Spatial and Temporal Relationships Between Atrophy and Hypometabolism in Behavioral-Variant Frontotemporal Dementia.

PURPOSE: Individuals with behavioral-variant frontotemporal dementia (bvFTD) show changes in brain structure as assessed by MRI and brain function assessed by 18FDG-PET hypometabolism. However, current understanding of the spatial and temporal interplay between these measures remains limited. METHODS: Here, we examined longitudinal atrophy and hypometabolism relationships in 15 bvFTD subjects with 2 to 4 follow-up MRI and PET scans (56 visits total). Subject-specific slopes of atrophy and hypometabolism over time were extracted across brain regions and correlated with baseline measures both locally, via Pearson correlations, and nonlocally, via sparse canonical correlation analyses (SCCA). RESULTS: Notably, we identified a robust link between initial hypometabolism and subsequent cortical atrophy rate changes in bvFTD subjects. Network-level exploration unveiled alignment between baseline hypometabolism and ensuing atrophy rates in the dorsal attention, language, and default mode networks. SCCA identified 2 significant and highly localized components depicting the connection between baseline hypometabolism and atrophy slope over time. The first centered around bilateral orbitofrontal, frontopolar, and medial prefrontal lobes, whereas the second concentrated in the left temporal lobe and precuneus. CONCLUSIONS: This study highlights 18FDG-PET as a dependable predictor of forthcoming atrophy in spatially adjacent brain regions for individuals with bvFTD.

AAV5-miHTT-mediated huntingtin lowering improves brain health in a Huntington's disease mouse model.

Huntingtin (HTT)-lowering therapies show great promise in treating Huntington's disease. We have developed a microRNA targeting human HTT that is delivered in an adeno-associated serotype 5 viral vector (AAV5-miHTT), and here use animal behaviour, MRI, non-invasive proton magnetic resonance spectroscopy and striatal RNA sequencing as outcome measures in preclinical mouse studies of AAV5-miHTT. The effects of AAV5-miHTT treatment were evaluated in homozygous Q175FDN mice, a mouse model of Huntington's disease with severe neuropathological and behavioural phenotypes. Homozygous mice were used instead of the more commonly used heterozygous strain, which exhibit milder phenotypes. Three-month-old homozygous Q175FDN mice, which had developed acute phenotypes by the time of treatment, were injected bilaterally into the striatum with either formulation buffer (phosphate-buffered saline + 5% sucrose), low dose (5.2 × 109 genome copies/mouse) or high dose (1.3 × 1011 genome copies/mouse) AAV5-miHTT. Wild-type mice injected with formulation buffer served as controls. Behavioural assessments of cognition, T1-weighted structural MRI and striatal proton magnetic resonance spectroscopy were performed 3 months after injection, and shortly afterwards the animals were sacrificed to collect brain tissue for protein and RNA analysis. Motor coordination was assessed at 1-month intervals beginning at 2 months of age until sacrifice. Dose-dependent changes in AAV5 vector DNA level, miHTT expression and mutant HTT were observed in striatum and cortex of AAV5-miHTT-treated Huntington's disease model mice. This pattern of microRNA expression and mutant HTT lowering rescued weight loss in homozygous Q175FDN mice but did not affect motor or cognitive phenotypes. MRI volumetric analysis detected atrophy in four brain regions in homozygous Q175FDN mice, and treatment with high dose AAV5-miHTT rescued this effect in the hippocampus. Like previous magnetic resonance spectroscopy studies in Huntington's disease patients, decreased total N-acetyl aspartate and increased myo-inositol levels were found in the striatum of homozygous Q175FDN mice. These neurochemical findings were partially reversed with AAV5-miHTT treatment. Striatal transcriptional analysis using RNA sequencing revealed mutant HTT-induced changes that were partially reversed by HTT lowering with AAV5-miHTT. Striatal proton magnetic resonance spectroscopy analysis suggests a restoration of neuronal function, and striatal RNA sequencing analysis shows a reversal of transcriptional dysregulation following AAV5-miHTT in a homozygous Huntington's disease mouse model with severe pathology. The results of this study support the use of magnetic resonance spectroscopy in HTT-lowering clinical trials and strengthen the therapeutic potential of AAV5-miHTT in reversing severe striatal dysfunction in Huntington's disease.

