2,034 research outputs found

    Effect of α<sup>+</sup> Thalassemia on the Severity of <i>Plasmodium falciparum</i> Malaria in Different Sickle Cell Genotypes in Indian Adults: A Hospital-Based Study

    No full text
    There is a paucity of literature on the association of α+-thalassemia, sickle-cell hemoglobin disorders, and malaria in India. This study aimed to understand the effect of α+-thalassemia on the severity of Plasmodium falciparum malaria in adults with respect to sickle-cell genotypes. The study subjects were categorized into ‘severe-malaria’ and ‘uncomplicated-malaria’ and age-gender matched ‘control’ groups. Sickle-cell and α+-thalassemia were investigated in all the recruited subjects. The effect of α+-thalassemia on the severity of malaria was analyzed in HbAA and sickle-cell genotypes (HbAS and HbSS) separately. The prevalence of α+-thalassemia in various groups ranged from 41.5% to 81.8%. The prevalence of α+-thalassemia was lower (OR = 1.64; p = 0.0013) in severe malaria (41.5%) as compared to healthy controls (53.8%) with HbAA genotype. In contrast, in HbAS genotype, the prevalence of α+-thalassemia was higher (OR = 4.11; p = 0.0002) in severe malaria (81.8%) compared to controls (52.2%). In severe malaria with HbAA genotype, there was a significantly higher hemoglobin level and low MCV and MCH level in patients with α+-thalassemia compared to the normal α-globin genotype. Further, the incidence of cerebral malaria, hepatopathy, and mortality was lower in patients (HbAA) with α+-thalassemia as compared to normal α-globin genotype (HbAA). In severe malaria with either HbAS or HbSS genotype, only a few parameters showed statistical differences with respect to α+-thalassemia. Low prevalence of α+-thalassemia in severe malaria with HbAA genotype compared to healthy controls with HbAA genotype indicates the protective effect of α+-thalassemia against severe malaria. However, the high prevalence of α+-thalassemia in patients with HbAS genotype depicts its interference in the protective effect of sickle-cell against severe malaria.</p

    Increasing human monoclonal antibody cloning efficiency with whole-cell modified Immunoglobulin-Capture Assay (mICA)

    No full text
    Expression cloning of fully human monoclonal antibodies (hmAbs) is seeing powerful utility in the field of vaccinology, especially for elucidating vaccine-induced B-cell responses and novel vaccine candidate antigen discovery. Precision of the hmAb cloning process relies on efficient isolation of hmAb-producing plasmablasts of interest. Previously, a novel immunoglobulin-capture assay (ICA) was developed, using single protein vaccine antigens, to enhance the pathogen-specific hmAb cloning output. Here, we report a novel modification of this single-antigen ICA using formalin-treated, fluorescently stained whole cell suspensions of the human bacterial invasive pathogens, Streptococcus pneumoniae and Neisseria meningitidis. Sequestration of IgG secreted by individual vaccine antigen-specific plasmablasts was achieved by the formation of an anti-CD45-streptavidin and biotin anti-IgG scaffold. Suspensions containing heterologous pneumococcal and meningococcal strains were then used to enrich for polysaccharide- and protein antigen-specific plasmablasts, respectively, during single cell sorting. Following application of the modified whole-cell ICA (mICA), ~61% (19/31) of anti-pneumococcal polysaccharide hmAbs were cloned compared to 14% (8/59) obtained using standard (non-mICA) methods – representing a ~4.4-fold increase in hmAb cloning precision. A more modest ~1.7-fold difference was obtained for anti-meningococcal vaccine hmAb cloning; ~88% of hmAbs cloned via mICA versus ~53% cloned via the standard method were specific for a meningococcal surface protein. VDJ sequencing revealed that cloned hmAbs reflected an anamnestic response to both pneumococcal and meningococcal vaccines; diversification within hmAb clones occurred by positive selection for replacement mutations. Thus, we have shown successful utilisation of whole bacterial cells in the ICA protocol enabling isolation of hmAbs targeting multiple disparate epitopes, thereby increasing the power of approaches such as reverse vaccinology 2.0 (RV 2.0) for bacterial vaccine antigen discovery

