Small extracellular vesicles derived from cerebral endothelial cells with elevated microRNA 27a promote ischemic stroke recovery

Axonal remodeling is a critical aspect of ischemic brain repair processes and contributes to spontaneous functional recovery.Our previous in vitro study demonstrated that exosomes/small extracellular vesicles(sEVs)isolated from cerebral endothelial cells(CEC-sEVs)of ischemic brain promote axonal growth of embryonic cortical neurons and that microRNA 27a(miR-27a)is an elevated miRNA in ischemic CEC-sEVs.In the present study,we investigated whether normal CEC-sEVs engineered to enrich their levels of miR-27a(27a-sEVs)further enhance axonal growth and improve neurological outcomes after ischemic stroke when compared with treatment with non-engineered CEC-sEVs.27a-sEVs were isolated from the conditioned medium of healthy mouse CECs transfected with a lentiviral miR-27a expression vector.Small EVs isolated from CECs transfected with a scramble vector(Scra-sEVs)were used as a control.Adult male mice were subjected to permanent middle cerebral artery occlusion and then were randomly treated with 27a-sEVs or Scra-sEVs.An array of behavior assays was used to measure neurological function.Compared with treatment of ischemic stroke with Scra-sEVs,treatment with 27a-sEVs significantly augmented axons and spines in the peri-infarct zone and in the corticospinal tract of the spinal grey matter of the denervated side,and significantly improved neurological outcomes.In vitro studies demonstrated that CEC-sEVs carrying reduced miR-27a abolished 27a-sEV-augmented axonal growth.Ultrastructural analysis revealed that 27a-sEVs systemically administered preferentially localized to the pre-synaptic active zone,while quantitative reverse transcription-polymerase chain reaction and Western Blot analysis showed elevated miR-27a,and reduced axonal inhibitory proteins Semaphorin 6A and Ras Homolog Family Member A in the peri-infarct zone.Blockage of the Clathrin-dependent endocytosis pathway substantially reduced neuronal internalization of 27a-sEVs.Our data provide evidence that 27a-sEVs have a therapeutic effect on stroke recovery by promoting axonal remodeling and improving neurological outcomes.Our findings also suggest that suppression of axonal inhibitory proteins such as Semaphorin 6A may contribute to the beneficial effect of 27a-sEVs on axonal remodeling.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Ultra-large aluminum shape casting:Opportunities and challenges

Ultra-large aluminum shape castings have been increasingly used in automotive vehicles,particularly in electric vehicles for light-weighting and vehicle manufacturing cost reduction.As most of them are structural components subject to both quasi-static,dynamic and cyclic loading,the quality and quantifiable performance of the ultra-large aluminum shape castings is critical to their success in both design and manufacturing.This paper briefly reviews some application examples of ultra-large aluminum castings in automotive industry and outlines their advantages and benefits.Factors affecting quality,microstructure and mechanical properties of ultra-large aluminum castings are evaluated and discussed as aluminum shape casting processing is very complex and often involves many competing mechanisms,multi-physics phenomena,and potentially large uncertainties that significantly influence the casting quality and performance.Metallurgical analysis and mechanical property assessment of an ultra-large aluminum shape casting are presented.Challenges are highlighted and suggestions are made for robust design and manufacturing of ultra-large aluminum castings.

MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.

Impact of an oligosaccharide-based polymer on the metabolic profiles and microbial ecology of weanling pigs experimentally infected with a pathogenic E.coli

Background Our previous study has reported that supplementation of oligosaccharide-based polymer enhances gut health and disease resistance of pigs infected with enterotoxigenic E.coli(ETEC)F18 in a manner similar to carbadox.The objective of this study was to investigate the impacts of oligosaccharide-based polymer or antibiotic on the host metabolic profiles and colon microbiota of weaned pigs experimentally infected with ETEC F18.Results Multivariate analysis highlighted the differences in the metabolic profiles of serum and colon digesta which were predominantly found between pigs supplemented with oligosaccharide-based polymer and antibiotic.The relative abundance of metabolic markers of immune responses and nutrient metabolisms,such as amino acids and carbohydrates,were significantly differentiated between the oligosaccharide-based polymer and antibiotic groups(q<0.2 and fold change>2.0).In addition,pigs in antibiotic had a reduced(P<0.05)relative abundance of Lachnospiraceae and Lactobacillaceae,whereas had greater(P<0.05)Clostridiaceae and Streptococcaceae in the colon digesta on d 11 post-inoculation(PI)compared with d 5 PI.Conclusions The impact of oligosaccharide-based polymer on the metabolic and microbial profiles of pigs is not fully understood,and further exploration is needed.However,current research suggest that various mechanisms are involved in the enhanced disease resistance and performance in ETEC-challenged pigs by supplementing this polymer.

