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The formation of protein aggregates is a hallmark of many neurodegenerative diseases and systemic amyloidoses. These disorders are associated with the fibrillation of a variety of proteins/peptides, which ultimately leads to cell toxicity and tissue damage. Understanding how amyloid aggregation occurs and developing compounds that impair this process is a major challenge in the health science community. Here, we demonstrate that pathogenic proteins associated with Alzheimer's disease, diabetes, AL/AA amyloidosis, and amyotrophic lateral sclerosis can aggregate within stress-inducible physiological amyloid-based structures, termed amyloid bodies (A-bodies). Using a limited collection of small molecule inhibitors, we found that diclofenac could repress amyloid aggregation of the β-amyloid (1–42) in a cellular setting, despite having no effect in the classic Thioflavin T (ThT) in vitro fibrillation assay. Mapping the mechanism of the diclofenac-mediated repression indicated that dysregulation of cyclooxygenases and the prostaglandin synthesis pathway was potentially responsible for this effect. Together, this work suggests that the A-body machinery may be linked to a subset of pathological amyloidosis, and highlights the utility of this model system in the identification of new small molecules that could treat these debilitating diseases. [ABSTRACT FROM AUTHOR]

Traditionally, in the oil and gas industry, accelerometers are mounted externally on motors for condition monitoring of vertically suspended, closed suction hydrocarbon pumps due to their inability to withstand harsh downhole environments, preventing the detection of impeller failures. This study addresses the need for encapsulation solutions for accelerometers submerged in hydrocarbon fluid environments. It evaluates the feasibility of epoxy and fluoroelastomer as encapsulation materials for long-term immersion in high-temperature hydrocarbon fluid and determines their impact on the accelerometer's performance. Extensive testing involved submersion in high-temperature hydrocarbon fluid at 150 °C for over 10,000 h and six months in brine. Material characterization, including mass variation, microscopic imaging, and FTIR spectroscopy, revealed negligible degradation. Encapsulated accelerometers effectively detected vibrations with an acceptable alteration in amplitude. In comparison with commercial alternatives, our encapsulation outperformed them. While oil traces became evident within just 24 h in the alternatives, our solution exhibited no signs of leakage. This research pioneers a novel packaging solution employing epoxy and fluoroelastomer for side-exit commercial sensors tailored for high-temperature hydrocarbon fluid applications, addressing a critical gap in the industry. Our work enhances reliability and safety for vertical oil pump condition monitoring in downhole applications, benefiting the oil and gas sector. [ABSTRACT FROM AUTHOR]

The fabrication of a Poly (vinylidene fluoride) membrane (PVDF) and ceramic-assisted bismuth vanadate-polyvinylidene fluoride (BiVO4-PVDF) composite membrane was achieved through the utilization of the electrospinning technique. The composition and structure of the fabricated membranes were characterized by X-ray powder diffraction, Raman analysis, scanning electron microscopy, Thermo gravimetric analyzer, Fourier transform infrared spectroscopy, and UV–Vis spectroscopy techniques. The prepared polymeric membranes were then utilized for catalytic investigation and to explore, how structure affects catalytic activity using 5 mg/L, 10 mL methylene blue (MB) dye solution. Ultrasonication, visible light irradiation, and the combination were used to study piezocatalysis, photocatalysis, and piezo-photocatalysis, moreover, degradation intermediates were also explored using scavengers. Electrospun BiVO4-PVDF (BV-PVDF) composite has been found to have better piezocatalytic and photocatalytic properties than PVDF. The experimental findings reveal that the composite of BiVO4-PVDF demonstrates the highest efficiency in dye degradation, achieving a maximum degradation rate of 61% within a processing time of 180 min. The rate of degradation was calculated to be 0.0047 min−1, indicating a promising potential for the composite in the field of dye degradation. [ABSTRACT FROM AUTHOR]

A novel information-theoretic approach is proposed to assess the global practical identifiability of Bayesian statistical models. Based on the concept of conditional mutual information, an estimate of information gained for each model parameter is used to quantify the identifiability with practical considerations. No assumptions are made about the structure of the statistical model or the prior distribution while constructing the estimator. The estimator has the following notable advantages: first, no controlled experiment or data is required to conduct the practical identifiability analysis; second, unlike popular variance-based global sensitivity analysis methods, different forms of uncertainties, such as model-form, parameter, or measurement can be taken into account; third, the identifiability analysis is global, and therefore independent of a realization of the parameters. If an individual parameter has low identifiability, it can belong to an identifiable subset such that parameters within the subset have a functional relationship and thus have a combined effect on the statistical model. The practical identifiability framework is extended to highlight the dependencies between parameter pairs that emerge a posteriori to find identifiable parameter subsets. The applicability of the proposed approach is demonstrated using a linear Gaussian model and a non-linear methane-air reduced kinetics model. It is shown that by examining the information gained for each model parameter along with its dependencies with other parameters, a subset of parameters that can be estimated with high posterior certainty can be found. [ABSTRACT FROM AUTHOR]

The formation of protein aggregates is a hallmark of many neurodegenerative diseases and systemic amyloidoses. These disorders are associated with the fibrillation of a variety of proteins/peptides, which ultimately leads to cell toxicity and tissue damage. Understanding how amyloid aggregation occurs and developing compounds that impair this process is a major challenge in the health science community. Here, we demonstrate that pathogenic proteins associated with Alzheimer's disease, diabetes, AL/AA amyloidosis, and amyotrophic lateral sclerosis can aggregate within stress-inducible physiological amyloid-based structures, termed amyloid bodies (A-bodies). Using a limited collection of small molecule inhibitors, we found that diclofenac could repress amyloid aggregation of the β-amyloid (1–42) in a cellular setting, despite having no effect in the classic Thioflavin T (ThT) in vitro fibrillation assay. Mapping the mechanism of the diclofenac-mediated repression indicated that dysregulation of cyclooxygenases and the prostaglandin synthesis pathway was potentially responsible for this effect. Together, this work suggests that the A-body machinery may be linked to a subset of pathological amyloidosis, and highlights the utility of this model system in the identification of new small molecules that could treat these debilitating diseases. [ABSTRACT FROM AUTHOR]

