Electronic nose(eNose) is a modern bioelectronic sensor for monitoring biological processes that convert CO_(2) into valueadded products, such as products formed during photosynthesis and microbial fermentation. eNose...Electronic nose(eNose) is a modern bioelectronic sensor for monitoring biological processes that convert CO_(2) into valueadded products, such as products formed during photosynthesis and microbial fermentation. eNose technology uses an array of sensors to detect and quantify gases, including CO_(2), in the air. This study briefly introduces the concept of eNose technology and potential applications thereof in monitoring CO_(2) conversion processes. It also provides background information on biological CO_(2) conversion processes. Furthermore, the working principles of eNose technology vis-à-vis gas detection are discussed along with its advantages and limitations versus traditional monitoring methods. This study also provides case studies that have used this technology for monitoring biological CO_(2) conversion processes. eNose-predicted measurements were observed to be completely aligned with biological parameters for R~2 values of 0.864, 0.808, 0.802, and 0.948. We test eNose technology in a variety of biological settings, such as algae farms or bioreactors, to determine its effectiveness in monitoring CO_(2) conversion processes. We also explore the potential benefits of employing this technology vis-à-vis monitoring biological CO_(2) conversion processes, such as increased reaction efficiency and reduced costs versus traditional monitoring methods. Moreover, future directions and challenges of using this technology in CO_(2) capture and conversion have been discussed. Overall, we believe this study would contribute to developing new and innovative methods for monitoring biological CO_(2) conversion processes and mitigating climate change.展开更多
The search for new biomarkers predictive of type 2 diabetes currently constitutes a research avenue in Bioclinical. Total homocysteine remains a preferred target due to its involvement in the occurrence of degenerativ...The search for new biomarkers predictive of type 2 diabetes currently constitutes a research avenue in Bioclinical. Total homocysteine remains a preferred target due to its involvement in the occurrence of degenerative complications in type 2 diabetics. The aim of this work was to study hyperhomocysteinemia and other biochemical markers associated with T2D in the Congolese population. This was an analytical case-control study carried out between October 2022 and October 2023. The study population consisted of 150 subjects including 100 T2D patients and 50 control subjects. The main clinical data were collected on a pre-established form. Homocysteine determination was carried out by the sandwich ELISA method. The other biochemical markers were measured by colorimetric enzymatic methods. Hyperhomocysteinemia was present in 27.3% (41/150) of the entire study population. Type 2 diabetics had a frequency of hyperhomocysteinemia of 36% (36/100) and control 10% (5/50) (p = 0.001). The mean hyperhomocysteinemia concentration was 31.9 μmol/l with extremes ranging from 18 to 103 μmol/l. Means of biological markers between diabetics and controls showed a statistically significant difference (p = 0.01). The risk factors associated with this HHcy were: sex (OR = 3.5), age (OR = 9.4), sedentary lifestyle (OR = 3.4) and glycosylated hemoglobin (OR = 12) with a p-value <0.05 respectively. Our results suggest that hyperhomocysteinemia can be considered as a predictive biomarker in the bioclinic of Congolese type 2 diabetic patients.展开更多
基金supported by the National Key Technologies R & D Program of China during the 14th Five-Year Plan period (No. 2021YFD1700904)Henan Provincial Important Project (No. 221100320200)+1 种基金State Key Laboratory of Wheat and Maize Crap Science (No. SKL2023ZZ09)the Henan Center for Outstanding Overseas Scientists (No. GZS2021007)。
文摘Electronic nose(eNose) is a modern bioelectronic sensor for monitoring biological processes that convert CO_(2) into valueadded products, such as products formed during photosynthesis and microbial fermentation. eNose technology uses an array of sensors to detect and quantify gases, including CO_(2), in the air. This study briefly introduces the concept of eNose technology and potential applications thereof in monitoring CO_(2) conversion processes. It also provides background information on biological CO_(2) conversion processes. Furthermore, the working principles of eNose technology vis-à-vis gas detection are discussed along with its advantages and limitations versus traditional monitoring methods. This study also provides case studies that have used this technology for monitoring biological CO_(2) conversion processes. eNose-predicted measurements were observed to be completely aligned with biological parameters for R~2 values of 0.864, 0.808, 0.802, and 0.948. We test eNose technology in a variety of biological settings, such as algae farms or bioreactors, to determine its effectiveness in monitoring CO_(2) conversion processes. We also explore the potential benefits of employing this technology vis-à-vis monitoring biological CO_(2) conversion processes, such as increased reaction efficiency and reduced costs versus traditional monitoring methods. Moreover, future directions and challenges of using this technology in CO_(2) capture and conversion have been discussed. Overall, we believe this study would contribute to developing new and innovative methods for monitoring biological CO_(2) conversion processes and mitigating climate change.
文摘The search for new biomarkers predictive of type 2 diabetes currently constitutes a research avenue in Bioclinical. Total homocysteine remains a preferred target due to its involvement in the occurrence of degenerative complications in type 2 diabetics. The aim of this work was to study hyperhomocysteinemia and other biochemical markers associated with T2D in the Congolese population. This was an analytical case-control study carried out between October 2022 and October 2023. The study population consisted of 150 subjects including 100 T2D patients and 50 control subjects. The main clinical data were collected on a pre-established form. Homocysteine determination was carried out by the sandwich ELISA method. The other biochemical markers were measured by colorimetric enzymatic methods. Hyperhomocysteinemia was present in 27.3% (41/150) of the entire study population. Type 2 diabetics had a frequency of hyperhomocysteinemia of 36% (36/100) and control 10% (5/50) (p = 0.001). The mean hyperhomocysteinemia concentration was 31.9 μmol/l with extremes ranging from 18 to 103 μmol/l. Means of biological markers between diabetics and controls showed a statistically significant difference (p = 0.01). The risk factors associated with this HHcy were: sex (OR = 3.5), age (OR = 9.4), sedentary lifestyle (OR = 3.4) and glycosylated hemoglobin (OR = 12) with a p-value <0.05 respectively. Our results suggest that hyperhomocysteinemia can be considered as a predictive biomarker in the bioclinic of Congolese type 2 diabetic patients.
