Molecular signatures of antibody responses derived from a systems biology study of five human vaccines.

Many vaccines induce protective immunity via antibodies. Systems biology approaches have been used to determine signatures that can be used to predict vaccine-induced immunity in humans, but whether there is a 'universal signature' that can be used to predict antibody responses to any vaccine is unknown. Here we did systems analyses of immune responses to the polysaccharide and conjugate vaccines against meningococcus in healthy adults, in the broader context of published studies of vaccines against yellow fever virus and influenza virus. To achieve this, we did a large-scale network integration of publicly available human blood transcriptomes and systems-scale databases in specific biological contexts and deduced a set of transcription modules in blood. Those modules revealed distinct transcriptional signatures of antibody responses to different classes of vaccines, which provided key insights into primary viral, protein recall and anti-polysaccharide responses. Our results elucidate the early transcriptional programs that orchestrate vaccine immunity in humans and demonstrate the power of integrative network modeling.

The fate of carbon in a mature forest under carbon dioxide enrichment.

Atmospheric carbon dioxide enrichment (eCO2) can enhance plant carbon uptake and growth1-5, thereby providing an important negative feedback to climate change by slowing the rate of increase of the atmospheric CO2 concentration6. Although evidence gathered from young aggrading forests has generally indicated a strong CO2 fertilization effect on biomass growth3-5, it is unclear whether mature forests respond to eCO2 in a similar way. In mature trees and forest stands7-10, photosynthetic uptake has been found to increase under eCO2 without any apparent accompanying growth response, leaving the fate of additional carbon fixed under eCO2 unclear4,5,7-11. Here using data from the first ecosystem-scale Free-Air CO2 Enrichment (FACE) experiment in a mature forest, we constructed a comprehensive ecosystem carbon budget to track the fate of carbon as the forest responded to four years of eCO2 exposure. We show that, although the eCO2 treatment of +150 parts per million (+38 per cent) above ambient levels induced a 12 per cent (+247 grams of carbon per square metre per year) increase in carbon uptake through gross primary production, this additional carbon uptake did not lead to increased carbon sequestration at the ecosystem level. Instead, the majority of the extra carbon was emitted back into the atmosphere via several respiratory fluxes, with increased soil respiration alone accounting for half of the total uptake surplus. Our results call into question the predominant thinking that the capacity of forests to act as carbon sinks will be generally enhanced under eCO2, and challenge the efficacy of climate mitigation strategies that rely on ubiquitous CO2 fertilization as a driver of increased carbon sinks in global forests.

4'-Fluorouridine mitigates lethal infection with pandemic human and highly pathogenic avian influenza viruses.

Influenza outbreaks are associated with substantial morbidity, mortality and economic burden. Next generation antivirals are needed to treat seasonal infections and prepare against zoonotic spillover of avian influenza viruses with pandemic potential. Having previously identified oral efficacy of the nucleoside analog 4'-Fluorouridine (4'-FlU, EIDD-2749) against SARS-CoV-2 and respiratory syncytial virus (RSV), we explored activity of the compound against seasonal and highly pathogenic influenza (HPAI) viruses in cell culture, human airway epithelium (HAE) models, and/or two animal models, ferrets and mice, that assess IAV transmission and lethal viral pneumonia, respectively. 4'-FlU inhibited a panel of relevant influenza A and B viruses with nanomolar to sub-micromolar potency in HAE cells. In vitro polymerase assays revealed immediate chain termination of IAV polymerase after 4'-FlU incorporation, in contrast to delayed chain termination of SARS-CoV-2 and RSV polymerase. Once-daily oral treatment of ferrets with 2 mg/kg 4'-FlU initiated 12 hours after infection rapidly stopped virus shedding and prevented transmission to untreated sentinels. Treatment of mice infected with a lethal inoculum of pandemic A/CA/07/2009 (H1N1)pdm09 (pdmCa09) with 4'-FlU alleviated pneumonia. Three doses mediated complete survival when treatment was initiated up to 60 hours after infection, indicating a broad time window for effective intervention. Therapeutic oral 4'-FlU ensured survival of animals infected with HPAI A/VN/12/2003 (H5N1) and of immunocompromised mice infected with pdmCa09. Recoverees were protected against homologous reinfection. This study defines the mechanistic foundation for high sensitivity of influenza viruses to 4'-FlU and supports 4'-FlU as developmental candidate for the treatment of seasonal and pandemic influenza.

