Search

Abstract Background Dementia care is challenging due to the divergent trajectories in disease progression and outcomes. Predictive models are needed to flag patients at risk of near-term mortality and identify factors contributing to mortality risk across different dementia types. Methods Here, we developed machine-learning models predicting dementia patient mortality at four different survival thresholds using a dataset of 45,275 unique participants and 163,782 visit records from the U.S. National Alzheimer’s Coordinating Center (NACC). We built multi-factorial XGBoost models using a small set of mortality predictors and conducted stratified analyses with dementiatype-specific models. Results Our models achieved an area under the receiver operating characteristic curve (AUC-ROC) of over 0.82 utilizing nine parsimonious features for all 1-, 3-, 5-, and 10-year thresholds. The trained models mainly consisted of dementia-related predictors such as specific neuropsychological tests and were minimally affected by other age-related causes of death, e.g., stroke and cardiovascular conditions. Notably, stratified analyses revealed shared and distinct predictors of mortality across eight dementia types. Unsupervised clustering of mortality predictors grouped vascular dementia with depression and Lewy body dementia with frontotemporal lobar dementia. Conclusions This study demonstrates the feasibility of flagging dementia patients at risk of mortality for personalized clinical management. Parsimonious machine-learning models can be used to predict dementia patient mortality with a limited set of clinical features, and dementiatype-specific models can be applied to heterogeneous dementia patient populations.

The accurate visualization and assessment of the complex cardiac and pulmonary structures in 3D is critical for the diagnosis and treatment of cardiovascular and respiratory disorders. Conventional 3D cardiac magnetic resonance imaging (MRI) techniques suffer from long acquisition times, motion artifacts, and limited spatiotemporal resolution. This study proposes a novel time-resolved 3D cardiopulmonary MRI reconstruction method based on spatial transformer networks (STNs) to reconstruct the 3D cardiopulmonary MRI acquired using 3D center-out radial ultra-short echo time (UTE) sequences. The proposed reconstruction method employed an STN-based deep learning framework, which used a combination of data-processing, grid generator, and sampler. The reconstructed 3D images were compared against the start-of-the-art time-resolved reconstruction method. The results showed that the proposed time-resolved 3D cardiopulmonary MRI reconstruction using STNs offers a robust and efficient approach to obtain high-quality images. This method effectively overcomes the limitations of conventional 3D cardiac MRI techniques and has the potential to improve the diagnosis and treatment planning of cardiopulmonary disorders.

Abstract Ticks are vectors of many diseases and are expanding in geographic distribution. However, how ticks will fare in their new environments, where they may experience stressful climatic conditions at the expansion front, remains unclear. Since there is a trade‐off in ticks between behaviors that promote longevity and behaviors that promote reproduction, we hypothesized that extreme climatic stress reduces the survivorship of ticks but increases the frequency of tick host‐seeking behavior, or questing. Here, we used a novel method to simulate climatic stress on individual ticks of three species—Amblyomma americanum, Dermacentor variabilis, and Ixodes scapularis—to evaluate their survival, physiology, and questing behavior. The first experiment involved placing 144 adult ticks of each species in two temperature ranges (15–25°C and 25–35°C) and three relative humidity (RH) treatments (32%, 58%, and 84% RH). We assessed the ticks daily for survivorship and questing, and we measured water loss by comparing the mass of each tick when it died to when it was fully hydrated. In this first experiment, ticks in warmer and less humid conditions generally died faster than those in cooler and more humid conditions. Ticks of all three species were more likely to quest shortly before their death and consistently died after losing approximately 50%–56% of their total body water content, but Ixodes reached that threshold much faster than the other two species. The second experiment involved placing 18 ticks of each species at 35°C and 32% RH. We assessed the ticks every 3 h for survivorship, questing, and water loss. Ticks again were more likely to quest shortly before their death. With frequent checks, we were able to measure the dehydration tolerance more accurately and the rate of water loss. Ticks of all three species consistently died after losing approximately 51% of their total body water content. However, Ixodes lost water approximately 5 times faster than Amblyomma and 11 times faster than Dermacentor. These results demonstrate that severe climatic stress tilts the trade‐off toward higher questing rates but not higher overall questing time because of reduced survival rates.

