The Department of Beni, in the country of Bolivia, is thought to host a significant level of biodiversity as a result of its tropical, moist, and diverse climate and landscape. However, the biodiversity of Beni is also considered poorly known and understudied due to its inaccessible landscapes, socio-economic challenges, and an overall lack of biodiversity infrastructure. This emphasizes the need for comprehensive species inventories and the development of effective conservation policies and strategies. We conducted an assessment of biodiversity, environmental vulnerability, and conservation status of reptiles documented in Beni. We identified 169 reptile species, spanning three orders and twenty-five families that have been officially documented in Beni. Utilizing the Environmental Vulnerability Score (EVS), we classified these species into high (17.8%), medium (68.1%), and low (14.2%) vulnerability categories, while IUCN categorization revealed 1.8% of reptile species in Beni are classified as vulnerable and 0.6% as near threatened. We found significant differences in ecological drivers of vulnerability among species within all categories (high, medium, low), with habitat specificity and human persecution being significantly higher for high and medium-vulnerability species. Our results demonstrate the intricate vulnerabilities of Beni’s reptiles, highlighting the need for comprehensive, species-specific conservation strategies and planning. Most importantly, our results offer a consolidated framework of information on reptile biodiversity and conservation for researchers, conservationists, and policymakers to use and build upon in the future that will facilitate the development of biodiversity infrastructure not only in the Department of Beni but throughout Bolivia and the Neotropics Full article

Mesenchymal adipose stromal cells (ASCs) are considered the most promising and accessible material for translational medicine. ASCs can be used independently or within the structure of scaffold-based constructs, as these not only ensure mechanical support, but can also optimize conditions for cell activity, as specific features of the scaffold structure have an impact on the vital activity of the cells. This manuscript presents a study of the secretion and accumulation that occur in a conditioned medium during the cultivation of human ASCs within the structure of such a partial skin-equivalent that is in contact with it. It is demonstrated that the ASCs retain their functional activity during cultivation both within this partial skin-equivalent structure and, separately, on plastic substrates: they proliferate and secrete various proteins that can then accumulate in the conditioned media. Our comparative study of changes in the conditioned media during cultivation of ASCs on plastic and within the partial skin-equivalent structure reveals the different dynamics of the release and accumulation of such secretory factors in the media under a variety of conditions of cell functioning. It is also demonstrated that the optimal markers for assessment of the ASCs’ secretory functions in the studied partial skin-equivalent structure are the trophic factors VEGF-A, HGF, MCP, SDF-1α, IL-6 and IL-8. The results will help with the development of an algorithm for preclinical studies of this skin-equivalent in vitro and may be useful in studying various other complex constructs that include ASCs. Full article

Visualizing the decision-making process is a key aspect of research regarding explainable arrhythmia recognition. This study proposed a visualized lead selection method to classify arrhythmia for multi-lead ECG signals. The proposed method has several advantages, as it uses a visualized approach to select effective leads, avoiding redundant leads and invalid information. It also captures the temporal dependencies of ECG signals and the complementary information between leads. The method deployed a lead activation heatmap (LA heatmap) based on a lead-wise network to select the proper 5 leads from 12-lead ECG heartbeats extracted from the public 2018 Chinese Physiological Signal Challenge database (CPSC 2018 DB), which were then fed into a ResBiTime network combining bidirectional long short-term memory (Bi-LSTM) networks and residual connections for a classification task of nine heartbeat categories (i.e., N, AF, I-AVB, RBBB, PAC, PVC, STD, LBBB, and STE). The results indicate an average precision of 93.25%, an average recall of 93.03%, an average F1-score of 0.9313, and that the proposed method can effectively extract additional information from ECG heartbeat data. Full article

