Physiology Information Research Articles

Recent advances of sweat sampling, sensing, energy-harvesting and data-display toward flexible sweat electronics

Sweat contains diverse types of biomarkers that can mirror an individual’s health condition. The forefront research of sweat monitoring primarily focuses on sensing basic parameters, i.e., sweat rate and single electrolyte imbalances in controlled laboratory settings. However, recent works show the potential of sweat for the rich biomarkers in aspects of comprehensive health status display, timely safety alarming, and energy harvesting. The advances in wearable flexible electronics enable continuous, real-time, noninvasive detection of multiple sweat components, providing molecular-level insights into human physiology and psychology information; additionally, the efficient sweat extraction technologies of flexible electronics promote its application in energy harvesting, contributing to advancing a flexible sweat platform. This review comprehensively explores flexible sweat-based electronics, encompassing four key aspects: sweat sampling methods, sweat-based sensors, sweat-based energy harvesters, and sweat data display methods. Firstly, the traditional sweat-based platform is discussed in sweat sampling, sensing, and data analysis. Then, the development of wearable sweat sampling methods is discussed with a comparison of the traditional sweat collection methods. After that, the recent advances in sweat-based biosensors for monitoring diverse sweat analytes, such as the perspiration volume, glucose, lactate, and uric acid levels, are summarized. Subsequently, this review also highlights the recent progress and potential value of sweat-based energy harvesters in sweat-activated batteries and bio-fuel cells. Furthermore, multiple data display methods are proposed to achieve accurate feedback on health status, such as colorimetric techniques, light-emitting diodes, actuators, etc. Finally, this review concludes the main current challenges faced in practical applications of sweat-based bioelectronic systems and proposes a vision for the future evolution of this promising field.

A multimodal driver monitoring benchmark dataset for driver modeling in assisted driving automation

In driver monitoring various data types are collected from drivers and used for interpreting, modeling, and predicting driver behavior, and designing interactions. Aim of this contribution is to introduce manD 1.0, a multimodal dataset that can be used as a benchmark for driver monitoring in the context of automated driving. manD is the short form of human dimension in automated driving. manD 1.0 refers to a dataset that contains data from multiple driver monitoring sensors collected from 50 participants, gender-balanced, aged between 21 to 65 years. They drove through five different driving scenarios in a static driving simulator under controlled laboratory conditions. The automation level (SAE International, Standard J3016) ranged from SAE L0 (no automation, manual) to SAE L3 (conditional automation, temporal). To capture data reflecting various mental and physical states of the subjects, the scenarios encompassed a range of distinct driving events and conditions. manD 1.0 includes environmental data such as traffic and weather conditions, vehicle data like the SAE level and driving parameters, and driver state that covers physiology, body movements, activities, gaze, and facial information, all synchronized. This dataset supports applications like data-driven modeling, prediction of driver reactions, crafting of interaction strategies, and research into motion sickness.

Clinically relevant and explainable feature extraction from remote monitoring data for the prediction of urinary tract infections

AbstractBackgroundA frequent cause for hospitalisation in people living with dementia (PLWD) is urinary tract infections (UTIs) (Dufour et al., 2015). Early detection aids in avoiding unplanned hospitalisations and machine learning and connected sensors enable development of risk analysis models based on in‐home monitoring data. This work makes use of data from the ongoing Minder study at the UK Dementia Research Institute, including in‐door movement, appliance use, physiology, sleep, and environmental information. Previous work (Li et al., 2020) shows complex models can achieve high accuracy when detecting UTIs, but interpretability and generalisability remain an open issue. This work evaluates how clinically interpretable features and simple models perform.MethodThe engineered features reflect visible symptoms of UTIs in older adults and are daily aggregated and pre‐processed information from PLWD’s homes containing passive sensors. 14 activity, sleep and physiological features were engineered relating to bathroom visits, entropy rate, physiological readings, and sleep behaviour. Raw data consisted of frequencies of the activity sensor firings. Their use in predicting cases of UTIs was compared by evaluating multilayer perceptron models on labelled data (643 negatives and 311 positives, from 39 PLWD), using 5‐fold cross‐validation (80%/20% train/test split), with 5 repeats. Prior to training and testing, the data was z‐normalised using unlabelled data. When evaluating, recall is most essential because reducing false positive rates is crucial in our setting.ResultThe highest performing model achieved the best accuracy, recall, precision and F1 score (85.6%, 69.9%, 81.5%, 74.8%) on combinations of engineered and raw features; though not significantly higher than with raw features alone (83.2%, 63.5%, 80.5%, 70.8%). Full results can be seen in the attached figure.ConclusionOur engineered features do not significantly improve results but add interpretability and generalisability to predictions. The models' hidden layers have a high capacity for learning patterns in the raw data, however, may not be clinically interpretable and we hypothesise that engineered features improve generalisation. Engineered features are homogeneous across the cohort and new data, and so create a way of representing the data which is not single device dependent. To verify this, we will continue our data collection and will conduct further experiments.