Neurovascular 4D-Flow MRI has emerged as a powerful tool for comprehensive cerebrovascular hemodynamic characterization. Clinical studies in at risk populations such as aging adults indicate hemodynamic markers can be confounded by motion-induced bias. This study develops and characterizes a high fidelity 3D self-navigation approach for retrospective rigid motion correction of neurovascular 4D-Flow data. A 3D radial trajectory with pseudorandom ordering was combined with a multi-resolution low rank regularization approach to enable high spatiotemporal resolution self-navigators from extremely undersampled data. Phantom and volunteer experiments were performed at 3.0T to evaluate the ability to correct for different amounts of induced motions. In addition, the approach was applied to clinical-research exams from ongoing aging studies to characterize performance in the clinical setting. Simulations, phantom and volunteer experiments with motion correction produced images with increased vessel conspicuity, reduced image blurring, and decreased variability in quantitative measures. Clinical exams revealed significant changes in hemodynamic parameters including blood flow rates, flow pulsatility index, and lumen areas after motion correction in probed cerebral arteries (Flow: P

Outdoor recreation continues to be persistently high in national parks across the United States, particularly as the COVID-19 pandemic has led to increased use. In popular frontcountry destinations such as national park campgrounds managers are challenged with new issues more familiar to urban settings. One of these challenges is waste management. The largest source of visitor-generated waste in national parks is campgrounds. This research uses a mixed-methods approach to develop and test strategic communications designed to increase recycling and minimize trash to the landfill by altering campground visitor behaviors. Intercept surveys were used to create theory-based messages, and a quasi-experimental approach was used to evaluate message effectiveness. Our results show that messages emphasizing ease concepts were two times more effective at changing campground visitor waste disposal behaviors than control conditions. The results help inform the management of visitors as national parks strive to meet sustainability goals.

With the increased availability of unmanned aerial systems (UAS) imagery, digitalized forest inventory has gained prominence in recent years. This paper presents a methodology for automated measurement of tree height and crown area in two broadleaf tree plantations of different species and ages using two different UAS platforms. Using structure from motion (SfM), we generated canopy height models (CHMs) for each broadleaf plantation in Indiana, USA. From the CHMs, we calculated individual tree parameters automatically through an open-source web tool developed using the Shiny R package and assessed the accuracy against field measurements. Our analysis shows higher tree measurement accuracy with the datasets derived from multi-rotor platform (M600) than with the fixed wing platform (Bramor). The results show that our automated method could identify individual trees (F-score > 90%) and tree biometrics (root mean square error < 1.2 m for height and 2 for the crown area) with reasonably good accuracy. Moreover, our automated tool can efficiently calculate tree-level biometric estimations for 4600 trees within 30 min based on a CHM from UAS-SfM derived images. This automated UAS imagery approach for tree-level forest measurements will be beneficial to landowners and forest managers by streamlining their broadleaf forest measurement and monitoring effort.

ObjectiveTumor metastasis and resistance to chemotherapy are two critical factors that contribute to the high death rate of colorectal cancer (CRC) patients. Metastasis is facilitated by the epithelial-mesenchymal transition (EMT) of tumor cells, which has emerged not only as a fundamental process during metastasis, but is also a key process leading to chemoresistance of cancer cells. However, the underlying mechanisms of EMT in CRC cell remain unknown. Here, we aim to assess the role of dual serine/threonine and tyrosine protein kinase (DSTYK) in CRC metastasis and chemoresistance.MethodsTo study the role of DSTYK in TGF-β-induced EMT, we employed techniques including Crispr/Cas9 knockout (KO) to generate DSTYK KO cell lines, RT-PCR to detect the mRNA expression, immunofluorescence analyses, and western blots to detect protein levels of DSTYK in the following 4 cell lines: control LS411N-TβRII and LS411N-TβRII/DSTYK KO, control LS513 and LS513/DSTYK KO cells, treated with/without TGF-β. The effects of DSTYK on apoptosis were investigated by MTT assays, flow cytometry assays, and TUNEL assays. The expression of DSTYK in CRC patients and its correlation with EMT markers were determined by bioinformatics analysis. For in vivo analysis, both xenograft and orthotopic tumor mouse models were employed to investigate the function of DSTYK in chemoresistance and metastasis of tumors.ResultsIn this study, we demonstrate that the novel kinase DSTYK promotes both TGF-β-induced EMT and the subsequent chemoresistance in CRC cells. DSTYK KO significantly attenuates TGF-β–induced EMT and chemoresistance in CRC cells. According to the Gene Expression Omnibus (GEO) database, the expression of DSTYK is not only positively correlated to the expression of TGF-β, but proportional to the death rate of CRC patients as well. Evidently, the expression of DSTYK in the metastatic colorectal cancer samples from patients was significantly higher than that of primary colorectal cancer samples. Further, we demonstrate in mouse models that chemotherapeutic drug treatment suppresses the growth of DSTYK KO tumors more effectively than control tumors.ConclusionOur findings identify DSTYK as a novel protein kinase in regulating TGF-β–mediated EMT and chemoresistance in CRC cells, which defines DSTYK as a potential therapeutic target for CRC therapy.

