Caloric restriction leading to attenuation of experimental Alzheimer's disease results from alterations in gut microbiome.

BACKGROUND: Caloric restriction (CR) might be effective for alleviating/preventing Alzheimer's disease (AD), but the biological mechanisms remain unclear. In the current study, we explored whether CR caused an alteration of gut microbiome and resulted in the attenuation of cognitive impairment of AD animal model. METHODS: Thirty-week-old male APP/PS1 transgenic mice were used as AD models (AD mouse). CR was achieved by 30% reduction of daily free feeding (ad libitum, AL) amount. The mice were fed with CR protocol or AL protocol for six consecutive weeks. RESULTS: We found that with CR treatment, AD mice showed improved ability of learning and spatial memory, and lower levels of Aß40, Aß42, IL-1ß, TNF-α, and ROS in the brain. By sequencing 16S rDNA, we found that CR treatment resulted in significant diversity in composition and abundance of gut flora. At the phylum level, Deferribacteres (0.04%), Patescibacteria (0.14%), Tenericutes (0.03%), and Verrucomicrobia (0.5%) were significantly decreased in CR-treated AD mice; at the genus level, Dubosiella (10.04%), Faecalibaculum (0.04%), and Coriobacteriaceae UCG-002 (0.01%) were significantly increased in CR-treated AD mice by comparing with AL diet. CONCLUSIONS: Our results demonstrate that the attenuation of AD following CR treatment in APP/PS1 mice may result from alterations in the gut microbiome. Thus, gut flora could be a new target for AD prevention and therapy.

Development of partial denitrification process in upflow-anaerobic sludge blanket and effect of electric field on partial denitrification performance.

Partial denitrification (PD) is an alternative to providing NO2- for the anaerobic ammonium oxidation (anammox) process. In this study, three upflow anaerobic sludge blankets (UASB) were used to investigate the effect of an external electric field on PD performance. The results indicated that the maximum nitrite transformation ratio (NTR) reached 76.3 %, with an average NTR of 54.1 %, in the presence of external electric field, whereas the average NTR of the control was only 49.8 %. The fitted maximum specific nitrate reduction rates of PD1, PD2, and PD3 were 83.7, 90.5, and 92.3 mg N g-1VSS h-1, respectively, according to the Haldane model analysis. Microbial community analysis demonstrated that the abundance of Thauera, Comamonas, and Accumulibacter increased with electric assistance. In summary, UASB reactor with electrodes set in the upper region was most feasible for the stable PD process, providing an alternative for developing a coupled PD-anammox process.

Study on Microstructure and Properties of WC Particle-Reinforced FeCoCrNi-Matrix High Entropy Alloy Composites.

In recent years, high entropy alloy (HEA) matrix composites have undergone rapid development. In this work, the effects of different WC contents (10 wt.%, 20 wt.%, and 30 wt.%) on the microstructure, mechanical properties, and wear resistance of FeCoCrNi HEA matrix composites prepared by spark plasma sintering (SPS) were studied. The results show that the WC-HEA composites are mainly composed of an FCC matrix phase (Ni, Fe) and carbide phases (Cr7C3, Co3W3C, WC, etc.). The hardness of the 30 WC-HEA composites was the highest at 459.2 HV, which is 71.2% higher than the 268.3 HV of the pure matrix material. Similarly, the compressive yield strength of the 30 WC-HEA composite was the largest, reaching 1315.1 MPa, which is 112.1% higher than that of the pure matrix material. However, the compression deformation rate of the 30 WC-HEA composite significantly decreased to 16.6%. Under the same dry friction conditions, the addition of an appropriate amount of WC particles can reduce the friction coefficient of the HEA matrix. The wear volume of the composites decreased rapidly with the increase of WC content. The wear volume of 30 WC-HEA was the lowest, only 3.17% of that of the pure matrix material.

Disrupted dynamic functional connectivity of hippocampal subregions mediated the slowed information processing speed in late-life depression.

