An Algorithm to Assess Calcium Bioavailability from Foods.

BACKGROUND: The recommended calcium intakes to meet calcium requirements at various ages are based on average population absorption values. Absorption is altered by physiology, the calcium load, and type of food. The calcium intake necessary, therefore, to meet requirements depends upon diet composition, through bioavailability. OBJECTIVE: The objectives of this study was to improve predictions of calcium bioavailability on the basis of the food matrix. METHODS: We modeled calcium absorption data from individual foods, beverages, and fortified foods that were determined with calcium isotopic tracers and compared with milk as a referent to adjust for physiologic differences of the host. RESULTS: Data from 496 observations were modeled to develop a predictive algorithm for calcium bioavailability in adults on the basis of calcium load and oxalate and phytate loads, which represent the 2 main inhibitors of calcium absorption. CONCLUSIONS: This algorithm will be helpful in assessing calcium availability from the food supply, for developing diets for individuals and research cohorts, and for designing policies and interventions to address inadequate calcium intake for populations.

Waste to protein: A systematic review of a century of advancement in microbial fermentation of agro-industrial byproducts.

Increasing global consumption of protein over the last five decades, coupled with concerns about the impact on emissions of animal-based protein production, has created interest in alternative protein sources. Microbial proteins (MPs), derived through the fermentation of agro-industrial byproducts, present a promising option. This review assesses a century of advancements in this domain. We conducted a comprehensive review and meta-analysis, examining 347 relevant research papers to identify trends, technological advancements, and key influencing factors in the production of MP. The analysis covered the types of feedstocks and microbes, fermentation methods, and the implications of nucleic acid content on the food-grade quality of proteins. A conditional inference tree model and Bayesian factor were used to ascertain the impact of various parameters on protein content. Out of all the studied parameters, such as type of feedstock (lignocellulose, free sugars, gases, and others), type of fermentation (solid, liquid, gas), type of microbe (bacteria, fungi, yeast, and mix), and operating parameters (temperature, time, and pH), the type of fermentation and microbe were identified as the largest influences on protein content. Gas and liquid fermentation demonstrated higher protein content, averaging 52% and 42%, respectively. Among microbes, bacterial species produced a higher protein content of 51%. The suitable operating parameters, such as pH, time, and temperature, were also identified for different microbes. The results point to opportunities for continued innovation in feedstock, microbes, and regulatory alignment to fully realize the potential of MP in contributing to global food security and sustainability goals.

Use of the DELTA Model to Understand the Food System and Global Nutrition.

BACKGROUND: Increasing attention is being directed at the environmental, social, and economic sustainability of the global food system. However, a key aspect of a sustainable food system should be its ability to deliver nutrition to the global population. Quantifying nutrient adequacy with current tools is challenging. OBJECTIVE: To produce a computational model illustrating the nutrient adequacy of current and proposed global food systems. METHODS: The DELTA Model was constructed using global food commodity balance sheet data, alongside demographic and nutrient requirement data from UN and European Food Safety Authority sources. It also includes nutrient bioavailability considerations for protein, the indispensable amino acids, iron, and zinc, sourced from scientific literature. RESULTS: The DELTA Model calculates global per capita nutrient availability under conditions of equal distribution and identifies areas of nutrient deficiency for various food system scenarios. Modeling the 2018 global food system showed that it supplied insufficient calcium (64% of demographically weighted target intake) and vitamin E (69%), despite supplying sufficient macronutrients. Several future scenarios were modeled, including variations in waste; scaling up current food production for the 2030 global population; plant-based food production systems; and removing sugar crops from the global food system. Each of these scenarios fell short of meeting requirements for multiple nutrients. These results emphasize the need for a balanced approach in the design of future food systems. CONCLUSIONS: Nutrient adequacy must be at the forefront of the sustainable food system debate. The DELTA Model was designed for both experts and nonexperts to inform this debate as to what may be possible, practical, and optimal for our food system. The model results strongly suggest that both plant and animal foods are necessary to achieve global nutrition. The model is freely available for public use so that anyone can explore current and simulated global food systems.

The relationship between transpiration and nutrient uptake in wheat changes under elevated atmospheric CO2.