Tumors exhibit high molecular, phenotypic, and physiological heterogeneity. In this effort, we employ quantitative magnetic resonance imaging (MRI) data to capture this heterogeneity through imaging-based subregions or "habitats" in a murine model of glioma. We then demonstrate the ability to model and predict the growth of the habitats using coupled ordinary differential equations (ODEs) in the presence and absence of radiotherapy. Female Wistar rats (N = 21) were inoculated intracranially with 106 C6 glioma cells, a subset of which received 20 Gy (N = 5) or 40 Gy (N = 8) of radiation. All rats underwent diffusion-weighted and dynamic contrast-enhanced MRI at up to seven time points. All MRI data at each visit were subsequently clustered using k-means to identify physiological tumor habitats. A family of four models consisting of three coupled ODEs were developed and calibrated to the habitat time series of control and treated rats and evaluated for predictive capability. The Akaike Information Criterion was used for model selection, and the normalized sum-of-square-error (SSE) was used to evaluate goodness-of-fit in model calibration and prediction. Three tumor habitats with significantly different imaging data characteristics (p < 0.05) were identified: high-vascularity high-cellularity, low-vascularity high-cellularity, and low-vascularity low-cellularity. Model selection resulted in a five-parameter model whose predictions of habitat dynamics yielded SSEs that were similar to the SSEs from the calibrated model. It is thus feasible to mathematically describe habitat dynamics in a preclinical model of glioma using biology-based ODEs, showing promise for forecasting heterogeneous tumor behavior. [ABSTRACT FROM AUTHOR]

Tumors exhibit high molecular, phenotypic, and physiological heterogeneity. In this effort, we employ quantitative magnetic resonance imaging (MRI) data to capture this heterogeneity through imaging-based subregions or "habitats" in a murine model of glioma. We then demonstrate the ability to model and predict the growth of the habitats using coupled ordinary differential equations (ODEs) in the presence and absence of radiotherapy. Female Wistar rats (N = 21) were inoculated intracranially with 106 C6 glioma cells, a subset of which received 20 Gy (N = 5) or 40 Gy (N = 8) of radiation. All rats underwent diffusion-weighted and dynamic contrast-enhanced MRI at up to seven time points. All MRI data at each visit were subsequently clustered using k-means to identify physiological tumor habitats. A family of four models consisting of three coupled ODEs were developed and calibrated to the habitat time series of control and treated rats and evaluated for predictive capability. The Akaike Information Criterion was used for model selection, and the normalized sum-of-square-error (SSE) was used to evaluate goodness-of-fit in model calibration and prediction. Three tumor habitats with significantly different imaging data characteristics (p < 0.05) were identified: high-vascularity high-cellularity, low-vascularity high-cellularity, and low-vascularity low-cellularity. Model selection resulted in a five-parameter model whose predictions of habitat dynamics yielded SSEs that were similar to the SSEs from the calibrated model. It is thus feasible to mathematically describe habitat dynamics in a preclinical model of glioma using biology-based ODEs, showing promise for forecasting heterogeneous tumor behavior. [ABSTRACT FROM AUTHOR]

WTe2 is one of the wonder layered materials, displays interesting overlapping of electron–hole pairs, opening of the surface bandgap, anisotropy in its crystal structure and very much sought appealing material for room temperature broadband photodection applications. Here we report the photoresponse of WTe2 thin films and microchannel devices fabricated on silicon nitride substrates. A clear sharp rise in photocurrent observed under the illumination of visible (532 nm) and NIR wavelengths (1064 nm). The observed phoresponse is very convincing and repetitive for ON /OFF cycles of laser light illumination. The channel length dependence of photocurrent is noticed for few hundred nanometers to micrometers. The photocurrent, rise & decay times, responsivity and detectivity are studied using different channel lengths. Strikingly microchannel gives few orders of greater responsivity compared to larger active area investigated here. The responsivity and detectivity are observed as large as 29 A/W and 3.6 × 108 Jones respectively. The high performing photodetection properties indicate that WTe2 can be used as a broad band material for future optoelectronic applications. [ABSTRACT FROM AUTHOR]

Adult central nervous system (CNS) axons fail to regenerate after injury, and master regulators of the regenerative program remain to be identified. We analyzed the transcriptomes of retinal ganglion cells (RGCs) at 1 and 5 days after optic nerve injury with and without a cocktail of strongly pro-regenerative factors to discover genes that regulate survival and regeneration. We used advanced bioinformatic analysis to identify the top transcriptional regulators of upstream genes and cross-referenced these with the regulators upstream of genes differentially expressed between embryonic RGCs that exhibit robust axon growth vs. postnatal RGCs where this potential has been lost. We established the transcriptional activator Elk-1 as the top regulator of RGC gene expression associated with axon outgrowth in both models. We demonstrate that Elk-1 is necessary and sufficient to promote RGC neuroprotection and regeneration in vivo, and is enhanced by manipulating specific phosphorylation sites. Finally, we co-manipulated Elk-1, PTEN, and REST, another transcription factor discovered in our analysis, and found Elk-1 to be downstream of PTEN and inhibited by REST in the survival and axon regenerative pathway in RGCs. These results uncover the basic mechanisms of regulation of survival and axon growth and reveal a novel, potent therapeutic strategy to promote neuroprotection and regeneration in the adult CNS. [ABSTRACT FROM AUTHOR]