In vivo effect of LATE-NC on integrity of white matter connections to the hippocampus.

INTRODUCTION: TAR DNA-binding protein 43 (TDP-43) is a highly prevalent proteinopathy that is involved in neurodegenerative processes, including axonal damage. To date, no ante mortem biomarkers exist for TDP-43, and few studies have directly assessed its impact on neuroimaging measures utilizing pathologic quantification. METHODS: Ante mortem diffusion-weighted images were obtained from community-dwelling older adults. Regression models calculated the relationship between post mortem TDP-43 burden and ante mortem fractional anisotropy (FA) within each voxel in connection with the hippocampus, controlling for coexisting Alzheimer's disease and demographics. RESULTS: Results revealed a significant negative relationship (false discovery rate [FDR] corrected p < .05) between post mortem TDP-43 and ante mortem FA in one cluster within the left medial temporal lobe connecting to the parahippocampal cortex, entorhinal cortex, and cingulate, aligning with the ventral subdivision of the cingulum. FA within this cluster was associated with cognition. DISCUSSION: Greater TDP-43 burden is associated with lower FA within the limbic system, which may contribute to impairment in learning and memory. HIGHLIGHTS: Post mortem TDP-43 pathological burden is associated with reduced ante mortem fractional anisotropy. Reduced FA located in the parahippocampal portion of the cingulum. FA in this area was associated with reduced episodic and semantic memory. FA in this area was associated with increased inward hippocampal surface deformation.

Neuroimaging feature extraction using a neural network classifier for imaging genetics.

BACKGROUND: Dealing with the high dimension of both neuroimaging data and genetic data is a difficult problem in the association of genetic data to neuroimaging. In this article, we tackle the latter problem with an eye toward developing solutions that are relevant for disease prediction. Supported by a vast literature on the predictive power of neural networks, our proposed solution uses neural networks to extract from neuroimaging data features that are relevant for predicting Alzheimer's Disease (AD) for subsequent relation to genetics. The neuroimaging-genetic pipeline we propose is comprised of image processing, neuroimaging feature extraction and genetic association steps. We present a neural network classifier for extracting neuroimaging features that are related with the disease. The proposed method is data-driven and requires no expert advice or a priori selection of regions of interest. We further propose a multivariate regression with priors specified in the Bayesian framework that allows for group sparsity at multiple levels including SNPs and genes. RESULTS: We find the features extracted with our proposed method are better predictors of AD than features used previously in the literature suggesting that single nucleotide polymorphisms (SNPs) related to the features extracted by our proposed method are also more relevant for AD. Our neuroimaging-genetic pipeline lead to the identification of some overlapping and more importantly some different SNPs when compared to those identified with previously used features. CONCLUSIONS: The pipeline we propose combines machine learning and statistical methods to benefit from the strong predictive performance of blackbox models to extract relevant features while preserving the interpretation provided by Bayesian models for genetic association. Finally, we argue in favour of using automatic feature extraction, such as the method we propose, in addition to ROI or voxelwise analysis to find potentially novel disease-relevant SNPs that may not be detected when using ROIs or voxels alone.

Brain Imaging Abnormalities in Mixed Alzheimer's and Subcortical Vascular Dementia.

