Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke.

PURPOSE: Clinical risk scores are essential for predicting outcomes in stroke patients. The advancements in deep learning (DL) techniques provide opportunities to develop prediction applications using magnetic resonance (MR) images. We aimed to develop an MR-based DL imaging biomarker for predicting outcomes in acute ischemic stroke (AIS) and evaluate its additional benefit to current risk scores. METHOD: This study included 3338 AIS patients. We trained a DL model using deep neural network architectures on MR images and radiomics to predict poor functional outcomes at three months post-stroke. The DL model generated a DL score, which served as the DL imaging biomarker. We compared the predictive performance of this biomarker to five risk scores on a holdout test set. Additionally, we assessed whether incorporating the imaging biomarker into the risk scores improved the predictive performance. RESULTS: The DL imaging biomarker achieved an area under the receiver operating characteristic curve (AUC) of 0.788. The AUCs of the five studied risk scores were 0.789, 0.793, 0.804, 0.810, and 0.826, respectively. The imaging biomarker's predictive performance was comparable to four of the risk scores but inferior to one (p = 0.038). Adding the imaging biomarker to the risk scores improved the AUCs (p-values) to 0.831 (0.003), 0.825 (0.001), 0.834 (0.003), 0.836 (0.003), and 0.839 (0.177), respectively. The net reclassification improvement and integrated discrimination improvement indices also showed significant improvements (all p < 0.001). CONCLUSIONS: Using DL techniques to create an MR-based imaging biomarker is feasible and enhances the predictive ability of current risk scores.

Anomaly-guided weakly supervised lesion segmentation on retinal OCT images.

The availability of big data can transform the studies in biomedical research to generate greater scientific insights if expert labeling is available to facilitate supervised learning. However, data annotation can be labor-intensive and cost-prohibitive if pixel-level precision is required. Weakly supervised semantic segmentation (WSSS) with image-level labeling has emerged as a promising solution in medical imaging. However, most existing WSSS methods in the medical domain are designed for single-class segmentation per image, overlooking the complexities arising from the co-existence of multiple classes in a single image. Additionally, the multi-class WSSS methods from the natural image domain cannot produce comparable accuracy for medical images, given the challenge of substantial variation in lesion scales and occurrences. To address this issue, we propose a novel anomaly-guided mechanism (AGM) for multi-class segmentation in a single image on retinal optical coherence tomography (OCT) using only image-level labels. AGM leverages the anomaly detection and self-attention approach to integrate weak abnormal signals with global contextual information into the training process. Furthermore, we include an iterative refinement stage to guide the model to focus more on the potential lesions while suppressing less relevant regions. We validate the performance of our model with two public datasets and one challenging private dataset. Experimental results show that our approach achieves a new state-of-the-art performance in WSSS for lesion segmentation on OCT images.

Sex-based differences in ischemic cardiovascular and bleeding outcomes following implantation of drug-eluting stent in patients at high bleeding risk.

BACKGROUND: Patients with high bleeding risk (HBR) may exhibit uncertain adherence to dual antiplatelet therapy (DAPT) following drug-eluting stent (DES) implantation. The current population-based cohort study aimed to investigate the sex-based differences in adverse outcomes among the HBR population by analyzing the National Health Insurance Research Database in Taiwan. METHODS: Patients who had HBR features defined by the Academic Research Consortium (ARC) and received DES implantation between January 1, 2007, and December 31, 2017, were enrolled. Propensity score matching was adopted to select 3,981 pairs with similar clinical cardiovascular risks but different sexes. A competing risk model was performed to evaluate the risk of adverse ischemic events (cardiac death, nonfatal myocardial infarction, and ischemic stroke) and any bleeding events in both sexes. Noncardiac death was considered a competing risk. RESULTS: Within a 5-year follow-up, the incidence rates (per 1,000 person-year (95% confidence interval (CI)) of composite ischemic events and any bleeding events in males were respectively 44.09 (40.25-48.30) and 42.55 (38.79-46.68), while those in females were respectively 40.18 (36.51-44.23) and 42.35 (38.57-46.51). After adjustment for clinical variables, male patients had a marginally increased risk in the composite ischemic events (adjusted subdistribution hazard ratio (SHR) = 1.15 (1.00-1.31), p = 0.045) and a similar risk of any bleeding events (adjusted SHR = 1.00 (0.88-1.15), p = 0.946) compared with female patients. CONCLUSIONS: Of the HBR population, males had an increased risk of ischemic outcomes but a similar risk of bleeding compared with females following DES implantation.

