Underestimated Dry Season Methane Emissions from Wetlands in the Pantanal.

Tropical wetlands contribute ∼30% of the global methane (CH4) budget. Limited observational constraints on tropical wetland CH4 emissions lead to large uncertainties and disparities in representing emissions. In this work, we combine remote sensing observations with atmospheric and wetland models to investigate dry season wetland CH4 emissions from the Pantanal region of South America. We incorporate inundation maps generated from the Cyclone Global Navigation Satellite System (CYGNSS) satellite constellation together with traditional inundation maps to generate an ensemble of wetland CH4 emission realizations. We challenge these realizations with daily satellite observations for May-July when wetland CH4 emission predictions diverge. We find that the CYGNSS inundation products predict larger emissions in May, in better agreement with observations. We use the model ensemble to generate an empirical observational constraint on CH4 emissions independent of choice of inundation map, finding large dry season wetland CH4 emissions (31.7 ± 13.6 and 32.0 ± 20.2 mg CH4/m2/day in May and June/July during 2018/2019, respectively). These May/June/July emissions are 2-3 times higher than current models, suggesting that annual wetland emissions may be higher than traditionally simulated. Observed trends in the early dry season indicate that dynamics during this period are of importance in representing tropical wetland CH4 behaviors.

Analysis of Cytological Misdiagnosis and Oversight of Adenoid Cystic Carcinoma of Salivary Gland.

OBJECTIVE: In this article on adenoid cystic carcinoma (ACC) of salivary gland, we intend to summarize the causes of misdiagnosis and oversight of ACC hoping to improve cytological diagnostic accuracy, clinical management and patient treatment. METHODS: The study retrospectively reviewed 32 patients with ACC of salivary gland, registered at the Affiliated Hospital of Southwest Medical University from July 2014 to June 2021. These cases were diagnosed by FNA and surgical excision biopsy. All cytopathological results were retrospectively categorized according to Milan system for reporting salivary gland cytopathology (MSRSGC). The accuracy of FNA was verified by surgical excision biopsy. RESULTS: Of these 32 patients, 16 (50.0%) cases were male, and 16 (50.0%) were female. Their age ranged from 21 to 79 years, with an average age of 50.32 years. The highest incidence (15/32, 46.9%) of ACC was observed in patients between 41 and 50 years of age. 10 cases (31.3%) occurred in the parotid gland, 9 cases (28.1%) in the submandibular gland, 9 cases (28.1%) in the sublingual gland, 3 cases (9.4%) in the palate, and 1 case (3.1%) in the lip. Among the 32 cases of ACC, 23 cases (71.9%) were classified to VI, 4 cases (12.5%) to IVa, and 5 cases (15.6%) to II by MSRSGC. A comparison of the FNA results with biopsy showed that the accuracy of FNA in ACC of salivary gland is 71.9%. Being able to identify the cytomorphological features is the key factor for accurate diagnosis of ACC of the salivary gland. CONCLUSION: Our results confirm that FNA is an important initial screening in the diagnosis of ACC of salivary gland. Increased study of the cytomorphology of ACC is beneficial for more accurate diagnosis of ACC, to reduce misdiagnosis and oversight.

Giant cell tumor of tendon sheath: A report of 216 cases.

BACKGROUND: In this article on giant cell tumor of tendon sheath (GCTTS), we intend to summarize and analyze the clinical and pathological features of GCTTS hoping to improve clinical management and patient treatment. METHODS: The study retrospectively reviewed 216 patients of GCTTS, registered at the Affiliated Hospital of Southwest Medical University from January 2010 to December 2020. These cases were diagnosed by surgical excision. The clinicopathological features and the prognosis were reviewed in the light of the current literature. RESULTS: Of these 216 GCTTS patients, 72 were males (33.3%) and 144 females (66.7%), with a ratio male-to-female of 1:2. The patients' age ranged from 5 to 82, the average being 41.5 years at diagnosis. A total of 96 cases (44.4%) occurred in the hand region, followed by 35 cases (16.2%) in the knee, 32 cases (14.8%) in the foot, 25 cases (11.6%) in the ankle, 12 cases (5.6%) in the wrist, 12 cases (5.6%) in the leg, 2 cases (0.9%) in the head, 1 case (0.5%) in the forearm, and 1 case (0.5%) inside and outside the spinal channel. Histopathology mainly revealed large synovial-like monocytes, small monocytes, and osteoclast-like giant cells. CONCLUSION: Our results confirm that GCTTS predominantly occurs in the hands of young women. Complete surgical resection with long-term follow-up is the preferred management.

