Higher Fitness Research Articles

The prevalence of musculoskeletal pain among school students and its association with physical fitness in Guwahati urban society: a cross sectional study

Introduction and backgroundThe musculoskeletal pain (MSK) develops at an early age and pains in adolescence dispose to subsequent pain episodes in adulthood. High physical fitness levels in childhood and adolescence are linked to favorable health outcomes.This study has evaluated the prevalence of musculoskeletal pain among school students. Additionally, it examines the existing physical fitness of those children and explores potential associations between musculoskeletal pain and physical fitness.MethodsA cross sectional study was conducted in the Guwahati urban area, a capital city of North East India, in different schools. The mean and standard deviation of age was 9.49 ± 2.53. Prevalence of MSK pain was determined by the Faces Pain Scale–Revised and pediatric Gait Arm Leg Spine (pGALS) assessment, whereas physical fitness was assessed by Fitnessgram test battery.Statistical analysisPaired “t” test and logistic regression analysis were used. The level of significance was set at 0.05 for all tests performed, and 95% confidence intervals (CIs) were used in all cases.ResultsThe percentage of musculoskeletal pain is 38.28% where female school students have 40.33% and the male students have 36.52%. The odd ratio of 0.934 (CI = 0.916–0.972) was found between pain occurrence and aerobic capacity. The odd ratio of 0.72 (CI = 0.704–0.761) was found between the chances of pain onset and abdominal strength and endurance. The odd ratio of 0.859 (CI = 0.831–0.899) was found between pain occurrence and trunk extensor muscle strength and endurance.ConclusionThe prevalence of the musculoskeletal pain in school students is found to be 38.28%. The incidence of musculoskeletal pain and the physical fitness of a child has a significant relationship, with children who have poor physical fitness being more likely to develop musculoskeletal pain.

Analysis of artificial intelligence medical treatment for closed muscle skin nerve injury caused by aerobics training

In aerobics training, closed myocutaneous nerve damage needs to be paid attention to, especially high-intensity training may cause minor damage to muscles and nerves. With the help of AI medical technology and the understanding of molecular and cellular biomechanics, we can more accurately explore the mechanism of injury, such as the effects of nerve tensile stress and microenvironment changes on nerve regeneration. This helps to develop scientific rehabilitation methods, such as AI-assisted personalized training, neural regeneration technology, and real-time monitoring of training intensity to speed up athletes’ rehabilitation and reduce the risk of future injuries. Purpose: Aerobics training is very strict and requires high physical fitness of dancers. During long-term training, dancers can easily cause closed musculocutaneous nerve injury. Traditional medicine is difficult to guarantee the treatment effect of patients with musculocutaneous nerve injury. The use of artificial intelligence medicine for closed musculocutaneous nerve injury treatment can improve the treatment effect of aerobics training induced closed musculocutaneous nerve injury. Method: This article utilized artificial intelligence medicine for the treatment of musculocutaneous nerve injury, and used artificial intelligence technology to analyze patient imaging and other data to assist doctors in accurate diagnosis. Utilize intelligent algorithms to predict medication plans, reduce medication errors, and intelligently adjust the course of treatment based on the patient’s condition. In artificial intelligence healthcare, high-quality online medical services can be created through intelligent technology, providing convenient medical consultation for patients. Result: This article selected 200 patients with musculocutaneous nerve injury caused by aerobics training for grouping experiments. The average diagnostic accuracy of traditional medicine and artificial intelligence medicine were 84.2% and 95.6%, respectively. Conclusion: Artificial intelligence medicine can achieve medical informatization and intelligently analyze patients’ medical information, which helps to improve the accuracy of medical diagnosis for aerobics training injuries.

An optimized surrogate model and algorithm with rapid multi-parameter processing capability for antenna design

A methodology based on an optimized surrogate model and Non-dominated Sorting Genetic Algorithm III(NSGA-III) algorithm is proposed to address the long design cycle issues that conventional antennas encounter, with fast multiple parameters processing capability. A Temporal Convolutional Network (TCN) network model with high fitting efficiency and a simple structure is first developed as a surrogate model for antenna performance prediction, taking antenna dimensional parameters as input and outputting the reflection coefficient (S11) and gain of the antenna. Then, an adaptive NSGA-III algorithm with enhanced search efficiency is presented. By combing it with the prior TCN surrogate model, the parameter optimization for a 5G millimeter-wave antenna design is realized. Results show that the proposed method achieves a remarkable reduction in Mean Squared Error (MSE) by 12.489 % and 3.277 % respectively, while also presents a decreased running time by 2.670 % and 70.419 % respectively, as compared to the Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) network models. The proposed method can rapidly and accurately perform the optimization task of multiple antenna parameters, demonstrating its feasibility and effectiveness for antenna applications requiring wide bandwidth, low loss and high gain.

