Venom-inspired somatostatin receptor 4 (SSTR4) agonists as new drug leads for peripheral pain conditions.

Persistent pain affects one in five people worldwide, often with severely debilitating consequences. Current treatment options, which can be effective for mild or acute pain, are ill-suited for moderate-to-severe persistent pain, resulting in an urgent need for new therapeutics. In recent years, the somatostatin receptor 4 (SSTR 4 ), which is expressed in sensory neurons of the peripheral nervous system, has emerged as a promising target for pain relief. However, the presence of several closely related receptors with similar ligand-binding surfaces complicates the design of receptor-specific agonists. In this study, we report the discovery of a potent and selective SSTR 4 peptide, consomatin Fj1, derived from extensive venom gene datasets from marine cone snails. Consomatin Fj1 is a mimetic of the endogenous hormone somatostatin and contains a minimized binding motif that provides stability and drives peptide selectivity. Peripheral administration of synthetic consomatin Fj1 provided analgesia in mouse models of postoperative and neuropathic pain. Using structure-activity studies, we designed and functionally evaluated several Fj1 analogs, resulting in compounds with improved potency and selectivity. Our findings present a novel avenue for addressing persistent pain through the design of venom-inspired SSTR 4 -selective pain therapeutics. One Sentence Summary: Venom peptides from predatory marine mollusks provide new leads for treating peripheral pain conditions through a non-opioid target.

Key residues in the VDAC2-BAK complex can be targeted to modulate apoptosis.

BAK and BAX execute intrinsic apoptosis by permeabilising the mitochondrial outer membrane. Their activity is regulated through interactions with pro-survival BCL-2 family proteins and with non-BCL-2 proteins including the mitochondrial porin VDAC2. VDAC2 is important for bringing both BAK and BAX to mitochondria where they execute their apoptotic function. Despite this important function in apoptosis, while interactions with pro-survival family members are well characterised and have culminated in the development of drugs that target these interfaces to induce cancer cell apoptosis, the interaction between BAK and VDAC2 remains largely undefined. Deep scanning mutagenesis coupled with cysteine linkage identified key residues in the interaction between BAK and VDAC2. Obstructive labelling of specific residues in the BH3 domain or hydrophobic groove of BAK disrupted this interaction. Conversely, mutating specific residues in a cytosol-exposed region of VDAC2 stabilised the interaction with BAK and inhibited BAK apoptotic activity. Thus, this VDAC2-BAK interaction site can potentially be targeted to either inhibit BAK-mediated apoptosis in scenarios where excessive apoptosis contributes to disease or to promote BAK-mediated apoptosis for cancer therapy.

Infection with mpox virus via the genital mucosae increases shedding and transmission in the multimammate rat (Mastomys natalensis).

The 2022 mpox virus (MPXV) outbreak was sustained by human-to-human transmission; however, it is currently unclear which factors lead to sustained transmission of MPXV. Here we present Mastomys natalensis as a model for MPXV transmission after intraperitoneal, rectal, vaginal, aerosol and transdermal inoculation with an early 2022 human outbreak isolate (Clade IIb). Virus shedding and tissue replication were route dependent and occurred in the presence of self-resolving localized skin, lung, reproductive tract or rectal lesions. Mucosal inoculation via the rectal, vaginal and aerosol routes led to increased shedding, replication and a pro-inflammatory T cell profile compared with skin inoculation. Contact transmission was higher from rectally inoculated animals. This suggests that transmission might be sustained by increased susceptibility of the anal and genital mucosae for infection and subsequent virus release.

A bivalent Adenovirus-Vectored Vaccine induces a robust humoral response, but does not protect cynomolgus macaques against a lethal challenge with Sudan virus.

The most recent Sudan virus (SUDV) outbreak in Uganda was first detected in September 2022 and resulted in 164 laboratory-confirmed cases and 77 deaths. There are no approved vaccines against SUDV. Here, we investigated the protective efficacy of ChAdOx1-biEBOV in cynomolgus macaques using a prime or a prime-boost regimen. ChAdOx1-biEBOV is a replication-deficient simian adenovirus vector encoding SUDV and Ebola virus (EBOV) glycoproteins (GPs). Intramuscular vaccination induced SUDV and EBOV GP-specific IgG responses and neutralizing antibodies. Upon challenge with SUDV, vaccinated animals showed signs of disease like those observed in control animals, and no difference in survival outcomes were measured among all three groups. Viral load in blood samples and in tissue samples obtained after necropsy were not significantly different between groups. Overall, this study highlights the importance of evaluating vaccines in multiple animal models and demonstrates the importance of understanding protective efficacy in both animal models and human hosts.

