The UK register of HIV seroconverters: Methods and analytical issues

A Register of HIV-infected persons who have had a negative antibody test within 3 years of their first antibody positive test (seroconverters) is being set up in the UK to monitor the distribution of times from HIV seroconversion to AIDS (the incubation period) and to death. It will also provide a national resource for use by those designing studies in this group of individuals. Clinicians caring for HIV-positive persons in Genito-Urinary Medicine, Infectious Disease and other departments throughout the UK were asked to participate by providing information on eligible subjects. Most laboratories undertaking HIV antibody testing were also contacted and asked to provide the name of the attending clinician for all seroconverters identified through the HIV laboratory reporting systems of the PHLS Communicable Disease Surveillance Centre (CDSC) and the Scottish Centre for Infection and Environmental Health (SCIEH) and for any other seroconverters known to them but not identified by CDSC or SCIEH. Data items sought for the Register include: sex, ethnic group, probable route of HIV transmission, annual CD4 counts, details of therapy and prophylaxis prescribed, AIDS-defining events and vital status. Follow up information is collected annually. Wherever possible, all seroconverters known to a clinic have been identified, whether currently alive or dead, either from clinic records or laboratory reporting or both. The objective is to establish and update a complete register of seroconverters on a long-term basis to provide reliable estimates of the incubation period on which future projections of AIDS cases in the UK can be made

Analyzing Network Level Information

This chapter provides a brief description of the methods employed for collecting initial information about a given suspicious online communication message, including header and network information; and how to forensically analyze the dataset to attain the information that would be necessary to trace back to the source of the crime. The header content and network information are usually the immediate sources for collecting preliminary information about a given collection of suspicious online messages. The header analysis of an e-mail corpus identifying all the senders, the recipients associated with each sender, and the frequency of messages exchanged between users helps an investigator to understand the overall nature of e-mail communication. Electronic messages like e-mails or virtual network data present a potential dataset or a source of evidence containing personal communications, critical business communications, or agreements. When a crime is committed, it is always possible for the perpetrator to manipulate e-mails or any electronic evidence, forging the details to remove relevant evidence or tampering the data to mislead the investigator. Possible manipulation of such evidence may include backdating, executing time-stamp changes, altering the message sender, recipient, or message content, etc. However, such attempts of manipulation and misleading can be detected by examining the message header. By examining e-mail header and analyzing network information through forensic analysis, investigators can gain valuable insight into the source of a message that is otherwise not traceable through the message body. Investigators can utilize a range of existing algorithms and models and build on leveraging typical forensic planning. Such models focus on what type of information should be collected, ensuring the forensically sound collection and preservation of identified Electronically Stored Information (ESI). By applying these models, it is possible to achieve a full analysis and collect all the relevant information pertaining to the crime. The collected finding is then compiled to reconstruct the whole crime scene, deduct more accurate and logical conclusions [1]

Identification of novel macrolides with antibacterial, anti-inflammatory and type I and III IFN-augmenting activity in airway epithelium

BACKGROUND: Exacerbations of asthma and COPD are triggered by rhinoviruses. Uncontrolled inflammatory pathways, pathogenic bacterial burden and impaired antiviral immunity are thought to be important factors in disease severity and duration. Macrolides including azithromycin are often used to treat the above diseases, but exhibit variable levels of efficacy. Inhaled corticosteroids are also readily used in treatment, but may lack specificity. Ideally, new treatment alternatives should suppress unwanted inflammation, but spare beneficial antiviral immunity. METHODS: In the present study, we screened 225 novel macrolides and tested them for enhanced antiviral activity against rhinovirus, as well as anti-inflammatory activity and activity against Gram-positive and Gram-negative bacteria. Primary bronchial epithelial cells were grown from 10 asthmatic individuals and the effects of macrolides on rhinovirus replication were also examined. Another 30 structurally similar macrolides were also examined. RESULTS: The oleandomycin derivative Mac5, compared with azithromycin, showed superior induction (up to 5-fold, EC50 = 5-11 μM) of rhinovirus-induced type I IFNβ, type III IFNλ1 and type III IFNλ2/3 mRNA and the IFN-stimulated genes viperin and MxA, yet had no effect on IL-6 and IL-8 mRNA. Mac5 also suppressed rhinovirus replication at 48 h, proving antiviral activity. Mac5 showed antibacterial activity against Gram-positive Streptococcus pneumoniae; however, it did not have any antibacterial properties compared with azithromycin when used against Gram-negative Escherichia coli (as a model organism) and also the respiratory pathogens Pseudomonas aeruginosa and non-typeable Haemophilus influenzae. Further non-toxic Mac5 derivatives were identified with various anti-inflammatory, antiviral and antibacterial activities. CONCLUSIONS: The data support the idea that macrolides have antiviral properties through a mechanism that is yet to be ascertained. We also provide evidence that macrolides can be developed with anti-inflammatory, antibacterial and antiviral activity and show surprising versatility depending on the clinical need