Modelling and simulation approaches to support formulation optimization, clinical development and regulatory assessment of the topically applied formulations – Nimesulide solution gel case study

The objective of the study was to show how mechanistic modelling can be used to characterize the skin absorption of Nimesulide (NIM) in both in vitro systems and in vivo subjects. A basic PBPK model for oral absorption to characterize the systemic disposition of NIM and MPML MechDermATM models for in vitro permeation and in vivo, topical absorption was developed and verified using published data. The developed models utilize drug physicochemical properties, formulation attributes and physiology information either collected from literature and/or from Simcyp databases (systems’ data). Following the verification of the PBPK models virtual bioequivalence (VBE) trials were performed both at systemic and local exposure levels (dermis concentrations) to compare these formulations. A parameter sensitivity analysis was conducted to understand the impact of vehicle-related attributes on IVPT (in vitro permeation test) data. The vehicle-stratum corneum lipids partition coefficient in the formulation layer (Kpsc_lip:vehicle) was identified to be an appropriate parameter to take into account the differences in dermal absorption of marketed preparations based on the qualitative composition. Thus, this parameter was optimized for each marketed product based on the published in vitro data. After verification of the IVPT model, IVIVE was performed to assess the predictability of the model for studying the in vivo pharmacokinetics of NIM. The VBE analysis concluded that these formulations are bioequivalent at the level of systemic and local dermis exposure. To summarize, the study shows the use of modelling and simulation (M&S) tools to better understand the behaviour of formulations and their interaction with human physiology.

Information of university nurses in physiology and anatomy

Anatomy and physiology, these two sciences form a pair of related disciplines, and are often studied together. Important of the study is evaluation and identification of weaknesses in the anatomy and physiology information of the functional systems of university nurses, but problem of study is what the level of the university nurses about their information in anatomy & physiology of functional systems ? The aim of study is to record level the university nurses in anatomy & physiology according to the test. Sample of the study include (22) university nurses. (17) Female and (5) male. The instrument of the study questionnaire format determined by (11) parts (systems), each part contain 10 question (5 true and false, 5 multiple choice questions). The most important results of the study are the nurses' information level in physiology and anatomy is acceptable , where the nurses success ( 54.54 %) while the nurses fails (45.45 %) as well as there is a shortage of nurses' information in the Integumentary (skin) system with a percentage of (22.72 %) and Immune lymph system (40.90 %).

Automatic Recognition Methods Supporting Pain Assessment: A Survey

Pain is a complex phenomenon, involving sensory and emotional experience, that is often poorly understood, especially in infants, anesthetized patients, and others who cannot speak. Technology supporting pain assessment has the potential to help reduce suffering; however, advances are needed before it can be adopted clinically. This survey paper assesses the state of the art and provides guidance for researchers to help make such advances. First, we overview pain’s biological mechanisms, physiological and behavioral responses, emotional components, as well as assessment methods commonly used in the clinic. Next, we discuss the challenges hampering the development and validation of pain recognition technology, and we survey existing datasets together with evaluation methods. We then present an overview of all automated pain recognition publications indexed in the Web of Science as well as from the proceedings of the major conferences on biomedical informatics and artificial intelligence, to provide understanding of the current advances that have been made. We highlight progress in both non-contact and contact-based approaches, tools using face, voice, physiology, and multi-modal information, the importance of context, and discuss challenges that exist, including identification of ground truth. Finally, we identify underexplored areas such as chronic pain and connections to treatments, and describe promising opportunities for continued advances.