Plant Silicon Defences Suppress Herbivore Performance, but Mode of Feeding Is Key.

The performance of herbivorous animals depends on the nutritional and defensive traits of the plants they consume. The uptake and deposition of biogenic silicon in plant tissues is arguably the most basic and ubiquitous anti-herbivore defence used by plants, especially grasses. We conducted meta-analyses of 150 studies reporting how vertebrate and invertebrate herbivores performed when feeding on silicon-rich plants relative to those feeding on low-silicon plants. Silicon levels were 52% higher and 32% more variable in silicon-rich plants compared to plants with low silicon, which resulted in an overall 33% decline in herbivore performance. Fluid-feeding herbivore performance was less adversely impacted (-14%) than tissue-chewing herbivores, including mammals (-45%), chewing arthropods (-33%) and plant-boring arthropods (-39%). Fluid-feeding arthropods with a wide diet breadth or those feeding on perennial plant species were mostly unaffected by silicon defences. Unlike many other plant defences, where diet specialisation often helps herbivores overcome their effects, silicon negatively impacts chewing herbivores regardless of diet breadth. We conclude that silicon defences primarily target chewing herbivores and impact vertebrate and invertebrate herbivores to a similar degree.

Identification of motifs and mechanisms for lipid droplet targeting of the lipolytic inhibitors G0S2 and HIG2.

G0S2 and HIG2 are two selective inhibitors of ATGL (also known as PNPLA2), the key enzyme for intracellular lipolysis. Whereas G0S2 regulates triglyceride (TG) mobilization in adipocytes and hepatocytes, HIG2 functions to enhance intracellular TG accumulation under hypoxic conditions. A homologous hydrophobic domain (HD) is shared by G0S2 and HIG2 (also known as HILPDA) for binding to ATGL. However, the determinants of their lipid droplet (LD) localization are unknown. Here, we study how G0S2 and HIG2 are targeted to LDs, and identify both ATGL-independent and -dependent mechanisms. Structural prediction and studies in cells reveal that ATGL-independent localization of G0S2 to both the endoplasmic reticulum (ER) and LDs is mediated by a hairpin structure consisting of two hydrophobic sequences. Positively charged residues in the hinge region play a crucial role in sorting G0S2, which initially localizes to ER, to LDs. Interestingly, the role of these positive charges becomes dispensable when ATGL is co-expressed. In comparison, HIG2, which lacks a similar hairpin structure, is dependent on ATGL for its full LD targeting. Thus, our studies identify specific structural features and mechanisms for mediating accumulation of these two ATGL inhibitors on LDs.

Accelerated cardiac cine with spatio-coil regularized deep learning reconstruction.

PURPOSE: To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization and multichannel k-space data consistency for accelerated cine imaging. METHODS: This study proposes a Spatio-Coil Regularized DL (SCR-DL) approach for iterative deep learning reconstruction incorporating multicoil information in data consistency and regularizer. SCR-DL uses shift-invariant convolutional kernels to interpolate missing k-space lines and reconstruct individual coil images, followed by a regularizer that operates simultaneously across spatial and coil dimensions using learned image priors. At 8-fold acceleration, SCR-DL was compared with Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA), sensitivity encoding (SENSE)-based DL and spatio-temporal regularized (STR)-DL reconstruction. In the retrospective undersampled cine, images were quantitatively evaluated using normalized mean square error (NMSE) and structural similarity index measure (SSIM). Additionally, agreement for left-ventricular ejection fraction and left-ventricular mass were assessed using prospectively accelerated cine images at 2-fold and 8-fold accelerations. RESULTS: The SCR-DL algorithm successfully reconstructed highly accelerated cine images. SCR-DL had significant improvements in NMSE (0.03 ± 0.02) and SSIM (91.4% ± 2.7%) compared with GRAPPA (NMSE: 0.09 ± 0.04, SSIM: 69.9% ± 11.1%; p < 0.001), SENSE-DL (NMSE: 0.07 ± 0.04, SSIM: 86.9% ± 3.2%; p < 0.001), and STR-DL (NMSE: 0.04 ± 0.03, SSIM: 90.0% ± 2.5%; p < 0.001) with retrospective undersampled cine. Despite the 3-fold reduction in scan time, there was no difference between left-ventricular ejection fraction (59.8 ± 4.5 vs. 60.8 ± 4.8, p = 0.46) or left-ventricular mass (73.6 ± 19.4 g vs. 73.2 ± 19.7 g, p = 0.95) between R = 2 and R = 8 prospectively accelerated cine images. CONCLUSIONS: SCR-DL enabled highly accelerated cardiac cine imaging, significantly reducing breath-hold time. Compared with GRAPPA or SENSE-DL, images reconstructed with SCR-DL showed superior NMSE and SSIM.

