RESUMEN

In order to improve the detection performance of image fusion in focus areas and realize end-to-end decision diagram optimization, we design a multi-focus image fusion network based on deep learning. The network is trained using unsupervised learning and a multi-scale hybrid attention residual network model is introduced to enable solving for features at different levels of the image. In the training stage, multi-scale features are extracted from two source images with different focal points using hybrid multi-scale residual blocks (MSRB), and the up-down projection module (UDP) is introduced to obtain multi-scale edge information, then the extracted features are operated to obtain deeper image features. These blocks can effectively utilize multi-scale feature information without increasing the number of parameters. The deep features of the image are extracted in its test phase, input to the spatial frequency domain to calculate and measure the activity level and obtain the initial decision map, and use post-processing techniques to eliminate the edge errors. Finally, the decision map is generated and optimized, and the final fused image is obtained by combining the optimized decision map with the source image. The comparative experiments show that our proposed model achieves better fusion performance in subjective evaluation, and the quality of the obtained fused images is more robust with richer details. The objective evaluation metrics work better and the image fusion quality is higher.

Asunto(s)

RESUMEN

Gut dysbiosis contributes to deterioration of chronic kidney disease (CKD). Probiotics are a potential approach to modulate gut microbiota and gut-derived metabolites to alleviate CKD progression. We aim to provide a comprehensive view of CKD-related gut dysbiosis and a critical perspective on probiotic function in CKD. First, this review addresses gut microbial alterations during CKD progression and the adverse effects associated with the changes in gut-derived metabolites. Second, we conduct a thorough examination of the latest clinical trials involving probiotic intervention to unravel critical pathways via the gut-kidney axis. Finally, we propose our viewpoints on limitations, further considerations, and future research prospects of probiotic adjuvant therapy in alleviating CKD progression. Enhancing our understanding of host-microbe interactions is crucial for gaining precise insights into the mechanisms through which probiotics exert their effects and identifying factors that influence the effectiveness of probiotics in developing strategies to optimize their use and enhance clinical outcomes.

Asunto(s)

RESUMEN

Low-light image enhancement (LLIE) improves lighting to obtain natural normal-light images from images captured under poor illumination. However, existing LLIE methods do not effectively utilize positional and frequency domain image information. To address this limitation, we proposed an end-to-end low-light image enhancement network called HPCDNet. HPCDNet uniquely integrates a hybrid positional coding technique into the self-attention mechanism by appending hybrid positional codes to the query and key, which better retains spatial positional information in the image. The hybrid positional coding can adaptively emphasize important local structures to improve modeling of spatial dependencies within low-light images. Meanwhile, frequency domain image information lost under low-light is recovered via discrete wavelet and cosine transforms. The resulting two frequency domain feature types are weighted and merged using a dual-attention module. More effective use of frequency domain information enhances the network's ability to recreate details, improving visual quality of enhanced low-light images. Experiments demonstrated that our approach can heighten visibility, contrast and color properties of low-light images while better preserving details and textures than previous techniques.

RESUMEN

With the growing number of user-side resources connected to the distribution system, an occasional imbalance between the distribution side and the user side arises, making short-term power load forecasting technology crucial for addressing this issue. To strengthen the capability of load multi-feature extraction and improve the accuracy of electric load forecasting, we have constructed a novel BILSTM-SimAM network model. First, the entirely non-recursive Variational Mode Decomposition (VMD) signal processing technique is applied to decompose the raw data into Intrinsic Mode Functions (IMF) with significant regularity. This effectively reduces noise in the load sequence and preserves high-frequency data features, making the data more suitable for subsequent feature extraction. Second, a convolutional neural network (CNN) mode incorporates Dropout function to prevent model overfitting, this improves recognition accuracy and accelerates convergence. Finally, the model combines a Bidirectional Long Short-Term Memory (BILSTM) network with a simple parameter-free attention mechanism (SimAM). This combination allows for the extraction of multi-feature from the load data while emphasizing the feature information of key historical time points, further enhancing the model's prediction accuracy. The results indicate that the R2 of the BILSTM-SimAM algorithm model reaches 97.8%, surpassing mainstream models such as Transformer, MLP, and Prophet by 2.0%, 2.7%, and 3.6%, respectively. Additionally, the remaining error metrics also show a reduction, confirming the validity and feasibility of the method proposed.

