Search

Around 70 million metric tonnes of fruit and vegetable waste (FVW) are produced each year and are eventually discarded as wholesale garbage. Microorganisms decompose this FVW, which has led to environmental contamination, greenhouse gas emissions, and other impacts related to climate change. If FVW are used properly, they can reduce environmental damage and also boost a nation’s economy. FVW contain vast amounts of biopolymers, viz., pectin, cellulose, and starch, all of which are hydrolysed by microbes with the aid of the pectinase, cellulase, and amylase enzymes, respectively. Therefore, in light of this, the intervention of microorganisms for the production of pectinase, cellulase, and amylase could be a safe, cost-effective, and eco-friendly approach for the precise utilisation of FVW. Nowadays, thermophilic multienzymes are extracted from a group of hot spring microbes. Thermophilic multienzymes are more capable of surviving at high temperatures and have less degrading capability. Moreover, through this advancement, we can obtain vast amounts of pectinase, cellulase, and amylase enzymes within a short period of time. This microbial enzyme preparation might be helpful in food, textiles, paper, pulp, animal feed supplements, detergents, juice/pulp clarity, leather, and other related sectors.

This study examines the socioeconomic impacts of large-scale land conversion from agriculture to industry on affected households, focusing on Sri City, an industrial hub in South India established under the SEZ Act 2005. Data from 250 households in and around Sri City were collected on socioeconomic indicators aligned with the Sustainable Development Goals using a structured survey method. Quasi-experimental methods, specifically nearest neighbor matching based on the Mahalanobis distance model, were employed for analysis. The findings indicate that affected households experience benefits, but these are not unequivocal. The study underscores the importance of project-specific factors, land acquisition strategies, and approaches to business leadership in shaping the socially sustainable outcomes of land conversion, from agriculture to industry.

Lipoprotein (a) (Lp(a)) is a risk factor for cardiovascular diseases and mainly regulated by the complex LPA gene. We investigated the types of variation in the LPA gene and their predictive performance on Lp(a) concentration. We determined the Kringle IV-type 2 (KIV-2) copy number (CN) using the DRAGEN LPA Caller (DLC) and a read depth-based CN estimator in 8351 short-read whole genome sequencing samples from the GENESIS-HD study. The pentanucleotide repeat in the promoter region was genotyped with GangSTR and ExpansionHunter. Lp(a) concentration was available in 4861 population-based subjects. Predictive performance on Lp(a) concentration was investigated using random forests. The agreement of the KIV-2 CN between the two specialized callers was high (r = 0.9966; 95% confidence interval [CI] 0.9965–0.9968). Allele-specific KIV-2 CN could be determined in 47.0% of the subjects using the DLC. Lp(a) concentration can be better predicted from allele-specific KIV-2 CN than total KIV-2 CN. Two single nucleotide variants, 4925G>A and rs41272114C>T, further improved prediction. The genetically complex LPA gene can be analyzed with excellent agreement between different callers. The allele-specific KIV-2 CN is more important for predicting Lp(a) concentration than the total KIV-2 CN.

Background: Left atrial (LA) assessment is an important marker of adverse cardiovascular outcomes. Cardiovascular magnetic resonance (CMR) accurately quantifies LA volume and function based on biplane long-axis imaging. We aimed to validate single-plane-derived LA indices against the biplane method to simplify the post-processing of cine CMR. Methods: In this study, 100 patients from Leeds Teaching Hospitals were used as the derivation cohort. Bias correction for the single plane method was applied and subsequently validated in 79 subjects. Results: There were significant differences between the biplane and single plane mean LA maximum and minimum volumes and LA ejection fraction (EF) (all p < 0.01). After correcting for biases in the validation cohort, significant correlations in all LA indices were observed (0.89 to 0.98). The area under the curve (AUC) for the single plane to predict biplane cutoffs of LA maximum volume ≥ 112 mL was 0.97, LA minimum volume ≥ 44 mL was 0.99, LA stroke volume (SV) ≤ 21 mL was 1, and LA EF ≤ 46% was 1, (all p < 0.001). Conclusions: LA volumetric and functional assessment by the single plane method has a systematic bias compared to the biplane method. After bias correction, single plane LA volume and function are comparable to the biplane method.

Wheat is one of the major sources of protein worldwide. Its hexaploidy significantly complicates the identification of genes that may be crucial for improving wheat production to meet the challenges of an increased world population and climate change. Virus-induced gene silencing (VIGS) using Barley stripe mosaic virus (BSMV)-based constructs has proven to be a very useful tool in the analysis of gene function in the hexaploid plant, wheat. However, most published applications of this technique focus on phenotypes that can be observed in the leaves of wheat. A few studies have reported successful VIGS in the spikes of wheat, but this has proven to be more difficult than the seedling leaf assays. This study reports a time course analysis of the movement of BSMV from the site of inoculation into the meristematic region of wheat. It also describes how the photobleaching phenotype resulting from silencing phytoene desaturase (PDS), which is often used as a reporter for VIGS, does not indicate the full extent of where VIGS occurs, and this can mislead scientists as they design silencing studies. These findings provide guidance for more effective VIGS studies to determine the function of genes expressed in the spikes of wheat and may be important for wheat improvement.

Tropospheric systems are widely used by military forces as they provide long-distance, real-time communication. Slow-fading propagation loss reduces link availability and limits its data-carrying capacity. Beam pointing dynamics provides knowledge of favorable heights at different times of the day in different seasons and a useful steering range. Beam steering, based on the beam pointing dynamics of the link, can overcome slow fading. The main contributions of this paper are the derivation of a realistic and accurate tropospheric channel model obtained by making important modifications to Dinc’s ray-based model. This paper also presents a method for determining beam pointing dynamics using the modified model. Beam pointing dynamics for two different links located in India have been determined in this paper using real-world data obtained from the Indian Meteorological Department. Another significant contribution of the paper is presenting the prospect of dual data streaming on tropospheric links using a fixed beam and a dynamically steered beam, based on the examination of beam pointing dynamics obtained for the two links. The main result presented in this paper is the comparison of powers received from the most favorable heights in a steerable beam system with the powers received in conventional fixed-beam systems for different days of the year. It has been shown that a higher received power can be achieved with beam steering. Another important result shown is the comparison of the achievable data rates for a single fixed-beam system and a dual-beam (one fixed beam and one dynamically steered beam) system. It has been shown that almost double the data rate is achievable in a dual-beam system. The method for the determination of beam pointing dynamics and the possibility of dual data streaming presented in this paper can significantly enhance the availability and capacity of tropospheric links.

Ultrafast pump–probe spectroscopic studies allow for deep insights into the mechanisms and timescales of photophysical and photochemical processes. Extracting valuable information from these studies, such as reactive intermediates’ lifetimes and coherent oscillation frequencies, is an example of the inverse problems of chemical kinetics. This article describes a consistent approach for solving this inverse problem that avoids the common obstacles of simple least-squares fitting that can lead to unreliable results. The presented approach is based on the regularized Markov Chain Monte-Carlo sampling for the strongly nonlinear parameters, allowing for a straightforward solution of the ill-posed nonlinear inverse problem. The software to implement the described fitting routine is introduced and the numerical examples of its application are given. We will also touch on critical experimental parameters, such as the temporal overlap of pulses and cross-correlation time and their connection to the minimal reachable time resolution.

