Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis

Diagnosis of asthma is often challenging in primary-care physicians due to lack of tools measuring airway obstruction and variability. Symptom-based diagnosis of asthma utilizing objective diagnostic parameters and appropriate software would be useful in clinical practice. A total of 302 adult patients with respiratory symptoms responded to a questionnaire regarding asthma symptoms and provoking factors. Questions were asked and recorded by physicians into a computer program. A definite diagnosis of asthma was made based on a positive response to methacholine bronchial provocation or bronchodilator response (BDR) testing. Multivariate logistic regression analysis was used to evaluate the significance of questionnaire responses in terms of discriminating asthmatics. Asthmatic patients showed higher total symptom scores than non-asthmatics (mean 5.93 vs. 4.93; p<0.01). Multivariate logistic regression analysis identified that response to questions concerning the following significantly discriminated asthmatics; wheezing with dyspnea, which is aggravated at night, and by exercise, cold air, and upper respiratory infection. Moreover, the presence of these symptoms was found to agree significantly with definite diagnosis of asthma (by kappa statistics). Receiver-operating characteristic curve analysis revealed that the diagnostic accuracy of symptom-based diagnosis was high with an area under the curve of 0.647±0.033. Using a computer-assisted symptom-based diagnosis program, it is possible to increase the accuracy of diagnosing asthma in general practice, when the facilities required to evaluate airway hyperresponsiveness or BDR are unavailable

Easy diagnosis of asthma: computer-assisted, symptom-based diagnosis

Diagnosis of asthma is often challenging in primary-care physicians due to lack of tools measuring airway obstruction and variability. Symptom-based diagnosis of asthma utilizing objective diagnostic parameters and appropriate software would be useful in clinical practice. A total of 302 adult patients with respiratory symptoms responded to a questionnaire regarding asthma symptoms and provoking factors. Questions were asked and recorded by physicians into a computer program. A definite diagnosis of asthma was made based on a positive response to methacholine bronchial provocation or bronchodilator response (BDR) testing. Multivariate logistic regression analysis was used to evaluate the significance of questionnaire responses in terms of discriminating asthmatics. Asthmatic patients showed higher total symptom scores than non-asthmatics (mean 5.93 vs. 4.93; p<0.01). Multivariate logistic regression analysis identified that response to questions concerning the following significantly discriminated asthmatics; wheezing with dyspnea, which is aggravated at night, and by exercise, cold air, and upper respiratory infection. Moreover, the presence of these symptoms was found to agree significantly with definite diagnosis of asthma (by kappa statistics). Receiver-operating characteristic curve analysis revealed that the diagnostic accuracy of symptom-based diagnosis was high with an area under the curve of 0.647 +/- 0.033. Using a computer-assisted symptom-based diagnosis program, it is possible to increase the accuracy of diagnosing asthma in general practice, when the facilities required to evaluate airway hyperresponsiveness or BDR are unavailable

Arachidicoccus soli Lee & Kim & Sang & Song & Kwon & Weon 2021, SP. NOV.