CoViD19 is a novel disease which has created panic worldwide by infecting millions of people around the world. The last significant variant of this virus, called as omicron, contributed to majority of cases in the third wave across globe. Though lesser in severity as compared to its predecessor, the delta variant, this mutation has shown higher communicable rate. This novel virus with symptoms of pneumonia is dangerous as it is communicable and hence, has engulfed entire world in a very short span of time. With the help of machine learning techniques, entire process of detection can be automated so that direct contacts can be avoided. Therefore, in this paper, experimentation is performed on CoViD19 chest X-ray images using higher order statistics with iterative and non-iterative models. Higher order statistics provide a way of analyzing the disturbances in the chest X-ray images. The results obtained are quite good with 96.64% accuracy using a non-iterative model. For fast testing of the patients, non-iterative model is preferred because it has advantage over iterative model in terms of speed. Comparison with some of the available state-of-the-art methods and some iterative methods proves efficacy of the work. [ABSTRACT FROM AUTHOR]

Software effort estimation is a significant part of software development and project management. The accuracy of effort estimation and scheduling results determines whether a project succeeds or fails. Many studies have focused on improving the accuracy of predicted results, yet accurate estimation of effort has proven to be a challenging task for researchers and practitioners, particularly when it comes to projects that use agile approaches. This work investigates the application of the adaptive neuro-fuzzy inference system (ANFIS) along with the novel Energy-Efficient BAT (EEBAT) technique for effort prediction in the Scrum environment. The proposed ANFIS-EEBAT approach is evaluated using real agile datasets. It provides the best results in all the evaluation criteria used. The proposed approach is also statistically validated using nonparametric tests, and it is found that ANFIS-EEBAT worked best as compared to various state-of-the-art meta-heuristic and machine learning (ML) algorithms such as fireworks, ant lion optimizer (ALO), bat, particle swarm optimization (PSO), and genetic algorithm (GA). [ABSTRACT FROM AUTHOR]

Every human being has a different electro-cardio-graphy (ECG) waveform that provides information about the well being of a human heart. Therefore, ECG waveform can be used as an effective identification measure in biometrics and many such applications of human identification. To achieve fast and accurate identification of human beings using ECG signals, a novel robust approach has been introduced here. The databases of ECG utilized during the experimentation are MLII, UCI repository arrhythmia and PTBDB databases. All these databases are imbalanced; hence, resampling techniques are helpful in making the databases balanced. Noise removal is performed with discrete wavelet transform (DWT) and features are obtained with multi-cumulants. This approach is mainly based on features extracted from the ECG data in terms of multi-cumulants. The multi-cumulants feature based ECG data is classified using kernel extreme learning machine (KELM). The parameters of multi-cumulants and KELM are optimized using genetic algorithm (GA). Excellent classification rate is achieved with 100% accuracy on MLII and UCI repository arrhythmia databases, and 99.57% on PTBDB database. Comparison with existing state-of-art approaches has also been performed to prove the efficacy of the proposed approach. Here, the process of classification in the proposed approach is named as evolutionary hybrid classifier. [ABSTRACT FROM AUTHOR]

Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-023-30010-6, published online 20 February 2023 The original version of this Article contained an error in the Funding section. The original article can be found online at https://doi.org/10.1038/s41598-023-30010-6. [Extracted from the article]

Industrial Internet of Things (IIoT) seeks more attention in attaining enormous opportunities in the field of Industry 4.0. But there exist severe challenges related to data privacy and security when processing the automatic and practical data collection and monitoring over industrial applications in IIoT. Traditional user authentication strategies in IIoT are affected by single factor authentication, which leads to poor adaptability along with the increasing users count and different user categories. For addressing such issue, this paper aims to implement the privacy preservation model in IIoT using the advancements of artificial intelligent techniques. The two major stages of the designed system are the sanitization and restoration of IIoT data. Data sanitization hides the sensitive information in IIoT for preventing it from leakage of information. Moreover, the designed sanitization procedure performs the optimal key generation by a new Grasshopper–Black Hole Optimization (G–BHO) algorithm. A multi-objective function involving the parameters like degree of modification, hiding rate, correlation coefficient between the actual data and restored data, and information preservation rate was derived and utilized for generating optimal key. The simulation result establishes the dominance of the proposed model over other state-of the-art models in terms of various performance metrics. In respect of privacy preservation, the proposed G–BHO algorithm has achieved 1%, 15.2%, 12.6%, and 1% enhanced result than JA, GWO, GOA, and BHO, respectively. [ABSTRACT FROM AUTHOR]

Monoclonal antibody Trastuzumab/Herceptin is considered as frontline therapy for Her2-positive breast cancer patients. However, it is not effective against several patients due to acquired or de novo resistance. In last one decade, several assays have been performed to understand the mechanism of Herceptin resistance with/without supplementary drugs. This manuscript describes a database HerceptinR, developed for understanding the mechanism of resistance at genetic level. HerceptinR maintains information about 2500 assays performed against various breast cancer cell lines (BCCs), for improving sensitivity of Herceptin with or without supplementary drugs. In order to understand Herceptin resistance at genetic level, we integrated genomic data of BCCs that include expression, mutations and copy number variations in different cell lines. HerceptinR will play a vital role in i) designing biomarkers to identify patients eligible for Herceptin treatment and ii) identification of appropriate supplementary drug for a particular patient. HerceptinR is available at http://crdd.osdd.net/raghava/herceptinr/. [ABSTRACT FROM AUTHOR]