T-cell help in the tumor microenvironment enhances rituximab-mediated NK-cell ADCC.

ABSTRACT: Rituximab (RTX) and other monoclonal antibodies (mAbs) that bind directly to malignant cells are of great clinical value but are not effective for all patients. A major mechanism of action of RTX is antibody-dependent cellular cytotoxicity (ADCC) mediated by natural killer (NK) cells. Prior in vitro studies in our laboratory demonstrated that T cells contribute to maintaining the viability and cytotoxic potential of NK cells activated by anti-CD20-coated target B cells. Here, we conducted studies using a novel mouse model and clinical correlative analysis to assess whether T-cell help contribute to RTX-mediated NK-cell ADCC in the tumor microenvironment (TME) in vivo. A humanized mouse model was developed using Raji lymphoma cells and normal donor peripheral blood mononuclear cells that allows for control of T-cell numbers in the lymphoma TME. In this model, NK-cell viability and CD16 and CD25 expression dropped after RTX in the absence of T cells but increased in the presence of T cells. RTX therapy was more effective when T cells were present and was ineffective when NK cells were depleted. In patients with indolent lymphoma, fine needle aspirates were obtained before and ∼1 week after treatment with a RTX-containing regimen. There was a strong correlation between CD4+ T cells as well as total T cells in the pretherapy TME and an increase in NK-cell CD16 and CD25 expression after RTX. We conclude that T-cell help in the TME enhances RTX-mediated NK-cell viability and ADCC.

In vivo delivery of engineered synthetic DNA-encoded SARS-CoV-2 monoclonal antibodies for pre-exposure prophylaxis in non-human primates.

COVID-19 remains a major public health concern. Monoclonal antibodies have received emergency use authorization (EUA) for pre-exposure prophylaxis against COVID-19 among high-risk groups for treatment of mild to moderate COVID-19. In addition to recombinant biologics, engineered synthetic DNA-encoded antibodies (DMAb) are an important strategy for direct in vivo delivery of protective mAb. A DMAb cocktail was synthetically engineered to encode the immunoglobulin heavy and light chains of two different two different Fc-engineered anti-SARS-CoV-2 antibodies. The DMAbs were designed to enhance in vivo expression and delivered intramuscularly to cynomolgus and rhesus macaques with a modified in vivo delivery regimen. Serum levels were detected in macaques, along with specific binding to SARS-CoV-2 spike receptor binding domain protein and neutralization of multiple SARS-CoV-2 variants of concern in pseudovirus and authentic live virus assays. Prophylactic administration was protective in rhesus macaques against signs of SARS-CoV-2 (USA-WA1/2020) associated disease in the lungs. Overall, the data support further study of DNA-encoded antibodies as an additional delivery mode for prevention of COVID-19 severe disease. These data have implications for human translation of gene-encoded mAbs for emerging infectious diseases and low dose mAb delivery against COVID-19.

The Precision Between Transcutaneous Carbon Dioxide Versus PaCO2 in Infants Undergoing Therapeutic Hypothermia.

BACKGROUND: Infants with hypoxic-ischemic encephalopathy are often treated with therapeutic hypothermia and high-frequency ventilation. Fluctuations in PaCO2 during therapeutic hypothermia are associated with poor neurodevelopmental outcomes. Transcutaneous CO2 monitors offer a noninvasive estimate of PaCO2 represented by transcutaneously measured partial pressure of carbon dioxide (PtcCO2 ). We aimed to assess the precision between PtcCO2 and PaCO2 values in neonates undergoing therapeutic hypothermia. METHODS: This was a retrospective chart review of 10 neonates who underwent therapeutic hypothermia requiring respiratory support over 2 y. A range of 2-27 simultaneous PtcCO2 and PaCO2 pairs of measurements per neonate were analyzed via linear mixed models and a Bland-Altman plot for multiple observations per neonate. RESULTS: A linear mixed-effect model demonstrated that PtcCO2 and PaCO2 (controlling for sex) were similar. The 95% CI of the mean difference ranged from -2.3 to 5.7 mm Hg (P = .41). However, precision was poor as the PtcCO2 ranged from > 18 mm Hg to < 13 mm Hg than PaCO2 values for 95% of observations. CONCLUSIONS: The neonates' PtcCO2 was as much as 18 mm Hg higher to 13 mm Hg lower than the PaCO2 95% of the time. Transcutaneous CO2 monitoring may not be a good trending tool, nor is it appropriate for estimating PaCO2 in patients undergoing therapeutic hypothermia.

