Evaluation of probiotic efficacy of indigenous yeast strain, Saccharomyces cerevisiae Y-89 isolated from a traditional fermented beverage of West Bengal, India having protective effect against DSS-induced colitis in experimental mice.

Increasing awareness regarding health promotion and disease prevention has driven inclusion of fermented foods and beverages in the daily diet. These are the enormous sources of beneficial microbes, probiotics. This study aims to isolate yeast strains having probiotic potential and effectivity against colitis. Initially, ninety-two yeast strains were isolated from Haria, an ethnic fermented beverage of West Bengal, India. Primary screening was done by their acid (pH 4) and bile salt (0.3%) tolerance ability. Four potent isolates were selected and found effective against Entamoeba histolytica, as this human pathogen is responsible to cause colitis. They were identified as Saccharomyces cerevisiae. They showed luxurious growth even at 37 oC, tolerance up to 5% of NaCl, resistance to gastric juice and high bile salt (2.0%) and oro-gastrointestinal transit tolerance. They exhibited good auto-aggregation and co-aggregation ability and strong hydrophobicity. Finally, heat map and principal component analysis revealed that strain Y-89 was the best candidate. It was further characterised and found to have significant protective effects against DSS-induced colitis in experimental mice model. It includes improvement in colon length, body weight and organ indices; reduction in disease activity index; reduction in cholesterol, LDL, SGPT, SGOT, urea and creatinine levels; improvement in HDL, ALP, total protein and albumin levels; decrease in coliform count and restoration of tissue damage. This study demonstrates that the S. cerevisiae strain Y-89 possesses remarkable probiotic traits and can be used as a potential bio-therapeutic candidate for the prevention of colitis.

A nomogram and heat map based on LASSO-Cox regression for predicting the risk of early-stage severe fever with thrombocytopenia syndrome patients developing into critical illness at 7-day and 14-day.

Severe fever with thrombocytopenia syndrome (SFTS) represents an emerging infectious disease characterized by a substantial mortality risk. Early identification of patients is crucial for effective risk assessment and timely interventions. In the present study, least absolute shrinkage and selection operator (LASSO)-Cox regression analysis was conducted to identify key risk factors associated with progression to critical illness at 7-day and 14-day. A nomogram was constructed and subsequently assessed for its predictive accuracy through evaluation and validation processes. The risk stratification of patients was performed using X-tile software. The performance of this risk stratification system was assessed using the Kaplan-Meier method. Additionally, a heat map was generated to visualize the results of these analyses. A total of 262 SFTS patients were included in this study, and four predictive factors were included in the nomogram, namely viral copies, aspartate aminotransferase (AST) level, C-reactive protein (CRP), and neurological symptoms. The AUCs for 7-day and 14-day were 0.802 [95% confidence interval (CI): 0.707-0.897] and 0.859 (95% CI: 0.794-0.925), respectively. The nomogram demonstrated good discrimination among low, moderate, and high-risk groups. The heat map effectively illustrated the relationships between risk groups and predictive factors, providing valuable insights with high predictive and practical significance.

Performance of machine learning algorithms for lung cancer prediction: a comparative approach.

Due to the excessive growth of PM 2.5 in aerosol, the cases of lung cancer are increasing rapidly and are most severe among other types as the highest mortality rate. In most of the cases, lung cancer is detected with least symptoms at its later stage. Hence, clinical records may play a vital role to diagnose this disease at the correct stage for suitable medication to cure it. To detect lung cancer an accurate prediction method is needed which is significantly reliable. In the digital clinical record era with advancement in computing algorithms including machine learning techniques opens an opportunity to ease the process. Various machine learning algorithms may be applied over realistic clinical data but the predictive power is yet to be comprehended for accurate results. This paper envisages to compare twelve potential machine learning algorithms over clinical data with eleven symptoms of lung cancer along with two major habits of patients to predict a positive case accurately. The result has been found based on classification and heat map correlation. K-Nearest Neighbor Model and Bernoulli Naive Bayes Model are found most significant methods for early lung cancer prediction.

Beyond mutations: Accounting for quantitative changes in the analysis of protein evolution.

