBC, and the treatment outcomes of chemotherapy and surgery in its different molecular subtypes are still unknown. Methods: The SEER database provided the data used for this study’s analysis (2010–2019). To identify the prognostic variables for patients with ODC, we conducted Cox regression analysis and constructed prognostic models using six machine learning algorithms to predict overall survival (OS) of OBC patients. A series of validation methods, including calibration curve and area under the curve (AUC value) of receiver operating characteristic curve (ROC) were employed to validate the accuracy and reliability of the logistic regression (LR) models. The effectiveness of clinical application of the predictive models was validated using decision curve analysis (DCA). We also investigated the role of chemotherapy and surgery in OBC patients with different molecular subtypes, with the help of K-M survival analysis as well as propensity score matching, and these results were further validated by subgroup Cox analysis. Results: The LR models performed best, with high precision and applicability, and they were proved to predict the OS of OBC patients in the most accurate manner (test set: 1-year AUC = 0.851, 3-year AUC = 0.790 and 5-year survival AUC = 0.824). Interestingly, we found that the N1 and N2 stage OBC patients had more favorable prognosis than N0 stage patients, but the N3 stage was similar to the N0 stage (OS: N0 vs. N1, HR = 0.6602, 95%CI 0.4568–0.9542, p < 0.05; N0 vs. N2, HR = 0.4716, 95%CI 0.2351–0.9464, p < 0.05; N0 vs. N3, HR = 0.96, 95%CI 0.6176–1.5844, p = 0.96). Patients aged >80 and distant metastases were also independent prognostic factors for OBC. In terms of treatment, our multivariate Cox regression analysis discovered that surgery and radiotherapy were both independent protective variables for OBC patients, but chemotherapy was not. We also found that chemotherapy significantly improved both OS and breast cancer-specific survival (BCSS) only in the HR−/HER2+ molecular subtype (OS: HR = 0.15, 95%CI 0.037–0.57, p < 0.01; BCSS: HR = 0.027, 95%CI 0.027–0.81, p < 0.05). However, surgery could help only the HR−/HER2+ and HR+/HER2− subtypes improve prognosis. Conclusions: We analyzed the clinical features and prognostic factors of OBC patients; meanwhile, machine learning prognostic models with high precision and applicability were constructed to predict their overall survival. The treatment results in different molecular subtypes suggested that primary surgery might improve the survival of HR+/HER2− and HR−/HER2+ subtypes, however, only the HR−/HER2+ subtype could benefit from chemotherapy. The necessity of surgery and chemotherapy needs to be carefully considered for OBC patients with other subtypes.

BackgroundCOVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic. ObjectiveNonpharmaceutical interventions (NPIs) may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aim to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China. MethodsTime series data sets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public data sets from the National Health Commission of the People’s Republic of China. Several indices (peak and trough amplitudes, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak. ResultsWe found that the prevention and control policies for COVID-19 had a strong, significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it was significantly stronger before the COVID-19 outbreak and does not correlate with the trough amplitude. ConclusionsOur results directly demonstrate that prevention policies for COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction in outbreaks. This study may guide the implementation of nonpharmaceutical interventions to control a wider range of infectious diseases.

The Ocean Drilling Program Site 1177 recovered the oldest (∼23 Ma) sedimentary records in the Shikoku Basin, northeastern part of the Philippine Sea Plate. Changes in sediment provenances bear important implications for the tectonic evolution of the Philippine Sea Plate, but existing data are still controversial for the early Miocene. By integrating Sr-Nd isotopes, rock-magnetic parameters, diffuse reflectance spectroscopy, and the previous data on the detrital zircons and clay minerals from Site 1177, we found that a significant provenance shift occurred at ∼16.5 Ma. The sediments of Site 1177 before ∼16.5 Ma were mainly sourced from the Pearl River and Izu-Bonin Arc, but changed to the Yangtze River and Izu-Bonin Arc sources after that. This provenance shift was strongly linked with the northward motion and clockwise rotation of the Shikoku Basin in the Miocene, which marked the final time of separation between the Shikoku Basin and the South China Sea.

