Aberrant dynamic functional network connectivity in progressive supranuclear palsy.

BACKGROUND: The clinical symptoms of progressive supranuclear palsy (PSP) may be mediated by aberrant dynamic functional network connectivity (dFNC). While earlier research has found altered functional network connections in PSP patients, the majority of those studies have concentrated on static functional connectivity. Nevertheless, in this study, we sought to evaluate the modifications in dynamic characteristics and establish the correlation between these disease-related changes and clinical variables. METHODS: In our study, we conducted a study on 53 PSP patients and 65 normal controls. Initially, we employed a group independent component analysis (ICA) to derive resting-state networks (RSNs), while employing a sliding window correlation approach to produce dFNC matrices. The K-means algorithm was used to cluster these matrices into distinct dynamic states, and then state analysis was subsequently employed to analyze the dFNC and temporal metrics between the two groups. Finally, we made a correlation analysis. RESULTS: PSP patients showed increased connectivity strength between medulla oblongata (MO) and visual network (VN) /cerebellum network (CBN) and decreased connections were found between default mode network (DMN) and VN/CBN, subcortical cortex network (SCN) and CBN. In addition, PSP patients spend less fraction time and shorter dwell time in a diffused state, especially the MO and SCN. Finally, the fraction time and mean dwell time in the distributed connectivity state (state 2) is negatively correlated with duration, bulbar and oculomotor symptoms. DISCUSSION: Our findings were that the altered connectivity was mostly concentrated in the CBN and MO. In addition, PSP patients had different temporal dynamics, which were associated with bulbar and oculomotor symptoms in PSPRS. It suggest that variations in dynamic functional network connectivity properties may represent an essential neurological mechanism in PSP.

Altered large-scale dynamic connectivity patterns in Alzheimer's disease and mild cognitive impairment patients: A machine learning study.

Alzheimer's disease (AD) is a common neurodegeneration disease associated with substantial disruptions in the brain network. However, most studies investigated static resting-state functional connections, while the alteration of dynamic functional connectivity in AD remains largely unknown. This study used group independent component analysis and the sliding-window method to estimate the subject-specific dynamic connectivity states in 1704 individuals from three data sets. Informative inherent states were identified by the multivariate pattern classification method, and classifiers were built to distinguish ADs from normal controls (NCs) and to classify mild cognitive impairment (MCI) patients with informative inherent states similar to ADs or not. In addition, MCI subgroups with heterogeneous functional states were examined in the context of different cognition decline trajectories. Five informative states were identified by feature selection, mainly involving functional connectivity belonging to the default mode network and working memory network. The classifiers discriminating AD and NC achieved the mean area under the receiver operating characteristic curve of 0.87 with leave-one-site-out cross-validation. Alterations in connectivity strength, fluctuation, and inter-synchronization were found in AD and MCIs. Moreover, individuals with MCI were clustered into two subgroups, which had different degrees of atrophy and different trajectories of cognition decline progression. The present study uncovered the alteration of dynamic functional connectivity in AD and highlighted that the dynamic states could be powerful features to discriminate patients from NCs. Furthermore, it demonstrated that these states help to identify MCIs with faster cognition decline and might contribute to the early prevention of AD.

Neuronal intranuclear inclusion disease mimicking progressive supranuclear palsy.

BACKGROUND: Given the variable nature of clinical manifestations, neuronal intranuclear inclusion disease (NIID) is regarded as a heterogeneous disease which is challenging to diagnose early. To the present, progressive supranuclear palsy (PSP)-like symptoms have never been listed in the performance of NIID. CASE PRESENTATION: A 58-year-old man presented with progressive Parkinsonism and postural instability for 3 years. Initially, he was considered as probable PSP due to vertical supranuclear gaze palsy, postural instability, and hummingbird sign. No high-intensity signal on diffusion-weighted imaging (DWI) was revealed. Eventually, the diagnosis was revised to NIID by Notch 2 N-terminal like C (NOTCH2NLC) GGC repeat expansions and skin biopsy showing intranuclear eosinophilic inclusions in the vesicles and ductal epithelial cells of sweat glands. CONCLUSION: Even if the typical high-intensity along the corticomedullary junction (CMJ) on DWI is lacking, clinicians should be alert to the possibility of NIID when PSP-like symptoms develop. This case report offers new features of NIID and expands its clinical spectrum.

