Integrating AI into Culinary Medicine: A Revolution in Nutrition and Home Cooking

Introduction With the growing popularity of the emerging field of culinary medicine, there is a growing understanding of the culinary barriers needed to be overcome to adopt healthier eating habits. Lack of confidence, low skills, and lack of time are some of the most common barriers that prevent individuals from cooking at home. However, integrating AI can offer personalized support for home cooking and help individuals overcome these barriers. AI-powered meal planning and recipe suggestions can guide healthy and nutritious food choices that cater to their dietary needs and preferences. Additionally, AI can modify recipes to accommodate individual health conditions and nutrient deficiencies, making cooking easier and more accessible. Individuals can improve their cooking skills, learn new recipes, and better manage chronic conditions with personalized nutrition recommendations. Therefore, the integration of AI has the potential to empower individuals to overcome culinary barriers and adopt a healthier lifestyle. Methods We systematically searched peer-reviewed articles using electronic databases, including Google Scholar and Scopus. Keywords used in the search included culinary medicine , nutrition , AI , machine learning , recipe generation , personalized nutrition , chronic disease, and healthcare. In addition to the systematic literature review, we also utilized ChatGPT, a large language model trained by OpenAI, to generate potential research ideas and identify further relevant literature. We inputted our research question and used the model\u27s capabilities to create new hypotheses and suggest additional search terms and databases to explore. We then analyzed the findings to identify the potential benefits of integrating AI into culinary medicine and provide insights into how patients and physicians can use AI to improve the field. Results The reviewed articles suggest that AI has the potential to address culinary barriers such as lack of confidence, low skills, and lack of time. By incorporating machine learning algorithms, AI can generate personalized dietary recommendations that cater to individual health conditions, dietary preferences, and nutrient deficiencies. These recommendations can help individuals make more informed food choices without requiring extensive culinary knowledge or skills. Additionally, AI-powered recipe recommendation systems can provide easy-to-follow recipes and meal plans, reducing the time and effort needed for meal planning and preparation. By simplifying the process of healthy eating, integrating AI into culinary medicine can increase confidence and motivation for individuals to adopt healthier lifestyles. The concept of culinary medicine, which combines the art of cooking with the science of medicine, is a promising approach to preventing and treating chronic diseases. Conclusion Overall, using AI in culinary medicine can revolutionize how we approach nutrition and disease prevention, providing more personalized and accessible dietary recommendations to improve public health. Furthermore, AI-powered nutrition interventions can be tailored to individuals with varying cultural backgrounds, dietary restrictions, and socioeconomic status, making healthy eating more accessible and inclusive. However, addressing concerns related to privacy, data security, and the potential for AI-generated recommendations to perpetuate bias and misinformation is essential

Health disparities within rural communities in the southern region of the United States

Intro: Historical studies have shown that health disparities exist between urban and rural communities, however additional disparities are also known to exist within rural communities as well. These include health disparities between races, ethnicities, and socioeconomic statuses, among others. While the disparities between urban and rural communities have been researched and described more extensively, there is a paucity of information available about the disparities that exist within rural communities. Our goal in this research initiative was to characterize the disparities that exist within rural communities by examining the findings of several publications that sought to describe this phenomenon in the past. Method: Protocols evaluated current research studies and identified areas where research was scarce, or nonexistent. Following this evaluation, a literature search was performed using PubMed with the goal of locating and utilizing papers from the last 10 years on the specified topic. Queries were used for pre-identified search terms, which aimed to include the entire range of this topic: ‘rural’, ‘health’, ‘disparities’, ‘minority’, ‘mental’. Inclusion criteria for the literature review included mention of health disparities in rural areas, and that data were from the United States. Exclusion criteria included if data were from a country outside of the United States, or if there was no discussion of rural health. Results of the initial literature search were reviewed manually, and the inclusion and exclusion criteria were applied at that time. Results: The results of this study reveal that nonmetropolitan households were less likely to have digital access which greatly contributed to being uninsured. These results also show that universal policies and procedures geared toward at-risk populations drastically reduced health disparities among these communities. An odds ratio of 1.69 based on a bivariate analysis revealed that rural residents were most likely to exhibit healthcare avoidance behaviors and an odds ratio of 2.24 was indicative in the lack of confidence in personal health care. Furthermore, rural areas were less likely to retain physicians and more likely to have residents with poorer health. Stressful living environments and broader community held beliefs were shown to impact perceptions of mental health and served as a barrier to seeking health. Disparities such as personal income and finances served as estimated predictors of 38.8% of microbial taxa. Such disparities were associated with higher infant mortality rates among black populations and were highest in rural counties. Discussion/Conclusion: This study was done to compile data from different studies and reports to prove that there is a need for equity amongst healthcare in all communities throughout the southern United States region. There is a significant decline in both the access and quality of healthcare in rural communities in this region. Multiple challenges exist due to several factors such as socioeconomic status, digital access, race/ethnicity and many other secondary resources that may need to be acquired in order to access necessary quality healthcare