Adiponectin concentration and cardiometabolic risk factors: the moderator role of cardiorespiratory fitness in adolescents.

The deleterious effects attributed to excess adiposity and unfavorable changes related to insulin resistance and sensitivity may be attenuated by CRF. • Adiponectin, a protein derived from adipose tissue, may play a role as a potential marker of protection and predictor of cardiometabolic disorders and its relationship with cardiorespiratory fitness is controversial. • The deleterious effects attributed to overweight and unfavorable changes related to insulin resistance and sensitivity may be attenuated by high cardiorespiratory fitness in adolescents.

Impacts of paternal latitudinal origin on herbivore response strategies in Lythrum salicaria

Plants have evolved different strategies to withstand and respond to herbivore stress. The two main strategies plants employ under herbivore stress are known as tolerance and induced resistance. Tolerance is the ability to maintain high fitness despite experiencing high levels of herbivore damage. While induced resistance typically involves changing the concentrations of internal secondary metabolites as a response to initial herbivory and to prevent further damage. These strategies can lead to fitness differences between populations that vary by latitudinal origin. Previous studies have focused on the occurrence of herbivore response in general, whereas this study will make a direct comparison between response types and their fitness implications. Our study investigates whether eastern North American populations of Lythrum salicaria respond differently to herbivore stress. F1 crosses between L. salicaria individuals with different parental latitudinal ranges were grown in a common garden under two experimental herbivory treatments (pesticide sprayed vs. no pesticide) at the Queen’s University Biological Station. To identify differences in herbivore tolerance, we measured plant growth and development over 13 weeks and quantified herbivore damage, caused by the biocontrol beetle Galerucella calmariensis. A 48-hour feeding assay was then conducted to identify differences in herbivore resistance between populations. This assay provided beetles with a choice between young and old L. salicaria leaves from each experimental treatment. Our preliminary analysis of the feeding assay showed differences in leaf damage between parental lines. The initial analysis also showed that older leaves generally experienced more damage than younger leaves over the course of the 48-hour period. These results indicate population differences in herbivory stress response and differences in stress response effectiveness that varies with plant age. This experiment showed that L. salicaria individuals have varying degrees of herbivore stress response and effectiveness. However, further analysis that includes reproductive outputs and developmental differences will be completed to clearly identify the type of strategies L. salicaria populations with different parental latitudinal origins employ in response to herbivore damage.

Evolutionary dynamics in gut-colonizing Candida glabrata during caspofungin therapy: Emergence of clinically important mutations in sphingolipid biosynthesis.

Invasive fungal infections are associated with high mortality, which is exacerbated by the limited antifungal drug armamentarium and increasing antifungal drug resistance. Echinocandins are a frontline antifungal drug class targeting β-glucan synthase (GS), a fungal cell wall biosynthetic enzyme. Echinocandin resistance is generally low but increasing in species like Candida glabrata, an opportunistic yeast pathogen colonizing human mucosal surfaces. Mutations in GS-encoding genes (FKS1 and FKS2 in C. glabrata) are strongly associated with clinical echinocandin failure, but epidemiological studies show that other, as yet unidentified factors also influence echinocandin susceptibility. Furthermore, although the gut is known to be an important reservoir for emergence of drug-resistant strains, the evolution of resistance is not well understood. Here, we studied the evolutionary dynamics of C. glabrata colonizing the gut of immunocompetent mice during treatment with caspofungin, a widely-used echinocandin. Whole genome and amplicon sequencing revealed rapid genetic diversification of this C. glabrata population during treatment and the emergence of both drug target (FKS2) and non-drug target mutations, the latter predominantly in the FEN1 gene encoding a fatty acid elongase functioning in sphingolipid biosynthesis. The fen1 mutants displayed high fitness in the gut specifically during caspofungin treatment and contained high levels of phytosphingosine, whereas genetic depletion of phytosphingosine by deletion of YPC1 gene hypersensitized the wild type strain to caspofungin and was epistatic to fen1Δ. Furthermore, high resolution imaging and mass spectrometry showed that reduced caspofungin susceptibility in fen1Δ cells was associated with reduced caspofungin binding to the plasma membrane. Finally, we identified several different fen1 mutations in clinical C. glabrata isolates, which phenocopied the fen1Δ mutant, causing reduced caspofungin susceptibility. These studies reveal new genetic and molecular determinants of clinical caspofungin susceptibility and illuminate the dynamic evolution of drug target and non-drug target mutations reducing echinocandin efficacy in patients colonized with C. glabrata.

