Transformer-based AI technology improves early ovarian cancer diagnosis using cfDNA methylation markers.

Epithelial ovarian cancer (EOC) is the deadliest women's cancer and has a poor prognosis. Early detection is the key for improving survival (a 5-year survival rate in stage I/II is over 70% compared to that of 25% in stage III/IV) and can be achieved through methylation markers from circulating cell-free DNA (cfDNA) using a liquid biopsy. In this study, we first identify top 500 EOC markers differentiating EOC from healthy female controls from 3.3 million methylome-wide CpG sites and validated them in 1,800 independent cfDNA samples. We then utilize a pretrained AI transformer system called MethylBERT to develop an EOC diagnostic model which achieves 80% sensitivity and 95% specificity in early-stage EOC diagnosis. We next develop a simple digital droplet PCR (ddPCR) assay which archives good performance, facilitating early EOC detection.

Gut microbiota-derived tryptamine and phenethylamine impair insulin sensitivity in metabolic syndrome and irritable bowel syndrome.

The incidence of metabolic syndrome is significantly higher in patients with irritable bowel syndrome (IBS), but the mechanisms involved remain unclear. Gut microbiota is causatively linked with the development of both metabolic dysfunctions and gastrointestinal disorders, thus gut dysbiosis in IBS may contribute to the development of metabolic syndrome. Here, we show that human gut bacterium Ruminococcus gnavus-derived tryptamine and phenethylamine play a pathogenic role in gut dysbiosis-induced insulin resistance in type 2 diabetes (T2D) and IBS. We show levels of R. gnavus, tryptamine, and phenethylamine are positively associated with insulin resistance in T2D patients and IBS patients. Monoassociation of R. gnavus impairs insulin sensitivity and glucose control in germ-free mice. Mechanistically, treatment of R. gnavus-derived metabolites tryptamine and phenethylamine directly impair insulin signaling in major metabolic tissues of healthy mice and monkeys and this effect is mediated by the trace amine-associated receptor 1 (TAAR1)-extracellular signal-regulated kinase (ERK) signaling axis. Our findings suggest a causal role for tryptamine/phenethylamine-producers in the development of insulin resistance, provide molecular mechanisms for the increased prevalence of metabolic syndrome in IBS, and highlight the TAAR1 signaling axis as a potential therapeutic target for the management of metabolic syndrome induced by gut dysbiosis.

Phase 1 clinical trial to assess safety and efficacy of NY-ESO-1-specific TCR T cells in HLA-A∗02:01 patients with advanced soft tissue sarcoma.

New York esophageal squamous cell carcinoma-1 (NY-ESO-1)-specific T cell receptor (TCR) T cell therapy is effective in tumors with NY-ESO-1 expression, but a safe and effective TCR-T cell therapeutic protocol remains to be improved. Here, we report a phase 1 investigational new drug clinical trial with TCR affinity-enhanced specific T cell therapy (TAEST16001) for targeting NY-ESO-1. Enrolled patients receive TAEST16001 cell infusion after dose-reduced lymphodepletion with cyclophosphamide (15 mg/kg/day × 3 days) combined with fludarabine (20 mg/m2/day × 3 days), and the TCR-T cells are maintained with low doses of interleukin-2 injection post-adoptive transfer. Analysis of 12 patients treated with the regimen demonstrates no treatment-related serious adverse events. The overall response rate is 41.7%. The median progression-free survival is 7.2 months, and the median duration of response is 13.1 months. The protocol of TAEST16001 cells delivers a safe and highly effective treatment for patients with advanced soft tissue sarcoma (ClinicalTrials.gov: NCT04318964).

Assessment of reliability and validity of a handheld surface spine scanner for measuring trunk rotation in adolescent idiopathic scoliosis.