Orthostatic tremor secondary to primary malignant melanoma of the spinal cord: A case report.

BACKGROUND AND PURPOSE: Orthostatic tremor and spinal cord melanoma are rare entities and seem unlikely to be associated. Herein, we report a patient diagnosed with orthostatic tremor secondary to primary malignant melanoma of the spinal cord. CASE PRESENTATION: We report the case of a 67-year-old man who experienced tremor when he was standing, which disappeared when he was sitting or walking. He also reported gait disturbance and cognitive dysfunction. Electromyography revealed a regular and symmetric high-frequency tremor in the lower extremities. The patient was admitted to a hospital several times and was diagnosed with primary orthostatic tremor and later hydrocephalus; thus, he received a ventriculoperitoneal shunt. Finally, he showed symptoms of the presence of melanoma in the spinal cord, which was supported by spinal cord magnetic resonance imaging findings. Primary malignant melanoma of the spinal cord was confirmed postoperatively. CONCLUSIONS: Orthostatic tremor is a rare entity that can be characterized by specific high-frequency tremors when the subject is standing. Considering that it remains unknown why this condition appears, some possible associations, such as primary spinal cord melanoma, should be considered. Thus, a comprehensive assessment of these types of patients is required. Our case report may facilitate the understanding of the pathophysiology and clinical symptoms of this disease.

Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease.

Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to elucidate the core disease mechanisms. In this study, we aim to comprehensively characterize AD-associated functional brain alterations using one of the world's largest resting-state functional MRI (fMRI) biobank for the disorder. The biobank includes fMRI data from six neuroimaging centers, with a total of 252 AD patients, 221 mild cognitive impairment (MCI) patients and 215 healthy comparison individuals. Meta-analytic techniques were used to unveil reliable differences in brain function among the three groups. Relative to the healthy comparison group, AD was associated with significantly reduced functional connectivity and local activity in the default-mode network, basal ganglia and cingulate gyrus, along with increased connectivity or local activity in the prefrontal lobe and hippocampus (p < .05, Bonferroni corrected). Moreover, these functional alterations were significantly correlated with the degree of cognitive impairment (AD and MCI groups) and amyloid-ß burden. Machine learning models were trained to recognize key fMRI features to predict individual diagnostic status and clinical score. Leave-one-site-out cross-validation established that diagnostic status (mean area under the receiver operating characteristic curve: 0.85) and clinical score (mean correlation coefficient between predicted and actual Mini-Mental State Examination scores: 0.56, p < .0001) could be predicted with high accuracy. Collectively, our findings highlight the potential for a reproducible and generalizable functional brain imaging biomarker to aid the early diagnosis of AD and track its progression.

A novel compound heterozygous mutation in AARS2 gene (c.965 G > A, p.R322H; c.334 G > C, p.G112R) identified in a Chinese patient with leukodystrophy involved in brain and spinal cord.

Leukodystrophies are genetic disorders leading to progressive white matter degeneration in the central nervous system. Mitochondrial aminoacyl tRNA synthase protein is encoded by the nuclear gene AARS2. An autosomal recessive mutation in this gene has been linked to AARS2 mutation-related adult-onset leukodystrophy (AARS2-L) or infantile mitochondrial cardiomyopathy. To date, only 16 AARS2-L cases have been reported in English literature. Thus, the clinical and genetic characteristics of this disease remain to be defined. Through whole-exome sequencing, we identified a Chinese patient with leukodystrophy related to two novel compounds heterozygous mutation in AARS2 (c.965 G > A, p.R322H; c.334 G > C, p.G112R). These two compounds heterozygous variants in AARS2 gene co-segregated with disease in his family. And pyramidal tracts in the spinal cord were involved. Our findings have important implications on genetic counseling for any case with leukodystrophy and extend the mutational spectrum in AARS2 gene.