Molecular phylogenetic research has relied on the analysis of the coding sequences by genes or of the amino acid sequences by the encoded proteins. Enumerating the numbers of mismatches, being indicators of mutation, has been central to pertinent algorithms. Specific amino acids possess quantifiable characteristics that enable the conversion from "words" (strings of letters denoting amino acids or bases) to "waves" (strings of quantitative values representing the physico-chemical properties) or to matrices (coordinates representing the positions in a comprehensive property space). The application of such numerical representations to evolutionary analysis takes into account not only the occurrence of mutations but also their properties as influences that drive speciation, because selective pressures favor certain mutations over others, and this predilection is represented in the characteristics of the incorporated amino acids (it is not born out solely by the mismatches). Besides being more discriminating sources for tree-generating algorithms than match/mismatch, the number strings can be examined for overall similarity with average mutual information, autocorrelation, and fractal dimension. Bivariate wavelet analysis aids in distinguishing hypermutable versus conserved domains of the protein. The matrix depiction is readily subjected to comparisons of distances, and it allows the generation of heat maps or graphs. This analysis preserves the accepted taxa order where tree construction with standard approaches yields conflicting results (for the protein S100A6). It also aids hypothesis generation about the origin of mitochondrial proteins. These analytical algorithms have been automated in R and are applicable to various processes that are describable in matrix format.

Quantitative evaluation of lower limb varicose veins using photoacoustic imaging.

PURPOSE: Varicose veins in the lower extremities are dilated subcutaneous varicose veins with a diameter of ≥ 3 mm, caused by increased venous pressure resulting from backflow of blood due to venous valve insufficiency (Gloviczki in Handbook of venous disorders: guidelines of the American venous forum, Hodder Arnold, London, 2009). When diagnosing varicose veins, the shape and thickness of the blood vessels should be accurately visualized in three dimensions. In this study, we investigated a new method for numerical evaluation of vascular morphology related to varicose veins in the lower extremities, using a photoacoustic imaging (PAI) system, which can acquire high-resolution and three-dimensional images noninvasively. METHODS: Nine patients with varicose veins participated in the study, and their images were captured using an optical camera and PAI system. We visualized the vascular structure, created a blood presence density (BPD) heat map, and examined the correlation between BPD and location of varicose veins. RESULTS: The obtained photoacoustic (PA) images demonstrated the ability of this method to visualize vessels ranging from as small as 0.2 mm in diameter to large, dilated vessels in three dimensions. Furthermore, the study revealed a correlation between the high-density part of the BPD heat map generated from the PAI images and the presence of varicose veins. CONCLUSION: PAI is a promising technique for noninvasive and accurate diagnosis of varicose veins in the lower extremities. By providing valuable information on the morphology and hemodynamics of the varicose veins, PAI may facilitate their early detection and treatment.

Volatile oil constituents, antioxidant and antibacterial activities of Lonicera caprifolium L. in different areas of Iran.

The genus of Lonicera is the largest genus of Caprifoliaceae family. This study revealed the composition, antioxidant, and antibacterial actions of essential oils of Lonicera caprifolium L. in different areas of Iran; Qom, Mashhad, Shiraz. Gas chromatography-mass spectrometry examination was applied to recognise the oil conformation. The essential oils of Qom included a high number of monoterpenes, with linalool as the significant constituent. In the essential oil of Mashhad, the main elements were methyl linoleate. The essential oil of Shiraz displayed a similar profile, including a large quantity of fatty acid, with methyl palmitate as the main component. The antioxidant activity was assessed via the DPPH exam, and the antimicrobial action was verified using the broth microdilution procedure. The essential oils of Qom revealed the maximum antimicrobial and antioxidant actions between the three regions, ascribed to its high concentration of monoterpenes and phenolic composites. Moreover, principal component analysis (PCA) and heat map successfully revealed the variation and correlation between metabolites of the three oils. These conclusions highlight the potential of L. caprifolium as natural foundations of antimicrobial and antioxidant representatives, with investigation required to reveal their therapeutic requests.

BarlowTwins-CXR: enhancing chest X-ray abnormality localization in heterogeneous data with cross-domain self-supervised learning.