ObjectiveSchizophrenia is a mental disorder that is characterized by progressive cognitive impairment. Objective measures of cognitive function may provide reliable neurobiomarkers for patients with schizophrenia. The goal of the current work is to explore the correlation between resting theta power and cognitive performance in patients with schizophrenia.MethodsTwenty-two patients with schizophrenia and 23 age-, sex-, and education-matched healthy controls were included in this study. The MATRICS Consensus Cognitive Battery (MCCB) was used for cognitive evaluation and the Positive and Negative Syndrome Scale (PANSS) for evaluation of clinical symptoms. EEGs were acquired in the resting state with closed and opened eyes. Between the two groups, we compared the relative theta power and examined their relationship with cognitive performance.ResultsCompared to healthy controls, patients with schizophrenia showed significantly higher theta power, both with eyes closed and open (P < 0.05). When the eyes were open, negative correlations were found in patients with schizophrenia between theta power in the central and parietal regions with processing speed scores, and between the theta power of the Pz electrode and verbal learning and reasoning and problem-solving scores (r ≥ −0.446). In the control group, theta power over the Fz electrode was negatively correlated with processing speed (r = −0.435).ConclusionsOur findings showed that theta activity increased in certain brain regions during resting state in schizophrenia. Negative associations between resting theta power (increased) over the parietal-occipital regions with MCCB domains scores (decreased) suggest that altered theta activity can be used as a neurobiological indicator to predict cognitive performance.

The study was to compare the performance of the regression models and fuzzy set qualitative comparative analysis (fsQCA) models in analyzing the possible effects of sociodemographic variables (age and sex) and lifestyle behaviors (physical activity, sedentary time, sleep duration, physical education class and screen time) on depressive symptoms in adolescents. This cross-sectional surgery was conducted among 726 adolescents in Jilin Province of China, selected by random cluster sampling. The regression model showed that age, physical education (PE) class and sleep duration were associated with depressive symptoms. Meanwhile, the fsQCA models showed that shorter physical activity, PE class and sleep duration as well as longer sedentary and screen time were related to higher levels of depressive symptoms. Both regression and fsQCA models indicated that promoting lifestyle behaviors could affect depressive symptoms. Considering the differences between the two methods, they are not superior to the other method, but complementary and should be used in other studies at the same time.

Controlling the growth processes of nanowires is vital for tailoring their properties. Here, the presence of tungstate ions on specific surface planes of zinc oxide nanowires causes nanowire growth and chemical doping along specific crystal planes.

EZH2 phosphorylation by CDK2 promotes progression of triple-negative breast cancer (TNBC). Here, the authors show that this signaling axis downregulates ERα, and thus combinatorial blockade of CDK2 and EZH2 sensitizes TNBC cells to tamoxifen.

Background: Keeping in view the high recurrence rate and risk of ischemic stroke, combinatorial therapy involving traditional Chinese medicine (TCM) with conventional Western medicine (WM) is receiving wider scientific attention. Thus, a systematical analysis was made to explore the efficacy of TCM+WM in the long-term secondary prevention for patients with ischemic stroke.Methods: Qualified inclusion and exclusion criteria were set up beforehand, and two researchers independently read the articles, extracted data, and evaluated the quality of included articles according to Cochrane Reviewer’s Handbook 5.1 method. For the sake of comprehensive data acquisition, seven databases from the time of their establishment to May 5, 2021, have been searched completely. Additionally, pairwise meta-analysis was made to compare TCM+WM vs. WM, and network meta-analysis was conducted by frequentist random effects models for the comparison of different kinds of TCM+WM via indirect evidence. The primary outcomes defined were recurrent stroke and NIHSS. Secondary outcomes were fibrinogen (Fib) fasting blood glucose (FBG), triglycerides (TG), and total cholesterol (TC). Safety outcomes were outlined as all-cause mortality and adverse events (AEs). Furthermore, Stata16.0 software was used to accomplish the systematical analysis and cluster analysis.Results: In total, 47 qualified randomized controlled trials (RCTs) including 10,732 patients were taken into consideration. Seven traditional Chinese medicines included in the study are Naoxintong capsule (NXT), Tongxinluo capsule (TXL), Buyang Huanwu decoction (BYHW), Naomaitai capsule (NMT), Dengzhan Shengmai capsule (DZSM), Naoshuantong capsule (NST), and Maixuekang capsule (MXK). With respect to their primary outcomes, all kinds of TCM+WM were significantly more effective than WM (e.g., NXT in recurrent stroke (OR=0.54, P

