The Niger Delta region of Nigeria has experienced persistent hydrocarbon contamination due to extensive oil and gas exploration activities. This study determined of total petroleum hydrocarbon (TPH) detection in hydrocarbon contaminated surface waters in the Niger Delta; using ELISA as an analytical technique. Ninety (90) surface water samples were collected from six (6) sampling locations, including a control site, and analyzed using the ELISA technique. Results revealed that TPH concentrations in surface water ranged from 0.033 to 10.32 mg/L, with an average of 3.49 ± 2.64 mg/L. These concentrations exceeded the Nigerian Standard for Drinking Water Quality (NSDWQ) limit of 0.003 mg/L and the Environmental Guidelines and Standards for the Petroleum Industry in Nigeria (EGASPIN) limit of 0.05 mg/L, indicating severe hydrocarbon pollution. The study concluded that ELISA method demonstrated high accuracy, sensitivity, and reproducibility, validating its efficiency as an alternative to conventional chromatographic methods for environmental hydrocarbon analysis.

Forestry activities require accurate inventories to support sustainable forest management; however, conventional field-based inventories are costly and difficult to implement over large areas. This study aimed to define and evaluate a methodology to estimate the number of trees in commercial plantations of Pinus elliottii and Eucalyptus sp. using images acquired by an Unmanned Aerial Vehicle (UAV) in the central region of Rio Grande do Sul, Brazil. The study was conducted in three plantations (P1 – Pinus, 17 ha; P2 and P3 – Eucalyptus, totaling 33 ha). Circular sampling plots of 400 m² were established for the conventional forest inventory. Orthomosaics were generated from UAV flights using a DJI Mavic 3M at 120 m altitude, with 80% forward and 70% side overlap. Circular and rectangular sampling units with the same area were delineated on the images at the same sampling locations. Image processing was performed in Agisoft Metashape, and spatial analysis was conducted in QGIS. Tree counts obtained by the three methods (field inventory, circular plots on imagery, and rectangular plots on imagery) were compared using the Shapiro–Wilk normality test and, when appropriate, Student’s t-test or the Mann–Whitney U test. Statistically significant differences were observed between field-based counts and UAV-derived estimates in all study areas, whereas no significant differences were found between the two image-based methods. Discrepancies were smaller in Pinus plantations and more pronounced in Eucalyptus stands, indicating underestimation related to crown architecture, stand density, crown overlap, and image resolution and illumination constraints. Under the evaluated conditions, UAV-based approaches were not efficient for sample-based estimation of tree numbers, highlighting the need for species-specific calibration, lower-altitude flights, and improved image processing strategies.

Mechanistic insights into ozone-induced reduction in antibiotic resistance gene abundance in PM2.5.

This study investigates the seasonal and spatial distribution of benzo[a]pyrene (BaP) in street dust across Raniganj, revealing significant variations linked to both seasonal shifts and land use types. BaP concentrations in street dust samples ranged from 82.2 ng.g-1 to 531.6 ng.g-1, with a mean value of 262.45±75.55 ng.g-1. The highest BaP levels were observed during winter, particularly in heavy traffic, coal mines, and industrial areas, suggesting contributions from industrial activities and vehicular emissions, coal chemical production, and gangue accumulation. An analysis by land use type indicated that BaP levels were highest in busy traffic areas, coal mine areas, and industrial areas, with traffic-congested sites showing the highest average concentration (328.29 ng.g-1). Seasonal analysis showed that winter BaP concentrations were the highest on average (336.28±93.43 ng.g-1), followed by monsoon and summer. These seasonal differences may be due to winter-specific factors, such as increased vehicular traffic, indoor heating, and atmospheric stability. In all five sampling locations, the hazard index (HI) values were moderate for both adults and children. Adults had an average overall cancer risk value of 2.89E-03, whereas children had an average of 2.61E-03, indicating that both age groups are at high risk. Samples collected from various land use types revealed a distinct difference in mean total BaP levels, as well as total cancer risk levels, with the following order observed: busy traffic area > coal mine area > industrial area > commercial area > residential area. The findings underscore the impact of anthropogenic activities and seasonal changes on BaP levels, emphasizing the need for targeted pollution management strategies in heavy-traffic and industrial regions, along with coal mining regions in Raniganj.

