Structural Determinants of Vibrio cholerae FeoB Nucleotide Promiscuity.

Ferrous iron (Fe2+) is required for the growth and virulence of many pathogenic bacteria, including Vibrio cholerae (Vc), the causative agent of the disease cholera. For this bacterium, Feo is the primary system that transports Fe2+ into the cytosol. FeoB, the main component of this system, is regulated by a soluble cytosolic domain termed NFeoB. Recent reanalysis has shown that NFeoBs can be classified as either GTP-specific or NTP-promiscuous, but the structural and mechanistic bases for these differences were not known. To explore this intriguing property of FeoB, we solved the X-ray crystal structures of VcNFeoB in both the apo and GDP-bound forms. Surprisingly, this promiscuous NTPase displayed a canonical NFeoB G-protein fold like GTP-specific NFeoBs. Using structural bioinformatics, we hypothesized that residues surrounding the nucleobase could be important for both nucleotide affinity and specificity. We then solved the X-ray crystal structures of N150T VcNFeoB in the apo and GDP-bound forms to reveal H-bonding differences surround the guanine nucleobase. Interestingly, isothermal titration calorimetry revealed similar binding thermodynamics of the WT and N150T proteins to guanine nucleotides, while the behavior in the presence of adenine nucleotides was dramatically different. AlphaFold models of VcNFeoB in the presence of ADP and ATP showed important conformational changes that contribute to nucleotide specificity among FeoBs. Combined, these results provide a structural framework for understanding FeoB nucleotide promiscuity, which could be an adaptive measure utilized by pathogens to ensure adequate levels of intracellular iron across multiple metabolic landscapes.

The Effect of Co-Morbid Psoriasis Diagnosis on Chronic Rhinosinusitis Immunopathology.

INTRODUCTION: Psoriasis is a papulosquamous condition characterized by type 1 (T1) inflammation, while chronic rhinosinusitis (CRS) concurrent with asthma is commonly a type 2 (T2) process. Since psoriasis is predictive for higher rates of CRS, our objective was to determine whether CRS with concurrent psoriasis would share its T1 pathogenic signature. In comparison to T1 CRS, a T2 process can be predicted by presence of more extensive sinus disease via Lund-MacKay score, reduced sense of smell, and greater concurrence of purulent drainage and pain/pressure. METHODS: Subjective measurements of CRS included the Sino-Nasal Outcome Test (SNOT-22) and objective measurements included Lund-MacKay sinus CT score and endoscopic scoring. Outcomes were compared with control subjects with CRS co-presenting with allergies, asthma, or aspirin-exacerbated respiratory disease (AERD). RESULTS: A total of 62 patients (12 CRS alone, 14 CRS/psoriasis, 12 CRS/AERD, 12 CRS/allergic asthmatic, 12 CRS/non-allergic asthmatic) were included. Comparative analysis utilizing χ2 revealed no significant differences in any factor between CRS/psoriatic patients and all other groups associated with T2 presentations. Specifically, psoriatic patients had comparable reductions in smell, similar complaints of pain/pressure, negligible purulent drainage/crusting, and comparable extent of disease on their CT scan, as well as similar blood eosinophilia. The only significant difference was in lack of productivity (p < 0.05) with trends toward reduced concentration, waking up tired, and lack of sleep parameters presumably related to systemic psoriatic manifestations. CONCLUSIONS: Despite the increased prevalence of CRS in psoriasis patients, our data suggest that when present, psoriasis does not predict the presence of a T1 process in the sinuses.

Challenges with the Synthesis of a Macrocyclic Thioether Peptide: From Milligram to Multigram Using Solid Phase Peptide Synthesis (SPPS).

We describe an optimization and scale-up of the 45-membered macrocyclic thioether peptide BMS-986189 utilizing solid-phase peptide synthesis (SPPS). Improvements to linear peptide isolation, macrocyclization, and peptide purification were demonstrated to increase the throughput and purification of material on scale and enabled the synthesis and purification of >60 g of target peptide. Taken together, not only these improvements resulted in a 28-fold yield increase from the original SPPS approach, but also the generality of this newly developed SPPS purification sequence has found application in the synthesis and purification of other macrocyclic thioether peptides.