BACKGROUND: Chest X-ray imaging based abnormality localization, essential in diagnosing various diseases, faces significant clinical challenges due to complex interpretations and the growing workload of radiologists. While recent advances in deep learning offer promising solutions, there is still a critical issue of domain inconsistency in cross-domain transfer learning, which hampers the efficiency and accuracy of diagnostic processes. This study aims to address the domain inconsistency problem and improve autonomic abnormality localization performance of heterogeneous chest X-ray image analysis, particularly in detecting abnormalities, by developing a self-supervised learning strategy called "BarlwoTwins-CXR". METHODS: We utilized two publicly available datasets: the NIH Chest X-ray Dataset and the VinDr-CXR. The BarlowTwins-CXR approach was conducted in a two-stage training process. Initially, self-supervised pre-training was performed using an adjusted Barlow Twins algorithm on the NIH dataset with a Resnet50 backbone pre-trained on ImageNet. This was followed by supervised fine-tuning on the VinDr-CXR dataset using Faster R-CNN with Feature Pyramid Network (FPN). The study employed mean Average Precision (mAP) at an Intersection over Union (IoU) of 50% and Area Under the Curve (AUC) for performance evaluation. RESULTS: Our experiments showed a significant improvement in model performance with BarlowTwins-CXR. The approach achieved a 3% increase in mAP50 accuracy compared to traditional ImageNet pre-trained models. In addition, the Ablation CAM method revealed enhanced precision in localizing chest abnormalities. The study involved 112,120 images from the NIH dataset and 18,000 images from the VinDr-CXR dataset, indicating robust training and testing samples. CONCLUSION: BarlowTwins-CXR significantly enhances the efficiency and accuracy of chest X-ray image-based abnormality localization, outperforming traditional transfer learning methods and effectively overcoming domain inconsistency in cross-domain scenarios. Our experiment results demonstrate the potential of using self-supervised learning to improve the generalizability of models in medical settings with limited amounts of heterogeneous data. This approach can be instrumental in aiding radiologists, particularly in high-workload environments, offering a promising direction for future AI-driven healthcare solutions.

Quadrilateral plate classification program of acetabular fractures based on three-column classification: a three-dimensional fracture mapping study.

BACKGROUND: A new classification system for acetabular fractures has been proposed in recent years, which is called the 3-column classification. However, this system does not provide information regarding quadrilateral plate fractures. To address this issue, we utilized three-dimensional (3D) fracture line mapping and heat map to analyze the link between the 3-column classification and quadrilateral plate fractures. METHODS: We collected CT scan data from 177 patients who had been diagnosed with acetabular fractures. Additionally, we utilized a CT scan of a healthy adult to generate a standard acetabular model. We utilized the collected CT data of the fracture to create a 3D model and subsequently reduced it. We then matched each acetabular fracture model with the standard acetabular model and mapped all of the fracture lines to the standard model. 3D fracture lines and heat maps were created by overlapping all fracture lines. Fracture characteristics were then summarized using these maps. RESULTS: This study analyzed a total of 221 acetabular fractures. The most frequently observed fracture type, based on the three-column classification, was A1.2, which corresponds to fractures of the anterior column. In contrast, the least common type of fracture was A4, which represents fractures of the central wall. It was noted that quadrilateral plate fractures were frequently observed in fractures classified as type B and C according to the three-column classification. CONCLUSIONS: Among the three-column classification, the QLP fractures are commonly observed in type B and C. It is important to carefully identify these fractures during the diagnostic process. Therefore, based on the three-column classification, we have amalgamated quadrilateral plate fractures and formulated a classification program for acetabular fractures.

Separation, identification, and fingerprinting of antioxidant components in persimmon (Diospyros kaki) leaves by offline two-dimensional liquid chromatography with electrochemical detection and tandem mass spectrometry.