Resveratrol, a natural polyphenol compound with multiple bioactivities, is widely used in food and pharmaceutical industry. Endophytic fungus Alternaria sp. MG1, as a native producer of resveratrol, shows increasing potential application. However, strategies for improvement of the biosynthesis of resveratrol in this species are still scarce. In this study, different elicitors were used to investigate their effect on the biosynthesis of resveratrol in MG1 and the induction mechanism. Ultrasound and sodium butyrate had no effect and slight inhibition on the resveratrol production and related gene expression, respectively. UV radiation and co-culture with Phomopsis sp. XP-8 significantly promoted the biosynthesis of resveratrol with the highest production (240.57μg/l) coming from UV 20min. Co-culture altered the profiles of secondary metabolites in MG1 by promoting and inhibiting the synthesis of stilbene and lignin compounds, respectively, and generating new flavonoids ((+/−)-taxifolin, naringin, and (+)-catechin). Oligomeric proanthocyanidins (OPC) also showed an obviously positive influence, leading to an increase in resveratrol production by 10 to 60%. Two calcium-dependent protein kinases (CDPK) were identified, of which CDPK1 was found to be an important regulatory factor of OPC induction. Synergistic treatment of UV 20min and 100μm OPC increased the production of resveratrol by 70.37% compared to control and finally reached 276.31μg/l.

Anxiety disorder is a mental illness that involves extreme fear or worry, which can alter the balance of chemicals in the brain. This change and evaluation of anxiety state are accompanied by a comprehensive treatment procedure. It is well-known that the treatment of anxiety is chiefly based on psychotherapy and drug therapy, and there is no objective standard evaluation. In this paper, the proposed method focuses on examining neural changes to explore the effect of mindfulness regulation in accordance with neurofeedback in patients with anxiety. We designed a closed neurofeedback experiment that includes three stages to adjust the psychological state of the subjects. A total of 34 subjects, 17 with anxiety disorder and 17 healthy, participated in this experiment. Through the three stages of the experiment, electroencephalography (EEG) resting state signal and mindfulness-based EEG signal were recorded. Power spectral density was selected as the evaluation index through the regulation of neurofeedback mindfulness, and repeated analysis of variance (ANOVA) method was used for statistical analysis. The findings of this study reveal that the proposed method has a positive effect on both types of subjects. After mindfulness adjustment, the power map exhibited an upward trend. The increase in the average power of gamma wave indicates the relief of anxiety. The enhancement of the wave power represents an improvement in the subjects’ mindfulness ability. At the same time, the results of ANOVA showed that P < 0.05, i.e., the difference was significant. From the aspect of neurophysiological signals, we objectively evaluated the ability of our experiment to relieve anxiety. The neurofeedback mindfulness regulation can effect on the brain activity pattern of anxiety disorder patients.

Guhong injection (GHI) is a drug for ischemic stroke created by combining safflower, a traditional Chinese medicine, and aceglutamide, a Western medicine. In this study, we investigated the curative effect of GHI on cerebral ischemia–reperfusion (I/R) injury via the PKC/HIF-1α pathway in rats. Adult male Sprague Dawley rats were randomly divided into seven groups: sham-operated, middle cerebral artery occlusion (MCAO), GHI, nimodipine injection (NMDP), MCAO + LY317615 (PKC inhibitor), GHI + LY317615, and NMDP + LY317615. After establishing an MCAO rat model, we performed neurological deficit testing, 2,3,5-triphenyltetrazolium chloride staining, hematoxylin and eosin (HE) staining, enzyme-linked immunosorbent assay, Western blotting, and q-PCR to detect the brain damage in rats. Compared with the MCAO group, the GHI and GHI + LY317615 group showed neurological damage amelioration as well as decreases in serum hypoxia-inducible factor-1α (HIF-1α), protein kinase C (PKC), and erythropoietin levels; brain HIF-1α and inducible nitric oxide synthase protein expression; and brain HIF-1α and NOX-4 mRNA expression. These effects were similar to those in the positive control groups NMDP and NMDP + LY317615. Thus, our results confirmed GHI can ameliorate cerebral I/R injury in MCAO rats possibly via the PKC/HIF-1α pathway.

