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Abstract Background The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study. Results Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant’s gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5. Conclusions The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies. Video abstract

Introduction: Nutritional habits and requirements are changing over the lifespan, but the dynamics of nutritional issues and the diet-health relationship in the major stages of the human life cycle are not sufficiently understood. A human phenotyping research platform for nutrition studies was established to recruit and phenotype selected population groups across different stages of life. The project is the backbone of the highly interdisciplinary enable competence cluster of nutrition research aiming to identify dietary determinants of a healthy life throughout the lifespan and to develop healthier and tasty convenience foods with high consumer acceptance.Methods: The phenotyping program included anthropometry, body composition analysis, assessment of energy metabolism, health and functional status, multisensory perception, metabolic phenotyping, lifestyle, sociodemography, chronobiology, and assessment of dietary intake including food preferences and aversions.Results: In total, 503 healthy volunteers at four defined phases of life including 3–5-year old children (n = 44), young adults aged 18–25 years (n = 94), adults aged 40–65 years (“middle agers,” n = 205), and older adults aged 75–85 years (n = 160) were recruited and comprehensively phenotyped. Plasma, serum, buffy coat, urine, feces and saliva samples were collected and stored at −80°C. Significant differences in anthropometric and metabolic parameters between the four groups were found. A major finding was the decrease in fat-free mass and the concomitant increase in % body fat in both sexes across the adult lifespan.Conclusions: The dataset will provide novel information on differences in diet-related parameters over the lifespan and is available for targeted analyses. We expect that this novel platform approach will have implications for the development of innovative food products tailored to promote healthy eating throughout life.Trial registration: DRKS, DRKS00009797. Registered on 20 January 2016, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&_ID=DRKS00009797.

In an aging population, support for independent living is increasingly critical for older generations. Currently, sarcopenia is a major cause of frailty, which increases the risk of decreased mobility, falls, morbidity, and mortality and leads to dependence on third parties. Sarcopenia is preventable by consumption of adequate protein. However, many older people do not meet the recommended daily allowance of protein, thereby supporting dependence rather than independent living. Current literature indicates that a protein drink could be an appropriate product for older peoples' protein consumption. We were interested in autonomous persons whose nutritional decisions were still self-determined and thus could preventively influence their personal health. This study evaluated three commercially available protein drinks in three focus groups (n = 25) to gain insight into which aspects influence the perception of commercial protein drinks on community-dwelling older people (age, 76.8 ± 4.9). Findings from the focus groups revealed only aspects, which influenced the perception of commercial protein drinks negatively. Most importantly, the drinks did not comply with relevant aspects when buying (healthy) foods, which where naturalness, freshness, locally grown ingredients, and trust. Furthermore, the target group did not see a need for additional protein consumption. Thus, we identify important aspects to be considered for the development of a target-group-specific protein drink as well as more suitable communication to prevent distrust in order to support independent living for community-dwelling older people.

Dietary intake and requirements in nursing home (NH) residents vary individually, but concepts for individualised interventions are currently lacking. Therefore, we present an individualised modular nutritional intervention concept for NH residents with (risk of) malnutrition and describe its application and acceptability. Three enrichment modules—a sweet and a savoury protein cream (40 g, 125 kcal, 10 g protein) and a protein-energy drink (250 mL, 220 kcal, 22 g protein)—were offered to residents of two German NHs single or in combination in five levels of enrichment from level 0 (no enrichment) to 4 (all enrichment modules) to compensate for individual energy and protein deficiencies. Residents with chewing and/or swallowing difficulties received reshaped instead of usual texture-modified meals. The intervention concept was applied to 55 residents (Mean age of 84 ± 8 years, 76.0% female, 25.5% malnutrition). Despite (risk of) malnutrition, 18.2% received no enrichment (level 0). Level 1 was allocated to 10.9%, level 2 to 27.3%, level 3 to 20.0% and level 4 to 23.6% of the residents. 32.7% received reshaped texture-modified meals (RTMM). Participants consuming RTMM were more often assigned to level 4 than residents receiving usual meals (38.8% vs 16.2%). We proposed and successfully applied an individualised modular nutritional intervention concept to NH residents with (risk of) malnutrition. In the next step, the effects of the concept and its transferability to other NHs need to be demonstrated.