DESCRIPTION OF ARACHIDICOCCUS SOLISP. NOV. Arachidicoccus soli (so′ li. L. gen. n. soli of soil). Cells are aerobic, Gram-stain-negative, non-motile and rod-shaped (0.5–0.6 µm wide and 1.3–10 µm long). Colonies grown at 28 °C on R2A agar for 2 days are light yellow, round and convex. Growth occurs at 10–33 °C, pH 6.0–7.5 and with 0–4 % NaCl (w/v). Tests for catalase and oxidase are negative. Tyrosine is hydrolysed, but casein, CM-cellulose, hypozanthine, DNA and Tween 80 are not. Positive for aesculin hydrolysis and β -galactosidase, but negative for nitrate reduction, indole production, glucose fermentation, arginine dihydrolase, urease and gelatin hydrolysis. Assimilates D-glucose, L-arabinose, D-mannose, N -acetylglucosamine, maltose, L-rhamnose and L-proline, but does not assimilate D-mannitol, potassium gluconate, capric acid, adipic acid, malic acid, trisodium citrate, phenylacetic acid, D-ribose, inositol, sucrose, itaconic acid, suberic acid, sodium malonate, sodium acetate, lactic acid, L-alanine, potassium 5-ketogluconate, glycogen, 3-hydroxybenzoic acid, L-serine, salicin, melibiose, L-fucose,D-sorbitol, propionic acid, valeric acid, L-histidine, potassium 2-ketogluconate, 3-hydroxybutyric acid and 4-hydroxybenzoic acid. Positive activities for alkaline phosphatase, esterase (C4), leucine arylamidase, valine arylamidase, cystine arylamidase, acid phosphatase, naphthol-AS-BI-phosphohydrolase, α-galactosidase, β -glucuronidase, α-glucosidase, N - acetylβ -glucosaminidase and α-fucosidase, but negative activities for esterase lipase (C8), lipase (C14), trypsin, α-chymotrypsin, β -glucosidase and α-mannosidase. The major respiratory quinone is MK-7. Polar lipids consist of phosphatidylethanolamine, four unknown aminolipids and three unknown lipids. The major fatty acids are iso-C 15:0, iso-C 17:0 3-OH and iso-C 15:1 G. The major polyamines were homospermidine and putrescine. The genomic DNA G+C content of the type strain is 36.4mol%. Data was taken from a, Madhaiyan et al. [1], b, Siddiqi et al. [2], and c, Siddiqi et al. [3]. *Summed features are groups of two or three fatty acids that cannot be separated by the MIDI system. Summed feature 2 comprised C12:0 aldehyde and/or unknown equivalent chain length (ECL) 10.928 and/or C14:0 3-OH and/or iso-C16:1 I. Summed feature 3 comprised C16:1 ω 6 c and/or C16:1 ω 7 c. The type strain, KIS59-12 T (= KACC 17340 T = NBRC 113161 T), was isolated from a soil sample collected on Hodo island, Boryeong, Chungcheongnam-do Province, Republic of Korea. The GenBank / EMBL / DDBJ accession numbers for the 16S rRNA gene sequence and the genome sequence of strain KIS59-12 T are MH 933978 and CP032489, respectively.Published as part of Lee, Shin Ae, Kim, Tae-Wan, Sang, Mee-Kyung, Song, Jaekyeong, Kwon, Soon-Wo & Weon, Hang-Yeon, 2021, Arachidicoccus soli sp. nov., a bacterium isolated from soil, pp. 1-6 in International Journal of Systematic and Evolutionary Microbiology (004566) (004566) 71 (1) on pages 4-5, DOI: 10.1099/ijsem.0.004566, http://zenodo.org/record/604870

Spin fluctuations in Sr 1.8 La 0.2 RuO 4

We use inelastic neutron scattering to study spin fluctuations in Sr1.8La0.2RuO4, where Lanthanum doping triggers a Lifshitz transition by pushing the van Hove singularity in the γ band to the Fermi energy. Strong spinfluctuations emerge at an incommensurate wave vector Qic = (0.3, 0.3), corresponding to the nesting vector between α and β Fermi sheets. The incommensurate antiferromagnetic fluctuations shift toward (0.25,0.25) with increasing energy up to ∼110 meV. By contrast, scatterings near the ferromagnetic wave vectors Q = (1, 0) and (1,1) remain featureless at all energies. This contradicts the weak-coupling perspective that suggests a sharpenhancement of ferromagnetic susceptibility due to the divergence of density of states in the associated γ band. Our findings imply that ferromagnetic fluctuations in Sr2RuO4 and related materials do not fit into the weakcoupling paradigm, but instead are quasilocal fluctuations induced by Hund’s coupling. This imposes significant constraints for the pairing mechanism involving spin fluctuations