The impact of minority physician representation on minority patient health

Background: Before the COVID-19 pandemic, the medical profession underwent a physician burnout crisis. Post pandemic, physician burnout transformed into an epidemic that has contributed to the inability of physician supply to meet patient demand in the USA. Recent studies by the American Medical Association predict by 2034, a widespread physician shortage across both primary care and non-primary care specialties (AAMC, 2021). As a result, medical institutions have implemented programs to address this shortage. While this shortage is concerning and needs to be addressed, it isn’t the only shortage at hand. Minorities are deeply underrepresented in the medical field with respect to their proportions in the overall USA population. The ongoing physician shortage further exacerbates the disproportionate number of minority physicians. Furthermore, minority underrepresentation isn’t confined to the profession but is also observed among students in medical schools across the United States. Simultaneously, these same underrepresented minority groups disproportionately experience mortality and disability from disease at higher rates compared to their White counterparts (Smedley, 2001). This study analyzes the inverse relationship between the amount minority physicians present in a community and the prevalence of disease among these same minority populations. It also seeks to understand how representation impacts minority health outcomes. Aim: Involving minority communities in the development and implementation of healthcare policies and programs can lead to better healthcare outcomes for those communities. Methods: A systematic literature review was conducted using PubMed, Scopus, and EBSCOhost databases using keywords [(“MINORITY PHYSICIAN” OR “UNDERREPRESENTED MINORITY PHYSICIANS”)] AND [(“MINORITY PATIENTS” OR “MINORITY PATIENT HEALTH OUTCOMES”) AND (“COMMUNITY-BASED PARTICIPATORY RESEARCH”)] Results: The excess burden of illness in minority populations can be contributed to numerous complex factors, including but not limited to socioeconomic inequality, environmental and occupational exposures, discrimination, health risk factors, and less access to health insurance and healthcare. Practical, actionable strategies to address these disparities should include the engagement of families in leadership roles, provision of comprehensive healthcare, cross-sectoral institutional and community collaborations, and the use of community-based participatory research (CBPR) methods. CBPR has demonstrated promise in enhancing the effectiveness of interventions. However, the challenge remains to understand how and what type of partnerships and participation most effectively enhance the integration of science and practice to eliminate disparities. Discussion: Researchers, community leaders, and healthcare professionals are integral in delivering quality healthcare to minority communities. Researchers must be culturally competent enough to be able to go out into these communities and collect accurate data about these communities. Researchers must find effective strategies and methodologies to gain the trust of the minority community that their research is directly impacting. This can effectively be done by working with local community leaders and community organizations. Local community leaders have the responsibility of voicing the issues and barriers that the community has in accessing quality healthcare. Healthcare professionals have a responsibility to take the research data and work with community leaders to find effective ways to address disparities. In some cases, they may even have to seek funding through government agencies to ensure long-term solutions

Developing a Prototype Ground Station for the Processing, Exploitation, and Dissemination of pLEO Sensor Data

The Air Force’s Space and Missile Systems Center (SMC) recently executed a quick-turnaround (16 month) effort through the Defense Innovation Unit to develop a prototype ground architecture demonstrating low-latency processing, exploitation, and dissemination of data collected by notional multi-phenomenology sensors hosted on small satellites in a proliferated LEO constellation. This effort, led by the Southwest Research Institute and supported by teammates, Amazon Web Services, SpaceX, and SciTec, Inc., involved the modeling and simulation of a variety of different OPIR, EO/IR, and SAR data streams; transporting these data via space and ground networks; processing the data in the AWS cloud environment; and then disseminating resulting products to tactical users. In this paper, we present an overview of the data transport and mission data processing, performance results from the application of our various Mission Data Processing Chains, a summary of our findings on the latencies associated with both data transport and data processing, and lessons learned including insight into ground-based vs. on-board processing