RESUMEN

Microbiota-based strategies are a novel auxiliary therapeutic and preventative way of moderating chronic kidney disease (CKD). Lactobacillus mixture (Lm) was previously demonstrated to exert a renal-protective function in the CKD mice model. The efficacy of probiotics in pet foods is a relatively new area of study, and thus verifying the potential health benefits is necessary. This study evaluated the efficacy of Lm treats in feline CKD and elucidated the mechanisms underlying host-microbe interactions. CKD cats (2 and 3 stages) were administrated probiotic pet treats daily (10 g) for 8 weeks. The results demonstrated that during the eight weeks of Lm administration, creatinine was reduced or maintained in all cats with CKD. Similarly, gut-derived uremic toxin (GDUT), indoxyl sulfate (IS), were potential clinical significance in IS after Lm treatment (confidence intervals = 90%). The life quality of the cats also improved. Feline gut microbiome data, metabolic functional pathway, and renal function indicator analyses revealed the possible mechanisms involved in modulating CKD feline microbial composition. Further regulation of the microbial functions in amino acid metabolism after Lm administration contributed to downregulating deleterious GDUTs. The current study provides potential adjuvant therapeutic insights into probiotic pet foods or treats for pets with CKD.

RESUMEN

In recent years, the global outbreak of COVID-19 has posed an extremely serious life-safety risk to humans, and in order to maximize the diagnostic efficiency of physicians, it is extremely valuable to investigate the methods of lesion segmentation in images of COVID-19. Aiming at the problems of existing deep learning models, such as low segmentation accuracy, poor model generalization performance, large model parameters and difficult deployment, we propose an UNet segmentation network integrating multi-scale attention for COVID-19 CT images. Specifically, the UNet network model is utilized as the base network, and the structure of multi-scale convolutional attention is proposed in the encoder stage to enhance the network's ability to capture multi-scale information. Second, a local channel attention module is proposed to extract spatial information by modeling local relationships to generate channel domain weights, to supplement detailed information about the target region to reduce information redundancy and to enhance important information. Moreover, the network model encoder segment uses the Meta-ACON activation function to avoid the overfitting phenomenon of the model and to improve the model's representational ability. A large number of experimental results on publicly available mixed data sets show that compared with the current mainstream image segmentation algorithms, the pro-posed method can more effectively improve the accuracy and generalization performance of COVID-19 lesions segmentation and provide help for medical diagnosis and analysis.

Asunto(s)

RESUMEN

BACKGROUND: The majority of kidney recipients are a subset of chronic kidney disease. Our previous study demonstrated that the combination of Lactobacillus plantarum and Lactobacillus paracasei (Lm) had the highest clearance ability of uremic toxins and improved kidney function in a mouse model. This study aimed to evaluate Lm in improving graft function, effects on immunosuppressants, and safety in transplant recipients. METHODS: We retrospectively reviewed 24 patients. Twelve of them take Lm regularly; we compared the creatinine measurements and estimated glomerular filtration rate 3 months before and after Lm using a 2-tailed Wilcoxon matched-pairs signed-rank test while also evaluating the drug level of immunosuppressants and infection events. Other 12 patients who do not have Lm for evaluation of laboratory calibration and compared the proportion of improving creatinine using Fisher's exact test. RESULTS: The creatinine decreased by 0.06 mg/dL (P = .02), and the estimated glomerular filtration rate increased by 3.1 mL/min/1.73 m2 (P = .03) after Lm supplementation. This pilot study revealed the association of higher incidence (odds ratio 13.3, 95% CI 1.64-77.2, P = .01) of decreasing creatinine in transplant recipients using Lm. Furthermore, results showed a trend of higher trough levels of tacrolimus and sirolimus, which might provide a potential strategy for reducing the dosages of immunosuppressants. CONCLUSION: Our findings revealed an association between a higher incidence of decreasing creatinine in kidney transplant recipients using Lm, which may also provide a potential strategy for reducing the acquired dosages of immunosuppressants.