Accelerated Chemical Shift Encoded Cardiac MRI with Use of Resolution Enhancement Network.

BACKGROUND: Cardiovascular magnetic resonance (CMR) chemical shift encoding (CSE) enables myocardial fat imaging. We sought to develop a deep learning network (FastCSE) to accelerate CSE. METHODS: FastCSE was built on a super-resolution generative adversarial network extended to enhance complex-valued image sharpness. FastCSE enhances each echo image independently before water-fat separation. FastCSE was trained with retrospectively identified cines from 1519 patients (56 ± 16 years; 866 men) referred for clinical 3T CMR. In a prospective study of 16 participants (58 ± 19 years; 7 females) and 5 healthy individuals (32 ± 17 years; 5 females), dual-echo CSE images were collected with 1.5 × 1.5mm2, 2.5 × 1.5 mm2, and 3.8 × 1.9mm2 resolution using generalized autocalibrating partially parallel acquisition (GRAPPA). FastCSE was applied to images collected with resolution of 2.5 × 1.5mm2 and 3.8 × 1.9 mm2 to restore sharpness. Fat images obtained from two-point Dixon reconstruction were evaluated using a quantitative blur metric and analyzed with 5-way analysis of variance. RESULTS: FastCSE successfully reconstructed CSE images inline. FastCSE acquisition, with a resolution of 2.5 × 1.5mm² and 3.8 × 1.9 mm², reduced the number of breath-holds without impacting visualization of fat by approximately 1.5-fold and 3-fold compared to GRAPPA acquisition with a resolution of 1.5 × 1.5 mm², from 3.0 ± 0.8 breath-holds to 2.0 ± 0.2 and 1.1 ± 0.4 breath-holds, respectively. FastCSE improved image sharpness and removed ringing artifacts in GRAPPA fat images acquired with a resolution of 2.5 × 1.5 mm2 (0.31 ± 0.03 vs. 0.35 ± 0.04, P < 0.001) and 3.8 × 1.9 mm2 (0.31 ± 0.03 vs. 0.42 ± 0.06, P < 0.001). Blurring in FastCSE images was similar to blurring in images with 1.5 × 1.5 mm² resolution (0.32 ±0.03 vs. 0.31 ± 0.03, P = 0.78; 0.32 ± 0.03 vs. 0.31 ± 0.03, P = 0.90). CONCLUSION: We showed that a deep learning-accelerated CSE technique based on complex-valued resolution enhancement can reduce the number of breath-holds in CSE imaging without impacting the visualization of fat. FastCSE showed similar image sharpness compared to a standardized parallel imaging method.

Chronic alcohol use primes bronchial cells for altered inflammatory response and barrier dysfunction during SARS-CoV-2 infection.