OzFlux data: network integration from collection to curation

Measurement of the exchange of energy and mass between the surface and the atmospheric boundary-layer by the eddy covariance technique has undergone great change in the last 2 decades. Early studies of these exchanges were confined to brief field campaigns in carefully controlled conditions followed by months of data analysis. Current practice is to run tower-based eddy covariance systems continuously over several years due to the need for continuous monitoring as part of a global effort to develop local-, regional-, continental- and global-scale budgets of carbon, water and energy. Efficient methods of processing the increased quantities of data are needed to maximise the time available for analysis and interpretation. Standardised methods are needed to remove differences in data processing as possible contributors to observed spatial variability. Furthermore, public availability of these data sets assists with undertaking global research efforts. The OzFlux data path has been developed (i) to provide a standard set of quality control and post-processing tools across the network, thereby facilitating inter-site integration and spatial comparisons; (ii) to increase the time available to researchers for analysis and interpretation by reducing the time spent collecting and processing data; (iii) to propagate both data and metadata to the final product; and (iv) to facilitate the use of the OzFlux data by adopting a standard file format and making the data available from web-based portals. Discovery of the OzFlux data set is facilitated through incorporation in FLUXNET data syntheses and the publication of collection metadata via the RIFCS format. This paper serves two purposes. The first is to describe the data sets, along with their quality control and post-processing, for the other papers of this Special Issue. The second is to provide an example of one solution to the data collection and curation challenges that are encountered by similar flux tower networks worldwide.J. Beringer is funded under an ARC FT (FT1110602)

Resting metabolic rate and lung function in wild offshore common bottlenose dolphins, Tursiops truncatus, near Bermuda

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Frontiers in Physiology 9 (2018): 886, doi:10.3389/fphys.2018.00886.Diving mammals have evolved a suite of physiological adaptations to manage respiratory gases during extended breath-hold dives. To test the hypothesis that offshore bottlenose dolphins have evolved physiological adaptations to improve their ability for extended deep dives and as protection for lung barotrauma, we investigated the lung function and respiratory physiology of four wild common bottlenose dolphins (Tursiops truncatus) near the island of Bermuda. We measured blood hematocrit (Hct, %), resting metabolic rate (RMR, l O2 ⋅ min-1), tidal volume (VT, l), respiratory frequency (fR, breaths ⋅ min-1), respiratory flow (l ⋅ min-1), and dynamic lung compliance (CL, l ⋅ cmH2O-1) in air and in water, and compared measurements with published results from coastal, shallow-diving dolphins. We found that offshore dolphins had greater Hct (56 ± 2%) compared to shallow-diving bottlenose dolphins (range: 30–49%), thus resulting in a greater O2 storage capacity and longer aerobic diving duration. Contrary to our hypothesis, the specific CL (sCL, 0.30 ± 0.12 cmH2O-1) was not different between populations. Neither the mass-specific RMR (3.0 ± 1.7 ml O2 ⋅ min-1 ⋅ kg-1) nor VT (23.0 ± 3.7 ml ⋅ kg-1) were different from coastal ecotype bottlenose dolphins, both in the wild and under managed care, suggesting that deep-diving dolphins do not have metabolic or respiratory adaptations that differ from the shallow-diving ecotypes. The lack of respiratory adaptations for deep diving further support the recently developed hypothesis that gas management in cetaceans is not entirely passive but governed by alteration in the ventilation-perfusion matching, which allows for selective gas exchange to protect against diving related problems such as decompression sickness.Funding for this project was provided by the Office of Naval Research (ONR YIP Award No. N000141410563, and Dolphin Quest, Inc. FHJ was supported by the Office of Naval Research (Award No. N00014-1410410) and an AIAS-COFUND fellowship from Aarhus Institute of Advanced Studies under the FP7 program of the EU (Agreement No. 609033)

