Defective regulation of the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signalling pathway in cancers, haematological diseases, and chronic inflammatory conditions ...highlights its clinical significance. While several biologic and small molecule therapeutics targeting this pathway have been developed, these have several limitations. Therefore, there is a need to identify new targets for intervention. Suppressor of cytokine signalling (SOCS) proteins are a family of inducible inhibitors of cytokine receptors that activate the JAK-STAT pathway. Here we propose that newly identified mechanisms controlling SOCS function could be exploited to develop molecularly targeted drugs with unique modes of action to inhibit JAK-STAT signalling in disease.
The JAK-STAT signalling system utilised by many cytokines and growth factors has recently been exploited to develop a range of new therapies for chronic inflammatory disease, autoimmune conditions, and cancers. However, there have been several limitations, emphasising the need for more therapeutic options.
JAK-STAT signalling is controlled by induction of SOCS proteins, which act as part of a negative feedback loop to prevent sustained activation.
Identification of new regulatory mechanisms and protein–protein interactions has revealed new targets for generating more selective drugs for the range of conditions resulting from hyperactivation of the JAK-STAT pathway.
Deep neural networks (DNNs) can learn accurately from large quantities of labeled input data but often fail to do so when labeled data are scarce. DNNs sometimes fail to generalize on test data ...sampled from different input distributions. Unsupervised deep domain adaptation (DDA) techniques have been proven useful when no labels are available and when distribution shifts are observed in the target domain (TD). In this study, experiments are performed on seismic images of the F3 block 3-D dataset from offshore Netherlands source domain (SD) and Penobscot 3-D survey data from Canada (TD). Three geological classes from SD and TD that have similar reflection patterns are considered. A DNN architecture named EarthAdaptNet (EAN) is proposed to semantically segment the seismic images when few classes have data scarcity, and we use a transposed residual unit to replace the traditional dilated convolution in the decoder block. The EAN achieved a pixel-level accuracy >84% and an accuracy of <inline-formula> <tex-math notation="LaTeX">\sim 70 </tex-math></inline-formula>% for the minority classes, showing improved performance compared to existing architectures. In addition, we introduce the correlation alignment (CORAL) method to the EAN to create an unsupervised deep domain adaptation network (EAN-DDA) for the classification of seismic reflections from F3 and Penobscot to demonstrate possible approaches when labeled data are unavailable. Maximum class accuracy achieved was <inline-formula> <tex-math notation="LaTeX">\sim 99 </tex-math></inline-formula>% for class 2 of Penobscot with an overall accuracy >50%. Taken together, the EAN-DDA has the potential to classify TD seismic facies classes with high accuracy.
In this study, Newlands coal, spirulina microalgae samples, and mixtures of them were gasified in a fixed-bed downdraft reactor by CO2 at the atmospheric pressure and in the temperature range of ...950–1000 °C. The effects of the reaction temperature, the CO2 partial pressure, and the blending ratio on the syngas yield were studied. Results showed that the CO2 partial pressure did not affect the gas production yield until its value exceeded 0.05 MPa. The cogasification experimental results showed higher values than the predicted ones in terms of the gas production yield, especially H2 and CO components when the blending ratio of algae is 50% wt. This synergetic effect was mainly attributed to the catalytic activity of the high content of alkali and alkaline metals in algae. The increase of the reaction temperature led to a higher gas production yield as the Boudouard reaction is an endothermic reaction that went to a higher extent with the temperature increase.
