Preoperative Evaluation of Neurovascular Relationship in Primary Trigeminal Neuralgia(PTN) by Magnetic Resonance Virtual Endoscopy(MRVE) Combined with 3D-FIESTA-c and 3D-TOF-MRA.

Objective: This study aims to evaluate the effectiveness of Magnetic Resonance Virtual Endoscopy combined with 3D-FIESTA-c and 3D-TOF-MRA in preoperative assessment of MVD for PTN, with a focus on accurately detecting neuromuscular contact. Methods: We retrospectively analyzed clinical and imaging data from 240 patients with unilateral primary trigeminal neuralgia undergoing MVD surgery between April 2016 and July 2023. Preoperative scans with 3D-FIESTA-c and 3D-TOF-MRA were performed, and MRVE images were obtained to analyze the relationship between the trigeminal nerve and adjacent vessels. Using the findings during microvascular decompression (MVD) surgery as the gold standard, the diagnostic results of 3D-TOF-MRA + 3D-FIESTA-c were considered as group I, while the combined use of MRVE, 3D-TOF-MRA + 3D-FIESTA-c was considered as group II. Results: In 240 cases, group I had a positive rate of 96.25% and an accuracy rate of 86.25% for identifying responsible blood vessels, while group II had a positive rate of 98.3% and an accuracy rate of 94.17%. There were no statistically significant differences in positive rates between group I and group II, group I and MVD, or group II and MVD (P > 0.05). However, there were statistically significant differences in accuracy rates (P < 0.05). The accuracy for single and multiple arteries with group I was 99.38% and 80.0%, respectively, while with group II, it was 100% and 95.0%. No statistically significant difference was found in accuracy for single or multiple arteries (P>0.05). The accuracy of evaluating responsibility veins with or without other vessels was 52.73% and 80.0%, respectively, with a statistically significant difference (P<0.05). Conclusion: MRVE combined with 3D-TOF-MRA + 3D-FIESTA-c significantly improves the accuracy of identifying responsibility vessels, especially veins, in preoperative assessment for MVD. This has important clinical implications for preoperative decision-making and surgical planning.

Rich Sulfur Vacancies and Reduced Schottky Barrier Height Synergistically Enable Au/ZnIn2S4 with Enhanced Photocatalytic CO2 Reduction into CO.

Constructing the plasmonic metal/semiconductor heterostructure with a suitable Schottky barrier height (SBH) and the sufficiently reliable active sites is of importance to achieve highly efficient and selective photocatalytic CO2 reduction into hydrocarbon fuels. Herein, we report Au/sulfur vacancy-rich ZnIn2S4 (Au/VSR-ZIS) hierarchical photocatalysts, fabricated via in situ photodepositing Au nanoparticles (NPs) onto the nanosheet self-assembled ZnIn2S4 (ZIS) micrometer flowers (MFs) with rich sulfur vacancies (VS). Density functional theory (DFT) calculations confirm that for the Au/VSR-ZIS system, the Au NPs serve as the reaction sites for H2O oxidation, and the VSR-ZIS MFs serve as those for CO2 reduction. The rich VS in the Au/VSR-ZIS hybrid can reduce its SBH so as to boost more hot electrons in the Au NPs across its Schottky barrier and then inject into the conduction band (CB) of the VSR-ZIS MFs. In addition, VS can also act as the electron sink to trap the photogenerated electrons, retarding the recombination of photogenerated carriers. The two merits effectively enhance the photogenerated electron density in the surface of VSR-ZIS MFs, availing CO2 photoreduction. In addition, the introduction of rich VS in the Au/VSR-ZIS hybrid can offer more active sites, benefiting the CO2 adsorption and accelerating the desorption of CO* from the surface of the photocatalyst. Therefore, under visible light illumination with no sacrificial reagent, the optimum photocatalyst (Au/VSR-ZIS-0.4) presents the enhanced and selective CO2 photoreduction into CO (8.15 µmol g-1h-1 and near 100%), which are superior to those of most of ZIS-based and plasmon-based photocatalysts. The photocatalytic activity is about 40.0-fold as high as that of the Vs-poor-ZIS (VSP-ZIS) MFs. This work contributes a viable strategy for designing highly efficient plasmonic photocatalysts by using the synergism of the anion vacancies and the optimized SBH induced by them.

Effects of calorie-restricted diet on health state and intestinal flora in Hashimoto's thyroiditis patients: Study protocol for a randomized controlled trial.

