11 research outputs found
Performance, Haematological and Serum Biochemical Profile of Cockerels Fed Diets Supplemented with Fermented Moringa oleifera Seeds
No full textStudies on the \u3b2-Lactamase Production of Bacterial Isolates From Smoked Bush Meats Correlated With Bacterial Resistance to Three \u3b2-Lactam Antibiotics
No full textEight bacterial species were isolated from smoked meats and screened
for the production of \u3b2-lactamase; which was detected by
penicillin impregnated starch paper strips. \u3b2-lactamase was
detected in the following bacterial isolates: Klebsiella pneumoniae
(75.0%), Escherichia coli (69.7%), Proteus sp. (33.3%), Pseudomonas
aeruginosa (25.9%), Staphylococcus aureus (80.0%) and Streptococcus
feacalis (12.5%). There was no \u3b2-lactamase detected in
Lactobacillus casei and Salmonella sp. isolated from the meats. The
prevalence of \u3b2-lactamase detected in the samples shows that the
bacteria posses the potential to produce \u3b2-lactamase irrespective
of the source of isolation. The sensitivity of the \u3b2-lactam
antibiotics (penicillin G, ampicillin and cloxacillin) used range from
8.3-100.0%. Although, penicillin G has the lowest sensitivity of 8.3%
to Klebsiella pneumoniae while, ampicillin and cloxacillin were 25.0%
and 16.7% sensitive to the same bacteria respectively. Salmonella
species is the most susceptible (range from 70.0-100.0%) to the tested
antibiotics among the \u3b2-lactamase positive bacteria screened. The
frequency of occurrence of the pathogenic bacteria and the feacal
indicator organism (E.coli) indicated gross contamination of some of
the meat samples analyzed; this indicates that the meats may have been
contaminated either during processing with faecal contaminated water or
handling by the sellers. In conclusion, the habit of eating uncooked
smoked meat should be discouraged and emphasis should be laid on
properly cooked meat before consumption
Studies on the β-Lactamase Production of Bacterial Isolates From Smoked Bush Meats Correlated With Bacterial Resistance to Three β-Lactam Antibiotics
No full textEight bacterial species were isolated from smoked meats and screened
for the production of β-lactamase; which was detected by
penicillin impregnated starch paper strips. β-lactamase was
detected in the following bacterial isolates: Klebsiella pneumoniae
(75.0%), Escherichia coli (69.7%), Proteus sp. (33.3%), Pseudomonas
aeruginosa (25.9%), Staphylococcus aureus (80.0%) and Streptococcus
feacalis (12.5%). There was no β-lactamase detected in
Lactobacillus casei and Salmonella sp. isolated from the meats. The
prevalence of β-lactamase detected in the samples shows that the
bacteria posses the potential to produce β-lactamase irrespective
of the source of isolation. The sensitivity of the β-lactam
antibiotics (penicillin G, ampicillin and cloxacillin) used range from
8.3-100.0%. Although, penicillin G has the lowest sensitivity of 8.3%
to Klebsiella pneumoniae while, ampicillin and cloxacillin were 25.0%
and 16.7% sensitive to the same bacteria respectively. Salmonella
species is the most susceptible (range from 70.0-100.0%) to the tested
antibiotics among the β-lactamase positive bacteria screened. The
frequency of occurrence of the pathogenic bacteria and the feacal
indicator organism (E.coli) indicated gross contamination of some of
the meat samples analyzed; this indicates that the meats may have been
contaminated either during processing with faecal contaminated water or
handling by the sellers. In conclusion, the habit of eating uncooked
smoked meat should be discouraged and emphasis should be laid on
properly cooked meat before consumption
Studies on the β-Lactamase Production of Bacterial Isolates From Smoked Bush Meats Correlated With Bacterial Resistance to Three β-Lactam Antibiotics
No full textEight bacterial species were isolated from smoked meats and screened
for the production of β-lactamase; which was detected by
penicillin impregnated starch paper strips. β-lactamase was
detected in the following bacterial isolates: Klebsiella pneumoniae
