ELIZA

return kwic search for specific out of >500 occurrences
279736 occurrences (No.90 in the rank) during 5 years in the PubMed. [cache]

17) Deviations in physiological signals following exposure to a pathogen are due to the underlying host's immunological response and are not specific to the pathogen.

--- ABSTRACT ---

PMID:34552498 DOI:10.3389/fphys.2021.691074

2021 Frontiers in physiology

* Detecting Pathogen Exposure During the Non-symptomatic Incubation Period Using Physiological Data: Proof of Concept in Non-human Primates.

- Background and Objectives: Early warning of bacterial and viral infection, prior to the development of overt clinical symptoms, allows not only for improved patient care and outcomes but also enables faster implementation of public health measures (patient isolation and contact tracing). Our primary objectives in this effort are 3-fold. First, we seek to determine the upper limits of early warning detection through physiological measurements. Second, we investigate whether the detected physiological response is specific to the pathogen. Third, we explore the feasibility of extending early warning detection with wearable devices. Research Methods: For the first objective, we developed a supervised random forest algorithm to detect pathogen exposure in the asymptomatic period prior to overt symptoms (fever). We used high-resolution physiological telemetry data (aortic blood pressure, intrathoracic pressure, electrocardiograms, and core temperature) from non-human primate animal models exposed to two viral pathogens: Ebola and Marburg (N = 20). Second, to determine reusability across different pathogens, we evaluated our algorithm against three independent physiological datasets from non-human primate models (N = 13) exposed to three different pathogens: Lassa and Nipah viruses and Y. pestis. For the third objective, we evaluated performance degradation when the algorithm was restricted to features derived from electrocardiogram (ECG) waveforms to emulate data from a non-invasive wearable device. Results: First, our cross-validated random forest classifier provides a mean early warning of 51 ± 12 h, with an area under the receiver-operating characteristic curve (AUC) of 0.93 ± 0.01. Second, our algorithm achieved comparable performance when applied to datasets from different pathogen exposures - a mean early warning of 51 ± 14 h and AUC of 0.95 ± 0.01. Last, with a degraded feature set derived solely from ECG, we observed minimal degradation - a mean early warning of 46 ± 14 h and AUC of 0.91 ± 0.001. Conclusion: Under controlled experimental conditions, physiological measurements can provide over 2 days of early warning with high AUC. Deviations in physiological signals following exposure to a pathogen are due to the underlying host's immunological response and are not specific to the pathogen. Pre-symptomatic detection is strong even when features are limited to ECG-derivatives, suggesting that this approach may translate to non-invasive wearable devices.

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(1)18 to	(21)3 for	(41)2 food	(61)2 or
(2)11 and	(22)3 genes	(42)2 foods	(62)2 parameters
(3)8 focus	(23)3 genetic	(43)2 gene	(63)2 patient
(4)7 vulnerability	(24)3 marker	(44)2 granule	(64)2 physical
(5)6 effects	(25)3 mechanisms	(45)2 group	(65)2 proteases
(6)6 factors	(26)3 proteins	(46)2 groups	(66)2 research
(7)5 recommendations	(27)2 GC	(47)2 immune	(67)2 responses
(8)4 IgA	(28)2 N3FA	(48)2 in	(68)2 risk
(9)4 aspects	(29)2 PHC	(49)2 information	(69)2 sensitization
(10)4 cancer	(30)2 antibodies	(50)2 interventional	(70)2 siRNA
(11)4 components	(31)2 antigens	(51)2 interventions	(71)2 social
(12)4 inhibitor	(32)2 area	(52)2 issues	(72)2 spatial
(13)4 population	(33)2 attention	(53)2 knockout	(73)2 study
(14)3 T	(34)2 binding	(54)2 mental	(74)2 target
(15)3 brain	(35)2 biological	(55)2 microbial	(75)2 terms
(16)3 cell	(36)2 biomarkers	(56)2 molecular	(76)2 topics
(17)3 changes	(37)2 cellular	(57)2 mortality	(77)2 treatment
(18)3 counseling	(38)2 clinical	(58)2 mutations	(78)2 type
(19)3 deletion	(39)2 emphasis	(59)2 needs
(20)3 differences	(40)2 factors,	(60)2 online

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--- WordNet output for specific --- =>特有の, 特効薬, 明確な, 特定の, 種の, はっきりした Overview of noun specific The noun specific has 2 senses (no senses from tagged texts) 1. particular, specific -- (a fact about some part (as opposed to general); "he always reasons from the particular to the general") 2. specific -- (a medicine that has a mitigating effect on a specific disease; "quinine is a specific for malaria") Overview of adj specific The adj specific has 4 senses (first 2 from tagged texts) 1. (39) specific -- ((sometimes followed by `to') applying to or characterized by or distinguishing something particular or special or unique; "rules with specific application"; "demands specific to the job"; "a specific and detailed account of the accident") 2. (5) specific -- (stated explicitly or in detail; "needed a specific amount") 3. specific -- (relating to or distinguishing or constituting a taxonomic species; "specific characters") 4. specific -- (being or affecting a disease produced by a particular microorganism or condition; used also of stains or dyes used in making microscope slides; "quinine is highly specific for malaria"; "a specific remedy"; "a specific stain is one having a specific affinity for particular structural elements") --- WordNet end ---