The diagnosis of dengue in patients presenting with acute febrile illness using supervised machine learning and impact of seasonality

Background: Symptomatic dengue infection can result in a life-threatening shock syndrome and timely diagnosis is essential. Point-of-care tests for non-structural protein 1 and IgM are used widely but performance can be limited. We developed a supervised machine learning model to predict whether patients with acute febrile illnesses had a diagnosis of dengue or other febrile illnesses (OFI). The impact of seasonality on model performance over time was examined. Methods: We analysed data from a prospective observational clinical study in Vietnam. Enrolled patients presented with an acute febrile illness of 90%). Conclusion: Supervised machine learning models are able to discriminate between dengue and OFI diagnoses in patients presenting with an early undifferentiated febrile illness. These models could be of clinical utility in supporting healthcare decision-making and provide passive surveillance across dengue endemic regions. Effects of seasonality and changing disease prevalence must however be taken into account—this is of significant importance given unpredictable effects of human-induced climate change and the impact on health

Stroke genetics: prospects for personalized medicine.

Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice

Real-time continuous measurement of lactate through a minimally invasive microneedle patch: a phase I clinical study

Introduction Determination of blood lactate levels supports decision-making in a range of medical conditions. Invasive blood-sampling and laboratory access are often required, and measurements provide a static profile at each instance. We conducted a phase I clinical study validating performance of a microneedle patch for minimally invasive, continuous lactate measurement in healthy volunteers. Methods Five healthy adult participants wore a solid microneedle biosensor patch on their forearms and undertook aerobic exercise for 30 min. The microneedle biosensor quantifies lactate concentrations in interstitial fluid within the dermis continuously and in real-time. Outputs were captured as sensor current and compared with lactate concentrations from venous blood and microdialysis. Results The biosensor was well-tolerated. Participants generated a median peak venous lactate of 9.25 mmol/L (IQR 6.73–10.71). Microdialysate concentrations of lactate closely correlated with blood. Microneedle biosensor current followed venous lactate concentrations and dynamics, with good agreement seen in all participants. There was an estimated lag-time of 5 min (IQR −4 to 11 min) between microneedle and blood lactate measurements. Conclusion This study provides first-in-human data on use of a minimally invasive microneedle patch for continuous lactate measurement, providing dynamic monitoring. This low-cost platform offers distinct advantages to frequent blood sampling in a wide range of clinical settings, especially where access to laboratory services is limited or blood sampling is infeasible. Implementation of this technology in healthcare settings could support personalised decision-making in a variety of hospital and community settings

Shigella sonnei genome sequencing and phylogenetic analysis indicate recent global dissemination from Europe

Shigella are human-adapted Escherichia coli that have gained the ability to invade the human gut mucosa and cause dysentery1,2, spreading efficiently via low-dose fecal-oral transmission3,4. Historically, S. sonnei has been predominantly responsible for dysentery in developed countries, but is now emerging as a problem in the developing world, apparently replacing the more diverse S. flexneri in areas undergoing economic development and improvements in water quality4-6. Classical approaches have shown S. sonnei is genetically conserved and clonal7. We report here whole-genome sequencing of 132 globally-distributed isolates. Our phylogenetic analysis shows that the current S. sonnei population descends from a common ancestor that existed less than 500 years ago and has diversified into several distinct lineages with unique characteristics. Our analysis suggests the majority of this diversification occurred in Europe, followed by more recent establishment of local pathogen populations in other continents predominantly due to the pandemic spread of a single, rapidly-evolving, multidrug resistant lineage

Discovery of mating in the major African livestock pathogen Trypanosoma congolense

The protozoan parasite, Trypanosoma congolense, is one of the most economically important pathogens of livestock in Africa and, through its impact on cattle health and productivity, has a significant effect on human health and well being. Despite the importance of this parasite our knowledge of some of the fundamental biological processes is limited. For example, it is unknown whether mating takes place. In this paper we have taken a population genetics based approach to address this question. The availability of genome sequence of the parasite allowed us to identify polymorphic microsatellite markers, which were used to genotype T. congolense isolates from livestock in a discrete geographical area of The Gambia. The data showed a high level of diversity with a large number of distinct genotypes, but a deficit in heterozygotes. Further analysis identified cryptic genetic subdivision into four sub-populations. In one of these, parasite genotypic diversity could only be explained by the occurrence of frequent mating in T. congolense. These data are completely inconsistent with previous suggestions that the parasite expands asexually in the absence of mating. The discovery of mating in this species of trypanosome has significant consequences for the spread of critical traits, such as drug resistance, as well as for fundamental aspects of the biology and epidemiology of this neglected but economically important pathogen

Depression and sickness behavior are Janus-faced responses to shared inflammatory pathways