PURPOSE: To assess the reliability and validity of a handheld scanner (SpineScan3D) for trunk rotation measurement in adolescent idiopathic scoliosis (AIS) subjects, as compared with Scoliometer. METHODS: This was a cross-sectional study with AIS subjects recruited. Biplanar spine radiographs were performed using an EOS imaging system with coronal Cobb angle (CCA) determined. The angle of trunk rotation (ATR) was measured using Scoliometer. SpineScan3D was employed to assess the axial rotation of subjects' back at forward bending, recorded as surface tilt angle (STA). Intra- and inter-examiner repeats were conducted to evaluate the reliability of SpineScan3D. RESULTS: 97 AIS patients were recruited. Intra- and inter-examiner reliability of STA measures were good to excellent in major thoracic and lumbar curves (p < 0.001). A strong correlation was found between STA and ATR measures in both curve types (p < 0.001) with a standard error of the ATR estimate of between 1 and 2 degrees from linear regression models (R squared: 0.8-0.9, p < 0.001). A similar correlation with CCA was found for STA and ATR measures (r: 0.5-0.6, p < 0.002), which also demonstrated a similar sensitivity (72%-74%) and specificity (62%-77%) for diagnosing moderate to severe curves. CONCLUSION: SpineScan3D is a handheld surface scanner with a potential of wide applications in subjects with AIS. The current study indicated that SpineScan3D is reliable and valid for measuring trunk rotation in AIS subjects, comparable to Scoliometer. Further studies are planned to investigate its measurements in coronal and sagittal planes and the potential of this device as a screening and monitoring tool. TRIAL REGISTRATION NUMBER (DATE OF REGISTRATION): HKUCTR-2288 (06 Dec 2017). LEVEL OF EVIDENCE: Level III.

Automated System for Multiplexing Detection of COVID-19 and Other Respiratory Pathogens.

OBJECTIVE: Infectious diseases are global health challenge, impacted the communities worldwide particularly in the midst of COVID-19 pandemic. The need of rapid and accurate automated systems for detecting pathogens of concern has always been critical. Ideally, such systems shall detect a large panel of pathogens simultaneously regardless of well-equipped facilities and highly trained operators, thus realizing on-site diagnosis for frontline healthcare providers and in critical locations such as borders and airports. METHODS & RESULTS: Avalon Automated Multiplex System, AAMST, is developed to automate a series of biochemistry protocols to detect nucleic acid sequences from multiple pathogens in one test. Automated processes include isolation of nucleic acids from unprocessed samples, reverse transcription and two rounds of amplifications. All procedures are carried out in a microfluidic cartridge performed by a desktop analyzer. The system was validated with reference controls and showed good agreement with their laboratory counterparts. In total 63 clinical samples, 13 positives including those from COVID-19 patients and 50 negative cases were detected, consistent with clinical diagnosis using conventional laboratory methods. CONCLUSIONS: The proposed system has demonstrated promising utility. It would benefit the screening and diagnosis of COVID-19 and other infectious diseases in a simple, rapid and accurate fashion. Clinical and Translational Impact Statement- A rapid and multiplex diagnostic system proposed in this work can clinically help to control spread of COVID-19 and other infectious agents as it can provide timely diagnosis, isolation and treatment to patients. Using the system at remoted clinical sites can facilitate early clinical management and surveillance.

Deep-learning-enabled protein-protein interaction analysis for prediction of SARS-CoV-2 infectivity and variant evolution.

Host-pathogen interactions and pathogen evolution are underpinned by protein-protein interactions between viral and host proteins. An understanding of how viral variants affect protein-protein binding is important for predicting viral-host interactions, such as the emergence of new pathogenic SARS-CoV-2 variants. Here we propose an artificial intelligence-based framework called UniBind, in which proteins are represented as a graph at the residue and atom levels. UniBind integrates protein three-dimensional structure and binding affinity and is capable of multi-task learning for heterogeneous biological data integration. In systematic tests on benchmark datasets and further experimental validation, UniBind effectively and scalably predicted the effects of SARS-CoV-2 spike protein variants on their binding affinities to the human ACE2 receptor, as well as to SARS-CoV-2 neutralizing monoclonal antibodies. Furthermore, in a cross-species analysis, UniBind could be applied to predict host susceptibility to SARS-CoV-2 variants and to predict future viral variant evolutionary trends. This in silico approach has the potential to serve as an early warning system for problematic emerging SARS-CoV-2 variants, as well as to facilitate research on protein-protein interactions in general.

Ruminococcus gnavus plays a pathogenic role in diarrhea-predominant irritable bowel syndrome by increasing serotonin biosynthesis.

Diarrhea-predominant irritable bowel syndrome (IBS-D), a globally prevalent functional gastrointestinal (GI) disorder, is associated with elevated serotonin that increases gut motility. While anecdotal evidence suggests that the gut microbiota contributes to serotonin biosynthesis, mechanistic insights are limited. We determined that the bacterium Ruminococcus gnavus plays a pathogenic role in IBS-D. Monocolonization of germ-free mice with R. gnavus induced IBS-D-like symptoms, including increased GI transit and colonic secretion, by stimulating the production of peripheral serotonin. R. gnavus-mediated catabolism of dietary phenylalanine and tryptophan generated phenethylamine and tryptamine that directly stimulated serotonin biosynthesis in intestinal enterochromaffin cells via a mechanism involving activation of trace amine-associated receptor 1 (TAAR1). This R. gnavus-driven increase in serotonin levels elevated GI transit and colonic secretion but was abrogated upon TAAR1 inhibition. Collectively, our study provides molecular and pathogenetic insights into how gut microbial metabolites derived from dietary essential amino acids affect serotonin-dependent control of gut motility.

