Quality of life in women with early-stage and metastatic hormone receptor-positive, HER2-negative breast cancer receiving endocrine therapy.

INTRODUCTION: Early discontinuation of endocrine therapy (ET) is higher among patients with early breast cancer (EBC) compared to patients with metastatic hormone receptor-positive (HR+) breast cancer (MBC). In our clinical experience the reasons for this may include a significant burden of ET side effects impacting quality of life (QOL) in patients with EBC.  We hypothesized that QOL is lower in patients with HR + EBC compared to patients with HR + MBC on ET. METHODS: We conducted a cross-sectional observational study to assess QOL utilizing FACT-ES & EORTC QLQ C30 tools among patients with EBC and MBC receiving ET across 5 Irish hospitals. RESULTS: A total of 417 patients were enrolled-EBC (79% n = 331) and MBC 21% (n = 86). Using the FACT-ES, we found no difference in overall QOL by stage (139.2 vs 141, P  = .33). Patients with HR + MBC had a lower symptom burden from ET compared to HR + EBC (61.4 vs 54, P < .01). In adjusted multivariate linear regression models, there was no difference in QOL for patients with EBC and MBC receiving ET. CONCLUSIONS: There was no significant difference in overall QOL for patients with EBC and MBC. However, patients with EBC experienced more endocrine symptoms. In adjusted multivariate linear regression models, the stage did not predict QOL. Our results suggest that endocrine symptoms are significant contributors to impaired QOL for patients with EBC but the role of other determinants of QOL (eg, stage) is less clear. Future work could include the development of stage-specific QOL tools and utilization of electronic patient-reported outcomes (ePROs) to identify and manage emergent toxicities.

Defining disease severity in atopic dermatitis and psoriasis for the application to biomarker research: an interdisciplinary perspective.

More severe atopic dermatitis and psoriasis are associated with a higher cumulative impact on quality of life, multimorbidity and healthcare costs. Proactive, early intervention in those most at risk of severe disease may reduce this cumulative burden and modify the disease trajectory to limit progression. The lack of reliable biomarkers for this at-risk group represents a barrier to such a paradigm shift in practice. To expedite discovery and validation, the BIOMarkers in Atopic Dermatitis and Psoriasis (BIOMAP) consortium (a large-scale European, interdisciplinary research initiative) has curated clinical and molecular data across diverse study designs and sources including cross-sectional and cohort studies (small-scale studies through to large multicentre registries), clinical trials, electronic health records and large-scale population-based biobanks. We map all dataset disease severity instruments and measures to three key domains (symptoms, inflammatory activity and disease course), and describe important codependencies and relationships across variables and domains. We prioritize definitions for more severe disease with reference to international consensus, reference standards and/or expert opinion. Key factors to consider when analysing datasets across these diverse study types include explicit early consideration of biomarker purpose and clinical context, candidate biomarkers associated with disease severity at a particular point in time and over time and how they are related, taking the stage of biomarker development into account when selecting disease severity measures for analyses, and validating biomarker associations with disease severity outcomes using both physician- and patient-reported measures and across domains. The outputs from this exercise will ensure coherence and focus across the BIOMAP consortium so that mechanistic insights and biomarkers are clinically relevant, patient-centric and more generalizable to current and future research efforts.

Atopic dermatitis (AD), and psoriasis are long-term skin conditions that can significantly affect people's lives, especially when symptoms are severe. Approximately 10% of adults and 20% of children are affected by AD, while psoriasis affects around 5% of people in the UK. Both conditions are associated with debilitating physical symptoms (such as itch) and have been linked to depression and anxiety. Biomarkers are naturally occurring chemicals in the human body and have potential to enhance the longer-term management of AD and psoriasis. Currently, there are no routinely used biomarkers that can identify people who experience or will go on to develop severe AD and psoriasis. For this reason, research is under way to understand which biomarkers are linked to severity. In this study, a multidisciplinary team of skin researchers from across Europe, along with patient groups, discussed the complexities of studying severity-related biomarkers. We identified a number of severity measurement approaches and there were recommendations for future biomarker research, including (i) considering multiple measures as no single measure can encompass all aspects of severity, (ii) exploring severity measures recorded by both healthcare professionals and patients, as each may capture different aspects, and (iii) accounting for influencing factors, such as different treatment approaches, that may impact AD and psoriasis severity, which make it challenging to compare findings across studies. Overall, we anticipate that the insights gained from these discussions will increase the likelihood of biomarkers being effectively applied in real-world settings, to ultimately improve outcomes for people with AD and psoriasis.