This study aimed to develop and validate a prognostic nomogram for recurrence-free survival (RFS) after surgery in the absence of adjuvant therapy to guide the selection for adjuvant imatinib therapy based on Residual Neural Network (ResNet).The ResNet model was developed based on contrast-enhanced computed tomography (CE-CT) in a training cohort consisted of 80 patients pathologically diagnosed gastrointestinal sromal tumors (GISTs) and validated in internal and external validation cohort respectively. Independent clinicopathologic factors were integrated with the ResNet model to construct the individualized nomogram. The performance of the nomogram was evaluated in regard to discrimination, calibration, and clinical usefulness.The ResNet model was significantly associated with RFS. Integrable predictors in the individualized ResNet nomogram included the tumor site, size, and mitotic count. Compared with modified NIH, AFIP, and clinicopathologic nomogram, both ResNet nomogram and ResNet model showed a better discrimination capability with AUCs of 0·947(95%CI, 0·910–0·984) for 3-year-RFS, 0·918(0·852–0·984) for 5-year-RFS, and AUCs of 0·912 (0·851–0·973) for 3-year-RFS, 0·887(0·816–0·960) for 5-year-RFS, respectively. Calibration curve shows the good calibration of the nomogram in terms of the agreement between the estimated and the observed 3- and 5- year outcomes. Decision curve analysis showed that the ResNet nomogram had a higher overall net benefit.In conclusion, we presented a deep learning-based prognostic nomogram to predict RFS after resection of localized primary GISTs with excellent performance and could be a potential tool to select patients for adjuvant imatinib therapy. Keywords: Gastrointestinal Stromal Tumors, Deep Learning, Residual Neural Network, Recurrence-free Survival, Imatinib

A variety of infectious diseases occur in mainland China every year. Cyclic oscillation is a widespread attribute of most viral human infections. Understanding the outbreak cycle of infectious diseases can be conducive for public health management and disease surveillance. In this study, we collected time-series data for 23 class B notifiable infectious diseases from 2004 to 2020 using public datasets from the National Health Commission of China. Oscillatory properties were explored using power spectrum analysis. We found that the 23 class B diseases from the dataset have obvious oscillatory patterns (seasonal or sporadic), which could be divided into three categories according to their oscillatory power in different frequencies each year. These diseases were found to have different preferred outbreak months and infection selectivity. Diseases that break out in autumn and winter are more selective. Furthermore, we calculated the oscillation power and the average number of infected cases of all 23 diseases in the first eight years (2004 to 2012) and the next eight years (2012 to 2020) since the update of the surveillance system. A strong positive correlation was found between the change of oscillation power and the change in the number of infected cases, which was consistent with the simulation results using a conceptual hybrid model. The establishment of reliable and effective analytical methods contributes to a better understanding of infectious diseases' oscillation cycle characteristics. Our research has certain guiding significance for the effective prevention and control of class B infectious diseases.

