This study uses a grounded approach with the aim of exploring shame in the clinical population and presenting a conceptual model for it. The participants consisted of 17 individuals (8 females and 9 males) who were chosen using purposive sampling at first and later using theoretical sampling. The data collection method was non-structured interviewing. To analyze data, the Corbin and Strauss method (2014) and the MAXQDA (2018) software were used. Based on the findings of this study, three conditions of shame were revealed as follows: “Do’s and Don’ts “, “Making a Mistake” and “The Others “. The revealed action- interaction was “Shame-relief Strategies “. The consequences of these strategies were “Being Fake” “Negative Self-attitude “, with three sub-categories of ”Clumsiness,” ”Inadequacy,” and “Worthlessness”. Based on the findings, the theory of ”Shame as a Pillory of Musts” was presented. According to this theory, violating ”Do’s and Don’ts” which has been transmitted to individuals leads to the experience of shame. In response, individuals use a variety of strategies to eliminate or reduce shame. Due to the continuous and inflexible use of these strategies, individuals feel distanced from their real selves and develop a negative attitude, which perpetuates the vicious cycle of shame.

Traditional trans-critical CO 2 refrigeration cycles are energy-intensive, and their efficiency is influenced by outdoor conditions. This study presents a novel technique to enhance the efficiency of these cycles by integrating a thermoelectric sub-cooler tailored to Jordan’s climate. The trans-critical CO 2 refrigeration cycle, with a nominal refrigeration capacity of 14 kW, was modeled using Engineering Equation Solver (EES) software. A key aspect of this study is the incorporation of solar energy through a custom-designed photovoltaic (PV) system to power the refrigeration cycle, contributing to sustainable cooling technology. Key performance indicators, including refrigeration capacity, power consumption, and coefficient of performance (COP), were thoroughly investigated across varying parameters such as gas cooler pressure (8,000–13,000 kPa), evaporation temperature (-15 to 15°C), ambient temperature (28–40°C), current supply (5–15A), and the number of thermoelectric pairs (50–150). Results showed that increasing gas cooling pressure increased refrigeration capacity by approximately 79%. At a gas cooling pressure of 9,000 kPa, the thermoelectric sub-cooler increased refrigeration capacity by 55%. Increasing the evaporation temperature improved the COP by approximately 125% and reduced power consumption by 67%. At an evaporation temperature of -15°C, the thermoelectric sub-cooler improved performance by 7.5%. Lowering the ambient temperature also enhanced COP by 60% and reduced power consumption by 33%. At a 40°C ambient temperature, the sub-cooler improved COP by 7.6%. Experimental validation showed a 6% average deviation between simulation and experimental results for COP. The on-grid PV system designed with PVsyst software successfully met the cycle’s energy demands, achieving 45.3% energy savings.

Residual neuromuscular blockade (RNB) commonly occurs when using neuromuscular blockers and increases the risk for pulmonary complications, such as airway obstruction and severe hypoxemia, in extubated patients. Rocuronium exhibits a high variability in recovery time, contributing to an increased risk for RNB. This study aimed to identify and characterize the sources of variability in rocuronium exposure and response via a population pharmacokinetic/pharmacodynamic (PK/PD) analysis and to apply the developed PK/PD model to investigate clinical implications. A nonlinear mixed-effect model was developed for rocuronium in patients undergoing general anaesthesia, using doses of 0.3–1.2 mg/kg. Plasma concentrations and the neuromuscular block [train of four ratio] were assessed up to 6 h after dosing. The influence of age, body mass index, renal function, and sex on PK and PD was explored. Simulations were performed to predict the recovery time. A two-compartment model with linear elimination and an indirect sigmoid I-max model was used to describe PK and PD. The transfer rate into the periphery increases with age. The predicted recovery time was significantly longer in older subjects compared to young adults following single bolus administrations of doses ≥ 0.7 mg/kg. Our findings suggest that geriatric patients take slightly longer to recover than younger adults due to an age-dependent increase in tissue uptake. However, a priori dose adjustments for rocuronium in elderly patients are not feasible, since age contribution is overshadowed by the overall variability in the recovery time.

