Citations

Abstract Objectives: Infection with the causative agent of visceral leishmaniasis (VL) may be either symptomatic or asymptomatic. In this study we aimed at investigating the prevalence of asymptomatic infections of leishmania in non-endemic villages in Gedaref state, Sudan. A descriptive cross-sectional study conducted during September and October 2014. Blood samples were collected for serological and molecular analysis. Sticky-traps, knockdown spray and CDC-miniature light traps were used for the collection of sandflies. Results: Ninety-Five participants were included; 52 from Abukishma, 15 Algadamblia Tirfa, 25 Abualnaja and 3 were from Algadamblia Aljabal . Females constituted 56 (58.9%) of the study participants while males were 39 (41.1%). The most frequent age group was >40-years (54.7%). Balanites/Acacia trees were the most planted tree inside the houses; 78 (82.1%). Also, 85 (89.5%) of the participants breed animals inside the house. DAT test revealed 5 positive participants (5.2%). 4/5 DAT positive were past VL infection. PCR detected 35 (36.8%) positive participants. A total of 31/35 was considered asymptomatic infections based on PCR. Households planted Balanites/Acacia trees or breed domestic animals were found in high percentages with L. donovani PCR positive participants (60.1%, 91.4%). No statistically significant was found for VL associated risk factors and VL asymptomatic participants.

Abstract Objectives: Infection with the causative agent of visceral leishmaniasis (VL) may be either symptomatic or asymptomatic. In this study we aimed at investigating the prevalence of asymptomatic infections of leishmania in non-endemic villages in Gedaref state, Sudan. A descriptive cross-sectional study conducted during September and October 2014. Blood samples were collected for serological and molecular analysis. Sticky-traps, knockdown spray and CDC-miniature light traps were used for the collection of sandflies. Results: Ninety-Five participants were included; 52 from Abukishma, 15 Algadamblia Tirfa, 25 Abualnaja and 3 were from Algadamblia Aljabal . Females constituted 56 (58.9%) of the study participants while males were 39 (41.1%). The most frequent age group was >40-years (54.7%). Balanites/Acacia trees were the most planted tree inside the houses; 78 (82.1%). Also, 85 (89.5%) of the participants breed animals inside the house. DAT test revealed 5 positive participants (5.2%). 4/5 DAT positive were past VL infection. PCR detected 35 (36.8%) positive participants. A total of 31/35 was considered asymptomatic infections based on PCR. Households planted Balanites/Acacia trees or breed domestic animals were found in high percentages with L. donovani PCR positive participants (60.1%, 91.4%). No statistically significant was found for VL associated risk factors and VL asymptomatic participants.

5-Fluorouracil (5-FU) is the third most common chemotherapeutic agent for treating solid cancers and the second most common to cause cardiotoxicity. We present a rare case of acute reversible severe left ventricular systolic dysfunction associated with 5-FU. A 54-year-old woman with a history of stage IV gastric cancer presented with features of transient ischaemic attack after receiving the first dose of FLOT (5-FU, leucovorin, oxaliplatin and docetaxel). During the diagnostic workup, it was found that her ejection fraction was severely reduced to 15% with features of global hypokinesis, which later improved back to 65% within 13 days. These cases challenge our current understanding of the underlying mechanisms of this cardiotoxicity. Additionally, even though the patient did not experience any cardiac symptoms, it is important to monitor these patients closely as they are at high risk for fatal complications like arrhythmia and thrombus formation.

Yacoub et al report excellent responses to pegylated interferon alfa-2a in patients with hydroxyurea-resistant/intolerant polycythemia vera or essential thrombocythemia.

Abstract Objectives Translational research in laboratory medicine and pathology is transforming health care based on recent quantum advances in omics technologies, computational science, and precision medicine. However, high-volume clinical settings where this research may be most effective often have significant constraints on faculty time that challenge productivity. The objective of this study was to assess our experience with a new resource designed to address this challenge. Methods In September 2016, we established the Research and Innovation Office (RIO) in the Department of Laboratory Medicine and Pathology, Mayo Clinic–Rochester. The goal was to provide infrastructure to unburden faculty from performing administrative, organizational, and operational tasks related to research. Over 30 months, we solicited faculty input into desired services, conducted surveys on utility and ease of use, and tracked metrics, including faculty participation, numbers of projects, and publications. Results Faculty members were highly satisfied with the range of services, ease of use, and service-oriented approach of RIO. Initial services included project organization, institutional process support (eg, IRB protocol management), biospecimen requests and handling, and data management. Based on early feedback, patient consenting, budget support, and manuscript assistance were added as additional services. Total RIO staff increased from 6 to 10 during in the first 30 months. Over this time, 97 of 160 faculty members (60%) utilized RIO services in over 1,000 discrete project requests. Annual departmental publications increased by 50% during this time. Conclusion Faculty time is a critical element for translational research productivity in laboratory medicine and pathology departments. Numerous tasks previously performed by faculty could be managed effectively by a team of research facilitators that unburdened constraints on research time and led to high levels of faculty engagement, satisfaction, and productivity. This model may promote advances in transformative laboratory medicine and pathology research in high-volume clinical settings.