Fecal pollution is a major water quality concern that poses significant health risks, primarily due to untreated domestic waste and inadequate sanitation. A coliform assessment was conducted at 20 selected sites in Lianga, Hinatuan, and Bislig Bays of Surigao del Sur from January 30 to February 8, 2019, to determine the presence of total and fecal coliforms and to estimate their densities using the most probable number (MPN) method. Water samples were analyzed using a standard multiple-tube fermentation technique, following the presumptive-confirmed and completed phases. Results were evaluated and classified in accordance with the 2016 Water Quality Guidelines and the General Effluent Standards established by the Department of Environment and Natural Resources (DENR). Nine sites recorded the highest total coliform counts (<gt;1600 MPN/100 mL) and eight sites recorded the highest fecal coliform counts, while the lowest counts (<lt;1.8 MPN/100 mL) were observed at three sites for total coliform and at four sites for fecal coliform across all sampling locations. Based on consolidated DENR classification, four sites were categorized as Class SA, one as Class SB, and two as Class SC, indicating suitability for marine protected areas, recreation, and mariculture, while the remaining sites were classified as Class SD for navigation. Physico-chemical parameters were within ranges suitable for marine life. Overall, most sites exhibited alarmingly high fecal coliform levels, particularly those used for mariculture/aquaculture and recreational activities. These findings reveal significant contamination in Lianga, Hinatuan, and Bislig Bays and emphasize the urgent need for improved waste management and stricter enforcement of environmental and sanitation regulations to protect public health.

Abstract. Monitoring water quality in inland water bodies is critical for environmental management, yet traditional sampling methods are costly and spatially limited. Remote sensing offers a viable alternative by enabling large-scale assessment of water quality parameters such as chlorophyll-a (Chl-a) concentrations through empirical models linking spectral indices to in situ measurements. However, the accuracy of these models depends on representative sampling strategies that capture spatial and temporal variability. This study evaluates a clustering-based approach to optimize sampling site selection in the Solís Dam, Mexico, using Sentinel-2 imagery. We analyzed a one-year time series of Sentinel-2 data to compute spectral indices related to Chl-a and turbidity. Unsupervised K-means clustering was applied to stratify the reservoir into zones of distinct water quality variability, guiding the placement of 20 sampling sites. Field campaigns during dry and wet seasons (2024) provided Chl-a measurements, which were correlated with spectral indices. The Gi033BDA index showed the strongest correlation (R2 > 0.7, p < 0.01) and was used to develop a linear regression model for Chl-a estimation. Results confirmed that clustering-derived sampling points effectively represented spatial variability, though temporal mismatches (1-day lag) and samples location inaccuracies introduced minor errors. The method demonstrates how pre-stratification using remote sensing can enhance sampling efficiency while maintaining model accuracy. This approach is particularly valuable for large-scale monitoring, reducing reliance on exhaustive field campaigns. Future work should address temporal dynamics and sensor resolution trade-offs for broader applicability.

Groundwater is a vital yet increasingly vulnerable resource, with nitrate contamination posing a significant risk to human beings and the ecosystem. The present study offers an integrated, sustainability-focused assessment of groundwater quality in India's eastern littoral state, based on groundwater quality data from 422 sampling locations. In 2024, nitrate concentrations peaked at 387ppm, with an average of over 37ppm; notably, more than 20% and 17% of samples exceeded the Bureau of Indian Standards and World Health Organization guidelines, respectively. Both non-carcinogenic and carcinogenic health risks were assessed, revealing that nitrate poses risks through oral and dermal exposure, while nitrite contributes to cancer risk through ingestion. Principal component analysis multiple linear regression highlighted strong correlations among nitrate and macro-elements such as sodium, chloride, calcium, magnesium, and potassium, indicating common anthropogenic sources such as fertilizer runoff and wastewater infiltration. Multivariate analysis showed that nitrate is the dominant contaminant influencing groundwater quality shifts from 2020 to 2024, largely driven by agricultural intensification and sewage disposal contributions. These findings underscore the critical importance of adopting strategic intervention policies and promoting resilient groundwater governance frameworks across national and international scales.