Deep decarbonization potential and implementation path under provincial differences in China's fleet electrification.

Fleet electrification is considered to be an important measure for reducing carbon emissions in the road transport industry. Considering the heterogeneity of the NEV market penetration and the vehicle types in different provinces, how to design targeted and time-sequenced road transport decarbonisation reduction strategies has become a key issue that needs to be discussed urgently. In this study, the NEVs ownership in China's 31 provinces is used as an intermediate variable. Considering the process of energy transition and changes in vehicle structure, a two-layer scenario framework that combines Shared Socioeconomic Pathways scenarios and model structure was developed to predict carbon emissions. This study firstly analyzes the electrification process and carbon emission reduction potential of provincial road transport industry by region, vehicle type and stage. The potential for reducing carbon emissions was determined under benchmark, transition, and electrification scenarios. The results indicate that the Pearson Correlation Coefficient-Discrete Wavelet Transform-Bidirectional Long Short-term Memory prediction model has an mean absolute percentage error of 8.583 and an R-squared of 0.975. China's road transportation industry total carbon emissions will reach its peak as early as 2027, due to the rapid implementation of renewable energy and fleet electrification. Shanghai, Jiangsu, Shandong, Henan, and Guangdong have set carbon peak targets that can be achieved faster with the transition plan for new energy vehicles to replace fossil fuel vehicles. This paper proposes a timing-responsive deep decarbonization path and policy recommendations for China's road transport industry in sub provincial and time-series settings.

Convergent Neuroimaging and Molecular Signatures in Mild Cognitive Impairment and Alzheimer's Disease: A Data-Driven Meta-Analysis with N = 3,118.

The current study aimed to evaluate the susceptibility to regional brain atrophy and its biological mechanism in Alzheimer's disease (AD). We conducted data-driven meta-analyses to combine 3,118 structural magnetic resonance images from three datasets to obtain robust atrophy patterns. Then we introduced a set of radiogenomic analyses to investigate the biological basis of the atrophy patterns in AD. Our results showed that the hippocampus and amygdala exhibit the most severe atrophy, followed by the temporal, frontal, and occipital lobes in mild cognitive impairment (MCI) and AD. The extent of atrophy in MCI was less severe than that in AD. A series of biological processes related to the glutamate signaling pathway, cellular stress response, and synapse structure and function were investigated through gene set enrichment analysis. Our study contributes to understanding the manifestations of atrophy and a deeper understanding of the pathophysiological processes that contribute to atrophy, providing new insight for further clinical research on AD.

Analysis of EIF4G1 in ethnic Chinese.

BACKGROUND: Eukaryotic translation initiation factor 4-gamma 1 (EIF4G1) gene mutations have recently been reported in autosomal dominant, late-onset Parkinson's disease (LOPD). We carried out genetic analysis to determine the prevalence of EIF4G1 variants in an ethnic Chinese population and to better understand the association between EIF4G1 and PD. METHODS: We conducted a comprehensive genetic analysis of EIF4G1 in a cohort of 29 probands of autosomal dominant, LOPD families. Polymerase chain reaction (PCR) analysis and sequencing was carried out of the entire EIF4G1 exonic regions and exon-intron boundaries. Specific mutation and exonic variants were chosen for further sequencing in a case-control study including 503 sporadic PD and 508 healthy controls. Statistical significance was analyzed by the Chi-square test. RESULTS: Our analysis revealed three exonic variants (rs2230571, rs13319149 and rs2178403) and eight intronic variants across the entire EIF4G1 gene. No reported mutations were detected in EIF4G1 exonic regions. The synonymous coding variant rs2230571 in exon 27 and the eight intronic variants were not used for further sequencing, but the specific mutation c.3614G > A (p.R1205H) and the two nonsynonymous variants (rs13319149 and rs2178403) were chosen for further analysis in a case-control study. None of the 503 sporadic PD or 508 healthy controls carried p.R1205H, and there was no statistical significance in rs2178403 genotype or allele frequencies in EIF4G1 between the PD cases and the healthy controls (p = 0.184 and p = 0.774, respectively; Chi-square test). The rs13319149 genotype in all PD cases and healthy controls was GG. CONCLUSIONS: Our data indicate that in an ethnic Chinese population, the pathogenic mutation p.R1205H in EIF4G1 is not common and that EIF4G1 exonic variants rs2178403 and rs13319149 are not associated with PD. EIF4G1 does not appear to be a frequent cause of PD in this ethnic Chinese population.