Back to Nature: Development and Optimization of Bioinspired Nanocarriers for Potential Breast Cancer Treatment

This study focuses on the preparation and optimization of caffeic acid (CA)-loaded casein nanoparticles (CS NPs) via the Box–Behnken design (BBD) for potential applications in cancer treatment. CS NPs were loaded with CA as a promising anti-cancer molecule. Non-hazardous green materials were exploited for nanoparticle fabrication. The BBD was used, followed by a desirability function to select the optimum formulation. The BBD was adopted as it avoids the runs implemented in extreme conditions, hence making it suitable for proteins. CS NPs were characterized regarding particle size (PS), size distribution (PDI), zeta potential (ZP), drug entrapment, morphology using TEM, differential scanning calorimetry, molecular docking, in vitro release, and cytotoxicity studies. PS, PDI, and ZP had significant responses, while EE% was insignificant. The suggested models were quadratic with high fitting. Optimized NPs showed PS = 110.31 ± 1.02 nm, PDI = 0.331 ± 0.029, ZP = −23.94 ± 1.64 mV, and EE% = 95.4 ± 2.56%. Molecular modeling indicated hydrophobic and electrostatic interactions between CA and CS, accounting for the high EE%. Almost spherical particles were realized with a sustained CA release pattern. Optimized NPs effectively suppressed the growth of MCF-7 cell lines by scoring the lowest IC50 = 78.45 ± 1.7 µg/mL. A novel combination of bioinspired-derived materials was developed for use in breast cancer treatment.

Research on Optimization of Intermittent Production Process System

As gas wells enter later production stages, the formation pressure decreases and liquid accumulates at the bottom of the gas well. The formation pressure is insufficient to lift the accumulated liquid from the bottom of the well to the surface. At this time, a large number of gas wells need to undergo intermittent production to maintain their production capacity. This article focuses on the four stages of intermittent production in gas wells, considering the changes in slip gas holdup, pressure, and gas–liquid flow in and out of tubing and casing, and establishes a transient mathematical model for intermittent production in gas wells in stages. By using the dynamic tracking technology of moving liquid slugs to divide the wellbore grid and solve it in stages, the optimal shut-in time for intermittent production of gas wells was obtained. The transient mathematical model developed for intermittent gas well production achieved a high historical fit accuracy of over 90%. This indicates that the simulation results are in line with the actual situation of gas well intermittent production and can effectively guide intermittent production. The optimized intermittent production system of gas wells has a higher cumulative gas production compared to the original system, achieving the optimization of intermittent production system. This method is beneficial for guiding efficient production of gas wells in low-pressure formations.

P135 FITNESS INFLUENCES THE RELATIONSHIP BETWEEN EXERCISE BLOOD PRESSURE AND LEFT VENTRICULAR STRUCTURE: EVIDENCE FROM THE EXERCISE STRESS TEST COLLABORATION (EXERTION) STUDY

