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Background Community-acquired pneumonia (CAP) is one of the most common infectious diseases and is a significant cause of mortality and morbidity globally. A microbial cause was not determined in a sizable percentage of patients with CAP; there are increasing data to suggest regional differences in bacterial aetiology. We devised a multiplex real-time PCR assay for detecting four microorganisms (Streptococcus pneumoniae, Haemophilus influenzae, Klebsiella pneumoniae and Burkholderia pseudomallei) of relevance to CAP infections in Asia. Methods Analytical validation was accomplished using bacterial isolates (n=10–33 of each target organism for analytical sensitivity and n=117 for analytical sensitivity) and clinical validation using 58 culture-positive respiratory tract specimens. Results The qPCR assay exhibited 100% analytical sensitivity and analytical specificity, and 100% clinical sensitivity and 94–100% clinical specificity. The limit of detection and efficiency for the multiplex PCR assay were 3–33 CFU/mL and 93–110%, respectively. The results showed that the PCR-based method had higher sensitivity than traditional culture-based methods. The assay also demonstrated an ability to semiquantify bacterial loads. Conclusion We have devised a reliable laboratory-developed multiplex qPCR assay, with a turnaround time of within one working day, for detection of four clinically important CAP-associated microorganisms in Asia. The availability of a test with improved diagnostic capabilities potentially leads to an informed choice of antibiotic usage and appropriate management of the patient to achieve a better treatment outcome and financial savings. [ABSTRACT FROM AUTHOR]

Abstract Background Microglia, the resident immune cells of the central nervous system (CNS), have two distinct phenotypes in the developing brain: amoeboid form, known to be amoeboid microglial cells (AMC) and ramified form, known to be ramified microglial cells (RMC). The AMC are characterized by being proliferative, phagocytic and migratory whereas the RMC are quiescent and exhibit a slow turnover rate. The AMC transform into RMC with advancing age, and this transformation is indicative of the gradual shift in the microglial functions. Both AMC and RMC respond to CNS inflammation, and they become hypertrophic when activated by trauma, infection or neurodegenerative stimuli. The molecular mechanisms and functional significance of morphological transformation of microglia during normal development and in disease conditions is not clear. It is hypothesized that AMC and RMC are functionally regulated by a specific set of genes encoding various signaling molecules and transcription factors. Results To address this, we carried out cDNA microarray analysis using lectin-labeled AMC and RMC isolated from frozen tissue sections of the corpus callosum of 5-day and 4-week old rat brain respectively, by laser capture microdissection. The global gene expression profiles of both microglial phenotypes were compared and the differentially expressed genes in AMC and RMC were clustered based on their functional annotations. This genome wide comparative analysis identified genes that are specific to AMC and RMC. Conclusions The novel and specific molecules identified from the trancriptome explains the quiescent state functioning of microglia in its two distinct morphological states.

Purification of bacteria from human blood samples is essential for rapid identification of pathogens by molecular methods, enabling faster and more accurate diagnosis of bloodstream infection than conventional gold standard blood culture methods. The inertial microfluidic method has been broadly studied to isolate biological cells of interest in various biomedical applications due to its label-free and high-throughput advantages. However, because of the bacteria's tininess, which ranges from 0.5 μm to 3 μm, they are challenging to be effectively focused and sorted out in existing inertial microfluidic devices that work well with biological cells larger than 10 μm. Efforts have been made to sort bacterial cells by utilizing extremely small channel dimensions or employing a sheath flow, which thus results in limitations on the throughput and ease of operation. To overcome this challenge, we develop a method that integrates a non-Newtonian fluid with a novel channel design to allow bacteria to be successfully sorted from larger blood cells in a channel dimension of 120 μm × 20 μm without the use of sheath flows. The throughput of this device with four parallel channels is above 400 μL per minute. The real-time polymerase chain reaction (qPCR) analysis indicates that our inertial sorting approach has a nearly 3-fold improvement in pathogen recovery compared with the commonly used lysis-centrifugation method at pathogen abundances as low as 102 cfu mL−1. With the rapid and simple purification and enrichment of bacterial pathogens, the present inertial sorting method exhibits an ability to enhance the fast and accurate molecular diagnosis of bloodstream bacterial infection. [ABSTRACT FROM AUTHOR]

