Cobalt Catalyzed α-Hydroxylation of Arylacetic Acid Equivalents with Dioxygen.

A cobalt catalyst, under oxidative conditions, facilitates the single electron transfer process in N-pyridyl arylacetamides to form α-carbon-centered radicals that readily react with molecular oxygen, giving access to mandelic acid derivatives. In contrast to the known benzylic hydroxylation approaches, this approach enables chemo- and regioselective hydroxylation at a benzylic position adjacent to (N-pyridyl)amides. Mild conditions, broad scope, excellent selectivity, and wide synthetic practicality set up the merit of the reaction.

A Systematic Review and Identification of the Challenges of Deep Learning Techniques for Undersampled Magnetic Resonance Image Reconstruction.

Deep learning (DL) in magnetic resonance imaging (MRI) shows excellent performance in image reconstruction from undersampled k-space data. Artifact-free and high-quality MRI reconstruction is essential for ensuring accurate diagnosis, supporting clinical decision-making, enhancing patient safety, facilitating efficient workflows, and contributing to the validity of research studies and clinical trials. Recently, deep learning has demonstrated several advantages over conventional MRI reconstruction methods. Conventional methods rely on manual feature engineering to capture complex patterns and are usually computationally demanding due to their iterative nature. Conversely, DL methods use neural networks with hundreds of thousands of parameters and automatically learn relevant features and representations directly from the data. Nevertheless, there are some limitations to DL-based techniques concerning MRI reconstruction tasks, such as the need for large, labeled datasets, the possibility of overfitting, and the complexity of model training. Researchers are striving to develop DL models that are more efficient, adaptable, and capable of providing valuable information for medical practitioners. We provide a comprehensive overview of the current developments and clinical uses by focusing on state-of-the-art DL architectures and tools used in MRI reconstruction. This study has three objectives. Our main objective is to describe how various DL designs have changed over time and talk about cutting-edge tactics, including their advantages and disadvantages. Hence, data pre- and post-processing approaches are assessed using publicly available MRI datasets and source codes. Secondly, this work aims to provide an extensive overview of the ongoing research on transformers and deep convolutional neural networks for rapid MRI reconstruction. Thirdly, we discuss several network training strategies, like supervised, unsupervised, transfer learning, and federated learning for rapid and efficient MRI reconstruction. Consequently, this article provides significant resources for future improvement of MRI data pre-processing and fast image reconstruction.

Catalytic Methylene Insertion between Amines and Terminal Alkynes via C-N Bond Cleavage of N,N-Dimethylacetamide: A Unique Route to Propargylic Amines.

A copper-based system allows for the methylene insertion between an amine and a milder nucleophile, including a terminal alkyne counterpart, via C-N bond cleavage of N,N-dimethylacetamide. The method gives an expedient access to propargylic amines in good to excellent yields. A wide-ranging substrate scope and late-stage functionalization of complex molecules make the protocol practically valuable.

Fluorescence "off" and "on" signalling of esculetin in the presence of copper and thiol: a possible implication in cellular thiol sensing.

The interaction of the cupric ion with esculetin, a dihydroxy coumarin derivative, was studied by absorption and fluorescence spectroscopic methods in aqueous medium. Esculetin formed a complex in the presence of the cupric ion which was characterised by the shift in its absorption band from 350 nm to 389 nm and the quenching of its fluorescence intensity at 466 nm. From Job's plot and fluorescence quenching studies, the stoichiometry of the copper ion and esculetin in the complex was estimated to be 1 : 2 respectively. Interestingly, the incubation of the Cu(ii)-esculetin complex with a thiol peptide, glutathione (GSH), showed restoration of the fluorescence intensity as well as absorption maxima to that of pure esculetin. Incubation with other common thiol and non-sulphur amino acids did not show a similar restoration of the photophysical properties of the complex except in the case of cysteine. Mechanistically, it was evident that two molecules of GSH were consumed in reducing the Cu(ii)-esculetin complex, which subsequently split into the copper ion and esculetin. In this process GSH was converted into oxidised GSH (GSSG) as evident from the mass spectroscopy and HPLC studies. The above florescence regeneration behaviour of the copper-esculetin system in the presence of GSH was also observed in the cellular system using Chinese hamster ovary (CHO) as model cells. In conclusion, these studies may find application in developing sensors for detecting the cellular thiol level.

Swin Transformer and the Unet Architecture to Correct Motion Artifacts in Magnetic Resonance Image Reconstruction.