In this work, the antioxidant components in persimmon (Diospyros kaki) leaves were separated by offline two-dimensional liquid chromatography-electrochemical detection (LC×LC-ECD) and identified by LC-tandem mass spectrometry (LC-MS/MS). A total of 33 antioxidants, mainly proanthocyanidins, and glycosides of kaempferol and quercetin, were identified. The antioxidant assays demonstrated that the fractions collected from the first-dimension LC (1D-LC) possessed considerable radical scavenging capabilities, with correlation coefficients of peak area versus radical scavenging capability of 1,1-diphenyl-2-picrylhydrazyl and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) being 0.9335 and 0.9116, respectively. The fingerprinting showed that 37 peaks were present in all samples. The major antioxidant components of persimmon leaves were the glycosides of kaempferol and quercetin. Finally, fourteen antioxidants were quantitatively assessed. Offline LC×LC provided high peak capacity and separation; ECD enabled specific screening and detection of antioxidant components; and MS/MS provided excellent identification capability. In this study, the combination of the three approaches was utilized to screen for antioxidant components in persimmon leaves, with satisfactory findings. In conclusion, this technique is an effective means for rapid analysis of antioxidant components and quality control of medicinal plants, achieving rapid separation of congeners and facilitating more accurate qualitative and quantitative analyses.

Geometric framework for statistical analysis of eye tracking heat maps, with application to a tobacco waterpipe study.

Health warning labels have been found to increase awareness of the harmful effects of tobacco products. An eye tracking study was conducted to determine the optimal placement and type of a health warning label on tobacco waterpipes. Participants viewed images that contained one of (1) four waterpipes, (2) three different types of warning labels, (3) placed in three locations. Typically, statistical analysis of eye tracking data is conducted based on summary statistics such as total dwell time, duration score, and number of visits to an area of interest. However, these summary statistics fail to capture the complete variability in a participant's eye movement. Instead, we propose to estimate heat maps defined on the entire image domain using the raw two-dimensional coordinates of eye movement via kernel density estimation. For statistical analysis of heat maps, we adopt the Fisher-Rao Riemannian geometric framework, which enables computationally efficient comparisons of heat maps, statistical summarization and exploration of variability in a sample of heat maps, and metric-based hierarchical clustering. We apply this framework to eye tracking data from the tobacco waterpipe study and comment on the results in the context of the optimal placement and type of health warning labels on tobacco waterpipes.

Volatile N-nitrosamines in processed meat products: An approach for monitoring dietary exposure, assessing human risk, and evaluating variable correlations by principal component analysis and heat map.

Several epidemiological studies have reported a positive association between the consumption of processed meats containing N-nitrosamines (NAs) and the incidence of hepatocellular and colon cancer. The health risk assessment in this investigation was based on the concentration of six volatile N-nitrosamines (VNAs) (N-nitrosodimethylamine, N-nitrosodiethylamine, N-nitrosomethylethylamine, N-nitrosopiperidine, N-nitrosodibutylamine, and N-nitrosodi-n-propylamine) found in processed meat products (sausage and kielbasa) in the Iranian market. Direct supported liquid membrane two-phase hollow fiber electromembrane extraction coupled to gas chromatography/mass spectrometry was used to analyse six VNAs. The mean concentration of the six VNAs in sausages and kielbasa was 38.677 ± 27.56 and 48.383 ± 35.76 µg/kg, respectively. The 95th percentile for the chronic daily intake of total VNAs for children (3-14 years) and adults (15-70 years) were calculated to be 5.06 × 10-4 and 1.09 × 10-4 mg/kg bw/day, respectively. The cancer risk assessment showed that the risk associated with NDEA was the highest among the other VNAs studied in Iranian processed meat, with a 95th percentile for the child and adult groups. Based on an incremental lifetime cancer risk (ILCR) value of ≤10-4 for the carcinogenic effects of exposure to a total of six VNAs, it indicates low concern for all age groups.

Gender-Based Heat Map Images of Campus Walking Settings: A Reflection of Lived Experience.

