51 research outputs found
ACSNI: An unsupervised machine-learning tool for prediction of tissue-specific pathway components using gene expression profiles
Disposition kinetics of ceftriaxone and determination of its therapeutic dose in dogs
Purpose: To evaluate the disposition kinetics of ceftriaxone (CFZ) in dogs with a view to determining its therapeutic dose and dosing frequency.Methods: Twelve (12) Basenji dogs (n = 4), divided into 3 groups (A, B and C), were used for the study. Ceftriaxone was administered intramuscularly at doses of 12.5, 25, and 50 mg/kg once to groups A, B and C respectively. Plasma CFZ concentration was determined by agar well diffusion assay at 0.25, 0.5, 1, 2, 3, 4, 6, 8, 10, 12, and 24 h post-treatment, and the pharmacokinetic parameters were determined.Results: Intramuscular injection of CFZ to dogs resulted in rapid absorption, distribution and elimination (p < 0.05). The elimination half-life was short and did not change significantly with increase in dose. Serum concentration of CFZ changed significantly (p < 0.05) with increase in dose of CFZ. The maximum serum concentration (Cmax, 15.00 ± 1.18, 141.37 ± 15.87 and 259 ± 5.21 μg/mL) for groups A, B and C respectively were significantly (p < 0.05) different. The steady state CFZ concentrations; 0.94, 8.81 and 16.19 μg/mL for groups A, B and C, respectively, were significantly (p < 0.05) different. However, there was no significant difference in the time to reach steady state concentrations (Tmax, 00±0.021, 4.00±0.10 and 4.30±0.12 for groups A, B and C respectively). The therapeutic dose of CFZ was therefore determined to be 25 – 50 mg/kg every 4 h.Conclusion: Ceftriaxone undergoes rapid elimination in dogs with a short elimination half-life, thus making it an inconvenient prescription for out-patients in veterinary clinics.
Keywords: Ceftriaxone, Pharmacokinetic profile, Dogs, Therapeutic dose, Veterinary clini
Comparison of hot wire TIG stellite 6 weld cladding and lost wax cast stellite 6 under corrosive wear conditions
This study compares Hot Wire Tungsten Inert Gas Stellite 6 weld cladding on a low carbon steel substrate with a lost wax cast Stellite 6 in impingement erosion-corrosion conditions. Austenitic stainless steel samples were used as a reference material. Tests were conducted in a closed loop impinged slurry vessel with a jet velocity of 18 m/s with 3.5%NaCl aqueous solution containing 500 µm spherical silica sand particles (0.5 g/l sand concentration). The testing temperature was 40 °C. Mass loss measurements and a volumetric analysis as well as microstructural evaluation were used as post-test analysis techniques. Results showed that weld cladding and lost wax cast Stellite 6 performed better than the stainless steel, with the weld cladding marginally outperforming the lost wax cast technique
Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multi-gene prognostic signature associated with metastasis.
BackgroundMetastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumours at high risk of metastasis would have a significant impact on management.ObjectiveTo develop a robust and validated gene expression profile (GEP) signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach.MethodsArchival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 non-metastasising and 86 metastasising) were collected retrospectively from four centres. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets.ResultsA 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk.LimitationsThis was a retrospective 4-centre study and larger prospective multicentre studies are now required.ConclusionThe 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC
Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multi-gene prognostic signature associated with metastasis.
BACKGROUND: Metastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumours at high risk of metastasis would have a significant impact on management. OBJECTIVE: To develop a robust and validated gene expression profile (GEP) signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach. METHODS: Archival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 non-metastasising and 86 metastasising) were collected retrospectively from four centres. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets. RESULTS: A 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk. LIMITATIONS: This was a retrospective 4-centre study and larger prospective multicentre studies are now required. CONCLUSION: The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC
Impact of dietary patterns, individual and workplace characteristics on blood pressure status among civil servants in Bida and Wushishi communities of Niger State, Nigeria
The global burden estimate of hypertension is alarming and results in several million deaths annually. A high incidence of sudden deaths from cardiovascular diseases in the civil workforce in Nigeria is often reported. However, the associations between Dietary Patterns (DPs), individual, and workplace characteristics of hypertension among this workforce have not been fully explored. This study aimed to identify DP in the Bida and Wushishi Communities of Niger State and establish its relationship with hypertension along with other individual and workplace characteristics. Factor analysis was used to establish DP, Chi-square test to identify their relationships with hypertension, and logistic regression to determine the predictor risk factors. The prevalence of hypertension was 43.7%; mean weight, height, and body fat were: 72.8±15 kg, 166±8.9 mm and 30.4%, respectively. Three DPs: “Efficient Diet,” “Local diet,” and “Energy Boost Diet” were identified. The factor loading scores for these factors were divided into quintiles Q1–Q5; none of them had a significant effect on hypertension status. Conversely, increase in age, the Ministry, Department, and Agency (MDA) of employment, frequency of eating in restaurants, and obesity were identified as significant risk factors. After adjusting for confounders (age, body mass index, MDA, and eating habits), a high score (Q5) in “efficient diet pattern” was significantly related to a lower likelihood of hypertension than a low score (Q1). The prevalence of hypertension among the participants was relatively very high. An increase in age and working in educational sector were risk factors associated with hypertension. Therefore, it is recommended that civil servants engage in frequent exercise and undergo regular medical checkups, especially as they get older. These findings highlight the need for large-scale assessment of the impact of variables considered in this study on hypertension, among the civil workforce across Niger state and Nigeria
Cumulative incidence and risk factors for cutaneous squamous-cell carcinoma metastases in organ transplant recipients: the SCOPE-ITSCC metastases study, a prospective multi-center study.