We present a deep learning-based method that corrects motion artifacts and thus accelerates data acquisition and reconstruction of magnetic resonance images. The novel model, the Motion Artifact Correction by Swin Network (MACS-Net), uses a Swin transformer layer as the fundamental block and the Unet architecture as the neural network backbone. We employ a hierarchical transformer with shifted windows to extract multiscale contextual features during encoding. A new dual upsampling technique is employed to enhance the spatial resolutions of feature maps in the Swin transformer-based decoder layer. A raw magnetic resonance imaging dataset is used for network training and testing; the data contain various motion artifacts with ground truth images of the same subjects. The results were compared to six state-of-the-art MRI image motion correction methods using two types of motions. When motions were brief (within 5 s), the method reduced the average normalized root mean square error (NRMSE) from 45.25% to 17.51%, increased the mean structural similarity index measure (SSIM) from 79.43% to 91.72%, and increased the peak signal-to-noise ratio (PSNR) from 18.24 to 26.57 dB. Similarly, when motions were extended from 5 to 10 s, our approach decreased the average NRMSE from 60.30% to 21.04%, improved the mean SSIM from 33.86% to 90.33%, and increased the PSNR from 15.64 to 24.99 dB. The anatomical structures of the corrected images and the motion-free brain data were similar.

A Hybrid Residual Attention Convolutional Neural Network for Compressed Sensing Magnetic Resonance Image Reconstruction.

We propose a dual-domain deep learning technique for accelerating compressed sensing magnetic resonance image reconstruction. An advanced convolutional neural network with residual connectivity and an attention mechanism was developed for frequency and image domains. First, the sensor domain subnetwork estimates the unmeasured frequencies of k-space to reduce aliasing artifacts. Second, the image domain subnetwork performs a pixel-wise operation to remove blur and noisy artifacts. The skip connections efficiently concatenate the feature maps to alleviate the vanishing gradient problem. An attention gate in each decoder layer enhances network generalizability and speeds up image reconstruction by eliminating irrelevant activations. The proposed technique reconstructs real-valued clinical images from sparsely sampled k-spaces that are identical to the reference images. The performance of this novel approach was compared with state-of-the-art direct mapping, single-domain, and multi-domain methods. With acceleration factors (AFs) of 4 and 5, our method improved the mean peak signal-to-noise ratio (PSNR) to 8.67 and 9.23, respectively, compared with the single-domain Unet model; similarly, our approach increased the average PSNR to 3.72 and 4.61, respectively, compared with the multi-domain W-net. Remarkably, using an AF of 6, it enhanced the PSNR by 9.87 ± 1.55 and 6.60 ± 0.38 compared with Unet and W-net, respectively.

Intelligent IoT (IIoT) Device to Identifying Suspected COVID-19 Infections Using Sensor Fusion Algorithm and Real-Time Mask Detection Based on the Enhanced MobileNetV2 Model.

This paper employs a unique sensor fusion (SF) approach to detect a COVID-19 suspect and the enhanced MobileNetV2 model is used for face mask detection on an Internet-of-Things (IoT) platform. The SF algorithm avoids incorrect predictions of the suspect. Health data are continuously monitored and recorded on the ThingSpeak cloud server. When a COVID-19 suspect is detected, an emergency email is sent to healthcare personnel with the GPS position of the suspect. A lightweight and fast deep learning model is used to recognize appropriate mask positioning; this restricts virus transmission. When tested with the real-world masked face dataset (RMFD) dataset, the enhanced MobileNetV2 neural network is optimal for Raspberry Pi. Our IoT device and deep learning model are 98.50% (compared to commercial devices) and 99.26% accurate, respectively, and the time required for face mask evaluation is 31.1 milliseconds. The proposed device is useful for remote monitoring of covid patients. Thus, the method will find medical application in the detection of COVID-19-positive patients. The device is also wearable.

Squeeze-MNet: Precise Skin Cancer Detection Model for Low Computing IoT Devices Using Transfer Learning.