Elimination, Kinetics and Thermodynamics of Fe(II) Ions by Adsorption in Static and Dynamic Conditions on Activated Carbons in Aqueous Media

This work investigated the removal, kinetics and thermodynamics of iron(II) ions (Fe(II)) by adsorption in static and dynamic conditions in aqueous media on activated carbons (AC-i30min, AC-i1h, and AC-i24h), prepared from palm nut shells collected in the city of Franceville to Gabon, using potassium hydroxide (KOH) as the activating agent. Results on the elimination of Fe(II) in static and dynamic adsorption on prepared activated carbons (ACs) showed that the AC-i24h adsorbent has the best Fe(II) adsorption capacities at saturation (Qsat). The Qsat obtained on AC-i24h in static and dynamic conditions (17.87 and 10.38 mg/g, respectively) were higher than those of AC-i30min (13.89 and 5.54 mg/g respectively) and AC-i1h (14.92 and 8.64 mg/g respectively). Moreover, the static adsorption was more effective in the removal of Fe(II) ions in aqueous media in our experimental conditions. The percentage removal (%E) of Fe(II) obtained on prepared activated carbons in static conditions was better than those obtained in dynamic conditions, especially on AC-i24h, where the %E was 89.27% in static and 61.56% in dynamic. In kinetics, results showed that the pseudo-second-order kinetic model best described the adsorption mechanisms of Fe(II) on prepared activated carbons in static adsorption, with mainly of chemisorption on the solid surfaces. However, in dynamic conditions, the pseudo-first-order kinetic model was more suitable. In addition to the weak interactions between Fe(II) and the activated carbon surfaces, strong interactions (chemisorption) were also observed. Also, thermodynamic data obtained on AC-i24h in static adsorption indicated that the adsorption of Fe(II) was spontaneous and increased with temperature (ΔG˚ H˚ = 503.54 KJ/mol).

Impact of index admission cholecystectomy vs interval cholecystectomy on readmission rate in acute cholangitis: National Readmission Database survey

BACKGROUND Elective cholecystectomy(CCY)is recommended for patients with gallstone-related acute cholangitis(AC)following endoscopic decompression to prevent recurrent biliary events.However,the optimal timing and implications of CCY remain unclear.AIM To examine the impact of same-admission CCY compared to interval CCY on patients with gallstone-related AC using the National Readmission Database(NRD).METHODS We queried the NRD to identify all gallstone-related AC hospitalizations in adult patients with and without the same admission CCY between 2016 and 2020.Our primary outcome was all-cause 30-d readmission rates,and secondary outcomes included in-hospital mortality,length of stay(LOS),and hospitalization cost.RESULTS Among the 124964 gallstone-related AC hospitalizations,only 14.67%underwent the same admission CCY.The all-cause 30-d readmissions in the same admission CCY group were almost half that of the non-CCY group(5.56%vs 11.50%).Patients in the same admission CCY group had a longer mean LOS and higher hospitalization costs attrib-utable to surgery.Although the most common reason for readmission was sepsis in both groups,the second most common reason was AC in the interval CCY group.CONCLUSION Our study suggests that patients with gallstone-related AC who do not undergo the same admission CCY have twice the risk of readmission compared to those who undergo CCY during the same admission.These readmis-sions can potentially be prevented by performing same-admission CCY in appropriate patients,which may reduce subsequent hospitalization costs secondary to readmissions.

Warm forming behavior of high strength aluminum alloy AA7075

The formability of aluminum alloy AA7075 at elevated temperature was investigated through experiment. Stress-strain relationship at different temperatures and forming speeds were investigated through tensile testing. Deep drawing and stretch formability were also tested through limiting drawing ratio （LDR） and limiting dome height （LDH） tests. Finally, post forming mechanical property testing was conducted to investigate the effects of exposure to warm forming temperatures on the mechanical properties. Results show that deep drawing and stretch formability of AA7075 can be significantly improved when the blank is heated to 140-220 °C. At temperature over 260 °C, formability and post forming mechanical properties begin to decrease due to the effect of the heating and forming processes on the material＇s temper.