BACKGROUND: Slowed information processing speed (IPS) is the core contributor to cognitive impairment in patients with late-life depression (LLD). The hippocampus is an important link between depression and dementia, and it may be involved in IPS slowing in LLD. However, the relationship between a slowed IPS and the dynamic activity and connectivity of hippocampal subregions in patients with LLD remains unclear. METHODS: One hundred thirty-four patients with LLD and 89 healthy controls were recruited. Sliding-window analysis was used to assess whole-brain dynamic functional connectivity (dFC), dynamic fractional amplitude of low-frequency fluctuations (dfALFF) and dynamic regional homogeneity (dReHo) for each hippocampal subregion seed. RESULTS: Cognitive impairment (global cognition, verbal memory, language, visual-spatial skill, executive function and working memory) in patients with LLD was mediated by their slowed IPS. Compared with the controls, patients with LLD exhibited decreased dFC between various hippocampal subregions and the frontal cortex and decreased dReho in the left rostral hippocampus. Additionally, most of the dFCs were negatively associated with the severity of depressive symptoms and were positively associated with various domains of cognitive function. Moreover, the dFC between the left rostral hippocampus and middle frontal gyrus exhibited a partial mediation effect on the relationships between the scores of depressive symptoms and IPS. CONCLUSIONS: Patients with LLD exhibited decreased dFC between the hippocampus and frontal cortex, and the decreased dFC between the left rostral hippocampus and right middle frontal gyrus was involved in the underlying neural substrate of the slowed IPS.

CYP2C19-rs4986893 confers risk to major depressive disorder and bipolar disorder in the Han Chinese population whereas ABCB1-rs1045642 acts as a protective factor.

BACKGROUND: Genetic risks may predispose individuals to major mood disorders differently. This study investigated the gene polymorphisms of previously reported candidate genes for major depressive disorder (MDD) and bipolar disorder (BPD) in the Han Chinese population. METHODS: Twenty loci of 13 candidate genes were detected by MALDI-TOF mass spectrometry in 439 patients with MDD, 600 patients with BPD, and 464 healthy controls. The distribution of genotypes in alleles, Hardy-Weinberg equilibrium, and genetic association were analyzed using the PLINK software. The linkage of disequilibrium and haplotype analyses were performed using the Haploview software. RESULTS: Out of the 20 loci analyzed, CYP2C19-rs4986893, ABCB1-rs1045642, and SCN2A-rs17183814 passed Bonferroni correction; their statistical powers were > 55%. The minor allele frequencies (MAF) of CYP2C19-rs4986893 in the MDD group (0.0547) and BPD group (0.0533) were higher than that of the control group (0.0259, P < 0.05), leading to the odds ratios (ORs) of MDD (2.178) and BPD (2.122), respectively. In contrast, the lower MAFs of ABCB1-rs1045642 were observed in both MDD (0.3599, OR = 0.726) and BPD (0.3700, OR = 0.758) groups than controls (0.4364, P < 0.05). The MDD group had a higher MAF of SCN2A-rs17183814 than controls (0.1743 vs. 0.1207, OR = 1.538, P < 0.05). Moreover, a G-A haplotype composed by CYP2C19-rs4986893 and -rs4244285 was associated with BPD (OR = 1.361, P < 0.01), and the A-G haplotype increased the risks to both MDD (OR = 2.306, P < 0.01) and BPD (OR = 2.332, P < 0.001). The CYP2C19 intermediate metabolizer and poor metabolizer (IM&PM) status was related to the raised risk of both MDD (OR = 1.547, P < 0.01) and BPD (OR = 1.808, P < 0.001). CONCLUSION: Our data indicate that the impaired CYP2C19 metabolism caused by the haplotypes integrated by CYP2C19 alleles might confer the risk to MDD and BPD, whereas the ABCB1-rs1045642 T allele serves as a protective factor.

Differences in olfactory functional connectivity in early-onset depression and late-onset depression.

Background: Late-onset depression (LOD) and early-onset depression (EOD) exhibit different pathological mechanisms and clinical phenotypes, including different extents of olfactory dysfunction. However, the brain abnormalities underlying the differences in olfactory dysfunction between EOD and LOD remain unclear. Objective: The aim of this study was to compare the functional connectivity (FC) patterns of olfactory regions between EOD patients and LOD patients and examine their relationship with cognitive function. Methods: One hundred and five patients with EOD, 101 patients with LOD and 160 normal controls (NCs) were recruited for the present study. Participants underwent clinical assessment, olfactory testing, cognitive assessments, and magnetic resonance imaging. Eight regions of the primary and secondary olfactory regions were selected to investigate olfactory FC. Results: Patients with LOD exhibited decreased odor identification (OI) compared with patients with EOD and NCs. The LOD group exhibited decreased FC compared with the EOD and NC groups when primary and secondary olfactory regions were selected as the regions of interest (the piriform cortex, lateral entorhinal cortex, and orbital-frontal cortex). Additionally, these abnormal olfactory FCs were associated with decreased cognitive function scores and OI, and the FC between the left orbital-frontal cortex and left amygdala was a partial mediator of the relationship between global cognitive scores and OI. Conclusion: Overall, patients with LOD exhibited decreased FC in both the primary and secondary olfactory cortices compared with patients with EOD, and abnormal olfactory FC was associated with OI dysfunction and cognitive impairment. The FC between the orbital-frontal cortex and amygdala mediated the relationship between global cognitive function and OI.