Abstract Introduction Our objective is to improve the assistive role of a deep, densely connected convolutional neural network (CNN) to hematopathologists in differentiating histologic images of Burkitt lymphoma (BL) from diffuse large B-cell lymphoma (DLBCL). We hypothesized that for the majority of cases, a CNN would accurately differentiate BL from DLBCL and attempted to identify design and input variables to improve performance. Methods and Materials In total, 3608 images of BL were collected from 18 cases and 2,071 images of DLBCL were collected from 20 cases using Aperio Image Scope (Leica Biosystems, Buffalo Grove, IL). Cases were randomized into training and unknowns, and three separate CNNs were trained and applied to unknown images. Networks differed by either the size in pixels of the images (network 1 used 32 × 32 while networks 2 and 3 used 224 × 224) or absence of color (in network 2). Decreased numbers of training images were used to evaluate network 3. Results Network 3 performed the best with 17 of 19 (89%) cases classified correctly, 10 with 100% of images correct. Overall, network 3 had 88% accuracy, 80% precision, 81% recall, and an F1 score of 0.81. Receiver operating characteristic (ROC) curve analysis showed an area under the curve (AUC) of 0.89 for DLBCL and 0.88 for BL. Networks 1 and 2 performed more poorly with F1 scores of 0.63 and 0.39, respectively. Decreasing training images by one-half and one-fourth resulted in decreased F1 scores of 0.63 and 0.60, respectively. Conclusions CNNs are promising augmented human intelligence tools for differentiating DLBCL from BL cases and potentially could contribute to improved workflow in the laboratory. More training images, larger image size, and color significantly improved performance of the CNN because of the added information available to the network. More research is under way to optimize the performance of CNNs’ lymphoma application.

Abstract Machine learning (ML) offers opportunities to advance pathological diagnosis, especially with increasing trends in digitalizing microscopic images. Diagnosing leukemia is time‐consuming and challenging in many areas globally and there is a growing trend in utilizing ML techniques for its diagnosis. In this review, we aimed to describe the literature of ML utilization in the diagnosis of the four common types of leukemia: acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), acute myeloid leukemia (AML), and chronic myelogenous leukemia (CML). Using a strict selection criterion, utilizing MeSH terminology and Boolean logic, an electronic search of MEDLINE and IEEE Xplore Digital Library was performed. The electronic search was complemented by handsearching of references of related studies and the top results of Google Scholar. The full texts of 58 articles were reviewed, out of which, 22 studies were included. The number of studies discussing ALL, AML, CLL, and CML was 12, 8, 3, and 1, respectively. No studies were prospectively applying algorithms in real‐world scenarios. Majority of studies had small and homogenous samples and used supervised learning for classification tasks. 91% of the studies were performed after 2010, and 74% of the included studies applied ML algorithms to microscopic diagnosis of leukemia. The included studies illustrated the need to develop the field of ML research, including the transformation from solely designing algorithms to practically applying them clinically.

BackgroundThe outcomes for patients with diffuse large B‐cell lymphoma (DLBCL) with adverse clinical prognostic factors such as a high age‐adjusted International Prognostic Index (aaIPI) are not optimal. In the current study, the authors performed a systematic review and meta‐analysis to assess the totality of evidence pertaining to the efficacy of autologous hematopoietic stem cell transplantation (auto‐HCT) consolidation for patients with DLBCL in first remission.MethodsThe authors searched the Cochrane and MEDLINE/PubMed databases through December 1, 2018, for studies comparing conventional chemotherapy with rituximab (R‐chemo) versus R‐chemo and auto‐HCT. Two authors independently reviewed all references for study inclusion and extracted data related to benefits (overall survival, progression‐free survival, and response rates) and harms (treatment‐related mortality and adverse events).ResultsFour studies (1173 patients) met the inclusion criteria and were included in the current analysis. The median duration of follow‐up ranged from 42 to 76 months. There was no difference noted with regard to the overall survival (hazard ratio, 1.01; 95% CI, 0.74‐1.37), progression‐free survival (hazard ratio, 0.77; 95% CI, 0.58‐1.04), or response rates (risk ratio, 0.98; 95% CI, 0.92‐1.04) between patients who received R‐chemo and auto‐HCT and those who received R‐chemo alone. The risk of mortality and therapy failure was not found to be different when the analysis was limited to high aaIPI between the 2 groups. Although there was no difference noted with regard to the risk of treatment‐related mortality, there was a significantly higher incidence of CTCAE grade 3 or 4 adverse events in patients who received R‐chemo and auto‐HCT compared with patients treated with R‐chemo alone.ConclusionsThe findings from what to the authors' knowledge is the first meta‐analysis performed in the rituximab era demonstrated no beneficial effect of upfront auto‐HCT consolidation in patients with aggressive B‐cell non‐Hodgkin lymphoma, including high‐risk clinical groups (high aaIPI).