Net ecosystem carbon exchange of a dry temperate eucalypt forest

Forest ecosystems play a crucial role in the global carbon cycle by sequestering a considerable fraction of anthropogenic CO₂, thereby contributing to climate change mitigation. However, there is a gap in our understanding about the carbon dynamics of eucalypt (broadleaf evergreen) forests in temperate climates, which might differ from temperate evergreen coniferous or deciduous broadleaved forests given their fundamental differences in physiology, phenology and growth dynamics. To address this gap we undertook a 3-year study (2010–2012) of eddy covariance measurements in a dry temperate eucalypt forest in southeastern Australia. We determined the annual net carbon balance and investigated the temporal (seasonal and inter-annual) variability in and environmental controls of net ecosystem carbon exchange (NEE), gross primary productivity (GPP) and ecosystem respiration (ER). The forest was a large and constant carbon sink throughout the study period, even in winter, with an overall mean NEE of −1234 ± 109 (SE) g C m⁻² yr⁻¹. Estimated annual ER was similar for 2010 and 2011 but decreased in 2012 ranging from 1603 to 1346 g C m⁻² yr⁻¹, whereas GPP showed no significant inter-annual variability, with a mean annual estimate of 2728 ± 39 g C m⁻² yr⁻¹. All ecosystem carbon fluxes had a pronounced seasonality, with GPP being greatest during spring and summer and ER being highest during summer, whereas peaks in NEE occurred in early spring and again in summer. High NEE in spring was likely caused by a delayed increase in ER due to low temperatures. A strong seasonal pattern in environmental controls of daytime and night-time NEE was revealed. Daytime NEE was equally explained by incoming solar radiation and air temperature, whereas air temperature was the main environmental driver of night-time NEE. The forest experienced unusual above-average annual rainfall during the first 2 years of this 3-year period so that soil water content remained relatively high and the forest was not water limited. Our results show the potential of temperate eucalypt forests to sequester large amounts of carbon when not water limited. However, further studies using bottom-up approaches are needed to validate measurements from the eddy covariance flux tower and to account for a possible underestimation in ER due to advection fluxes

MUSIC for sub/millimeter astrophysics

MUSIC (the Multiwavelength Submillimeter kinetic Inductance Camera) is an instrument being developed for the Caltech Submillimeter Observatory by Caltech, JPL, the University of Colorado, and UCSB. MUSIC uses microwave kinetic inductance detectors (MKIDs) - superconducting micro-resonators - as photon detectors. The readout is almost entirely at room temperature and is highly multiplexed. MUSIC will have 576 spatial pixels in four bands at 850, 1100, 1300 and 2000 microns. MUSIC is scheduled for deployment at the CSO in the winter of 2010/2011. We present an overview of the camera design and readout and describe the current status of the instrument and some results from the highly successful May/June 2010 observing run at the CSO with the prototype camera, which verified the performance of the complete system (optics, antennas/filters, resonators, and readout) and produced the first simultaneous 3-color observations with any MKID camera

Status of MUSIC, the MUltiwavelength Sub/millimeter Inductance Camera

We present the status of MUSIC, the MUltiwavelength Sub/millimeter Inductance Camera, a new instrument for the Caltech Submillimeter Observatory. MUSIC is designed to have a 14', diffraction-limited field-of-view instrumented with 2304 detectors in 576 spatial pixels and four spectral bands at 0.87, 1.04, 1.33, and 1.98 mm. MUSIC will be used to study dusty star-forming galaxies, galaxy clusters via the Sunyaev-Zeldovich effect, and star formation in our own and nearby galaxies. MUSIC uses broadband superconducting phased-array slot-dipole antennas to form beams, lumpedelement on-chip bandpass filters to define spectral bands, and microwave kinetic inductance detectors to sense incoming light. The focal plane is fabricated in 8 tiles consisting of 72 spatial pixels each. It is coupled to the telescope via an ambient-temperature ellipsoidal mirror and a cold reimaging lens. A cold Lyot stop sits at the image of the primary mirror formed by the ellipsoidal mirror. Dielectric and metal-mesh filters are used to block thermal infrared and out-ofband radiation. The instrument uses a pulse tube cooler and ^(3)He/^(3)He/^(4)He closed-cycle cooler to cool the focal plane to below 250 mK. A multilayer shield attenuates Earth's magnetic field. Each focal plane tile is read out by a single pair of coaxes and a HEMT amplifier. The readout system consists of 16 copies of custom-designed ADC/DAC and IF boards coupled to the CASPER ROACH platform. We focus on recent updates on the instrument design and results from the commissioning of the full camera in 2012