Value of conventional ultrasound and shear­wave elastography in the assessment of mesenteric lymphadenitis in a paediatric population.

The present retrospective study was designed to explore the value of conventional ultrasound (US) and Virtual Touch Tissue Imaging and Quantification (VTIQ) in the assessment of mesenteric lymphadenitis (ML) in a paediatric population. A total of 103 patients with ML and 60 healthy paediatric patients were examined. VTIQ was performed to assess mesenteric lymph node (MLN) stiffness via shear-wave velocity (SWV). Univariate and multivariate logistic regression analyses were conducted to reveal independent variables for the identification of ML. The diagnostic performance of US, and US combined with VTIQ, were compared. All the quantitative VTIQ parameters (including the SWVMean, SWVMax and SWVMin) were significantly greater for MLNs in the control group than for MLNs in the ML group (all P<0.001). The SWV values in the control group were nearly 2-fold greater than that in the ML group. According to the multivariate logistic regression analysis, the longest diameter [odds ratio (OR)=6.042; P=0.046] was revealed to be the strongest independent predictor for ML, followed by the CRP level (OR=2.310; P<0.001) and the SWVMean (OR=0.106; P<0.001). According to the receiver operating characteristic analysis, the area under the curve (AUC) for US combined with VTIQ was 0.890 (95% CI: 0.831-0.949) with a greater sensitivity of 91.26% and a greater specificity of 86.67% than that for US alone (AUC: 0.798; 95% CI: 0.724-0.872; sensitivity: 79.61%; specificity: 80.00%). A significant negative correlation between increased VTIQ parameters and ML was observed. Utilizing VTIQ to assess MLN stiffness offers a non-invasive, convenient, reliable and reproducible approach for identifying mesenteric lymphadenopathy.

Clinical characteristics of cerebral amyloid angiopathy and risk factors of cerebral amyloid angiopathy related intracerebral hemorrhage.

OBJECTIVES: There is limited understanding of the differences between cerebral amyloid angiopathy (CAA) with and without intracerebral hemorrhage (ICH). This article aimed to describe the characteristics of CAA and identify the risk factors of CAA-ICH in a multicenter cohort. METHODS: Patients consecutively enrolled in the national multicenter prospective Cerebral Small Vessel Disease Cohort Study who met the Boston diagnostic criteria for CAA or CAA-related inflammation were included in this study. The demographic characteristics and clinical data were collected. The clinical and radiographic differences between CAA with and without ICH were compared to identify the risk factors for CAA-ICH. RESULTS: A total of 219 CAA patients were included, with an average age of 67.12 ± 9.93. Of all patients, 26.0% were CAA with ICH. Univariate analysis showed that CAA-ICH is associated with carrying more APOE ε2 allele, less lobar cerebral microbleeds (CMBs), cortical superficial siderosis (cSS), lower Fazekas scale, a tendency of gait disorder, and acute onset (P < 0.05). The generalized linear mixed model yielded statistically significant associations between CAA with ICH and carrying the APOE ε2 allele, cSS, the lower number of lobar CMBs, and the lower Fazekas scale (P < 0.05). CONCLUSION: It is meaningful to classify CAA with and without ICH, as there may be different mechanisms between the two. CAA with ICH has a susceptibility to carrying APOE ε2, cSS, and a relatively small number of CMBs. Fewer CMBs do not mean lower susceptibility to ICH in CAA. Larger prospective cohort studies are necessary to further clarify these conclusions.

Dynamic Mechanism of Cerebral Venous Disruption: Longitudinal Evidence From a Community-Based Cohort.

