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The incidence of Candida infections in intensive care units (ICU) has significantly increased in recent years, and these infections have become one of the most serious complications threatening the lives of ICU patients. The proportion of non-Candida albicans infections, such as Candida krusei and Candida glabrata infections, which are resistant to fluconazole, is increasing each year. Early identification of the strains causing Candida infections is important for the timely implementation of targeted treatments to save patients’ lives. However, the current methods of direct microscopy, culture, and histopathology, as well as other diagnostic methods, have many shortcomings, such as their low sensitivity and long assay times; therefore, they cannot meet the needs for early clinical diagnosis. Recombinant polymerase amplification (RPA) is a promising isothermal amplification technique that can be performed without sophisticated instruments and equipment, and is suitable for use in resource-poor areas. RPA combined with lateral flow strips (LFS) can be used to rapidly amplify and visualize target genes within 20 min. In this study, RPA-LFS was used to amplify the internal transcribed spacer 2 (ITS2) region of C. krusei. The primer-probe design was optimized by introduction of base mismatches (probe modification of five bases) to obtain a specific and sensitive primer-probe combination for the detection of clinical specimens. Thirty-five common clinical pathogens were tested with RPA-LFS to determine the specificity of the detection system. The RPA-LFS system specifically detected C. krusei without cross-reaction with other fungi or bacteria. A gradient dilution of the template was tested to explore the lower limit of detection and sensitivity of the assay. The sensitivity was 10 CFU/50 µL per reaction, without interference from genomic DNA of other species. The RPA-LFS and qPCR assays were performed on 189 clinical specimens to evaluate the detection performance of the RPA-LFS system. Seventy-six specimens were identified as C. krusei, indicating a detection rate of 40.2%. The results were consistent with those of qPCR and conventional culture methods. The RPA-LFS system established in our study provides a reliable molecular diagnostic method for the detection of C. krusei, thus meeting the urgent need for rapid, specific, sensitive, and portable clinical field testing.

The molecular mechanisms underlying the pathogenesis of pigment dispersion syndrome and pigmentary glaucoma remain unclear. In pedigree-based studies, familial aggregation and recurrences in relatives suggest a strong genetic basis for pigmentary glaucoma. In this study, we aimed to identify the genetic background of two Chinese pedigrees with pigmentary glaucoma. All members of these two pedigrees who enrolled in the study underwent a comprehensive ophthalmologic examination, and genomic DNA was extracted from peripheral venous blood samples. Whole-exome sequencing and candidate gene verifications were performed to identify the disease-causing variants; in addition, screening of the CPAMD8 gene was performed on 38 patients of sporadic pigmentary glaucoma. Changes in the structure and function of abnormal proteins caused by gene variants were analyzed with a bioinformatics assessment. Pigmentary glaucoma was identified in a total of five patients from the two pedigrees, as were compound heterozygous variants of the CPAMD8 gene. No signs of pigmentary glaucoma were found in carriers of monoallelic CPAMD8 variant/variants. All four variants were inherited in an autosomal recessive mode. In addition to the 38 patients of sporadic pigmentary glaucoma, 13 variants of the CPAMD8 gene were identified in 11 patients. This study reported a possible association between CPAMD8 variants and pigment dispersion syndrome/pigmentary glaucoma.

Maximizing the percentage of people who can use an electric vehicle is crucial to achieving full electric transportation. Residents living in older multi-family dwellings without access to a personal charging station do not have the facilities to join this electricity powered movement. Public accessible, street-light charging is identified as a solution to this issue. The world is moving towards full electric transportation, however, the emissions from traditional combustion engine vehicles are still contributing to global warming. An increase in electric vehicle usage will lower the carbon footprint of the transportation sector. Geographic Information System (GIS) research determined the ideal street-light electric vehicle charging locations throughout the City of Vancouver by assigning importance weights to areas such as high population density, parking spots, multi-family dwellings, and proximity to public transit. A number of street lights were chosen as the most ideal locations to install level 2 and level 3 electric chargers. Kitsilano and Downtown are representative case studies due to their high population density and electrical infrastructure. A cost estimate of implementing street-light charging stations in Kitsilano and Downtown was determined. The results of this research presents itself as an option for stakeholders to consider when they decide to upgrade the electric transportation infrastructure. Implementing street-light charging stations removes a barrier which has prevented drivers from going electric in the past. Electric vehicle users contribute to the fight against global warming.

In earthquake monitoring, an important aspect of the operational effect of earthquake intensity rapid reporting and earthquake early warning networks depends on the density and performance of the deployed seismic sensors. To improve the resolution of seismic sensors as much as possible while keeping costs low, in this article the use of multiple low-cost and low-resolution digital MEMS accelerometers is proposed to increase the resolution through the correlation average method. In addition, a cost-effective MEMS seismic sensor is developed. With ARM and Linux embedded computer technology, this instrument can cyclically store the continuous collected data on a built-in large-capacity SD card for approximately 12 months. With its real-time seismic data processing algorithm, this instrument is able to automatically identify seismic events and calculate ground motion parameters. Moreover, the instrument is easy to install in a variety of ground or building conditions. The results show that the RMS noise of the instrument is reduced from 0.096 cm/s2 with a single MEMS accelerometer to 0.034 cm/s2 in a bandwidth of 0.1–20 Hz by using the correlation average method of eight low-cost MEMS accelerometers. The dynamic range reaches more than 90 dB, the amplitude–frequency response of its input and output within −3 dB is DC −80 Hz, and the linearity is better than 0.47%. In the records from our instrument, earthquakes with magnitudes between M2.2 and M5.1 and distances from the epicenter shorter than 200 km have a relatively high SNR, and are more visible than they were prior to the joint averaging.