Type 2 diabetes mellitus (T2DM) is a global public health epidemic. Diet and lifestyle changes have been demonstrated as effective measures in managing T2DM and preventing or delaying the progression from prediabetes to diabetes, yet the relationship between diet, prediabetes and diabetes is still not entirely clear. The present study aimed to further elucidate the relationship between diet, diabetes and especially prediabetes. A total of 1542 participants of the cross-sectional, population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013/2014) were included in this analysis. Dietary intake was derived using a method combining information from a FFQ and repeated 24-h food lists. Glucose tolerance status was assessed via oral glucose tolerance tests in all participants without a previous physician-confirmed diagnosis of T2DM, and was classified according to the 2003 American Diabetes Association criteria. Crude and fully adjusted multinomial logistic regression models were fitted to examine associations between diet and prediabetes, undetected diabetes mellitus (UDM) and prevalent T2DM. After adjusting for major covariates, fruit was significantly inversely and total meat, processed meat, sugar-sweetened beverages and moderate alcohol significantly associated with UDM and/or prevalent diabetes. Sex-specific analyses showed that in men, coffee was significantly inversely (OR 0·80; 95 % CI 0·67, 0·96) and heavy alcohol significantly (OR 1·84; 95 % CI 1·14, 2·95) associated with prediabetes. Our findings on diet and T2DM are consistent with current literature, while our results regarding coffee, heavy alcohol consumption and prediabetes highlight new possible targets for primary prevention of the derangement of glucose homeostasis.

Nursing home (NH) residents receiving texture-modified diet (TMD) are at risk of inadequate nutritional intake and subsequent malnutrition. It is essential to monitor dietary intake to take corrective actions, if necessary. Plate diagrams (PDs) are widely used to assess dietary intake in institutions but little is known about their validity for TMD. Dietary intake at main meals was assessed by nursing personnel via PDs and scientific personnel via weighing records (WRs). 17 NH residents receiving TMD on a regular basis. Intake from main meals (breakfast, lunch, and dinner) at 48 days was estimated by nursing personnel in quarters of the offered amount [nothing, ¼, ½, ¾, all, all plus second helping (5 4), or I do not know] and by scientific personnel via WRs. PD estimation was multiplied by the energy and protein content of the offered meal determined by WR and compared to WR intake results. Sums of daily PD quarters were drawn against WR intake results. Energy and protein intake from main meals separately and in total per day were highly correlated (r > 0.854, all P <.001). Paired statistics showed no significant differences between assessment methods (P >.05). Mean differences [±standard deviation (SD)] between PD and WR were 13.9 (±68.6) kcal, which is 1.7% of the mean weighed caloric intake, and 0.2 (±3.3) g protein, which is 0.5% of the mean weighed protein intake per day. Daily energy and protein intake from main meals determined by WR varies widely within each category of summed daily intake quarters; for example, a sum of PD quarters of 12 (ie, "all eaten at all meals") showed corresponding WR intake levels from 394.6 to 1368.9 kcal and 16.3 to 63.0 g protein. Energy and protein intake from TMD estimated by PD corresponds very well to WR-determined intake, if the energy and protein content of the offered meals is known. [ABSTRACT FROM AUTHOR]

Recent decades have witnessed the increasing adoption of personalized price promotion (PPP) at grocery stores. Despite the growing body of research debating whether PPP is more effective than untargeted price promotions, there is no literature synthesizing the relevant evidence on food products. Therefore, we conduct a systematic review to examine empirical findings on the effects of PPP targeting food products. Outcomes of 12 identified studies demonstrate larger sales and profit boosting effects of PPP than its non-personalized counterparts. Meanwhile, the results on how this approach influences consumer behavior are mixed. The effectiveness of PPP varies among different targeting strategies (e.g. reward or cross-selling) and information collection methods (e.g. using within- or across-chain data). The findings of this review have important managerial implications for the future evaluation and application of PPP as well as imply potential directions of further research on this topic. [ABSTRACT FROM AUTHOR]

We are often interested in clustering objects that evolve over time and identifying solutions to the clustering problem for every time step. Evolutionary clustering provides insight into cluster evolution and temporal changes in cluster memberships while enabling performance superior to that achieved by independently clustering data collected at different time points. In this article we introduce evolutionary affinity propagation (EAP), an evolutionary clustering algorithm that groups data points by exchanging messages on a factor graph. EAP promotes temporal smoothness of the solution to clustering time-evolving data by linking the nodes of the factor graph that are associated with adjacent data snapshots, and introduces consensus nodes to enable cluster tracking and identification of cluster births and deaths. Unlike existing evolutionary clustering methods that require additional processing to approximate the number of clusters or match them across time, EAP determines the number of clusters and tracks them automatically. A comparison with existing methods on simulated and experimental data demonstrates effectiveness of the proposed EAP algorithm. [ABSTRACT FROM AUTHOR]