Cutaneous manifestations of cystic fibrosis.

Cystic fibrosis (CF) is caused by a mutation in the Cystic fibrosis transmembrane conductance regulator (CFTR) gene, and features recurrent sinus and pulmonary infections, steatorrhea, and malnutrition. CF is associated with diverse cutaneous manifestations, including transient reactive papulotranslucent acrokeratoderma of the palms, nutrient deficiency dermatoses, and vasculitis. Rarely these are presenting symptoms of CF, prior to pulmonary or gastrointestinal sequelae. Cutaneous drug eruptions are also highly common in patients with CF (PwCF) given frequent antibiotic exposure. Finally, CFTR modulating therapy, which has revolutionized CF management, is associated with cutaneous side effects ranging from acute urticaria to toxic epidermal necrolysis. Recognition of dermatologic clinical manifestations of CF is important to appropriately care for PwCF. Dermatologists may play a significant role in the diagnosis and management of CF and associated skin complications.

Integrated monitoring and modeling to disentangle the complex spatio-temporal dynamics of urbanized streams under drought stress.

We have a poor understanding of how urban drainage and other engineered components interact with more natural hydrological processes in green and blue spaces to generate stream flow. This limits the scientific evidence base for predicting and mitigating the effects of future development of the built environment and climate change on urban water resources and their ecosystem services. Here, we synthesize > 20 years of environmental monitoring data to better understand the hydrological function of the 109-km2 Wuhle catchment, an important tributary of the river Spree in Berlin, Germany. More than half (56%) of the catchment is urbanized, leading to substantial flow path alterations. Young water from storm runoff and rapid subsurface flow provided around 20% of stream flow. However, most of it was generated by older groundwater (several years old), mainly recharged through the rural headwaters and non-urban green spaces. Recent drought years since 2018 showed that this base flow component has reduced in response to decreased recharge, causing deterioration in water quality and sections of the stream network to dry out. Attempts to integrate the understanding of engineered and natural processes in a traditional rainfall-runoff model were only partly successful due to uncertainties over the catchment area, effects of sustainable urban drainage, adjacent groundwater pumping, and limited conceptualization of groundwater storage dynamics. The study highlights the need for more extensive and coordinated monitoring and data collection in complex urban catchments and the use of these data in more advanced models of urban hydrology to enhance management.

Creating High-Quality Synthetic Health Data: Framework for Model Development and Validation.

BACKGROUND: Electronic health records are a valuable source of patient information that must be properly deidentified before being shared with researchers. This process requires expertise and time. In addition, synthetic data have considerably reduced the restrictions on the use and sharing of real data, allowing researchers to access it more rapidly with far fewer privacy constraints. Therefore, there has been a growing interest in establishing a method to generate synthetic data that protects patients' privacy while properly reflecting the data. OBJECTIVE: This study aims to develop and validate a model that generates valuable synthetic longitudinal health data while protecting the privacy of the patients whose data are collected. METHODS: We investigated the best model for generating synthetic health data, with a focus on longitudinal observations. We developed a generative model that relies on the generalized canonical polyadic (GCP) tensor decomposition. This model also involves sampling from a latent factor matrix of GCP decomposition, which contains patient factors, using sequential decision trees, copula, and Hamiltonian Monte Carlo methods. We applied the proposed model to samples from the MIMIC-III (version 1.4) data set. Numerous analyses and experiments were conducted with different data structures and scenarios. We assessed the similarity between our synthetic data and the real data by conducting utility assessments. These assessments evaluate the structure and general patterns present in the data, such as dependency structure, descriptive statistics, and marginal distributions. Regarding privacy disclosure, our model preserves privacy by preventing the direct sharing of patient information and eliminating the one-to-one link between the observed and model tensor records. This was achieved by simulating and modeling a latent factor matrix of GCP decomposition associated with patients. RESULTS: The findings show that our model is a promising method for generating synthetic longitudinal health data that is similar enough to real data. It can preserve the utility and privacy of the original data while also handling various data structures and scenarios. In certain experiments, all simulation methods used in the model produced the same high level of performance. Our model is also capable of addressing the challenge of sampling patients from electronic health records. This means that we can simulate a variety of patients in the synthetic data set, which may differ in number from the patients in the original data. CONCLUSIONS: We have presented a generative model for producing synthetic longitudinal health data. The model is formulated by applying the GCP tensor decomposition. We have provided 3 approaches for the synthesis and simulation of a latent factor matrix following the process of factorization. In brief, we have reduced the challenge of synthesizing massive longitudinal health data to synthesizing a nonlongitudinal and significantly smaller data set.