BACKGROUND AND OBJECTIVES: Hashimoto's thyroiditis (HT) is an autoimmune disease, characterized by abnormal elevation in thyroid peroxidase antibody and/or thyroglobulin antibody. In recent decades, HT disease has become more and more widespread. Patients always report multiple symptoms, even though their thyroid hormone levels are kept in normal ranges. However, no treatment exists to effectively reduce the levels of thyroid antibodies. Our study aims to determine whether calorie-restricted diet is helpful in improving health of HT patients. METHODS AND STUDY DESIGN: This is a 3-month randomized controlled trial. HT patients will be randomized into a calorie-restricted (CR) group or a calorie-unrestricted control group. All the participants will be instructed to consume a diet that includes a combination of 45-55% calories from carbohydrates, 20-30% from fats, and 15-25% from proteins, according to current Chinese Dietary Guidelines. Participants in CR group need to limit their calories intake equal to their basal energy expenditure, which means that their daily caloric intake will be limited by about 20-30%. RESULTS: The study population is planned to be 66 HT patients aged 18 to 65 years. The primary outcome is change of thyroid antibody levels from baseline. Secondary outcomes include the changes of non-hypothyroid symptoms scores, thyroid function indexes, morphology of thyroid, T lymphocyte subpopulations, inflammatory biomarkers and lipids from baseline to 12 weeks. CONCLUSIONS: This trial will have implications for nutrition treatment policy in regard to thyroid antibodies control, immune dysfunction and related non-hypothyroid symptoms improvement among HT patients.

Directed Functional Connectivity Changes of Triple Networks for Stable and Progressive Mild Cognitive Impairment.

Mild cognitive impairment includes two distinct subtypes, namely progressive mild cognitive impairment and stable mild cognitive impairment. While alterations in extensive functional connectivity have been observed in both subtypes, limited attention has been given to directed functional connectivity. A triple network, composed of the central executive network, default mode network, and salience network, is considered to be the core cognitive network. We evaluated the alterations in directed functional connectivity within and between the triple network in progressive and stable mild cognitive impairment groups and investigated its role in predicting disease conversion. Resting-state functional magnetic resonance imaging was used to analyze directed functional connectivity within the triple networks. A correlation analysis was performed to investigate potential associations between altered directed functional connectivity within the triple networks and the neurocognitive performance of the participants. Our study revealed significant differences in directed functional connectivity within and between the triple network in the progressive and stable mild cognitive impairment groups. Altered directed functional connectivity within the triple network was involved in episodic memory and executive function. Thus, the directed functional connectivity of the triple network may be used as an imaging marker of mild cognitive impairment.

MDMX in Cancer: A Partner of p53 and a p53-Independent Effector.

The p53 tumor suppressor protein plays an important role in physiological and pathological processes. MDM2 and its homolog MDMX are the most important negative regulators of p53. Many studies have shown that MDMX promotes the growth of cancer cells by influencing the regulation of the downstream target gene of tumor suppressor p53. Studies have found that inhibiting the MDMX-p53 interaction can effectively restore the tumor suppressor activity of p53. MDMX has growth-promoting activities without p53 or in the presence of mutant p53. Therefore, it is extremely important to study the function of MDMX in tumorigenesis, progression and prognosis. This article mainly reviews the current research progress and mechanism on MDMX function, summarizes known MDMX inhibitors and provides new ideas for the development of more specific and effective MDMX inhibitors for cancer treatment.

MDM4 was associated with poor prognosis and tumor-immune infiltration of cancers.

MDM4 is one of the MDM protein family and is generally recognized as the key negative regulator of p53. As a cancer-promoting factor, it plays a non-negligible role in tumorigenesis and development. In this article, we analyzed the expression levels of MDM4 in pan-cancer through multiple databases. We also investigated the correlations between MDM4 expression and prognostic value, immune features, genetic mutation, and tumor-related pathways. We found that MDM4 overexpression is often accompanied by adverse clinical features, poor prognosis, oncogenic mutations, tumor-immune infiltration and aberrant activation of oncogenic signaling pathways. We also conducted transcriptomic sequencing to investigate the effect of MDM4 on transcript levels in colon cancer and performed qPCR to verify this. Finally, we carried out some in vitro experiments including colony formation assay, chemoresistance and senescence-associated ß-galactosidase activity assay to study the anti-tumor treatment effect of small molecule MDM4 inhibitor, NSC146109. Our research confirmed that MDM4 is a prognostic biomarker and potential therapeutic target for a variety of malignancies.