Asunto(s)

RESUMEN

Introduction: There are differences in the gut microbiome and metabolome when the host undergoes different physical or pathological conditions. However, the inter-relationship of microbiome and metabolome biomarkers to potentially promote the health of dairy cows needs to be studied. Further, the development of next-generation probiotics for dairy cattle health promotion has not been demonstrated. Objective: In the present study, we identified the microbiome and metabolome biomarkers associated with healthy cows. Methods: We analyzed the relationships of the ruminal microorganism profile and metabolites between healthy and mastitis lactating dairy cows. The roles of bacterial biomarker were further verified by in vitro fermentation and cow-to-mouse fecal microbiota transplantation (FMT). Results: Two species, Ruminococcus flavefaciens and Bifidobacterium longum subsp. longum, and six rumen metabolites were positively correlated with healthy cows by Spearman's correlation analysis. Through in vitro ruminal fermentation, inoculating R. flavefaciens and B. longum subsp. longum showed the upregulation of the levels of putrescine, xanthurenic acid, and pyridoxal in the mastitis ruminal fluid, which confirmed the inter-relationships between these microbiota and metabolites associated with healthy cows. Further, we verified the role of R. flavefaciens and B. longum subsp. longum in promoting health by FMT. The administration of R. flavefaciens and B. longum subsp. longum reduced the death rate and recovered the bodyweight loss of germ-free mice caused by FMT mastitis feces. Discussion: We provided evidence that the bacterial biomarkers alter downstream metabolites. This could indirectly indicate that the two bacterial biomarkers have the potential to be used as next-generation probiotics for dairy cattle, although it needs more evidence to support our hypothesis. Two species, R. flavefaciens and B. longum subsp. longum, with three metabolites, putrescine, xanthurenic acid, and pyridoxal, identified in the ruminal fluid, may point to a new health-promoting and disease-preventing approach for dairy cattle.

RESUMEN

Exposure to ambient particulate matter (PM) and cigarette smoking (CS) is a risk factor for respiratory/lung infections and metabolic disorders. Lung-gut axis disruption involving the upregulation of oxidative stress, systemic inflammation, and gut barrier dysfunction by PM is one of the potential mechanisms. Thus, we designed a novel in vitro platform for pre-selecting probiotics with potentially protective effects against PM-induced lung damage through the lung-gut axis to reduce animal usage. The results showed that a high dose of Lactobacillus acidophilus TW01 (1 × 108 CFU/mL) inhibited reactive oxygen species (ROS) production. This strain could also reduce respiratory epithelial cell death induced by cigarette smoke extraction (CSE), as well as promoting Caco-2 cell migration in 1 × 106 CFU/mL. Although further animal experiments are needed to validate the in vitro findings, L. acidophilus TW01 is a promising probiotic strain for the potential prevention of PM2.5-induced damage.

RESUMEN

Improperly using safety harness hooks is a major factor of safety hazards during power maintenance operation. The machine vision-based traditional detection methods have low accuracy and limited real-time effectiveness. In order to quickly discern the status of hooks and reduce safety incidents in the complicated operation environments, three improvements are incorporated in YOLOv5s to construct the novel HDS-YOLOv5 network. First, HOOK-SPPF (spatial pyramid pooling fast) feature extraction module replaces the SPPF backbone network. It can enhance the network's feature extraction capability with less feature loss and extract more distinctive hook features from complex backgrounds. Second, a decoupled head module modified with confidence and regression frames is implemented to reduce negative conflicts between classification and regression, resulting in increased recognition accuracy and accelerated convergence. Lastly, the Scylla intersection over union (SIoU) is employed to optimize the loss function by utilizing the vector angle between the real and predicted frames, thereby improving the model's convergence. Experimental results demonstrate that the HDS-YOLOv5 algorithm achieves a 3% increase in mAP@0.5, reaching 91.2%. Additionally, the algorithm achieves a detection rate of 24.0 FPS (frames per second), demonstrating its superior performance compared to other models.