Jinhua Qinggan granules for non-hospitalized COVID-19 patients: A double-blind, placebo-controlled, and randomized controlled trial.

Background: Key findings from the World Health Organization Expert Meeting on Evaluation of Traditional Chinese Medicine (TCM) in treating coronavirus disease 2019 (COVID-19) reported that TCMs are beneficial, particularly for mild-to-moderate cases. The efficacy of Jinhua Qinggan granules (JHQG) in COVID-19 patients with mild symptoms has yet to be clearly defined. Methods: We conducted a phase 2/3, double-blind, randomized, placebo-controlled trial to evaluate the efficacy and safety of treatment with JHQG in mild, non-hospitalized, laboratory-confirmed COVID-19 patients. Participants were randomly assigned to receive 5 g/sacket of JHQG or placebo granules orally thrice daily for 10 days. The primary outcomes were the improvement in clinical symptoms and a proportion tested negative on viral polymerase chain reaction (PCR) after treatment. Secondary outcomes were the time to recover from clinical symptoms and changes in white blood cells (WBC) and acute phase reactants (C-reactive protein (CRP) and ferritin) on the 10th day after treatment initiation. Results: A total of 300 patients were randomly assigned to receive JHQG (150 patients) and placebo (150 patients). Baseline characteristics were similar in the two groups. In the modified intention-to-treat analysis, JHQG showed greater clinical efficacy (82.67%) on the 10th day of the trial compared with the placebo group (10.74%; rate difference: 71.93%; 95% CI 64.09-79.76). The proportion of patients with a negative PCR after treatment was comparable (rate difference: -4.67%; 95% CI -15.76 to 6.42). In contrast, all changes in WBC, ferritin, and CRP levels showed a statistically significant decline in JHQG (P ≤ 0.044) after treatment, but not the latter in placebo (P = 0.077). The median time to recovery of COVID-19-related symptoms including cough, sputum, sore throat, dyspnea, headache, nasal obstruction, fatigue, and myalgia was shorter in the JHQG group compared to the placebo group (P < 0.001 for all). Three patients experienced mild-to-moderate adverse events (AEs) duringthe treatment period in the JHQG group. Findings were similar between the modified intention-to-treat and the per-protocol analysis that included only patients who reported 100% adherence to the assigned regimen. Conclusion: Based on the time to recover from the COVID-19-related symptoms and AEs, it is concluded that JHQG is a safe and effective TCM for symptomatic relief of patients with mild COVID-19. A symptomatic improvement in the JHQG group patients was observed and JHQG use would have important public health implications in such patients. Clinical Trial Registration: The Trial was prospectively registered on www.clinicaltrials.gov with registration number: NCT04723524.

A novel galactose electrochemical biosensor intended for point-of-care measurement of quantitative liver function using galactose single-point test.

Liver disease has emerged as a healthcare burden because of high hospitalization rates attributed both to steatohepatitis and to severe hepatic toxicity associated with changes of drug exposure. Early detection of hepatic insufficiency is critical to preventing long-term liver damage. The galactose single-point test is recommended by the US FDA as a sensitive means to quantify liver function, yet the conventional method used for quantitation of circulating galactose still relies on the standard colorimetric method, requiring time-consuming and labor-intensive processes, and is confined to the medical laboratory, thus limiting prevalence. To facilitate time- and cost-effective disease management particularly during a pandemic, a pocket-sized rapid quantitative device consisting of a biosensor and electrochemical detection has been developed. An in vitro validation study demonstrated that the coefficient of variation was less than 15% and deviations were between -4 and 14% in the range of 100-1500 µg/mL. The device presented good linear fit (correlation coefficient, r = 0.9750) over the range of 150-1150 µg/mL. Moreover, the device was found to be free from interference of common endogenous and exogenous substances, and deviated hematocrit, enabling a direct measurement of galactose in the whole blood without sample pre-treatment steps. The clinical validation comprising 118 subjects showed high concordance (r = 0.953) between the device and the conventional colorimetric assay. Thus, this novel miniaturized device is reliable and robust for routine assessment of quantitative liver function intended for follow-up of hepatectomy, drug dose adjustment, and screening for galactosemia, allowing timely and cost-effective clinical management of patients.

