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Heat stress (HS) is well known to influence animal health and livestock productivity negatively. Heat stress is a multi-billion-dollar global problem. It impairs animal performance during summer when animals are exposed to high ambient temperatures, direct and indirect solar radiations, and humidity. While significant developments have been achieved over the last few decades to mitigate the negative impact of HS, such as physical modification of the environment to protect the animals from direct heat, HS remains a significant challenge for the dairy industry compromising dairy cattle health and welfare. In such a scenario, it is essential to have a thorough understanding of how the immune system of dairy cattle responds to HS and identify the variable responses among the animals. This understanding could help to identify heat-resilient dairy animals for breeding and may lead to the development of climate resilient breeds in the future to support sustainable dairy cattle production. There are sufficient data demonstrating the impact of increased temperature and humidity on endocrine responses to HS in dairy cattle, especially changes in concentration of hormones like prolactin and cortisol, which also provide an indication of the likely im-pact on the immune system. In this paper, we review the recent research on the impact of HS on immunity of calves during early life to adult lactating and dry cows. Additionally, different strategies for amelioration of negative effects of HS have been presented.

Aims/hypothesisType 2 diabetes mellitus has been implicated as a risk factor for hearing loss, with possible mechanisms including microvascular disease, acoustic neuropathy or oxidative stress. A few small studies have examined the longitudinal association between type 2 diabetes and hearing loss, but larger studies are needed. Our objective was to examine whether type 2 diabetes (including diabetes duration) is associated with incident hearing loss in two prospective cohorts: Nurses’ Health Studies (NHS) I and II.MethodsWe conducted a longitudinal study of 139,909 women to examine the relationship between type 2 diabetes and the risk of self-reported incident hearing loss. A physician-diagnosis of diabetes was ascertained from biennial questionnaires. The primary outcome was hearing loss reported as moderate or worse in severity (categorised as a ‘moderate or severe’ hearing problem, or ‘moderate hearing trouble or deaf’) on questionnaires administered in 2012 in NHS I and 2009 or 2013 in NHS II. Cox proportional hazards regression was used to adjust for potential confounders.ResultsDuring >2.4 million person-years of follow-up, 664 cases of moderate or worse hearing loss were reported among those with type 2 diabetes and 10,022 cases among those without type 2 diabetes. Compared with women who did not have type 2 diabetes, those with type 2 diabetes were at higher risk for incident moderate or worse hearing loss (pooled multivariable-adjusted HR 1.16 [95% CI 1.07, 1.27]). Participants who had type 2 diabetes for ≥8 years had a higher risk of moderate or worse hearing loss compared with those without type 2 diabetes (pooled multivariable-adjusted HR 1.24 [95% CI 1.10, 1.40]).Conclusions/interpretationIn this large longitudinal study, type 2 diabetes was associated with a modestly higher risk of moderate or worse hearing loss. Furthermore, longer duration diabetes was associated with a higher risk of moderate or worse hearing loss.

This article presents the recent advancements in recirculating aquaculture systems (RAS). The review explores new developments and potential future breakthroughs in RAS systems across leading countries. It highlights technical and technological advancement in plant management aimed at improving water quality, production efficiency, and animal welfare. A significant aspect of recent progress is the integration of artificial intelligence (AI), which is being used to optimize system performance, enhance monitoring, and support more precise and predictive management strategies. The review also addresses advancements in pathogen control and the prevention of disease outbreaks. Specific case studies of cutting‐edge RAS systems from different parts of the world are discussed. The review also investigates how the improvements in RAS technology can help mitigate environmental impact. Finally, the paper focuses on advancements in the production of six fish species farmed in Europe, namely Atlantic salmon ( Salmo salar ), European seabass ( Dicentrarchus labrax ), gilthead seabream ( Sparus aurata ), yellowtail kingfish ( Seriola lalandi ), arctic charr ( Salvelinus alpinus ), and rainbow trout ( Oncorhynchus mykiss ). This review is part of the ERA‐NET BlueBio cofound‐funded project titled “Optimizing land‐based fish production in next generation digital recirculating aquaculture systems,” which is focusing on the above‐mentioned fish species.

