33 results on '"Wekesa C"'
Search Results
2. Distribution, characterization and the commercialization of elite Rhizobia strains in Africa
- Author
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Wekesa, C., Jalloh, A., Muoma, J., Korir, H., Omenge, K., Maingi, J., Furch, A., and Oelmüller, R.
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- 2022
3. The cell membrane of a novel Rhizobium phaseoli strain is the crucial target for Aluminium toxicity and tolerance
- Author
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Wekesa, C., Muoma, J., Reichelt, M., Asudi, G., Furch, A., and Oelmüller, R.
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- 2022
4. Traditional ecological knowledge associated with Acacia senegal (Gum arabic tree) management and gum arabic production in northern Kenya
- Author
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WEKESA, C., MAKENZI, P. M., CHIKAMAI, B. N., LUVANDA, A. M., and MUGA, M. O.
- Published
- 2010
5. MPC-Based Arctan Droop Control Strategy of the Parallel Inverter System in an Islanded AC Microgrid
- Author
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Iyakaremye, J. D. D., primary, Nyakoe, G. N., additional, and Wekesa, C. W., additional
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- 2021
- Full Text
- View/download PDF
6. Vitamin B12 deficiency presenting as an acute confusional state: a case report and review of literature
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Kibirige, D, Wekesa, C, Kaddu-Mukasa, M, and Waiswa, M
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- 2013
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7. Evaluation of MPC-based arctan droop control strategy in islanded microgrid.
- Author
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Iyakaremye, J. D. D., Nyakoe, G. N., and Wekesa, C. W.
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MICROGRIDS ,RENEWABLE energy sources ,POWER sharing governments ,ELECTRIC inverters ,DYNAMIC loads - Abstract
The microgrid (MG) is an emerging technology for supplying energy from renewable energy sources (RES). Due to their intermittent nature, RES require an inverter and smooth operation control system when integrated into an MG. Conventional droop control is commonly used in microgrid control but cannot achieve adequate power-sharing when output impedances of inverters are different; thus, enhancing its performance is required. This paper's main objective is to design a finite control set model predictive control (FSC-MPC) based arctan droop control and evaluate its performance against the conventional droop control strategy. The proposed control technique guarantees a strong transient response when there is a dynamic load change during MG operation. The results showed that the proposed control strategy ensures proportionate power-sharing of paralleled voltage source inverters with unequal line impedances than the traditional droop controller, which can vary. [ABSTRACT FROM AUTHOR]
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- 2021
- Full Text
- View/download PDF
8. with Ascites
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Facciorusso, A, Roy, S, Livadas, S, Fevrier-Paul, A, Wekesa, C, Kilic, ID, Chaurasia, AK, Sadeq, M, and Muscatiello, N
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NSBB ,Cirrhosis ,Mortality ,Hazard ratio - Abstract
The role of nonselective beta-blockers in cirrhotic patients with ascites has been recently questioned; however, definitive evidence in this regard is still lacking. To analyze published data on the influence of nonselective beta-blockers as compared to control group on survival of cirrhotic patients with ascites. Computerized bibliographic search on the main databases was performed. Hazard ratios from Kaplan-Meier curves were extracted in order to perform an unbiased comparison of survival estimates. Secondary outcomes were mortality in patients with refractory ascites, pooled rate of nonselective beta-blockers interruption, spontaneous bacterial peritonitis and hepato-renal syndrome incidence. Three randomized controlled trials and 13 observational studies with 8279 patients were included. Overall survival was comparable between the two groups (hazard ratio = 0.86, 0.71-1.03, p = 0.11). Study design resulted as the main source of heterogeneity in sensitivity analysis and meta-regression. Mortality in refractory ascites patients was similar in the two groups (odds ratio = 0.90, 0.45-1.79; p = 0.76). No difference in spontaneous bacterial peritonitis (odds ratio = 0.78, 0.47-1.29, p = 0.33) and hepato-renal syndrome incidence (odds ratio = 1.22, 0.48-3.09; p = 0.67) was observed. Pooled rate of nonselective beta-blockers interruption was 18.6% (5.2-32.1%). Based on our findings, nonselective beta-blockers should not be routinely withheld in patients with cirrhosis and ascites, even if refractory.
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- 2018
9. Nonselective Beta-Blockers Do Not Affect Survival in Cirrhotic Patients with Ascites
- Author
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Facciorusso AAUID- ORCID: 0000-0002-2107-2156, Roy S, Livadas S, Fevrier-Paul A, Wekesa C, Kilic ID, Chaurasia AK, Sadeq M, and Muscatiello N
- Subjects
Adrenergic beta-Antagonists/adverse effects/*therapeutic use ,Ascites/*drug therapy/etiology/mortality ,Chi-Square Distribution ,Hepatorenal Syndrome/etiology/mortality ,Humans ,Incidence ,Kaplan-Meier Estimate ,Liver Cirrhosis/complications/*drug therapy/mortality ,Odds Ratio ,Peritonitis/microbiology/mortality ,Risk Factors ,Time Factors ,Treatment Outcome - Abstract
BACKGROUND: The role of nonselective beta-blockers in cirrhotic patients with ascites has been recently questioned; however, definitive evidence in this regard is still lacking. AIMS: To analyze published data on the influence of nonselective beta-blockers as compared to control group on survival of cirrhotic patients with ascites. METHODS: Computerized bibliographic search on the main databases was performed. Hazard ratios from Kaplan-Meier curves were extracted in order to perform an unbiased comparison of survival estimates. Secondary outcomes were mortality in patients with refractory ascites, pooled rate of nonselective beta-blockers interruption, spontaneous bacterial peritonitis and hepato-renal syndrome incidence. RESULTS: Three randomized controlled trials and 13 observational studies with 8279 patients were included. Overall survival was comparable between the two groups (hazard ratio = 0.86, 0.71-1.03, p = 0.11). Study design resulted as the main source of heterogeneity in sensitivity analysis and meta-regression. Mortality in refractory ascites patients was similar in the two groups (odds ratio = 0.90, 0.45-1.79; p = 0.76). No difference in spontaneous bacterial peritonitis (odds ratio = 0.78, 0.47-1.29, p = 0.33) and hepato-renal syndrome incidence (odds ratio = 1.22, 0.48-3.09; p = 0.67) was observed. Pooled rate of nonselective beta-blockers interruption was 18.6% (5.2-32.1%). CONCLUSIONS: Based on our findings, nonselective beta-blockers should not be routinely withheld in patients with cirrhosis and ascites, even if refractory.
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- 2018
10. Genetic Diversity of Fusarium Oxysporum Races Associated with Cowpea Fields in Kakamega County
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Ajanga S, Muyekho Fn, Wamalwa Eni, Wekesa C, and Muoma J
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Crop ,Fusarium ,Horticulture ,Genetic diversity ,biology ,Disease management (agriculture) ,Fusarium oxysporum ,Phoma ,food and beverages ,Sorghum ,biology.organism_classification ,Mycelium - Abstract
Fusarium oxysporum is the most abundant and most damaging species of the genus Fusarium responsible forcrop wilt diseases in cultivated fields. It possess risk to production of banana, tomato, onions, beans, peas, palm,wheat, sorghum, maize, potatoes, garlic and cowpea among others. Fusarium involves several species that producemycotoxins associated with serious animal diseases. Fusarium is a potential threat to global food security.Furthermore, disease incidence of pathogenic Fusarium species could increase due to the effects of the predictedglobal changes. Limitation of occurrence records and diversity of the races of F. oxysporum in Kakamega Countynecessitated this study. This study aimed to characterize strains of Fusarium pathogens in cowpea fields ofKakamega County. The colonies had sparse to abundant mycelia with colour ranging from white to pale violet. Theisolates gave rise to elliptical microchonidia without septa, smooth walled terminal and intercalary chlamydosporesat times singly and paired in some cases on microscopy. Further, PCR amplification of ITS gene region in the tenisolates of F. oxysporum was performed using universal ITS primers. Fusarium the genus was amplified as afragment of about 500 bp corresponding to the region between the 18S-28S rRNA intervening sequence forFusarium spp. The selected isolates of Fusarium spp. were sequenced and submitted in NCBI database with theaccession numbers of KY855504, KY855505, KY855506, KY855507, KY855508, KY855509, KY855510, KY855511,KY855512, KY855513 and KY855514. Eight soil-borne fungal isolates [KY855505, KY855506, KY855507,KY855508, KY855510, KY855511, KY855512 and KY855514] were identified as F. oxysporum based on its cultural,morphological and molecular characteristics. KY855504 and KY855509 had molecular identity to Ascotamycota andKY855513 had the molecular identity of Phoma sp. This study contributes knowledge on genetic diversity of localpathogenic Fusarium strains useful in crop breeding and disease management of cowpea crop in KakamegaCounty, Kenya
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- 2018
11. Traditional ecological knowledge associated withAcacia senegal(Gum arabic tree) management and gum arabic production in northern Kenya
- Author
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Wekesa, C, primary, Makenzi, P. M, additional, Chikamai, B. N, additional, Luvanda, A. M, additional, and Muga, M. O, additional
- Published
- 2010
- Full Text
- View/download PDF
12. Traditional ecological knowledge associated with Acacia senegal(Gum arabic tree) management and gum arabic production in northern Kenya
- Author
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Wekesa, C, Makenzi, P. M, Chikamai, B. N, Luvanda, A. M, and Muga, M. O
- Abstract
This study documented traditional ecological knowledge (TEK) on the management of Acacia senegal trees (Gum arabic trees) using a structured questionnaire. A total of 149 randomly selected respondents from six locations in two districts of Samburu (Rift valley Province) and Isiolo (Eastern Province) were interviewed. Results show that local communities use their indigenous knowledge to manage natural gum arabic tree resources to sustain and improve their livelihoods. Restriction to the collection of only dead and fallen wood, community by-laws and nomadism were the main conservation strategies employed by the locals to protect gum arabic trees. Collection of gum arabic from wild gum arabic trees was mainly done by women during the dry months of the year. June to September season yielded higher quantities of gum arabic than the January to March season. More gum arabic was collected from gum arabic trees located on hilly and rocky sites than on plain and flat areas and along riverbanks. Small sized trees with small girth were prefered to big trees with a wide girth during gum arabic collection. Apart from harvesting gum arabic from the trees and selling it to earn cash income, the local communities got fodder, fuel wood, traditional medicine, fencing material and fiber from the trees. Besides, gum arabic is used as food during hunger season. There is strong evidence that TEK is a useful concept for sustainable management of gum arabic trees and could be used in designing of sustainable conservation and exploitation strategies of gum arabic trees and consequently environmental conservation.