Naturally colored fermented foods currently represent the trend toward a global demand for healthier products. This work produced naturally blue and green ice creams using C-phycocyanin (C-PC) and spirulina residual biomass (RB). The ice creams were assessed based on microbiological analysis, color stability over 6 months, antioxidant activity before and after in vitro digestion, and sensory evaluation. Considering the microorganisms that must be analyzed in accordance with Brazilian legislation, no growth was detected during the storage period. L*, a*, and b* were maintained according to the expected colors. The blue color was intoned over the shelf life (SC-PC *b −9.46 to −19.44 and MC-PC *b from −9.87 to −18.04). The antioxidant activity of the fermented ice creams SC-PC and SRB increased from 15.4 to 41.3 and from 15.3 to 38.0 µM TE/g, respectively, after bioaccessibility analysis. The C-PC ice cream’s appearance received the highest rating, with 70.26% of volunteers expressing a strong preference, highlighting its attractiveness. However, there were no significant differences compared to control samples in the global acceptance. The RB ice cream presented lower results for flavor but moderate acceptance. Thus, these fermented ice creams presented color stability over 6 months, and their antioxidant activity increased after in vitro digestion, highlighting their biological potential. Full article

Background and Objectives: As brain lesions present complex diagnostic challenges, accurate tissue sampling via biopsy is critical for effective treatment planning. Traditional frame-based stereotactic biopsy has been complemented by navigated biopsy techniques, leveraging advancements in imaging and navigation technology. This study aims to compare the navigated and frame-based stereotactic biopsy methods in a clinical setting, evaluating their efficacy, safety, and diagnostic outcomes to determine the optimal approach for precise brain lesion targeting. Materials and Methods: retrospective analysis was conducted on patients who underwent brain biopsies between January 2017 and August 2023 at an academic medical center. Data on patient demographics, clinical characteristics, biopsy technique (navigated vs. frame-based), and outcomes including accuracy, complications, and hospital stay duration were analyzed. Results: The cohort comprised 112 patients, with no significant age or gender differences between groups. Symptoms leading to biopsy were predominantly diminished muscle strength (42.0%), cognitive issues (28.6%), and aphasia (24.1%). Tumors were most common in the deep hemisphere (24.1%). The median hospital stay was 5 days, with a rehospitalization rate of 27.7%. Complications occurred in 4.47% of patients, showing no significant difference between biopsy methods. However, navigated biopsies resulted in fewer samples (p < 0.001) but with comparable diagnostic accuracy as frame-based biopsies. Conclusions: Navigated and frame-based stereotactic biopsies are both effective and safe, with comparable accuracy and complication rates. The choice of technique should consider lesion specifics, surgeon preference, and technological availability. The findings highlight the importance of advanced neurosurgical techniques in enhancing patient care and outcomes. Full article

There is a significant need to develop new environmentally friendly, extraction-free sample collection mediums that can effectively preserve and protect genetic material for point-of-care and/or self-collection, home-collection, and mail-back testing. Systematic evolution of ligands by exponential enrichment (SELEX) was used to create anti-ribonuclease (RNase) deoxyribonucleic acid (DNA) aptamers against purified RNase A conjugated to paramagnetic carboxylated beads. Following eight rounds of SELEX carried out under various stringency conditions, e.g., selection using Xtract-Free™ (XF) specimen collection medium and elevated ambient temperature of 28 °C, a panel of five aptamers was chosen following bioinformatic analysis using next-generation sequencing. The efficacy of aptamer inactivation of RNase was assessed by monitoring ribonucleic acid (RNA) integrity via fluorometric and real-time RT-PCR analysis. Inclusion of aptamers in reaction incubations resulted in an 8800- to 11,200-fold reduction in RNase activity, i.e., digestion of viral RNA compared to control. Thus, anti-RNase aptamers integrated into XF collection medium as well as other commercial reagents and kits have great potential for ensuring quality intact RNA for subsequent genomic analyses. Full article