BACKGROUND: This study aims to investigate the temporal and spatial patterns of structural brain injury related to deep medullary veins (DMVs) damage. METHODS AND RESULTS: This is a longitudinal analysis of the population-based Shunyi cohort study. Baseline DMVs numbers were identified on susceptibility-weighted imaging. We assessed vertex-wise cortex maps and diffusion maps at both baseline and follow-up using FSL software and the longitudinal FreeSurfer analysis suite. We performed statistical analysis of global measurements and voxel/vertex-wise analysis to explore the relationship between DMVs number and brain structural measurements. A total of 977 participants were included in the baseline, of whom 544 completed the follow-up magnetic resonance imaging (age 54.97±7.83 years, 32% men, mean interval 5.56±0.47 years). A lower number of DMVs was associated with a faster disruption of white matter microstructural integrity, presented by increased mean diffusivity and radial diffusion (ß=0.0001 and SE=0.0001 for both, P=0.04 and 0.03, respectively), in extensive deep white matter (threshold-free cluster enhancement P<0.05, adjusted for age and sex). Of particular interest, we found a bidirectional trend association between DMVs number and change in brain volumes. Specifically, participants with mild DMVs disruption showed greater cortical enlargement, whereas those with severe disruption exhibited more significant brain atrophy, primarily involving clusters in the frontal and parietal lobes (multiple comparison corrected P<0.05, adjusted for age, sex, and total intracranial volume). CONCLUSIONS: Our findings posed the dynamic pattern of brain parenchymal lesions related to DMVs injury, shedding light on the interactions and chronological roles of various pathological mechanisms.

Rifampicin synergizes the toxicity of insecticides against the green peach aphid, Myzus persicae.

Myzus persicae is an important pest that has developed resistance to nearly all currently used insecticidal products. The employment of insecticide synergists is one of the effective strategies that need to be developed for the management of this resistance. Our study showed that treatment with a combination of the antibiotic, rifampicin, with imidacloprid, cyantraniliprole, or clothianidin significantly increased their toxicities against M. persicae, by 2.72, 3.59, and 2.41 folds, respectively. Rifampicin treatment led to a noteworthy reduction in the activities of multifunctional oxidases (by 32.64%) and esterases (by 23.80%), along with a decrease in the expression of the CYP6CY3 gene (by 58.57%) in M. persicae. It also negatively impacted the fitness of the aphids, including weight, life span, number of offspring, and elongation of developmental duration. In addition, bioassays showed that the combination of rifampicin and a detoxification enzyme inhibitor, piperonyl butoxide, or dsRNA of CYP6CY3 further significantly improved the toxicity of imidacloprid against M. persicae, by 6.19- and 7.55-fold, respectively. The present study suggests that development of active ingredients such as rifampicin as candidate synergists, show promise to overcome metabolic resistance to insecticides in aphids.

NOTCH localizes to mitochondria through the TBC1D15-FIS1 interaction and is stabilized via blockade of E3 ligase and CDK8 recruitment to reprogram tumor-initiating cells.

The P53-destabilizing TBC1D15-NOTCH protein interaction promotes self-renewal of tumor-initiating stem-like cells (TICs); however, the mechanisms governing the regulation of this pathway have not been fully elucidated. Here, we show that TBC1D15 stabilizes NOTCH and c-JUN through blockade of E3 ligase and CDK8 recruitment to phosphodegron sequences. Chromatin immunoprecipitation (ChIP-seq) analysis was performed to determine whether TBC1D15-dependent NOTCH1 binding occurs in TICs or non-TICs. The TIC population was isolated to evaluate TBC1D15-dependent NOTCH1 stabilization mechanisms. The tumor incidence in hepatocyte-specific triple knockout (Alb::CreERT2;Tbc1d15Flox/Flox;Notch1Flox/Flox;Notch2Flox/Flox;HCV-NS5A) Transgenic (Tg) mice and wild-type mice was compared after being fed an alcohol-containing Western diet (WD) for 12 months. The NOTCH1-TBC1D15-FIS1 interaction resulted in recruitment of mitochondria to the perinuclear region. TBC1D15 bound to full-length NUMB and to NUMB isoform 5, which lacks three Ser phosphorylation sites, and relocalized NUMB5 to mitochondria. TBC1D15 binding to NOTCH1 blocked CDK8- and CDK19-mediated phosphorylation of the NOTCH1 PEST phosphodegron to block FBW7 recruitment to Thr-2512 of NOTCH1. ChIP-seq analysis revealed that TBC1D15 and NOTCH1 regulated the expression of genes involved in mitochondrial metabolism-related pathways required for the maintenance of TICs. TBC1D15 inhibited CDK8-mediated phosphorylation to stabilize NOTCH1 and protect it from degradation The NUMB-binding oncoprotein TBC1D15 rescued NOTCH1 from NUMB-mediated ubiquitin-dependent degradation and recruited NOTCH1 to the mitochondrial outer membrane for the generation and expansion of liver TICs. A NOTCH-TBC1D15 inhibitor was found to inhibit NOTCH-dependent pathways and exhibited potent therapeutic effects in PDX mouse models. This unique targeting of the NOTCH-TBC1D15 interaction not only normalized the perinuclear localization of mitochondria but also promoted potent cytotoxic effects against TICs to eradicate patient-derived xenografts through NOTCH-dependent pathways.

