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Development of a Novel, Genome Subtraction-Derived, SARS-CoV-2-Specific COVID-19-nsp2 Real-Time RT-PCR Assay and Its Evaluation Using Clinical Specimens

Yip, Cyril Chik-Yan ; Ho, Chi-Chun ; Chan, Jasper Fuk-Woo ; [et al.]

MDPI AG ; 2020

In: International Journal of Molecular Sciences Vol. 21, No. 7 ( 2020-04-08), p. 2574-

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In: International Journal of Molecular Sciences, MDPI AG, Vol. 21, No. 7 ( 2020-04-08), p. 2574-

Abstract: The pandemic novel coronavirus infection, Coronavirus Disease 2019 (COVID-19), has affected at least 190 countries or territories, with 465,915 confirmed cases and 21,031 deaths. In a containment-based strategy, rapid, sensitive and specific testing is important in epidemiological control and clinical management. Using 96 SARS-CoV-2 and 104 non-SARS-CoV-2 coronavirus genomes and our in-house program, GolayMetaMiner, four specific regions longer than 50 nucleotides in the SARS-CoV-2 genome were identified. Primers were designed to target the longest and previously untargeted nsp2 region and optimized as a probe-free real-time reverse transcription-polymerase chain reaction (RT-PCR) assay. The new COVID-19-nsp2 assay had a limit of detection (LOD) of 1.8 TCID50/mL and did not amplify other human-pathogenic coronaviruses and respiratory viruses. Assay reproducibility in terms of cycle threshold (Cp) values was satisfactory, with the total imprecision (% CV) values well below 5%. Evaluation of the new assay using 59 clinical specimens from 14 confirmed cases showed 100% concordance with our previously developed COVID-19-RdRp/Hel reference assay. A rapid, sensitive, SARS-CoV-2-specific real-time RT-PCR assay, COVID-19-nsp2, was developed.

Type of Medium: Online Resource

ISSN: 1422-0067

URL: Article

DOI: 10.3390/ijms21072574

Language: English

Publisher: MDPI AG

Publication Date: 2020

detail.hit.zdb_id: 2019364-6

SSG: 12

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Evaluation of the commercially available LightMix® Modular E-gene kit using clinical and proficiency testing specimens for SARS-CoV-2 detection

Yip, Cyril Chik-Yan ; Sridhar, Siddharth ; Cheng, Andrew Kim-Wai ; [et al.]

Elsevier BV ; 2020

In: Journal of Clinical Virology Vol. 129 ( 2020-08), p. 104476-

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In: Journal of Clinical Virology, Elsevier BV, Vol. 129 ( 2020-08), p. 104476-

Type of Medium: Online Resource

ISSN: 1386-6532

URL: Article

DOI: 10.1016/j.jcv.2020.104476

Language: English

Publisher: Elsevier BV

Publication Date: 2020

detail.hit.zdb_id: 1499932-8

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Transmission of Rat Hepatitis E Virus Infection to Humans in Hong Kong: A Clinical and Epidemiological Analysis

Sridhar, Siddharth ; Yip, Cyril Chik‐Yan ; Wu, Shusheng ; [et al.]

Ovid Technologies (Wolters Kluwer Health) ; 2021

In: Hepatology Vol. 73, No. 1 ( 2021-01), p. 10-22

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In: Hepatology, Ovid Technologies (Wolters Kluwer Health), Vol. 73, No. 1 ( 2021-01), p. 10-22

