Objective To observe the change patterns of functional connectivity(FC)of basal forebrain subregions in Alzheimer disease(AD)patients.Methods Totally 42 AD patients(AD group)and 41 healthy controls(HC group)were retrospectively enrolled.Seed-based FC analysis was performed on basal forebrain subregions(Ch123 and Ch4)based on their resting-state functional MRI data and compared between groups.Results Compared with HC group,FC between left Ch4 and left hippocampus as well as left posterior cingulate gyrus significantly decreased,but between right Ch4 and right precentral gyrus,as well as right postcentral gyrus increased in AD group(GRF correction,voxel level P＜0.001,cluster level P＜0.05).Meanwhile,FC between left Ch123 and left superior temporal gyrus,left insula,between right Ch123 and left superior temporal gyrus,left temporal pole significantly increased,while between right Ch123 and right orbital superior frontal gyrus,right orbital inferior frontal gyrus significantly decreased in AD group(GRF correction,voxel level P＜0.001,cluster level P＜0.05).Conclusion FC changes of different basal forebrain subregions in AD patients were various.

Objective To explore the value of 18F-flortaucipir tau PET combined with APOE ε4 genotype status for diagnosing mild cognitive impairment(MCI).Methods A total of 213 MCI patients(MCI group)and 402 healthy controls(HC group)were selected from Alzheimer's disease neuroimaging initiative(ADNI)database.The neuropsychological information,APOE ε4 gene carrier status,tau PET and high-resolution structural MRI data were recorded.The random forest algorithm was used to screen the most informative brain regions of tau PET for diagnosing MCI,and the efficacy of tau PET for distinguishing MCI with or without APOE ε4 gene and HC were compared.Results Amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus in turn were the important brain regions of tau PET for diagnosing MCI.The accuracy and the area under the curve(AUC)of tau PET standardized uptake value ratio(SUVR)model for identifying MCI with APOE ε4 gene and HC was 86.68％and 0.784,respectively,both higher than those for identifying MCI and HC,as well as MCI without APOE e4 gene and HC(with accuracy of 70.57％and 75.05％,and AUC of 0.711 and 0.609).Conclusion 18F-flortaucipir tau PET SUVR model established based on amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus could be used to diagnosing MCI.Combining with APOE ε4 gene could further improve its efficacy.

Objective To observe the functional connectivity and glucose metabolism of insular subregions in behavior variant of frontotemporal dementia(bvFTD)patients,also their correlations with cognitive function.Methods Thirty-eight bvFTD patients(bvFTD group)and 44 healthy individuals(control group)were retrospectively enrolled.The average time series signals of insular subregions were extracted as seed points based on functional MRI(fMRI)and 18F-FDG PET,then whole brain functional connectivity map was obtained.Meanwhile,the pons was selected as the reference brain region,and the standard uptake value ratio(SUVR)of insular subregions were calculated.The above parameters were compared between groups,and the correlations of SUVR of insular subregions with clinical cognitive function scale scores in bvFTD group were analyzed.Results Compared with control group,the functional connections between all insular subregions and bilateral frontal lobe,temporal lobe,anterior cingulate gyrus,anterior cingulate gyrus and middle cingulate gyrus,as well as between some subregions and bilateral parietal and occipital lobes were weakened in bvFTD group(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05).SUVR of all insular subregions significantly decreased(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05),which in right ventral agranular insula(vIa),dorsal agranular insula(dIa),dorsal dysgranular insula(dId)and left dorsal agranular insula(dIa)were negatively correlated with frontal behavioral inventory(FBI)score in bvFTD group(r=-0.452--0.330,all P＜0.05).Conclusion In bvFTD patients,the functional connectivity and glucose metabolism of insular subregions changed,and SUVR of right vIa,dIa,dId and left dIa were negatively correlated with FBI score.

Objective To observe the change patterns of functional connectivity(FC)of basal forebrain subregions in Alzheimer disease(AD)patients.Methods Totally 42 AD patients(AD group)and 41 healthy controls(HC group)were retrospectively enrolled.Seed-based FC analysis was performed on basal forebrain subregions(Ch123 and Ch4)based on their resting-state functional MRI data and compared between groups.Results Compared with HC group,FC between left Ch4 and left hippocampus as well as left posterior cingulate gyrus significantly decreased,but between right Ch4 and right precentral gyrus,as well as right postcentral gyrus increased in AD group(GRF correction,voxel level P＜0.001,cluster level P＜0.05).Meanwhile,FC between left Ch123 and left superior temporal gyrus,left insula,between right Ch123 and left superior temporal gyrus,left temporal pole significantly increased,while between right Ch123 and right orbital superior frontal gyrus,right orbital inferior frontal gyrus significantly decreased in AD group(GRF correction,voxel level P＜0.001,cluster level P＜0.05).Conclusion FC changes of different basal forebrain subregions in AD patients were various.

