PreTP-2L: identification of therapeutic peptides and their types using two-layer ensemble learning framework.

MOTIVATION: Therapeutic peptides play an important role in immune regulation. Recently various therapeutic peptides have been used in the field of medical research, and have great potential in the design of therapeutic schedules. Therefore, it is essential to utilize the computational methods to predict the therapeutic peptides. However, the therapeutic peptides cannot be accurately predicted by the existing predictors. Furthermore, chaotic datasets are also an important obstacle of the development of this important field. Therefore, it is still challenging to develop a multi-classification model for identification of therapeutic peptides and their types. RESULTS: In this work, we constructed a general therapeutic peptide dataset. An ensemble-learning method named PreTP-2L was developed for predicting various therapeutic peptide types. PreTP-2L consists of two layers. The first layer predicts whether a peptide sequence belongs to therapeutic peptide, and the second layer predicts if a therapeutic peptide belongs to a particular species. AVAILABILITY AND IMPLEMENTATION: A user-friendly webserver PreTP-2L can be accessed at http://bliulab.net/PreTP-2L.

sAMPpred-GAT: prediction of antimicrobial peptide by graph attention network and predicted peptide structure.

MOTIVATION: Antimicrobial peptides (AMPs) are essential components of therapeutic peptides for innate immunity. Researchers have developed several computational methods to predict the potential AMPs from many candidate peptides. With the development of artificial intelligent techniques, the protein structures can be accurately predicted, which are useful for protein sequence and function analysis. Unfortunately, the predicted peptide structure information has not been applied to the field of AMP prediction so as to improve the predictive performance. RESULTS: In this study, we proposed a computational predictor called sAMPpred-GAT for AMP identification. To the best of our knowledge, sAMPpred-GAT is the first approach based on the predicted peptide structures for AMP prediction. The sAMPpred-GAT predictor constructs the graphs based on the predicted peptide structures, sequence information and evolutionary information. The Graph Attention Network (GAT) is then performed on the graphs to learn the discriminative features. Finally, the full connection networks are utilized as the output module to predict whether the peptides are AMP or not. Experimental results show that sAMPpred-GAT outperforms the other state-of-the-art methods in terms of AUC, and achieves better or highly comparable performance in terms of the other metrics on the eight independent test datasets, demonstrating that the predicted peptide structure information is important for AMP prediction. AVAILABILITY AND IMPLEMENTATION: A user-friendly webserver of sAMPpred-GAT can be accessed at http://bliulab.net/sAMPpred-GAT and the source code is available at https://github.com/HongWuL/sAMPpred-GAT/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Differentiating the impact of fine and coarse particulate matter on cause-specific cerebrovascular mortality: An individual-level, case-crossover study.

BACKGROUND AND OBJECTIVES: Many studies suggested that short-term exposure to fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) was linked to elevated risk of cerebrovascular disease. However, little is known about the potentially differential effects of PM2.5 and PM2.5-10 on various types of cerebrovascular disease. METHODS: We collected individual cerebrovascular death records for all residents in Shanghai, China from 2005 to 2021. Residential daily air pollution data were predicted from a satellite model. The associations between particulate matters (PM) and cerebrovascular mortality were investigated by an individual-level, time-stratified, case-crossover design. The data was analyzed by the conditional logistic regression combined with the distributed lag model with a maximum lag of 7 days. Furthermore, we explored the effect modifications by sex, age and season. RESULTS: A total of 388,823 cerebrovascular deaths were included. Monotonous increases were observed for mortality of all cerebrovascular diseases except for hemorrhagic stroke. A 10 µg/m3 rise in PM2.5 was related to rises of 1.35% [95% confidence interval (CI): 1.04%, 1.66%] in mortality of all cerebrovascular diseases, 1.84% (95% CI: 1.25%, 2.44%) in ischemic stroke, 1.53% (95% CI: 1.07%, 1.99%) in cerebrovascular sequelae and 1.56% (95% CI: 1.08%, 2.05%) in ischemic stroke sequelae. The excess risk estimates per each 10 µg/m3 rise in PM2.5-10 were 1.47% (95% CI: 1.10%, 1.84%), 1.53% (95% CI: 0.83%, 2.24%), 1.93% (95% CI: 1.38%, 2.49%) and 2.22% (95% CI: 1.64%, 2.81%), respectively. The associations of both pollutants with all cerebrovascular outcomes were robust after controlling for co-pollutants. The associations were greater in females, individuals > 80 years, and during the warm season. CONCLUSIONS: Short-term exposures to both PM2.5 and PM2.5-10 may independently increase the mortality risk of cerebrovascular diseases, particularly of ischemic stroke and stroke sequelae.

