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In recent years, 3D printing has experienced significant growth in the manufacturing sector due to its ability to produce intricate and customized components. The advent of Industry 4.0 further boosted this progress by seamlessly incorporating artificial intelligence (AI) in 3D printing processes. As a result, design precision and production efficiency have significantly improved. Although numerous studies have explored the integration of AI and 3D printing, the literature still lacks a comprehensive overview that emphasizes material selection and formulation, predictive modeling, design optimization, and quality control. To fully understand the impacts of these emerging technologies on advanced manufacturing, a thorough assessment is required. This review aims to examine the intersection of AI and 3D printing to create a technologically advanced and environment-friendly manufacturing environment. It examines factors such as material, process efficiency, and design enhancements to highlight the benefits of combining these technologies. By focusing on predictive modeling, material selection and quality control, this analysis aims to unlock the potential for a sustainable and efficient 3D printing process. This review provided a thorough analysis of the challenges and potential benefits, proving valuable for academics and practitioners alike. It presents solutions that may establish a foundation for sustained growth and outlines a strategy for leveraging 3D printing and AI capabilities in the manufacturing sector.

A 57-year-old man presented after a fall, which resulted in acetabular and pelvic fractures. He underwent fracture fixation, which was complicated by iliac vein occlusion, leading to phlegmasia cerulea dolens. He underwent lower extremity surgical venous thrombectomy, contralateral iliac vein stent placement, and modified Palma procedure with an expanded polytetrafluoroethylene venous crossover bypass and arteriovenous fistula creation. His postoperative course was unremarkable and he regained full function of the extremity without significant stasis complications. The bypass and stent remain patent 3 years postoperatively. Although iliac vein injury during acetabular fracture repair is rare, prompt recognition and intervention prevent limb loss.

Neural tube closure in vertebrates is achieved through a highly dynamic and coordinated series of morphogenic events involving neuroepithelium, surface ectoderm, and neural plate border. Failure of this process in the caudal region causes spina bifida. Grainyhead-like 3 (GRHL3) is an indispensable transcription factor for neural tube closure as constitutive inactivation of the Grhl3 gene in mice leads to fully penetrant spina bifida. Here, through single-cell transcriptomics we show that at E8.5, the time-point preceding mouse neural tube closure, co-expression of Grhl3, Tfap2a, and Tfap2c defines a previously unrecognised progenitor population of surface ectoderm integral for neural tube closure. Deletion of Grhl3 expression in this cell population using a Tfap2a-Cre transgene recapitulates the spina bifida observed in Grhl3-null animals. Moreover, conditional inactivation of Tfap2c expression in Grhl3-expressing neural plate border cells also induces spina bifida. These findings indicate that a specific neural plate border cellular cohort is required for the early-stage neurulation.

Abstract Background Gay, bisexual, and other men who have sex with men (GBM) report high rates of problematic alcohol use, anxiety, and depression. This may, in part, be due to stressors related to their sexual identity (i.e., minority stressors). However, few studies have examined both distal and proximal stressors, as well as the specific psychological mechanisms by which these stressors may be related to alcohol use outcomes, in a representative sample of GBM. We explored the relationship between distal and proximal stressors and alcohol use outcomes, as well as the role of anxiety and depression as potential mediators of these relationships. Methods We analyzed the baseline data of 2,449 GBM from Engage, a cohort study of sexually active GBM recruited using respondent-driven sampling (RDS) in Montreal, Toronto, and Vancouver from February 2017 to August 2019. Using structural equation modeling, we examined the associations between distal minority stressors (i.e., experiences of heterosexist harassment, rejection, and discrimination), proximal minority stressors (i.e., internalized homonegativity, concerns about acceptance, concealment, and lack of affirmation), anxiety and depression, and alcohol consumption and alcohol use problems. RDS-adjusted analyses controlled for age, income, sexual orientation, ethnicity, recruitment city, and HIV serostatus. Results There were positive direct associations between distal stress and proximal stress, anxiety, and depression, but not alcohol use outcomes. Proximal stress had a positive direct association with anxiety, depression, and alcohol use problems, but not alcohol consumption. Anxiety was positively associated with alcohol consumption and alcohol use problems. Depression was negatively associated with alcohol consumption but not alcohol use problems. Regarding indirect effects, distal stress was associated with alcohol use outcomes via proximal stress and anxiety, but not via depression. Conclusions We found support for a minority stress model as it relates to alcohol use outcomes among GBM. Findings suggest that proximal minority stress and anxiety differentially impact the problematic alcohol use among GBM who experience heterosexist discrimination. Clinical providers should consider incorporating the treatment of proximal minority stressors and anxiety into existing alcohol interventions for GBM.

