There are more than 350 real‐time polymerase chain reaction (RT‐PCR) coronavirus disease‐2019 (COVID‐19) testing kits commercially available but these kits have not been evaluated for pooled sample ...testing. Thus, this study was planned to compare and evaluate seven commercially available kits for pooled samples testing. Diagnostic accuracy of (1) TRUPCR SARS‐CoV‐2 Kit (Black Bio), (2) TaqPath RT‐PCR COVID‐19 Kit (Thermo Fisher Scientific), (3) Allplex 2019‐nCOV Assay (Seegene), (4) Patho detect COVID‐19 PCR kit (My Lab), (5) LabGun COVID‐19 RT‐PCR Kit (Lab Genomics, Korea), (6) Fosun COVID‐19 RT‐PCR detection kit (Fosun Ltd.), (7) Real‐time Fluorescent RT‐PCR kit for SARS CoV‐2 (BGI) was evaluated on precharacterised 40 positive and 10 negative COVID‐19 sample pools. All seven kits detected all sample pools with low Ct values (<30); while testing weak positive pooled samples with high Ct value (>30); the TRUPCR Kit, TaqPath Kit, Allplex Assay, and BGI RT‐PCR kit showed 100% sensitivity, specificity, and accuracy. However, the Fosun kit, LabGun Kit, and Patho detect kit could detect only 90%, 85%, and 75% of weakly positive samples, respectively. We conclude that all seven commercially available RT‐PCR kits included in this study can be used for routine molecular diagnosis of COVID‐19. However, regarding performing pooled sample testing, it might be advisable to use those kits that performed best regarding positive identification in samples' pool, that is TRUPCR SARS‐CoV‐2 Kit, TaqPath RT‐PCR COVID‐19 Kit, Allplex 2019‐nCOV Assay, and BGI Real‐time RT‐PCR kit for detecting SARS CoV‐2.
COVID-19 testing is required before admission of a patient in the hospitals, invasive procedures, major and minor surgeries etc. Real Time Polymerase chain reaction is the gold standard test for the ...diagnosis, but requires well equipped biosafety laboratory along with trained manpower. In this study we have evaluated the diagnostic accuracy of novel TrueNat molecular assay for detecting SARS CoV-2. TrueNat is a chip-based real time PCR test and works on portable, light weight, battery powered equipment and can be used in remote areas with poor infrastructure. In this study 1807 patients samples were collected for both TrueNat and RTPCR COVID-19 testing during study period. Of these 174 (9.7%) and 174 (15%) were positive by RTPCR and TrueNat respectively and taking results of RTPCR as gold standard TrueNat test showed a sensitivity, specificity and diagnostic accuracy of 69.5, 90.9% and 89.2% respectively. It can be concluded that TrueNat is a simple, easy to use, good rapid molecular diagnostic test for diagnosis of COVID-19 especially in resource limited settings and will prove to be a game changer of molecular diagnostics in future.
Background Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 continues to spread globally. Reverse transcriptase ...polymerase chain reaction (RT-PCR), which is considered the gold standard for diagnosis, does not always indicate contagiousness. This study was planned to evaluate the performance of the rapid antigen test (RAT) with the duration of symptoms and the usefulness of these tests in determining the infectivity of patients by performing sub-genomic RT-PCR. Methodology This prospective, observational study was designed to compare the diagnostic value of the COVID-19 RAT (SD Biosensor, Korea) with COVID-19 RT-PCR (Thermo Fisher, USA) by serial testing of patients. To evaluate the infectivity of the virus, sub-genomic RT-PCR was performed on previous RAT and RT-PCR-positive samples. Results Of 200 patients, 102 were positive on both RT-PCR and RAT, with 87 patients serially followed and tested. The sensitivity and specificity of RAT were 92.73% and 93.33%, respectively, in symptomatic patients. The mean duration of RAT positivity was 9.1 days, and the mean duration of RT-PCR positivity was 12.6 days. Sub-genomic RT-PCR test was performed on samples that were reported to be positive by RAT, and 73/87 (83.9%) patients were found to be positive. RAT was positive in symptomatic patients whose duration of illness was less than 10 days or those with a cycle threshold value below 32. Conclusions Thus, RAT can be used as the marker of infectivity of SARS-CoV-2 in symptomatic patients, especially in healthcare workers.