Genomic Landscape of NSCLC in the Republic of Ireland.

Introduction: The identification of genomic "targets" through next-generation sequencing (NGS) of patient's NSCLC tumors has resulted in a rapid expansion of targeted treatment options for selected patients. This retrospective study aims to identify the proportion of patients with advanced NSCLC in the Republic of Ireland whose tumors harbor actionable genomic alterations through broad NGS panel testing. Methods: Institutional review board approval was obtained before study initiation. Patients with NSCLC whose tumors underwent genomic testing through the largest available NGS panel at a nationally funded Cancer Molecular Diagnostics laboratory (St. James's Hospital) between June 2017 and June 2022 were identified. Patient demographics and tumor-related data were collected by retrospective review from all cancer centers in Ireland, referring to the Cancer Molecular Diagnostics laboratory. A total of 203 (9%) tumor samples were excluded due to insufficient neoplastic cell content. Genomic data were collected through retrospective search of Ion Reporter software. The spectrum and proportion of patients with oncogenic driver mutations were evaluated using descriptive statistics (SPSS version 29.0). Results: In total, 2052 patients were identified. Patients were referred from 23 different hospital sites and all four geographic regions (Leinster = 1091, 53%; Munster = 763, 37.2%; Connacht = 191, 9.3%; Ulster = 7, 0.3%). Median age was 69 (range: 26-94) years; 53% were male. The most common tumor histologic subtype was adenocarcinoma (77%, n = 1577). An actionable genomic alteration was identified in 1099 cases (53%), the most common of which was KRAS (n = 657, 32%). Less frequently, NSCLC tumors harbored the following: MET exon 14 skipping (n = 53, 2.6%), MET amplification (n = 26, 1.3%), EGFR (n = 181, 8.8%), HER2 (n = 35, 1.7%), and BRAF (n = 72, 3.5%) mutations. Fusions were detected in 76 patients (3.7%) including ALK (n = 44, 58%), RET (n = 11, 14.5%), ROS1 (n = 16, 21%), and FGFR3 (n = 5, 6.6%), whereas no NTRK fusion was identified. Co-alterations were detected in 114 patients (5.6%), the most common of which was KRAS/PIK3CA (n = 19, 17%), EGFR/PIK3CA (n = 10, 8.5%), and KRAS/IDH1 (n = 9, 8%). Other co-alterations of interest identified included KRAS G12A/ROS1 fusion (n = 1) and KRAS G12C/BRAF G469A (n = 2). Conclusions: This is the first retrospective study to comprehensively characterize the genomic landscape of NSCLC in Ireland, using the broadest available NGS panel. Actionable alterations were identified in 53.4% of the patients, and KRAS was the most common oncogenic driver alteration. Our study revealed a lower prevalence of patients whose tumor harbors ALK, ROS1, and RET fusions, compared with similar data sets.

Is Immunotherapy Beneficial in Patients with Oncogene-Addicted Non-Small Cell Lung Cancers? A Narrative Review.

