GREMA: modelling of emulated gene regulatory networks with confidence levels based on evolutionary intelligence to cope with the underdetermined problem.

MOTIVATION: Non-linear ordinary differential equation (ODE) models that contain numerous parameters are suitable for inferring an emulated gene regulatory network (eGRN). However, the number of experimental measurements is usually far smaller than the number of parameters of the eGRN model that leads to an underdetermined problem. There is no unique solution to the inference problem for an eGRN using insufficient measurements. RESULTS: This work proposes an evolutionary modelling algorithm (EMA) that is based on evolutionary intelligence to cope with the underdetermined problem. EMA uses an intelligent genetic algorithm to solve the large-scale parameter optimization problem. An EMA-based method, GREMA, infers a novel type of gene regulatory network with confidence levels for every inferred regulation. The higher the confidence level is, the more accurate the inferred regulation is. GREMA gradually determines the regulations of an eGRN with confidence levels in descending order using either an S-system or a Hill function-based ODE model. The experimental results showed that the regulations with high-confidence levels are more accurate and robust than regulations with low-confidence levels. Evolutionary intelligence enhanced the mean accuracy of GREMA by 19.2% when using the S-system model with benchmark datasets. An increase in the number of experimental measurements may increase the mean confidence level of the inferred regulations. GREMA performed well compared with existing methods that have been previously applied to the same S-system, DREAM4 challenge and SOS DNA repair benchmark datasets. AVAILABILITY AND IMPLEMENTATION: All of the datasets that were used and the GREMA-based tool are freely available at https://nctuiclab.github.io/GREMA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identification and characterization of the bacteriocin Carocin S3 from the multiple bacteriocin producing strain of Pectobacterium carotovorum subsp. carotovorum.

BACKGROUND: Pectobacterium carotovorum subsp. carotovorum belongs to the Enterobacteriaceae family, which causes soft-rot disease in numerous plants worldwide resulting in significant economic losses. Results from our previous studies showed that the strain H-rif-8-6 produces low-molecular-weight bacteriocin (LMWB) Carocin S1. Interestingly, TH22-10, the caroS1K:Tn5 insertional mutant in H-rif-8-6, loses Carocin S1 producing ability, but still produces other LMWBs which the indicator strain SP33 can detect. The SP33 is one of the many strains that are sensitive toward the cytotoxic effects of Carocin S3K, but not Carocin S1. The result revealed that H-rif-8-6 is a multiple-bacteriocin producing strain. RESULTS: In this study, a 4.1-kb DNA fragment was isolated from the chromosomal DNA of Pcc strain, H-rif-8-6, by a DNA probe using the caroS1K gene as the template. DNA sequencing and analysis by GenBank revealed two complete open reading frames (ORFs), designated ORF1 and ORF2, which were identified within the sequence fragment. ORF1 and ORF2, similar to the identified carocin S2 genes, encode the killer (Carocin S3K) and the immunity (Carocin S3I) proteins, respectively, which were homologous to the colicin E3 gene. Carocin S3K and Carocin S3I were expressed, isolated, and purified in Escherichia coli BL21 after subcloning of the expression plasmid pGS3KI or pGSK3I. SDS-PAGE analysis showed that the relative masses of Carocin S3K and Carocin S3I were 95.6 kDa and 10.2 kDa, respectively. The results reveal that Carocin S3K has higher antimicrobial and specific antimicrobial activities for Pcc along with a nuclease activity than Carocin S3I. However, Carocin S3I inhibits the activity of Carocin S3K. Interestingly, a high concentration of Carocin S3I protein is also a DNA nuclease, and Carocin S3K also inhibits its activity. CONCLUSION: This study showed that another type of bacteriocin was found in Pectobacterium carotovorum. This new type of bacteriocin, Carocin S3, has the killer protein, Carocin S3K, and the immunity protein, Carocin S3I.

Avapritinib: A Selective Inhibitor of KIT and PDGFRα that Reverses ABCB1 and ABCG2-Mediated Multidrug Resistance in Cancer Cell Lines.

