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Activities such as childbirth and breastfeeding can cause severe oxidative stress and inflammatory damage to the mother during early lactation, and can affect animal milk production, and the growth and development of offspring. Trehalose alleviates damage to the body by endowing it with stress resistance. In this study, we used trehalose combined with Lactobacillus plantarum, Bifidobacterium longum, Bacillus subtilis, and Saccharomyces cerevisiae to explore whether dietary intervention can alleviate oxidative stress and inflammatory damage in early lactation and to evaluate the growth ability, acid production ability, antioxidant ability, non-specific adhesion ability, antibacterial ability, and other parameters to determine the optimal combinations and proportions. The results showed that the synbiotics composed of 2.5% trehalose and 1 × 107 cfu/g of Bifidobacterium longum could regulate the gut microbiota, and promote mammary gland development in dams by reducing progesterone (PROG) content in the blood, increasing prolactin (PRL) and insulin-like growth factor-1 (IGF-1) content, enhancing their antioxidant and immune abilities, and effectively increasing the weight and lactation of early lactating dams. In addition, it can also affect the growth of offspring and the development of the intestinal barrier. These results indicate that trehalose synbiotics have great potential in alleviating oxidative stress and inflammatory damage in early lactation. [ABSTRACT FROM AUTHOR]

Background: Despite the widespread adoption of TMR or PMR and the formulas designed to sufficiently cover the cows' requirements, individual dairy cows' milk production varies significantly. The liver is one of the most important organs in cow lactation metabolism and plays an essential role in the initiation of lactation. Objectives: This study aimed to investigate the potential key genes in the liver contributing to the different milk production. Methods: We enrolled 64 cows and assigned them to high or low milk yield (MY) groups according to their first 3 weeks of milk production. We performed RNAseq for 35 liver samples with 18 from prepartum and 17 from postpartum cows. Results: The continuous milk yield observation showed a persistently higher milk yield in high MY cows than low MY cows in the first 3 weeks. High MY cows showed better feed conversion efficiency. We identified 795 differentially expressed genes (DGEs) in the liver of high MY cows compared with low MY cows, with up-regulated genes linked to morphogenesis and development pathways. Weighted gene co-expression network analysis (WGCNA) revealed four gene modules positively correlating with milk yield, and protein and lactose yield (p < 0.05). Using the intersected genes between the four gene modules and DEGs, we constructed the linear mixed-effects models and identified six hub genes positively associated and two hub genes negatively associated with milk yield (Coefficients > 0.25, p < 0.05). Random forest machine learning model training based on these eight hub genes could efficiently predict the milk yield (p < 0.001, R2 = 0.946). Interestingly, the expression patterns of these eight hub genes remained remarkably similar before and after parturition. Conclusions: The present study indicated the critical role of liver in milk production. Activated processes involved in morphogenesis and development in liver may contribute to the higher milk production. Eight hub genes identified in this study may provide genetic research materials for dairy cow breeding. [ABSTRACT FROM AUTHOR]

Glomalin-related soil proteins (GRSP) play a crucial role in strengthening soil structure and increasing carbon (C) storage. However, the chemical stability of GRSP and related arbuscular mycorrhizal fungi (AMF) community response to fertilization remains unclear. This study investigated C and nitrogen (N) contents, three-dimensional fluorescence characteristics in GRSP, and AMF properties based on a field experiment that was subjected to 29 years of various fertilizations. The experiment included treatments with no fertilizer (CK), chemical fertilizer (NPK), manure (M), and manure combined with NPK (NPKM) treatments. Results showed that GRSP contained 37–49% C and 6–9% N, respectively. Compared with CK and NPK, the C and N proportions in GRSP significantly increased under M and NPKM. Using the parallel factor model, four fluorescent components of GRSP were identified: one fulvic acid-like component (C2), one tyrosine-like component (C4), and two humic acid-like components (C1, C3). Under M and NPKM, the fluorescent intensity of C2 and C4 decreased, while the humification index (HIX) increased relative to CK and NPK, indicating that organic fertilization could enhance the stability of GRSP. The C and N proportion in GRSP positively associated with soil organic C (SOC), total N (TN), available phosphorus (AP), AMF biomass, and diversity, while C2 and C4 showed negative associations. Structural equation modeling further revealed that manure-induced changes in pH, SOC, TN, and AP increased AMF biomass and diversity, thereby altering GRSP composition and stability. This study provides valuable insights into the compositional traits of GRSP, contributing to sustainable soil management and C sequestration in agroecosystems. [ABSTRACT FROM AUTHOR]

