RESUMO
The Kingdom of Morocco approved BBIBP-CorV (Sinopharm) COVID-19 vaccine for emergency use on 22 January 2021 in a two-dose, three-to-four-week interval schedule. We conducted a case-control study to determine real-world BBIBP-CorV vaccine effectiveness (VE) against serious or critical hospitalization of individuals RT-PCR-positive for SARS-CoV-2 during the first five months of BBIBP-CorV use in Morocco. The study was conducted among adults 18-99 years old who were tested by RT-PCR for SARS-CoV-2 infection between 1 February and 30 June 2021. RT-PCR results were individually linked with outcomes from the COVID-19 severe or critical hospitalization dataset and with vaccination histories from the national vaccination registration system. Individuals with partial vaccination (<2 weeks after dose two) or in receipt of any other COVID-19 vaccine were excluded. Unadjusted and adjusted VE estimates against hospitalization for serious or critical illness were made by comparing two-dose vaccinated and unvaccinated individuals in logistic regression models, calculated as (1-odds ratio) * 100%. There were 348,190 individuals able to be matched across the three databases. Among these, 140,892 were fully vaccinated, 206,149 were unvaccinated, and 1,149 received homologous BBIBP-CorV booster doses. Unadjusted, full-series, unboosted BBIBP-CorV VE against hospitalization for serious or critical illness was 90.2% (95%CI: 87.8% - 92.0%). Full-series, unboosted VE, adjusted for age, sex, and calendar day of RT-PCR test, was 88.5% (95%CI: 85.8% - 90.7%). Calendar day- and sex-adjusted VE ranged from 93.9% to 100% for individuals <60 years, and was 53.3% for individuals 60 years and older. There were no serious or critical illnesses among BBIBP-CorV-boosted individuals. Effectiveness of Sinopharms BBIBP-CorV was consistent with phase III clinical trial results. Two doses of BBIBP-CorV was highly protective against COVID-19-associated serious or critical hospitalization in working-age adults under real-world conditions and moderately effective in older adults. Booster dose VE should be evaluated, as booster doses of BBIBP-CorV are recommended and are being used.
RESUMO
Objective To investigate the expressions of spleen tyrosine kinase (Syk), c-Jun amino terminal kinase (JNK) and nucleotide binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome in the heart tissue in SD rat model of diabetic cardiomyopathy, and to explore the relationship between Syk, JNK and NLRP3. Methods Clean male SD rats were randomly divided into the control (Ctrl) group and diabetic cardiomyopathy model (DCM) group. Rats of DCM group were treated with a single intraperitoneal injection of streptozotocin (STZ), while rats of Ctrl group were injected with the same dose of citrate buffer. The random blood glucose level and body weight were monitored every week until 20 weeks after STZ or citrate buffer injection, then all the rats were killed and their hearts were obtained. Rat H 9c2 cardiomyocytes were randomly divided into normal glucose treatment (NG) group, high glucose treatment (HG) group, Syk inhibitor control (BAY) group and Syk inhibitor high glucose (HG+BAY) group. The Syk and JNK phosphorylations and NLRP3 protein expression were detected by Western blot assay in the heart tissue of SD rats and H9c2 cardiomyocytes. The NLRP3, cysteine-containing aspartate specific protease 1(caspase-1) and interleukin (IL)-1β expressions at mRNA level were detected by reverse transcription-polymerase chain reaction (RT-PCR). Results The random blood glucose level was significantly increased (P<0.05) and the body weight was significantly decreased (P<0.05) in DCM group compared with those of Ctrl group. The expressions of cardiac p-Syk, p-JNK and NLRP3 at protein level were significantly increased in DCM group compared with those of Ctrl group (P<0.05). Furthermore, the mRNA levels of NLRP3, caspase-1 and IL-1β were significantly up-regulated (P < 0.05). BAY treatment significantly inhibited the high glucose-induced NLRP3, caspase-1 and IL-1β mRNA expressions and p-JNK, NLRP3 protein expressions in H9c2 cardiomyocytes (P < 0.05). Conclusion JNK phosphorylation and NLRP3 inflammasome activation induced by Syk play an important role in the pathogenesis of diabetic cardiomyopathy.
RESUMO
Objective To clarify the role of syk kinase in inflammasome activation in mouse peritoneal macrophages during Listeria monocytogenes (LM) infection. Methods Murine peritoneal macrophages were randomly divided into BAY treatment group, SB treatment group, WO treatment group, no treatment group and negative control group (NI). There were three wells in each group. The syk inhibitor BAY 117082, P38MAPK inhibitor SB203580 and PI3K inhibitor wotamine were used to treat murine peritoneal macrophages for 1h in BAY treatment group, SB treatment group and WO treatment group. Murine peritoneal macrophages were infected with LM for 24 h except NI group. The protein level of interleukin (IL)-18 in the supernatant was detected by ELISA kit. The activation condition of key molecule ASC in the infected-macrophages cyto-plasm was observed under fluorescence microscope. The phosphorylation levels of syk protein kinase at different time points during LM infection were determined by Western blot assay. Results There was no significant difference in IL-18 protein level before and after BAY treatment in NI group (P>0.05). The IL-18 protein level was significantly lower after LM infec-tion in BAY treatment group compared with that in no treatment group (P0.05). Meanwhile, the per-centage of ASC-speck positive cells was obviously diminished in BAY treatment group compared with that in no treatment group (P<0.01). The phosphorylation levels of syk were significantly increased in 5 min, 15 min and 30 min post-infection. Conclusion Syk kinase signaling is involved in the inflammasomes activation upon Listeria monocytogenes infection in mu-rine macrophages.
RESUMO
BACKGROUND: No previous study reported the efficacy of current natural language processing (NLP) methods for extracting laboratory test information from narrative documents. This study investigates the pathology informatics question of how accurately such information can be extracted from text with the current tools and techniques, especially machine learning and symbolic NLP methods. The study data came from a text corpus maintained by the U.S. Food and Drug Administration, containing a rich set of information on laboratory tests and test devices. METHODS: THE AUTHORS DEVELOPED A SYMBOLIC INFORMATION EXTRACTION (SIE) SYSTEM TO EXTRACT DEVICE AND TEST SPECIFIC INFORMATION ABOUT FOUR TYPES OF LABORATORY TEST ENTITIES: Specimens, analytes, units of measures and detection limits. They compared the performance of SIE and three prominent machine learning based NLP systems, LingPipe, GATE and BANNER, each implementing a distinct supervised machine learning method, hidden Markov models, support vector machines and conditional random fields, respectively. RESULTS: Machine learning systems recognized laboratory test entities with moderately high recall, but low precision rates. Their recall rates were relatively higher when the number of distinct entity values (e.g., the spectrum of specimens) was very limited or when lexical morphology of the entity was distinctive (as in units of measures), yet SIE outperformed them with statistically significant margins on extracting specimen, analyte and detection limit information in both precision and F-measure. Its high recall performance was statistically significant on analyte information extraction. CONCLUSIONS: Despite its shortcomings against machine learning methods, a well-tailored symbolic system may better discern relevancy among a pile of information of the same type and may outperform a machine learning system by tapping into lexically non-local contextual information such as the document structure.