Age is a significant risk factor for common noncommunicable diseases, yet the physiological alterations of aging are poorly understood. We were interested in metabolic patterns between cross‐sectional cohorts of different age ranges with particular emphasis on waist circumference. We recruited three cohorts of healthy subjects with different age ranges (adolescents 18–25 years, adults 40–65 years, and older citizens 75–85 years) and stratified these based on waist circumference. Using targeted LC‐MS/MS metabolite profiling, we analyzed 112 analytes in plasma (amino acids, acylcarnitines, and derivatives). We associated age‐related alterations with various anthropometric and functional parameters such as insulin sensitivity and handgrip strength. Strongest age‐dependent increases were found for fatty acid‐derived acylcarnitines. Amino acid‐derived acylcarnitines displayed increased associations with BMI and adiposity. Some essential amino acids changed in opposite directions, being lower at increased age and higher with increasing adiposity. τ‐methylhistidine was elevated in older subjects, especially on an adiposity background, suggesting an increased protein turnover. Both aging and adiposity are associated with impaired insulin sensitivity. Skeletal muscle mass decreased with age and increased with adiposity. Profound differences in the metabolite signatures during healthy aging and elevated waist circumference/body weight were found. Opposite changes in skeletal muscle mass as well as possible differences in insulin signaling (relative insulin deficiency in older subjects versus hyperinsulinemia associated with adiposity), might be underlying origins for the observed metabolite signatures. We describe novel associations between metabolites and anthropometric factors during aging which underlines the complex interplay of aging, insulin resistance, and metabolic health. [ABSTRACT FROM AUTHOR]

Circulating tumor cells (CTCs) are extremely rare in the blood, yet they account for metastasis. Notably, it was reported that CTC clusters (CTCCs) can be 50–100 times more metastatic than single CTCs, making them particularly salient as a liquid biopsy target. Yet they can split apart and are even rarer, complicating their recovery. Isolation by filtration risks loss when clusters squeeze through filter pores over time, and release of captured clusters can be difficult. Deterministic lateral displacement is continuous but requires channels not much larger than clusters, leading to clogging. Spiral inertial focusing requires large blood dilution factors (or lysis). Here, we report a microfluidic chip that continuously isolates untouched CTC clusters from large volumes of minimally (or undiluted) whole blood. An array of 100 μm-wide channels first concentrates clusters in the blood, and then a similar array transfers them into a small volume of buffer. The microscope-slide-sized PDMS device isolates individually-spiked CTC clusters from >30 mL per hour of whole blood with 80% efficiency into enumeration (fluorescence imaging), and on-chip yield approaches 100% (high speed video). Median blood cell removal (in base-10 logs) is 4.2 for leukocytes, 5.5 for red blood cells, and 4.9 for platelets, leaving less than 0.01% of leukocytes alongside CTC clusters in the product. We also demonstrate that cluster configurations are preserved. Gentle, high throughput concentration and separation of circulating tumor cell clusters from large blood volumes will enable cluster-specific diagnostics and speed the generation of patient-specific CTC cluster lines. [ABSTRACT FROM AUTHOR]

Establishing long-term relative bounded motion between orbits in perturbed dynamics is a key challenge in astrodynamics to enable cluster flight with minimum propellant expenditure. In this work, we present an approach that allows for the design of long-term relative bounded motion considering a zonal gravitational model. Entire sets of orbits are obtained via high-order Taylor expansions of Poincarè return maps about reference fixed points. The high-order normal form algorithm is used to determine a change in expansion variables of the map into normal form space, in which the phase space behavior is circular and can be easily parameterized by action–angle coordinates. The action–angle representation of the normal form coordinates is then used to parameterize the original Poincarè return map and average it over a full phase space revolution by a path integral along the angle parameterization. As a result, the averaged nodal period and drift in the ascending node are obtained, for which the bounded motion conditions are straightforwardly imposed. Sets of highly accurate bounded orbits are obtained, extending over several thousand kilometers, and valid for decades. [ABSTRACT FROM AUTHOR]

At the second stage of China Spallation Neutron Source (CSNS-II), it is predicted that 2 PB raw experimental data will be produced annually from twenty instruments. Scientific computing puts forward higher requirements for data sharing, utilization, retrieval, analysis efficiency, and security. However, the existing data management system (DMS) based on ICAT has several limitations including poor scalability of metadata database, imperfect data-management lifecycle and inflexible API. To ensure the accuracy, usability, scalability and efficiency of CSNS-II experimental data, a new scientific data management system is therefore designed based on the DOMAS framework developed by the Computing Center of IHEP. The data acquisition, transmission, storage and service systems are re-designed and tailored specifically for CSNS-II. Upon its completion, the new DMS will overcome the existing challenges and offer functions such as online display, search functionality and rapid download capabilities for metadata, raw data and analyzed data; flexible and user-friendly authorization; and data lifecycle management. Ultimately, the implementation of the new Data Management System (DMS) is expected to enhance the efficiency of experimental data analysis, propelling CSNS-II to achieve international advanced standards. Furthermore, it aims to reinforce self-reliance and technological strength in the field of science and technology at a high level in China. The development and deployment of the new DMS begin at the end of 2023. [ABSTRACT FROM AUTHOR]

