Corrigendum: What can the common fruit fly teach us about stroke?: lessons learned from the hypoxic tolerant Drosophila melanogaster.

[This corrects the article DOI: 10.3389/fncel.2024.1347980.].

What can the common fruit fly teach us about stroke?: lessons learned from the hypoxic tolerant Drosophila melanogaster.

Stroke, resulting in hypoxia and glucose deprivation, is a leading cause of death and disability worldwide. Presently, there are no treatments that reduce neuronal damage and preserve function aside from tissue plasminogen activator administration and rehabilitation therapy. Interestingly, Drosophila melanogaster, the common fruit fly, demonstrates robust hypoxic tolerance, characterized by minimal effects on survival and motor function following systemic hypoxia. Due to its organized brain, conserved neurotransmitter systems, and genetic similarity to humans and other mammals, uncovering the mechanisms of Drosophila's tolerance could be a promising approach for the development of new therapeutics. Interestingly, a key facet of hypoxic tolerance in Drosophila is organism-wide metabolic suppression, a response involving multiple genes and pathways. Specifically, studies have demonstrated that pathways associated with oxidative stress, insulin, hypoxia-inducible factors, NFκB, Wnt, Hippo, and Notch, all potentially contribute to Drosophila hypoxic tolerance. While manipulating the oxidative stress response and insulin signaling pathway has similar outcomes in Drosophila hypoxia and the mammalian middle cerebral artery occlusion (MCAO) model of ischemia, effects of Notch pathway manipulation differ between Drosophila and mammals. Additional research is warranted to further explore how other pathways implicated in hypoxic tolerance in Drosophila, such as NFκB, and Hippo, may be utilized to benefit mammalian response to ischemia. Together, these studies demonstrate that exploration of the hypoxic response in Drosophila may lead to new avenues of research for stroke treatment in humans.

Safely and autonomously cutting meat with a collaborative robot arm.

Labor shortages in the United States are impacting a number of industries including the meat processing sector. Collaborative technologies that work alongside humans while increasing production abilities may support the industry by enhancing automation and improving job quality. However, existing automation technologies used in the meat industry have limited collaboration potential, low flexibility, and high cost. The objective of this work was to explore the use of a robot arm to collaboratively work alongside a human and complete tasks performed in a meat processing facility. Toward this objective, we demonstrated proof-of-concept approaches to ensure human safety while exploring the capacity of the robot arm to perform example meat processing tasks. In support of human safety, we developed a knife instrumentation system to detect when the cutting implement comes into contact with meat within the collaborative space. To demonstrate the capability of the system to flexibly conduct a variety of basic meat processing tasks, we developed vision and control protocols to execute slicing, trimming, and cubing of pork loins. We also collected a subjective evaluation of the actions from experts within the U.S. meat processing industry. On average the experts rated the robot's performance as adequate. Moreover, the experts generally preferred the cuts performed in collaboration with a human worker to cuts completed autonomously, highlighting the benefits of robotic technologies that assist human workers rather than replace them. Video demonstrations of our proposed framework can be found here: https://youtu.be/56mdHjjYMVc .

Rumen fermentation of meal-fed sheep in response to diets formulated to vary in fiber and protein degradability.