Magnetic Resonance Imaging of Iron Metabolism with T2* Mapping Predicts an Enhanced Clinical Response to Pharmacologic Ascorbate in Patients with GBM.

PURPOSE: Pharmacologic ascorbate (P-AscH-) is hypothesized to be an iron (Fe)-dependent tumor-specific adjuvant to chemoradiation in treating glioblastoma (GBM). This study determined the efficacy of combining P-AscH- with radiation and temozolomide in a phase II clinical trial while simultaneously investigating a mechanism-based, noninvasive biomarker in T2* mapping to predict GBM response to P-AscH- in humans. PATIENTS AND METHODS: The single-arm phase II clinical trial (NCT02344355) enrolled 55 subjects, with analysis performed 12 months following the completion of treatment. Overall survival (OS) and progression-free survival (PFS) were estimated with the Kaplan-Meier method and compared across patient subgroups with log-rank tests. Forty-nine of 55 subjects were evaluated using T2*-based MRI to assess its utility as an Fe-dependent biomarker. RESULTS: Median OS was estimated to be 19.6 months [90% confidence interval (CI), 15.7-26.5 months], a statistically significant increase compared with historic control patients (14.6 months). Subjects with initial T2* relaxation < 50 ms were associated with a significant increase in PFS compared with T2*-high subjects (11.2 months vs. 5.7 months, P < 0.05) and a trend toward increased OS (26.5 months vs. 17.5 months). These results were validated in preclinical in vitro and in vivo model systems. CONCLUSIONS: P-AscH- combined with temozolomide and radiotherapy has the potential to significantly enhance GBM survival. T2*-based MRI assessment of tumor iron content is a prognostic biomarker for GBM clinical outcomes. See related commentary by Nabavizadeh and Bagley, p. 255.

Interferometric Imaging Using Shared Quantum Entanglement.

Quantum entanglement-based imaging promises significantly increased resolution by extending the spatial separation of optical collection apertures used in very-long-baseline interferometry for astronomy and geodesy. We report a tabletop entanglement-based interferometric imaging technique that utilizes two entangled field modes serving as a phase reference between two apertures. The spatial distribution of a simulated thermal light source is determined by interfering light collected at each aperture with one of the entangled fields and performing joint measurements. This experiment demonstrates the ability of entanglement to implement interferometric imaging.

Prioritization of Fluorescence In Situ Hybridization (FISH) Probes for Differentiating Primary Sites of Neuroendocrine Tumors with Machine Learning.

Determining neuroendocrine tumor (NET) primary sites is pivotal for patient care as pancreatic NETs (pNETs) and small bowel NETs (sbNETs) have distinct treatment approaches. The diagnostic power and prioritization of fluorescence in situ hybridization (FISH) assay biomarkers for establishing primary sites has not been thoroughly investigated using machine learning (ML) techniques. We trained ML models on FISH assay metrics from 85 sbNET and 59 pNET samples for primary site prediction. Exploring multiple methods for imputing missing data, the impute-by-median dataset coupled with a support vector machine model achieved the highest classification accuracy of 93.1% on a held-out test set, with the top importance variables originating from the ERBB2 FISH probe. Due to the greater interpretability of decision tree (DT) models, we fit DT models to ten dataset splits, achieving optimal performance with k-nearest neighbor (KNN) imputed data and a transformation to single categorical biomarker probe variables, with a mean accuracy of 81.4%, on held-out test sets. ERBB2 and MET variables ranked as top-performing features in 9 of 10 DT models and the full dataset model. These findings offer probabilistic guidance for FISH testing, emphasizing the prioritization of the ERBB2, SMAD4, and CDKN2A FISH probes in diagnosing NET primary sites.

