Exosomes are endosome derived extracellular vesicles of 30–120 nm size ranges. Exosomes have been identified as mediators of cell-to-cell communication by transferring bioactive molecules such as nucleic acids, proteins and lipids into recipient cells. While exosomes are secreted by multiple cell types, cancer derived exosomes not only influence the invasive potentials of proximally located cells, but also affect distantly located tissues. Based on their ability to alter tumor microenvironment by regulating immunity, angiogenesis and metastasis, there has been growing interest in defining the clinical relevance of exosomes in cancers. In particular, exosomes are valuable sources for biomarkers due to selective cargo loading and resemblance to their parental cells. In this review, we summarize the recent findings to utilize exosomes as cancer biomarkers for early detection, diagnosis and therapy selection.
We report the implementation of field effect transistors based on exfoliated nano-membranes of a layered two-dimensional semiconductor SnS(2), which exhibit an on/off ratio exceeding 2 × 10(6) and a carrier mobility of ∼1 cm(2) V(-1) s(-1). The results demonstrate the great potential of SnS(2), a layered semiconductor with finite band gap, as the building block for future nanoelectronic applications complementary to graphene-based materials with zero or small band gaps.
We present CoSQL, a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems. It consists of 30k+ turns plus 10k+ annotated SQL queries, obtained from a Wizard-of-Oz (WOZ) collection of 3k dialogues querying 200 complex DBs spanning 138 domains. Each dialogue simulates a real-world DB query scenario with a crowd worker as a user exploring the DB and a SQL expert retrieving answers with SQL, clarifying ambiguous questions, or otherwise informing of unanswerable questions. When user questions are answerable by SQL, the expert describes the SQL and execution results to the user, hence maintaining a natural interaction flow. CoSQL introduces new challenges compared to existing task-oriented dialogue datasets: (1) the dialogue states are grounded in SQL, a domain-independent executable representation, instead of domain-specific slotvalue pairs, and (2) because testing is done on unseen databases, success requires generalizing to new domains. CoSQL includes three tasks: SQL-grounded dialogue state tracking, response generation from query results, and user dialogue act prediction. We evaluate a set of strong baselines for each task and show that CoSQL presents significant challenges for future research. The dataset, baselines, and leaderboard will be released at https:// yale-lily.github.io/cosql.
We present SParC, a dataset for cross-domain Semantic Parsing in Context. It consists of 4,298 coherent question sequences (12k+ individual questions annotated with SQL queries), obtained from controlled user interactions with 200 complex databases over 138 domains. We provide an in-depth analysis of SParC and show that it introduces new challenges compared to existing datasets. SParC (1) demonstrates complex contextual dependencies, (2) has greater semantic diversity, and (3) requires generalization to new domains due to its cross-domain nature and the unseen databases at test time. We experiment with two state-of-the-art text-to-SQL models adapted to the context-dependent, crossdomain setup. The best model obtains an exact set match accuracy of 20.2% over all questions and less than 10% over all interaction sequences, indicating that the crossdomain setting and the contextual phenomena of the dataset present significant challenges for future research. The dataset, baselines, and leaderboard are released at https:// yale-lily.github.io/sparc. AS T2 ON T1.dormid = T2.dormid JOIN dorm_amenity AS T3 ON T2.amenid = T3.amenid WHERE T3.amenity_name = 'TV Lounge'What is the total capacity of these dorms? Q 2 : SELECT SUM (T1.student_capacity) FROM dorm AS T1 S 2 : JOIN has_amenity AS T2 ON T1.dormid = T2.dormid JOIN dorm_amenity AS T3 ON T2.amenid = T3.amenid WHERE T3.amenity_name = 'TV Lounge' How many students are living there? Q 3 : SELECT COUNT (*) FROM student AS T1 JOIN lives_in S 3 : AS T2 ON T1.stuid = T2.stuid WHERE T2.dormid IN ( SELECT T3.dormid FROM has_amenity AS T3 JOIN dorm_amenity AS T4 ON T3.amenid = T4.amenid WHERE T4.amenity_name = 'TV Lounge')
Castleman disease (CD) describes a group of rare hematologic conditions involving lymphadenopathy with characteristic histopathology and a spectrum of clinical abnormalities. CD is divided into localized or unicentric CD (UCD) and multicentric CD (MCD) by imaging. MCD is further divided based on etiological driver into human herpesvirus-8-associated MCD, POEMS-associated MCD, and idiopathic MCD. There is notable heterogeneity across MCD, but increased level of pro-inflammatory cytokines, particularly interleukin-6, is an established disease driver in a portion of patients. FDG-PET/CT can help determine UCD versus MCD, evaluate for neoplastic conditions that can mimic MCD clinico-pathologically, and monitor therapy responses. CD requires more robust characterization, earlier diagnosis, and an accurate tool for both monitoring and treatment response evaluation; FDG-PET/CT is particularly suited for this. Moving forward, future prospective studies should further characterize the use of FDG-PET/CT in CD and specifically explore the utility of global disease assessment and dual time point imaging.Trial registration ClinicalTrials.gov, NCT02817997, Registered 29 June 2016, https://clinicaltrials.gov/ct2/show/NCT02817997
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