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OBJECTIVE: To study the effects of chemotherapy on cognitive function in breast cancer patients, and to investigate the relationship of MemTrax test of memory and related functions to the FACT-Cog functional self-assessment for the evaluation and management of chemobrain. METHODS: In this prospective cohort study, clinical information of pathologically confirmed female breast cancer patients who decided to receive chemotherapy were collected in a questionnaire which was developed for this study and provided as a supplementary file. The FACT-Cog self-assessment and MemTrax test were administered before and after the chemotherapy treatments. Patients with chemobrain were identified using published criteria based on FACT-Cog scores, and MemTrax scores from chemobrain patients were analyzed. RESULTS: Fifty-six patients participated in this study, of which 41 participants completed 4 or more cycles of chemotherapy and were included in the final analyses here. Using the reported high end of minimal clinical differences (10.6 points) of FACT-Cog before and after chemotherapy, 18 patients suffered from chemobrain in this study. In these 18 chemobrain patients, no cognitive impairments were detected by MemTrax, which paradoxically demonstrated an improvement in the normal cognitive range. CONCLUSION: The cognitive impairment induced by chemotherapy in breast cancer patients is detectable by the FACT-Cog in a Chinese cohort but is not detected by the MemTrax memory test. The fact that the more objective MemTrax could not detect the impairment could alleviate patients' concerns which in turn would be beneficial for patients' mental health.
Subject(s)
Breast Neoplasms , Humans , Female , Breast Neoplasms/drug therapy , Breast Neoplasms/psychology , Middle Aged , Prospective Studies , Adult , Neuropsychological Tests/statistics & numerical data , Antineoplastic Agents/adverse effects , Antineoplastic Agents/therapeutic use , Chemotherapy-Related Cognitive Impairment/drug therapy , Aged , Memory/drug effects , Surveys and Questionnaires , Cohort StudiesABSTRACT
Vector-borne diseases are a leading cause of death worldwide and pose a substantial unmet medical need. Pathogens binding to host extracellular proteins (the "exoproteome") represents a crucial interface in the etiology of vector-borne disease. Here, we used bacterial selection to elucidate host-microbe interactions in high throughput (BASEHIT)-a technique enabling interrogation of microbial interactions with 3,324 human exoproteins-to profile the interactomes of 82 human-pathogen samples, including 30 strains of arthropod-borne pathogens and 8 strains of related non-vector-borne pathogens. The resulting atlas revealed 1,303 putative interactions, including hundreds of pairings with potential roles in pathogenesis, including cell invasion, tissue colonization, immune evasion, and host sensing. Subsequent functional investigations uncovered that Lyme disease spirochetes recognize epidermal growth factor as an environmental cue of transcriptional regulation and that conserved interactions between intracellular pathogens and thioredoxins facilitate cell invasion. In summary, this interactome atlas provides molecular-level insights into microbial pathogenesis and reveals potential host-directed targets for next-generation therapeutics.
Subject(s)
Host-Pathogen Interactions , Humans , Animals , Lyme Disease/microbiology , Vector Borne Diseases , Host Microbial Interactions , Borrelia burgdorferi/pathogenicity , Borrelia burgdorferi/metabolismABSTRACT
Background: Postoperative ileus (POI) after colorectal surgery leads to increased morbidity, costs, and hospital stays. Identifying POI risk for early intervention is important for improving surgical outcomes especially given the increasing trend towards early discharge after surgery. While existing studies have assessed POI risk with regression models, the role of deep learning's remains unexplored. Methods: We assessed the performance and transferability (brutal force/instance/parameter transfer) of Gated Recurrent Unit with Decay (GRU-D), a longitudinal deep learning architecture, for real-time risk assessment of POI among 7,349 colorectal surgeries performed across three hospital sites operated by Mayo Clinic with two electronic health records (EHR) systems. The results were compared with atemporal models on a panel of benchmark metrics. Results: GRU-D exhibits robust transferability across different EHR systems and hospital sites, showing enhanced performance by integrating new measurements, even amid the extreme sparsity of real-world longitudinal data. On average, for labs, vitals, and assisted living status, 72.2%, 26.9%, and 49.3% respectively lack measurements within 24 hours after surgery. Over the follow-up period with 4-hour intervals, 98.7%, 84%, and 95.8% of data points are missing, respectively. A maximum of 5% decrease in AUROC was observed in brutal-force transfer between different EHR systems with non-overlapping surgery date frames. Multi-source instance transfer witnessed the best performance, with a maximum of 2.6% improvement in AUROC over local learning. The significant benefit, however, lies in the reduction of variance (a maximum of 86% decrease). The GRU-D model's performance mainly depends on the prediction task's difficulty, especially the case prevalence rate. Whereas the impact of training data and transfer strategy is less crucial, underscoring the challenge of effectively leveraging transfer learning for rare outcomes. While atemporal Logit models show notably superior performance at certain pre-surgical points, their performance fluctuate significantly and generally underperform GRU-D in post-surgical hours. Conclusion: GRU-D demonstrated robust transferability across EHR systems and hospital sites with highly sparse real-world EHR data. Further research on built-in explainability for meaningful intervention would be highly valuable for its integration into clinical practice.
