Towards phenotyping adaptive traits in camels: A study of the influence of hypotonic saline solutions on blood cell area
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ABSTRACT:
SUBMITTER: Alhaddad H
PROVIDER: S-EPMC10927079 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe traditional recommendations which suggest that hypotonic intravenous (i.v.) maintenance fluids are the solutions of choice in paediatric patients have not been rigorously tested in clinical trials, and may not be appropriate for all children.AimsTo systematically review the evidence from studies evaluating the safety of administering hypotonic versus isotonic i.v. maintenance fluids in hospitalised children.MethodsData sourcesMedline (1966-2006), Embase (1980-2006), the Cochrane Library, abstract proceedings, personal files, and reference lists. Studies that compared hypotonic to isotonic maintenance solutions in children were selected. Case reports and studies in neonates or patients with a pre-existing history of hyponatraemia were excluded.ResultsSix studies met the selection criteria. A meta-analysis combining these studies showed that hypotonic solutions significantly increased the risk of developing acute hyponatraemia (OR 17.22; 95% CI 8.67 to 34.2), and resulted in greater patient morbidity.ConclusionsThe current practice of prescribing i.v. maintenance fluids in children is based on limited clinical experimental evidence from poorly and differently designed studies, where bias could possibly raise doubt about the results. They do not provide evidence for optimal fluid and electrolyte homoeostasis in hospitalised children. This systematic review indicates potential harm with hypotonic solutions in children, which can be anticipated and avoided with isotonic solutions. No single fluid rate or composition is ideal for all children. However, isotonic or near-isotonic solutions may be more physiological, and therefore a safer choice in the acute phase of illness and perioperative period.
| S-EPMC2066024 | biostudies-literature
Project description:The popularity of dogs as human companions explains why these pets regularly come into focus in forensic cases such as bite attacks or accidents. Canine evidence, e.g., dog hairs, can also act as a link between the victim and suspect in a crime case due to the close contact between dogs and their owners. In line with human DNA identification, dog individualization from crime scene evidence is mainly based on the analysis of short tandem repeat (STR) markers. However, when the DNA profile does not match a reference, additional information regarding the appearance of the dog may provide substantial intelligence value. Key features of the dog's appearance, such as the body size and coat colour are well-recognizable and easy to describe even to non-dog experts, including most investigating officers and eyewitnesses. Therefore, it is reasonable to complement eyewitnesses' testimonies with externally visible traits predicted from associated canine DNA samples. Here, the feasibility and suitability of canine DNA phenotyping is explored from scratch in the form of a proof of concept study. To predict the overall appearance of an unknown dog from its DNA as accurately as possible, the following six traits were chosen: (1) coat colour, (2) coat pattern, (3) coat structure, (4) body size, (5) ear shape, and (6) tail length. A total of 21 genetic markers known for high predicting values for these traits were selected from previously published datasets, comprising 15 SNPs and six INDELS. Three of them belonged to SINE insertions. The experiments were designed in three phases. In the first two stages, the performance of the markers was tested on DNA samples from dogs with well-documented physical characteristics from different breeds. The final blind test, including dogs with initially withheld appearance information, showed that the majority of the selected markers allowed to develop composite sketches, providing a realistic impression of the tested dogs. We regard this study as the first attempt to evaluate the possibilities and limitations of forensic canine DNA phenotyping.
| S-EPMC8230911 | biostudies-literature
Project description:Tibetans are the ideal population to study genetic adaptation in extreme environments. Here, we performed systematic phenotyping of 11,880 highlanders, covering 133 quantitative traits of 13 organ systems. We provided a comprehensive phenotypic atlas by comparing altitude adaptation and altitude acclimatization. We found the differences between adaptation and acclimatization are quantitative rather than qualitative, with a whole-system "blunted effect" seen in the adapted Tibetans. We characterized twelve different functional changes between adaptation and acclimatization. More importantly, we established a landscape of adaptive phenotypes of indigenous Tibetans, including 45 newly identified Tibetan adaptation-nominated traits, involving specific changes of Tibetans in internal organ state, metabolism, eye morphology, and skin pigmentation. In addition, we observed a sex-biased pattern between altitude acclimatization and adaptation. The generated atlas of phenotypic landscape provides new insights into understanding of human adaptation to high-altitude environments, and it serves as a valuable blueprint for future medical and physiological studies.