BACKGROUND: A large proportion of Alzheimer's disease (AD) patients have coexisting subcortical vascular dementia (SVaD), a condition referred to as mixed dementia (MixD). Brain imaging features of MixD presumably include those of cerebrovascular disease and AD pathology, but are difficult to characterize due to their heterogeneity. OBJECTIVE: To perform an exploratory analysis of conventional and non-conventional structural magnetic resonance imaging (MRI) abnormalities in MixD and to compare them to those observed in AD and SVaD. METHODS: We conducted a cross-sectional, region-of-interest-based analysis of 1) hyperintense white-matter signal abnormalities (WMSA) on T2-FLAIR and hypointense WMSA on T1-weighted MRI; 2) diffusion tensor imaging; 3) quantitative susceptibility mapping; and 4) effective transverse relaxation rate (R2*) in N = 17 participants (AD:5, SVaD:5, MixD:7). General linear model was used to explore group differences in these brain imaging measures. RESULTS: Model findings suggested imaging characteristics specific to our MixD group, including 1) higher burden of WMSAs on T1-weighted MRI (versus both AD and SVaD); 2) frontal lobar preponderance of WMSAs on both T2-FLAIR and T1-weighted MRI; 3) higher fractional anisotropy values within normal-appear white-matter tissues (versus SVaD, but not AD); and 4) lower R2* values within the T2-FLAIR WMSA areas (versus both AD and SVaD). CONCLUSION: These findings suggest a preliminary picture of the location and type of brain imaging characteristics associated with MixD. Future imaging studies may employ region-specific hypotheses to distinguish MixD more rigorously from AD or SVaD.

Facile extraction of berberine from different plants, separation, and identification by thin-layer chromatography, high-performance liquid chromatography, and biological evaluation against Leishmaniosis.

The extraction of berberine was carried out from Berberis vulgaris, Berberis aquifolium, and Hydrastis canadensis plants using ethanol and water (70:30, v/v). The extracted berberine was characterized by ultraviolet-visible and Fourier-transform infrared spectroscopy. The purity of berberine was ascertained by thin-layer chromatography using n-propanol-formic acid-water (95:1:4) and (90:1:9) solvents. hRf values were in the range of 44-49 with compact spots (diameter 0.2-0.4 cm). HPLC was carried out using ammonium acetate buffer and acetonitrile in gradient mode with Zodiac (4.6 × 150 mm, 3 µm) column. The flow rate was 1.0 mL/min and detection was at 220 nm. The values of separation and resolution factors of the standard and the extracted berberine were in the range of 1.13-1.16 and 1.40-1.71, respectively. A comparison has shown that both thin-layer chromatography and high-performance liquid chromatography (HPLC) methods found applications in different situations and requirements. The extracted berberine samples were used to treat Leishmaniosis and the results showed better activity of berberine in comparison to the standard drug Amphotericin B. Briefly, the reported research is a novel and may be used to extract berberine from plants, separation and identification of berberine by thin layer chromatography and HPLC and to treat Leishmaniosis.

Clinostomum complanatum: Anthelmintic potential of curcumin on the infective progenetic metacercarial stage.

The emerging resistance against commonly used antiparasitic drugs has driven investigators to explore alternative approaches using plant-derived active ingredients. These compounds have been tested for antiviral, antibacterial, and anthelmintic properties, particularly against adult worms. However, their effects on larval forms have been neglected. Curcumin is a polyphenol that is a significant constituent of the rhizome of Curcuma longa and possesses various biological activities, including antioxidant, anti-inflammatory, anti-infectious, and anti-carcinogenic. In the present study, the anthelmintic potential of curcumin was tested in vitro for its efficacy against the zoonotically important larval form, the progenetic metacercariae of Clinostomum complanatum, which were procured from the forage fish, Trichogaster fasciatus. Curcumin produced time and concentration-dependent inhibition in the motility of treated metacercarial worms, with the maximum inhibition of motility reported at 60 µM along with a significant increase of (36-92%) in ROS and (57-112%) in GSH levels at the end of a period of 6 h. In contrast, curcumin at the highest concentration significantly inhibited the activities of the antioxidant and detoxification enzymes SOD (36%) and GST (16%), respectively, in addition to altering the polypeptide profile and inhibiting cysteine proteases. The tegumental surface appeared to be highly disrupted in curcumin-treated worms, exhibiting severe blebbing, shearing of the tegument, and spine erosion. Such changes would affect the tegumental functions and survival of worms in the hostile microenvironment. This would render worms more susceptible to host-mediated rejection responses. Based on the results of the present study, it is inferred that C. complanatum could serve as an excellent model for screening novel anthelmintic drugs against larval trematodes of great economic significance. Furthermore, we conclude that curcumin could be exploited as an excellent phytotherapeutic agent against the virulent larval form under investigation.

