Pheno- and genotyping of Pasteurella multocida isolated from goat in Iran

In this study, phenotype, capsular type and some virulence factors (pfha1, tbpA, and toxA) of caprine Pasteurella multocida were described in 10 isolates from goat. Two biochemical biovars were recognized among the isolates based on dulcitol and sorbitol fermentation. The isolates belonged to biovars P. multocida sub. multocida (80%) and P. multocida sub. septica (20%). Capsular typing of isolates by PCR demonstrated two capsular types A (90%) and D. Among 3 virulence genes detected by PCR, we found a remarkable high prevalence of tbpA (80%) and toxA (70%) genes among caprine isolates. The high prevalence of these genes owning association of disease status among healthy animals showed high potential of the strains in induction of disease. The high prevalence of toxA and tbpA among goat is very similar to the ones in sheep isolates. Comparison of virulence genes profile showed possibility of P. multocida transmission between sheep and goat

Machine Learning Based Decision-Making: A Sensemaking Perspective

The integration of machine learning (ML), functioning as the core of various artificial intelligence (AI)-enabled systems in organizations, comes with the assertion that ML models offer automated decisions or assist domain experts in refining their decision-making. The current research presents substantial evidence of ML’s positive impact on business and organizational performance. Nonetheless, there is a limited understanding of how decision-makers participate in the process of generating ML-driven insights and enhancing their comprehension of business environments through ML outcomes. To enhance this engagement and understanding, this study examines the interactive process between decision-makers and ML experts as they strive to comprehend an environment and gather business insights for decision-making. It builds upon Weick’s sensemaking model by integrating ML’s pivotal role. By conducting interviews with 31 ML experts and ML end-users, we explore the dimensions of sensemaking in the context of ML utilization for decision-making. Consequently, this study proposes a process model which advances the organizational ML research by operationalizing Weick’s work into a structured ML-driven sensemaking model. This model charts a pragmatic pathway, outlining the interaction sequence between decision-makers and ML tools as they navigate through recognizing and utilizing ML, exploring opportunities, assessing ML model outcomes, and translating ML models into action, thereby advancing both the theoretical framework and its practical deployment in organizational contexts

Effect of temperature on life table parameters of Diaphania indica (Lep.: Pyralidae) under laboratory conditions

The cucumber moth, Diaphania indica (Saunders), is a tropical and sub-tropical pest on cucurbits and a key pest of greenhouse crops in Jiroft region of Iran. The effect of temperature on life table parameters of this pest was investigated in a growth chamber at four constant temperatures i.e. 20, 25, 30 and 35 ºC on Cucumis sativus L. The net reproductive rates (R0) were found to be 68.19, 120.977, 64.05 and 21.23, respectively. The intrinsic rates of increase (rm) were 0.0619, 0.1746, 0.1934 and 0.1491, and mean generation times (T) were 69.063, 27.45, 21.49 and 20.44, respectively. According to the results, for the intrinsic rate of increase (rm), finite rate of increase (λ) and intrinsic birth rate (b), the optimum temperature was 30 ºC and the least suitable temperature was 20 ºC

Machine Learning Based Decision-Making: A Sensemaking Perspective

The integration of machine learning (ML), functioning as the core of various artificial intelligence (AI)-enabled systems in organizations, comes with the assertion that ML models offer automated decisions or assist domain experts in refining their decision-making. The current research presents substantial evidence of ML’s positive impact on business and organizational performance. Nonetheless, there is a limited understanding of how decision-makers participate in the process of generating ML-driven insights and enhancing their comprehension of business environments through ML outcomes. To enhance this engagement and understanding, this study examines the interactive process between decision-makers and ML experts as they strive to comprehend an environment and gather business insights for decision-making. It builds upon Weick’s sensemaking model by integrating ML’s pivotal role. By conducting interviews with 31 ML experts and ML end-users, we explore the dimensions of sensemaking in the context of ML utilization for decision-making. Consequently, this study proposes a process model which advances the organizational ML research by operationalizing Weick’s work into a structured ML-driven sensemaking model. This model charts a pragmatic pathway, outlining the interaction sequence between decision-makers and ML tools as they navigate through recognizing and utilizing ML, exploring opportunities, assessing ML model outcomes, and translating ML models into action, thereby advancing both the theoretical framework and its practical deployment in organizational contexts