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Introduction: Continuous recognition tasks (CRTs) assess episodic memory (EM), the central functional disturbance in Alzheimer's disease and several related disorders. The online MemTrax computerized CRT provides a platform for screening and assessment that is engaging and can be repeated frequently. MemTrax presents complex visual stimuli, which require complex involvement of the lateral and medial temporal lobes and can be completed in less than 2 min. Results include number of correct recognitions (HITs), recognition failures (MISSes = 1-HITs), correct rejections (CRs), false alarms (FAs = 1-CRs), total correct (TC = HITs + CRs), and response times (RTs) for each HIT and FA. Prior analyses of MemTrax CRT data show no effects of sex but an effect of age on performance. The number of HITs corresponds to faster RT-HITs more closely than TC, and CRs do not relate to RT-HITs. RT-HITs show a typical skewed distribution, and cumulative RT-HITs fit a negative survival curve (RevEx). Thus, this study aimed to define precisely the effects of sex and age on HITS, CRs, RT-HITs, and the dynamics of RTs in an engaged population. Methods: MemTrax CRT online data on 18,255 individuals was analyzed for sex, age, and distributions of HITs, CRs, MISSes, FAs, TC, and relationships to both RT-HITs and RT-FAs. Results: HITs corresponded more closely to RT-HITs than did TC because CRs did not relate to RT-HITs. RT-FAs had a broader distribution than RT-HITs and were faster than RT-HITs in about half of the sample, slower in the other half. Performance metrics for men and women were the same. HITs declined with age as RT-HITs increased. CRs also decreased with age and RT-FAs increased, but with no correlation. The group over aged 50 years had RT-HITs distributions slower than under 50 years. For both age ranges, the RevEx model explained more than 99% of the variance in RT-HITs. Discussion: The dichotomy of HITs and CRs suggests opposing cognitive strategies: (1) less certainty about recognitions, in association with slower RT-HITs and lower HIT percentages suggests recognition difficulty, leading to more MISSes, and (2) decreased CRs (more FAs) but faster RTs to HITs and FAs, suggesting overly quick decisions leading to errors. MemTrax CRT performance provides an indication of EM (HITs and RT-HITs may relate to function of the temporal lobe), executive function (FAs may relate to function of the frontal lobe), processing speed (RTs), cognitive ability, and age-related changes. This CRT provides potential clinical screening utility for early Alzheimer's disease and other conditions affecting EM, other cognitive functions, and more accurate impairment assessment to track changes over time.
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Introduction: Peritoneal dialysis (PD)-related peritonitis (PDRP) is a common cause of transfer to hemodialysis, patient morbidity, and is a risk factor for mortality. Associated patient anxiety can deter selection of PD for renal replacement therapy. Diagnosis relies on hospital laboratory tests; however, this might be achieved earlier if such information was available at the point-of-care (POC), thereby significantly improving outcomes. The presence of culturable microbes and the concentration of leukocytes in effluent both aid peritonitis diagnosis, as specified in the International Society for Peritoneal Dialysis (ISPD) diagnostic guidelines. Here, we report the development of 2 new methods providing such information in simple POC tests. Methods: One approach uses a tetrazolium-based chemical reporting system, primarily focused on detecting bacterial contamination and associated vancomycin-sensitivity. The second approach uses a novel forward light-scatter device (QuickCheck) to provide an instant quantitative cell count directly from PD patient effluent. Results: The tetrazolium approach detected and correctly distinguished laboratory isolates, taking 10 hours to provide non-quantitative results. We compared the technical performance of the light scatter leukocyte counting approach with spectrophotometry, hemocytometer counting and flow cytometry (Sysmex) using patient effluent samples. QuickCheck had high accuracy (94%) and was the most precise (coefficient of variation <4%), showing minimal bias, overall performing similarly to flow cytometry. Conclusion: These complementary new approaches provide a simple means to obtain information to assist diagnosis at the POC. The first provides antibiotic sensitivity following 10 hours incubation, whereas the second optical approach (QuickCheck), provides instant accurate total leukocyte count.