Head and Neck Cancer Segmentation in FDG PET Images: Performance Comparison of Convolutional Neural Networks and Vision Transformers.

Convolutional neural networks (CNNs) have a proven track record in medical image segmentation. Recently, Vision Transformers were introduced and are gaining popularity for many computer vision applications, including object detection, classification, and segmentation. Machine learning algorithms such as CNNs or Transformers are subject to an inductive bias, which can have a significant impact on the performance of machine learning models. This is especially relevant for medical image segmentation applications where limited training data are available, and a model's inductive bias should help it to generalize well. In this work, we quantitatively assess the performance of two CNN-based networks (U-Net and U-Net-CBAM) and three popular Transformer-based segmentation network architectures (UNETR, TransBTS, and VT-UNet) in the context of HNC lesion segmentation in volumetric [F-18] fluorodeoxyglucose (FDG) PET scans. For performance assessment, 272 FDG PET-CT scans of a clinical trial (ACRIN 6685) were utilized, which includes a total of 650 lesions (primary: 272 and secondary: 378). The image data used are highly diverse and representative for clinical use. For performance analysis, several error metrics were utilized. The achieved Dice coefficient ranged from 0.833 to 0.809 with the best performance being achieved by CNN-based approaches. U-Net-CBAM, which utilizes spatial and channel attention, showed several advantages for smaller lesions compared to the standard U-Net. Furthermore, our results provide some insight regarding the image features relevant for this specific segmentation application. In addition, results highlight the need to utilize primary as well as secondary lesions to derive clinically relevant segmentation performance estimates avoiding biases.

Rapid single crystal growth via guest displacement from host-guest complexes.

The preparation of single crystals of sparingly soluble polycyclic aromatic compounds in MeCN is facilitated by solubilizing ionic host-guest complexation under otherwise poor solvent conditions. The guest is then crystallized within minutes through controlled guest displacement from the host via competitor equilibria, or over days through direct crystallization of the host-guest complex itself.

Microbial Communities in Gynecological Cancers and Their Association with Tumor Somatic Variation.

There are strong correlations between the microbiome and human disease, including cancer. However, very little is known about potential mechanisms associated with malignant transformation in microbiome-associated gynecological cancer, except for HPV-induced cervical cancer. Our hypothesis is that differences in bacterial communities in upper genital tract epithelium may lead to selection of specific genomic variation at the cellular level of these tissues that may predispose to their malignant transformation. We first assessed differences in the taxonomic composition of microbial communities and genomic variation between gynecologic cancers and normal samples. Then, we performed a correlation analysis to assess whether differences in microbial communities selected for specific single nucleotide variation (SNV) between normal and gynecological cancers. We validated these results in independent datasets. This is a retrospective nested case-control study that used clinical and genomic information to perform all analyses. Our present study confirms a changing landscape in microbial communities as we progress into the upper genital tract, with more diversity in lower levels of the tract. Some of the different genomic variations between cancer and controls strongly correlated with the changing microbial communities. Pathway analyses including these correlated genes may help understand the basis for how changing bacterial landscapes may lead to these cancers. However, one of the most important implications of our findings is the possibility of cancer prevention in women at risk by detecting altered bacterial communities in the upper genital tract epithelium.

Characteristics, Identification, Training, and Perception of Leaders in Respiratory Care.

BACKGROUND: Leadership is critical to high-functioning teams; however, data are lacking for what defines successful respiratory therapist (RT) leadership. Leaders need a wide range of skills to be successful, although the exact characteristics, behaviors, and accomplishments of successful RT leaders are unknown. We performed a survey of respiratory care leaders to evaluate different aspects of RT leadership. METHODS: We developed a survey of RT leaders to examine respiratory care leadership in a variety of professional settings. Different aspects of leadership and the relationships between perceptions of leadership and well-being were assessed. Data analysis was descriptive. RESULTS: We received 124 responses, with a response rate of 37%. Respondents had a median 22 y of RT experience, and 69% were in leadership positions. The most-important skills identified for potential leaders were critical thinking (90%) and people skills (88%). Self-initiated projects (82%), intradepartmental education (71%), and precepting (63%) were noted accomplishments. Reasons for exclusion from leadership included poor work ethic (94%), dishonesty (92%), difficulty getting along with others (89%), unreliable (90%), and not being a team player (86%). Most respondents (77%) agreed American Association for Respiratory Care membership be a requirement for leadership; however, 31% required membership. Integrity (71%) was noted consistently as a characteristic of successful leaders. There was no consensus for behaviors of successful versus unsuccessful leaders or what defines successful leadership. Ninety-five percent of leaders had received some leadership training. Respondents reported that well-being is affected by leadership, departmental culture, peers, and leaders with burnout; 34% of respondents felt people with burnout received good support at their institution, whereas 61% felt maintaining well-being is left to individuals. CONCLUSIONS: Critical thinking and people skills were the most-important skills for potential leaders. Limited consensus existed on characteristics, behaviors, and defined success of leaders. Most respondents agreed leadership influences well-being.