RESUMEN

Blurring is one of the main degradation factors in image degradation, so image deblurring is of great interest as a fundamental problem in low-level computer vision. Because of the limited receptive field, traditional CNNs lack global fuzzy region modeling, and do not make full use of rich context information between features. Recently, a transformer-based neural network structure has performed well in natural language tasks, inspiring rapid development in the field of defuzzification. Therefore, in this paper, a hybrid architecture based on CNN and transformers is used for image deblurring. Specifically, we first extract the shallow features of the blurred images using a cross-layer feature fusion block that emphasizes the contextual information of each feature extraction layer. Secondly, an efficient transformer module for extracting deep features is designed, which fully aggregates feature information at medium and long distances using vertical and horizontal intra- and inter-strip attention layers, and a dual gating mechanism is used as a feedforward neural network, which effectively reduces redundant features. Finally, the cross-layer feature fusion block is used to complement the feature information to obtain the deblurred image. Extensive experimental results on publicly available benchmark datasets GoPro, HIDE, and the real dataset RealBlur show that the proposed method outperforms the current mainstream deblurring algorithms and recovers the edge contours and texture details of the images more clearly.

RESUMEN

Velvet antler is a precious traditional Chinese medicine used for thousands of years. This study investigated the anti-colitis effects of water extracts of Formosan sambar deer (SVAE) and red deer (RVAE) to identify the possible mechanisms and the bioactive compounds using a dextran sulfate sodium (DSS)-induced colitis mouse model. The mechanism of action and the ameliorating effects of SVAE and RVAE on DSS-induced colitis were evaluated using a mouse model. Ultra-high performance liquid chromatography-mass/mass and gas chromatography-mass/mass were applied to identify the bioactive components of the SVAE and RVAE water extracts. The results revealed that both high-dose SVAE and RVAE could ameliorate the symptoms of colitis due to reduced systemic inflammatory responses, enhanced intestinal barrier integrity by restoration of tight junction proteins, and improved gut dysbiosis. The potentially bioactive components of SVAE and RVAE were identified as small molecules (<3 kDa). Further identification by untargeted metabolomics analysis suggested that l-carnitine, hypoxanthine, adrenic acid, creatinine, gamma-aminobutyric-lysine, oleic acid, glycine, poly-γ-glutamic acid, and eicosapentaenoic acid in VAWEs might be involved in ameliorating the symptoms of colitis. This study provided evidence for the potential usage of SVAE and RVAE as anti-colitis agents.

RESUMEN

Liver fibrosis refers to the pathophysiological process of dysplasia on the connective tissue of the liver, caused by a variety of pathogenic factors. Glaucocalyxin A (GLA) has anticoagulation, antibacterial, anti-inflammation, antioxidant and antitumour properties. However, whether GLA ameliorates liver fibrosis or not is still unclear. In this study, a liver fibrosis model was established using male C57BL/6 mice. The mice were treated with 5 and 10 mg/kg GLA via intraperitoneal injection, respectively. The ones that were treated with 5 mg/kg OCA were used as the positive control group. The levels of liver function, liver fibrosis biomarkers and liver pathological changes were then evaluated. We also explored the effects of GLA on inflammatory response and liver cell apoptosis. In addition, we investigated the gut microbiota mechanisms of GLA on liver fibrosis. The results from this study that GLA could significantly decrease the level of liver function (AST, ALT, TBA) and liver fibrosis (HA, LN, PC-III, IV-C). On the other hand, a significant decrease in inflammation levels (IL-1ß, TNF-α) were also noted. GLA also improves CCl4-induced pathological liver injuries and collagen deposition, in addition to decreasing apoptosis levels. In addition, an increase in the ratio of Bacteroidetes and Firmicutes in liver disease was also observed. GLA also improves the gut microbiota. In conclusion, GLA attenuates CCl4-induced liver fibrosis and improves the associated gut microbiota imbalance.