This paper introduces a detailed procedure to utilize the high temporal and spatial resolution capabilities of an unmanned aerial system (UAS) to document vegetation at regular intervals both before and after a planned disturbance, a key component in natural disturbance-based management (NDBM), which uses treatments such as harvest and prescribed burns toward the removal of vegetation fuel loads. We developed a protocol and applied it to timber harvest and prescribed burn events. Geographic image-based analysis (GEOBIA) was used for the classification of UAS orthomosaics. The land cover classes included (1) bare ground, (2) litter, (3) green vegetation, and (4) burned vegetation for the prairie burn site, and (1) mature canopy, (2) understory vegetation, and (3) bare ground for the timber harvest site. Sample datasets for both kinds of disturbances were used to train a support vector machine (SVM) classifier algorithm, which produced four land cover classifications for each site. Statistical analysis (a two-tailed t-test) indicated there was no significant difference in image classification efficacies between the two disturbance types. This research provides a framework to use UASs to assess land cover, which is valuable for supporting effective land management practices and ensuring the sustainability of land practices along with other planned disturbances, such as construction and mining.

A systematic analysis of lignin biosynthetic genes to quantitatively understand their effect on wood properties is still lacking. Here, the authors integrate transcriptomic, proteomic, fluxomic and phenomic data to quantify the impact of perturbations of transcript abundance on lignin biosynthesis and wood properties.

Objective: To investigate associations between peripheral innate immune activation and frontotemporal lobar degeneration (FTLD) in progranulin gene (GRN) haploinsufficiency.Methods: In this cross-sectional study, ELISA was used to measure six markers of innate immunity (sCD163, CCL18, LBP, sCD14, IL-18, and CRP) in plasma from 30 GRN mutation carriers (17 asymptomatic, 13 symptomatic) and 29 controls. Voxel based morphometry was used to model associations between marker levels and brain atrophy in mutation carriers relative to controls. Linear regression was used to model relationships between plasma marker levels with mean frontal white matter integrity [fractional anisotropy (FA)] and the FTLD modified Clinical Dementia Rating Scale sum of boxes score (FTLD-CDR SB).Results: Plasma sCD163 was higher in symptomatic GRN carriers [mean 321 ng/ml (SD 125)] compared to controls [mean 248 ng/ml (SD 58); p < 0.05]. Plasma CCL18 was higher in symptomatic GRN carriers [mean 56.9 pg/ml (SD 19)] compared to controls [mean 40.5 pg/ml (SD 14); p < 0.05]. Elevation of plasma LBP was associated with white matter atrophy in the right frontal pole and left inferior frontal gyrus (p FWE corrected