A Genome-Wide Association Study of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants.

We performed a genome-wide association study (GWAS) of human extreme longevity (EL), defined as surviving past the 99th survival percentile, by aggregating data from four centenarian studies. The combined data included 2304 EL cases and 5879 controls. The analysis identified a locus in CDKN2B-AS1 (rs6475609, p = 7.13 × 10-8) that almost reached genome-wide significance and four additional loci that were suggestively significant. Among these, a novel rare variant (rs145265196) on chromosome 11 had much higher longevity allele frequencies in cases of Ashkenazi Jewish and Southern Italian ancestry compared to cases of other European ancestries. We also correlated EL-associated SNPs with serum proteins to link our findings to potential biological mechanisms that may be related to EL and are under genetic regulation. The findings from the proteomic analyses suggested that longevity-promoting alleles of significant genetic variants either provided EL cases with more youthful molecular profiles compared to controls or provided some form of protection from other illnesses, such as Alzheimer's disease, and disease progressions.

Effect of Ozone, Clothing, Temperature, and Humidity on the Total OH Reactivity Emitted from Humans.

People influence indoor air chemistry through their chemical emissions via breath and skin. Previous studies showed that direct measurement of total OH reactivity of human emissions matched that calculated from parallel measurements of volatile organic compounds (VOCs) from breath, skin, and the whole body. In this study, we determined, with direct measurements from two independent groups of four adult volunteers, the effect of indoor temperature and humidity, clothing coverage (amount of exposed skin), and indoor ozone concentration on the total OH reactivity of gaseous human emissions. The results show that the measured concentrations of VOCs and ammonia adequately account for the measured total OH reactivity. The total OH reactivity of human emissions was primarily affected by ozone reactions with organic skin-oil constituents and increased with exposed skin surface, higher temperature, and higher humidity. Humans emitted a comparable total mixing ratio of VOCs and ammonia at elevated temperature-low humidity and elevated temperature-high humidity, with relatively low diversity in chemical classes. In contrast, the total OH reactivity increased with higher temperature and higher humidity, with a larger diversity in chemical classes compared to the total mixing ratio. Ozone present, carbonyl compounds were the dominant reactive compounds in all of the reported conditions.

Total OH Reactivity of Emissions from Humans: In Situ Measurement and Budget Analysis.

Humans are a potent, mobile source of various volatile organic compounds (VOCs) in indoor environments. Such direct anthropogenic emissions are gaining importance, as those from furnishings and building materials have become better regulated and energy efficient homes may reduce ventilation. While previous studies have characterized human emissions in indoor environments, the question remains whether VOCs remain unidentified by current measuring techniques. In this study conducted in a climate chamber occupied by four people, the total OH reactivity of air was quantified, together with multiple VOCs measured by proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) and fast gas chromatography-mass spectrometry (fast-GC-MS). Whole-body, breath, and dermal emissions were assessed. The comparison of directly measured OH reactivity and that of the summed reactivity of individually measured species revealed no significant shortfall. Ozone exposure (37 ppb) was found to have little influence on breath OH reactivity but enhanced dermal OH reactivity significantly. Without ozone, the whole-body OH reactivity was dominated by breath emissions, mostly isoprene (76%). With ozone present, OH reactivity nearly doubled, with the increase being mainly caused by dermal emissions of mostly carbonyl compounds (57%). No significant difference in total OH reactivity was observed for different age groups (teenagers/young adults/seniors) without ozone. With ozone present, the total OH reactivity decreased slightly with increasing age.

Ozone Initiates Human-Derived Emission of Nanocluster Aerosols.