Introduction: SARS-CoV-2 antigen tests can complement and substitute for RT-PCR tests. Centralized laboratory automated SARS-CoV-2 antigen tests that can be scaled to process a large number COVID-19 cases simultaneously are now available. We have evaluated the new Roche Elecsys SARS-CoV-2 antigen electro-chemiluminescent immunoassay. Methods: The Roche SARS-CoV-2 antigen assay is a double-antibody sandwich electro-chemiluminescent immunoassay, which reports a cut-off index (COI) (COI ≥ 1.0 considered positive). We assessed assay precision and linearity, and confirmed the reactivity limit. We determined the assay sensitivity and specificity with a verification group (289 controls and 61 RT-PCR positive COVID-19 cases). Assay performance was also validated against the consecutive samples we received (7657 controls and 17 cases) for SARS-CoV-2 antigen testing from June to October 2021. Result: The assay had a within-run precision CV of 3.0% at COI 0.68, and a CV of 1.5% at COI 3.49. Between-run precision was 3.0% at COI 0.68 and 1.8% at COI 3.49. The assay was linear from COI 0.65 to 7.84. All 35 C50 ± 20% test results performed over 7 days were positive/negative, respectively. In the verification group, overall sensitivity was 42.6% (26/61 positive, 95% CI 30.0–55.9), and specificity was 99.7% (1/289 positive, 95% CI 98.1–100). The agreement between the SARS-CoV-2 antigen and the RT-PCR cycle threshold (Ct) count was good (r = 0.90). In cases with Ct counts ≤ 30, the antigen assay sensitivity improved to 94.7% (18/19 positive, 95% CI 74.0–99.9). In our validation group, antigen sensitivity was 62.5% (5/8 antigen positive, 95% CI 24.5–91.5) within the first week of disease onset, but no cases were reactive after the first week of disease onset. Conclusion: The Elecsys SARS-CoV-2 antigen assay has good performance within manufacturer specifications. The sensitivity of the Roche antigen assay was greatest when used in patients with lower RT-PCR Ct values (≤30) and within the first week of disease onset. [ABSTRACT FROM AUTHOR]

The number of leaves in maize plant is one of the key traits describing its growth conditions. It is directly related to plant development and leaf counts also give insight into changing plant development stages. Compared with the traditional solutions which need excessive human interventions, the methods of computer vision and machine learning are more efficient. However, leaf counting with computer vision remains a challenging problem. More and more researchers are trying to improve accuracy. To this end, an automated, deep learning based approach for counting leaves in maize plants is developed in this paper. A Convolution Neural Network(CNN) is used to extract leaf features. The CNN model in this paper is inspired by Google Inception Net V3, which using multi-scale convolution kernels in one convolution layer. To compress feature maps generated from some middle layers in CNN, the Fisher Vector (FV) is used to reduce redundant information. Finally, these encoded feature maps are used to regress the leaf numbers by using Random Forests. To boost the related research, a relatively single maize image dataset (Different growth stage with 2845 samples, which 80% for train and 20% for test) is constructed by our team. The proposed algorithm in single maize data set achieves Mean Square Error (MSE) of 0.32. [ABSTRACT FROM AUTHOR]