The frequent occurrence of multidrug resistance (MDR) conferred by the overexpression of ATP-binding cassette (ABC) transporters ABCB1 and ABCG2 in cancer cells remains a therapeutic obstacle for scientists and clinicians. Consequently, developing or identifying modulators of ABCB1 and ABCG2 that are suitable for clinical practice is of great importance. Therefore, we have explored the drug repositioning approach to identify candidate modulators of ABCB1 and ABCG2 from tyrosine kinase inhibitors with known pharmacological properties and anticancer activities. In this study, we discovered that avapritinib (BLU-285), a potent, selective, and orally bioavailable tyrosine kinase inhibitor against mutant forms of KIT and platelet-derived growth factor receptor alpha (PDGFRA), attenuates the transport function of both ABCB1 and ABCG2. Moreover, avapritinib restores the chemosensitivity of ABCB1- and ABCG2-overexpressing MDR cancer cells at nontoxic concentrations. These findings were further supported by results of apoptosis induction assays, ATP hydrolysis assays, and docking of avapritinib in the drug-binding pockets of ABCB1 and ABCG2. Altogether, our study highlights an additional action of avapritinib on ABC drug transporters, and a combination of avapritinib with conventional chemotherapy should be further investigated in patients with MDR tumors.

The Selective Class IIa Histone Deacetylase Inhibitor TMP195 Resensitizes ABCB1- and ABCG2-Overexpressing Multidrug-Resistant Cancer Cells to Cytotoxic Anticancer Drugs.

Multidrug resistance caused by the overexpression of the ATP-binding cassette (ABC) proteins in cancer cells remains one of the most difficult challenges faced by drug developers and clinical scientists. The emergence of multidrug-resistant cancers has driven efforts from researchers to develop innovative strategies to improve therapeutic outcomes. Based on the drug repurposing approach, we discovered an additional action of TMP195, a potent and selective inhibitor of class IIa histone deacetylase. We reveal that in vitro TMP195 treatment significantly enhances drug-induced apoptosis and sensitizes multidrug-resistant cancer cells overexpressing ABCB1 or ABCG2 to anticancer drugs. We demonstrate that TMP195 inhibits the drug transport function, but not the protein expression of ABCB1 and ABCG2. The interaction between TMP195 with these transporters was supported by the TMP195-stimulated ATPase activity of ABCB1 and ABCG2, and by in silico docking analysis of TMP195 binding to the substrate-binding pocket of these transporters. Furthermore, we did not find clear evidence of TMP195 resistance conferred by ABCB1 or ABCG2, suggesting that these transporters are unlikely to play a significant role in the development of resistance to TMP195 in cancer patients.

ESA-UbiSite: accurate prediction of human ubiquitination sites by identifying a set of effective negatives.

Motivation: Numerous ubiquitination sites remain undiscovered because of the limitations of mass spectrometry-based methods. Existing prediction methods use randomly selected non-validated sites as non-ubiquitination sites to train ubiquitination site prediction models. Results: We propose an evolutionary screening algorithm (ESA) to select effective negatives among non-validated sites and an ESA-based prediction method, ESA-UbiSite, to identify human ubiquitination sites. The ESA selects non-validated sites least likely to be ubiquitination sites as training negatives. Moreover, the ESA and ESA-UbiSite use a set of well-selected physicochemical properties together with a support vector machine for accurate prediction. Experimental results show that ESA-UbiSite with effective negatives achieved 0.92 test accuracy and a Matthews's correlation coefficient of 0.48, better than existing prediction methods. The ESA increased ESA-UbiSite's test accuracy from 0.75 to 0.92 and can improve other post-translational modification site prediction methods. Availability and Implementation: An ESA-UbiSite-based web server has been established at http://iclab.life.nctu.edu.tw/iclab_webtools/ESAUbiSite/ . Contact: syho@mail.nctu.edu.tw. Supplementary information: Supplementary data are available at Bioinformatics online.

Curcumin downregulates 8-br-cAMP-induced steroidogenesis in mouse Leydig cells by suppressing the expression of Cyp11a1 and StAR independently of the PKA-CREB pathway.