Predicting mental and psychomotor delay in very pre-term infants using machine learning.

BACKGROUND: Very preterm infants are at elevated risk for neurodevelopmental delays. Earlier prediction of delays allows timelier intervention and improved outcomes. Machine learning (ML) was used to predict mental and psychomotor delay at 25 months. METHODS: We applied RandomForest classifier to data from 1109 very preterm infants recruited over 20 years. ML selected key predictors from 52 perinatal and 16 longitudinal variables (1-22 mo assessments). SHapley Additive exPlanations provided model interpretability. RESULTS: Balanced accuracy with perinatal variables was 62%/61% (mental/psychomotor). Top predictors of mental and psychomotor delay overlapped and included: birth year, days in hospital, antenatal MgSO4, days intubated, birth weight, abnormal cranial ultrasound, gestational age, mom's age and education, and intrauterine growth restriction. Highest balanced accuracy was achieved with 19-month follow-up scores and perinatal variables (72%/73%). CONCLUSIONS: Combining perinatal and longitudinal data, ML modeling predicted 24 month mental/psychomotor delay in very preterm infants ½ year early, allowing intervention to start that much sooner. Modeling using only perinatal features fell short of clinical application. Birth year's importance reflected a linear decline in predicting delay as birth year became more recent. IMPACT: Combining perinatal and longitudinal data, ML modeling was able to predict 24 month mental/psychomotor delay in very preterm infants ½ year early (25% of their lives) potentially advancing implementation of intervention services. Although cognitive/verbal and fine/gross motor delays require separate interventions, in very preterm infants there is substantial overlap in the risk factors that can be used to predict these delays. Birth year has an important effect on ML prediction of delay in very preterm infants, with those born more recently (1989-2009) being increasing less likely to be delayed, perhaps reflecting advances in medical practice.

A new formula to predict the size and insertion depth of cuffed nasotracheal tube in children receiving dental surgery: a retrospective study.

This retrospective study aimed to develop a new formula for selecting the appropriate size and determining the depth of the cuffed nasotracheal intubation (NTI) for a cuffed endotracheal tube (cETT) in pediatric patients undergoing dental surgery. In addition, the clinical data on cETT (i.e., the size and depth of insertion) was compared with those calculated with age-based formulas to evaluate their correlation. A total number of 684 patients who received NTI were enrolled (healthy group, n = 607; special-need group, n = 77). The ETT size used in real-world scenarios was smaller (i.e., about 0.5 and 0.94 mm) than the age-based formula, while the ETT depth was greater (i.e., about 1.5 cm) than the age-based formula in both groups. In the healthy group, age, gender, and body weight were identified as predictors of ETT size and depth through multiple linear regression analysis, while only age and body weight were predictors in the special-needs group. New formulas were developed based on these findings, with ETT size = 3.98 + 0.052 × age + 0.048 × gender (male = 1, female = 0) + 0.023 × body weight (kg) and ETT depth = 15.1 + 0.43 × age + 0.300 × gender (male = 1, female = 0) + 0.007 × body weight (kg). The new formula could be useful for both healthy and special-need pediatric populations undergoing dental procedures.

Superstorm Sandy exposure in utero is associated with neurobehavioral phenotypes and brain structure alterations in childhood: A machine learning approach.

Introduction: Prenatal maternal stress (PNMS), including exposure to natural disasters, has been shown to serve as a risk factor for future child psychopathology and suboptimal brain development, particularly among brain regions shown to be sensitive to stress and trauma exposure. However, statistical approaches deployed in most studies are usually constrained by a limited number of variables for the sake of statistical power. Explainable machine learning, on the other hand, enables the study of high data dimension and offers novel insights into the prominent subset of behavioral phenotypes and brain regions most susceptible to PNMS. In the present study, we aimed to identify the most important child neurobehavioral and brain features associated with in utero exposure to Superstorm Sandy (SS). Methods: By leveraging an explainable machine learning technique, the Shapley additive explanations method, we tested the marginal feature effect on SS exposures and examined the individual variable effects on disaster exposure. Results: Results show that certain brain regions are especially sensitive to in utero exposure to SS. Specifically, in utero SS exposure was associated with larger gray matter volume (GMV) in the right caudate, right hippocampus, and left amygdala and smaller GMV in the right parahippocampal gyrus. Additionally, higher aggression scores at age 5 distinctly correlated with SS exposure. Discussion: These findings suggest in utero SS exposure may be associated with greater aggression and suboptimal developmental alterations among various limbic and basal ganglia brain regions.