WNT7A promotes tumorigenesis of head and neck squamous cell carcinoma via activating FZD7/JAK1/STAT3 signaling.

Wnt signaling are critical pathway involved in organ development, tumorigenesis, and cancer progression. WNT7A, a member of the Wnt family, remains poorly understood in terms of its role and the underlying molecular mechanisms it entails in head and neck squamous cell carcinoma (HNSCC). According to the Cancer Genome Atlas (TCGA), transcriptome sequencing data of HNSCC, the expression level of WNT7A in tumors was found to be higher than in adjacent normal tissues, which was validated using Real-time RT-PCR and immunohistochemistry. Unexpectedly, overexpression of WNT7A did not activate the canonical Wnt-ß-catenin pathway in HNSCC. Instead, our findings suggested that WNT7A potentially activated the FZD7/JAK1/STAT3 signaling pathway, leading to enhanced cell proliferation, self-renewal, and resistance to apoptosis. Furthermore, in a patient-derived xenograft (PDX) tumor model, high expression of WNT7A and phosphorylated STAT3 was observed, which positively correlated with tumor progression. These findings underscore the significance of WNT7A in HNSCC progression and propose the targeting of key molecules within the FZD7/JAK1/STAT3 pathway as a promising strategy for precise treatment of HNSCC.

Aberrant spontaneous static and dynamic amplitude of low-frequency fluctuations in cerebral small vessel disease with or without mild cognitive impairment.

BACKGROUND: Cerebral small vessel disease (CSVD) is considered an age-related degenerative neurological disorder and the most common risk factor for vascular cognitive impairment (VCI). The amplitude of fluctuation of low frequency (ALFF) can detect altered intrinsic brain activity in CSVD. This study explored the static and dynamic ALFFs in the early stage of CSVD with (CSVD-M) or without (CSVD-W) mild cognitive impairment (MCI) in these patients and how these changes contribute to cognitive deterioration. METHODS: Thirty consecutive CSVD cases and 18 healthy controls (HC) were included in this study. All the participants underwent a 3D magnetization-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images. Simultaneous multislice imaging 5(SMS5) was used for resting-state functional MRI (rs-fMRI), and Data Processing and Analysis of Brain Imaging software helped determine static ALFF (sALFF). The dynamic ALFF (dALFF) was calculated using the sliding window method of DynamicBC software. Analysis of Covariance (ANCOVA) and two-sample t-test were used to evaluate the sALFF and temporal variability of dALFF among the three groups. The subjects were rated on a broad standard neuropsychological scale. Partial correlation analysis was used to evaluate the correlation between sALFF and dALFF variability and cognition (Bonferroni correction, statistical threshold set at p < .05). RESULTS: Compared with HCs, the CSVD-M group indicated decreased sALFF values in the bilateral cerebellum posterior lobe (CPL) and the left inferior Parietal Lobule (IPL), with increased sALFF values in the right SFG. For dALFF analysis, the CSVD-W group had significant dALFF variability in the right fusiform gyrus compared with HC. Moreover, the postcentral gyrus (PoCG) was significantly high in the CSVD-W group. While in the CSVD-M group, the bilateral paracentral lobules (PL) revealed significantly elevated dALFF variability and low dALFF variability in the left CPL and right IPL compared with HCs. The CSVD-M group had high dALFF variability in the bilateral PL but low dALFF variability in the left middle temporal gyrus (MTG) and right PoCG compared with the CSVD-W group. The partial correlation analysis indicated that dALFF variability in the left MTG was positively associated with EM (r = 0.713, p = .002) in CSVD-W and CSVD-M groups. In the groups with CSVD-M and HC, altered dALFF variability in the bilateral PL was negatively correlated with EM (r = -0.560, p = .002). CONCLUSION: There were significant changes in sALFF and dALFF variability in CSVD patients. Abnormal spontaneous static and dynamic ALFFs may provide new insights into cognitive dysfunction in CSVD with MCI and may be valuable biomarkers for early diagnosis.

Intracranial cholesteatoma in the thalamus: Uncommon location and atypical imaging findings.