SLC26A4 mutation in Pendred syndrome with hypokalemia: A case report.

RATIONALE: Pendred syndrome is an autosomal recessive disorder characterized by sensorineural hearing loss, inner ear malformations, goiter, and abnormal organification of iodide. It is caused by mutations in SLC26A4 gene, which encodes pendrin (a transporter of chloride, bicarbonate, and iodide). Pendred syndrome is a common cause of syndromic deafness, but the metabolic abnormalities it causes are often overlooked. Here, we report the case of a patient diagnosed with Pendred syndrome with hypokalemia. PATIENT CONCERNS: A 53-year-old deaf-mute woman was hospitalized due to severe limb asthenia. The emergency examination showed that her blood potassium level was 1.8 mmol/L. DIAGNOSES: Through the genetic test, we found a mutation of SLC26A4 gene in NM_000441: c.2027T>A, p.L676Q, as well as the SLC26A4 exon 5-6 deletion. These genetic variations pointed to Pendred syndrome (an autosomal recessive disorder that mainly affects the inner ear, thyroid, and kidney) which is a common cause of syndromic deafness. INTERVENTIONS: The patient was treated with potassium supplements and screened for the cause of hypokalemia. OUTCOMES: The patient was discharged after her potassium levels rose to the normal range. LESSONS: Patients with Pendred syndrome may also have certain metabolic abnormalities; thus, more attention should be paid to them during clinical diagnosis.

Static and dynamic functional connectivity variability of the anterior-posterior hippocampus with subjective cognitive decline.

BACKGROUND: Subjective cognitive decline (SCD) is a putative Alzheimer's disease (AD) precursor without objective neuropsychological deficits. The hippocampus plays an important role in cognitive function and emotional responses and is generally aberrant in SCD. However, previous studies have mainly focused on static functional connectivity (sFC) by resting-state functional magnetic resonance imaging (fMRI) in SCD individuals, and it remains unclear whether hippocampal dynamic functional connectivity (dFC) changes exist in SCD and whether those changes are associated with subtle changes in cognitive function or affect. METHODS: Seventy SCD patients and 65 healthy controls were recruited. Demographic data, comprehensive neuropsychology assessments, and resting-state fMRI data were collected. The bilateral anterior and posterior hippocampi were selected as seeds to investigate the static and dynamic functional connectivity alterations in SCD. RESULTS: Compared to healthy controls, subjects with SCD exhibited: (1) decreased sFC between the left caudal hippocampus and left precuneus; (2) decreased dFC variability between the bilateral caudal hippocampus and precuneus; (3) increased dFC variability between the bilateral rostral hippocampus and caudate nucleus; and (4) increased dFC variability between the left rostral hippocampus and left olfactory cortex. Additionally, the attention scores were positively correlated with dFC variability between the left posterior hippocampus and left precuneus, and the dFC variability between the bilateral anterior hippocampus and caudate nucleus was positively correlated with depression scores and negatively correlated with global cognition scores. CONCLUSION: SCD individuals exhibited abnormal sFC and dFC in the anterior-posterior hippocampus, and abnormal dFC was more widespread than abnormal sFC. A combination of sFC and dFC provides a new perspective for exploring the brain pathophysiological mechanisms in SCD and offers potential neuroimaging biomarkers for the early diagnosis and intervention of AD.

Shared and specific dynamics of brain activity and connectivity in amnestic and nonamnestic mild cognitive impairment.