Metabolic Fluctuations in the Human Stool Obtained from Blastocystis Carriers and Non-Carriers.

Blastocystis is an obligate anaerobic microbial eukaryote that frequently inhabits the gastrointestinal tract. Despite this prevalence, very little is known about the extent of its genetic diversity, pathogenicity, and interaction with the rest of the microbiome and its host. Although the organism is morphologically static, it has no less than 28 genetically distinct subtypes (STs). Reports on the pathogenicity of Blastocystis are conflicting. The association between Blastocystis and intestinal bacterial communities is being increasingly explored. Nonetheless, similar investigations extending to the metabolome are non-existent.Using established NMR metabolomics protocols in 149 faecal samples from individuals from South Korea (n = 38), Thailand (n = 44) and Turkey (n = 69), we have provided a snapshot of the core metabolic compounds present in human stools with (B+) and without (B−) Blastocystis. Samples included hosts with gastrointestinal symptoms and asymptomatics. A total of nine, 62 and 98 significant metabolites were associated with Blastocystis carriage in the South Korean, Thai and Turkish sample sets respectively, with a number of metabolites increased in colonised groups. The metabolic profiles of B+ and B− samples from all countries were distinct and grouped separately in the partial least squares-discriminant analysis (PLS-DA). Typical inflammation-related metabolites negatively associated with Blastocystis positive samples. This data will assist in directing future studies underlying the involvement of Blastocystis in physiological processes of both the gut microbiome and the host. Future studies using metabolome and microbiome data along with host physiology and immune responses information will contribute significantly towards elucidating the role of Blastocystis in health and disease.

Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption

Wireless sensor network (WSN) can achieve real-time data collection and transmission of environment, soil, meteorology, crop physiology and other information in agriculture. The data provided by WSN could be used for decision making and management, which is very important in precision agriculture. Wheat farmland wireless sensor network has the characteristics of wide coverage area, long planting period, inconvenient energy supply, and serious impact of crop environment on wireless signal transmission. Routing protocol is an important method to achieve long-term WSN monitoring by selecting an appropriate path with low energy consumption for data transmission. According to the phenomenon of uneven environment and channel parameters caused by intensive crop growth in farmland, a non-uniform clustering routing protocol based on effective energy consumption (UCEEC) was proposed in this work. The method combined with the characteristics of multi-path fading of farmland environment signals. The idea of image segmentation was introduced. Nodes with high similarity were divided into a cluster area by the dissimilarity between nodes in order to improve the intracluster communication performance. Meanwhile, a multi-hop path selection method between cluster-heads based on the estimation of two-hop effective energy consumption is designed. The energy consumption cost factor is calculated by the effective energy consumption and the average energy consumption within the cluster to achieve the minimum and balance of the overall energy consumption of the network. Simulation results show that, compared with the existing Maximum Residual Energy Based Routing (MREBR) protocol, minimum Energy Consumption Based Routing (MEC) routing protocols, UCEEC improves the energy balance effect between nodes, prolongs the network life cycle, and realizes efficient energy utilization of wireless sensor network data collection in the complex environment of wheat field. Keywords: farmland, wireless sensor networks, multi-path fading channel, routing protocol, energy optimization DOI: 10.25165/j.ijabe.20211403.6540 Citation: Miao Y S, Zhao C J, Wu H R. Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption. Int J Agric & Biol Eng, 2021; 14(3): 163–170.

The Design of Abnormal Microenvironment Responsive MRI Nanoprobe and Its Application.

