[Malignant Adenomyoepithelioma of the Breast:Report of One Case and Literature Review].

Malignant adenomyoepithelioma(MAME)of the breast is a rare tumor with an incidence less than 1% of primary breast cancer.The low incidence and diverse histomorphology pose challenges to the accurate diagnosis and clinical management of MAME.This paper reports a case of MAME of the breast with an intraductal papillary growth pattern and summarizes the clinical features,pathological features,diagnosis,treatment,and prognosis of MAME of the breast in the last 5 years.

3-Methyl-4-nitrophenol Exposure Deteriorates Oocyte Maturation by Inducing Spindle Instability and Mitochondrial Dysfunction.

3-methyl-4-nitrophenol (PNMC), a well-known constituent of diesel exhaust particles and degradation products of insecticide fenitrothion, is a widely distributed environmental contaminant. PNMC is toxic to the female reproductive system; however, how it affects meiosis progression in oocytes is unknown. In this study, in vitro maturation of mouse oocytes was applied to investigate the deleterious effects of PNMC. We found that exposure to PNMC significantly compromised oocyte maturation. PNMC disturbed the spindle stability; specifically, it decreased the spindle density and increased the spindle length. The weakened spindle pole location of microtubule-severing enzyme Fignl1 may result in a defective spindle apparatus in PNMC-exposed oocytes. PNMC exposure induced significant mitochondrial dysfunction, including mitochondria distribution, ATP production, mitochondrial membrane potential, and ROS accumulation. The mRNA levels of the mitochondria-related genes were also significantly impaired. Finally, the above-mentioned alterations triggered early apoptosis in the oocytes. In conclusion, PNMC exposure affected oocyte maturation and quality through the regulation of spindle stability and mitochondrial function.

Predicting multiple observations in complex systems through low-dimensional embeddings.

Forecasting all components in complex systems is an open and challenging task, possibly due to high dimensionality and undesirable predictors. We bridge this gap by proposing a data-driven and model-free framework, namely, feature-and-reconstructed manifold mapping (FRMM), which is a combination of feature embedding and delay embedding. For a high-dimensional dynamical system, FRMM finds its topologically equivalent manifolds with low dimensions from feature embedding and delay embedding and then sets the low-dimensional feature manifold as a generalized predictor to achieve predictions of all components. The substantial potential of FRMM is shown for both representative models and real-world data involving Indian monsoon, electroencephalogram (EEG) signals, foreign exchange market, and traffic speed in Los Angeles Country. FRMM overcomes the curse of dimensionality and finds a generalized predictor, and thus has potential for applications in many other real-world systems.

DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies.

MOTIVATION: The prediction of cancer drug response is a challenging subject in modern personalized cancer therapy due to the uncertainty of drug efficacy and the heterogeneity of patients. It has been shown that the characteristics of the drug itself and the genomic characteristics of the patient can greatly influence the results of cancer drug response. Therefore, accurate, efficient, and comprehensive methods for drug feature extraction and genomics integration are crucial to improve the prediction accuracy. RESULTS: Accurate prediction of cancer drug response is vital for guiding the design of anticancer drugs. In this study, we propose an end-to-end deep learning model named DeepAEG which is based on a complete-graph update mode to predict IC50. Specifically, we integrate an edge update mechanism on the basis of a hybrid graph convolutional network to comprehensively learn the potential high-dimensional representation of topological structures in drugs, including atomic characteristics and chemical bond information. Additionally, we present a novel approach for enhancing simplified molecular input line entry specification data by employing sequence recombination to eliminate the defect of single sequence representation of drug molecules. Our extensive experiments show that DeepAEG outperforms other existing methods across multiple evaluation parameters in multiple test sets. Furthermore, we identify several potential anticancer agents, including bortezomib, which has proven to be an effective clinical treatment option. Our results highlight the potential value of DeepAEG in guiding the design of specific cancer treatment regimens.