Although curcumin was widely applied as a functional food for different diseases, it was found to reduce serum testosterone level and fertility in male animals by unknown molecular mechanisms. Here in our study, we investigated the possible mechanisms of curcumin-suppressed testosterone production in Leydig cells. Our enzyme immunoassay results showed that curcumin cell-autonomously suppressed ovine luteinizing hormone-stimulated testosterone production in primary Leydig cells and 8-bromo-cyclic adenosine monophosphate (8-br-cAMP)-induced progesterone production in MA-10 cells. Furthermore, our real-time PCR, Western blot, and 22R-OHC/pregnenolone supplementing experiment data demonstrated that curcumin suppressed 8-br-cAMP-induced steroidogenesis in Leydig cells by inhibiting the expression of StAR and Cyp11a1. Interestingly, our Western blot data showed that although curcumin suppressed PKA activity, it did not alter the 8-br-cAMP-induced phosphorylation of CREB. On the contrary, the real-time PCR results showed that curcumin suppressed 8-br-cAMP-induced expression of Nr5a1 and Fos, which are crucial for cAMP-stimulated StAR and Cyp11a1 expression in Leydig cells. Collectively, our data demonstrated that curcumin may suppress cAMP-induced steroidogenesis in mouse Leydig cells by down-regulating Nr5a1/Fos-controlled StAR and Cyp11a1 expression independently of the PKA-CREB signaling pathway.

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

BACKGROUND: Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. RESULTS: This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. CONCLUSIONS: The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein complexes. The characterization analysis revealed that the average numbers of beta turns and hydrogen bonds at protein-protein interfaces in high binding affinity complexes are more than those in low binding affinity complexes.

Astaxanthin protects steroidogenesis from hydrogen peroxide-induced oxidative stress in mouse Leydig cells.

Androgens, especially testosterone produced in Leydig cells, play an essential role in development of the male reproductive phenotype and fertility. However, testicular oxidative stress may cause a decline in testosterone production. Many antioxidants have been used as reactive oxygen species (ROS) scavengers to eliminate oxidative stress to protect steroidogenesis. Astaxanthin (AST), a natural extract from algae and plants ubiquitous in the marine environment, has been shown to have antioxidant activity in many previous studies. In this study, we treated primary mouse Leydig cells or MA-10 cells with hydrogen peroxide (H2O2) to cause oxidative stress. Testosterone and progesterone production was suppressed and the expression of the mature (30 kDa) form of StAR protein was down-regulated in MA-10 cells by H2O2 and cAMP co-treatment. However, progesterone production and expression of mature StAR protein were restored in MA-10 cells by a one-hour pretreatment with AST. AST also reduced ROS levels in cells so that they were lower than the levels in untreated controls. These results provide additional evidence of the potential health benefits of AST as a potential food additive to ease oxidative stress.

Kisspeptin modulates fertilization capacity of mouse spermatozoa.

Kisspeptin acts as an upstream regulator of the hypothalamus-pituitary-gonad axis, which is one of the main regulatory systems for mammalian reproduction. Kiss1 and its receptor Kiss1r (also known as G protein-coupled receptor 54 (Gpr54)) are expressed in various organs, but their functions are not well understood. The purpose of this study was to investigate the expression profiles and functions of kisspeptin and KISS1R in the reproductive tissues of imprinting control region mice. To identify the expression pattern and location of kisspeptin and KISS1R in gonads, testes and ovarian tissues were examined by immunohistochemical or immunofluorescent staining. Kisspeptin and KISS1R were expressed primarily in Leydig cells and seminiferous tubules respectively. KISS1R was specifically localized in the acrosomal region of spermatids and mature spermatozoa. Kisspeptin, but not KISS1R, was expressed in the cumulus-oocyte complex and oviductal epithelium of ovarian and oviductal tissues. The sperm intracellular calcium concentrations significantly increased in response to treatment with kisspeptin 10 in Fluo-4-loaded sperm. The IVF rates decreased after treatment of sperm with the kisspeptin antagonist peptide 234. These results suggest that kisspeptin and KISS1R might be involved in the fertilization process in the female reproductive tract. In summary, this study indicates that kisspeptin and KISS1R are expressed in female and male gametes, respectively, and in mouse reproductive tissues. These data strongly suggest that the kisspeptin system could regulate mammalian fertilization and reproduction.