Deep learning (DL) supervised techniques have been extensively employed in magnetic resonance imaging (MRI) reconstruction, delivering notable performance enhancements over traditional non-DL methods. Nonetheless, these models have vulnerabilities during testing such as their susceptibility to worst-case or noise-based measurement perturbations, variations in training/testing settings like acceleration factors, contrast, $k$ -space sampling locations, and distribution shifts stemming from unseen lesions and different anatomies. This article addresses these robustness challenges by leveraging diffusion models (DMs). In particular, we present a robustification strategy that improves the resilience of DL-based MRI reconstruction methods by utilizing pretrained DMs as purifiers. We dub our method as robust DL-based MRI with diffusion purification (RODIO). In contrast to conventional robustification methods for DL-based MRI reconstruction, such as adversarial training (AT), our proposed approach eliminates the need to tackle a minimax optimization problem. It only necessitates efficient fine-tuning on purified examples. Our experimental results underscore the effectiveness of our approach in addressing the mentioned instabilities, outperforming standalone diffusion-based MRI reconstructors and leading robustification methods for deep supervised MRI reconstruction, including AT and randomized smoothing (RS). Our experiments demonstrate: 1) the adaptability of our approach across multiple DL-based supervised MRI reconstruction models; 2) compatibility with accelerated diffusion-based samplers; 3) robustness to data with unseen lesions; and 4) effectiveness when applied to unsupervised single-shot generative reconstructors.

Resistance of Gram-negative bacteria to the recommended and available antimicrobial drugs is a growing public health problem in different locations worldwide, leading to increased morbidity and mortality in patients. This study was conducted in the Korhogo Department to enhance the understanding of Shiga toxin-producing Escherichia coli O157:H7 (STEC O157:H7) in local swine populations. A total of 200 rectal swabs were collected from pigs across four sub-prefectures. Isolation of STEC O157:H7 was performed on a chromogenic selective medium. Subsequently, 62 isolates obtained were tested for antimicrobial susceptibility against nine agents using the standard disk diffusion method. Following analysis, 62 of the 200 samples tested were positive, yielding an overall prevalence of 31%. The study further revealed that, aside from the sampling location, neither sex nor age had a significant effect on the prevalence of this bacterium. Antibiotic susceptibility testing demonstrated that 100% of the isolates were sensitive to gentamicin, colistin, and ceftriaxone. Conversely, all isolates exhibited complete (100%) resistance to the six other antibiotics tested. The study confirms a high prevalence of E. coli O157:H7 in pig farms, alongside a high level of resistance to commonly used antimicrobials. Further research is needed to better understand the epidemiology and transmission dynamics of this zoonotic agent.

This study is an attempt to determine natural radioactivity levels in soils collected from the mountains surrounding the Koya District in the Kurdistan Region, Iraq. A portable radioisotope identifier was used for gamma-ray detection from the sampling points to avoid random sample collection. Surface soil samples were taken based on the level of gamma ray detection from the sample locations. A high-resolution detector was used to measure radionuclide content of the samples. The obtained results ranged from 11.49 to 90.32Bqkg-1 for 226Ra, 18.15 to 106.8Bqkg-1 for 232Th, and 51.59 to 817.9Bqkg-1 for 40K. Additionally, the radiation hazard parameters were calculated. The average values of absorbed dose rate (D), annual effective dose equivalent (AEDE), and excess lifetime cancer risk (ELCR) were found to be higher than the permissible limits. The distribution of 226Ra, 232Th, and 40K in the soils of the study area was visually depicted by spatial distribution maps. In addition, the correlation between radionuclides and radiological risk metrics was investigated using a multivariate statistical approach. The results showed that the soils of the Bawajy and Bnabawe mountains present a moderate radiation risk due to moderately high levels of 226Ra, 232Th, and 40K.

First evidence of elemental accumulation patterns in the hard tick Dermacentor reticulatus exoskeleton using EDS analysis: Insights into bioindicator potential across diverse habitats in Poland and Ukraine.

