Skin Lesion Analyser: An Efficient Seven-Way Multi-Class Skin Cancer Classification Using MobileNet

Skin cancer, a major form of cancer, is a critical public health problem with 123,000 newly diagnosed melanoma cases and between 2 and 3 million non-melanoma cases worldwide each year. The leading cause of skin cancer is high exposure of skin cells to UV radiation, which can damage the DNA inside skin cells leading to uncontrolled growth of skin cells. Skin cancer is primarily diagnosed visually employing clinical screening, a biopsy, dermoscopic analysis, and histopathological examination. It has been demonstrated that the dermoscopic analysis in the hands of inexperienced dermatologists may cause a reduction in diagnostic accuracy. Early detection and screening of skin cancer have the potential to reduce mortality and morbidity. Previous studies have shown Deep Learning ability to perform better than human experts in several visual recognition tasks. In this paper, we propose an efficient seven-way automated multi-class skin cancer classification system having performance comparable with expert dermatologists. We used a pretrained MobileNet model to train over HAM10000 dataset using transfer learning. The model classifies skin lesion image with a categorical accuracy of 83.1 percent, top2 accuracy of 91.36 percent and top3 accuracy of 95.34 percent. The weighted average of precision, recall, and f1-score were found to be 0.89, 0.83, and 0.83 respectively. The model has been deployed as a web application for public use at (https://saketchaturvedi.github.io). This fast, expansible method holds the potential for substantial clinical impact, including broadening the scope of primary care practice and augmenting clinical decision-making for dermatology specialists.Comment: This is a pre-copyedited version of a contribution published in Advances in Intelligent Systems and Computing, Hassanien A., Bhatnagar R., Darwish A. (eds) published by Chaturvedi S.S., Gupta K., Prasad P.S. The definitive authentication version is available online via https://doi.org/10.1007/978-981-15-3383-9_1

Neutrophils from Both Susceptible and Resistant Mice Efficiently Kill Opsonized \u3cem\u3eListeria monocytogenes\u3c/em\u3e

Inbred mouse strains differ in their susceptibility to infection with the facultative intracellular bacterium Listeria monocytogenes, largely due to delayed or deficient innate immune responses. Previous antibody depletion studies suggested that neutrophils (polymorphonuclear leukocytes [PMN]) were particularly important for clearance in the liver, but the ability of PMN from susceptible and resistant mice to directly kill L. monocytogenes has not been examined. In this study, we showed that PMN infiltrated the livers of BALB/c/By/J (BALB/c) and C57BL/6 (B6) mice in similar numbers and that both cell types readily migrated toward leukotriene B4 in an in vitro chemotaxis assay. However, CFU burdens in the liver were significantly higher in BALB/c mice than in other strains, suggesting that PMN in the BALB/c liver might not be able to clear L. monocytogenes as efficiently as B6 PMN. Unprimed PMN harvested from either BALB/c or B6 bone marrow killed L. monocytogenes directly ex vivo, and pretreatment with autologous serum significantly enhanced killing efficiency for both. L. monocytogenes were internalized within 10 min and rapidly triggered intracellular production of reactive oxygen species in a dose-dependent manner. However, PMN from gp91phox-deficient mice also readily killed L. monocytogenes, which suggested that nonoxidative killing mechanisms may be sufficient for bacterial clearance. Together, these results indicate that there is not an intrinsic defect in the ability of PMN from susceptible BALB/c mice to kill L. monocytogenes and further suggest that if PMN function is impaired in BALB/c mice, it is likely due to locally produced modulating factors present in the liver during infection

Increasing Support for Contraception as HIV Prevention: Stakeholder Mapping to Identify Influential Individuals and Their Perceptions

BACKGROUND: Voluntary contraceptive use by HIV-positive women currently prevents more HIV-positive births, at a lower cost, than anti-retroviral drug (ARV) regimens. Despite this evidence, most prevention of mother-to-child transmission (PMTCT) programs focus solely on providing ARV prophylaxis to pregnant women and rarely include the prevention of unintended pregnancies among HIV-positive women. METHODOLOGY/PRINCIPAL FINDINGS: To strengthen support for family planning as HIV prevention, we systematically identified key individuals in the field of international HIV/AIDS-those who could potentially influence the issue-and sought to determine their perceptions of barriers to and facilitators for implementing this PMTCT strategy. We used a criteria-based approach to determine which HIV/AIDS stakeholders have the most significant impact on HIV/AIDS research, programs, funding and policy and stratified purposive sampling to conduct interviews with a subset of these individuals. The interview findings pointed to obstacles to strengthening linkages between family planning and HIV/AIDS, including the need for: resources to integrate family planning and HIV services, infrastructure or capacity to provide integrated services at the facility level, national leadership and coordination, and targeted advocacy to key decision-makers. CONCLUSIONS/SIGNIFICANCE: The individuals we identified as having regional or international influence in the field of HIV/AIDS have the ability to leverage an increasingly conducive funding environment and a growing evidence base to address the policy, programmatic and operational challenges to integrating family planning with HIV/AIDS. Fostering greater support for implementing contraception for HIV prevention will require the dedication, collaboration and coordination of many such actors. Our findings can inform a targeted advocacy campaign

Deep neural network or dermatologist?