Asunto(s)

RESUMEN

Atopic dermatitis (AD) is a chronic and relapsing inflammatory skin disease accompanied with severe itching and skin lesions. Current studies have demonstrated that probiotics can exert an immunomodulatory effect, improve epithelial barrier function, and normalize the composition of gut microbiota. Thus, the aim of this study was to investigate the effect of probiotics on the immune balance of AD in vivo. We first screened two lactic acid bacteria strains, which were Lactococcus lactis subsp. cremoris MP01 and Lactobacillus paracasei subsp. paracasei MP02, from 10 strains isolated from traditional fermented milk with inflammation regulating activities in vitro. In the house dust mite (HDM) extraction-induced AD mouse model, mice were assigned randomly to four groups: control group (PC), HDM-induced AD group (NC), HDM-induced AD mice with administration of a mixture of heat-killed MP01 and MP02 at a low concentration (LD), and high concentration (HD) groups. Compared with the NC group, the probiotic treatments could relieve the AD symptoms. Moreover, the LD group significantly decreased total and HDM-specific IgE concentration. These results indicated that a combination of heat-killed MP01 and MP02 strains modulated the proportion of IL4+CD4+ T cells and IFNγ+CD4+ T cells in the spleen of HDM extraction-induced AD mice. In conclusion, administration of the heat-killed MP01 and MP02 mixtures appeared to relieve the classic AD signs, decrease serum IgE concentration, and rebalance the population of Th1/Th2 cells in HDM extraction-induced AD mice. The immunomodulatory activities of a combination of heat-killed MP01 and MP02 provided a potential new therapeutic strategy against AD.

RESUMEN

(1) Background: Strains HL1 and M1, isolated from kefir grains, have been tentatively identified, based on their partial 16S rRNA gene sequences, as Lactobacillus kefiranofaciens. The two strains demonstrated different health benefits. Therefore, not only the genetic factors exerting diverse functionalities in different L. kefiranofaciens strains, but also the potential niche-specific genes and pathways among the L. kefiranofaciens strains, should be identified. (2) Methods: Phenotypic and genotypic approaches were employed to identify strains HL1 and M1 at the subspecies level. For the further characterization of the probiotic properties of both strains, comparative genomic analyses were used. (3) Results: Both strains were identified as L. kefiranofaciens subsp. kefirgranum. According to the COG function category, dTDP-rhamnose and rhamnose-containing glycans were specifically detected in the L. kefiranofaciens subsp. Kefirgranum genomes. Three unique genes (epsI, epsJ, and epsK) encoding glycosyltransferase in the EPS gene cluster, and the ImpB/MucB/SamB family protein encoding gene were found in HL1 and M1. The specific ability to degrade arginine via the ADI pathway was found in HL1. The presence of the complete glycogen metabolism (glg) operon in the L. kefiranofaciens strains suggested the importance of glycogen synthesis to enable colonization in kefir grains and extend survival under environmental stresses. (4) Conclusions: The obtained novel information on the potential genes and pathways for polysaccharide synthesis and other functionalities in our HL1 and M1 strains could be applied for further functionality predictions for potential probiotic screening.