Nanocluster aerosols (NCAs, particles <3 nm) are important players in driving climate feedbacks and processes that impact human health. This study reports, for the first time, NCA formation when gas-phase ozone reacts with human surfaces. In an occupied climate-controlled chamber, we detected NCA only when ozone was present. NCA emissions were dependent on clothing coverage, occupant age, air temperature, and humidity. Ozone-initiated chemistry with human skin lipids (particularly their primary surface reaction products) is the key mechanism driving NCA emissions, as evidenced by positive correlations with squalene in human skin wipe samples and known gaseous products from ozonolysis of skin lipids. Oxidation by OH radicals, autoxidation reactions, and human-emitted NH3 may also play a role in NCA formation. Such chemical processes are anticipated to generate aerosols of the smallest size (1.18-1.55 nm), whereas larger clusters result from subsequent growth of the smaller aerosols. This study shows that whenever we encounter ozone indoors, where we spend most of our lives, NCAs will be produced in the air around us.

[Realization of non-invasive blood glucose detector based on nonlinear auto regressive model and dual-wavelength].

The use of non-invasive blood glucose detection techniques can help diabetic patients to alleviate the pain of intrusive detection, reduce the cost of detection, and achieve real-time monitoring and effective control of blood glucose. Given the existing limitations of the minimally invasive or invasive blood glucose detection methods, such as low detection accuracy, high cost and complex operation, and the laser source's wavelength and cost, this paper, based on the non-invasive blood glucose detector developed by the research group, designs a non-invasive blood glucose detection method. It is founded on dual-wavelength near-infrared light diffuse reflection by using the 1 550 nm near-infrared light as measuring light to collect blood glucose information and the 1 310 nm near-infrared light as reference light to remove the effects of water molecules in the blood. Fourteen volunteers were recruited for in vivo experiments using the instrument to verify the effectiveness of the method. The results indicated that 90.27% of the measured values of non-invasive blood glucose were distributed in the region A of Clarke error grid and 9.73% in the region B of Clarke error grid, all meeting clinical requirements. It is also confirmed that the proposed non-invasive blood glucose detection method realizes relatively ideal measurement accuracy and stability.

Human Ammonia Emission Rates under Various Indoor Environmental Conditions.

Ammonia (NH3) is typically present at higher concentrations in indoor air (∼10-70 ppb) than in outdoor air (∼50 ppt to 5 ppb). It is the dominant neutralizer of acidic species in indoor environments, strongly influencing the partitioning of gaseous acidic and basic species to aerosols, surface films, and bulk water. We have measured NH3 emissions from humans in an environmentally controlled chamber. A series of experiments, each with four volunteers, quantified NH3 emissions as a function of temperature (25.1-32.6 °C), clothing (long-sleeved shirts/pants or T-shirts/shorts), age (teenagers, adults, and seniors), relative humidity (low or high), and ozone (<2 ppb or ∼35 ppb). Higher temperature and more skin exposure (T-shirts/shorts) significantly increased emission rates. For adults and seniors (long clothing), NH3 emissions are estimated to be 0.4 mg h-1 person-1 at 25 °C, 0.8 mg h-1 person-1 at 27 °C, and 1.4 mg h-1 person-1 at 29 °C, based on the temperature relationship observed in this study. Human NH3 emissions are sufficient to neutralize the acidifying impacts of human CO2 emissions. Results from this study can be used to more accurately model indoor and inner-city outdoor NH3 concentrations and associated chemistry.

The Indoor Chemical Human Emissions and Reactivity (ICHEAR) project: Overview of experimental methodology and preliminary results.

With the gradual reduction of emissions from building products, emissions from human occupants become more dominant indoors. The impact of human emissions on indoor air quality is inadequately understood. The aim of the Indoor Chemical Human Emissions and Reactivity (ICHEAR) project was to examine the impact on indoor air chemistry of whole-body, exhaled, and dermally emitted human bioeffluents under different conditions comprising human factors (t-shirts/shorts vs long-sleeve shirts/pants; age: teenagers, young adults, and seniors) and a variety of environmental factors (moderate vs high air temperature; low vs high relative humidity; presence vs absence of ozone). A series of human subject experiments were performed in a well-controlled stainless steel climate chamber. State-of-the-art measurement technologies were used to quantify the volatile organic compounds emitted by humans and their total OH reactivity; ammonia, nanoparticle, fluorescent biological aerosol particle (FBAP), and microbial emissions; and skin surface chemistry. This paper presents the design of the project, its methodologies, and preliminary results, comparing identical measurements performed with five groups, each composed of 4 volunteers (2 males and 2 females). The volunteers wore identical laundered new clothes and were asked to use the same set of fragrance-free personal care products. They occupied the ozone-free (<2 ppb) chamber for 3 hours (morning) and then left for a 10-min lunch break. Ozone (target concentration in occupied chamber ~35 ppb) was introduced 10 minutes after the volunteers returned to the chamber, and the measurements continued for another 2.5 hours. Under a given ozone condition, relatively small differences were observed in the steady-state concentrations of geranyl acetone, 6MHO, and 4OPA between the five groups. Larger variability was observed for acetone and isoprene. The absence or presence of ozone significantly influenced the steady-state concentrations of acetone, geranyl acetone, 6MHO, and 4OPA. Results of replicate experiments demonstrate the robustness of the experiments. Higher repeatability was achieved for dermally emitted compounds and their reaction products than for constituents of exhaled breath.