Effect of Resistance Exercises on Function and Pain in Fibromyalgia: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

OBJECTIVE: This review aimed to compare the effectiveness of resistance exercise with that of other exercises in functional improvement and pain control in patients with fibromyalgia. DESIGN: PubMed, Embase, Scopus, and Cochrane databases were searched for studies published from their inception until March 2023. The following medical search heading terms were used: "resistance OR strength OR strengthening" AND "fibromyalgia." The analysis was performed using the statistical package Review Manager, version 5.4.1. RESULTS: This study reviewed 11 randomized controlled trials involving 530 patients. In comparison with no intervention, resistance exercise reduced the Fibromyalgia Impact Questionnaire total score, pain score, tender points, and depression and improved physical function. Compared with flexibility exercise, resistance exercise reduced the Fibromyalgia Impact Questionnaire total score. Compared with aerobic exercise, resistance exercise shows similar effects on pain control, reduction of tender points, and improvement of physical function. CONCLUSIONS: Compared with other exercises, resistance exercise demonstrated a more favorable effect on the Fibromyalgia Impact Questionnaire total score, and the effects on pain control, tender points, physical function, and depression were comparable. Thus, resistance exercise exhibits comparable or superior effects when compared with other interventions and more precise research is needed to confirm this conclusion. TO CLAIM CME CREDITS: Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME. CME OBJECTIVES: Upon completion of this article, the reader should be able to: (1) Appraise the effectiveness and role of resistance exercise as a treatment option for patients with fibromyalgia; (2) Differentiate the comparative effectiveness of resistance exercise in relation to other forms of exercise for patients with fibromyalgia; and (3) Identify demographic factors commonly associated with fibromyalgia. LEVEL: Advanced. ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s) ™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

R3D-BLAST: a search tool for similar RNA 3D substructures.

R3D-BLAST is a BLAST-like search tool that allows the user to quickly and accurately search against the PDB for RNA structures sharing similar substructures with a specified query RNA structure. The basic idea behind R3D-BLAST is that all the RNA 3D structures deposited in the PDB are first encoded as 1D structural sequences using a structural alphabet of 23 distinct nucleotide conformations, and BLAST is then applied to these 1D structural sequences to search for those RNA substructures whose 1D structural sequences are similar to that of the query RNA substructure. R3D-BLAST takes as input an RNA 3D structure in the PDB format and outputs all substructures of the hits similar to that of the query with a graphical display to show their structural superposition. In addition, each RNA substructure hit found by R3D-BLAST has an associated E-value to measure its statistical significance. R3D-BLAST is now available online at http://genome.cs.nthu.edu.tw/R3D-BLAST/ for public access.

Application and future perspectives of gastric cancer technology based on artificial intelligence.

Gastric cancer is among the most common cancers and the second-leading cause of death globally. A variety of artificial intelligence (AI) applications have been developed to facilitate the image-based diagnosis of gastric cancer through pathological analysis, endoscopy, and computerized tomography. This article provides an overview of these AI applications as well as suggestions pertaining to future developments in this field and their application in clinical practice.

Review of hierarchical database access control for E-medicine systems.

Key management schemes for hierarchical access control enable users who have hierarchical relationships with each other to manage their secret keys efficiently. In these schemes, the users are divided into several groups, and all groups have their own central authorities. Each central authority is responsible for setting parameters and generating user's secret keys in a hierarchical structure such that all users efficiently derive their secret keys and solve dynamic access control problems. Several key management schemes with Health Insurance Portability Accountability Act regulations were recently proposed for hierarchical access control in e-medicine systems. However, these schemes either are insecure or require a large amount of storage and heavy computations. Therefore, this study reviews and discusses hierarchical access control schemes with privacy/security regulations for medical record databases.

Correlation between facial asymmetry of skeletal class III jaw relationship and morphology of the temporomandibular joint: A cone beam computed tomography study.

