published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references (leaves 84-96). Also available in electronic version. Access restricted to campus users.

Regensburg, Univ., Diss., 2008.

Würzburg, Univ., Diss., 2009.

Objetivos: Determinar hallazgos estructurales o funcionales ecocardiográficos en pacientes recuperados de infección SARS-CoV-2. Materiales y métodos: Estudio observacional transversal, que incluyó pacientes trabajadores de un hospital nacional COVID, estudiados entre 3 a 6 meses luego del diagnostico de infección SARS-CoV-2. La exploración ecocardiográfica se desarrolló de forma sistemática e incluyó las modalidades convencionales. Resultados: Se incluyeron 65 casos con infección-CoV-2, la edad promedio fue 37.7 años, la obesidad resultó la comorbilidad mas frecuente (13.8%) y la presentación clínica leve fue la de mayor prevalencia (84.6%). Las medias del diámetro diastólico y la fracción de eyección ventrículo izquierdo fueron 42mm y 57% respectivamente. Así mismo la media del diámetro basal del ventrículo derecho fue de 31mm, de la fracción de acortamiento 44% y en todos los casos se reportó probabilidad de hipertensión pulmonar como baja. No se encontró efusión pericárdica en ninguno de los casos. Conclusiones Los pacientes recuperados de infección SARS-CoV-2, no presentan alteraciones estructurales ni funcionales en la exploración ecocardiográfica convencional.

SARS-CoV-2 wastewater surveillance is a promising tool for monitoring the spread of infection during pandemic outbreaks. 24-hour composite sampling of wastewater using autosamplers is the preferred means for wastewater surveillance sample collection. Autosamplers however require a significant capital cost and furthermore some sampling locations are not amenable to autosampler deployment because of a lack of space and lack of access to electricity. Grab sampling is an alternative to auto sampling for wastewater surveillance, however it may be less effective compared to 24-hour composite sampling due to the possibility to miss the collection of shed disease targets during critical shedding events. Torpedo-style passive samplers packed with medical gauze and tampon-style passive samplers are alternatives to grab sampling when deployment of autosamplers is not possible. Torpedo-style and tampon-style passive samplers are characterized as being easy to deploy and collect and have shown promise for disease surveillance using wastewater. Although passive samplers have shown the ability to detect SARS-CoV-2, they have not demonstrated the ability to quantify the viral load in the wastewater due to the fact that the collection of the liquid phase of the sampler is not consistent across the deployment period of a passive sampler. As SARS-CoV-2 disease targets have been shown to largely partition to the solids phase of wastewaters, it is hypothesized that mass fraction quantitation may enable passive samplers to quantify wastewater signals comparably to autosamplers. In this study, wastewater samples were collected from the same location over a period of three months from a sewer access point at the University of Ottawa using conventional 24-hour auto sampling. Two types of torpedostyle passive samplers and a tampon-style passive sampler were tested to assess whether passive sampler measurements of SARS-CoV-2 N1 and N2 gene targets can be used in the place of autosampler quantitated values. When comparing the wastewater characteristics of centrifuged pellets collected by various passive samplers and a conventional autosampler, the results of this study showed that the torpedo-style passive sampler packed with two pieces of gauze (P2) collected significantly lower water content compared to the autosampler, and P2 collected significantly greater total solids and volatile solids compared to the autosampler. When measuring SARS-CoV-2 N1 and N2 signals, the results indicate that N1 and N2 gene region copy numbers from all of the samplers were not significantly distinct. However, the P2 sampler, a torpedo-style passive sampler packed with four pieces of gauze (P4), and the tampon-style passive sampler (T) captured a greater quantity of pepper mild iii mottle virus (PMMoV) gene targets compared to the autosampler; where PMMoV is the most commonly measured fecal biomarker for wastewater surveillance of SARS-CoV-2. The greater quantity of PMMoV gene targets compared to the autosampler was likely due to proportionally higher total solids and volatile solids in the centrifuged pellet material captured. When N1 and N2 measurements were normalized against sample volume, pellet mass or PMMoV gene copy numbers, P2, P4, and T showed no significant differences compared to the autosampler. In contrast, differences were observed between passive samplers and the autosampler when PMMoV measurements were normalized against the matrix volumes or pellet mass. High statistical percentage differences were observed between all passive samplers and the autosampler. Overall, passive samplers are reliable, cost-effective devices for sampling disease targets in wastewater if results are expressed as copies/g or copies/copies PMMoV. These devices are feasible substitutes for autosamplers when detection and quantification of SARS-CoV-2 in wastewater are required. P2 passive samplers using units of measurement of copies/g are recommended for SARS-CoV-2 surveillance in the wastewater.

SARS-CoV-2 has plagued the world since 2019 with continuously emergence of new variants, resulting in repeated waves of outbreak. Although the countermeasures like vaccination campaign has taken worldwide, the sophisticated virus mutated to escape immune system, threatening the public health. To win the race with the virus and ultimately end the pandemic, we have to take one step ahead to predict how the SARSCoV-2 might evolve and defeat it at the beginning of a new wave. Hence, we proposed a deep learning based framework to first build a deep learning model to shape the fitness landscape of the virus and then use genetic algorithm to predict the high-risk variants that might appear in the future. By combining pre-trained protein language model and structure modeling, the model is trained in a supervised way, predicting the viral transmissibility and antibodies escape ability to eight antibodies simultaneously. The prevenient virus evolution trajectory can be largely recovered by our model with high correlation to their sampling time. Novel mutations predicted by our model show high antibody escape through in silico simulation and overlapped with the mutations developed in prevenient infected patients. Overall, our scheme can provide insights into the evolution of SARS-CoV-2 and hopefully guide the development of vaccination and increase the preparedness.