Association of Rare NOTCH3 Variants With Prevalent and Incident Stroke and Dementia in the General Population.

BACKGROUND: It is uncertain whether rare NOTCH3 variants are associated with stroke and dementia in the general population and whether they lead to alterations in cognitive function. This study aims to determine the associations of rare NOTCH3 variants with prevalent and incident stroke and dementia, as well as cognitive function changes. METHODS AND RESULTS: In the prospective community-based Shunyi Study, a total of 1007 participants were included in the baseline analysis. For the follow-up analysis, 1007 participants were included in the stroke analysis, and 870 participants in the dementia analysis. All participants underwent baseline brain magnetic resonance imaging, carotid ultrasound, and whole exome sequencing. Rare NOTCH3 variants were defined as variants with minor allele frequency <1%. A total of 137 rare NOTCH3 carriers were enrolled in the baseline study. At baseline, rare NOTCH3 variant carriers had higher rates of stroke (8.8% versus 5.6%) and dementia (2.9% versus 0.8%) compared with noncarriers. After adjustment for associated risk factors, the epidermal growth factor-like repeats (EGFr)-involving rare NOTCH3 variants were associated with a higher risk of prevalent stroke (odds ratio [OR], 2.697 [95% CI, 1.266-5.745]; P=0.040) and dementia (OR, 8.498 [95% CI, 1.727-41.812]; P=0.032). After 5 years of follow-up, we did not find that the rare NOTCH3 variants increased the risk of incident stroke and dementia. There was no statistical difference in the change in longitudinal cognitive scale scores. CONCLUSIONS: Rare NOTCH3 EGFr-involving variants are genetic risk factors for stroke and dementia in the general Chinese population.

Single-Molecule Protein Analysis by Centrifugal Droplet Immuno-PCR with Magnetic Nanoparticles.

Detecting proteins in ultralow concentrations in complex media is important for many applications but often relies on complicated techniques. Herein, a single-molecule protein analyzer with the potential for high-throughput applications is reported. Gold-coated magnetic nanoparticles with DNA-labeled antibodies were used for target recognition and separation. The immunocomplex was loaded into microdroplets generated with centrifugation. Immuno-PCR amplification of the DNA enabled the quantification of proteins at the level of single molecules. As an example, ultrasensitive detection of α-synuclein, a biomarker for neurodegenerative diseases, is achieved. The limit of detection was determined to be ∼50 aM in buffer and ∼170 aM in serum. The method exhibited high specificity and could be used to analyze post-translational modifications such as protein phosphorylation. This study will inspire wider studies on single-molecule protein detection, especially in disease diagnostics, biomarker discovery, and drug development.

Classification of breast lesions in ultrasound images using deep convolutional neural networks: transfer learning versus automatic architecture design.

Deep convolutional neural networks (DCNNs) have demonstrated promising performance in classifying breast lesions in 2D ultrasound (US) images. Exiting approaches typically use pre-trained models based on architectures designed for natural images with transfer learning. Fewer attempts have been made to design customized architectures specifically for this purpose. This paper presents a comprehensive evaluation on transfer learning based solutions and automatically designed networks, analyzing the accuracy and robustness of different recognition models in three folds. First, we develop six different DCNN models (BNet, GNet, SqNet, DsNet, RsNet, IncReNet) based on transfer learning. Second, we adapt the Bayesian optimization method to optimize a CNN network (BONet) for classifying breast lesions. A retrospective dataset of 3034 US images collected from various hospitals is then used for evaluation. Extensive tests show that the BONet outperforms other models, exhibiting higher accuracy (83.33%), lower generalization gap (1.85%), shorter training time (66 min), and less model complexity (approximately 0.5 million weight parameters). We also compare the diagnostic performance of all models against that by three experienced radiologists. Finally, we explore the use of saliency maps to explain the classification decisions made by different models. Our investigation shows that saliency maps can assist in comprehending the classification decisions.

