Publications by authors named "Jade Wang"

Spatial transcriptomic technologies are becoming increasingly high-resolution, enabling precise measurement of gene expression at the subcellular level. Here, we introduce a computational method called subcellular expression localization analysis (ELLA), for modeling the subcellular localization of mRNAs and detecting genes that display spatial variation within cells in high-resolution spatial transcriptomics. ELLA creates a unified cellular coordinate system to anchor diverse cell shapes and morphologies, utilizes a nonhomogeneous Poisson process to model spatial count data, leverages an expression gradient function to characterize subcellular expression patterns, and produces effective control of type I error and high statistical power.

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  • Acute lymphoblastic leukemia (ALL) is the most prevalent cancer among children, but survivors often face long-lasting neurocognitive issues.
  • This study uses data from the TOTXVI clinical trial to investigate how treatment affects brain connectivity and contributes to these cognitive side effects.
  • A new analysis method called network mediation structural shrinkage (NMSS) is introduced to accurately assess these effects, revealing that changes in brain connectivity significantly impact visual processing speed in survivors, suggesting potential for targeted interventions.
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Surveillance systems that monitor pathogen genome sequences are critical for rapidly detecting the introduction and emergence of pathogen variants. To evaluate how interactions between surveillance capacity, variant properties, and the epidemiological context influence the timeliness of pathogen variant detection, we developed a geographically explicit stochastic compartmental model to simulate the transmission of a novel SARS-CoV-2 variant in New York City. We measured the impact of (1) testing and sequencing volume, (2) geographic targeting of testing, (3) the timing and location of variant emergence, and (4) the relative variant transmissibility on detection speed and on the undetected disease burden.

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  • * Genetic analysis showed that individuals linked to mpox clusters had a higher likelihood of previously being diagnosed with HIV, indicating overlapping sexual networks for both viruses.
  • * The study found that highly connected individuals were more likely to get infected early in the outbreak, leading to a rapid rise and fall of cases, and emphasized that mpox transmission shares dynamics with other sexually transmitted infections.
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Objective: Endoscopic retrograde cholangiopancreatography (ERCP) may be unsuccessful in patients with duodenal stenosis or malignant ampullary infiltration. Endoscopic ultrasound-guided biliary drainage (EUS-BD) has been proposed as an alternative. We aimed to assess the efficacy and safety of EUS-BD for malignant distal bile duct obstruction using the newly introduced smaller caliber 6 or 8 mm cautery-enhanced lumen-apposing metal stent.

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Socio-economic disparities were associated with disproportionate viral incidence between neighborhoods of New York City (NYC) during the first wave of SARS-CoV-2. We investigated how these disparities affected the co-circulation of SARS-CoV-2 variants during the second wave in NYC. We tested for correlation between the prevalence, in late 2020/early 2021, of Alpha, Iota, Iota with E484K mutation (Iota-E484K), and B.

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Background: PSMA PET has emerged as a "gold standard" imaging modality for assessing prostate cancer metastases. However, it is not universally available, and this limits its impact. In contrast, whole-body MRI is much more widely available but misses more lesions.

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  • A study focused on 13 patients with advanced HIV (CD4 count under 200 cells/μL) who also had severe mpox and multiple organ issues.* -
  • These patients underwent long treatments with various medications, including tecovirimat and others, but still faced serious health complications.* -
  • The outcomes showed that they had long hospital stays and a high death rate, highlighting the severity of their conditions.*
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With the rapid spread and evolution of SARS-CoV-2, the ability to monitor its transmission and distinguish among viral lineages is critical for pandemic response efforts. The most commonly used software for the lineage assignment of newly isolated SARS-CoV-2 genomes is pangolin, which offers two methods of assignment, pangoLEARN and pUShER. PangoLEARN rapidly assigns lineages using a machine-learning algorithm, while pUShER performs a phylogenetic placement to identify the lineage corresponding to a newly sequenced genome.

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Introduction: Research to date has established that the COVID-19 pandemic has not impacted everyone equitably. Whether this unequitable impact was seen educationally with regards to educator reported barriers to distance learning, concerns and mental health is less clear.

Objective: The objective of this study was to explore the association between the neighbourhood composition of the school and kindergarten educator-reported barriers and concerns regarding children's learning during the first wave of COVID-19 related school closures in Ontario, Canada.

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The first three SARS-CoV-2 phylogenetic lineages classified as variants of concern (VOCs) in the United States (U.S.) from December 15, 2020 to February 28, 2021, Alpha (B.