A high urinary urobilinogen/serum total bilirubin ratio indicates acute hepatic porphyria in patients with abdominal pain.

Acute hepatic porphyria (AHP) has always been a diagnostic dilemma for physicians due to its variable symptoms. Correct diagnosis mainly depends on the detection of an elevated urinary porphobilinogen (PBG), which is not a routine test and highly relies on the physician's awareness of AHP. In the present study, we identified a more convenient indicator during routine examinations to improve the diagnosis of AHP. We found that AHP patients showed a significant higher "FALSE" urinary urobilinogen level caused by urinary PBG during the urinalysis when detected by strips impregnated with Ehrlich reagent (P < 0.05). And a remarkable increase in the urinary urobilinogen/serum total bilirubin ratio was observed in AHP patients. The area under the ROC curve of this ratio for AHP was 1.000 (95% confidence interval 1.000-1.000, P < 0.01). A cutoff value of 3.22 for this ratio yielded a sensitivity of 100% and a specificity of 100% to distinguish AHP patients from the controls. Thus, we proved that a "falsely" high urinary urobilinogen level that was adjusted by the serum total bilirubin level (urinary urobilinogen/serum total bilirubin ratio) could be used as a sensitive and specific screening marker for AHP in patients with abdominal pain.

Four Distinct Subtypes of Alzheimer's Disease Based on Resting-State Connectivity Biomarkers.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder with significant heterogeneity. Different AD phenotypes may be associated with specific brain network changes. Uncovering disease heterogeneity by using functional networks could provide insights into precise diagnoses. METHODS: We investigated the subtypes of AD using nonnegative matrix factorization clustering on the previously identified 216 resting-state functional connectivities that differed between AD and normal control subjects. We conducted the analysis using a discovery dataset (n = 809) and a validated dataset (n = 291). Next, we grouped individuals with mild cognitive impairment according to the model obtained in the AD groups. Finally, the clinical measures and brain structural characteristics were compared among the subtypes to assess their relationship with differences in the functional network. RESULTS: Individuals with AD were clustered into 4 subtypes reproducibly, which included those with 1) diffuse and mild functional connectivity disruption (subtype 1), 2) predominantly decreased connectivity in the default mode network accompanied by an increase in the prefrontal circuit (subtype 2), 3) predominantly decreased connectivity in the anterior cingulate cortex accompanied by an increase in prefrontal cortex connectivity (subtype 3), and 4) predominantly decreased connectivity in the basal ganglia accompanied by an increase in prefrontal cortex connectivity (subtype 4). In addition to these differences in functional connectivity, differences between the AD subtypes were found in cognition, structural measures, and cognitive decline patterns. CONCLUSIONS: These comprehensive results offer new insights that may advance precision medicine for AD and facilitate strategies for future clinical trials.

Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer's Disease.

Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.