The upcoming energy transition requires not only renewable energy sources but also novel electricity storage systems such as batteries. Despite Li-ion batteries being the main storage systems, other batteries have been proposed to fulfil the requirements on safety, costs, and resource availability. Moving away from lithium, materials such as sodium, magnesium, zinc, and calcium are being considered. Water-based electrolytes are known for their improved safety, environmentally friendliness, and affordability. The key, however, is how to utilize the negative metal electrode, as using water-based electrolytes with these metals becomes an issue with respect to oxidation and/or dendrite formation. This work studied magnesium, where we aimed to determine if it can be electrochemically deposited in aqueous solutions with alginate-based additives to protect the magnesium. In order to do so, atomic force microscopy was used to research the morphological structure of magnesium deposition at the local scale by using a probe—the tip of a cantilever—as the active electrode, during charging and discharging. The second goal of using the AFM probe technology for magnesium deposition and stripping was an extension of our previous study in which we investigated, for lithium, whether it is possible to measure ion current and perform nonfaradaic impedance measurements at the local scale. The work presented here shows that this is possible in a relatively simple way because, with magnesium, no dendrite formation occurs, which hinders the stripping process. Full article

The high nutritional value of alfalfa hay makes it a widely utilized component in animal feed. However, the current prevalent drying methods for forage have a significantly detrimental impact on the quality of alfalfa during the drying process. This study investigates the effects of high-voltage corona discharge (HVCD) treatment on post-cut alfalfa. Gradient experiments are conducted by adjusting the air-gap spacing at a voltage of 25 kV. The results demonstrate that as the distance decreases, there is an observed increase in the drying rate, rehydration rate, and color intensity of the HVCD-treated material. HVCD treatment significantly enhances crude protein content, which increases with decreasing air-gap spacing. Meanwhile, it negatively affects lignin, neutral detergent fiber (NDF), and acid detergent fiber (ADF) levels. The relative forage quality (RFQ) of alfalfa reaches its peak at an air-gap spacing of 7 cm. The application of HVCD disrupts the fiber structure and induces significant electroporation effects in cells. Minimal changes in functional groups preserve nutrient integrity. Furthermore, HVCD exhibits lower energy consumption compared to hot air dryers. The HVCD treatment is a highly efficient and effective method, with a gradual improvement in alfalfa hay quality as the air-gap distance decreases. Full article

Purpose: To assess the feasibility and the diagnostic accuracy of the new tool, DEvice© (AI, Rome, Italy), for screening patients with dry eye disease (DED). Methods: This study was performed at the University Magna Græcia of Catanzaro. Enrolled patients were classified as affected by DED (group 1) or not (group 2) using an already validated tool (Keratograph 5M, Oculus, Germany), evaluating the noninvasive keratograph breakup time (NIKBUT), tear meniscus height (TMH), meibomian gland loss (MGL), and bulbar redness. All the patients were then examined by means of DEvice©, which allowed the measurement of the relative humidity (RH) and temperature of the ocular surface. Symptoms were scored using the Ocular Surface Disease Index (OSDI) questionnaire. Results: Overall, 40 patients (17 males and 23 females, mean age 38.0 ± 17.1 years) were included: of these, 20 belonged to group 1 and the remaining 20 to group 2. Using Keratograph 5M, significant differences between groups 1 and 2 were detected for NIKBUT-first (respectively, 4.97 ± 1.85 vs. 13.95 ± 4.8 s; p < 0.0001) and for NIKBUT-average (10.55 ± 4.39 vs. 15.96 ± 4.08 s; p = 0.0003). No statistically significant changes were detected for TMH (p = 0.565), MGL (p = 0.051), and bulbar redness (p = 0.687). Using Device©, a statistically significant higher value of RH was found in group 1 compared to group 2 (respectively, 85.93 ± 10.63 vs. 73.05 ± 12.84%; p = 0.0049). A statistically significant correlation was found between RH and OSDI (r = 0.406; p = 0.009). The value RH showed a discriminating power to detect DED with an AUC = 0.782 (standard error 0.07264; 95% CI 0.6401–0.9249; p = 0.0022). Conclusions: The DEvice© can effectively discriminate DED patients from healthy subjects. The parameter RH showed good sensitivity, making this tool ideal for a fast and noninvasive DED screening. Full article