The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the "Relatively Static Management" COVID-19 Strategy: A Perspective of Network Analysis.

Background: Suicidality is a global public health problem which has increased considerably during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the inter-relationships between depressive symptoms and suicidality using network analysis among Macau residents after the "relatively static management" COVID-19 strategy. Methods: An assessment of suicidal ideation (SI), suicide plan (SP), suicide attempt (SA) and depressive symptoms was conducted with the use of individual binary response items (yes/no) and Patient Health Questionnaire (PHQ-9). In the network analysis, central and bridge symptoms were identified in the network through "Expected Influence" and "Bridge Expected Influence", and specific symptoms that were directly associated with suicidality were identified via the flow function. Network Comparison Tests (NCT) were conducted to examine the gender differences in network characteristics. Results: The study sample included a total of 1008 Macau residents. The prevalence of depressive symptoms and suicidality were 62.50% (95% CI = 59.4-65.5%) and 8.9% (95% CI = 7.2-10.9%), respectively. A network analysis of the sample identified SI ("Suicidal ideation") as the most central symptom, followed by SP ("Suicide plan") and PHQ4 ("Fatigue"). SI ("Suicidal ideation") and PHQ6 ("Guilt") were bridge nodes connecting depressive symptoms and suicidality. A flow network revealed that the strongest connection was between S ("Suicidality") and PHQ6 ("Guilt"), followed by S ("Suicidality") and PHQ 7 ("Concentration"), and S ("Suicidality") and PHQ3 ("Sleep"). Conclusion: The findings indicated that reduction of specific depressive symptoms and suicidal thoughts may be relevant in decreasing suicidality among adults. Further, suicide assessment and prevention measures should address the central and bridge symptoms identified in this study.

Depression, anxiety and suicidality among Chinese mental health professionals immediately after China's dynamic zero-COVID policy: A network perspective.

BACKGROUND: Using network analysis, the interactions between mental health problems at the symptom level can be explored in depth. This study examined the network structure of depressive and anxiety symptoms and suicidality among mental health professionals after the end of China's Dynamic Zero-COVID Policy. METHODS: A total of 10,647 mental health professionals were recruited nationwide from January to February 2023. Depression and anxiety were assessed using the 9-item Patient Health Questionnaire (PHQ-9) and 7-item Generalized Anxiety Disorder Scale (GAD-7), respectively, while suicidality was defined by a 'yes' response to any of the standard questions regarding suicidal ideation (SI), suicide plan (SP) and suicide attempt (SA). Expected Influence (EI) and Bridge Expected Influence (bEI) were used as centrality indices in the symptom network to characterize the structure of the symptoms. RESULTS: The prevalence of depression, anxiety, and suicidality were 45.99 %, 28.40 %, and 7.71 %, respectively. The network analysis identified GAD5 ("Restlessness") as the most central symptom, followed by PHQ4 ("Fatigue") and GAD7 ("Feeling afraid"). Additionally, PHQ6 ("Guilt"), GAD5 ("Restlessness"), and PHQ8 ("Motor disturbance") were bridge nodes linking depressive and anxiety symptoms with suicidality. The flow network indicated that the strongest connections of S ("Suicidality") was with PHQ6 ("Guilt"), GAD7 ("Feeling afraid"), and PHQ2 ("Sad mood"). CONCLUSIONS: Depression, anxiety, and suicidality among mental health professionals were highly prevalent after China's Dynamic Zero-COVID Policy ended. Effective measures should target central and bridge symptoms identified in this network model to address the mental health problems in those at-risk.

Efficient biosynthesis of prunin in methanol cosolvent system by an organic solvent-tolerant α-L-rhamnosidase from Spirochaeta thermophila.