(1) Background and Objectives: Flow assessment using cardiovascular magnetic resonance (CMR) provides important implications in determining physiologic parameters and clinically important markers. However, post-processing of CMR images remains labor- and time-intensive. This study aims to assess the validity and repeatability of fully automated segmentation of phase contrast velocity-encoded aortic root plane. (2) Materials and Methods: Aortic root images from 125 patients are segmented by artificial intelligence (AI), developed using convolutional neural networks and trained with a multicentre cohort of 160 subjects. Derived simple flow indices (forward and backward flow, systolic flow and velocity) and complex indices (aortic maximum area, systolic flow reversal ratio, flow displacement, and its angle change) were compared with those derived from manual contours. (3) Results: AI-derived simple flow indices yielded excellent repeatability compared to human segmentation (p < 0.001), with an insignificant level of bias. Complex flow indices feature good to excellent repeatability (p < 0.001), with insignificant levels of bias except flow displacement angle change and systolic retrograde flow yielding significant levels of bias (p < 0.001 and p < 0.05, respectively). (4) Conclusions: Automated flow quantification using aortic root images is comparable to human segmentation and has good to excellent repeatability. However, flow helicity and systolic retrograde flow are associated with a significant level of bias. Overall, all parameters show clinical repeatability.

Maleimides serve as crucial components in various synthetic processes and are of significant interest to researchers in bioorganic chemistry and biotechnology. Although thermal reactions involving maleimides have been studied extensively, light-mediated reactions with maleimides remain relatively underutilized. This review focuses on understanding the behavior of maleimides in their excited state, particularly their role as synthetic scaffolds for excited-state reactions. Specific emphasis is placed on the diverse photoreactions involving maleimides and photophysical evaluation from our research group.

In the present report, we have described the synthesis of N-aminopolyhydroquinoline (N-PHQ) derivatives using highly efficient β-cyclodextrin (β-CD) as a catalyst by the Hantzsch condensation of substituted aromatic aldehydes, dimedone, and hydrazine hydrate in one pot. The reactions were completed in a shorter time without the generation of any other byproduct. The synthesized N-PHQs were washed thoroughly with distilled water and recrystallized with ethanol to get highly purified products (as crystals). The structure of the synthesized N-PHQs was established by using advanced spectroscopic techniques like FT-IR, NMR (1H, 13C, DEPT, COSY, and HSQC), ESI-MS, and Elemental Analyzer. The N-PHQs derivatives demonstrated moderate to excellent resistance against the tested strains (both fungal as well as bacterial). The presence of polar groups, which are able to form H-bonds, attached to the phenyl ring like -NO2 (4b and 4c), and -OMe (4i, 4j, and 4k) exhibits excellent activity, which is comparable to standard drugs, amoxicillin and fluconazole.

The authors wish to make a change to the published paper [...]

Chemotherapy is an important treatment option for advanced prostate cancer, especially for metastatic prostate cancer (PCa). Resistance to first-line chemotherapeutic drugs such as docetaxel often accompanies prostate cancer progression. Attempts to overcome resistance to docetaxel by combining docetaxel with other biological agents have been mostly unsuccessful. A better understanding of the mechanisms underlying docetaxel resistance may provide new avenues for the treatment of advanced PCa. We have previously found that the fatty acid-binding protein 12 (FABP12)-PPARγ pathway modulates lipid-related bioenergetics and PCa metastatic transformation through induction of Slug, a master driver of epithelial-to-mesenchymal transition (EMT). Here, we report that the FABP12-Slug axis also underlies chemoresistance in PCa cells. Cell sensitivity to docetaxel is markedly suppressed in FABP12-expressing cells, along with induction of Survivin, a typical apoptosis inhibitor, and inhibition of cleaved PARP, a hallmark of programmed cell death. Importantly, Slug depletion down-regulates Survivin and restores cell sensitivity to docetaxel in FABP12-expressing cells. Finally, we also show that high levels of Survivin are associated with poor prognosis in PCa patients, with FABP12 status determining its prognostic significance. Our research identifies a FABP12-Slug-Survivin pathway driving docetaxel resistance in PCa cells, suggesting that targeting FABP12 may be a precision approach to improve chemodrug efficacy and curb metastatic progression in PCa.

Acute myeloid leukemia (AML) is a heterogeneous hematological malignancy that is often associated with relapse and drug resistance after standard chemotherapy or targeted therapy, particularly in older patients. Hematopoietic stem cell transplants are looked upon as the ultimate salvage option with curative intent. Adoptive cell therapy using chimeric antigen receptors (CAR) has shown promise in B cell malignancies and is now being investigated in AML. Initial clinical trials have been disappointing in AML, and we review current strategies to improve efficacy for CAR approaches. The extensive number of clinical trials targeting different antigens likely reflects the genetic heterogeneity of AML. The limited number of patients reported in multiple early clinical studies makes it difficult to draw conclusions about CAR safety, but it does suggest that the efficacy of this approach in AML lags behind the success observed in B cell malignancies. There is a clear need not only to improve CAR design but also to identify targets in AML that show limited expression in normal myeloid lineage cells.

The recent rise in telemedicine, notably during the COVID-19 pandemic, highlights the potential of integrating artificial intelligence tools in healthcare. This study assessed the effectiveness of ChatGPT versus medical oncologists in the telemedicine-based management of metastatic prostate cancer. In this retrospective study, 102 patients who met inclusion criteria were analyzed to compare the competencies of ChatGPT and oncologists in telemedicine consultations. ChatGPT’s role in pre-charting and determining the need for in-person consultations was evaluated. The primary outcome was the concordance between ChatGPT and oncologists in treatment decisions. Results showed a moderate concordance (Cohen’s Kappa = 0.43, p < 0.001). The number of diagnoses made by both parties was not significantly different (median number of diagnoses: 5 vs. 5, p = 0.12). In conclusion, ChatGPT exhibited moderate agreement with oncologists in management via telemedicine, indicating the need for further research to explore its healthcare applications.

This study introduces DAVE (Digital Assistant for Virtual Engineering), a Generative Pre-trained Transformer (GPT)-powered digital assistant prototype, designed to enable real-time, multimodal interactions within Building Information Modeling (BIM) environments for updating and querying BIM models using text or voice commands. DAVE integrates directly with Autodesk Revit through Python scripts, the Revit API, and the OpenAI API and utilizes Natural Language Processing (NLP). This study presents (1) the development of a practical AI chatbot application that leverages conversational AI and BIM for dynamic actions within BIM models (e.g., updates and queries) at any stage of a construction project and (2) the demonstration of real-time, multimodal BIM model management through voice or text, which aims to reduce the complexity and technical barriers typically associated with BIM processes. The details of DAVE’s development and system architecture are outlined in this paper. Additionally, the comprehensive process of prototype testing and evaluation including the response time analysis and error analysis, which investigated the issues encountered during system validation, are detailed. The prototype demonstrated 94% success in accurately processing and executing single-function user queries. By enabling conversational interactions with BIM models, DAVE represents a significant contribution to the current body of knowledge.