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

BACKGROUND: Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and its dysregulation can lead to glycometabolic disorders. This study aimed to identify hub biomarkers of these disorders to provide a theoretical foundation for enhancing diagnosis and treatment. METHODS: Gene expression profiles from liver tissues of three well-characterized gluconeogenesis mouse models were analyzed to identify commonly differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA), machine learning techniques, and diagnostic tests on transcriptome data from publicly available datasets of type 2 diabetes mellitus (T2DM) patients were employed to assess the clinical relevance of these DEGs. Subsequently, we identified hub biomarkers associated with gluconeogenesis-related glycometabolic disorders, investigated potential correlations with immune cell types, and validated expression using quantitative polymerase chain reaction in the mouse models. RESULTS: Only a few common DEGs were observed in gluconeogenesis-related glycometabolic disorders across different contributing factors. However, these DEGs were consistently associated with cytokine regulation and oxidative stress (OS). Enrichment analysis highlighted significant alterations in terms related to cytokines and OS. Importantly, osteomodulin ( OMD ), apolipoprotein A4 ( APOA4 ), and insulin like growth factor binding protein 6 ( IGFBP6 ) were identified with potential clinical significance in T2DM patients. These genes demonstrated robust diagnostic performance in T2DM cohorts and were positively correlated with resting dendritic cells. CONCLUSIONS Gluconeogenesis-related glycometabolic disorders exhibit considerable heterogeneity, yet changes in cytokine regulation and OS are universally present. OMD , APOA4 , and IGFBP6  may serve as hub biomarkers for gluconeogenesis-related glycometabolic disorders.
Machine Learning ; Humans ; Computational Biology/methods* ; Biomarkers/metabolism* ; Diabetes Mellitus, Type 2/genetics* ; Animals ; Mice ; Gluconeogenesis/physiology* ; Gene Expression Profiling ; Transcriptome/genetics* ; Gene Regulatory Networks/genetics* ; Clinical Relevance

Objective To explore the value of 18F-flortaucipir tau PET combined with APOE ε4 genotype status for diagnosing mild cognitive impairment(MCI).Methods A total of 213 MCI patients(MCI group)and 402 healthy controls(HC group)were selected from Alzheimer's disease neuroimaging initiative(ADNI)database.The neuropsychological information,APOE ε4 gene carrier status,tau PET and high-resolution structural MRI data were recorded.The random forest algorithm was used to screen the most informative brain regions of tau PET for diagnosing MCI,and the efficacy of tau PET for distinguishing MCI with or without APOE ε4 gene and HC were compared.Results Amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus in turn were the important brain regions of tau PET for diagnosing MCI.The accuracy and the area under the curve(AUC)of tau PET standardized uptake value ratio(SUVR)model for identifying MCI with APOE ε4 gene and HC was 86.68％and 0.784,respectively,both higher than those for identifying MCI and HC,as well as MCI without APOE e4 gene and HC(with accuracy of 70.57％and 75.05％,and AUC of 0.711 and 0.609).Conclusion 18F-flortaucipir tau PET SUVR model established based on amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus could be used to diagnosing MCI.Combining with APOE ε4 gene could further improve its efficacy.

Objective To observe the functional connectivity and glucose metabolism of insular subregions in behavior variant of frontotemporal dementia(bvFTD)patients,also their correlations with cognitive function.Methods Thirty-eight bvFTD patients(bvFTD group)and 44 healthy individuals(control group)were retrospectively enrolled.The average time series signals of insular subregions were extracted as seed points based on functional MRI(fMRI)and 18F-FDG PET,then whole brain functional connectivity map was obtained.Meanwhile,the pons was selected as the reference brain region,and the standard uptake value ratio(SUVR)of insular subregions were calculated.The above parameters were compared between groups,and the correlations of SUVR of insular subregions with clinical cognitive function scale scores in bvFTD group were analyzed.Results Compared with control group,the functional connections between all insular subregions and bilateral frontal lobe,temporal lobe,anterior cingulate gyrus,anterior cingulate gyrus and middle cingulate gyrus,as well as between some subregions and bilateral parietal and occipital lobes were weakened in bvFTD group(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05).SUVR of all insular subregions significantly decreased(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05),which in right ventral agranular insula(vIa),dorsal agranular insula(dIa),dorsal dysgranular insula(dId)and left dorsal agranular insula(dIa)were negatively correlated with frontal behavioral inventory(FBI)score in bvFTD group(r=-0.452--0.330,all P＜0.05).Conclusion In bvFTD patients,the functional connectivity and glucose metabolism of insular subregions changed,and SUVR of right vIa,dIa,dId and left dIa were negatively correlated with FBI score.

Objective To investigate the feasibility and accuracy of an ultrasound-based transfer learning artificial intelligence model in predicting the malignancy probability of partially cystic thyroid nodules(PCTN).Methods A retrospective analysis was conducted on 246 patients with PCTN who had definitive pathological results and were admitted to Weihai Municipal Hospital,Cheeloo College of Medicine,Shandong University from January 2021 to December 2023.Patients were randomly divided into training and test cohorts at a ratio of 7:3.Ultrasonic image features of PCTN were evaluated,and independent risk factors were identified using multivariate logistic regression analysis,with the area under the curve(AUC)subsequently calculated.Additionally,five different pre-trained models-Inception_v3,EfficientNet,VGG19,ResNet50,and DenseNet121-were selected for transfer learning after data preprocessing using the PyTorch framework in Python.The AUC values of these models were calculated and compared.Results Solid portion greater than 50%,eccentric acute angle,ill-defined margin,spiculated or microlobulated margin,rim calcification,and microcalcification exhibited statistically significant differences(P<0.05)in distinguishing between benign and malignant PCTN.The AUC value derived from these independent risk factors was 0.843.Furthermore,among the five transfer learning models evaluated,the ResNet50 model demonstrated the highest diagnostic efficiency,achieving an AUC value of 0.903 2.Conclusion The ultrasound-based transfer learning artificial intelligence model demonstrated superior performance compared to traditional ultrasound image evaluation methods,enabling accurate prediction of the nature of PCTN and thereby reducing unnecessary ultrasound-guided fine needle biopsies.