Simple Summary: Following weaning, piglets exhibit an immature immune system, reduced capacity to digest and absorb nutrients, and encounter diverse stressors that significantly compromise their overall health. The supplementation of probiotics in animal feed has proven to be a beneficial strategy for enhancing the welfare of livestock and poultry. The findings of this research demonstrate that supplementing the diet with 5 × 108 CFU/kg of Clostridium butyricum enhances fecal microflora diversity and richness through the modulation of specific metabolites such as L-aspartic acid, 5-hydroxyindole-3-acetic acid, stearic acid, and adipic acid. This mechanism contributes to a reduction in the incidence of diarrhea in weaned piglets triggered by E. coli K88. Consequently, the study outcomes offer both empirical evidence and theoretical support for the utilization of Clostridium butyricum in combatting diarrhea in piglet rearing. This study aimed to evaluate the effects of Clostridium butyricum (C. butyricum) on the prevention of the diarrhea rates and growth performances of weaned piglets induced by Escherichia coli K88 (E. coli K88). Twenty-four weaned piglets (6.92 ± 0.11 kg) were randomly assigned to one of three treatment groups for a period of 21 days. Each group consisted of eight pigs, with each pig being housed in an individual pen. Group I received the control diet along with normal saline, Group II received the control diet along with E. coli K88, and Group III received the control diet supplemented with 5 × 108 CFU/kg of C. butyricum and E. coli K88. We examined alterations in rectal microbiota and metabolites, analyzed the incidence of diarrhea, and investigated the interactions between microbiota and metabolites through the application of Illumina MiSeq sequencing and liquid chromatography–mass spectrometry. The results showed that, from days 14 to 21, the diarrhea incidence in Group III decreased significantly by 83.29% compared to Group II (p < 0.05). Over the entire experimental duration, the average daily feed intake of Group III decreased significantly by 11.13% compared to Group I (p < 0.05), while the diarrhea incidence in Group III decreased by 71.46% compared to Group II (p < 0.05). The predominant microbial flora in the rectum consisted of Firmicutes (57.32%), Bacteroidetes (41.03%), and Proteobacteria (0.66%). Administering E. coli K88 orally can elevate the relative abundance of Megasphaera (p < 0.05). Conversely, the supplementation of C. butyricum in the diet reduced the relative abundance of Megasphaera (p < 0.05), while increasing the relative abundance of unclassified_f_Lachnospiraceae (p < 0.05). Rectal metabolomics analysis revealed that supplementing C. butyricum in the feed significantly altered the amino acids and fatty acids of the piglets infected with E. coli K88 (p < 0.05). The correlation analysis showed that the occurrence of diarrhea was inversely related to adipic acid (p < 0.05) and positively associated with (5-hydroxyindol-3-YL) acetic acid and L-aspartic acid (p < 0.05). Prevotella_1 exhibited a negative correlation with octadecanoic acid (p < 0.05). Prevotellaceae_UCG-005 showed a negative correlation with (5-hydroxyindol-3-YL) acetic acid (p < 0.05). The findings from this research study aid in probiotic development and the enhancement of healthy growth in weaned piglets. [ABSTRACT FROM AUTHOR]