COVID-19 testing is required before admission of a patient in the hospitals, invasive procedures, major and minor surgeries etc. Real Time Polymerase chain reaction is the gold standard test for the ...diagnosis, but requires well equipped biosafety laboratory along with trained manpower. In this study we have evaluated the diagnostic accuracy of novel TrueNat molecular assay for detecting SARS CoV-2. TrueNat is a chip-based real time PCR test and works on portable, light weight, battery powered equipment and can be used in remote areas with poor infrastructure. In this study 1807 patients samples were collected for both TrueNat and RTPCR COVID-19 testing during study period. Of these 174 (9.7%) and 174 (15%) were positive by RTPCR and TrueNat respectively and taking results of RTPCR as gold standard TrueNat test showed a sensitivity, specificity and diagnostic accuracy of 69.5, 90.9% and 89.2% respectively. It can be concluded that TrueNat is a simple, easy to use, good rapid molecular diagnostic test for diagnosis of COVID-19 especially in resource limited settings and will prove to be a game changer of molecular diagnostics in future.
Singlet fission is an exciton multiplication process in organic molecules in which a photogenerated spin-singlet exciton is rapidly and efficiently converted to two spin-triplet excitons. This ...process offers a mechanism to break the Shockley–Queisser limit by overcoming the thermalization losses inherent to all single-junction photovoltaics. One of the most promising methods to harness the singlet fission process is via the efficient extraction of the dark triplet excitons into quantum dots (QDs) where they can recombine radiatively, thereby converting high-energy photons to pairs of low-energy photons, which can then be captured in traditional inorganic PVs such as Si. Such a singlet fission photon multiplication (SF-PM) process could increase the efficiency of the best Si cells from 26.7% to 32.5%, breaking the Shockley–Queisser limit. However, there has been no demonstration of such a singlet fission photon multiplication (SF-PM) process in a bulk system to date. Here, we demonstrate a solution-based bulk SF-PM system based on the singlet fission material TIPS-Tc combined with PbS QDs. Using a range of steady-state and time-resolved measurements combined with analytical modeling we study the dynamics and mechanism of the triplet harvesting process. We show that the system absorbs >95% of incident photons within the singlet fission material to form singlet excitons, which then undergo efficient singlet fission in the solution phase (135 ± 5%) before quantitative harvesting of the triplet excitons (95 ± 5%) via a low concentration of QD acceptors, followed by the emission of IR photons. We find that in order to achieve efficient triplet harvesting it is critical to engineer the surface of the QD with a triplet transfer ligand and that bimolecular decay of triplets is potentially a major loss pathway which can be controlled via tuning the concentration of QD acceptors. We demonstrate that the photon multiplication efficiency is maintained up to solar fluence. Our results establish the solution-based SF-PM system as a simple and highly tunable platform to understand the dynamics of a triplet energy transfer process between organic semiconductors and QDs, one that can provide clear design rules for new materials.
Abstract only Background: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death among young people and be detected from ECGs using artificial intelligence. Wearable devices ...could allow for broad AI-based screening but obtain noisy ECGs. We report the development of a wearable-adapted AI-ECG model that retains performance for detecting HCM in noisy single-lead ECGs. Methods: In 11,883 ECGs obtained within 30 days of transthoracic echocardiograms from Yale New Haven Hospital (2015-2021), we defined HCM as interventricular septal wall thickness (end diastole) (IVSd) > 15 mm and moderate to severe left ventricular diastolic dysfunction (LVDD). Standard and noise-adapted models were trained using a 1:10 age-sex matched dataset. For the noise-adapted model, each ECG was included four times in the training set, augmented each time with random gaussian noise within four distinct frequency ranges emulating different real-world noise sources. We evaluated the performance of the noise-adapted and standard models on an independent set of ECGs with four different real-world noisy artifacts, including noise extracted from a portable device ECG, at multiple signal-to-noise ratios (SNRs). Results: In single-lead ECGs without noise, the noise-adapted model outperformed the standard model, with an AUROC of 0.920 and 0.906, respectively for HCM. With the same ECGs augmented with noise ranging from half (SNR 2) to twice (SNR 0.5) the signal, the noise-adapted model maintained their performance across real-world noise signatures (A). At an SNR of 0.5, the noise adapted model had a significantly greater performance in detecting HCM in ECGs augmented with portable device ECG noise (AUROC 0.917 0.861-0.974 vs 0.609 0.398, 0.821) (B). Conclusions: We developed a model which accurately screens for HCM in noisy single-lead ECGs. This approach represents a more accessible and scalable method for screening for HCM using wearable device ECGs.