The impact of elevated [CO2 ] (e[CO2 ]) on crops often includes a decrease in their nutrient concentrations where reduced transpiration-driven mass flow of nutrients has been suggested to play a role. We used two independent approaches, a free-air CO2 enrichment (FACE) experiment in the South Eastern wheat belt of Australia and a simulation study employing the agricultural production systems simulator (APSIM), to show that transpiration (mm) and nutrient uptake (g m-2 ) of nitrogen (N), potassium (K), sulfur (S), calcium (Ca), magnesium (Mg) and manganese (Mn) in wheat are correlated under e[CO2 ], but that nutrient uptake per unit water transpired is higher under e[CO2 ] than under ambient [CO2 ] (a[CO2 ]). This result suggests that transpiration-driven mass flow of nutrients contributes to decreases in nutrient concentrations under e[CO2 ], but cannot solely explain the overall decline.

Heat shock inhibition of CDK5 increases NOXA levels through miR-23a repression.

Hyperthermia is a proteotoxic stress that is lethal when exposure is extreme but also cytoprotective in that sublethal exposure leads to the synthesis of heat shock proteins, including HSP70, which are able to inhibit stress-induced apoptosis. CDK5 is an atypical cyclin-dependent kinase family member that regulates many cellular functions including motility and survival. Here we show that exposure of a human lymphoid cell line to hyperthermia causes CDK5 insolubilization and loss of tyrosine-15 phosphorylation, both of which were prevented in cells overexpressing HSP70. Inhibition of CDK5 activity with roscovitine-sensitized cells to heat induced apoptosis indicating a protective role for CDK5 in inhibiting heat-induced apoptosis. Both roscovitine and heat shock treatment caused increased accumulation of NOXA a pro-apoptotic BH3-only member of the BCL2 family. The increased abundance of NOXA by CDK5 inhibition was not a result of changes in NOXA protein turnover. Instead, CDK5 inhibition increased NOXA mRNA and protein levels by decreasing the expression of miR-23a, whereas overexpressing the CDK5 activator p35 attenuated both of these effects on NOXA and miR-23a expression. Lastly, overexpression of miR-23a prevented apoptosis under conditions in which CDK5 activity was inhibited. These results demonstrate that CDK5 activity provides resistance to heat-induced apoptosis through the expression of miR-23a and subsequent suppression of NOXA synthesis. Additionally, they indicate that hyperthermia induces apoptosis through the insolubilization and inhibition of CDK5 activity.

Correction: Alvarado, M., et al. Towards the Development of a Low Cost Airborne Sensing System to Monitor Dust Particles after Blasting at Open-Pit Mine Sites. Sensors 2015, 15, 19667-19687.

The author wishes to change Figure 1 and Figure 3 from his paper published in Sensors [1], doi:10.3390/s150819667, website: http://www.mdpi.com/1424-8220/15/8/19667 for Figures 1 and 2 presented in this 'Correction'.[...].

Towards the Development of a Low Cost Airborne Sensing System to Monitor Dust Particles after Blasting at Open-Pit Mine Sites.

Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R(2)) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning.

Analysis of global nutrient gaps and their potential to be closed through redistribution and increased supply.

Global food systems are crucial for sustaining life on Earth. Although estimates suggest that the current production system can provide enough food and nutrients for everyone, equitable distribution remains challenging. Understanding global nutrient distribution is vital for addressing disparities and creating effective solutions for the present and future. This study analyzes global nutrient supply changes to address inadequacies in certain populations using the existing DELTA Model®, which uses aggregates of global food production to estimate nutrient adequacy. By examining the 2020 global food commodity and nutrient distribution, we project future food production in 2050 needs to ensure global adequate nutrition. Our findings reveal that while some nutrients appear to be adequately supplied on a global scale, many countries face national insufficiencies (% supply below the population reference intake) in essential vitamins and minerals, such as vitamins A, B12, B2, potassium, and iron. Closing these gaps will require significant increases in nutrient supply. For example, despite global protein supply surpassing basic needs for the 2050 population, significant shortages persist in many countries due to distribution variations. A 1% increase in global protein supply, specifically targeting countries with insufficiencies, could address the observed 2020 gaps. However, without consumption pattern changes, a 26% increase in global protein production is required by 2050 due to population growth. In this study, a methodology was developed, applying multi-decade linear convergence to sufficiency values at the country level. This approach facilitates a more realistic assessment of future needs within global food system models, such as the DELTA Model®, transitioning from idealized production scenarios to realistic projections. In summary, our study emphasizes understanding global nutrient distribution and adjusting minimum global nutrient supply targets to tackle country-level inequality. Incorporating these insights into global food balance models can improve projections and guide policy decisions for sustainable, healthy diets worldwide.