This study aimed to explore the protective effects of raffinose (Raf) against inflammatory bowel disease in mice with colitis. Mice were administered 100, 200, or 400 mg/kg Raf for 21 d, followed by drinking-water containing 3% dextran sulfate sodium salt (DSS) for 3 d. Thereafter, the phenotype, pathological lesions in the colon, cytokines levels, and gut microbiota were evaluated. Treatment with Raf reduced the severity of the pathological changes in the colon, mitigating the reduction in colon length. Following Raf intervention, serum levels of inflammatory cytokines (IL-2, IL-6, IL-1β, and TNF-α) tended to return to normal. These results suggest that the anti-inflammatory effects of Raf are associated with a reduction in TLR4–MyD88–NF-κB pathway expression in mouse colonic tissues. Analysis of gut microbiota abundance and its correlation with colitis parameters revealed that DSS-induced dysbiosis was partially mitigated by Raf. In conclusion, Raf exerts a protective effect in colitis by modulating the gut microbiota and TLR4-MyD88-NF-κB pathway. [ABSTRACT FROM AUTHOR]

Simple Summary: In the process of calf rearing, it is inevitable to encounter issues of illness and death among calves. Often, due to the inability to detect sicknesses such as diarrhoea in a timely fashion, these sicknesses lead to the calves' demise. This research starts from the practical application needs, and proposes the development of a monitoring system using deep learning technology to monitor the daily standing and lying behaviour of calves to predict their condition and adaptation to the environment. By analysing the standing and lying time of calves, the system can provide early warnings about calves' condition and health status. This research helps to promptly grasp calves' condition and growth status, thereby improving their welfare and management, enhancing the health condition of reared calves, ensuring the quality and safety of meat and milk, and reducing production costs. This research method also offers a new idea for the construction of smart ranches, as the construction of precision and smart ranches is not only a demand of consumers but also an inevitable direction for the development of the breeding industry. Standing and lying are the fundamental behaviours of quadrupedal animals, and the ratio of their durations is a significant indicator of calf health. In this study, we proposed a computer vision method for non-invasively monitoring of calves' behaviours. Cameras were deployed at four viewpoints to monitor six calves on six consecutive days. YOLOv8n was trained to detect standing and lying calves. Daily behavioural budget was then summarised and analysed based on automatic inference on untrained data. The results show a mean average precision of 0.995 and an average inference speed of 333 frames per second. The maximum error in the estimated daily standing and lying time for a total of 8 calf-days is less than 14 min. Calves with diarrhoea had about 2 h more daily lying time (p < 0.002), 2.65 more daily lying bouts (p < 0.049), and 4.3 min less daily lying bout duration (p = 0.5) compared to healthy calves. The proposed method can help in understanding calves' health status based on automatically measured standing and lying time, thereby improving their welfare and management on the farm. [ABSTRACT FROM AUTHOR]

Calf intestines are colonized by rich and complex microbial communities, playing a crucial role in animal physiology, metabolism, nutrition, and immune function. In this study, we provide insight into the composition of fecal microbial bacteria and fungi, respectively, as well as the cross-kingdom interactions. We investigated the intestinal microbiota of different breeds of calves by characterizing the bacterial and fungal communities in the rectal feces of Holstein calves and German Simmental × Holstein cross F1 generation (GXH) using 16S rRNA and ITS amplicon sequencing techniques. PICRUSt2 (version 2.2.0) were used to determine microbial diversity and function and explore the reasons why Holstein calves are more susceptible to diarrhea. The results revealed no significant difference in the diversity of fecal microbiota among the groups (p > 0.05). We identified Firmicutes, Bacteroidetes, and Proteobacteria as the dominant bacterial phyla in the fecal bacterial communities of the two breeds of calves. Ascomycota and Basidiomycota play important roles in the fungal community but differ in relative abundance. Bacteroides was the dominant genus at the group level for calf fecal microbiota in both breeds. The relative abundance of Prevotella, Escherichia-Shigella, Peptostreptococcus, and Butyricicoccus was higher in Holstein calves, and the relative abundance of Faecalibacterium, Megamonas, Butyricicoccus, and Alloprevotella was lower than GXH group. Aspergillus and Cladosporium were the dominating genera of fecal fungi in both groups of calves. LEfSe analysis revealed 33 different bacteria and 23 different fungi between the two groups, with more differential strains found in GXH. In addition, the feces fungi-bacteria interkingdom interactions varied among breeds. Thus, the composition and structure of bacterial and fungal communities in calf feces varied by breed, indicating a potential association between breed and microbial communities. We also found differences in the network between bacterial–fungal kingdoms. We explain the reasons for Holstein calves being more prone to diarrhea. This indicated that breed makes differences in calf diarrhea rates by influencing gut microbial composition and interactions. [ABSTRACT FROM AUTHOR]