The semantic variant of primary progressive aphasia (svPPA) is a clinical syndrome characterized by semantic memory deficits with relatively preserved motor speech, syntax, and phonology. There is consistent evidence linking focal neurodegeneration of the anterior temporal lobes (ATL) to the semantic deficits observed in svPPA. Less is known about large-scale functional connectivity changes in this syndrome, particularly regarding the interplay between affected and spared language networks that leads to the unique cognitive dissociations typical of svPPA.Using whole-brain, seed-based connectivity on task-free Magnetic Resonance Imaging (MRI) data, we studied connectivity of networks anchored to three left-hemisphere regions crucially involved in svPPA symptomatology: ATL just posterior to the main atrophic area, opercular inferior frontal gyrus, and posterior inferior temporal lobe. First, in 32 healthy controls, these seeds isolated three networks: a ventral semantic network involving anterior middle temporal and angular gyri, a dorsal articulatory-phonological system involving inferior frontal and supramarginal regions, and a third functional connection between posterior inferior temporal and intraparietal regions likely involved in linking visual and linguistic processes. We then compared connectivity strength of these three networks between 16 svPPA patients and the 32 controls. In svPPA, decreased functional connectivity in the ventral semantic network correlated with weak semantic skills, while connectivity of the network seeded from the posterior inferior temporal lobe, though not significantly different between the two groups, correlated with pseudoword reading skills. Increased connectivity between the inferior frontal gyrus and the superior portion of the angular gyrus suggested possible adaptive changes.Our findings have two main implications. First, they support a functional subdivision of the left IPL based on its connectivity to specific language-related regions. Second, the unique neuroanatomical and linguistic profile observed in svPPA provides a compelling model for the functional interplay of these networks, being either up- or down- regulated in response to disease. Keywords: Primary progressive aphasia, Functional connectivity, Resting-state connectivity, Language, Parietal lobe

The present study investigated the pattern of longitudinal changes in cognition and anatomy in three variants of primary progressive aphasia (PPA). Eight patients with the non-fluent variant of PPA (nfvPPA), 13 patients with the semantic variant (svPPA), seven patients with the logopenic variant (lvPPA), and 29 age-matched, neurologically healthy controls were included in the study. All participants underwent longitudinal MRI, neuropsychological and language testing at baseline and at a 1-year follow-up. Tenser-based morphometry (TBM) was applied to T1-weighted MRI images in order to map the progression of gray and white matter atrophy over a 1-year period. Results showed that each patient group was characterized by a specific pattern of cognitive and anatomical changes. Specifically, nfvPPA patients showed gray matter atrophy progression in the left frontal and subcortical areas as well as a decline in motor speech and executive functions; svPPA patients presented atrophy progression in the medial and lateral temporal lobe and decline in semantic memory abilities; and lvPPA patients showed atrophy progression in lateral/posterior temporal and medial parietal regions with a decline in memory, sentence repetition and calculations. In addition, in all three variants, the white matter fibers underlying the abovementioned cortical areas underwent significant volume contraction over a 1-year period. Overall, these results indicate that the three PPA variants present distinct patterns of neuroanatomical contraction, which reflect their clinical and cognitive progression.

Five persons contracted tick-borne relapsing fever after staying in a cabin in western Montana. Borrelia hermsii was isolated from the blood of two patients, and Ornithodoros hermsi ticks were collected from the cabin, the first demonstration of this bacterium and tick in Montana. Relapsing fever should be considered when patients who reside or have vacationed in western Montana exhibit a recurring febrile illness.

The proteasome is a key regulator of cellular protein homeostasis and is a clinically validated anticancer target. The immunoproteasome, a subtype of proteasome expressed mainly in hematopoietic cells, was initially recognized for its role in antigen presentation during the immune response. Recently, the immunoproteasome has been implicated in several disease conditions including cancer and autoimmune disorders, but many of the factors contributing to these pathological processes remain unknown. In particular, the codon 60 polymorphism of the PSMB9 gene encoding the β1i immunoproteasome catalytic subunit has been investigated in the context of a variety of diseases. Despite this, previous studies have so far reported inconsistent findings regarding the impact of this polymorphism on proteasome activity. Thus, we set out to investigate the impact of the PSMB9 codon 60 polymorphism on the expression and activity of the β1i immunoproteasome subunit in a panel of human cancer cell lines. The β1i-selective fluorogenic substrate Acetyl-Pro-Ala-Leu-7-amino-4-methylcoumarin was used to specifically measure β1i catalytic activity. Our results indicate that the codon 60 Arg/His polymorphism does not significantly alter the expression and activity of β1i among the cell lines tested. Additionally, we also examined the expression of β1i in clinical samples from colon and pancreatic cancer patients. Our immunohistochemical analyses showed that ≈ 70% of clinical colon cancer samples and ≈ 53% of pancreatic cancer samples have detectable β1i expression. Taken together, our results indicate that the β1i subunit of the immunoproteasome is frequently expressed in colon and pancreatic cancers but that the codon 60 genetic variants of β1i display similar catalytic activities and are unlikely to contribute to the significant inter-cell-line and inter-individual variabilities in the immunoproteasome activity.