Prunin of desirable bioactivity and bioavailability can be transformed from plant-derived naringin by the key enzyme α-L-rhamnosidase. However, the production was limited by unsatisfactory properties of α-L-rhamnosidase such as thermostability and organic solvent tolerance. In this study, biochemical characteristics, and hydrolysis capacity of a novel α-L-rhamnosidase from Spirochaeta thermophila (St-Rha) were investigated, which was the first characterized α-L-rhamnosidase for Spirochaeta genus. St-Rha showed a higher substrate specificity towards naringin and exhibited excellent thermostability and methanol tolerance. The Km of St-Rha in the methanol cosolvent system was decreased 7.2-fold comparing that in the aqueous phase system, while kcat/Km value of St-Rha was enhanced 9.3-fold. Meanwhile, a preliminary conformational study was implemented through comparative molecular dynamics simulation analysis to explore the mechanism underlying the methanol tolerance of St-Rha for the first time. Furthermore, the catalytic ability of St-Rha for prunin preparation in the 20% methanol cosolvent system was explored, and 200 g/L naringin was transformed into 125.5 g/L prunin for 24 h reaction with a corresponding space-time yield of 5.2 g/L/h. These results indicated that St-Rha was a novel α-L-rhamnosidase suitable for hydrolyzing naringin in the methanol cosolvent system and provided a better alternative for improving the efficient production yield of prunin.

A comparison of psychiatric symptoms between mental health professionals with and without post-infection sequelae of COVID-19.

Post-infection sequelae of COVID-19 (PISC) have raised public health concerns. However, it is not clear whether infected mental health professionals (MHPs) with PISC have experienced more psychiatric symptoms than MHPs without PISC do. This study examined differences in the prevalence of self-reported depression, anxiety, insomnia and suicidality as well as the network structures of these symptoms between these two groups. Participants completed questionnaire measures of psychiatric symptoms and demographics. Expected influence was used to measure centrality of symptoms and network comparison tests were adopted to compare differences in the two network models. The sample comprised 2,596 participants without PISC and 2,573 matched participants with PISC. MHPs with PISC had comparatively higher symptom levels related to depression (55.2% vs. 23.5 %), anxiety (32.0% vs. 14.9 %), insomnia (43.3% vs. 17.3 %), and suicidality (9.6% vs. 5.3 %). PHQ4 ("Fatigue"), PHQ6 ("Guilt"), and GAD2 ("Uncontrollable Worrying") were the most central symptoms in the "without PISC" network model. Conversely, GAD3 ("Worry too much"), GAD5 ("Restlessness"), and GAD4 ("Trouble relaxing") were more central in the "with PISC" network model. In sum, MHPs with PISC experienced comparatively more psychiatric symptoms and related disturbances. Network results provide foundations for the expectation that MHPs with PISC may benefit from interventions that address anxiety-related symptoms, while those without PISC may benefit from interventions targeting depression-related symptoms.

Prevalence and network structure of post-traumatic stress symptoms and their association with suicidality among Chinese mental health professionals immediately following the end of China's Dynamic Zero-COVID Policy: a national survey.