Anti-HER2 scFv-nCytc-Modified Lipid-Encapsulated Oxygen Nanobubbles Prepared with Bulk Nanobubble Water for Inducing Apoptosis and Improving Photodynamic Therapy.

Bulk nanobubbles fascinate scientists because of their stability over long periods of time and their ability to carry gases, leading to numerous potential applications. Considering the hypoxic tumor microenvironment and the advantages of bulk nanobubbles, lipid-encapsulated oxygen nanobubbles are prepared from free bulk oxygen nanobubbles in this study. The obtained carrier is then modified with a protein fused with the single-chain antibody of human epidermal growth factor receptor 2 (anti-HER2 scFv) and tandem-repeat cytochrome c (anti-HER2 scFv-nCytc) to enhance tumor targeting and induce tumor apoptosis. Copper phthalocyanine is used as the photosensitizer to demonstrate how the oxygen in the nanobubbles affects the efficiency of photodynamic therapy (PDT). The combination of anti-HER2 scFv-nCytc and PDT synergistically improves the therapeutic effect and alleviates hypoxia in tumors in vivo while causing little inflammatory response. Based on the findings, bulk nanobubble water shows promise in the targeted delivery of oxygen and can be combined with antibody therapy to enhance the efficiency of PDT.

PreTP-EL: prediction of therapeutic peptides based on ensemble learning.

Therapeutic peptides are important for understanding the correlation between peptides and their therapeutic diagnostic potential. The therapeutic peptides can be further divided into different types based on therapeutic function sharing different characteristics. Although some computational approaches have been proposed to predict different types of therapeutic peptides, they failed to accurately predict all types of therapeutic peptides. In this study, a predictor called PreTP-EL has been proposed via employing the ensemble learning approach to fuse the different features and machine learning techniques in order to capture the different characteristics of various therapeutic peptides. Experimental results showed that PreTP-EL outperformed other competing methods. Availability and implementation: A user-friendly web-server of PreTP-EL predictor is available at http://bliulab.net/PreTP-EL.

TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model.

MOTIVATION: Therapeutic peptide prediction is important for the discovery of efficient therapeutic peptides and drug development. Researchers have developed several computational methods to identify different therapeutic peptide types. However, these computational methods focus on identifying some specific types of therapeutic peptides, failing to predict the comprehensive types of therapeutic peptides. Moreover, it is still challenging to utilize different properties to predict the therapeutic peptides. RESULTS: In this study, an adaptive multi-view based on the tensor learning framework TPpred-ATMV is proposed for predicting different types of therapeutic peptides. TPpred-ATMV constructs the class and probability information based on various sequence features. We constructed the latent subspace among the multi-view features and constructed an auto-weighted multi-view tensor learning model to utilize the high correlation based on the multi-view features. Experimental results showed that the TPpred-ATMV is better than or highly comparable with the other state-of-the-art methods for predicting eight types of therapeutic peptides. AVAILABILITY AND IMPLEMENTATION: The code of TPpred-ATMV is accessed at: https://github.com/cokeyk/TPpred-ATMV. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Protein nanoparticle-induced osmotic pressure gradients modify pulmonary edema through hyperpermeability in acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS), caused by noncardiogenic pulmonary edema (PE), contributes significantly to Coronavirus 2019 (COVID-19)-associated morbidity and mortality. We explored the effect of transmembrane osmotic pressure (OP) gradients in PE using a fluorescence resonance energy transfer-based Intermediate filament (IF) tension optical probe. Angiotensin-II- and bradykinin-induced increases in intracellular protein nanoparticle (PN)-OP were associated with inflammasome production and cytoskeletal depolymerization. Intracellular protein nanoparticle production also resulted in cytomembrane hyperpolarization and L-VGCC-induced calcium signals, which differed from diacylglycerol-induced calcium increment via TRPC6 activation. Both pathways involve voltage-dependent cation influx and OP upregulation via SUR1-TRPM4 channels. Meanwhile, intra/extracellular PN-induced OP gradients across membranes upregulated pulmonary endothelial and alveolar barrier permeability. Attenuation of intracellular PN, calcium signals, and cation influx by drug combinations effectively relieved intracellular OP and pulmonary endothelial nonselective permeability, and improved epithelial fluid absorption and PE. Thus, PN-OP is pivotal in pulmonary edema in ARDS and COVID-19, and transmembrane OP recovery could be used to treat pulmonary edema and develop new drug targets in pulmonary injury.