Bilingualism is associated with distinct patterns of resting-state functional brain connectivity – a consequence of ongoing language control demands that do not apply to monolinguals. However, it is not well understood how these patterns affect, and are affected by, brain activation for domain-general cognitively demanding tasks. Here, we employ a novel task-driven resting-state electroencephalography design including an implicit Lindenmayer grammar learning task, which tracks aperiodic and hierarchical dependencies, to determine task-related functional connectivity changes in bilinguals. Quantified bilingual experience was used as a predictor of directional effects, using Generalised Additive Models to account for non-linear patterns. Our results revealed post-task alterations to connectivity involving increased involvement of occipital regions, reduced involvement of frontal and central regions, and faster reaction times to stimuli at higher levels of bilingual experience. Crucially, the regions implicated post-task appear to reflect task-relevant regions which are involved in the language and executive control networks, reflecting greater short-term task-driven flexibility. These findings have important implications for our understanding of how domain-general processing and connectivity are shaped by linguistic experience.

Purpose - Cause-related marketing activities are increasingly becoming a meaningful part of corporate marketing plans. This paper aims to examine the relationship between the company, cause and customer, and how fit between these three groups influences consumer response via generating a positive attitude toward the company-cause alliance and purchase intent for the sponsored product.Design methodology approach - Two studies are carried out, first among students and second among consumers.Findings - Two studies (study 1=232 students, study 2=531 consumers) demonstrate that company-cause fit improves attitude toward the company-cause alliance and increases purchase intent. Additionally, this effect is enhanced under conditions of customer-company and customer-cause congruence, and the consumer's overall attitude toward the sponsoring company. Skepticism about the company's motivation for participating in a cause-related marketing initiative was not relevant to consumer purchase decisions.Research limitations implications - Results from these studies suggest that consumers may in fact make two different assessments of the sponsoring company in a cause-related marketing campaign. One assessment may be more cognitive where the consumer compares his or her own identity to that of the company: \"Is this company like me? Are our identities alike?\" The second assessment is more affective or emotional: \"Do I like this company? Do I feel positively about this company?\" The strength of the consumer sample suggests that when building a cause-related marketing program, marketing managers should select a cause that makes sense to the consumer to be a partner in the alliance, build a general positive feeling toward their brand, and limit any self-serving promotion of the cause-related marketing alliance to the target consumer population.Originality value - The paper provides useful information on the relationship between the company, cause and customer, and how the fit between these three groups influences consumer response.

Symbiosis between insects and bacteria has been established countless times. While it is well known that the symbionts originated from a variety of different bacterial taxa, it is usually difficult to determine their environmental source and a route of their acquisition by the host. In this study, we address this question using a model of Neisseriaceae symbionts in rodent lice. These bacteria established their symbiosis independently with different louse taxa ( Polyplax , Hoplopleura , Neohaematopinus ), most likely from the same environmental source. We first applied amplicon analysis to screen for candidate source bacterium in the louse environment. Since lice are permanent ectoparasites, often specific to the particular host, we screened various microbiomes associated with three rodent species ( Microtus arvalis , Clethrionomys glareolus , and Apodemus flavicollis ). The analyzed samples included fur, skin, spleen, and other ectoparasites sampled from these rodents. The fur microbiome data revealed a Neisseriaceae bacterium, closely related to the known louse symbionts. The draft genomes of the environmental Neisseriaceae, assembled from all three rodent hosts, converged to a remarkably small size of approximately 1.4 Mbp, being even smaller than the genomes of the related symbionts. Our results suggest that the rodent fur microbiome can serve as a source for independent establishment of bacterial symbiosis in associated louse species. We further propose a hypothetical scenario of the genome evolution during the transition of a free-living bacterium to the member of the rodent fur-associated microbiome and subsequently to the facultative and obligate louse symbionts.

