Primary Data on ATTR-Amyloidosis Prevalence Among Elderly Patients With Left Ventricular Hypertrophy in Russia.

AIM: To estimate the prevalence of amyloid cardiomyopathy (CM) caused by transthyretin amyloidosis (ATTR) and immunoglobulin light chain (AL) amyloidosis among patients aged >65 years with interventricular septal (IVS) hypertrophy of ≥14 mm. MATERIAL AND METHODS: From January through August 2023, 60 patients (mean age 7.2±7.3 years, 34 (56.67%) men) were enrolled. Patients meeting the inclusion criteria underwent an echocardiographic study with determining the myocardial longitudinal strain, myocardial scintigraphy with 99mTc-pyrfotech, myocardial single-photon emission computed tomography, measurement of N-terminal fragment of brain natriuretic peptide and troponin I, and the immunochemical study of serum and urine proteins with measurement of free light chains. In the presence of grades 2 and 3 radiopharmaceutical uptake according to scintigraphy, a molecular genetic study was performed for differential diagnosis of wild-type transthyretin amyloidosis (wtATTR) and hereditary/variant (hATTR) ATTR-CM. RESULTS: According to data of myocardial scintigraphy with 99mTc-pyrfotech, grade 3 uptake in the absence of monoclonal secretion was detected in 5 (8.3%) cases and grade 2 radiotracer uptake in the absence of monoclonal secretion was detected in 6 (10%) patients. Myeloma complicated by AL amyloidosis and primary AL amyloidosis were found in 5 (8.3%) patients. CONCLUSION: Among patients aged ≥65 years with IVS hypertrophy ≥14 mm, amyloid CM was detected in 20% of cases (12 patients), including 5 cases (8.3%) of AL amyloidosis and 7 cases (11.7%) of ATTR amyloidosis.

How natural are the forests in Rajiv Gandhi (Nagarhole) Tiger Reserve? A multi-source data approach.

This study aimed to monitor long-term land use dynamics for understanding the natural forest integrity and intactness of the Rajiv Gandhi (Nagarhole) Tiger Reserve (RTR) pre- and post-declarations as TR. We employed multi-source data from Survey of India Toposheets (1:50 k), Landsat-7, and Sentinel-2A along with Global Ecosystem Dynamics Investigation (GEDI) vegetation canopy height (10 m) data, a high-spatial resolution CORONA (1970) images and temporal Google Earth Pro images for mapping and validation. To map vegetation type, land use and land cover (LULC) transitions, and fragmentation (1980-2022) we employed a hybrid classification approach. This study also analyzed decadal forest dynamics within TRs using India's State of Forest Reports (ISFR). Findings reveal significant forest fragmentation and habitat loss due to anthropogenic activities in the TR. Mono-plantations (teak and eucalyptus) were found inside TR, while the buffer (1 km) was occupied mainly with coffee and orange plantations which indicates the prevalence of human footprint. The overall accuracy of the current period (2022) is 92.0% with a kappa coefficient value of 0.90. These plantations were established during the British colonial period (early 1900s) for commercial purposes by clearing natural forests. The present study highlights that mono-plantations have not transitioned into natural forests even after a century. This lack of transformation could potentially compromise the integrity of the native forest. Despite its ecological significance, RTR has experienced disturbance due to human footprint. Hence, there is a need for an action plan to protect this vital landscape by replacing mono-plantations with suitable species to preserve the integrity of the forest. These issues extend beyond the protected areas, impacting surrounding regions and require regular monitoring. The proposed methods can be applied to other protected areas facing similar problems in the country and world.

Experiment to Demonstrate Pesticide-Induced Antimicrobial Resistance (AMR): An Emerging Health Threat.