Traditional animal pose estimation techniques based on images face significant hurdles, including scarce training data, costly data annotation, and challenges posed by non-rigid deformation. Addressing these issues, we proposed dynamic conditional prompts for the prior knowledge of animal poses in language modalities. Then, we utilized a multimodal (language–image) collaborative training and contrastive learning model to estimate animal poses. Our method leverages text prompt templates and image feature conditional tokens to construct dynamic conditional prompts that integrate rich linguistic prior knowledge in depth. The text prompts highlight key points and relevant descriptions of animal poses, enhancing their representation in the learning process. Meanwhile, transformed via a fully connected non-linear network, image feature conditional tokens efficiently embed the image features into these prompts. The resultant context vector, derived from the fusion of the text prompt template and the image feature conditional token, generates a dynamic conditional prompt for each input sample. By utilizing a contrastive language–image pre-training model, our approach effectively synchronizes and strengthens the training interactions between image and text features, resulting in an improvement to the precision of key-point localization and overall animal pose estimation accuracy. The experimental results show that language–image contrastive learning based on dynamic conditional prompts enhances the average accuracy of animal pose estimation on the AP-10K and Animal Pose datasets. Full article

Landscapes have been shaped and reshaped by humans to meet the changing needs of shifting subsistence strategies and demographic patterns. In the Mediterranean region, a widespread subsistence strategy that has left a major imprint is pastoralism, often tied with transhumance. Pastoralism and the associated tensions between pastoralists and settled agriculturalists have political and legal dimensions which are sometimes overlooked in mainstream accounts of national “patrimony”. The rapid transformations of subsistence strategies witnessed in the twentieth century have changed pastoral landscapes in diverse ways. This paper focusses on the central Mediterranean archipelago of Malta to explore how the values and management of such landscapes require holistic assessment, taking into account the intangible practices and embedded legal rights and obligations that maintained these systems. While in Malta pastoralism has practically disappeared, its physical imprint persists in the form of a network of droveways, which was once a carefully regulated form of commons. Burgeoning demographic growth is erasing large tracts of the historic environment. Against this backdrop of contestation, this paper draws on interdisciplinary approaches to interrogate the shifting legal and historical narratives through which pastoral landscapes have been managed, in the process revealing how dominant epistemological and legal frameworks are also implicated in the erasure of these landscapes. Full article

Screening for osteoporosis is crucial for early detection and prevention, yet it faces challenges due to the low accuracy of calcaneal quantitative ultrasound (QUS) and limited access to dual-energy X-ray absorptiometry (DXA) scans. Recent advances in AI offer a promising solution through opportunistic screening using existing medical images. This study aims to utilize deep learning techniques to develop a model that analyzes chest X-ray (CXR) images for osteoporosis screening. This study included the AI model development stage and the clinical validation stage. In the AI model development stage, the combined dataset of 5122 paired CXR images and DXA reports from the patients aged 20 to 98 years at a medical center was collected. The images were enhanced and filtered for hardware retention such as pedicle screws, bone cement, artificial intervertebral discs or severe deformity in target level of T12 and L1. The dataset was then separated into training, validating, and testing datasets for model training and performance validation. In the clinical validation stage, we collected 440 paired CXR images and DXA reports from both the TCVGH and Joy Clinic, including 304 pared data from TCVGH and 136 paired data from Joy Clinic. The pre-clinical test yielded an area under the curve (AUC) of 0.940, while the clinical validation showed an AUC of 0.946. Pearson’s correlation coefficient was 0.88. The model demonstrated an overall accuracy, sensitivity, and specificity of 89.0%, 88.7%, and 89.4%, respectively. This study proposes an AI model for opportunistic osteoporosis screening through CXR, demonstrating good performance and suggesting its potential for broad adoption in preliminary screening among high-risk populations. Full article