Alcohol use disorder (AUD) is a significant public health concern and people with AUD are more likely to develop severe acute respiratory distress syndrome (ARDS) in response to respiratory infections. To examine whether AUD was a risk factor for more severe outcome in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, we examined early responses to infection using cultured differentiated bronchial epithelial cells derived from brushings obtained from people with AUD or without AUD. RNA-seq analysis of uninfected cells determined that AUD cells were enriched for expression of epidermal genes as compared with non-AUD cells. Bronchial epithelial cells from patients with AUD showed a significant decrease in barrier function 72 h postinfection, as determined by transepithelial electrical resistance. In contrast, barrier function of non-AUD cells was enhanced 72 h after SARS-CoV-2 infection. AUD cells showed claudin-7 that did not colocalize with zonula occludens-1 (ZO-1), indicative of disorganized tight junctions. However, both AUD and non-AUD cells showed decreased ß-catenin expression following SARS-CoV-2 infection. To determine the impact of AUD on the inflammatory response to SARS-CoV-2 infection, cytokine secretion was measured by multiplex analysis. SARS-CoV-2-infected AUD bronchial cells had enhanced secretion of multiple proinflammatory cytokines including TNFα, IL-1ß, and IFNγ as opposed to non-AUD cells. In contrast, secretion of the barrier-protective cytokines epidermal growth factor (EGF) and granulocyte macrophage-colony stimulating factor (GM-CSF) was enhanced for non-AUD bronchial cells. Taken together, these data support the hypothesis that AUD is a risk factor for COVID-19, where alcohol primes airway epithelial cells for increased inflammation and increased barrier dysfunction and increased inflammation in response to infection by SARS-CoV-2.NEW & NOTEWORTHY Alcohol use disorder (AUD) is a significant risk factor for severe acute respiratory distress syndrome. We found that AUD causes a phenotypic shift in gene expression in human bronchial epithelial cells, enhancing expression of epidermal genes. AUD cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had higher levels of proinflammatory cytokine secretion and barrier dysfunction not present in infected non-AUD cells, consistent with increased early COVID-19 severity due to AUD.

HILPDA promotes NASH-driven HCC development by restraining intracellular fatty acid flux in hypoxia.

BACKGROUND & AIMS: The prevalence of non-alcoholic steatohepatitis (NASH)-driven hepatocellular carcinoma (HCC) is rising rapidly, yet its underlying mechanisms remain unclear. Herein, we aim to determine the role of hypoxia-inducible lipid droplet associated protein (HILPDA)/hypoxia-inducible gene 2 (HIG2), a selective inhibitor of intracellular lipolysis, in NASH-driven HCC. METHODS: The clinical significance of HILPDA was assessed in human NASH-driven HCC specimens by immunohistochemistry and transcriptomics analyses. The oncogenic effect of HILPDA was assessed in human HCC cells and in 3D epithelial spheroids upon exposure to free fatty acids and either normoxia or hypoxia. Lipidomics profiling of wild-type and HILPDA knockout HCC cells was assessed via shotgun and targeted approaches. Wild-type (Hilpdafl/fl) and hepatocyte-specific Hilpda knockout (HilpdaΔHep) mice were fed a Western diet and high sugar in drinking water while receiving carbon tetrachloride to induce NASH-driven HCC. RESULTS: In patients with NASH-driven HCC, upregulated HILPDA expression is strongly associated with poor survival. In oxygen-deprived and lipid-loaded culture conditions, HILPDA promotes viability of human hepatoma cells and growth of 3D epithelial spheroids. Lack of HILPDA triggered flux of polyunsaturated fatty acids to membrane phospholipids and of saturated fatty acids to ceramide synthesis, exacerbating lipid peroxidation and apoptosis in hypoxia. The apoptosis induced by HILPDA deficiency was reversed by pharmacological inhibition of ceramide synthesis. In our experimental mouse model of NASH-driven HCC, HilpdaΔHep exhibited reduced hepatic steatosis and tumorigenesis but increased oxidative stress in the liver. Single-cell analysis supports a dual role of hepatic HILPDA in protecting HCC cells and facilitating the establishment of a pro-tumorigenic immune microenvironment in NASH. CONCLUSIONS: Hepatic HILPDA is a pivotal oncometabolic factor in the NASH liver microenvironment and represents a potential novel therapeutic target. IMPACT AND IMPLICATIONS: Non-alcoholic steatohepatitis (NASH, chronic metabolic liver disease caused by buildup of fat, inflammation and damage in the liver) is emerging as the leading risk factor and the fastest growing cause of hepatocellular carcinoma (HCC), the most common form of liver cancer. While curative therapeutic options exist for HCC, it frequently presents at a late stage when such options are no longer effective and only systemic therapies are available. However, systemic therapies are still associated with poor efficacy and some side effects. In addition, no approved drugs are available for NASH. Therefore, understanding the underlying metabolic alterations occurring during NASH-driven HCC is key to identifying new cancer treatments that target the unique metabolic needs of cancer cells.

Radiation necrosis or tumor progression? A review of the radiographic modalities used in the diagnosis of cerebral radiation necrosis.