Real-World Data on Comparison of Lipid-Lowering Effects between Alirocumab and Evolocumab in Patients with Hypercholesterolemia.

Background: Even though the proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, alirocumab and evolocumab, have been approved to reduce plasma low-density lipoprotein cholesterol (LDL-C) and the risk of atherosclerotic cardiovascular disease in high-risk patients, real-world data showing comparisons of the lipid-lowering effects between alirocumab and evolocumab are scarce because of the low prescription rates of PCSK9 inhibitors in clinical practice. Methods: Between Feb 2018 and Sep 2021, 22 patients who received alirocumab and 22 patients who received evolocumab at a tertiary medical center were enrolled. The patients' baseline characteristics, prescribed medications, plasma LDL-C levels, and percentages of reduction in LDL-C were compared between alirocumab users and evolocumab users. Results: The alirocumab users more frequently received ezetimibe treatment (72.7% vs. 40.9%, p = 0.03) and had higher baseline LDL-C (165.6 ± 63.2 mg/dL vs. 130.8 ± 56.3 mg/dL, p = 0.04) compared with the evolocumab users. At 6 months of follow-up, the plasma LDL-C levels in the alirocumab users were similar to those in the evolocumab users (79.3 ± 64.0 mg/dL vs. 63.5 ± 44.1 mg/dL, p = 0.48). Additionally, the percentages of LDL-C reduction following treatment were similar between the alirocumab users and evolocumab users (-47.0% ± 45.0% vs. -49.8 ± 24.9%, p = 0.66). Conclusions: The LDL-C lowering effects of alirocumab are similar to those of evolocumab in clinical practice.

The Application of Artificial-Intelligence-Assisted Dental Age Assessment in Children with Growth Delay.

BACKGROUND: This study aimed to reveal the efficacy of the artificial intelligence (AI)-assisted dental age (DA) assessment in identifying the characteristics of growth delay (GD) in children. METHODS: The panoramic films matching the inclusion criteria were collected for the AI model training to establish the population-based DA standard. Subsequently, the DA of the validation dataset of the healthy children and the images of the GD children were assessed by both the conventional methods and the AI-assisted standards. The efficacy of all the studied modalities was compared by the paired sample t-test. RESULTS: The AI-assisted standards can provide much more accurate chronological age (CA) predictions with mean errors of less than 0.05 years, while the traditional methods presented overestimated results in both genders. For the GD children, the convolutional neural network (CNN) revealed the delayed DA in GD children of both genders, while the machine learning models presented so only in the GD boys. CONCLUSION: The AI-assisted DA assessments help overcome the long-standing populational limitation observed in traditional methods. The image feature extraction of the CNN models provided the best efficacy to reveal the nature of delayed DA in GD children of both genders.

Tafenoquine and its derivatives as inhibitors for the severe acute respiratory syndrome coronavirus 2.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has severely affected human lives around the world as well as the global economy. Therefore, effective treatments against COVID-19 are urgently needed. Here, we screened a library containing Food and Drug Administration (FDA)-approved compounds to identify drugs that could target the SARS-CoV-2 main protease (Mpro), which is indispensable for viral protein maturation and regard as an important therapeutic target. We identified antimalarial drug tafenoquine (TFQ), which is approved for radical cure of Plasmodium vivax and malaria prophylaxis, as a top candidate to inhibit Mpro protease activity. The crystal structure of SARS-CoV-2 Mpro in complex with TFQ revealed that TFQ noncovalently bound to and reshaped the substrate-binding pocket of Mpro by altering the loop region (residues 139-144) near the catalytic Cys145, which could block the catalysis of its peptide substrates. We also found that TFQ inhibited human transmembrane protease serine 2 (TMPRSS2). Furthermore, one TFQ derivative, compound 7, showed a better therapeutic index than TFQ on TMPRSS2 and may therefore inhibit the infectibility of SARS-CoV-2, including that of several mutant variants. These results suggest new potential strategies to block infection of SARS-CoV-2 and rising variants.

Diagnosis of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning.