This paper analyses the flow of MHD Casson nanofluid in a steady-state on a linearly stretched sheet on a 2D boundary layer with radiation and heat generation. Parametric study of heat generation, radiation, suction/injection, Casson fluid flow parameter, Lewis number, thermophoresis, and Prandtl number have been carried out. The nonlinear coupled partial differential equations are changed into a nonlinear coupled ordinary differential equation by similarity transformations and are solved with the 4 th order Runge-Kutta method with the shooting technique. From the current investigation it is been recorded that, magnifying heat generation and radiation parameters amplify the thermal process and diminishes the concentration diffusion. Amplifying heat generation led to the decelerating of local Nusselt number. To conclude, the novelty of current research work is to simplify the earlier works by considering heat source, Ohmic heating, thermophoresis, Brownian and radiation effects into the corresponding governing equations. Comparative study has been presented with the previous outcomes and observed to be in good understanding with the previously presented results.

This research highlights the possibility of increasing the thermal efficiency of evacuated tube solar collectors by adding fins to the factory fin without changing it. The goal is to harness solar energy at the lowest cost, smallest area, and best thermal performance by using a solar collector with evacuated tubes and heat pipes. The evacuated tube consists of two concentric glass tubes with a vacuum between them. The inner tube contains a carefully selected absorbing layer to obtain the highest absorption. The collector also contains an aluminum fin connected to the absorbing surface on one side and the heat pipe on the other side. Adding additional fins fixed between the fin on the evacuated tube side and the side of the fin connected to the heat pipe, and this addition leads to increasing the heat transfer efficiency because aluminum has a higher conductivity than air, and holes in adding fins get more turbulent, leading to cracking boundary layer and increase heat transfer. Aluminum discs with holes of different diameters were added. The diameters of the holes were calculated as follows (4, 6, 8, and 10) mm, with the number of discs fixed at ten discs for each of the five evacuated tubes in each case, as the experiment consists of two solar collectors, each of which consists of five tubes, the first within the factory specifications and the second to which the above discs were added. To validate the results of the experiment, SPSS was used under identical conditions for the two devices above, and the data were analyzed. The output of the experiment was Tout, and the readings used were the results of the two devices at a flow rate of (0.5, 1.0, 1.5) l/min. The significance criterion was 95%, which was used to evaluate the results of the study and the effectiveness of the additives by comparing the significance calculated at a threshold of 0.05. The model is ranked if the two elements on which the reliability depends are less than a point or 0.05. It is effective in terms of flow rate and type of improvement. If the estimated value exceeds the point or 0.05 limits, no improvement or data analysis will be based on the flow rate and type of increase.

Lung cancer during pregnancy is exceptionally rare, with only 93 reported cases from 1953 to 2024. Our study identified 40 cases of lung cancer during pregnancy from a 9 million patient database, contributing to a total to 133 documented instances in the literature, and the only powered case series. Using the HCUP-NIS database (2004-2014), we conducted a retrospective analysis comparing maternal and fetal outcomes in women with and without lung cancer. Results showed that pregnant women with lung cancer were older and had higher rates of smoking, chronic hypertension, and pregestational diabetes (P<0.01, all). Significant risks included placenta previa (OR: 5.67, 95% CI:1.36-23.65, p=0.017), abruptio placenta (OR: 4.99, 95% CI: 1.49-16.74, p=0.009), operative vaginal delivery (OR: 4.88, 95% CI: 2.14-11.11, p<0.001), and transfusion (OR: 8.92, 95% CI: 3.28-24.28, p<0.001). They also have markedly higher odds of venous thromboembolism (OR:21.83, 95% CI: 2.92-163.47, p<0.001), disseminated intravascular coagulation (OR:  8.45, 95% CI: 1.14-62.42, p=0.04), and maternal death (OR: 195.02, 95% CI: 40.61-936.55, p<0.001), highlighting the necessity for specialized care and further research into this rare and complex condition.