Fear of crime can influence our view of and experience with the world around us. This can be problematic for individuals seeking physical activity, including from walk commuting. Prior work shows fear is especially evident among women, who report fear of rape and sexual abuse by men as a primary concern. We present the results of a cross-sectional survey (n = 571) where participants were shown images from college campus (n = 4 campuses) depicting different lighting (daytime, nighttime), and entrapment levels (high, low; i.e., able to easily escape if needed, with high entrapment being difficult and low being easy), and using the Qualtrics heat map tool, selected features that stood out to them most. Data were segregated by gender and analyzed to determine similarity of heat maps for the same base image. Heat map images were analyzed using canonical correlation (Rc) to determine the relationship between the two groups; dispersion testing to decipher spatial uniformity within the images; the Structural Similarity Index (SSIM) to characterize the nature of image patterns differences; and, the Breslow-Day Test to specify pattern locations within images. Several heat map images are also presented in the results. Overall, female and male participants appear to "see" different things when imagining walk-commuting (as seen by poor Rc values) and the nature of what they were looking at were different (as seen by poor SSIM values). Female participants tended to focus on areas outside the walking path, such as bushes and dark areas, whereas men's focus was on the path ahead [χ2(1) = 4.29, p = 0.04]. Furthermore, women were more likely to select areas outside the walking path during high entrapment settings [χ2(1) = 15.49, p < 0.001] and at nighttime [χ2(1) = 4.98, p = 0.02]. Our study demonstrates point-of-view differences in female-male walking space assessments. Viewing walking safety through the lens of lived experience could be productive for holistic community walking safety.

Analyzing the Diversity of MYB Family Response Strategies to Drought Stress in Different Flax Varieties Based on Transcriptome Data.

The MYB transcription factor family has numerous members, and is involved in biological activities, such as ABA signaling, which plays an important role in a plant's resistance to abiotic stresses such as drought. However, the diversity of MYB members that respond to drought stress and their regulatory mechanisms in different flax varieties were unclear. In this study, we obtained 855.69 Gb of clean data from 120 flax root samples from 20 flax (Linum usitatissimum L.) varieties, assembled 92,861 transcripts, and identified 434 MYB family members in each variety. The expression profiles of the MYB transcription factor family from 20 flax varieties under drought stress were analyzed. The results indicated that there are four strategies by which the MYB family responds to drought stress in these 20 flax varieties, each of which has its own specific processes, such as development, reproduction, and localization processes. The four strategies also include common biological processes, such as stimulus responses, metabolic processes, and biological regulation. The WGCNA method was subsequently employed to identify key members of the MYB family involved in response strategies to drought stress. The results demonstrated that a 1R-MYB subfamily gene co-expression network is significantly related to the gibberellin response and cytokinin-activated signaling pathway processes in the 'Strategy 4' for MYB family response to drought, identifying core genes such as Lus.scaffold70.240. Our results showed a diversity of MYB family responses to drought stress within flax varieties, and these results contribute to deciphering the mechanisms of the MYB family regulation of drought resistance. This will promote the more accurate breeding development of flax to adapt to agricultural production under drought conditions.

Three-dimensional Mapping Analysis of Talus Fractures and Demonstration of Different Surgical Approaches for Talus Fractures.

OBJECTIVE: The talus is an important component in the ankle, and its treatment after injury is crucial. However, complications and adverse events due to incomplete traditional classifications may still occur, and these classifications fail to analyze the patterns and distribution of fractures from a three-dimensional perspective. Therefore, in this study, we aimed to analyze the location and distribution of fracture lines in different types of talus fractures using three-dimensional (3D) and heat mapping techniques. Additionally, we aimed to determine the surface area of the talus that can be utilized for different approaches of internal fixation, aiding in the planning of surgical procedures. METHODS: We retrospectively analyzed data from CT scans from 126 patients diagnosed with talus fractures at our two hospitals. We extracted the CT data of a healthy adult and created a standard talus model. We performed 3D reconstruction using patients' CT images and superimposed the fracture model onto the standard model for drawing fracture lines. Subsequently, we converted the fracture lines into a heat map for visualization. Additionally, we measured 20 specimens to determine the boundary for various ligaments attached to the talus. We determined the surface area of the talus available for different surgical approaches by integrating the boundary data with previously reported data on area of exposure. RESULTS: Without considering the displacement distance of the fracture, fracture types were classified as follows, by combining Hawkins and Sneppen classifications: talar neck, 41.3%; posterior talar tubercle, 22.2%; body for the talus and comminuted, 17.5%; lateral talar tubercle, 11.9%; and talar head, 7.1%. We established fracture line and heat maps using this classification. Additionally, we demonstrated the available area for anteromedial, anterolateral, posteromedial, posterolateral, and medial malleolus osteotomy and Chaput osteotomy approaches. CONCLUSION: Fracture line and heat map analyses can aid surgeons in planning a single or combined surgical approach for the reduction and internal fixation of talus fractures. Demonstrating the different surgical approaches can help surgeons choose the most effective technique for individual cases.