It is of considerable translational importance whether depression is a form or a consequence of sickness behavior. Sickness behavior is a behavioral complex induced by infections and immune trauma and mediated by pro-inflammatory cytokines. It is an adaptive response that enhances recovery by conserving energy to combat acute inflammation. There are considerable phenomenological similarities between sickness behavior and depression, for example, behavioral inhibition, anorexia and weight loss, and melancholic (anhedonia), physio-somatic (fatigue, hyperalgesia, malaise), anxiety and neurocognitive symptoms. In clinical depression, however, a transition occurs to sensitization of immuno-inflammatory pathways, progressive damage by oxidative and nitrosative stress to lipids, proteins, and DNA, and autoimmune responses directed against self-epitopes. The latter mechanisms are the substrate of a neuroprogressive process, whereby multiple depressive episodes cause neural tissue damage and consequent functional and cognitive sequelae. Thus, shared immuno-inflammatory pathways underpin the physiology of sickness behavior and the pathophysiology of clinical depression explaining their partially overlapping phenomenology. Inflammation may provoke a Janus-faced response with a good, acute side, generating protective inflammation through sickness behavior and a bad, chronic side, for example, clinical depression, a lifelong disorder with positive feedback loops between (neuro)inflammation and (neuro)degenerative processes following less well defined triggers

Novel Molecular Targets of Azadirachta indica Associated with Inhibition of Tumor Growth in Prostate Cancer

Advanced prostate cancer has significant long-term morbidity, and there is a growing interest in alternative and complimentary forms of therapy that will improve the outcomes of patients. Azadirachta indica (common name: neem) contains multiple active compounds that have potent anti-inflammatory and anticancer properties. The present study investigates the novel targets of the anticancer activity of ethanol extract of neem leaves (EENL) in vitro and evaluates the in vivo efficacy in the prostate cancer models. Analysis of the components in the EENL by mass spectrometry suggests the presence of 2′,3′-dehydrosalannol, 6-desacetyl nimbinene, and nimolinone. Treatment of C4-2B and PC-3M-luc2 prostate cancer cells with EENL inhibited the cell proliferation. Genome-wide expression profiling, using oligonucleotide microarrays, revealed genes differentially expressed with EENL treatment in prostate cancer cells. Functional analysis unveiled that most of the up-regulated genes were associated with cell death, and drug metabolism, and the down-regulated genes were associated with cell cycle, DNA replication, recombination, and repair functions. Quantitative PCR confirmed significant up-regulation of 40 genes and immunoblotting revealed increase in the protein expression levels of HMOX1, AKR1C2, AKR1C3, and AKR1B10. EENL treatment inhibited the growth of C4-2B and PC-3M-luc2 prostate cancer xenografts in nude mice. The suppression of tumor growth is associated with the formation of hyalinized fibrous tumor tissue and the induction of cell death by apoptosis. These results suggest that EENL-containing natural bioactive compounds could have potent anticancer property and the regulation of multiple cellular pathways could exert pleiotrophic effects in prevention and treatment of prostate cancer

A novel tumor suppressor gene ECRG4 interacts directly with TMPRSS11A (ECRG1) to inhibit cancer cell growth in esophageal carcinoma

<p>Abstract</p> <p>Background</p> <p>The esophageal carcinoma related gene 4 (ECRG4) was initially identified and cloned from human normal esophageal epithelium in our laboratory (GenBank accession no.<ext-link ext-link-id="AF325503" ext-link-type="gen">AF325503</ext-link>). ECRG4 has been described as a novel tumor suppressor gene associated with prognosis in esophageal squamous cell carcinoma (ESCC).</p> <p>Methods</p> <p>In this study, binding affinity assay in vitro and co-immunoprecipitation experiment in vivo were utilized to verify the physical interaction between ECRG4 and transmembrane protease, serine 11A (TMPRSS11A, also known as ECRG1, GenBank accession no. <ext-link ext-link-id="AF 071882" ext-link-type="gen">AF 071882</ext-link>). Then, p21 protein expression, cell cycle and cell proliferation regulations were examined after ECRG4 and ECRG1 co-transfection in ESCC cells.</p> <p>Results</p> <p>We revealed for the first time that ECRG4 interacted directly with ECRG1 to inhibit cancer cell proliferation and induce cell cycle G1 phase block in ESCC. Binding affinity and co-immunoprecipitation assays demonstrated that ECRG4 interacted directly with ECRG1 in ESCC cells. Furthermore, the ECRG4 and ECRG1 co-expression remarkably upregulatd p21 protein level by Western blot (P < 0.001), induced cell cycle G1 phase block by flow cytometric analysis (P < 0.001) and suppressed cell proliferation by MTT and BrdU assay (both P < 0.01) in ESCC cells.</p> <p>Conclusions</p> <p>ECRG4 interacts directly with ECRG1 to upregulate p21 protein expression, induce cell cycle G1 phase block and inhibit cancer cells proliferation in ESCC.</p