To improve the potassium availability of feldspar at ordinary temperatures, the mechanical grinding and addition of sodium hydroxide/salts were employed to study the effects of mechanical activation and strong alkali addition on particle characteristics, water-soluble potassium, and the available potassium of feldspar. A laser particle size analyzer was utilized for the direct determination of particle size distribution (PSD) using ground samples. The Brunauer–Emmett–Teller (BET) method was employed for specific surface areas. X-ray diffraction (XRD) was employed for structural characterization, scanning electron microscopy (SEM) for morphology exploration, and energy dispersive spectroscopy (EDS) to determine the chemical composition of potassium feldspar powder. The results revealed that the mechanical activation of potassium feldspar could reduce the particle size and produce agglomerated nanoparticles in the later period. The addition of NaOH and sodium salt did not cause agglomeration, and NaOH dissolved the nanoparticles. The water-soluble potassium content of feldspar in each treatment increased during mechanical grinding, from 21.64 mg kg−1 to 1495.81 mg·kg−1, by adding NaOH 5% weight of potassium feldspar powder and to 3044.08 mg·kg−1 by adding NaOH 10% weight with effects different from those of mechanical shaking. By comparison, only 162.93 mg·kg−1 water-soluble potassium was obtained by adding NaOH 5% weight. The dissolved potassium in the former case was significantly higher than in the latter, and the addition of NaOH and sodium salts significantly enhanced the water-soluble potassium contents due to ion exchange. Furthermore, the addition of sodium hydroxide improved the water-soluble potassium due to its mechanochemical action on potassium feldspar. The mechanical energy changed the crystal structure of potassium feldspar, explaining the increase in available potassium. The addition of sodium salts did not promote change in the feldspar's structure, thereby did not raise the available potassium content. The reason for this was related to the mechanochemical action on sodium hydroxide and feldspar, which could promote the dissolution of fine particles, thereby incrementing the available potassium. [ABSTRACT FROM AUTHOR]

Partial substitution of synthetic nitrogen fertilizer with manure (organic substitution) is highly recommended to minimize environmental risks without compromising crop productivity in intensive agricultural systems. However, our understanding of the effect of organic substitution on soil organic carbon (OC) and total nitrogen (TN) in deep soil and its impact on crop productivity remains limited. Here we investigated OC and TN changes in soil profile down to 100 cm, crop yield, and sustainable yield index under synthetic nitrogen, phosphate, and potassium fertilizers (NPK), NPK plus straw (NPKS), and organic substitution (NPKM) treatments over two decades in four upland fields across different climate zones. Compared with the initial values, two decades of NPKM treatment significantly (p < 0.05) increased OC and TN stocks in either topsoil (by 25.6–103.8 and 15.8–89.8%) or deep soil (by 2.9–71.3 and 5.7–36.9%), respectively, across all sites. The increases in OC and TN stocks in 0–100 cm soil receiving NPKM were significantly higher than those receiving NPK at all sites and NPKS at three high-evaporation sites. Compared with NPKS and NPK treatments, crop yield and N uptake were significantly increased under NPKM treatment only at the Qiyang site. Furthermore, OC sequestration in the entire soil profile down to 100 cm and TN accumulation in topsoil exhibited significant positive correlations with crop N uptake, relative crop yield, and sustainable yield index. In conclusion, long-term partial substitution of synthetic N fertilizer with manure facilitates soil OC and TN sequestration in the entire 100 cm profile and thus maintains high crop productivity in upland areas. [ABSTRACT FROM AUTHOR]