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Many intracellular pathogens structurally disrupt the Golgi apparatus as an evolutionarily conserved promicrobial strategy. Yet, the host factors and signaling processes involved are often poorly understood, particularly for Anaplasma phagocytophilum, the agent of human granulocytic anaplasmosis. We found that A. phagocytophilum elevated cellular levels of the bioactive sphingolipid, ceramide-1-phosphate (C1P), to promote Golgi fragmentation that enables bacterial proliferation, conversion from its non-infectious to infectious form, and productive infection. A. phagocytophilum poorly infected mice deficient in ceramide kinase, the Golgi-localized enzyme responsible for C1P biosynthesis. C1P regulated Golgi morphology via activation of a PKCα/Cdc42/JNK signaling axis that culminates in phosphorylation of Golgi structural proteins, GRASP55 and GRASP65. siRNA-mediated depletion of Cdc42 blocked A. phagocytophilum from altering Golgi morphology, which impaired anterograde trafficking of trans-Golgi vesicles into and maturation of the pathogen-occupied vacuole. Cells overexpressing phosphorylation-resistant versions of GRASP55 and GRASP65 presented with suppressed C1P- and A. phagocytophilum-induced Golgi fragmentation and poorly supported infection by the bacterium. By studying A. phagocytophilum, we identify C1P as a regulator of Golgi structure and a host factor that is relevant to disease progression associated with Golgi fragmentation.IMPORTANCECeramide-1-phosphate (C1P), a bioactive sphingolipid that regulates diverse processes vital to mammalian physiology, is linked to disease states such as cancer, inflammation, and wound healing. By studying the obligate intracellular bacterium Anaplasma phagocytophilum, we discovered that C1P is a major regulator of Golgi morphology. A. phagocytophilum elevated C1P levels to induce signaling events that promote Golgi fragmentation and increase vesicular traffic into the pathogen-occupied vacuole that the bacterium parasitizes. As several intracellular microbial pathogens destabilize the Golgi to drive their infection cycles and changes in Golgi morphology is also linked to cancer and neurodegenerative disorder progression, this study identifies C1P as a potential broad-spectrum therapeutic target for infectious and non-infectious diseases.
Subject(s)
Anaplasma phagocytophilum , Neoplasms , Animals , Humans , Mice , Anaplasma phagocytophilum/metabolism , Golgi Apparatus/metabolism , Ceramides , Mammals/metabolismABSTRACT
INTRODUCTION: A valid, reliable, accessible measurement for the early detection of cognitive decline in patients with Parkinson's disease (PD) is in urgent demand. The objective of the study is to assess the clinical utility of the MemTrax Memory Test in detecting cognitive impairment in patients with PD. METHODS: The MemTrax, a fast on-line cognitive screening tool based on continuous recognition task, and Montreal Cognitive Assessment (MoCA) were administered to 61 healthy controls (HC), 102 PD patients with normal cognition (PD-N), 74 PD patients with mild cognitive impairment (PD-MCI) and 52 PD patients with dementia (PD-D). The total percent correct (MTx- %C), average response time (MTx-RT), composite score (MTx-Cp) of MemTrax and the MoCA scores were comparatively analyzed. RESULTS: The MoCA scores were similar between HC and PD-N, however, MTx- %C and MTx-Cp were lower in PD-N than HC(p < 0.05). MTx- %C, MTx-Cp and the MoCA scores were significantly lower in PD-MCI versus PD-N and in PD-D versus PD-MCI (p ≤ 0.001), while MTx-RT was statistically longer in PD-D versus PD-MCI (p ≤ 0.001). For PD groups, the MemTrax performance correlated with the MoCA scores. To detect PD-MCI, the optimal MTx- %C and MTx-Cp cutoff were 75 % and 50.0, respectively. To detect PD-D, the optimal MTx- %C, MTx-RT and MTx-Cp cutoff were 69 %, 1.341s and 40.6, respectively. CONCLUSION: The MemTrax provides rapid, valid and reliable metrics for assessing cognition in PD patients which could be useful for identifying PD-MCI at early stage and monitoring cognitive function decline during the progression of disease.
