Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment

Subjective cognitive decline (SCD) is a high‐risk yet less understood status before developing Alzheimer's disease (AD). This work included 76 SCD individuals with two (baseline and 7 years later) neuropsychological evaluations and a baseline T1‐weighted structural MRI. A machine learning‐based model was trained based on 198 baseline neuroimaging (morphometric) features and a battery of 25 clinical measurements to discriminate 24 progressive SCDs who converted to mild cognitive impairment (MCI) at follow‐up from 52 stable SCDs. The SCD progression was satisfactorily predicted with the combined features. A history of stroke, a low education level, a low baseline MoCA score, a shrunk left amygdala, and enlarged white matter at the banks of the right superior temporal sulcus were found to favor the progression. This is to date the largest retrospective study of SCD‐to‐MCI conversion with the longest follow‐up, suggesting predictable far‐future cognitive decline for the risky populations with baseline measures only. These findings provide valuable knowledge to the future neuropathological studies of AD in its prodromal phase.

Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review

We performed a systematic review of studies focusing on the automatic prediction of the progression of mild cognitive impairment to Alzheimer's disease (AD) dementia, and a quantitative analysis of the methodological choices impacting performance. This review included 172 articles, from which 234 experiments were extracted. For each of them, we reported the used data set, the feature types, the algorithm type, performance and potential methodological issues. The impact of these characteristics on the performance was evaluated using a multivariate mixed effect linear regressions. We found that using cognitive, fluorodeoxyglucose-positron emission tomography or potentially electroencephalography and magnetoencephalography variables significantly improved predictive performance compared to not including them, whereas including other modalities, in particular T1 magnetic resonance imaging, did not show a significant effect. The good performance of cognitive assessments questions the wide use of imaging for predicting the progression to AD and advocates for exploring further fine domain-specific cognitive assessments. We also identified several methodological issues, including the absence of a test set, or its use for feature selection or parameter tuning in nearly a fourth of the papers. Other issues, found in 15% of the studies, cast doubts on the relevance of the method to clinical practice. We also highlight that short-term predictions are likely not to be better than predicting that subjects stay stable over time. These issues highlight the importance of adhering to good practices for the use of machine learning as a decision support system for the clinical practice.

[Establishment of nutrition literacy core items for Chinese preschool children]

Objective: To establish the nutrition literacy core items for preschool children in China. Methods: The framework system and preliminary items of nutrition literacy were established through literature review and experts consultation. E-Delphi method was used to determine the nutrition literacy items. Nine experts in the field of nutrition, child and adolescent health, health education were invited to score the importance of each nutrition literacy item via Email. The judgment basis and familiarity of experts towards the items, active coefficient, authority coefficient and harmony coefficient were evaluated and analyzed to generate the final list of nutrition literacy items. Results: In the first round of E-Delphi consultation, the active coefficient and authority coefficient were 88.9%(8/9) and(0.88±0.07).The harmony coefficient was 0.350 (χ²=36.432, P=0.001). In the second round, the active coefficient and authority coefficient were 100% (9/9) and (0.89±0.11).The harmony coefficient was 0.347 (χ²=34.330, P<0.001). After qualitative and quantitative analyses, we identified the final list of nutrition literacy items consisting of two scales (basic knowledge, lifestyles and dietary behaviors), six subscales (food knowledge, food characteristic, food choice, dietary behavior, dietary safety, and physical activity)with 14 items in total. Conclusion: The framework system and core items of nutrition literacy are established for Chinese preschool children, which could provide a reference basis for the implementation of nutrition education project and the establishment of standardized evaluation tools.