Intrinsically disordered regions (IDRs) play a pivotal role in organellar remodeling. They transduce signals across membranes, scaffold signaling complexes, and mediate vesicular traffic. Their functions are regulated by constraining conformational ensembles through specific intra- and intermolecular interactions, physical tethering, and posttranslational modifications. The endoplasmic reticulum (ER)-phagy receptor FAM134B/RETREG1, known for its reticulon homology domain (RHD), includes a substantial C-terminal IDR housing the LC3 interacting motif. Beyond engaging the autophagic machinery, the function of the FAM134B-IDR is unclear. Here, we investigate the characteristics of the FAM134B-IDR by extensive modeling and molecular dynamics simulations. We present detailed structural models for the IDR, mapping its conformational landscape in solution and membrane-anchored configurations. Our analysis reveals that depending on the membrane anchor, the IDRs collapse onto the membrane and induce positive membrane curvature to varying degrees. The charge patterns underlying this Janus-like behavior are conserved across other ER-phagy receptors. We found that IDRs alone are sufficient to sense curvature. When combined with RHDs, they intensify membrane remodeling and drive efficient protein clustering, leading to faster budding, thereby amplifying RHD remodeling functions. Our simulations provide a perspective on IDRs of FAM134B, their Janus-like membrane interactions, and the resulting modulatory functions during large-scale ER remodeling. [ABSTRACT FROM AUTHOR]

Background and Aims: Evidence suggests that people react differently to the same diet due to inter-individual differences. However, few studies have investigated variation in response to dietary interventions based on individuals' baseline metabolic characteristics. This study aims to examine the differential reaction of metabotype subgroups to an OGTT and a dietary fiber intervention.Methods and Results: We assigned 356 healthy participants of an OGTT sub-study and a 12-week dietary fiber intervention sub-study within the enable cluster to three metabotype subgroups previously identified in the KORA F4 study population. To explore the association between plasma glucose level and metabotype subgroups, we used linear mixed models adjusted for age, sex, and physical activity. Individuals in different metabotype subgroups showed differential responses to OGTT. Compared to the healthy metabotype (metabotype 1), participants in intermediate metabotype (metabotype 2) and unfavorable metabotype (metabotype 3) had significantly higher plasma glucose concentrations at 120 min after glucose bolus (β = 7.881, p = 0.005; β = 32.79, p < 0.001, respectively). Additionally, the linear regression model showed that the Area under the curve (AUC) of plasma glucose concentrations was significantly different across the metabotype subgroups. The associations between metabotype subgroups and metabolic parameters among fiber intervention participants remained insignificant in the multivariate-adjusted linear model. However, the metabotype 3 had the highest mean reduction in insulin, cholesterol parameters (TC, LDLc, and non-HDLc), and systolic and diastolic blood pressure at the end of the intervention period.Conclusion: This study supports the use of the metabotype concept to identify metabolically similar subgroups and to develop targeted dietary interventions at the metabotype subgroup level for the primary prevention of diet-related diseases. [ABSTRACT FROM AUTHOR]

Vanadium oxide clusters with a mean diameter below 10 nm are investigated by high resolution Scanning Transmission Electron Microscopy (STEM), Electron Energy Loss Spectroscopy (EELS) and UV-vis absorption spectroscopy. The clusters are synthesised by sublimation from bulk vanadium(V) oxide, in combination with a pick-up by superfluid helium droplets. The latter act as reaction chambers which enable cluster growth under fully inert and solvent-free conditions. High-resolution STEM images of deposited vanadium oxide particles allowing for the determination of lattice constants, clearly indicate a dominating presence of V2O5. This finding is further supported by UV-vis absorption spectra of nanoparticles after deposition on fused silica substrates, which indicates that the oxidation state of the material is preserved over the entire process. From the results of the UV-vis measurement, the band gap of the nanosized V2O5 could be determined to be 3.3 eV. The synthesis approach provides a route to clean V2O5 clusters as it does not involve any surfactant or solvents, which is crucial for an unbiased measurement of intrinsic catalyst properties. [ABSTRACT FROM AUTHOR]