Magnetic resonance imaging (MRI) is often used to diagnose diseases due to its high spatial, temporal and soft tissue resolution. Frequently, probes or contrast agents are used to enhance the contrast in MRI to improve diagnostic accuracy. With the development of molecular imaging techniques, molecular MRI can be used to obtain 3D anatomical structure, physiology, pathology, and other relevant information regarding the lesion, which can provide an important reference for the accurate diagnosis and treatment of the disease in the early stages. Among existing contrast agents, smart or activatable nanoprobes can respond to selective stimuli, such as proving the presence of acidic pH, active enzymes, or reducing environments. The recently developed environment-responsive or smart MRI nanoprobes can specifically target cells based on differences in the cellular environment and improve the contrast between diseased tissues and normal tissues. Here, we review the design and application of these environment-responsive MRI nanoprobes.

Two-dimensional integration approach to teaching cardiovascular physiology: effectiveness and students\u2019 perspectives

BackgroundPre-clerkship medical curriculums consist of a series of organ system-based courses and lectures but often lack an integration between organ systems. Such integration could be beneficial for clerkship years and students’ future career. Hence, we aimed to share our process of organising an integrative teaching approach in a large class of pre-clerkship medical students and to reflect the students’ perspective toward the teaching process in this observational study. In addition, we tested effectiveness of this integrative approach compared with the traditional teaching (lecture).MethodsWe organised a two-dimensional (2D)-integrative teaching for 309 students in selected topics of cardiovascular physiology of the medical curriculum of the Faculty of Medicine, Chulalongkorn University, Thailand. The first dimension of integration is the incorporation of physiology of other organ systems into the cardiovascular physiology class. The second is the integration of multiple teaching methods and strategies, including small group discussion, student presentation, wrap-up, quiz, and question-and-answer sessions. Unless opting out, students evaluated this integrative teaching by filling in a questionnaire. The summative scores were also used to determine their comprehensive understandings of the content.ResultsThe course evaluation showed that most students (81.9–91.2%) had positive attitudes toward all organised sessions, i.e. this teaching method helps promote their basic and applied physiology knowledge, critical thinking, information searching, presentation, and teamwork skills. In general, students at all performance levels attained higher scores in the summative exam for the 2D-integrative-class–relevant questions (74.4±16.1%) than for the lecture-pertinent questions (65.2±13.6%).ConclusionsIn a large class size of pre-clerkship students, 2D-integrative teaching strategies with careful planning and preparation can be successfully implemented, based on positive attitudes and relatively high summative scores of students in this study. Hence, this comprehensive teaching could be incorporated in current medical curriculums, particularly for the complex learning topics.

Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption

Wireless sensor network (WSN) can achieve real-time data collection and transmission of environment, soil, meteorology, crop physiology and other information in agriculture. The data provided by WSN could be used for decision making and management, which is very important in precision agriculture. Wheat farmland wireless sensor network has the characteristics of wide coverage area, long planting period, inconvenient energy supply, and serious impact of crop environment on wireless signal transmission. Routing protocol is an important method to achieve long-term WSN monitoring by selecting an appropriate path with low energy consumption for data transmission. According to the phenomenon of uneven environment and channel parameters caused by intensive crop growth in farmland, a non-uniform clustering routing protocol based on effective energy consumption (UCEEC) was proposed in this work. The method combined with the characteristics of multi-path fading of farmland environment signals. The idea of image segmentation was introduced. Nodes with high similarity were divided into a cluster area by the dissimilarity between nodes in order to improve the intracluster communication performance. Meanwhile, a multi-hop path selection method between cluster-heads based on the estimation of two-hop effective energy consumption is designed. The energy consumption cost factor is calculated by the effective energy consumption and the average energy consumption within the cluster to achieve the minimum and balance of the overall energy consumption of the network. Simulation results show that, compared with the existing Maximum Residual Energy Based Routing (MREBR) protocol, minimum Energy Consumption Based Routing (MEC) routing protocols, UCEEC improves the energy balance effect between nodes, prolongs the network life cycle, and realizes efficient energy utilization of wireless sensor network data collection in the complex environment of wheat field. Keywords: farmland, wireless sensor networks, multi-path fading channel, routing protocol, energy optimization DOI: 10.25165/j.ijabe.20211403.6540 Citation: Miao Y S, Zhao C J, Wu H R. Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption. Int J Agric & Biol Eng, 2021; 14(3): 163–170.