Yangyin Tongnao (YYTN) prescription is used as a traditional Chinese herbal formula, and it has antioxidant activity that mainly contributes in the treatment of cardiovascular and cerebrovascular diseases. However, the compounds related to its antioxidant activity are still unknown. In the present study, the fingerprints of YYTN extracts under different extraction conditions were obtained by high performance liquid chromatography (HPLC) to identify the common peaks to all the samples processed. A 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity assay and ferric reducing antioxidant power (FRAP) assay were carried out to evaluate the antioxidant activity of the extracts. Spectrum-effect relationship between HPLC fingerprints and antioxidant activity of YYTN was assessed by Pearson product-moment correlation coefficient (PPMCC) and multiple linear regression analysis (MLRA). The results showed that peaks 5, 6, 13, 15, and 24 of the fingerprints were closely connected to antioxidant activity. Five peaks were identified: vanillic acid (P5), puerarin (P7), ferulic acid (P13), daidzein (P21), and formononetin (P23). Our study successfully established the spectrum-effect relationship between HPLC fingerprints and antioxidant activity of YYTN, which provided a general method for establishing quality standards with a combination of chromatography and antioxidant activity.

Background: Quzhou Fructus Aurantii (QFA) is an herb that is commonly used to alleviate inflammation in individuals dealing with obesity.To date, however, no systematic pharmacokinetic (PK) or pharmacodynamic (PD) analyses of the clinical efficacy of QFA under hyperlipemia-associated oxidative stress conditions have been conducted. The present study, was therefore designed to construct a PK-PD model for this herb, with the goal of linking QFA PK profiles to key therapeutic outlines to guide the therapeutic use of this herb in clinical settings. Methods: Rats were fed a high-fat diet in order to establish a model of hyperlipidemia, after which they were randomized into a normal control group (NCG), a normal treatment group (NTG), a model control group (MCG), and a model treated group (MTG) (n = 6 each). QAF decoction was used to treat rats in the NTG and MTG groups (25 g/kg), while equivalent volumes of physiological saline were administered to rats in the NCG and MCG groups. Plasma samples were collected from the mandibular vein for animals at appropriate time points and analyzed via high-performance liquid chromatography (HPLC). We evaluated PK properties for three QAF components and compared these dynamics between the NTG and MTG groups, while also measuring levels of lipid peroxidation (LPO) in the plasma of rats in all four treatment groups. We then constructed a PK-PD model based upon plasma neohesperidin, luteolin, and nobiletin concentrations and LPO levels using a three-compartment PK model together with a Sigmoid Emax PD model. This model thereby enabled us to assess the antioxidative impact of neohesperidin, luteolin, and nobiletin on hyperlipidemia in rats. Results: When comparing the NTG and MTG groups, we detected significant differences in the following parameters pertaining to neohesperidin, luteolin, and nobiletin:t1/2β, V1, t1/2γ, CL1 (p < 0.01) and AUC0-t, Tmax, Cmax (p < 0.05). Relative to NTG group rats, AUC0-t, Tmax and Cmax values significantly higher for MTG group rats (p < 0.01), while t1/2β, V1, and t1/2γ values were significantly lower in MTG group rats (p < 0.01) in MTG rats. QAF decoction also exhibited excellent PD efficacy in MTG rats, with significant reductions in plasma LPO levels relative to NTG rats (p < 0.01) following treatment. This therapeutic efficacy may be attributable to the activity of neohesperidin, luteolin, and nobiletin, as LPO levels and plasma concentrations of these compounds were negatively correlated in treated rats. Based upon Akaike Information Criterion (AIC) values, we determined that neohesperidin, luteolin, and nobiletin PK processes were consistent with a three-compartment model. Together, these findings indicated that three active components in QAF decoction (neohesperidin, luteolin, and nobiletin) may exhibit antioxidant activity in vivo. Conclusion: Our in vivo data indicated that neohesperidin, luteolin and nobiletin components of QAF decoctions exhibit distinct PK and PD properties. Together, these findings suggest that hyperlipidemia-related oxidative stress can significantly impact QFA decoction PK and PD parameters. Our data additionally offer fundamental insights that can be used to design appropriate dosing regimens for individualized clinical QAF decoction treatment.