Systematic analysis of the transcriptional landscape of melanoma reveals drug-target expression plasticity.

Metastatic melanoma originates from melanocytes of the skin. Melanoma metastasis results in poor treatment prognosis for patients and is associated with epigenetic and transcriptional changes that reflect the developmental program of melanocyte differentiation from neural crest stem cells. Several studies have explored melanoma transcriptional heterogeneity using microarray, bulk and single-cell RNA-sequencing technologies to derive data-driven models of the transcriptional-state change which occurs during melanoma progression. No study has systematically examined how different models of melanoma progression derived from different data types, technologies and biological conditions compare. Here, we perform a cross-sectional study to identify averaging effects of bulk-based studies that mask and distort apparent melanoma transcriptional heterogeneity; we describe new transcriptionally distinct melanoma cell states, identify differential co-expression of genes between studies and examine the effects of predicted drug susceptibilities of different cell states between studies. Importantly, we observe considerable variability in drug-target gene expression between studies, indicating potential transcriptional plasticity of melanoma to down-regulate these drug targets and thereby circumvent treatment. Overall, observed differences in gene co-expression and predicted drug susceptibility between studies suggest bulk-based transcriptional measurements do not reliably gauge heterogeneity and that melanoma transcriptional plasticity is greater than described when studies are considered in isolation.

Structural Determinants of Vibrio cholerae FeoB Nucleotide Promiscuity.

Ferrous iron (Fe2+) is required for the growth and virulence of many pathogenic bacteria, including Vibrio cholerae (Vc), the causative agent of the disease cholera. For this bacterium, Feo is the primary system that transports Fe2+ into the cytosol. FeoB, the main component of this system, is regulated by a soluble cytosolic domain termed NFeoB. Recent reanalysis has shown that NFeoBs can be classified as either GTP-specific or NTP-promiscuous, but the structural and mechanistic bases for these differences were not known. To explore this intriguing property of FeoB, we solved the X-ray crystal structures of VcNFeoB in both the apo and GDP-bound forms. Surprisingly, this promiscuous NTPase displayed a canonical NFeoB G-protein fold like GTP-specific NFeoBs. Using structural bioinformatics, we hypothesized that residues surrounding the nucleobase could be important for both nucleotide affinity and specificity. We then solved the X-ray crystal structures of N150T VcNFeoB in the apo and GDP-bound forms to reveal H-bonding differences surround the guanine nucleobase. Interestingly, isothermal titration calorimetry revealed similar binding thermodynamics of the WT and N150T proteins to guanine nucleotides, while the behavior in the presence of adenine nucleotides was dramatically different. AlphaFold models of VcNFeoB in the presence of ADP and ATP showed important conformational changes that contribute to nucleotide specificity among FeoBs. Combined, these results provide a structural framework for understanding FeoB nucleotide promiscuity, which could be an adaptive measure utilized by pathogens to ensure adequate levels of intracellular iron across multiple metabolic landscapes.

Large-scale purification of a deprotected macrocyclic peptide by supercritical fluid chromatography (SFC) integrated with liquid chromatography in discovery chemistry.