PURPOSE: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks. METHODS: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation of PCV. RESULTS: AG-CNN is validated with a dataset containing 167 FA sequences of PCV and 70 FA sequences of CNV. AG-CNN achieves a classification accuracy of 82.80% at image-level, and 86.21% at patient-level for PCV. Grad-CAM shows that regions contributing to decision-making have on average 21.91% agreement with pathological regions identified by experts. AG-PCVNet is validated with 56 PCV sequences from the EVEREST-I study and achieves a balanced accuracy of 81.132% and dice score of 0.54. CONCLUSIONS: The developed software provides a means of performing detection and segmentation of PCV on FA images for the first time. This study is a promising step in changing the diagnostic procedure of PCV and therefore improving the detection rate of PCV using FA alone. TRANSLATIONAL RELEVANCE: The developed deep learning system enables early diagnosis of PCV using FA to assist the physician in choosing the best treatment for optimal visual prognosis.

GJB2 mutation spectrum in the Taiwanese population and genotype-phenotype comparisons in patients with hearing loss carrying GJB2 c.109G>A and c.235delC mutations.

Hearing loss, the most common sensory abnormality, is caused by the death of or damage to inner ear hair cells. Genetic mutations are the main cause of hearing loss. We used nex-generation sequencing data released by the Taiwan Biobank to investigate the GJB2 mutation spectrum in 1517 patients. We compared hearing function in Taiwanese patients with nonsyndromic hearing loss (NSHL) caused by the two most common GJB2 mutations c.109G>A (p.V37I) and c.235delC. We extracted DNA from the oral mucosa of patients with NSHL and performed Sanger sequencing to confirm the genotype. Of 240 patients with NSHL, we identified 25 with GJB2 c.109G>A and 9 with GJB2 c.235delC mutations, after excluding patients aged >10 years, in whom hearing loss may have been caused due to age-related degeneration. We investigated genotype-phenotype correlations in patients harboring GJB2 c.109G>A and c.235delC mutations. Furthermore, we described the GJB2 mutation spectrum in the Taiwanese population and identified the role of homozygous and heterozygous GJB2 mutations associated with hearing phenotypes in patients with NSHL. Thus, our study provides insights into the complexity of GJB2 genetics. Our data indicate that GJB2 c.109G>A heterozygotes had poorer hearing than did homozygotes. The mechanism underlying the more severe phenotype in heterozygotes and whether the phenotype is caused by GJB2 heterozygotes or compound heterozygotes warrant future investigation.

Real-world data on the prescription of proprotein convertase subtilisin/kexin type 9 inhibitors in high-risk patients in a tertiary medical center.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, alirocumab and evolocumab, are currently approved for clinical use by Taiwan National Health Insurance (NHI) in patients who had a recent atherosclerotic cardiovascular disease with persistent LDL-C levels >135 mg/dL despite high-intensity statin (HIS) or maximally tolerated statin in combination with ezetimibe treatment. Since January 2020 to July 2020, total of 10 patients who had received coronary revascularization received NHI-approved alirocumab or evolocumab in our institution. The mean reduction of LDL-C following PCSK9 inhibitors treatment at 6-month and 12-month were respectively 62.5% and 60.2%. The patients in our study were younger, had more frequently received HIS/ezetimibe, and had higher baseline LDL-C levels with a greater LDL-C reduction following PCSK9 inhibitors treatment compared with those patients in previously studies. Our findings highlight that the NHI's regulation of PCSK9 inhibitors application should be re-evaluation to increase the use of NHI-approved PCSK9 inhibitors in high-risk patients.

Management of Patients with Type V Hyperlipoproteinemia: An Uncommon Phenotype of Dyslipidemia with Chylomicronemia and Severe Hypertriglyceridemia.