Abstract Background Despite growing evidence of the potential of arts-based modalities to translate knowledge and spark discussion on complex issues, applications to health policy are rare. This study explored the potential of a research-based theatrical video to increase public capacity and motivation to engage with the complex issues that make Emergency Department wait times such an intractable problem. Methods Larry Saves the Canadian Healthcare System is a digital musical micro-series developed from extensive research examining system-level causes of Emergency crowding and the ineffectiveness of prevailing approaches. We released individual episodes and a revised full-length version on YouTube, using organic promotion strategies and paid advertising. We used YouTube Analytics to track views, engagement and viewer demographics, and content-analyzed viewer comments. We also conducted five university-based screenings; 92 students completed questionnaires, rating Larry on 16 descriptors using a 7-point Likert scale. Results From June 2022 through May 2023, Larry garnered over 100,000 views (76,752 of the full-length version, 35,535 of episodes), 1329 likes, 2780 shares, and 139 comments. Views and watch time were higher among women and positively associated with age. Among YouTube comments, the predominating themes were praise for the video and criticism of the healthcare system. Many commenters applauded the show’s accuracy, humor, and/or resonance with their experience; several shared healthcare horror stories. Students overwhelmingly agreed with all positive and disagreed with all negative descriptors, and nearly unanimously deemed the video informative, thought-provoking, and entertaining. Most also affirmed that it had increased their knowledge, interest, and confidence to participate in discussions about healthcare issues. Neither gender, primary language, nor employment in healthcare predicted ratings, but graduate students and those 25+ years old evaluated the video most positively. Discussion These findings highlight the promise of research-informed musical satire to inform and invigorate discourse on an urgent health policy problem. Larry has reached tens of thousands of viewers, garnered excellent feedback, and received high student ratings. Further research should directly assess educational and behavioural outcomes and explore what facilitative strategies could maximize this knowledge translation product’s potential to foster informed, impactful policy dialogue.

Summary: Oscillatory activity in the local field potential (LFP) is thought to be a marker of cognitive processes. To understand how it differentiates tasks and brain areas in humans, we recorded LFPs in 15 adults with intracranial depth electrodes, as they performed visual-spatial and shape working memory tasks. Stimulus appearance produced widespread, broad-band activation, including in occipital, parietal, temporal, insular, and prefrontal cortex, and the amygdala and hippocampus. Occipital cortex was characterized by most elevated power in the high-gamma (100–150 Hz) range during the visual stimulus presentation. The most consistent feature of the delay period was a systematic pattern of modulation in the beta frequency (16–40 Hz), which included a decrease in power of variable timing across areas, and rebound during the delay period. These results reveal the widespread nature of oscillatory activity across a broad brain network and region-specific signatures of oscillatory processes associated with visual working memory.

Over the past decade, the production of biofuels from lignocellulosic biomass has steadily increased to offset the use of fuels from petroleum. To make biofuels cost-competitive, however, it is necessary to add value to the “ligno-” components (up to 30% by mass) of the biomass. The properties of lignin, in terms of molecular weight (MW), chemical functionality, and mineral impurities often vary from biomass source and biorefinery process, resulting in a challenging precursor for product development. Activated carbon (AC) is a feasible target for the lignin-rich byproduct streams because it can be made from nearly any biomass, and it has a market capacity large enough to use much of the lignin generated from the biorefineries. However, it is not known how the variability in the lignin affects the key properties of AC, because, until now, they could not be well controlled. In this work, various fractions of ultraclean (2/g (absorption capacity). Furthermore, single step activation carbonization using zinc chloride allows for minimal carbon burn off (

