OBJECTIVETo identify the mutation of human androgen receptor gene (AR) in a patient with complete androgen insensitivity syndrome (CAIS).

METHODSDNA sequences of 8 exons and their exon/intron boundaries of the AR gene in the patient were amplified by PCR and directly sequenced.

RESULTSDNA sequencing revealed a nonsense mutation in exon 1, resulting in a change of codon 441 GAA (glutamic acid) to a stop codon (TAA).

CONCLUSIONA novel mutation Glu441stop (GAA to TAA) of the androgen receptor gene leading to complete androgen insensitivity syndrome was identified in this study in a Chinese patient. It may help us further understanding the pathogenesis of CAIS.

Adult ; Androgen-Insensitivity Syndrome ; genetics ; Base Sequence ; Humans ; Male ; Molecular Sequence Data ; Mutation ; Polymerase Chain Reaction ; methods ; Receptors, Androgen ; genetics ; Sequence Analysis, DNA ; methods

Objective:To evaluate the values of 18F-PI-2620 PET/CT brain imaging with SUV ratio (SUVR) in the assessment of tau protein deposition in the brain of patients with different cognitive disorders and its correlation with cognition. Methods:This was a cross-sectional study. From December 2019 to November 2022, a total of 67 subjects including 54 patients with Alzheimer′s disease (AD; 21 males, 33 females, age (68.6±7.8) years), 7 patients with mild cognitive impairment (MCI; 1 male, 6 females, age (63.1±11.2) years) and 6 healthy controls (HC; 4 males, 2 females, age (69.0±5.8) years) were enrolled retrospectively in Renji Hospital. All participants were examined by 18F-PI-2620 PET/CT. SUVRs of brain regions were obtained, including frontal lobe, temporal lobe, occipital lobe, parietal lobe, insular lobe, whole brain, as well as 10 independent brain ROIs (amygdala, orbitofrontal cortex, cingulate gyrus, superior occipital gyrus, superior parietal gyrus, inferior angular gyrus, precuneus, inferior temporal gyrus, entorhinal cortex and parahippocampal gyrus), with inferior cerebellum cortex as the reference region. All participants were estimated by cognitive scales(mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA)). One-way analysis of variance and the least significant difference t test were used to compare the differences of SUVR in each brain region among HC, MCI and AD groups. ROC curve analysis was used to determine the optimal cut-off values of SUVR in each brain region for the differential diagnosis of AD-MCI and AD-HC. Pearson correlation analysis was employed to examine the correlations of SUVR with cognitive scale scores. Results:The SUVR of whole brain was 1.40±0.31 in AD group, 1.08±0.19 in MCI group, and 1.01±0.12 in HC group. SUVR analysis in the whole brain and each brain region could distinguish AD from HC, AD from MCI ( F values: 1.76-10.09, t values: 2.98-7.47, all P<0.05), but could not distinguish HC from MCI ( t values: 0.17-1.53, all P>0.05). ROC curve analysis showed that the best cut-off value of SUVR was 1.18 for whole brain (AUC=0.89), 1.13 for amygdala (AUC=0.94) and 1.26 for parahippocampal gyrus (AUC=0.94) for differential diagnosis of AD and HC, which was 1.06 for whole brain (AUC=0.82), 1.18 for amygdala (AUC=0.88) and 1.28 (AUC=0.88) for infratemporal gyrus to differential diagnosis of AD and MCI. SUVRs of the whole brain, frontal, occipital, parietal, temporal and insula were significantly negatively correlated with MMSE and MoCA cognitive scale scores ( r values: from -0.64 to -0.40, all P<0.05). Conclusions:SUVR quantitative analysis in 18F-PI-2620 PET imaging can assist the differential diagnosis of AD and HC, AD and MCI. The SUVRs of whole brain and five lobes show negative correlations with MMSE and MoCA scores.

Objective:To assess the diagnostic efficiency of 18F-FDG PET for Alzheimer′s disease (AD) in patients with memory impairment. Methods:A retrospective analysis was conducted on 96 patients (40 males, 56 females, age: 69.0(62.8, 74.0) years) initially diagnosed with memory impairment in Renji Hospital, School of Medicine, Shanghai Jiao Tong University between August 2019 and September 2023. The amyloid-tau-neurodegeneration (ATN) criteria, based on 18F-AV45+ 18F-PI-2620 PET/CT+ MRI imaging results, were used as the diagnostic standard for AD. Visual analysis (temporoparietal or posterior cingulate cortex (PCC) hypometabolism) and semi-quantitative analysis methods (PET-SCORE and NeuroQ software analysis (SUV ratio, SUVR)) were applied to evaluate the diagnostic efficiency of 18F-FDG PET imaging for AD. Diagnostic efficiencies of visual assessment and semi-quantitative parameters were compared by χ2 test. Additionally, Pearson correlation analysis was performed to examine the relationship between results of PET-SCORE and cognitive scales. Results:Of the 96 patients initially diagnosed with memory impairment, 61 were clinically diagnosed with AD, while 35 were non-AD patients. Visual assessment of temporoparietal hypometabolism showed the highest sensitivity (91.80%, 56/61), which was significantly different from the sensitivities of PET-SCORE (40.98%(25/61); χ2=29.03, P<0.001) and visual assessment of PCC hypometabolism (77.05%(47/61); χ2=5.82, P=0.016). While semi-quantitative assessment using PET-SCORE demonstrated the highest specificity (100%, 35/35), which was significantly different from the specificities of visual assessment methods (temporoparietal hypometabolism: 17.14%(6/35), χ2=27.03, P<0.001; PCC hypometabolism: 54.29%(19/35), χ2=14.06, P<0.001). PET-SCORE exhibited statistically significant correlations with Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Activities of Daily Living (ADL) scores ( r values: -0.38, -0.36, 0.31, all P<0.01). Conclusions:Among patients initially diagnosed with memory impairment, visual assessment in 18F-FDG PET imaging analysis demonstrates higher sensitivity, while semi-quantitative analysis using PET-SCORE exhibits higher specificity. PET-SCORE shows statistically significant correlation with the severity of cognitive decline.

To establish and analyze the HPLC specific chromatograms of Xingnaojing injection manufactured by different factories. The separation was performed on a Thermo BDS Hypersil C₁₈ column (4.6 mm×250 mm, 5 μm), with the mobile phase consisting of acetonitrile-0.02% formic acid aqueous solution for gradient elution. The flow rate was 1.0 mL•min⁻¹, and the column temperature was 35 ℃. The detection wavelength was set at 254 nm, and the sample size was 20 μL. Eleven chromatographic peaks were identified as characteristic peaks of HPLC specific chromatograms of Xingnaojing injection, after analyzing 29 batches of Xingnaojing injection samples. Compared with the reference substances, seven of them were identified as eucarvone, camphor, curcumenone, curcumenol, curdione, curzerenone and germacrone, respectively. HPLC specific chromatograms of Xingnaojing injection manufactured by three factories could be easily classified into three categories after investigation with computer-aided similarity evaluation system combined with principal component analysis. The established HPLC specific chromatograms provide a basis for scientific evaluation and effective control of the quality of Xingnaojing injection.