The concentration of volatile fatty acid (VFA) provides an imprecise view of VFA dynamics due to the confounding effects of fluid pool size and dynamics. Determination of VFA flux using isotope is expensive and a complex methodology. Therefore, a rapid and affordable approach to explore VFA dynamics may allow comprehensive characterization of VFA availability. The objective of this study was to explore the use of VFA dynamics generated by meal feeding to derive time-series rates of VFA apparent appearance and disappearance driven by different protein and fiber sources. Six ruminally cannulated wethers were fed diets containing timothy hay or beet pulp (TH and BP) and soybean meal (SBM) or heated soybean meal (HSBM). Diets were, TH + HSBM; TH + SBM; BP + HSBM; and BP + SBM and the experimental design was a partially replicated 4 × 4 Latin Square. Concentrations of VFA and polyethylene glycol (PEG) in rumen fluid samples were estimated. Concentrations of PEG were used to estimate fluid passage and volume to calculate VFA mass, and fluid-mediated exit. Maximum apparent appearance rate (mmol/h), the rate of apparent appearance decline (mmol/mmol/h), mean apparent appearance flux (mmol/h), mean apparent disappearance (mmol/h), and apparent disappearance rate (mmol/mmol/h) were estimated by deriving a 1 pool model for each VFA on a mass basis where appearance was assumed to follow an exponential decay pattern and disappearance followed mass-action kinetics. Statistical analyses were conducted using a linear mixed effect regression with fixed effects for fiber source, protein source, and their interaction, as well as random effects for animal and period. Rumen fluid volume (L) was greater in HSBM diets (P = 0.033) and fluid passage (%/h) was greater in SBM diets (P = 0.048). Concentrations (higher acetate and butyrate, P = 0.002 and 0.004, respectively) and molar proportions (higher valerate, P = 0.035) of VFA were affected only by fiber source; however, protein source and fiber source interacted to significantly influence apparent appearance rates and absorption rates of many major VFA. On a flux basis, HSBM supported significantly elevated mean disappearance of propionate (P = 0.033). This data demonstrates that time-series evaluation of fermentation dynamics, including fluid dynamics and VFA concentrations can be used to estimate apparent appearance and disappearance of VFA. Although further work is needed to confirm the alignment of these estimates with measurements of VFA supplies to the animal, this modeling approach may provide a simpler way to better understand the kinetics of rumen.

We estimated apparent appearance, apparent disappearance, appearance, and disappearance rates of rumen volatile fatty acid (VFA) of sheep in response to the different degradability of nutrients using time-series fermentation indicators with regular meal feeding. Two fiber sources (timothy hay [TH], and beet pulp [BP]) and two protein sources (soybean meal [SBM], and heat-treated soybean meal [HSBM]) were used in combination to prepare four dietary treatments. Polyethylene glycol (PEG) was used as the fluid marker to estimate rumen fluid volume and passage rate. The dynamics of VFA were estimated by deriving one pool model for individual VFA and concentrations of VFA, rumen fluid volume, and fluid passage rate were used in calculations. The interaction effect of protein and fiber source significantly influenced apparent appearance rates and disappearance rates of many major VFA. Significantly altered VFA dynamics, especially apparent disappearance was associated with HSBM-based diets. In conclusion, use of time-series evaluation of fermentation dynamics provides a minimal approach to integrate fluid dynamics and VFA concentrations to estimate apparent appearance and disappearance of VFA. With further development of this approach, we assume that estimated VFA dynamics will provide a better depiction of rumen VFA beyond concentrations and molar proportions in making inferences on rumen fermentation.

Abdominal computed tomography and exploratory laparotomy have high agreement in dogs with surgical disease.

OBJECTIVE: To compare the results of abdominal CT with exploratory laparotomy in the dog. ANIMALS: 100 client-owned dogs from 1 academic institution. METHODS: Medical records were searched for dogs that had undergone a preoperative abdominal CT scan read by a board-certified veterinary radiologist followed by an exploratory laparotomy. CT and surgical reports were compared. RESULTS: The overall agreement between abdominal CT scan and exploratory laparotomy in all cases was 97%. Overall, there was no evidence that proportion agreement differed on the basis of body condition score, time interval between CT and surgery, or oncologic versus nononcologic disease. CLINICAL RELEVANCE: Abdominal CT scan read by a board-certified diplomate is a sensitive presurgical diagnostic tool for surgical abdominal disease in the dog. When performing a specific abdominal surgery, it is acceptable for the surgeon to fully explore the abdomen or forego it for a smaller approach to the organ of interest if an abdominal CT was performed prior.

Effects of wearable therapies on jump performance in sport horses.