Facial palsy causes the face to droop due to sudden weakness in the muscles on one side of the face. Computer-added assistance systems for the automatic recognition of palsy faces present a promising solution to recognizing the paralysis of faces at an early stage. A few research studies have already been performed to handle this research issue using an automatic deep feature extraction by deep learning approach and handcrafted machine learning approach. This empirical research work designed a multi-model facial palsy framework which is a combination of two convolutional models—a multi-task cascaded convolutional network (MTCNN) for face and landmark detection and a hyperparameter tuned and parametric setting convolution neural network model for facial palsy classification. Using the proposed multi-model facial palsy framework, we presented results on a dataset of YouTube videos featuring patients with palsy. The results indicate that the proposed framework can detect facial palsy efficiently. Furthermore, the achieved accuracy, precision, recall, and F1-score values of the proposed framework for facial palsy detection are 97%, 94%, 90%, and 97%, respectively, for the training dataset. For the validation dataset, the accuracy achieved is 95%, precision is 90%, recall is 75.6%, and F-score is 76%. As a result, this framework can easily be used for facial palsy detection.

Background: Eye-tracking technology could be used to study human factors during teamwork. Objectives: This work aimed to compare the visual attention (VA) of a team member acting as both a team leader and managing the airway, compared to a team member performing the focused task of managing the airway in the presence of a dedicated team leader. This work also aimed to report differences in team performance, behavioural skills, and workload between the two groups using validated tools. Methods: We conducted a simulation-based, pilot randomised controlled study. The participants included were volunteer paediatric trainees, nurse practitioners, and neonatal nurses. Three teams consisting of four team members were formed. Each team participated in two identical neonatal resuscitation simulation scenarios in a random order, once with and once without a team leader. Using a commercially available eye-tracking device, we analysed VA regarding attention to (1) a manikin, (2) a colleague, and (3) a monitor. Only the trainee who was the airway operator would wear eye-tracking glasses in both simulations. Results: In total, 6 simulation scenarios and 24 individual role allocations were analysed. Participants in a no-team-leader capacity had a greater number of total fixations on manikin and monitors, though this was not significant. There were no significant differences in team performance, behavioural skills, and individual workload. Physical demand was reported as significantly higher by participants in the group without a team leader. During debriefing, all the teams expressed their preference for having a dedicated team leader. Conclusion: In our pilot study using low-cost technology, we could not demonstrate the difference in VA with the presence of a team leader.

Next-generation sequencing (NGS) has emerged as a promising tool for diagnosing fungal infections. It enables the identification of a wide range of fungal species and provides more accurate and rapid results than traditional diagnostic methods. NGS-based approaches involve the sequencing of DNA or RNA from clinical samples, which can be used to detect and identify fungal pathogens in complex clinical samples. The development of targeted gene panels and whole-genome sequencing has allowed for identifying genetic markers associated with antifungal drug resistance, enabling clinicians to tailor patient treatment options. NGS can also provide insights into the pathogenesis of fungal infections and aid in discovering novel drug targets. Although NGS has some limitations, such as cost and data analysis, it can potentially revolutionize the future diagnosis and treatment of fungal infections.

DFOS (distributed fiber-optic sensing) technology has shown the potential to increase the accuracy of measurement after years of development and experimenting in geoengineering monitoring. To better understand the development of DFOS technology and its contribution to geoengineering, an objective and data-driven review of the development process of DFOS technology in construction was completed. The review was accomplished by using text mining methods on the Web of Science, covering a wide range of relevant data, including 3970 articles from 1989 to 2023. The results indicate that DFOS technology research demonstrates the typical characteristics of multi-author, multi-country, and multi-institution collaborations, spanning various research fields. Over the past 35 years, the number of published articles has exhibited exponential growth, with China making significant contributions and leading in terms of its total publication growth rate, which has been higher than that of the United States since 2016. In the analysis of author keywords, emerging technologies, such as machine learning and distributed acoustic sensing, have garnered attention. The findings contribute to a comprehensive understanding of the development, impact, and future trends of DFOS technology in geotechnical engineering, offering valuable insights for researchers, scholars, and students in the field and inspiring new approaches for research methods in this domain.

This study explores the spatial patterns of particulate matter (PM) in the megacity of Delhi. A GRIMM aerosol spectrometer is used to analyze different aerodynamic diameters (PM10, PM2.5, PM1.0), inhalable, thoracic, and alveolic particles, and black carbon (BC) at six prominent locations in Delhi during summer and winter. Additionally, metals (Pb, Fe, Ca, Al, Zn), along with silicon and sulfur, are analyzed using an ED-XRF spectrometer over the sampling locations during the summer season. The sampling site data are interpolated using the Kriging method to generate spatial maps to explore the air pollution problem in Delhi. East Delhi is observed to be the most polluted site, while Guru Gobind Singh Indraprastha University (GGSIPU) is the least polluted site. We further observe a high correlation between Al-Fe, Al-Ca, Zn-Pb, Ca-Fe, and S-Zn, indicating their common source of emission. Aerosols are also found to be highly enriched with metals like Al, S, Fe, Zn, and Pb, suggesting strong anthropogenic sources of these metals. Construction activities, resuspended dust, an increased number of vehicles, faulty agricultural practices, and soil could be recognized as major sources of the particulate concentration in an urban area like Delhi.

Tick-borne illnesses (TBIs), especially those caused by Borrelia, are increasingly prevalent worldwide. These diseases progress through stages of initial localization, early spread, and late dissemination. The final stage often leads to post-treatment Lyme disease syndrome (PTLDS) or chronic Lyme disease (CLD), characterized by persistent and non-specific multisystem symptoms affecting multiple systems, lasting over six months after antibiotic therapy. PTLDS significantly reduces functional ability, with 82–96% of patients experiencing pain, including arthritis, arthralgia, and myalgia. Inflammatory markers like CRP and TNF-alpha indicate ongoing inflammation, but the link between chronic pain and other biomarkers is underexplored. This study examined the relationship between pain and biomarkers in TBI patients from an Irish hospital and their response to antibiotic treatment. Pain ratings significantly decreased after antibiotic treatment, with median pain scores dropping from 7 to 5 (U = 27215.50, p < 0.001). This suggests a persistent infection responsive to antibiotics. Age and gender did not influence pain ratings before and after treatment. The study found correlations between pain ratings and biomarkers such as transferrin, CD4%, platelets, and neutrophils. However, variations in these biomarkers did not significantly predict pain changes when considering biomarkers outside the study. These findings imply that included biomarkers do not directly predict pain changes, possibly indicating allostatic load in symptom variability among long-term TBI patients. The study emphasizes the need for appropriate antibiotic treatment for TBIs, highlighting human rights issues related to withholding pain relief.