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- 2010
13. MPC-Based Arctan Droop Control Strategy of the Parallel Inverter System in an Islanded AC Microgrid
- Author
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D. D. Iyakaremye, J., N. Nyakoe, G., and W. Wekesa, C.
- Abstract
Distributed generations (DG) are one of the upcoming technologies recently used by many electric utilities in all corners of the world. Most of those DG form the microgrid (MG) to serve local loads and can be connected to the grid. This DG’s technology is enabled by utilizing renewable energy sources (REs) that are ecofriendly; however, these REs are intermittent by their nature, so controlling a power electronic device interfaced with them to be connected to the grid is another challenge. Many researchers have worked on the inverters’ control in MG. This study also elaborates on the control strategy for inverters adapted to REs for proper control of voltage and frequency used in an islanded microgrid. The study proposes a hybrid control strategy made of the virtual impedance droop control with arctan function and model predictive control. Extensive simulations have been carried out to validate the proposed control strategy’s effectiveness in terms of rapid transient response and stabilization of voltage, frequency, and power equitability among the microsources in the islanded microgrid.
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- 2021
- Full Text
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14. Co-limitation towards lower latitudes shapes global forest diversity gradients
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Jingjing Liang, Javier G. P. Gamarra, Nicolas Picard, Mo Zhou, Bryan Pijanowski, Douglass F. Jacobs, Peter B. Reich, Thomas W. Crowther, Gert-Jan Nabuurs, Sergio de-Miguel, Jingyun Fang, Christopher W. Woodall, Jens-Christian Svenning, Tommaso Jucker, Jean-Francois Bastin, Susan K. Wiser, Ferry Slik, Bruno Hérault, Giorgio Alberti, Gunnar Keppel, Geerten M. Hengeveld, Pierre L. Ibisch, Carlos A. Silva, Hans ter Steege, Pablo L. Peri, David A. Coomes, Eric B. Searle, Klaus von Gadow, Bogdan Jaroszewicz, Akane O. Abbasi, Meinrad Abegg, Yves C. Adou Yao, Jesús Aguirre-Gutiérrez, Angelica M. Almeyda Zambrano, Jan Altman, Esteban Alvarez-Dávila, Juan Gabriel Álvarez-González, Luciana F. Alves, Bienvenu H. K. Amani, Christian A. Amani, Christian Ammer, Bhely Angoboy Ilondea, Clara Antón-Fernández, Valerio Avitabile, Gerardo A. Aymard, Akomian F. Azihou, Johan A. Baard, Timothy R. Baker, Radomir Balazy, Meredith L. Bastian, Rodrigue Batumike, Marijn Bauters, Hans Beeckman, Nithanel Mikael Hendrik Benu, Robert Bitariho, Pascal Boeckx, Jan Bogaert, Frans Bongers, Olivier Bouriaud, Pedro H. S. Brancalion, Susanne Brandl, Francis Q. Brearley, Jaime Briseno-Reyes, Eben N. Broadbent, Helge Bruelheide, Erwin Bulte, Ann Christine Catlin, Roberto Cazzolla Gatti, Ricardo G. César, Han Y. H. Chen, Chelsea Chisholm, Emil Cienciala, Gabriel D. Colletta, José Javier Corral-Rivas, Anibal Cuchietti, Aida Cuni-Sanchez, Javid A. Dar, Selvadurai Dayanandan, Thales de Haulleville, Mathieu Decuyper, Sylvain Delabye, Géraldine Derroire, Ben DeVries, John Diisi, Tran Van Do, Jiri Dolezal, Aurélie Dourdain, Graham P. Durrheim, Nestor Laurier Engone Obiang, Corneille E. N. Ewango, Teresa J. Eyre, Tom M. Fayle, Lethicia Flavine N. Feunang, Leena Finér, Markus Fischer, Jonas Fridman, Lorenzo Frizzera, André L. de Gasper, Damiano Gianelle, Henry B. Glick, Maria Socorro Gonzalez-Elizondo, Lev Gorenstein, Richard Habonayo, Olivier J. Hardy, David J. Harris, Andrew Hector, Andreas Hemp, Martin Herold, Annika Hillers, Wannes Hubau, Thomas Ibanez, Nobuo Imai, Gerard Imani, Andrzej M. Jagodzinski, Stepan Janecek, Vivian Kvist Johannsen, Carlos A. Joly, Blaise Jumbam, Banoho L. P. R. Kabelong, Goytom Abraha Kahsay, Viktor Karminov, Kuswata Kartawinata, Justin N. Kassi, Elizabeth Kearsley, Deborah K. Kennard, Sebastian Kepfer-Rojas, Mohammed Latif Khan, John N. Kigomo, Hyun Seok Kim, Carine Klauberg, Yannick Klomberg, Henn Korjus, Subashree Kothandaraman, Florian Kraxner, Amit Kumar, Relawan Kuswandi, Mait Lang, Michael J. Lawes, Rodrigo V. Leite, Geoffrey Lentner, Simon L. Lewis, Moses B. Libalah, Janvier Lisingo, Pablito Marcelo López-Serrano, Huicui Lu, Natalia V. Lukina, Anne Mette Lykke, Vincent Maicher, Brian S. Maitner, Eric Marcon, Andrew R. Marshall, Emanuel H. Martin, Olga Martynenko, Faustin M. Mbayu, Musingo T. E. Mbuvi, Jorge A. Meave, Cory Merow, Stanislaw Miscicki, Vanessa S. Moreno, Albert Morera, Sharif A. Mukul, Jörg C. Müller, Agustinus Murdjoko, Maria Guadalupe Nava-Miranda, Litonga Elias Ndive, Victor J. Neldner, Radovan V. Nevenic, Louis N. Nforbelie, Michael L. Ngoh, Anny E. N’Guessan, Michael R. Ngugi, Alain S. K. Ngute, Emile Narcisse N. Njila, Melanie C. Nyako, Thomas O. Ochuodho, Jacek Oleksyn, Alain Paquette, Elena I. Parfenova, Minjee Park, Marc Parren, Narayanaswamy Parthasarathy, Sebastian Pfautsch, Oliver L. Phillips, Maria T. F. Piedade, Daniel Piotto, Martina Pollastrini, Lourens Poorter, John R. Poulsen, Axel Dalberg Poulsen, Hans Pretzsch, Mirco Rodeghiero, Samir G. Rolim, Francesco Rovero, Ervan Rutishauser, Khosro Sagheb-Talebi, Purabi Saikia, Moses Nsanyi Sainge, Christian Salas-Eljatib, Antonello Salis, Peter Schall, Dmitry Schepaschenko, Michael Scherer-Lorenzen, Bernhard Schmid, Jochen Schöngart, Vladimír Šebeň, Giacomo Sellan, Federico Selvi, Josep M. Serra-Diaz, Douglas Sheil, Anatoly Z. Shvidenko, Plinio Sist, Alexandre F. Souza, Krzysztof J. Stereńczak, Martin J. P. Sullivan, Somaiah Sundarapandian, Miroslav Svoboda, Mike D. Swaine, Natalia Targhetta, Nadja Tchebakova, Liam A. Trethowan, Robert Tropek, John Tshibamba Mukendi, Peter Mbanda Umunay, Vladimir A. Usoltsev, Gaia Vaglio Laurin, Riccardo Valentini, Fernando Valladares, Fons van der Plas, Daniel José Vega-Nieva, Hans Verbeeck, Helder Viana, Alexander C. Vibrans, Simone A. Vieira, Jason Vleminckx, Catherine E. Waite, Hua-Feng Wang, Eric Katembo Wasingya, Chemuku Wekesa, Bertil Westerlund, Florian Wittmann, Verginia Wortel, Tomasz Zawiła-Niedźwiecki, Chunyu Zhang, Xiuhai Zhao, Jun Zhu, Xiao Zhu, Zhi-Xin Zhu, Irie C. Zo-Bi, Cang Hui, Liang, Jingjing, Gamarra, Javier GP, Picard, Nicolas, Zhou, Mo, Keppel, Gunnar, Hui, Cang, Liang J., Gamarra J.G.P., Picard N., Zhou M., Pijanowski B., Jacobs D.F., Reich P.B., Crowther T.W., Nabuurs G.-J., de-Miguel S., Fang J., Woodall C.W., Svenning J.-C., Jucker T., Bastin J.-F., Wiser S.K., Slik F., Herault B., Alberti G., Keppel G., Hengeveld G.M., Ibisch P.L., Silva C.A., ter Steege H., Peri P.L., Coomes D.A., Searle E.B., von Gadow K., Jaroszewicz B., Abbasi A.O., Abegg M., Yao Y.C.A., Aguirre-Gutierrez J., Zambrano A.M.A., Altman J., Alvarez-Davila E., Alvarez-Gonzalez J.G., Alves L.F., Amani B.H.K., Amani C.A., Ammer C., Ilondea B.A., Anton-Fernandez C., Avitabile V., Aymard G.A., Azihou A.F., Baard J.A., Baker T.R., Balazy R., Bastian M.L., Batumike R., Bauters M., Beeckman H., Benu N.M.H., Bitariho R., Boeckx P., Bogaert J., Bongers F., Bouriaud O., Brancalion P.H.S., Brandl S., Brearley F.Q., Briseno-Reyes J., Broadbent E.N., Bruelheide H., Bulte E., Catlin A.C., Cazzolla Gatti R., Cesar R.G., Chen H.Y.H., Chisholm C., Cienciala E., Colletta G.D., Corral-Rivas J.J., Cuchietti A., Cuni-Sanchez A., Dar J.A., Dayanandan S., de Haulleville T., Decuyper M., Delabye S., Derroire G., DeVries B., Diisi J., Do T.V., Dolezal J., Dourdain A., Durrheim G.P., Obiang N.L.E., Ewango C.E.N., Eyre T.J., Fayle T.M., Feunang L.F.N., Finer L., Fischer M., Fridman J., Frizzera L., de Gasper A.L., Gianelle D., Glick H.B., Gonzalez-Elizondo M.S., Gorenstein L., Habonayo R., Hardy O.J., Harris D.J., Hector A., Hemp A., Herold M., Hillers A., Hubau W., Ibanez T., Imai N., Imani G., Jagodzinski A.M., Janecek S., Johannsen V.K., Joly C.A., Jumbam B., Kabelong B.L.P.R., Kahsay G.A., Karminov V., Kartawinata K., Kassi J.N., Kearsley E., Kennard D.K., Kepfer-Rojas S., Khan M.L., Kigomo J.N., Kim H.S., Klauberg C., Klomberg Y., Korjus H., Kothandaraman S., Kraxner F., Kumar A., Kuswandi R., Lang M., Lawes M.J., Leite R.V., Lentner G., Lewis S.L., Libalah M.B., Lisingo J., Lopez-Serrano P.M., Lu H., Lukina N.V., Lykke A.M., Maicher V., Maitner B.S., Marcon E., Marshall A.R., Martin E.H., Martynenko O., Mbayu F.M., Mbuvi M.T.E., Meave J.A., Merow C., Miscicki S., Moreno V.S., Morera A., Mukul S.A., Muller J.C., Murdjoko A., Nava-Miranda M.G., Ndive L.E., Neldner V.J., Nevenic R.V., Nforbelie L.N., Ngoh M.L., N'Guessan A.E., Ngugi M.R., Ngute A.S.K., Njila E.N.N., Nyako M.C., Ochuodho T.O., Oleksyn J., Paquette A., Parfenova E.I., Park M., Parren M., Parthasarathy N., Pfautsch S., Phillips O.L., Piedade M.T.F., Piotto D., Pollastrini M., Poorter L., Poulsen J.R., Poulsen A.D., Pretzsch H., Rodeghiero M., Rolim S.G., Rovero F., Rutishauser E., Sagheb-Talebi K., Saikia P., Sainge M.N., Salas-Eljatib C., Salis A., Schall P., Schepaschenko D., Scherer-Lorenzen M., Schmid B., Schongart J., Seben V., Sellan G., Selvi F., Serra-Diaz J.M., Sheil D., Shvidenko A.Z., Sist P., Souza A.F., Sterenczak K.J., Sullivan M.J.P., Sundarapandian S., Svoboda M., Swaine M.D., Targhetta N., Tchebakova N., Trethowan L.A., Tropek R., Mukendi J.T., Umunay P.M., Usoltsev V.A., Vaglio Laurin G., Valentini R., Valladares F., van der Plas F., Vega-Nieva D.J., Verbeeck H., Viana H., Vibrans A.C., Vieira S.A., Vleminckx J., Waite C.E., Wang H.