Search Results (272)

Staphylococcus aureus frequently causes intramammary infections in dairy cows (bovine mastitis), which impair animal welfare, milk yield, and food safety. This study determined the prevalence and genetic diversity of S. aureus in bulk tank milk (BTM) samples from community-based Alpine dairy pastures in Tyrol, a major milk-producing region in Austria. Throughout the 2023 Alpine season (May–September), 60.3% (94/156) of BTM samples tested positive for S. aureus at least once over the course of up to four samplings. A total of 140 isolates collected from the 94 S. aureus-positive community-based Alpine dairy pastures revealed 33 distinct spa types, with t2953 (n = 33), t529 (n = 12), t267 (n = 11), and t024 (n = 10) being the most common. Selected isolates representing the different spa types were characterised by DNA microarray-based genotyping, multi-locus sequence typing (MLST), and antimicrobial susceptibility testing. Isolates with spa types associated with bovine-adapted CC8 (CC8bov/GTB) were identified as the most common subtype, being detected in BTM samples from 35.3% (55/156) of the pastures. This emphasises the high prevalence of this subtype in dairy herds across European Alpine countries. Other common bovine-associated subtypes were also detected, including CC97, CC151, and CC479. While antimicrobial resistance was rare, enterotoxin-producing genes were detected in all CC8bov-associated spa types. Overall, these findings underscore the importance of rigorous hygiene practices in dairy farming, particularly in community-based Alpine dairy pastures, where the risk of transmission is particularly high. It also emphasises the need for continued surveillance and subtyping to improve animal health, ensure food safety, and promote sustainable milk production. Full article

Objective: Lower third impacted molar extraction, despite being a routinary procedure for oral and maxillo-facial surgeons, may often result in a significantly negative impact in patient’s post-operatory quality of life. Among others, treatments based on oxygen-enriched oils have been shown to provide valuable therapeutic benefits in promoting wound healing, and therefore improving the immediate post-operatory symptomatology. The aim of this triple-blinded randomized controlled study is to supplement the existing evidence in the scientific literature by assessing the effectiveness of NovoX^®-Drop (Moss S.p.A., Lesa, Novara), a specific type of oxygen enriched oil-based device in reducing pain and inflammatory stimulus of post-surgical wounds following the extraction of lower third impacted molars. Materials and methods: Seventy-one patients undergoing surgical extraction of a single lower third impacted molar were randomly assigned to receive either NovoX^®-Drop (Group A) or a glycerin-based gel (Group B). Additionally, both patient groups followed the same standard therapy with amoxicillin-clavulanic acid and ibuprofen. Data were collected preoperative (T0) and after three (T3) and seven (T7) days postoperative in order to assess the following outcomes: mean visual analogue scale (VAS) score during the seven days protocol treatment, total duration of nonsteroidal anti-inflammatory drug (NSAID) usage, trismus (maximum mouth opening) and facial oedema. Results: Group A (treatment group) reported significatively lower pain levels at T7 compared to group B (average VAS value during the week: Group A: 3.57 ± 0.39 cm; Group B: 4.47 ± 0.40 cm; p-value = 0.0014) despite a significatively shorter period of NSAID usage (average NSAID usage duration: Group A: 2.43 ± 0.38 days; Group B: 3.38 ± 0.44 days; p-value = 0.00001). Therefore, trismus seems to be better controlled in group A, although the difference between the groups did not reach the threshold for statistical significance. Conclusions: The results of this study suggest that application of NovoX^®-Drop is capable of significantly reducing the post-operatory pain as well as NSAID usage, representing a promising and effective option for third impacted molar extraction surgery management. Full article

T-2 toxin, a type A trichothecene mycotoxin produced by Fusarium species, is widely present in cereals and their processed products, posing a significant contaminant in food safety. To address the food safety challenges caused by this toxin, we established a dual signal enhancement by magnetic separation and split aptamer for ultrasensitive T-2 toxin detection. In this method, the introduction of magnetic graphene oxide (MGO) enhanced signal and increased sensitivity by reducing background interference. The shortened split aptamer reduces non-specific binding to MGO via decreased steric hindrance, thereby facilitating rapid target-induced dissociation and signal generation. A FAM fluorophore-labeled split aptamer probe FAM-SpA1-1 was quenched by MGO. While the fluorescence intensity remained nearly unchanged when the unlabeled split aptamer probe SpA1-2 was introduced alone, a significant fluorescence recovery was observed upon simultaneous addition of SpA1-2 and T-2 toxin. This recovery resulted from the cooperative binding of SpA1-1 and SpA1-2 to T-2 toxin, which distanced the FAM-SpA1-1 probe from MGO. Therefore, the proposed biosensor demonstrated excellent stability, reproducibility, and specificity, with a linear response range of 10–500 pM and a limit of detection (LOD) of 0.83 pM. Satisfactory recovery rates were achieved in spiked wheat (86.0–114.2%) and beer (112.0–129.6%) samples, highlighting the biosensor’s potential for practical applications in real-sample detection. This study establishes the T-2 toxin split aptamer and demonstrates a novel dual-signal enhancement paradigm that pushes the sensitivity frontier of aptamer-based mycotoxin sensors. Full article