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Pediatric cancer treatment, especially for brain tumors, can have profound and complicated late effects. With the survival rates increasing because of improved detection and treatment, a more comprehensive understanding of the impact of current treatments on neurocognitive function and brain structure is critically needed. A frontline medulloblastoma clinical trial (SJMB03) has collected data, including treatment, clinical, neuroimaging, and cognitive variables.

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Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B.

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Background: Monitoring the emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is an important public health objective. We investigated how the Gamma variant was established in New York City (NYC) in early 2021 in the presence of travel restrictions that aimed to prevent viral spread from Brazil, the country where the variant was first identified.

Methods: We performed phylogeographic analysis on 15 967 Gamma sequences sampled between 10 March and 1 May 2021, to identify geographic sources of Gamma lineages introduced into NYC.

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  • * In this case, an individual was superinfected with two SARS-CoV-2 variants, Alpha (B.1.1.7) and Epsilon (B.1.429), which led to unexpected genomic characteristics in the Alpha variant.
  • * Full genome sequencing indicated that the Alpha variant made up about 75% of the viral presence, with the Epsilon variant at around 20%, and revealed multiple recombinant forms that could influence the virus's evolution.
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  • Recent advancements in neuroimaging and genetic sequencing have led to a deep learning approach called IGnet for detecting and classifying Alzheimer's disease (AD) using MRI and genetic data.
  • The method combines computer vision and natural language processing techniques, utilizing a 3D convolutional network for MRI data and a Transformer encoder for genetic sequences.
  • When tested on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, IGnet achieved a classification accuracy of 83.78% and an AUC-ROC of 0.924, showcasing the effectiveness of integrating imaging and genetic data for AD diagnosis.
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  • Qualitative research has historically supported quantitative studies to better understand pandemics, with the COVID-19 crisis introducing new challenges that researchers have addressed using innovative methods.
  • The authors detail their experience conducting a multilingual global study on healthcare resilience among pediatric oncology teams during the pandemic, highlighting their unique methodology and factors that contributed to their success.
  • They aim to share insights on their use of technology, collaboration within a diverse team, and rapid analysis techniques to benefit other researchers in similar contexts.
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To characterize the epidemiological properties of the B.1.526 SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) variant of interest, here we used nine epidemiological and population datasets and model-inference methods to reconstruct SARS-CoV-2 transmission dynamics in New York City, where B.

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Unlabelled: When the COVID-19 pandemic was declared in March 2020, the lives of families all over the world were disrupted. Many adults found themselves working from home while their children were unable to go to school. To better understand the potential impact of these educational disruptions, it is important to establish what learning looked like during the first school shutdown in the spring of 2020, particularly for the youngest learners who may feel the longest lasting impacts from this pandemic.

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  • This study investigates how effective natural language processing (NLP) and machine learning (ML) are in identifying pain and fatigue symptoms reported by child and adolescent cancer survivors, comparing these methods to expert evaluations.
  • Conducted with a group of 8 to 17-year-olds and their caregivers, researchers analyzed interview data from St. Jude Children's Research Hospital, extracting 391 units related to pain and 423 related to fatigue.
  • Results indicate that the BERT NLP model outperformed other ML methods in accurately classifying symptom attributes, achieving high accuracy rates for cognitive and social aspects of pain and fatigue.
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  • Wide-scale genome sequencing of SARS-CoV-2 is essential for tracking how the virus evolves during the pandemic.
  • A new software tool called Variant Database (VDB) has been developed to analyze changes in spike mutations, leading to the identification of a new lineage, B.1.526, in New York.
  • The B.1.526 lineage has mutations that may weaken the effectiveness of vaccines and natural immunity, which potentially impacted the duration of the second wave of COVID-19 cases.
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  • - Recent studies have shown that B.1.526, a new variant of SARS-CoV-2, emerged in New York City in November 2020, with two main subclades, one of which has a mutation (E484K) that reduces the effectiveness of some antibodies.
  • - The NYC Department of Health analyzed data on B.1.526 cases, finding that it doesn’t seem to cause more severe illness or increase the risk of breakthrough infections among vaccinated individuals.
  • - However, the study's limited amount of sequenced data may not have been enough to identify smaller differences in outcomes, highlighting the need for better genomic data collection and integration to understand the effects of new variants.
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Background: While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions typically warrant prostate biopsy and PI-RADS 1 and 2 lesions may be safely observed, PI-RADS 3 lesions are equivocal.

Purpose: To construct and cross-validate a machine learning model based on radiomics features from T -weighted imaging (T WI) of PI-RADS 3 lesions to identify clinically significant prostate cancer (csPCa), that is, pathological Grade Group ≥ 2.

Study Type: Single-center retrospective study.

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