A Physiologically Based Pharmacokinetic (PBPK) Model for Adults to Characterize BIVV001 Activity, a New Class of Factor VIII (FVIII) with High Sustained Factor Activity

Introduction PBPK models incorporate complex drug and system (ie, physiology) information into a mathematical framework to support dose selection while considering various patient factors (eg, age, sex, and comorbidity). Through "predict-learn-confirm cycles," PBPK models enable dose prediction to optimize clinical study design. BIVV001 (rFVIIIFc-VWF-XTEN), a new class of FVIII replacement therapy designed to break the von Willebrand factor (VWF) half-life ceiling (Chhabra et al.Blood. 2020; Konkle et al.Blood. 2018), consists of a single recombinant FVIII fused to dimeric Fc (to permit recycling of BIVV001 by a naturally occurring pathway via Fc neonatal receptors [FcRn]), a VWF D′D3 domain, and two XTEN® polypeptides (XTEN® is a registered trademark of Amunix Pharmaceuticals, Inc.). In a Phase 1 study (Lissitchkov et al.Blood. 2019), four once-weekly BIVV001 50 IU/kg infusions provided high sustained FVIII activity with a mean half-life of 41.3 hours. We aimed to build and verify an initial PBPK model to characterize BIVV001 activity levels in adults with severe hemophilia A. Methods To our knowledge, this is the first time that a PBPK model has been studied in hemophilia. We assumed that the distribution of BIVV001 and recombinant FVIII Fc fusion protein (rFVIIIFc) (Eloctate®) involves the FcRn recycling pathway that is similar to monoclonal antibodies. First, to evaluate the feasibility of the modeling approach, we built a PBPK model (Simcyp, Sheffield, UK) that captured FcRn-dependent recycling of Fc fusion proteins. Model input parameters were adjusted to capture observed rFVIIIFc activity levels with a prediction error of <1.35 by fitting values for the physiological parameters, equilibrium dissociation constant for FcRn binding (KD1), endothelial uptake rate (Kup), rate of recycling (Krc), and clearance by catabolism (CLcat). Next, a similar approach was used to characterize FVIII activity levels during the Phase 1 BIVV001 repeat-dose study (BIVV001 50 IU/kg and 65 IU/kg). The PBPK model virtual trial simulations were conducted at both BIVV001 doses using 100 virtual male subjects with an age range of 18-51 years. Results To fit the BIVV001 data, the PBPK model input parameters, KD1, vascular reflection coefficient (σv), and Kup, were modified compared with those used for the rFVIIIFc PBPK model. The PBPK model captured observed BIVV001 exposure with a low prediction error (<1.30) for maximal FVIII activity and area under the activity-time curve (Figure 1). The predicted inter-subject variability was lower than that for the observed data, which is likely due to the inability to include coefficients of variation for all parameters in the current Simcyp biologics module. Conclusions We have developed a PBPK model that accurately predicts the high sustained FVIII activity levels observed with BIVV001 exposure in adults with severe hemophilia A. The PBPK model framework can be a useful tool in the development of FVIII replacement therapies for hemophilia A. Disclosures Xia: Sanofi:Current Employment, Current equity holder in publicly-traded company.Katragadda:Sanofi:Current Employment, Current equity holder in publicly-traded company.Teutonico:Sanofi:Current Employment, Current equity holder in publicly-traded company.Macha:Sanofi:Current Employment, Current equity holder in publicly-traded company.Demissie:Sanofi:Current Employment, Current equity holder in publicly-traded company.Benson:Sanofi:Current Employment, Current equity holder in publicly-traded company.

The impact of hypertonic saline on cerebrovascular reactivity and compensatory reserve in traumatic brain injury: an exploratory analysis.