Adaptation to climate change through strategic integration of long fallow into cropping system in a dryland Mediterranean-type environment.

The crop-growing region of Western Australia characterized by a Mediterranean-type climate is projected to become warmer and drier. Appropriate selection of crop sequences will be of importance to cope with these climatic changes for this largest grain-producing region of Australia. Through linking a widely used crop model (APSIM), 26 General Circulation Models (GCMs) with one Shared Socioeconomic Pathway (SSP585) and economic analysis, we explored how the climate change would affect dryland wheat cropping and whether/how long fallow (the practice of leaving a field out of production for an entire growing season) could be integrated into wheat cropping system in Western Australia. The potential adaptation of long fallow into wheat system was assessed with four fixed rotations (fallow-wheat, fallow-wheat-wheat, fallow-wheat-wheat-wheat, and fallow-wheat-wheat-wheat-wheat) and four flexible sowing rule-based rotations (the land was fallowed if sowing rule was not met), compared with continuous wheat. The simulation results at four representing locations show that climate change would have negative impacts on both yield and economic return of continuous wheat cropping in Western Australia. Wheat after fallow out-yielded and out-profited wheat after wheat under future climate. But integrating fallow into wheat cropping systems with the above fixed rotations would lead to yield and economic loss. By contrast, cropping systems in which fallowing took place when sowing condition could not be met at a certain time would achieve comparable yield and economic return to continuous wheat, with wheat yield being only 5 % less than continuous wheat and the gross margin being $12 ha-1 more than continuous wheat averaged across locations. We highlight strategic integration of long fallow into cropping system in a dryland Mediterranean-type environment would have a great potential to cope with future climate change. These findings can be extended into other Mediterranean-type cropping regions in Australia and beyond.

A machine learning-based score for precise echocardiographic assessment of cardiac remodelling in hypertensive young adults.

Aims: Accurate staging of hypertension-related cardiac changes, before the development of significant left ventricular hypertrophy, could help guide early prevention advice. We evaluated whether a novel semi-supervised machine learning approach could generate a clinically meaningful summary score of cardiac remodelling in hypertension. Methods and results: A contrastive trajectories inference approach was applied to data collected from three UK studies of young adults. Low-dimensional variance was identified in 66 echocardiography variables from participants with hypertension (systolic ≥160 mmHg) relative to a normotensive group (systolic < 120 mmHg) using a contrasted principal component analysis. A minimum spanning tree was constructed to derive a normalized score for each individual reflecting extent of cardiac remodelling between zero (health) and one (disease). Model stability and clinical interpretability were evaluated as well as modifiability in response to a 16-week exercise intervention. A total of 411 young adults (29 ± 6 years) were included in the analysis, and, after contrastive dimensionality reduction, 21 variables characterized >80% of data variance. Repeated scores for an individual in cross-validation were stable (root mean squared deviation = 0.1 ± 0.002) with good differentiation of normotensive and hypertensive individuals (area under the receiver operating characteristics 0.98). The derived score followed expected hypertension-related patterns in individual cardiac parameters at baseline and reduced after exercise, proportional to intervention compliance (P = 0.04) and improvement in ventilatory threshold (P = 0.01). Conclusion: A quantitative score that summarizes hypertension-related cardiac remodelling in young adults can be generated from a computational model. This score might allow more personalized early prevention advice, but further evaluation of clinical applicability is required.

What is evidence as evidence is used? A case of dualism?

How 'evidence' is conceptualised, generated and deployed in meso-level policy implementation on the ground is critical to health delivery. Using the case of a large-scale health service reconfiguration in northwest England, this study began as a narrative investigation into how different data types and sources are prioritised as NHS administrative structures change over time. During the research, one unpopular reconfiguration decision, the downgrading of a hospital, was challenged using judicial review. Suddenly, a key decision was being based not upon 'facts and data' type evidence but upon evidence of adherence to administrative procedure. This transferred focus away from the ever-shifting categories and hierarchies of data 'types' towards an emphasis on process. By comparing two deliberative contexts-committee and judicial review-this article proposes that evidence can be understood as simultaneously entity and process. As health service reconfigurations continue in response to austerity, integration agendas, evolving organisational landscapes, and demographic and political change, it is increasingly important to recognise the different meanings and uses of evidence.