Iron is often accumulated in the liver during pathological conditions such as cirrhosis and cancer. Elevated expression of glucose transporters GLUT1 and GLUT3 is associated with reduced overall survival in patients with hepatocellular carcinoma. However, it is not known whether iron can regulate glucose transporters and contribute to tumor proliferation. In the present study, we found that treatment of human liver cell line HepG2 with ferric ammonium citrate (FAC) resulted in a significant upregulation of GLUT3 mRNA and protein in a dose-dependent manner. Similarly, iron accumulation in mice fed with high dietary iron as well as in mice injected intraperitoneally with iron dextran enhanced the GLUT3 expression drastically in the liver. We demonstrated that iron-induced hepatic GLUT3 upregulation is mediated by the LKB1/AMPK/CREB1 pathway, and this activation was reversed when treated with iron chelator deferiprone. In addition, inhibition of GLUT3 using siRNA prevented iron-mediated increase in the expression of cell cycle markers and cellular hyperproliferation. Furthermore, exogenous sodium beta-hydroxybutyrate treatment prevented iron-mediated hepatic GLUT3 activation both in vitro and in vivo. Together, these results underscore the importance of iron, AMPK, CREB1 and GLUT3 pathways in cell proliferation and highlight the therapeutic potential of sodium beta-hydroxybutyrate in hepatocellular carcinoma with high GLUT3 expression.

Since the earliest days, people have been employing herbal treatments extensively around the world. The development of phytochemical and phytopharmacological sciences has made it possible to understand the chemical composition and biological properties of a number of medicinal plant products. Due to certain challenges like large molecular weight and low bioavailability, some components of herbal extracts are not utilized for therapeutic purposes. It has been suggested that herbal medicine and nanotechnology can be combined to enhance the benefits of plant extracts by lowering dosage requirements and adverse effects and increasing therapeutic activity. Using nanotechnology, the active ingredient can be delivered in an adequate concentration and transported to the targeted site of action. Conventional therapy does not fulfill these requirements. This review focuses on different skin diseases and nanotechnology-based herbal medicines that have been utilized to treat them.

Rheumatoid arthritis (RA) is a persistent autoimmune disorder that is characterized by joint inflammation, discomfort, and impairment. Despite the existence of several therapeutic approaches, their effectiveness is often restricted and may be linked to unfavorable side effects. Consequently, there has been growing interest in investigating naturally derived compounds as plausible therapeutic agents for RA disease. The objective of this review is to summarize the existing preclinical and clinical evidence regarding the efficacy of naturally extracted compounds and plant extracts in the treatment of RA, focusing on their anti-inflammatory, anti-oxidative, and immunomodulatory properties. Some of the problems with using natural chemicals are the uneven quality of commercially available preparations and the poor bioavailability of these compounds. Future investigations should focus on improving the formulations, conducting thorough clinical trials, and exploring different techniques to fully utilize the intrinsic potential of naturally derived chemicals in treating RA.

We aimed to characterize the echocardiographic alterations in dogs from an endemic region that were naturally infected with T. cruzi. Dogs (n = 130) seropositive for antibodies against T. cruzi and/or with acute parasitemia were enrolled in the study. Indicators of changes in the structure and systolic and diastolic functions of the left ventricle (LV) and blood flow patterns were evaluated by echocardiography. The frequency and extent of alterations in these indicators were associated with the severity of the disease. Briefly, 15 (11.54%) dogs were diagnosed with dilated cardiomyopathy (DCM), and 115 (88.46%) dogs were diagnosed as being without DCM. Infected dogs with DCM exhibited structural features of LV dysfunction, e.g., a significant (p < 0.05) increase in the LV internal diameter at systole and diastole (LVID-s, LVID-d) and a decline in the LV posterior wall (LVPW-d) thickness at diastole. Despite an increase in stroke volume and cardiac output indicating contraction force, DCM resulted in a decreased ejection fraction, affecting systolic function. Dogs that were diagnosed as DCM-negative but were positive for T. cruzi by PCR exhibited a high frequency of an increase in the thickness of the interventricular septum in systole (IVS-s) and the LV posterior wall in diastole (LVPW-d), a decline in the LV inner diameter (LVID-d, LVID-s), and fractional shortening (FS). The thinning of the LVPW at systole was the most defining feature observed in chronically infected dogs. In summary, this is the first study reporting the echocardiographic changes occurring in dogs naturally infected with T. cruzi and developing DCM. Our data suggest that changes in LVID are a major indicator of risk of cardiac involvement, and the observation of changes in the IVS, LVPW, and FS have predictive value in determining the risk of DCM development in infected dogs.

In veterinary medicine and livestock production, ensuring good animal husbandry is vital for the physical and emotional wellbeing of animals under our care. Pain poses challenges for assessment and mitigation, especially in species unable to express pain overtly. This review examines current pain mitigation interventions in routine husbandry, focuses on the duration of pain after procedures and implications for animal welfare. Pain behaviours have been observed for days or weeks after regular husbandry procedures, and many studies have noted pain-related behaviour persisting until study finalisation, suggesting potential undocumented pain beyond study completion. Current products registered in Australia for pain mitigation in livestock primarily target immediate pain associated with procedures. The future of pain relief in livestock demands longer-acting solutions to address post-procedural pain adequately. Providing pain relief for at least 72 h post surgery is recommended, but current products require retreatment intervals to achieve this, posing practical challenges, especially in livestock. Methods of pain relief provision, such as voluntary consumption of medicated feed, transdermal medication delivery and long-acting formulations offer potential solutions for prolonged pain relief, with research ongoing in these areas. There is a need for further research and development of longer-acting pain relief to ensure optimal welfare of livestock.

The tremendous growth of the Internet of Things (IoT) has gained a lot of attention in the global market. The massive deployment of IoT is also inherent in various security vulnerabilities, which become easy targets for hackers. IoT botnets are one type of critical malware that degrades the performance of the IoT network and is difficult to detect by end-users. Although there are several traditional IoT botnet mitigation techniques such as access control, data encryption, and secured device configuration, these traditional mitigation techniques are difficult to apply due to normal traffic behavior, similar packet transmission, and the repetitive nature of IoT network traffic. Motivated by botnet obfuscation, this article proposes an intelligent mitigation technique for IoT botnets, named IMTIBoT. Using this technique, we harnessed the stacking of ensemble classifiers to build an intelligent system. This stacking classifier technique was tested using an experimental testbed of IoT nodes and sensors. This system achieved an accuracy of 0.984, with low latency.

Electrostatic charging of powders becomes important, when particles become smaller, especially for fine powders at micron or sub-micron size. Charging of powders causes strong particle adhesion and consequently difficulties in processes such as blending or mixing, and sieving, etc. Not only does the charge of powders influence the process and the quality of the products, but also the discharge creates risks of dust explosion. Assessing powder charge and the hazards in manufacturing can be difficult. One of the major challenges is to evaluate the charge levels and polarity in the powders but this requires a significant number of tests to detect charge tendency and distributions in bulk materials, which is time-consuming. In this paper, electrostatic charging of powders in material handling processes and the associated hazards are briefly reviewed. For an assessment, the challenges for sensing electrostatic charges of particulate solids, particularly for fine powders, are discussed. It was revealed that sensing the charge polarity for representative samples of powders can be the main challenge because of the difficulty in separation of the charged particles. The inductive charge sensor showed great potential to measure charge levels and polarity distributions in powders. Experimental trials for several fine powders showed that the inductive charge sensor can be used for rapidly assessing chargeability and charge polarity distribution of powders.