Over the past 20 years, there has been a paradigm shift in the care of patients with non-small cell lung cancer (NSCLC), who now have a range of systemic treatment options including targeted therapy, chemotherapy, immunotherapy (ICI), and antibody-drug conjugates (ADCs). A proportion of these cancers have single identifiable alterations in oncogenes that drive their proliferation and cancer progression, known as "oncogene-addiction". These "driver alterations" are identified in approximately two thirds of patients with lung adenocarcinomas, via next generation sequencing or other orthogonal tests. It was noted in the early clinical development of ICIs that patients with oncogene-addicted NSCLC may have differential responses to ICI. The toxicity signal for patients with oncogene-addicted NSCLC when treated with ICIs also seemed to differ depending on the alteration present and the specific targeted agent used. Developing a greater understanding of the underlying reasons for these clinical observations has become an important area of research in NSCLC. In this review, we analyze the efficacy and safety of ICI according to specific mutations, and consider possible future directions to mitigate safety concerns and improve the outcomes for patients with oncogene-addicted NSCLC.

The Acceptability of post-stroke cognitive testing through the lens of the theory of acceptability, a qualitative study.

Background: Cognitive impairment is common after stroke and screening is recommended. However, there is a lack of evidence on the best way to assess cognition after stroke and a tendency to focus on the clinician rather than stroke survivor. The Theoretical Framework of Acceptability (TFA) was developed to better understand the factors that contribute to the acceptability of healthcare interventions from the patient perspective. We aimed to explore the acceptability of post-stroke cognitive assessment from the stroke survivor perspective, using the TFA as a lens. Methods: We analysed interviews conducted with people admitted to hospital after stroke. Inclusion criteria: ≥18 years, able to provide informed consent. Semi-structured interviews were conducted 1-3 weeks after discharge from hospital in the participant's home to explore the experience of cognitive assessment in hospital. Interviews were audio recorded and transcribed verbatim. Data were analysed using framework analysis, with a framework underpinned by the TFA. Results: Of the 13 participants interviewed, 8 were male, 6 lived in the most deprived SIMD quintile. Ages were 62-84 years. Five themes were identified that describe the factors that influence acceptability of cognitive screening from the patient perspective: (1) participation motives; (2) trust in health professionals; (3) perceived risks of harm; (4) information provision; (5) burden of testing. Conclusion: Clinical teams should be confident that stroke survivors expect cognitive testing and understand its rational. However, the provision of information and results of cognitive testing should be person-centred.

Research protocol - Assessing Post-Stroke Psychology Longitudinal Evaluation (APPLE) study: A prospective cohort study in stroke.

Background: Cognitive and mood problems have been highlighted as priorities in stroke research and guidelines recommend early screening. However, there is limited detail on the preferred approach.We aimed to (1) determine the optimal methods for evaluating psychological problems that pre-date stroke; (2) assess the test accuracy, feasibility and acceptability of brief cognitive and mood tests used at various time-points following stroke; (3) describe temporal changes in cognition and mood following stroke and explore predictors of change. Methods: We established a multi-centre, prospective, observational cohort with acute stroke as the inception point - Assessing Post-stroke Psychology Longitudinal Evaluation (APPLE). We approached patients admitted with stroke or transient ischaemic attack (TIA) from 11 different hospital sites across the United Kingdom. Baseline demographics, clinical, functional, cognitive, and mood data were collected. Consenting stroke survivors were followed up with more extensive evaluations of cognition and mood at 1, 6, 12 and 18 months. Results: Continuous recruitment was from February 2017 to February 2019. With 357 consented to full follow-up. Eighteen-month assessments were completed in September 2020 with permissions in-place for longer term in-person or electronic follow-up. A qualitative study has been completed, and a participant sample biobank and individual participant database are both available. Discussion: The APPLE study will provide guidance on optimal tool selection for cognitive and mood assessment both before and after stroke, as well as information on prognosis and natural history of neuropsychological problems in stroke. The study data, neuroimaging and tissue biobank are all available as a resource for future research.

Parallel functional subnetworks embedded in the macaque face patch system.

During normal vision, our eyes provide the brain with a continuous stream of useful information about the world. How visually specialized areas of the cortex, such as face-selective patches, operate under natural modes of behavior is poorly understood. Here we report that, during the free viewing of movies, cohorts of face-selective neurons in the macaque cortex fractionate into distributed and parallel subnetworks that carry distinct information. We classified neurons into functional groups on the basis of their movie-driven coupling with functional magnetic resonance imaging time courses across the brain. Neurons from each group were distributed across multiple face patches but intermixed locally with other groups at each recording site. These findings challenge prevailing views about functional segregation in the cortex and underscore the importance of naturalistic paradigms for cognitive neuroscience.