Objective To characterise surgical site infections (SSIs) after open surgery in the UK’s National Health Service.Design Retrospective cohort analysis of electronic records of patients from Clinical Practice Research Datalink, linked with Hospital Episode Statistics’ secondary care datasets.Setting Clinical practice in the community and secondary care.Participants Cohort of 50 000 adult patients who underwent open surgery between 2017 and 2022.Outcome measures Incidence of SSI, clinical outcomes, patterns of care and costs of wound management.Results 11% (5281/50 000) of patients developed an SSI a mean of 18.4±14.7 days after their surgical procedure, of which 15% (806/5281) were inpatients and 85% (4475/5281) were in the community after hospital discharge. The incidence of SSI varied according to anatomical site of surgery. The incidence also varied according to a patient’s risk and whether they underwent an emergency procedure. SSI onset reduced the 6 months healing rate by a mean of 3 percentage points and increased time to wound healing by a mean of 15 days per wound. SSIs were predominantly managed in the community by practice and district nurses and 16% (850/5281) of all patients were readmitted into hospital. The total health service cost of surgical wound management following SSI onset was a mean of £3537 per wound ranging from £2542 for a low-risk patient who underwent an elective procedure to £4855 for a high-risk patient who underwent an emergency procedure.Conclusions This study provides important insights into several aspects of SSI management in clinical practice in the UK that have been difficult to ascertain from surveillance data. Surgeons are unlikely to be fully aware of the true incidence of SSI and how they are managed once patients are discharged from hospital. Current SSI surveillance services appear to be under-reporting the actual incidence.

The thermal conductance of nanowires is an oft-explored quantity, but its dependence on the nanowire shape is not completely understood. The behaviour of the conductance is examined as kinks of varying angular intensity are included into nanowires. The effects on thermal transport are evaluated through molecular dynamics simulations, phonon Monte Carlo simulations and classical solutions of the Fourier equation. A detailed look is taken at the nature of heat flux within said systems. The effects of the kink angle are found to be complex, influenced by multiple factors including crystal orientation, details of transport modelling, and the ratio of mean free path to characteristic system lengths. The effect of varying phonon reflection specularity on the heat flux is also examined. It is found that, in general, the flow of heat through systems simulated through phonon Monte Carlo methods is concentrated into a channel smaller than the wire dimensions, while this is not the case in the classical solutions of the Fourier model.

Abstract Background The Cancer Center Cessation Initiative (C3I) is a National Cancer Institute (NCI) Cancer Moonshot Program that supports NCI-designated cancer centers developing tobacco treatment programs for oncology patients who smoke. C3I-funded centers implement evidence-based programs that offer various smoking cessation treatment components (e.g., counseling, Quitline referrals, access to medications). While evaluation of implementation outcomes in C3I is guided by evaluation of reach and effectiveness (via RE-AIM), little is known about technical efficiency—i.e., how inputs (e.g., program costs, staff time) influence implementation outcomes (e.g., reach, effectiveness). This study demonstrates the application of data envelopment analysis (DEA) as an implementation science tool to evaluate technical efficiency of C3I programs and advance prioritization of implementation resources. Methods DEA is a linear programming technique widely used in economics and engineering for assessing relative performance of production units. Using data from 16 C3I-funded centers reported in 2020, we applied input-oriented DEA to model technical efficiency (i.e., proportion of observed outcomes to benchmarked outcomes for given input levels). The primary models used the constant returns-to-scale specification and featured cost-per-participant, total full-time equivalent (FTE) effort, and tobacco treatment specialist effort as model inputs and reach and effectiveness (quit rates) as outcomes. Results In the DEA model featuring cost-per-participant (input) and reach/effectiveness (outcomes), average constant returns-to-scale technical efficiency was 25.66 (SD = 24.56). When stratified by program characteristics, technical efficiency was higher among programs in cohort 1 (M = 29.15, SD = 28.65, n = 11) vs. cohort 2 (M = 17.99, SD = 10.16, n = 5), with point-of-care (M = 33.90, SD = 28.63, n = 9) vs. no point-of-care services (M = 15.59, SD = 14.31, n = 7), larger (M = 33.63, SD = 30.38, n = 8) vs. smaller center size (M = 17.70, SD = 15.00, n = 8), and higher (M = 29.65, SD = 30.99, n = 8) vs. lower smoking prevalence (M = 21.67, SD = 17.21, n = 8). Conclusion Most C3I programs assessed were technically inefficient relative to the most efficient center benchmark and may be improved by optimizing the use of inputs (e.g., cost-per-participant) relative to program outcomes (e.g., reach, effectiveness). This study demonstrates the appropriateness and feasibility of using DEA to evaluate the relative performance of evidence-based programs.