Objective: This meta-analysis explored the relationship between burnout and psychological distress across different academic disciplines, measurement tools, institutional contexts, and the pandemic. Method: We synthesized 76 effect sizes from 29 studies involving 20,037 students, residents, and fellows in the United States. Results: The correlation between burnout and psychological distress was (r = 0.44), with stress showing the strongest correlation (r = 0.48). Notably, the correlations were higher during the pandemic (r = 0.46) compared to pre-pandemic (r = 0.44). Our subgroup analysis indicated that medical students exhibited a stronger association (r = 0.5) than fellows and residents. Additionally, samples from a multiple organization yielded higher correlations (r = 0.46). Conclusions: Among the dimensions of burnout, emotional exhaustion demonstrated a stronger correlation with psychological distress. Meta-regression confirmed that the students’ disciplines, sample locations, and COVID-19 moderated the overall effect size. Findings highlight the urgent need for targeted interventions to address environmental stressors within medical training.

Background: Equine piroplasmosis (EP), caused by Babesia caballi and Theileria equi, is a prevalent tick-borne hemoprotozoan disease worldwide. In Iran, the disease is endemic and often manifests in subclinical form. To control the disease by detecting carrier horses, real-time polymerase chain reaction (PCR) is a suitable method. Objectives: We aimed to detect B. caballi and T. equi in horses in Ardabil Province, Iran, using SYBR Green I real-time PCR. Methods: This study was conducted from April to August 2015 in 5 cities (Ardabil, Nir, Namin, Sareyn, and Meshginshahr) in Ardabil Province, Iran. Blood samples were randomly collected from 92 healthy horses, noting their age, gender, and sampling location. Genomic DNA was extracted from each sample and assessed, followed by SYBR green I real-time PCR. Data analysis was conducted using Rotor-Gene Q Series software to calculate the target DNA concentration based on the unknown sample’s cycle threshold (Ct) value. Positive values were defined as exceeding 1 ng/reaction. The relationship between horse infection rate and different age groups (1-5, 6-10, and >10 years), gender, and sampling locations was investigated using a chi-square test through SPSS statistical software. P<0.05 were considered significant. Results: In this study, the frequency of B. caballi-infected horses was 9(9.8%), and that of T. equi-infected horses was 4(4.4%). A significant relationship was observed between the B. caballi infection and the age group of 5-10 years. However, there was no significant relationship between the B. caballi infection and gender or sampling locations. Furthermore, no significant relationship was observed between the T. equi infection and the age groups, gender, and sampling locations of the horses. Conclusion: The infection found in apparently healthy horses suggests endemic EP in this region. Therefore, greater focus is needed on controlling and treating carrier horses.

PFAS and adsorbable organic fluorine characterization, fate, and transport throughout the aqueous treatment train of an advanced wastewater treatment plant.

Evolution of oil droplet size distributions entrained by breaking waves.

Fecal contamination of coastal waters threatens human and ecosystem health. Microbial source tracking (MST) methods offer a strategy to identify sources of fecal contamination through the measurement of genetic markers associated with a particular animal host. In this study, we measured fecal indicator bacteria (FIB) and employed MST methods to evaluate the sources of fecal contamination in a coupled stream-beach system in Kailua Bay, Hawai'i where residents adjacent to the shoreline use onsite cesspools for sewage management. In a baseline campaign, we measured enterococci concentrations in surface water samples from the stream and beach (n = 36). Results indicated that the stream contained enterococci in exceedance of the state standard (50% of samples) and therefore represented a potential source of contamination to the coastal ocean. To identify potential fecal sources, five MST genetic markers - three indicative of human feces (HF183/BacR287, CPQ_056, and ToBRFV), one of dog feces (DG3), and one of avian feces (GFD) - were measured alongside enterococci concentrations and environmental parameters (water temperature, salinity, tidal stage, and rainfall) in stream and beach water samples from longitudinal (n = 78) and spatial (n = 25) sampling campaigns. During the two-week longitudinal campaign, detections were observed for the avian marker (78% of samples positive), human marker ToBRFV (40%), and dog marker (10%), while HF183/BacR287 and CPQ_056 were not detected. Marker detection frequency varied by sampling location, with GFD most frequently detected in the stream and ToBRFV most frequently detected at the site adjacent to cesspools. In the spatial campaign, enterococci concentrations significantly decreased along the stream towards the beach (p < 0.001) but similar trends were not observed for MST markers. The occurrence of human, avian, and canine MST genetic markers in this study confirms these are important sources of fecal contamination in the Kailua Bay area. This study is the first to implement the RNA-based ToBRFV digital PCR assay in tropical coastal waters.