Enhancing Respiratory Therapists' Well-Being: Battling Burnout in Respiratory Care.

Burnout is a major problem in health care and is associated with adverse sequelae for patients, health care workers, and organizations. Burnout among respiratory therapists (RTs) is as high as 79% and is associated with poor or ineffective leadership, inadequate staffing, high work load, non-leadership position, and work environment. An understanding of burnout is necessary for both staff and leadership to ensure RT well-being. This narrative review will discuss the psychology of burnout, prevalence, drivers, mitigation strategies, and future directions for research.

Predictive power of deep-learning segmentation based prognostication model in non-small cell lung cancer.

Purpose: The study aims to create a model to predict survival outcomes for non-small cell lung cancer (NSCLC) after treatment with stereotactic body radiotherapy (SBRT) using deep-learning segmentation based prognostication (DESEP). Methods: The DESEP model was trained using imaging from 108 patients with NSCLC with various clinical stages and treatment histories. The model generated predictions based on unsupervised features learned by a deep-segmentation network from computed tomography imaging to categorize patients into high and low risk groups for overall survival (DESEP-predicted-OS), disease specific survival (DESEP-predicted-DSS), and local progression free survival (DESEP-predicted-LPFS). Serial assessments were also performed using auto-segmentation based volumetric RECISTv1.1 and computer-based unidimensional RECISTv1.1 patients was performed. Results: There was a concordance between the DESEP-predicted-LPFS risk category and manually calculated RECISTv1.1 (φ=0.544, p=0.001). Neither the auto-segmentation based volumetric RECISTv1.1 nor the computer-based unidimensional RECISTv1.1 correlated with manual RECISTv1.1 (p=0.081 and p=0.144, respectively). While manual RECISTv1.1 correlated with LPFS (HR=6.97,3.51-13.85, c=0.70, p<0.001), it could not provide insight regarding DSS (p=0.942) or OS (p=0.662). In contrast, the DESEP-predicted methods were predictive of LPFS (HR=3.58, 1.66-7.18, c=0.60, p<0.001), OS (HR=6.31, 3.65-10.93, c=0.71, p<0.001) and DSS (HR=9.25, 4.50-19.02, c=0.69, p<0.001). The promising results of the DESEP model were reproduced for the independent, external datasets of Stanford University, classifying survival and 'dead' group in their Kaplan-Meyer curves (p = 0.019). Conclusion: Deep-learning segmentation based prognostication can predict LPFS as well as OS, and DSS after SBRT for NSCLC. It can be used in conjunction with current standard of care, manual RECISTv1.1 to provide additional insights regarding DSS and OS in NSCLC patients receiving SBRT. Summary: While current standard of care, manual RECISTv1.1 correlated with local progression free survival (LPFS) (HR=6.97,3.51-13.85, c=0.70, p<0.001), it could not provide insight regarding disease specific survival (DSS) (p=0.942) or overall survival (OS) (p=0.662). In contrast, the deep-learning segmentation based prognostication (DESEP)-predicted methods were predictive of LPFS (HR=3.58, 1.66-7.18, c=0.60, p<0.001), OS (HR=6.31, 3.65-10.93, c=0.71, p<0.001) and DSS (HR=9.25, 4.50-19.02, c=0.69, p<0.001). DESEP can be used in conjunction with current standard of care, manual RECISTv1.1 to provide additional insights regarding DSS and OS in NSCLC patients.