AIMS: The present study aimed to compare temporal variability in the spontaneous fluctuations of activity and connectivity between amnestic MCI (aMCI) and nonamnestic MCI (naMCI), which enhances the understanding of their different pathophysiologies and provides targets for individualized intervention. METHODS: Sixty-five naMCI and 48 aMCI subjects and 75 healthy controls were recruited. A sliding window analysis was used to evaluate the dynamic amplitude of low-frequency fluctuations (dALFF), dynamic regional homogeneity (dReHo), and dynamic functional connectivity (dFC). The caudal/rostral hippocampus was selected as the seeds for calculating dFC. RESULTS: Both aMCI and naMCI exhibited abnormal dALFF, dReHo, and hippocampal dFC compared with healthy controls. Compared with individuals with naMCI, those with aMCI exhibited (1) higher dALFF variability in the right putamen, left Rolandic operculum, and right middle cingulum, (2) lower dReHo variability in the right superior parietal lobule, and (3) lower dFC variability between the hippocampus and other regions (left superior occipital gyrus, middle frontal gyrus, inferior cerebellum, precuneus, and right superior frontal gyrus). Additionally, variability in dALFF, dReHo, and hippocampal dFC exhibited different associations with cognitive scores in aMCI and naMCI patients, respectively. Finally, dReHo variability in the right superior parietal lobule and dFC variability between the right caudal hippocampus and left inferior cerebellum exhibited partially mediated effects on the different memory scores between people with aMCI and naMCI. CONCLUSION: The aMCI and naMCI patients exhibited shared and specific patterns of dynamic brain activity and connectivity. The dReHo of the superior parietal lobule and dFC of the hippocampus-cerebellum contributed to the memory heterogeneity of MCI subtypes. Analyzing the temporal variability in the spontaneous fluctuations of brain activity and connectivity provided a new perspective for exploring the different pathophysiological mechanisms in MCI subtypes.

Integrity of cerebellar tracts associated with the risk of bipolar disorder.

This study examined the structural brain differences across individuals of different BD stages and the risks of developing bipolar disorder (BD) associated with these brain differences. A total of 221 participants who were recruited from the Guangzhou Brain Hospital and the community were categorized into four groups: NC (healthy control) (N = 77), high risk (HR) (N = 42), ultra-high risk (UHR) (N = 38), and bipolar disorder (BD) (N = 64) based on a list of criteria. Their demographics, clinical characteristics, and diffusion magnetic resonance imaging (dMRI) data were collected. ANCOVA results showed that the HR group had significantly reduced mean diffusivity (MD) (p = 0.043) and radial diffusivity (RD) (p = 0.039) of the left portico-ponto-cerebellar tracts when compared with the BD group. Moreover, logistic regression results showed that the specific diffusivity measures of cerebellar tracts (e.g., cortico-ponto-cerebellar tract), particularly the RD and MD revealed differences between groups at different BD stages after controlling for the covariates. The findings suggested that specific diffusivity (RD and MD) of cerebellar tracts (e.g., cortico-ponto-cerebellar tract) revealed differences between groups at different BD stages which is helpful in detecting the trajectory changes in BD syndromes in the early stages of BD, particularly when the BD syndromes start from HR stage.

[Clinical Characteristic, Diagnosis and Treatment of Acute Lymphoblastic Leukemia Combined with Pneumocystis Carinii Pneumonia in Children].

OBJECTIVE: To investigate the clinical characteristics and treatment of pneumocystis carinii pneumonia (PCP) in children with acute lymphoblastic leukemia (ALL), in order to improve the early diagnosis and effective treatment. METHODS: Clinical data of five children with ALL developing PCP in the post-chemotherapy granulocyte deficiency phase were analyzed retrospectively. The clinical manifestations, laboratory tests, imaging findings, treatment methods and effect were summarized. RESULTS: The male-to-female ratio of the five children was 1∶4, and the median age was 5.5 (2.9-8) years old. All patients developed PCP during granulocyte deficiency phase after induction remission chemotherapy. The clinical manifestations were generally non-specific, including high fever, tachypnea, dyspnea, non-severe cough, and rare rales in two lungs (wet rales in two patients). Laboratory tests showed elevated C-reactive protein (CRP), serum procalcitonin (PCT), (1,3)-ß-D-glucan (BDG), lactate dehydrogenase (LDH) and inflammatory factors including IL-2R, IL-6 and IL-8. Chest CT showed diffuse bilateral infiltrates with patchy hyperdense shadows. Pneumocystis carinii(PC) was detected in bronchoalveolar lavage fluid (BALF) or induced sputum by high-throughput sequencing in all patients. When PCP was suspected, chemotherapy was discontinued immediately, treatment of trimethoprim-sulfame thoxazole (TMP-SMX) combined with caspofungin against PC was started, and adjunctive methylprednisolone was used. Meanwhile, granulocyte-stimulating factor and gammaglobulin were given as the supportive treatment. All patients were transferred to PICU receiving mechanical ventilation due to respiratory distress during treatment. Four children were cured and one died. CONCLUSION: PCP should be highly suspected in ALL children with high fever, dyspnea, increased LDH and BDG, and diffuse patchy hyperdense shadow or solid changes in lung CT. The pathogen detection of respiratory specimens should be improved as soon as possible. TMP/SMZ is the first-line drug against PCP, and the combination of Caspofungin and TMP/SMZ treatment for NH-PCP may have a better efficacy. Patients with moderate and severe NH-PCP may benefit from glucocorticoid.