Three-Dimensional Heat Map: The OTA/AO Type 43C Pilon Fracture Lines Distribution.

Background: This study aimed to create three-dimensional heat map and study the characteristic of fracture lines and represented fragments of OTA/AO type 43C pilon fractures. Methods: CT scan was performed in105 fractures diagnosed with OTA/AO type 43C pilon fractures between January 2017 and December 2022. Three-dimensional pilon fracture maps were created and converted into fracture heat maps. CT scan graphic parameters including the fracture line height, α angle, ß angle, the ratio of the area and size of bone fragment represented by the fracture line to the total articular surface were measured. Results: The study included 105 patients with 91 males and 14 females. The fractures included C1 (n=16), C2 (n=23), and C3 (n=66). There was no statistically different among the most parameters except in the fracture-line height of the anterior fracture line (p=0.03) and the sagittal fracture line (p=0.02) between C2 and C3 pilon fractures. The average size of the anterolateral fragment, occupied approximately 13.5% of the articular surface area, was (11.5±2.8) mm × (20.5±6.3) mm with the average height of 29.8 mm. The average size of the posterolateral fragment, occupied approximately 13.0% of the articular surface area, was (15.7±4.6) mm × (19.3±4.0) mm with the average height of 19.1 mm. Conclusion: This study demonstrates that the articular surface fracture lines in the C type pilon fracture are formed by fixed main fracture lines. The understand of morphological and distribution characteristics of the fracture lines and size of fragments in OTA/AO type 43C pilon fractures would help the surgeons take suitable approach and fixation.

Neurofibromatosis type 1-associated plexiform neurofibromas of the neck: topography of lesions and surgical treatment data of 69 patients.

PURPOSE: Plexiform neurofibromas (PNF) are rare tumors arising from peripheral nerve sheath cells. PNF are a hallmark in patients with neurofibromatosis type 1 (NF1), a tumor predisposition syndrome. PNF often grow invasively and destructively, what may complicate surgical treatment. Data on frequency, location, and surgical procedures of patients with NF1-associated FPNF are scarce. This study provides treatment data of NF1 patients. METHODS: Localization and treatment data of 69 NF1 patients with neck PNF were analyzed. Frequency of lesions was recorded in coded colors on schematic neck drawings. RESULTS: The tumors showed no side preference, were located in the entire area under investigation, and did not respect anatomical units/dermatomes. However, the sternocleidomastoid region was particularly frequently affected. The mean number of surgical measures per patient was 1.33. Complications were extensive swelling, hematoma, and bleeding. Histological assessment usually confirmed the clinical assessment of neoplasm. However, histologic differentiation of PNST reveals differences in between tumors that have been unified in clinical assessment as PNF. CONCLUSION: The color-coded, schematic overview of the frequency distribution of surgical neck interventions in NF1 patients with PNF proved a useful tool to gain assessment of preferred treatment needs. The imaging procedure may be suitable for controlling the external aspect of natural tumor development (growth, effects of aging) in the same way as the documentation of the post-surgical course. Treatment plans for patients with these tumors should consider that repeated interventions may be necessary to achieve a longer-term stable result.

Plasma metabonomics of classical swine fever virus-infected pigs.