Multiyear in-situ L-band microwave radiometry of land surface processes on the Tibetan Plateau

We report a unique multiyear L-band microwave radiometry dataset collected at the Maqu site on the eastern Tibetan Plateau and demonstrate its utilities in advancing our understandings of microwave observations of land surface processes. The presented dataset contains measurements of L-band brightness temperature by an ELBARA-III microwave radiometer in horizontal and vertical polarization, profile soil moisture and soil temperature, turbulent heat fluxes, and meteorological data from the beginning of 2016 till August 2019, while the experiment is still continuing. Auxiliary vegetation and soil texture information collected in dedicated campaigns are also reported. This dataset can be used to validate the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite based observations and retrievals, verify radiative transfer model assumptions and validate land surface model and reanalysis outputs, retrieve soil properties, as well as to quantify land-atmosphere exchanges of energy, water and carbon and help to reduce discrepancies and uncertainties in current Earth System Models (ESM) parameterizations. Measurement cases in winter, pre-monsoon, monsoon and post-monsoon periods are presented.

Computational modelling for the spiral flow in umbilical arteries with different systole/diastole flow velocity ratios

The systole/diastole (S/D) flow velocity ratios in umbilical arteries (UAs) have been used to assess the health status of the feto-placental circulation, yet its connection to the morphology of UAs, specifically its coiling pattern remains unclear. Spiral flow induces unbalanced wall shear stress (WSS) distribution in UAs, and may contribute to the uneven arterial wall thickness, and the chirality. In this paper, we use a 3D computational fluid dynamics (CFD) technique to quantify the wall shear stress (WSS) in UA models of two configurations, i.e. at 0.17 and 0.50 spirals per centimeter, to represent normo- and hyper-coiling, respectively. For CFD simulations we use two different S/D ratios (3.02 and 5.70) revealed from the ultrasonography waveforms of a normal and an intrauterine growth restriction (IUGR) case. We found that more coils in the UA model enhanced WSS throughout a cardiac cycle (up to 24%) with the same inflow condition. In addition, time-averaged WSS are generally increased and more uneven in the hyper-coiling model. We suggest that the large WSS difference between the peak systole and end diastole (62% higher in the IURG case than the normal case) may induce uneven stenosis distribution at UAs, and contribute to UA chirality.

LepR-Expressing Stem Cells Are Essential for Alveolar Bone Regeneration

Stem cells play a critical role in bone regeneration. Multiple populations of skeletal stem cells have been identified in long bone, while their identity and functions in alveolar bone remain unclear. Here, we identified a quiescent leptin receptor–expressing (LepR+) cell population that contributed to intramembranous bone formation. Interestingly, these LepR+ cells became activated in response to tooth extraction and generated the majority of the newly formed bone in extraction sockets. In addition, genetic ablation of LepR+ cells attenuated extraction socket healing. The parabiosis experiments revealed that the LepR+ cells in the healing sockets were derived from resident tissue rather than peripheral blood circulation. Further studies on the mechanism suggested that these LepR+ cells were responsive to parathyroid hormone/parathyroid hormone 1 receptor (PTH/PTH1R) signaling. Collectively, we demonstrate that LepR+ cells, a postnatal skeletal stem cell population, are essential for alveolar bone regeneration of extraction sockets.

Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

Numerous machine learning (ML) approaches have been proposed for automatic classification of Alzheimer's disease (AD) from brain imaging data. In particular, over 30 papers have proposed to use convolutional neural networks (CNN) for AD classification from anatomical MRI. However, the classification performance is difficult to compare across studies due to variations in components such as participant selection, image preprocessing or validation procedure. Moreover, these studies are hardly reproducible because their frameworks are not publicly accessible and because implementation details are lacking. Lastly, some of these papers may report a biased performance due to inadequate or unclear validation or model selection procedures. In the present work, we aim to address these limitations through three main contributions. First, we performed a systematic literature review. We identified four main types of approaches: i) 2D slice-level, ii) 3D patch-level, iii) ROI-based and iv) 3D subject-level CNN. Moreover, we found that more than half of the surveyed papers may have suffered from data leakage and thus reported biased performance. Our second contribution is the extension of our open-source framework for classification of AD using CNN and T1-weighted MRI. The framework comprises previously developed tools to automatically convert ADNI, AIBL and OASIS data into the BIDS standard, and a modular set of image preprocessing procedures, classification architectures and evaluation procedures dedicated to deep learning. Finally, we used this framework to rigorously compare different CNN architectures. The data was split into training/validation/test sets at the very beginning and only the training/validation sets were used for model selection. To avoid any overfitting, the test sets were left untouched until the end of the peer-review process. Overall, the different 3D approaches (3D-subject, 3D-ROI, 3D-patch) achieved similar performances while that of the 2D slice approach was lower. Of note, the different CNN approaches did not perform better than a SVM with voxel-based features. The different approaches generalized well to similar populations but not to datasets with different inclusion criteria or demographical characteristics. All the code of the framework and the experiments is publicly available: general-purpose tools have been integrated into the Clinica software (www.clinica.run) and the paper-specific code is available at: https://github.com/aramis-lab/AD-DL.