Interactive Effects of Agitation and Cognitive Impairment on Odor Identification in Patients With Late-Life Depression.

Background: Late-life depression (LLD) is a risk factor for cognitive decline in older adults, and odor identification (OI) deficits are an early indicator of cognitive decline with LLD. However, neuropsychiatric symptoms (NPSs) are common in LLD and are associated with OI deficits. In subjects with LLD, when OI deficits forecast cognitive decline, whether and how NPS affects the relationship between OI and cognition still must be further explored. Objective: To comprehensively explore the potential effects of various NPSs on the relationship between OI and cognition in participants with LLD. Methods: There were 167 patients with LLD and 105 normal elderly (NE) participants. The odor identification test (Sniffin' Sticks), cognitive function assessments (global cognition, memory, executive function, attention, language, visual space), and an NPS assessment (the neuropsychiatric inventory questionnaire) were performed on the subjects. In patients with LLD, the relationship among OI, cognition and NPSs was examined using correlation analysis and moderation analysis. Results: In patients with LLD, OI was positively correlated with cognition (global cognition, memory, executive function, attention, language) and negatively associated with NPSs (agitation and aberrant motor behavior). In NE group, OI was correlated with executive function. Moderation analysis showed that there was an interactive effect of agitation and cognitive impairment (language deficit or attention deficit) on OI in patients with LLD. Conclusion: The coexistence of agitation and language or attention deficit was associated with worse OI in subjects with LLD. Agitation should be considered since OI predicts cognitive decline in patients with LLD.

Differences in Odor Identification in Early-Onset and Late-Onset Depression.

(1) Background: Odor identification (OI) dysfunction is a potential predictor of developing dementia in late life depression (LLD). However, it is not clear whether patients with early onset depression (EOD) and late onset depression (LOD) may exhibit different OI dysfunctions. The aim of this study was to compare OI between EOD patients and LOD patients and its relationship with cognitive function. (2) Methods: A total of 179 patients with LLD and 189 normal controls were recruited. Participants underwent clinical assessment, olfactory testing, and comprehensive neuropsychological assessment. The OI scores of EOD patients and LOD patients were compared, and correlation analyses and mediation analyses were used to explore the relationship between OI and cognition. (3) Result: LOD patients exhibited lower OI scores than EOD patients and normal controls (NCs). Additionally, the LOD patients exhibited a higher percentage of OI dysfunction than the EOD patients. Moreover, OI scores were associated with global cognition, memory, language, and visuospatial ability in the EOD group (p < 0.05) but were not associated with any cognitive score in the LOD patients (p > 0.05). Finally, the scores of the Auditory Verbal Learning Test Immediate recall and Boston Naming Test exhibited a partially mediating effect on the difference in OI scores between the EOD and LOD patients. (4) Conclusions: LOD patients exhibited worse OI than EOD patients, and their difference in OI was mediated by their memory and language function.

Large Scale Shadow Annotation and Detection Using Lazy Annotation and Stacked CNNs.