Elevated S100A4 in asthmatics and an allergen-induced mouse asthma model.

The elevated S100A4 level has been found in some inflammatory diseases. However, the expression and role of S100A4 in asthma is unknown. The expression of S100A4 in induced sputum and plasma from healthy control and asthmatics were assessed by ELISA. Then an allergen-induced asthma mouse model treatment with anti-S100A4 antibody was used to explore the role of S100A4 in the pathogenesis of asthma. The S100A4 levels in sputum not in plasma in asthmatics were significantly increased than those of healthy controls and were negatively correlated with some lung function parameters and were positively correlated with sputum eosinophilia and lymphocyte. The expression of S100A4 in the lung as well as in BALF were also significantly higher in the asthma mouse model and treatment with anti-S100A4 antibody exhibited reductions in inflammatory cell accumulation, inflammatory mediators, and airway hyper-responsiveness. We further showed that LY294002, a specific inhibitor of PI3K, markedly decreased S100A4 expression in lung and S100A4 secretion in BALF in asthmatic mice. In conclusion, these data demonstrated that S100A4 may be involved in the pathogenesis of airway inflammation in asthma.

Tracking the dynamic functional connectivity structure of the human brain across the adult lifespan.

The transition from early adulthood to the elder is marked by functional and structural brain transformations. Many previous studies examined the correlation between the functional connectivity (FC) and aging using resting-state fMRI. Results showed that the changes in FC are linked to aging as well as the cognitive ability changes. However, some researchers proposed that the FC is not static but dynamic changes during the resting-state fMRI scan. In this study, we examined the correlation between the resting-state dynamic functional network connectivity and age using resting scan data of 434 subjects. The results suggested: (a) age is negatively associated with variability of dynamic functional network connectivity state; (b) the dwell time of each age range spends in each state is different; (c) the dynamic graph metrics curve of each age ranges is different and 19-30 age range has the largest average global efficiency and average local efficiency; (d) some dynamic functional network connectivity measures were correlated to the certain cognitive ability. Overall, the results suggested the changes in dynamic functional network connectivity measures may be a characteristic of the aging process and in further investigations may provide a deep understanding of the aging process.

Non-Invasive Continuous Blood-Pressure Monitoring Models Based on Photoplethysmography and Electrocardiography.

Blood pressure is an extremely important blood hemodynamic parameter. The pulse wave contains abundant blood-pressure information, and the convenience and non-invasivity of its measurement make it ideal for non-invasive continuous monitoring of blood pressure. Based on combined photoplethysmography and electrocardiogram signals, this study aimed to extract the waveform information, introduce individual characteristics, and construct systolic and diastolic blood-pressure (SBP and DBP) estimation models using the back-propagation error (BP) neural network. During the model construction process, the mean impact value method was employed to investigate the impact of each feature on the model output and reduce feature redundancy. Moreover, the multiple population genetic algorithm was applied to optimize the BP neural network and determine the initial weights and threshold of the network. Finally, the models were integrated for further optimization to generate the final individualized continuous blood-pressure monitoring models. The results showed that the predicted values of the model in this study correlated significantly with the measured values of the electronic sphygmomanometer. The estimation errors of the model met the Association for the Advancement of Medical Instrumentation (AAMI) criteria (the SBP error was 2.5909 ± 3.4148 mmHg, and the DBP error was 2.6890 ± 3.3117 mmHg) and the Grade A British Hypertension Society criteria.

yQTL Pipeline: A structured computational workflow for large scale quantitative trait loci discovery and downstream visualization.

Quantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. To facilitate and automate large-scale QTL analysis, we developed the yQTL Pipeline, where the 'y' indicates the dependent quantitative variable being modeled. Prior to the association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. The options to run an ANOVA model or testing the interaction with a covariate are also available. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. It can generate Manhattan and Miami plots of phenotype traits, genotype-phenotype boxplots, and trait-QTL connection networks. We applied the yQTL Pipeline to analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ~90 min to ~26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. The yQTL Pipeline is available with documentation on GitHub at https://github.com/montilab/yQTLpipeline.

Risk and mechanisms of phosphorus release at the sediment-water interface of lakes in cold and arid regions during non-frozen seasons.

In recent years, the eutrophication of lakes has accelerated in cold arid regions; the release of nutrients from sediments is an important contributor. The sequential extraction method, high-resolution peeper (HR-Peeper), and diffusive gradients in thin films (DGT) techniques were used to study the occurrence characteristics, release risk, and release mechanism of phosphorus (P) at the sediment-water interface (SWI) of Ulanor Wetland in the Hulun Lake Basin, Inner Mongolia, China. The mean total P concentration in overlying water was lower in August than that in May. Dissolved organic P (DOP) or particulate P (PP) was the main form of P in the overlying water. PP dominates in May and DOP in August. Refractory P was the main form of P in sediments. The concentrations of soluble reactive P and DGT-active P in the pore water of the sediment column were higher than those in the overlying water, and the concentrations were higher in August than those in May. Release of P in the wetland sediments occurred during the non-frozen seasons, with a higher risk in August than in May. The good linear correlation between dissolved P, Fe, and Mn in the DGT profiles verified their co-release due to the anaerobic reduction of Fe/Mn oxides. Moreover, alkaline sediments are also conducive to the release of sediment P. This study can provide data and theoretical support for eutrophication control in Ulanor Wetland and other similar water bodies in cold and arid regions.

yQTL Pipeline: a structured computational workflow for large scale quantitative trait loci discovery and downstream visualization.

Quantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. In order to facilitate and automate large-scale QTL analysis, we developed the yQTL Pipeline, where the 'y' indicates the dependent quantitative variable being modeled. Prior to genome-wide association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. Upon uploading the result file, it can generate Manhattan plots of user-selected phenotype traits and trait-QTL connection networks based on user-specified p-value thresholds. We applied the yQTL Pipeline to analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs cumulatively associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ~90 min to ~26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. The yQTL Pipeline is available with documentation on GitHub at https://github.com/montilab/yQTL-Pipeline.

Balance recovery for lower limb exoskeleton in standing posture based on orbit energy analysis.

Introduction: The need for effective balance control in lower limb rehabilitation exoskeletons is critical for ensuring stability and safety during rehabilitation training. Current research into specialized balance recovery strategies is limited, highlighting a gap in biomechanics-inspired control methods. Methods: We introduce a new metric called "Orbit Energy" (OE), which assesses the balance state of the human-exoskeleton system based on the dynamics of the overall center of mass. Our control framework utilizes OE to choose appropriate balance recovery strategies, including torque controls at the ankle and hip joints. Results: The efficacy of our control algorithm was confirmed through Matlab Simulink simulations, which analyzed the recovery of balance under various disturbance forces and conditions. Further validation came from physical experiments with human subjects wearing the exoskeleton, where a significant reduction in muscle activation was observed during balance maintenance under external disturbances. Discussion: Our findings underscore the potential of biomechanics-inspired metrics like OE in enhancing exoskeleton functionality for rehabilitation purposes. The introduction of such metrics could lead to more targeted and effective balance recovery strategies, ultimately improving the safety and stability of exoskeleton use in rehabilitation settings.

Bidirectional two-sample Mendelian randomization analysis identifies causal associations between cardiovascular diseases and frozen shoulder.