Investigating the temporal pattern of neuroimaging-based brain age estimation as a biomarker for Alzheimer's Disease related neurodegeneration.

Neuroimaging-based brain-age estimation via machine learning has emerged as an important new approach for studying brain aging. The difference between one's estimated brain age and chronological age, the brain age gap (BAG), has been proposed as an Alzheimer's Disease (AD) biomarker. However, most past studies on the BAG have been cross-sectional. Quantifying longitudinal changes in an individual's BAG temporal pattern would likely improve prediction of AD progression and clinical outcome based on neurophysiological changes. To fill this gap, our study conducted predictive modeling using a large neuroimaging dataset with up to 8 years of follow-up to examine the temporal patterns of the BAG's trajectory and how it varies by subject-level characteristics (sex, APOEɛ4 carriership) and disease status. Specifically, we explored the pattern and rate of change in BAG over time in individuals who remain stable with normal cognition or mild cognitive impairment (MCI), as well as individuals who progress to clinical AD. Combining multimodal imaging data in a support vector regression model to estimate brain age yielded improved performance over single modality. Multilevel modeling results showed the BAG followed a linear increasing trajectory with a significantly faster rate in individuals with MCI who progressed to AD compared to cognitively normal or MCI individuals who did not progress. The dynamic changes in the BAG during AD progression were further moderated by sex and APOEɛ4 carriership. Our findings demonstrate the BAG as a potential biomarker for understanding individual specific temporal patterns related to AD progression.

Aberrant hydroxymethylation in promoter CpG regions of genes related to the cell cycle and apoptosis characterizes advanced chronic myeloid leukemia disease, poor imatinib respondents and poor survival.

BACKGROUND: There is strong evidence that disease progression, drug response and overall clinical outcomes of CML disease are not only decided by BCR/ABL1 oncoprotein but depend on accumulation of additional genetic and epigenetic aberrations. DNA hydroxymethylation is implicated in the development of variety of diseases. DNA hydroxymethylation in gene promoters plays important roles in disease progression, drug response and clinical outcome of various diseases. Therefore in this study, we aimed to explore the role of aberrant hydroxymethylation in promoter regions of different tumor suppressor genes in relation to CML disease progression, response to imatinib therapy and clinical outcome. METHODS: We recruited 150 CML patients at different clinical stages of the disease. Patients were followed up for 48 months and haematological/molecular responses were analysed. Haematological response was analysed by peripheral blood smear. BCR/ABL1 specific TaqMan probe based qRT-PCR was used for assessing the molecular response of CML patients on imatinib therapy. Promoter hydroxymethylation of the genes was characterized using MS-PCR. RESULTS: We observed that promoter hydroxymethylation of DAPK1, RIZ1, P16INK4A, RASSF1A and p14ARFARF genes characterize advanced CML disease and poor imatinib respondents. Although, cytokine signalling (SOCS1) gene was hypermethylated in advanced stages of CML and accumulated in patients with poor imatinib response, but the differences were not statistically significant. Moreover, we found hypermethylation of p14ARF, RASSF1 and p16INK4A genes and cytokine signalling gene (SOCS1) significantly associated with poor overall survival of CML patients on imatinib therapy. The results of this study are in agreement of the role of aberrant DNA methylation of different tumor suppressor genes as potential biomarkers of CML disease progression, poor imatinib response and overall clinical outcome. CONCLUSION: In this study, we report that promoter hydroxymethylation of DAPK1, RIZ1, P16INK4A, RASSF1A and p14ARFARF genes is a characteristic feature of CML disease progressions, defines poor imatinib respondents and poor overall survival of CML patients to imatinib therapy.

