Explore the vast range of titles available.

Background A proportion of women undergoing mastectomy for breast cancer choose to undergo breast reconstruction. Evidence suggests that women’s preparedness for this surgery is low and that this may contribute to feelings of unmatched expectations and anxiety. There is substantial interest in decision-aids to remedy this. This study explores the incorporation of digitally rendered three-dimensional images into pre-operative counselling sessions as a means of enhancing patient preparedness. Methods A database of three-dimensional images was produced showing both optimal and sub-optimal aesthetic outcome, matched to participant on the basis of type of surgical reconstruction, body habitus, and skin tone. Women undergoing mastectomy for breast cancer followed by immediate reconstruction were targeted for inclusion. Participants interacted with image software during pre-operative counselling sessions by viewing, rotating, and zooming in/out to gain a more in-depth appreciation of post-operative aesthetic outcome. Semi-structured face-to-face interviews followed thereafter. Interviews were audio-recorded, transcribed, coded, and themes identified. Results Eight semi-structured interviews took place. The major emergent theme was ‘increased preparedness’ with subthemes including ‘expectation management’, ‘software interaction’, and ‘enhanced realism’. There were no prohibitively negative emotions after interacting with images. Women reported gaining ‘more of a perspective’ and feeling ‘more informed’ after viewing images. They also valued the enhanced interactivity and better appreciation of reconstructed breast symmetry that viewing three-dimensional images offered when compared to viewing two-dimensional photographs. Finally, women also commented that three-dimensional images were more realistic. Conclusions Results suggest that incorporation of three-dimensional images into pre-operative counselling sessions prior to breast reconstruction, is a fairly simple yet effective method of enhancing patient preparedness prior to surgery. Women particularly valued the ability to use the software to generate a more realistic idea of what to expect after their operation. Future work should focus on better understanding any quantifiable benefit from incorporating three-dimensional images routinely into pre-operative decision-making.

The aim of this study was to document cancer trial participation since establishment of the Northern Ireland Cancer Trials Network and investigate population and disease factors associated with trial participation. An independent cohort of over 51 000 cancer patients from the Northern Ireland Cancer Registry covering the same population (2007–2012) was linked to a database of 1316 interventional cancer trial participants in a UK region. The primary outcome measure was participation in an intervention clinical trial. Patients were followed up until 31 March 2013. Kaplan–Meier tests and Cox proportional hazard models using person days at risk to allow for death were used to investigate factors associated with trial participation. Multivariate analysis assessed the impact of age, cancer type and stage, distance from the cancer centre (radiotherapy), marital status, deprivation quintile and rurality. Participation was analysed separately for children (< 15 years) and young individuals (15–24 years). Trial recruitment increased three-fold with establishment of a network. Participation was the highest for children at 21%, but relatively low at 2.05% for adults, although higher for haematological malignancies (4.5%). Lower likelihood of trial participation in adults was associated with female sex, older age, distance from regional Cancer Centre and stage 1 disease. The introduction of a regional Cancer Trials Network was associated with increased participation; however, trial participation remains relatively low at the population level especially among elderly patients. Linkage of clinical trials and cancer registry database provide an easy mechanism to monitor trial representativeness at the population level.

Countries have sought to stop the spread of coronavirus disease 2019 (COVID-19) by severely restricting travel and in-person commercial activities. Here, we analyse the supply-chain effects of a set of idealized lockdown scenarios, using the latest global trade modelling framework. We find that supply-chain losses that are related to initial COVID-19 lockdowns are largely dependent on the number of countries imposing restrictions and that losses are more sensitive to the duration of a lockdown than its strictness. However, a longer containment that can eradicate the disease imposes a smaller loss than shorter ones. Earlier, stricter and shorter lockdowns can minimize overall losses. A ‘go-slow’ approach to lifting restrictions may reduce overall damages if it avoids the need for further lockdowns. Regardless of the strategy, the complexity of global supply chains will magnify losses beyond the direct effects of COVID-19. Thus, pandemic control is a public good that requires collective efforts and support to lower-capacity countries. Guan et al. analyse the impacts of COVID-19 restrictions on global supply chains. Earlier, stricter and shorter lockdowns can minimize overall losses. A ‘go-slow’ approach to lifting restrictions may reduce overall damages if it avoids the need for further lockdowns.