Background Over ten years since the first qualitative evidence synthesis (QES) was published in the Cochrane Library, QES and mixed-methods reviews (MMR) with a qualitative component have become increasingly common and influential in healthcare research and policy development. The quality of such reviews and the completeness with which they are reported is therefore of paramount importance. Aim This review aimed to assess the reporting quality of published QESs and MMRs with a qualitative component in the Cochrane Library. Methods All published QESs and MMRs were identified from the Cochrane Library. A bespoke framework developed by key international experts based on the Effective Practice and Organisation of Care (EPOC), Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) and meta-ethnography reporting guidance (eMERGe) was used to code the quality of reporting of QESs and MMRs. Results Thirty-one reviews were identified, including 11 MMRs. The reporting quality of the QESs and MMRs published by Cochrane varied considerably. Based on the criteria within our framework, just over a quarter (8, 26%) of the reviews achieved a score of at least 80%, 18 (58%) required fuller detail in their reporting (scoring between 65%-79%) and 5 (16%) achieved a score of less than 65%. Conclusion This assessment offers important insights into the reporting practices prevalent in these review types and underscores the need for ongoing surveillance. The variability in reporting quality within QESs and MMRs reinforces the need to develop Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) specifically for QES.

Hepatocellular carcinoma (HCC) is one of the therapeutically challenging liver cancer with high mortality rate in human worldwide. Animal model plays pivotal role in basic and translational research in cancer and which is most important for complex and challenging cancers such as hepatocellular carcinoma. Until now different animal models have been developed which includes induced, immunocompromised, humanized, genetically modified and syngeneic rodent models considering different etiological factors such as viral, chemical carcinogen, genetic mutation, alcoholism etc. Nowadays, orthotopic models of HCC which mimic similar microenvironment as like human HCC are commonly used and validation of these models are challenging, as characterization and quantification of the tumors is not easy due to anatomical and physiological peculiarities of liver. So non-invasive preclinical imaging techniques such as Computed Tomography (CT), Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), Bioluminescence Imaging (BLI) and fluorescence Imaging are being utilized for better monitoring and understanding of tumor growth as well as to avoid mortality and to improve reproducibility of the data with minimum number of animals. This review provides an overview of recent developments in animal models for liver cancer research and also focusses on advances in validation of these models using non-invasive preclinical imaging modalities.

Microevolutionary processes shape adaptive responses to heterogeneous environments, where these effects vary both among and within species. However, it remains largely unknown to which degree signatures of adaptation to environmental drivers can be detected based on the choice of spatial scale and genomic marker. We studied signatures of local adaptation across two levels of spatial extents, investigating complementary types of genomic variants–single nucleotide polymorphisms (SNPs) and polymorphic transposable elements (TEs)–in populations of the alpine model plant species Arabis alpina. We coupled environmental factors, derived from remote sensing digital elevation models at very high resolution (0.5m), with whole-genome sequencing data of 304 individuals across four populations. By comparing putatively adaptive loci detected between each local population versus a regional assessment including all populations simultaneously, we demonstrate that responses of A. alpina to similar amounts of abiotic variation are largely governed by local evolutionary processes. Furthermore, we find minimally overlapping signatures of local adaptation between SNPs and polymorphic TEs. Notably, functional annotations of candidate genes for adaptation revealed several symbiosis-related genes associated with the abiotic factors studied, which could represent selective pressures from biotic agents. Our results highlight the importance of considering different spatial extents and types of genomic polymorphisms when searching for signatures of adaptation to environmental variation. Such insights provide key information on microevolutionary processes and could guide management decisions to mitigate negative impacts of climate change on alpine plant populations.

A document by Zainab Shehzadi. Click on the document to view its contents.

1. Title: Unveiling Crohn’s Disease Through Extraintestinal Symptoms: A Case Study and Management ApproachAuthors: Dr. Mohammed Omer Elbadawi Elhassan1, Dr. Feroz Jenner Poolakundan2, Dr. Sara Alawneh1, Dr. Namaa Abubaker Suliman Elshaikh1, Dr. Abdelkarim Hashim Mohamed2Medical Education Department, Hamad Medical Corporation, Doha, QatarDepartment of Medicine, Hamad Medical Corporation, Doha, Qatar*Corresponding author:Name: Mohammed Omer Elbadawi Elhassan Email:mohdomer42@yahoo.comHamad Medical Corporation (HMC), Doha, QatarP.O. Box 3050 Doha, QatarEmails :mohdomer42@yahoo.com, https://orcid.org/0009-0005-7367-0974 fpoolakundan@hamad.qa Salawneh@hamad.qa namaabubker800@gmail.com amohamed48@hamad.qa

Cold agglutinin Syndrome as the Initial Presentation of Acute Myeloid Leukemia: A Case Report