Hypertriglyceridemia (HTG) remains a risk-enhancing factor of atherosclerotic cardiovascular disease. We aimed to report real-world data on the management of patients with type V hyperlipoproteinemia (HLP5), an uncommon phenotype of dyslipidemia characterized by fasting chylomicronemia and severe HTG. Between July 2018 and May 2021, 90 patients with HTG, including 83 patients with type IV hyperlipoproteinemia (HLP4) and 7 patients with HLP5, were identified by plasma apolipoprotein B (apoB) and lipoprotein electrophoresis. Patients with HLP5 were younger, had higher total cholesterol (TC) (264.9 ± 26.7 mg/dL vs. 183.9 ± 26.1 mg/dL; p < 0.01) and higher triglyceride (TG) (1296.7 ± 380.5 mg/dL vs. 247.6 ± 96.1 mg/dL; p < 0.01), and had lower high-density lipoprotein cholesterol (HDL-C) (30.6 ± 4.8 mg/dL vs. 40.5 ± 8.7 mg/dL; p < 0.01) and lower low-density lipoprotein cholesterol (LDL-C) (62.9 ± 16.4 vs. 103.0 ± 21.1 mg/dL; p < 0.01) compared with patients with HLP4. Despite an aggressive use of statin and fenofibrate with greater reductions in TG (-65.9 ± 13.7% vs. -27.9 ± 30.5%; p < 0.01) following 6 months of treatment, patients with HLP5 had persistent HTG (440.1 ± 239.0 mg/dL vs. 173.9 ± 94.8 mg/dL; p < 0.01) and an increase in LDL-C (28.3 ± 57.2% vs. -19.5 ± 32.0%; p < 0.01) compared with patients with HLP4. Our findings highlight that the lack of novel TG-lowering medications and management guidelines remains an unmet medical need in patients with HLP5. Closely monitoring lipid profiles, full assessment of individual's risk of cardiovascular disease, and emphasis on medication adherence are of clinical importance.

Crystal structure and functional implication of a bacterial cyclic AMP-AMP-GMP synthetase.

Mammalian cyclic GMP-AMP synthase (cGAS) and its homologue dinucleotide cyclase in Vibrio cholerae (VcDncV) produce cyclic dinucleotides (CDNs) that participate in the defense against viral infection. Recently, scores of new cGAS/DncV-like nucleotidyltransferases (CD-NTases) were discovered, which produce various CDNs and cyclic trinucleotides (CTNs) as second messengers. Here, we present the crystal structures of EcCdnD, a CD-NTase from Enterobacter cloacae that produces cyclic AMP-AMP-GMP, in its apo-form and in complex with ATP, ADP and AMPcPP, an ATP analogue. Despite the similar overall architecture, the protein shows significant structural variations from other CD-NTases. Adjacent to the donor substrate, another nucleotide is bound to the acceptor binding site by a non-productive mode. Isothermal titration calorimetry results also suggest the presence of two ATP binding sites. GTP alone does not bind to EcCdnD, which however binds to pppApG, a possible intermediate. The enzyme is active on ATP or a mixture of ATP and GTP, and the best metal cofactor is Mg2+. The conserved residues Asp69 and Asp71 are essential for catalysis, as indicated by the loss of activity in the mutants. Based on structural analysis and comparison with VcDncV and RNA polymerase, a tentative catalytic pathway for the CTN-producing EcCdnD is proposed.

Structural basis of SARS-CoV-2 main protease inhibition by a broad-spectrum anti-coronaviral drug.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or 2019 novel coronavirus (2019-nCoV), took tens of thousands of lives and caused tremendous economic losses. The main protease (Mpro) of SARS-CoV-2 is a potential target for treatment of COVID-19 due to its critical role in maturation of viral proteins and subsequent viral replication. Conceptually and technically, targeting therapy against Mpro is similar to target therapy to treat cancer. Previous studies show that GC376, a broad-spectrum dipeptidyl Mpro inhibitor, efficiently blocks the proliferation of many animal and human coronaviruses including SARS-CoV, Middle East respiratory syndrome coronavirus (MERS-CoV), porcine epidemic diarrhea virus (PEDV), and feline infectious peritonitis virus (FIPV). Due to the conservation of structure and catalytic mechanism of coronavirus main protease, repurposition of GC376 against SARS-CoV-2 may be an effective way for the treatment of COVID-19 in humans. To validate this conjecture, the binding affinity and IC50 value of Mpro with GC376 was determined by isothermal titration calorimetry (ITC) and fluorescence resonance energy transfer (FRET) assay, respectively. The results showed that GC376 binds to SARS-CoV-2 Mpro tightly (KD = 1.6 µM) and efficiently inhibit its proteolytic activity (IC50 = 0.89 µM). We also elucidate the high-resolution structure of dimeric SARS-CoV-2 Mpro in complex with GC376. The cocrystal structure showed that GC376 and the catalytic Cys145 of Mpro covalently linked through forming a hemithioacetal group and releasing a sulfonic acid group. Because GC376 is already known as a broad-spectrum antiviral medication and successfully used in animal, it will be a suitable candidate for anti-COVID-19 treatment.

Targeting protein palmitoylation decreases palmitate­induced sphere formation of human liver cancer cells.