Background: Carcinoma penis is a rare neoplasm, and the literature is scarce on long-term survival and its predictors. The aim of the study was to determine the clinical profile and management patterns, identify predictors of survival, and the impact of education and rural/urban dwelling on survival. Methods: Patients with a histological diagnosis of carcinoma penis from January 2015 to December 2019 were included in the study. Demographics, clinical profile, education status, primary residence address, and outcomes were obtained from the case records. Distance from the treatment centre was obtained from the postal code. The primary objectives were to assess relapse-free survival (RFS) and overall survival (OS). The secondary objectives were to identify the predictors of RFS and OS and to determine the clinical profile and treatment patterns in patients with carcinoma penis in India. Time-to-event was calculated by Kaplan–Meir analysis and survival was compared by the log-rank test. Univariate and multivariable Cox regression analyses were used to find independent predictors of relapse and mortality. Logistic regression analyses to examine the associations of rural residence, education status, and distance from the treatment centre with the relapse adjusting for measured confounding variables. Results: Case records of 102 patients treated during the above period were retrieved. The median age was 55.5 (interquartile range [IQR] 42–65 years). Ulcero-proliferative growth (65%), pain (57%), and dysuria (36%) were the most common presenting features. Clinical examination or imaging revealed inguinal lymphadenopathy in 70.6% of patients, however, only 42% of these lesions were pathologically involved. A total of 58.8% of patients were from rural areas, 46.9% had no formal education, and 50.9% had a primary residence ≥100 km from the hospital. Patients with lower education and rural households had higher TNM stages and nodal involvement. Median RFS and OS were 57.6 months (15.8 months to not reached) and 83.9 months (32.5 months to not reached), respectively. On univariate analysis tumor stage, involvement of lymph nodes, T stage, performance status, and albumin was predictive for relapse and survival. However, on multivariate analysis, the stage remained the only predictor of RFS and nodal involvement, and metastatic disease was a predictor of OS. Education status, rural habitation, and distance from the treatment centre were not predictors for relapse or survival. Conclusions: Patients with carcinoma have locally advanced disease at presentation. Rural dwellings and lower education were associated with the advanced stage but did not have a significant bearing on the survival outcomes. The stage at diagnosis and nodal involvement is the most important predictor of RFS and OS.

Neurodegenerative diseases (Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and others) and cancer, seemingly disparate in their etiology and manifestation, exhibit intriguing associations in certain cellular and molecular processes. Both cancer and neurodegenerative diseases involve the deregulation of cellular processes such as apoptosis, proliferation, and DNA repair and pose a significant global health challenge. Afzelin (kaempferol 3-O-rhamnoside) is a flavonoid compound abundant in various plant sources. Afzelin exhibits a diverse range of biological activities, offering promising prospects for the treatment of diseases hallmarked by oxidative stress and deregulation of cell death pathways. Its protective potential against oxidative stress is also promising for alleviating the side effects of chemotherapy. This review explores the potential therapeutic implications of afzelin, including its capacity to mitigate oxidative stress, modulate inflammation, and promote cellular regeneration in neurodegenerative and cancer diseases.

The journal retracts the article, “A Novel Herbal Hydrogel Formulation of Moringa oleifera for Wound Healing” [...]

Dissolved Oxygen (DO) in water enables marine life. Measuring the prevalence of DO in a body of water is an important part of sustainability efforts because low oxygen levels are a primary indicator of contamination and distress in bodies of water. Therefore, aquariums and aquaculture of all types are in need of near real-time dissolved oxygen monitoring and spend a lot of money on purchasing and maintaining DO meters that are either expensive, inefficient, or manually operated—in which case they also need to ensure that manual readings are taken frequently which is time consuming. Hence a cost-effective and sustainable automated Internet of Things (IoT) system for this task is necessary and long overdue. DOxy, is such an IoT system under research and development at Santa Clara University’s Ethical, Pragmatic, and Intelligent Computing (EPIC) Laboratory which utilizes cost-effective, accessible, and sustainable Sensing Units (SUs) for measuring the dissolved oxygen levels present in bodies of water which send their readings to a web based cloud infrastructure for storage, analysis, and visualization. DOxy’s SUs are equipped with a High-sensitivity Pulse Oximeter meant for measuring dissolved oxygen levels in human blood, not water. Hence a number of parallel readings of water samples were gathered by both the High-sensitivity Pulse Oximeter and a standard dissolved oxygen meter. Then, two approaches for relating the readings were investigated. In the first, various machine learning models were trained and tested to produce a dynamic mapping of sensor readings to actual DO values. In the second, curve-fitting models were used to produce a successful conversion formula usable in the DOxy SUs offline. Both proved successful in producing accurate results.

Plant-based diets (PBDs) have been associated with a lower risk of cardiovascular disease (CVD). The aim was to investigate the predicted 5-year and 10-year risk of developing CVD in individuals following PBDs compared to regular meat-eating diets. This cross-sectional study included n = 240 middle-aged adults habitually consuming dietary patterns for ≥6 months: vegan, lacto-ovo vegetarian (LOV), pesco-vegetarian (PV), semi-vegetarian (SV) or regular meat-eater (RME) (n = 48 per group). Predicted 5-year and 10-year CVD risks were quantified using the Framingham Risk Equation and the Australian Absolute CVD risk calculator, respectively. Multivariable regression analysis was used to adjust for age, sex, smoking status, physical activity, alcohol use and BMI. Over three-quarters of the participants were women, mean age of 53.8 yrs. After adjustments for potential confounders, there was no difference in the predicted risk of CVD between regular-meat diets and PBDs, although crude analyses revealed that vegans had a lower 5-year and 10-year predicted risk of CVD compared to RMEs. SVs, PVs and LOVs had lower CVD risk scores, however, not significantly. Vegans had a favourable cardiometabolic risk profile including significantly lower serum lipid levels, fasting blood glucose and dietary fats and higher dietary fibre intake compared to RMEs. This was the first study to purposefully sample Australians habitually following PBDs. We found that PBDs do not independently influence the predicted risk of CVD, although PBDs tended to have lower risk and vegans had significantly lower cardiometabolic risk factors for CVD.

Methionine dependence is a characteristic of most cancer cells where they are unable to proliferate when the essential amino acid methionine is replaced with its precursor homocysteine in the growing media. Normal cells, on the other hand, thrive under these conditions and are referred to as methionine-independent. The reaction that adds a methyl group from 5-methyltetrahydrofolate to homocysteine to regenerate methionine is catalyzed by the enzyme methionine synthase with the cofactor cobalamin (vitamin B12). However, decades of research have shown that methionine dependence in cancer is not due to a defect in the activity of methionine synthase. Cobalamin metabolism has been tied to the dependent phenotype in rare cell lines. We have identified a human colorectal cancer cell line in which the cells regain the ability to proliferation in methionine-free, L-homocystine-supplemented media when cyanocobalamin is supplemented at a level of 1 µg/mL. In human SW48 cells, methionine replacement with L-homocystine does not induce any measurable increase in apoptosis or reactive oxygen species production in this cell line. Rather, proliferation is halted, then restored in the presence of cyanocobalamin. Our data show that supplementation with cyanocobalamin prevents the activation of the integrated stress response (ISR) in methionine-deprived media in this cell line. The ISR-associated cell cycle arrest, characteristic of methionine-dependence in cancer, is also prevented, leading to the continuation of proliferation in methionine-deprived SW48 cells with cobalamin. Our results highlight differences between cancer cell lines in the response to cobalamin supplementation in the context of methionine dependence.