The atmospheric chemistry of organic nitrogen compounds (ONCs) is of great importance for understanding the formation of carcinogenic nitrosamines, and ONC oxidation products might influence atmospheric aerosol particle formation and growth. Indole is a polyfunctional heterocyclic secondary amine with a global emission quantity almost equivalent to that of trimethylamine, the amine with the highest atmospheric emission. However, the atmospheric chemistry of indole remains unclear. Herein, the reactions of indole with ⚫OH and ⚫Cl, and subsequent reactions of resulting indole radicals with O2 under 200 ppt NO and 50 ppt HO2⚫ conditions, were investigated by a combination of quantum chemical calculations and kinetics modeling. The results indicate that ⚫OH addition is the dominant pathway for the reaction of ⚫OH with indole. However, both ⚫Cl addition and H abstraction are feasible for the corresponding reaction with ⚫Cl. All favorably formed indole radicals further react with O2 to produce peroxy radicals, which mainly react with NO and HO2⚫ to form organonitrates, alkoxy radicals and hydroperoxide products. Therefore, the oxidation mechanism of indole is distinct from that of previously reported amines, which primarily form highly oxidized multifunctional compounds, imines or carcinogenic nitrosamines. In addition, the peroxy radicals from the ⚫OH reaction can form N-(2-formylphenyl)formamide (C8H7NO2), for the first time providing evidence for the chemical identity of the C8H7NO2 mass peak observed in the ⚫OH + indole experiments. More importantly, this study is the first to demonstrate that despite forming radicals by abstracting an H atom at the N site, carcinogenic nitrosamines were not produced in the indole oxidation reaction.

Atmospheric organic acids (OAs) are expected to enhance methanesulfonic acid (MSA)-driven new particle formation (NPF). However, the exact role of OAs in MSA-driven NPF remains unclear. Here, we employed a two-step strategy to probe the role of OAs in MSA–methylamine (MA) NPF. Initially, we evaluated the enhancing potential of 12 commonly detected OAs in ternary MA–MSA–OA cluster formation by considering the formation free energies of the (MSA)1(MA)1(OA)1 clusters and the atmospheric concentrations of the OAs. It was found that formic acid (ForA) has the highest potential to stabilize the MA–MSA clusters. The high enhancing potential of ForA results from its acidity, structural factors such as no intramolecular H bonds, and high atmospheric abundance. The second step is to extend the MSA–MA–ForA system to larger cluster sizes. The results indicate that ForA can indeed enhance MSA–MA NPF at atmospheric conditions (the upper limited temperature is 258.15 K), indicating that ForA might have an important role in MSA-driven NPF. The enhancing effect of ForA is mainly caused by an increased formation of the (MSA)2(MA)1 cluster, which is involved in the pathway of binary MSA–MA nucleation. Hence, our results indicate that OAs might be required to facilitate MSA-driven NPF in the atmosphere.

Endomyocardial biopsy (EMB) screening represents the standard of care for detecting allograft rejections after heart transplant. Manual interpretation of EMBs is affected by substantial interobserver and intraobserver variability, which often leads to inappropriate treatment with immunosuppressive drugs, unnecessary follow-up biopsies and poor transplant outcomes. Here we present a deep learning-based artificial intelligence (AI) system for automated assessment of gigapixel whole-slide images obtained from EMBs, which simultaneously addresses detection, subtyping and grading of allograft rejection. To assess model performance, we curated a large dataset from the United States, as well as independent test cohorts from Turkey and Switzerland, which includes large-scale variability across populations, sample preparations and slide scanning instrumentation. The model detects allograft rejection with an area under the receiver operating characteristic curve (AUC) of 0.962; assesses the cellular and antibody-mediated rejection type with AUCs of 0.958 and 0.874, respectively; detects Quilty B lesions, benign mimics of rejection, with an AUC of 0.939; and differentiates between low-grade and high-grade rejections with an AUC of 0.833. In a human reader study, the AI system showed non-inferior performance to conventional assessment and reduced interobserver variability and assessment time. This robust evaluation of cardiac allograft rejection paves the way for clinical trials to establish the efficacy of AI-assisted EMB assessment and its potential for improving heart transplant outcomes. Deep learning applied to endomyocardial biopsy images, developed using datasets from three different countries, can detect rejection of transplanted hearts and determine the subtype and grade of rejection, with potential for reducing the interobserver variability inherent in manual interpretation of these biopsies.

The electrochemical ammonia oxidation reaction (AOR) shows considerable potential for its applications in waste removal and the production of clean energy. While Pt remains the most investigated catalyst for this reaction, its limitations have prompted research into Pt‐based bimetallic alloys. This study investigates both uniform and mixed PtM (M = Au, Ir, Pd, Rh, and Ru) alloys as catalysts for the AOR using density functional theory (DFT). A systematic selection method is used to choose suitable surfaces for testing. The findings indicate that the Oswin–Salomon mechanism is preferred across all surfaces for N2 (g) formation. Additionally, the results demonstrate that mixed alloys exhibit superior catalytic activity compared to uniform alloys for the AOR. It is found that the atoms in the topmost layer of the alloy are the most significant factor in influencing catalytic activity. Furthermore, the linear relationship between the d $d$ ‐band center and adsorption energy of key intermediate *NH2 is confirmed in this work, highlighting the effect of the secondary metal on the electronic structure of the catalyst. The findings provide theoretical insights for the design of high‐performance Pt alloys for AOR and serve as a general guideline for modulating the reactivity of binary alloys for electrocatalysis. Herein, it is demonstrated that alloying platinum with various transition metals can reduce the limiting potential for the ammonia oxidation reaction, with mixed alloys exhibiting more favorable potentials than their uniform counterparts. By applying the d‐band model to the potential‐limiting step of different Pt─M alloy configurations, a linear correlation between electronic structure and limiting potential is revealed.