High levels of node power in Mobile Wireless Sensor Networks (MWSN) can have an effect on the reliability of a number of different aspects of the service. Due to their inherently low energy efficiency, sensor nodes lose power with every bit of data they transmit. In order to accomplish any data transfer, however, the nodes must engage in cooperative communication. To aid optimal routing in mobile wireless sensor networks, researchers have developed a new method inspired by the work of bee colony optimizers. To enhance service in a mobile wireless sensor network, we present a cluster energy hop-based dynamic route selection (CEH-DRS) that takes into account individual production zones. In this case, sensor nodes can collect data and send it out to the network. They also help with the routing of data packets coming from various origin nodes. Finally, this study optimizes the system's route while still meeting the criterion of selecting the shortest way. This technique improves cluster selection by taking into account the state of affairs in the area and other characteristics (such as throughput, delay and packet delivery ratio). It is also discovered that the soft computing approaches accurately detect and select the best path, whereas the conventional methods cannot. The proposed CEH-DRS method improved network performance in a better way to achieve higher throughput than all approaches like optimized route cache protocol-ad hoc on-demand distance vector, fuzzy and bee colony optimization, selectively turning ON/OFF the sensors, hidden Markov model. [ABSTRACT FROM AUTHOR]

Due to the uniqueness of the underwater environment, traditional data aggregation schemes face many challenges. Most existing data aggregation solutions do not fully consider node trustworthiness, which may result in the inclusion of falsified data sent by malicious nodes during the aggregation process, thereby affecting the accuracy of the aggregated results. Additionally, because of the dynamically changing nature of the underwater environment, current solutions often lack sufficient flexibility to handle situations such as node movement and network topology changes, significantly impacting the stability and reliability of data transmission. To address the aforementioned issues, this paper proposes a secure data aggregation algorithm based on a trust mechanism. By dynamically adjusting the number and size of node slices based on node trust values and transmission distances, the proposed algorithm effectively reduces network communication overhead and improves the accuracy of data aggregation. Due to the variability in the number of node slices, even if attackers intercept some slices, it is difficult for them to reconstruct the complete data, thereby ensuring data security. [ABSTRACT FROM AUTHOR]

Background: Food-related behaviour is a very complex topic. A common way to reduce complex issues to their essential content is to create a typology. In Germany, with regard to food-related behaviour, the creation of a typology has often been carried out by commercial research institutes, but also by (international) scientific institutes. The former have mostly used quantitative methods, the latter usually have a specific content focus. Within this study, we want to investigate how people integrate eating into their everyday lives while engaging with themselves and the environment, thereby living out personality development and related socialisation. Methods: 37 qualitative interviews were conducted and evaluated by means of content-structuring qualitative analysis and type-forming qualitative content analysis. Interviewees were recruited via recruitment calls using different channels, such as newspapers or university e-mail lists. Participants over the age of seventeen were eligible to take part in the study. Both the individual action processes and the interpretation processes regarding food-related behaviour were taken into account. The final sample consisted of 20 male and 18 female participants with an age range from 18 to 83. Results: The result were seven eating action types, namely: Eating as a way of life, The Relaxed, Eating as self-determination, Eating as a necessary Evil, The Adaptive, The Overstrained and The Controlled. Conclusions: We contribute to the study of food-related behaviour with the chosen qualitative method of type-building and by looking at how people integrate eating into their everyday lives. This contributes to a broader understanding of this phenomenon and complements the findings of existing commercial and academic food-related typing-building activities. Specifically, through identifying "The Overstrained" as a novel eating action type, this study adds to the literature in the field and may be a useful baseline for future research. [ABSTRACT FROM AUTHOR]

For future large-scale CubeSat applications in orbit, the deployer must accommodate a greater number of CubeSats and facilitate cluster releases. This paper introduces an improved A* algorithm tailored for CubeSat in-orbit transfer path planning. Unlike the traditional A* algorithm, this enhanced version incorporates a path coordination strategy to manage congestion caused by the simultaneous transfer of many CubeSats, ensuring they reach their designated release positions smoothly and thus significantly boosting the efficiency of CubeSat transfers. Additionally, the algorithm develops a cost model for attitude disturbances on the electromagnetic conveying platform and crafts an improved cost function. It strategically balances the reduction in attitude disturbances caused by CubeSat transfers with the efficiency of these transfers. The primary goal is to minimize platform disturbances while optimizing the number of steps CubeSats need to reach their intended positions. The effectiveness of this algorithm is demonstrated through detailed case studies, which confirm that during the CubeSat transfer process, the platform's attitude remains stable, and the transfer efficiency is well-managed, achieving efficient path planning for the in-orbit transfer of numerous CubeSats. [ABSTRACT FROM AUTHOR]

