A cytomics-on-a-chip platform and diagnostic model stratifies risk for oral lichenoid conditions.

OBJECTIVE: A small fraction of oral lichenoid conditions (OLC) have potential for malignant transformation. Distinguishing OLCs from other oral potentially malignant disorders (OPMDs) can help prevent unnecessary concern or testing, but accurate identification by nonexpert clinicians is challenging due to overlapping clinical features. In this study, the authors developed a 'cytomics-on-a-chip' tool and integrated predictive model for aiding the identification of OLCs. STUDY DESIGN: All study subjects underwent both scalpel biopsy for histopathology and brush cytology. A predictive model and OLC Index comprising clinical, demographic, and cytologic features was generated to discriminate between subjects with lichenoid (OLC+) (N = 94) and nonlichenoid (OLC-) (N = 237) histologic features in a population with OPMDs. RESULTS: The OLC Index discriminated OLC+ and OLC- subjects with area under the curve (AUC) of 0.76. Diagnostic accuracy of the OLC Index was not significantly different from expert clinician impressions, with AUC of 0.81 (P = .0704). Percent agreement was comparable across all raters, with 83.4% between expert clinicians and histopathology, 78.3% between OLC Index and expert clinician, and 77.3% between OLC Index and histopathology. CONCLUSIONS: The cytomics-on-a-chip tool and integrated diagnostic model have the potential to facilitate both the triage and diagnosis of patients presenting with OPMDs and OLCs.

Correction: Srinivasan Rajsri et al. Acute Myeloid Leukemia Stem Cells in Minimal/Measurable Residual Disease Detection. Cancers 2023, 15, 2866.

In the original publication [...].

A brief review of cytology in dentistry.

Oral cytology is a non-invasive adjunctive diagnostic tool with a number of potential applications in the practice of dentistry. This brief review begins with a history of cytology in medicine and how cytology was initially applied in oral medicine. A description of the different technical aspects of oral cytology is provided, including the collection and processing of oral cytological samples, and the microscopic interpretation and reporting, along with their advantages and limitations. Applications for oral cytology are listed with a focus on the triage of patients presenting with oral potentially malignant disorders and oral mucosal infections. Furthermore, the utility of oral cytology roles across both expert (for example, secondary oral medicine or tertiary head and neck oncology services) and non-expert (for example, primary care general dental practice) clinical settings is explored. A detailed section covers the evidence-base for oral cytology as a diagnostic adjunctive technique in both the early detection and monitoring of patients with oral cancer and oral epithelial dysplasia. The review concludes with an exploration of future directions, including the integration of artificial intelligence for automated analysis and point of care 'smart diagnostics', thereby offering some insight into future opportunities for a wider application of oral cytology in dentistry.

Simultaneous Quantitative SARS-CoV-2 Antigen and Host Antibody Detection and Pre-Screening Strategy at the Point of Care.

As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane over time and the immunocompromised populations can no longer expect benefit from monoclonal antibody prophylaxis. Hence, there is a need to monitor new variants and its effect on vaccine performance. In this context, surveillance of new SARS-CoV-2 infections and serology testing are gaining consensus for use as screening methods, especially for at-risk groups. Here, we described an improved COVID-19 screening strategy, comprising predictive algorithms and concurrent, rapid, accurate, and quantitative SARS-CoV-2 antigen and host antibody testing strategy, at point of care (POC). We conducted a retrospective analysis of 2553 pre- and asymptomatic patients who were tested for SARS-CoV-2 by RT-PCR. The pre-screening model had an AUC (CI) of 0.76 (0.73-0.78). Despite being the default method for screening, body temperature had lower AUC (0.52 [0.49-0.55]) compared to case incidence rate (0.65 [0.62-0.68]). POC assays for SARS-CoV-2 nucleocapsid protein (NP) and spike (S) receptor binding domain (RBD) IgG antibody showed promising preliminary results, demonstrating a convenient, rapid (<20 min), quantitative, and sensitive (ng/mL) antigen/antibody assay. This integrated pre-screening model and simultaneous antigen/antibody approach may significantly improve accuracy of COVID-19 infection and host immunity screening, helping address unmet needs for monitoring vaccine effectiveness and severe disease surveillance.

Acute Myeloid Leukemia Stem Cells in Minimal/Measurable Residual Disease Detection.

Acute myeloid leukemia (AML) is a hematological malignancy characterized by an abundance of incompletely matured or immature clonally derived hematopoietic precursors called leukemic blasts. Rare leukemia stem cells (LSCs) that can self-renew as well as give rise to leukemic progenitors comprising the bulk of leukemic blasts are considered the cellular reservoir of disease initiation and maintenance. LSCs are widely thought to be relatively resistant as well as adaptive to chemotherapy and can cause disease relapse. Therefore, it is imperative to understand the molecular bases of LSC forms and functions during different stages of disease progression, so we can more accurately identify these cells and design therapies to target them. Irrespective of the morphological, cytogenetic, and cellular heterogeneity of AML, the uniform, singularly important and independently significant prognosticator of disease response to therapy and patient outcome is measurable or minimal residual disease (MRD) detection, defined by residual disease detection below the morphology-based 5% blast threshold. The importance of LSC identification and frequency estimation during MRD detection, in order to make MRD more effective in predicting disease relapse and modifying therapeutic regimen is becoming increasingly apparent. This review focuses on summarizing functional and cellular composition-based LSC identification and linking those studies to current techniques of MRD detection to suggest LSC-inclusive MRD detection as well as outline outstanding questions that need to be addressed to improve the future of AML clinical management and treatment outcomes.

Poxvirus-driven human diseases and emerging therapeutics.

Poxviridae have been successful pathogens throughout recorded history, infecting humans among a variety of other hosts. Although eradication of the notorious smallpox has been a globally successful healthcare phenomenon, the recent emergence of Monkeypox virus, also belonging to the Orthopoxvirus genus and causing human disease, albeit milder than smallpox, is a cause of significant public health concern. The ongoing outbreak of monkeypox, demonstrating human-human transmission, in previously nonendemic countries, calls for critical need into further research in the areas of viral biology, ecology, and epidemiology to better understand, prevent and treat human infections. In the wake of these recent events, it becomes important to revisit poxviral infections, their pathogenesis and ability to cause infection across multiple nonhuman hosts and leap to a human host. The poxviruses that cause human diseases include Monkeypox virus, Molluscum contagiosum virus, and Orf virus. In this review, we summarize the current understanding of various poxviruses causing human diseases, provide insights into their replication and pathogenicity, disease progression and symptoms, preventive and treatment options, and their importance in shaping modern medicine through application in gene therapy, oncolytic viral therapies for human cancers, or as poxvirus vectors for vaccines.