Studies on post-traumatic stress symptoms (PTSS) among mental health professionals (MHPs) are limited, particularly since restrictions due to coronavirus disease (COVID-19) have been lifted such as the recent termination of China's Dynamic Zero-COVID Policy. The current study filled this gap by exploring the prevalence, correlates, and network structure of PTSS as well as its association with suicidality from a network analysis perspective. A cross-sectional, national survey was conducted using a convenience sampling method on MHPs between January 22 and February 10, 2023. PTSS were assessed using the Post-Traumatic Stress Disorder Checklist-Civilian version, while suicidality was assessed using standardized questions related to ideation, plans, and attempts. Univariate and multivariate analyses examined correlates of PTSS. Network analysis explored the structure of PTSS and suicidality. The centrality index of "Expected influence" was used to identify the most central symptoms in the network, reflecting the relative importance of each node in the network. The "flow" function was adopted to identify specific symptoms that were directly associated with suicidality. A total of 10,647 MHPs were included. The overall rates of PTSS and suicidality were 6.7% (n = 715; 95% CI = 6.2-7.2%) and 7.7% (n = 821; 95% CI = 7.2-8.2%), respectively. Being married (OR = 1.523; P < 0.001), quarantine experience (OR = 1.288; P < 0.001), suicidality (OR = 3.750; P < 0.001) and more severe depressive symptoms (OR = 1.229; P < 0.001) were correlates of more PTSS. Additionally, higher economic status (e.g., good vs. poor: OR = 0.324; P = 0.001) and health status (e.g., good vs. poor: OR = 0.456; P < 0.001) were correlates of reduced PTSS. PCL6 ("Avoiding thoughts"; EI = 1.189), PCL7 ("Avoiding reminders"; EI = 1.157), and PCL11 ("Feeling emotionally numb"; EI = 1.074) had the highest centrality, while PCL12 ("Negative belief"), PCL 16 ("Hypervigilance") and PCL 14 ("Irritability") had the strongest direct, positive associations with suicidality. A high prevalence of lingering PTSS was found among MHPs immediately after China's "Dynamic Zero-COVID Policy" was terminated. Avoidance and hyper-arousal symptoms should be monitored among at-risk MHPs after the COVID-19 pandemic and serve as potential targets for the prevention and treatment of PTSS in this population.

Bioleaching of metals from spent fluid catalytic cracking catalyst using adapted Acidithiobacillus caldus.

In this study, an adapted bioleaching strain of Acidithiobacillus caldus UVS10 was successfully developed. Batch tests and tests in bioreactor were conducted to evaluate the metals bioleaching performance of A. caldus UVS10 to spent FCC catalyst (SFCCC). Results of batch experiments showed the bioleaching efficiency of Ni, V, La, and Ce in SFCCC reached 19.40%, 22.06%, 53.75%, and 59.56%, respectively. High SFCCC pulp density inhibited the leaching of metals. Sb leaching was inhibited in acidic environment caused by A. caldus UVS10. Contents of Ni, V, La, and Ce in extracellular polymeric substances (EPS) were significantly higher than those intracellular. Accumulation of metal in EPS and cytosol increased with the increase of SFCCC pulp density. V was less intercepted by EPS than Ni, La, and Ce, because of lower toxicity. Experimental results in bioreactor showed that Ni, V, La, and Ce could be effectively leached by A. caldus UVS10 under 10% pulp density. The aeration and stirring operating environment in bioreactor improved the leaching efficiency of metals in SFCCC. After bioleached in bioreactor, the available fraction content of four metals in SFCCC decreased significantly. Ecological risk analysis demonstrated the environmental risks of bioleached SFCCC were significantly lower than raw SFCCC. Different reaction kinetic models were used to represent metals leaching behavior under bioleaching of A. caldus UVS10, leaching of La and Ce showed good agreement with the product layer diffusion model, while Ni and V leaching kinetics fit well with the surface chemical reaction models.

Prevalence of insomnia and its association with quality of life in caregivers of psychiatric inpatients during the COVID-19 pandemic: a network analysis.