PURPOSE: Cerebral radiation necrosis is a complication of radiation therapy that can be seen months to years following radiation treatment. Differentiating radiation necrosis from tumor progression on standard magnetic resonance imaging (MRI) is often difficult and advanced imaging techniques may be needed to make an accurate diagnosis. The purpose of this article is to review the imaging modalities used in differentiating radiation necrosis from tumor progression following radiation therapy for brain metastases. METHODS: We performed a review of the literature addressing the radiographic modalities used in the diagnosis of radiation necrosis. RESULTS: Differentiating radiation necrosis from tumor progression remains a diagnostic challenge and advanced imaging modalities are often required to make a definitive diagnosis. If diagnostic uncertainty remains following conventional imaging, a multi-modality diagnostic approach with perfusion MRI, magnetic resonance spectroscopy (MRS), positron emission tomography (PET), single photon emission spectroscopy (SPECT), and radiomics may be used to improve diagnosis. CONCLUSION: Several imaging modalities exist to aid in the diagnosis of radiation necrosis. Future studies developing advanced imaging techniques are needed.

18F-fluciclovine PET/CT to distinguish radiation necrosis from tumor progression for brain metastases treated with radiosurgery: results of a prospective pilot study.

PURPOSE: Distinguishing radiation necrosis from tumor progression among patients with brain metastases previously treated with stereotactic radiosurgery represents a common diagnostic challenge. We performed a prospective pilot study to determine whether PET/CT with 18F-fluciclovine, a widely available amino acid PET radiotracer, repurposed intracranially, can accurately diagnose equivocal lesions. METHODS: Adults with brain metastases previously treated with radiosurgery presenting with a follow-up tumor-protocol MRI brain equivocal for radiation necrosis versus tumor progression underwent an 18F-fluciclovine PET/CT of the brain within 30 days. The reference standard for final diagnosis consisted of clinical follow-up until multidisciplinary consensus or tissue confirmation. RESULTS: Of 16 patients imaged from 7/2019 to 11/2020, 15 subjects were evaluable with 20 lesions (radiation necrosis, n = 16; tumor progression, n = 4). Higher SUVmax statistically significantly predicted tumor progression (AUC = 0.875; p = 0.011). Lesion SUVmean (AUC = 0.875; p = 0.018), SUVpeak (AUC = 0.813; p = 0.007), and SUVpeak-to-normal-brain (AUC = 0.859; p = 0.002) also predicted tumor progression, whereas SUVmax-to-normal-brain (p = 0.1) and SUVmean-to-normal-brain (p = 0.5) did not. Qualitative visual scores were significant predictors for readers 1 (AUC = 0.750; p < 0.001) and 3 (AUC = 0.781; p = 0.045), but not for reader 2 (p = 0.3). Visual interpretations were significant predictors for reader 1 (AUC = 0.898; p = 0.012) but not for reader 2 (p = 0.3) or 3 (p = 0.2). CONCLUSIONS: In this prospective pilot study of patients with brain metastases previously treated with radiosurgery presenting with a contemporary MRI brain with a lesion equivocal for radiation necrosis versus tumor progression, 18F-fluciclovine PET/CT repurposed intracranially demonstrated encouraging diagnostic accuracy, supporting the pursuit of larger clinical trials which will be necessary to establish diagnostic criteria and performance.

Artificial Intelligence Optical Biopsy for Evaluating the Functional State of Wounds.

INTRODUCTION: The clinical characterization of the functional status of active wounds in terms of their driving cellular and molecular biology remains a considerable challenge that currently requires excision via a tissue biopsy. In this pilot study, we use convolutional Siamese neural network (SNN) architecture to predict the functional state of a wound using digital photographs of wounds in a canine model of volumetric muscle loss (VML). METHODS: Digital images of VML injuries and tissue biopsies were obtained in a standardized fashion from an established canine model of VML. Gene expression profiles for each biopsy site were obtained using RNA sequencing. These profiles were converted to functional profiles by a manual review of validated gene ontology databases in which we determined a hierarchical representation of gene functions based on functional specificity. An SNN was trained to regress functional profile expression values, informed by an image segment showing the surface of a small tissue biopsy. RESULTS: The SNN was able to predict the functional expression of a range of functions based with error ranging from ∼5% to ∼30%, with functions that are most closely associated with the early state of wound healing to be those best-predicted. CONCLUSIONS: These initial results suggest promise for further research regarding this novel use of machine learning regression on medical images. The regression of functional profiles, as opposed to specific genes, both addresses the challenge of genetic redundancy and gives a deeper insight into the mechanistic configuration of a region of tissue in wounds.