To investigate if the timing of initiation of invasive mechanical ventilation (IMV) for critically ill patients with COVID-19 is associated with mortality. The data for this study were derived from a multicenter cohort study of critically ill adults with COVID-19 admitted to ICUs at 68 hospitals across the US from March 1 to July 1, 2020. We examined the association between early (ICU days 1-2) versus late (ICU days 3-7) initiation of IMV and time-to-death. Patients were followed until the first of hospital discharge, death, or 90 days. We adjusted for confounding using a multivariable Cox model. Among the 1879 patients included in this analysis (1199 male [63.8%]; median age, 63 [IQR, 53-72] years), 1526 (81.2%) initiated IMV early and 353 (18.8%) initiated IMV late. A total of 644 of the 1526 patients (42.2%) in the early IMV group died, and 180 of the 353 (51.0%) in the late IMV group died (adjusted HR 0.77 [95% CI, 0.65-0.93]). In critically ill adults with respiratory failure from COVID-19, early compared to late initiation of IMV is associated with reduced mortality.

Purpose Presently, there is a rising awareness of the additional health benefits and market potential for functional foods. Among various functional foods short chain Fructooligosaccharides (FOS) have make its prestige in food industry. Therefore, FOS producing enzymes seems very promising as in the future, FOS markets are expected to thriving worldwide. Keeping in view the potential of microbial Fructosyltransferase in FOS production, an attempt has been made to produce FTase of microbial origin followed by its partial purification and characterization. Methods Stevia rebaudiana was exploited to isolate Fructosyltransferase (FTase) enzyme producing endophytic bacteria. Preliminary screening to select FTase producers was done by Triphenyl Tetrazolium Chloride (TTC) plate assay. Fructosyltransferase producer was identified by morphological, biochemical techniques followed by 16S rRNA gene technique. Fructosyltransferase production of B. stercoris S1 was enhanced by optimization of inoculum size, incubation time, temperature, pH of medium, carbon source concentration by following one variable at time method. Partial purification of FTase was achieved by ammonium sulphate precipitation at 30–60%. Partially purified enzyme was characterized for its temperature, pH and shelf stability. Results In total 07 bacterial isolates were isolated. The bacterial isolate S1 was selected as it exhibited maximum zone of hydrolysis (22 mm) in TTC plate assay. Quantitative screening was done in terms of transfructosylating activities. Isolate S1 exhibited 50.06 U/ml. Maximum Fructosyltransferase activity 119.55 U/ml was recorded in nutrient broth supplemented with 60% sucrose at 72 h with an optimized pH of 6.0 at 40 °C. FTase titres after partial purification were 161.25 U/ml with specific activity 497.68 U/mg, purification fold and recovery percent 1.73 and 73.6% respectively. Partially purified FTase were found active in a temperature range 30 0 C to 80 0 C and in pH range of 5.0 to 9.0. FTase was found stable at -20 0 C for 45 days. Conclusion The results obtained showed that the B. stercoris S1 represents a promising source for FTase enzyme that can be efficiently utilized for FOS production.

AI is becoming increasingly recognised as a key enabler of Sustainable Development Goals 6 and 7, but there is a lack of integrated evidence of AI applications in the Water–Sanitation–Hygiene and Clean Energy (WASH–CE) nexus. The study presents bibliometric analysis of 11,817 publications (2016–2024) collected from Dimensions database. VOSviewer and Biblioshiny were used for bibliometric mapping and network analyses to assess publication trends, major journals and institutions, keywords, and international collaboration. Outcomes point to a pronounced upsurge in AI-infused WASH-CE (Water, Sanitation and Hygiene is an acronym for WASH) research post-2019, registering an average annual growth rate of 23.47%. China was the biggest contributor followed by the United States, India, and Australia, while Asian and Middle Eastern countries collaborated strongly with one another. This thematic evolution signifies a shift from traditional statistical methods to more advanced artificial intelligence techniques such as deep learning, transformer models, reinforcement learning, federated learning, explainable AI, etc. The paper proposes a systematic mapping of global research patterns which will help identify structural gaps and emerging priorities and thereby act as a foundation for evidence-based, scalable, inclusive and policy-relevant WASH–CE AI solutions.