Antimicrobial resistance (AMR) in poultry production chain is one of the major food safety concerns due to indiscriminate usage of antibiotics and the presence of pathogens such as Salmonella which ...causes infections in various stages of production. In the present study, 182 samples were collected from commercial broiler supply chain, viz., three hatcheries (n=29), three commercial broiler farms (CBF; n=99), and three retail meat shops (RMS; n=54), and used for isolation and identification of Salmonella using three different selective agar media and a selective enrichment medium followed by PCR confirmation targeting the hilA gene. The overall prevalence of Salmonella was 47/182 (25.82%), and a significantly higher (P<0.05) prevalence was observed in retail meat shops (46.29%), CBF (19.19%), and hatcheries (10.34%). Comparison of three agar media for isolation of Salmonella revealed that all the media were equally selective. However, PCR amplification of hilA gene fragment was significantly higher (P<0.01) in selective enrichment culture tetrathionate brilliant green bile broth (TTB) as compared to all solid (agar-based) media. Susceptibility pattern against most frequently used antibiotics revealed that 100% of the isolates were resistant to at least one antibiotic. High resistance was observed for doxycycline (94.34%), followed by cefpodoxime (84.91%), ciprofloxacin (72.64%), gentamicin (65.09%), enrofloxacin (61.32%), colistin sulphate (40.42%), amikacin (34.91%), ampicillin (33.96%), neomycin (33.02), cefotaxime (30.19%), ceftazidime (29.25%), trimethoprim-sulfamethoxazole (23.58%), amoxicillin+clavulanic acid (21.70%), and chloramphenicol (12.26%); 16.98% of the isolates were ex-tended spectrum β-lactamase (ESBL) producers, and 76.41% were multidrug resistant (MDR). MDR Salmonella were significantly higher (P<0.01) in RMS (91.66%) followed by CBF (82.75%), whereas no MDR isolates were present in the isolates from hatcheries. The results indicated a higher prevalence of Salmonella and AMR for commonly used antibiotics in the complete broiler supply chain, especially RMS and CBF. Also, this study idicated that TTB enrichment followed by PCR and colony PCR was found to be rapid, specific and time-saving method.
Abstract
Attempts have been made to treat nonsense-associated genetic disorders by chemical agents and hence an improved mechanistic insight into the decoding of readthrough signals is essential for ...the identification and characterisation of factors for the treatment of these disorders. To identify either novel compounds or genes that modulate translation readthrough, we have employed dual reporter-based high-throughput screens that use enzymatic and fluorescence activities and screened bioactive National Institute of Neurological Disease Syndrome (NINDS) compounds (n = 1000) and siRNA (n = 288) libraries. Whilst siRNAs targeting kinases such as CSNK1G3 and NME3 negatively regulate readthrough, neither the bioactive NINDS compounds nor PTC124 promote readthrough. Of note, PTC124 has previously been shown to promote readthrough. Furthermore, the impacts of G418 on the components of eukaryotic selenocysteine incorporation machinery have also been investigated. The selenocysteine machinery decodes the stop codon UGA specifying selenocysteine in natural selenoprotein genes. We have found that the eukaryotic SelC gene promotes the selenocysteine insertion sequence (SECIS)-mediated readthrough but inhibits the readthrough activity induced by G418. We have previously reported that SECIS-mediated readthrough at UGA codons follows a non-processive mechanism. Here, we show that G418-mediated promotion of readthrough also occurs through a non-processive mechanism which competes with translation termination. Based on our observations, we suggest that proteins generated through a non-processive mechanism may be therapeutically beneficial for the resolution of nonsense-associated genetic disorders.
Raster logs are scanned representations of the analog data recorded in subsurface drilling. Geologists rely on these images to interpret well-log curves and deduce the physical properties of ...geological formations. Scanned images contain various artifacts, including hand-written texts, brightness variability, scan defects, etc. The manual effort involved in reading the data is substantial. To mitigate this, unsupervised computer vision techniques are employed to extract and interpret the curves digitally. Existing algorithms predominantly require manual intervention, resulting in slow processing times, and are erroneous. This research aims to address these challenges by proposing VeerNet, a deep neural network architecture designed to semantically segment the raster images from the background grid to classify and digitize (i.e., extracting the analytic formulation of the written curve) the well-log data. The proposed approach is based on a modified UNet-inspired architecture leveraging an attention-augmented read-process-write strategy to balance retaining key signals while dealing with the different input-output sizes. The reported results show that the proposed architecture efficiently classifies and digitizes the curves with an overall F1 score of 35% and Intersection over Union of 30%, achieving 97% recall and 0.11 Mean Absolute Error when compared with real data on binary segmentation of multiple curves. Finally, we analyzed VeerNet's ability in predicting Gamma-ray values, achieving a Pearson coefficient score of 0.62 when compared to measured data.