With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT) based solutions are gaining prominence and innovative Peer To Peer (P2P) energy trading at micro-level are being deployed. Such advancement, however leave traditional security models vulnerable and pave the path for Blockchain, an Distributed Ledger Technology (DLT) with its decentralized, open and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, massive volumes of micro transactions are required to be supported, which become a performance bottleneck with existing Blockchain solution such as Hyperledger, Ethereum and so on. In this paper, a lightweight 'Tangle' based framework, namely IOTA (Third generation DLT) is employed for designing an energy trading market that uses Directed Acyclic Graph (DAG) based solution that not only alleviates the reward overhead for micro-transactions but also provides scalability, quantum-proof, and high throughput of such transactions at low confirmation latency. Furthermore the Masked Authentication Messaging (MAM) protocol is used over the IOTA P2P energy trading framework that allows energy producer and consumer to share the data while maintaining the confidentiality, and facilitates the data accessibility. The Raspberry Pi 3 board along with voltage sensor (INA219) used for the setting up light node and publishing and fetching data from the Tangle. The results of the obtained benchmarking indicate low confirmation latency, high throughput, system with Hyperledger Fabric and Ethereum. Moreover, the effect of transaction rate decreases when the IOTA bundle size increases more than 10. For bundle size 5 and 10 it behaves absolutely better than any other platform. The speedy confirmation time of transactions in IOTA, is most suitable for peer to peer energy trading scenarios. This study serves as a guideline for deploying, end-to-end transaction with IOTA Distributed Ledger Technology (DLT) and improving the performance of Blockchain in the energy sector under various operating conditions. [ABSTRACT FROM AUTHOR]

Angiogenesis is a critical process in tumor progression. Inhibition of angiogenesis by blocking VEGF signaling can impair existing tumor vessels and halt tumor progression. However, the benefits are transient, and most patients who initially respond to these therapies develop resistance. Accordingly, there is a need for new anti-angiogenesis therapeutics to delay the processes of resistance or eliminate the resistive effects entirely. This manuscript presents the results of a screen of the National Institutes of Health Clinical Collections Libraries I & II (NIHCCLI&II) for novel angiogenesis inhibitors. The 727 compounds of the NIHCCLI&II library were screened with a high-throughput drug discovery platform (HTP) developed previously with angiogenesis-specific protocols utilizing zebrafish. The screen resulted in 14 hit compounds that were subsequently narrowed down to one, with PD 81,723 chosen as the lead compound. PD 81,723 was validated as an inhibitor of angiogenesis in vivo in zebrafish and in vitro in human umbilical vein endothelial cells (HUVECs). Zebrafish exposed to PD 81,723 exhibited several signs of a diminished endothelial network due to the inhibition of angiogenesis. Immunochemical analysis did not reveal any significant apoptotic or mitotic activity in the zebrafish. Assays with cultured HUVECs elucidated the ability of PD 81,723 to inhibit capillary tube formation, migration, and proliferation of endothelial cells. In addition, PD 81,723 did not induce apoptosis while significantly down regulating p21, AKT, VEGFR-2, p-VEGFR-2, eNOS, and p-eNOS, with no notable change in endogenous VEGF-A in cultured HUVECs. [ABSTRACT FROM AUTHOR]

Saroglitazar, a dual peroxisome proliferator activated receptor α/γ agonist, approved for diabetic dyslipidemia (DD), is potential therapeutic option for non-alcoholic fatty liver disease (NAFLD). This prospective, observational, real-world study aimed to determine efficacy and safety of Saroglitazar in patients with NAFLD and DD. We included patients with DD and NAFLD who received Saroglitazar 4 mg once daily for 24 weeks. Blood investigations, liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) (FibroScan) were compared at baseline and 24 weeks. Of 163 patients screened, 107 were included, and 101 completed 24 weeks treatment (mean age 50.4 ± 12.3 years, 78.5% males, mean body mass index 28.8 ± 4.2). After 24 weeks, alanine transaminase (ALT) reduced significantly from 94 (47–122) to 39 (31–49) (p < 0.0001) and aspartate aminotransferase (AST) (U/L) from 89 (43–114) to 37 (30–47) (p < 0.0001) and LSM (kPa) from 8.4 (7.1–9.3) to 7.5 (6.4–8.4) (p = 0.0261). CAP, glycated hemoglobin and lipid parameters also improved significantly. On linear regression, there was significant association between percent change in ALT and AST with TG reduction after treatment (p = 0.024 and 0.037 respectively).We conclude that Saroglitazar leads to significant improvement in transaminases, LSM, and CAP in NAFLD patients with DD. [ABSTRACT FROM AUTHOR]

Blast disease incited by Magnaporthe oryzae is a major threat to sustain rice production in all rice growing nations. The pathogen is widely distributed in all rice paddies and displays rapid aerial transmissions, and seed-borne latent infection. In order to understand the genetic variability, host specificity, and molecular basis of the pathogenicity-associated traits, the whole genome of rice infecting Magnaporthe oryzae (Strain RMg_Dl) was sequenced using the Illumina and PacBio (RSII compatible) platforms. The high-throughput hybrid assembly of short and long reads resulted in a total of 375 scaffolds with a genome size of 42.43 Mb. Furthermore, comparative genome analysis revealed 99% average nucleotide identity (ANI) with other oryzae genomes and 83% against M. grisea, and 73% against M. poe genomes. The gene calling identified 10,553 genes with 10,539 protein-coding sequences. Among the detected transposable elements, the LTR/Gypsy and Type LINE showed high occurrence. The InterProScan of predicted protein sequences revealed that 97% protein family (PFAM), 98% superfamily, and 95% CDD were shared among RMg_Dl and reference 70-15 genome, respectively. Additionally, 550 CAZymes with high GH family content/distribution and cell wall degrading enzymes (CWDE) such endoglucanase, beta-glucosidase, and pectate lyase were also deciphered in RMg_Dl. The prevalence of virulence factors determination revealed that 51 different VFs were found in the genome. The biochemical pathway such as starch and sucrose metabolism, mTOR signaling, cAMP signaling, MAPK signaling pathways related genes were identified in the genome. The 49,065 SNPs, 3267 insertions and 3611 deletions were detected, and majority of these varinats were located on downstream and upstream region. Taken together, the generated information will be useful to develop a specific marker for diagnosis, pathogen surveillance and tracking, molecular taxonomy, and species delineation which ultimately leads to device improved management strategies for blast disease. [ABSTRACT FROM AUTHOR]