Background/Objectives: Severe COVID-19 pneumonia damages alveolar type II cells and disrupts surfactant homeostasis, contributing to acute respiratory distress syndrome (ARDS). Surfactant proteins (SP-A, SP-B, SP-C, SP-D) are critical for reducing alveolar surface tension and for innate immune defense. We aimed to evaluate whether surfactant protein gene expression varies with the severity of COVID-19. Methods: Peripheral blood was collected from 122 adults with confirmed COVID-19, categorized as asymptomatic (no symptoms), mild (requiring hospitalization), or severe (requiring ICU admission). We quantified mRNA expression of surfactant protein genes (SFTPA1, SFTPA2, SFTPB, SFTPC, SFTPD) in blood cells using RT-qPCR. Relative expression was normalized to GAPDH and compared among the groups using the 2^−ΔΔCt method. Outliers (Ct values > 3 SD from the mean) were excluded before analysis. Results: Distinct surfactant gene expression patterns were markedly associated with disease severity. Transcripts of SFTPB and SFTPC decreased with increasing severity of the disease. Notably, SFTPC expression was ~49-fold higher in mild cases compared to asymptomatic COVID-19-positive patients (p < 0.0001), but then decreased by ~54-fold in severe cases relative to mild (p < 0.0001), returning to near-baseline levels. In contrast, SFTPA2 and SFTPD were dramatically upregulated in severe cases. SFTPA2 was ~50-fold higher in severe versus mild cases (p < 0.0001), and SFTPD was ~4346-fold higher in severe versus asymptomatic cases (p < 0.0001; ~9.6-fold higher than in mild). SFTPA1 showed only a modest ~1.4-fold decrease in severe cases (vs. mild). All noted differences remained statistically significant after outlier exclusion. Conclusions: COVID-19 severity is correlated with profound changes in surfactant gene expression in blood. Critically ill patients exhibit loss of key surfactant components (SP-B and SP-C transcripts) alongside an excessive SP-D response. These preliminary findings suggest an imbalance that may contribute to lung injury in severe disease. However, further validation is needed to establish surfactant proteins, such as SP-D, as biomarkers of COVID-19 severity. Full article

Staphylococcus aureus (S. aureus) is a major pathogen responsible for mastitis in dairy cows and can contaminate raw milk, thereby posing significant health risks to consumers. The emergence of methicillin-resistant S. aureus (MRSA) has further heightened public health concerns due to its antibiotic resistance and infectious potential. In this study, we examined the prevalence, virulence genes, antimicrobial resistance, spa types, and biofilm formation of S. aureus isolates from dairy farms in Guangxi Province, China. Among 242 randomly selected samples, 37 S. aureus strains were identified (15.3% infection rate), including 67.5% MRSA. Antibiotic resistance was observed in 78.4% of isolates, with 35.1% exhibiting multidrug resistance (MDR). Enterotoxin gene analysis showed sea as the most common (67.6%), followed by ser (54.1%) and seh (51.4%), whereas seb and selj were absent. All isolates formed biofilms in vitro, with 64.8% showing strong biofilm-forming ability. Staphylococcal protein A (spa) typing classified the 37 S. aureus strains into 11 spa types, with t030 being the most prevalent (43.2%). These findings indicate that S. aureus is moderately prevalent in raw milk, often carrying multiple virulence genes, forming robust biofilms, and showing antimicrobial resistance. The MRSA that is “latent” in raw milk reminds us of the need for monitoring at the farm level. Full article