A computational approach to design potential siRNA molecules as a prospective tool for silencing nucleocapsid phosphoprotein and surface glycoprotein gene of SARS-CoV-2.

An outbreak, caused by an RNA virus, SARS-CoV-2 named COVID-19 has become pandemic with a magnitude which is daunting to all public health institutions in the absence of specific antiviral treatment. Surface glycoprotein and nucleocapsid phosphoprotein are two important proteins of this virus facilitating its entry into host cell and genome replication. Small interfering RNA (siRNA) is a prospective tool of the RNA interference (RNAi) pathway for the control of human viral infections by suppressing viral gene expression through hybridization and neutralization of target complementary mRNA. So, in this study, the power of RNA interference technology was harnessed to develop siRNA molecules against specific target genes namely, nucleocapsid phosphoprotein gene and surface glycoprotein gene. Conserved sequence from 139 SARS-CoV-2 strains from around the globe was collected to construct 78 siRNA that can inactivate nucleocapsid phosphoprotein and surface glycoprotein genes. Finally, based on GC content, free energy of folding, free energy of binding, melting temperature, efficacy prediction and molecular docking analysis, 8 siRNA molecules were selected which are proposed to exert the best action. These predicted siRNAs should effectively silence the genes of SARS-CoV-2 during siRNA mediated treatment assisting in the response against SARS-CoV-2.

A novel technique for prevention of anterior fistula and facilitation of alveolar cleft repair: Gingivoperiosteoplasty with palatoplasty.

Background & Objectives: The Cleft palate is one of the most commonly encountered congenital deformity in plastic surgery clinics and can be associated with cleft lip and alveolus. Though palate repair can be associated with several complications, the most frequent and troublesome is anterior fistula formation. Various technical modifications are in practice to avoid this dreaded complication. We have started combining gingivoperiosteoplasty with palate repair to avoid postoperative anterior fistula formation and to close alveolar cleft at the same time. Methods: A prospective study was performed at the department of plastic and reconstructive surgery, Liaquat National Hospital, Karachi and selected patients were enrolled in the study after informed consent. A total of 15 patients were operated on from January 2017 to December 2020. All patients had cleft palate repair along with primary gingivoperiosteoplasty (GPP) at the age of standard palatal repair. Buccal/oral and nasal layers of the alveolus were dissected as per standard gingivoperiosteoplasty and repaired in continuation with nasal and oral layers of the palate. Postoperatively, the standard cleft palate repair protocol was followed. Follow-up was done at four weeks, 12 weeks, and six months and repair integrity was checked. Future follow-up at 4-5 years of age is planned to see the effect on alveolar collapse, bone growth, and the need for secondary bone grafting. Results: All patients were followed up regularly. None had a complication of fistula. The repairs of both palate and alveolus remained intact. Patients were kept on the follow-up to assess the need for alveolar bone grafting in the future. Conclusion: Gingivoperiosteoplasty combined with the palatal repair is a novel technique for the prevention of anterior palatal fistula.

Phase-corrected buffer averaging for enhanced OCT angiography using FDML laser.

Megahertz-rate optical coherence tomography angiography (OCTA) is highly anticipated as an ultrafast imaging tool in clinical settings. However, shot-noise-limited sensitivity is inevitably reduced in high-speed imaging systems. In this Letter, we present a coherent buffer averaging technique for use with a Fourier-domain mode-locked (FDML) laser to improve OCTA contrast at 1060 nm MHz-rate retinal imaging. Full characterization of spectral variations among the FDML buffers and a numerical correction method are also presented, with the results demonstrating a 10-fold increase in the phase alignment among buffers. Coherent buffer averaging provided better OCTA contrast than the conventional multi-frame averaging approach with a faster acquisition time.

Increased mRNA expression of key cytokines among suspected cases of Pneumocystis jirovecii infection.