Abnormal Expression of microRNA-296-3p in Type 2 Diabetes Patients and its Role in Pancreatic ß-Cells Function by Targeting Tensin Homolog Deleted on Chromosome Ten.

Diabetes mellitus (DM), a familiar disease, is characterized by high blood glucose levels owing to insulin deficiency. Researches have suggested that the incidence rate of diabetes is increasing and it has become an important global epidemic. The type 2 diabetes mellitus (T2DM) is featured with pancreatic ß-cell loss and lack of insulin release. Nevertheless, the therapeutic methods that was helpful to improve pancreatic ß-cell damage still unclear. Previous report have revealed that tensin homolog deleted on chromosome ten (PTEN) was remarkably enhanced in serum of patients with T2DM, and the lack of PTEN may prevent function deficiency of pancreatic ß-cells in DM. However, the underlying mechanisms are rarely illustrated. Our purpose in this report was to illustrated the roles and potential mechanism of microRNA-296-3p (miR-296-3p) in uric acid (UA)-induced pancreatic ß-cell injury. The direct target of miR-296-3p was predicted and verified by dual-luciferase reporter system and TargetScan assay. Moreover, Min6 cells were induced by 5 mg/dl UA and the cell proliferation, apoptosis, and insulin release were evaluated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, flow cytometry and glucose-stimulated insulin secretion (GSIS), respectively. Quantitative reverse transcription PCR (qRT-PCR) and western blot assay were adopted to analyze the levels of miR-296-3p, PTEN and apoptosis-related proteins. TargetScan and Dual-luciferase reporter system confirmed that PTEN directly target miR-296-3p. MiR-296-3p was downregulated in UA-induced Min6 cells and the serum of type 2 diabetes patients, while PTEN was upregulated in UA-induced Min6 cells. Upregulation of miR-296-3p by mimic dramatically promoted miR-296-3p level and decreased PTEN level. Besides, PTEN was over-expressed after PTEN-plasmid transfection. UA treatment prominently decreased cell viability, promoted apoptotic cells, enhanced Bax levels, declined Bcl-2 level as well as decreased insulin release in Min6 cells. MiR-296-3p mimic significantly alleviated UA-induced pancreatic ß-cells dysfunction, and PTEN-plasmid eliminated the protective effect of miR-296-3p on insulin release, cell viability, and apoptosis of pancreatic ß-cells in UA-stimulated Min6 cells. In summary, our findings revealed that upregulation of miR-296-3p protected pancreatic ß-cells functions against UA-induced dysfunction by targeting PTEN, which provides a novel agent for type 2 diabetes treatment.

Fusion of apoptosis-related protein Cytochrome c with anti-HER-2 single-chain antibody targets the suppression of HER-2+ breast cancer.