An Improved Total Uncertainty Measure in the Evidence Theory and Its Application in Decision Making

Dempster–Shafer evidence theory (DS theory) has some superiorities in uncertain information processing for a large variety of applications. However, the problem of how to quantify the uncertainty of basic probability assignment (BPA) in DS theory framework remain unresolved. The goal of this paper is to define a new belief entropy for measuring uncertainty of BPA with desirable properties. The new entropy can be helpful for uncertainty management in practical applications such as decision making. The proposed uncertainty measure has two components. The first component is an improved version of Dubois–Prade entropy, which aims to capture the non-specificity portion of uncertainty with a consideration of the element number in frame of discernment (FOD). The second component is adopted from Nguyen entropy, which captures conflict in BPA. We prove that the proposed entropy satisfies some desired properties proposed in the literature. In addition, the proposed entropy can be reduced to Shannon entropy if the BPA is a probability distribution. Numerical examples are presented to show the efficiency and superiority of the proposed measure as well as an application in decision making.

Effect of high concentrations of dietary vitamin D3 on pullet and laying hen performance, skeleton health, eggshell quality, and yolk vitamin D3 content when fed to W36 laying hens from day of hatch until 68 wk of age

The objective of this experiment was to investigate the effects of various dietary concentrations of vitamin D₃ (D₃) on pullet and laying hen performance, eggshell quality, bone health, and yolk D₃ content from day of hatch until 68 wk of age. Initially, 440 Hy-line W36-day-old chicks were randomly assigned to 5 dietary treatments: 1,681 (control); 8,348; 18,348; 35,014; 68,348 IU D₃/kg. At 17 wk of age, pullets were assigned to experimental diets with 12 replicate groups of 6 birds. At 17 wk of age, pullets fed diets containing 8,348 and 35,014 IU D₃/kg had an increased bone mineral density in comparison to the control fed birds (P ≤ 0.01). Body weights of pullets fed the diet with 68,348 IU D₃/kg were lower than other treatments (P ≤ 0.01). Hen-housed egg production (HHEP) of hens fed the 35,014 IU D₃/kg diet was increased in comparison to control-fed hens (P ≤ 0.01), whereas HHEP of those fed 68,348 IU D₃/kg diet was reduced in comparison to all other treatments (P ≤ 0.01). Shell breaking strength of eggs from hens fed 8,348, 35,014 and 68,348 IU D₃/kg was increased in comparison to eggs from control-fed birds (P ≤ 0.01). Fat-free tibia ash content of hens fed any of the diets supplemented with D₃ (8,348 to 68,348 IU D₃/kg) was increased in comparison to control-fed hens (P ≤ 0.05). Yolk D₃ content increased linearly with dietary D₃ and the D₃ transfer efficiency for the control, 8,348 IU, 18,348 IU, 35,014 IU, and 68,348 IU D₃ treatments were 8.24, 10.29, 11.27, 12.42, and 12.06%, respectively. These data suggest that supplementation of dietary D₃ up to 35,014 IU D₃/kg feed maintained if not increased laying hen performance and enhanced pullet and laying hen skeletal quality as well as yolk D₃ content and eggshell quality. Feeding pullets at a higher level 68,348 IU of D₃ resulted in reduced growth and ultimately decreased performance of laying hens.