BACKGROUND: Studies on sleep problems among caregivers of psychiatric patients, especially during the COVID-19 pandemic, are limited. This study examined the prevalence and correlates of insomnia symptoms (insomnia hereafter) among caregivers of psychiatric inpatients during the COVID-19 pandemic as well as the association with quality of life (QoL) from a network analysis perspective. METHODS: A multi-center cross-sectional study was conducted on caregivers of inpatients across seven tertiary psychiatric hospitals and psychiatric units of general hospitals. Network analysis explored the structure of insomnia using the R program. The centrality index of "Expected influence" was used to identify central symptoms in the network, and the "flow" function was adopted to identify specific symptoms that were directly associated with QoL. RESULTS: A total of 1,101 caregivers were included. The overall prevalence of insomnia was 18.9% (n = 208; 95% CI = 16.7-21.3%). Severe depressive (OR = 1.185; P < 0.001) and anxiety symptoms (OR = 1.099; P = 0.003), and severe fatigue (OR = 1.320; P < 0.001) were associated with more severe insomnia. The most central nodes included ISI2 ("Sleep maintenance"), ISI7 ("Distress caused by the sleep difficulties") and ISI1 ("Severity of sleep onset"), while "Sleep dissatisfaction" (ISI4), "Distress caused by the sleep difficulties" (ISI7) and "Interference with daytime functioning" (ISI5) had the strongest negative associations with QoL. CONCLUSION: The insomnia prevalence was high among caregivers of psychiatric inpatients during the COVID-19 pandemic, particularly in those with depression, anxiety and fatigue. Considering the negative impact of insomnia on QoL, effective interventions that address insomnia and alteration of sleep dissatisfaction should be developed.

Prevalence of COVID-19 fear and its association with quality of life and network structure among Chinese mental health professionals after ending China's dynamic zero-COVID policy: a national survey.

Background: China recorded a massive COVID-19 pandemic wave after ending its Dynamic Zero-COVID Policy on January 8, 2023. As a result, mental health professionals (MHPs) experienced negative mental health consequences, including an increased level of fear related to COVID-19. This study aimed to explore the prevalence and correlates of COVID-19 fear among MHPs following the end of the Policy, and its association with quality of life (QoL) from a network analysis perspective. Methods: A cross-sectional national study was conducted across China. The correlates of COVID-19 fear were examined using both univariate and multivariate analyses. An analysis of covariance (ANCOVA) was conducted to determine the relationship between fear of COVID-19 and QoL. Central symptoms were identified using network analysis through the "Expected Influence" of the network model while specific symptoms directly correlated with QoL were identified through the "flow function." Results: A total of 10,647 Chinese MHPs were included. The overall prevalence of COVID-19 fear (FCV-19S total score ≥ 16) was 60.8% (95% CI = 59.9-61.8%). The binary logistic regression analysis found that MHPs with fear of COVID-19 were more likely to be married (OR = 1.198; p < 0.001) and having COVID-19 infection (OR = 1.235; p = 0.005) and quarantine experience (OR = 1.189; p < 0.001). Having better economic status (good vs. poor: OR = 0.479; p < 0.001; fair vs. poor: OR = 0.646; p < 0.001) and health status (good vs. poor: OR = 0.410; p < 0.001; fair vs. poor: OR = 0.617; p < 0.001) were significantly associated with a lower risk of COVID-19 fear. The ANCOVA showed that MHPs with fear of COVID-19 had lower QoL [F = 228.0, p < 0.001]. "Palpitation when thinking about COVID-19" was the most central symptom in the COVID-19 fear network model, while "Uncomfortable thinking about COVID-19" had the strongest negative association with QoL (average edge weight = -0.048). Conclusion: This study found a high prevalence of COVID-19 fear among Chinese MHPs following the end of China's Dynamic Zero-COVID Policy. Developing effective prevention and intervention measures that target the central symptoms as well as symptoms correlated with QoL in our network structure would be important to address COVID-19 fear and improve QoL.

Research on the crisis propagation in the global coal trade under the Russia-Ukraine conflict.

The outbreak of the 2022 Russia-Ukraine conflict exacerbated the natural gas supply shortage in European countries. European countries restarted coal-fired power plants to maintain economic and social operations. The uneven distribution of coal resources in the world makes coal international trade inevitable. The intricate trade relations between trading countries have formed a coal trade network. When a country's coal exports are limited due to geopolitical factors, it will cause coal supply risks. The risk will spread to more countries along the trade network, eventually leading to the collapse of the trade network. This paper builds a crisis propagation model of the coal supply under the Russia-Ukraine conflict using the cascading failure model. The results showed that the Czech Republic, Ireland, Portugal, and Bulgaria become abnormal as the proportion of coal exports ß increases. When the Russian Federation reduced its coal exports by 80% and countries maintained only 10% coal exports against crisis, 23 European countries were the worst. Iceland, Ireland, Turkey and other countries were spread by the indirect risk and became abnormal countries. The Czech Republic and Bulgaria were spread by multiple risk and became abnormal countries.