Modeling the Contribution of Meat to Global Nutrient Availability.

An increasing global population requires increasing food and nutrient availability. Meat is recognized as a nutrient dense food, particularly notable for its high-quality protein content, B vitamin and mineral content. However, it is not known how important meat is currently in nourishing the global population. The DELTA Model was used to calculate the contribution of meat (defined as animal flesh, excluding fish and seafood) to the global availability of 29 nutrients. This model utilizes global food production and use data, coupled with data for food waste, food nutrient composition and nutrient bioavailability to calculate the total amount of each nutrient available for consumption by the global population. Around 333 million tons of meat were produced globally in 2018, 95% of which was available as food, constituting ~7% of total food mass. Meat's contribution to nutrient availability was disproportionately higher than this: meat provided 11% of global food energy availability, 29% of dietary fat and 21% of protein. For the micronutrients, meat provided high proportions of vitamins: A (24%), B1 and B2 (15% each), B5 (10%), B6 (13%), and B12 (56%). Meat also provided high proportions of several trace elements: zinc (19%), selenium (18%), iron (13%), phosphorous (11%), and copper (10%). Meat is a poor contributor to fiber, magnesium and vitamins C and E. Meat was responsible for 16% (cystine) to 32% (lysine) of global availability of the bioavailable indispensable amino acids included in the model, due partly to the high digestibility of these nutrients from meat (83-100%). Of the total meat mass available as food in 2018, 23% was ruminant meat, 34% poultry meat, 32% pig meat, 2% other meat, and 9% offal and fats. The disproportionate contribution of meat to the global availability of nutrients emphasizes its important place in delivering nutrition to the current global population.

Current state of laboratory test utilization practices in the clinical laboratory.

Appropriate laboratory test utilization is of growing interest in the face of rising healthcare costs and documented evidence of over- and under-utilization. Building from published literature, laboratory organizations have recently published guidelines for establishing laboratory utilization management programs. However, systematic reviews and meta-analyses have consistently struggled to define rigorous evidence-based best practice recommendations due to the paucity of published data or the heterogeneity of available data. We sought to gain information about utilization practices and programs currently in use and which factors contribute to their success by distributing a survey among laboratory professionals. The survey received seventy-four eligible respondents. We observed a wide range in the duration of laboratory utilization programs and the number of stewardship initiatives. In addition, there was great variety in the utilization practices used and the tests or processes targeted by programs. There was similarity in how initiatives are evaluated and who is involved with utilization programs. Finally, respondents often credited a multidisciplinary committee, support from leadership, and strong IT support/data access as important factors for their program's perceived success. Many of these factors agree with previously published literature.

Identification of drought-response genes and a study of their expression during sucrose accumulation and water deficit in sugarcane culms.

BACKGROUND: The ability of sugarcane to accumulate high concentrations of sucrose in its culm requires adaptation to maintain cellular function under the high solute load. We have investigated the expression of 51 genes implicated in abiotic stress to determine their expression in the context of sucrose accumulation by studying mature and immature culm internodes of a high sucrose accumulating sugarcane cultivar. Using a sub-set of eight genes, expression was examined in mature internode tissues of sugarcane cultivars as well as ancestral and more widely related species with a range of sucrose contents. Expression of these genes was also analysed in internode tissue from a high sucrose cultivar undergoing water deficit stress to compare effects of sucrose accumulation and water deficit. RESULTS: A sub-set of stress-related genes that are potentially associated with sucrose accumulation in sugarcane culms was identified through correlation analysis, and these included genes encoding enzymes involved in amino acid metabolism, a sugar transporter and a transcription factor. Subsequent analysis of the expression of these stress-response genes in sugarcane plants that were under water deficit stress revealed a different transcriptional profile to that which correlated with sucrose accumulation. For example, genes with homology to late embryogenesis abundant-related proteins and dehydrin were strongly induced under water deficit but this did not correlate with sucrose content. The expression of genes encoding proline biosynthesis was associated with both sucrose accumulation and water deficit, but amino acid analysis indicated that proline was negatively correlated with sucrose concentration, and whilst total amino acid concentrations increased about seven-fold under water deficit, the relatively low concentration of proline suggested that it had no osmoprotectant role in sugarcane culms. CONCLUSIONS: The results show that while there was a change in stress-related gene expression associated with sucrose accumulation, different mechanisms are responding to the stress induced by water deficit, because different genes had altered expression under water deficit.