The recovery and re-calibration of a dataset of vertical aerosol extinction profiles of the 1963/64 stratospheric aerosol layer measured by a searchlight at 32° N in New Mexico, US, is reported. The recovered dataset consists of 105 aerosol extinction profiles at 550 nm that cover the period from December 1963 to December 1964. It is a unique record of the portion of the aerosol cloud from the March 1963 Agung volcanic eruption that was transported into the Northern Hemisphere subtropics. The data-recovery methodology involved re-digitizing the 105 original aerosol extinction profiles from individual Figures within a research report, followed by the re-calibration. It involves inverting the original equation used to compute the aerosol extinction profile to retrieve the corresponding normalized detector response profile. The re-calibration of the original aerosol extinction profiles used Rayleigh extinction profiles calculated from local soundings. Rayleigh and aerosol slant transmission corrections are applied using the MODTRAN code in transmission mode. Also, a best-estimate aerosol phase function was calculated from observations and applied to the entire column. The tropospheric aerosol phase function from an AERONET station in the vicinity of the searchlight location was applied between 2.76 to 11.7 km. The stratospheric phase function, applied for a 12.2 to 35.2 km altitude range, is calculated from particle-size distributions measured by a high-altitude aircraft in the vicinity of the searchlight in early 1964. The original error estimate was updated considering unaccounted errors. Both the re-calibrated aerosol extinction profiles and the re-calibrated stratospheric aerosol optical depth magnitudes showed higher magnitudes than the original aerosol extinction profiles and the original stratospheric aerosol optical depth, respectively. However, the magnitudes of the re-calibrated variables show a reasonable agreement with other contemporary observations. The re-calibrated stratospheric aerosol optical depth demonstrated its consistency with the tropics-to-pole decreasing trend, associated with the major volcanic eruption stratospheric aerosol pattern when compared to the time-coincident stratospheric aerosol optical depth lidar observations at Lexington at 42° N.

Mycotoxins are potent fungal toxins that frequently contaminate agricultural crops and foods. Mycotoxin exposure is frequently reported in humans, and children are known to be particularly at risk of exceeding safe levels of exposure. Urinary biomonitoring is used to assess overall dietary exposure to multiple mycotoxins. This study aims to quantify multi-mycotoxin exposure in UK children and to identify major food groups contributing to exposure. Four repeat urine samples were collected from 29 children (13 boys and 16 girls, aged 2.4–6.8 years), and food diaries were recorded to assess their exposure to eleven mycotoxins. Urine samples (n = 114) were hydrolysed with β-glucuronidase, enriched through immunoaffinity columns and analysed by LC-MS/MS for deoxynivalenol (DON), nivalenol (NIV), T-2/HT-2 toxins, zearalenone (ZEN), ochratoxin A (OTA) and aflatoxins. Food diaries were analysed using WinDiet software, and the daily intake of high-risk foods for mycotoxin contamination summarised. The most prevalent mycotoxins found in urine samples were DON (95.6% of all samples), OTA (88.6%), HT-2 toxin (53.5%), ZEN (48.2%) and NIV (26.3%). Intake of total cereal-based foods was strongly positively associated with urinary levels of DON and T-2/HT-2 and oat intake with urinary T-2/HT-2. Average daily mycotoxin excretion ranged from 12.10 µg/d (DON) to 0.03 µg/d (OTA), and co-exposure to three or more mycotoxins was found in 66% of samples. Comparing mycotoxin intake estimates to tolerable daily intakes (TDI) demonstrates frequent TDI exceedances (DON 34.2% of all samples, T-2/HT-2 14.9%, NIV 4.4% and ZEN 5.2%). OTA was frequently detected at low levels. When mean daily OTA intake was compared to the reference value for non-neoplastic lesions, the resulting Margin of Exposure (MoE) of 65 was narrow, indicating a health concern. In conclusion, this study demonstrates frequent exposure of UK children to multiple mycotoxins at levels high enough to pose a health concern if exposure is continuous.