Cancer treatment has gradually developed from toxic chemotherapy to targeted therapy with fewer side effects. Approximately 30% of breast cancer patients overexpress human epidermal growth factor receptor 2 (HER-2). Previous studies have successfully produced single-chain antibodies (scFv) targeting HER-2+ breast cancer; however, scFv have poor stability, easy aggregation and a shorter half-life, which have no significant effect on targeting therapy. Moreover, scFv has been considered as a drug delivery platform that can kill target cells by effector molecules. However, the functional killing domains of immunotoxins are mainly derived from plant or bacterial toxins, which have a large molecular weight, low tissue permeability and severe side effects. To address these concerns, we designed several apoptotic immune molecules to replace exogenous toxins using endogenous apoptosis-related protein DNA fragmentation factor 40 (DFF40) and tandem-repeat Cytochrome c base on caspase-3 responsive peptide (DEVD). Our results suggest that DFF40 or Cytc fusion scFv specifically targets HER-2 overexpressing breast cancer cells (SK-BR-3 and BT-474) rather than HER-2 negative cells (MDA-MB-231 and MCF-7). Following cellular internalization, apoptosis-related proteins inhibited tumour activity by initiating endogenous apoptosis pathways, which significantly reduced immunogenicity and toxic side effects. Therefore, we suggest that immunoapoptotic molecules may become potential drugs for targeted immunotherapy of breast cancer.

Prognostic value of olfactory evoked potentials in patients with post-infectious olfactory dysfunction.

PURPOSE: Prognostic assessment of patients with post-infectious olfactory dysfunction (PIOD) poses a challenge for clinicians. While there have been some studies on the prognostic factors of PIOD focusing on demographic factors, the aim of this study was to investigate whether event-related potentials (ERPs) could be used as a new predictor of olfactory recovery in PIOD. METHODS: This was a retrospective study involving patients who underwent olfactory examinations using Sniffin' Sticks test before treatment and after 1 year of follow-up. The responder group was defined by an increase of threshold-discrimination-identification (TDI) score of ≥ 6 points. All patients underwent ERP examination and the amplitude and latency of each wave of ERPs were recorded before treatment. RESULTS: A total of 61 patients (age 47.50 ± 11.04 years, 27 males) were analyzed. The presence of olfactory ERPs (oERPs) was greater in the responder group than in the non-responder group (P = 0.007), while that of trigeminal ERPs (tERPs) did not differ between the two groups (P = 0.346). Logistic-regression analyses showed that factors associated with improvement of subjective olfactory function were duration (OR, 1.604; 95% CI, 1.062-2.423; P = 0.025), initial threshold (odds ratio [OR], 0.043; 95% confidence interval [CI], 0.004-0.439; P = 0.008), and latency of N1 in oERPs (OR, 1.007; 95% CI, 1.001-1.013; P = 0.021). CONCLUSION: Our study shows that duration of OD, initial threshold, and latency of N1 in oERPs were associated with olfactory improvement in PIOD patients, which may provide guidance for clinicians.

Podosome formation impairs endothelial barrier function by sequestering zonula occludens proteins.

Podosomes and tight junctions (TJs) are subcellular compartments that both exist in endothelial cells and localize at cell surfaces. In contrast to the well-characterized role of TJs in maintaining cerebrovascular integrity, the specific function of endothelial podosomes remains unknown. Intriguingly, we discovered cross-talk between podosomes and TJs in human brain endothelial cells. Tight junction scaffold proteins ZO-1 and ZO-2 localize at podosomes in response to phorbol-12-myristate-13-acetate treatment. We found that both ZO proteins are essential for podosome formation and function. Rather than being derived from new protein synthesis, podosomal ZO-1 and ZO-2 are relocated from a pre-existing pool found at the peripheral plasma membrane with enhanced physical interaction with cortactin, a known protein marker for podosomes. Sequestration of ZO proteins in podosomes weakens tight junction complex formation, leading to increased endothelial cell permeability. This effect can be further attenuated by podosome inhibitor PP2. Altogether, our data revealed a novel cellular function of podosomes, specifically, their ability to negatively regulate tight junction and endothelial barrier integrity, which have been linked to a variety of cerebrovascular diseases.

ReFold-MAP: Protein remote homology detection and fold recognition based on features extracted from profiles.