Current status and value of testing antiphospholipid antibody in patients with acute ischemic stroke: a retrospective single-center study in China.

BACKGROUND AND PURPOSE: Testing for antiphospholipid antibodies (aPL) is useful to determine the cause of ischemic stroke in young and female patients. However, the clinical relevance of aPL in older patients with ischemic stroke remains unclear. We aimed to explore the status and diagnostic value of initial aPL testing in all patients with acute ischemic stroke. METHODS: We retrospectively analyzed patients with acute ischemic stroke who were consecutively hospitalized in our hospital between June 2012 and January 2022 and investigated the factors associated with performing aPL screening in real-world clinical practice. Furthermore, factors associated with initial aPL positivity were evaluated by comparing the demographic, etiological, and therapeutic characteristics. RESULTS: Of 1209 patients, 287 (23.7%) were tested for aPL and 58 (20.2%) tested positive. Physicians tended to conduct aPL testing on female patients (P<0.001), younger patients (P<0.001), patients with fewer vascular risk factors (P<0.001), and multiple infarctions in the multivascular blood supply area (P<0.001). Multivariate logistic regression analysis showed that only stroke of other determined etiology type was a significant influencing factor for positive aPL results (OR 2.97, 95% CI 1.137, 7.774, P=0.026), adjusting for sex, age, and causes of stroke, etc. CONCLUSION: Approximately one-quarter of the patients with acute ischemic stroke were tested for aPL. Age, sex, number of vascular risk factors, and neuroimaging features affected the discretion in performing aPL testing. aPL testing may be appropriate in older patients with no identified cause of ischemic stroke and may provide additional diagnostic opportunities for acute ischemic stroke.

Automatic Detection of Thyroid Nodule Characteristics From 2D Ultrasound Images.

Thyroid cancer is one of the common types of cancer worldwide, and Ultrasound (US) imaging is a modality normally used for thyroid cancer diagnostics. The American College of Radiology Thyroid Imaging Reporting and Data System (ACR TIRADS) has been widely adopted to identify and classify US image characteristics for thyroid nodules. This paper presents novel methods for detecting the characteristic descriptors derived from TIRADS. Our methods return descriptions of the nodule margin irregularity, margin smoothness, calcification as well as shape and echogenicity using conventional computer vision and deep learning techniques. We evaluate our methods using datasets of 471 US images of thyroid nodules acquired from US machines of different makes and labeled by multiple radiologists. The proposed methods achieved overall accuracies of 88.00%, 93.18%, and 89.13% in classifying nodule calcification, margin irregularity, and margin smoothness respectively. Further tests with limited data also show a promising overall accuracy of 90.60% for echogenicity and 100.00% for nodule shape. This study provides an automated annotation of thyroid nodule characteristics from 2D ultrasound images. The experimental results showed promising performance of our methods for thyroid nodule analysis. The automatic detection of correct characteristics not only offers supporting evidence for diagnosis, but also generates patient reports rapidly, thereby decreasing the workload of radiologists and enhancing productivity.

Protocol for generation of humanized HCC mouse model and cancer-driver mutations using CRISPR-Cas9.

We detail procedures for generating a humanized mouse model of hepatocellular carcinoma (HCC) recapitulating genetic mutations associated with metabolic liver diseases (MLD). We humanized liver parenchymal, non-parenchymal, and hematopoietic cells. We employed CRISPR-Cas9-based ARID1A knockout and constitutively active CTNNB1 knockin combined with an alcohol Western diet to generate cancer-driver mutations commonly found in MLD-HCC patients. This HCC model facilitates the study of tumor-promoting gene-environment interactions. For complete details on the use and execution of this protocol, please refer to Yeh et al.1.

LncRNA RP11-10E18.7 cooperates with lncRNA RP11-481C4.2 to affect the overall survival of breast cancer patients: a TCGA-based retrospective study.