Discovery and Characterization of Potent Dual P-Glycoprotein and CYP3A4 Inhibitors: Design, Synthesis, Cryo-EM Analysis, and Biological Evaluations.

Targeted concurrent inhibition of intestinal drug efflux transporter P-glycoprotein (P-gp) and drug metabolizing enzyme cytochrome P450 3A4 (CYP3A4) is a promising approach to improve oral bioavailability of their common substrates such as docetaxel, while avoiding side effects arising from their pan inhibitions. Herein, we report the discovery and characterization of potent small molecule inhibitors of P-gp and CYP3A4 with encequidar (minimally absorbed P-gp inhibitor) as a starting point for optimization. To aid in the design of these dual inhibitors, we solved the high-resolution cryo-EM structure of encequidar bound to human P-gp. The structure guided us to prudently decorate the encequidar scaffold with CYP3A4 pharmacophores, leading to the identification of several analogues with dual potency against P-gp and CYP3A4. In vivo, dual P-gp and CYP3A4 inhibitor 3a improved the oral absorption of docetaxel by 3-fold as compared to vehicle, while 3a itself remained poorly absorbed.

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidney disease and type 2 diabetes solely from fundus images or in combination with clinical metadata (age, sex, height, weight, body-mass index and blood pressure) with areas under the receiver operating characteristic curve of 0.85-0.93. The models were trained and validated with a total of 115,344 retinal fundus photographs from 57,672 patients and can also be used to predict estimated glomerulal filtration rates and blood-glucose levels, with mean absolute errors of 11.1-13.4 ml min-1 per 1.73 m2 and 0.65-1.1 mmol l-1, and to stratify patients according to disease-progression risk. We evaluated the generalizability of the models for the identification of chronic kidney disease and type 2 diabetes with population-based external validation cohorts and via a prospective study with fundus images captured with smartphones, and assessed the feasibility of predicting disease progression in a longitudinal cohort.

A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.

Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneumonia caused by coronavirus disease 2019 (COVID-19) and assess its severity, and can also discriminate between viral pneumonia caused by COVID-19 and other types of pneumonia. The deep-learning system was developed using a heterogeneous multicentre dataset of 145,202 images, and tested retrospectively and prospectively with thousands of additional images across four patient cohorts and multiple countries. The system generalized across settings, discriminating between viral pneumonia, other types of pneumonia and the absence of disease with areas under the receiver operating characteristic curve (AUCs) of 0.94-0.98; between severe and non-severe COVID-19 with an AUC of 0.87; and between COVID-19 pneumonia and other viral or non-viral pneumonia with AUCs of 0.87-0.97. In an independent set of 440 chest X-rays, the system performed comparably to senior radiologists and improved the performance of junior radiologists. Automated deep-learning systems for the assessment of pneumonia could facilitate early intervention and provide support for clinical decision-making.

COVID-19 in early 2021: current status and looking forward.

Since the first description of a coronavirus-related pneumonia outbreak in December 2019, the virus SARS-CoV-2 that causes the infection/disease (COVID-19) has evolved into a pandemic, and as of today, >100 million people globally in over 210 countries have been confirmed to have been infected and two million people have died of COVID-19. This brief review summarized what we have hitherto learned in the following areas: epidemiology, virology, and pathogenesis, diagnosis, use of artificial intelligence in assisting diagnosis, treatment, and vaccine development. As there are a number of parallel developments in each of these areas and some of the development and deployment were at unprecedented speed, we also provided some specific dates for certain development and milestones so that the readers can appreciate the timing of some of these critical events. Of note is the fact that there are diagnostics, antiviral drugs, and vaccines developed and approved by a regulatory within 1 year after the virus was discovered. As a number of developments were conducted in parallel, we also provided the specific dates of a number of critical events so that readers can appreciate the evolution of these research data and our understanding. The world is working together to combat this pandemic. This review also highlights the research and development directions in these areas that will evolve rapidly in the near future.

Apolipoprotein E Gene Revisited: Contribution of Rare Variants to Alzheimer's Disease Susceptibility in Southern Chinese.

