Examining Clinical Features and Severe Neurologic Disease of Parechovirus Infection in Young Infants: A Multi-State Cohort Study.

BACKGROUND: Human parechovirus (HPeV) infection can result in severe disease in infants, including sepsis, seizures, brain injury, and death. In 2022, a resurgence of HPeV was noted in young infants. Spectrum of illness and outcomes remain to be fully described. METHODS: A multi-state retrospective cohort study was conducted to evaluate hospitalizations and outcomes of infants aged ≤6 months admitted in 2022 with laboratory-confirmed HPeV infection. Infants with severe disease were defined as having clinical seizures, or abnormalities on MRI or EEG during admission. Infants with severe vs non-severe disease were compared using descriptive statistics. RESULTS: 124 U.S. infants were identified with HPeV in 11 states. Cases of HPeV peaked in May and presented at a median of 25.8 days of life (0-194 d) with fever, fussiness, and poor feeding. Bacterial and other viral co-infections were rare. 33 (27%) of infants had severe neurologic disease, were more likely to present at an earlier age (13.9 vs 30 days of life, p<0.01), have preterm gestation (12% vs. 1%, p = 0.02), and present with respiratory symptoms (26% vs. 8%, p = 0.01) or apnea (41% vs. 1%, p <0.001). Subcortical white matter cytoxic cerebral edema was common in severe cases. Two infants with HPeV died during admission with severe neurologic HPeV disease; no infant with mild HPeV disease died. CONCLUSIONS: This is the largest, geographically-diverse U.S. study to describe the 2022 HPeV outbreak among infants. Longitudinal follow up of infants is needed to define predictors and outcomes of severe HPeV disease.

Nutrition's checkpoint inhibition: The impact of nutrition on immunotherapy outcomes.

OBJECTIVES: To determine if nutritional status effects response to immunotherapy in women with gynecologic malignancies. METHODS: A retrospective chart review was conducted on gynecologic cancer patients who received immunotherapy at a single institution between 2015 and 2022. Immunotherapy included checkpoint inhibitors and tumor vaccines. The prognostic nutritional index (PNI) was calculated from serum albumin levels and total lymphocyte count. PNI values were determined at the beginning of treatment for each patient and assessed for their association with immunotherapy response. Disease control response (DCR) as an outcome of immunotherapy was defined as complete response, partial response, or stable disease. RESULTS: One hundred and ninety-eight patients received immunotherapy (IT) between 2015 and 2022. The gynecological cancers treated were uterine (38%), cervix (32%), ovarian (25%), and vulvar or vaginal (4%) cancers. The mean PNI for responders was higher than the non-responder group (p < 0.05). The AUC value for PNI as a predictor of response was 49. A PNI value of 49 was 43% sensitive and 85% specific for predicting a DCR. In Cox proportional hazards analysis, after adjusting for ECOG score and the number of prior chemotherapy lines, severe malnutrition was associated with progression-free survival (PFS) (HR = 1.85, p = 0.08) and overall survival (OS) (HR = 3.82, p < 0.001). Patients with PNI < 49 were at a higher risk of IT failure (HR = 2.24, p = 0.0001) and subsequent death (HR = 2.84, p = 9 × 10-5). CONCLUSIONS: PNI can be a prognostic marker to predict response rates of patients with gynecologic cancers treated with immunotherapy. Additional studies needed to understand the mechanistic role of malnutrition in immunotherapy response.

The Legionella collagen-like protein employs a distinct binding mechanism for the recognition of host glycosaminoglycans.

Bacterial adhesion is a fundamental process which enables colonisation of niche environments and is key for infection. However, in Legionella pneumophila, the causative agent of Legionnaires' disease, these processes are not well understood. The Legionella collagen-like protein (Lcl) is an extracellular peripheral membrane protein that recognises sulphated glycosaminoglycans on the surface of eukaryotic cells, but also stimulates bacterial aggregation in response to divalent cations. Here we report the crystal structure of the Lcl C-terminal domain (Lcl-CTD) and present a model for intact Lcl. Our data reveal that Lcl-CTD forms an unusual trimer arrangement with a positively charged external surface and negatively charged solvent exposed internal cavity. Through molecular dynamics simulations, we show how the glycosaminoglycan chondroitin-4-sulphate associates with the Lcl-CTD surface via distinct binding modes. Our findings show that Lcl homologs are present across both the Pseudomonadota and Fibrobacterota-Chlorobiota-Bacteroidota phyla and suggest that Lcl may represent a versatile carbohydrate-binding mechanism.