We report on a scanned superconducting quantum interference device (SQUID) microscope operating in a cryogen-free cryostat, with the capability of up to forty RF connections with 20GHz bandwidth to a device under test. The system utilizes planar gradiometric DC SQUIDs, which are fully shielded except for a pair of pickup coils with radii as small as 250nm and have on-chip field coils allowing for susceptometry. The system noise is 1.3 μΦ0/Hz at the base temperature of 3.3K. The sample temperature is variable, and both magnetometry and susceptibility measurements are simultaneously possible with the sample temperature above 40K. Through the use of a cryogenic chip socket and silicon interposer, round-trip RF losses to a sample are ∼15 dB at 20GHz. A combination of both active and passive magnetic shielding results in a residual magnetic field of less than 100 nT at the sample location.

This study assessed the Effects of Economic Activities on River Benue Water Quality: Case studies of Rice Mill Wadata and Pure Biotech Company Makurdi, Benue State, Nigeria. The objectives of the study include; to examine and analyse the physical, chemical, biological/microbiological water quality and to examine the suitability of water for human consumption and its implications for public health in the study area. Water samples were collected from 3 sample location (River Benue at Abinsi, the waste water discharge points of the Pure Biotech Company and Rice Mill Wadata). The study used purposive sampling technique to select the points (upstream, midstream, and downstream) were water samples were collected and analyzed for various parameters. Raw data (water samples) were analysed at Greater Makurdi Water Works Laboratory, Makurdi while the results were presented via frequencies in a tabular form. Results showed that all locations exceeded Nigerian Standard for Drinking Water Quality (NSDWQ) and World Health Organization (WHO) limits for colour, turbidity, Cr6+, and total coliform. High biochemical oxygen demand (BOD) levels indicated organic pollution. The study concludes that water quality in all locations is compromised, posing potential health risks. The study recommended strengthening environmental regulations on waste management before discharging in to the river, regular monitoring, treatment, and mitigation measures to improve water quality as well as engaging in public health education in and around the communities around riverine areas.

ABSTRACT Amphibian skin bacteria are important for host health by protecting against pathogens, but communities can vary greatly among host populations, influenced by environmental factors, habitats, and ecological interactions. Understanding this variation is key to studying how amphibians adapt and remain healthy across diverse environments. In this study, we sampled skin bacteria on coquí frogs ( Eleutherodactylus coqui ) from two sites in each of two regions: Puerto Rico, where they are native, and Hawaii, where they are introduced. We tested the hypothesis that bacterial communities differ between regions but are relatively more similar within each region. We also expected that comparing bacteria at the genus level would show more similarity than at the level of unique sequences, indicating the importance of microdiversity and functional roles. Beta diversity provided mixed support for these hypotheses, showing differences between sites that became less pronounced within each region at the bacterial genus level. Interestingly, one Hawaiian site stood out as distinct in multiple analyses. Despite predicted variation, we expected to find core (prevalent) bacteria shared across sampling locations, which was confirmed for a few taxa, suggesting they play important functional roles and may be selected by the host. Microbial community variation on coquí frogs is influenced by their habitat‐generalist nature, with habitat likely affecting environmental bacterial sources, but can also be shaped by invasion history, disease, development stages, and season. This research enhances our understanding of how environmental and biological factors shape amphibian microbiomes, which is valuable for conservation efforts and studying invasive species.

Matrix metalloproteinases as prognostic markers in oral squamous cell carcinoma: A systematic review, meta-analysis and meta regression of MMP-2, MMP-7, and MMP-9 expression and their serum and saliva concentrations.