ZFP36 has been shown to be involved in ABA-induced antioxidant defense and enhance rice tolerance to drought, salt stress and oxidative stress. Using ZFP36 as bait, a yeast two-hybrid system was used to obtain the interacting protein OsDjC46, which belongs to heat shock protein and usually exists in the form of molecular chaperone, was identified. Further Co-IP (co-immunoprecipitation), BiFC (bimolecular fluorescence complement) and GST (glutathione-S-transferase) pull-down experiments verified that ZFP36 interacted with OsDjC46 in vivo and in vitro. Heat shock protein has been shown to increase plant resistance to stresses, but whether OsDjC46 was a key factor in plant response to various stresses has not been reported. Here, various stimuli, such as abscisic acid (ABA), hydrogen peroxidase (H2O2), polyethylene (PEG) and sodium chloride (NaCl) markedly induced the expression of OsDjC46 in the seedlings. Overexpression of OsDjC46 in rice can enhance the tolerance to salinity and drought; in contrast, knockout of OsDjC46 rice plants was more sensitive to salt stress and drought. Further investigation revealed that OsDjC46 could participate in regulating the expression and activities of antioxidant of SOD and CAT under drought and salt stress. Taken together, these findings reveal a novel function of OsDjC46 in adjusting ABA-induced antioxidant defense.

Abstract Gyro‐remanent magnetization (GRM) is a frequently occurring yet unwanted remanence contamination for certain samples during alternating field (AF) demagnetization of the natural remanent magnetization. The origin and detailed properties of GRM have not yet been fully understood. In this study, systematic rock magnetic analyses were conducted on marine greigite‐bearing samples of Hole U1433A drilled by the IODP Expedition 349 from the South China Sea. Results show that GRM is mostly acquired above ~55 mT AF demagnetization and can be effectively removed by heating to ~400°C during thermal demagnetization but a secondary tail could remain until ~585°C. In addition, no apparent GRM was observed during the AF demagnetization for the 400°C thermally treated samples. These results strongly suggest that GRM is dominantly carried by single domain (SD) greigite but with minor contributions from SD magnetite. Thus, thermal treatment alone or the hybrid demagnetization (i.e., thermal demagnetization at ~400°C first then systematical AF demagnetization) can efficiently avoid the GRM acquisition and be beneficial for relative paleointensity estimation for greigite‐bearing samples. Besides, GRM carried by greigite has a low thermal stability. Our results also show AF demagnetization spectra of anhysteretic remanent magnetization (ARM) could be strongly distorted by GRM effects due to both have a preference of SD particles. Thus, the median destructive field of ARM is improper to be used as a coercivity proxy for greigite‐bearing samples. Instead, the biplot analysis of AF demagnetization of natural remanent magnetization and ARM can be used to evaluate the relative content of greigite.

BackgroundWe investigated working memory (WM) processing in a longitudinal sample of young adults with persistent and remittent childhood-onset ADHD to investigate the neural correlates of working memory with adult outcomes of ADHD.MethodsForty-seven young Chinese adults who had been diagnosed with ADHD during childhood underwent follow-up assessments for an average of 9 years. The ADHD sample consisted of 25 ADHD persisters (mean age =18.38 ± 0.5 years) and 22 remitters (mean age = 18.78 ± 1.10 years), who were compared with 25 sex ratio- and IQ-matched healthy adults (mean age = 19.60 ± 1.22 years) in a verbal n-back task.ResultsNo differences in behavioral measures were observed across the three groups. Compared with the healthy controls, the ADHD persisters and remitters had larger N1 amplitudes and smaller P2 amplitudes, while no significant differences between the persistence and remission groups were observed. The P3 amplitudes of the remission and control groups were higher than that of the persistence group, but there was no significant difference between the remitters and healthy controls.ConclusionThe P3 amplitudes reflecting postdecisional processing and/or WM updating were sensitive to ADHD remission, as they might improve concurrently with ADHD symptoms. These results indicate that the N1, P2, and P3 components of WM processing might be potential biomarkers for different ADHD outcomes.