Cancer remains a deadly disease. We developed a lightweight, accurate, general-purpose deep learning algorithm for skin cancer classification. Squeeze-MNet combines a Squeeze algorithm for digital hair removal during preprocessing and a MobileNet deep learning model with predefined weights. The Squeeze algorithm extracts important image features from the image, and the black-hat filter operation removes noise. The MobileNet model (with a dense neural network) was developed using the International Skin Imaging Collaboration (ISIC) dataset to fine-tune the model. The proposed model is lightweight; the prototype was tested on a Raspberry Pi 4 Internet of Things device with a Neo pixel 8-bit LED ring; a medical doctor validated the device. The average precision (AP) for benign and malignant diagnoses was 99.76% and 98.02%, respectively. Using our approach, the required dataset size decreased by 66%. The hair removal algorithm increased the accuracy of skin cancer detection to 99.36% with the ISIC dataset. The area under the receiver operating curve was 98.9%.

Comparison of a novel immunocapture assay with standard serological methods in the diagnosis of brucellosis.

BACKGROUND: Microbiological culture methods and immunological assays currently available are technically challenging, difficult to interpret even in non-endemic areas. They are also time consuming leading to misdiagnosis, treatment delay, and severe morbidity and mortality. Therefore, the development of a simple and accurate diagnostic assay which could be performed even in small laboratories is a pressing need. This has prompted us to evaluate an assay based on the immunocapture technique in a region where brucellosis is prevalent. METHODS: The immunocapture test was evaluated for diagnostic efficacy on 211 patients with suspected brucellosis. Standard tube agglutination test (SAT), 2-mercaptoethanol (2-ME) agglutination, Coombs, immunocapture tests, and blood cultures were performed on these 211 blood samples. 190 sera belonging to healthy blood donors of endemic and non-endemic areas and 43 sera obtained from non-brucellosis patients were also subjected to SAT, 2-ME, Coombs, and immunocapture tests. A total of 15 blood cultures belonging to blood donors of endemic area and non-brucellosis cases were done. RESULTS: SAT picked up only 21 (9.9%), Coombs established the diagnosis in 69 (32.7%), while the immunocapture test confirmed the diagnosis in 76 (36%; p < 0.001)) patients with brucellosis, including 48 culture-confirmed cases. Sensitivity and specificity of the immunocapture technique were 97.29% and 97.08% respectively. SAT could not exclude the diagnosis in 55 cases as they were confirmed in most cases by the Coombs test and in all by immunocapture. CONCLUSIONS: Our results clearly show that immunocapture is superior to SAT in all stages of illness but is not significantly superior to Coombs. It also seems to be a useful tool in diagnosing a relapse. Immunocapture and Coombs tests were found to be more sensitive eliminating the ambiguity in the interpretation of the results for diagnosing brucellosis. The Coombs test is laborious, subjective in interpretation and demanding on skills. The immunocapture technique does not have the subjective reading errors, is simple to perform, and the results of the immunocapture technique seem to be reproducible. Thus we recommend the immunocapture technique especially for brucellosis-endemic countries. The Coombs, immunocapture, and 2-ME tests may also be considered useful tools in assessing treatment outcome.

Formation of two centre three electron bond by hydroxyl radical induced reaction of thiocoumarin: evidence from experimental and theoretical studies.

Radiation chemical studies of thioesculetin (1), a thioketone derivative of coumarin, were performed by both pulse radiolysis technique and DFT calculations. Hydroxyl (•OH) radical reaction with 1 resulted transients absorbing at 320, 360 and 500 nm. To identify the nature of the transients, the reaction was studied with specific one-electron oxidant (N3•) radical, where 360 nm band was absent. The transient absorption at 500 nm was concentration-dependent. The overall impression for •OH radical reaction was that the transient absorbing at 320, 360 and 500 nm was due to sulphur centred monomer radical, hydroxysulfuranyl and dimer radical of 1 respectively. The equilibrium constant between the monomer to dimer radical was 3.75 × 104 M-1. From the transients' redox nature, it was observed that 57 and 24% of •OH radical yielded to oxidising and reducing products respectively. Further, the product analysis by HPLC suggested that the dimer radical disproportionate to esculetin and thioesculetin. DFT energy calculation for all the possible transients revealed that dimer radical has the lowest energy. The HOMO of 1 and its monomer radical suggested that the electron density was localised on the sulphur atom. The bond length between the two sulphur atoms in dimer radical was 2.88 Å which was less than the van der Waals distance. Bond order between the two sulphur atoms was 0.55, suggesting that the bond was two centre three electron (2c-3e). From TD-DFT calculation, the electronic transition of dimer radical was at 479 nm which was in close agreement with the experimental value. The nature of the electronic transition was σ → σ* from a 2c - 3e bond.

Resurgence of diphtheria in rural areas of North Karnataka, India.