Dendroclimatological study of Sabina saltuaria and Abies faxoniana in the mixed forests of the Qionglai Mountains,eastern Tibetan Plateau

Tree-ring chronologies were developed for Sabina saltuaria and Abies faxoniana in mixed forests in the Qionglai Mountains of the eastern Tibetan Plateau.Climate-growth relationship analysis indicated that the two co-exist-ing species reponded similarly to climate factors,although S.saltuaria was more sensitive than A.faxoniana.The strong-est correlation was between S.saltuaria chronology and regional mean temperatures from June to November.Based on this relationship,a regional mean temperature from June to November for the period 1605-2016 was constructed.Reconstruction explained 37.3%of the temperature variance during th period 1961-2016.Six major warm periods and five major cold periods were identified.Spectral analysis detected significant interannual and multi-decadal cycles.Reconstruction also revealed the influence of the Atlantic Multi-decadal Oscillation,confirming its importance on climate change on the eastern Tibetan Plateau.

Bound-Preserving Discontinuous Galerkin Methods with Modified Patankar Time Integrations for Chemical Reacting Flows

In this paper,we develop bound-preserving discontinuous Galerkin(DG)methods for chemical reactive flows.There are several difficulties in constructing suitable numerical schemes.First of all,the density and internal energy are positive,and the mass fraction of each species is between 0 and 1.Second,due to the rapid reaction rate,the system may contain stiff sources,and the strong-stability-preserving explicit Runge-Kutta method may result in limited time-step sizes.To obtain physically relevant numerical approximations,we apply the bound-preserving technique to the DG methods.Though traditional positivity-preserving techniques can successfully yield positive density,internal energy,and mass fractions,they may not enforce the upper bound 1 of the mass fractions.To solve this problem,we need to(i)make sure the numerical fluxes in the equations of the mass fractions are consistent with that in the equation of the density;(ii)choose conservative time integrations,such that the summation of the mass fractions is preserved.With the above two conditions,the positive mass fractions have summation 1,and then,they are all between 0 and 1.For time discretization,we apply the modified Runge-Kutta/multi-step Patankar methods,which are explicit for the flux while implicit for the source.Such methods can handle stiff sources with relatively large time steps,preserve the positivity of the target variables,and keep the summation of the mass fractions to be 1.Finally,it is not straightforward to combine the bound-preserving DG methods and the Patankar time integrations.The positivity-preserving technique for DG methods requires positive numerical approximations at the cell interfaces,while Patankar methods can keep the positivity of the pre-selected point values of the target variables.To match the degree of freedom,we use polynomials on rectangular meshes for problems in two space dimensions.To evolve in time,we first read the polynomials at the Gaussian points.Then,suitable slope limiters can be applied to enforce the positivity of the solutions at those points,which can be preserved by the Patankar methods,leading to positive updated numerical cell averages.In addition,we use another slope limiter to get positive solutions used for the bound-preserving technique for the flux.Numerical examples are given to demonstrate the good performance of the proposed schemes.

April-September minimum temperature reconstruction based on Sabina tibetica ring-width chronology in the central eastern Tibetan Plateau,China

Minimum temperatures have remarkable impacts on tree growth at high-elevation sites on the Tibetan Plateau,but the shortage of long-term and high-resolution paleoclimate records inhibits understanding of recent minimum temperature anomalies.In this study,a warm season(April–September)reconstruction is presented for the past 467 years(1550–2016)based on Sabina tibetica ring-width chronology on the Lianbaoyeze Mountain of the central eastern Tibetan Plateau.Eight warm periods and eight cold periods were identified.Long-term minimum temperature variations revealed a high degree of coherence with nearby reconstructions.Spatial correlations between our reconstruction and global sea surface temperatures suggest that warm season minimum temperature anomalies in the central eastern Tibetan Plateau were strongly influenced by large-scale ocean atmospheric circulations,such as the El Ni?o-Southern Oscillation and the Atlantic Multidecadal Oscillation.