Background/purpose: Facial asymmetry is a common dentofacial deformity especially in skeletal Class III jaw relation. The purpose of this study was to evaluate the condylefossa relationship of Taiwanese people in skeletal Class III jaw relation with or without facial asymmetry by CBCT image. Materials and methods: CBCT images were collected from Kaohsiung Medical University Hospital and then divided into symmetric Class III group (Menton [Mn] deviation â‰¦ 4 mm) and asymmetric Class III group (Menton [Mn] deviation > 4 mm). Maxilla deviation, upper and lower dental midline deviation, joint space, condylar axial angle and condylar volume was measured. Independent t test was used for comparison between groups, and paired t test was applied for comparison between both condyles within each group. The Pearson correlation coefficient was used to analyze the correlation between skeletal midline deviations and joint morphology. Results: No significant difference was found in joint space between groups or between sides within each group, but we can find a significant difference in axial condylar angle easurement which was greater on the non-deviation side of condyle. Significant lesser condylar volume was also found on the deviation side in asymmetric group. There had a significant positive correlation between Mn point deviation, geometric center difference and condylar volume ratio. Conclusion: These results demonstrated that in the side with greater mandibular growth potential, the axis rotation in axial plane would be greater. In the side with lesser mandibular growth potential, the total condyle volume would be lesser, even though with large variation.

Molecular Mechanism of Isocupressic Acid Supresses MA-10 Cell Steroidogenesis.

Consumption of ponderosa pine needles causes late-term abortions in cattle and is a serious poisonous plant problem in foothill and mountain rangelands. Isocupressic acid (IA) is the component of pine needles responsible for the abortifacient effect, its abortifacient effect may be due to inhibition of steroidogenesis. To investigate the more detail molecular mechanism, we used MA-10 cell, which is wild used to investigate molecular mechanism of steroidogenesis, to characterize the molecular mechanisms underlying the actions of IA in more detail. In this report, we focus on the function of IA on important steroidogenic genes, including steroidogenic acute regulatory protein (StAR), cytochrome P450 cholesterol side-chain cleavage (P450scc), and 3ß-hydroxysteroid dehydrogenase (3ß-HSD). We found that IA does not affect enzyme activities of these genes but inhibits transcription of P450scc and translation of StAR and P450scc through attenuating cAMP-PKA signaling. Thus, steroid productions of cells were suppressed.

Improvement in the metabolic markers of prediabetic subjects due to the partial substitution of Taiken9 rice by RD43 rice in their daily diet: a randomized clinical trial.

Although RD43 rice is characterized by high amounts of undigestible starch, its potential health benefits for prediabetic individuals remain unknown. Thus, the effect of regular consumption of RD43 rice on the glycemic response, body composition, and metabolic markers was investigated in a sample of 34 participants with prediabetes (aged from 32 to 68 years) who were randomly allocated to either the treatment or the control group. The first were required to consume RD43 rice (Glycemic Index [GI] = 78) containing 14.1 g of undigestible starch daily as a substitute for two meals per day while the second were given the Taiken9 rice (GI = 98) for 12 continuous weeks. The evaluations were performed at baseline, at the end of week 6 and 12, and at follow-up conducted two weeks after the intervention had ended. The results obtained at the week 12 assessment clearly showed a significant decrease in fasting plasma glucose, insulin, HbA1c, and HOMA-IR in the group that consumed RD43 rice. In addition, daily ingestion of RD43 rice markedly reduced body weight, Body Mass Index (BMI), total fat mass, and waist circumference at both week 6 and 12 compared with the baseline. When compared with the controls, the treatment group also exhibited a significant decrease in fasting plasma insulin and HOMA-IR at week 12. However, no significant inter- or intra-group differences in lipid profiles were detected. These findings suggest that RD43 rice could be a potential staple food with the capacity to improve glycemic control and body composition in prediabetic individuals.

Deep learning assessment of left ventricular hypertrophy based on electrocardiogram.