Background Pesticides, including insecticides, herbicides, and fungicides, are essential for global food production, boosting crop yields, and preventing disease transmission. However, their excessive and improper use raises concerns about potential long-term consequences, affecting microbial ecosystems and fostering antimicrobial resistance. Materials and methods The objective of the study was to identify the effect of the pesticide compound (Imidacloprid 17.1% w/w) on the ATCC Escherichia coli. An experiment was conducted on ATCC Escherichia coli 27852. A 0.5 McFarland suspension of the strain was incubated in the presence of a pesticide compound (Imidacloprid 17.1% w/w) at a dilution of 1:4, 1:8, and 1:16. at 370C. Antibiotic susceptibility for cefoxitin, ciprofloxacin, ceftazidime, amikacin, and imipenem was determined via the Kirby-Bauer disk diffusion test at intervals of 24 hours, 48 hours, seven days, and 21 days. The results were then compared to the standard zone of inhibition diameter for ATCC Escherichia coli 27852 by Clinical and Laboratory Standards Institute (CLSI) guidelines. Results No bacterial growth was detected at pesticide dilutions of 1:1 and 1:2, indicating their inability to tolerate high pesticide concentrations. However, growth became evident at a 1:4 dilution and beyond, with mutants thriving within the inhibition zone. The experiment caused significant alterations in the inhibition zone sizes for all antibiotics, especially notable with imipenem, amikacin, and ceftazidime compared to the initial zone size for ATCC Escherichia coli 27852. Conclusion Our study concludes that the pesticide (Imidacloprid 17.1% w/w) significantly influences antibiotic resistance, especially with carbapenems, aminoglycosides, and cephalosporins in the tested groups at various concentrations and durations of exposure.

A novel flexible CO2 gas sensor based on polyvinyl alcohol/yttrium oxide nanocomposite films.

Polyvinyl alcohol/yttrium oxide (PVA/Y2O3) nanocomposite films with five different weight ratios of PVA and Y2O3 nanoparticles (NPs) were prepared using a simple solution casting method. The prepared polymer nanocomposite (PNC) films were examined using Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). FTIR spectra exhibited a strong interaction between the PVA matrix and Y2O3 NPs. SEM results indicated that Y2O3 NPs were properly dispersed in the PVA matrix. The thermal stability of the PVA/Y2O3 nanocomposite films was found to be dependent on Y2O3 NP loading (wt%) in the nanocomposite films. Furthermore, chemiresistive gas sensing properties of the PVA/Y2O3 nanocomposite films were evaluated and the sensing parameters including sensing response, operating temperature, selectivity, stability, response/recovery time, and repeatability were systematically investigated based on the change in electrical resistance of the nanocomposite film in the presence of carbon dioxide (CO2) gas. The maximum sensing response (S) of 92.72% at a concentration of 100 ppm under an optimized operating temperature of 100 °C with a fast response/recovery time of ∼15/11 s towards CO2 gas detection was observed for the PVA/Y2O3 nanocomposite film with 5 wt% loading of Y2O3 NPs in the PVA matrix. The finding in this work suggest that Y2O3 NPs are sufficiently fast as a CO2 gas sensing material at a relatively low operating temperature. Moreover, the key role of the Y2O3 NPs in modulating the electrical and gas sensing properties of the PVA matrix is discussed here.

Global spatial distribution of Prosopis juliflora - one of the world's worst 100 invasive alien species under changing climate using multiple machine learning models.

Climate change is one of the factors contributing to the spread of invasive alien species. As a result, it is critical to investigate potential invasion dynamics on a global scale in the face of climate change. We used updated occurrence data, bioclimatic variables, and Köppen-Geiger climatic zones to better understand the climatic niche dynamics of Prosopis juliflora L. (Fabaceae). In this study, we first compared several algorithms-MaxEnt, generalized linear model (GLM), artificial neural network (ANN), generalized boosted model (GBM), generalized additive model (GAM), and random forest (RF)-to investigate the relationships between species-environment and climate for mesquite. We identified the global climate niche similarity sites (NSSs) using the coalesce approach. This study focused on the current and future climatic suitability of P. juliflora under two global circulation models (GCMs) and two climatic scenarios, i.e., Representative Concentration Pathways (RCPs), 4.5 and 8.5, for 2050 and 2070, respectively. Sensitivity, specificity, true skill statistic (TSS), kappa coefficient, and correlation were used to evaluate model performance. Among the tested models, the machine learning algorithm random forest (RF) demonstrated the highest accuracy. The vast swaths of currently uninvaded land on multiple continents are ideal habitats for invasion. Approximately 9.65% of the area is highly suitable for the establishment of P. juliflora. Consequently, certain regions in the Americas, Africa, Asia, Europe, and Oceania have become particularly vulnerable to invasion. In relation to RCPs, we identified suitable area changes (expansion, loss, and stability). The findings of this study show that NSSs and RCPs increase the risk of invasion in specific parts of the world. Our findings contribute to a cross-border continental conservation effort to combat P. juliflora  expansion into new potential invasion areas.