Serum Proteomic Signatures in Cervical Cancer: Current Status and Future Directions.

In 2020, the World Health Organization (WHO) reported 604,000 new diagnoses of cervical cancer (CC) worldwide, and over 300,000 CC-related fatalities. The vast majority of CC cases are caused by persistent human papillomavirus (HPV) infections. HPV-related CC incidence and mortality rates have declined worldwide because of increased HPV vaccination and CC screening with the Papanicolaou test (PAP test). Despite these significant improvements, developing countries face difficulty implementing these programs, while developed nations are challenged with identifying HPV-independent cases. Molecular and proteomic information obtained from blood or tumor samples have a strong potential to provide information on malignancy progression and response to therapy in CC. There is a large amount of published biomarker data related to CC available but the extensive validation required by the FDA approval for clinical use is lacking. The ability of researchers to use the big data obtained from clinical studies and to draw meaningful relationships from these data are two obstacles that must be overcome for implementation into clinical practice. We report on identified multimarker panels of serum proteomic studies in CC for the past 5 years, the potential for modern computational biology efforts, and the utilization of nationwide biobanks to bridge the gap between multivariate protein signature development and the prediction of clinically relevant CC patient outcomes.

Evaluating the WISE (Women in the South-East) Telehealth Network: A Model of Healthcare and Health Promotion at Rural Libraries.

PURPOSE: The purpose of this study was to evaluate the effectiveness of the WISE (Women in the South-East) Telehealth Network. DESIGN: A follow-up survey design was used to determine the impact of the program on access to healthcare. SETTING: WISE provided preventive care to women and gender expansive people at local libraries and the Mobile Library in the rural South Carolina Lowcountry. SUBJECTS: In 1 year (February 2021-2022), WISE reached 523 individuals with 151 agreeing to participate in the study. Most participants identified as white (66%) or Black (22%). INTERVENTION: A Community Health Worker provided health education, connection to telehealth services, referrals, and connected individuals with community and social services. MEASURES: The Telehealth Usability Questionnaire (TUQ), changes in knowledge, satisfaction with WISE, Acceptability of Intervention measure (AIM), and sociodemographic characteristics. RESULTS: Participants with a high telehealth usability score were significantly more likely to be under the age of 35 (OR 4.60 [95% CI 1.21-17.52]), married (OR 10.00 [95% CI 2.19-45.64]), or white (OR 4.00 [95% CI 1.06-15.08]). The intervention earned a high acceptability score 4.46 (± .61)/5.0 by helping participants obtain necessary medical care and resources, as well as meeting their educational needs. CONCLUSION: This study offers practical suggestions to expand the use of telehealth initiatives to improve health outcomes by engaging libraries in rural communities.

The planetary commons: A new paradigm for safeguarding Earth-regulating systems in the Anthropocene.

The Anthropocene signifies the start of a no-analogue trajectory of the Earth system that is fundamentally different from the Holocene. This new trajectory is characterized by rising risks of triggering irreversible and unmanageable shifts in Earth system functioning. We urgently need a new global approach to safeguard critical Earth system regulating functions more effectively and comprehensively. The global commons framework is the closest example of an existing approach with the aim of governing biophysical systems on Earth upon which the world collectively depends. Derived during stable Holocene conditions, the global commons framework must now evolve in the light of new Anthropocene dynamics. This requires a fundamental shift from a focus only on governing shared resources beyond national jurisdiction, to one that secures critical functions of the Earth system irrespective of national boundaries. We propose a new framework-the planetary commons-which differs from the global commons framework by including not only globally shared geographic regions but also critical biophysical systems that regulate the resilience and state, and therefore livability, on Earth. The new planetary commons should articulate and create comprehensive stewardship obligations through Earth system governance aimed at restoring and strengthening planetary resilience and justice.

Multiplex analysis of inflammatory proteins associated with risk of coronary artery disease in type-1 diabetes patients.