    Increasing human monoclonal antibody cloning efficiency with a whole-cell modified immunoglobulin-capture assay (mICA)

    Get PDF
    Expression cloning of fully human monoclonal antibodies (hmAbs) is seeing powerful utility in the field of vaccinology, especially for elucidating vaccine-induced B-cell responses and novel vaccine candidate antigen discovery. Precision of the hmAb cloning process relies on efficient isolation of hmAb-producing plasmablasts of interest. Previously, a novel immunoglobulin-capture assay (ICA) was developed, using single protein vaccine antigens, to enhance the pathogen-specific hmAb cloning output. Here, we report a novel modification of this single-antigen ICA using formalin-treated, fluorescently stained whole cell suspensions of the human bacterial invasive pathogens, Streptococcus pneumoniae and Neisseria meningitidis. Sequestration of IgG secreted by individual vaccine antigen-specific plasmablasts was achieved by the formation of an anti-CD45-streptavidin and biotin anti-IgG scaffold. Suspensions containing heterologous pneumococcal and meningococcal strains were then used to enrich for polysaccharide- and protein antigen-specific plasmablasts, respectively, during single cell sorting. Following application of the modified whole-cell ICA (mICA), ~61% (19/31) of anti-pneumococcal polysaccharide hmAbs were cloned compared to 14% (8/59) obtained using standard (non-mICA) methods – representing a ~4.4-fold increase in hmAb cloning precision. A more modest ~1.7-fold difference was obtained for anti-meningococcal vaccine hmAb cloning; ~88% of hmAbs cloned via mICA versus ~53% cloned via the standard method were specific for a meningococcal surface protein. VDJ sequencing revealed that cloned hmAbs reflected an anamnestic response to both pneumococcal and meningococcal vaccines; diversification within hmAb clones occurred by positive selection for replacement mutations. Thus, we have shown successful utilization of whole bacterial cells in the ICA protocol enabling isolation of hmAbs targeting multiple disparate epitopes, thereby increasing the power of approaches such as reverse vaccinology 2.0 (RV 2.0) for bacterial vaccine antigen discovery

    Bone mineral density in women newly diagnosed with breast cancer: a prospective cohort study

    Get PDF
    Estrogen may have opposing effects on health, namely increasing the risk of breast cancer and improving bone health by increasing bone mineral density (BMD). The objective of this study was to compare dual-energy X-ray absorptiometry (DXA) BMD between women newly diagnosed with breast cancer and matched controls without breast cancer. Women newly diagnosed with breast cancer treated between April 2012 and October 2017 were prospectively enrolled. A control group was established of women with negative mammography or breast ultrasound, matched 1:1 by age, body mass index, parity, and the use of hormone replacement therapy. All those included had DXA BMD, and lab assessments at enrollment. Of 869 women with newly diagnosed breast cancer, 464 signed informed consent. Of the 344 who completed the study protocol, 284 were matched to controls. Overall, the mean age was 58 years. Compared to the control group, for the breast cancer group, the mean vitamin D level was lower (48.9 ± 19.0 vs. 53.8 ± 28.8 nmol/L, p = 0.022); and mean values were higher of total hip BMD (0.95 ± 0.14 vs. 0.92 ± 0.12 g/cm2, p = 0.002), T score (-0.38 ± 1.17 vs. -0.68 ± 0.98, p = 0.002), and Z score (0.32 ± 1.09 vs. 0.01 ± 0.88, p < 0.001). Among the women with breast cancer, no correlations were found of baseline BMD with tumor size or grade, nodal involvement, or breast cancer stage. We concluded that women with newly diagnosed breast cancer tend to have higher BMD than women with similar characteristics but without breast cancer. This implies that BMD might be considered a biomarker for breast cancer risk