BACKGROUND: Although prior observational studies indicate an association between cardiovascular diseases (CVDs) and frozen shoulder (FS), the potential causal relationship between them remains uncertain. This study aims to explore the genetic causal relationship between CVDs and FS using Mendelian randomization (MR). METHODS: Genetic variations closely associated with FS were obtained from the FinnGen Consortium. Summary data for CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), myocardial infarction (MI), stroke, and ischemic stroke (IS), were sourced from several large-scale genome-wide association studies (GWAS). MR analysis was performed using inverse variance weighting (IVW), MR Egger, and weighted median methods. IVW, as the primary MR analysis method, complemented by other sensitivity analyses, was utilized to validate the robustness of the results. Further reverse MR analysis was conducted to explore the presence of reverse causal relationships. RESULTS: In the forward MR analysis, genetically determined risk of stroke and IS was positively associated with FS (OR [95% CI] = 1.58 (1.23-2.03), P < 0.01; OR [95% CI] = 1.46 (1.16-1.85), P < 0.01, respectively). There was no strong evidence of an effect of genetically predicted other CVDs on FS risk. Sensitivity analyses confirmed the robustness of the results. In the reverse MR analysis, no causal relationships were observed between FS and various CVDs. CONCLUSION: The study suggests that stroke increases the risk of developing FS. However, further basic and clinical research is needed to substantiate our findings.

L-Histidine attenuates NEFA-induced inflammatory responses by suppressing Gab2 expression.

Non-esterified fatty acids (NEFAs), key to energy metabolism, may become pathogenic at elevated levels, potentially eliciting immune reactions. Our laboratory's findings of reduced L-histidine in ketotic states, induced by heightened NEFA concentrations, suggest an interrelation with NEFA metabolism. This observation necessitates further investigation into the mitigating role of L-histidine on the deleterious effects of NEFAs. Our study unveiled that elevated NEFA concentrations hinder the proliferation of Bovine Mammary Epithelial Cells (BMECs) and provoke inflammation in a dose-responsive manner. Delving into L-histidine's influence on BMECs, RNA sequencing revealed 2124 genes differentially expressed between control and L-histidine-treated cells, with notable enrichment in pathways linked to proliferation and immunity, such as cell cycle and TNF signaling pathways. Further analysis showed that L-histidine treatment positively correlated with an increase in EdU-555-positive cell rate and significantly suppressed IL-6 and IL-8 levels (p < 0.05) compared to controls. Crucially, concurrent treatment with high NEFA and L-histidine normalized the number of EdU-555-positive cells and cytokine expression to control levels. Investigating the underlying mechanisms, Gab2 (Grb2-associated binder 2) emerged as a central player; L-histidine notably reduced Gab2 expression, while NEFA had the opposite effect (p < 0.05). Gab2 overexpression escalated nitric oxide (NO) production and IL6 and IL8 expression. However, L-histidine addition to Gab2-overexpressing cells resulted in NO concentrations indistinguishable from controls. Our findings collectively indicate that L-histidine can counteract NEFA-induced inflammation in BMECs by inhibiting Gab2 expression, highlighting its therapeutic potential against NEFA-related metabolic disturbances.

Comparative Metabolomic Profiling of L-Histidine and NEFA Treatments in Bovine Mammary Epithelial Cells.

Non-esterified fatty acids (NEFAs) are pivotal in energy metabolism, yet high concentrations can lead to ketosis, a common metabolic disorder in cattle. Our laboratory observed lower levels of L-histidine in cattle suffering from ketosis, indicating a potential interaction between L-histidine and NEFA metabolism. This relationship prompted us to investigate the metabolomic alterations in bovine mammary epithelial cells (BMECs) induced by elevated NEFA levels and to explore L-histidine's potential mitigating effects. Our untargeted metabolomic analysis revealed 893 and 160 metabolite changes in positive and negative models, respectively, with VIP scores greater than 1 and p-values below 0.05. Notable metabolites like 9,10-epoxy-12-octadecenoic acid were upregulated, while 9-Ethylguanine was downregulated. A pathway analysis suggested disruptions in fatty acid and steroid biosynthesis pathways. Furthermore, L-histidine treatment altered 61 metabolites in the positive model and 34 in the negative model, with implications for similar pathways affected by NEFA. Overlaying differential metabolites from both conditions uncovered a potential key mediator, 1-Linoleoylglycerophosphocholine, which was regulated in opposite directions by NEFA and L-histidine. Our study uncovered that both NEFA L- and histidine metabolomics analyses pinpoint similar lipid biosynthesis pathways, with 1-Linoleoylglycerophosphocholine emerging as a potential key metabolite mediating their interaction, a discovery that may offer insights for therapeutic strategies in metabolic diseases.