Cholera—Modern Pandemic Disease of Ancient Lineage

Environmental triggers may lead to increases in Vibrio cholerae in environmental reservoirs, with spillover into human populations

Ranking the Risks: The 10 Pathogen-Food Combinations With the Greatest Burden on Public Health

Examines food-borne pathogens with the highest disease burdens and the top ten foods most commonly contaminated by them, such as salmonella in poultry, toxoplasma in pork, and listeria in deli meats. Makes policy recommendations for improving prevention

Hyperinfectivity: A Critical Element in the Ability of V. cholerae to Cause Epidemics?

BACKGROUND: Cholera is an ancient disease that continues to cause epidemic and pandemic disease despite ongoing efforts to limit its spread. Mathematical models provide one means of assessing the utility of various proposed interventions. However, cholera models that have been developed to date have had limitations, suggesting that there are basic elements of cholera transmission that we still do not understand. METHODS AND FINDINGS: Recent laboratory findings suggest that passage of Vibrio cholerae O1 Inaba El Tor through the gastrointestinal tract results in a short-lived, hyperinfectious state of the organism that decays in a matter of hours into a state of lower infectiousness. Incorporation of this hyperinfectious state into our disease model provides a much better fit with the observed epidemic pattern of cholera. These findings help to substantiate the clinical relevance of laboratory observations regarding the hyperinfectious state, and underscore the critical importance of human-to-human versus environment-to-human transmission in the generation of epidemic and pandemic disease. CONCLUSIONS: To have maximal impact on limiting epidemic spread of cholera, interventions should be targeted toward minimizing risk of transmission of the short-lived, hyperinfectious form of toxigenic Vibrio cholerae. The possibility of comparable hyperinfectious states in other major epidemic diseases also needs to be evaluated and, as appropriate, incorporated into models of disease prevention

Joint Application of the Target Trial Causal Framework and Machine Learning Modeling to Optimize Antibiotic Therapy: Use Case on Acute Bacterial Skin and Skin Structure Infections due to Methicillin-resistant Staphylococcus aureus

Bacterial infections are responsible for high mortality worldwide. Antimicrobial resistance underlying the infection, and multifaceted patient's clinical status can hamper the correct choice of antibiotic treatment. Randomized clinical trials provide average treatment effect estimates but are not ideal for risk stratification and optimization of therapeutic choice, i.e., individualized treatment effects (ITE). Here, we leverage large-scale electronic health record data, collected from Southern US academic clinics, to emulate a clinical trial, i.e., 'target trial', and develop a machine learning model of mortality prediction and ITE estimation for patients diagnosed with acute bacterial skin and skin structure infection (ABSSSI) due to methicillin-resistant Staphylococcus aureus (MRSA). ABSSSI-MRSA is a challenging condition with reduced treatment options - vancomycin is the preferred choice, but it has non-negligible side effects. First, we use propensity score matching to emulate the trial and create a treatment randomized (vancomycin vs. other antibiotics) dataset. Next, we use this data to train various machine learning methods (including boosted/LASSO logistic regression, support vector machines, and random forest) and choose the best model in terms of area under the receiver characteristic (AUC) through bootstrap validation. Lastly, we use the models to calculate ITE and identify possible averted deaths by therapy change. The out-of-bag tests indicate that SVM and RF are the most accurate, with AUC of 81% and 78%, respectively, but BLR/LASSO is not far behind (76%). By calculating the counterfactuals using the BLR/LASSO, vancomycin increases the risk of death, but it shows a large variation (odds ratio 1.2, 95% range 0.4-3.8) and the contribution to outcome probability is modest. Instead, the RF exhibits stronger changes in ITE, suggesting more complex treatment heterogeneity.Comment: This is the Proceedings of the KDD workshop on Applied Data Science for Healthcare (DSHealth 2022), which was held on Washington D.C, August 14 202

Primary laminopathy fibroblasts display altered genome organization and apoptosis