Oxidative stress represents a critical facet of the array of abiotic stresses affecting crop growth and yield. In this paper, we investigated the potential differences in the functions of two highly homologous Arabidopsis DSS1 proteins in terms of maintaining genome integrity and response to oxidative stress. In the context of homologous recombination (HR), it was shown that overexpressing AtDSS1(I) using a functional complementation test increases the resistance of the Δdss1 mutant of Ustilago maydis to genotoxic agents. This indicates its conserved role in DNA repair via HR. To investigate the global transcriptome changes occurring in dss1 plant mutant lines, gene expression analysis was conducted using Illumina RNA sequencing technology. Individual RNA libraries were constructed from three total RNA samples isolated from dss1(I), dss1(V), and wild-type (WT) plants under hydrogen peroxide-induced stress. RNA-Seq data analysis and real-time PCR identification revealed major changes in gene expression between mutant lines and WT, while the dss1(I) and dss1(V) mutant lines exhibited analogous transcription profiles. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed significantly enriched metabolic pathways. Notably, genes associated with HR were upregulated in dss1 mutants compared to the WT. Otherwise, genes of the metabolic pathway responsible for the synthesis of secondary metabolites were downregulated in both dss1 mutant lines. These findings highlight the importance of understanding the molecular mechanisms of plant responses to oxidative stress. Full article

Background: There is limited evidence on the association between psychological distress, academic stress, and burnout among Saudi nursing students. Clarifying such an association is crucial to understanding the factors associated with psychological distress and developing interventions to prevent it. Aim: To explore the prevalence and association of psychological distress with academic stress and burnout among Saudi nursing students. Methods: A cross-sectional design was used, and 237 students participated from a nursing college in Riyadh, Saudi Arabia. Students’ demographics; the Depression, Anxiety, and Stress Scale; the Academic Stress Inventory; and the Maslach Burnout Inventory were used for data collection. Results: Most of the participants reported no-to-mild depression, anxiety, and stress. Stress related to studying in groups, time management, emotional exhaustion, depersonalization, and personal accomplishment were the significant predictors of psychological distress, explaining 52.1% of the variance. Conclusions: This study suggest implementing tailored mental health screenings and support services for nursing students, embedding mental health professionals in the program, and using telehealth or mobile apps for remote monitoring to ensure comprehensive care for nursing students. Future research should consider these predictors while designing strategies to decrease psychological distress among students. Full article

Eco-labels promote environmentally conscious behavior through logos and accompanying information. However, research on the optimal combinations of this information is limited. This study examines the impact of the Japanese Eco Mark logo and recycled plastic input information on consumers’ willingness to pay (WTP) for mugs and pens. The survey results show that both elements positively influence WTP, though logos have a greater impact than recycled plastic information. The analysis of personal attributes revealed that females have a higher WTP than males, with no significant differences across age groups. Consistent with behavioral theories, WTP for mugs increased with environmental awareness towards the 3Rs (Reduce, Reuse, Recycle), while trends for pens were less distinct. This indicates that the effectiveness of eco-labels and recycling information varies by product, highlighting the need for further research to explore these differences. Full article

West Nile virus (WNV) is a re-emerging flavivirus, primarily circulating among avian hosts and mosquito vectors, causing periodic outbreaks in humans and horses, often leading to neuroinvasive disease and mortality. Spain has reported several outbreaks, most notably in 2020 with seventy-seven human cases and eight fatalities. WNV has been serologically detected in horses in the Community of Madrid, but to our knowledge, it has never been reported from wild birds in this region. To estimate the seroprevalence of WNV in wild birds and horses in the Community of Madrid, 159 wild birds at a wildlife rescue center and 25 privately owned equines were sampled. Serum from thirteen birds (8.2%) and one equine (4.0%) tested positive with a WNV competitive enzyme-linked immunosorbent assay (cELISA) designed for WNV antibody detection but sensitive to cross-reacting antibodies to other flaviviruses. Virus-neutralization test (VNT) confirmed WNV antibodies in four bird samples (2.5%), and antibodies to undetermined flavivirus in four additional samples. One equine sample (4.0%) tested positive for WNV by VNT, although this horse previously resided in a WN-endemic area. ELISA-positive birds included both migratory and resident species, juveniles and adults. Two seropositive juvenile birds suggest local flavivirus transmission within the Community of Madrid, while WNV seropositive adult birds may have been infected outside Madrid. The potential circulation of flaviviruses, including WNV, in birds in the Madrid Community raises concerns, although further surveillance of mosquitoes, wild birds, and horses in Madrid is necessary to establish the extent of transmission and the principal species involved. Full article