Staphylococcus aureus is an important cause of food intoxication, which has the potential to induce diverse infections, toxinoses and life-threatening diseases among humans and animals. This study investigated the prevalence, antimicrobial resistance, and genetic diversity of S. aureus and methicillin-resistant S. aureus (MRSA) in retail raw meat from Shandong (March 2021–October 2022). The distribution of virulence genes, antimicrobial susceptibility, and genetic diversity of these isolates were analyzed. From a total of 442 samples, 87 (19.7%) S. aureus and 11 (2.5%) MRSA were isolated. According to the antimicrobial susceptibility testing, it was found that all the S. aureus isolates were resistant to at least one antimicrobial. Most isolates (95.9%) were resistant to penicillin, with high resistance to ampicillin (82.7%) and multidrug resistance in 76.5% of cases. One isolate could simultaneously resist eleven antimicrobials (ERY-CLI-GEN-SMZ-FFC-PEN-PRL-AMC-CIP-TET-AMP). In contrast, all the isolates showed sensitivity to vancomycin. The most prevalent virulence gene was sed, accounting for 10.2%, followed by sec (8.2%). Regarding genetic polymorphism, these isolates were divided into 21 different sequence types (STs) using multilocus sequence typing (MLST) and 33 staphylococcal protein A (spa) types using spaTyper 1.0 tool. The most prevalent sequence types were ST398 (22.4%), followed by ST7 (20.4%), while ST59, ST1, ST188, ST9, ST398, and ST7 were observed in MRSA isolates. The most prevalent spa types were t034 (15.3%), followed by t899 (10.2%), while t441, t127, t184, t899, t034, and t091 were observed in MRSA isolates. In conclusion, our study highlights the high prevalence of S. aureus and MRSA in different retail raw meats in Shandong. This poses a potential threat to food safety and underscores the need for enhanced surveillance and stricter antibiotic control measures. Full article

Wear resistance is of paramount importance for the long-term success of dental materials, especially when they are used for extensive indirect restorations in full-mouth rehabilitations. The present in vitro study aimed to evaluate the two-body wear resistance of a new and recently introduced CAD/CAM resin composite disc (Ena Cad, Micerium S.pA.), to compare it to the wear resistance of other two well-known and already marketed CAD/CAM composites (Brilliant Crios, Coltene/Whaledent AG; Grandio disc, Voco Gmbh) and to a conventional type 3 gold alloy (Aurocast 8, Nobil-Metal). Ten cylindrical specimens (diameter 8 mm, height 6 mm) were manufactured with each material and subjected to a two-body wear test in a dual-axis chewing simulator, performing 120,000 chewing cycles opposing antagonists (2-mm-diameter round tip) made out of the same corresponding materials. The total vertical wear (mm) and the total volumetric loss (mm³) for each sample/antagonist pair were calculated. Representative scanning electron microscope images were also taken. Data were statistically analyzed using one-way analysis of variance tests. No statistically significant differences were recorded among the wear properties of the restorative materials under investigation. The Ena Cad disc showed a wear resistance comparable to the type 3 gold alloy and to the already marketed Brilliant Crios and Grandio disc. Full article

Staphylococcus aureus (S. aureus), especially methicillin-resistant S. aureus (MRSA), remains a major public health concern. This study reports the antimicrobial resistance profiles and molecular characteristics of 31 S. aureus isolated during 2017–2018 from inpatient and outpatient clinical specimens from Queen Sirikit Naval Hospital (QSH) in Chonburi province, Thailand. All isolates were tested for antimicrobial susceptibility. Staphylococcal cassette chromosome mec (SCCmec) typing, Panton–Valentine leukocidin (pvl) toxin, pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and staphylococcal protein A (spa) typing were performed. Twenty-seven isolates were confirmed to be MRSA and exhibited resistance to up to seven antibiotics classes. The main MLST type was SCCmec type II (51.9%) and ST764 (55.6%). Five spa types were identified with t045 (55.6%) as the major type. All 31 S. aureus isolates were grouped into seven types using PFGE with the SCCmecII-ST764-t045 clone being the most prevalent. Overall, our findings reveal that the S. aureus isolates in this study differ from previous reports in Thailand, indicating a potential shift in local strains, highlighting the need for ongoing molecular surveillance of multidrug resistance patterns of MRSA in Southeast Asia. Full article