The spatial pattern and community assembly of soil microbial taxa have notable meanings for biodiversity shaping and maintaining mechanisms. Rare fungal taxa may exhibit distinct patterns and assembly mechanisms compared to abundant taxa, but such information is limited, especially at large scales. Here, we investigated distance-decay patterns and underlying assembly mechanisms for abundant and rare fungal taxa in 129 soil samples collected across 4,000 km in Chinese Northern grasslands, based on high-throughput sequencing data. A total of 208 abundant OTUs (relative abundance > 0.1%, 2.73% of entire OTUs) and 5,779 rare OTUs (relative abundance < 0.01%, 75.85% of entire OTUs) were identified. Both abundant and rare fungal taxa showed significant distance-decay relationships (P < 0.001), but the turnover rate for rare taxa (0.0024 per 100 km) was nearly half that of abundant taxa (0.0054 per 100 km) based on the binary Bray-Curtis distance. The lower turnover of rare fungal taxa was likely due to their community assembly mechanism dominated by stochastic processes, which were less influenced by environmental gradients. In contrast, abundant taxa assembly was dominated by deterministic factors like soil variables and plant traits, which varied significantly along the geographic distance. Consistently, rare fungal taxa were also less sensitive to environmental changes, with a lower turnover rate by environmental distance (0.0027 vs. 0.0099) than abundant taxa. In summary, our findings revealed that rare fungal taxa, shaped mainly by stochastic processes, had lower spatial turnover compared to abundant taxa, dominated by deterministic processes, enhancing our understanding of rare microbial biogeography.

Bacteria are key players in shaping the dynamics of marine ecosystems. This study specifically examines heterotrophic communities in the Eastern Arabian Sea (EAS) along the West Coast of India (WCI) during the Southwest monsoon. We hypothesize that heterotrophic productivity, bacterial biomass and community distribution varies from south to north of WCI-EAS. Measurements were made along the EAS from 4 transects – Kochi (L1-L3), Mangalore (L4-L6), Goa (L7-L9) and Mumbai (L10-L12); 9°N-21°N - during September, 2019. The water samples were analyzed for bacterial production (3H), prokaryotic abundance (epifluorescence) and bacterial biomass (SEM) as cell specific carbon density. Metagenomic analysis was carried out to understand the genetic and functional diversity of bacterial community using Oxford Nanopore sequencing platform. Taxonomic analysis identified Proteobacteria as the dominant phyla in all stations (47-56%) followed by Bacteroidetes (3-26%) in the coastal stations. In the deeper station Proteobacteria is followed by Candidatus Marinimicrobia (3-24%), whereas Actinobacteria (2-24%) and Cyanobacteria (0-13%) higher in offshore surface waters. KEGG pathway analysis showed that bacterial communities of L1 (0m) and L10 (0m) were functionally more active in terms of metabolism than the rest of the stations; the KEGG level two analysis confirms the same in the case of carbohydrate energy metabolism, amino acid metabolism, lipid metabolism, translation and transcription as well. Distinct Carbohydrate active enzymes (CAZy) gene profile was observed between coastal and offshore as well as between north and south. Conclusively, our findings underscore substantial disparities in carbon-associated genes, unraveling their profound implications for the biogeochemical intricacies within the WCI.

Competence is an important bioprocess for Streptococcus pneumoniae. Previously, we demonstrated that bacterial second messenger cyclic di-adenosine monophosphate (c-di-AMP) modulates pneumococcal competence. Surprisingly, a low c-di-AMP-producing strain, cdaA*, due to a mutation in the diadenylate cyclase CdaA, is highly susceptible to competence-stimulating peptide (CSP). In this study, we screened cdaA* suppressor mutations resistant to CSP to explore c-di-AMP signaling in S. pneumoniae. A total of 14 clones were sequenced, nine clones possessed mutations in the c-di-AMP phosphodiesterase Pde1, indicating that the susceptibility to CSP of cdaA* is correlated to c-di-AMP levels. Another two clones exhibited a mutation in FabT, a transcription factor controlling cell membrane fatty acid biosynthesis and metabolism. We further showed that deletion of fabT, disruption of the FabT-binding site within the P fabK promoter, deletion of a fabT activator BriC, or disruption of K + uptake in cdaA* all rescued the growth defect of cdaA* in media supplemented with CSP. Finally, we found that a c-di-AMP phosphodiesterase-null mutant with high levels of c-di-AMP is highly sensitive to treatment with either ethanol or Triton X-100, which could be corrected by reducing c-di-AMP levels through introducing point mutations in CdaA. Together, these findings indicate that c-di-AMP affects cell membrane integrity.