Differential proinflammatory responses to Aspergillus fumigatus by airway epithelial cells in vitro are protease dependent

Aspergillus fumigatus is an important human respiratory mould pathogen. In addition to a barrier function, airway epithelium elicits a robust defence against inhaled A. fumigatus by initiating an immune response. The manner by which A. fumigatus initiates this response and the reasons for the immunological heterogeneity with different isolates are unclear. Both direct fungal cell wall–epithelial cell interaction and secretion of soluble proteases have been proposed as possible mechanisms. Our aim was to determine the contribution of fungal proteases to the induction of epithelial IL-6 and IL-8 in response to different A. fumigatus isolates. Airway epithelial cells were exposed to conidia from a low or high protease-producing strain of A. fumigatus, and IL-6 and IL-8 gene expression and protein production were quantified. The role of proteases in cytokine production was further determined using specific protease inhibitors. The proinflammatory cytokine response correlated with conidia germination and hyphal extension. IL-8 induction was significantly reduced in the presence of matrix metalloprotease or cysteine protease inhibitors. With a high protease-producing strain of A. fumigatus, IL-6 release was metalloprotease dependent. Dectin-1 antagonism also inhibited the production of both cytokines. In conclusion, A. fumigatus-secreted proteases mediate a proinflammatory response by airway epithelial cells in a strain-dependent manner

Genital herpes evaluation by quantitative TaqMan PCR: correlating single detection and quantity of HSV-2 DNA in cervicovaginal lavage fluids with cross-sectional and longitudinal clinical data

Abstract Objective To evaluate the utility of a single quantitative PCR (qPCR) measurement of HSV (HSV-1&2) DNA in cervicovaginal lavage (CVL) specimens collected from women with predominantly chronic HSV-2 infection in assessing genital HSV shedding and the clinical course of genital herpes (GH) within a cohort with semiannual schedule of follow up and collection of specimens. Methods Two previously described methods used for detection of HSV DNA in mucocutaneous swab samples were adapted for quantification of HSV DNA in CVLs. Single CVL specimens from 509 women were tested. Presence and quantity of CVL HSV DNA were explored in relation to observed cross-sectional and longitudinal clinical data. Results The PCR assay was sensitive and reproducible with a limit of quantification of ~50 copies per milliliter of CVL. Overall, 7% of the samples were positive for HSV-2 DNA with median log10 HSV-2 DNA copy number of 3.9 (IQR: 2.6-5.7). No HSV-1 was detected. Presence and quantity of HSV-2 DNA in CVL directly correlated with the clinical signs and symptoms of presence of active symptomatic disease with frequent recurrences. Conclusion Single qPCR measurement of HSV DNA in CVL fluids of women with chronic HSV-2 infection provided useful information for assessing GH in the setting of infrequent sampling of specimens. Observed positive correlation of the presence and quantity of HSV-2 DNA with the presence of active and more severe course of HSV-2 infection may have clinical significance in the evaluation and management of HSV-2 infected patients

Electrochemically synthesized polymers in molecular imprinting for chemical sensing

This critical review describes a class of polymers prepared by electrochemical polymerization that employs the concept of molecular imprinting for chemical sensing. The principal focus is on both conducting and nonconducting polymers prepared by electropolymerization of electroactive functional monomers, such as pristine and derivatized pyrrole, aminophenylboronic acid, thiophene, porphyrin, aniline, phenylenediamine, phenol, and thiophenol. A critical evaluation of the literature on electrosynthesized molecularly imprinted polymers (MIPs) applied as recognition elements of chemical sensors is presented. The aim of this review is to highlight recent achievements in analytical applications of these MIPs, including present strategies of determination of different analytes as well as identification and solutions for problems encountered