Uncertain Wireless Sensor Network (WSN) conditions create a continuous burden for ensuring feasible data communication. Particularly, the characteristics such as movement of sensor nodes, frequent link breaks, unexpected node failures, channel distortions and energy conservation limits of WSN make the data sessions at uncertain state. Under these conditions, the deployment of an optimal WSN model is a challenging task on the field. The existing solutions use various node management, clustering procedures and link management techniques against the uncertain issues of WSN fields. Yet the successful and stable data transmission is unpredictable in complex WSN environment. On the constraint, the proposed Optimal Dynamic Convex Hull Computation Model (ODCHM) is developed to initiate more sophisticated clustering principles to achieve better data delivery rate in WSNs. Under this model, the novel phases such as uncertain (reactive) quick hull principles, secure trust evaluation schemes, network dynamic monitoring principles, modified routing protocol (Hybrid and Clustered Multi-Path Routing Protocol, HCRP) and network regeneration procedures. According to this proposed model, reactive quick hull principles are creating and managing network boundaries against uncertain conditions of WSNs. In the next phase, secure trust evaluation procedures are executed to compute the trust cost functions, hash validations, event log validations and malicious event identification. Third phase of proposed model gives the technical benefits of creating random convex hull-based clusters on demand basis under uncertain WSN changes with the help of modified HCRP rules. The integrated technical solutions of proposed ODCHM are providing the better data delivery rate than existing techniques by 12% to 15%. The implementation details and results are given in appropriate section. [ABSTRACT FROM AUTHOR]

The overuse of chemical-based agricultural inputs has led to the degradation of soil with associated adverse effects on soil attributes and microbial population. This scenario leads to poor soil health and is reportedly on the rise globally. Additionally, chemical fertilizers pose serious risks to the ecosystem and human health. In this study, foliar sprays of biostimulant (AgroGain/LBS6) prepared from the cultivated, tropical red seaweed Kappaphycus alvarezii increased the phenotypic growth of Zea mays in terms of greater leaf area, total plant height, and shoot fresh and dry weights. In addition, LBS6 improved the accumulation of chlorophyll a and b, total carotenoids, total soluble sugars, amino acids, flavonoids, and phenolics in the treated plants. LBS6 applications also improved the total bacterial and fungal count in rhizospheric soil. The V3-V4 region of 16S rRNA gene from the soil metagenome was analyzed to study the abundance of bacterial communities which were increased in the rhizosphere of LBS6-treated plants. Treatments were found to enrich beneficial soil bacteria, i.e., Proteobacteria, especially the classes Alphaproteobacteria, Cyanobacteria, Firmicutes, Actinobacteriota, Verrucomicrobiota, Chloroflexi, and Acidobacteriota and several other phyla related to plant growth promotion. A metagenomic study of those soil samples from LBS6-sprayed plants was correlated with functional potential of soil microbiota. Enrichment of metabolisms such as nitrogen, sulfur, phosphorous, plant defense, amino acid, co-factors, and vitamins was observed in soils grown with LBS6-sprayed plants. These results were further confirmed by a significant increase in the activity of soil enzymes such as urease, acid phosphatase, FDAse, dehydrogenase, catalase, and biological index of fertility in the rhizosphere of LBS6-treated corn plant. These findings conclude that the foliar application of LBS6 on Z. mays improves and recruits beneficial microbes and alters soil ecology in a sustainable manner. [ABSTRACT FROM AUTHOR]

In recent years, CRISPR-Cas toolboxes for Streptomyces editing have rapidly accelerated natural product discovery and engineering. However, Cas efficiencies are oftentimes strain-dependent, and the commonly used Streptococcus pyogenes Cas9 (SpCas9) is notorious for having high levels of off-target toxicity effects. Thus, a variety of Cas proteins is required for greater flexibility of genetic manipulation within a wider range of Streptomyces strains. This study explored the first use of Acidaminococcus sp. Cas12j, a hypercompact Cas12 subfamily, for genome editing in Streptomyces and its potential in activating silent biosynthetic gene clusters (BGCs) to enhance natural product synthesis. While the editing efficiencies of Cas12j were not as high as previously reported efficiencies of Cas12a and Cas9, Cas12j exhibited higher transformation efficiencies compared to SpCas9. Furthermore, Cas12j demonstrated significantly improved editing efficiencies compared to Cas12a in activating BGCs in Streptomyces sp. A34053, a strain wherein both SpCas9 and Cas12a faced limitations in accessing the genome. Overall, this study expanded the repertoire of Cas proteins for genome editing in actinomycetes and highlighted not only the potential of recently characterized Cas12j in Streptomyces but also the importance of having an extensive genetic toolbox for improving the editing success of these beneficial microbes. [ABSTRACT FROM AUTHOR]