The purpose of this study is to investigate the potential of AI technology in developing a decision support system that can improve the effectiveness of wireless sensor networks (WSNs) in e-commerce, specifically in enhancing the features of consumer electronics. This research project is focused on optimizing wireless sensor networks for e-commerce consumer electronics by incorporating AI-based decision support systems. The primary objective of this study is to enhance energy efficiency and performance in online shopping platforms. Various algorithms and methodologies are proposed and assessed, including Adaptive Clustering, the Path Selection Algorithm, Fuzzy Logic-Controlled Energy Management, the Genetic Algorithm for Resource Allocation, and Deep Sleep Scheduling. These techniques improve network efficiency and reduce power consumption in e-commerce applications. The study demonstrates that integrating AI in consumer electronics can result in a remarkable 40% increase in energy efficiency. Comparative analyses conducted through simulations and real-world assessments indicate that the proposed methodology outperforms traditional techniques by 35%. This research underscores the vital role of AI in enhancing network performance and energy efficiency in e-commerce. The results suggest that implementing AI-driven strategies in wireless sensor networks for consumer electronics can significantly improve online shopping experiences. AI-based decision support systems can optimize wireless sensor networks for consumer electronics, improving energy efficiency and network performance on online shopping platforms. Full article

Extreme weather events, increased intensity of droughts and floods, and changes to growing seasons are results of climate change that impact horticulture, agriculture, and food systems. In the United States, Georgia, North Carolina, and South Carolina experience similar impacts caused by climate change such as rising sea levels and extreme heat. In these states, community gardens can be a source of local, fresh foods, especially in areas experiencing food insecurity. The goals of this study were to identify garden coordinators’ perceptions of the need for climate change adaptation, perceptions regarding the five perceived attributes of climate change adaptation, and where community garden coordinators stand in the innovation–decision process when it comes to climate change adaptation. The findings show that participants valued relative advantage and low levels of complexity when adopting and implementing climate-smart practices into their gardens. This study found that the community gardens were all implementing some form of climate-smart adaptations even if implementation was not for climate-related reasons. All participants noted that the largest barrier to adopting new practices was a lack of extra money. The findings from this study should be used to inform environmental education and communication strategies that encourage adoption of climate-smart practices. Full article

Background: Recent advancements in deep learning have significantly impacted ophthalmology, especially in glaucoma, a leading cause of irreversible blindness worldwide. In this study, we developed a reliable predictive model for glaucoma detection using deep learning models based on clinical data, social and behavior risk factor, and demographic data from 1652 participants, split evenly between 826 control subjects and 826 glaucoma patients. Methods: We extracted structural data from control and glaucoma patients’ electronic health records (EHR). Three distinct machine learning classifiers, the Random Forest and Gradient Boosting algorithms, as well as the Sequential model from the Keras library of TensorFlow, were employed to conduct predictive analyses across our dataset. Key performance metrics such as accuracy, F1 score, precision, recall, and the area under the receiver operating characteristics curve (AUC) were computed to both train and optimize these models. Results: The Random Forest model achieved an accuracy of 67.5%, with a ROC AUC of 0.67, outperforming the Gradient Boosting and Sequential models, which registered accuracies of 66.3% and 64.5%, respectively. Our results highlighted key predictive factors such as intraocular pressure, family history, and body mass index, substantiating their roles in glaucoma risk assessment. Conclusions: This study demonstrates the potential of utilizing readily available clinical, lifestyle, and demographic data from EHRs for glaucoma detection through deep learning models. While our model, using EHR data alone, has a lower accuracy compared to those incorporating imaging data, it still offers a promising avenue for early glaucoma risk assessment in primary care settings. The observed disparities in model performance and feature significance show the importance of tailoring detection strategies to individual patient characteristics, potentially leading to more effective and personalized glaucoma screening and intervention. Full article