Although non­alcoholic fatty liver disease (NAFLD) is considered a benign disorder, hepatic steatosis has been proposed to be involved in the tumorigenesis of liver cancer. However, the underlying mechanism for carcinogenesis in fatty liver diseases remains unclear. Cancer stem cells (CSCs) have been hypothesized to serve a key role in tumorigenesis. Tumor formation begins with a subset of heterogeneous cells that share properties with stem cells, such as self­renewal and undifferentiated properties. Our previous study reported that the saturated fatty acid palmitate (PA) significantly enhanced the CSC properties of the HepG2 human liver cancer cell line; however, its underlying mechanisms are unknown. In the present study, a proteomic approach was used to investigate the palmitoylation of proteins in HepG2 CSCs. CSC behavior was induced in HepG2 cells via 200 µM PA. Proteomic analysis was performed to identify post­transcriptional modifications of proteins in HepG2 CSCs in response to PA treatment. The present study identified proteins modified by palmitoylation in HepG2 CSC spheres formed following PA treatment. It was therefore hypothesized that palmitoylation may be crucial for CSC sphere formation. Furthermore, the present study demonstrated that two palmitoylation inhibitors, tunicamycin (5, 10 and 25 µg/ml) and 2­bromohexadecanoic acid (25, 50 and 150 µM), significantly decreased CSC sphere formation without affecting cell viability. An association was identified between sphere formation capacity and tumor­initiating capacity of CSCs. The results of the present study demonstrated that protein palmitoylation may influence the PA­induced CSC tumor­initiating capacity, and that the inhibition of palmitoylation may be a suitable chemopreventive strategy for treating patients with NAFLD.

Three-step two-pot automated production of NCA [18F]FDOPA with FlexLab module.

Automated three-step two-pot production of no-carrier-added (NCA) [18F]FDOPA was first implemented in the iPHASE FlexLab module. Decay-corrected radiochemical yield (RCY) of [18F]FDOPA synthesized by this method was 10~14% (n = 7) with a synthesis time of ~110 min [18F]FDOPA was obtained in > 95% of radiochemical purity with a molar activity of ~431 GBq/µmol. With the method successfully implementing on the commercial FlexLab module and its built-in step-by-step activity monitoring, further processes optimization would be achieved.

Generation of induced pluripotent stem cells MMCi001-A from a Taiwanese hearing loss patient carrying GJB2 pV37I mutation.

Hearing loss is the most common disorder in the sensory system. Mutations in GJB2 have been reported to be very common in sensorineural hearing loss patients. In this report, we generated an induced pluripotent stem cell (iPSC) line, MMCi001-A, from the peripheral blood mononuclear cells of a 4-year-old male hearing loss patient carrying GJB2 pV37I mutation by using the Sendai virus delivery system. The generated iPSCs were demonstrated to express pluripotent markers and be differentiated into three germ layers in vitro and in vivo. This GJB2-pV37I iPSCs is valuable for studying the pathogenic mechanisms and drug discovery of hearing loss.

Tannic acid suppresses SARS-CoV-2 as a dual inhibitor of the viral main protease and the cellular TMPRSS2 protease.

The cell surface protein TMPRSS2 (transmembrane protease serine 2) is an androgen-responsive serine protease important for prostate cancer progression and therefore an attractive therapeutic target. Besides its role in tumor biology, TMPRSS2 is also a key player in cellular entry by the SARS-CoV viruses. The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 has resulted in huge losses in socio-economy, culture, and human lives for which safe and effective cures are highly demanded. The main protease (Mpro/3CLpro) of SARS-CoV-2 is a critical enzyme for viral propagation in host cells and, like TMPRSS2, has been exploited for treatment of the infectious disease. Numerous natural compounds abundant in common fruits have been suggested with anti-coronavirus infection in the previous outbreaks of SARS-CoV. Here we show that screening of these compounds identified tannic acid a potent inhibitor of both SARS-CoV-2 Mpro and TMPRSS2. Molecular analysis demonstrated that tannic acid formed a thermodynamically stable complex with the two proteins at a KD of 1.1 mM for Mpro and 1.77 mM for TMPRSS2. Tannic acid inhibited the activities of the two proteases with an IC50 of 13.4 mM for Mpro and 2.31 mM for TMPRSS2. Mpro protein. Consistently, functional assays using the virus particles pseudotyped (Vpp) of SARS-CoV2-S demonstrated that tannic acid suppressed viral entry into cells. Thus, our results demonstrate that tannic acid has high potential of developing anti-COVID-19 therapeutics as a potent dual inhibitor of two independent enzymes essential for SARS-CoV-2 infection.