Black Stork Down: Military Discourses in Bird Conservation in Malta

Tensions between Maltese hunters and bird conservation NGOs have intensified over the past decade. Conservation NGOs have become frustrated with the Maltese State for conceding to the hunter lobby and negotiating derogations from the European Union’s Bird Directive. Some NGOs have recently started to organize complex field-operations where volunteers are trained to patrol the landscape, operate drones and other surveillance technologies, detect illegalities, and lead police teams to arrest poachers. We describe the sophisticated military metaphors which conservation NGOs have developed to describe, guide and legitimize their efforts to the Maltese public and their fee-paying members. We also discuss why such groups might be inclined to adopt these metaphors. Finally, we suggest that anthropological studies of discourse could help understand delicate contexts such as this where conservation NGOs, hunting associations and the State have ended in political deadlock

Consumers’ perceived corporate social responsibility evaluation and support: the moderating role of consumer information

This study analyzes how consumers’ evaluations of various dimensions of corporate social responsibility (CSR) affect their support of it and how consumers’ searches for CSR information influence such evaluations. The empirical analysis relies on data on CSR from a wide representative sample of 3543 Spanish hotel consumers. We use hierarchical multiple regressions to test the relationships and use factorial analysis to test the validity of the different CSR dimensions. The proposed positive effects of legal, ethical, economic, philanthropic and environmental dimensions of CSR on consumers’ support for corporate reputation, the selection of an establishment, and future purchase intention are corroborated, although they are only partially corroborated in the case of the economic dimension. These relationships are moderated in some cases by consumers’ search for information about hotels’ CSR practices. Managerial and economic implications are derived from the results

Safety, tumor trafficking and immunogenicity of chimeric antigen receptor (CAR)-T cells specific for TAG-72 in colorectal cancer.

BackgroundT cells engineered to express chimeric antigen receptors (CARs) have established efficacy in the treatment of B-cell malignancies, but their relevance in solid tumors remains undefined. Here we report results of the first human trials of CAR-T cells in the treatment of solid tumors performed in the 1990s.MethodsPatients with metastatic colorectal cancer (CRC) were treated in two phase 1 trials with first-generation retroviral transduced CAR-T cells targeting tumor-associated glycoprotein (TAG)-72 and including a CD3-zeta intracellular signaling domain (CART72 cells). In trial C-9701 and C-9702, CART72 cells were administered in escalating doses up to 1010 total cells; in trial C-9701 CART72 cells were administered by intravenous infusion. In trial C-9702, CART72 cells were administered via direct hepatic artery infusion in patients with colorectal liver metastases. In both trials, a brief course of interferon-alpha (IFN-α) was given with each CART72 infusion to upregulate expression of TAG-72.ResultsFourteen patients were enrolled in C-9701 and nine in C-9702. CART72 manufacturing success rate was 100% with an average transduction efficiency of 38%. Ten patients were treated in CC-9701 and 6 in CC-9702. Symptoms consistent with low-grade, cytokine release syndrome were observed in both trials without clear evidence of on target/off tumor toxicity. Detectable, but mostly short-term (≤14 weeks), persistence of CART72 cells was observed in blood; one patient had CART72 cells detectable at 48 weeks. Trafficking to tumor tissues was confirmed in a tumor biopsy from one of three patients. A subset of patients had 111Indium-labeled CART72 cells injected, and trafficking could be detected to liver, but T cells appeared largely excluded from large metastatic deposits. Tumor biomarkers carcinoembryonic antigen (CEA) and TAG-72 were measured in serum; there was a precipitous decline of TAG-72, but not CEA, in some patients due to induction of an interfering antibody to the TAG-72 binding domain of humanized CC49, reflecting an anti-CAR immune response. No radiologic tumor responses were observed.ConclusionThese findings demonstrate the relative safety of CART72 cells. The limited persistence supports the incorporation of co-stimulatory domains in the CAR design and the use of fully human CAR constructs to mitigate immunogenicity