Abstract Substantial and prolonged enhancements in stratospheric water vapor (SWV) have occurred after large‐magnitude explosive tropical volcanic eruptions, with modified tropopause entry caused by aerosol‐absorptive heating. Here, we analyze the timing and longevity of heating‐driven post‐eruption SWV changes within CMIP6‐VolMIP short‐term climate‐response experiments with the UK Earth System Model (UKESM1). We find aerosol‐absorptive heating causes peak SWV increases of 17% (∼1 ppmv) and 10% (0.5 ppmv) at 100 and 50 hPa, at ∼18 and ∼23 months after a Pinatubo‐like eruption, respectively. We track the temperature response in the tropical lower stratosphere and identify the main SWV increase occurs only after the descending aerosol heating reaches the tropopause, suggesting a key role for aerosol microphysical processes (sedimentation rate). We explore how El Niño–Southern Oscillation variability modulates this effect. Post‐eruption SWV increases are ∼80% stronger for the La Nina phase compared to the ensemble mean. Tropical upwelling strongly mediates this effect.

Raft-Seq is a generalizable pooled screening platform that combines high-content imaging, machine learning and microraft isolation, and enables efficient screening of genetic perturbations based on their impact on phenotypes.

The molecular mechanisms ensuring the specialized structure of small intestinal villus tip blood vessels are incompletely understood. Here the authors show that ADAMTS18+ telocytes maintain a “just-right” level and location of VEGFA signaling on intestinal villus blood vessels, thereby ensuring the presence of endothelial fenestrae for nutrient absorption, while avoiding excessive leakiness and destabilization of villus tip epithelial structures.

Abstract Effective approaches towards sustainability need to be informed by a diverse array of stakeholder perspectives. However, capturing these perspectives in a way that can be integrated with other forms of knowledge can represent a challenge. Here we present the first application of the conceptual framework of the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services (IPBES) to a participatory assessment of local perspectives on nature, people and sustainability on Mount Kilimanjaro, Tanzania. This assessment was organized in the form of a participatory workshop with five different groups of stakeholders. Following this framework, we assembled information on the state of and trends in species diversity, Nature's Contributions to People (NCP), and on the main drivers of changes in species and habitats. Additionally, we gathered perspectives on the needs and opportunities for the sustainable management and conservation of natural resources from the individual to the international level. The various stakeholders agreed that both the condition and extent of the various habitats and NCP are declining. In line with available knowledge, the key direct drivers of change mentioned by the workshop participants were land use and climate change, whereas human population growth was singled out as the most important indirect driver. The most frequently suggested measures to address the observed decline in species diversity and its drivers were related to land and water management and to education and awareness raising. Yet, the stakeholder groups differed in the measures they suggested. The willingness of a diversity of knowledge holders to systematically engage in a structured discussion around all the elements of the IPBES framework provides support for its applicability in participatory workshops aimed at capturing nuanced and context‐based perspectives on social–ecological systems from informed stakeholders. The application of the IPBES framework enabled the comparability needed for developing narratives of stakeholder visions that can help identify new pathways towards sustainability and guide planning while retaining the context‐based nuances that remain unresolved with non‐participatory methods. Read the free Plain Language Summary for this article on the Journal blog.

Summary: Much of systems neuroscience posits the functional importance of brain activity patterns that lack natural scales of sizes, durations, or frequencies. The field has developed prominent, and sometimes competing, explanations for the nature of this scale-free activity. Here, we reconcile these explanations across species and modalities. First, we link estimates of excitation-inhibition (E-I) balance with time-resolved correlation of distributed brain activity. Second, we develop an unbiased method for sampling time series constrained by this time-resolved correlation. Third, we use this method to show that estimates of E-I balance account for diverse scale-free phenomena without need to attribute additional function or importance to these phenomena. Collectively, our results simplify existing explanations of scale-free brain activity and provide stringent tests on future theories that seek to transcend these explanations.