Background. A hypertensive response to exercise is associated with left ventricular (LV) remodelling, a principal sign of hypertensive heart disease. Fitness may modify this relationship, making clinical interpretation of peak exercise systolic blood pressure (SBP) challenging. This study examines the influence of fitness on the relationship between peak exercise SBP and LV structure. Methods. Cardiovascular structure and function (LV mass index (LVMI), LV relative wall thickness (RWT), cardiac output (CO) and total peripheral resistance (TPR)) were assessed at rest by echocardiography on 4,309 individuals (aged 58.6±12.7 years,52.0% male). SBP was measured at peak treadmill exercise, and fitness (exercise duration (minutes)) was grouped into thirds. Multiple regression analysis was conducted with fitness as an interaction term with peak exercise SBP, adjusted for age, sex, pre-exercise SBP, and cardiovascular disease (CVD) history. Results. Peak exercise SBP was similar across low (180±26.5mmHg), moderate (181±26.3mmHg) and high (182±24.5mmHg) fitness groups. Fitness modified the relationship between exercise SBP and LVMI; each 5mmHg increase in exercise SBP was associated with LVMI in moderate [0.27(0.10–0.43) and high [0.25(0.06–0.43)] fitness groups, which was not observed among those with low fitness [-0.05(-0.22–0.12)]. RWT increased with higher peak exercise SBP at all fitness levels (all p<0.001), with higher values among those with low fitness. Prevalence of LV concentric remodelling was highest in those with low fitness (29.9%) and lowest in those with high fitness (10.8%). A lower CO and higher TPR were observed in the low fitness group (7.5±2.5L/min and 14.3±5.1mmHg min/L) compared to those with high fitness (10.9±3.1L/min and 9.2±2.09mmHg min/L). Conclusion. Whilst a small effect, fitness modified the peak exercise SBP-LV structure relationship, such that for similar peak exercise SBP, those with low fitness exhibit a more adverse LV remodelling, with lower CO and higher TPR, compared to those with higher fitness. Considering fitness when interpreting SBP and cardiac imaging results from exercise stress testing may be relevant in identifying CVD risk and optimal patient management.

Better approximation of sigmoid function for privacy-preserving neural networks

Abstract With the development of artificial intelligence technology, privacy protection has become a prominent research direction. Homomorphic encryption is an important and promising technology in the construction of privacy-preserving neural networks. However, computing nonlinear activation functions remains a challenging task in the context of homomorphic encryption. Considering Sigmoid is one of the most commonly used activation functions, this paper proposes a polynomial approximation method for the Sigmoid function and applies it to the homomorphic encryption scheme of CKKS. We design polynomial approximation functions using Improved Taylor Expansion Segmentation (ITES), Least Squares method (LS), and Random Noise Addition method, respectively. These methods are implemented through the CKKS scheme in the homomorphic encryption library of SEAL. The experimental results show that the ITES achieves high fitting accuracy, reducing the average absolute error by 11.09% and the mean squared error by 38.06% compared to previous fitting methods. Therefore, experiments have identified methods with better fitting results in the CKKS scheme, which can meet the requirements of using homomorphic encryption in deep learning technologies. Finally, our analysis points out that different technologies have unique advantages and adapt to different scenarios, e.g., ITES has higher accuracy, LS has higher performance in scenarios with limited computing resources.

Manganese metal ion removal from aqueous solution using industrial wastes derived geopolymer

Heavy metal pollutants, highly toxic and invisible, have garnered attention due to bioaccumulation. Increased manganese production from steel industries is expected to lead to harmful concentrations in water, adversely affecting the environment and public health. The sustainable approach of utilizing industrial by-products to synthesize geopolymers for the immobilization of heavy metal ions has gained research interest. The current study aims to verify the feasibility of Paper sludge ash (PSA) in conventional geopolymer (CGP) to immobilize manganese (Mn) heavy metal ions from aqueous solutions. CGP was prepared using Fly ash (FA) as resource material, which was replaced by PSA at a level of 30 %, by weight. The precursors were treated with alkali solutions, namely sodium hydroxide and sodium silicate, incorporating ambient curing. The characterization studies of precursors and CGP were investigated using XRD, XRF, SEM, EDS, FTIR, and Brunauer-Emmett-Teller surface area (BET) analysis techniques to outline the crystal structure, morphology, and pore parameters. Additionally, the experimental investigation comprehensively examined the impact of various pH levels, dosages, contact times, and initial concentrations on the removal efficiency of Mn heavy metal ions. The difference in concentration of Mn heavy metal ions quantified by atomic absorption spectrometry. The Langmuir models effectively explained the removal of Mn ions by CGP due to high fitting coefficients. The highest value of uptake capacity was found to be 28 mg/g at 30 °C with pH value of 4. Therefore, blending industrial wastes improves the potential of decontamination agents in removing heavy metals from wastewater, promoting environmental sustainability.