| S-EPMC10481350 | biostudies-literature
Project description:Breeding for resilience to climate change requires considering adaptive traits such as plant architecture, stomatal conductance and growth, beyond the current selection for yield. Robotized indoor phenotyping allows measuring such traits at high throughput for speed breeding, but is often considered as non-relevant for field conditions. Here, we show that maize adaptive traits can be inferred in different fields, based on genotypic values obtained indoor and on environmental conditions in each considered field. The modelling of environmental effects allows translation from indoor to fields, but also from one field to another field. Furthermore, genotypic values of considered traits match between indoor and field conditions. Genomic prediction results in adequate ranking of genotypes for the tested traits, although with lesser precision for elite varieties presenting reduced phenotypic variability. Hence, it distinguishes genotypes with high or low values for adaptive traits, conferring either spender or conservative strategies for water use under future climates.
| S-EPMC10587076 | biostudies-literature
Project description:Induced morphology changes of cells and organelles are by far the easiest way to determine precise protein sub-locations and organelle quantities in light microscopy. By using hypotonic solutions to swell mammalian cell organelles we demonstrate that precise membrane, lumen or matrix protein locations within the endoplasmic reticulum, Golgi and mitochondria can reliably be established. We also show the benefit of this approach for organelle quantifications, especially for clumped or intertwined organelles like peroxisomes and mitochondria. Since cell and organelle swelling is reversible, it can be applied to live cells for successive high-resolution analyses. Our approach outperforms many existing imaging modalities with respect to resolution, ease-of-use and cost-effectiveness without excluding any co-utilization with existing optical (super)resolution techniques.
| S-EPMC6733880 | biostudies-literature
Project description:The cell volume changes induced by hypotonic electrolyte and sucrose solutions were studied in Chinese-hamster-ovary epithelial cells. The effects in the solutions with osmolarities between 32 and 315 mosM/L and distilled water were analyzed using bright-field and fluorescence confocal microscopy. The changes of the cell volume, accompanied by the detachment of cells, the formation of blebs, and the occurrence of almost spherical vesicle-like cells ("cell-vesicles"), showed significant differences in the long-time responses of the cells in the electrolyte solutions compared with the sucrose-containing solutions. A theoretical model based on different permeabilities of ions and sucrose molecules and on the action of Na+/K+-ATPase pumps is applied. It is consistent with the observed temporal behavior of the cells' volume and the occurrence of tension-induced membrane ruptures and explains lower long-time responses of the cells in the sucrose solutions.
| S-EPMC7750460 | biostudies-literature
Project description:Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L.) entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1) alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI), canopy height, normalized difference vegetative index (NDVI), and leaf area index (LAI) differed among entries and showed an interaction with the water regime (p < 0.05). Broad-sense heritability (H2) estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033). Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions.
| S-EPMC5961097 | biostudies-literature
Project description:Current serological diagnosis of Trypanosoma evansi infection in camels is based on the native variable antigen type RoTat 1.2. The goal of this study was to develop a novel serological diagnostic test based on a nonvariable protein and freed from the use of rats or mice for its production. An enzyme-linked immunosorbent assay using a recombinant extracellular domain of invariant surface glycoprotein 75 (ELISA/rISG75) was developed and tested on a collection of 184 camel sera. The results were compared to those obtained from three established antibody detection tests based on variable surface glycoprotein RoTat 1.2: an ELISA for T. evansi (ELISA/T. evansi), a card agglutination test for trypanosomiasis (CATT/T. evansi), and an immune trypanolysis (TL) assay. The ELISA/rISG75 and the ELISA/T. evansi showed a sensitivity of 94.6% (95% confidence interval [CI], 87.8 to 98.2%, at 19% positivity cutoff value) and 98.9% (95% CI, 94.1 to 99.8, at 12% positivity cutoff value), respectively. The ELISA/rISG75 had 100% specificity (CI, 95.9 to 100%), while the ELISA/T. evansi showed 98.9% specificity (CI, 95.9 to 100%). The ELISA/rISG75 demonstrated an almost perfect agreement with the TL assay, the CATT/T. evansi, and the ELISA/T. evansi, with kappa scores of at least 0.94. The ELISA/rISG75, having a performance comparable to that of the gold standard (the TL assay) and being independent of antigenic variation, may become a new reference test for surra in camels. It opens avenues for the diagnosis of T. evansi infections in other hosts as well as for the development of a pan-Trypanozoon test for detection of Trypanosoma brucei brucei, T. b. gambiense, T. b. rhodesiense, T. evansi, and T. equiperdum.