Intracranial cholesteatoma is an uncommon condition that can occur anywhere in the intracranial cavity, but its occurrence in the thalamus is exceedingly rare. We present a case of thalamic cholesteatoma with atypical imaging findings and review the previous literature to explore the pathophysiological basis of these findings. A 55-year-old male presented to the hospital with right upper limb weakness and right ear hearing loss for more than 2 years. Imaging studies of the brain were performed, revealing a mixed density mass in the left thalamic region with calcification at the margin. Magnetic resonance imaging revealed a mixed signal intensity on T1-weighted and T2-weighted images, diffusion limitation on diffusion-weighted images, and ring enhancement on enhanced T1-weighted images. The mass caused mild obstructive hydrocephalus due to compression of the 3 ventricles and midbrain aqueduct. Thalamic cholesteatoma is an uncommon and often misdiagnosed lesion due to its unusual location and imaging characteristics. The pathophysiological basis of the atypical imaging findings associated with intracranial cholesteatoma is not well understood but may be related to the keratinization of the cyst lining or the presence of cholesterol crystals. Thalamic cholesteatoma should be considered in the differential diagnosis of thalamic lesions, especially in cases with calcifications or cystic components. Further studies are needed to better understand the pathophysiology of intracranial cholesteatoma and its associated atypical imaging findings.

Performance, community structure, metabolic pathway, and mechanism in a three-dimensional electrocatalytic biofilter (3DEBF) for the degradation of multiple concentrations of clofibric acid (CA).

A three-dimensional electrocatalytic biofilter (3DEBF) was constructed to remove clofibric acid (CA). This study compared the effectiveness of 3DEBF and biological aerated filter (BAF) in the removal of refractory CA, examined the effects of influent CA concentrations (0.1, 0.3, 0.5, 0.7, and 1.0 mg/L) on microbial community, and proposed a possible 3DEBF degradation mechanism. Results indicated that the average removal efficiency of 3DEBF reached a peak (76.09%) at 0.7 mg/L, which was 14.43% higher than that of BAF. Based on the microbial community analysis, the significant enrichment of Rhodobacter, Mycobacterium, and Sphingopyxis in 3DEBF was associated with the effect of the CA concentration and the electric field. The degradation pathway indicated that xenobiotics biodegradation and metabolism, membrane transport and replication and repair related genes were upregulated in 3DEBAF. Moreover, CA degradation is based on a combination of adsorption, electrochemical oxidation, and biodegradation.

Hierarchical S-Scheme Heterostructure of CdIn2S4@UiO-66-NH2 toward Synchronously Boosting Photocatalytic Removal of Cr(VI) and Tetracycline.

Developing highly efficient photocatalysts toward synchronously removing heavy metals and organic pollutants is still a serious challenge. Herein, we depict hierarchical S-scheme heterostructured photocatalysts prepared via in situ anchoring UiO-66-NH2 nanoparticles onto the CdIn2S4 porous microsphere structures assembled with numerous nanosheets. In the mixed system of Cr(VI) and tetracycline (TC), the optimal photocatalyst (CIS@U66N-30) shows remarkable photocatalytic activities toward the synchronous removal of Cr(VI) (97.26%) and TC (close to 100% of) under visible-light irradiation for 60 min, being the best removal rates among those of the reported photocatalysts, and sustains the outstanding stability and reusability. Its reaction rate constants of Cr(VI) reduction and TC degradation are about 2.06 and 1.58 folds that in the single Cr(VI) and TC systems, respectively. The enhanced photocatalytic activities of CIS@U66N-30 mainly result from the following synergism: (1) its hierarchical structure offers abundant active sites, and the S-scheme migration mechanism of charge carriers in the heterostructure accelerates the separation and migration of the useful photoinduced electrons and holes with the high redox capability; (2) Cr(VI) and TC can serve as the electron scavenger for TC oxidation degradation and the hole and •OH scavenger for Cr(VI) reduction, respectively, further enhancing the separation and utilization efficiency of photoinduced electrons and holes. Besides, the possible TC degradation pathway and plausible S-scheme photocatalytic mechanism over CIS@U66N-30 for the concurrent elimination of Cr(VI) and TC are proposed.

A PARP1 PROTAC as a novel strategy against PARP inhibitor resistance via promotion of ferroptosis in p53-positive breast cancer.