A prospective Canadian gastroesophageal cancer database: What have we learned?

BACKGROUND: Minimal literature exists on outcomes for Canadian patients with gastroesophageal adenocarcinoma (GEA). The objective of our study was to establish a prospective clinical database to evaluate demographic characteristics, presentation and outcomes of patients with GEA. METHODS: Patients diagnosed with GEA were recruited from Jan. 30, 2017, to Aug. 30, 2020. Data collected included demographic characteristics, presentation, treatment and survival. A multivariable model for overall survival in patients treated with curative intent was created using sex, lymph node status, resection margin status, age and tumour location as variables. RESULTS: A total of 122 patients with adenocarcinoma of the stomach or gastroesophageal junction were included. Median age was 65 years (interquartile range [IQR] 59-74), 70% of patients were male and 26% were born outside of Canada. Median follow-up time was 14.5 (IQR 8.0-31.0) months. Following staging computed tomography scanning, 88% of patients were deemed to have potentially resectable disease. Eighty-one (76%) received staging laparoscopy and 74 (61%) were treated with curativeintent surgery. Forty-six (62%) patients had nodal metastases. The median number of nodes harvested was 22 (IQR 18-30). The R0 resection margin rate was 82%. The 3-year overall survival for patients who received curative-intent treatment was 63% and 38% for all patients. On multivariable analysis, female sex (hazard ratio [HR] 3.88, p = 0.01), positive nodal status (HR 3.58, p = 0.02), positive margins (HR 3.11, p = 0.03) and tumour location (HR 3.00, p = 0.03) were associated with decreased overall survival. CONCLUSION: Many of the patients with GEA in this study presented with advanced disease, and only 61% were offered curative-intent surgery. A prospective multicentre national GEA database is now being established.

Validation of a Novel Multitarget Blood Test Shows High Sensitivity to Detect Early Stage Hepatocellular Carcinoma.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Although biannual ultrasound surveillance with or without α-fetoprotein (AFP) testing is recommended for at-risk patients, sensitivity for early stage HCC, for which potentially curative treatments exist, is suboptimal. We conducted studies to establish the multitarget HCC blood test (mt-HBT) algorithm and cut-off values and to validate test performance in patients with chronic liver disease. METHODS: Algorithm development and clinical validation studies were conducted with participants in an international, multicenter, case-control study. Study subjects had underlying cirrhosis or chronic hepatitis B virus; HCC cases were diagnosed per the American Association for the Study of Liver Diseases criteria and controls were matched for age and liver disease etiology. Whole blood and serum were shipped to a central laboratory and processed while blinded to case/control status. An algorithm was developed for the mt-HBT, which incorporates methylation biomarkers (HOXA1, TSPYL5, and B3GALT6), AFP, and sex. RESULTS: In algorithm development, with 136 HCC cases (60% early stage) and 404 controls, the mt-HBT showed 72% sensitivity for early stage HCC at 88% specificity. Test performance was validated in an independent cohort of 156 HCC cases (50% early stage) and 245 controls, showing 88% overall sensitivity, 82% early stage sensitivity, and 87% specificity. Early stage sensitivity in clinical validation was significantly higher than AFP at 20 ng/mL or greater (40%; P < .0001) and GALAD (gender, age, Lens culinaris agglutinin-reactive AFP, AFP, and des-γ-carboxy-prothrombin score) of -0.63 or greater (71%; P = .03), although AFP and GALAD at these cut-off values had higher specificities (100% and 93%, respectively). CONCLUSIONS: The mt-HBT may significantly improve early stage HCC detection for patients undergoing HCC surveillance, a critical step to increasing curative treatment opportunities and reducing mortality. ClinicalTrials.gov number NCT03628651.

Elevated atmospheric CO2 changes defence allocation in wheat but herbivore resistance persists.