Subject(s)
Cognitive Dysfunction , Parkinson Disease , Humans , Parkinson Disease/complications , Parkinson Disease/diagnosis , Neuropsychological Tests , Cognitive Dysfunction/diagnosis , Cognitive Dysfunction/etiology , Cognition , Mental Status and Dementia TestsABSTRACT
Canola/oilseed rape (Brassica napus L.) production in Canada has increased to become a foundational crop in the Canadian Prairies and an important economic driver of this region. The increase in seeded area, and by association its reduction in-crop rotation frequency, has made it easier for pests to overcome current recommended agronomic management practices. The Canola Council of Canada has been successful in involving the entire commodity value chain in promoting and strengthening the Canadian canola industry; however, because of this production increase it is critically important to understand, evaluate and mitigate the potential risks of canola yield losses to current and potential pests. This Perspective provides an overview of what are currently the most damaging insects, pathogens and weeds to canola in the Canadian Prairies, potential future threats and opportunities farmers, agronomists and researchers can take to minimize these risks. © 2023 Society of Chemical Industry.
Subject(s)
Brassica napus , Grassland , Canada , AgricultureABSTRACT
Plant breeding is used to develop crops with host resistance to aphids, however, virulent biotypes often develop that overcome host resistance genes. We tested whether the symbionts, Arsenophonus (A) and Wolbachia (W), affect virulence and fecundity in soybean aphid biotypes Bt1 and Bt3 cultured on whole plants and detached leaves of three resistant, Rag1, Rag2 and Rag1 + 2, and one susceptible, W82, soybean genotypes. Whole plants and individual aphid experiments of A. glycines with and without Arsenophonus and Wolbachia did not show differences in overall fecundity. Differences were observed in peak fecundity, first day of deposition, and day of maximum nymph deposition of individual aphids on detached leaves. Bt3 had higher fecundity than Bt1 on detached leaves of all plant genotypes regardless of bacterial profile. Symbionts did not affect peak fecundity of Bt1 but increased it in Bt3 (A+W+) and all Bt3 strains began to deposit nymphs earlier than the Bt1 (A+W-). Arsenophonus in Bt1 delayed the first day of nymph deposition in comparison to aposymbiotic Bt1 except when reared on Rag1 + 2. For the Bt1 and Bt3 strains, symbionts did not result in a significant difference in the day they deposited the maximum number of nymphs nor was there a difference in survival or variability in number of nymphs deposited. Variability of number of aphids deposited was higher in aphids feeding on resistant plant genotypes. The impact of Arsenophonus on soybean aphid patterns of fecundity was dependent on the aphid biotype and plant genotype. Wolbachia alone had no detectable impact but may have contributed to the increased fecundity of Bt3 (A+W+). An individual based model, using data from the detached leaves experiment and with intraspecific competition removed, found patterns similar to those observed in the greenhouse and growth chamber experiments including a significant interaction between soybean genotype and aphid strain. Combining individual data with the individual based model of population growth isolated the impact of fecundity and host resistance from intraspecific competition and host health. Changes to patterns of fecundity, influenced by the composition and concentration of symbionts, may contribute to competitive interactions among aphid genotypes and influence selection on virulent aphid populations.