Therapeutic targeting of the nuclear enzyme poly (ADP-ribose) polymerase 1 (PARP1) with PARP inhibitors (PARPis) in patients with a homologous recombination (HR)- deficient phenotype based on the mechanism of synthetic lethality has been shown tremendous success in cancer therapy. With the clinical use of various PARPis, emerging evidence has shown that some PARPis offer hope for breakthroughs in triple-negative breast cancer (TNBC) therapy, regardless of HR status. However, similar to other conventional cytotoxic drugs, PARPis are also subject to the intractable problem of drug resistance. Notably, acquired resistance to PARPis caused by point mutations in the PARP1 protein is hard to overcome with current strategies. To explore modalities to overcome resistance and identify patients who are most likely to benefit from PARP1-targeted therapy, we developed a proteolysis-targeted chimaera (PROTAC) to degrade mutant PARP1 in TNBC. Here, we investigated a PARP1 PROTAC termed "NN3″, which triggered ubiquitination and proteasome-mediated degradation of PARP1. Moreover, NN3 degraded PARP1 with resistance-related mutations. Interestingly, compared with other reported PARP1 degraders, NN3 exhibited a unique antitumor mechanism in p53-positive breast cancer cells that effectively promoted ferroptosis by downregulating the SLC7A11 pathway. Furthermore, NN3 showed potent activity and low toxicity in vivo. In conclusion, we propose PROTAC-mediated degradation of PARP1 as a novel strategy against mutation-related PARPi resistance and a paradigm for targeting breast cancer with functional p53 via ferroptosis induction.

Effectiveness of yoga therapy for migraine treatment: A meta-analysis of randomized controlled studies.

INTRODUCTION: Yoga therapy may have some potential in treating migraine, and thus this meta-analysis aims to explore the efficacy of yoga therapy for patients with migraine. METHODS: PubMed, EMbase, Web of science, EBSCO and Cochrane library databases have been systematically searched and we included the randomized controlled trials (RCTs) reporting the efficacy of yoga therapy for migraine patients. The outcomes included. RESULTS: This meta-analysis included six RCTs. The results revealed that compared with control group for migraine, yoga therapy was associated with remarkably decreased pain intensity (SMD = -1.21; 95% CI = -2.17 to -0.25; P = 0.01), headache frequency (SMD = -1.43; 95% CI = -2.23 to -0.64; P = 0.0004), headache duration (SMD = -1.03; 95% CI = -1.85 to -0.21; P = 0.01), HIT-6 score (SMD = -2.28; 95% CI = -3.81 to -0.75; P = 0.003) and MIDAS score (SMD = -0.52; 95% CI = -0.77 to -0.27; P < 0.0001). CONCLUSIONS: Yoga therapy may be effective to treat migraine patients, but it should be recommended with caution because of heterogeneity.

Aberrant Structure MRI in Parkinson's Disease and Comorbidity with Depression Based on Multinomial Tensor Regression Analysis.

BACKGROUND: Depression is a prominent and highly prevalent nonmotor feature in patients with Parkinson's disease (PD). The neural and pathophysiologic mechanisms of PD with depression (DPD) remain unclear. The current diagnosis of DPD largely depends on clinical evaluation. METHODS: We proposed a new family of multinomial tensor regressions that leveraged whole-brain structural magnetic resonance imaging (MRI) data to discriminate among 196 non-depressed PD (NDPD) patients, 84 DPD patients, 200 healthy controls (HC), and to assess the special brain microstructures in NDPD and DPD. The method of maximum likelihood estimation coupled with state-of-art gradient descent algorithms was used to predict the individual diagnosis of PD and the development of DPD in PD patients. RESULTS: The results reveal that the proposed efficient approach not only achieved a high prediction accuracy (0.94) with a multi-class AUC (0.98) for distinguishing between NDPD, DPD, and HC on the testing set but also located the most discriminative regions for NDPD and DPD, including cortical regions, the cerebellum, the brainstem, the bilateral basal ganglia, and the thalamus and limbic regions. CONCLUSIONS: The proposed imaging technique based on tensor regression performs well without any prior feature information, facilitates a deeper understanding into the abnormalities in DPD and PD, and plays an essential role in the statistical analysis of high-dimensional complex MRI imaging data to support the radiological diagnosis of comorbidity of depression with PD.

The anode is more beneficial to the advanced treatment of wastewater containing antibiotics by three-dimensional electro-biofilm reactor: Degradation, mechanism and optimization.