Background: As either oncogenes or tumor suppressor genes, long non-coding RNAs (lncRNAs) have a major role in both tumorigenesis and progression of human cancers, including breast cancer (BC). However, the statistical correlation between the lncRNA-lncRNA interaction and prognosis of BC remains unclear. Methods: We analyzed the fragments per kilobase per million (FPKM) lncRNA expression data in tumor tissue samples from 890 female patients with BC in The Cancer Genome Atlas (TCGA) between May 2021 and October 2022. The Cox proportional hazards model adjusted for age, race, clinical stage, neoadjuvant therapy, estrogen receptor (ER), and progesterone receptor (PR) was adopted to evaluate the lncRNA-lncRNA interaction regarding overall survival (OS) of BC. The multiple comparison was corrected by Bonferroni method. Results: RP11-10E18.7×RP11-481C4.2 was significantly associated with OS of BC patients [hazard ratio (HR)interaction =1.04, 95% confidence interval (CI): 1.03-1.06, P=3.35×10-9]. Then, gene-gene interaction analysis was performed for genes co-expressed with lncRNAs. FOXA1×U2SURP (HRinteraction =1.49, 95% CI: 1.28-1.73, P=2.16×10-7) was found to have a similar interactive pattern to RP11-10E18.7×RP11-481C4.2. after classifying the patients by intersection (3.47), we observed that the effect of FOXA1 opposite in patients with different U2SURP expression level (HRhigh vs. low =0.58, 95% CI: 0.34-0.99, P=0.046 in low expression of U2SURP; HRhigh vs. low =1.56, 95% CI: 1.18-2.87, P=0.029 in high expression of U2SURP). Conclusions: Our comprehensive study identified RP11-10E18.7×RP11-481C4.2 as a potential biomarker of BC prognosis. The results play an essential role in the impact of lncRNA-lncRNA interaction on BC survival. Our findings elucidated potential molecular mechanisms of BC progression under complex association patterns and provided potential dynamic and reversible therapeutic targets for BC patients.

Real-time carotid plaque recognition from dynamic ultrasound videos based on artificial neural network.

PURPOSE: Carotid ultrasound allows noninvasive assessment of vascular anatomy and function with real-time display. Based on the transfer learning method, a series of research results have been obtained on the optimal image recognition and analysis of static images. However, for carotid plaque recognition, there are high requirements for self-developed algorithms in real-time ultrasound detection. This study aims to establish an automatic recognition system, Be Easy to Use (BETU), for the real-time and synchronous diagnosis of carotid plaque from ultrasound videos based on an artificial neural network. MATERIALS AND METHODS: 445 participants (mean age, 54.6±7.8 years; 227 men) were evaluated. Radiologists labeled a total of 3259 segmented ultrasound images from 445 videos with the diagnosis of carotid plaque, 2725 images were collected as a training dataset, and 554 images as a testing dataset. The automatic plaque recognition system BETU was established based on an artificial neural network, and remote application on a 5G environment was performed to test its diagnostic performance. RESULTS: The diagnostic accuracy of BETU (98.5%) was consistent with the radiologist's (Kappa = 0.967, P < 0.001). Remote diagnostic feedback based on BETU-processed ultrasound videos could be obtained in 150ms across a distance of 1023 km between the ultrasound/BETU station and the consultation workstation. CONCLUSION: Based on the good performance of BETU in real-time plaque recognition from ultrasound videos, 5G plus Artificial intelligence (AI)-assisted ultrasound real-time carotid plaque screening was achieved, and the diagnosis was made.

Social Presence, Negative Emotions, and Self-Protective Behavioral Intentions of Nonsmokers in Response to Secondhand Smoking in Virtual Reality: Quasi-Experimental Design.