Nowadays, the use of new compound chemical stabilizers to treat marine clay has gained significant attention. However, the complex non-linear relationship between the influencing factors and the unconfined compressive strength of chemically treated marine clay is not clear. In order to study the influence of various factors (dosage, type of stabilizer, curing age) on the unconfined compressive strength of solidified soil during chemical treatment, experiments were performed to determine the unconfined compressive strength of soft marine clay modified with various types of stabilizers. Further, an artificial neural network (ANN) model was used to establish a prediction model based on the unconfined compressive strength test data and to verify the performance. Sensitivity and optimization analyses were further conducted to explore the relative significance of parameters as well as the optimal dosage amount. Research has found that when the content of aluminate cement is 89.5% and the content of curing agent is 30%, the unconfined compressive strength significantly increases after 28 days of solidification, and the change in quicklime content has the greatest effect on the improvement in the unconfined compressive strength. The influence of modifiers on the unconfined compressive strength is in the order: potassium hydroxide > kingsilica > quick lime > bassanite. The values of each factor were obtained when the unconfined compressive strength was the maximum, which provided support for the optimization of the treatment scheme. The analysis of chemical treatment is no longer limited to the linear relationship according to the test results, which proves the feasibility of non-linear relationship analysis based on the artificial neural network.

Textile polymer composite is made of structured fibre matrix using textile technologies in fabrication, and gains benefits from strong mechanical properties with extra light weight. However, erosion behaviours and associated wear mechanisms of the composites may be influenced by the fibre structures due to heterogeneous composition and complex architectural topologies. Understanding the erosive mechanisms of the structured composites can be important, not only for preventing surface damage and loss of mechanical strength but also for improving design and fabrication of the composites. This paper presents an experimental study of erosive wear under sand blasting on 3D woven carbon-fibre-reinforced textile composites with epoxy. The architectural topology methods of the composites include non-crimped bidirectional, tufted bidirectional, 3D layer-to-layer and 3D orthogonal textile methods. The erosion tests were conducted on four impact angles (20°, 30°, 45° and 90°) under one impact velocity at 40 m/s. The study results show that the erosive mechanism of the textile composites is different from that of the neat substrate material. The observations from this study also reveal the different erosive behaviours between the composites with different fibre structures. It concludes that architectural structures can influence the erosion of a textile composite but will not result in significant differences in the wear resistance of the composites (

5-fluorouracil (5-FU), commercially available as a topical product, is approved for non-melanoma skin cancer (NMSC) treatment with several clinical limitations. This work aimed to develop 5-FU-loaded topical patches as a potential alternative to overcome such drawbacks. The patches offer accurate dosing, controlled drug release and improved patient compliance. Our study highlights the development of Eudragit® E (EuE)-based drug-in-adhesive (DIA) patches containing a clinically significant high level of 5-FU (approximately 450 µg/cm2) formulated with various chemical permeation enhancers. The patches containing Transcutol® (Patch-TRAN) or oleic acid (Patch-OA) demonstrated significantly higher skin penetration ex vivo than their control counterpart, reaching 5-FU concentrations of 76.39 ± 27.7 µg/cm2 and 82.56 ± 8.2 µg/cm2, respectively. Furthermore, the findings from in vitro permeation studies also validated the superior skin permeation of 5-FU achieved by Patch-OA and Patch-TRAN over 72 h. Moreover, the EuE-based DIA patch platform demonstrated suitable adhesive and mechanical properties with an excellent safety profile evaluated through an inaugural in vivo human study involving 11 healthy volunteers. In conclusion, the DIA patches could be a novel alternative option for NMSC as the patches effectively deliver 5-FU into the dermis layer and receptor compartment ex vivo for an extended period with excellent mechanical and safety profiles.

Patient education materials (PEM)s were extracted from provincial cancer agencies to determine their organizational health literacy by evaluating the quality, actionability, and functional accessibility (e.g., readability and understandability) of their PEMs. PEMs from 10 provincial agencies were assessed for their grade reading level (GRL), using eight numerical and two graphical readability scales, and underwent a difficult word analysis. The agencies were assessed for PEM quality using two methods (JAMA benchmarks and DISCERN), while actionability and understandability were assessed using the Patient Education Materials Assessment Tool (PEMAT). Seven hundred and eighty-six PEMs were analyzed. The overall average GRL was 9.3 ± 2.1, which is above the recommended 7th GRL for health information. The difficult word analysis showed that 15.4% ± 5.1% of texts contained complex words, 35.8% ± 6.8% of texts contained long words, and 24.2% ± 6.6% of texts contained unfamiliar words. Additionally, there was high overlap between the most frequently identified difficult words in the PEMs and the most frequently misunderstood words by cancer patients identified in the literature. Regarding quality indicators, no agency displayed all four indicators according to the JAMA benchmarks and DISCERN scores ranged between 38 (poor) to 66 (excellent). PEMAT scores ranged between 68% to 88% for understandability and 57% to 88% for actionability. PEMs continue to be written at a level above the recommended GRL across all provinces, and there was overall high variability in the quality, understandability, and actionability of PEMs among provincial agencies. This represents an opportunity to optimize materials, thus ensuring understanding by a wider audience and improving health literacy among Canadian cancer patients.

The COVID-19 pandemic has impacted healthcare delivery to patients with ST-segment elevation myocardial infarction (STEMI). The aim of our retrospective study was to determine the effect of COVID-19 on inpatient STEMI outcomes and to investigate changes in cardiac care delivery during 2020. We utilized the National Inpatient Sample database to examine inpatient mortality and cardiac procedures among STEMI patients with and without COVID-19. In our study, STEMI patients with COVID-19 had higher inpatient mortality (47.4% vs. 11.2%, aOR: 3.8, 95% CI: 3.2–4.6, p < 0.001), increased length of stay (9.0 days vs. 4.3 days, p < 0.001) and higher cost of hospitalization (USD 172,518 vs. USD 131,841, p = 0.004) when compared to STEMI patients without COVID-19. STEMI patients with COVID-19 also received significantly less invasive cardiac procedures (coronary angiograms: 30.4% vs. 50.8%, p < 0.001; PCI: 32.9% vs. 70.1%, p < 0.001; CABG: 0.9% vs. 4.1%, p < 0.001) and were more likely to receive systemic thrombolytic therapy (4.2% vs. 1.1%, p < 0.001) when compared to STEMI patients without COVID-19. Our findings are the result of complications of SARS-CoV2 infection as well as alterations in healthcare delivery due to the burden of the COVID-19 pandemic.

The strong association between endometriosis and infertility is of high clinical significance. High proliferative bias in eutopic endometrium during the secretory phase is a hallmark of endometriosis, which may result in high occurrence of implantation failure and resultant infertility in endometriosis. The ErbB family of proteins regulates the proliferation capacity in the endometrium, potentially causing endometrial hostility to the implantation process in endometriosis. However, our knowledge regarding the involvement of the ErbB family in human endometrium during the window of implantation (WOI) in endometriosis-associated infertility is scant. In the present study, the cellular profiles of immunopositive ErbBs-1 to -4 in the endometrium of endometriosis-free, infertile women (Group 1; n = 11) and in eutopic endometrium of infertile women diagnosed with stage IV ovarian endometriosis (Group 2; n = 13) during the mid-secretory phase were compared using standardized guidelines. Computer-aided standardized combinative analysis of immunoprecipitation in different compartments revealed an overexpression of ErbB-1 in the epithelial, stromal and vascular compartments, along with marginally higher ErbB-3 expression (p < 0.06) in the vascular compartment and ErbB-4 expression (p < 0.05) in the glandular epithelium and stroma in the endometrium during the WOI in women with primary infertility associated with stage IV ovarian endometriosis compared with disease-free endometrium of control infertile women. It appears that changes in ErbBs in the eutopic endometrium during WOI induce anomalous proliferative, inflammatory and angiogenic activities in it, which can antagonize endometrial preparation for embryo implantation in endometriosis. This knowledge appears usable in strategizing methods for the treatment of endometriosis-associated infertility, as well as preempting the oncogenic potential of endometriosis.