Soil Carbon Pool as Influenced by Soil Microbial Activity—An Overview

Soil is a significant carbon reservoir with the capacity to store carbon twice as much as the atmosphere or plants. Given the significant potential of soil to capture and store atmospheric CO2, it presents a viable solution for mitigating the present and future impacts of climate change. However, due to its high susceptibility to global environmental issues like land degradation, loss of biodiversity, and climate change, monitoring and protecting soil carbon pools is a complex challenge. Intensive agricultural operations have detrimental effects on the soil, including the rapid breakdown of soil organic carbon, which releases excess carbon into the air, causing increased atmospheric CO2 levels and a depletion of the soil carbon reserves. The diversity and abundance of soil microbial communities play a crucial role in controlling essential ecosystem processes, including the decomposition of organic matter and nutrient cycling, including carbon. Heterotrophic soil microorganisms facilitate the soil organic matter turnover to obtain the nutrients and energy required for their growth and maintenance. Therefore, the microbial residues and exudates have up to 80% carbon in the stable soil organic matter fractions. This overview attempts to summarize the information on various carbon pools, soil carbon interaction with microbes, impacts on environmental changes, and strategies to enhance the storage of belowground carbon.

Three Dimensional Optimum Node Localization in Dynamic Wireless Sensor Networks

Location information plays an important role in most of the applications in Wireless Sensor Network(WSN).Recently,many localization techniques have been proposed,while most of these deals with two Dimensional applications.Whereas,in Three Dimensional applications the task is complex and there are large variations in the altitude levels.In these 3D environments,the sensors are placed in mountains for tracking and deployed in air for monitoring pollution level.For such applications,2D localization models are not reliable.Due to this,the design of 3D localization systems in WSNs faces new challenges.In this paper,in order to find unknown nodes in Three-Dimensional environment,only single anchor node is used.In the simulation-based environment,the nodes with unknown locations are moving at middle&lower layers whereas the top layer is equipped with single anchor node.A novel soft computing technique namely Adaptive Plant Propagation Algorithm(APPA)is introduced to obtain the optimized locations of these mobile nodes.Thesemobile target nodes are heterogeneous and deployed in an anisotropic environment having an Irregularity(Degree of Irregularity(DOI))value set to 0.01.The simulation results present that proposed APPAalgorithm outperforms as tested among other meta-heuristic optimization techniques in terms of localization error,computational time,and the located sensor nodes.

Growth Inhibition of Escherichia coli and Staphylococcus epidermidis from Various Types of Honey

Honey has long been considered a wound treatment used to keep cuts and other epidermal injuries clean. This study tested that claim by comparing manuka honey used in medicine today, local unprocessed honey taken straight from a hive, and pasteurized honey found at a store, on strains of E. coli and S. epidermidis. The study evaluated the effects these honeys had on bacterial growth to determine which had the greatest inhibition of bacterial growth. To determine this, plates streaked with strains of E. coli or S. epidermidis bacteria and agar wells filled with one of the honeys were incubated and subsequently the diameter of the zone of inhibition was measured. After 20 trials using each honey and bacteria type, manuka and unprocessed were shown to have a statistically significant advantage over the pasteurized honey at inhibiting the growth of E. coli and S. epidermidis, though it was variable whether manuka had an advantage over the unprocessed honey.

Preparation and Characterization of Activated Carbons from Palm Nut Shells: Effects of Calcination Temperature on Porosity and Chemical Properties