BACKGROUND: The application of virtual reality (VR) in health care has grown rapidly in China, where approximately half of the population is directly exposed to secondhand smoke (SHS). As VR headsets have become increasingly popular and short video platforms have incorporated 360° videos in China, new formats and opportunities for health campaigns about SHS have emerged. OBJECTIVE: In a simulated environment of exposure to SHS, this study aims to explore the emotional and behavioral responses to enhanced social presence brought about by VR in contrast to flat-screen videos. It also aims to examine whether and to what extent video modality (360° video vs flat-screen video) and contextual cues (high threat vs low threat) influence psychometric and intentional variables among viewers. METHODS: A total of 245 undergraduate and graduate students who were nonsmokers and from a large university in China participated in this study between October 2020 and January 2021. This study created 4 different versions of a SHS experience in a café with a 2 (360° video on a head-mounted display vs flat-screen display) × 2 (high threat vs low threat) experimental design. It developed and tested a path model examining the effects of experience modality and threat levels on social presence, emotions (anger and disgust), and eventually behavioral intentions (staying away and asking for help). RESULTS: We found that both video modality (P<.001) and threat level (P=.005) significantly influenced social presence, whereas the interaction of video modality and threat level did not have a statistically significant effect on social presence (P=.55). Negative emotions mediated the relationships between social presence and SHS-related self-protective behaviors. Specifically, anger positively predicted the intention to ask smokers to stop smoking through the waitress (P<.001). Disgust and fear both positively predicted the intention to stay away from the SHS environment (P<.001 for disgust; P=.002 for fear). CONCLUSIONS: This study explored the potential mediating mechanisms that influence individuals' responses to the risks of SHS in public areas. The results demonstrated that social presence and negative emotions are 2 important mediators that underlie the relationship between video modality and behavioral intention regarding SHS in a VR setting. These findings suggest that an immersive environment could be a better stimulator of anti-SHS emotions and behaviors than flat-screen videos.

Topic and Trend Analysis of Weibo Discussions About COVID-19 Medications Before and After China's Exit from the Zero-COVID Policy: Retrospective Infoveillance Study.

BACKGROUND: After 3 years of its zero-COVID policy, China lifted its stringent pandemic control measures with the announcement of the 10 new measures on December 7, 2022. Existing estimates suggest 90%-97% of the total population was infected during December. This change created a massive demand for COVID-19 medications and treatments, either modern medicines or traditional Chinese medicine (TCM). OBJECTIVE: This study aimed to explore (1) how China's exit from the zero-COVID policy impacted media and the public's attention to COVID-19 medications; (2) how social COVID-19 medication discussions were related to existing model estimates of daily cases during that period; (3) what the diversified themes and topics were and how they changed and developed from November 1 to December 31, 2022; and (4) which topics about COVID-19 medications were focused on by mainstream and self-media accounts during the exit. The answers to these questions could help us better understand the consequences of exit strategies and explore the utilities of Sina Weibo data for future infoveillance studies. METHODS: Using a scrapper for data retrieval and the structural topic modeling (STM) algorithm for analysis, this study built 3 topic models (all data, before a policy change, and after a policy change) of relevant discussions on the Chinese social media platform Weibo. We compared topic distributions against existing estimates of daily cases and between models before and after the change. We also compared proportions of weibos published by mainstream versus self-media accounts over time on different topics. RESULTS: We found that Weibo discussions shifted sharply from concerns of social risks (case tracking, governmental regulations, etc) to those of personal risks (symptoms, purchases, etc) surrounding COVID-19 infection after the exit from the zero-COVID policy. Weibo topics of "symptom sharing" and "purchase and shortage" of modern medicines correlated more strongly with existing susceptible-exposed-infected-recovered (SEIR) model estimates compared to "TCM formulae" and other topics. During the exit, mainstream accounts showed efforts to specifically engage in topics related to worldwide pandemic control policy comparison and regulations about import and reimbursement of medications. CONCLUSIONS: The exit from the zero-COVID policy in China was accompanied by a sudden increase in social media discussions about COVID-19 medications, the demand for which substantially increased after the exit. A large proportion of Weibo discussions were emotional and expressed increased risk concerns over medication shortage, unavailability, and delay in delivery. Topic keywords showed that self-medication was sometimes practiced alone or with unprofessional help from others, while mainstream accounts also tried to provide certain medication instructions. Of the 16 topics identified in all 3 STM models, only "symptom sharing" and "purchase and shortage" showed a considerable correlation with SEIR model estimates of daily cases. Future studies could consider topic exploration before conducting predictive infoveillance analysis, even with narrowly defined search criteria with Weibo data.

Identifying underlying patterns in Alzheimer's disease trajectory: a deep learning approach and Mendelian randomization analysis.