A macrocyclic peptide A was successfully purified in large quantities (∼30 g) in >95 % purity by an integrated two-step orthogonal purification process combining supercritical fluid chromatography (SFC) with medium-pressure reverse-phase liquid chromatography (MP-RPLC). MP-RPLC was used to fractionate the crude peptide A, remove unwanted trifluoroacetic acid (TFA) originating from the peptide A cleavage off the resin, and convert the peptide A into ammonium acetate salt form, prior to the final purification by SFC. A co-solvent of methanol/acetonitrile containing ammonium acetate and water in CO2 was developed on a Waters BEH 2-Ethylpyridine column. The developed SFC method was readily scaled up onto a 5 cm diameter column to process multi-gram quantities of the MP-RPLC fraction to reach > 95 % purity with a throughput/productivity of 0.96 g/h. The incorporation of SFC with MP-RPLC has been demonstrated to have a broader application in other large-scale polypeptide purifications.

Effectiveness of atopic dermatitis patient education programs - a systematic review and meta-analysis.

Patient education in atopic dermatitis (AD) has worked in parallel to the gold standard of pharmacological treatment as a foundational component of therapeutic regimens. In addition to improving patient education, past investigations of educational interventions have demonstrated profound reductions in disease severity for patients living with AD. However, prior meta-analytical work has focused mostly on comparing in-person interventions, and thus the need to determine the effectiveness of virtual methodologies in the current post-COVID era remains. In this study, we conducted a systematic review of the literature to determine the effectiveness of online programming in AD education compared to in-person interventions. A comprehensive search was conducted in accordance with the Cochrane Handbook for Systematic Reviews of Interventions 2019. Studies were retrieved based on articles published up to 04 April 2023. Adherence to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement guided the reportage process for this systematic review and meta-analysis. The primary outcome of our meta-analysis was the effect of various educational modalities on atopic dermatitis severity as measured by multiple scales across the studies, the most common including SCORAD, Dermatology Life Quality Index (DLQI), Patient Oriented Eczema Measure (POEM), and Eczema Area and Severity Index (EASI). Most studies were randomized controlled trials, primarily from North America and Western Europe and focused on patient and/or caregiver education about disease management, self-care techniques, avoidance of triggers, and comprehensive understanding of the disease process. Our pooled analyses showed that targeted educational programs in understudied adult populations can be as impactful as those in pediatric groups. Moreover, virtual interventions can be employed as constructive tools for reducing barriers of access to patient education. Future research on educational interventions should utilize various methodologies to encourage individual learning preferences with a focus on adult cohorts.

Increasing acceptance of AI-generated digital twins through clinical trial applications.

Today's approach to medicine requires extensive trial and error to determine the proper treatment path for each patient. While many fields have benefited from technological breakthroughs in computer science, such as artificial intelligence (AI), the task of developing effective treatments is actually getting slower and more costly. With the increased availability of rich historical datasets from previous clinical trials and real-world data sources, one can leverage AI models to create holistic forecasts of future health outcomes for an individual patient in the form of an AI-generated digital twin. This could support the rapid evaluation of intervention strategies in silico and could eventually be implemented in clinical practice to make personalized medicine a reality. In this work, we focus on uses for AI-generated digital twins of clinical trial participants and contend that the regulatory outlook for this technology within drug development makes it an ideal setting for the safe application of AI-generated digital twins in healthcare. With continued research and growing regulatory acceptance, this path will serve to increase trust in this technology and provide momentum for the widespread adoption of AI-generated digital twins in clinical practice.

Protocol for a single-arm, pilot trial of creatine monohydrate supplementation in patients with Alzheimer's disease.