Abstract: Hepatitis E virus (HEV) variants causing human infection predominantly belong to HEV species A (HEV‐A). HEV species C genotype 1 (HEV‐C1) circulates in rats and is highly divergent from HEV‐A. It was previously considered unable to infect humans, but the first case of human HEV‐C1 infection was recently discovered in Hong Kong. The aim of this study is to further describe the features of this zoonosis in Hong Kong. Approach and Results We conducted a territory‐wide prospective screening study for HEV‐C1 infection over a 31‐month period. Blood samples from 2,860 patients with abnormal liver function (n = 2,201) or immunosuppressive conditions (n = 659) were screened for HEV‐C1 RNA. In addition, 186 captured commensal rats were screened for HEV‐C1 RNA. Sequences of human‐derived and rat‐derived HEV‐C1 isolates were compared. Epidemiological and clinical features of HEV‐C1 infection were analyzed. HEV‐C1 RNA was detected in 6/2,201 (0.27%) patients with hepatitis and 1/659 (0.15%) immunocompromised persons. Including the previously reported case, eight HEV‐C1 infections were identified, including five in patients who were immunosuppressed. Three patients had acute hepatitis, four had persistent hepatitis, and one had subclinical infection without hepatitis. One patient died of meningoencephalitis, and HEV‐C1 was detected in cerebrospinal fluid. HEV‐C1 hepatitis was generally milder than HEV‐A hepatitis. HEV‐C1 RNA was detected in 7/186 (3.76%) rats. One HEV‐C1 isolate obtained from a rat captured near the residences of patients was closely related to the major outbreak strain. Conclusions HEV‐C1 is a cause of hepatitis E in humans in Hong Kong. Immunosuppressed individuals are susceptible to persistent HEV‐C1 infection and extrahepatic manifestations. Subclinical HEV‐C1 infection threatens blood safety. Tests for HEV‐C1 are required in clinical laboratories.

Type of Medium: Online Resource

ISSN: 0270-9139 , 1527-3350

URL: Article

DOI: 10.1002/hep.31138

Language: English

Publisher: Ovid Technologies (Wolters Kluwer Health)

Publication Date: 2021

detail.hit.zdb_id: 1472120-X

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Clinical Outcome of Cryptococcal Meningitis of HIV-Infected and Non-HIV-Infected Patients in Hong Kong: A 2-Center Retrospective Review

Tang, Tommy Hing-Cheung ; Ting, Wan-Man ; Wu, Alan Ka-Lun ; [et al.]

Oxford University Press (OUP) ; 2016

In: Open Forum Infectious Diseases Vol. 3, No. suppl_1 ( 2016-12-01)

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In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 3, No. suppl_1 ( 2016-12-01)

Type of Medium: Online Resource

ISSN: 2328-8957

URL: Article

DOI: 10.1093/ofid/ofw172.1310

Language: English

Publisher: Oxford University Press (OUP)

Publication Date: 2016

detail.hit.zdb_id: 2757767-3

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Hepatitis E Virus Species C Infection in Humans, Hong Kong

Sridhar, Siddharth ; Yip, Cyril Chik Yan ; Lo, Kelvin Hon Yin ; [et al.]

Oxford University Press (OUP) ; 2022

In: Clinical Infectious Diseases Vol. 75, No. 2 ( 2022-08-25), p. 288-296

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In: Clinical Infectious Diseases, Oxford University Press (OUP), Vol. 75, No. 2 ( 2022-08-25), p. 288-296

Abstract: Hepatitis E virus (HEV) variants belonging to Orthohepevirus species A (HEV-A) are the primary cause of human hepatitis E. However, we previously reported that Orthohepevirus species C genotype 1 (HEV-C1), a divergent HEV variant commonly found in rats, also causes hepatitis in humans. Here, we present a clinical-epidemiological investigation of human HEV-C1 infections detected in Hong Kong, with an emphasis on outcomes in immunocompromised individuals. Methods A surveillance system for detecting human HEV-C1 infections was established in Hong Kong. Epidemiological and clinical characteristics of HEV-C1 cases identified via this system between 1 August 2019 and 31 December 2020 were retrieved. Phylogenetic analysis of HEV-C1 strain sequences was performed. Infection outcomes of immunocompromised individuals with HEV-A and HEV-C1 infections were analyzed. Results HEV-C1 accounted for 8 of 53 (15.1%) reverse-transcription polymerase chain reaction (RT-PCR)–confirmed HEV infections in Hong Kong during the study period, raising the total number of HEV-C1 infections detected in the city to 16. Two distinct HEV-C1 strain groups caused human infections. Patients were elderly and/or immunocompromised; half tested negative for HEV immunoglobulin M. Cumulatively, HEV-C1 accounted for 9 of 21 (42.9%) cases of hepatitis E recorded in immunocompromised patients in Hong Kong. Immunocompromised HEV-C1 patients progressed to persistent hepatitis at similar rates (7/9 [77.8%]) as HEV-A patients (10/12 [75%] ). HEV-C1 patients responded to oral ribavirin, although response to first course was sometimes poor or delayed. Conclusions Dedicated RT-PCR–based surveillance detected human HEV-C1 cases that evade conventional hepatitis E diagnostic testing. Immunosuppressed HEV-C1–infected patients frequently progress to persistent HEV-C1 infection, for which ribavirin is a suitable treatment option.