BACKGROUND: Chronic uncontrolled hyperglycemia, a precursor to chronic low-grade inflammation, is a leading cause of coronary artery disease (CAD) due to plaque buildup in type-1 diabetes (T1D) patients. We evaluated levels of 22 inflammatory markers in cross-sectional serum samples from 1222 subjects to evaluate their potential as risk factors for CAD in T1D patients. HYPOTHESIS: Circulating levels of markers of inflammation may be the risk factors for incident CAD. METHODS: The T1D subjects were divided into two groups: those without CAD (n = 1107) and with CAD (n = 115). Serum levels of proteins were assayed using multiplex immunoassays on a Luminex Platform. Differences between the two groups were made by univariate analysis. Multivariate logistic regression was used to ascertain the potential of proteins as risk factors for CAD. Influence of age, duration of diabetes, sex, hypertension, and dyslipidemia was determined in a stepwise manner. Serum levels of 22 proteins were combined into a composite score using Ridge regression for risk-based stratification. RESULTS: Mean levels of CRP, IGFBP1, IGFBP2, insulin-like growth factors binding protein-6 (IGFBP6), MMP1, SAA, sTNFRI, and sTNFRII were elevated in CAD patients (n = 115) compared to T1D patients without CAD (nCAD, n = 1107). After adjusting for age, duration of diabetes, sex, hypertension, and dyslipidemia, higher levels of sTNFRI (odds ratio [OR] = 2.18, 1.1 × 10-3 ), sTNFRII (OR = 1.52, 1 × 10-2 ), and IGFBP6 (OR = 3.62, 1.8 × 10-3 ) were significantly associated with CAD. The composite score based on Ridge regression, was able to stratify CAD patients into low, medium, and high-risk groups. CONCLUSIONS: The results show activation of the TNF pathway in CAD patients. Evaluating these markers in serum can be a potential tool for identifying high-risk T1D patients for intensive anti-inflammatory therapeutic interventions.

The Legionella collagen-like protein employs a unique binding mechanism for the recognition of host glycosaminoglycans.

Bacterial adhesion is a fundamental process which enables colonisation of niche environments and is key for infection. However, in Legionella pneumophila, the causative agent of Legionnaires' disease, these processes are not well understood. The Legionella collagen-like protein (Lcl) is an extracellular peripheral membrane protein that recognises sulphated glycosaminoglycans (GAGs) on the surface of eukaryotic cells, but also stimulates bacterial aggregation in response to divalent cations. Here we report the crystal structure of the Lcl C-terminal domain (Lcl-CTD) and present a model for intact Lcl. Our data reveal that Lcl-CTD forms an unusual dynamic trimer arrangement with a positively charged external surface and a negatively charged solvent exposed internal cavity. Through Molecular Dynamics (MD) simulations, we show how the GAG chondroitin-4-sulphate associates with the Lcl-CTD surface via unique binding modes. Our findings show that Lcl homologs are present across both the Pseudomonadota and Fibrobacterota-Chlorobiota-Bacteroidota phyla and suggest that Lcl may represent a versatile carbohydrate binding mechanism.

Energetic driving force for LHCII clustering in plant membranes.

Plants capture and convert solar energy in a complex network of membrane proteins. Under high light, the luminal pH drops and induces a reorganization of the protein network, particularly clustering of the major light-harvesting complex (LHCII). While the structures of the network have been resolved in exquisite detail, the thermodynamics that control the assembly and reorganization had not been determined, largely because the interaction energies of membrane proteins have been inaccessible. Here, we describe a method to quantify these energies and its application to LHCII. Using single-molecule measurements, LHCII proteoliposomes, and statistical thermodynamic modeling, we quantified the LHCII-LHCII interaction energy as ~-5 kBT at neutral pH and at least -7 kBT at acidic pH. These values revealed an enthalpic thermodynamic driving force behind LHCII clustering. Collectively, this work captures the interactions that drive the organization of membrane protein networks from the perspective of equilibrium statistical thermodynamics, which has a long and rich tradition in biology.

Ovarian recurrence risk assessment using machine learning, clinical information, and serum protein levels to predict survival in high grade ovarian cancer.

In ovarian cancer, there is no current method to accurately predict recurrence after a complete response to chemotherapy. Here, we develop a machine learning risk score using serum proteomics for the prediction of early recurrence of ovarian cancer after initial treatment. The developed risk score was validated in an independent cohort with serum collected prospectively during the remission period. In the discovery cohort, patients scored as low-risk had a median time to recurrence (TTR) that was not reached at 10 years compared to 10.5 months (HR 4.66, p < 0.001) in high-risk patients. In the validation cohort, low-risk patients had a median TTR which was not reached compared to 4.7 months in high-risk patients (HR 4.67, p = 0.009). In advanced-stage patients with a CA125 < 10, low-risk patients had a median TTR of 68 months compared to 6 months in high-risk patients (HR 2.91, p = 0.02). The developed risk score was capable of distinguishing the duration of remission in ovarian cancer patients. This score may help guide maintenance therapy and develop innovative treatments in patients at risk at high-risk of recurrence.

High serum levels of inflammatory markers are associated with early recurrence in patients with high-grade serous ovarian cancer after platinum therapy.