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BACKGROUND: Accessible measurements for the early detection of mild cognitive impairment (MCI) due to Alzheimer's disease (AD) are urgently needed to address the increasing prevalence of AD. OBJECTIVE: To determine the benefits of a composite MemTrax Memory Test and AD-related blood biomarker assessment for the early detection of MCI-AD in non-specialty clinics. METHODS: The MemTrax Memory Test and Montreal Cognitive Assessment were administered to 99 healthy seniors with normal cognitive function and 101 patients with MCI-AD; clinical manifestation and peripheral blood samples were collected. We evaluated correlations between the MemTrax Memory Test and blood biomarkers using Spearman's rank correlation analyses and then built discrimination models using various machine learning approaches that combined the MemTrax Memory Test and blood biomarker results. The models' performances were assessed according to the areas under the receiver operating characteristic curve. RESULTS: The MemTrax Memory Test and Montreal Cognitive Assessment areas under the curve for differentiating patients with MCI-AD from the healthy controls were similar. The MemTrax Memory Test strongly correlated with phosphorylated tau 181 and amyloid-ß42/40. The area under the curve for the best composite MemTrax Memory Test and blood biomarker model was 0.975 (95% confidence interval: 0.950-0.999). CONCLUSION: Combining MemTrax Memory Test and blood biomarker results is a promising new technique for the early detection of MCI-AD.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Humans , Alzheimer Disease/diagnosis , Cognitive Dysfunction/psychology , tau Proteins , Biomarkers , Early Diagnosis , Amyloid beta-PeptidesABSTRACT
BACKGROUND: As primary care populations age, timely identification of palliative care need is becoming increasingly relevant. Previous studies have targeted particular patient populations with life-limiting disease, but few have focused on patients in a primary care setting. Toward this end, we propose a stepped-wedge pragmatic randomized trial whereby a machine learning algorithm identifies patients empaneled to primary care units at Mayo Clinic (Rochester, Minnesota, United States) with high likelihood of palliative care need. METHODS: 42 care team units in 9 clusters were randomized to 7 wedges, each lasting 42 days. For care teams in treatment wedges, palliative care specialists review identified patients, making recommendations to primary care providers when appropriate. Care teams in control wedges receive palliative care under the standard of care. DISCUSSION: This pragmatic trial therefore integrates machine learning into clinical decision making, instead of simply reporting theoretical predictive performance. Such integration has the possibility to decrease time to palliative care, improving patient quality of life and symptom burden. TRIAL REGISTRATION: Clinicaltrials.gov NCT04604457 , restrospectively registered 10/26/2020. PROTOCOL: v0.5, dated 9/23/2020.
Subject(s)
Hospice and Palliative Care Nursing , Palliative Care , Humans , Palliative Care/methods , Patients , Primary Health Care , Quality of Life , Randomized Controlled Trials as Topic , Pragmatic Clinical Trials as TopicABSTRACT
CONTEXT: Palliative care services are commonly provided to hospitalized patients, but accurately predicting who needs them remains a challenge. OBJECTIVES: To assess the effectiveness on clinical outcomes of an artificial intelligence (AI)/machine learning (ML) decision support tool for predicting patient need for palliative care services in the hospital. METHODS: The study design was a pragmatic, cluster-randomized, stepped-wedge clinical trial in 12 nursing units at two hospitals over a 15-month period between August 19, 2019, and November 17, 2020. Eligible patients were randomly assigned to either a medical service consultation recommendation triggered by an AI/ML tool predicting the need for palliative care services or usual care. The primary outcome was palliative care consultation note. Secondary outcomes included: hospital readmissions, length of stay, transfer to intensive care and palliative care consultation note by unit. RESULTS: A total of 3183 patient hospitalizations were enrolled. Of eligible patients, A total of 2544 patients were randomized to the decision support tool (1212; 48%) and usual care (1332; 52%). Of these, 1717 patients (67%) were retained for analyses. Patients randomized to the intervention had a statistically significant higher incidence rate of palliative care consultation compared to the control group (IRR, 1.44 [95% CI, 1.11-1.92]). Exploratory evidence suggested that the decision support tool group reduced 60-day and 90-day hospital readmissions (OR, 0.75 [95% CI, 0.57, 0.97]) and (OR, 0.72 [95% CI, 0.55-0.93]) respectively. CONCLUSION: A decision support tool integrated into palliative care practice and leveraging AI/ML demonstrated an increased palliative care consultation rate among hospitalized patients and reductions in hospitalizations.
Subject(s)
Artificial Intelligence , Palliative Care , Humans , Hospitalization , Patient Readmission , Referral and ConsultationABSTRACT
Increased prevalence and abundance of Selenomonas sputigena have been associated with periodontitis, a chronic inflammatory disease of tooth-supporting tissues, for more than 50 years. Over the past decade, molecular surveys of periodontal disease using 16S and shotgun metagenomic sequencing approaches have confirmed the disease association of classically recognized periodontal pathogens such as Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia while highlighting previously underappreciated organisms such as Filifactor alocis and S. sputigena. Despite abundant clinical association between S. sputigena and periodontal disease, we have little to no understanding of its pathogenic potential, and virulence mechanisms have not been studied. In this study, we sought to characterize the response of gingival epithelial cells to infection with S. sputigena. Here, we show that S. sputigena attaches to gingival keratinocytes and induces expression and secretion of cytokines and chemokines associated with inflammation and leukocyte recruitment. We demonstrate that S. sputigena induces signaling through Toll-like receptor 2 (TLR2) and TLR4 but evades activation of TLR5. Cytokines released from S. sputigena-infected keratinocytes induced monocyte and neutrophil chemotaxis. These results show that S. sputigena-host interactions have the potential to contribute to bacterially driven inflammation and tissue destruction, the hallmark of periodontitis. Characterization of previously unstudied pathogens may provide novel approaches to develop therapeutics to treat or prevent periodontal disease.