Sand blasting for hydrophobic surface generation in polymers: Experimental and machine learning approaches

Wettability is a crucial surface feature of polymers due to their numerous interaction-destined applications. This study focuses on the application of sand blasting process for investigating the wettability of polymeric materials to produce hydrophobic behavior. Four different polymeric materials, Acrylonitrile Butadiene Styrene (ABS), Poly(methyl methacrylate) (PMMA), Polypropylene (PP), and Polycarbonate (PC) underwent sand blasting with varying process parameters, following a comprehensive plan for the design of experiments. Subsequent analyses included surface roughness measurement and wettability tests, supplemented by scanning electron and confocal microscopy observations to gain deeper insights into the blasted surfaces. A predictive model based on a machine learning algorithm was developed using the backpropagation technique to correlate the surface treatment parameters to surface roughness and wettability indexes. From the experimental results sand blasting proved to be efficient in creating hydrophobic surfaces on all the tested materials. The developed neural network demonstrated high fitting degrees between the predicted and measured values. ABS exhibited the most hydrophobic behavior and emerged as a strong candidate for further investigations.

Adsorption of Uranium (VI) From Aqueous Solution Using Melamine Formaldehyde Organo Clay Nanocomposite Foam as a Novel Adsorbent

Uranium is a toxic radioactive element and is usually found in the environment in hexavalent form. It has become necessary to remove uranium, which can be released into the environment in excessive amounts through nuclear industrial activities, from access waters. Melamine formaldehyde/organo clay nano composite foam (MFCNCF) was prepared as a novel adsorbent by hardening with thermal treatment. Structural, crystallographic textural and surface morphological characterization of the prepared adsorbent was made by Fourier transform infrared spectrophotometry (FTIR), X-Ray diffraction (XRD), Scanning electron microscopy (SEM) and High-resolution transmission electron microscopy (HRTEM) analyses. This study aimed to investigate the adsorption of U(VI) from aqueous solutions by MFCNCF and its dependence on various variables, such as initial uranium concentration, adsorption time, adsorbent dosage, initial pH, and temperature. Additionally, its adsorption isotherm analysis and adsorption kinetics and thermodynamics were also examined. For this purpose, batch adsorption experiments were carried out and the equilibrium concentration of U(VI) in the aqueous solution was measured with a UV-Vis spectrophotometer at a wavelength of 433 nm, which corresponds to its maximum absorptivity. The results regarding adsorption kinetics showed that 30 min was sufficient to reach adsorption equilibrium and the data showed a high fit to the pseudo-second-order kinetic model. Isotherm analysis also revealed a high fit of the data to the Type III isotherm and the Halsey model. Based on these fits, an adsorption mechanism involving two regions (electrostatic and complex formation) is proposed for the current adsorption system. The adsorption isosteric enthalpy and entropy values for the first and second regions were found to be −5.35 and 2.02 kJ/mol and −16.98 and 6.40 J/mol, respectively. The experimental results showed that the prepared nanocomposite foam adsorbent is an effective and potential alternative for the effective removal of U(VI) from aqueous solutions.

Process Parameters Optimization and Numerical Simulation of AlCoCrFeNi High-Entropy Alloy Coating via Laser Cladding.

The use of laser cladding technology to prepare coatings of AlCoCrFeNi high-entropy alloy holds enormous potential for application. However, the cladding quality will have a considerable effect on the properties of the coatings. In this study, considering the complex coupling relationship between cladding quality and the process parameters, an orthogonal experimental design was employed, with laser power, scanning speed, and powder feed rate as correlation factor variables, and microhardness, dilution rate, and aspect ratio as characteristic variables. The experimental data underwent gray correlation analysis to determine the effect of various process parameters on the quality of cladding. Then, the NSGA-II algorithm was used to establish a multi-objective optimization model of process parameters. Finally, the ANSYS Workbench simulation model was employed to conduct numerical simulations on a group of optimized process parameters and analyze the change rule of the temperature field. The results demonstrate that the laser cladding coating of AlCoCrFeNi high-entropy alloy with the single pass is of high quality within the determined orthogonal experimental parameters. The powder feed rate exerts the most significant influence on microhardness, while laser power has the greatest impact on dilution rate, and scanning speed predominantly affects aspect ratio. The designed third-order polynomial nonlinear regression model exhibits a high fitting accuracy, and the NSGA-II algorithm can be used for multi-objective optimization to obtain the Pareto front solution set. The numerical simulation results demonstrate that the temperature field of AlCoCrFeNi high-entropy alloy laser cladding exhibits a "comet tail" phenomenon, where the highest temperature of the molten pool is close to 3000 °C. The temperature variations in the molten pool align with the features of laser cladding technology. This study lays the groundwork for the widespread application of laser cladding AlCoCrFeNi high-entropy alloy in surface engineering, additive manufacturing, and remanufacturing. Researchers and engineering practitioners can utilize the findings from this research to judiciously manage processing parameters based on the results of gray correlation analysis. Furthermore, the outcomes of multi-objective optimization can assist in the selection of appropriate process parameters aligned with specific application requirements. Additionally, the methodological approach adopted in this study offers valuable insights applicable to the exploration of various materials and diverse additive manufacturing techniques.