Solid organ transplant recipients (SOTRs) are believed to have an increased risk of metastatic cutaneous squamous-cell carcinoma (cSCC), but reliable data are lacking regarding the precise incidence and associated risk factors. In a prospective cohort study, including 19 specialist dermatology outpatient clinics in 15 countries, patient and tumor characteristics were collected using standardized questionnaires when SOTRs presented with a new cSCC. After a minimum of 2 years of follow-up, relevant data for all SOTRs were collected. Cumulative incidence of metastases was calculated by the Aalen-Johansen estimator. Fine and Gray models were used to assess multiple risk factors for metastases. Of 514 SOTRs who presented with 623 primary cSCCs, 37 developed metastases with a 2-year patient-based cumulative incidence of 6.2%. Risk factors for metastases included location in the head and neck area, local recurrence, size >2cm, clinical ulceration, poor differentiation grade, perineural invasion and deep invasion. A high-stage tumor that is also ulcerated showed the highest risk of metastasis, with a 2-year cumulative incidence of 46.2% (31.9% - 68.4%). SOTRs have a high risk of cSCC metastases and well-established clinical and histological risk factors have been confirmed. High-stage, ulcerated cSCCs have the highest risk of metastasis. [Abstract copyright: Copyright © 2024. Published by Elsevier Inc.
Brucellosis as an Emerging Threat in Developing Economies:Lessons from Nigeria
Nigeria is the most populous country in Africa, has a large proportion of the world's poor livestock keepers, and is a hotspot for neglected zoonoses. A review of the 127 accessible publications on brucellosis in Nigeria reveals only scant and fragmented evidence on its spatial and temporal distribution in different epidemiological contexts. The few bacteriological studies conducted demonstrate the existence of Brucella abortus in cattle and sheep, but evidence for B. melitensis in small ruminants is dated and unclear. The bulk of the evidence consists of seroprevalence studies, but test standardization and validation are not always adequately described, and misinterpretations exist with regard to sensitivity and/or specificity and ability to identify the infecting Brucella species. Despite this, early studies suggest that although brucellosis was endemic in extensive nomadic systems, seroprevalence was low, and brucellosis was not perceived as a real burden; recent studies, however, may reflect a changing trend. Concerning human brucellosis, no studies have identified the Brucella species and most reports provide only serological evidence of contact with Brucella in the classical risk groups; some suggest brucellosis misdiagnoses as malaria or other febrile conditions. The investigation of a severe outbreak that occurred in the late 1970s describes the emergence of animal and human disease caused by the settling of previously nomadic populations during the Sahelian drought. There appears to be an increasing risk of re-emergence of brucellosis in sub-Saharan Africa, as a result of the co-existence of pastoralist movements and the increase of intensive management resulting from growing urbanization and food demand. Highly contagious zoonoses like brucellosis pose a threat with far-reaching social and political consequences
A proteomics approach reveals molecular manipulators of distinct cellular processes in the salivary glands of Glossina m. morsitans in response to Trypanosoma b. brucei infections
ACSNI: An unsupervised machine-learning tool for prediction of tissue-specific pathway components using gene expression profiles
Determining the tissue- and disease-specific circuit of biological pathways remains a fundamental goal of molecular biology. Many components of these biological pathways still remain unknown, hindering the full and accurate characterization of biological processes of interest. Here we describe ACSNI, an algorithm that combines prior knowledge of biological processes with a deep neural network to effectively decompose gene expression profiles (GEPs) into multi-variable pathway activities and identify unknown pathway components. Experiments on public GEP data show that ACSNI predicts cogent components of mTOR, ATF2, and HOTAIRM1 signaling that recapitulate regulatory information from genetic perturbation and transcription factor binding datasets. Our framework provides a fast and easy-to-use method to identify components of signaling pathways as a tool for molecular mechanism discovery and to prioritize genes for designing future targeted experiments (https://github.com/caanene1/ACSNI)
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