A fresh and frozen high-quality patient bio-sample is required in molecular medicine for the identification of disease-associated mechanism at molecular levels. A common cooling procedure is immersing the tissue enclosed in a vial in a coolant such as liquid nitrogen. This procedure is not user friendly and is laborious as reducing the lag time from excision time to freezing depends on the logistic organizational structure within a hospital. Moreover snapfreezing must be done as soon as possible after tissue excision to preserve the tissue quality for molecular tests. Herein, we report an electrically powered snap freezing device as an alternative to quenching the vial in liquid nitrogen and therefore can be used directly at the location where the tissue is acquired. This device also facilitates the study of the effect of freezing conditions on the various molecular processes in the samples. Cooling experiments of a vial in the snap freezing device show that the cooling rates similar to or faster than quenching in liquid nitrogen are feasible. We performed experiments with several set point conditions and compared the results with a mathematical model. [ABSTRACT FROM AUTHOR]

Exposure to particulate matter less than 2.5 µm in diameter (PM2.5) is a cause of concern in cities and major emission regions of northern India. An intensive field campaign involving the states of Punjab, Haryana and Delhi national capital region (NCR) was conducted in 2022 using 29 Compact and Useful PM2.5 Instrument with Gas sensors (CUPI-Gs). Continuous observations show that the PM2.5 in the region increased gradually from < 60 µg m−3 in 6–10 October to up to 500 µg m−3 on 5–9 November, which subsequently decreased to about 100 µg m−3 in 20–30 November. Two distinct plumes of PM2.5 over 500 µg m−3 are tracked from crop residue burning in Punjab to Delhi NCR on 2–3 November and 10–11 November with delays of 1 and 3 days, respectively. Experimental campaign demonstrates the advantages of source region observations to link agricultural waste burning and air pollution at local to regional scales. [ABSTRACT FROM AUTHOR]

We evaluated the 6-year incidence and risk factors of pterygium in a multi-ethnic Asian population. Participants who attended the baseline visit of the Singapore Epidemiology of Eye Diseases Study (year 2004–2011) and returned six years later, were included in this study. Pterygium was diagnosed based on anterior segment photographs. Incident pterygium was defined as presence of pterygium at 6-year follow-up in either eye, among individuals without pterygium at baseline. Multivariable logistic regression models were used to determine factors associated with incident pterygium, adjusting for baseline age, gender, ethnicity, body mass index, occupation type, educational level, income status, smoking, alcohol consumption, presence of hypertension, diabetes and hyperlipidemia. The overall age-adjusted 6-year incidence of pterygium was 1.2% (95% confidence interval [CI] 1.0–1.6%); with Chinese (1.9%; 95% CI 1.4%-2.5%) having the highest incidence rate followed by Malays (1.4%; 95% CI 0.9%-2.1%) and Indians (0.3%; 95% CI 0.3–0.7%). In multivariable analysis, Chinese (compared with Indians; odds ratio [OR] = 4.21; 95% CI 2.12–9.35) and Malays (OR 3.22; 95% CI 1.52–7.45), male (OR 2.13; 95% CI 1.26–3.63), outdoor occupation (OR 2.33; 95% CI 1.16–4.38), and smoking (OR 0.41; 95% CI 0.16–0.87) were significantly associated with incident pterygium. Findings from this multi-ethnic Asian population provide useful information in identifying at-risk individuals for pterygium. [ABSTRACT FROM AUTHOR]

Exposure to particulate matter less than 2.5 µm in diameter (PM2.5) is a cause of concern in cities and major emission regions of northern India. An intensive field campaign involving the states of Punjab, Haryana and Delhi national capital region (NCR) was conducted in 2022 using 29 Compact and Useful PM2.5 Instrument with Gas sensors (CUPI-Gs). Continuous observations show that the PM2.5 in the region increased gradually from < 60 µg m−3 in 6–10 October to up to 500 µg m−3 on 5–9 November, which subsequently decreased to about 100 µg m−3 in 20–30 November. Two distinct plumes of PM2.5 over 500 µg m−3 are tracked from crop residue burning in Punjab to Delhi NCR on 2–3 November and 10–11 November with delays of 1 and 3 days, respectively. Experimental campaign demonstrates the advantages of source region observations to link agricultural waste burning and air pollution at local to regional scales. [ABSTRACT FROM AUTHOR]

Identification of appropriate breeds of broilers and development of new feed additives is required for the development of poultry industry at high altitude. Therefore, this experiment was conducted first to identify the suitable broiler strain for this region. One week old chicks (150) from three broiler strains, i.e. Vencobb, RIR cross-bred, and Hubbard were randomly selected and divided equally into three groups. All the chicks were provided the same basal diet. The body weight gain and feed: gain responses were significantly (P < 0.05) improved in RIR cross-bred. Mortality was also observed lower in RIR cross-bred. Thereafter, the second trial was conducted in RIR cross-bred to evaluate the effect of probiotic supplementation (T1@ 9 gm/kg feed, T2@ 18 gm/kg feed) on their performance and mortality. No significant differences (P > 0.05) were observed in weight gain, feed intake, feed: gain, and water intake among the three groups, however, mortality from ascites and coccidiosis was reduced in probiotic treated groups. Hence, our results suggest that RIR cross-bred is suitable for rearing in high altitude regions and probiotic supplementation has no beneficial effects on production performance of broilers at high altitude. However, probiotic supplementation indicated lesser loss due to mortality of birds. [ABSTRACT FROM AUTHOR]

Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-022-18603-z, published online 25 August 2022 The original version of this Article contained an error in Affiliation 1, which was incorrectly given as 'School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Vijayawada 522237, Andhra Pradesh, India'. The correct affiliation is listed below: School of Computer Science and Engineering (SCOPE), VIT-AP University, Vijayawada 522237, Andhra Pradesh, India. [Extracted from the article]

The CCR4-NOT complex is conserved in eukaryotes and is involved in mRNA metabolism, though its molecular physiological roles remain to be established. We show here that CNOT3-depleted mouse embryonic fibroblasts (MEFs) undergo cell death. Levels of other complex subunits are decreased in CNOT3-depleted MEFs. The death phenotype is rescued by introduction of wild-type (WT), but not mutated CNOT3, and is not suppressed by the pan-caspase inhibitor, zVAD-fluoromethylketone. Gene expression profiling reveals that mRNAs encoding cell death-related proteins, including receptor-interacting protein kinase 1 (RIPK1) and RIPK3, are stabilized in CNOT3-depleted MEFs. Some of these mRNAs bind to CNOT3, and in the absence of CNOT3 their poly(A) tails are elongated. Inhibition of RIPK1-RIPK3 signaling by a short-hairpin RNA or a necroptosis inhibitor, necrostatin-1, confers viability upon CNOT3-depleted MEFs. Therefore, we conclude that CNOT3 targets specific mRNAs to prevent cells from being disposed to necroptotic death. [ABSTRACT FROM AUTHOR]

For the past 30 years, oocytes from Xenopus laevis have been extensively used to express and characterise ion channels in an easily controlled environment. Here we report the first use of oocytes from the closely related species Xenopus borealis as an alternative expression system for neuronal ion channels. Using the two-electrode voltage-clamp technique, we show that a wide variety of voltageand ligand-gated ion channels have the same channel properties and pharmacological profiles when expressed in either X. laevis or X. borealis oocytes. Potential advantages of the X. borealis oocytes include a smaller endogenous chloride current and the ability to produce more intense fluorescence signals when studied with voltage-clamp fluorometry. Scanning electron microscopy revealed a difference in vitelline membrane structure between the two species, which may be related to the discrepancy in fluorescence signals observed. We demonstrate that X. borealis oocytes are a viable heterologous system for expression of neuronal ion channels with some potential advantages over X. laevis oocytes for certain applications. [ABSTRACT FROM AUTHOR]

Colorectal cancer is one of the most common cancers worldwide, accounting for an annual estimated 1.8 million incident cases. With the increasing number of colonoscopies being performed, colorectal biopsies make up a large proportion of any histopathology laboratory workload. We trained and validated a unique artificial intelligence (AI) deep learning model as an assistive tool to screen for colonic malignancies in colorectal specimens, in order to improve cancer detection and classification; enabling busy pathologists to focus on higher order decision-making tasks. The study cohort consists of Whole Slide Images (WSI) obtained from 294 colorectal specimens. Qritive's unique composite algorithm comprises both a deep learning model based on a Faster Region Based Convolutional Neural Network (Faster-RCNN) architecture for instance segmentation with a ResNet-101 feature extraction backbone that provides glandular segmentation, and a classical machine learning classifier. The initial training used pathologists' annotations on a cohort of 66,191 image tiles extracted from 39 WSIs. A subsequent application of a classical machine learning-based slide classifier sorted the WSIs into 'low risk' (benign, inflammation) and 'high risk' (dysplasia, malignancy) categories. We further trained the composite AI-model's performance on a larger cohort of 105 resections WSIs and then validated our findings on a cohort of 150 biopsies WSIs against the classifications of two independently blinded pathologists. We evaluated the area under the receiver-operator characteristic curve (AUC) and other performance metrics. The AI model achieved an AUC of 0.917 in the validation cohort, with excellent sensitivity (97.4%) in detection of high risk features of dysplasia and malignancy. We demonstrate an unique composite AI-model incorporating both a glandular segmentation deep learning model and a classical machine learning classifier, with excellent sensitivity in picking up high risk colorectal features. As such, AI plays a role as a potential screening tool in assisting busy pathologists by outlining the dysplastic and malignant glands. [ABSTRACT FROM AUTHOR]

This study aimed to determine COVID-19-related awareness, knowledge, impact and preparedness among elderly Asians; and to evaluate their acceptance towards digital health services amidst the pandemic. 523 participants (177 Malays, 171 Indians, 175 Chinese) were recruited and underwent standardised phone interview during Singapore's lockdown period (07 April till 01 June 2020). Multivariable logistic regression models were performed to evaluate the associations between demographic, socio-economic, lifestyle, and systemic factors, with COVID-19 awareness, knowledge, preparedness, well-being and digital health service acceptance. The average perception score on the seriousness of COVID-19 was 7.6 ± 2.4 (out of 10). 75.5% of participants were aware that COVID-19 carriers can be asymptomatic. Nearly all (≥ 90%) were aware of major prevention methods for COVID-19 (i.e. wearing of mask, social distancing). 66.2% felt prepared for the pandemic, and 86.8% felt confident with government's handling and measures. 78.4% felt their daily routine was impacted. 98.1% reported no prior experience in using digital health services, but 52.2% felt these services would be helpful to reduce non-essential contact. 77.8% were uncomfortable with artificial intelligence software interpreting their medical results. In multivariable analyses, Chinese participants felt less prepared, and more likely felt impacted by COVID-19. Older and lower income participants were less likely to use digital health services. In conclusion, we observed a high level of awareness and knowledge on COVID-19. However, acceptance towards digital health service was low. These findings are valuable for examining the effectiveness of COVID-19 communication in Singapore, and the remaining gaps in digital health adoption among elderly. [ABSTRACT FROM AUTHOR]