OBJECTIVE: To determine if inflammatory biomarkers can predict the long-term outcome of platinum therapy in patients with high-grade serous ovarian cancer. METHODS: Women diagnosed with high-grade serous epithelial ovarian cancer (n = 70) at a single institution were enrolled in a prospective serum collection study between 2005 and 2020. Seventeen markers of inflammation and oxidative stress were measured in serum samples on a chemistry analyzer. Association was tested for serum levels with progression-free survival (PFS), time to recurrence (TTR), overall survival (OS), and time to death (TTD) using Cox proportional hazards and Kaplan-Meier curves. Patient survival was censored at 10 years. RESULTS: Higher serum levels of LDH were associated with worse PFS (HR 2.57, p = 0.028). High serum levels of BAP (HR 0.38, p = 0.025), GSP (HR 0.40, p = 0.040), HDL-c (HR 0.27, p = 0.002), and MG (HR 0.36, p = 0.017) were associated with improved PFS. Higher expression of LDH was associated with worse OS (HR 2.16, p = 0.023). Higher levels of CK.nac (HR 0.39, p = 0.033) and HDL-c (HR 0.35, p = 0.029) were associated with improved OS. Similar outcomes were found with TTR and TTD analyses. CONCLUSION: General inflammatory biomarkers may serve as a guide for prognosis and treatment benefit. Future studies needed to further define their role in predicting prognosis or how these markers may affect response to therapy.

Earth beyond six of nine planetary boundaries.

This planetary boundaries framework update finds that six of the nine boundaries are transgressed, suggesting that Earth is now well outside of the safe operating space for humanity. Ocean acidification is close to being breached, while aerosol loading regionally exceeds the boundary. Stratospheric ozone levels have slightly recovered. The transgression level has increased for all boundaries earlier identified as overstepped. As primary production drives Earth system biosphere functions, human appropriation of net primary production is proposed as a control variable for functional biosphere integrity. This boundary is also transgressed. Earth system modeling of different levels of the transgression of the climate and land system change boundaries illustrates that these anthropogenic impacts on Earth system must be considered in a systemic context.

Phytoplankton diversity explained by connectivity across a mesoscale frontal system in the open ocean.

Phytoplankton community composition is important in establishing ecosystem structure and function. Intuitively, we recognize that water movements must be important for modifying spatial gradients and plankton diversity. However, identifying boundaries and exchange between habitats in the open ocean is not straightforward. Here, we use the abundance of nine phytoplankton species closely sampled in a mesoscale frontal system in the northeastern North Sea as a proxy for community composition and explore the relationship between phytoplankton biogeography and transport patterns. Subsurface community distributions could be related to modeled patterns in water movement. A methodology for analyzing pelagic diversity that includes a representation of plankton community composition and an Eulerian connectivity tracer was developed, and the relative importance of connectivity and geographical distance for phytoplankton species composition analyzed. The connectivity tracer identifies timescales and dispersal barriers in the open ocean. Connectivity was found to be superior in explaining pelagic plankton diversity and found to be a prerequisite for understanding the pelagic phytoplankton composition. This approach is a valuable tool for establishing the link between ocean transports, ecosystem structure and biodiversity and for informing the placement of marine protected areas.

William Steffen (1947-2023).

Earth system scientist with passion for people and planet.

Sequential Two-Photon Delayed Fluorescence Anisotropy for Macromolecular Size Determination.

Time-resolved fluorescence anisotropy (FA) uses the fluorophore depolarization rate to report on rotational diffusion, conformation changes, and intermolecular interactions in solution. Although FA is a rapid, sensitive, and nondestructive tool for biomolecular interaction studies, the short (∼ns) fluorescence lifetime of typical dyes largely prevents the application of FA on larger macromolecular species and complexes. By using triplet shelving and recovery of optical excitation, we introduce optically activated delayed fluorescence anisotropy (OADFA) measurements using sequential two-photon excitation, effectively stretching fluorescence anisotropy measurement times from the nanosecond scale to hundreds of microseconds. We demonstrate this scheme for measuring slow depolarization processes of large macromolecular complexes, derive a quantitative rate model, and perform Monte Carlo simulations to describe the depolarization process of OADFA at the molecular level. This setup has great potential to enable future biomacromolecular and colloidal studies.

Thermodynamic determination of RNA duplex stability in magnesium solutions.