-F., Wasingya E.K., Wekesa C., Westerlund B., Wittmann F., Wortel V., Zawila-Niedzwiecki T., Zhang C., Zhao X., Zhu J., Zhu X., Zhu Z.-X., Zo-Bi I.C., Hui C., Purdue University [West Lafayette], Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Groupement d'Interêt Public Ecosystèmes Forestiers GIP ECOFOR (GIP ECOFOR ), Forêts et Sociétés (UPR Forêts et Sociétés), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Département Environnements et Sociétés (Cirad-ES), Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Montpellier (UM), SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National Polytechnique Félix Houphouët-Boigny, and Stellenbosch University
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Bos- en Landschapsecologie ,WASS ,Plant Ecology and Nature Conservation ,Forests ,[SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy ,Co-limitation ,Ontwikkelingseconomie ,Forest and Nature Conservation Policy ,Trees ,Soil ,[SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems ,Development Economics ,Laboratory of Geo-information Science and Remote Sensing ,Settore BIO/07 - ECOLOGIA ,Life Science ,Laboratorium voor Moleculaire Biologie ,Bos- en Natuurbeleid ,Forest and Landscape Ecology ,Bosecologie en Bosbeheer ,Laboratorium voor Geo-informatiekunde en Remote Sensing ,BIOS Plant Development Systems ,Vegetatie ,Ecology, Evolution, Behavior and Systematics ,biogeography ,biodiversity ,Vegetation ,Ecology ,Biodiversity ,[SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics ,Latitudinal gradients ,PE&RC ,Forest Ecology and Forest Management ,Bioclimatic dominance ,Biogeography ,LATITUDE ,Plantenecologie en Natuurbeheer ,Vegetatie, Bos- en Landschapsecologie ,Vegetation, Forest and Landscape Ecology ,Laboratory of Molecular Biology ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology ,Corporate Governance & Legal Services ,Tree ,Global LDG - Abstract
The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers. The team collaboration and manuscript development are supported by the web-based team science platform: science-i.org, with the project number 202205GFB2. We thank the following initiatives, agencies, teams and individuals for data collection and other technical support: the Global Forest Biodiversity Initiative (GFBI) for establishing the data standards and collaborative framework; United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program; University of Alaska Fairbanks; the SODEFOR, Ivory Coast; University Félix Houphouët-Boigny (UFHB, Ivory Coast); the Queensland Herbarium and past Queensland Government Forestry and Natural Resource Management departments and staff for data collection for over seven decades; and the National Forestry Commission of Mexico (CONAFOR). We thank M. Baker (Carbon Tanzania), together with a team of field assistants (Valentine and Lawrence); all persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3); the French National Forest Inventory (NFI campaigns (raw data 2005 and following annual surveys, were downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159; site accessed on 1 January 2015)); the Italian Forest Inventory (NFI campaigns raw data 2005 and following surveys were downloaded by GFBI at https://inventarioforestale.org/; site accessed on 27 April 2019); Swiss National Forest Inventory, Swiss Federal Institute for Forest, Snow and Landscape Research WSL and Federal Office for the Environment FOEN, Switzerland; the Swedish NFI, Department of Forest Resource Management, Swedish University of Agricultural Sciences SLU; the National Research Foundation (NRF) of South Africa (89967 and 109244) and the South African Research Chair Initiative; the Danish National Forestry, Department of Geosciences and Natural Resource Management, UCPH; Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES, grant number 88881.064976/2014-01); R. Ávila and S. van Tuylen, Instituto Nacional de Bosques (INAB), Guatemala, for facilitating Guatemalan data; the National Focal Center for Forest condition monitoring of Serbia (NFC), Institute of Forestry, Belgrade, Serbia; the Thünen Institute of Forest Ecosystems (Germany) for providing National Forest Inventory data; the FAO and the United Nations High Commissioner for Refugees (UNHCR) for undertaking the SAFE (Safe Access to Fuel and Energy) and CBIT-Forest projects; and the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network (AfriTRON) and the ForestPlots.net initiative for their contributions from Amazonian and African forests. The Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment are provided by the New Zealand National Vegetation Survey Databank https://nvs.landcareresearch.co.nz/. We thank the International Boreal Forest Research Association (IBFRA); the Forestry Corporation of New South Wales, Australia; the National Forest Directory of the Ministry of Environment and Sustainable Development of the Argentine Republic (MAyDS) for the plot data of the Second National Forest Inventory (INBN2); the National Forestry Authority and Ministry of Water and Environment of Uganda for their National Biomass Survey (NBS) dataset; and the Sabah Biodiversity Council and the staff from Sabah Forest Research Centre. All TEAM data are provided by the Tropical Ecology Assessment and Monitoring (TEAM) Network, a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors, with thanks to all current and previous TEAM site manager and other collaborators that helped collect data. We thank the people of the Redidoti, Pierrekondre and Cassipora village who were instrumental in assisting with the collection of data and sharing local knowledge of their forest and the dedicated members of the field crew of Kabo 2012 census. We are also thankful to FAPESC, SFB, FAO and IMA/SC for supporting the IFFSC. This research was supported in part through computational resources provided by Information Technology at Purdue, West Lafayette, Indiana.This work is supported in part by the NASA grant number 12000401 ‘Multi-sensor biodiversity framework developed from bioacoustic and space based sensor platforms’ (J. Liang, B.P.); the USDA National Institute of Food and Agriculture McIntire Stennis projects 1017711 (J. Liang) and 1016676 (M.Z.); the US National Science Foundation Biological Integration Institutes grant NSF‐DBI‐2021898 (P.B.R.); the funding by H2020 VERIFY (contract 776810) and H2020 Resonate (contract 101000574) (G.-J.N.); the TEAM project in Uganda supported by the Moore foundation and Buffett Foundation through Conservation International (CI) and Wildlife Conservation Society (WCS); the Danish Council for Independent Research | Natural Sciences (TREECHANGE, grant 6108- 00078B) and VILLUM FONDEN grant number 16549 (J.-C.S.); the Natural Environment Research Council of the UK (NERC) project NE/T011084/1 awarded to J.A.