We evaluated the agreements in foveal avascular zone (FAZ) area and vessel density (VD) parameters (within the superficial capillary plexus region), between two widely used optical coherence tomography angiography machines. Participants who attended the Singapore Malay Eye Study III between 29th March and 6th August 2018, were enrolled in this study. Participants underwent fovea-centered 6×6-mm macular cube scan, using both AngioVue and Cirrus HDOCT machines. Scans were analyzed automatically using built-in review software of each machine. 177 eyes (95 participants) without retinal diseases were included for final analysis. Mean FAZ area was 0.38 ± 0.11 mm2 and 0.30 ± 0.10 mm2, based on AngioVue and Cirrus HDOCT, respectively. Mean parafoveal VD was 0.50 ± 0.04 in Angiovue, and 0.43 ± 0.04 in Cirrus HDOCT. Cirrus HDOCT measurements were consistently lower than those by AngioVue, with a mean difference of −0.08 (95% limits of agreement [LOA], −0.30–0.13) mm2 for FAZ area, and −0.07 (95% LOA, −0.17–0.03) for parafoveal VD. Intraclass correlation coefficients for FAZ area and parafoveal VD were 0.33 and 0.07, respectively. Our data suggest that agreements between AngioVue and Cirrus HDOCT machines were poor to fair, thus alternating use between these two machines may not be recommended especially for follow up evaluations. [ABSTRACT FROM AUTHOR]

Induction of posterior vitreous detachment (PVD) by pharmacologic vitreolysis has been largely attempted through the use of enzymatic reagents. Ocriplasmin has been the only FDA-approved clinical reagent so far. Several adverse effects of ocriplasmin have emerged, however, and the search for alternative PVD-inducing reagents continues. Since i) collagen forms an important structural component of the vitreous, and ii) strong vitreo-retinal adhesions exist between the cortical vitreous and the internal limiting membrane (ILM) of the retina, an effective PVD-inducing reagent would require both, vitreous liquefaction, and concurrent dehiscence of vitreoretinal adhesion, without being toxic to retinal cells. We designed a combination of two reagents to achieve these two objectives; a triple helix-destabilizing collagen binding domain (CBD), and a fusion of RGD (integrin-binding) tripeptide with CBD (RCBD) to facilitate separation of posterior cortical vitreous from retinal surface. Based on in vitro, ex-vivo, and in vivo experiments, we show that a combination of CBD and RCBD displays potential for safe pharmacologic vitreolysis. Our findings assume significance in light of the fact that synthetic RGD-containing peptides have already been used for inhibition of tumor cell invasion. Proteins such as variants of collagen binding domains could have extended therapeutic uses in the future. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the association between optical coherence tomography (OCT)-measured retinal layer thickness parameters with clinical and patient-centred visual outcomes in healthy eyes. Participants aged 40 and above were recruited from the Singapore Epidemiology of Eye Diseases Study, a multi-ethnic population-based study. Average macular, ganglion cell-inner plexiform layer (GCIPL), and outer retinal thickness parameters were obtained using the Cirrus High Definition-OCT. Measurements of best-corrected visual acuity (BCVA) and 11-item visual functioning questionnaire (VF-11) were performed. Associations between macular thickness parameters, with BCVA and Rasch-transformed VF-11 scores (in logits) were assessed using multivariable linear regression models with generalized estimating equations, adjusted for relevant confounders. 4,540 subjects (7,744 eyes) with a mean age of 58.8 ± 8.6 years were included. The mean BCVA (LogMAR) was 0.10 ± 0.11 and mean VF-11 score was 5.20 ± 1.29. In multivariable regression analysis, thicker macula (per 20 µm; β = −0.009) and GCIPL (per 20 µm; β = −0.031) were associated with better BCVA (all p ≤ 0.001), while thicker macula (per 20 µm; β = 0.04) and GCIPL (per 20 µm, β = 0.05) were significantly associated with higher VF-11 scores (all p < 0.05). In conclusion, among healthy Asian eyes, thicker macula and GCIPL were associated with better vision and self-reported visual functioning. These findings provide further understanding on the potential influence of macular thickness on visual function. [ABSTRACT FROM AUTHOR]

Memristors represent the fourth electrical circuit element complementing resistors, capacitors and inductors. Hallmarks of memristive behavior include pinched and frequency-dependent I–V hysteresis loops and most importantly a functional dependence of the magnetic flux passing through an ideal memristor on its electrical charge. Microtubules (MTs), cylindrical protein polymers composed of tubulin dimers are key components of the cytoskeleton. They have been shown to increase solution's ionic conductance and re-orient in the presence of electric fields. It has been hypothesized that MTs also possess intrinsic capacitive and inductive properties, leading to transistor-like behavior. Here, we show a theoretical basis and experimental support for the assertion that MTs under specific circumstances behave consistently with the definition of a memristor. Their biophysical properties lead to pinched hysteretic current–voltage dependence as well a classic dependence of magnetic flux on electric charge. Based on the information about the structure of MTs we provide an estimate of their memristance. We discuss its significance for biology, especially neuroscience, and potential for nanotechnology applications. [ABSTRACT FROM AUTHOR]