Recent shadow detection algorithms have shown initial success on small datasets of images from specific domains. However, shadow detection on broader image domains is still challenging due to the lack of annotated training data, caused by the intense manual labor required for annotating shadow data. In this paper we propose "lazy annotation", an efficient annotation method where an annotator only needs to mark the important shadow areas and some non-shadow areas. This yields data with noisy labels that are not yet useful for training a shadow detector. We address the problem of label noise by jointly learning a shadow region classifier and recovering the labels in the training set. We consider the training labels as unknowns and formulate label recovery as the minimization of the sum of squared leave-one-out errors of a Least Squares SVM, which can be efficiently optimized. Experimental results show that a classifier trained with recovered labels achieves comparable performance to a classifier trained on the properly annotated data. These results motivated us to collect a new dataset that is 20 times larger than existing datasets and contains a large variety of scenes and image types. Naturally, such a large dataset is appropriate for training deep learning methods. Thus, we propose a stacked Convolutional Neural Network architecture that efficiently trains on patch level shadow examples while incorporating image level semantic information. This means that the detected shadow patches are refined based on image semantics. Our proposed pipeline, trained on recovered labels, performs at state-of-the art level. Furthermore, the proposed model performs exceptionally well on a cross dataset task, proving the generalization power of the proposed architecture and dataset.

Deep Learning-Based Mapping of Tumor Infiltrating Lymphocytes in Whole Slide Images of 23 Types of Cancer.

The role of tumor infiltrating lymphocytes (TILs) as a biomarker to predict disease progression and clinical outcomes has generated tremendous interest in translational cancer research. We present an updated and enhanced deep learning workflow to classify 50x50 um tiled image patches (100x100 pixels at 20x magnification) as TIL positive or negative based on the presence of 2 or more TILs in gigapixel whole slide images (WSIs) from the Cancer Genome Atlas (TCGA). This workflow generates TIL maps to study the abundance and spatial distribution of TILs in 23 different types of cancer. We trained three state-of-the-art, popular convolutional neural network (CNN) architectures (namely VGG16, Inception-V4, and ResNet-34) with a large volume of training data, which combined manual annotations from pathologists (strong annotations) and computer-generated labels from our previously reported first-generation TIL model for 13 cancer types (model-generated annotations). Specifically, this training dataset contains TIL positive and negative patches from cancers in additional organ sites and curated data to help improve algorithmic performance by decreasing known false positives and false negatives. Our new TIL workflow also incorporates automated thresholding to convert model predictions into binary classifications to generate TIL maps. The new TIL models all achieve better performance with improvements of up to 13% in accuracy and 15% in F-score. We report these new TIL models and a curated dataset of TIL maps, referred to as TIL-Maps-23, for 7983 WSIs spanning 23 types of cancer with complex and diverse visual appearances, which will be publicly available along with the code to evaluate performance. Code Available at: https://github.com/ShahiraAbousamra/til_classification.

BACE1 and Other Alzheimer's-Related Biomarkers in Cerebrospinal Fluid and Plasma Distinguish Alzheimer's Disease Patients from Cognitively-Impaired Neurosyphilis Patients.

BACKGROUND: Patients with spirochetal infection, which causes neurosyphilis (NS) and at a later stage general paresis of the insane (GPI), present with brain pathology features of Alzheimer's disease (AD). However, the relationships among these illnesses regarding biomarker levels are still unclear. OBJECTIVE: To explore biomarker levels in NS and GPI compared with those in AD and the relationship between biomarker levels and cognitive function in NS and GPI. METHODS: Levels of neurogranin (NGRN) and ß-amyloid precursor protein cleaving enzyme (BACE1) in cerebrospinal fluid (CSF)/plasma, together with amyloid-ß 1-40 (Aß40), Aß42, and total tau in the CSF of 23 AD patients, 55 GPI patients, and 13 NS patients were measured. Patients were classified into none-to-mild, moderate, and severe stages of cognitive impairment. RESULTS: Levels of CSF NGRN, BACE1, and tau as well as plasma BACE1 levels were significantly different among groups. In the none-to-mild stage, plasma BACE1 levels correlated with the protein levels in CSF and were significantly increased in AD patients versus GPI patients. The CSF tau levels in AD patients were significantly increased versus GPI patients in the moderate and severe stages. Pooling data from GPI and NS patients, both CSF tau and plasma NGRN levels correlated with cognitive scale scores. CONCLUSION: GPI and NS patients might have different biomarker level patterns compared to AD patients. While plasma BACE1 could be a promising early biomarker for distinguishing AD from GPI, CSF tau and plasma NGRN levels might be valuable in indications of cognitive function in pooled NS populations.

Dataset of segmented nuclei in hematoxylin and eosin stained histopathology images of ten cancer types.