BackgroundIn China, the combination of herb Salvia miltiorrhiza Bge. (Danshen) and Carthamus tinctorius L. (Honghua) is an effective treatment for stroke. A previous study showed that the combination of four herbal components: danshensu (DSS), hydroxysafflor yellow A (HSYA), salvianolic acid A (SAA), and salvianolic acid B (SAB) was effective for treatment of cerebral ischemia-reperfusion (I/R) injury in rats. However, the pharmacokinetic characteristics of this formula require further investigation. The present study investigated the pharmacokinetic differences between each component of in two formulas in cerebral I/R injury rats. The influencing factors may affect the compatibility of components were analyzed.MethodsFocal cerebral I/R was induced by middle cerebral artery occlusion (MCAO). Rats that underwent MCAO were randomly divided into two groups and administered treatments through the tail vein. Blood samples were collected at predetermined time points following administration. The concentrations of DSS, HSYA, SAB, and SAA in rat plasma were determined using HPLC-DAD, and the main pharmacokinetic parameters were calculated. Pharmacokinetic parameters were calculated using DAS 3.2.6 software and SPSS 23.0 statistical analysis software.ResultsOur results showed that DSS, HSYA, SAB, and SAA in MCAO model rats had statistically significant differences in two formulas. For DSS and SAA, pharmacokinetic parameters with statistically significant differences including AUC(0−t), AUMC(0−t), MRT(0−t), VRT(0−t), t1/2z, Vz, CLz, and Cmax (P < 0.01). For HSYA, significant differences in the parameters including AUC(0−t), AUMC(0−t), MRT(0−t), VRT(0−t) (P < 0.01), CLz and Cmax (P < 0.05).ConclusionThe difference in pharmacokinetic parameters in response to each component may have been due to differences in the dosages of the components (HSYA, SAA, SAB) and the compatibility of components. Meanwhile, there were many influencing factors could affect the compatibility of components, such as the metabolism by CYP450 enzymes, plasma protein binding rates, and effects related to the blood-brain barrier (BBB). Moreover, our study provided new insights, such as choosing appropriate dosages of active components of traditional Chinese medicine (TCM) to aid in prevention and treatment of cerebral ischemic diseases. The method and results in this study could provide a foundation for future pharmacological studies of the active components in Danshen and Honghua.

Working memory impairment is a typical cognitive abnormality in patients with attention-deficit/hyperactivity disorder (ADHD) and is closely related to attention. Exploring the interaction between working memory and attention in patients with ADHD is of great significance for studying the pathological mechanism of this disease. In this study, electrophysiological markers of attention, posterior contralateral N2 (N2pc), and working memory, contralateral delay activity (CDA), were used to explore the relationship between these two cognitive abilities in patients with ADHD. EEG data were collected from adults with ADHD and age-, sex-, and IQ-matched normal controls while performing a classical visuospatial working memory task that consisted of low-load and high-load memory conditions. In different memory load conditions, the memory array elicited a smaller N2pc (220–260 ms) and a smaller CDA (400–800 ms) in adults with ADHD than in normal controls. Further analysis revealed that the reduced CDA amplitude could be significantly predicted by the earlier and reduced N2pc amplitude in adults with ADHD. Moreover, when the number of memory items increased, the increase in N2pc highly predicted the increases in CDA. Our findings illustrate the relationship between spatial working memory and attention ability in ADHD adults from the neurophysiological aspect that reduced working memory is closely related to insufficient attention ability and provide a potential physiological basis for the pathological mechanism of ADHD. Keywords: ADHD, Adults, ERP, Attentional selection, Working memory

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Clay mineralogy and major-element geochemistry of Miocene sedimentary rock and modern river sediment samples collected from the Ba River basin in central Vietnam are used to evaluate the chemical weathering processes during the Miocene and the present time. The results show that Miocene andesitic sedimentary rocks consist of high smectite (average 72%) with moderate kaolinite (24%), while Miocene felsic sedimentary rocks display abundant kaolinite (65%) with moderate smectite (25%). In comparison, modern river sediments are characterized by moderate smectite (43%) and kaolinite (37%). The typical distribution of clay minerals in the Ba River basin can be resulted from abundant occurrence of felsic intrusive rocks and volcanic rocks along with weak tectonic uplift and the tropical East Asian monsoon climate during the Miocene and in the present time. Despite their different clay mineralogical compositions, major elements of these Miocene sedimentary rocks and modern river sediments display stronger depletion of Ca, Na and Mg than of K and Si during the chemical weathering. The chemical index of alteration (CIA) combined with kaolinite/illite ratio demonstrated moderate chemical weathering during the Miocene and in the present time in central Vietnam, demonstrating similar tectonic activity and climatic conditions occurred during these two periods.