Introduction: Failure to properly prepare the equine athlete for exercise and support post-exercise recovery is a contributing factor to physical breakdown and lameness. Equine physiotherapy was not introduced until the early twentieth century and has since evolved to allow for wearable therapies such as therapeutic boots to be accessible to a broad spectrum of equestrians. The purpose of this study was to evaluate the effects of ceramic boots, boots combining vibration and cryotherapy, and boots containing tourmaline on the performance of sport horses during jumping as well as to examine changes in vital signs in response to treatment. Methods: Eight healthy horses received the 3 therapeutic boot treatments or a control (no boot) in a Latin square experiment for a period of 5 days each. Horses performed approximately 10 min of exercise through a jump chute for the 5 consecutive days and jump performance parameters were recorded during each exercise session. Therapeutics were applied in the morning prior to exercise per the manufacturer's recommendation and were removed only for exercise. Results and Discussion: In a Bayesian network analysis, changes in vital signs (heart rate, respiration, and temperature) were driven by individual animal, rather than boot treatment. Jump performance was influenced by boot treatment, physiological measurements, and individual animal. Therapeutic boots were associated with changes in conditional probabilities of numerous performance outcomes. This study indicates the use of wearable therapies may result in improved performance outcomes of sport horses in jumping exercises.

Advice-giving skills in pre-registration physiotherapy training.

BACKGROUND: With increased emphasis on self-management in healthcare, clinicians need outstanding skills in offering advice and empowering patients to attain an optimal outcome. OBJECTIVES: This study explores how undergraduate physiotherapists acquire knowledge, skills, and confidence to offer advice to patients in clinical practice. METHODS: Convenience sampling was used to recruit 50 BSc and MSc pre-registration physiotherapy students across all years of study in one university in southern England, UK. Semi-structured interviews were conducted for first year BSc students (n = 13). Six focus groups of mixed BSc and MSc students were conducted, three groups (n = 15 students) were mid-training, and three groups (n = 22 students) were in their final year. RESULTS: Thematic analysis identified 6 themes: advice content; a patient-centered approach; delivery; acquisitions; perceptions; and uptake of advice. Students placed high value on advice-giving, drawing upon multiple learning opportunities, however they felt under-prepared to deliver this skill in practice. Furthermore, perceptions of their student status, and pressures to perform on graded placements were reported to influence the advice they offered to patients. CONCLUSIONS: Developing high-level skills in promoting self-management is essential in physiotherapy, this study highlights the challenges for students to develop these skills. Academic and practice educators must explicitly enable and support students to develop the knowledge and skills to confidently offer high-quality advice to patients.

Invited review: integration of technologies and systems for precision animal agriculture-a case study on precision dairy farming.

Precision livestock farming (PLF) offers a strategic solution to enhance the management capacity of large animal groups, while simultaneously improving profitability, efficiency, and minimizing environmental impacts associated with livestock production systems. Additionally, PLF contributes to optimizing the ability to manage and monitor animal welfare while providing solutions to global grand challenges posed by the growing demand for animal products and ensuring global food security. By enabling a return to the "per animal" approach by harnessing technological advancements, PLF enables cost-effective, individualized care for animals through enhanced monitoring and control capabilities within complex farming systems. Meeting the nutritional requirements of a global population exponentially approaching ten billion people will likely require the density of animal proteins for decades to come. The development and application of digital technologies are critical to facilitate the responsible and sustainable intensification of livestock production over the next several decades to maximize the potential benefits of PLF. Real-time continuous monitoring of each animal is expected to enable more precise and accurate tracking and management of health and well-being. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring auditability in value chains while assuaging concerns associated with labor shortages. Despite notable advances in PLF technology adoption, a number of critical concerns currently limit the viability of these state-of-the-art technologies. The potential benefits of PLF for livestock management systems which are enabled by autonomous continuous monitoring and environmental control can be rapidly enhanced through an Internet of Things approach to monitoring and (where appropriate) closed-loop management. In this paper, we analyze the multilayered network of sensors, actuators, communication, networking, and analytics currently used in PLF, focusing on dairy farming as an illustrative example. We explore the current state-of-the-art, identify key shortcomings, and propose potential solutions to bridge the gap between technology and animal agriculture. Additionally, we examine the potential implications of advancements in communication, robotics, and artificial intelligence on the health, security, and welfare of animals.

Precision technologies are revolutionizing animal agriculture by enhancing the management of animal welfare and productivity. To fully realize the potential benefits of precision livestock farming (PLF), the development and application of digital technologies are needed to facilitate the responsible and sustainable intensification of livestock production over the next several decades. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring audibility in value chains while assuaging concerns associated with labor shortages. In this paper, we analyze the multilayered network of sensors, actuators, communication, and analytics currently in use in PLF. We analyze the various aspects of sensing, communication, networking, and intelligence on the farm leveraging dairy farms as an example system. We also discuss the potential implications of advancements in communication, robotics, and artificial intelligence on the security and welfare of animals.

