We examined the introduction of diphtheria-tetanus-pertussis (DTP) and oral polio vaccine (OPV) in an urban community in Guinea-Bissau in the early 1980s.
There is growing concern around the effects of concussion and sub-concussive impacts in sport. Routine game-play in soccer involves intentional and repeated head impacts through ball heading. Although heading is frequently cited as a risk to brain health, little data exist regarding the consequences of this activity. This study aims to assess the immediate outcomes of routine football heading using direct and sensitive measures of brain function.
Public trust in immunization is an increasingly important global health issue. Losses in confidence in vaccines and immunization programmes can lead to vaccine reluctance and refusal, risking disease outbreaks and challenging immunization goals in high- and low-income settings. National and international immunization stakeholders have called for better monitoring of vaccine confidence to identify emerging concerns before they evolve into vaccine confidence crises.
Senescence is a tumor suppressor mechanism activated in stressed cells to prevent replication of damaged DNA. Senescent cells have been demonstrated to play a causal role in driving aging and age-related diseases using genetic and pharmacologic approaches. We previously demonstrated that the combination of dasatinib and the flavonoid quercetin is a potent senolytic improving numerous age-related conditions including frailty, osteoporosis and cardiovascular disease. The goal of this study was to identify flavonoids with more potent senolytic activity.
Since it emerged in Brazil in May 2015, the mosquito-borne Zika virus (ZIKV) has raised global concern due to its association with a significant rise in the number of infants born with microcephaly and neurological disorders such as Guillain-Barré syndrome. We developed prototype subunit and adenoviral-based Zika vaccines encoding the extracellular portion of the ZIKV envelope gene (E) fused to the T4 fibritin foldon trimerization domain (Efl). The subunit vaccine was delivered intradermally through carboxymethyl cellulose microneedle array (MNA). The immunogenicity of these two vaccines, named Ad5.ZIKV-Efl and ZIKV-rEfl, was tested in C57BL/6 mice. Prime/boost immunization regimen was associated with induction of a ZIKV-specific antibody response, which provided neutralizing immunity. Moreover, protection was evaluated in seven-day-old pups after virulent ZIKV intraperitoneal challenge. Pups born to mice immunized with Ad5.ZIKV-Efl were all protected against lethal challenge infection without weight loss or neurological signs, while pups born to dams immunized with MNA-ZIKV-rEfl were partially protected (50%). No protection was seen in pups born to phosphate buffered saline-immunized mice. This study illustrates the preliminary efficacy of the E ZIKV antigen vaccination in controlling ZIKV infectivity, providing a promising candidate vaccine and antigen format for the prevention of Zika virus disease.
The gut microbiota is interlinked with obesity, but direct evidence of effects of its modulation on body fat mass is still scarce. We investigated the possible effects of Bifidobacterium animalisssp. lactis 420 (B420) and the dietary fiber Litesse® Ultra polydextrose (LU) on body fat mass and other obesity-related parameters.
Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and automated image analysis approaches have great potential to increase precision of diagnosis and help reduce human error. In this study, we utilize several computational methods based on convolutional neural networks (CNN) and build a stand-alone pipeline to effectively classify different histopathology images across different types of cancer. In particular, we demonstrate the utility of our pipeline to discriminate between two subtypes of lung cancer, four biomarkers of bladder cancer, and five biomarkers of breast cancer. In addition, we apply our pipeline to discriminate among four immunohistochemistry (IHC) staining scores of bladder and breast cancers. Our classification pipeline includes a basic CNN architecture, Google’s Inceptions with three training strategies, and an ensemble of two state-of-the-art algorithms, Inception and ResNet. Training strategies include training the last layer of Google’s Inceptions, training the network from scratch, and fine-tunning the parameters for our data using two pre-trained version of Google’s Inception architectures, Inception-V1 and Inception-V3. We demonstrate the power of deep learning approaches for identifying cancer subtypes, and the robustness of Google’s Inceptions even in presence of extensive tumor heterogeneity. On average, our pipeline achieved accuracies of 100%, 92%, 95%, and 69% for discrimination of various cancer tissues., subtypes, biomarkers, and scores, respectively. Our pipeline and related documentation is freely available at https://github.com/ih-_lab/CNN_Smoothie.
The objective of this study was to identify blood-based protein biomarkers of early stage Mycobacterium tuberculosis (Mtb) infection. We utilized plasma and serum specimens from TB patients and their contacts (age≥12) enrolled in a household contact study in Uganda. In the discovery phase cross-sectional samples from 104 HIV-uninfected persons classified as either active TB, latent Mtb infection (LTBI), tuberculin skin test (TST) converters, or persistent TST-negative were analyzed. Two hundred eighty-nine statistically significant (false discovery rate corrected p<0.05) differentially expressed proteins were identified across all comparisons. Proteins associated with cellular immunity and lipid metabolism were induced early after Mtb infection. One hundred and fifty-nine proteins were selected for a targeted mass spectrometry assay. A set of longitudinal samples from 52 TST-negative subjects who converted to TST-positive or remained TST-negative were analyzed, and multivariate logistic regression was used to identify unique protein panels able to predict TST conversion with cross-validated AUC>0.85. Panel performance was confirmed with an independent validation set of longitudinal samples from 16 subjects. These candidate protein biomarkers may allow for the identification of recently Mtb infected individuals at highest risk for developing active TB and most likely to benefit from preventive therapy.
Infection of respiratory mucosa with viral pathogens triggers complex immunologic events in the affected host. We sought to characterize this response through proteomic analysis of nasopharyngeal lavage in human subjects experimentally challenged with influenza A/H3N2 or human rhinovirus, and to develop targeted assays measuring peptides involved in this host response allowing classification of acute respiratory virus infection. Unbiased proteomic discovery analysis identified 3285 peptides corresponding to 438 unique proteins, and revealed that infection with H3N2 induces significant alterations in protein expression. These include proteins involved in acute inflammatory response, innate immune response, and the complement cascade. These data provide insights into the nature of the biological response to viral infection of the upper respiratory tract, and the proteins that are dysregulated by viral infection form the basis of signature that accurately classifies the infected state. Verification of this signature using targeted mass spectrometry in independent cohorts of subjects challenged with influenza or rhinovirus demonstrates that it performs with high accuracy (0.8623 AUROC, 75% TPR, 97.46% TNR). With further development as a clinical diagnostic, this signature may have utility in rapid screening for emerging infections, avoidance of inappropriate antibacterial therapy, and more rapid implementation of appropriate therapeutic and public health strategies.
The complexity of the traumatic brain injury (TBI) pathology, particularly concussive injury, is a serious obstacle for diagnosis, treatment, and long-term prognosis. Here we utilize modern systems biology in a rodent model of concussive injury to gain a thorough view of the impact of TBI on fundamental aspects of gene regulation, which have the potential to drive or alter the course of the TBI pathology. TBI perturbed epigenomic programming, transcriptional activities (expression level and alternative splicing), and the organization of genes in networks centered around genes such as Anax2, Ogn, and Fmod. Transcriptomic signatures in the hippocampus are involved in neuronal signaling, metabolism, inflammation, and blood function, and they overlap with those in leukocytes from peripheral blood. The homology between genomic signatures from blood and brain elicited by TBI provides proof of concept information for development of biomarkers of TBI based on composite genomic patterns. By intersecting with human genome-wide association studies, many TBI signature genes and network regulators identified in our rodent model were causally associated with brain disorders with relevant link to TBI. The overall results show that concussive brain injury reprograms genes which could lead to predisposition to neurological and psychiatric disorders, and that genomic information from peripheral leukocytes has the potential to predict TBI pathogenesis in the brain.