Review of clinical practice guidelines relating to cognitive assessment in stroke.

PURPOSE: To assess the content, quality, and supporting evidence base of clinical practice guidelines (CPGs) with reference to cognitive assessment in stroke. MATERIALS AND METHODS: We performed a systematic review to identify eligible CPGs pertaining to cognitive assessment in adult stroke survivors. We compared content and strength of recommendations. We used the AGREE-II (appraisal of guidelines for research and evaluation) tool to appraise the quality of the guideline. RESULTS: Eight eligible guidelines were identified and seven were rated as high quality (i.e., appropriately addressing at least four domains of the AGREE-II tool including "rigor of development"). There was heterogeneity in the recommendations offered and limited guidance on fundamental topics such as which cognitive test to use or when to perform testing. Generally, the lowest quality of evidence (expert opinion) was used to inform these recommendations. CONCLUSIONS: Although assessment of cognition is a key aspect of stroke care, there is a lack of guidance for clinicians. The limited evidence base, in part, reflects the limited research in the area. A prescriptive approach to cognitive assessment may not be suitable, but more primary research may help inform practice.Implications for rehabilitationCognitive assessment in stroke exhibits substantial variation in practice, clinical practice guidelines rarely give prescriptive recommendations on which approach to take.Where guideline recommendations on cognitive assessment in stroke were made these were based on expert opinion.Our summary of the guideline content found certain areas of consensus, for example, routine assessment using validated tools.

Laser to laser power conversion with remote signaling.

We demonstrate laser power conversion using an edge-coupled waveguide configuration. A laser with an emission energy of 0.87 eV (1427 nm) optically pumps a second with an emission energy of 0.80 eV (1540 nm), achieving the maximum possible open circuit voltage of 0.83 V due to optically pumped lasing. A fiber to device power conversion efficiency of 33% is achieved with internal power conversion efficiency ranging from 57% to 51%. The voltage at maximum power is 0.6 V, which is a record for the wavelength range. The same optically pumped device is used for effectively power-free 500 Mbps upstream data transmission, enabling compact powering and signaling for emerging applications in minimally invasive medical interventions and remote photonics.

Virtual oncology clinics during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has resulted in radical changes in the delivery of healthcare worldwide. Our oncology service (at an Irish national cancer centre) rapidly transitioned to the use of telemedicine or virtual clinics (VC) to minimise potential risk of exposure to COVID-19 amongst an immunosuppressed, high-risk population. Our study aimed to evaluate the use of VC in this setting. METHODS: An 18-point questionnaire was designed to investigate the patient experience of VC during the COVID-19 pandemic in Ireland and compliance with guidelines developed in Ireland to conduct VC and the role of VC in the future. Questionnaires were distributed following the receipt of verbal consent from patients during the VC. Descriptive statistics were utilised for data analysis using SPSS®. RESULTS: One hundred and four patients returned completed surveys (n = 104/164, 63% response rate). Overall satisfaction levels were high with most patients (n = 58/100, 58%; no answer provided (NAP), n = 4) equally satisfied or nearly equally satisfied with VC in comparison to a usual clinic encounter. The majority of patients felt that there should be a role for VC in the future (n = 84/102, 82%; NAP, n = 2). The majority of patients (n = 61/99, 61%; NAP, n = 5) were very relieved to avoid a hospital visit due to perceived risk of potential exposure to COVID-19. CONCLUSION: The majority of oncology patients were satisfied with a VC encounter. VC may have a role in the future of medical care in Ireland post the COVID-19 pandemic.

Acupuncture, Shingles, and Allergen Immunotherapy.