| S-EPMC2708406 | biostudies-literature
Project description:Global changes are thought to affect most Arctic species, yet some populations are more at risk. Today, the Barents Sea ecoregion is suffering the strongest sea ice retreat ever measured; and these changes are suspected to modify food access and thus diet of several species. Biochemical diet tracers enable investigation of diet in species such as polar bears (Ursus maritimus). We examined individual diet variation of female polar bears in Svalbard, Norway, and related it to year, season (spring and autumn), sampling area and breeding status (solitary, with cubs of the year or yearlings). Sampling areas were split according to their ice cover: North-West (less sea ice cover), South-East (larger amplitude in sea ice extent) and North-East/South-West (NESW) as bears from that zone are more mobile among all regions of Svalbard. We measured fatty acid (FA) composition in adipose tissue and carbon (δ13C) and nitrogen (δ15N) stable isotopes in plasma and red blood cells. Females feeding in the North-West area had lower δ15N values than those from the NESW. In South-East females, δ13C values were lower in autumn compared to spring and females seemed less selective in their diet as depicted by large variances in stable isotope values. Considering the differences in FA composition and stable isotope values, we suggest that females from the North-West and South-East could ingest a higher proportion of avian prey. With regard to breeding status, solitary females had higher δ15N values and smaller variance in their stable isotopic values than females with cubs, suggesting that solitary females were more selective and prey on higher trophic level species (i.e. seals). Overall, our results indicate that prey availability for Svalbard polar bears varies according to geographical area and prey selectivity differs according to breeding status. Our findings suggest that complex changes in sea ice and prey availability will interact to affect Svalbard polar bear feeding patterns and associated nutrition.
| S-EPMC4873193 | biostudies-literature
Project description:BackgroundManually curating standardized phenotypic concepts such as Human Phenotype Ontology (HPO) terms from narrative text in electronic health records (EHRs) is time consuming and error prone. Natural language processing (NLP) techniques can facilitate automated phenotype extraction and thus improve the efficiency of curating clinical phenotypes from clinical texts. While individual NLP systems can perform well for a single cohort, an ensemble-based method might shed light on increasing the portability of NLP pipelines across different cohorts.MethodsWe compared four NLP systems, MetaMapLite, MedLEE, ClinPhen and cTAKES, and four ensemble techniques, including intersection, union, majority-voting and machine learning, for extracting generic phenotypic concepts. We addressed two important research questions regarding automated phenotype recognition. First, we evaluated the performance of different approaches in identifying generic phenotypic concepts. Second, we compared the performance of different methods to identify patient-specific phenotypic concepts. To better quantify the effects caused by concept granularity differences on performance, we developed a novel evaluation metric that considered concept hierarchies and frequencies. Each of the approaches was evaluated on a gold standard set of clinical documents annotated by clinical experts. One dataset containing 1,609 concepts derived from 50 clinical notes from two different institutions was used in both evaluations, and an additional dataset of 608 concepts derived from 50 case report abstracts obtained from PubMed was used for evaluation of identifying generic phenotypic concepts only.ResultsFor generic phenotypic concept recognition, the top three performers in the NYP/CUIMC dataset are union ensemble (F1, 0.634), training-based ensemble (F1, 0.632), and majority vote-based ensemble (F1, 0.622). In the Mayo dataset, the top three are majority vote-based ensemble (F1, 0.642), cTAKES (F1, 0.615), and MedLEE (F1, 0.559). In the PubMed dataset, the top three are majority vote-based ensemble (F1, 0.719), training-based (F1, 0.696) and MetaMapLite (F1, 0.694). For identifying patient specific phenotypes, the top three performers in the NYP/CUIMC dataset are majority vote-based ensemble (F1, 0.610), MedLEE (F1, 0.609), and training-based ensemble (F1, 0.585). In the Mayo dataset, the top three are majority vote-based ensemble (F1, 0.604), cTAKES (F1, 0.531) and MedLEE (F1, 0.527).ConclusionsOur study demonstrates that ensembles of natural language processing can improve both generic phenotypic concept recognition and patient specific phenotypic concept identification over individual systems. Among the individual NLP systems, each individual system performed best when they were applied in the dataset that they were primary designed for. However, combining multiple NLP systems to create an ensemble can generally improve the performance. Specifically, the ensemble can increase the results reproducibility across different cohorts and tasks, and thus provide a more portable phenotyping solution compared to individual NLP systems.
| S-EPMC6899194 | biostudies-literature