Metabolic Heat Production Modulates the Cardiovascular Drift-V̇O2max Relationship Independent of Aerobic Fitness in Women.

The purpose of this study was to test the hypothesis that cardiovascular (CV) drift and associated decrements in maximal oxygen uptake (V̇O2max) are greater in high-fit compared to low-fit women during exercise at the same %V̇O2max, but comparable at the same rate of metabolic heat production. Six high-fit (HI) and 6 low-fit (LO) women cycled in 35 °C for 15 min or 45 min at the same relative intensity (60% V̇O2max; 15REL and 45REL) or fixed rate of heat production (500 W; 15FX and 45FX), immediately followed by a GXT to measure V̇O2max. The separate 15- and 45-min trials permitted measurements of V̇O2max over the same time interval as CV drift. During 45REL, higher heat production in HI (496 ± 51 W vs. 364 ± 44 W in LO) resulted in greater end-exercise core temperature (38.7 ± 0.4 °C vs. 38.2 ± 0.1 °C, P = 0.03); greater increases in HR [15 beats·min-1 (10%) vs. 10 beats·min-1 (6%), P = 0.03] and decreases in SV [11 mL·beat-1 (16%) vs. 5 mL·beat-1 (8%), P = 0.001]; and larger reductions in V̇O2max (16% vs. 5%, P = 0.04) compared to LO. During 45FX, temperature responses, CV drift and decreased V̇O2max were not different between groups (all P > 0.05), despite differences in %V̇O2max (60% vs. 75% for HI and LO, respectively). We conclude metabolic heat production modulates the CV drift-V̇O2max relationship, independent of fitness level. These results support previous findings showing the magnitude of CV drift is proportional to reductions in V̇O2max.

Identification of pathways to high-level vancomycin resistance in Clostridioides difficile that incur high fitness costs in key pathogenicity traits.

Clostridioides difficile is an important human pathogen, for which there are very limited treatment options, primarily the glycopeptide antibiotic vancomycin. In recent years, vancomycin resistance has emerged as a serious problem in several gram-positive pathogens, but high-level resistance has yet to be reported for C. difficile, although it is not known if this is due to constraints upon resistance evolution in this species. Here, we show that resistance to vancomycin can evolve rapidly under ramping selection but is accompanied by fitness costs and pleiotropic trade-offs, including sporulation defects that would be expected to severely impact transmission. We identified 2 distinct pathways to resistance, both of which are predicted to result in changes to the muropeptide terminal D-Ala-D-Ala that is the primary target of vancomycin. One of these pathways involves a previously uncharacterised D,D-carboxypeptidase, expression of which is controlled by a dedicated two-component signal transduction system. Our findings suggest that while C. difficile is capable of evolving high-level vancomycin resistance, this outcome may be limited clinically due to pleiotropic effects on key pathogenicity traits. Moreover, our data identify potential mutational routes to resistance that should be considered in genomic surveillance.

In vivo fitness of sul gene-dependent sulfonamide-resistant Escherichia coli in the mammalian gut.