Predicting how plants allocate to different anti-herbivore defences in response to elevated carbon dioxide (CO2) concentrations is important for understanding future patterns of crop susceptibility to herbivory. Theories of defence allocation, especially in the context of environmental change, largely overlook the role of silicon (Si), despite it being the major anti-herbivore defence in the Poaceae. We demonstrated that elevated levels of atmospheric CO2 (e[CO2]) promoted plant growth by 33% and caused wheat (Triticum aestivum) to switch from Si (-19%) to phenolic (+44%) defences. Despite the lower levels of Si under e[CO2], resistance to the global pest Helicoverpa armigera persisted; relative growth rates (RGRs) were reduced by at least 33% on Si-supplied plants, irrespective of CO2 levels. RGR was negatively correlated with leaf Si concentrations. Mandible wear was c. 30% higher when feeding on Si-supplemented plants compared to those feeding on plants with no Si supply. We conclude that higher carbon availability under e[CO2] reduces silicification and causes wheat to increase concentrations of phenolics. However, Si supply, at all levels, suppressed the growth of H. armigera under both CO2 regimes, suggesting that shifts in defence allocation under future climate change may not compromise herbivore resistance in wheat.

Matrix Protein 2 Extracellular Domain-Specific Monoclonal Antibodies Are an Effective and Potentially Universal Treatment for Influenza A.

Influenza virus infection causes significant morbidity and mortality worldwide. Humans fail to make a universally protective memory immune response to influenza A. Hemagglutinin and Neuraminidase undergo antigenic drift and shift, resulting in new influenza A strains to which humans are naive. Seasonal vaccines are often ineffective and escape mutants have been reported to all treatments for influenza A. In the absence of a universal influenza A vaccine or treatment, influenza A will remain a significant threat to human health. The extracellular domain of the M2-ion channel (M2e) is an ideal antigenic target for a universal therapeutic agent, as it is highly conserved across influenza A serotypes, has a low mutation rate, and is essential for viral entry and replication. Previous M2e-specific monoclonal antibodies (M2e-MAbs) show protective potential against influenza A, however, they are either strain specific or have limited efficacy. We generated seven murine M2e-MAbs and utilized in vitro and in vivo assays to validate the specificity of our novel M2e-MAbs and to explore the universality of their protective potential. Our data shows our M2e-MAbs bind to M2e peptide, HEK cells expressing the M2 channel, as well as, influenza virions and MDCK-ATL cells infected with influenza viruses of multiple serotypes. Our antibodies significantly protect highly influenza A virus susceptible BALB/c mice from lethal challenge with H1N1 A/PR/8/34, pH1N1 A/CA/07/2009, H5N1 A/Vietnam/1203/2004, and H7N9 A/Anhui/1/2013 by improving survival rates and weight loss. Based on these results, at least four of our seven M2e-MAbs show strong potential as universal influenza A treatments.IMPORTANCE Despite a seasonal vaccine and multiple therapeutic treatments, Influenza A remains a significant threat to human health. The biggest obstacle is producing a vaccine or treatment for influenza A is their universality or efficacy against not only seasonal variances in the influenza virus, but also against all human, avian, and swine serotypes and, therefore, potential pandemic strains. M2e has huge potential as a target for a vaccine or treatment against influenza A. It is the most conserved external protein on the virus. Antibodies against M2e have made it to clinical trials, but not succeeded. Here, we describe novel M2e antibodies produced in mice that are not only protective at low doses, but that we extensively test to determine their universality and found to be cross protective against all strains tested. Additionally, our work begins to elucidate the critical role of isotype for an influenza A monoclonal antibody therapeutic.

Mechanical stress acclimation in plants: Linking hormones and somatic memory to thigmomorphogenesis.

A single event of mechanical stimulation is perceived by mechanoreceptors that transduce rapid transient signalling to regulate gene expression. Prolonged mechanical stress for days to weeks culminates in cellular changes that strengthen the plant architecture leading to thigmomorphogenesis. The convergence of multiple signalling pathways regulates mechanically induced tolerance to numerous biotic and abiotic stresses. Emerging evidence showed prolonged mechanical stimulation can modify the baseline level of gene expression in naive tissues, heighten gene expression, and prime disease resistance upon a subsequent pathogen encounter. The phenotypes of thigmomorphogenesis can persist throughout growth without continued stimulation, revealing somatic-stress memory. Epigenetic processes regulate TOUCH gene expression and could program transcriptional memory in differentiating cells to program thigmomorphogenesis. We discuss the early perception, gene regulatory and phytohormone pathways that facilitate thigmomorphogenesis and mechanical stress acclimation in Arabidopsis and other plant species. We provide insights regarding: (1) the regulatory mechanisms induced by single or prolonged events of mechanical stress, (2) how mechanical stress confers transcriptional memory to induce cross-acclimation to future stress, and (3) why thigmomorphogenesis might resemble an epigenetic phenomenon. Deeper knowledge of how prolonged mechanical stimulation programs somatic memory and primes defence acclimation could transform solutions to improve agricultural sustainability in stressful environments.