Gossypol is a polyphenolic toxic secondary metabolite derived from cotton. Free gossypol in cotton meal is remarkably harmful to animals. Furthermore, microbial degradation of gossypol produces metabolites that reduce feed quality. We adopted an enzymatic method to degrade free gossypol safely and effectively. We cloned the gene cce001a encoding carboxylesterase (CarE) into pPICZαA and transformed it into Pichia pastoris GS115. The target protein was successfully obtained, and CarE CCE001a could effectively degrade free gossypol with a degradation rate of 89%. When esterase was added, the exposed toxic groups of gossypol reacted with different amino acids and amines to form bound gossypol, generating substances with (M + H) m/z ratios of 560.15, 600.25, and 713.46. The molecular formula was C27H28O13, C34H36N2O6, and C47H59N3O3. The observed instability of the hydroxyl groups caused the substitution and shedding of the group, forming a substance with m/z of 488.26 and molecular formula C31H36O5. These properties render the CarE CCE001a a valid candidate for the detoxification of cotton meal. Furthermore, the findings help elucidate the degradation process of gossypol in vitro. [ABSTRACT FROM AUTHOR]

Simple Summary: The monitoring and analysis of sheep behavior can reflect their welfare and health, which is beneficial for grazing management. For automatic classification and the continuous monitoring of grazing sheep behavior, wearable devices based on inertial measurement unit (IMU) sensors are important. The accuracy of different machine learning algorithms was compared, and the best one was used for the continuous monitoring and behavior classification of three grazing sheep on pasture with three different sward surface heights. The results showed that the algorithm automatically monitored the behavior of grazing sheep individuals and quantified the time of each behavior. Behavior classification and recognition of sheep are useful for monitoring their health and productivity. The automatic behavior classification of sheep by using wearable devices based on IMU sensors is becoming more prevalent, but there is little consensus on data processing and classification methods. Most classification accuracy tests are conducted on extracted behavior segments, with only a few trained models applied to continuous behavior segments classification. The aim of this study was to evaluate the performance of multiple combinations of algorithms (extreme learning machine (ELM), AdaBoost, stacking), time windows (3, 5 and 11 s) and sensor data (three-axis accelerometer (T-acc), three-axis gyroscope (T-gyr), and T-acc and T-gyr) for grazing sheep behavior classification on continuous behavior segments. The optimal combination was a stacking model at the 3 s time window using T-acc and T-gyr data, which had an accuracy of 87.8% and a Kappa value of 0.836. It was applied to the behavior classification of three grazing sheep continuously for a total of 67.5 h on pasture with three different sward surface heights (SSH). The results revealed that the three sheep had the longest walking, grazing and resting times on the short, medium and tall SHH, respectively. These findings can be used to support grazing sheep management and the evaluation of production performance. [ABSTRACT FROM AUTHOR]