Classical swine fever (CSF) is an infectious disease caused by Classical swine fever virus (CSFV), which is characterized by depression, high fever, extensive skin bleeding, leukopenia, anorexia, alternating constipation, and diarrhea. Hemorrhagic infarction of the spleen is the main characteristic pathological change following CSFV infection. Large-scale outbreaks of CSF are rare in China and are mainly distributed regionally. The clinical symptoms of CSF are not obvious, and show variation from typical to atypical symptoms, which makes diagnosis based on clinical symptoms and pathology challenging. In recent years, the incidence of CSF-immunized pig farms in China has increased and new CSFV gene subtypes have appeared, posing new challenges to the prevention and control of CSF in China. Changes in metabolites caused by viral infection reflect the pathogenic process. Metabonomics can reveal the trace metabolites of organisms; however, plasma metabonomics of CSFV-infected pigs have rarely been investigated. Therefore, we used an established pig CSFV infection model to study changes in plasma metabolites. The results showed significant differences in forty-five plasma metabolites at different time periods after CSFV infection in pigs, with an increase in twenty-five metabolites and a decrease in twenty metabolites. These changed metabolites were mainly attributed to the tricarboxylic acid cycle, amino acid cycle, sugar metabolism, and fat metabolism. Thirteen metabolic pathways changed significantly in CSFV-infected pigs, including tricarboxylic acid cycle, inositol phosphate metabolism, glycine, serine and threonine metabolism,lysine degradation, alanine, aspartate and glutamic acid metabolism, pantothenate and CoA biosynthesis, ß-alanine metabolism, lysine degradation, arginine and proline metabolism, glycerolipid metabolism, phenylalanine metabolism, arachidonic acid metabolism, linoleic acid metabolism. Among these, changes in fatty acid biosynthesis and metabolism occurred at all time periods post-infection. These results indicate that CSFV infection in pigs could seriously alter metabolic pathways.

RichPathR: a gene set enrichment analysis and visualization tool.

Gene set enrichment analysis (GSEA) is an important step for disease and drug discovery. Genomic, transcriptomics, proteomics and epigenetic analysis of tissue or cells generates gene lists that need to be further investigated in the known biological context. The advent of high-throughput technologies generates the vast number of gene lists that are up or down regulated together. One way of getting meaningful insights of the relationship of these genes is utilizing existing knowledge bases linking them with biological functions or phenotypes. Multiple public databases with annotated gene sets are available for GSEA, and enrichR is the most popular web application still requiring custom tools for large-scale mining. richPathR package is a collection of R functions that helps researchers carry out exploratory analysis and visualization of gene set enrichment using EnrichR.

Non-targeted Profiling of Sea Buckthorn Fruit Oil Fingerprints from 3 Regions and Study on Its Antioxidant Activity.

This study investigated the chemical and volatile characteristics of sea buckthorn fruits from three different regions in China. The chemical composition of the volatile oil was determined by using a non-targeted gas chromatography and mass spectrometry (GC/MS) method and the differences in chemical composition among the three producing areas were compared by heatmap providing a visual basis for researchers. A total of 93 compounds were identified, including 52 compounds from the Northeast China, 51 from the Xinjiang region, and 37 from Inner Mongolia region. Then, the in vitro antioxidant activity of sea buckthorn fruit oil was measured using DPPH, ABTS, and SOD inhibition tests, and the results showed that sea buckthorn fruit oil in northeast China was the strongest antioxidant, followed by Inner Mongolia and Xinjiang. The results of the CCK-8 experiment indicated that within the tested concentration, there is no cell cytotoxicity of the essential oil in human umbilical vein endothelial cells (HUVECs) cells. The results could supply reference to distinguish sea buckthorn fruit from different production areas and, meanwhile, clarify the activity and safety of sea buckthorn oil.

Prevalence of enterotoxin genes of Staphylococcus sp. isolated from marine fish to reveal seafood contamination.

Seafood is a valuable nutritional source, but it is highly susceptible to bacterial contamination, posing a severe health risk to humans. Enterotoxin-producing genes carrying Staphylococcus sp. are a significant concern in marine fish. This study aimed to investigate the prevalence of enterotoxin genes in Staphylococcus sp. isolated from 17 common fish species and emphasise the need for improving seafood quality and hygiene. The potential risks of contamination by enterotoxin-producing Staphylococcus sp. were assessed. The results indicated the risk associated with the consumption of contaminated seafood, especially from marketed and frozen samples. Gene expression analysis on a heat map revealed that samples stored in markets are heavily loaded with Staphylococcus enterotoxin genes due to the unhygienic water that was used from the local markets for fish processing. To enhance seafood quality, effective measures on handling and storage should be regularly monitored, and they must be implemented throughout the local seafood markets.