RESUMEN

Exercise causes changes in the gut microbiota, and in turn, the composition of the gut microbiota affects exercise performance. In addition, the supplementation of probiotics is one of the most direct ways to change the gut microbiota. In recent years, the development and application of human-origin probiotics has gradually attracted attention. Therefore, we obtained intestinal Lactiplantibacillus plantarum "Tana" from a gold-medal-winning weightlifter, who has taken part in various international competitions such as the World Championships and the Olympic Games, to investigate the benefits of Tana supplementation for improving exercise performance and promoting antifatigue effects in mice. A total of 40 male Institute of Cancer Research (ICR) mice were divided into four groups (10 mice/group): (1) vehicle (0 CFU/mice/day), (2) Tana-1× (6.15 × 107 CFU/mice/day), (3) Tana-2× (1.23 × 108 CFU /mice/day), and (4) Tana-5× (3.09 × 108 CFU/mice/day). After four weeks of Tana supplementation, we found that the grip strength, endurance exercise performance, and glycogen storage in the liver and muscle were significantly improved compared to those in the vehicle group (p < 0.05). In addition, supplementation with Tana had significant effects on fatigue-related biochemical markers; lactate, ammonia, and blood urea nitrogen (BUN) levels and creatine kinase (CK) activity were significantly lowered (p < 0.05). We also found that the improved exercise performance and antifatigue benefits were significantly dose-dependent on increasing doses of Tana supplementation (p < 0.05), which increased the abundance and ratio of beneficial bacteria in the gut. Taken together, Tana supplementation for four weeks was effective in improving the gut microbiota, thereby enhancing exercise performance, and had antifatigue effects. Furthermore, supplementation did not cause any physiological or histopathological damage.

Asunto(s)

RESUMEN

BACKGROUND: Estrogen has been usually used in clinic for medical pretreatment of early pregnancy loss. There was little reported the effect of estrogen combined with prostaglandin analogs in the medical management of early pregnancy loss. This retrospective study aimed to evaluate the efficacy of estrogen pretreatment for medical management of early pregnancy loss and explore the confounding factor of intrauterine adhesion (IUA) on the outcome of medical management. METHODS: A total of 226 early pregnancy loss patients who received pretreatment with estradiol valerate and/or mifepristone, followed by carboprost methylate suppositories (study groups), or carboprost methylate suppositories alone (control group) in a regional central institution from March 2020 to February 2021 were retrospectively studied. All patients were evaluated by hysteroscopy 6 h after carboprost methylate suppositories use to assess whether the gestational sac was complete expulsion and assess the morphology of uterine cavity. RESULTS: The complete expulsion rate was 56.94% in the mifepristone and estradiol valerate-pretreatment group, 20.69% in the estradiol valerate-pretreatment group, 62.5% in the mifepristone-pretreatment group, and 12.5% in the control group. Compared with the control group, pretreatment with estradiol valerate did not increase the complete expulsion rate significantly (P = 0.297), pretreatment with mifepristone increased the complete expulsion rate significantly (P < 0.001). Pretreatment with mifepristone combined with estradiol valerate did not increase the complete expulsion rate significantly comparing with pretreatment with mifepristone (P = 0.222). The data of IUA showed that the complete expulsion rate in patients with IUA was lower than that in those patients without IUA (P < 0.001). CONCLUSIONS: Pretreatment with estrogen was not a sensible substitute for mifepristone in the medical management of early pregnancy loss. Mifepristone followed by carboprost methylate suppositories was likelihood of the ideal medical scheme in early pregnancy loss. IUA decreased the complete expulsion rate of medical management, it is cautious about medical management for early pregnancy loss with risk of IUA. TRIAL REGISTRATION NUMBER: ChiCTR2100046503. Date of registration (retrospectively registered): May 18, 2021. Trial registration website: http://www.chictr.org.cn/ .

Asunto(s)

RESUMEN

(1) Background: We aimed to isolate and identify potential next-generation probiotics (NGP) by investigating the interrelationships between gastrointestinal microbiota and diarrhea in preruminant Holstein calves. (2) Material and methods: Twenty preruminant Holstein calves were divided into healthy and diarrheic groups after the combination outcomes of veterinary diagnosis and fecal scores. The fecal microbiome, plasma cytokines, plasma immunoglobulin (Ig) G and haptoglobin were analyzed. The potential probiotic bacteria were identified by comparing the microbiota difference between healthy and diarrheic calves and correlation analysis with fecal scores and inflammatory markers. The identified bacteria were also isolated for further evaluation for antimicrobial activities and immunoregulatory effects. (3) Results: Microbiota analysis suggested that Ruminococcaceae_UCG_014, Bifidobacterium and Pseudoflavonifractor positively correlated with bovine IgG and negatively correlated with fecal score; inflammatory factors, bovine HP, and IL-8 were classified as beneficial bacteria contributing to the health of the calves. The alternation of gut microbial composition also induced changes in the functional gene enrichment of gut microbiota in calves. The gathering of microbiomic data strongly indicated the possible beneficial effects of Bifidobacterium longum subsp. longum, expected to develop as NGP. After isolation and evaluation of the potential functionality in vitro, two specific bifidobacterial strains demonstrated antimicrobial activities and immunoregulatory effects. (4) Conclusions: The results provide a new probiotic searching approach for preventing gastrointestinal disorders in preruminant calves. Further animal study is necessary to verify the results.