Simple Summary: Traditionally, farmers are unable to pay enough attention to individual livestock. An increasing number of sensors are being used to monitor animal behavior, early disease detection, and evaluation of animal welfare. In this study, we used machine learning algorithms to identify multiple unitary behaviors and movements of dairy cattle recorded by motion sensors. We also investigated the effect of time window on the performance of unitary behaviors classification and discussed the necessity of movement analysis. This study shows a feasible way to explore more detailed movements based on the result of unitary behaviors classification. Low-cost sensors provide remote monitoring of animal behaviors to help producers comprehensively and accurately identify the health status of individual livestock in real-time. The behavior of livestock on farms is the primary representation of animal welfare, health conditions, and social interactions to determine whether they are healthy or not. The objective of this study was to propose a framework based on inertial measurement unit (IMU) data from 10 dairy cows to classify unitary behaviors such as feeding, standing, lying, ruminating-standing, ruminating-lying, and walking, and identify movements during unitary behaviors. Classification performance was investigated for three machine learning algorithms (K-nearest neighbors (KNN), random forest (RF), and extreme boosting algorithm (XGBoost)) in four time windows (5, 10, 30, and 60 s). Furthermore, feed tossing, rolling biting, and chewing in the correctly classified feeding segments were analyzed by the magnitude of the acceleration. The results revealed that the XGBoost had the highest performance in the 60 s time window with an average F1 score of 94% for the six unitary behavior classes. The F1 score of movements is 78% (feed tossing), 87% (rolling biting), and 87% (chewing). This framework offers a possibility to explore more detailed movements based on the unitary behavior classification. [ABSTRACT FROM AUTHOR]

Individual identification plays an important part in disease prevention and control, traceability of meat products, and improvement of agricultural false insurance claims. Automatic and accurate detection of cattle face is prior to individual identification and facial expression recognition based on image analysis technology. This paper evaluated the possibility of the cutting-edge object detection algorithm, RetinaNet, performing multi-view cattle face detection in housing farms with fluctuating illumination, overlapping, and occlusion. Seven different pretrained CNN models (ResNet 50, ResNet 101, ResNet 152, VGG 16, VGG 19, Densenet 121 and Densenet 169) were fine-tuned by transfer learning and re-trained on the dataset in the paper. Experimental results showed that RetinaNet incorporating the ResNet 50 was superior in accuracy and speed through performance evaluation, which yielded an average precision score of 99.8% and an average processing time of 0.0438 s per image. Compared with the typical competing algorithms, the proposed method was preferable for cattle face detection, especially in particularly challenging scenarios. This research work demonstrated the potential of artificial intelligence towards the incorporation of computer vision systems for individual identification and other animal welfare improvements. [ABSTRACT FROM AUTHOR]

With the overuse of antibiotics, multidrug-resistant bacteria pose a significant threat to human health. Antimicrobial peptides (AMPs) are a promising alternative to conventional antibiotics. This study examines the antimicrobial and membrane activity of HJH-1, a cationic peptide derived from the hemoglobin α-subunit of bovine erythrocytes P3. HJH-1 shows potent antimicrobial activity against different bacterial species associated with infection and causes weaker hemolysis of erythrocytes, at least five times the minimum inhibitory concentration (MIC). HJH-1 has good stability to tolerance temperature, pH value, and ionic strength. The anionic membrane potential probe bis-(1,3-dibutylbarbituric acid) trimethine oxonol [DiBAC4(3)] and propidium iodide are used as indicators of membrane integrity. In the presence of HJH-1 (1× MIC), Escherichiacoli membranes rapidly depolarise, whereas red blood cells show gradual hyperpolarisation. Scanning electron microscopy and transmission electron micrographs show that HJH-1 (1× MIC) damaged the membranes of Escherichia coli, Staphylococcus aureus, and Candida albicans. In conclusion, HJH-1 damages the integrity of the bacterial membrane, preventing the growth of bacteria. HJH-1 has broad-spectrum antibacterial activity, and these activities are performed by changing the normal cell transmembrane potential and disrupting the integrity of the bacterial membrane. [ABSTRACT FROM AUTHOR]