BACKGROUND: APOE ε4 is the best-known risk factor for late-onset alzheimer's disease (AD). Population studies have demonstrated a relatively low prevalence of APOE ε4 among Chinese population, implying additional risk factors that are Chinese-specific may exist. Apart from - alleles, genetic variation profile along the full-length APOE has rarely been investigated. OBJECTIVE: In this study, we filled this gap by comprehensively determining all genetic variations in APOE and investigated their potential associations with late-onset AD and mild cognitive impairment (MCI) in southern Chinese. METHODS: Two hundred and fifty-seven southern Chinese participants were recruited, of whom 69 were AD patients, 83 had MCI, and 105 were normal controls. Full-length APOE from promoter to 3'UTR regions were sequenced. Genetic variants were identified and compared among the three groups. RESULTS: While APOE ε4 was more significantly found in AD patients, the prevalence of APOE ε4 in southern Chinese AD patients was the lowest when compared to other areas of China and nearby regions, as well as other countries worldwide. We further identified 13 rare non-singleton variants in APOE. Significantly more AD patients carried any of the rare non-singleton variants than MCI and normal subjects. Such difference was observed in the non-carriers of ε4-allele only. Among the identified rare variants, the potential functional impact was predicted for rs532314089, rs553874843, rs533904656 and rs370594287. CONCLUSION: Our study suggests an ethnic difference in genetic risk composition of AD in southern Chinese. Rare variants on APOE are a potential candidate for AD risk stratification biomarker in addition to APOE-ε4.

Discovery of Encequidar, First-in-Class Intestine Specific P-glycoprotein Inhibitor.

Many chemotherapeutics, such as paclitaxel, are administered intravenously as they suffer from poor oral bioavailability, partly because of efflux mechanism of P-glycoprotein in the intestinal epithelium. To date, no drug has been approved by the U.S. Food and Drug Administration (FDA) that selectively blocks this efflux pump. We sought to identify a compound that selectively inhibits P-glycoprotein in the gastrointestinal mucosa with poor oral bioavailability, thus eliminating the issues such as bone marrow toxicity associated with systemic inhibition of P-glycoprotein. Here, we describe the discovery of highly potent, selective, and poorly orally bioavailable P-glycoprotein inhibitor 14 (encequidar). Clinically, encequidar was found to be well tolerated and minimally absorbed; and importantly, it enabled the oral delivery of paclitaxel.

A Double-blind, Randomized Phase 2 Controlled Trial of Intradermal Hepatitis B Vaccination With a Topical Toll-like Receptor 7 Agonist Imiquimod, in Patients on Dialysis.

BACKGROUND: Patients on dialysis are hyporesponsive to the hepatitis B virus vaccines (HBVv). We examined intradermal (ID) HBVv Sci-B-Vac, with topical Toll-like receptor 7 (TLR7) agonist imiquimod pretreatment in dialysis patients. METHODS: We enrolled and prospectively followed adult patients on dialysis between January 2016 and September 2018. Eligible patients were randomly allocated (1:1:1) into 1 treatment group, topical imiquimod cream followed by ID HBVv (IMQ + ID); and 2 control groups: topical aqueous cream (placebo) followed by ID HBVv (AQ + ID) or topical aqueous cream followed by intramuscular HBVv (AQ + IM). The primary endpoint was the seroprotection rate (hepatitis B surface antibody ≥10 mIU/mL) at 52 weeks. RESULTS: Ninety-four patients were enrolled, among which 57.4% were previous nonresponders. Seroprotection rate was significantly better at week 52 for the IMQ + ID group with 96.9% compared to 74.2% and 48.4% for AQ + ID and AQ + IM groups, respectively (P < .0001). The geometric mean concentration was significantly higher at week 52 for the IMQ + ID group: 1135 (95% confidence interval [CI], 579.4-2218.2) mIU/mL, compared to 86.9 (95% CI, 18.5-409.3) mIU/mL and 7.2 (2.0-26.5) mIU/mL for the AQ + ID and AQ + IM groups, respectively (P < .0001). IMQ + ID vaccination (odds ratio, 3.70 [95% CI, 1.16-11.81]; P = .027) was the only factor independently associated with higher 52-week seroprotection rate. Adverse reaction was infrequent. CONCLUSIONS: Pretreatment with topical imiquimod before ID HBVv Sci-B-Vac was safe with favorable seroprotection in dialysis patients. CLINICAL TRIALS REGISTRATION: NCT02621112.

COVID-19 Delta variants-Current status and implications as of August 2021.

The SARS-CoV-2 Delta variant has evolved as the dominant strain of the current pandemic. Studies have shown that this variant has increased infectivity/viral load, and reduced neutralization by the host antibodies from convalescent patients/vaccinees. Clinically, Delta variant infection has been observed/documented in convalescent patients/vaccinees, although with less incidence of severe diseases, but can serve as reservoir to spread the infection to the unvaccinated. The current understanding (as of 18 August 2021) on the virologic aspect (including the amino acid substitutions), clinical implications, and public health implications will be discussed in this mini review, and recommendations to health authorities will be provided.