The ability of contemporary language models to process and adapt to evolving contextual demands has brought remarkable progress, yet consistently achieving contextually accurate and semantically coherent outputs remains an intricate task in adaptive representation learning. Dynamic Context Shaping (DCS) introduces a significant departure from traditional approaches through a novel mechanism designed to embed context-sensitivity at the core of model architecture, empowering language models to recalibrate representations dynamically across diverse, context-rich tasks without imposing excessive computational overhead. This paradigm utilizes multi-layered parameter modulation, embedding context-aware adjustments at various stages of processing, thereby allowing each layer to refine its output according to the evolving semantic cues within the input, resulting in enhanced model adaptability and responsiveness. Empirical evaluations reveal that DCS surpasses traditional fixedcontext frameworks, demonstrating substantial gains in context alignment accuracy, semantic stability across temporal shifts, and efficiency in resource utilization, with a noted reduction in computational strain even during high-dimensional tasks. The incorporation of context-modulation functions further enables the model to retain critical information through adaptive control of coherence parameters, significantly minimizing representational drift and thereby enhancing interpretative stability in complex, real-world applications. Additionally, implementing DCS within an open-source language model highlights its accessibility and reproducibility, underscoring its adaptability for a wide range of linguistic environments. DCS's contribution to the landscape of adaptive representation learning is not limited to incremental performance improvements; it represents a reimagining of how language models process and prioritize contextual information, with implications for diverse applications that require sustained contextual precision. Through its layered, context-sensitive recalibration, DCS redefines adaptability, marking a promising trajectory for future advancements in language modeling and adaptive learning frameworks suited to the nuanced demands of dynamic linguistic contexts.

Note: Strings and micro cylinders of structured  nanowires  (silicon/germanium)  are used for possible applications in energy, electronics, optics and other fields.Nanowires  (Si Silicon / Germanium Gi)  , narrow structures whose diameter is only a few billionths of a meter but thousands or millions of times longer.  They exist in various forms—made of metals, semiconductors, insulators, and organic compounds—and are used for applications in the fields of electronics, energy conversion, optics, and chemical sensing. Because of their extreme thinness, nanowires  with a (Si Silicon / Germanium Gi) structure  are essentially one-dimensional. Nanowires  are quasi-one-dimensional materials, "their two dimensions are on the nanometer scale."  This one-dimensionality confers distinct electrical and optical properties. For one thing, this means that the electrons and photons in these nanowires experience "confined quantum effects." However  , unlike other materials that produce such quantum effects, such as quantum dots, the length of nanowires allows them to communicate with other macroscopic devices and the outside world.

Adaptive detection frameworks are crucial for addressing the sophisticated and evolving tactics of ransomware, which poses significant risks to cybersecurity infrastructures worldwide. The Adaptive Signature Extraction Framework introduced here leverages dynamic signature generation alongside advanced machine learning algorithms to improve detection accuracy and system responsiveness. Central to its design are adaptive mechanisms that automatically refine detection signatures based on real-time data, enabling the system to counteract new ransomware behaviors effectively. Evaluation results reveal substantial improvements in precision and recall metrics compared to conventional detection models, achieving a low false positive rate while maintaining high processing efficiency. The framework's architecture, which integrates ensemble learning and feature extraction, demonstrates a balance between computational demand and detection accuracy, making it suitable for both large-scale and resource-constrained environments. By reducing detection latency and adapting dynamically to emerging threats, the framework presents a significant advancement in cybersecurity measures, ensuring resilience against both known and novel ransomware attacks.