Prevalence, correlates, and network analysis of depression and its associated quality of life among ophthalmology nurses during the COVID-19 pandemic.

Background: Nurses in Ophthalmology Department (OD) had a high risk of infection during the novel coronavirus disease 2019 (COVID-19) pandemic. This study examined the prevalence, correlates, and network structure of depression, and explored its association with quality of life (QOL) in Chinese OD nurses. Methods: Based on a cross-sectional survey, demographic and clinical data were collected. Depression was measured with the 9-item Self-reported Patient Health Questionnaire (PHQ-9), and QOL was measured using the World Health Organization Quality of Life Questionnaire-brief version (WHOQOL-BREF). Univariate analyses, multivariate logistic regression analyses, and network analyses were performed. Results: Altogether, 2,155 OD nurses were included. The overall prevalence of depression among OD nurses was 32.71% (95%CI: 30.73-34.70%). Multiple logistic regression analysis revealed that having family or friends or colleagues who were infected (OR = 1.760, p = 0.003) was significantly associated with higher risk of depression. After controlling for covariates, nurses with depression reported lower QOL (F(1, 2,155) = 596.784, p < 0.001) than those without depression. Network analyses revealed that 'Sad Mood', 'Energy Loss' and 'Worthlessness' were the key central symptoms. Conclusion: Depression was common among OD nurses during the COVID-19 pandemic. Considering the negative impact of depression on QOL and daily life, regular screening for depression, timely counselling service, and psychiatric treatment should be provided for OD nurses, especially those who had infected family/friends or colleagues. Central symptoms identified in network analysis should be targeted in the treatment of depression.

Genome-Wide Survey of the RWP-RK Gene Family in Cassava (Manihot esculenta Crantz) and Functional Analysis.

The plant-specific RWP-RK transcription factor family plays a central role in the regulation of nitrogen response and gametophyte development. However, little information is available regarding the evolutionary relationships and characteristics of the RWP-RK family genes in cassava, an important tropical crop. Herein, 13 RWP-RK proteins identified in cassava were unevenly distributed across 9 of the 18 chromosomes (Chr), and these proteins were divided into two clusters based on their phylogenetic distance. The NLP subfamily contained seven cassava proteins including GAF, RWP-RK, and PB1 domains; the RKD subfamily contained six cassava proteins including the RWP-RK domain. Genes of the NLP subfamily had a longer sequence and more introns than the RKD subfamily. A large number of hormone- and stress-related cis-acting elements were found in the analysis of RWP-RK promoters. Real-time quantitative PCR revealed that all MeNLP1-7 and MeRKD1/3/5 genes responded to different abiotic stressors (water deficit, cold temperature, mannitol, polyethylene glycol, NaCl, and H2O2), hormonal treatments (abscisic acid and methyl jasmonate), and nitrogen starvation. MeNLP3/4/5/6/7 and MeRKD3/5, which can quickly and efficiently respond to different stresses, were found to be important candidate genes for further functional assays in cassava. The MeRKD5 and MeNLP6 proteins were localized to the cell nucleus in tobacco leaf. Five and one candidate proteins interacting with MeRKD5 and MeNLP6, respectively, were screened from the cassava nitrogen starvation library, including agamous-like mads-box protein AGL14, metallothionein 2, Zine finger FYVE domain containing protein, glyceraldehyde-3-phosphate dehydrogenase, E3 Ubiquitin-protein ligase HUWE1, and PPR repeat family protein. These results provided a solid basis to understand abiotic stress responses and signal transduction mediated by RWP-RK genes in cassava.