BACKGROUND: Pneumocystis pneumonia (PCP) is a fatal infectious disease caused by Pneumocystis jirovecii (PJP). The major factor relevant to morbidity and mortality seems to be the host inflammatory reaction. The objective of this study was to evaluate the role of IL-2, IL-4, IL-10, and IL-13 cytokine mRNA expression among suspected P. jirovecii infection. METHODS: This was a cross-sectional analytical study undertaken in Aseer region, Saudi Arabia. One hundred suspected PCP cases and 100 healthy controls were included in the study. Basic clinical manifestations, radiological findings, microbiological and immunological findings were extracted from the hospital records from January 2019 to August 2019, Pneumocystis detection was done by immune-fluorescent staining (IFAT, Gomorimethanamine silver staining (GMSS), Giemsa staining, Toluidine blue O (TBO), and Pneumocystis RT-PCR. RESULTS: Increased more than 5 fold, 3 fold, 4 fold, and 7 fold of IL-2, IL-4, IL-10, and IL-13 mRNA expression were observed in PCP cases compared to controls. Higher expression of IL-2 mRNA was connected with crept, wheezing and chest X-ray findings like central perihilar infiltrate, patchy infiltrate, consolidation, hilar lymphadenopathy, pneumothorax, pleural effusion which showed higher expression compared to counterpart (p< 0.0001). Higher expression of IL-4 mRNA was found to be significantly associated with weight loss (p=0.002), dyspnea (p=0.003), crept (p=0.01), and chest X-ray findings (p< 0.0001). Significantly increased expression of IL-10 mRNA was observed to be associated with weight loss, dyspnea, night sweats, wheezing, and different findings of chest X-ray compared to their counterparts, whereas, IL-13 mRNA was observed in cases with fever. Suspected cases of PCP confirmed positive by IFTA with higher IL-2, IL-4, and IL-10 mRNA expression compared to negative cases. RT-PCR confirmed PCP cases had significantly higher expression of IL-2, IL-4, and IL-10 as well as IL-13 mRNA compared to negative cases. Positive detected cases by GMSS showed higher IL-2, IL-10 mRNA expression, while Giemsa showed only higher IL-4 mRNA expression compared to negative cases. CONCLUSION: Confirmed cases of P. jirovecii showed higher IL-2, IL-4, IL-10, and IL-13 mRNA expression comparatively to negative cases. Increased expression of cytokines may be indicative of infection severity and could help in patients' management.

Biocomputational Prediction Approach Targeting FimH by Natural SGLT2 Inhibitors: A Possible Way to Overcome the Uropathogenic Effect of SGLT2 Inhibitor Drugs.

The Food and Drug Administration (FDA) approved a new class of anti-diabetic medication (a sodium-glucose co-transporter 2 (SGLT2) inhibitor) in 2013. However, SGLT2 inhibitor drugs are under evaluation due to their associative side effects, such as urinary tract and genital infection, urinary discomfort, diabetic ketosis, and kidney problems. Even clinicians have difficulty in recommending it to diabetic patients due to the increased probability of urinary tract infection. In our study, we selected natural SGLT2 inhibitors, namely acerogenin B, formononetin, (-)-kurarinone, (+)-pteryxin, and quinidine, to explore their potential against an emerging uropathogenic bacterial therapeutic target, i.e., FimH. FimH plays a critical role in the colonization of uropathogenic bacteria on the urinary tract surface. Thus, FimH antagonists show promising effects against uropathogenic bacterial strains via their targeting of FimH's adherence mechanism with less chance of resistance. The molecular docking results showed that, among natural SGLT2 inhibitors, formononetin, (+)-pteryxin, and quinidine have a strong interaction with FimH proteins, with binding energy (∆G) and inhibition constant (ki) values of -5.65 kcal/mol and 71.95 µM, -5.50 kcal/mol and 92.97 µM, and -5.70 kcal/mol and 66.40 µM, respectively. These interactions were better than those of the positive control heptyl α-d-mannopyranoside and far better than those of the SGLT2 inhibitor drug canagliflozin. Furthermore, a 50 ns molecular dynamics simulation was conducted to optimize the interaction, and the resulting complexes were found to be stable. Physicochemical property assessments predicted little toxicity and good drug-likeness properties for these three compounds. Therefore, formononetin, (+)-pteryxin, and quinidine can be proposed as promising SGLT2 inhibitors drugs, with add-on FimH inhibition potential that might reduce the probability of uropathogenic side effects.