The three-dimensional electrode biological aerated filter (3DE-BAF) has the potential to overcome inherent limitations of conventional electrochemical and biofilm methods. Electrochemical means could enhance the performance and sustainability of biofilm technologies and stimulate the spread of new applications in (waste) water treatment. This paper describes the construction and performance of 3DE-BAF in the treatment of simulated wastewater represented by tetracycline (TC). This is followed by a discussion of electrode performance, the electron transport mechanism and the electrode's effect on the biological community of 3D-EBAF. Given the gap between experimental studies and practical applications, the enlarged anode 3DE-BAF named 3DEAE-BAF reactor was applied with good results to duck farm wastewater. This study could provide guidance as to developing new methods to construct a highly stable 3DE-BAF. The paper concludes that improved 3DE-BAF technology is promising for advanced treatment of livestock wastewater containing antibiotics.

Altered Patterns of Amplitude of Low-Frequency Fluctuations and Fractional Amplitude of Low-Frequency Fluctuations Between Amnestic and Vascular Mild Cognitive Impairment: An ALE-Based Comparative Meta-Analysis.

Background: Changes in the amplitude of low-frequency fluctuations (ALFF) and the fractional amplitude of low-frequency fluctuations (fALFF) have provided stronger evidence for the pathophysiology of cognitive impairment. Whether the altered patterns of ALFF and fALFF differ in amnestic cognitive impairment (aMCI) and vascular mild cognitive impairment (vMCI) is largely unknown. The purpose of this study was to explore the ALFF/fALFF changes in the two diseases and to further explore whether they contribute to the diagnosis and differentiation of these diseases. Methods: We searched PubMed, Ovid, and Web of Science databases for articles on studies using the ALFF/fALFF method in patients with aMCI and vMCI. Based on the activation likelihood estimation (ALE) method, connectivity modeling based on coordinate meta-analysis and functional meta-analysis was carried out. Results: Compared with healthy controls (HCs), patients with aMCI showed increased ALFF/fALFF in the bilateral parahippocampal gyrus/hippocampus (PHG/HG), right amygdala, right cerebellum anterior lobe (CAL), left middle temporal gyrus (MTG), left cerebrum temporal lobe sub-gyral, left inferior temporal gyrus (ITG), and left cerebrum limbic lobe uncus. Meanwhile, decreased ALFF/fALFF values were also revealed in the bilateral precuneus (PCUN), bilateral cuneus (CUN), and bilateral posterior cingulate (PC) in patients with aMCI. Compared with HCs, patients with vMCI predominantly showed decreased ALFF/fALFF in the bilateral CUN, left PCUN, left PC, and right cingulate gyrus (CG). Conclusions: The present findings suggest that ALFF and fALFF displayed remarkable altered patterns between aMCI and vMCI when compared with HCs. Thus, the findings of this study may serve as a reliable tool for distinguishing aMCI from vMCI, which may help understand the pathophysiological mechanisms of these diseases.

Aberrant functional connectivity and activity in Parkinson's disease and comorbidity with depression based on radiomic analysis.

INTRODUCTION: The current diagnosis of Parkinson's disease (PD) comorbidity with depression (DPD) largely depends on clinical evaluation. However, the modality may tend to lack precision in detecting PD with depression. A radiomic approach that combines functional connectivity and activity with clinical scores has the potential to achieve accurate and differential diagnosis between PD and DPD. METHODS: In this study, we aimed to employ the radiomic approach to extract large-scale features of functional connectivity and activity for differentiating among DPD, PD with no depression (NDPD), and healthy controls (HC). We extracted 6,557 features of five types from all subjects including clinical characteristics, resting-state functional connectivity (RSFC), amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC). Lasso, random forest, and support vector machine (SVM) were implemented for feature selection and dimension reduction based on the training sets, and the prediction performance for different methods in the testing sets was compared. RESULTS: The results showed that nineteen features were selected for the group of DPD versus HC, 34 features were selected for the group of NDPD versus HC, and 17 features were retained for the group of DPD versus NDPD. In the testing sets, Lasso prediction achieved the accuracies of 0.95, 0.96, and 0.85 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Random forest achieved the accuracies of 0.90, 0.82, and 0.90 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively, while SVM yielded the accuracies of 1, 0.86 and 0.65 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. CONCLUSIONS: By identifying aberrant functional connectivity and activity as potential biomarkers, the radiomic approach facilitates a deeper understanding and provides new insights into the pathophysiology of DPD to support the clinical diagnosis with high prediction accuracy.

Bayesian variable selection in logistic regression with application to whole-brain functional connectivity analysis for Parkinson's disease.