Protein remote homology detection and protein fold recognition are two important tasks in protein structure and function prediction. There are three kinds of methods in this field, including the discriminative methods, the alignment methods, and the ranking methods. In this study, a new discriminative method called ReFold-MAP is proposed. The proposed method extracts comprehensive features based on three profile-based features: Motif-PSSM, ACC-PSSM, and PDT-profile. We call these features as MAP features, which incorporate the structural motif kernel information, the evolutionary information, and the sequence information. The experiments prove that ReFold-MAP outperforms other approaches. Therefore, ReFold-MAP will be a useful tool for protein remote homology detection and fold recognition.

B vitamins attenuate the epigenetic effects of ambient fine particles in a pilot human intervention trial.

Acute exposure to fine particle (PM2.5) induces DNA methylation changes implicated in inflammation and oxidative stress. We conducted a crossover trial to determine whether B-vitamin supplementation averts such changes. Ten healthy adults blindly received a 2-h, controlled-exposure experiment to sham under placebo, PM2.5 (250 µg/m3) under placebo, and PM2.5 (250 µg/m3) under B-vitamin supplementation (2.5 mg/d folic acid, 50 mg/d vitamin B6, and 1 mg/d vitamin B12), respectively. We profiled epigenome-wide methylation before and after each experiment using the Infinium HumanMethylation450 BeadChip in peripheral CD4+ T-helper cells. PM2.5 induced methylation changes in genes involved in mitochondrial oxidative energy metabolism. B-vitamin supplementation prevented these changes. Likewise, PM2.5 depleted 11.1% [95% confidence interval (CI), 0.4%, 21.7%; P = 0.04] of mitochondrial DNA content compared with sham, and B-vitamin supplementation attenuated the PM2.5 effect by 102% (Pinteraction = 0.01). Our study indicates that individual-level prevention may be used to complement regulations and control potential mechanistic pathways underlying the adverse PM2.5 effects, with possible significant public health benefit in areas with frequent PM2.5 peaks.

Impact of Systematic Factors on the Outbreak Outcomes of the Novel COVID-19 Disease in China: Factor Analysis Study.

BACKGROUND: The novel COVID-19 disease has spread worldwide, resulting in a new pandemic. The Chinese government implemented strong intervention measures in the early stage of the epidemic, including strict travel bans and social distancing policies. Prioritizing the analysis of different contributing factors to outbreak outcomes is important for the precise prevention and control of infectious diseases. We proposed a novel framework for resolving this issue and applied it to data from China. OBJECTIVE: This study aimed to systematically identify national-level and city-level contributing factors to the control of COVID-19 in China. METHODS: Daily COVID-19 case data and related multidimensional data, including travel-related, medical, socioeconomic, environmental, and influenza-like illness factors, from 343 cities in China were collected. A correlation analysis and interpretable machine learning algorithm were used to evaluate the quantitative contribution of factors to new cases and COVID-19 growth rates during the epidemic period (ie, January 17 to February 29, 2020). RESULTS: Many factors correlated with the spread of COVID-19 in China. Travel-related population movement was the main contributing factor for new cases and COVID-19 growth rates in China, and its contributions were as high as 77% and 41%, respectively. There was a clear lag effect for travel-related factors (previous vs current week: new cases, 45% vs 32%; COVID-19 growth rates, 21% vs 20%). Travel from non-Wuhan regions was the single factor with the most significant impact on COVID-19 growth rates (contribution: new cases, 12%; COVID-19 growth rate, 26%), and its contribution could not be ignored. City flow, a measure of outbreak control strength, contributed 16% and 7% to new cases and COVID-19 growth rates, respectively. Socioeconomic factors also played important roles in COVID-19 growth rates in China (contribution, 28%). Other factors, including medical, environmental, and influenza-like illness factors, also contributed to new cases and COVID-19 growth rates in China. Based on our analysis of individual cities, compared to Beijing, population flow from Wuhan and internal flow within Wenzhou were driving factors for increasing the number of new cases in Wenzhou. For Chongqing, the main contributing factor for new cases was population flow from Hubei, beyond Wuhan. The high COVID-19 growth rates in Wenzhou were driven by population-related factors. CONCLUSIONS: Many factors contributed to the COVID-19 outbreak outcomes in China. The differential effects of various factors, including specific city-level factors, emphasize the importance of precise, targeted strategies for controlling the COVID-19 outbreak and future infectious disease outbreaks.