BackgroundIntravenous hypertonic saline is utilized commonly in critical care for treatment of acute or refractory elevations of intracranial pressure (ICP) in traumatic brain injury (TBI) patients. Though there is a clear understanding of the general physiological effects of a hypertonic saline solution over long periods of time, smaller epoch effects of hypertonic saline (HTS) have not been thoroughly analyzed. The aim of this study was to perform a direct evaluation of the high-frequency response of HTS on the cerebrovascular physiological responses in TBI.MethodsWe retrospectively reviewed our prospectively maintained adult TBI database for those with archived high-frequency cerebral physiology and available HTS treatment information. We evaluated different epochs of physiology around HTS bolus dosing, comparing pre- with post-HTS. We assessed for changes in slow fluctuations in ICP, pulse amplitude of ICP (AMP), cerebral perfusion pressure (CPP), mean arterial pressure (MAP), cerebrovascular reactivity (as measured through pressure reactivity index (PRx)), and cerebral compensatory reserve (correlation (R) between AMP (A) and ICP (P)). Comparisons of mean measures and percentage time above clinically relevant thresholds for the physiological parameters were compared pre- and post-HTS using descriptive statistics and Mann-Whitney U testing. We assessed for subgroups of physiological responses using latent profile analysis (LPA).ResultsFifteen patients underwent 69 distinct bolus infusions of hypertonic saline. Apart from the well-documented decrease in ICP, there was also a reduction in AMP. The analysis of cerebrovascular reactivity response to HTS solution had two main effects. For patients with grossly impaired cerebrovascular reactivity pre-HTS (PRx > + 0.30), HTS bolus led to improved reactivity. However, for those with intact cerebrovascular reactivity pre-HTS (PRx < 0), HTS bolus demonstrated a trend towards more impaired reactivity. This indicates that HTS has different impacts, dependent on pre-bolus cerebrovascular status. There was no significant change in metrics of cerebral compensatory reserve. LPA failed to demonstrate any subgroups of physiological responses to HTS administration.ConclusionsThe direct decrease in ICP and AMP confirms that a bolus dose of a HTS solution is an effective therapeutic agent for intracranial hypertension. However, in patients with intact autoregulation, hypertonic saline may impair cerebral hemodynamics. These findings regarding cerebrovascular reactivity remain preliminary and require further investigation.Electronic supplementary materialThe online version of this article (10.1007/s00701-020-04579-0) contains supplementary material, which is available to authorized users.

Retrieval Enhances Higher and Lower Order Thinking in Anatomy and Physiology Students

Retrieval practice is a learning strategy that was developed by cognitive scientists and is based on the act of recalling information after exposure. Over the last two decades, many dozens of studies have found that retrieval‐based strategies can enhance learning and memory more effectively than more commonly‐used strategies such as repetitive reading. Although the advantages of retrieval practice have been demonstrated in both well‐controlled laboratories and real‐world settings such as middle school and university classrooms, the evidence also indicates that most educators and students remain unaware of the benefits of the strategy. It is especially unfortunate when such an effective learning strategy is underutilized in courses that cover anatomy and physiology information because many students find those subjects to be particularly complex, overwhelming, and difficult to learn. The purpose of this presentation is to review key studies that examined the effects of retrieval practice on lower and higher orders of thinking with anatomy, physiology, and medical information. Lower orders of thinking include the abilities to identify, define, and distinguish; whereas higher orders of thinking include the abilities to transfer, critique, and evaluate. The evidence reviewed in this presentation demonstrates that retrieval practice is a relatively effective means by which to increase both higher and lower order thinking with anatomy and physiology information.Support or Funding InformationNone

Teaching Difficult Physiological Concepts to the Medical Students Using Minicases, Educreations and Mentimeter