[Artificial intelligence evaluation of simulated phantom lung nodules with different pre-adaptive iteration techniques]

Objective: To investigate the detection rate of pulmonary nodules and the accuracy of automated measurement in chest simulation phantom by artificial intelligent computer-aided detection of pulmonary nodules with different pre-adaptive iterative techniques (ASIR-V) in wide-spectrum CT scanning. Methods: Sixteen pulmonary nodules with different diameters, densities and shapes were placed in the chest simulation phantom from December 2017 to March 2018. The weight of ASIR-V was set at 0%, 20%, 30%, 40% and 50% respectively by using Revolution CT broadband energy spectrum scanning protocol. Spearman correlation analysis was used to analyze the dose volume CT dose index (CTDIvol) and dose length product (DLP) of each group. Scanning data were imported into Tuma Shenwei artificial pulmonary nodule analysis software to evaluate the nature of the detected nodules, and ICC was used to detect the differences among groups. Results: With the increase of ASIR-V weight, the effective dose of patients decreased gradually. CTDIvol of five groups of radiation dose volume CT dose index was 7.93, 7.24, 5.85, 5.15, 3.76 mGy,dose-length product DLP was 379, 346, 280, 246, 179 mGy·cm.There was a linear negative correlation between ASIR-V weights and CTDIvol as well as DLP, r value was-0.969, P<0.01.There was no significant difference in the detection rate of pulmonary nodules between AI and physicians (P>0.05). There was high intraclass correlation coefficients for the diameter, volume, CT value and malignant percentage of pulmonary nodules (ICCs:0.981-1.000). Conclusions: Radiation dose of unenhanced chest CT scan using wide detector spectral imaging decreased with the increasing of preset ASIR-V. Lung nodule detection rate and evaluation performance can be maintained well by using ASIR-V reconstructions at lower radiation dosage.

Ptprj-as1 mediates inflammatory injury after intracerebral hemorrhage by activating NF-κB pathway

OBJECTIVE

We aimed at investigating the expression of long non-coding RNA (lncRNA) Ptprj-as1 and the role of lncRNAPtprj-as1 in inflammatory cells after intracerebral hemorrhage and its potential mechanism.

MATERIALS AND METHODS

The rat model of intracerebral hemorrhage was established. Expressions of Ptprj-as1 and inflammatory cytokines in inflammatory cells were detected by quantitative Real-time PCR (qRT-PCR). After BV2 cells were transfected with lentivirus, cell proliferation, migrative ability and apoptosis were detected by cell counting kit-8 (CCK-8) assay, transwell chamber and flow cytometry, respectively. Immunofluorescence was used to explore the ratio of M1 and M2 glial cells. The detection of tumor necrosis factor alpha (TNF-α) expression was performed using enzyme-linked immunosorbent assay (ELISA). Moreover, the expressions of key genes in NF-κB pathway were evaluated using Western blot.

RESULTS

Ptprj-as1 was highly expressed in inflammatory tissues caused by intracerebral hemorrhage (ICH). Overexpressed Ptprj-as1 promoted the migration of BV2 cells and expression levels of inflammatory cytokines such as TNF-α, interleukin-1β (IL-1β), interleukin-6 (IL-6), iNOS and NO. Meanwhile, Ptprj-as1 enhanced the proportion of M1 glial cells, the mechanism of which might be related to the activation of NF-κB pathway.

CONCLUSIONS

Ptprj-as1 activates NF-κB pathway in microglia and promotes the secretion of inflammatory cytokines, which is involved in inflammatory injury caused by intracerebral hemorrhage.

Crocin Protects Human Umbilical Vein Endothelial Cells from High Glucose-Induced Injury Via Inhibiting the Endoplasmic Reticulum Stress Response

BACKGROUND

Endothelial dysfunction plays a key role in diabetic atherosclerosis. High glucose (HG) is considered a stimulator in the development of diabetic atherosclerosis. The endoplasmic reticulum (ER) stress response is involved in HG-induced vascular injury. Crocin has antioxidative and antiapoptotic properties.