Activated carbons (ACs) calcined at 400˚C, 500˚C, and 600˚C (AC-400, AC-500, and AC-600) were prepared using palm nut shells from Gabon as raw material and zinc chloride (ZnCl2) as a chemical activating agent. Prepared ACs were characterized by physisorption of nitrogen (N2), determination of diode and methylene blue numbers for studies of porosity and by quantification and determination of surface functional groups and pH at point of zero charge (pHpzc) respectively, for studies of chemical properties of prepared ACs. Then, effects of calcination temperature (Tcal) on porosity and chemical properties of prepared ACs were studied. The results obtained showed that when the calcination temperature increases from 500˚C to 600˚C, the porosity and chemical properties of prepared ACs are modified. Indeed, the methylene blue and iodine numbers determined for activated carbons AC-400 (460 and 7.94 mg·g−1, respectively) and AC-500 (680 and 8.90 mg·g−1, respectively) are higher than those obtained for AC-600 (360 and 5.75 mg·g−1, respectively). Compared to the AC-500 adsorbent, specific surface areas (SBET) and microporous volume losses for AC-600 were estimated to 44.7% and 45.8%, respectively. Moreover, in our experimental conditions, the effect of Tcal on the quantities of acidic and basic functional groups on the surface of the ACs appears negligible. In addition, results of the pHpzc of prepared ACs showed that as Tcal increases, the pH of the adsorbents increases and tends towards neutrality. Indeed, a stronger acidity was determined on AC-400 (pHpzc = 5.60) compared to those on AC-500 and AC-600 (pHpzc = 6.85 and 6.70, respectively). Also according to the results of porosity and chemical characterizations, adsorption being a surface phenomenon, 500˚C appears to be the optimal calcination temperature for the preparation of activated carbons from palm nut shells in our experimental conditions.

Recurrent stroke admissions with vs without COVID-19 and associated in-hospital mortality: A United States nationwide analysis, 2020

BACKGROUND Coronavirus disease 2019(COVID-19)has been shown to increase the risk of stroke.However,the prevalence and risk of recurrent stroke in COVID-19 patients with prior stroke/transient ischemic attack(TIA),as well as its impact on mor-tality,are not established.AIM To evaluate the impact of COVID-19 on in-hospital mortality,length of stay,and healthcare costs in patients with recurrent strokes.METHODS We identified admissions of recurrent stroke(current acute ischemic stroke admissions with at least one prior TIA or stroke)in patients with and without COVID-19 using ICD-10-CM codes using the National Inpatient Sample(2020).We analyzed the impact of COVID-19 on mortality following recurrent stroke admissions by subgroups.RESULTS Of 97455 admissions with recurrent stroke,2140(2.2%)belonged to the COVID-19-positive group.The COVID-19-positive group had a higher prevalence of diabetes and chronic kidney disease vs the COVID-19 negative group(P<0.001).Among the subgroups,patients aged>65 years,patients aged 45–64 years,Asians,Hispanics,whites,and blacks in the COVID-19 positive group had higher rates of all-cause mortality than the COVID-19 negative group(P<0.01).Higher odds of in-hospital mortality were seen in the group aged 45-64(OR:8.40,95%CI:4.18-16.91)vs the group aged>65(OR:7.04,95%CI:5.24-9.44),males(OR:7.82,95%CI:5.38-11.35)compared to females(OR:6.15,95%CI:4.12-9.18),and in Hispanics(OR:15.47,95%CI:7.61-31.44)and Asians/Pacific Islanders(OR:14.93,95%CI:7.22-30.87)compared to blacks(OR:5.73,95%CI:3.08-10.68),and whites(OR:5.54,95%CI:3.79-8.09).CONCLUSION The study highlights the increased risk of all-cause in-hospital mortality in recurrent stroke patients with COVID-19,with a more pronounced increase in middle-aged patients,males,Hispanics,or Asians.

A Convolutional Deep Neural Network Approach for miRNA Clustering

The regulatory role of the Micro-RNAs (miRNAs) in the messenger RNAs (mRNAs) gene expression is well understood by the biologists since some decades, even though the delving into specific aspects is in progress. Clustering is a cornerstone in bioinformatics research, offering a potent computational tool for analyzing diverse types of data encountered in genomics and related fields. MiRNA clustering plays a pivotal role in deciphering the intricate regulatory roles of miRNAs in biological systems. It uncovers novel biomarkers for disease diagnosis and prognosis and advances our understanding of gene regulatory networks and pathways implicated in health and disease, as well as drug discovery. Namely, we have implemented clustering procedure to find interrelations among miRNAs within clusters, and their relations to diseases. Deep clustering (DC) algorithms signify a departure from traditional clustering methods towards more sophisticated techniques, that can uncover intricate patterns and relationships within gene expression data. Deep learning (DL) models have shown remarkable success in various domains, and their application in genomics, especially for tasks like clustering, holding immense promise. The deep convolutional clustering procedure used is different from other traditional methods, demonstrating unbiased clustering results. In the paper, we implement the procedure on a Multiple Myeloma miRNA dataset publicly available on GEO platform, as a template of a cancer instance analysis, and hazard some biological issues.