The prediction of RNA secondary structure and thermodynamics from sequence relies on free energy minimization and nearest neighbor parameters. Currently, algorithms used to make these predictions are based on parameters from optical melting studies performed in 1 M NaCl. However, many physiological and biochemical buffers containing RNA include much lower concentrations of monovalent cations and the presence of divalent cations. In order to improve these algorithms, thermodynamic data was previously collected for RNA duplexes in solutions containing 71, 121, 221, and 621 mM Na+. From this data, correction factors for free energy (ΔG°37) and melting temperature (Tm) were derived. Despite these newly derived correction factors for sodium, the stabilizing effects of magnesium have been ignored. Here, the same RNA duplexes were melted in solutions containing 0.5, 1.5, 3.0, and 10.0 mM Mg2+ in the absence of monovalent cations. Correction factors for Tm and ΔG°37 were derived to scale the current parameters to a range of magnesium concentrations. The Tm correction factor predicts the melting temperature within 1.2°C, and the ΔG°37 correction factor predicts the free energy within 0.30 kcalmol. These newly derived magnesium correction factors can be incorporated into algorithms that predict RNA secondary structure and stability from sequence.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma.

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

Use of a glycomics array to establish the anti-carbohydrate antibody repertoire in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease, characterized by the presence of autoantibodies to protein and non-protein antigens. Here we report the identification of specific anti-carbohydrate antibodies (ACAs) that are associated with pathogenesis and progression to T1D. We compare circulatory levels of ACAs against 202 glycans in a cross-sectional cohort of T1D patients (n = 278) and healthy controls (n = 298), as well as in a longitudinal cohort (n = 112). We identify 11 clusters of ACAs associated with glycan function class. Clusters enriched for aminoglycosides, blood group A and B antigens, glycolipids, ganglio-series, and O-linked glycans are associated with progression to T1D. ACAs against gentamicin and its related structures, G418 and sisomicin, are also associated with islet autoimmunity. ACAs improve discrimination of T1D status of individuals over a model with only clinical variables and are potential biomarkers for T1D.

Development of a Single Molecule Counting Assay to Differentiate Chromophobe Renal Cancer and Oncocytoma in Clinics.

Malignant chromophobe renal cancer (chRCC) and benign oncocytoma (RO) are two renal tumor types difficult to differentiate using histology and immunohistochemistry-based methods because of their similarity in appearance. We previously developed a transcriptomics-based classification pipeline with "Chromophobe-Oncocytoma Gene Signature" (COGS) on a single-molecule counting platform. Renal cancer patients (n = 32, chRCC = 17, RO = 15) were recruited from Augusta University Medical Center (AUMC). Formalin-fixed paraffin-embedded (FFPE) blocks from their excised tumors were collected. We created a custom single-molecule counting code set for COGS to assay RNA from FFPE blocks. Utilizing hematoxylin-eosin stain, pathologists were able to correctly classify these tumor types (91.8%). Our unsupervised learning with UMAP (Uniform manifold approximation and projection, accuracy = 0.97) and hierarchical clustering (accuracy = 1.0) identified two clusters congruent with their histology. We next developed and compared four supervised models (random forest, support vector machine, generalized linear model with L2 regularization, and supervised UMAP). Supervised UMAP has shown to classify all the cases correctly (sensitivity = 1, specificity = 1, accuracy = 1) followed by random forest models (sensitivity = 0.84, specificity = 1, accuracy = 1). This pipeline can be used as a clinical tool by pathologists to differentiate chRCC from RO.

Spatially differentiated marine eutrophication method for absolute environmental sustainability assessments.

Marine eutrophication and hypoxia caused by excess nutrient availability is a growing environmental problem. In this study, we explore marine nitrogen enrichment in the context of Absolute Environmental Sustainability Assessment (AESA), a method combining life cycle assessment (LCA) with environmental boundaries aiming to compare environmental impacts from an activity (product or system) with the safe operating space (SOS) for the activity. Specifically, we aim to increase the spatial resolution and improve life cycle impact assessment (LCIA) models for marine eutrophication for use in AESAs. By estimating a proxy of the areal extent of eutrophication and hypoxia in coastal large marine ecosystems (LME), we increased model resolution from 66 LMEs in the original LCIA method to 289 coastal LME subsegments and updated relevant LME parameters to the new scale (residence time, bottom water volume, reference O2 concentration, primary production rates and depths). The new method was tested and validated by comparing the global and spatially differentiated occupation of SOS by global nitrogen emissions with observations and it showed an improved ability to identify critical areas where the SOS is exceeded, in accordance with observations of hypoxic events. Despite limitations such as the estimation of benthic zone volume and low spatial differentiation of environmental boundaries, the method can be used by AESA and LCA practitioners wishing to assess the impact of nitrogen release on marine eutrophication with a higher and more relevant spatial resolution.