Background: Current electrocardiogram (ECG) criteria of left ventricular hypertrophy (LVH) have low sensitivity. Deep learning (DL) techniques have been widely used to detect cardiac diseases due to its ability of automatic feature extraction of ECG. However, DL was rarely applied in LVH diagnosis. Our study aimed to construct a DL model for rapid and effective detection of LVH using 12-lead ECG. Methods: We built a DL model based on convolutional neural network-long short-term memory (CNN-LSTM) to detect LVH using 12-lead ECG. The echocardiogram and ECG of 1,863 patients obtained within 1 week after hospital admission were analyzed. Patients were evenly allocated into 3 sets at 3:1:1 ratio: the training set (n = 1,120), the validation set (n = 371) and the test set 1 (n = 372). In addition, we recruited 453 hospitalized patients into the internal test set 2. Different DL model of each subgroup was developed according to gender and relative wall thickness (RWT). Results: The LVH was predicted by the CNN-LSTM model with an area under the curve (AUC) of 0.62 (sensitivity 68%, specificity 57%) in the test set 1, which outperformed Cornell voltage criteria (AUC: 0.57, sensitivity 48%, specificity 72%) and Sokolow-Lyon voltage (AUC: 0.51, sensitivity 14%, specificity 96%). In the internal test set 2, the CNN-LSTM model had a stable performance in predicting LVH with an AUC of 0.59 (sensitivity 65%, specificity 57%). In the subgroup analysis, the CNN-LSTM model predicted LVH by 12-lead ECG with an AUC of 0.66 (sensitivity 72%, specificity 60%) for male patients, which performed better than that for female patients (AUC: 0.59, sensitivity 50%, specificity 71%). Conclusion: Our study established a CNN-LSTM model to diagnose LVH by 12-lead ECG with higher sensitivity than current ECG diagnostic criteria. This CNN-LSTM model may be a simple and effective screening tool of LVH.

Cardio- and Neurotoxicity of Selected Anti-COVID-19 Drugs.

Since December 2019, the novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected ~435 million people and caused ~6 million related deaths as of March 2022. To combat COVID-19, there have been many attempts to repurpose FDA-approved drugs or revive old drugs. However, many of the current treatment options have been known to cause adverse drug reactions. We employed a population-based drug screening platform using 13 human leukocyte antigen (HLA) homozygous human induced pluripotent cell (iPSC) lines to assess the cardiotoxicity and neurotoxicity of the first line of anti-COVID-19 drugs. We also infected iPSC-derived cells to understand the viral infection of cardiomyocytes and neurons. We found that iPSC-derived cardiomyocytes express the ACE2 receptor which correlated with a higher infection of the SARS-CoV-2 virus (r = 0.86). However, we were unable to detect ACE2 expression in neurons which correlated with a low infection rate. We then assessed the toxicity of anti-COVID-19 drugs and identified two cardiotoxic compounds (remdesivir and arbidol) and four neurotoxic compounds (arbidol, remdesivir, hydroxychloroquine, and chloroquine). These data show that this platform can quickly and easily be employed to further our understanding of cell-specific infection and identify drug toxicity of potential treatment options helping clinicians better decide on treatment options.

Population-based high-throughput toxicity screen of human iPSC-derived cardiomyocytes and neurons.

In this study, we establish a population-based human induced pluripotent stem cell (hiPSC) drug screening platform for toxicity assessment. After recruiting 1,000 healthy donors and screening for high-frequency human leukocyte antigen (HLA) haplotypes, we identify 13 HLA-homozygous "super donors" to represent the population. These "super donors" are also expected to represent at least 477,611,135 of the global population. By differentiating these representative hiPSCs into cardiomyocytes and neurons we show their utility in a high-throughput toxicity screen. To validate hit compounds, we demonstrate dose-dependent toxicity of the hit compounds and assess functional modulation. We also show reproducible in vivo drug toxicity results using mouse models with select hit compounds. This study shows the feasibility of using a population-based hiPSC drug screening platform to assess cytotoxicity, which can be used as an innovative tool to study inter-population differences in drug toxicity and adverse drug reactions in drug discovery applications.

Hybrid cable television and orthogonal-frequency-division-multiplexing transport system basing on single wavelength polarization and amplitude remodulation schemes.

A hybrid community antenna television (CATV) and orthogonal-frequency-division-multiplexing (OFDM) transport system is proposed and experimentally demonstrated to transmit multiple CATV channels and bi-directional radio frequency signals on a single optical carrier. By polarization remodulating an optical CATV signal with downstream OFDM signals and then amplitude remodulating upstream OFDM signals with the hybrid CATV/OFDM signals, this architecture can efficiently utilize only one optical carrier to support optical analog/digital CATV transmission and bi-directional wireless broadband services for each client. Good experimental results prove that this architecture provides a proper wavelength utilization scheme for future multiwavelength optical transport systems.