The utilization of street view big data is increasingly being used to uncover visual characteristics and spatial perceptions of urban streets. However, there is a lack of studies that combine street view big data for perceptual evaluation in underdeveloped ethnic areas and better street quality. This study integrates deep learning methods to create a human–computer confrontational model for perception score, with a focus on the central city of Lhasa in Tibet. Pearson correlation analysis was conducted on six dimensions of perception data (beautiful, wealthy, safe, lively, boring and depressing) and visual elements. The streets in the top 20% for both visual elements and perceptual scores were identified to reveal areas with high visual element proportions and high perceptual scores. The spatial distribution characteristics and correlation between visual elements and street perceptions were thoroughly analyzed. The findings of this study reveal that the central city of Lhasa exhibited high percentages of visual elements in buildings (88.23%), vegetation (89.52%), and poles (3.14%). Out of the six perceptions examined, the highest scores were for boring (69.70) and depressing (67.76) perceptions, followed by beautiful (60.66) and wealthy (59.91) perceptions, with lively (56.68) and safe (50.64) perceptions receiving the lowest scores. Visual components like roads (−0.094), sidewalks (−0.031), fences (−0.036), terrain (−0.020), sky (−0.098), cars (−0.016), and poles (−0.075) were observed to have a significant deterring effect on the boring perception, while other visual elements showed a positive influence. This investigation seeks to provide valuable insights for the design and advancement of urban streets in marginalized ethnic localities, addressing a void in perception research of urban streets in such areas. Full article

This article aims to investigate the atmospheric corrosion of carbon steel in a marine environment abundant in hydrogen sulfide (H₂S) resulting from the decomposition of Sargassum seaweed. To accomplish this, four sites with varying degrees of impact were chosen along the coast of Martinique. The corrosion rates of steel were evaluated through mass loss measurements. After one year of exposure, the corrosion rates were notably high, particularly in atmospheres rich in Cl⁻ ions and H₂S, ranging from 107 µm to 983 µm. Complementing these findings, surface and product morphologies were characterized using scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD). These analyses revealed a significant degradation of the corrosion surface in the most affected atmospheres compared to those unaffected by Sargassum seaweed strandings. Lepidocrocite (γFeOOH) was identified as the predominant product regardless of the exposure atmosphere. However, goethite (αFeOOH) was found to be present in atmospheres most impacted by H₂S. Full article

During an epidemiological survey following a mortality event of freshwater mussels in 2018 in the Embarrass River, Wisconsin, USA, we identified a novel microsporidian parasite in the ovaries of mucket (Actinonaias ligamentina), plain pocketbook (Lampsilis cardium), and fatmucket (Lampsilis siliquoidea) (Unionidae). Histopathology showed round-to-oval microsporidian spores in the cytoplasm of oocytes in 60% (3/5) of female mucket, 100% (4/4) of female plain pocketbook, and 50% (1/2) of female fatmucket. Using transmission electron microscopy, we found that mature spores were round-to-oval and measured 4.13 ± 0.64 µm (3.14–5.31) long by 2.88 ± 0.37 µm (2.36–3.68) wide. The spores had a thin electron-dense exospore with a spiky “hairy” coat, a thick electron lucent endospore, diplokaryotic nuclei, a polar vacuole, and 27–28 polar filaments arranged in 1–3. Sequencing of the small subunit rRNA produced a 1356 bp sequence most similar to that of Pseudonosema cristatellae (92%), and phylogenetic analysis grouped it within the freshwater Neopereziida. Genetic, morphological, and ultrastructural characteristics did not closely match those of other Pseudonosema spp., and a new genus and species, Hirsutonosema embarrassi n. gen. n. sp., were designated. Additional studies could evaluate host susceptibility, distribution, seasonality, transmission, and lethal or sub-lethal effects of this parasite on freshwater mussels. Full article