Unraveling Links between Chronic Inflammation and Long COVID: Workshop Report.

As COVID-19 continues, an increasing number of patients develop long COVID symptoms varying in severity that last for weeks, months, or longer. Symptoms commonly include lingering loss of smell and taste, hearing loss, extreme fatigue, and "brain fog." Still, persistent cardiovascular and respiratory problems, muscle weakness, and neurologic issues have also been documented. A major problem is the lack of clear guidelines for diagnosing long COVID. Although some studies suggest that long COVID is due to prolonged inflammation after SARS-CoV-2 infection, the underlying mechanisms remain unclear. The broad range of COVID-19's bodily effects and responses after initial viral infection are also poorly understood. This workshop brought together multidisciplinary experts to showcase and discuss the latest research on long COVID and chronic inflammation that might be associated with the persistent sequelae following COVID-19 infection.

Metabolic Regulation of Inflammation and Its Resolution: Current Status, Clinical Needs, Challenges, and Opportunities.

Metabolism and inflammation have been viewed as two separate processes with distinct but critical functions for our survival: metabolism regulates the utilization of nutrients, and inflammation is responsible for defense and repair. Both respond to an organism's stressors to restore homeostasis. The interplay between metabolic status and immune response (immunometabolism) plays an important role in maintaining health or promoting disease development. Understanding these interactions is critical in developing tools for facilitating novel preventative and therapeutic approaches for diseases, including cancer. This trans-National Institutes of Health workshop brought together basic scientists, technology developers, and clinicians to discuss state-of-the-art, innovative approaches, challenges, and opportunities to understand and harness immunometabolism in modulating inflammation and its resolution.

Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.

ABSTRACT: The potential of artificial intelligence (AI) applied to clinical data from electronic health records (EHRs) to improve early detection for pancreatic and other cancers remains underexplored. The Kenner Family Research Fund, in collaboration with the Cancer Biomarker Research Group at the National Cancer Institute, organized the workshop entitled: "Early Detection of Pancreatic Cancer: Opportunities and Challenges in Utilizing Electronic Health Records (EHR)" in March 2021. The workshop included a select group of panelists with expertise in pancreatic cancer, EHR data mining, and AI-based modeling. This review article reflects the findings from the workshop and assesses the feasibility of AI-based data extraction and modeling applied to EHRs. It highlights the increasing role of data sharing networks and common data models in improving the secondary use of EHR data. Current efforts using EHR data for AI-based modeling to enhance early detection of pancreatic cancer show promise. Specific challenges (biology, limited data, standards, compatibility, legal, quality, AI chasm, incentives) are identified, with mitigation strategies summarized and next steps identified.

Imaging inflammation and its resolution in health and disease: current status, clinical needs, challenges, and opportunities.

Inflammation is a normal process in our body; acute inflammation acts to suppress infections and support wound healing. Chronic inflammation likely leads to a wide range of diseases, including cancer. Tools to locate and monitor inflammation are critical for developing effective interventions to arrest inflammation and promote its resolution. To identify current clinical needs, challenges, and opportunities in advancing imaging-based evaluations of inflammatory status in patients, the U.S. National Institutes of Health convened a workshop on imaging inflammation and its resolution in health and disease. Clinical speakers described their needs for image-based capabilities that could help determine the extent of inflammatory conditions in patients to guide treatment planning and undertake necessary interventions. The imaging speakers showcased the state-of-the-art in vivo imaging techniques for detecting inflammation in different disease areas. Many imaging capabilities developed for 1 organ or disease can be adapted for other diseases and organs, whereas some have promise for clinical utility within the next 5-10 yr. Several speakers demonstrated that multimodal imaging measurements integrated with serum-based measures could improve in robustness for clinical utility. All speakers agreed that multiple inflammatory measures should be acquired longitudinally to comprehend the dynamics of unresolved inflammation that leads to disease development. They also agreed that the best strategies for accelerating clinical translation of imaging inflammation capabilities are through integration between new imaging techniques and biofluid-based biomarkers of inflammation as well as already established imaging measurements.-Liu, C. H., Abrams, N. D., Carrick, D. M., Chander, P., Dwyer, J., Hamlet, M. R. J., Kindzelski, A. L., PrabhuDas, M., Tsai, S.-Y. A., Vedamony, M. M., Wang, C., Tandon, P. Imaging inflammation and its resolution in health and disease: current status, clinical needs, challenges, and opportunities.