BACKGROUND: A diphtheria outbreak was identified from Vijayapura (formerly Bijapur) district in the South Indian state of Karnataka in 2011. There was a surge in the number of throat swab samples received under the Integrated Disease Surveillance Programme (IDSP) in North Karnataka since then. OBJECTIVES: A microbiological study was undertaken to generate information on the status of resurgence of the disease in the region. MATERIALS AND METHODS: Throat swabs from 432 suspected cases of diphtheria during 2012-2015 were obtained from government hospitals and primary health centres of 8 districts in North Karnataka and were processed for the culture and identification of Corynebacterium diphtheriae. Polymerase chain reaction for the presence of toxin gene (toxA and toxB) was carried out on the isolates. Antibiotic sensitivity tests were performed on the isolates with a panel of 14 antibiotics. RESULTS: Thirty-eight (8.79%) out of 432 samples yielded C. diphtheriae on culture. All isolates possessed the diphtheria toxin gene. Out of the 38 confirmed cases, whereas 21 (55.26%) were between 1 and 5 years of age, 14 (36.84%) were aged between 5 and 10 years. Male children were three times more than females in confirmed cases. No information was available on the immunisation status of the cases. Emergence of resistance to penicillin was found with minimum inhibitory concentration reaching up to 6.00 µg/ml. CONCLUSION AND DISCUSSION: Our study identified an upsurge in cases of diphtheria in North Karnataka, particularly in Vijayapura District, and to the best of our knowledge, reports the emergence of penicillin resistance for the first time in India. The study calls for enhanced surveillance for the disease, making antidiphtheritic serum available in key hospitals in the region and serves to provide a baseline for future assessment of the impact of the recently launched 'Mission Indradhanush' programme in strengthening Universal Immunisation Programme (UIP).

A rare case of mycetoma due to curvularia.

Mycetoma due to Curvularia is a rare clinical entity. Here, we report a case of 27-year-old female presented with multiple swellings and discharging wounds around left shoulder joint since 12 years. Local examination showed diffuse nodular swellings over left anterior chest wall, posterior chest wall, and axilla. Multiple nodules and discharging sinuses were seen. Fungal culture of the biopsy of the lesion revealed Curvularia species. Patient showed significant clinical improvement with itraconazole therapy.

Molecular testing for oncogenic gene mutations in thyroid lesions: a case-control validation study in 413 postsurgical specimens.

Molecular testing for oncogenic gene alterations provides clinically actionable information essential for the optimal management of follicular cell thyroid cancer. We aimed to establish the distribution and frequency of common oncogenic gene mutations and chromosomal rearrangements in a comprehensive set of benign and malignant thyroid lesions. A case-control study was conducted in 413 surgical cases comprising 17 distinct histopathologic categories, 244 malignant, 169 benign, and 304 double-blinded specimens. Seventeen alterations of BRAF, HRAS, KRAS, NRAS, PAX8, and RET genes were evaluated using a single validated technology platform. Following verification of analytical sensitivity, accuracy, and precision in model and surgical specimens, 152 molecular positive results were generated in lesions representing multiple stages of progression and epithelial differentiation as well as rare subtypes of primary, secondary, or recurring tumors. Single mutations were found in 58% of primary malignant lesions and 12% of benign (P < .001). In the blinded validation set, mutation distribution and frequency were distinct across variants of follicular and papillary carcinomas. BRAF or RET-PTC was detected exclusively in malignant lesions but not in follicular carcinomas (P < .001). RAS or PAX8-PPARG were present in 23% of adenomas, and NRAS was found in a single nonneoplastic lesion (P = .0014). These data substantiate the diagnostic utility of molecular testing for oncogenic mutations and validate its performance in a variety of surgical specimens. Standardized and validated multianalyte molecular panels can complement the preoperative and postoperative assessment of thyroid nodules and support a growing number of clinical and translational applications with potential diagnostic, prognostic, or theranostic utility.

Abiotic stress-induced oscillations in steady-state transcript levels of Group 3 LEA protein genes in the moss, Physcomitrella patens.