-G. and NE/S011811/1; ERC Advanced Grant 291585 (‘T-FORCES’) and a Royal Society-Wolfson Research Merit Award (O.L.P.); RAINFOR plots supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council, notably NERC Consortium Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘BIO-RED’ (NE/N012542/1); CIFOR’s Global Comparative Study on REDD+ funded by the Norwegian Agency for Development Cooperation, the Australian Department of Foreign Affairs and Trade, the European Union, the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) and donors to the CGIAR Fund; AfriTRON network plots funded by the local communities and NERC, ERC, European Union, Royal Society and Leverhume Trust; a grant from the Royal Society and the Natural Environment Research Council, UK (S.L.L.); National Science Foundation CIF21 DIBBs: EI: number 1724728 (A.C.C.); National Natural Science Foundation of China (31800374) and Shandong Provincial Natural Science Foundation (ZR2019BC083) (H.L.). UK NERC Independent Research Fellowship (grant code: NE/S01537X/1) (T.J.); a Serra-Húnter Fellowship provided by the Government of Catalonia (Spain) (S.d.-M.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.A.S.); a grant from the Franklinia Foundation (D.A.C.); Russian Science Foundation project number 19-77-300-12 (R.V.); the Takenaka Scholarship Foundation (A.O.A.); the German Research Foundation (DFG), grant number Am 149/16-4 (C.A.); the Romania National Council for Higher Education Funding, CNFIS, project number CNFIS-FDI-2022-0259 (O.B.); Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-05109 and STPGP506284) and the Canadian Foundation for Innovation (36014) (H.Y.H.C.); the project SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797) (E.C.); Consejo de Ciencia y Tecnología del estado de Durango (2019-01-155) (J.J.C.-R.); Science and Engineering Research Board (SERB), New Delhi, Government of India (file number PDF/2015/000447)— ‘Assessing the carbon sequestration potential of different forest types in Central India in response to climate change’ (J.A.D.); Investissement d’avenir grant of the ANR (CEBA: ANR-10-LABEX-0025) (G.D.); National Foundation for Science & Technology Development of Vietnam, 106-NN.06-2013.01 (T.V.D.); Queensland government, Department of Environment and Science (T.J.E.); a Czech Science Foundation Standard grant (19-14620S) (T.M.F.); European Union Seventh Framework Program (FP7/2007– 2013) under grant agreement number 265171 (L. Finer, M. Pollastrini, F. Selvi); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (J.F.); CNPq productivity grant number 311303/2020-0 (A.L.d.G.); DFG grant HE 2719/11-1,2,3; HE 2719/14-1 (A. Hemp); European Union’s Horizon Europe research project OpenEarthMonitor grant number 101059548, CGIAR Fund INIT-32-MItigation and Transformation Initiative for GHG reductions of Agrifood systems RelaTed Emissions (MITIGATE+) (M.H.); General Directorate of the State Forests, Poland (1/07; OR-2717/3/11; OR.271.3.3.2017) and the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (A.M.J.); Czech Science Foundation 18-10781 S (S.J.); Danish of Ministry of Environment, the Danish Environmental Protection Agency, Integrated Forest Monitoring Program—NFI (V.K.J.); State of São Paulo Research Foundation/FAPESP as part of the BIOTA/FAPESP Program Project Functional Gradient-PELD/BIOTA-ECOFOR 2003/12595-7 & 2012/51872-5 (C.A.J.); Danish Council for Independent Research—social sciences—grant DFF 6109– 00296 (G.A.K.); Russian Science Foundation project 21-46-07002 for the plot data collected in the Krasnoyarsk region (V.K.); BOLFOR (D.K.K.); Department of Biotechnology, New Delhi, Government of India (grant number BT/PR7928/ NDB/52/9/2006, dated 29 September 2006) (M.L.K.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (J.N.K.); Korea Forest Service (2018113A00-1820-BB01, 2013069A00-1819-AA03, and 2020185D10- 2022-AA02) and Seoul National University Big Data Institute through the Data Science Research Project 2016 (H.S.K.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.K.); CSIR, New Delhi, government of India (grant number 38(1318)12/EMR-II, dated: 3 April 2012) (S.K.); Department of Biotechnology, New Delhi, government of India (grant number BT/ PR12899/ NDB/39/506/2015 dated 20 June 2017) (A.K.); Coordination for the Improvement of Higher Education Personnel (CAPES) #88887.463733/2019-00 (R.V.L.); National Natural Science Foundation of China (31800374) (H.L.); project of CEPF RAS ‘Methodological approaches to assessing the structural organization and functioning of forest ecosystems’ (AAAA-A18-118052590019-7) funded by the Ministry of Science and Higher Education of Russia (N.V.L.); Leverhulme Trust grant to Andrew Balmford, Simon Lewis and Jon Lovett (A.R.M.); Russian Science Foundation, project 19-77-30015 for European Russia data processing (O.M.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (M.T.E.M.); the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (S.M.); the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund (A. Morera); Queensland government, Department of Environment and Science (V.J.N.); Pinnacle Group Cameroon PLC (L.N.N.); Queensland government, Department of Environment and Science (M.R.N.); the Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05201) (A.P.); the Russian Foundation for Basic Research, project number 20-05-00540 (E.I.P.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 778322 (H.P.); Science and Engineering Research Board, New Delhi, government of India (grant number YSS/2015/000479, dated 12 January 2016) (P.S.); the Chilean Government research grants Fondecyt number 1191816 and FONDEF number ID19 10421 (C.S.-E.); the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 Biodiversity Exploratories (P.S.); European Space Agency projects IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) (D. Schepaschenko); FunDivEUROPE, European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 265171 (M.S.-L.); APVV 20-0168 from the Slovak Research and Development Agency (V.S.); Manchester Metropolitan University’s Environmental Science Research Centre (G.S.); the project ‘LIFE+ ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques’ which is co-funded by the EU Life Plus programme (contract number LIFE13 ENV/PL/000048) and the National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D) (K.J.S.); Global Challenges Research Fund (QR allocation, MMU) (M.J.P.S.); Czech Science Foundation project 21-27454S (M.S.); the Russian Foundation for Basic Research, project number 20-05-00540 (N. Tchebakova); Botanical Research Fund, Coalbourn Trust, Bentham Moxon Trust, Emily Holmes scholarship (L.A.T.); the programmes of the current scientific research of the Botanical Garden of the Ural Branch of Russian Academy of Sciences (V.A.U.); FCT—Portuguese Foundation for Science and Technology—Project UIDB/04033/2020. Inventário Florestal Nacional—ICNF (H. Viana); Grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (C.W.); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (B.W.); ATTO project (grant number MCTI-FINEP 1759/10 and BMBF 01LB1001A, 01LK1602F) (F.W.); ReVaTene/ PReSeD-CI 2 is funded by the Education and Research Ministry of Côte d’Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD (I.C.Z.-B.); the National Research Foundation of South Africa (NRF, grant 89967) (C.H.). The Tropical Plant Exploration Group 70 1 ha plots in Continental Cameroon Mountains are supported by Rufford Small Grant Foundation, UK and 4 ha in Sierra Leone are supported by the Global Challenge Research Fund through Manchester Metropolitan University, UK; the National Geographic Explorer Grant, NGS-53344R-18 (A.C.-S.); University of KwaZulu-Natal Research Office grant (M.J.L.); Universidad Nacional Autónoma de México, Dirección General de Asuntos de Personal Académico, Grant PAPIIT IN-217620 (J.A.M.). Czech Science Foundation project 21-24186M (R.T., S. Delabye). Czech Science Foundation project 20-05840Y, the Czech Ministry of Education, Youth and Sports (LTAUSA19137) and the long-term research development project of the Czech Academy of Sciences no. RVO 67985939 (J.A.). The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (grant number 0452995) and the Wenner-Gren Foundation for Anthropological Research (grant number 7330) (M.B.). Research grants from Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq, Brazil) (309764/2019; 311303/2020) (A.C.V., A.L.G.). The Project of Sanya Yazhou Bay Science and Technology City (grant number CKJ-JYRC-2022-83) (H.-F.W.). The Ugandan NBS was supported with funds from the Forest Carbon Partnership Facility (FCPF), the Austrian Development Agency (ADC) and FAO. FAO’s UN-REDD Program, together with the project on ‘Native Forests and Community’ Loan BIRF number 8493-AR UNDP ARG/15/004 and the National Program for the Protection of Native Forests under UNDP funded Argentina’s INBN2.