Smoking cessation after a cancer diagnosis can improve health outcomes, but the Coronavirus disease 2019 (COVID-19) pandemic significantly altered healthcare patterns and strained resources, including for smoking cessation support for cancer patients. A Network that included all 13 provinces and territories (jurisdictions) in Canada received funding and coordinated support from a national organization to implement access to smoking cessation support in cancer care between 2016 and 2021, including throughout the COVID-19 pandemic. Descriptive analyses of meetings between the organization and jurisdictions between March of 2020 and August of 2021 demonstrated that all jurisdictions reported disruptions of existing smoking cessation approaches. Common challenges include staff redeployment, inability to deliver support in person, disruptions in travel, and loss of connections with other clinical resources. Common adaptations included budget and workflow adjustments, transition to virtual approaches, partnering with other community resources, and coupling awareness of the harms of smoking and COVID-19. All jurisdictions reported adaptations that maintained or improved access to smoking cessation services. Collectively, data suggest coordinated national efforts to address smoking cessation in cancer care could be crucial to maintaining access during an international healthcare crisis.

Introduction: In primary hyperoxaluria type 1 (PH1), oxalate overproduction frequently causes kidney stones, nephrocalcinosis, and kidney failure. As PH1 is caused by a congenital liver enzyme defect, combined liver–kidney transplantation (CLKT) has been recommended in patients with kidney failure. Nevertheless, systematic analyses on long-term transplantation outcomes are scarce. The merits of a sequential over combined procedure regarding kidney graft survival remain unclear as is the place of isolated kidney transplantation (KT) for patients with vitamin B6-responsive genotypes. Methods: We used the OxalEurope registry for retrospective analyses of patients with PH1 who underwent transplantation. Analyses of crude Kaplan–Meier survival curves and adjusted relative hazards from the Cox proportional hazards model were performed. Results: A total of 267 patients with PH1 underwent transplantation between 1978 and 2019. Data of 244 patients (159 CLKTs, 48 isolated KTs, 37 sequential liver–KTs [SLKTs]) were eligible for comparative analyses. Comparing CLKTs with isolated KTs, adjusted mortality was similar in patients with B6-unresponsive genotypes but lower after isolated KT in patients with B6-responsive genotypes (adjusted hazard ratio 0.07, 95% CI: 0.01–0.75, P = 0.028). CLKT yielded higher adjusted event-free survival and death-censored kidney graft survival in patients with B6-unresponsive genotypes (P = 0.025, P < 0.001) but not in patients with B6-responsive genotypes (P = 0.145, P = 0.421). Outcomes for 159 combined procedures versus 37 sequential procedures were comparable. There were 12 patients who underwent pre-emptive liver transplantation (PLT) with poor outcomes. Conclusion: The CLKT or SLKT remains the preferred transplantation modality in patients with PH1 with B6-unresponsive genotypes, but isolated KT could be an alternative approach in patients with B6-responsive genotypes.

Abstract The artificial intelligence revolution has been spurred forward by the availability of large-scale datasets. In contrast, the paucity of large-scale medical datasets hinders the application of machine learning in healthcare. The lack of publicly available multi-centric and diverse datasets mainly stems from confidentiality and privacy concerns around sharing medical data. To demonstrate a feasible path forward in medical image imaging, we conduct a case study of applying a differentially private federated learning framework for analysis of histopathology images, the largest and perhaps most complex medical images. We study the effects of IID and non-IID distributions along with the number of healthcare providers, i.e., hospitals and clinics, and the individual dataset sizes, using The Cancer Genome Atlas (TCGA) dataset, a public repository, to simulate a distributed environment. We empirically compare the performance of private, distributed training to conventional training and demonstrate that distributed training can achieve similar performance with strong privacy guarantees. We also study the effect of different source domains for histopathology images by evaluating the performance using external validation. Our work indicates that differentially private federated learning is a viable and reliable framework for the collaborative development of machine learning models in medical image analysis.