Sex differences in the ovine fetal cortisol response to stress.

This study tested the hypothesis that the sexually dimorphic adrenocortical response to stress is already established before birth. Chronically instrumented late gestation pregnant sheep carrying 16 male and 15 female age-matched singleton fetuses were subjected to an acute episode of hypoxic stress. Maternal and fetal blood gases, adrenocorticotrophic hormone (ACTH), and cortisol were measured. In addition, six male and six female fetuses received the ACTH analog, Synacthen, and plasma cortisol was measured. During hypoxic stress, the increment in plasma cortisol was 2-fold greater in male versus females fetuses (30.6 ± 3.2 versus 14.3 ± 2.0 ng/mL; p < 0.001) mediated, in part, by greater adrenocortical sensitivity to ACTH. The data support the hypothesis tested and show that sex-specific differences in the cortisol stress response are present before birth with the output of cortisol being much greater in male than in female fetuses.

ProExC triage of atypical glandular cells on liquid-based cervical cytology specimens.

OBJECTIVE: Morphologic distinction between atypical glandular cells not otherwise specified (AGC-NOS) and AGC-favor neoplasia (AGC-FN) can be difficult. Distinction between these entities is important as the American Society for Colposcopy and Cervical Pathology 2006 consensus guidelines state that management of AGC-NOS differs from that of AGC-FN. The objective of this study was to determine the potential role of ProExC immunocytochemical triage of AGC-NOS. MATERIALS AND METHODS: Cytopathology records from a pathology practice were reviewed from January 2006 to December 2009 to identify AGC-NOS liquid-based Pap smears with subsequent biopsy correlation. Archival slides were examined, and ProExC immunocytochemistry was performed. The AGC groups were assessed for nuclear staining, and results were correlated with subsequent biopsy findings. RESULTS: Twenty-eight AGC-NOS cases with biopsy correlation were identified: 13 with subsequent high-grade neoplastic or malignant (positive) diagnoses and 15 with benign diagnoses. Of 13 AGC-NOS cases with positive diagnosis, 10 were ProExC-positive and 3 were ProExC-negative (metastatic tumors from distant sites). Of 15 AGC cases with benign follow-up, 13 were ProExC-negative and 2 were ProExC-positive (sensitivity, 77%; specificity, 87%). For patients with cervical intraepithelial neoplasia or carcinoma originating from the female genital tract, 100% (10/10) were ProExC-positive (sensitivity, 100%; specificity, 87%). CONCLUSIONS: Results suggest that ProExC-positive AGC-NOS may be classified as AGC-FN. Although positive immunocytochemical staining for ProExC requires management similar to AGC-FN, negative staining does not rule out malignancy such as metastatic tumor. Management for ProExC-negative AGC-NOS cases should proceed according to the current guidelines for AGC-NOS.

Machine Learning Augmented Echocardiography for Diastolic Function Assessment.

Cardiac diastolic dysfunction is prevalent and is a diagnostic criterion for heart failure with preserved ejection fraction-a burgeoning global health issue. As gold-standard invasive haemodynamic assessment of diastolic function is not routinely performed, clinical guidelines advise using echocardiography measures to determine the grade of diastolic function. However, the current process has suboptimal accuracy, regular indeterminate classifications and is susceptible to confounding from comorbidities. Advances in artificial intelligence in recent years have created revolutionary ways to evaluate and integrate large quantities of cardiology data. Imaging is an area of particular strength for the sub-field of machine-learning, with evidence that trained algorithms can accurately discern cardiac structures, reliably estimate chamber volumes, and output systolic function metrics from echocardiographic images. In this review, we present the emerging field of machine-learning based echocardiographic diastolic function assessment. We summarise how machine-learning has made use of diastolic parameters to accurately differentiate pathology, to identify novel phenotypes within diastolic disease, and to grade diastolic function. Perspectives are given about how these innovations could be used to augment clinical practice, whilst areas for future investigation are identified.