CEACAM1 as a molecular target in oral cancer.

OBJECTIVE: The majority of oral cancer is caused by malignant transformation of squamous cells in surface of the oral mucosa. However, the relationship between CEACAM1 and oral cancer is unclear. METHODS: GSE23558 and GSE25099 profiles were downloaded from gene expression omnibus (GEO). Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. Construction and analysis of protein-protein interaction (PPI) Network. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG), gene set enrichment analysis (GSEA), gene expression heatmap, immune infiltration analysis, comparative toxicogenomics database (CTD) were performed. TargetScan screened miRNAs that regulated central DEGs. Western blotting (WB) experiment was performed. RESULTS: 1269 DEGs were identified. According to GO analysis, they were mainly enriched in same protein binding, signal receptor binding, cell surface, epithelial cell development. KEGG analysis showed that they were mainly enriched in cancer pathways, PI3K Akt signaling pathway, TNF signaling pathway, NF kappa B signaling pathway, TGF beta signaling pathway. PPI network showed that 11 genes (CDCA8, CCNA2, MELK, KIF2C, CDC45, HMMR, TPX2, CENPF, CDK1, CEP55, CEACAM1) were obtained. Gene expression heatmap showed that CEP55 and MELK were highly expressed in oral cancer samples. CEACAM1 was lowly expressed in oral cancer samples. CEACAM1, CEP55 and MELK were involved in tumor, inflammation, necrosis, and proliferation. Western blotting (WB) showed that CEACAM1 in oral cancer samples was lower than that in normal samples, after CEACAM1 knockdown, it was lower than that in oral cancer samples. CONCLUSION: CEACAM1 is lowly expressed in oral cancer, the lower CEACAM1, the worse prognosis.

TET Family Members Are Integral to Porcine Oocyte Maturation and Parthenogenetic Pre-Implantation Embryogenesis.

The ten-eleven translocation (TET) enzyme family, which includes TET1/2/3, participates in active DNA demethylation in the eukaryotic genome; moreover, TET1/2/3 are functionally redundant in mice embryos. However, the combined effect of TET1/2/3 triple-gene knockdown or knockout on the porcine oocytes or embryos is still unclear. In this study, using Bobcat339, a specific small-molecule inhibitor of the TET family, we explored the effects of TET enzymes on oocyte maturation and early embryogenesis in pigs. Our results revealed that Bobcat339 treatment blocked porcine oocyte maturation and triggered early apoptosis. Furthermore, in the Bobcat339-treated oocytes, spindle architecture and chromosome alignment were disrupted, probably due to the huge loss of 5-hydroxymethylcytosine (5hmC)and concurrent increase in 5-methylcytosine (5mC). After Bobcat339 treatment, early parthenogenetic embryos exhibited abnormal 5mC and 5hmC levels, which resulted in compromised cleavage and blastocyst rate. The mRNA levels of EIF1A and DPPA2 (ZGA marker genes) were significantly decreased, which may explain why the embryos were arrested at the 4-cell stage after Bobcat339 treatment. In addition, the mRNA levels of pluripotency-related genes OCT4 and NANOG were declined after Bobcat339 treatment. RNA sequencing analysis revealed differentially expressed genes in Bobcat339-treated embryos at the 4-cell stage, which were significantly enriched in cell proliferation, cell component related to mitochondrion, and cell adhesion molecule binding. Our results indicated that TET proteins are essential for porcine oocyte maturation and early embryogenesis, and they act by mediating 5mC/5hmC levels and gene transcription.

Ethyl caffeate attefnuates Aß-induced toxicity in Caenorhabditis elegans AD models via the insulin/insulin-like growth factor-1 signaling pathway.