Abstract only Background: Deep learning-based models could identify hypertrophic cardiomyopathy (HCM) signatures on ECG, with emerging evidence of being able to track disease modification with ...mavacamten. To explore the mechanism of HCM detection on ECG, we developed an AI-ECG model for echocardiographically confirmed HCM and evaluated HCM detection after septal reduction therapy (SRT, alcohol septal ablation ASA or ventricular myectomy VM). Methods: The AI-ECG model for HCM detection was developed in a cohort of 25,652 ECGs (1:10, age-sex matched HCM to control) obtained within 30 days of a transthoracic echocardiogram (TTE) at Yale (2015-21). We defined HCM by end-diastolic interventricular septal wall thickness > 15 mm with moderate to severe diastolic dysfunction on TTE. The model was developed using a convolutional neural network and transfer learning. HCM phenotype was defined by high predicted probabilities for HCM and was assessed on ECGs spanning SRT. Results: Our AI-ECG model for HCM had an AUROC of 0.93 (0.88-0.97), sensitivity of 0.90, and specificity of 0.89 in the held-out test set. The mean HCM probability among HCM patients vs control was 0.51±0.33 vs 0.07±0.20 (P<.001). The mechanism of detection was evaluated in 1400 ECGs from 78 patients (mean age 66 y; 47% women) spanning SRT (20 ASA, 58 VM). In this group, the mean HCM probability for all ECGs performed before & after SRT was 0.49±0.34 & 0.72±0.30, respectively. The mean HCM probability in the closest ECGs per patient before SRT (median 35 days before SRT) was 0.53±0.35, and in farthest ECGs after SRT (median 536 days) was 0.70±0.32 (P diff = 0.002). Conclusion: We developed and validated an AI-ECG model that detects HCM from 12-lead ECG. The model does not merely detect thickened septum, and the continued identification of HCM signature after SRT suggests HCM prediction based on disordered myocardial kinetics. This supports the role of AI-ECG in both detection and monitoring of phenotypic effects of therapies in HCM.
Artificial intelligence (AI) can detect left ventricular systolic dysfunction (LVSD) from electrocardiograms (ECGs). Wearable devices could allow for broad AI-based screening but frequently obtain ...noisy ECGs. We report a novel strategy that automates the detection of hidden cardiovascular diseases, such as LVSD, adapted for noisy single-lead ECGs obtained on wearable and portable devices. We use 385,601 ECGs for development of a standard and noise-adapted model. For the noise-adapted model, ECGs are augmented during training with random gaussian noise within four distinct frequency ranges, each emulating real-world noise sources. Both models perform comparably on standard ECGs with an AUROC of 0.90. The noise-adapted model performs significantly better on the same test set augmented with four distinct real-world noise recordings at multiple signal-to-noise ratios (SNRs), including noise isolated from a portable device ECG. The standard and noise-adapted models have an AUROC of 0.72 and 0.87, respectively, when evaluated on ECGs augmented with portable ECG device noise at an SNR of 0.5. This approach represents a novel strategy for the development of wearable-adapted tools from clinical ECG repositories.
Study was carried out to design and evaluate clinical application of caps for intramedullary pinning to mange long bone fractures in dogs. Cannulated cancellous caps made of 316 L stainless steel ...with dimensions of 10 mm × 25 mm (length) cap for 4 mm, 4.5 mm and 5 mm steinmann pin and 8 mm × 25 mm (length) cap for 2.5 mm and 3 mm steinmann pin were designed. A total of 14 cases of dogs presented with simple transverse, short oblique fractures of long bones were equally divided into groups A and B having 7 animals in each. Simple intramedullary pinning was done in group A, whereas, in group B designed caps were fixed at entry point at trochanteric fossa after intramedullary pinning to prevent proximal migration of pins. Posture, gait, perception of pain and lameness scores were assessed during 15, 30 and 60 day, postoperatively. Caps offered rigid fixation along with intramedullary pin resulting in mild or moderate callus formation. Excellent postoperative functional recovery without any pin migration, seroma formation and valgus limb deformity were observed in group B. Results of present preliminary study suggested that designed capped intramedullary pinning offers stable internal fixation and prevented pin migration, sciatic injury and seroma formation.
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