Deep learning techniques have proven high accuracy for identifying melanoma in digitised dermoscopic images. A strength is that these methods are not constrained by features that are pre-defined by human semantics. A down-side is that it is difficult to understand the rationale of the model predictions and to identify potential failure modes. This is a major barrier to adoption of deep learning in clinical practice. In this paper we ask if two existing local interpretability methods, Grad-CAM and Kernel SHAP, can shed light on convolutional neural networks trained in the context of melanoma detection. Our contributions are (i) we first explore the domain space via a reproducible, end-to-end learning framework that creates a suite of 30 models, all trained on a publicly available data set (HAM10000), (ii) we next explore the reliability of GradCAM and Kernel SHAP in this context via some basic sanity check experiments (iii) finally, we investigate a random selection of models from our suite using GradCAM and Kernel SHAP. We show that despite high accuracy, the models will occasionally assign importance to features that are not relevant to the diagnostic task. We also show that models of similar accuracy will produce different explanations as measured by these methods. This work represents first steps in bridging the gap between model accuracy and interpretability in the domain of skin cancer classification

Analysis of TACI mutations in CVID & RESPI patients who have inherited HLA B*44 or HLA*B8

<p>Abstract</p> <p>Background</p> <p>Recent reports have suggested that Common Variable Immunodeficieny (CVID) can present as an autosomal dominant trait dependent on the inheritance of a set of uncommon mutations/alleles of TACI (transmembrane activator and calcium-modulator and cyclophilin ligand interactor) involving exons 3 or 4. Penetrance, however, appears to be incomplete. Among our clinic population, the greatest genetic linkage for CVID is to the major histocompatibility complex (MHC) on chromosome 6. The majority of our patients have inherited HLA *DQ2, *DR7, *DR3(17), *B8, and/or *B44. Of these, HLA*B44 was present in almost half of the patients and was thus the most common susceptibility allele. HLA *B44 was also found to be over-represented among patients who presented to our clinic with adult-onset recurrent sinopulmonary infections (RESPI) and normal serum immunoglobulin levels, a cohort that included first and second degree relatives of patients with CVID. One of the two original reports of the association between TACI and CVID also reported Human Leukocyte Antigen (HLA) haplotypes. Of 13 affected subjects, nine had inherited HLA *B8 and six had inherited HLA B44. This raised the possibility that TACI mutations might synergize with MHC class I alleles to enhance susceptibility to humoral immune deficiency.</p> <p>Methods</p> <p>We identified 63 CVID patients irrespective of HLA status and 13 RESPI patients who had inherited HLA*B44. To evaluate for mutations in the gene for TACI, we PCR amplified and sequenced TACI exons 3 and 4 from these patients.</p> <p>Results</p> <p>Of the 76 patients, eleven proved heterozygous for a previously reported, silent T->G polymorphism [rs35062843] at proline 97 in exon 3. However, none of the 13 RESPI patients and only one of the 63 CVID patients inherited a TACI allele previously associated with CVID. This patient was heterozygous for the TACI A181E allele (exon 4). She did not carry *DQ2, *DR7, *DR3(17), *B8, or *B44.</p> <p>Conclusion</p> <p>These findings suggest that TACI mutations are unlikely to play a critical role in creating susceptibility to CVID among patients with previously recognized MHC class I and class II susceptibility alleles.</p> <p>Supported by NIH/USIDNET N01-AI30070, NIH R21 AI079741 and NIH M01-RR00032</p

The effectiveness of public health interventions to reduce the health impact of climate change:a systematic review of systematic reviews

Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases

Theories for influencer identification in complex networks

In social and biological systems, the structural heterogeneity of interaction networks gives rise to the emergence of a small set of influential nodes, or influencers, in a series of dynamical processes. Although much smaller than the entire network, these influencers were observed to be able to shape the collective dynamics of large populations in different contexts. As such, the successful identification of influencers should have profound implications in various real-world spreading dynamics such as viral marketing, epidemic outbreaks and cascading failure. In this chapter, we first summarize the centrality-based approach in finding single influencers in complex networks, and then discuss the more complicated problem of locating multiple influencers from a collective point of view. Progress rooted in collective influence theory, belief-propagation and computer science will be presented. Finally, we present some applications of influencer identification in diverse real-world systems, including online social platforms, scientific publication, brain networks and socioeconomic systems.Comment: 24 pages, 6 figure

The initial experience of electronic brachytherapy for the treatment of non-melanoma skin cancer

<p>Abstract</p> <p>Background</p> <p>Millions of people are diagnosed with non-melanoma skin cancers (NMSC) worldwide each year. While surgical approaches are the standard treatment, some patients are appropriate candidates for radiation therapy for NMSC. High dose rate (HDR) brachytherapy using surface applicators has shown efficacy in the treatment of NMSC and shortens the radiation treatment schedule by using a condensed hypofractionated approach. An electronic brachytherapy (EBT) system permits treatment of NMSC without the use of a radioactive isotope.</p> <p>Methods</p> <p>Data were collected retrospectively from patients treated from July 2009 through March 2010. Pre-treatment biopsy was performed to confirm a malignant cutaneous diagnosis. A CT scan was performed to assess lesion depth for treatment planning, and an appropriate size of surface applicator was selected to provide an acceptable margin. An HDR EBT system delivered a dose of 40.0 Gy in eight fractions twice weekly with 48 hours between fractions, prescribed to a depth of 3-7 mm. Treatment feasibility, acute safety, efficacy outcomes, and cosmetic results were assessed.</p> <p>Results</p> <p>Thirty-seven patients (mean age 72.5 years) with 44 cutaneous malignancies were treated. Of 44 lesions treated, 39 (89%) were T1, 1 (2%) Tis, 1 (2%) T2, and 3 (7%) lesions were recurrent. Lesion locations included the nose for 16 lesions (36.4%), ear 5 (11%), scalp 5 (11%), face 14 (32%), and an extremity for 4 (9%). Median follow-up was 4.1 months. No severe toxicities occurred. Cosmesis ratings were good to excellent for 100% of the lesions at follow-up.</p> <p>Conclusions</p> <p>The early outcomes of EBT for the treatment of NMSC appear to show acceptable acute safety and favorable cosmetic outcomes. Using a hypofractionated approach, EBT provides a convenient treatment schedule.</p