Analyzing food value chains for nutrition goals

First proposed in 2010, the use of ‘value chain analysis’ to identify opportunities for targeted nutrition interventions in food systems is still an emerging method. This review explores and summarizes the application of value chain analysis to nutrition and from this provides five insights into how to more effectively conduct value chain analysis for nutrition: 1) use a consumer perspective to inform selection of foods and chains; 2) consider the research question, available resources, and the type of chain; 3) situate consumer research at the center of the analysis; 4) assess economic trade-offs; and 5) pay attention to governance and stakeholders’ capacity for and incentives to change

Characterisation of the bacterial and fungal communities associated with different lesion sizes of Dark Spot Syndrome occurring in the Coral Stephanocoenia intersepta

The number and prevalence of coral diseases/syndromes are increasing worldwide. Dark Spot Syndrome (DSS) afflicts numerous coral species and is widespread throughout the Caribbean, yet there are no known causal agents. In this study we aimed to characterise the microbial communities (bacteria and fungi) associated with DSS lesions affecting the coral Stephanocoenia intersepta using nonculture molecular techniques. Bacterial diversity of healthy tissues (H), those in advance of the lesion interface (apparently healthy AH), and three sizes of disease lesions (small, medium, and large) varied significantly (ANOSIM R = 0.052 p,0.001), apart from the medium and large lesions, which were similar in their community profile. Four bacteria fitted into the pattern expected from potential pathogens; namely absent from H, increasing in abundance within AH, and dominant in the lesions themselves. These included ribotypes related to Corynebacterium (KC190237), Acinetobacter (KC190251), Parvularculaceae (KC19027), and Oscillatoria (KC190271). Furthermore, two Vibrio species, a genus including many proposed coral pathogens, dominated the disease lesion and were absent from H and AH tissues, making them candidates as potential pathogens for DSS. In contrast, other members of bacteria from the same genus, such as V. harveyii were present throughout all sample types, supporting previous studies where potential coral pathogens exist in healthy tissues. Fungal diversity varied significantly as well, however the main difference between diseased and healthy tissues was the dominance of one ribotype, closely related to the plant pathogen, Rhytisma acerinum, a known causal agent of tar spot on tree leaves. As the corals’ symbiotic algae have been shown to turn to a darker pigmented state in DSS (giving rise to the syndromes name), the two most likely pathogens are R. acerinum and the bacterium Oscillatoria, which has been identified as the causal agent of the colouration in Black Band Disease, another widespread coral disease

Data requirements for crop modelling-Applying the learning curve approach to the simulation of winter wheat flowering time under climate change

A prerequisite for application of crop models is a careful parameterization based on observational data. However, there are limited studies investigating the link between quality and quantity of observed data and its suitability for model parameterization. Here, we explore the interactions between number of measurements, noise and model predictive skills to simulate the impact of 2050′s climate change (RCP8.5) on winter wheat flowering time. The learning curve of two winter wheat phenology models is analysed under different assumptions about the size of the calibration dataset, the measurement error and the accuracy of the model structure. Our assessment confirms that prediction skills improve asymptotically with the size of the calibration dataset, as with statistical models. Results suggest that less precise but larger training datasets can improve the predictive abilities of models. However, the non-linear relationship between number of measurements, measurement error, and prediction skills limit the compensation between data quality and quantity. We find that the model performance does not improve significantly with a theoretical minimum size of 7–9 observations when the model structure is approximate. While simulation of crop phenology is critical to crop model simulation, more studies are needed to explore data needs for assessing entire crop models

GIS and spatial data analysis: Converging perspectives

We take as our starting point the state of geographic information systems (GIS) and spatial data analysis 50 years ago when regional science emerged as a new field of enquiry. In the late 1950s and 1960s advances in computing technology were making possible forms of automated cartography that in due course would lead to th