The use of prostate-specific membrane antigen targeted PET imaging for the evaluation of prostate cancer has increased significantly in the last couple of decades. When evaluating these imaging findings based on the PSMA reporting and data system version 1.0, which categorize lesions based on their likelihood of prostate cancer involvement, PSMA-RADS-3A lesions are commonly seen, which are indeterminate for the presence of disease. A total of 28 patients with 171 PSMA-RADS-3A lesions on 18F-DCFPyL PET/CT scans from June 2016 to May 2017 who had follow-up cross-sectional imaging over time were included in this study. The PSA levels of patients with PSMA-RADS-3A lesions were categorized into four groups, 0–0.2, 0.2–1, 1–2, and >2 ng/mL. The pre-operative Gleason score of these patients was categorized into two groups, Gleason score < 7 or ≥7. The median age for these patients was 72.5 years (range 59–81). The median PSA value for patients with positive lesions was significantly higher than those with negative lesions (5.8 ng/mL vs. 0.2 ng/mL, p < 0.0001). The lesion positivity rate was significantly higher in patients with PSA > 1 ng/mL (18.2% vs. 81.9%, p < 0.001). On ROC analysis, the highest classification accuracy was seen at PSA ≥ 0.6 ng/mL of 80.12% (95% CI = 73.69–86.16%), and the area under the curve was 71.32% (95% CI = 61.9–80.7%, p < 0.0001). A total of 96.4% (108/112) of patients with positive lesions and 86.4% (51/59) of patients with negative lesions had a PSMA-RADS-4/5 lymph node on the initial 18F-DCFPyL PET/CT scan (p = 0.02). In patients with a Gleason score ≥ 7, the presence of positive PSMA-RADS-3A lesions was higher, compared to negative PSMA-RADS-3A lesions (p = 0.049). Higher PSA levels in patients with PSMA-RADS-3A lesions can point towards the presence of true positivity. PSA levels may be considered in deciding whether to call an indeterminate lesion on PSMA PET.

Trypanosoma cruzi (T. cruzi), the causative agent of Chagas disease, has infected 6 million people, putting 70 million people at risk worldwide. Presently, very limited drugs are available, and these have severe side effects. Hence, there is an urgency to delve into other pathways and targets for novel drugs. Trypanosoma cruzi (T. cruzi) expresses a number of different cyclic AMP (cAMP)-specific phosphodiesterases (PDEs). cAMP is one of the key regulators of mammalian cell proliferation and differentiation, and it also plays an important role in T. cruzi growth. Very few studies have demonstrated the important role of cyclic nucleotide-specific PDEs in T. cruzi’s survival. T. cruzi phosphodiesterase C (TcrPDEC) has been proposed as a potential new drug target for treating Chagas disease. In the current study, we screen several analogs of xanthine for potency against trypomastigote and amastigote growth in vitro using three different strains of T. cruzi (Tulahuen, Y and CA-1/CL72). One of the potent analogs, GVK14, has been shown to inhibit all three strains of amastigotes in host cells as well as axenic cultures. In conclusion, xanthine analogs that inhibit T. cruzi PDE may provide novel alternative therapeutic options for Chagas disease.

Prostate cancer is one of the most life-threatening disorders that occur in males. It has now become the third most common disease all over the world, and emerging cases and spiking mortality rates are becoming more challenging day by day. Several approaches have been used to treat prostate cancer, including surgery, radiation therapy, chemotherapy, etc. These are painful and invasive ways of treatment. Primarily, chemotherapy has been associated with numerous drawbacks restricting its further application. The majority of prostate cancers have the potential to become castration-resistant. Prostate cancer cells exhibit resistance to chemotherapy, resistance to radiation, ADT (androgen-deprivation therapy) resistance, and immune stiffness as a result of activating tumor-promoting signaling pathways and developing resistance to various treatment modalities. Nanomedicines such as liposomes, nanoparticles, branched dendrimers, carbon nanotubes, and quantum dots are promising disease management techniques in this context. Nanomedicines can target the drugs to the target site and enhance the drug’s action for a prolonged period. They may also increase the solubility and bioavailability of poorly soluble drugs. This review summarizes the current data on nanomedicines for the prevention and treatment of prostate cancer. Thus, nanomedicine is pioneering in disease management.

We propose and investigate a queueing model of a battery swapping and charging station (BSCS) for electric vehicles (EVs). A new approach to the analysis of the queueing model is developed, which combines the representation of the model as a stochastic dynamic system with the use of the methods and results of tropical algebra, which deals with the theory and applications of algebraic systems with idempotent operations. We describe the dynamics of the queueing model by a system of recurrence equations that involve random variables (RVs) to represent the interarrival time of incoming EVs. A performance measure for the model is defined as the mean operation cycle time of the station. Furthermore, the system of equations is represented in terms of the tropical algebra in vector form as an implicit linear state dynamic equation. The performance measure takes on the meaning of the mean growth rate of the state vector (the Lyapunov exponent) of the dynamic system. By applying a solution technique of vector equations in tropical algebra, the implicit equation is transformed into an explicit one with a state transition matrix with random entries. The evaluation of the Lyapunov exponent reduces to finding the limit of the expected value of norms of tropical matrix products. This limit is then obtained using results from the tropical spectral theory of deterministic and random matrices. With this approach, we derive a new exact formula for the mean cycle time of the BSCS, which is given in terms of the expected value of the RVs involved. We present the results of the Monte Carlo simulation of the BSCS’s operation, which show a good agreement with the exact solution. The application of the obtained solution to evaluate the performance of one BSCS and to find the optimal distribution of battery packs between stations in a network of BSCSs is discussed. The solution may be of interest in the case when the details of the underlying probability distributions are difficult to determine and, thus, serves to complement and supplement other modeling techniques with the need to fix a distribution.

It is commonly acknowledged that polymer composites in service are often subjected to not only intricate mechanical loads but also harsh environmental conditions. The mechanical and thermal properties of five particular composites are explored here. The composites are composed of laminates of glass cloth type “E” sheet infilled with a duroplastic matrix. This is a thermoset polymer—epoxy resin with different molecular weights. The composites were fabricated by IZOERG company, which is based in Poland. The final articles were 1.5 mm thick by 60 cm long and 30 cm wide, with the glass layers arranged parallel to the thickness. Young’s modulus and tensile strength were measured at room temperature. Using the thermal analysis of dynamic mechanical properties (DMTA), the values of the storage modulus and the loss modulus were determined, and the damping factor was used to determine the glass transition temperature (Tg). It was revealed that the nature of changes in the storage modulus, loss modulus, and damping factor of composite materials depends on the type of epoxy resin used. Thermal expansion is a crucial parameter when choosing a material for application in cryogenic conditions. Thanks to the TMA method, thermal expansion coefficients for composite materials were determined. The results show that the highest value of the coefficient of thermal expansion leads the laminate EP_4_2 based on brominated epoxy resin cured with novolac P. Duroplastic composites were characterized at cryogenic temperatures, and the results are interesting for developing cryogenic applications, including electric motors, generators, magnets, and other devices.