OBJECTIVE

The current study was to evaluate whether crocin can protect human umbilical vein endothelial cells (HUVECs) from HG-induced injury and explored the associated mechanism.

METHODS

HUVECs were treated with 33 mmol/L glucose as the HG condition. The endothelial protective effects of crocin were evaluated by comparison with the control groups.

RESULTS

The exposure of HUVECs to HG for 24 h remarkably induced the ER stress response and a sequence of injuries, as demonstrated an increase in the apoptotic cell number, the reactive oxygen species level and inflammatory cytokine generation, as well as a decline in vascular endothelial growth factor A expression. These changes were markedly alleviated by pretreating the HUVECs with either crocin or 4-phenylbutyrate (ER stress inhibitor) before exposure to HG.

CONCLUSION

Crocin exerted antioxidative, antiapoptotic, anti-inflammatory and proangiogenic effects in the HG-induced HUVEC injury model, which were probably mediated by a favorable modification of ER stress that requires further investigation.

Early Cognitive, Structural, and Microstructural Changes in Presymptomatic C9orf72 Carriers Younger Than 40 Years

Importance

Presymptomatic carriers of chromosome 9 open reading frame 72 (C9orf72) mutation, the most frequent genetic cause of frontotemporal lobar degeneration and amyotrophic lateral sclerosis, represent the optimal target population for the development of disease-modifying drugs. Preclinical biomarkers are needed to monitor the effect of therapeutic interventions in this population.

Objectives

To assess the occurrence of cognitive, structural, and microstructural changes in presymptomatic C9orf72 carriers.

Design, Setting, and Participants

The PREV-DEMALS study is a prospective, multicenter, observational study of first-degree relatives of individuals carrying the C9orf72 mutation. Eighty-four participants entered the study between October 2015 and April 2017; 80 (95%) were included in cross-sectional analyses of baseline data. All participants underwent neuropsychological testing and magnetic resonance imaging; 63 (79%) underwent diffusion tensor magnetic resonance imaging. Gray matter volumes and diffusion tensor imaging metrics were calculated within regions of interest. Anatomical and microstructural differences between individuals who carried the C9orf72 mutation (C9+) and those who did not carry the C9orf72 mutation (C9-) were assessed using linear mixed-effects models. Data were analyzed from October 2015 to April 2017.

Main Outcomes and Measures

Differences in neuropsychological scores, gray matter volume, and white matter integrity between C9+ and C9- individuals.

Results

Of the 80 included participants, there were 41 C9+ individuals (24 [59%] female; mean [SD] age, 39.8 [11.1] years) and 39 C9- individuals (24 [62%] female; mean [SD] age, 45.2 [13.9] years). Compared with C9- individuals, C9+ individuals had lower mean (SD) praxis scores (163.4 [6.1] vs 165.3 [5.9]; P = .01) and intransitive gesture scores (34.9 [1.6] vs 35.7 [1.5]; P = .004), atrophy in 8 cortical regions of interest and in the right thalamus, and white matter alterations in 8 tracts. When restricting the analyses to participants younger than 40 years, compared with C9- individuals, C9+ individuals had lower praxis scores and intransitive gesture scores, atrophy in 4 cortical regions of interest and in the right thalamus, and white matter alterations in 2 tracts.

Conclusions and Relevance

Cognitive, structural, and microstructural alterations are detectable in young C9+ individuals. Early and subtle praxis alterations, underpinned by focal atrophy of the left supramarginal gyrus, may represent an early and nonevolving phenotype related to neurodevelopmental effects of C9orf72 mutation. White matter alterations reflect the future phenotype of frontotemporal lobar degeneration/amyotrophic lateral sclerosis, while atrophy appears more diffuse. Our results contribute to a better understanding of the preclinical phase of C9orf72 disease and of the respective contribution of magnetic resonance biomarkers.

Trial Registration

clinicaltrials.gov Identifier: NCT02590276.