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- 2022
15. Molecular Footprints of Potato Virus Y Isolate Infecting Potatoes ( Solanum tuberosum ) in Kenya.
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Nyakio M, Were M, Wekesa C, Lungayia H, Okoth P, and Were H
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Potato virus Y (PVY) is a highly diverse and genetically variable virus with various strains. Differential evolutionary routes have been reported in the genus Potyvirus, caused by natural selection pressure, mutation, and recombination, with their virulence being dependent on different environmental conditions. Despite its significance and economic impact on Solanaceous species, the understanding of PVY's phylogeography in Kenya remains limited and inadequately documented. The study centers on the molecular characterization of a Kenyan PVY isolate, GenBank accession number PP069009. In-depth phylogenetic analysis unveiled a strong evolutionary association between the Kenyan isolate and isolate [JQ924287] from the United States of America, supported by a robust 92% probability. Recombinant analyses exposed a mosaic-like genetic architecture within the Kenyan isolate, indicating multiple gene recombination events. Selection pressure scrutiny identified specific sites under selective pressure, with evidence of positive/diversifying and negative/purifying selection. Population genetics analysis revealed a calculated nucleotide diversity ( π ) of 0.00354881, while analysis of molecular variance (AMOVA) unveiled a structured genetic landscape with an øST value of 0.45224. The extensive haplotype network depicted the possibility of diverse PVY strains occurring across continents. This analysis provides valuable insights into the genetic diversity and distribution of PVY globally, highlighting the importance of understanding evolutionary dynamics for effective management and control strategies of PVY on a global scale., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2024 Maryrose Nyakio et al.)
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- 2024
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16. The role of vegetation structural diversity in regulating the microclimate of human-modified tropical ecosystems.
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Terschanski J, Nunes MH, Aalto I, Pellikka P, Wekesa C, and Maeda EE
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- Trees, Humans, Temperature, Forests, Biodiversity, Kenya, Microclimate, Ecosystem, Climate Change, Tropical Climate
- Abstract
Vegetation regulates microclimate stability through biophysical mechanisms such as evaporation, transpiration and shading. Therefore, thermal conditions in tree-dominated habitats will frequently differ significantly from standardized free-air temperature measurements. The ability of forests to buffer temperatures nominates them as potential sanctuaries for tree species intolerant to the increasingly challenging thermal conditions established by climate change. Although many factors influencing thermal conditions beneath the vegetation cover have been ascertained, the role of three-dimensional vegetation structure in regulating the understory microclimate remains understudied. Recent advances in remote sensing technologies, such as terrestrial laser scanning, have allowed scientists to capture the three-dimensional structural heterogeneity of vegetation with a high level of accuracy. Here, we examined the relationships between vegetation structure parametrized from voxelized laser scanning point clouds, air and soil temperature ranges, as well as offsets between field-measured temperatures and gridded free-air temperature estimates in 17 sites in a tropical mountain ecosystem in Southeast Kenya. Structural diversity generally exerted a cooling effect on understory temperatures, but vertical diversity and stratification explained more variation in the understory air and soil temperature ranges (30%-40%) than canopy cover (27%), plant area index (24%) and average stand height (23%). We also observed that the combined effects of stratification, canopy cover and elevation explained more than half of the variation (53%) in understory air temperature ranges. Stratification's attenuating effect was consistent across different levels of elevation. Temperature offsets between field measurements and free-air estimates were predominantly controlled by elevation, but stratification and structural diversity were influential predictors of maximum and median temperature offsets. Moreover, stable understory temperatures were strongly associated with a large offset in daytime maximum temperatures, suggesting that structural diversity primarily contributes to thermal stability by cooling daytime maximum temperatures. Our findings shed light on the thermal influence of vertical vegetation structure and, in the context of tropical land-use change, suggest that decision-makers aiming to mitigate the thermal impacts of land conversion should prioritize management practices that preserve structural diversity by retaining uneven-aged trees and mixing plant species of varying sizes, e.g., silvopastoral, or agroforestry systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
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- 2024
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17. Shotgun Metagenomic Analyses of Microbial Assemblages in the Aquatic Ecosystem of Winam Gulf of Lake Victoria, Kenya Reveals Multiclass Pollution.
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Khatiebi S, Kiprotich K, Onyando Z, Wekesa C, Chi CN, Mulambalah C, and Okoth P
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- Animals, Humans, Lakes, Ecosystem, Kenya, Plastics, Environmental Monitoring, Water, Pharmaceutical Preparations, Water Pollutants, Chemical analysis, Microbiota genetics
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Lake Victoria, the second-largest freshwater lake in the world, provides an important source of food and income, particularly fish for both domestic consumption and for export market. In recent years, Lake Victoria has suffered massive pollution from both industrial and wastewater discharge. Microplastic biomes, pharmaceutical residues, drugs of abuse, heavy metals, agrochemicals, and personal care products are ubiquitous in the aquatic ecosystem of Winam Gulf. These pollutants are known to alter microbial assemblages in aquatic ecosystems with far-reaching ramification including a calamitous consequence to human health. Indeed, some of these pollutants have been associated with human cancers and antimicrobial resistance. There is a paucity of data on the microbial profiles of this important but heavily polluted aquatic ecosystem. The current study sought to investigate the metagenomic profiles of microbial assemblages in the Winam Gulf ecosystem. Water and sediment samples were collected from several locations within the study sites. Total genomic DNA pooled from all sampling sites was extracted and analyzed by whole-genome shotgun sequencing. Analyses revealed three major kingdoms: bacteria, archaea and eukaryotes belonging to 3 phyla, 13 classes, 14 families, 9 orders, 14 genera, and 10 species. Proteobacteria , Betaproteobacteria , Comamonadaceae , Burkholdariales , and Arcobacter were the dominated phyla, class, family, order, genera, and species, respectively. The Kyoto Encyclopedia of Genes and Genomes indicated the highest number of genes involved in metabolism. The presence of carbohydrate metabolism genes and enzymes was used to infer organic pollutions from sewage and agricultural runoffs. Similarly, the presence of xylene and nutrotoluene degradation genes and enzyme was used to infer industrial pollution into the lake. Drug metabolism genes lend credence to the possibility of pharmaceutical pollutants in water. Taken together, there is a clear indication of massive pollution. In addition, carbohydrate-active enzymes were the most abundant and included genes in glycoside hydrolases. Shotgun metagenomic analyses conveyed an understanding of the microbial communities of the massively polluted aquatic ecosystem of Winam Gulf, Lake Vicoria, Kenya. The current study documents the presence of multiclass pollutants in Lake Victoria and reveals information that might be useful for a potential bioremediation strategy using the native microbial communities., Competing Interests: The authors declare no conflict of interest to the research, authorship, and publication of this manuscript., (Copyright © 2023 Sandra Khatiebi et al.)
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- 2023
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18. Molecular Characterization of Indigenous Rhizobia from Kenyan Soils Nodulating with Common Beans.
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Wekesa C, Kiprotich K, Okoth P, Asudi GO, Muoma JO, Furch ACU, and Oelmüller R
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- Kenya, Soil, Symbiosis genetics, Nitrogen, Rhizobium genetics, Phaseolus microbiology
- Abstract
Kenya is the seventh most prominent producer of common beans globally and the second leading producer in East Africa. However, the annual national productivity is low due to insufficient quantities of vital nutrients and nitrogen in the soils. Rhizobia are symbiotic bacteria that fix nitrogen through their interaction with leguminous plants. Nevertheless, inoculating beans with commercial rhizobia inoculants results in sparse nodulation and low nitrogen supply to the host plants because these strains are poorly adapted to the local soils. Several studies describe native rhizobia with much better symbiotic capabilities than commercial strains, but only a few have conducted field studies. This study aimed to test the competence of new rhizobia strains that we isolated from Western Kenya soils and for which the symbiotic efficiency was successfully determined in greenhouse experiments. Furthermore, we present and analyze the whole-genome sequence for a promising candidate for agricultural application, which has high nitrogen fixation features and promotes common bean yields in field studies. Plants inoculated with the rhizobial isolate S3 or with a consortium of local isolates (COMB), including S3, produced a significantly higher number of seeds and seed dry weight when compared to uninoculated control plants at two study sites. The performance of plants inoculated with commercial isolate CIAT899 was not significantly different from uninoculated plants ( p > 0.05), indicating tight competition from native rhizobia for nodule occupancy. Pangenome analysis and the overall genome-related indices showed that S3 is a member of R. phaseoli . However, synteny analysis revealed significant differences in the gene order, orientation, and copy numbers between S3 and the reference R. phaseoli. Isolate S3 is phylogenomically similar to R. phaseoli . However, it has undergone significant genome rearrangements (global mutagenesis) to adapt to harsh conditions in Kenyan soils. Its high nitrogen fixation ability shows optimal adaptation to Kenyan soils, and the strain can potentially replace nitrogenous fertilizer application. We recommend that extensive fieldwork in other parts of the country over a period of five years be performed on S3 to check on how the yield changes with varying whether conditions.
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- 2023
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19. Mutational signatures for breast cancer diagnosis using artificial intelligence.