PurposeIt is a consensus in medical schools that basic science courses is offered in a compressed curriculum, and medical students have difficulty in retaining essential basic science concepts. It is well established that medical, nursing, and healthcare schools use various pedagogical methods to deliver physiology curriculum. Our abstract focuses on medical education, it is always challenging for medical students to retain a plethora of physiology and pharmacology information. These concepts are considered high yield for passing standardized exams. We have shown the effectiveness of new modern tools in medical education that enhances the student learning experience. 1MethodsIn collaboration with the students, we inquired and collected feedback and created a grid of physiological concepts that students find difficult to understand, examples include current multiplication in renal physiology, flow volume loops in respiratory.We then planned three modes of content delivery methods. First, we designed short videos using novel technological tools like educreations clarifying those concepts. The students could view these videos at any time, anywhere, and on any device. We then offered mini‐cases in small groups that promoted higher‐level thinking on Bloom’s Taxonomy, for example, a case on diabetes insipidus that touched upon functions of ADH and integrated clinical reasoning. Finally, using Mentimeter (a novel audience response system), we conducted a short quiz as an interactive readiness experience for our students. The informal 15‐minute quiz was an effective way for students to gauge their performance. In this live session, the basic science instructor(s) were tasked to refresh, review, and validate physiology/pharmacology concepts with the students.Results/OutcomesAccording to our satisfaction surveys, students appreciated digital cognition. The survey response rate was 75% (n=24/32). More than 80% of students found the active learning sessions met their expectations or far exceeded their expectations. Examples of student narratives include, “The learning checkpoints and engaging activities with mini‐cases were good. It exceeded my expectations because I didn’t expect dedicated time to be given to that, but I am glad it did and would like to see similar things like this done in the future.” “The dedication of the instructor to providing learning materials in the forms of videos, readings, and mini‐lectures was a huge strength of the curriculum.”DiscussionWe conclude that our method of content delivery will provide an ideal opportunity for all students to learn the importance of contextual and difficult physiological concepts. The approach can help in identifying knowledge gaps and can serve a useful model for curricular delivery in medical schools, nursing, or any healthcare school that would like to promote critical thinking with a deeper understanding of physiology integrated with clinical science.

Estimating economic minimums of mowing, fertilizing, and irrigating turfgrass

AbstractThe public health crisis and economic recession caused by the COVID‐19 pandemic have forced turfgrass industry professionals to re‐evaluate standard practices. Minimum costs required to fertilize, irrigate, and mow turfgrasses can be roughly estimated using climate data, turfgrass physiology information, and resource costs. Although the actual minimum costs vary situationally and regionally, mowing golf putting greens optimally requires about US$34 per acre per month, whereas other turfgrass areas cost less than US$11 per acre per growing month. Fertilizer applications to turfgrass cost US$22 or less per acre per growing month. Irrigation costs (water and electricity for pumping) vary widely, with the least expensive regions requiring ∼US$300 per acre per year compared with 12 times more than that total in other parts of the United States.

Establishment of the review criteria of blood cell analysis in children and its application in clinical diagnosis

Objective To establish the review criteria for children′s blood cell analysis, ensure the accuracy of blood cell analysis results, and ensure that pathological cells are not missed. Methods A total of 1 420 samples of blood cell analysis were collected from outpatients and inpatients in Shanxi Children′s Hospital from May to June 2018, which were detected by SYSMEXXN-350 and XN-A1 automated blood cell analyzer. Blood smears weredouble-blindly examinedunder microscope. Among them, 463 were used for the establishment of review criteria, 586 were used for the verification and evaluation of review criteria, and 371 were used for the application effect study of review criteria. According tothe 41 rules recommended by ISLH, combining the characteristics of children′s physiology, pathology, disease and abnormal alarming information of hematology analyzer, the review criteria suitable for children′s blood cells were established. Results Through the evaluation and optimization of 41 rules recommended by ISLH, 23 rules for reexamination of children′s blood cell analysis were formulated, with a reexamination rate of 25.09%, and a false positive rate was 14.16%. A total of 371 samples of patients with hematological diseases were selected for the application of the review criteria. The false negative rate was 2.96%, and no pathological cells were missed. Conclusion The children′s blood cell review criteria established in this study has been verified and evaluated, which not only ensures the quality of the report, but also improves the work efficiency, and provides an important basis for the diagnosis and differential diagnosis of childhood leukemia, infectious mononucleosis and other hematological diseases. Key words: Review criteria; Hematology analyzer; Children; Hematologic disease

Atacama Database: a platform of the microbiome of the Atacama Desert.