Type of Medium: Online Resource

ISSN: 1058-4838 , 1537-6591

URL: Article

DOI: 10.1093/cid/ciab919

RVK:

XA 10000

Language: English

Publisher: Oxford University Press (OUP)

Publication Date: 2022

detail.hit.zdb_id: 2002229-3

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Tang, Tommy Hing-cheung ; Cheng, Naomi Hua-yin ; Ho, Roy Tsz-chung ; [et al.]

Oxford University Press (OUP) ; 2016

In: Open Forum Infectious Diseases Vol. 3, No. 3 ( 2016-05-01)

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In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 3, No. 3 ( 2016-05-01)

Abstract: Shewanella algae and Shewanella putrefaciens have been implicated for causing serious infections in humans, including disseminated infection. We report the possible first case of Shewanella-related Fournier's gangrene and bacteremia caused in a 65-year-old Chinese male with nephrotic syndrome. He was successfully managed by surgical debridement and antibiotic therapy.

Type of Medium: Online Resource

ISSN: 2328-8957

URL: Article

DOI: 10.1093/ofid/ofw148

Language: English

Publisher: Oxford University Press (OUP)

Publication Date: 2016

detail.hit.zdb_id: 2757767-3

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Prevalence of Psychological Problems in Chinese Peritoneal Dialysis Patients

Lai, Ka-Yau ; Chan, Helen Shuk-Ying ; Leung, Vincent Kwok-Hung ; [et al.]

Elsevier BV ; 2005

In: Hong Kong Journal of Nephrology Vol. 7, No. 2 ( 2005-10), p. 82-89

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In: Hong Kong Journal of Nephrology, Elsevier BV, Vol. 7, No. 2 ( 2005-10), p. 82-89

Type of Medium: Online Resource

ISSN: 1561-5413

URL: Article

DOI: 10.1016/S1561-5413(09)60219-2

Language: English

Publisher: Elsevier BV

Publication Date: 2005

detail.hit.zdb_id: 2054979-9

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Prognostic Model of COVID-19 Severity and Survival among Hospitalized Patients Using Machine Learning Techniques

Lodato, Ivano ; Iyer, Aditya Varna ; To, Isaac Zachary ; [et al.]

MDPI AG ; 2022

In: Diagnostics Vol. 12, No. 11 ( 2022-11-08), p. 2728-

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In: Diagnostics, MDPI AG, Vol. 12, No. 11 ( 2022-11-08), p. 2728-

Abstract: We conducted a statistical study and developed a machine learning model to triage COVID-19 patients affected during the height of the COVID-19 pandemic in Hong Kong based on their medical records and test results (features) collected during their hospitalization. The correlation between the values of these features is studied against discharge status and disease severity as a preliminary step to identify those features with a more pronounced effect on the patient outcome. Once identified, they constitute the inputs of four machine learning models, Decision Tree, Random Forest, Gradient and RUSBoosting, which predict both the Mortality and Severity associated with the disease. We test the accuracy of the models when the number of input features is varied, demonstrating their stability; i.e., the models are already highly predictive when run over a core set of (6) features. We show that Random Forest and Gradient Boosting classifiers are highly accurate in predicting patients’ Mortality (average accuracy ∼99%) as well as categorize patients (average accuracy ∼91%) into four distinct risk classes (Severity of COVID-19 infection). Our methodical and broad approach combines statistical insights with various machine learning models, which paves the way forward in the AI-assisted triage and prognosis of COVID-19 cases, which is potentially generalizable to other seasonal flus.

Type of Medium: Online Resource

ISSN: 2075-4418

URL: Article

DOI: 10.3390/diagnostics12112728

Language: English

Publisher: MDPI AG

Publication Date: 2022

detail.hit.zdb_id: 2662336-5

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