Microstructure and mechanical properties of overcast aluminum joints

The aluminum joints were prepared by overcasting liquid aluminum A356 onto 6101 aluminum extrusion bars. The microstructure, element distribution, hardness and tensile strength of the joint interface area were investigated, the mechanism of interface formation and fracture behavior were analyzed. The results show that good metallurgical bonding was formed in the joints by electro-plating the solid 6101 aluminum alloy with a layer of zinc coating and carefully controlling the overcasting process. There is a transition zone between the two bonded aluminum alloys, and the fine equiaxed grained structure in the transition zone is due to the high undercooling during solidification. The tensile strength of the joint interface is higher than that of the as-cast A356 aluminum alloy(about 145 MPa) and the final fracture is always located in the as-cast A356 material.

Effects of improved amino acid balance diet on lysine mammary utilization, whole body protein turnover and muscle protein breakdown on lactating sows

Background The study objective was to test the hypothesis that low crude protein(CP)diet with crystalline amino acids(CAA)supplementation improves Lys utilization efficiency for milk production and reduces protein turnover and muscle protein breakdown.Eighteen lactating multiparous Yorkshire sows were allotted to 1 of 2 isocaloric diets(10.80 MJ/kg net energy):control(CON;19.24%CP)and reduced CP with“optimal”AA profile(OPT;14.00%CP).Sow body weight and backfat were recorded on d 1 and 21 of lactation and piglets were weighed on d 1,14,18,and 21 of lactation.Between d 14 and 18,a subset of 9 sows(CON=4,OPT=5)was infused with a mixed solution of 3-[methyl-2H3]histidine(bolus injection)and[13C]bicarbonate(priming dose)first,then a constant 2-h[13C]bicarbonate infusion followed by a 6-h primed constant[1-13C]lysine infusion.Serial blood and milk sampling were performed to determine plasma and milk Lys enrichment,Lys oxidation rate,whole body protein turnover,and muscle protein breakdown.Results Over the 21-d lactation period,compared to CON,sows fed OPT had greater litter growth rate(P<0.05).Compared to CON,sows fed OPT had greater efficiency of Lys(P<0.05),Lys mammary flux(P<0.01)and whole-body protein turnover efficiency(P<0.05).Compared to CON,sows fed OPT tended to have lower whole body protein breakdown rate(P=0.069).Muscle protein breakdown rate did not differ between OPT and CON(P=0.197).Conclusion Feeding an improved AA balance diet increased efficiency of Lys and reduced whole-body protein turnover and protein breakdown.These results imply that the lower maternal N retention observed in lactating sows fed improved AA balance diets in previous studies may be a result of greater partitioning of AA towards milk rather than greater body protein breakdown.

Role of fecal microbiota transplant in management of hepatic encephalopathy: Current trends and future directions

Fecal microbiota transplantation(FMT)offers a potential treatment avenue for hepatic encephalopathy(HE)by leveraging beneficial bacterial displacement to restore a balanced gut microbiome.The prevalence of HE varies with liver disease severity and comorbidities.HE pathogenesis involves ammonia toxicity,gut-brain communication disruption,and inflammation.FMT aims to restore gut microbiota balance,addressing these factors.FMT's efficacy has been explored in various conditions,including HE.Studies suggest that FMT can modulate gut microbiota,reduce ammonia levels,and alleviate inflammation.FMT has shown promise in alcohol-associated,hepatitis B and C-associated,and non-alcoholic fatty liver disease.Benefits include improved liver function,cognitive function,and the slowing of disease progression.However,larger,controlled studies are needed to validate its effectiveness in these contexts.Studies have shown cognitive improvements through FMT,with potential benefits in cirrhotic patients.Notably,trials have demonstrated reduced serious adverse events and cognitive enhancements in FMT arms compared to the standard of care.Although evidence is promising,challenges remain:Limited patient numbers,varied dosages,administration routes,and donor profiles.Further large-scale,controlled trials are essential to establish standardized guidelines and ensure FMT's clinical applications and efficacy.While FMT holds potential for HE management,ongoing research is needed to address these challenges,optimize protocols,and expand its availability as a therapeutic option for diverse hepatic conditions.