The moss, Physcomitrella patens is a non-seed land plant belonging to early diverging lineages of land plants following colonization of land in the Ordovician period in Earth's history. Evidence suggests that mosses can be highly tolerant of abiotic stress. We showed previously that dehydration stress and abscisic acid treatments induced oscillations in steady-state levels of LEA (Late Embryogenesis Abundant) protein transcripts, and that removal of ABA resulted in rapid attenuation of oscillatory increases in transcript levels. Here, we show that other abiotic stresses like salt and osmotic stresses also induced oscillations in steady-state transcript levels and that the amplitudes of the oscillatory increases in steady-state transcript levels are reflective of the severity of the abiotic stress treatment. Together, our results suggest that oscillatory increases in transcript levels in response to abiotic stresses may be a general phenomenon in P. patens and that temporally dynamic increases in steady-state transcript levels may be important for adaptation to life in constantly fluctuating environmental conditions.

Targeted, high-depth, next-generation sequencing of cancer genes in formalin-fixed, paraffin-embedded and fine-needle aspiration tumor specimens.

Implementation of highly sophisticated technologies, such as next-generation sequencing (NGS), into routine clinical practice requires compatibility with common tumor biopsy types, such as formalin-fixed, paraffin-embedded (FFPE) and fine-needle aspiration specimens, and validation metrics for platforms, controls, and data analysis pipelines. In this study, a two-step PCR enrichment workflow was used to assess 540 known cancer-relevant variants in 16 oncogenes for high-depth sequencing in tumor samples on either mature (Illumina GAIIx) or emerging (Ion Torrent PGM) NGS platforms. The results revealed that the background noise of variant detection was elevated approximately twofold in FFPE compared with cell line DNA. Bioinformatic algorithms were optimized to accommodate this background. Variant calls from 38 residual clinical colorectal cancer FFPE specimens and 10 thyroid fine-needle aspiration specimens were compared across multiple cancer genes, resulting in an accuracy of 96.1% (95% CI, 96.1% to 99.3%) compared with Sanger sequencing, and 99.6% (95% CI, 97.9% to 99.9%) compared with an alternative method with an analytical sensitivity of 1% mutation detection. A total of 45 of 48 samples were concordant between NGS platforms across all matched regions, with the three discordant calls each represented at <10% of reads. Consequently, NGS of targeted oncogenes in real-life tumor specimens using distinct platforms addresses unmet needs for unbiased and highly sensitive mutation detection and can accelerate both basic and clinical cancer research.

High-throughput identification and quantification of Candida species using high resolution derivative melt analysis of panfungal amplicons.

Fungal infections pose unique challenges to molecular diagnostics; fungal molecular diagnostics consequently lags behind bacterial and viral counterparts. Nevertheless, fungal infections are often life-threatening, and early detection and identification of species is crucial to successful intervention. A high throughput PCR-based method is needed that is independent of culture, is sensitive to the level of one fungal cell per milliliter of blood or other tissue types, and is capable of detecting species and resistance mutations. We introduce the use of high resolution melt analysis, in combination with more sensitive, inclusive, and appropriately positioned panfungal primers, to address these needs. PCR-based amplification of the variable internal transcribed regions of the rDNA genes generates an amplicon whose sequence melts with a shape that is characteristic and therefore diagnostic of the species. Simple analysis of the differences between test and reference melt curves generates a single number that calls the species. Early indications suggest that high resolution melt analysis can distinguish all eight major species of Candida of clinical significance without interference from excess human DNA. Candida species, including mixed and novel species, can be identified directly in vaginal samples. This tool can potentially detect, count, and identify fungi in hundreds of samples per day without further manipulation, costs, or delays, offering a major step forward in fungal molecular diagnostics.

ELISA versus conventional methods of diagnosing endemic brucellosis.

The diagnostic value of enzyme-linked immunosorbent assay (ELISA) was evaluated when blood specimens of 92 patients suspected of brucellosis underwent the ELISA (IgM and IgG), standard tube agglutination (SAT), and 2-mercaptoethanol (2-ME) tests and blood cultures; 38 sera from non-brucellosis patients and 34 sera from blood donors were also subjected to ELISA, SAT, and 2-ME tests. SAT was able to pinpoint only 23 (25%), whereas ELISA confirmed the etiology in 56 (60.9%; P < 0.001) patients with brucellosis, including 31 culture-confirmed cases. The sensitivity and specificity of ELISA were 100% and 71.31%, respectively. Because they were confirmed by ELISA, the diagnosis could never be excluded with SAT in 33 cases. ELISA has been found to be more sensitive in acute (28% higher sensitivity; P < 0.02) and chronic (55% higher sensitivity; P < 0.01) cases. For accurate diagnosis in suspected brucellosis cases detection, we recommend both ELISA IgM and IgG tests. ELISA IgG and 2-ME tests seem to be promising tools in judging prognosis.