Broccoli is a highly nutritious vegetable that is favored worldwide. Assessing and predicting the shelf life of broccoli holds considerable importance for effective resource optimization and management. The physicochemical parameters and spectral characteristics of broccoli are important indicators partially reflecting its shelf life. However, few studies have used spectral image information to predict and evaluate the shelf life of broccoli. In this study, multispectral imaging combined with multi-feature data fusion was used to predict and evaluate the shelf life of broccoli. Spectral data and textural features were extracted from multispectral images of broccoli and fused with the physicochemical parameters for analysis. Savitzky–Golay (SG) convolution smoothing and standard normal variate (SNV) and normalization (Norm) preprocessing methods were employed to preprocess the original spectral data and textural features, while a successive projection algorithm (SPA) was used to extract relevant feature bands. The physicochemical parameters for broccoli shelf life were predicted using three methods: support vector regression (SVR), random forest classification (RF), and 2D convolutional neural network (2D-CNN) models. Broccoli shelf life prediction models were evaluated using three classification methods: RF, 1D-CNN, and 2D-CNN. The results demonstrate that, among the models used for predicting and evaluating the shelf life of broccoli, the SPA+SG+RF classification model employing fused data Type C achieves the highest accuracy. Specifically, this method achieves accuracies of 88.98% and 88.64% for the training and validation sets, respectively. Multi-feature data fusion of spectral image information and physical and chemical parameters were combined with different machine learning methods to predict and evaluate the shelf life of broccoli. Full article

(1) Background: Soybean storage quality is crucial for subsequent processing and consumption, making it essential to explore an objective, rapid, and non-destructive technology for assessing its quality. (2) Methods: crude fatty acid value is an important indicator for evaluating the storage quality of soybeans. In this study, three types of soybeans were subjected to accelerated aging to analyze trends in crude fatty acid values. The study focused on acquiring raw spectral information using hyperspectral imaging technology, preprocessing by the derivative method (1ST, 2ND), multiplicative scatter correction (MSC), and standard normal variate (SNV). The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). Partial least squares regression (PLSR), support vector machine (SVM), and extreme learning machine (ELM) models were developed to predict crude fatty acid values of soybeans. The optimal model was used to visualize the dynamic distribution of these values. (3) Results: the crude fatty acid values exhibited a positive correlation with storage time, functioning as a direct indicator of soybean quality. The 1ST-VISSA-SVM model was the optimal predictive model for crude fatty acid values, achieving a coefficient of determination (R²) of 0.9888 and a root mean square error (RMSE) of 0.1857 and enabling the visualization of related chemical information. (4) Conclusions: it has been confirmed that hyperspectral imaging technology possesses the capability for the non-destructive and rapid detection of soybean storage quality. Full article

A crucial factor in shaping the character of a spa and wellness hotel’s character is the design and functionality of the recreational area. This element is linked to other areas in the hotel, such as dining, accommodation, and conference facilities. The spatial layout of the spa and wellness zone, along with its location, programming, size, and style, greatly affects the overall operation of the establishment. Few European publications analyze the architectural design of contemporary spa and wellness hotels in the specialist literature. These publications are often concerned with general programming-related assumptions rather than specific functional and spatial research. The aim of this research is to create a well-organized taxonomy of spa and wellness zones in the region. The set of typologies presented was developed based on spatial and functional analyses, as well as descriptions of European objects found in the literature, and the author’s research. This research results in the discovery of six typologies and a total of seventeen independent types of spa and wellness zones found in hotels. Full article

Background: Staphylococcus aureus is one of the most prevalent pathogens causing mastitis in dairy animals and represents a serious issue of public health concern due to its resistance against multiple antimicrobials. Objectives: This study assessed 101 S. aureus isolates obtained from quarter milk of animals with subclinical mastitis in the Ragusa area (Sicily, Italy). Methods: Antibiotic resistance against nine antibiotics was evaluated using the Kirby–Bauer method, and the Minimum Inhibitory Concentration (MIC) values were measured for oxacillin (OXA) and vancomycin (VA). Additionally, the isolates were genetically characterized through multiplex PCR to identify the presence of spa, mecA, mecC, pvl, vanA, vanB, and vanC genes, along with pulsed-field gel electrophoresis analysis and multi-locus sequence typing (MLST). Results: The highest rates of antibiotic resistance were found against gentamicin (47.5%) and erythromycin (29.7%), with 86.1% of strains exhibiting resistance to at least two antimicrobials and 33.7% showing resistance to three antimicrobial classes. Furthermore, the results indicated that the presence of antibiotic resistance genes was not correlated with phenotypic resistance, and a phylogenetic analysis revealed varying phenotypic resistance profiles even within the same PFGE cluster. Lastly, alongside a new allelic profile ST 9471, MLST analysis identified five additional STs clustered into three CCs, with CC5 originating from human ancestral strains through human-to-animal host transfers, making it the dominant group. Conclusions: This study provided valuable insights into regional trends, allowing for the identification of significant antibiotic-resistant patterns and offering an understanding of bacterial dynamics in these environments, underscoring the importance of routine resistance surveillance in dairy farms. Full article