(75.0%), Escherichia coli (69.7%), Proteus sp. (33.3%), Pseudomonas
aeruginosa (25.9%), Staphylococcus aureus (80.0%) and Streptococcus
feacalis (12.5%). There was no β-lactamase detected in
Lactobacillus casei and Salmonella sp. isolated from the meats. The
prevalence of β-lactamase detected in the samples shows that the
bacteria posses the potential to produce β-lactamase irrespective
of the source of isolation. The sensitivity of the β-lactam
antibiotics (penicillin G, ampicillin and cloxacillin) used range from
8.3-100.0%. Although, penicillin G has the lowest sensitivity of 8.3%
to Klebsiella pneumoniae while, ampicillin and cloxacillin were 25.0%
and 16.7% sensitive to the same bacteria respectively. Salmonella
species is the most susceptible (range from 70.0-100.0%) to the tested
antibiotics among the β-lactamase positive bacteria screened. The
frequency of occurrence of the pathogenic bacteria and the feacal
indicator organism (E.coli) indicated gross contamination of some of
the meat samples analyzed; this indicates that the meats may have been
contaminated either during processing with faecal contaminated water or
handling by the sellers. In conclusion, the habit of eating uncooked
smoked meat should be discouraged and emphasis should be laid on
properly cooked meat before consumption
Effect of Graded Levels of Lemongrass (Cymbopogon citratus) on Oxidative Stability of Raw or Cooked Pork Patties
No full textEvaluation of amino acid and fatty acid profiles of commercially cultivated oyster mushroom (Pleurotus sajor-caju) grown on gmelina wood waste
No full textAbstractEdible mushrooms are used in the preparation of several delicacies in many parts of Nigeria; however, little information is available on the nutritional qualities of oyster mushroom (Pleurotus sajor-caju) cultivated on gmelina wood waste. This study ascertains the nutritional and anti-nutritional amino acid and fatty acid composition of commercially grown oyster mushroom (P. sajor-caju) on gmelina wood waste in Forestry Research Institute of Nigeria. The sample was obtained and analyzed for fatty acid profile and amino acid profile on dry weight basis using standard methods. The chemical score of the essential amino acid of the sample, which ranged from 55.94% (methionine) to 150.31% (isoleucine), was comparable to standard dietary reference intake requirement. Fatty acid profile showed the presence of polyunsaturated (linolenic 29.54%, linoleic 11.6% and arachidonic 0.22%), monounsaturated (oleic 41.71%, palmitioleic 0.22% and erucic 7.09%) and some saturated (caprylic 0.92%, myristic 0.18%, palmitic 5.34%, margaric 0.21%, stearic 2.38%, arachidic 012%, behenic 0.25% and lignoceric 0.16%) fatty acid. This study showed that oyster mushroom grown on gmelina wood waste has potential for use as acceptable human food
Physico-chemical and anti-nutritional characterization of the kernels of some mango (Mangifera indica) cultivars grown in Western parts of Nigeria
No full textTen mango (Mangifera indica) cultivars grown in western parts of Nigeria were identified as Alphonso, Indesina, Julie, Kent, Mabranka, Magadugu, Peach, Peter, Taymour, and Oori. The percentage weight ratio (PWR) of kernel to fruit, seed to fruit and kernel to seed of the mangoes ranged between 2.38 – 10.79%, 6.36 – 17.21% and 36.22 – 63.35% respectively. The PWR of kernel to fruit (10.79%), seed to fruit (17.21%) and kernel to seed (63.35%) of “Oori” cultivar were significantly higher (p < 0.05) than other cultivars, except the values of PWR of kernel to seed of Indesina (60.05%) and Kent (62.72%). Values of Julie cultivar on the parameters measured were significantly lower (p < 0.05) than others. The range of nutrients of the kernels were protein (6.24 – 8.19%), fat (5.92 – 13.50%), fibre (2.22 – 3.95%), ash (0.52 – 3.54%) and carbohydrate (75.02 – 83.04%). The protein of Julie (7.88%), Indesina (8.05%) and Oori (8.19%) and fat of Mabranka (13.10%) and Alphonso (13.50%) were significantly higher (p< 0.05) than other cultivars. The