Background: The Varicella-zoster virus (VZV) remains dormant in the dorsal root ganglia and can become reactive later in a person's life. Factors such as stress, trauma, chronic disease, systemic illness, immune disorders, and age-related decline in host immunologic responses can potentially incite reactivation. Activation of VZV resulting in shingles following acupuncture has been reported in the literature previously, and some mechanisms have been proposed for this observation. Case: A patient with a history of total thyroidectomy for thyroid cancer presented with chronic neck pain. She was clinically and biochemically in a euthyroid state and on thyroid replacement therapy. She had a history of chickenpox, at age 13, and seasonal allergies. After her first acupuncture session, she received an allergy shot for her seasonal allergies. A day after the procedure, she developed a vesicular rash and was subsequently diagnosed with acute Herpes zoster. Subsequent acupuncture was withheld following this event. She received acyclovir and applied topical Aloe vera to the cutaneous lesions, and developed mild scarring, but did not experience postherpetic neuralgia. Conclusions: Acupuncture is a minor trauma that can predispose a patient to reactivation of VZV and shingles in the setting of immune activation with allergen immunotherapy.

Dynamic Suppression of Average Facial Structure Shapes Neural Tuning in Three Macaque Face Patches.

The visual perception of identity in humans and other primates is thought to draw upon cortical areas specialized for the analysis of facial structure. A prominent theory of face recognition holds that the brain computes and stores average facial structure, which it then uses to efficiently determine individual identity, though the neural mechanisms underlying this process are controversial. Here, we demonstrate that the dynamic suppression of average facial structure plays a prominent role in the responses of neurons in three fMRI-defined face patches of the macaque. Using photorealistic face stimuli that systematically varied in identity level according to a psychophysically based face space, we found that single units in the AF, AM, and ML face patches exhibited robust tuning around average facial structure. This tuning emerged after the initial excitatory response to the face and was expressed as the selective suppression of sustained responses to low-identity faces. The coincidence of this suppression with increased spike timing synchrony across the population suggests a mechanism of active inhibition underlying this effect. Control experiments confirmed that the diminished responses to low-identity faces were not due to short-term adaptation processes. We propose that the brain's neural suppression of average facial structure facilitates recognition by promoting the extraction of distinctive facial characteristics and suppressing redundant or irrelevant responses across the population.

Mining predicted crystal structure landscapes with high throughput crystallisation: old molecules, new insights.

Organic molecules tend to close pack to form dense structures when they are crystallised from organic solvents. Porous molecular crystals defy this rule: they contain open space, which is typically stabilised by inclusion of solvent in the interconnected pores during crystallisation. The design and discovery of such structures is often challenging and time consuming, in part because it is difficult to predict solvent effects on crystal form stability. Here, we combine crystal structure prediction (CSP) with a robotic crystallisation screen to accelerate the discovery of stable hydrogen-bonded frameworks. We exemplify this strategy by finding new phases of two well-studied molecules in a computationally targeted way. Specifically, we find a new 'hidden' porous polymorph of trimesic acid, δ-TMA, that has a guest-free hexagonal pore structure, as well as three new solvent-stabilized diamondoid frameworks of adamantane-1,3,5,7-tetracarboxylic acid (ADTA). Beyond porous solids, this hybrid computational-experimental approach could be applied to a wide range of materials problems, such as organic electronics and drug formulation.

Computational modelling of solvent effects in a prolific solvatomorphic porous organic cage.

Crystal structure prediction methods can enable the in silico design of functional molecular crystals, but solvent effects can have a major influence on relative lattice energies, sometimes thwarting predictions. This is particularly true for porous solids, where solvent included in the pores can have an important energetic contribution. We present a Monte Carlo solvent insertion procedure for predicting the solvent filling of porous structures from crystal structure prediction landscapes, tested using a highly solvatomorphic porous organic cage molecule, CC1. Using this method, we can understand why the predicted global energy minimum structure for CC1 is never observed from solvent crystallisation. We also explain the formation of three different solvatomorphs of CC1 from three structurally-similar chlorinated solvents. Calculated solvent stabilisation energies are found to correlate with experimental results from thermogravimetric analysis, suggesting a future computational framework for a priori materials design that factors in solvation effects.