Beclin 1 regulates astrocyte phagocytosis and phagosomal recruitment of retromer.

Phagocytosis plays an important role in maintaining brain homeostasis and when impaired can result in the accumulation of unwanted cellular material. While microglia are traditionally considered the phagocytes of the brain, astrocytes are also capable of phagocytosis and are the most numerous cells in the brain. In Alzheimer's disease (AD), astrocytes can be found surrounding ß-amyloid (Aß) plaques yet they seem unable to eliminate these deposits, suggesting phagocytosis may be impaired in AD. Mechanisms that might diminish astrocyte phagocytosis in AD are currently unclear. Here, we demonstrate that the autophagy protein beclin 1, which is reduced in AD, plays a role in regulating astrocyte phagocytosis. Specifically, we show that reducing beclin 1 in C6 astrocytes impairs the phagocytosis of latex beads, reduces retromer levels, and impairs retromer recruitment to the phagosomal membrane. Furthermore, we show that these beclin 1-mediated changes are accompanied by reduced expression of the phagocytic receptor Scavenger Receptor Class B type I (SR-BI). Collectively, these findings suggest a critical role for the protein beclin 1 in both receptor trafficking and receptor-mediated phagocytosis in astrocytes. Moreover, these findings provide insight into mechanisms by which astrocytes may become impaired in AD.

Finisher lamb growth and rumen fermentation responses to the plane of nutrition and naturally occurring coccidiosis.

The objective of the present study was to investigate the interaction of plane of nutrition and naturally occurring coccidiosis on finisher lamb growth performance, FAMACHA score, and rumen volatile fatty acid profile. The study included 30 Suffolk, Dorset or Suffolk x Dorset lambs and were divided into 2 groups based on their initial body weight and assigned to 2 feeding groups differing in dietary energy intake to create lambs representing divergent growth curves due to differing nutritional management. Lambs with naturally occurring coccidiosis and healthy lambs were present in both feeding groups making a 2 × 2 factorial arrangement of treatments, (a) high plane of nutrition (HPN) lambs with no clinical coccidiosis diagnosis (HPNH), (b) HPN lambs with clinical coccidiosis (HPNC), (c) low plane of nutrition (LPN) lambs with no clinical coccidiosis diagnosis (LPNH), (d) LPN lambs with clinical coccidiosis (LPNC). Body weight and FAMACHA scores were recorded once every 2 weeks. On d 65 of feeding, lambs were slaughtered, and rumen fluid samples were collected and analyzed for volatile fatty acid concentrations. All response variables were analyzed statistically using a linear mixed effects model with fixed effects for plane of nutrition, health status, and a random effect for initial body weight nested within the pen. The total and average weight gain were not associated with planes of nutrition, health status, or the interaction. Health status had an impact on FAMACHA© score (P = 0.047) and concentration of isobutyrate (P = 0.037) and tended to affect total VFA (P = 0.085) and acetate (P = 0.071) concentrations. The interaction between the plane of nutrition and the health status tended to affect butyrate concentration (P = 0.058). These data support the conclusion that coccidiosis infection impacted on rumen fermentation in a manner independent of the plane of nutrition; however, the translation of these rumen level impacts did not translate to the production responses.

Network analysis to evaluate complexities in relationships among fermentation variables measured within continuous culture experiments.