Standard clinical markers can improve tick-borne infection (TBI) diagnoses. We investigated immune and other clinical biomarkers in 110 patients clinically diagnosed with TBIs before (T0) and after antibiotic treatment (T2). At T0, both the initial observation group and patients without seroconversion for tick-borne pathogens exhibited notably low percentages and counts of CD3 percentage (CD3%), CD3+ cells, CD8+ suppressors, CD4 percentage (CD4%), and CD4+ helper cells, with the latter group showing reductions in CD3%, CD3+, and CD8+ counts in approximately 15-22% of cases. Following treatment at the T2 follow-up, patients typically experienced enhancements in their previously low CD3%, CD3+ counts, CD4%, and CD4+ counts; however, there was no notable progress in their low CD8+ counts, and a higher number of patients presented with insufficient transferrin levels. Moreover, among those with negative serology for tick-borne infections, there was an improvement in low CD3% and CD3+ counts, which was more pronounced in patients with deficient transferrin amounts. Among those with CD57+ (n = 37) and CD19+ (n = 101) lymphocyte analysis, 59.46% of patients had a low CD57+ count, 14.85% had a low CD19 count, and 36.63% had a low CD19 percentage (CD19%). Similar findings were observed concerning low CD57+, CD19+, and CD19% markers for negative TBI serology patients. Overall, this study demonstrates that routine standard clinical markers could assist in a TBI diagnosis.

Non-alcoholic fatty liver disease (NAFLD), a significant cause of chronic liver disease, presents a considerable public health concern. Despite this, there is currently no treatment available. This study aimed to investigate dietary flaxseed in the JCR:LA-corpulent rat strain model of NAFLD. Both obese male and female rats were studied along with their lean counterparts after 12 weeks of ingestion of a control diet, or control diet with flaxseed, or high fat, high sucrose (HFHS), or HFHS plus flaxseed. Obese rats showed higher liver weight and increased levels of cholesterol, triglyceride, and saturated fatty acid, which were further elevated in rats on the HFHS diet. The HFHS diet induced a significant two-fold elevation in the plasma levels of both aspartate aminotransferase and alanine aminotransferase in the obese male and female rats. Including flaxseed in the HFHS diet significantly lowered liver weight, depressed the plasma levels of both enzymes in the obese male rats, and reduced hepatic cholesterol and triglyceride content as well as improving the fatty acid profile. In summary, including flaxseed in the diet of male and female obese rats led to an improved lipid composition in the liver and significantly reduced biomarkers of tissue injury despite consuming a HFHS chow.

The importance of selecting an appropriate berseem variety and implementing effective nutrient management practices is crucial for maximizing both the production and economic potential of forage crops. This was clearly demonstrated in a field experiment conducted during the rabi seasons of 2019–2020 and 2020–2021. The experimental setup was a factorial randomized block design incorporating five berseem varieties (Mescavi, HB-1, HB-2, BL-10, and BL-42) and five integrated nutrient management practices: 100% recommended dose of fertilizers (RDF) or NM-1, 75% RDF + plant growth-promoting rhizobacteria (PGPR) or NM-2, 75% RDF + municipal solid waste compost (MSWC) or NM-3, 75% RDF + farmyard manure (FYM) + PGPR or NM-4, and 50% RDF + MSWC + PGPR or NM-5. The objective of the experiment was to evaluate the physio-morphological responses, biomass yield, and economic efficiencies of different berseem varieties under various nutrient management practices. The experimental results highlighted the superior performance of the BL-42 variety in terms of growth and yield attributes compared to the other tested berseem varieties. Specifically, BL-42 showed an enhancement in total green fodder yield by 17.10%, 26.60%, 37.75%, and 28.04% over the varieties BL-10, HB-2, HB-1, and Mescavi, respectively. Moreover, the application of the 75% RDF + FYM + PGPR treatment (NM-4) significantly boosted the total green fodder yield by 13.08%, 14.29%, 34.48%, and 39.02% over the 75% RDF + MSWC, 100% RDF, 75% RDF + PGPR, and 50% RDF + MSWC + PGPR treatments, respectively. In terms of economic returns, BL-42 achieved a significantly higher gross return (GR) and net return (NR) of 194,989 ₹/ha and 145,142 ₹/ha, respectively, compared to the GR and NR of BL-10 (166,512 and 116,665 ₹/ha, respectively). Similarly, the nutrient management practice of 75% RDF + FYM + PGPR recorded the highest GR and NR (191,638 and 137,346 ₹/ha, respectively) compared to the 100% RDF treatment (167,593 and 120,716 ₹/ha, respectively). These findings underscore the critical role of variety selection and tailored nutrient management in optimizing both the yield and economic gains in forage crop cultivation. The significant differences in production and returns highlight the potential of targeted agronomic strategies to enhance the profitability and sustainability of forage farming.

The fidelity of the decadal experiment in Coupled Model Intercomparison Project Phase-5 (CMIP5) has been examined, over different climate variables for multiple temporal and spatial scales, in many previous studies. However, most of the studies were for the temperature and temperature-based climate indices. A quite limited study was conducted on precipitation of decadal experiment, and no attention was paid to the catchment level. This study evaluates the performances of eight GCMs (MIROC4h, EC-EARTH, MRI-CGCM3, MPI-ESM-MR, MPI-ESM-LR, MIROC5, CMCC-CM, and CanCM4) for the monthly hindcast precipitation of decadal experiment over the Brisbane River catchment in Queensland, Australia. First, the GCMs datasets were spatially interpolated onto a spatial resolution of 0.05 × 0.05° (5 × 5 km) matching with the grids of observed data and then were cut for the catchment. Next, model outputs were evaluated for temporal skills, dry and wet periods, and total precipitation (over time and space) based on the observed values. Skill test results revealed that model performances varied over the initialization years and showed comparatively higher scores from the initialization year 1990 and onward. Models with finer spatial resolutions showed comparatively better performances as opposed to the models of coarse spatial resolutions, where MIROC4h outperformed followed by EC-EARTH and MRI-CGCM3. Based on the performances, models were grouped into three categories, where models (MIROC4h, EC-EARTH, and MRI-CGCM3) with high performances fell in the first category, and middle (MPI-ESM-LR and MPI-ESM-MR) and comparatively low-performing models (MIROC5, CanCM4, and CMCC-CM) fell in the second and third categories, respectively. To compare the performances of multi-model ensembles’ mean (MMEMs), three MMEMs were formed. The arithmetic mean of the first category formed MMEM1, the second and third categories formed MMEM2, and all eight models formed MMEM3. The performances of MMEMs were also assessed using the same skill tests, and MMEM2 performed best, which suggests that evaluation of models’ performances is highly important before the formation of MMEM.