Formulating pharmaceutical cocrystals as inhalable dosage forms represents a unique niche in effective management of respiratory infections. Favipiravir, a broad-spectrum antiviral drug with potential pharmacological activity against SARS-CoV-2, exhibits a low aqueous solubility. An ultra-high oral dose is essential, causing low patient compliance. This study reports a Quality-by-Design (QbD)-guided development of a carrier-free inhalable dry powder formulation containing a 1:1 favipiravir–theophylline (FAV-THP) cocrystal via spray drying, which may provide an alternative treatment strategy for individuals with concomitant influenza infections and chronic obstructive pulmonary disease/asthma. The cocrystal formation was confirmed by single crystal X-ray diffraction, powder X-ray diffraction, and the construction of a temperature–composition phase diagram. A three-factor, two-level, full factorial design was employed to produce the optimized formulation and study the impact of critical processing parameters on the resulting median mass aerodynamic diameter (MMAD), fine particle fraction (FPF), and crystallinity of the spray-dried FAV-THP cocrystal. In general, a lower solute concentration and feed pump rate resulted in a smaller MMAD with a higher FPF. The optimized formulation (F1) demonstrated an MMAD of 2.93 μm and an FPF of 79.3%, suitable for deep lung delivery with no in vitro cytotoxicity observed in A549 cells.

Concerns about the adverse public health consequences of informal electronic waste (e-waste) recycling are increasing. This study adopted a cross-sectional study design to gain insights into health risks (cancer and non-cancer risks) associated with exposure to e-waste chemicals among informal e-waste workers via three main routes: Dermal contact, ingestion, and inhalation. The e-waste chemicals (PBDE and metals) were measured in the dust and top soils at e-waste sites (burning, dismantling, and repair sites). Adverse health risks were calculated using the EPA model developed by the Environmental Protection Agency of the United States. The concentrations of the e-waste chemicals and the health risks at the e-waste sites increased as the intensity of the e-waste recycling activities increased: control sites < repair sites < dismantling sites < burning sites. Dermal contact was the main route of exposure while exposure via inhalation was negligible for both carcinogenic and non-carcinogenic risks. Cumulative health risks via all routes of exposure (inhalation, ingestion, and dermal contact) exceeded the acceptable limits of both non-cancer effects and cancer risk at all e-waste sites. This indicates that overall the e-waste workers are at the risk of adverse health effects. Therefore, the importance of occupational safety programs and management regulations for e-waste workers cannot be over emphasised.

The relationship between hemodynamic parameters and body mass index (BMI) in the context of blood pressure regulation in hypertension is unclear. Here, we analyzed data from 1368 uncontrolled hypertensive patients, including key hemodynamic indicators such as heart rate (HR), cardiac index (CI), arterial stiffness (AS), systemic vascular resistance index (SVRI), and thoracic blood ratio (TBR). In this cohort, the average BMI across all hypertension patients was 26.859 ± 3.897 (kg/m2), with obese patients (BMI ≥ 28 kg/m2) averaging 31.01 ± 2.87 kg/m2 and non‐obese (BMI<28 kg/m2) averaging 24.70 ± 2.28 kg/m2. Younger obese patients exhibited higher diastolic pressures than non‐obese peers (p < 0.01). Hemodynamic analysis showed obese patients had increased HR and SVRI but lower CI and AS (p < 0.01). Hypertensive males aged under 60 with obesity displayed a more prominent peripheral vascular phenotype (p < 0.05) and volemic phenotype (p < 0.01) than non‐obese males. Obese females aged under 60 showed a higher incidence of cardiac phenotype (p < 0.01). Across genders, obese hypertensive patients aged over 60 had a greater prevalence of volemic phenotype than non‐obese patients (p < 0.05, p < 0.01, respectively). BMI inversely correlated with CI and positively with SVRI across age and gender categories (p < 0.01). Taken together, we find that patients with hypertension exhibit diverse hemodynamic profiles, and BMI significantly correlates with hemodynamic parameters such as SVRI and CI. Our research identifies BMI as a valuable target for personalized hypertension treatment.