Altered global signal topography in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disease associated with widespread disruptions in intrinsic local specialization and global integration in the functional system of the brain. These changes in integration may further disrupt the global signal (GS) distribution, which might represent the local relative contribution to global activity in functional magnetic resonance imaging (fMRI). METHODS: fMRI scans from a discovery dataset (n = 809) and a validated dataset (n = 542) were used in the analysis. We investigated the alteration of GS topography using the GS correlation (GSCORR) in patients with mild cognitive impairment (MCI) and AD. The association between GS alterations and functional network properties was also investigated based on network theory. The underlying mechanism of GSCORR alterations was elucidated using imaging-transcriptomics. FINDINGS: Significantly increased GS topography in the frontal lobe and decreased GS topography in the hippocampus, cingulate gyrus, caudate, and middle temporal gyrus were observed in patients with AD (Padj < 0.05). Notably, topographical GS changes in these regions correlated with cognitive ability (P < 0.05). The changes in GS topography also correlated with the changes in functional network segregation (ρ = 0.5). Moreover, the genes identified based on GS topographical changes were enriched in pathways associated with AD and neurodegenerative diseases. INTERPRETATION: Our findings revealed significant changes in GS topography and its molecular basis, confirming the informative role of GS in AD and further contributing to the understanding of the relationship between global and local neuronal activities in patients with AD. FUNDING: Beijing Natural Science Funds for Distinguished Young Scholars, China; Fundamental Research Funds for the Central Universities, China; National Natural Science Foundation, China.

Autophagy and Its Comprehensive Impact on ALS.

Autophagy is a degradative modality that involves intracellular elimination of proteins and organelles by lysosomes. It is a conservative process and plays a crucial role in cell growth and development, and keeping cellular homeostasis especially under stress-induced situations. Recently, increasing evidence suggests that autophagic alternations may contribute to amyotrophic lateral sclerosis (ALS) as one of initial factors. LC3-II and p62 are found increased in spinal cord of both ALS patients and experimental models, indicating overwhelming autophagic level. But the aggregation of ALS-associated proteins, including SOD1 and TDP-43 suggest possible insufficiency of autophagy induction. Besides, augment autophagic level through genetic pathway or rapamycin leads to paradoxical results in different neurodegenerative diseases models. So, it remains controversial about autophagic effects on ALS progress. In this review, we will depict a comprehensive role that autophagy plays in ALS and focus on the influence of impaired autophagic flux and excessive autophagic vacuoles (AVs) that may aggregate ALS development. And we will discuss the potential therapeutic targets through modulating autophagic level to treat this disease.

Forecasting of China's solar PV industry installed capacity and analyzing of employment effect: based on GRA-BiLSTM model.

With the acceleration of China's energy transformation process and the rapid increase of renewable energy market demand, the photovoltaic (PV) industry has created more jobs and effectively alleviated the employment pressure of the labor market under the normalization of the epidemic situation. First, to accurately predict China's solar PV installed capacity, this paper proposes a multi-factor installed capacity prediction model based on bidirectional long short-term memory-grey relation analysis. The results show that, the MAPE value of the GRA-LSTM combined model established in this paper is 5.995, compared with the prediction results of other models, the prediction accuracy of the GRA-BiLSTM model is higher. Second, the BiLSTM model is used to forecast China's installed solar PV capacity from 2020 to 2035. The forecast results show that China's newly installed solar PV capacity will continue to grow and reach 2833GW in 2035. Third, the employment number in China's solar PV industry during 2020-2035 is predicted by the employment factors (EF) method. The results show that the energy transition in China during 2020-2035 will have a positive impact on the future stability and growth of the labor market in the solar PV industry. Overall, an accurate forecast of solar PV installed capacity can provide effective decision support for planning electric power development strategy and formulating employment policy of solar PV industry.

Growth Differentiation Factor 15 Protects SH-SY5Y Cells From Rotenone-Induced Toxicity by Suppressing Mitochondrial Apoptosis.