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Odhiambo P, Okello H, Wakaanya A, Wekesa C, and Okoth P
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- Female, Humans, Artificial Intelligence, Genetic Predisposition to Disease, Mutation, Genes, BRCA2, Breast Neoplasms diagnosis, Breast Neoplasms genetics, Breast Neoplasms pathology
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Background: Breast cancer is the most common female cancer worldwide. Its diagnosis and prognosis remain scanty, imprecise, and poorly documented. Previous studies have indicated that some genetic mutational signatures are suspected to lead to progression of various breast cancer scenarios. There is paucity of data on the role of AI tools in delineating breast cancer mutational signatures. This study sought to investigate the relationship between breast cancer genetic mutational profiles using artificial intelligence models with a view to developing an accurate prognostic prediction based on breast cancer genetic signatures. Prior research on breast cancer has been based on symptoms, origin, and tumor size. It has not been investigated whether diagnosis of breast cancer can be made utilizing AI platforms like Cytoscape, Phenolyzer, and Geneshot with potential for better prognostic power. This is the first ever attempt for a combinatorial approach to breast cancer diagnosis using different AI platforms., Method: Artificial intelligence (AI) are mathematical algorithms that simulate human cognitive abilities and solve difficult healthcare issues such as complicated biological abnormalities like those experienced in breast cancer scenarios. The current models aimed to predict outcomes and prognosis by correlating imaging phenotypes with genetic mutations, tumor profiles, and hormone receptor status and development of imaging biomarkers that combine tumor and patient-specific features. Geneshotsav 2021, Cytoscape 3.9.1, and Phenolyzer Nature Methods, 12:841-843 (2015) tools, were used to mine breast cancer-associated mutational signatures and provided useful alternative computational tools for discerning pathways and enriched networks of genes of similarity with the overall goal of providing a systematic view of the variety of mutational processes that lead to breast cancer development. The development of novel-tailored pharmaceuticals, as well as the distribution of prospective treatment alternatives, would be aided by the collection of massive datasets and the use of such tools as diagnostic markers., Results: Specific DNA-maintenance defects, endogenous or environmental exposures, and cancer genomic signatures are connected. The PubMed database (Geneshot) search for the keywords yielded a total of 21,921 genes associated with breast cancer. Then, based on their propensity to result in gene mutations, the genes were screened using the Phenolyzer software. These platforms lend credence to the fact that breast cancer diagnosis using Cytoscape 3.9.1, Phenolyzer, and Geneshot 2021 reveals high profile of the following mutational signatures: BRCA1, BRCA2, TP53, CHEK2, PTEN, CDH1, BRIP1, RAD51C, CASP3, CREBBP, and SMAD3., (© 2023. The Author(s).)
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- 2023
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20. Comparing adherence to MDR-TB treatment among patients on self-administered therapy and those on directly observed therapy: non-inferiority randomized controlled trial.
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Wekesa C, Sekaggya-Wiltshire C, Muyanja SZ, Lume I, Nabaggala MS, Parkes-Ratanshi R, and Akello SA
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- Humans, Directly Observed Therapy, Treatment Outcome, Clinical Protocols, Medication Adherence, Antitubercular Agents adverse effects, Tuberculosis, Multidrug-Resistant diagnosis, Tuberculosis, Multidrug-Resistant drug therapy
- Abstract
Background: Adherence is key to the treatment success of multi-drug resistant tuberculosis (MDR-TB) and prevention of community transmission. Directly observed therapy (DOT) is the recommended approach for the management of patients with MDR-TB. Uganda implements a health facility-based DOT approach where all patients diagnosed with MDR-TB report to the nearest private or public health facility for daily observation of ingesting their medicines by a health care provider. Directly observed therapy is very costly for both the patient and health care system. It follows the assumption that MDR TB patients have a history of poor adherence to TB treatment. But only 21% of MDR-TB patients notified globally and 1.4-12% notified in Uganda had been previously treated for TB. The shift to all oral treatment regimen for MDR-TB provides an opportunity for the exploration of self-administered therapy for this group of patients even with use of remotely operated adherence technology. We are conducting a non-inferiority open-label randomized controlled trial to compare adherence to MDR-TB treatment among patients on self-administered therapy (measured by Medication Events Monitoring System (MEMS) technology) with a control group on DOT., Methods: We plan to enrol 164 newly diagnosed MDR-TB patients aged ≥ 8 years from three regional hospitals based in rural and urban Uganda. Patients with conditions that affect their dexterity and ability to operate the MEMS-operated medicine equipment will not be eligible to participate in the trial. Patients are randomized to either of the two study arms: self-administered therapy with adherence being monitored using MEMS technology (intervention arm) or health facility-based DOT (control arm) and will be followed up monthly. Adherence is measured by the number of days the medicine bottle is open to access medication as recorded by the MEMS software in the intervention arm and treatment complaint days as recorded in the TB treatment card in the control arm. The primary outcome is the comparison of adherence rates between the two study arms., Discussion: The evaluation of self-administered therapy for patients with MDR-TB is important to inform cost-effective management strategies for these patients. The approval of all oral regimens for the treatment of MDR-TB provides an opportunity for innovations such as MEMS technology to support sustainable options for MDR-TB treatment adherence support in low-resource settings., Trial Registration: Pan African Clinical Trials Registry, Cochrane #PACTR202205876377808. Retrospectively registered on 13 May 2022., (© 2023. The Author(s).)
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- 2023
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21. Whole Transcriptome Analysis of Differentially Expressed Genes in Cultured Nile Tilapia ( O. niloticus ) Subjected to Chronic Stress Reveals Signaling Pathways Associated with Depressed Growth.
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Mwaura JG, Wekesa C, Ogutu PA, and Okoth P
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- Animals, Ammonia, Gene Expression Profiling, Transcriptome genetics, Signal Transduction genetics, Cichlids genetics
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Chronic stress is a serious threat to aquaculture as it lowers fish growth performance and compromises fish welfare. The exact mechanism by which growth is retarded is, however, not clearly understood. This study sought to elucidate the gene expression profiles associated with chronic stress in cultured Nile tilapia ( Oreochromis niloticus ) reared for 70 days at different ammonia concentrations and stocking densities. Fish in the treatment groups showed negative growth, while the controls showed positive allometric growth. The specific condition factor (K
n ) ranged from 1.17 for the controls to 0.93 for the ammonia and 0.91 for the stocking density treatments. RNA was extracted from muscle tissue using TRIzol followed by library construction and Illumina sequencing. Comparative transcriptome analysis revealed 209 differentially expressed genes (DEGs) (156 up- and 53 down-regulated) in the ammonia and 252 DEGs (175 up- and 77 down-regulated) in the stocking density treatment. In both treatments, 24 and 17 common DEGs were up- and down-regulated, respectively. DEGs were significantly enriched in six pathways associated with muscle activity, energy mobilization and immunity. The heightened muscular activity consumes energy which would otherwise have been utilized for growth. These results bring to fore the molecular mechanisms underlying chronic stress' suppression of growth in cultured Nile tilapia.- Published
- 2023
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22. Molecular Characterization and Mineralizing Potential of Phosphorus Solubilizing Bacteria Colonizing Common Bean ( Phaseolus vulgaris L.) Rhizosphere in Western Kenya.
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Kiprotich K, Muoma J, Omayio DO, Ndombi TS, and Wekesa C
- Abstract
Phosphorus solubilizing bacteria (PSB) are a category of microbes that transform insoluble phosphates in soil into soluble forms that crops can utilize. Phosphorus in natural soils is abundant but poorly soluble. Hence, introducing PSB is a safer way of improving its solubility. The aim of this study was to genetically characterize and determine the mineralization capability of selected PSB colonizing rhizospheres of common beans in Western Kenya. Seven potential phosphorus solubilizing bacteria (PSB) were isolated from various subregions of Western Kenya. 16S ribosomal RNA gene sequencing and National Center for Biotechnology Information (NCBI), Basic Local Alignment Search Tool (BLAST) identified the isolates. The phosphate solubilization potential of the isolates was evaluated under agar and broth medium of National Botanical Research Institute's phosphate (NBRIP) supplemented with tricalcium calcium phosphate (TCP). Identified isolates were as follows: KK3 as Enterobacter mori , B5 (KB5) as Pseudomonas kribbensis , KV1 as Enterobacter asburiae , KB3 as Enterobacter mori, KK1 as Enterobacter cloacae , KBU as Enterobacter tabaci , and KB2 as Enterobacter bugandensis . The strains B5 and KV1 were the most effective phosphorus solubilizers with 4.16 and 3.64 indices, respectively. The microbes converted total soluble phosphate concentration in broth medium which was 1395 and 1471 P μ g/mL, respectively. The least performing isolate was KBU with a 2.34 solubility index. Significant ( p ≤ 0.05) differences in plant biomass for Rose coco and Mwitemania bean varieties were observed under inoculation with isolates B5 and KV1. PSB isolates found in common bean rhizospheres exhibited molecular variations and isolates B5 and KV1 are the potential in solving the insufficiency of phosphorus for sustainable crop production., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2023 Kelvin Kiprotich et al.)
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- 2023
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23. Liver Injury Patterns and Hepatic Toxicity among People Living with and without HIV and Attending Care in Urban Uganda.
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Wekesa C, Parkes-Ratanshi R, Kirk GD, and Ocama P
- Abstract
Introduction: The evaluation of the patterns of liver injury, derived from liver chemistry panels, often may narrow on probable causes of the liver insult especially when coupled with clinical history, examination, and other diagnostic tests., Methods: Among people living with and without HIV and attending care, we used the R ratio to evaluate for liver injury patterns. Liver injury patterns were defined as cholestatic ( R < 2), mixed ( R = 2-5), and hepatocellular ( R > 5)., Results: Overall, the proportions of participants with cholestatic liver injury, mixed liver injury, and hepatocellular liver injury were 55%, 34%, and 4%, respectively, with similar distribution when stratified by HIV status. Alcohol use among participants without HIV was associated with all patterns of liver injury (cholestatic liver injury (OR = 4.9 CI (1.0-24.2); p = 0.054), mixed liver injury (OR = 5.3 CI (1.1-27.3); p = 0.043), and hepatocellular liver injury (OR = 13.2 CI (1.0-167.3); p = 0.046)). Increasing age was associated with cholestatic liver injury among participants with HIV (OR = 2.3 CI (1.0-5.3); p = 0.038). Despite a high hepatitis B prevalence among participants with HIV, there was no association with liver injury., Conclusions: Liver injury is prevalent among both people living with and without HIV in care, and cholestatic liver injury is the most common pattern. Alcohol is associated with all patterns of liver injury and increasing age associated with cholestatic liver injury among people living without HIV and people living with HIV, respectively., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2023 Clara Wekesa et al.)