A selection method of chickens with blue-eggshell and dwarf traits by molecular marker-assisted selection

The blue-eggshell and dwarf traits have an important economic value in poultry production. Using a genetic aggregation-based strategy, the molecular marker-assisted selection technology was jointly used to provide a rapid breeding method for pure strain chickens simultaneously with hens exhibiting the blue-eggshell and dwarf traits. Overall, 80 male dwarf chickens and 1,000 hybrid blue-eggshell hens (F0) were used for the hybridization experiment. Subsequently, the crossing of F1 or F2 chicks was performed in succession. The F1 and F2 chicks were respectively detected by the joint molecular markers of the solute carrier organic anion transporter family, namely, 1B3 (SLCO1B3) and the growth hormone receptor (GHR) genes, which relate to blue-eggshell and dwarf traits. Meanwhile, the selection of blue-eggshell and dwarf phenotypes was used to validate the data obtained by the molecular markers. The results showed that F1 chicks included the heterozygous and wild-type of SLCO1B3, as well as the homozygous (hens) and heterozygous (roosters) of GHR. However, F2 chicks included 3 different genotypes of both SLCO1B3 and GHR. Ultimately, 196 F1 roosters (concurrently with heterozygous genotype of SLCO1B3 and GHR) and 1,073 F1 hens (concurrently with heterozygous genotype of SLCO1B3 and homozygous genotype of GHR) were obtained from the initial 10,040 F1 chicks. Further, 27 F2 roosters and 345 F2 hens, which simultaneously carried the homozygous genotype of SLCO1B3 and GHR, were screened from the initial 6,000 F2 chicks. Data obtained on the blue-eggshell and dwarf phenotypes were consistent with the results by molecular markers. Similarly, the purity verification of the strain obtained through 2 crossing experiments (F0♂ × F2♀ and F2♂ × F2♀) revealed that all chickens had the blue-eggshell and dwarf traits, supporting that the obtained F2 strain was pure. In summary, for the first time, we successfully bred a pure strain chicken with blue-eggshell and dwarf traits by jointly using the molecular markers of the SLCO1B3 and GHR genes. Our study provides a new method for the rapid cultivation of new chicken strains.

[Epidemiological survey of mental disorders in the rural left behind elderly aged 60 years and older in Gansu]

Objective: To investigate the prevalence, demographic characteristics and social life function of mental disorders in the rural left behind elderly aged 60 years and older in Gansu. Methods: Between November 2017 and June 2018, a multi-stage stratified cluster sampling method was used to randomly select the rural left behind elderly aged 60 years and older in Gansu, and totally 6 000 elderly were enrolled. By using the extended general health questionnaire (GHQ-12) and the American Handbook for Diagnosis and Statistics of Mental Disorders (DSM-Ⅳ) Axis Ⅰ Disorders Formal Clinical Examination Patient Edition, all the included subjects were screened and diagnosed. Functional status was assessed by the Global Assessment Function scale (GAF). Statistical analysis of the prevalence of various mental illnesses, as well as the differences in the prevalence of different gender, marital status and age groups was performed. Results: Totally, 6 000 subjects completed the survey. The adjusted current prevalence of any mental disorder was 20.11% (95%CI 17.70%-22.85%). The six most prevalent specific disorders were major depressive disorder (9.20%), pain disorder (2.71%), mood disorder due to the body condition (2.08%), generalized anxiety disorder (1.99%), anxiety disorder not otherwise specified (1.15%) and dysthymic disorder (0.84%). The lifetime prevalence of mental disorders was 20.54% (95%CI 18.40%-23.39%). The overall current prevalence of mental disorders was higher in women (242.89‰) than in men (119.55‰), and the unmarried (248.37‰) was higher than those married (187.53‰). There was no significant difference in the prevalence of mental disorders among different age groups (P>0.05). The GAF score of mental disorders was 56±11, and 71.82% was moderate to severe functional impairment. Conclusions: The prevalence of mental disorders is high in rural left-behind population aged 60 years and over in Gansu Province. Major depression is a condition that deserves special attention.