The reduction in clinical and surgical exposure of trainees during COVID-19 and its impact on their training.

OBJECTIVE: To assess the impact of coronavirus disease on surgical training. Methods: The cross-sectional study was conducted at the General Surgery Department of Liaquat National Hospital, Karachi, from August 2019 to May 2020, and comprised surgical trainees from year 1 to 4. The subjects were interviewed and inquired about their opinion regarding the impact of coronavirus disease on their training. Data was prospectively collected in two equal phases of 5 months each, separating the phases on the basis of the application of preventive measures and changes relating to coronavirus disease. Data of cases from log books was divided into major and minor cases. RESULTS: Of the 24 surgical trainees available, 18(75%) participated; 12(66.6%) females and 6(33.3%) males. There was a significant difference between the two phases, with the number of surgical case going down drastically in the second phase (p=0.005), affecting the training process. CONCLUSIONS: Considering the ongoing pandemic, it may be worthwhile to look into the possibility of increasing the duration of training.

Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellar cortex of the Tc1 mouse model of down syndrome - a comprehensive morphometric analysis with active staining contrast-enhanced MRI.

Down Syndrome is a chromosomal disorder that affects the development of cerebellar cortical lobules. Impaired neurogenesis in the cerebellum varies among different types of neuronal cells and neuronal layers. In this study, we developed an imaging analysis framework that utilizes gadolinium-enhanced ex vivo mouse brain MRI. We extracted the middle Purkinje layer of the mouse cerebellar cortex, enabling the estimation of the volume, thickness, and surface area of the entire cerebellar cortex, the internal granular layer, and the molecular layer in the Tc1 mouse model of Down Syndrome. The morphometric analysis of our method revealed that a larger proportion of the cerebellar thinning in this model of Down Syndrome resided in the inner granule cell layer, while a larger proportion of the surface area shrinkage was in the molecular layer.

Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score.

18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images have shown great promise in revealing the altered metabolism patterns in Alzheimer's disease (AD). The AD pathology is progressive, and leads to structural and functional alterations that lie on a continuum. There is a need to quantify the altered metabolism patterns that exist on a continuum into a simple measure. This work proposes a 3D convolutional neural network with residual connections that generates a probability score useful for interpreting the FDG-PET images along the continuum of AD. This network is trained and tested on images of stable normal control and stable Dementia of the Alzheimer's type (sDAT) subjects, achieving an AUC of 0.976 via repeated fivefold cross-validation. An independent test set consisting of images in between the two extreme ends of the DAT spectrum is used to further test the generalization performance of the network. Classification performance of 0.811 AUC is achieved in the task of predicting conversion of mild cognitive impairment to DAT for conversion time of 0-3 years. The saliency and class activation maps, which highlight the regions of the brain that are most important to the classification task, implicate many known regions affected by DAT including the posterior cingulate cortex, precuneus, and hippocampus.

Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases.