The objective of this study was to leverage a frequentist (ELN) and Bayesian learning (BLN) network analyses to summarize quantitative associations among variables measured in 4 previously published dual-flow continuous culture fermentation experiments. Experiments were originally designed to evaluate effects of nitrate, defaunation, yeast, and/or physiological shifts associated with pH or solids passage rates on rumen conditions. Measurements from these experiments that were used as nodes within the networks included concentrations of individual volatile fatty acids, mM and nitrate, NO3-,%; outflows of non-ammonia nitrogen (NAN, g/d), bacterial N (BN, g/d), residual N (RN, g/d), and ammonia N (NH3-N, mg/dL); degradability of neutral detergent fiber (NDFd, %) and degradability of organic matter (OMd, %); dry matter intake (DMI, kg/d); urea in buffer (%); fluid passage rate (FF, L/d); total protozoa count (PZ, cells/mL); and methane production (CH4, mmol/d). A frequentist network (ELN) derived using a graphical LASSO (least absolute shrinkage and selection operator) technique with tuning parameters selected by Extended Bayesian Information Criteria (EBIC) and a BLN were constructed from these data. The illustrated associations in the ELN were unidirectional yet assisted in identifying prominent relationships within the rumen that were largely consistent with current understanding of fermentation mechanisms. Another advantage of the ELN approach was that it focused on understanding the role of individual nodes within the network. Such understanding may be critical in exploring candidates for biomarkers, indicator variables, model targets, or other measurement-focused explorations. As an example, acetate was highly central in the network suggesting it may be a strong candidate as a rumen biomarker. Alternatively, the major advantage of the BLN was its unique ability to imply causal directionality in relationships. Because the BLN identified directional, cascading relationships, this analytics approach was uniquely suited to exploring the edges within the network as a strategy to direct future work researching mechanisms of fermentation. For example, in the BLN acetate responded to treatment conditions such as the source of N used and the quantity of substrate provided, while acetate drove changes in the protozoal populations, non-NH3-N and residual N flows. In conclusion, the analyses exhibit complementary strengths in supporting inference on the connectedness and directionality of quantitative associations among fermentation variables that may be useful in driving future studies.

This study leveraged frequentist (ELN) and Bayesian networks (BLN) to evaluate the potential of network analysis to explore complex rumen environments with interconnected quantitative associations. The approaches were selected based on their capacity for holistic exploration of all possible quantitative associations among variables, including opportunities to explore the potential strength and directionality of those associations. Data from 4 continuous culture experiments, involving 18 rumen variables [major and minor volatile fatty acid (VFA), degradability variables and nitrogen related variables], were used for network derivation. Variables within a network are denoted as nodes and relationships between two nodes are referred to as edges. The different networking approaches had different strengths for biological interpretation. Although the ELN approach was useful for exploring the role and importance of specific variables in the network, the BLN had more relevance in selecting edges or relationships linking those variables. These strengths are complementary and make a case for joint exploration of datasets using both approaches. Many of the biological inferences derived from the networks are well-acknowledged within the literature, acetate, valerate, isobutyrate, and isovalerate were important nodes within both networks, and important edges focused on the driving role of N dynamics within the rumen. Overall, these analyses demonstrated potential to illustrate associations and directionality of quantitative associations among fermentation variables. These associations can be used to direct future studies based on more comprehensive datasets.

Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning.

Proton exchange membrane fuel cells, consuming hydrogen and oxygen to generate clean electricity and water, suffer acute liquid water challenges. Accurate liquid water modelling is inherently challenging due to the multi-phase, multi-component, reactive dynamics within multi-scale, multi-layered porous media. In addition, currently inadequate imaging and modelling capabilities are limiting simulations to small areas (<1 mm2) or simplified architectures. Herein, an advancement in water modelling is achieved using X-ray micro-computed tomography, deep learned super-resolution, multi-label segmentation, and direct multi-phase simulation. The resulting image is the most resolved domain (16 mm2 with 700 nm voxel resolution) and the largest direct multi-phase flow simulation of a fuel cell. This generalisable approach unveils multi-scale water clustering and transport mechanisms over large dry and flooded areas in the gas diffusion layer and flow fields, paving the way for next generation proton exchange membrane fuel cells with optimised structures and wettabilities.

Accurate Collection of Reasons for Treatment Discontinuation to Better Define Estimands in Clinical Trials.