BACKGROUND: Impaired brain bioenergetics is a pathological hallmark of Alzheimer's disease (AD) and is a compelling target for AD treatment. Patients with AD exhibit dysfunction in the brain creatine (Cr) system, which is integral in maintaining bioenergetic flux. Recent studies in AD mouse models suggest Cr supplementation improves brain mitochondrial function and may be protective of AD peptide pathology and cognition. AIMS: The Creatine to Augment Bioenergetics in Alzheimer's disease (CABA) study is designed to primarily assess the feasibility of supplementation with 20 g/day of creatine monohydrate (CrM) in patients with cognitive impairment due to AD. Secondary aims are designed to generate preliminary data investigating changes in brain Cr levels, cognition, peripheral and brain mitochondrial function, and muscle strength and size. METHODS: CABA is an 8-week, single-arm pilot study that will recruit 20 patients with cognitive impairment due to AD. Participants attend five in-person study visits: two visits at baseline to conduct screening and baseline assessments, a 4-week visit, and two 8-week visits. Outcomes assessment includes recruitment, retention, and compliance, cognitive testing, magnetic resonance spectroscopy of brain metabolites, platelet and lymphocyte mitochondrial function, and muscle strength and morphology at baseline and 8 weeks. DISCUSSION: CABA is the first study to investigate CrM as a potential treatment in patients with AD. The pilot data generated by this study are pertinent to inform the design of future large-scale efficacy trials. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05383833 , registered on 20 May 2022.

Metabolism-driven in vitro/in vivo disconnect of an oral ERɑ VHL-PROTAC.

Targeting the estrogen receptor alpha (ERα) pathway is validated in the clinic as an effective means to treat ER+ breast cancers. Here we present the development of a VHL-targeting and orally bioavailable proteolysis-targeting chimera (PROTAC) degrader of ERα. In vitro studies with this PROTAC demonstrate excellent ERα degradation and ER antagonism in ER+ breast cancer cell lines. However, upon dosing the compound in vivo we observe an in vitro-in vivo disconnect. ERα degradation is lower in vivo than expected based on the in vitro data. Investigation into potential causes for the reduced maximal degradation reveals that metabolic instability of the PROTAC linker generates metabolites that compete for binding to ERα with the full PROTAC, limiting degradation. This observation highlights the requirement for metabolically stable PROTACs to ensure maximal efficacy and thus optimisation of the linker should be a key consideration when designing PROTACs.

Safer not to know? Shaping liability law and policy to incentivize adoption of predictive AI technologies in the food system.

Governments, researchers, and developers emphasize creating "trustworthy AI," defined as AI that prevents bias, ensures data privacy, and generates reliable results that perform as expected. However, in some cases problems arise not when AI is not trustworthy, technologically, but when it is. This article focuses on such problems in the food system. AI technologies facilitate the generation of masses of data that may illuminate existing food-safety and employee-safety risks. These systems may collect incidental data that could be used, or may be designed specifically, to assess and manage risks. The predictions and knowledge generated by these data and technologies may increase company liability and expense, and discourage adoption of these predictive technologies. Such problems may extend beyond the food system to other industries. Based on interviews and literature, this article discusses vulnerabilities to liability and obstacles to technology adoption that arise, arguing that "trustworthy AI" cannot be achieved through technology alone, but requires social, cultural, political, as well as technical cooperation. Implications for law and further research are also discussed.

Understanding mechanisms and the role of differentiation in pathogenesis of Toxoplasma gondii: a review

Parasite differentiation from proliferating tachyzoites into latent bradyzoites is central to pathogenesis and transmission of the intracellular protozoan pathogen Toxoplasma gondii. The presence of bradyzoite-containing cysts in human hosts and their subsequent rupture can cause life-threatening recrudescence of acute infection in the immunocompromised and cyst formation in other animals contributes to zoonotic transmission and widespread dissemination of the parasite. In this review, we discuss the evidence showing how the clinically relevant process of bradyzoite differentiation is regulated at both transcriptional and post-transcriptional levels. Specific regulatory factors implicated in modulating bradyzoite differentiation include promoter-based cis-elements, epigenetic modifications and protein translation control through eukaryotic initiation factor -2 (eIF2). In addition to a summary of the current state of knowledge in these areas we discuss the pharmacological ramifications and pose some questions for future research.