The pathogenesis of Alzheimer's disease (AD), a multifactorial progressive neurodegenerative disease associated with aging, is unclear. Ethyl caffeate is a plant polyphenol that has been reported to have neuroprotective effects, but the mechanisms by which it acts are unclear. In this study, for the first time, we investigated the molecular mechanism of its anti-AD properties using the Caernorhabditis elegans model. The results of our experiments showed that ethyl caffeate delayed the paralysis symptoms of CL4176 to a different extent and reduced the exogenous 5-hydroxytryptophan-induced paralysis phenotype. Further studies revealed that ethyl caffeate lowered Aß plaques and depressed the expression of Aß monomers and oligomers, but did not influence the mRNA levels of Aß. Moreover, it was able to bring paraquat-induced ROS levels down to near-standard conditions. Real-time quantitative PCR experiment showed a significant upregulation of the transcript abundance of daf-16, skn-1 and hsf-1, key factors associated with the insulin/insulin-like growth factor 1 (IGF-1) signaling pathway (IIS), and their downstream genes sod-3, gst-4 and hsp-16.2. It was further shown that ethyl caffeate activated the translocation of DAF-16 and SKN-1 from the cytoplasm to the nucleus and enhanced the expression of sod-3::GFP, gst-4::GFP and hsp-16.2::GFP in transgenic nematodes. This meant that the protection against Aß toxicity by ethyl caffeate may be partly through the IIS signaling pathway. In addition, ethyl caffeate suppressed the aggregation of polyglutamine proteins in AM141, which indicated a potential protective effect against neurodegenerative diseases based on abnormal folding and aggregation of amyloid proteins. Taken together, ethyl caffeate is expected to develop as a potential drug for the management of AD.

Accurate Full-Dimensional Global Diabatic Potential Energy Matrix for the Two Lowest-Lying Electronic States of the H + O2 ↔ HO + O Reaction.

A new and more accurate diabatic potential energy matrix (DPEM) is developed for the two lowest-lying electronic states of HO2, covering both the strong interaction region and reaction asymptotes. The ab initio calculations were performed at the Davidson corrected multireference configuration interaction level with the augmented correlation-consistent polarized valence quintuple-zeta basis set (MRCI+Q/AV5Z). The accuracy of the electronic structure calculations is validated by excellent agreement with the experimental HO2 equilibrium geometry, fundamental vibrational frequencies, and H + O2 ↔ OH + O reaction energy. Through the combination of an electronic angular momentum-method and a configuration interaction vector-based method, the mixing angle between the first two 2A″ states of HO2 was successfully determined. Elements of the 2×2 DPEM were fit to neural networks with a proper account of the complete nuclear permutation inversion symmetry of HO2. The DPEM correctly predicted the properties of conical intersection seams at linear and T-shape geometries, thus providing a reliable platform for studying both the spectroscopy of HO2 and the nonadiabatic dynamics for the H + O2 ↔ OH + O reaction.

Extraction, Modification and Biomedical Application of Agarose Hydrogels: A Review.

Numerous compounds present in the ocean are contributing to the development of the biomedical field. Agarose, a polysaccharide derived from marine red algae, plays a vital role in biomedical applications because of its reversible temperature-sensitive gelling behavior, excellent mechanical properties, and high biological activity. Natural agarose hydrogel has a single structural composition that prevents it from adapting to complex biological environments. Therefore, agarose can be developed into different forms through physical, biological, and chemical modifications, enabling it to perform optimally in different environments. Agarose biomaterials are being increasingly used for isolation, purification, drug delivery, and tissue engineering, but most are still far from clinical approval. This review classifies and discusses the preparation, modification, and biomedical applications of agarose, focusing on its applications in isolation and purification, wound dressings, drug delivery, tissue engineering, and 3D printing. In addition, it attempts to address the opportunities and challenges associated with the future development of agarose-based biomaterials in the biomedical field. It should help to rationalize the selection of the most suitable functionalized agarose hydrogels for specific applications in the biomedical industry.