BACKGROUND: Reasons for treatment discontinuation are important not only to understand the benefit and risk profile of experimental treatments, but also to help choose appropriate strategies to handle intercurrent events in defining estimands. The current case report form (CRF) commonly in use mixes the underlying reasons for treatment discontinuation and who makes the decision for treatment discontinuation, often resulting in an inaccurate collection of reasons for treatment discontinuation. METHODS AND RESULTS: We systematically reviewed and analyzed treatment discontinuation data from nine phase 2 and phase 3 studies for insulin peglispro. A total of 857 participants with treatment discontinuation were included in the analysis. Our review suggested that, due to the vague multiple-choice options for treatment discontinuation present in the CRF, different reasons were sometimes recorded for the same underlying reason for treatment discontinuation. Based on our review and analysis, we suggest an intermediate solution and a more systematic way to improve the current CRF for treatment discontinuations. CONCLUSION: This research provides insight and directions on how to optimize the CRF for recording treatment discontinuation. Further work needs to be done to build the learning into Clinical Data Interchange Standards Consortium standards. CLINICAL TRIALS: Clinicaltrials.gov numbers: NCT01027871 (Phase 2 for type 2 diabetes), NCT01049412 (Phase 2 for type 1 diabetes), NCT01481779 (IMAGINE 1 Study), NCT01435616 (IMAGINE 2 Study), NCT01454284 (IMAGINE 3 Study), NCT01468987 (IMAGINE 4 Study), NCT01582451 (IMAGINE 5 Study), NCT01790438 (IMAGINE 6 Study), NCT01792284 (IMAGINE 7 Study).

Development of Tetrapod Zinc Oxide-Based UV Sensor for Precision Livestock Farming and Productivity.

In order to ensure the health and welfare of livestock, there has been an emphasis on precision farming of ruminant animals. Monitoring the life index of ruminant animals is of importance for intelligent farming. Here, a wearable sensor for monitoring ultraviolet (UV) radiation is demonstrated to understand the effect of primary and secondary photosensitization on dairy animals. Thin films of wide bandgap semiconductor zinc oxide (ZnO) comprising multilevel of nanostructures from microparticles (MP) to nanoparticles (NP), and tetrapod (T-ZnO), were prepared as the UV sensing active materials. The sensitivity was evaluated by exposing the films to various radiation sources, i.e., 365 nm (UV A), 302 nm (UV B), and 254 nm (UV C), and measuring the electrical resistance change. T-ZnO is found to exhibit higher sensitivity and stable response (on/off) upon exposure to UV A and UV B radiation, which is attributed to their higher surface area, aspect ratio, porosity, and interconnective networks inducing a high density of chemical interaction sites and consequently improved photocurrent generation. A wearable sensor using T-ZnO is packaged and attached to a collar for dynamic monitoring of UV response on ruminant animals (e.g., sheep in this study). The excellent performance of T-ZnO wearable sensors for ruminant animals also holds the potential for a wider range of applications such as residential buildings and public spaces.

Invited review: Sensor technologies for real-time monitoring of the rumen environment.

Quantifying digestive and fermentative processes within the rumen environment has been the subject of decades of research; however, our existing research methodologies preclude time-sensitive and spatially explicit investigation of this system. To better understand the temporal and spatial dynamics of the rumen environment, real-time and in situ monitoring of various chemical and physical parameters in the rumen through implantable microsensor technologies is a practical solution. Moreover, such sensors could contribute to the next generation of precision livestock farming, provided sufficient wireless data networking and computing systems are incorporated. In this review, various microsensor technologies applicable to real-time metabolic monitoring for ruminants are introduced, including the detection of parameters for rumen metabolism, such as pH, temperature, histamine concentrations, and volatile fatty acid concentrations. The working mechanisms and requirements of the sensors are summarized with respect to the selected target parameters. Lastly, future challenges and perspectives of this research field are discussed.

Organelles coordinate milk production and secretion during lactation: Insights into mammary pathologies.

The mammary gland undergoes a spectacular series of changes during its development and maintains a remarkable capacity to remodel and regenerate during progression through the lactation cycle. This flexibility of the mammary gland requires coordination of multiple processes including cell proliferation, differentiation, regeneration, stress response, immune activity, and metabolic changes under the control of diverse cellular and hormonal signaling pathways. The lactating mammary epithelium orchestrates synthesis and apical secretion of macromolecules including milk lipids, milk proteins, and lactose as well as other minor nutrients that constitute milk. Knowledge about the subcellular compartmentalization of these metabolic and signaling events, as they relate to milk production and secretion during lactation, is expanding. Here we review how major organelles (endoplasmic reticulum, Golgi apparatus, mitochondrion, lysosome, and exosome) within mammary epithelial cells collaborate to initiate, mediate, and maintain lactation, and how study of these organelles provides insight into options to maintain mammary/breast health.