With the rapid advances in remote-sensing technologies and the larger number of satellite images, fast and effective object detection plays an important role in understanding and analyzing image information, which could be further applied to civilian and military fields. Recently object detection methods with region-based convolutional neural network have shown excellent performance. However, these two-stage methods contain region proposal generation and object detection procedures, resulting in low computation speed. Because of the expensive manual costs, the quantity of well-annotated aerial images is scarce, which also limits the progress of geospatial object detection in remote sensing. In this paper, on the one hand, we construct and release a large-scale remote-sensing dataset for geospatial object detection (RSD-GOD) that consists of 5 different categories with 18,187 annotated images and 40,990 instances. On the other hand, we design a single shot detection framework with multi-scale feature fusion. The feature maps from different layers are fused together through the up-sampling and concatenation blocks to predict the detection results. High-level features with semantic information and low-level features with fine details are fully explored for detection tasks, especially for small objects. Meanwhile, a soft non-maximum suppression strategy is put into practice to select the final detection results. Extensive experiments have been conducted on two datasets to evaluate the designed network. Results show that the proposed approach achieves a good detection performance and obtains the mean average precision value of 89.0% on a newly constructed RSD-GOD dataset and 83.8% on the Northwestern Polytechnical University very high spatial resolution-10 (NWPU VHR-10) dataset at 18 frames per second (FPS) on a NVIDIA GTX-1080Ti GPU. [ABSTRACT FROM AUTHOR]

Introduction: Onychomycosis is a debilitating, difficult-to-treat nail fungal infection with increasing prevalence worldwide. The main etiological agents are dermatophytes, which are common causative pathogens in superficial fungal mycoses. Conventional detection methods such as fungal culture have low sensitivity and specificity and are time-consuming. Aim: The main objective of this study was to design, develop and validate a real-time probe-based multiplex qPCR assay for the detection of dermatophytes and Fusarium species. Methodology: The performance characteristics of the qPCR assays were evaluated. The multiplex qPCR assays targeted four genes (assay 1:  pan-dermatophytes /Fusarium spp.; assay 2: Trichophyton rubrum/Microsporum spp.). Analytical validation was accomplished using 150 fungal isolates and clinical validation was done on 204 nail specimens. The performance parameters were compared against the gold standard (fungal culture) and expanded gold standard (culture in conjunction with sequencing). Results: Both the single-plex and multiplex qPCR assays performed well especially when compared against the expanded gold standard. Among the 204 tested nail specimens, the culture method showed that 125 (61.3 %) were infected with at least one organism, of which 40 yielded positive results for dermatophytes and Fusarium spp. These target organisms detected include 20 dermatophytes and 22 Fusarium spp. The developed qPCR assays demonstrated excellent limit of detection, efficiency, coefficient of determination, analytical and clinical sensitivity and specificity. Conclusion: The multiplex qPCR assays were reliable for the diagnosis of onychomycosis, with shorter turn-around time as compared to culture method. This aids in the planning of treatment strategies to achieve optimal therapeutic outcome.

Background: Despite the potential usefulness of plasmids as reference materials for PCR, there are very few reports documenting the experience with using these materials in quality control (QC) of laboratory developed tests (LDTs), in a clinical diagnostic setting. In this study, an approach to preparing and titering such controls is detailed. The practicality of using plasmids as QC materials was explored and presented., Methods: Target DNA fragments (n = 11) were amplified from positive samples and cloned using TA-cloning. Identities of the fragments were ascertained using DNA sequencing. Real-time PCR was carried out using TaqMan probes on RGQ or CFX-96 thermal-cyclers., Results: All the 11 targeted DNA fragments were successfully cloned into E. coli vectors. Plasmid pools could be repeatedly reconstituted to generate stable and usable positive controls for multiplex PCR assays in a simple workflow. Importantly, plasmid controls generated meaningful run data that could be used in QC processes for monitoring routine runs. Further, plasmid material could be spiked into clinical specimens for quality assurance (QA) purposes, avoiding the culture of live infectious organisms, showing another routine usefulness of plasmids., Conclusions: Plasmid pools are useful and inexhaustible sources of reference materials for various routine QC uses in the diagnostic laboratory.