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- 2023
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24. Rhizobia Contribute to Salinity Tolerance in Common Beans ( Phaseolus vulgaris L.).
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Wekesa C, Asudi GO, Okoth P, Reichelt M, Muoma JO, Furch ACU, and Oelmüller R
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- Salt Tolerance, Kenya, Soil chemistry, Phaseolus, Rhizobium
- Abstract
Rhizobia are soil bacteria that induce nodule formation on leguminous plants. In the nodules, they reduce dinitrogen to ammonium that can be utilized by plants. Besides nitrogen fixation, rhizobia have other symbiotic functions in plants including phosphorus and iron mobilization and protection of the plants against various abiotic stresses including salinity. Worldwide, about 20% of cultivable and 33% of irrigation land is saline, and it is estimated that around 50% of the arable land will be saline by 2050. Salinity inhibits plant growth and development, results in senescence, and ultimately plant death. The purpose of this study was to investigate how rhizobia, isolated from Kenyan soils, relieve common beans from salinity stress. The yield loss of common bean plants, which were either not inoculated or inoculated with the commercial R. tropici rhizobia CIAT899 was reduced by 73% when the plants were exposed to 300 mM NaCl, while only 60% yield loss was observed after inoculation with a novel indigenous isolate from Kenyan soil, named S3. Expression profiles showed that genes involved in the transport of mineral ions (such as K
+ , Ca2+ , Fe3+ , PO4 3- , and NO3 - ) to the host plant, and for the synthesis and transport of osmotolerance molecules (soluble carbohydrates, amino acids, and nucleotides) are highly expressed in S3 bacteroids during salt stress than in the controls. Furthermore, genes for the synthesis and transport of glutathione and γ-aminobutyric acid were upregulated in salt-stressed and S3-inocculated common bean plants. We conclude that microbial osmolytes, mineral ions, and antioxidant molecules from rhizobia enhance salt tolerance in common beans.- Published
- 2022
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25. Indirect serum biomarkers perform sub optimally in screening for significant liver fibrosis among HIV-infected and uninfected adults in Uganda.
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Wekesa C, Parkes-Ratanshi R, Kirk GD, Aizire J, and Ocama P
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- Humans, Adult, Cross-Sectional Studies, Uganda, Platelet Count methods, Severity of Illness Index, Biomarkers, ROC Curve, Aspartate Aminotransferases, Liver pathology, Liver Cirrhosis, HIV Infections
- Abstract
Introduction: Indirect serum bio-markers present an acceptable noninvasive and cheap alternative for screening of significant liver fibrosis (SLF). Evaluation of their use in resource limited settings is important to determine their utility., Methods: We conducted a cross sectional study among 520 HIV infected and HIV uninfected adults attending care clinics in Kampala Uganda. Presence of SLF was determined using Fibroscan® liver stiffness measurement of ≥7.2KPa. The diagostic value of indirect serum bio-markers for diagnosis of SLF was evaluated using the area under the receiver operating characteristics curve (AUROC) using Fibroscan® as gold standard., Results: Overall AUROC values for Age Platelet Index (API), Aspartate to Alanine Ratio (AAR), AST-to-Platelet Ratio Index (APRI), Fibrosis Index based on 4 Factors (FIB-4) and Gamma glutamyl transferase to Platelet Ratio Index (GPR) were 0.52, 0.49, 0.55, 0.55 and 0.54 respectively. Among HIV-infected participants AUROC values were slightly improved at predicting presence of SLF but still under 70%., Conclusion: Despite APRI and FIB-4 being more likely to identify participants with SLF, the overall diagnostic value of all serum bio-markers was poor with and without stratification by HIV status. We recommend the use of Fibroscan® technology as more accurate non-invasive diagnostic method for screening of SLF., (© 2022 Wekesa C et al.)
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- 2022
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26. Burden and correlates of significant liver fibrosis among HIV-infected and uninfected adults in urban Uganda.
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Wekesa C, Ocama P, Parkes-Ratanshi R, and Kirk GD
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Introduction: Following chronic inflammation and other disease specific factors, the risk of liver disease is believed to be higher among HIV-infected patients than in the general population despite shared risk factors. Understanding this differentiated burden and its drivers will inform policy and priority populations for intervention., Methods: This was a cross sectional study among 516 adults attending care clinics in Kampala Uganda. Significant liver fibrosis (SLF) was defined as liver stiffness measurement ≥7.2 KPa identified by Fibroscan®. Data analyses were stratified by HIV status and we performed logistic regression performed to identify correlates., Results: The prevalence of SLF was higher among HIV un-infected patients ((24% Vs 14%; p0.004). Overall HIV-uninfected patients were more likely to be overweight and or obese, with elevated serum cholesterol levels. Elevated measurement of fatty change in the liver (CAP scores >248 dB/m) was associated with SLF among HIV un-infected patients (OR 2.3 CI (1.0-5.2); p = 0.046). Low nadir CD4 counts (200cell/mm3) was predictive of SLF among HIV-infected patients (OR 3.3 CI (1.0-10.7); p = 0.05)., Conclusion: The prevalence of SLF was unexpectedly higher among HIV un-infected than HIV affected patients attending care clinics in urban Uganda. This observed burden is most likely driven by non-alcoholic fatty liver disease (NAFLD) resulting from metabolic syndrome., Competing Interests: None declared., (© 2022 The Authors.)
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- 2022
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27. Distribution, Characterization and the Commercialization of Elite Rhizobia Strains in Africa.
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Wekesa C, Jalloh AA, Muoma JO, Korir H, Omenge KM, Maingi JM, Furch ACU, and Oelmüller R
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- Nitrogen Fixation, Soil, Symbiosis, Fabaceae microbiology, Rhizobium
- Abstract
Grain legumes play a significant role in smallholder farming systems in Africa because of their contribution to nutrition and income security and their role in fixing nitrogen. Biological Nitrogen Fixation (BNF) serves a critical role in improving soil fertility for legumes. Although much research has been conducted on rhizobia in nitrogen fixation and their contribution to soil fertility, much less is known about the distribution and diversity of the bacteria strains in different areas of the world and which of the strains achieve optimal benefits for the host plants under specific soil and environmental conditions. This paper reviews the distribution, characterization, and commercialization of elite rhizobia strains in Africa.
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- 2022
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28. The Cell Membrane of a Novel Rhizobium phaseoli Strain Is the Crucial Target for Aluminium Toxicity and Tolerance.
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Wekesa C, Muoma JO, Reichelt M, Asudi GO, Furch ACU, and Oelmüller R
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- Aluminum toxicity, Amino Acids, Cell Membrane, Kenya, Soil, gamma-Aminobutyric Acid, Rhizobium, Rhizobium phaseoli
- Abstract
Soils with low pH and high aluminium (Al) contamination restrict common bean production, mainly due to adverse effects on rhizobia. We isolated a novel rhizobium strain, B3, from Kenyan soil which is more tolerant to Al stress than the widely used commercial strain CIAT899. B3 was resistant to 50 µM Al and recovered from 100 µM Al stress, while CIAT899 did not. Calcein labeling showed that less Al binds to the B3 membranes and less ATP and mScarlet-1 protein, a cytoplasmic marker, leaked out of B3 than CIAT899 cells in Al-containing media. Expression profiles showed that the primary targets of Al are genes involved in membrane biogenesis, metal ions binding and transport, carbohydrate, and amino acid metabolism and transport. The identified differentially expressed genes suggested that the intracellular γ-aminobutyric acid (GABA), glutathione (GSH), and amino acid levels, as well as the amount of the extracellular exopolysaccharide (EPS), might change during Al stress. Altered EPS levels could also influence biofilm formation. Therefore, these parameters were investigated in more detail. The GABA levels, extracellular EPS production, and biofilm formation increased, while GSH and amino acid level decreased. In conclusion, our comparative analysis identified genes that respond to Al stress in R. phaseoli . It appears that a large portion of the identified genes code for proteins stabilizing the plasma membrane. These genes might be helpful for future studies investigating the molecular basis of Al tolerance and the characterization of candidate rhizobial isolates that perform better in Al-contaminated soils than commercial strains.
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- 2022
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29. Comparison of four outdoor mosquito trapping methods as potential replacements for human landing catches in western Kenya.