Purpose: Innovativeness is crucial for industrial cluster firms to gain sustained competitive advantage. This study aims to investigate the effects of inter-firm coopetition on firm innovativeness within a cluster and examines the moderating role of institutional support. Design/methodology/approach: This research adopts an empirical survey method using multi-source data from 181 industrial cluster firms. Regression is used to test the hypotheses of this study. Findings: The results show that cooperation and constructive conflict promote firm innovativeness, while destructive conflict is detrimental to firm innovativeness. Moreover, the study also finds that cooperation interacts with both types of conflict to affect firm innovativeness, where cooperation and constructive conflict interact negatively on firm innovativeness, while cooperation and destructive conflict interact positively on firm innovativeness. In addition, institutional support weakens the effects of cooperation and destructive conflict on innovativeness, respectively, but has no significant moderating effect on the relationship between constructive conflict and innovativeness. Originality/value: These findings enrich the current research on coopetition. The interaction effects of cooperation and both types of conflict on innovativeness deepen the concept of coopetition and responds to the call to further explore the interaction effects within coopetition. The moderating role of institutional support fills a gap in the empirical research on the role of institutional factors affecting coopetition on innovation and also provides valuable suggestions for firm managers and governments in industrial clusters. [ABSTRACT FROM AUTHOR]

Stress-related overeating can lead to excessive weight gain, increasing the risk of metabolic and cardiovascular disease. Mindfulness meditation has been demonstrated to reduce stress and increase interoceptive awareness and could, therefore, be an effective intervention for stress-related overeating behavior. To investigate the effects of mindfulness meditation on stress-eating behavior, meditation-naïve individuals with a tendency to stress-eat (N = 66) participated in either a 31-day, web-based mindfulness meditation training or a health training condition. Behavioral and resting-state fMRI data were acquired before and after the intervention. Mindfulness meditation training, in comparison to health training, was found to significantly increase mindfulness while simultaneously reducing stress- and emotional-eating tendencies as well as food cravings. These behavioral results were accompanied by functional connectivity changes between the hypothalamus, reward regions, and several areas of the default mode network in addition to changes observed between the insula and somatosensory areas. Additional changes between seed regions (i.e., hypothalamus and insula) and brain areas attributed to emotion regulation, awareness, attention, and sensory integration were observed. Notably, these changes in functional connectivity correlated with behavioral changes, thereby providing insight into the underlying neural mechanisms of the effects of mindfulness on stress-eating. Clinical trial on the ISRCTN registry: trial ID ISRCTN12901054 [ABSTRACT FROM AUTHOR]

17-β-hydroxysteroid dehydrogenase 13 (HSD17B13), a lipid droplet-associated enzyme, is primarily expressed in the liver and plays an important role in lipid metabolism. Targeted inhibition of enzymatic function is a potential therapeutic strategy for treating steatotic liver disease (SLD). The present study is aimed at investigating the effects of the first selective HSD17B13 inhibitor, BI-3231, in a model of hepatocellular lipotoxicity using human cell lines and primary mouse hepatocytes in vitro. Lipotoxicity was induced with palmitic acid in HepG2 cells and freshly isolated mouse hepatocytes and the cells were coincubated with BI-3231 to assess the protective effects. Under lipotoxic stress, triglyceride (TG) accumulation was significantly decreased in the BI-3231-treated cells compared with that of the control untreated human and mouse hepatocytes. In addition, treatment with BI-3231 led to considerable improvement in hepatocyte proliferation, cell differentiation, and lipid homeostasis. Mechanistically, BI-3231 increased the mitochondrial respiratory function without affecting β-oxidation. BI-3231 inhibited the lipotoxic effects of palmitic acid in hepatocytes, highlighting the potential of targeting HSD17B13 as a specific therapeutic approach in steatotic liver disease. [ABSTRACT FROM AUTHOR]

The article aims to explore the evolutionary stages and paths of an innovation network in industrial cluster through case studying of Nanchong SSGIC in China. After reviewing the structure of the innovation network in industrial cluster, the article considers that the industrial cluster innovation network could be divided into three stages (the initial formation stage, the aggregation development stage, and the coordinated development stage) and probes different evolutionary paths based on the perspective of network structure characteristics and hub enterprises. Through the case analysis of the Nanchong SSGIC, the results show that (1) the evolutionary stages which be divided by this article could be well used in the analysis of the development stage of the Nanchong SSGIC innovation network; (2) based on the structural characteristics of the innovation network and the development of hub enterprises in Nanchong SSGIC, moving forward according to the path E is a good choice; (3) the strong support of the governments is an important guarantee force for the evolution of the cluster innovation network; (4) and a clear understanding of the characteristics of the evolutionary stages and paths of the Nanchong SSGIC innovation network is important for guiding the development of the cluster. The findings provide a valuable reference for research in relevant fields, especially for the study of traditional industrial clusters in developing countries. [ABSTRACT FROM AUTHOR]