    FAKTOR YANG MEMPENGARUHI PEMILIHAN LOKASI PERMUKIMAN BERDASARKAN PERSEPSI MASYARAKAT DI KECAMATAN GUNUNGSARI

    Get PDF
    Tujuan dari penelitian ini untuk mengetahui faktor yang mempengaruhi pemilihan lokasi permukiman di pinggiran kota berdasarkan persepsi masya rakat di Kecamatan Gunungsari. Penelitian ini menggunakan jenis penelitian deskriptif. Penelitian deskriptif adalah salah satu jenis metode penelitian yang berusaha menggambarkan dan menginterpretasi objek sesuai dengan apa adanya. Kecamatan Gunungsari merupakan salah satu Kecamatan yang berbatasan dengan kota Mataram yang secara administrasi berada sebelah Utara Kota Mataram. Keadaan tersebut menyebabkan pertumbuhan lahan terbangun setiap tahunnya meningkat di Kecamatan Gunungsari yang ditandai dengan pertumbuhan penduduk semakin meningkat dan untuk penggunaan lahan nya di dominasi oleh lahan terbangun Berdasarkan hasil penelitian terkait faktor-faktor yang mempengaruhi pemilihan lokasi permukiman berdasarkan persepsi masyarakat di Kecamatan Gunungsari terdapat 7 variabel yakni aksesbilitias, lingkungan, peluang kerja, kelengkapan prasarana, estetika, fasilitas pelayanan dan biaya. Diketahui pada variabel aksesbilitas masyarakat menyatakan kurang setuju terhadap sub variabel kemudahan transportasi dikarenakan tingkat kepadatan berlalu lalang transportasi dan 21% memilih setuju dikarenakan kondisi jalannya baik. Sedangkan terkait sub variabel jarak ke pusat kota bahwa 60% masyarakat menyatakan kurang setuju dikarenakan sebagian masyarakat di Kecamatan Gunungsari berprofesi sebagai petani sehingga kurang begitu memperdulikan jarak ke pusat kota dan 14% masyarakat di Kecamatan Gunungsari menyatakan setuju karena mempunyai keperluan atau kebutuhan di pusat kota

    Scene Context-Aware Salient Object Detection

    Get PDF

    Delving into human visual attention for saliency detection of real-world images

    No full text
    Saliency detection explores the problem of identifying regions or objects that stand out from its surroundings. It is one of the fundamental problems in computer vision, with its appli-cation widely used in other graphics, vision and robotics tasks. Relative saliency ranking is a new problem that has been introduced with the idea of determining ranking based on the differences in the saliency agreement between multiple observers. This approach can lead to multiple objects being given the same saliency ranks. However, psychology studies and behavioural observations show that humans shift their attention from one location to another when viewing an image. This is due to the fact that the human visual system have limited capacity in simultaneously processing multiple visual inputs. We consider the sequential shift-ing of attention on objects as a form of saliency ranking, thus, we propose a new problem of saliency ranking based on attention shift. Although there are methods proposed for predicting saliency ranks, they are not able to model this human attention shift well. They are primarily based on ranking saliency values from binary prediction, which does not properly facilitate saliency rank reasoning between multiple individual objects. In this thesis, we aim to explore deep learning techniques for learning to rank salient objects by inferring human attention shift. We first construct a large-scale salient object ranking dataset. We define the saliency rank of objects by the order that an observer attends to these objects based on attention shift. We then propose a deep learning model that is built from bottom-up and top-down attention mechanisms for performing saliency ranking. Our model is evaluated with both quantitative and qualitative experiments, in which our proposed approach achieves state-of-the-art performance.Regarding traditional salient object detection, we observe two main issues that lead to recent techniques failing in real-world complex image scenes. Firstly, most existing datasets consist of images with simple foregrounds and backgrounds, and limited number of objects that hardly represent real-life scenarios. Second, current methods only learn contextual features of salient objects with binary saliency labels. This is not very sufficient for a model to learn high-level semantics for saliency reasoning in complex scenes. We begin to address these problems by constructing a new large-scale dataset with complex scenes rich in context. We then propose a context-aware saliency network that learns to explicitly exploit the semantic scene contexts of an image. We perform extensive experiments to demonstrate that our proposed network outperforms state-of-the-arts. The evaluation also show the effectiveness of leveraging high-level scene semantics for saliency detection in complex scenarios, while also transferring well to other existing datasets