The widespread sulfonamide resistance genes sul1, sul2, and sul3 in food and gut bacteria have attracted considerable attention. In this study, we assessed the in vivo fitness of sul gene-dependent sulfonamide-resistant Escherichia coli, using a murine model. High fitness costs were incurred for sul1 and sul3 gene-dependent E. coli strains in vivo. A fitness advantage was found in three of the eight mice after intragastric administration of sul2 gene-dependent E. coli strains. We isolated three compensatory mutant strains (CMSs) independently from three mice that outcompeted the parent strain P2 in vivo. Whole-genome sequencing revealed seven identical single nucleotide polymorphism (SNP) mutations in the three CMSs compared with strain P2, an additional SNP mutation in strain S2-2, and two additional SNP mutations in strain S2-3. Furthermore, tandem mass tag-based quantitative proteomic analysis revealed abundant differentially expressed proteins (DEPs) in the CMSs compared with P2. Of these, seven key fitness-related DEPs distributed in two-component systems, galactose and tryptophan metabolism pathways, were verified using parallel reaction monitoring analysis. The DEPs in the CMSs influenced bacterial motility, environmental stress tolerance, colonization ability, carbohydrate utilization, cell morphology maintenance, and chemotaxis to restore fitness costs and adapt to the mammalian gut environment.IMPORTANCESulfonamides are traditional synthetic antimicrobial agents used in clinical and veterinary medical settings. Their long-term excessive overuse has resulted in widespread microbial resistance, limiting their application for medical interventions. Resistance to sulfonamides is primarily conferred by the alternative genes sul1, sul2, and sul3 encoding dihydropteroate synthase in bacteria. Studying the potential fitness cost of these sul genes is crucial for understanding the evolution and transmission of sulfonamide-resistant bacteria. In vitro studies have been conducted on the fitness cost of sul genes in bacteria. In this study, we provide critical insights into bacterial adaptation and transmission using an in vivo approach.

Are there fitness benefits to violence? The case of medieval Iceland

Males that behave violently to achieve social and reproductive objectives are a widespread phenomenon among mammals, as well as humans. Because this kind of behaviour can be socially very disruptive, its continued survival in human populations, in particular, remains a puzzle. We use historical data on the pedigrees of medieval Icelandic Vikings to test the hypothesis that males who killed had higher fitness than other males. Whereas most studies that examine the evolutionary benefits of behaviour focus on the numbers of offspring sired, in this paper we measure fitness more directly in terms of the number of grandchildren produced both directly and indirectly via collateral relatives, as well as determining the costs of pursuing alternative strategies in terms of experienced mortality rates. We show that, on average, killers gain a very significant fitness advantage despite the often high costs they pay and, more importantly, that they had a dramatic effect on the fitness of their male kin. We suggest that such behaviour represents a phenotypic, rather than genetic, response to opportunities provided by local circumstances.

Prediction and Classification of Phenol Contents in Cnidium officinale Makino Using a Stacking Ensemble Model in Climate Change Scenarios

Recent studies have focused on using big-data-based machine learning to address the effects of climate change scenarios on the production and quality of medicinal plants. Challenges relating to data collection can hinder the analysis of key feature variables that affect the quality of medicinal plants. In the study presented herein, we analyzed feature variables that affect the phenolic content of Korean Cnidium officinale Makino (C. officinale Makino) under different climate change scenarios. We applied different climate change scenarios based on environmental information obtained from Yeongju city, Gyeongsangbuk-do, Republic of Korea, and cultivated C. officinale Makino to collect data. The collected data included 3237, 75, and 45 records, and data augmentation was performed to address this data imbalance. We designed a function based on the DPPH value to set the phenolic content grade in C. officinale Makino and proposed a stacking ensemble model for predicting the total phenol contents and classifying the phenolic content grades. The regression model in the performance evaluation presented an improvement of 6.23–7.72% in terms of the MAPE; in comparison, the classification model demonstrated a 2.48–3.34% better performance in terms of accuracy. The classification accuracy was >0.825 when classifying phenol content grades using the predicted total phenol content values from the regression model, and the area under the curve values of the model indicated high model fitness (0.987–0.981). We plan to identify the key feature variables for the optimal cultivation of C. officinale Makino and explore the relationships among these feature variables.

Legal and Financial Risk Management in Large-Scale Construction Projects

Construction projects involve many parties and experts such as builders, contractors, designers, and consultants, which causes project arrangements to be complicated with many risks and uncertainties, including legal and financial risks. Legal risks include aspects of contracts, permits, certificates, claims, lawsuits, and sanctions. Conflicts or disputes can arise due to legal risks, which can lead to cost overruns and delays in project schedules. The project manager must be able to mitigate these risks in order to achieve the project objectives. This study uses descriptive qualitative and descriptive analytical methods to provide a detailed description of the research problem. The results showed that the risks adversely affect the legal aspects of construction, time, cost, and quality of the project. Legal risks in construction projects can arise due to several reasons, namely problems with documents and contract articles, lawsuits from third parties, and problems in acquiring project land. Good risk management is required to improve project efficiency, and project performance is improved when the organization can create a high fit between risk exposure and risk management profile.