Introduction: We aimed to develop and implement a short tandem repeat (STR) polymerase chain reaction alternative to fluorescence in situ hybridisation (FISH) for the preimplantation genetic diagnosis (PGD) of chromosomal translocations., Methods: Selected informative STRs located on translocated arms of relevant chromosomes were used to discriminate between normal and unbalanced chromosome states in each embryo., Results: PGD cycles were performed on five couples where one spouse carried a balanced translocation. 27 embryos were analysed, of which 12 were normal/balanced, 12 were abnormal/unbalanced and three were indeterminate. Four PGD cycles proceeded to embryo transfer, of which two led to pregnancy. The first pregnancy showed a normal male karyotype, and a healthy baby was delivered at term. A second pregnancy unexpectedly miscarried in the second trimester from unknown causes., Conclusion: STR analysis is a simple and suitable alternative to FISH for detecting unbalanced chromosomal states in preimplantation embryos.

Background and Results: Embryos from diabetic mice exhibit several forms of neural tube defects, including non-closure of the neural tube. In the present study, embryos collected at embryonic day 11.5 from diabetic pregnancies displayed open neural tube with architectural disruption of the surrounding tissues. The percentage of proliferating cells was found to be increased in the dorsal and ventral domains of the spinal neural tube of embryos from diabetic mice, indicating a defect in the proliferation index. We have analyzed the development of various cell types, including motoneurons, interneurons, oligodendrocytes and migrating neurons, as well as radial glial cells in the open neural tube using specific molecular markers. Immunofluorescence results revealed a significantly reduced number of Pax2+ interneurons and increased number of Isl-1+ motoneurons, as well as Olig2+ oligodendrocytes in the neural tube of embryos from diabetic mice as compared to controls. In addition, these embryos exhibited a decreased number of doublecortin positive migrating neurons and Glast/Blbp positive radial glial cells with shortened processes in the neural tube. Expression levels of several developmental control genes involved in the generation of different neuronal cell types (such as Shh, Ngn, Ngn2, Ascl1) were also found to be altered in the neural tube of embryos from diabetic mice., Conclusions: Overall, the open neural tube in embryos of diabetic mice exhibits defects in the specification of different cell types, including motoneurons and interneurons, as well as glial cells along the dorsoventral axis of the developing spinal cord. Although these defects are associated with altered expression of several development control genes, the exact mechanisms by which maternal diabetes contributes to these changes remain to be investigated.

Maternal diabetes causes congenital malformations in various organs including the neural tube in fetuses. In this study, we have analyzed the differential gene expression profiling in the cranial neural tube of embryos from diabetic and control mice by using the oligonucleotide microarray. Expression patterns of genes and proteins that are differentially expressed in the cranial neural tube were further examined by the real-time reverse transcriptase-polymerase chain reaction, in situ hybridization, and immunohistochemistry. Proliferation index and apoptosis were examined by BrdU (5-bromo-2-deoxyuridine) labeling and TUNEL (terminal deoxynucleotidyl transferase dUTP nick-end labeling) assay, respectively. Embryos (E11.5) of diabetic pregnancies displayed distortion in neuroepithelia of the cranial neural tube. Microarray analysis revealed that a total of 390 genes exhibited more than twofold changes in expression level in the cranial neural tube of embryos from diabetic mice. Several genes involving apoptosis, proliferation, migration, and differentiation of neurons in the cranial neural tube were differentially expressed in embryos of diabetic pregnancy. In addition, maternal diabetes perturbed the development of choroid plexus and ventricular systems and reduced the production of proteins such as Ttr and Igf2 in the developing brain, indicating that these changes could impair the survival and proliferation of neuroepithelial cells and neurogenesis in embryos of diabetic mice. It is concluded that altered expression of a variety of genes involved in brain development is associated with cranial neural tube dysmorphogenesis that may subsequently contribute to intellectual impairment of the offspring of a diabetic mother., ((c) 2008 Wiley-Liss, Inc.)