Perpendicular magnetic anisotropy (PMA) ferromagnetic CoFeB with dual MgO interfaces is an attractive material system for realizing magnetic memory applications that require highly efficient, high speed current-induced magnetic switching. Using this structure, a sub-nanometer CoFeB layer has the potential to simultaneously exhibit efficient, high speed switching in accordance with the conservation of spin angular momentum, and high thermal stability owing to the enhanced interfacial PMA that arises from the two CoFeB-MgO interfaces. However, the difficulty in attaining PMA in ultrathin CoFeB layers has imposed the use of thicker CoFeB layers which are incompatible with high speed requirements. In this work, we succeeded in depositing a functional CoFeB layer as thin as five monolayers between two MgO interfaces using magnetron sputtering. Remarkably, the insertion of Mg within the CoFeB gave rise to an ultrathin CoFeB layer with large anisotropy, high saturation magnetization, and good annealing stability to temperatures upwards of 400 °C. When combined with a low resistance-area product MgO tunnel barrier, ultrathin CoFeB magnetic tunnel junctions (MTJs) demonstrate switching voltages below 500 mV at speeds as fast as 1 ns in 30 nm devices, thus opening a new realm of high speed and highly efficient nonvolatile memory applications. [ABSTRACT FROM AUTHOR]

The association between objective measures of body composition (BC) with type 2 diabetes (T2DM) is inconclusive. We conducted a systematic review and meta-analysis to examine the association between several body composition (BC) indices assessed using dual energy X-ray absorptiometry (DXA), and T2DM. Using PRISMA guidelines, we searched for observational studies investigating BC measures, including total body fat mass (BFM), visceral fat mass (VFM), subcutaneous fat mass (SFM), and fat free mass (FFM); and T2DM. Of 670 titles initially identified, 20 were included. High VFM was consistently associated with T2DM. For every kg increase in VFM, the odds of having T2DM increased by two-fold for males (OR 2.28 [95% CI 1.42 to 3.65], p = 0.001) and more than 4-fold for females (OR 4.24 [1.64 to 11.02], p = 0.003). The presence of T2DM was associated with 2-fold higher odds of low FFM (OR 2.38 [1.44 to 3.95]). We found evidence that greater VFM is a risk factor for prevalent and incident T2DM. While the presence of T2DM is associated with reduced FFM; the relationship between FFM and BFM with T2DM remains unclear. Reducing VFM and increasing FFM through lifestyle changes may reduce the risk of T2DM and mitigate its deleterious effect on BC, respectively. [ABSTRACT FROM AUTHOR]

AAV vectors poorly transduce Dendritic cells (DC), a feature invoked to explain AAV's low immunogenicity. However, the reason for this non-permissiveness remained elusive. Here, we performed an in-depth analysis using human monocyte-derived immature DC (iDC) as model. iDC internalized AAV vectors of various serotypes, but even the most efficient serotype failed to transduce iDC above background. Since AAV vectors reached the cell nucleus, we hypothesized that AAV's intracellular processing occurs suboptimal. On this basis, we screened an AAV peptide display library for capsid variants more suitable for DC transduction and identified the I/VSS family which transduced DC with efficiencies of up to 38%. This property correlated with an improved vector uncoating. To determine the consequence of this novel feature for AAV's in vivo performance, we engineered one of the lead candidates to express a cytoplasmic form of ovalbumin, a highly immunogenic model antigen, and assayed transduction efficiency as well as immunogenicity. The capsid variant clearly outperformed the parental serotype in muscle transduction and in inducing antigen-specific humoral and T cell responses as well as anti-capsid CD8+ T cells. Hence, vector uncoating represents a major barrier hampering AAV vector-mediated transduction of DC and impacts on its use as vaccine platform. [ABSTRACT FROM AUTHOR]

Most prostate cancer patients will progress to a castration-resistant state (CRPC) after androgen ablation therapy and despite the development of new potent anti-androgens, like enzalutamide (ENZ), which prolong survival in CRPC, ENZ-resistance (ENZR) rapidly occurs. Re-activation of the androgen receptor (AR) is a major mechanism of resistance. Interrogating our in vivo derived ENZR model, we discovered that transcription factor STAT3 not only displayed increased nuclear localization but also bound to and facilitated AR activity. We observed increased STAT3 S727 phosphorylation in ENZR cells, which has been previously reported to facilitate AR binding. Strikingly, ENZR cells were more sensitive to inhibition with STAT3 DNA-binding inhibitor galiellalactone (GPA500) compared to CRPC cells. Treatment with GPA500 suppressed AR activity and significantly reduced expression of Cyclin D1, thus reducing cell cycle progression into S phase and hindering cell proliferation. In vivo, GPA500 reduced tumor volume and serum PSA in ENZR xenografts. Lastly, the combination of ENZ and GPA500 was additive in the inhibition of AR activity and proliferation in LNCaP and CRPC cells, providing rationale for combination therapy. Overall, these results suggest that STAT3 inhibition is a rational therapeutic approach for ENZR prostate cancer, and could be valuable in CRPC in combination with ENZ. [ABSTRACT FROM AUTHOR]

Control of immunologic tolerance and homeostasis rely on Foxp3+CD4+CD25+ regulatory T cells (Tregs) that constitutively express the high affinity receptor for Interleukin-2, CD25. Tregs proliferate in response to injections of IL-2/anti-IL-2 antibody complexes or low doses of IL-2. However, little is known about endogenous mechanisms that regulate the sensitivity of CD25 to signaling by IL-2. Here we demonstrate that CD25 is ADP-ribosylated at Arg35 in the IL-2 binding site by ecto-ADP-ribosyltransferase ARTC2.2, a toxin-related GPI-anchored ecto-enzyme. ADP-ribosylation inhibits binding of IL-2 by CD25, IL-2- induced phosphorylation of STAT5, and IL-2-dependent cell proliferation. Our study elucidates an as-yet-unrecognized mechanism to tune IL-2 signaling. This newly found mechanism might thwart Tregs at sites of inflammation and thereby permit a more potent response of activated effector T cells. [ABSTRACT FROM AUTHOR]