Adaptive Signature Analysis (ASA) provides a robust framework for enhancing ransomware detection through an innovative combination of dynamic pattern recognition and adaptive learning. Unlike conventional detection models, ASA identifies both known and previously unseen ransomware strains with precision, leveraging continuous updates to its detection parameters and maintaining high accuracy even against advanced evasion techniques. The methodology employs a multilayered approach to classify and analyze ransomware, utilizing comprehensive datasets that capture behavioral and structural attributes across diverse ransomware families. Rigorous experimental assessments highlight ASA's superior detection accuracy, achieving 98.7% accuracy with reduced false positive and negative rates in comparison to baseline methods, and it exhibits efficient processing times suited for real-time applications. ASA's scalability was further demonstrated through its consistent performance across datasets of increasing size, with minimal computational resource requirements, positioning it as a viable solution in environments constrained by limited hardware. The study emphasizes ASA's resilience and adaptability, showing its contribution as an effective response to the evolving threat landscape posed by ransomware.

This article develops a duality principle through a D.C. approach applicable to some originally non-convex primal variational formulations. More specifically, in a first step, we develop applications to a Ginzburg-Landau type equation. The results are obtained through basic tools of functional analysis, calculus of variations, duality and optimization theory in infinite dimensional spaces. It is worth emphasizing we have obtained a convex dual variational formulation which may be applied to a large class of similar models in the calculus of variations. Finally, in the last sections we present a numerical example and related software.

Future long-duration crewed space missions beyond Low Earth Orbit (LEO) will bring new healthcare challenges for astronauts for which pharmacological countermeasures (PCMs) are crucial. This paper highlights current PCMs challenges described in the ESA SciSpacE Roadmap, with a focus on the cardiovascular system as a model to demonstrate the potential implication of the challenges and recommendations. New pharmacological approaches and procedures need to be adapted to spaceflight (SF) conditions. Potential strategies include combining pharmacological biomarkers such as pharmacogenomics with therapeutic drug monitoring, advancing microsampling techniques, and implementing a pharmacovigilance system to gain deep insights into pharmacokinetics/pharmacodynamics (PK/PD) spaceflight alteration on drug exposure. Emerging therapeutic approaches (such as long-term regimens) or manufacturing drugs in the space environment, can address specific issues related to drug storage and stability. The integration of biobanks and innovative technologies like organoids and organ-on-a-chip, artificial intelligence (AI), including machine learning will further enhance PK modelling leading to personalized treatments. These innovative pharmaceutical tools will also enable reciprocal game-changing healthcare developments to be made on Earth as well as in space and are essential to ensure space explorers receive safe effective pharmaceutical care.

Note: The interaction of gold nanoparticles with light is strongly determined by their environment, size and physical dimensions.  The oscillating electric fields of a light beam emitted in the vicinity of a colloidal nanoparticle interfere with the free electrons and cause a coordinated oscillation of the electron charge that corresponds to the frequency of visible light.  These resonant oscillations are known as surface plasmons.  For small (30 nm) monodisperse gold nanoparticles, the phenomenon of surface plasmon resonance causes absorption of light in the blue-spectral part (~450 nm) while red light (~700 nm) is reflected.Gold is a soft and malleable metal with a bright and shiny yellow color that does not rust or darken in the vicinity of air and water. This metal can be found pure in nature in the form of grains or pieces among stones, minerals. Crystallized and alluvial deposits were found. The chemical symbol of this element, Au, is derived from its Latin name, aurum, which means "dawn glow". The value of gold is due to its rarity, easy application, easy purification, resistance to rust. Corrosion, distinctive color, non-reactivity with other elements, characteristics that are seen in few other metals. One gram of this element can be hammered to the size of a sheet with an area of one square meter.

Urbanization has greatly affected wildlife and will continue to do so into the future, but we know little about whether traits of closely related species respond similarly to this environmental change. To address this gap, we tested the association between urbanization and morphological traits of two congeneric songbird species-northern cardinals (Cardinalis cardinalis) and pyrrhuloxia (C. sinuatus)-that largely share a niche in and around the Sonoran Desert city of Tucson, Arizona over 137 years. We measured museum and field-collected specimens and used novel hindcast models of urban areas to score urbanization over time. Both urbanization and time of sampling were associated with larger bills in male pyrrhuloxia and in female northern cardinals, which may affect foraging, song, and heat tolerance. Degree of urbanization was also associated with changes in coloration of male northern cardinal face masks and female northern cardinal breast patches. We demonstrate that the effects of urbanization can differ even in two closely related species, with effects on traits involved in visual signaling, heat tolerance, and foraging.

Glenn Jakobsen, DO, FAAPMR, MPH (Candidate)