A number of diseases associated with specific tissue degeneration and premature aging have mutations in the nuclear envelope proteins A-type lamins or emerin. Those diseases with A-type lamin mutation are inclusively termed laminopathies. Due to various hypothetical roles of nuclear envelope proteins in genome function we investigated whether alterations to normal genomic behaviour are apparent in cells with mutations in A-type lamins and emerin. Even though the distributions of these proteins in proliferating laminopathy fibroblasts appear normal, there is abnormal nuclear positioning of both chromosome 18 and 13 territories, from the nuclear periphery to the interior. This genomic organization mimics that found in normal nonproliferating quiescent or senescent cells. This finding is supported by distributions of modified pRb in the laminopathy cells. All laminopathy cell lines tested and an X-linked Emery-Dreifuss muscular dystrophy cell line also demonstrate increased incidences of apoptosis. The most extreme cases of apoptosis occur in cells derived from diseases with mutations in the tail region of the LMNA gene, such as Dunningan-type familial partial lipodystrophy and mandibuloacral dysplasia, and this correlates with a significant level of micronucleation in these cells

Researching Zika in pregnancy:lessons for global preparedness

Our understanding of congenital infections is based on prospective studies of women infected during pregnancy. The EU has funded three consortia to study Zika virus, each including a prospective study of pregnant women. Another multi-centre study has been funded by the US National Institutes of Health. This Personal View describes the study designs required to research Zika virus, and questions whether funding academics in the EU and USA to work with collaborators in outbreak areas is an effective strategy. 3 years after the 2015\u201316 Zika virus outbreaks, these collaborations have taught us little about vertical transmission of the virus. In the time taken to approve funding, agree contracts, secure ethics approval, and equip laboratories, Zika virus had largely disappeared. By contrast, prospective studies based on local surveillance and standard-of-care protocols have already provided valuable data. Threats to fetal and child health pose new challenges for global preparedness requiring support for the design and implementation of locally appropriate protocols. These protocols can answer the key questions earlier than externally designed studies and at lower cost. Local protocols can also provide a framework for recruitment of unexposed controls that are required to study less specific outcomes. Other priorities include accelerated development of non-invasive tests, and longer-term storage of neonatal and antenatal samples to facilitate retrospective reconstruction of cohort studies

Attributing Illness to Food

Identification and prioritization of effective food safety interventions require an understanding of the relationship between food and pathogen from farm to consumption. Critical to this cause is food attribution, the capacity to attribute cases of foodborne disease to the food vehicle or other source responsible for illness. A wide variety of food attribution approaches and data are used around the world, including the analysis of outbreak data, case-control studies, microbial subtyping and source tracking methods, and expert judgment, among others. The Food Safety Research Consortium sponsored the Food Attribution Data Workshop in October 2003 to discuss the virtues and limitations of these approaches and to identify future options for collecting food attribution data in the United States. We summarize workshop discussions and identify challenges that affect progress in this critical component of a risk-based approach to improving food safety

Observations of the Goldreich-Kylafis effect in star-forming regions with XPOL at the IRAM 30m telescope

The Goldreich-Kylafis (GK) effect causes certain molecular line emission to be weakly linearly polarized, e.g., in the presence of a magnetic field. Compared to polarized dust emission, the GK effect has the potential to yield additional information along the line of sight through its dependence on velocity in the line profile. Our goal was to detect polarized molecular line emission toward the DR21(OH), W3OH/H2O, G34.3+0.2, and UYSO1 dense molecular cloud cores in transitions of rare CO isotopologues and CS. The feasibility of such observations had to be established by studying the influence of polarized sidelobes, e.g., in the presence of extended emission in the surroundings of compact sources. The observations were carried out with the IRAM 30m telescope employing the correlation polarimeter XPOL and using two orthogonally polarized receivers. We produced beam maps to investigate instrumental polarization. While in nearly all transitions toward all sources a polarized signal is found, its degree of polarization only in one case surpasses the polarization that can be expected due to instrumental effects. It is shown that any emission in the polarized sidelobes of the system can produce instrumental polarization, even if the source is unpolarized. Tentative evidence for astronomically polarized line emission with pL<~1.5% was found in the CS(2-1) line toward G34.3+0.2.Comment: 10 pages, 6 figures, accepted for publication in A&