Background: Alzheimer's disease (AD) is a heterogeneously progressive neurodegeneration disorder with varied rates of deterioration, either between subjects or within different stages of a certain subject. Estimating the course of AD at early stages has treatment implications. We aimed to analyze disease progression to identify distinct patterns in AD trajectory. Methods: We proposed a deep learning model to identify underlying patterns in the trajectory from cognitively normal (CN) to a state of mild cognitive impairment (MCI) to AD dementia, by jointly predicting time-to-conversion and clustering out distinct subgroups characterized by comprehensive features as well as varied progression rates. We designed and validated our model on the ADNI dataset (1370 participants). Prediction of time-to-conversion in AD trajectory was used to validate the expression of the identified patterns. Causality between patterns and time-to-conversion was further inferred using Mendelian randomization (MR) analysis. External validation was performed on the AIBL dataset (233 participants). Findings: The proposed model clustered out patterns characterized by significantly different biomarkers and varied progression rates. The discovered patterns also showed a strong prediction ability, as indicated by hazard ratio (CN→MCI, HR = 3.51, p < 0.001; MCI→AD, HR = 8.11, p < 0.001), C-Index (CN→MCI, 0.618; MCI→AD, 0.718), and AUC (CN→MCI, 3 years 0.802, 5 years 0.876; MCI→AD, 3 years 0.914, 5 years 0.957). In the external validation cohort, our model demonstrated competitive performance on conversion time prediction (CN→MCI, C-Index = 0.693; MCI→AD, C-Index = 0.752). Moreover, suggestive associations between CN→MCI/MCI→AD patterns with four/three SNPs were mediated and MR analysis indicated a causal link between MCI→AD patterns and time-to-conversion in the first three years. Interpretation: Our proposed model identifies biologically and clinically meaningful patterns from real-world data and provides promising performance on time-to-conversion prediction in AD trajectory, which could promote the understanding of disease progression, facilitate clinical trial design, and provide potential for decision-making. Funding: The National Key Research and Development Program of China, the Key R&D Program of Zhejiang, and the National Nature Science Foundation of China.

A large pedigree study confirmed the CGG repeat expansion of RILPL1 Is associated with oculopharyngodistal myopathy.

BACKGROUND: Oculopharyngodistal myopathy (OPDM) is an autosomal dominant adult-onset degenerative muscle disorder characterized by ptosis, ophthalmoplegia and weakness of the facial, pharyngeal and limb muscles. Trinucleotide repeat expansions in non-coding regions of LRP12, G1PC1, NOTCH2NLC and RILPL1 were reported to be the etiologies for OPDM. RESULTS: In this study, we performed long-read whole-genome sequencing in a large five-generation family of 156 individuals, including 21 patients diagnosed with typical OPDM. We identified CGG repeat expansions in 5'UTR of RILPL1 gene in all patients we tested while no CGG expansion in unaffected family members. Repeat-primed PCR and fluorescence amplicon length analysis PCR were further confirmed the segregation of CGG expansions in other family members and 1000 normal Chinese controls. Methylation analysis indicated that methylation levels of the RILPL1 gene were unaltered in OPDM patients, which was consistent with previous studies. Our findings provide evidence that RILPL1 is associated OPDM in this large pedigree. CONCLUSIONS: Our results identified RILPL1 is the associated the disease in this large pedigree.

Pembrolizumab for the treatment of progressive multifocal leukoencephalopathy in China.

The aim of this study is to analyze the clinical characteristics and outcomes of Chinese patients with progressive multifocal leukoencephalopathy (PML) who were treated with programmed cell death protein 1 (PD1) blockade therapies. We retrospectively analyzed patients who were admitted to our hospital between October 1, 2020, and October 1, 2022, diagnosed with PML and treated with PD1 blockade therapies. Four patients with PML who were treated with PD1 blockade therapies were identified. All patients were male, and their ages ranged from 19 to 54 years old. One patient (Case 2) exhibited mild pleocytosis, while three patients (Cases 2-4) had markedly reduced T lymphocyte cell counts prior to treatment. The time interval between symptom onset and treatment initiation ranged from six to 54 weeks. All patients received pembrolizumab treatment, with a total of two to four doses administered. Three patients who responded to pembrolizumab treatment showed clinical improvement starting around 8 weeks after the initiation of therapy. Although one patient did not show clinical improvement, they ultimately survived until the last follow-up. None of the patients in this study exhibited immune-related adverse events or immune reconstitution inflammatory syndrome. PD1 blockade appears to be a promising novel therapeutic option for PML; additional prospective studies are necessary to confirm its efficacy.