Meta-analysis of the effects of chemical and microbial preservatives on hay spoilage during storage.

A meta-analysis was performed to evaluate the effects of chemical (50 articles) and microbial (21 articles) additives on hay preservation during storage. Multilevel linear mixed-effects models were fit with response variables calculated as predicted differences (Δ) between treated and untreated samples. Chemical preservatives were classified into five groups such as propionic acid (PropA), buffered organic acids (BOA), other organic acids (OOA), urea, and anhydrous ammonia (AA). Moderators of the models included preservative class (PC), forage type (FT; grass, legumes, and mixed hay), moisture concentration (MC), and application rate (AR). Dry matter (DM) loss during storage was affected by PC × FT (P = 0.045), PC × AR (P < 0.001), and PC × MC (P = 0.009), relative to the overall effect of preservatives (-0.37%). DM loss in PropA-treated hay was numerically reduced to a greater extent in grasses (-16.2), followed by mixed hay (-1.76), but it increased (+2.2%) in legume hay. Increasing AR of PropA resulted in decrease in DM loss (slope = -1.34). Application of BOA, OOA, PropA, and AA decreased visual relative moldiness by -22.1, -29.4, -45.5, and -12.2 percentage points, respectively (PC; P < 0.001). Sugars were higher in treated grass hay (+1.9) and lower in treated legume hay (-0.8% of DM) relative to their untreated counterparts (P < 0.001). The application of all preservatives resulted in higher crude protein (CP) than untreated hay, particularly urea (+7.92) and AA (+5.66% of DM), but PropA, OOA, and BOA also increased CP by 2.37, 2.04, and 0.73 percentage points, respectively. Additionally, preservative application overall resulted in higher in vitro DM digestibility (+1.9% of DM) relative to the untreated hay (x¯=58.3%), which increased with higher AR (slope = 1.64) and decreased with higher MC (slope = -0.27). Microbial inoculants had small effects on hay spoilage because the overall DM loss effect size was -0.21%. Relative to untreated (x¯=4.63% DM), grass hay preserved more sugars (+1.47) than legumes (+0.33) when an inoculant was applied. In conclusion, organic acid-based preservatives prevent spoilage of hay during storage, but their effectiveness is affected by FT, MC, and AR. Microbial inoculants had minor effects on preservation that were impaired by increased MC. Moreover, legume hay was less responsive to the effects of preservatives than grass hay.

Storing hay that has not been properly dried to a moisture concentration (MC) below 20% can lead to the growth of undesirable microbes, such as molds, that decrease the nutritive value of the hay and compromise animal performance and health. Hay preservatives such as propionic acid (PropA), buffered organic acids (BOA), other organic acids (OOA), urea, anhydrous ammonia (AA), and microbial inoculants have been commonly applied to high moisture (>20%) hay to reduce microbial growth during hay storage. The present study compiled the results of 62 published articles on hay preservatives and performed a quantitative analysis (meta-analysis) to determine the effect of preservative treatment on dry matter (DM) loss, moldiness, bale heating, nutritional composition, and DM digestibility, and their interactions with forage type, application rate, and bale moisture. Organic acid-based preservatives (PropA, BOA, and OOA) were effective at reducing DM loss, moldiness, bale maximum temperature, and insoluble nitrogen, and at preserving sugars and DM digestibility during storage to different extents. Microbial inoculants had small effects on the prevention of hay spoilage, and were negatively affected by the increase of hay MC. Legume hay was less responsive to the effects of preservatives than grass hay during storage.

Short-Term Adaptation of Dairy Cattle Production Parameters to Individualized Changes in Dietary Top Dress.