Objective: Parkinson's disease (PD) is the second most common neurodegenerative disorder worldwide. Mitochondrial dysfunction is suspected as one of the pathogenic mechanisms of PD. Growth/differentiation Factor-15 (GDF15) has been reported to affect mitochondrial function in PD. However, the relationship between mitochondrial function and GDF15 induction has not been explained well. Hence, we aimed to reveal the effect of GDF15 induction on SH-SY5Y cells with rotenone toxicity, a cell model of PD. Methods: SH-SY5Y cells were exposed to 1 µM rotenone as a PD model. Cells were transfected with a GDF15-overexpression plasmid and empty vector. We then analyzed the expression level of GDF15, BCL-2/BAX, P53, PGC1-α, α-syn, and TH in GDF15-overexpressing cells by western blotting, enzyme-linked immunosorbent assay, and quantitative real-time polymerase chain reaction. The cytotoxicity of rotenone was measured by CCK-8 assays. Cell apoptosis was detected by flow cytometric and TUNEL assays. The effect of GDF15 on oxidative stress and mitochondrial function was revealed using DCFH-DA, mito-SOX, and JC-10 assays and a Seahorse XF Cell Mito Stress Test. Results: GDF15 protected rotenone-treated SH-SY5Y cells from toxicity by preserving mitochondrial function and decreasing apoptosis, during which GDF15 might function by influencing PGC1α through the regulation of p53. In addition, GDF15 overexpression could improve Akt and mTOR phosphorylation, leading to PI3K/Akt/mTOR pathway activation. However, these protective effects were eliminated when cells were treated with the PI3K/Akt specific inhibitor LY294002. Conclusion: Our findings suggest that GDF15 can protect mitochondrial function and inhibit apoptosis in SH-SY5Y cells after exposure to rotenone by upregulating PGC1α via p53. These properties might comprise its anti-apoptotic effects, mediated by the PI3K/Akt/mTOR signaling pathway.

Celastrol attenuates 6-hydroxydopamine-induced neurotoxicity by regulating the miR-146a/PI3K/Akt/mTOR signaling pathways in differentiated rat pheochromocytoma cells.

BACKGROUND: Parkinson's disease (PD) is a neurological disorder. Recently, celastrol (Cel) has been reported to have neuroprotective properties. We investigated the protective effects of Cel on PD in a cell model with 6-hydroxydopamine (6-OHDA)-induced neurotoxicity in PC12 cells and further addressed the underlying protective mechanisms of Cel. METHODS: PC12 cells were treated with 6-OHDA, and Cel was added to the medium at various concentrations. The CCK-8 assay, Hoechst/PI staining, and flow cytometry analysis were performed to detect cellular viability and apoptosis. Mitochondrial membrane potential (MMP) was examined by JC-1 staining. ROS level was quantified by ROS staining. The effects of Cel on the expression of miR-146a and PI3K/Akt/mTOR pathway were then clarified using real-time PCR and Western blotting. Moreover, a miR-146a mimic was synthesized and transfected into PC12 cells to further determine the mechanisms of Cel's neuronal protection against 6-OHDA-induced neurotoxicity. RESULTS: Cel greatly improved cell viability and lessened apoptosis. Flow cytometry showed that Cel especially inhibited early apoptosis. Cel also obviously restored the MMP and decreased ROS level destroyed by 6-OHDA. Moreover, 6-OHDA increased the expression of miR-146a and decreased pAkt/mTOR protein levels, whereas Cel reversed these changes. In particular, miR-146a targeted and inhibited the expression of PI3K, an upstream molecule of Akt/mTOR. Transfection of 6-OHDA-treated neurons with miR-146a mimic notably attenuated Cel's protective effects. LIMITATIONS: There were no animal experiments in our study. CONCLUSIONS: Cel exerts neuroprotective activity against 6-OHDA-caused neurotoxicity by regulating miR-146a/PI3K/Akt/mTOR pathway, which provides a potential application of Cel for treating neurodegenerative diseases.

Independent and reproducible hippocampal radiomic biomarkers for multisite Alzheimer's disease: diagnosis, longitudinal progress and biological basis.