ABSTRACT The study of aflatoxin in Aspergillus spp. has garnered the attention of many researchers due to aflatoxin’s carcinogenic properties and frequency as a food and feed contaminant. Significant progress has been made by utilizing the model organism Aspergillus nidulans to characterize the regulation of sterigmatocystin (ST), the penultimate precursor of aflatoxin. A previous forward genetic screen identified 23 A. nidulans mutants involved in regulating ST production. Six mutants were characterized from this screen using classical mapping (five mutations in mcsA) and complementation with a cosmid library (one mutation in laeA). The remaining mutants were backcrossed and sequenced using Illumina and Ion Torrent sequencing platforms. All but one mutant contained one or more sequence variants in predicted open reading frames. Deletion of these genes resulted in identification of mutant alleles responsible for the loss of ST production in 12 of the 17 remaining mutants. Eight of these mutations were in genes already known to affect ST synthesis (laeA, mcsA, fluG, and stcA), while the remaining four mutations (in laeB, sntB, and hamI) were in previously uncharacterized genes not known to be involved in ST production. Deletion of laeB, sntB, and hamI in A. flavus results in loss of aflatoxin production, confirming that these regulators are conserved in the aflatoxigenic aspergilli. This report highlights the multifaceted regulatory mechanisms governing secondary metabolism in Aspergillus. Additionally, these data contribute to the increasing number of studies showing that forward genetic screens of fungi coupled with whole-genome resequencing is a robust and cost-effective technique. IMPORTANCE In a postgenomic world, reverse genetic approaches have displaced their forward genetic counterparts. The techniques used in forward genetics to identify loci of interest were typically very cumbersome and time-consuming, relying on Mendelian traits in model organisms. The current work was pursued not only to identify alleles involved in regulation of secondary metabolism but also to demonstrate a return to forward genetics to track phenotypes and to discover genetic pathways that could not be predicted through a reverse genetics approach. While identification of mutant alleles from whole-genome sequencing has been done before, here we illustrate the possibility of coupling this strategy with a genetic screen to identify multiple alleles of interest. Sequencing of classically derived mutants revealed several uncharacterized genes, which represent novel pathways to regulate and control the biosynthesis of sterigmatocystin and of aflatoxin, a societally and medically important mycotoxin.

Aspergillus flavus is a saprophytic soil fungus that poses a serious threat worldwide as it contaminates many food and feed crops with the carcinogenic mycotoxin called aflatoxin. This pathogen persists as sclerotia in the soil which enables fungal survival in harsh environmental conditions. Sclerotia formation by A. flavus depends on successful cell communication and hyphal fusion events. Loss of LaeA, a conserved developmental regulator in fungi, abolishes sclerotia formation in this species whereas overexpression (OE) of laeA results in enhanced sclerotia production. Here we demonstrate that sclerotia loss and inability to form heterokaryons in A. flavusΔlaeA is mediated by homologs of the Neurospora crassa ham (hyphal anastomosis) genes termed hamE-I in A. flavus. LaeA positively regulates ham gene expression and deletion of hamF, G, H, or I phenocopies ΔlaeA as demonstrated by heterokaryon and sclerotia loss and reduced aflatoxin synthesis and virulence of these mutants. Deletion of hamE showed a less severe phenotype. hamE-I homologs are positively regulated by the clock controlled transcription factor ADV-1 in N. crassa. Similarly, the ADV-1 homolog NosA regulates hamE-I expression in A. flavus, is required for sclerotial development and is itself positively regulated by LaeA. We speculate that a putative LaeA>NosA>fusion cascade underlies the previously described circadian clock regulation of sclerotia production in A. flavus.