Stigma in Early-Stage Lung Cancer.

BACKGROUND: The phenomenon of lung cancer stigma has been firmly established in the literature. However, studies have predominantly focused on patients with advanced disease, whose experiences may differ from patients with earlier stage, surgically resectable lung cancer and an improved prognosis. PURPOSE: The objective of the study was to examine the stigma experienced in a Canadian population with early-stage, resectable lung cancer. METHODS: Patients with newly diagnosed lung cancer were enrolled at a tertiary thoracic surgery clinic. The 25-item Lung Cancer Stigma Inventory (LCSI) was self-administered by patients to quantitatively measure experiences of lung cancer stigma. LCSI results informed the development of a semi-structured focus group and individual interviews. RESULTS: Of the 53 participants completing the survey, 38 (72%) met established LCSI score threshold, indicating a clinically meaningful level of stigma. No significant relationship was found between total LCSI scores and any demographic variable. Analysis of qualitative data revealed multiple themes related to experiences of lung cancer stigma. The major themes were classified into four categories: impact of the association between lung cancer and smoking, societal attitudes and assumptions, personal choices in relation to diagnosis, and experiences related to care. CONCLUSIONS: A surgical population of patients with predominantly early-stage lung cancer experienced lung cancer stigma at a high incidence and a level similar to previously studied populations with more advanced disease. The qualitative results support the quantitative findings that respondents experienced more internal stigma than either perceived stigma from others or constrained disclosure related to their diagnosis.

Optical Biopsy Using a Neural Network to Predict Gene Expression From Photos of Wounds.

BACKGROUND: The clinical characterization of the biological status of complex wounds remains a considerable challenge. Digital photography provides a non-invasive means of obtaining wound information and is currently employed to assess wounds qualitatively. Advances in machine learning (ML) image processing provide a means of identifying "hidden" features in pictures. This pilot study trains a convolutional neural network (CNN) to predict gene expression based on digital photographs of wounds in a canine model of volumetric muscle loss (VML). MATERIALS AND METHODS: Images of volumetric muscle loss injuries and tissue biopsies were obtained in a canine model of VML. A CNN was trained to regress gene expression values as a function of the extracted image segment (color and spatial distribution). Performance of the CNN was assessed in a held-back test set of images using Mean Absolute Percentage Error (MAPE). RESULTS: The CNN was able to predict the gene expression of certain genes based on digital images, with a MAPE ranging from ∼10% to ∼30%, indicating the presence and identification of distinct, and identifiable patterns in gene expression throughout the wound. CONCLUSIONS: These initial results suggest promise for further research regarding this novel use of ML regression on medical images. Specifically, the use of CNNs to determine the mechanistic biological state of a VML wound could aid both the design of future mechanistic interventions and the design of trials to test those therapies. Future work will expand the CNN training and/or test set, with potential expansion to predicting functional gene modules.

Lead optimization of cathepsin K inhibitors for the treatment of Osteoarthritis.

Cathepsin K (Cat K) is a cysteine protease involved in bone remodeling. In addition to its role in bone biology, Cat K is upregulated in osteoclasts, chondrocytes and synoviocytes in osteoarthritic (OA) disease states making it a potential therapeutic target for disease-modifying OA. Starting from a prior preclinical compound, MK-1256, lead optimization efforts were carried out in the search for potent Cat K inhibitors with improved selectivity profiles with an emphasis on cathepsin F. Herein, we report the SAR studies which led to the discovery of the highly selective oxazole compound 23, which was subsequently shown to inhibit cathepsin K in vivo as measured by reduced levels of urinary C-telopeptide of collagen type I in dog.