Amyotrophic Lateral Sclerosis-associated GGGGCC repeat expansion promotes Tau phosphorylation and toxicity.

Microtubule-associated protein Tau (MAPT) and GGGGCC (G4C2) repeat expansion in chromosome 9 open reading frame 72 (C9ORF72) are the major known genetic causes of frontotemporal dementia (FTD) and other neurodegenerative diseases, such as Amyotrophic Lateral Sclerosis (ALS). Although expanded G4C2 repeats and Tau traditionally are associated with different clinical presentations, pathological and genetic studies have suggested a strong association between them. Here we demonstrate a strong genetic interaction between expanded G4C2 repeats and Tau. We found that co-expression of expanded G4C2 repeats and Tau could produce a synergistic deterioration of rough eyes, motor function, life span and neuromuscular junction morphological abnormalities in Drosophila. Mechanistically, compared with the normal allele containing (G4C2)3 repeats, the (G4C2)30 allele increased Tau phosphorylation levels and promoted Tau R406W aggregation. These results together suggest a potential crosstalk between expanded G4C2 repeats and Tau in modulating neurodegeneration.

The influence of roughness on stem cell differentiation using 3D printed polylactic acid scaffolds.

With the increase in popularity of 3D printing, an important question arises as to the equivalence between devices manufactured by standard methods vs. those presenting with identical bulk specifications, but manufactured via fused deposition modeling (FDM) printing. Using thermal imaging in conjunction with electron and atomic force microscopy, we demonstrate that large thermal gradients, whose distribution is difficult to predict, are associated with FDM printing and result in incomplete fusion and sharkskin of the printing filament. Even though these features are micro or submicron scale, and hence may not interfere with the intended function of the device, they can have a profound influence if the device comes in contact with living tissue. Dental pulp stem cells were cultured on substrates of identical dimensions, which were either printed or molded from the same PLA stock material. The cultures exhibited significant differences in plating efficiency, migration trajectory, and morphology at early times stemming from attempts by the cells to minimize cytoplasm deformation as they attempt to adhere on the printed surfaces. Even though biomineralization without dexamethasone induction was observed in all cultures at later times, different gene expression patterns were observed on the two surfaces. (Osteogenic markers were upregulated on molded substrates, while odontogenic markers were upregulated on the FDM printed surfaces.) Our results clearly indicate that the method of manufacturing is an important consideration in comparing devices, which come in contact with living tissues.

Welding fume exposure is associated with inflammation: a global metabolomics profiling study.

BACKGROUND: Increasing evidence suggests that welding fume exposure is associated with systemic inflammation. Although celluar metabolites may be associated with inflammation, there is limited information on metabolomic changes during welding fume exposure. Such changes may play an important role in the occurrence, development, and prevention of metal-associated diseases. We aim to investigate human metabolomics changes pre- and post-welding fume exposure. METHODS: This study included 52 boilermakers totally. We collected plasma samples pre- and post-shift welding fume exposure and prepared samples using the automated MicroLab STAR® system. Metabolite concentrations were measured using ultra performance liquid chromatography - tandem mass spectrometer (UPLC-MS/MS) methods. Two-way analysis of variance was used to test the significance of metabolite changes with false discovery rate correction. RESULTS: Analysis detected several metabolic changes after welding fume exposure, mainly involved in the lipid pathway [glucocorticoid class (cortisol, corticosterone, and cortisone), acylcarnitine class, and DiHOME species (9,10-DiHOME and 12,13-DiHOME)], amino acid utilization (isoleucine, proline and phenylalanine), and S-(3-hydroxypropyl) mercapturic acid (3-HPMA). These compounds are all associated with inflammation according to previous studies. Further, additive interaction effects linked smoking and 3-HPMA levels. In the metabolite set enrichment analysis for diseases, the top two disease-associated metabolite pathways were systemic inflammation-related diseases including rheumatoid arthritis and systemic lupus erythematosus. CONCLUSIONS: This global metabolomics study shows evidence that metabolite changes during welding fume exposure are closely associated with systemic inflammation. The altered metabolites detected may be potential health monitoring biomarkers for boilermakers, especially for inflammation-related disease prevention.