Biomarkers for dementia of Alzheimer's type (DAT) are sought to facilitate accurate prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1-weighted magnetic resonance imaging (MRI) is a commonly used neuroimaging modality for measuring brain structure in vivo, potentially providing information enabling the design of biomarkers for DAT. We propose a novel biomarker using structural MRI volume-based features to compute a similarity score for the individual's structural patterns relative to those observed in the DAT group. We employed ensemble-learning framework that combines structural features in most discriminative ROIs to create an aggregate measure of neurodegeneration in the brain. This classifier is trained on 423 stable normal control (NC) and 330 DAT subjects, where clinical diagnosis is likely to have the highest certainty. Independent validation on 8,834 unseen images from ADNI, AIBL, OASIS, and MIRIAD Alzheimer's disease (AD) databases showed promising potential to predict the development of DAT depending on the time-to-conversion (TTC). Classification performance on stable versus progressive mild cognitive impairment (MCI) groups achieved an AUC of 0.81 for TTC of 6 months and 0.73 for TTC of up to 7 years, achieving state-of-the-art results. The output score, indicating similarity to patterns seen in DAT, provides an intuitive measure of how closely the individual's brain features resemble the DAT group. This score can be used for assessing the presence of AD structural atrophy patterns in normal aging and MCI stages, as well as monitoring the progression of the individual's brain along with the disease course.

Generation of oxidative stress and induction of apoptotic like events in curcumin and thymoquinone treated adult Fasciola gigantica worms.

Fasciolosis is a neglected tropical disease caused by the liver fluke Fasciola gigantica. The absence of successful vaccine and emerging resistance in flukes against the drug of choice, triclabendazole, has necessitated the search for alternatives including phyto-therapeutic approaches. Curcumin and thymoquinone, the active ingredients of Curcuma longa and Nigella sativa plants respectively, were first screened for their binding affinity with Glutathione-S-transferase (GST) molecule through in silico molecular docking followed by in vitro treatment of worms with varying concentrations of the test compounds. The in silico molecular docking of curcumin and thymoquinone with sigma GST revealed strong hydrogen bonding as well as hydrophobic interactions with high fitness scores but showing inter-specific differences. The in vitro treatment of F. gigantica worms with both curcumin and thymoquinone resulted in a significant increase in the generation of reactive oxygen species (ROS) whereas the level of reduced glutathione, a primary redox regulator, was found to be significantly decreased (p < 0.05). The two compounds not only inhibited the GST activity, which is an important detoxification enzyme and also a key drug/vaccine target for the control of fasciolosis but also significantly inhibited the activity of antioxidant enzymes glutathione peroxidase and glutathione reductase that are vital in maintenance of redox homeostasis. The immunohistochemistry performed using anti sigma GST polyclonal antibodies revealed that both the compounds used in the present study significantly reduced immunofluorescence in the vitellaria, developing eggs present in the ovary and the intestinal caecae indicating inhibition of GST enzyme in these regions of the worms. Further, following treatment with curcumin and thymoquinone, chromatin condensation and DNA fragmentation was also observed in F. gigantica worms. In conclusion, both curcumin and thymoquinone generated oxidative stress in the worms by production of ROS and significantly inhibiting their antioxidant and detoxification ability. The oxidative stress along with induction of apoptotic like events would compromise the survival ability of worms within the host. However, further studies are required to establish their anthelmintic potential alone and in combination with the commonly used anthelmintic drugs under in vivo conditions.

The Contribution Plot: Decomposition and Graphical Display of the RV Coefficient, with Application to Genetic and Brain Imaging Biomarkers of Alzheimer's Disease.

BACKGROUND/AIMS: Alzheimer's disease (AD) is a chronic neurodegenerative disease that causes memory loss and a decline in cognitive abilities. AD is the sixth leading cause of death in the USA, affecting an estimated 5 million Americans. To assess the association between multiple genetic variants and multiple measurements of structural changes in the brain, a recent study of AD used a multivariate measure of linear dependence, the RV coefficient. The authors decomposed the RV coefficient into contributions from individual variants and displayed these contributions graphically. METHODS: We investigate the properties of such a "contribution plot" in terms of an underlying linear model, and discuss shrinkage estimation of the components of the plot when the correlation signal may be sparse. RESULTS: The contribution plot is applied to simulated data and to genomic and brain imaging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). CONCLUSIONS: The contribution plot with shrinkage estimation can reveal truly associated explanatory variables.