Immediate and short-term changes in diet composition can support individualized, real-time interventions in precision dairy production systems, and might increase feed efficiency (FE) of dairy cattle in the short-term. The objective of this study was to determine immediate and short-term effects of changes in diet composition on production parameters of dairy cattle fed varying amounts of top dressed commodities. A 4 × 4 replicated Latin square design was used to evaluate responses of twenty-four Holstein cows fed either no top dress (Control) or increasing amounts of: corn grain (CG), soybean meal (SBM), or chopped mixed grass hay (GH) top dressed on a total mixed ration (TMR) over four, 9-day periods. Throughout each period, top dressed commodities were incrementally increased, providing 0% to 20% of calculated net energy of lactation (NEL) intake. Measured production responses were analyzed for each 9-d period using a mixed-effects model considering two different time ranges. Samples collected from d 3 and 4 and from d 7 and 8 of each period were averaged and used to reflect "immediate" vs. "short-term" responses, respectively. In the immediate response time frame, control fed cows had lower milk yield, milk fat yield, and milk true protein yield than CG and SBM supplemented animals but similar responses to GH supplemented animals. Milk fat and protein percentages were not affected by top dress type in the immediate term. In the short-term response time-frame, GH supplemented animals had lower DMI and milk fat yield than all other groups. Control and GH supplemented cows had lower milk yield than CG and SBM fed cows. In the immediate response time frame, FE of SBM supplemented cows was superior to other groups. In the short-term time frame, FE of GH and SBM groups was improved over the control group. Results suggest that lactating dairy cows show rapid performance responses to small (<20% NEL) changes in dietary composition, which may be leveraged within automated precision feeding systems to optimize efficiency of production. Before this potential can be realized, further research is needed to examine integration of such strategies into automatic feeding systems and downstream impacts on individual animal FE and farm profitability.

Extreme suction attachment performance from specialised insects living in mountain streams (Diptera: Blephariceridae).

Suction is widely used by animals for strong controllable underwater adhesion but is less well understood than adhesion of terrestrial climbing animals. Here we investigate the attachment of aquatic insect larvae (Blephariceridae), which cling to rocks in torrential streams using the only known muscle-actuated suction organs in insects. We measured their attachment forces on well-defined rough substrates and found that their adhesion was less reduced by micro-roughness than that of terrestrial climbing insects. In vivo visualisation of the suction organs in contact with microstructured substrates revealed that they can mould around large asperities to form a seal. We have shown that the ventral surface of the suction disc is covered by dense arrays of microtrichia, which are stiff spine-like cuticular structures that only make tip contact. Our results demonstrate the impressive performance and versatility of blepharicerid suction organs and highlight their potential as a study system to explore biological suction mechanisms.

Suction cups are widely used to attach objects to surfaces in bathrooms and kitchens. They work well on tiles and other smooth surfaces, but do not stick well to rougher materials like brick or wood because they are unable to form an air-tight seal. Researchers have been searching for ways to improve these cups by studying how octopuses, remora fish and other sea animals use muscle-powered suction organs to stick to wet and rough surfaces. However, the experiments needed to understand the detailed mechanics of suction organs are difficult to perform on living specimens of these animals. The aquatic larvae of a family of insects known as the net-winged midges also have suction organs that are powered by muscles. These insects survive in fast flowing mountain streams where they use their suction organs to stick to rocks underwater. However, it remained unclear how these suction organs work. Here, Kang et al. found that net-winged midge larvae attach extremely well to a variety of surfaces. The larvae were able to withstand forces over one thousand times their body weight when attached to smooth surfaces. Even on rough materials, where human-made suction cups attach poorly, the larvae were able to withstand forces up to 240-times their body weight. Further experiments using several microscopy approaches revealed that the suction organs of the larvae are covered in multiple spine-like structures called microtrichia that interlock with bumps and dips on a surface to help the organ remain in place. Similar structures have previously been found on the suction organs of remora fish, but are not as tightly packed together. These findings demonstrate that net-winged midge larvae may be useful model systems to study how natural suction organs operate. Furthermore, they provide a new source of inspiration for scientists and engineers to design and manufacture suction cups capable of attaching to a wider variety of surfaces.

Unerupted Supernumerary Mandibular Fourth Premolar in a dog.

A 2.5-year-old intact male Irish setter was presented for a draining tract associated with the right mandibular first molar tooth (409). Conscious oral examination yielded two draining tracts associated with the right mandibular first molar tooth. No obvious missing teeth or other gross abnormalities associated with the oral cavity were observed. Upon anesthetized radiographic evaluation, the presence of an unerupted, abnormally positioned, supernumerary premolar tooth was observed. The following article describes the extraction of the right mandibular first molar tooth (409) as well as the unerupted supernumerary premolar tooth with associated supernumerary root and the diagnostic approach taken for this uncommon abnormality.