Cripto-1 as a novel therapeutic target for triple negative breast cancer.

Triple-negative breast cancer (TNBC) presents the poorest prognosis among the breast cancer subtypes and no current standard therapy. Here, we performed an in-depth molecular analysis of a mouse model that establishes spontaneous lung metastasis from JygMC(A) cells. These primary tumors resembled the triple-negative breast cancer (TNBC) both phenotypically and molecularly. Morphologically, primary tumors presented both epithelial and spindle-like cells but displayed only adenocarcinoma-like features in lung parenchyma. The use of laser-capture microdissection combined with Nanostring mRNA and microRNA analysis revealed overexpression of either epithelial and miRNA-200 family or mesenchymal markers in adenocarcinoma and mesenchymal regions, respectively. Cripto-1, an embryonic stem cell marker, was present in spindle-like areas and its promoter showed activity in primary tumors. Cripto-1 knockout by the CRISPR-Cas9 system inhibited tumor growth and pulmonary metastasis. Our findings show characterization of a novel mouse model that mimics the TNBC and reveal Cripto-1 as a TNBC target hence may offer alternative treatment strategies for TNBC.

Genome Sequence of Aspergillus flavus NRRL 3357, a Strain That Causes Aflatoxin Contamination of Food and Feed.

Aflatoxin contamination of food and livestock feed results in significant annual crop losses internationally. Aspergillus flavus is the major fungus responsible for this loss. Additionally, A. flavus is the second leading cause of aspergillosis in immunocompromised human patients. Here, we report the genome sequence of strain NRRL 3357.

Genome Sequence of the AIDS-Associated Pathogen Penicillium marneffei (ATCC18224) and Its Near Taxonomic Relative Talaromyces stipitatus (ATCC10500).

Penicillium marneffei can cause a fatal systemic mycosis in patients infected with the HIV. Infections are endemic in the tropical regions of southeast Asia. Here, we report the genome sequences of the type strains of P. marneffei and its avirulent near relative, Talaromyces stipitatus.

Systematic and searchable classification of cytochrome P450 proteins encoded by fungal and oomycete genomes.

BACKGROUND: Cytochrome P450 proteins (CYPs) play diverse and pivotal roles in fungal metabolism and adaptation to specific ecological niches. Fungal genomes encode extremely variable "CYPomes" ranging from one to more than 300 CYPs. Despite the rapid growth of sequenced fungal and oomycete genomes and the resulting influx of predicted CYPs, the vast majority of CYPs remain functionally uncharacterized. To facilitate the curation and functional and evolutionary studies of CYPs, we previously developed Fungal Cytochrome P450 Database (FCPD), which included CYPs from 70 fungal and oomycete species. Here we present a new version of FCPD (1.2) with more data and an improved classification scheme. RESULTS: The new database contains 22,940 CYPs from 213 species divided into 2,579 clusters and 115 clans. By optimizing the clustering pipeline, we were able to uncover 36 novel clans and to assign 153 orphan CYP families to specific clans. To augment their functional annotation, CYP clusters were mapped to David Nelson's P450 databases, which archive a total of 12,500 manually curated CYPs. Additionally, over 150 clusters were functionally classified based on sequence similarity to experimentally characterized CYPs. Comparative analysis of fungal and oomycete CYPomes revealed cases of both extreme expansion and contraction. The most dramatic expansions in fungi were observed in clans CYP58 and CYP68 (Pezizomycotina), clans CYP5150 and CYP63 (Agaricomycotina), and family CYP509 (Mucoromycotina). Although much of the extraordinary diversity of the pan-fungal CYPome can be attributed to gene duplication and adaptive divergence, our analysis also suggests a few potential horizontal gene transfer events. Updated families and clans can be accessed through the new version of the FCPD database. CONCLUSIONS: FCPD version 1.2 provides a systematic and searchable catalogue of 9,550 fungal CYP sequences (292 families) encoded by 108 fungal species and 147 CYP sequences (9 families) encoded by five oomycete species. In comparison to the first version, it offers a more comprehensive clan classification, is fully compatible with Nelson's P450 databases, and has expanded functional categorization. These features will facilitate functional annotation and classification of CYPs encoded by newly sequenced fungal and oomycete genomes. Additionally, the classification system will aid in studying the roles of CYPs in the evolution of fungal adaptation to specific ecological niches.