Subject(s)
Periodontal Diseases , Periodontitis , Humans , Inflammation , Periodontitis/pathology , Porphyromonas gingivalis/metabolism , Cytokines/metabolism , Epithelial Cells/metabolismABSTRACT
A critical issue in addressing medical conditions is measurement. Memory measurement is difficult, especially episodic memory, which is disrupted by many conditions. On-line computer testing can precisely measure and assess several memory functions. This study analyzed memory performances from a large group of anonymous, on-line participants using a continuous recognition task (CRT) implemented at https://memtrax.com. These analyses estimated ranges of acceptable performance and average response time (RT). For 344,165 presumed unique individuals completing the CRT a total of 602,272 times, data were stored on a server, including each correct response (HIT), Correct Rejection, and RT to the thousandth of a second. Responses were analyzed, distributions and relationships of these parameters were ascertained, and mean RTs were determined for each participant across the population. From 322,996 valid first tests, analysis of correctness showed that 63% of these tests achieved at least 45 correct (90%), 92% scored at or above 40 correct (80%), and 3% scored 35 correct (70%) or less. The distribution of RTs was skewed with 1% faster than 0.62 s, a median at 0.890 s, and 1% slower than 1.57 s. The RT distribution was best explained by a novel model, the reverse-exponential (RevEx) function. Increased RT speed was most closely associated with increased HIT accuracy. The MemTrax on-line memory test readily provides valid and reliable metrics for assessing individual episodic memory function that could have practical clinical utility for precise assessment of memory dysfunction in many conditions, including improvement or deterioration over time.
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Background: Lyme disease (LD) is the most common tick-borne illness in North America. LD is acquired through exposure to the tick vector, Ixodes scapularis, known as the blacklegged tick. In Canada, LD is rapidly emerging, with the establishment of I. scapularis in many newly endemic regions posing a growing risk to local communities. In the Canadian context, many environmental and socioeconomic risk factors for human LD infection are yet to be ascertained and the degree of risk associated with residential and community exposure to ticks is not well known. Methods: We conducted a matched case-control study in southeastern Ontario, using LD patient data from provincial laboratory databases and uninfected population controls from 2014 to 2018. We aimed to identify area-level risk factors for LD and associations with residence in environmental risk areas, defined as areas with high model-predicted probability of I. scapularis occurrence, using the neighborhood dissemination area as the unit of analysis. Results: Using multivariable conditional logistic regression analysis, we identified that patients with LD had higher odds (odds ratio, OR; 95% confidence interval, CI) of living in neighborhoods with high probability of tick occurrence in the environment (OR = 2.2; 95% CI: 2.0-2.5), low walkability (OR = 1.6; 95% CI: 1.2-2.1), low material deprivation (OR = 1.4; 95% CI: 1.2-1.7), and low ethnic concentration (OR = 8.1; 95% CI: 6.7-9.9). We also found that the odds of LD infection for individuals residing in environmental risk areas was highest for those living in public health units (PHUs) with <250,000 population (OR = 3.0; 95% CI: 2.4-3.9) compared to those living in PHUs with >1,000,000 population (OR = 1.5; 95% CI: 1.1-2.1). Conclusion: This study shows that odds of human LD infection in Ontario, Canada is higher in less urbanized areas with higher socioeconomic status and indicates that exposure to ticks around the home residence or neighborhood is linked to increased odds of LD.