The functional evolution of architecturally different plant geranyl diphosphate synthases from geranylgeranyl diphosphate synthase.

Terpenoids constitute the largest class of plant primary and secondary metabolites with a broad range of biological and ecological functions. They are synthesized from isopentenyl diphosphate and dimethylallyl diphosphate, which in plastids are condensed by geranylgeranyl diphosphate synthases (GGPPSs) to produce GGPP (C20) for diterpene biosynthesis and by geranyl diphosphate synthases (GPPSs) to form GPP (C10) for monoterpene production. Depending on the plant species, unlike homomeric GGPPSs, GPPSs exist as homo- and heteromers, the latter of which contain catalytically inactive GGPPS-homologous small subunits (SSUs) that can interact with GGPPSs. By combining phylogenetic analysis with functional characterization of GGPPS homologs from a wide range of photosynthetic organisms, we investigated how different GPPS architectures have evolved within the GGPPS protein family. Our results reveal that GGPPS gene family expansion and functional divergence began early in nonvascular plants, and that independent parallel evolutionary processes gave rise to homomeric and heteromeric GPPSs. By site-directed mutagenesis and molecular dynamics simulations, we also discovered that Leu-Val/Val-Ala pairs of amino acid residues were pivotal in the functional divergence of homomeric GPPSs and GGPPSs. Overall, our study elucidated an evolutionary path for the formation of GPPSs with different architectures from GGPPSs and uncovered the molecular mechanisms involved in this differentiation.

Protocol-Driven Initiation and Weaning of High-Flow Nasal Cannula for Patients With Bronchiolitis: A Quality Improvement Initiative.

OBJECTIVES: Bronchiolitis is the most common cause for nonelective infant hospitalization in the United States with increasing utilization of high-flow nasal cannula (HFNC). We standardized initiation and weaning of HFNC for bronchiolitis and quantified the impact on outcomes. Our specific aim was to reduce hospital and ICU length of stay (LOS) by 10% between two bronchiolitis seasons after implementation. DESIGN: A quality improvement (QI) project using statistical process control methodology. SETTING: Tertiary-care children's hospital with 24 PICU and 48 acute care pediatric beds. PATIENTS: Children less than 24 months old with bronchiolitis without other respiratory diagnoses or underlying cardiac, respiratory, or neuromuscular disorders between December 2017 and November 2018 (baseline), and December 2018 and February 2020 (postintervention). INTERVENTIONS: Interventions included development of an HFNC protocol with initiation and weaning guidelines, modification of protocol and respiratory assessment classification, education, and QI rounds with a focus on efficient HFNC weaning, transfer, and/or discharge. MEASUREMENTS AND MAIN RESULTS: A total of 223 children were included (96 baseline and 127 postintervention). The primary outcome metric, average LOS per patient, decreased from 4.0 to 2.8 days, and the average ICU LOS per patient decreased from 2.8 to 1.9 days. The secondary outcome metric, average HFNC treatment hours per patient, decreased from 44.0 to 36.3 hours. The primary and secondary outcomes met criteria for special cause variation. Balancing measures included ICU readmission rates, 30-day readmission rates, and adverse events, which were not different between the two periods. CONCLUSIONS: A standardized protocol for HFNC management for patients with bronchiolitis was associated with decreased hospital and ICU LOS, less time on HFNC, and no difference in readmissions or adverse events.

Density-dependent habitat selection alters drivers of population distribution in northern Yellowstone elk.

Although it is well established that density dependence drives changes in organismal abundance over time, relatively little is known about how density dependence affects variation in abundance over space. We tested the hypothesis that spatial trade-offs between food and safety can change the drivers of population distribution, caused by opposing patterns of density-dependent habitat selection (DDHS) that are predicted by the multidimensional ideal free distribution. We addressed this using winter aerial survey data of northern Yellowstone elk (Cervus canadensis) spanning four decades. Supporting our hypothesis, we found positive DDHS for food (herbaceous biomass) and negative DDHS for safety (openness and roughness), such that the primary driver of habitat selection switched from food to safety as elk density decreased from 9.3 to 2.0 elk/km2 . Our results demonstrate how population density can drive landscape-level shifts in population distribution, confounding habitat selection inference and prediction and potentially affecting community-level interactions.