Hippocampal morphological change is one of the main hallmarks of Alzheimer's disease (AD). However, whether hippocampal radiomic features are robust as predictors of progression from mild cognitive impairment (MCI) to AD dementia and whether these features provide any neurobiological foundation remains unclear. The primary aim of this study was to verify whether hippocampal radiomic features can serve as robust magnetic resonance imaging (MRI) markers for AD. Multivariate classifier-based support vector machine (SVM) analysis provided individual-level predictions for distinguishing AD patients (n = 261) from normal controls (NCs; n = 231) with an accuracy of 88.21% and intersite cross-validation. Further analyses of a large, independent the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (n = 1228) reinforced these findings. In MCI groups, a systemic analysis demonstrated that the identified features were significantly associated with clinical features (e.g., apolipoprotein E (APOE) genotype, polygenic risk scores, cerebrospinal fluid (CSF) Aß, CSF Tau), and longitudinal changes in cognition ability; more importantly, the radiomic features had a consistently altered pattern with changes in the MMSE scores over 5 years of follow-up. These comprehensive results suggest that hippocampal radiomic features can serve as robust biomarkers for clinical application in AD/MCI, and further provide evidence for predicting whether an MCI subject would convert to AD based on the radiomics of the hippocampus. The results of this study are expected to have a substantial impact on the early diagnosis of AD/MCI.

Generalizable, Reproducible, and Neuroscientifically Interpretable Imaging Biomarkers for Alzheimer's Disease.

Precision medicine for Alzheimer's disease (AD) necessitates the development of personalized, reproducible, and neuroscientifically interpretable biomarkers, yet despite remarkable advances, few such biomarkers are available. Also, a comprehensive evaluation of the neurobiological basis and generalizability of the end-to-end machine learning system should be given the highest priority. For this reason, a deep learning model (3D attention network, 3DAN) that can simultaneously capture candidate imaging biomarkers with an attention mechanism module and advance the diagnosis of AD based on structural magnetic resonance imaging is proposed. The generalizability and reproducibility are evaluated using cross-validation on in-house, multicenter (n = 716), and public (n = 1116) databases with an accuracy up to 92%. Significant associations between the classification output and clinical characteristics of AD and mild cognitive impairment (MCI, a middle stage of dementia) groups provide solid neurobiological support for the 3DAN model. The effectiveness of the 3DAN model is further validated by its good performance in predicting the MCI subjects who progress to AD with an accuracy of 72%. Collectively, the findings highlight the potential for structural brain imaging to provide a generalizable, and neuroscientifically interpretable imaging biomarker that can support clinicians in the early diagnosis of AD.

Minocycline Protects against Rotenone-Induced Neurotoxicity Correlating with Upregulation of Nurr1 in a Parkinson's Disease Rat Model.

The aim of this study was to investigate the effect of minocycline in rats with rotenone-induced Parkinson's disease (PD). The open field test was performed to determine the motor ability of the rats. Double immunofluorescence staining was used to detect the expression of tyrosine hydroxylase (TH) and Nurr1 in the substantia nigra (SN) of rats. The relative protein levels of TH, Nurr1, and the total- and phosphorylated-cAMP-response element binding protein (CREB) were determined by western blot analysis. The production of reactive oxygen species (ROS) and nitric oxide (NO) was detected by commercial kits. After exposure to rotenone for 28 days, rats exhibited decreased ambulation and rearing frequency and prolonged immobility time with loss of TH positive neurons in the SN. The phosphorylation levels of CREB and Nurr1 expression decreased significantly accompanied with the release of ROS and NO. Minocycline alleviated the motor deficits of rats lesioned by rotenone and elevated the expression of TH, as well as suppressing the release of ROS and NO in the SN. That was in line with the elevated phosphorylation levels of CREB and Nurr1 expression. In conclusion, our present study showed minocycline protected against neurotoxicity in a rotenone-induced rat model of PD, which was correlated with upregulation of Nurr1.