We present photoionization cross-sections of the ground state (S1/2) and the first four excited states (2P1/2, 3/2, 2D3/2, 5/2) of the Fe xvi ion using the fully relativistic R-matrix code darc. The ...target wavefunctions are constructed with the fully relativistic grasp1 code. In our calculations, we have included core excitations up to n = 3, 4, which give rise to 89 fine-structure target levels of Fe xvii. In particular, the total photoionization cross-sections, which include important resonance structures for the four excited states of Fe xvi, are reported here for the first time. Our target state energies and the binding energy of the ground state of Fe xvi are found to be in good agreement with the experimental and theoretical results.
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► A novel synthetic method for the preparation of hydroxyl capped fluorescent carbon nanoparticles is reported. ► Functionalized carbon nanoparticles were derived from candle soot ...using organic base and surfactant. ► The minimum grain size of synthesized nanoparticles is reported as ≈7.3nm using Raman, TEM and DLS. ► Quantum yield of hydroxyls-coated carbon dots is calculated 0.1% using comparative method.
A new type of fluorescent carbon based nanomaterial has drawn considerable attention due to their unique physicochemical properties. Carboxyl functionalized carbon nanoparticles are well documented in the literature. However, the carbonyl moiety in the carboxyl group considerably reduces the photoluminescence quantum yield. In this study, we present a direct, simple and novel synthetic route to produce hydroxyl functionalized fluorescent carbon nanoparticles derived from candle soot using organic base and surfactant which could be readily scaled up. The functionalization of carbon nanoparticle was confirmed by various spectroscopic techniques. 1H NMR and FTIR measurements have been used to confirm the presence of sp2 carbon in the form of aryl and hydroxyl moieties. MALDI-TOF Mass and TGA measurements further confirmed the functionalization. Structural characterization of these particles by Raman spectroscopy showed characteristic peaks located at 1333 and 1583cm−1 corresponding to diamond-like (D) and graphite-like (G) bands of the carbon allotropes respectively. The minimum grain size of 7.3nm was calculated using Raman spectra of the functionalized carbon nanoparticles which corroborate well with the results of dynamic light scattering (DLS) and TEM studies. UV–vis spectroscopic measurements displayed an absorption band at ca. 245nm, which was consistent with the optical characteristics of functionalized carbon nanoparticles. PL measurements confirmed that the functionalized carbon nanoparticles have characteristic emission peak and shows fluorescence under blue light excitation. With a combination of free dispersion in water and attractive PL properties, these functionalized carbon nanoparticles hold promise for application in nanotechnology.
Acute kidney injury (AKI) is a common manifestation among patients critically ill with SARS-CoV-2 infection (Coronavirus 2019) and is associated with significant morbidity and mortality. The ...pathophysiology of renal failure in this context is not fully understood, but likely to be multifactorial. The intensive care unit outcomes of patients following COVID-19 acute critical illness with associated AKI have not been fully explored. We conducted a cohort study to investigate the risk factors for acute kidney injury in patients admitted to and intensive care unit with COVID-19, its incidence and associated outcomes.
We reviewed the medical records of all patients admitted to our adult intensive care unit suffering from SARS-CoV-2 infection from 14th March 2020 until 12th May 2020. Acute kidney injury was defined using the Kidney Disease Improving Global Outcome (KDIGO) criteria. The outcome analysis was assessed up to date as 3rd of September 2020.
A total of 81 patients admitted during this period. All patients had acute hypoxic respiratory failure and needed either noninvasive or invasive mechanical ventilatory support. Thirty-six patients (44%) had evidence of AKI (Stage I-33%, Stage II-22%, Renal Replacement Therapy (RRT)-44%). All patients with AKI stage III had RRT. Age, diabetes mellitus, immunosuppression, lymphopenia, high D-Dimer levels, increased APACHE II and SOFA scores, invasive mechanical ventilation and use of inotropic or vasopressor support were significantly associated with AKI. The peak AKI was at day 4 and mean duration of RRT was 12.5 days. The mortality was 25% for the AKI group compared to 6.7% in those without AKI. Among those received RRT and survived their illness, the renal function recovery is complete and back to baseline in all patients.
Acute kidney injury and renal replacement therapy is common in critically ill patients presenting with COVID-19. It is associated with increased severity of illness on admission to ICU, increased mortality and prolonged ICU and hospital length of stay. Recovery of renal function was complete in all survived patients.
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