Background: Respiratory tract infections are responsible for millions of deaths annually. Interferon-stimulated genes (ISGs) play a significant role in fighting off viral respiratory tract infections in the antiviral defence system. Measuring extracellular protein products of ISGs could be potential biomarkers of viral infection. Although, the feasibility and performance of ISGs as functional and robust clinical biomarkers from a non-invasive sample format remains unknown. Methods: Three ISGs, CXCL10, CXCL11, and TNFSF10, were examined in in-vivo and in-vitro gene expression datasets (RNA-sequencing and microarray) infected with common respiratory tract infections (Rhinovirus, Respiratory syncytial virus, influenza A and SARS-CoV-2) samples and compared to negative controls. Using qualitative selection criteria of 1) elevated presence in at least one dataset with viral infection, 2) secreted protein product, and 3) commercially available antibodies for detection, CXCL10, CXCL11 and TNFSF10 gene expression levels were assessed. A correlation analysis was performed with SARS-CoV-2 infection severity and gene expression kinetics. CXCL10 was subsequently validated at the protein level in saliva as a prerequisite for developing a host-response LFA. Results: CXCL10 and CXCL11 upregulation were positively correlated with RSV compared to control (p < 0.05). CXCL10/CXCL11/TNFSF10 were not different between samples collected from RV infected subjects relative to controls (p > 0.05). No significant association was found with influenza A for all three genes. CXCL10/CXCL11/TNFSF10 upregulation was positively correlated with SARS-CoV-2 infection compared to control (p < 0.001). CXCL10 expression correlated with COVID-19 viral load. CXCL10 was chosen as a lead biomarker candidate based on these analyses that included different virus infections, time-courses, and measures of severity. CXCL10 was not detected at the protein level in healthy saliva but was elevated in saliva from COVID-19 patients. A CXCL10 LFA was developed with a sensitivity of 2 ng/ml in a buffer and artificial saliva. Conclusion: We establish and validate the potential of developing rapid test techniques to examine host immune response from a bioinformatic approach to developing a prototype rapid test with capabilities to be used in point-of-care settings. / Thesis / Master of Science (MSc) / Respiratory tract infections are a leading cause of death and one of the main reasons to seek primary care. Both historically and in the present day, respiratory tract infections remain a massive socioeconomic burden. Current diagnostics fail to quickly identify a respiratory tract infection's etiology, and prognosis, leading to suboptimal patient care and the over prescription of antibiotics. Advanced tools used in academia and research, including next-generation -omics sequencing and metagenomics, have capabilities to identify all nucleic acid material in a sample - including host RNA- which offers potential to improve the diagnosing of respiratory tract infections. However, these technologies have not been integrated into routine care due to economic, technical, and logistical barriers. We explored host RNA (transcriptomics), looking at antiviral interferon-stimulated genes for their potential as a biomarker of viral infection amenable to point-of-care testing platforms from non-invasive sample types.

Darstellung von Entstehung, Ausbreitung und Maßnahmen sowohl von staatlicher als auch von medizinischer Seite gegen die Lungenpest-Epidemie in der Mandschurei 1910 bis 1914 und Vergleich des Handelns des Staates China damals und bei der SARS-Epidemie 2002. / The abstract gives a detail description on the topic of the lung plaque epidemic in the Manchuria (1910-1914). It depicts the cause, spread and measure both on the part of government and medicine against it and compares the efforts with those China had during the SARS Epidemic 2002.

The Coronavirus disease 2019 (COVID-19) pandemic has highlighted the critical need for accurate and sensitive diagnostic tools for detecting the SARS-CoV-2 virus. The nucleocapsid (N) protein is essential for virus replication and plays vital roles in virus assembly, packaging, and RNA transcription. This protein is a crucial component of the viral particle and is less prone to mutations than the other essential proteins in SARS-COV-2. All of these make the N protein a reliable target for virus detection. Aptamers, single-stranded oligonucleotides that can specifically bind to target molecules, have been proposed as a promising alternative to antibodies for detecting and treating viral infections. This study aimed to select DNA aptamers against the N protein of SARS-CoV-2 using capillary electrophoresis (CE) and validate the binding specificity of the aptamers. After selecting seven clones, a preliminary binding validation was performed, and the two best binding clones were identified as ECK4 and ECK6. The structures of the aptamers were then modified by removing the primer regions from the original sequence, and the binding capacity of the truncated aptamers was confirmed. Dissociation constant (KD) values were calculated to provide further supportive information for the quality of the two clones. Additionally, Biolayer interferometry (BLI) was used to calculate Apparent KD as an alternative technique and provided consistent results with CE. Our results demonstrate the successful selection of aptamers for the N protein of SARS-CoV-2 using CE-SELEX. Confirming the aptamers' binding capacity to N protein paves the way for developing aptamer-based diagnostics for COVID-19.