The distribution and appearance of nuclei are essential markers for the diagnosis and study of cancer. Despite the importance of nuclear morphology, there is a lack of large scale, accurate, publicly accessible nucleus segmentation data. To address this, we developed an analysis pipeline that segments nuclei in whole slide tissue images from multiple cancer types with a quality control process. We have generated nucleus segmentation results in 5,060 Whole Slide Tissue images from 10 cancer types in The Cancer Genome Atlas. One key component of our work is that we carried out a multi-level quality control process (WSI-level and image patch-level), to evaluate the quality of our segmentation results. The image patch-level quality control used manual segmentation ground truth data from 1,356 sampled image patches. The datasets we publish in this work consist of roughly 5 billion quality controlled nuclei from more than 5,060 TCGA WSIs from 10 different TCGA cancer types and 1,356 manually segmented TCGA image patches from the same 10 cancer types plus additional 4 cancer types.

Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor-Infiltrating Lymphocytes in Invasive Breast Cancer.

Quantitative assessment of spatial relations between tumor and tumor-infiltrating lymphocytes (TIL) is increasingly important in both basic science and clinical aspects of breast cancer research. We have developed and evaluated convolutional neural network analysis pipelines to generate combined maps of cancer regions and TILs in routine diagnostic breast cancer whole slide tissue images. The combined maps provide insight about the structural patterns and spatial distribution of lymphocytic infiltrates and facilitate improved quantification of TILs. Both tumor and TIL analyses were evaluated by using three convolutional neural network networks (34-layer ResNet, 16-layer VGG, and Inception v4); the results compared favorably with those obtained by using the best published methods. We have produced open-source tools and a public data set consisting of tumor/TIL maps for 1090 invasive breast cancer images from The Cancer Genome Atlas. The maps can be downloaded for further downstream analyses.

Increasing trimethylamine N-oxide levels as a predictor of early neurological deterioration in patients with acute ischemic stroke.

Background and aims: Trimethylamine N-oxide (TMAO), a pro-atherosclerotic intestinal microbiota metabolite, has mechanistic links to atherosclerosis development and cardiovascular diseases. In this study, we aimed to investigate whether serum TMAO levels could predict early neurological deterioration (END) after acute ischemic stroke.Methods: We prospectively recruited patients with first-ever ischemic stroke and hospitalized within 24 h of symptoms onset during Mar 2018 to Mar 2019. Plasma TMAO levels were quantified using stable isotope dilution high-performance liquid chromatography with tandem mass spectrometry after admission. END was defined as an increase in the total National Institutes of Health Stroke Scale by 2 or more points within 3 days.Results: Of the 362 patients included, END was diagnosed in 97 subjects (26.8%). The median TMAO concentrations were 4.8 µmol/L, with tertile levels as follows: first tertile (<3.9 µmol/L), second tertile (3.9-5.6 µmol/L), and third tertile (>5.6 µmol/L). Patients with END showed higher levels of TMAO (median 5.0 vs. 4.5 µmol/L, P = 0.005) at admission. In univariate logistic analysis, elevated plasma levels of TMAO [odd ratios for highest tertile vs. lowest tertile, 2.14; 95% confidence interval, 1.19-3.82] was a significant predictor of END in patients with ischemic stroke. This association remained significant after controlling for confounders in multivariate logistic analysis. Multiple-adjusted spline regression model further confirmed the dose-response relationship between TMAO levels and END (P < 0.001 for linearity).Conclusions: Our study indicated that increasing TMAO levels at admission might be associated with END after acute ischemic stroke.

Anion-Coordination-Assisted Assembly of Supramolecular Charge-Transfer Complexes Based on Tris(urea) Ligands.

Charge-transfer (CT) complexes, formed by noncovalent bonding between electron-rich (donor, D) and electron-deficient (acceptor, A) molecules (or moieties) have attracted considerable attention due to their fascinating structures and potential applications. Herein, we demonstrate that anion coordination is a promising strategy to promote CT complex formation between anion-binding, electron-rich tris(urea) donor ligands (D) and electron-deficient viologen cation acceptors (A), which form co-crystals featuring infinite ⋅⋅⋅DADA⋅⋅⋅ or discrete (circular DADA or three-decker DAD) π-stacking interactions. These CT complexes were studied by X-ray diffraction, UV/Vis spectroscopy, electric conductivity measurements, charge displacement curve (CDC) calculations, and DFT computations.