A Novel Combination Therapy for Patients With Dry Eye Disease: A Pilot Study.

Context • Approximately 25% of the US population suffers from dry eyes or some abnormality of the exposed ocular surface. Investigation of effective modalities for their management is needed. Objective • The study intended to examine the efficacy of a proprietary, daily, Dry Eye Protocol consisting of daily use of a moist, heated, ocular compress and intake of an omega-3 dietary supplement in treatment of ocular surface disease. Design • The research team designed a 4-wk, clinically based, open-label, multicenter cohort study. Setting • The study took place at 6 private eye care practices throughout the United States: Beverly Hills, CA, USA; San Diego, CA, USA; Sunnyvale, CA, USA; Park City, UT, USA; Tarpon Spring, FL, USA; and Kennewick, WA, USA. Participants • Participants were adults between 18 and 75 y of age who had established ocular surface disease based on clinical findings and the results of testing using the ocular surface disease index (OSDI). Intervention • For period of 30 d, participants used a combined daily protocol that included (1) application of a moist, heated, eye compress and (2) a nutritional therapy via an omega-3 supplement in an oral triglyceride form. Outcome Measures • Measures included the OSDI and a test of tear break-up time (TBUT). Results • Of the original 35 participants, 33 completed the 4-wk protocol. The participants using the proprietary Dry Eye Protocol showed significant improvements from baseline, demonstrated by a 49% decrease in OSDI scores (P = .0015); and 46% of participants reported becoming asymptomatic of dry eye symptoms. A significant improvement was also observed in TBUT, increasing from 3.0 to 5.4 s. Conclusions • Daily use of the proprietary Dry Eye Protocol that included a high dosage of triglyceride omega-3 and use of a moist, heated, compress daily showed significant improvement for participants in OSDI and TBUT and should be considered to be a first-line therapy for patients with dry eye disease.

Functional Subpopulations of Neurons in a Macaque Face Patch Revealed by Single-Unit fMRI Mapping.

Neurons within fMRI-defined face patches of the macaque brain exhibit shared categorical responses to flashed images but diverge in their responses under more natural viewing conditions. Here we investigate functional diversity among neurons in the anterior fundus (AF) face patch, combining whole-brain fMRI with longitudinal single-unit recordings in a local population (<1 mm3). For each cell, we computed a whole-brain correlation map based on its shared time course with voxels throughout the brain during naturalistic movie viewing. Based on this mapping, neighboring neurons showed markedly different affiliation with distant visually responsive areas and fell coarsely into subpopulations. Of these, only one subpopulation (∼16% of neurons) yielded similar correlation maps to the local fMRI signal. The results employ the readout of large-scale fMRI networks and, by indicating multiple functional domains within a single voxel, present a new view of functional diversity within a local neural population.

Functional materials discovery using energy-structure-function maps.

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

Prediction of Excited-State Energies and Singlet-Triplet Gaps of Charge-Transfer States Using a Restricted Open-Shell Kohn-Sham Approach.

Organic molecules with charge-transfer (CT) excited states are widely used in industry and are especially attractive as candidates for fabrication of energy efficient OLEDs, as they can harvest energy from nonradiative triplets by means of thermally activated delayed fluorescence (TADF). It is therefore useful to have computational protocols for accurate estimation of their electronic spectra in order to screen candidate molecules for OLED applications. However, it is difficult to predict the photophysical properties of TADF molecules with LR-TDDFT, as semilocal LR-TDDFT is incapable of accurately modeling CT states. Herein, we study absorption energies, emission energies, zero-zero transition energies, and singlet-triplet gaps of TADF molecules using a restricted open-shell Kohn-Sham (ROKS) approach instead and discover that ROKS calculations with semilocal hybrid functionals are in good agreement with experiments-unlike TDDFT, which significantly underestimates energy gaps. We also propose a cheap computational protocol for studying excited states with large CT character that is found to give good agreement with experimental results without having to perform any excited-state geometry optimizations.