To improve the potassium availability of feldspar at ordinary temperatures, the mechanical grinding and addition of sodium hydroxide/salts were employed to study the effects of mechanical activation and strong alkali addition on particle characteristics, water-soluble potassium, and the available potassium of feldspar. A laser particle size analyzer was utilized for the direct determination of particle size distribution (PSD) using ground samples. The Brunauer-Emmett-Teller (BET) method was employed for specific surface areas. X-ray diffraction (XRD) was employed for structural characterization, scanning electron microscopy (SEM) for morphology exploration, and energy dispersive spectroscopy (EDS) to determine the chemical composition of potassium feldspar powder. The results revealed that the mechanical activation of potassium feldspar could reduce the particle size and produce agglomerated nanoparticles in the later period. The addition of NaOH and sodium salt did not cause agglomeration, and NaOH dissolved the nanoparticles. The water-soluble potassium content of feldspar in each treatment increased during mechanical grinding, from 21.64 mg kg -1 to 1495.81 mg·kg -1 , by adding NaOH 5% weight of potassium feldspar powder and to 3044.08 mg·kg -1 by adding NaOH 10% weight with effects different from those of mechanical shaking. By comparison, only 162.93 mg·kg -1 water-soluble potassium was obtained by adding NaOH 5% weight. The dissolved potassium in the former case was significantly higher than in the latter, and the addition of NaOH and sodium salts significantly enhanced the water-soluble potassium contents due to ion exchange. Furthermore, the addition of sodium hydroxide improved the water-soluble potassium due to its mechanochemical action on potassium feldspar. The mechanical energy changed the crystal structure of potassium feldspar, explaining the increase in available potassium. The addition of sodium salts did not promote change in the feldspar's structure, thereby did not raise the available potassium content. The reason for this was related to the mechanochemical action on sodium hydroxide and feldspar, which could promote the dissolution of fine particles, thereby incrementing the available potassium.

With the overuse of antibiotics, multidrug-resistant bacteria pose a significant threat to human health. Antimicrobial peptides (AMPs) are a promising alternative to conventional antibiotics. This study examines the antimicrobial and membrane activity of HJH-1, a cationic peptide derived from the hemoglobin α-subunit of bovine erythrocytes P3. HJH-1 shows potent antimicrobial activity against different bacterial species associated with infection and causes weaker hemolysis of erythrocytes, at least five times the minimum inhibitory concentration (MIC). HJH-1 has good stability to tolerance temperature, pH value, and ionic strength. The anionic membrane potential probe bis -(1,3-dibutylbarbituric acid) trimethine oxonol [DiBAC₄(3)] and propidium iodide are used as indicators of membrane integrity. In the presence of HJH-1 (1× MIC), Escherichia coli membranes rapidly depolarise, whereas red blood cells show gradual hyperpolarisation. Scanning electron microscopy and transmission electron micrographs show that HJH-1 (1× MIC) damaged the membranes of Escherichia coli , Staphylococcus aureus , and Candida albicans . In conclusion, HJH-1 damages the integrity of the bacterial membrane, preventing the growth of bacteria. HJH-1 has broad-spectrum antibacterial activity, and these activities are performed by changing the normal cell transmembrane potential and disrupting the integrity of the bacterial membrane.

Branched chain amino acids (BCAAs), including leucine (Leu), isoleucine (Ile), and valine (Val), play critical roles in the regulation of energy homeostasis, nutrition metabolism, gut health, immunity and disease in humans and animals. As the most abundant of essential amino acids (EAAs), BCAAs are not only the substrates for synthesis of nitrogenous compounds, they also serve as signaling molecules regulating metabolism of glucose, lipid, and protein synthesis, intestinal health, and immunity via special signaling network, especially phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) signal pathway. Current evidence supports BCAAs and their derivatives as the potential biomarkers of diseases such as insulin resistance (IR), type 2 diabetes mellitus (T2DM), cancer, and cardiovascular diseases (CVDs). These diseases are closely associated with catabolism and balance of BCAAs. Hence, optimizing dietary BCAA levels should have a positive effect on the parameters associated with health and diseases. This review focuses on recent findings of BCAAs in metabolic pathways and regulation, and underlying the relationship of BCAAs to related disease processes., Competing Interests: The authors declare no conflict of interest.