The Atacama Desert is one of the oldest and driest places on Earth. In the last decade, microbial richness and diversity has been acknowledged as an important biological resource of this region. Owing to the value of the microbial diversity apparent in potential biotechnology applications and conservation purposes, it is necessary to catalogue these microbial communities to promote research activities and help to preserve the wide range of ecological niches of the Atacama region. A prototype Atacama Database has been designed and it provides a description of the rich microbial diversity of the Atacama Desert, and helps to visualise available literature resources. Data has been collected, curated, and organised into several categories to generate a single record for each organism in the database that covers classification, isolation metadata, morphology, physiology, genome and metabolism information. The current version of Atacama Database contains 2302 microorganisms and includes cultured and uncultured organisms retrieved from different environments within the desert between 1984 and 2016. These organisms are distributed in bacterial, archaeal or eukaryotic domains, along with those that are unclassified taxonomically. The initial prototype of the Atacama Database includes a basic search and taxonomic and advanced search tools to allow identification and comparison of microbial populations, and space distribution within this biome. A geolocation search was implemented to visualise the microbial diversity of the ecological niches defined by sectors and extract general information of the sampling sites. This effort will aid understanding of the microbial ecology of the desert, microbial population dynamics, seasonal behaviour, impact of climate change over time, and reveal further biotechnological applications of these microorganisms. The Atacama Database is freely available at: https://www.atacamadb.cl.

How much do preclinical medical students utilize the internet to study physiology?

Medical students increasingly utilize social media platforms to supplement their preclinical learning; however, the prevalence of social media use for physiology learning in medical education remains unclear. The aim of the present study was to determine how first-year medical students from both direct entry medicine and graduate entry medicine interacted with social media as a learning tool by assessing its prevalence, perceived benefits, favored platforms, and reason(s) for its use. Seventy-one percent of surveyed students (out of 139 participants) stated that they interacted with social media in general more than 12 times per week. However, 98% had previously used internet platforms to source physiology information, with 89.2% doing so at least once per week during term. YouTube was the primary source of learning for 76% of students. Significantly, 94% of students indicated that they would first search for answers online if they did not understand something in physiology rather than contacting their instructor in person or by e-mail. However, only 31% of students "fact-checked" physiology information obtained from online sources, by using textbooks, papers, and/or instructors. Our study has revealed that most preclinical medical students utilize social media extensively to study physiology. However, the absence of academic and ethical oversight, paired with students' lack of critical appraisal of possibly inaccurate information, does raise concerns about the overall utility of social media as part of physiology education.

A kinetic metabolic study of lipid production in Chlorella protothecoides under heterotrophic condition

BackgroundMicroalgae have been proposed as potential platform to produce lipid-derived products, such as biofuels. Knowledge on the intracellular carbon flow distribution may identify key metabolic processes during lipid synthesis thus refining culture/genetic strategies to maximize cell lipid productivity. A kinetic metabolic model simulating cell metabolic behavior and lipid production was first applied in the microalgae platform Chlorella protothecoides under heterotrophic condition. It combines both physiology and flux information in a kinetic approach. Cell nutrition, growth, lipid production and almost 30 metabolic intermediates covering central carbon metabolism were included and simulated.ResultsModel simulations were shown to adequately agree with experimental data, which is suggesting that the proposed model copes with Chlorella protothecoides cells’ biology. The dynamic metabolic flux analysis using the model showed a reversible starch flux from accumulation to decomposing when glucose reached depletion, while net lipid flux shows a quasi-constant rate. The sensitive flux parameters on starch and lipid metabolism suggested that starch synthesis is the major competing pathway that affects lipid accumulation in C. protothecoides. Flux analysis also demonstrated that high lipid yield under heterotrophic condition is accompanied with high lipid flux and low TCA activity. Meanwhile, the dynamic flux distribution also suggests a relatively constant ratio of glucose distributed to biomass, lipid, starch, nucleotides as well as pentose phosphate pathway.ConclusionThe model described not only experimental data, but also unraveled intracellular carbon flow distribution and identify key metabolic processes during lipid synthesis. Most of the metabolic kinetics also showed statistical significance for metabolic mechanism. Therefore, this study unravels the mechanisms of the glucose impact on the dynamic carbon flux distribution, thus improving our understanding of the links between carbon fluxes and lipid metabolism in C. protothecoides.