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Abong'o B, Gimnig JE, Longman B, Odongo T, Wekesa C, Webwile A, Oloo B, Nduta M, Muchoki M, Omoke D, Wacira D, Opondo K, Ochomo E, Munga S, Donnelly MJ, and Oxborough RM
- Subjects
- Animals, Entomology methods, Feeding Behavior, Female, Humans, Kenya, Male, Mosquito Control methods, Mosquito Vectors parasitology, Specimen Handling, Anopheles parasitology, Malaria prevention & control, Mosquito Control instrumentation, Mosquito Control standards
- Abstract
Introduction: Longitudinal monitoring of outdoor-biting malaria vector populations is becoming increasingly important in understanding the dynamics of residual malaria transmission. However, the human landing catch (HLC), the gold standard for measuring human biting rates indoors and outdoors, is costly and raises ethical concerns related to increased risk of infectious bites among collectors. Consequently, routine data on outdoor-feeding mosquito populations are usually limited because of the lack of a scalable tool with similar sensitivity to outdoor HLC., Methodology: The Anopheles trapping sensitivity of four baited proxy outdoor trapping methods-Furvela tent trap (FTT), host decoy trap (HDT), mosquito electrocuting traps (MET) and outdoor CDC light traps (OLT)-was assessed relative to HLC in a 5 × 5 replicated Latin square conducted over 25 nights in two villages of western Kenya. Indoor CDC light trap (ILT) was run in one house in each of the compounds with outdoor traps, while additional non-Latin square indoor and outdoor HLC collections were performed in one of the study villages., Results: The MET, FTT, HDT and OLT sampled approximately 4.67, 7.58, 5.69 and 1.98 times more An. arabiensis compared to HLC, respectively, in Kakola Ombaka. Only FTT was more sensitive relative to HLC in sampling An. funestus in Kakola Ombaka (RR = 5.59, 95% CI 2.49-12.55, P < 0.001) and Masogo (RR = 4.38, 95% CI 1.62-11.80, P = 0.004) and in sampling An. arabiensis in Masogo (RR = 5.37, 95% CI 2.17-13.24, P < 0.001). OLT sampled significantly higher numbers of An. coustani in Kakola Ombaka (RR = 3.03, 95% CI 1.65-5.56, P < 0.001) and Masogo (RR = 2.88, 95% CI 1.15-7.22, P = 0.02) compared to HLC. OLT, HLC and MET sampled mostly An. coustani, FTT had similar proportions of An. funestus and An. arabiensis, while HDT sampled predominantly An. arabiensis in both villages. FTT showed close correlation with ILT in vector abundance for all three species at both collection sites., Conclusion: FTT and OLT are simple, easily scalable traps and are potential replacements for HLC in outdoor sampling of Anopheles mosquitoes. However, the FTT closely mirrored indoor CDC light trap in mosquito indices and therefore may be more of an indoor mimic than a true outdoor collection tool. HDT and MET show potential for sampling outdoor host-seeking mosquitoes. However, the traps as currently designed may not be feasible for large-scale, longitudinal entomological monitoring. Therefore, the baited outdoor CDC light trap may be the most appropriate tool currently available for assessment of outdoor-biting and malaria transmission risk.
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- 2021
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30. Prevalence and Factors Associated With Liver Fibrosis Among Adult HIV-Infected Patients Attending Urban and Rural Care Clinics in Uganda.
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Wekesa C, Kirk GD, Aizire J, Benson EM, Karabarinde A, Parkes-Ratanshi R, and Ocama P
- Abstract
Background: Liver fibrosis is common among HIV-infected patients. Risk factors vary by location. Understanding this variation may inform prevention strategies. We compared the prevalence and correlates of liver fibrosis among HIV-infected patients attending care clinics in Uganda., Methods: This was a cross-sectional study involving 2030 HIV-infected patients attending care clinics in urban and rural Uganda. Liver fibrosis was defined as liver stiffness measurement (LSM) >7.1 KPa. Proportions and correlates of liver fibrosis were assessed and compared using logistic regression stratified by gender and site., Results: Prevalence of liver fibrosis was higher among participants in the rural clinic (15% vs 11%; P = .017). History of tobacco use (urban P = .022; rural P = .035) and serologic evidence of hepatitis C infection (HCV; urban P = .028; rural P = .03) was associated with liver fibrosis in all men. Elevated liver transaminases (urban P = .002; rural P = .028) and increasing age (urban P = .008; rural P = .052) were risk factors among all women. Tobacco use among women was only a risk factor in those attending the rural clinic ( P = .003), and detectable HIV viral load ( P = .002) for men in the urban clinic., Conclusions: Liver fibrosis is prevalent among HIV-infected persons in Uganda. HIV viral suppression and avoiding tobacco may be strategies to prevent liver fibrosis and cancer risk., (© The Author(s) 2020. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)
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- 2020
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31. Predictors of loss to follow up among patients with type 2 diabetes mellitus attending a private not for profit urban diabetes clinic in Uganda - a descriptive retrospective study.
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Tino S, Wekesa C, Kamacooko O, Makhoba A, Mwebaze R, Bengo S, Nabwato R, Kigongo A, Ddumba E, Mayanja BN, Kaleebu P, Newton R, and Nyerinda M
- Subjects
- Adult, Aged, Ambulatory Care statistics & numerical data, Ambulatory Care Facilities, Blood Glucose metabolism, Diabetes Mellitus, Type 2 blood, Female, Follow-Up Studies, Hospitals, Voluntary, Humans, Male, Middle Aged, Proportional Hazards Models, Retrospective Studies, Risk Factors, Social Class, Uganda, Urban Health, Young Adult, Diabetes Mellitus, Type 2 therapy, Lost to Follow-Up
- Abstract
Background: Although the prevalence of type 2 diabetes mellitus is increasing in Uganda, data on loss to follow up (LTFU) of patients in care is scanty. We aimed to estimate proportions of patients LTFU and document associated factors among patients attending a private not for profit urban diabetes clinic in Uganda., Methods: We conducted a descriptive retrospective study between March and May 2017. We reviewed 1818 out-patient medical records of adults diagnosed with type 2 diabetes mellitus registered between July 2003 and September 2016 at St. Francis Hospital - Nsambya Diabetes clinic in Uganda. Data was extracted on: patients' registration dates, demographics, socioeconomic status, smoking, glycaemic control, type of treatment, diabetes mellitus complications and last follow-up clinic visit. LTFU was defined as missing collecting medication for six months or more from the date of last clinic visit, excluding situations of death or referral to another clinic. We used Kaplan-Meier technique to estimate time to defaulting medical care after initial registration, log-rank test to test the significance of observed differences between groups. Cox proportional hazards regression model was used to determine predictors of patients' LTFU rates in hazard ratios (HRs)., Results: Between July 2003 and September 2016, one thousand eight hundred eighteen patients with type 2 diabetes mellitus were followed for 4847.1 person-years. Majority of patients were female 1066/1818 (59%) and 1317/1818 (72%) had poor glycaemic control. Over the 13 years, 1690/1818 (93%) patients were LTFU, giving a LTFU rate of 34.9 patients per 100 person-years (95%CI: 33.2-36.6). LTFU was significantly higher among males, younger patients (< 45 years), smokers, patients on dual therapy, lower socioeconomic status, and those with diabetes complications like neuropathy and nephropathy., Conclusion: We found high proportions of patients LTFU in this diabetes clinic which warrants intervention studies targeting the identified risk factors and strengthening follow up of patients.
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- 2019
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32. Genetic Diversity of Cowpea ( Vigna unguiculata (L.) Walp.) Accession in Kenya Gene Bank Based on Simple Sequence Repeat Markers.
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Wamalwa EN, Muoma J, and Wekesa C
- Abstract
Increased agricultural production is an urgent issue. Projected global population is 9 million people by mid of this century. Estimation projects death of 1 million people for lack of food quality (micronutrient deficit) and quantity (protein deficit). Majority of these people will be living in developing countries. Other global challenges include shrinking cultivable lands, salinity, and flooding due to climate changes, new emerging pathogens, and pests. These affect crop production. Furthermore, they are major threats to crop genetic resources and food security. Genetic diversity in cultivated crops indicates gene pool richness. It is the greatest resource for plant breeders to select lines that enhance food security. This study was conducted by Masinde Muliro University to evaluate genetic diversity in 19 cowpea accessions from Kenya national gene bank. Accessions clustered into two major groups. High divergence was observed between accessions from Ethiopia and Australia and those from Western Kenya. Upper Volta accessions were closely related to those from Western Kenya. Low variation was observed between accessions from Eastern and Rift Valley than those from Western and Coastal regions of Kenya. Diversity obtained in this study can further be exploited for the improvement of cowpea in Kenya as a measure of food security., Competing Interests: The authors declare that they have no competing interests.
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- 2016
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33. Atherogenic Risk Assessment among Persons Living in Rural Uganda.
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Wekesa C, Asiki G, Kasamba I, Waswa L, Reynolds SJ, Nsubuga RN, Newton R, and Kamali A
- Abstract
Background. Hypertension and dyslipidemia are independent risk factors for coronary heart disease and commonly coexist. Cardiovascular risk can be reliably predicted using lipid ratios such as the atherogenic index, a useful prognostic parameter for guiding timely interventions. Objective. We assessed the cardiovascular risk profile based on the atherogenic index of residents within a rural Ugandan cohort. Methods. In 2011, a population based survey was conducted among 7507 participants. Sociodemographic characteristics, physical measurements (blood pressure, weight, height, and waist and hip circumference), and blood sampling for nonfasting lipid profile were collected for each participant. Atherogenic risk profile, defined as logarithm base ten of (triglyceride divided by high density lipoprotein cholesterol), was categorised as low risk (<0.1), intermediate risk (0.1-0.24), and high risk (>0.24). Results. Fifty-five percent of participants were female and the mean age was 49.9 years (SD ± 20.2). Forty-two percent of participants had high and intermediate atherogenic risk. Persons with hypertension, untreated HIV infection, abnormal glycaemia, and obesity and living in less urbanised villages were more at risk. Conclusion. A significant proportion of persons in this rural population are at risk of atherosclerosis. Key identified populations at risk should be considered for future intervention against cardiovascular related morbidity and mortality. The study however used parameters from unfasted samples that may have a bearing on observed results.
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- 2016
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