Subject(s)
Lyme Disease , Social Class , Animals , Humans , Case-Control Studies , Ontario/epidemiology , Socioeconomic Factors , Lyme Disease/epidemiology , Lyme Disease/veterinaryABSTRACT
Anaplasma phagocytophilum is the etiologic agent of the emerging infection, granulocytic anaplasmosis. This obligate intracellular bacterium lives in a host cell-derived vacuole that receives membrane traffic from multiple organelles to fuel its proliferation and from which it must ultimately exit to disseminate infection. Understanding of these essential pathogenic mechanisms has remained poor. Multivesicular bodies (MVBs) are late endosomal compartments that receive biomolecules from other organelles and encapsulate them into intralumenal vesicles (ILVs) using endosomal sorting complexes required for transport (ESCRT) machinery and ESCRT-independent machinery. Association of the ESCRT-independent protein, ALIX, directs MVBs to the plasma membrane where they release ILVs as exosomes. We report that the A. phagocytophilum vacuole (ApV) is acidified and enriched in lysobisphosphatidic acid, a lipid that is abundant in MVBs. ESCRT-0 and ESCRT-III components along with ALIX localize to the ApV membrane. siRNA-mediated inactivation of ESCRT-0 and ALIX together impairs A. phagocytophilum proliferation and infectious progeny production. RNA silencing of ESCRT-III, which regulates ILV scission, pronouncedly reduces ILV formation in ApVs and halts infection by arresting bacterial growth. Rab27a and its effector Munc13-4, which drive MVB trafficking to the plasma membrane and subsequent exosome release, localize to the ApV. Treatment with Nexinhib20, a small molecule inhibitor that specifically targets Rab27a to block MVB exocytosis, abrogates A. phagocytophilum infectious progeny release. Thus, A. phagocytophilum exploits MVB biogenesis and exosome release to benefit each major stage of its intracellular infection cycle: intravacuolar growth, conversion to the infectious form, and exit from the host cell. IMPORTANCE Anaplasma phagocytophilum causes granulocytic anaplasmosis, a globally emerging zoonosis that can be severe, even fatal, and for which antibiotic treatment options are limited. A. phagocytophilum lives in an endosomal-like compartment that interfaces with multiple organelles and from which it must ultimately exit to spread within the host. How the bacterium accomplishes these tasks is poorly understood. Multivesicular bodies (MVBs) are intermediates in the endolysosomal pathway that package biomolecular cargo from other organelles as intralumenal vesicles for release at the plasma membrane as exosomes. We discovered that A. phagocytophilum exploits MVB biogenesis and trafficking to benefit all aspects of its intracellular infection cycle: proliferation, conversion to its infectious form, and release of infectious progeny. The ability of a small molecule inhibitor of MVB exocytosis to impede A. phagocytophilum dissemination indicates the potential of this pathway as a novel host-directed therapeutic target for granulocytic anaplasmosis.
Subject(s)
Anaplasma phagocytophilum , Anaplasmosis , Cell Proliferation , Multivesicular Bodies , Organelle Biogenesis , Animals , Anaplasma phagocytophilum/pathogenicity , Anaplasma phagocytophilum/physiology , Anaplasmosis/metabolism , Anaplasmosis/microbiology , Endosomal Sorting Complexes Required for Transport/metabolism , Multivesicular Bodies/metabolism , Protein TransportABSTRACT
The causes that trigger the onset of dementia are still unknown. Recently there has been an increasing interest in the possible role of infectious agents in the brain in the pathogenesis of this condition. Amongst the viruses, members of the Herpesviridae family, namely herpes simplex virus-1 (HSV1), cytomegalovirus (CMV), human herpesvirus-6 (HHV6), human herpesvirus-7 (HHV7) and varicella zoster virus (VZV) have been suggested as potential causes of the disease. However, the relative importance of these and other viruses in contributing to dementia remains unclear. We evaluated the association between seropositivity status of all viruses available in a large, population-based dataset (the UK Biobank) and dementia risk in an unbiased way. Of the 15 viruses investigated, our results showed a statistically significant increase of dementia risk associated only with HSV1 seropositivity (OR 2.14, 95% C.I. 1.21-3.81). However, by combining the data we found that seropositivity for 4 viruses (HSV1, HHV6, HHV7 and VZV) also significantly increases the risk of dementia (OR = 2.37, 95% C.I. 1.43-3.92). These four viruses have been described previously as neurotropic viruses. Our results provide support for a role for neurotropic viruses in the pathology of dementia.