Life cycle assessment (LCA) is a fundamental tool used in eco-design. However, it can be costly and resource intensive. We take steps toward the automation of the inventory and impact analyses stages of LCA via the proposal and development of a case-based reasoning (CBR) procedure to estimate the ecological effects of a product. The case memory in CBR, which contains representations and ecological effects of known products, is organized using an extension of the function-behavior-structure (FBS) representation for products. The extension includes ecological characteristics and values. We develop similarity metrics to measure the distance between cases in the case memory and the new product. The k-medoids algorithm is used to cluster the case memory, our metrics enable cluster retrieval and case selection, and multiple linear regression analysis is employed for adaptation. Using a database of 100 fans, we test the accuracy of the proposed approach on a cross flow fan not in the database. The method gives ecological effect estimates within 3% of the true values when there are similar fans in the retrieved cluster and about 7% when the retrieved cluster does not contain similar fans. [ABSTRACT FROM PUBLISHER]

Background: Interactions between tumor cells and cells in the microenvironment contribute to tumor development and metastasis. The spatial arrangement of individual cells in relation to each other influences the likelihood of whether and how these cells interact with each other. Methods: This study investigated the effect of spatial distribution on the function of leukocyte subsets in the microenvironment of human head and neck squamous cell carcinoma (HNSCC) using multiplex immunohistochemistry (IHC). Leukocyte subsets were further classified based on analysis of two previously published HNSCC single-cell RNA datasets and flow cytometry (FC). Results: IHC revealed distinct distribution patterns of leukocytes differentiated by CD68 and CD163. While CD68hiCD163lo and CD68hiCD163hi cells accumulated near tumor sites, CD68loCD163hi cells were more evenly distributed in the tumor stroma. PD-L1hi and PD-1hi cells accumulated predominantly around tumor sites. High cell density of PD-L1hi CD68hiCD163hi cells or PD-1hi T cellsnear the tumor site correlated with improved survival. FC and single cell RNA revealed high variability within the CD68/CD163 subsets. CD68hiCD163lo and CD68hiCD163hi cells were predominantly macrophages (MF), whereas CD68loCD163hi cells appeared to be predominantly dendritic cells (DCs). Differentiation based on CD64, CD80, CD163, and CD206 revealed that TAM in HNSCC occupy a broad spectrum within the classical M1/M2 polarization. Notably, the MΦ subsets expressed predominantly CD206 and little CD80. The opposite was observed in the DC subsets. Conclusion: The distribution patterns and their distinct interactions via the PDL1/PD-1 pathway suggest divergent roles of CD68/CD163 subsets in the HNSCC microenvironment. PD-L1/PD-1 interactions appear to occur primarily between specific cell types close to the tumor site. Whether PD-L1/PD-1 interactions have a positive or negative impact on patient survival appears to depend on both the spatial localization and the entity of the interacting cells. Co-expression of other markers, particularly CD80 and CD206, supports the hypothesis that CD68/CD163 IHC subsets have distinct functions. These results highlight the association between spatial leukocyte distribution patterns and the clinical presentation of HNSCC. [ABSTRACT FROM AUTHOR]

Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) is one of the leading causes of foodborne infections associated with broilers and laying hens. Portugal has had the lowest notification rates of salmonellosis in recent years, due to the vaccinations of layer and breeder flocks and strict compliance with biosecurity measures. However, data about the genetic diversity of S. Enteritidis in Portugal are scarce. In this study, 102 S. Enteritidis isolates selected from human (n = 63) and non-human sources (n = 39) were characterized by serotyping, antimicrobial susceptibility, and whole genome sequencing. The S. Enteritidis population was mainly resistant to fluoroquinolones, and a sole isolate showed resistance to extended-spectrum cephalosporins. ST11 was the most frequent sequence type, and three novel STs from human isolates (ST9236, ST4457, and ST9995) were assigned. Several Salmonella pathogenic islands (SPI) and Putative SPI were present in the genomes, namely SPI-1, 2, 3, 4, 5, 9, 10, 12, 13, and 14, C63PI, CS54_island, and 170 virulence genes were identified. The phylogenetic analysis revealed that strains from Portugal are genetically heterogeneous regarding sample type, collection date, and genetic content. This study increases the available data, essential to a better characterization of strains in a global context. [ABSTRACT FROM AUTHOR]