RESUMEN

OBJECTIVE: The aim of this study was to characterize the exopolysaccharides (EPS)-producing lactic acid bacteria from Taiwanese ropy fermented milk (TRFM) for developing a clean label low-fat fermented milk. METHODS: Potential isolates from TRFM were selected based on the Gram staining test and observation of turbid suspension in the culture broth. Random amplified polymorphic DNA-polymerase chain reaction, 16S rRNA gene sequencing, and API CHL 50 test were used for strain identification. After evaluation of EPS concentration, target strains were introduced to low-fat milk fermentation for 24 h. Fermentation characters were checked: pH value, acidity, viable count, syneresis, and viscosity. Sensory evaluation of fermented products was carried out by 30 volunteers, while the storage test was performed for 21 days at 4°C. RESULTS: Two EPS-producing strains (APL15 and APL16) were isolated from TRFM and identified as Lactococcus (Lc.) lactis subsp. cremoris. Their EPS concentrations in glucose and lactose media were higher than other published strains of Lc. lactis subsp. cremoris. Low-fat fermented milk separately prepared with APL15 and APL16 reached pH 4.3 and acidity 0.8% with a viable count of 9 log colony-forming units/mL. The physical properties of both products were superior to the control yogurt, showing significant improvements in syneresis and viscosity (p<0.05). Our low-fat products had appropriate sensory scores in appearance and texture according to sensory evaluation. Although decreasing viable cells of strains during the 21-day storage test, low-fat fermented milk made by APL15 exhibited stable physicochemical properties, including pH value, acidity, syneresis and sufficient viable cells throughout the storage period. CONCLUSION: This study demonstrated that Lc. lactis subsp. cremoris APL15 isolated from TRFM had good fermentation abilities to produce low-fat fermented milk. These data indicate that EPS-producing lactic acid bacteria have great potential to act as natural food stabilizers for low-fat fermented milk.

RESUMEN

Mastitis in dairy cow significantly affects animal performance, ultimately reducing profitability. The reciprocal interrelationships among ruminal microbiota, metabolome, and mastitis combining early inflammatory factors (serum proinflammatory cytokines) in lactating dairy cows has not been explored, thus, this study evaluated these reciprocal interrelationships in early lactating Holstein dairy cows to identify potential microbial biomarkers and their relationship with ruminal metabolites. The ruminal fluid was sampled from 8 healthy and 8 mastitis cows for the microbiota and metabolite analyses. The critical ruminal microbial biomarkers and metabolites related to somatic cell counts (SCC) and serum proinflammatory cytokines were identified by the linear discriminant analysis effect size (LEfSe) algorithm and Spearman's correlation analysis, respectively. The SCC level and proinflammatory cytokines positively correlated with Sharpea and negatively correlated with Ruminococcaceae UCG-014, Ruminococcus flavefaciens, and Treponema saccharophilum. Furthermore, the metabolites xanthurenic acid, and 1-(1H-benzo[d]imidazol-2-yl) ethan-1-ol positively correlated with microbial biomarkers of healthy cows, whereas, xanthine, pantothenic acid, and anacardic acid were negatively correlated with the microbial biomarkers of mastitis cows. In conclusion, Ruminococcus flavefaciens and Treponema saccharophilum are potential strains for improving the health of dairy cows. The current study provides a novel perspective to assist in targeting the ruminal microbiota with preventive/therapeutic strategies against inflammatory diseases in the future.