    IoT Group Membership Management Using Decentralized Identifiers and Verifiable Credentials

    No full text
    Many IoT use cases can benefit from group communication, where a user requests an IoT resource and this request can be handled by multiple IoT devices, each of which may respond back to the user. IoT group communication involves one-to-many requests and many-to-one responses, and this creates security challenges. In this paper, we focus on the provenance that has been received by an authorized device. We provide an effective and flexible solution for securing IoT group communication using CoAP, where a CoAP client sends a request to a CoAP group and receives multiple responses by many IoT devices, acting as CoAP servers. We design a solution that allows CoAP servers to digitally sign their responses in a way that clients can verify that a response has been generated by an authorized member of the CoAP group. In order to achieve our goal, we leverage Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs). In particular, we consider that each group is identified by a DID, and each group member has received a VC that allows it to participate in that group. The only information a client needs to know is the DID of the group, which is learned using DNSSEC. Our solution allows group members to rotate their signing keys, it achieves group member revocation, and it has minimal communication and computational overhead

    Scene context-aware salient object detection

    No full text
    Salient object detection identifies objects in an image that grab visual attention. Although contextual features are considered in recent literature, they often fail in real-world complex scenarios. We observe that this is mainly due to two issues: First, most existing datasets consist of simple foregrounds and backgrounds that hardly represent real-life scenarios. Second, current methods only learn contextual features of salient objects, which are insufficient to model high-level semantics for saliency reasoning in complex scenes. To address these problems, we first construct a new large-scale dataset with complex scenes in this paper. We then propose a context-aware learning approach to explicitly exploit the semantic scene contexts. Specifically, two modules are proposed to achieve the goal: 1) a Semantic Scene Context Refinement module to enhance contextual features learned from salient objects with scene context, and 2) a Contextual Instance Transformer to learn contextual relations between objects and scene context. To our knowledge, such high-level semantic contextual information of image scenes is under-explored for saliency detection in the literature. Extensive experiments demonstrate that the proposed approach outperforms state-of-the-art techniques in complex scenarios for saliency detection, and transfers well to other existing datasets. The code and dataset are available at https://github.com/SirisAvishek/Scene_Context_Aware_Saliency

    Rape, Consent, and the U.S. Military

    Get PDF
    The military’s sexual assault prevention and response program is unable to effectively eliminate or even minimize occurrences of sexual assault in the service. This program focuses primarily on the elimination of sexual assault through yearly mandatory education on the current policies and procedures that occur when a victim comes forward. The Sexual Assault Prevention and Response (SAPR) program is reactionary and unequipped to tackle a culture that continues to promote a climate in which sexual assault and harassment exist without fear of retaliation. This thesis explores these issues and provides suggestions for changes in future revisions of the SAPR program. First, the SAPR program relies heavily on the victim’s actions while simultaneously creating a complex and largely ineffective response to the accusations from one service member to another. Second, affected service members risk being ostracized in their primary communities if they come forward with claims of assault. These primary communities vary from their shop, command, squadron, and base and can overlap. Third, consent can only be truly utilized in spaces where a person is able to have complete bodily autonomy over themselves. Consent, as seen through this lens, functions as one of the ways in which service members are set up for failure when they report sexual assault or harassment. In a military environment the voluntary limits of personal freedoms are accepted and understood by service members as a reasonable cost for the benefits received. However, those benefits are insufficient when a service member finds themselves unable to report without also accepting the risk of losing everything gained under their contracted service
    corecore