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Bacterial Isolates and Their Antibiotic Susceptibility Pattern among Patients with Infected Wounds Admited in Orthopaedic and Trauma Ward in Tertiary Care Hospital North-Eastern Tanzania

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Journal of Biosciences and Medicines 2022年第7期10卷 83-96页

作者： Lee Kapalisya Mwakalinga rogers joachim temu Pius Gerald Horumpende Nicolaus Ngowi Anthony Japhet Pallangyo Department of Orthopedic and Traumatology Facult of Medicine Kilimanjaro Christian Medical University College Moshi Tanzania Department of Orthopedics and Traumatology Kilimanjaro Christian Medical Center Moshi Tanzania Kilimanjaro College of Health and Allied Sciences Moshi Tanzania Department of Biochemistry and Molecular Biology Kilimanjaro Clinical Research Institute Moshi Tanzania Department of Biochemistry and Molecular Biology Kilimanjaro Christian Medical Center Moshi Tanzania Lugalo General Military Hospital Military College of Medical Sciennces Dar es Salaam Tanzania

The hospital environment contributes to wound infections. Effects of such infections include prolonged hospitalization, increased morbidity, potential for antibiotics resistance and mortality due to sepsis. An updated knowledge of antibiotics susceptibility profiles of clinical isolates will assist both in choosing the most appropriate antibiotic treatment for wound infections and help in curbing the escalation of drug resistance. Cross sectional hospital based study, analysis of 125 pus samples collected from January 2018 to December 2020 was conducted. Identification and characterization of isolates were performed on the basis of Gram staining, microscopic characteristics, colony characteristic, and biochemical tests using standard microbiological methods. Antibiotic susceptibilities of bacterial isolates were determined by Kirby Bauer disc diffusion. A total of 125 pus samples were studied, 94 (75%) were from male patients, mean age was 38.5 (SD ± 19) years. Single bacterial isolates were recovered from 120 (96%) samples, 67 (53.6%) shows Multiple Drug Resistance (MDR) pattern, 74 (59.2%) were gram negative, the predominant organism isolated was Staphylococcus aureus 46 (36.8%). Gram negative isolates showed high resistance to ampicillin and cephalosporins. Gram positive isolates showed high resistance to erythromycin. Both gram positive and negative were found to be highly susceptible to gentamicin, amikacin, clindamycin, ciprofloxacin and amoxicillin/clavulanic acid. The study showed that Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli are the major bacteria isolated from pus samples. High proportion (53.6%) of the isolates was MDR. In the light of these findings, a change in antibiotic prescription policy is required at this hospital.

关键词： Pus Bacteria Antibiotic Tanzania

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An integrative approach of digital image analysis and transcriptome profiling to explore potential predictive biomarkers for TGFβblockade therapy

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Acta Pharmaceutica Sinica B 2022年第9期12卷 3594-3601页

作者： Robert Pomponio Qi Tang Anthony Mei Anne Caron Bema Coulibaly joachim Theilhaber Maximilian rogers-Grazado Michele Sanicola-Nadel Souad Naimi Reza Olfati-Saber Cecile Combeau Jack Pollard Tun Tun Lin Rui Wang Sanofi Translational Medicine Early Development Cambridge MA 02142USA Sanofi Artificial Intelligence and Deep Analytics Data and Data Sciences CambridgeMA 02142USA Sanofi Translational Science Vitry sur Seine 94403France Sanofi Precision Oncology Cambridge MA 02142USA Sanofi Oncology Early Development Cambridge MA 02142USA

Increasing evidence suggests that the presence and spatial localization and distribution pattern of tumor infiltrating lymphocytes(TILs)is associate with response to immunotherapies.Recent studies have identified TGFβactivity and signaling as a determinant of T cell exclusion in the tumor microenvironment and poor response to PD-1/PD-L1 blockade.Here we coupled the artificial intelligence(AI)-powered digital image analysis and gene expression profiling as an integrative approach to quantify distribution of TILs and characterize the associated TGFβpathway activity.Analysis of T cell spatial distribution in the solid tumor biopsies revealed substantial differences in the distribution patterns.The digital image analysis approach achieves 74%concordance with the pathologist assessment for tumor-immune phenotypes.The transcriptomic profiling suggests that the TIL score was negatively correlated with TGFβpathway activation,together with elevated TGFβsignaling activity observed in excluded and desert tumor phenotypes.The present results demonstrate that the automated digital pathology algorithm for quantitative analysis of CD8 immunohistochemistry image can successfully assign the tumor into one of three infiltration phenotypes:immune desert,immune excluded or immune inflamed.The association between“cold”tumor-immune phenotypes and TGFβsignature further demonstrates their potential as predictive biomarkers to identify appropriate patients that may benefit from TGFβblockade.

关键词： Digital pathology Artificial intelligence TGFβ Predictive biomarker Tumor topography T cell infiltration Transcriptomic profiling Machine learning

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CFD-simulation of a circulating fluidized bed riser

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Particuology 2009年第4期7卷 283-296页

作者： Ernst-Ulrich Hartge Lars Ratschow Reiner Wischnewski joachim Werther Hamburg-University of Technology Institute of Solids Process Engineering and Particle TechnologyD-21071 HamburgGermany

In the current work, a model of the fluid mechanics in the riser of a circulating fluidized bed （CFB） has been implemented using computational fluid dynamics （CFD）. The model developed shall be used in future as the basis of 3D-reactor model for the simulation of large scale CFB combustors. The two-fluid model （TFM） approach is used to represent the fluid mechanics involved in the flow. The computational implementation is accomplished by the commercial software FLUENT. Different closure formulations are tested on a simplified geometry. Two different turbulence formulations, namely the swirl modified RNG k-e model and the Realizable k-e model, are tested in combination with two different approaches to solid phase turbulence, namely the dispersion and per phase approach. One focus of the current work is put on the study of different drag correlations. Besides the drag correlations by Syamlal et al. [Syamlal, M., rogers, W., ＆ O＇Brien, T. J. （1993）. MFIX documentation theory guide. Technical Report DOE/METC-9411004, U.S. Department of Energy （DOE）. Morgantown Energy Technology Center： Morgantown, WV] and Gidaspow [Gidaspow, D. （1994）. Multiphaseflow andfluidization. New York： Academic Press] the EMMS model has been used to determine the momentum exchange between the two phases. The resulting formulation is then used to simulate a 1-m × 0.3-m cold CFB setup and is validated by experimental results [Schlichtharle, P. （2000）. Fluid dynamics and mixing of solids and gas in the bottom zone of circulating fluidized beds. Unoublished doctoral dissertation, Technische Universitaet Hamburg-Harburg, Shaker Verlag： Aachen].

关键词： Circulating fluidized bed Two-fuid model EMMS model Drag correlations

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