carbohydrates in the mango kernels was high; although values recorded for Mabranka (75.02%) and Alphonso (75.09%) were significantly lower (p< 0.05) than other cultivars. The pH of fresh mango kernels ranged between 4.10 and 5.80, while titratable acidity was between 9.92 – 64.35mg/100g. The anti-nutrients in the mango kernels were tannin, flavonoid, phenolic compound, oxalate and phytate. Tannin (37.30 – 163.33g/kg), phytate (0.442 – 0.897mol/kg) and oxalate (18.74 – 54.24mg/100g) were significantly different (p< 0.05) among the mango cultivars. Tannin and oxalate contents of Oori (157.33; 54.24g/kg), Alphonso (163.33; 49.55g/kg) and Phytate content of Mabranka (0.442mol/kg), Alphonso (0.453mol/kg) and Indesina (0.478mol/kg) respectively were significantly higher (p< 0.05) compared with other cultivars. Key words: Mango cultivars, percentage weight ratio, nutrients, anti-nutrients
Modifiable Risk Factors and Trends in Changes in Glucose Regulation during the First Three Years Postdelivery: The St Carlos Gestational Diabetes Mellitus Prevention Cohort
No full textAuthor Contributions: M.A.-R., A.B., A.L.C.-P., A.D., P.M.-M., M.A.R., P.d.M., J.A.D., L.d.V., V.M., J.V., I.R., M.P. and R.M.O. were involved in conceptualization and design, data curation, analysis, and interpretation of data. A.L.C.-P. was responsible for funding acquisition. A.L.C.-P., C.F., I.M., I.J., M.A.-R., M.J.T., M.M.-N., M.P., A.D., P.d.M., A.B., L.d.V., V.M., J.V. and R.M.O. were involved in supervision, validation, and visualization of researched data, and contributed to discussion and investigation. M.C., M.P., P.M.-M., M.A.-R. and M.A.R. were involved in data research and reviewed and edited the manuscript. Writing—original draft: A.L.C.-P., M.A.-R., V.M., I.R. and P.M.-M. wrote the first draft of the manuscript. Writing—review & editing: M.A.-R., A.L.C.-P., P.M.-M., V.M., and I.R. A.L.C.-P. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors have read and agreed to the published version of the manuscript.Objective: Evaluation of the influence of potential risk factors (RFs) on glycemic changes at 3 years postpartum. Methods: The glycemic status of 1400 women, in absence of a new pregnancy, was evaluated at 3 months (3 m) and 3 years (3 y) postpartum, after participation in the St. Carlos Gestational Study (2228 normoglycemic pregnant women followed from before gestational week 12 to delivery, from 2015–2017). Abnormal glucose regulation (AGR) was defined as fasting serum glucose ≥ 100 mg/dL and/or HbA1c ≥ 5.7% and/or 2 h 75 g OGTT glucose ≥ 140 mg/dL. In total, 12 modifiable and 3 unmodifiable RFs were analyzed. Results: 3 m postpartum, 110/1400 (7.9%) women had AGR; 3 y postpartum, 137 (9.8%) women exhibited AGR (110 with 3 m normal glucose tolerance [NGT]); 1263 (90.2%) had NGT (83 with 3 m AGR). More women with gestational diabetes mellitus (GDM) progressed to AGR at 3 y (OR: 1.60 [1.33–1.92]) than women without GDM. Yet, most women with 3 m and/or 3 y AGR had no GDM history. Having ≥2 unmodifiable RFs was associated with increased risk for progression to AGR (OR: 1.90 [1.28–2.83]) at 3 y postpartum. Having >5/12 modifiable RFs was associated with increased progression from NGT to AGR (OR: 1.40 [1.00–2.09]) and AGR persistence (OR: 2.57 [1.05–6.31]). Pregestational BMI ≥ 25 kg/m2 (OR: 0.59 [0.41–0.85]), postdelivery weight gain (OR: 0.53 [0.29–0.94]), and waist circumference > 89.5 cm (OR: 0.54 [0.36–0.79]) reduced the likelihood of NGT persisting at 3 y. Conclusions: 3-month and/or 3-year postpartum AGR can be detected if sought in women with no prior GDM. Modifiable and unmodifiable RF predictors of AGR at 3 y postpartum were identified. Universal screening for glycemic alterations should be considered in all women following delivery, regardless of prior GDM. These findings could be useful to design personalized strategies in women with risk factors for 3 y AGR.Ministerio de Ciencia, Innovación y Universidades (España)Depto. de MedicinaFac. de MedicinaTRUEpu