Circadian rhythm genes mediate fenvalerate-induced inhibition of testosterone synthesis in mouse Leydig cells.

Fenvalerate (Fen), a widely used pesticide, is known to impair male reproductive functions by mechanisms that remain to be elucidated. Recent studies indicated that circadian clock genes may play an important role in successful male reproduction. The aim of this study was to determine the effects of Fen on circadian clock genes involved in the biosynthesis of testosterone using TM3 cells derived from mouse Leydig cells. Data demonstrated that the circadian rhythm of testosterone synthesis in TM3 cells was disturbed following Fen treatment as evidenced by changes in the circadian rhythmicity of core clock genes (Bmal1, Rev-erbα, Rorα). Further, the observed altered rhythms were accompanied by increased intracellular Ca2+ levels and modified steroidogenic acute regulatory (StAR) mRNA expression. Thus, data suggested that Fen inhibits testosterone synthesis via pathways involving intracellular Ca2+ and clock genes (Bmal1, Rev-Erbα, Rorα) as well as StAR mRNA expression in TM3 cells.

Mechanisms underlying melatonin-mediated prevention of fenvalerate-induced behavioral and oxidative toxicity in zebrafish.

The neurotoxic effects attributed to the pesticide fenvalerate (FEN) are well-established. The aim of this study was to determine whether melatonin (MLT) was able to protect against FEN-induced behavior, oxidative stress, apoptosis, and neurogenesis using zebrafish (Danio rerio) model. Zebrafish exposed to 100 µg/L FEN for 120 h exhibited decreased swimming activity accompanied by downregulated expression of neurogenesis-related genes (Dlx2, Shha, Ngn1, Elavl3, and Gfap), suggesting that neurogenesis were impaired. In addition, FEN exposure significantly elevated oxidative stress as evidenced by increased malondialdehyde levels, as well as activities of Cu/Zn superoxide dismutase (Cu/Zn SOD), catalase, and glutathione peroxidase. Acridine orange staining demonstrated that embryos treated with FEN for 120 h significantly enhanced apoptosis mainly in the brain. FEN also produced upregulation of the expression of the pro-apoptotic genes (Bax, Fas, caspase 8, caspase 9, and caspase 3) and decreased expression of the anti-apoptotic gene Bcl-2. MLT significantly attenuated the FEN-mediated oxidative stress, modulated apoptotic-regulating genes, and diminished apoptotic responses. Further, MLT blocked the FEN-induced effects on swimming behavior as well as on neurogenesis-related genes. In conclusion, MLT protected against FEN-induced developmental neurotoxicity and apoptosis by inhibiting pesticide-mediated oxidative stress in zebrafish.

Mechanical dynamics in live cells and fluorescence-based force/tension sensors.

Three signaling systems play the fundamental roles in modulating cell activities: chemical, electrical, and mechanical. While the former two are well studied, the mechanical signaling system is still elusive because of the lack of methods to measure structural forces in real time at cellular and subcellular levels. Indeed, almost all biological processes are responsive to modulation by mechanical forces that trigger dispersive downstream electrical and biochemical pathways. Communication among the three systems is essential to make cells and tissues receptive to environmental changes. Cells have evolved many sophisticated mechanisms for the generation, perception and transduction of mechanical forces, including motor proteins and mechanosensors. In this review, we introduce some background information about mechanical dynamics in live cells, including the ubiquitous mechanical activity, various types of mechanical stimuli exerted on cells and the different mechanosensors. We also summarize recent results obtained using genetically encoded FRET (fluorescence resonance energy transfer)-based force/tension sensors; a new technique used to measure mechanical forces in structural proteins. The sensors have been incorporated into many specific structural proteins and have measured the force gradients in real time within live cells, tissues, and animals.