Parkinson's disease is a progressive, chronic, and neurodegenerative disorder that is primarily diagnosed by clinical examinations and magnetic resonance imaging (MRI). In this paper, we propose a Bayesian model to predict Parkinson's disease employing a functional MRI (fMRI) based radiomics approach. We consider a spike and slab prior for variable selection in high-dimensional logistic regression models, and present an approximate Gibbs sampler by replacing a logistic distribution with a t-distribution. Under mild conditions, we establish model selection consistency of the induced posterior and illustrate the performance of the proposed method outperforms existing state-of-the-art methods through simulation studies. In fMRI analysis, 6216 whole-brain functional connectivity features are extracted for 50 healthy controls along with 70 Parkinson's disease patients. We apply our method to the resulting dataset and further show its benefits with a higher average prediction accuracy of 0.83 compared to other contenders based on 10 random splits. The model fitting procedure also reveals the most discriminative brain regions for Parkinson's disease. These findings demonstrate that the proposed Bayesian variable selection method has the potential to support radiological diagnosis for patients with Parkinson's disease.

Altered Patterns of the Fractional Amplitude of Low-Frequency Fluctuation in Drug-Naive First-Episode Unipolar and Bipolar Depression.

Background: An early and correct diagnosis is crucial for treatment of unipolar depression (UD) and bipolar disorder (BD). The fractional amplitude of low-frequency fluctuations (fALFFs) has been widely used in the study of neuropsychiatric diseases, as it can detect spontaneous brain activities. This study was conducted to survey changes of fALFF within various frequency bands of the UD and BD patients, as well as to explore the effects on changes in fALFF on cognitive function. Methods: In total, 58 drug-naive first-episode patients, including 32 UD and 26 BD, were enrolled in the study. The fALFF values were calculated under slow-5 band (0.01-0.027 Hz) and slow-4 band (0.027-0.073 Hz) among UD patients, BD patients, and healthy control (HC). Additionally, we conducted correlation analyses to examine the association between altered fALFF values and cognitive function. Results: Under the slow-5 band, compared to the HC group, the UD group showed increased fALFF values in the right cerebellum posterior lobe, whereas the BD group showed increased fALFF values in the left middle temporal gyrus (MTG). Under the slow-4 band, in comparison to HC, the UD group showed increased fALFF values in the left superior temporal gyrus, whereas the right inferior parietal lobule (IPL) and BD group showed increased fALFF values in the bilateral postcentral gyrus. Notably, compared to BD, the UD group showed increased fALFF values in the right IPL under the slow-4 band. Furthermore, altered fALFF values in the left MTG and the right IPL were significantly positively correlated with Verbal Fluency Test scores. Conclusions: This current study indicated that there were changes in brain activities in the early UD and BD groups, and changes were related to executive function. The fALFF values can serve as potential biomarker to diagnose and differentiate UD and BD patients.

A Radiomics Approach to Predicting Parkinson's Disease by Incorporating Whole-Brain Functional Activity and Gray Matter Structure.

Parkinson's disease (PD) is a progressive, chronic, and neurodegenerative disorder that is primarily diagnosed by clinical examinations and magnetic resonance imaging (MRI). In this study, we proposed a machine learning based radiomics method to predict PD. Fifty healthy controls (HC) along with 70 PD patients underwent resting-state magnetic resonance imaging (rs-fMRI). For all subjects, we extracted five types of 6664 features, including mean amplitude of low-frequency fluctuation (mALFF), mean regional homogeneity (mReHo), resting-state functional connectivity (RSFC), voxel-mirrored homotopic connectivity (VMHC) and gray matter (GM) volume. After conducting dimension reduction utilizing Least absolute shrinkage and selection operator (LASSO), fifty-three radiomic features including 46 RSFCs, 1 mALFF, 3 mReHos, 1 VMHC, 2 GM volumes and 1 clinical factor were retained. The selected features also indicated the most discriminative regions for PD. We further conducted model fitting procedure for classifying subjects in the training set employing random forest and support volume machine (SVM) to evaluate the performance of the two methods. After cross-validation, both methods achieved 100% accuracy and area under curve (AUC) for distinguishing between PD and HC in the training set. In the testing set, SVM performed better than random forest with the accuracy, true positive rate (TPR) and AUC being 85%, 1 and 0.97, respectively. These findings demonstrate the radiomics technique has the potential to support radiological diagnosis and to achieve high classification accuracy for clinical diagnostic systems for patients with PD.