Dual Mode Sensing of Binding and Blocking of Cancer Exosomes to Biomimetic Human Primary Stem Cell Surfaces
No full textCancer-derived exosomes (cEXOs) facilitate transfer of information between tumor and human primary stromal cells, favoring cancer progression. Although the mechanisms used during this information exchange are still not completely understood, it is known that binding is the initial contact established between cEXOs and cells. Hence, studying binding and finding strategies to block it are of great therapeutic value. However, such studies are challenging for a variety of reasons, including the need for human primary cell culture, the difficulty in decoupling and isolating binding from internalization and cargo delivery, and the lack of techniques to detect these specific interactions. In this work, we created a supported biomimetic stem cell membrane incorporating membrane components from human primary adipose-derived stem cells (ADSCs). We formed the supported membrane on glass and on multielectrode arrays to offer the dual option of optical or electrical detection of cEXO binding to the membrane surface. Using our platform, we show that cEXOs bind to the stem cell membrane and that binding is blocked when an antibody to integrin β1, a component of ADSC surface, is exposed to the membrane surface prior to cEXOs. To test the biological outcome of blocking this interaction, we first confirm that adding cEXOs to cultured ADSCs leads to the upregulation of vascular endothelial growth factor, a measure of proangiogenic activity. Next, when ADSCs are first blocked with anti-integrin β1 and then exposed to cEXOs, the upregulation of proangiogenic activity and cell proliferation are significantly reduced. This biomimetic membrane platform is the first cell-free label-free in vitro platform for the recapitulation and study of cEXO binding to human primary stem cells with potential for therapeutic molecule screening as it is compatible with scale-up and multiplexing.We wish to acknowledge Zixuan Henry Lu for his assistance with the electrical measurements, Achilleas Savva for his assistance with the EEC modeling, and Anil Koklu for his assistance in MAE design and fabrication. This work was supported by the National Science Foundation Graduate Research Fellowship (grant number DGE-1650441), the Sloan Foundation (grant number 70481) to J.U., and a research grant from King Abdullah University of Science and Technology under contract OSR-2018-CRG7-3709 to S.I., R.M.O, and S.D. W.T. acknowledges funding from the Cambridge Trust. This work was performed in part at the Cornell NanoScale Facility, an NNCI member supported by the NSF grant NNCI-2025233. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of any of the funding institutions
The Tenth Visual Object Tracking VOT2022 Challenge Results
No full textThe Visual Object Tracking challenge VOT2022 is the tenth annual tracker benchmarking activity organized by the VOT initiative. Results of 93 entries are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2022 challenge was composed of seven sub-challenges focusing on different tracking domains: (i) VOT-STs2022 challenge focused on short-term tracking in RGB by segmentation, (ii) VOT-STb2022 challenge focused on short-term tracking in RGB by bounding boxes, (iii) VOT-RTs2022 challenge focused on “real-time” short-term tracking in RGB by segmentation, (iv) VOT-RTb2022 challenge focused on “real-time” short-term tracking in RGB by bounding boxes, (v) VOT-LT2022 focused on long-term tracking, namely coping with target disappearance and reappearance, (vi) VOT-RGBD2022 challenge focused on short-term tracking in RGB and depth imagery, and (vii) VOT-D2022 challenge focused on short-term tracking in depth-only imagery. New datasets were introduced in VOT-LT2022 and VOT-RGBD2022, VOT-ST2022 dataset was refreshed, and a training dataset was introduced for VOT-LT2022. The source code for most of the trackers, the datasets, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net ). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.</p