Marine Protected Areas (MPAs) require efficient monitoring tools to assess habitats and biodiversity, particularly in remote or understudied regions. This study demonstrates the utility of the towed video-diver technique combined with high-resolution video for rapidly surveying benthic habitats and associated taxa. Applied in Arredondo, a shallow bay within an MPA in Atlantic Patagonia, the method covered 14,000 m² through eight transects, utilizing just 180 min of dive time and ~300 min of video analysis. Substrate types and their associated taxa were classified using the CATAMI framework, yielding a list of 28 taxa and density estimates of mobile organisms. Additionally, the percentage cover of Gracilaria sp.—a commercially valuable macroalga historically overexploited in the region—was estimated for the bay. The invasive crab Carcinus maenas was found across all substrate types on the bay, underscoring its ecological tolerance and the need for ongoing monitoring. This cost-effective, rapid methodology is highly effective for detecting and describing areas of ecological or conservation interest, providing critical baseline data for targeted, detailed studies. Its simplicity and efficiency make it ideal for initial surveys in remote regions, supporting the conservation and management of MPAs. Full article

Antibiotic-resistant Staphylococcus aureus (S. aureus) in retail meat poses a public health threat requiring continuous surveillance. This study investigated the frequency of isolation, toxin genes, and antibiotic resistance profile of S. aureus recovered from retail poultry meat samples and presented results beneficial to public health interventions. Of 200 samples collected, 16% (32/200) tested positive for S. aureus, and these were recovered from thigh 37.5% (12/32), wing 34.4% (11/32), gizzard (15.6% (5/32), and liver 12.5% (4/32) samples. Findings of spa typing analysis revealed that 68.8% (22/32), 18.8% (6/32), 9.4% (3/32), and 3.0% (1/32) of the isolates belonged to the spa types t267, t160, t548, and t008, respectively. For antibiotic susceptibility testing, 12.5% (4/32) of the isolates were resistant to only penicillin, but one isolate (1/32; 3%) showed resistance to the antibiotics penicillin, erythromycin, ampicillin, and oxacillin. PCR analysis revealed that 9.4% (3/32) of the isolates carried the mecA gene associated with methicillin-resistant Staphylococcus aureus (MRSA) isolates. One MRSA isolate was identified as a t008 spa type, and harbored a 26,974 bp-sized plasmid, which was the source of its resistance to penicillin, ampicillin, erythromycin, and oxacillin. The staphylococcal enterotoxin (SE) genes seg, sei, sek, seb, selm, and seln were also identified among the isolates, and mostly the antimicrobial and enterotoxin genes were carried on plasmids of the isolates. This study raises awareness on the continuous circulation of pathogenic microbes like S. aureus in retail poultry meat. Full article

Soil salinization affects agricultural productivity and ecosystem health in Xinjiang, especially in arid areas. The region’s complex topography and limited agricultural data emphasize the pressing need for effective, large-scale monitoring technologies. Therefore, 1044 soil samples were collected from arid farmland in northern Xinjiang, and the potential effectiveness of soil salinity monitoring was explored by combining environmental variables with Landsat 8 and Sentinel-2. The study applied four types of feature selection algorithms: Random Forest (RF), Competitive Adaptive Reweighted Sampling (CARS), Uninformative Variable Elimination (UVE), and Successive Projections Algorithm (SPA). These variables are then integrated into various machine learning models—such as Ensemble Tree (ETree), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and LightBoost—as well as deep learning models, including Convolutional Neural Networks (CNN), Residual Networks (ResNet), Multilayer Perceptrons (MLP), and Kolmogorov–Arnold Networks (KAN), for modeling. The results suggest that fertilizer use plays a critical role in soil salinization processes. Notably, the interpretable model KAN achieved an accuracy of 0.75 in correctly classifying the degree of soil salinity. This study highlights the potential of integrating multi-source remote sensing data with deep learning technologies, offering a pathway to large-scale soil salinity monitoring, and thereby providing valuable support for soil management. Full article