Subject(s)
Dementia , Herpesvirus 1, Human , Herpesvirus 6, Human , Herpesvirus 7, Human , Antibody Formation , Biological Specimen Banks , Dementia/epidemiology , Herpesvirus 3, Human , Humans , United Kingdom/epidemiologyABSTRACT
BACKGROUND: Post-surgical complications (PSCs) have been an increasing concern for hospitals in light of Medicare penalties for 30-day readmissions. PSCs have become a target for quality improvement and benchmark for the healthcare system. Over half (60 %) of the deep or organ space surgical site infections are discovered after discharge, leading to a readmission. There has thus been a push to develop risk prediction models for targeted preventive interventions for PSCs. OBJECTIVE: We experiment several Gated Recurrent Unit with Decay (GRU-D) based deep learning architectures with various feature sampling schemes in predicting the risk of colorectal PSCs and compare with atemporal logistic regression models (logit). METHOD: We used electronic health record (EHR) data of 3,535 colorectal surgical patients involved in the national surgical quality improvement program (NSQIP) between 2006 and 2018. Single layer, stacked layer, and multimodal GRU-D models with sigmoid activation were used to develop risk prediction models. Area Under the Receiver Operating Characteristic curve (AUROC) was calculated by comparing predicted probability of developing complications versus truly observed PSCs (NSQIP adjudicated) within 30 days after surgery. We set up cross-validation and an independent held-out dataset for testing model performance consistency. RESULTS AND CONCLUSION: The primary contribution of our study is the formulation of a novel real-time PSC risk prediction task using GRU-D with demonstrated clinical utility. GRU-D outperforms the logit model in predicting wound and organ space infection and shows improved performance as additional data points become available. Logit model outperforms GRU-D before surgery for superficial infection and bleeding. For the same sampling scheme, there is no obvious advantage of complex architectures (stacked, multimodal) over single layer GRU-D. Obtaining more data points closer to the occurrence of PSCs is more important than using a more frequent sampling scheme in training GRU-D models. The fourth predicted risk quartile by single layer GRU-D contains 63 %, 59 %, and 66 % organ space infection cases, at 4 h before, 72 h after, and 168 h after surgery, respectively, suggesting its potential application as a bedside risk assessment tool.
Subject(s)
Colorectal Neoplasms , Colorectal Surgery , Aged , Humans , United States , Colorectal Surgery/adverse effects , Medicare , Patient Readmission , Surgical Wound Infection/epidemiology , Surgical Wound Infection/complications , Risk Assessment/methods , Postoperative Complications/epidemiology , Postoperative Complications/etiology , Retrospective StudiesABSTRACT
The American dog tick, Dermacentor variabilis, is a tick of public and veterinary health importance in North America. Using passive tick surveillance data, we document distribution changes for the American dog tick in Ontario, Canada, from 2010 through 2018. Dermacentor variabilis submissions from the public were geocoded and aggregated-from large to small administrative geographies-by health region, public health unit (PHU) and Forward Sortation Area (FSA). PHU hot spots with high rates of D. variabilis submissions were (1) Brant County, Haldimand-Norfolk and Niagara Regional in the Central West region and (2) Lambton and Winsor-Essex County in the South West region. The number of established D. variabilis populations with ≥ 6 submissions per year increased significantly during the study at regional (PHUs: 22 to 31) and local (FSAs: 27 to 91) scales. The range of D. variabilis increased similarly to the positive control (Ixodes scapularis) during the study and in contrast to the static range of the negative control (Ixodes cookei). Submission hot spots were in warmer, low elevation areas with poorly drained soils, compared to the province's low submission areas. Dermacentor variabilis is spreading in Ontario and continued research into their vector ecology is required to assess medicoveterinary health risks.
Subject(s)
Ixodes , Rhipicephalus sanguineus , Animals , Data Collection , Dogs , New Jersey , Ontario/epidemiologyABSTRACT
Background: Lyme disease (caused by Borrelia burgdorferi) is an infectious disease transmitted to humans by a bite from infected blacklegged ticks (Ixodes scapularis) in eastern North America. Lyme disease can be prevented if antibiotic prophylaxis is given to a patient within 72 hours of a blacklegged tick bite. Therefore, recognizing a blacklegged tick could facilitate the management of Lyme disease. Methods: In this work, we build an automated detection tool that can differentiate blacklegged ticks from other tick species using advanced computer vision approaches in real-time. Specially, we use convolution neural network models, trained end-to-end, to classify tick species. Also, advanced knowledge transfer techniques are adopted to improve the performance of convolution neural network models. Results: Our best convolution neural network model achieves 92% accuracy on unseen tick species. Conclusion: Our proposed vision-based approach simplifies tick identification and contributes to the emerging work on public health surveillance of ticks and tick-borne diseases. In addition, it can be integrated with the geography of exposure and potentially be leveraged to inform the risk of Lyme disease infection. This is the first report of using deep learning technologies to classify ticks, providing the basis for automation of tick surveillance, and advancing tick-borne disease ecology and risk management.