Objective To assess the impact of the COVID-19 pandemic on venous leg ulcer (VLU) management by the UK’s health services and associated outcomes.Design Retrospective cohort analysis of the electronic records of patients from The Health Improvement Network database.Setting Clinical practice in primary and secondary care.Participants A cohort of 1946 patients of whom 1263, 1153 and 733 had a VLU in 2019, 2020 and 2021, respectively.Primary and secondary outcome measures Clinical outcomes and wound-related healthcare resource use.Results VLU healing rate in 2020 and 2021 decreased by 16% and 42%, respectively, compared with 2019 and time to heal increased by >85%. An estimated 3% of patients in 2020 and 2021 had a COVID-19 infection. Also, 1% of patients in both years had VLU-related sepsis, 0.1%–0.2% developed gangrene and 0.3% and 0.6% underwent an amputation on part of the foot or lower limb in 2020 and 2021 (of whom 57% had diabetes), respectively. The number of community-based face-to-face clinician visits decreased by >50% in both years and >35% fewer patients were referred to a hospital specialist. In 2020 and 2021, up to 20% of patients were prescribed dressings without compression compared with 5% in 2019. The total number of wound care products prescribed in 2020 and 2021 was >50% less than that prescribed in 2019, possibly due to the decreased frequency of dressing change from a mean of once every 11 days in 2019 to once every 21 days in 2020 and 2021.Conclusions There was a significant trend towards decreasing care during 2020 and 2021, which was outside the boundaries considered to be good care. This led to poorer outcomes including lower VLU healing rates and increased risk of amputation. Hence, the COVID-19 pandemic appears to have had a deleterious impact on the health of patients with a VLU.

ObjectiveA scoping review of studies published in the first year of the COVID-19 pandemic focused on individuals with pre-existing symptoms of depression, anxiety, and specified stressor-related disorders, with the objective of mapping the research conducted.Eligibility criteria(1) direct study of individuals with pre-existing depressive, anxiety, and/or specified stressor-related (i.e., posttraumatic stress, acute stress) disorders/issues; (2) focus on mental health-related pandemic effects, and; (3) direct study of mental health symptoms related to depression, anxiety, or psychological distress.Sources of evidenceDatabase-specific subject headings and natural language keywords were searched in Medline, Embase, APA PsycInfo, and Cumulative Index to Nursing & Allied Health Literature (CINAHL) up to March 3, 2021. Review of potentially relevant studies was conducted by two independent reviewers and proceeded in two stages: (1) title and abstract review, and; (2) full paper review.Data chartingStudy details (i.e., location, design and methodology, sample or population, outcome measures, and key findings) were extracted from included studies by one reviewer and confirmed by the Principal Investigator.Results66 relevant articles from 26 countries were identified. Most studies adopted a cross-sectional design and were conducted via online survey. About half relied on general population samples, with the remainder assessing special populations, primarily mental health patients. The most commonly reported pre-existing category of disorders or symptoms was depression, followed closely by anxiety. Most studies included depressive and anxiety symptoms as outcome measures and demonstrated increased vulnerability to mental health symptoms among individuals with a pre-existing mental health issue.ConclusionThese findings suggest that improved mental health supports are needed during the pandemic and point to future research needs, including reviews of other diagnostic categories and reviews of research published in subsequent years of the pandemic.

ATTR amyloidosis causes heart failure through the accumulation of misfolded transthyretin in cardiac muscle. Here the authors report a mouse model of ATTR amyloidosis and demonstrate the involvement of protease activity in ATTR amyloid deposition.

Summary: Lignin recovered from poplar, a key woody biomass resource proposed for lignocellulosic refineries, was investigated for conversion into carbon fibers. Aqueous solutions of ethanol at selected temperatures and compositions, where the requisite solvent and liquefied-lignin phases form, were used to purify and fractionate hybrid poplar (HP) lignin using the Aqueous Lignin Purification with Hot Agents (ALPHA) process. Sugars (

It is unclear why C. elegans continues to produce large quantities of yolk after reproduction. Here the authors show that post-reproductive C. elegans mothers vent yolk which supports their offspring’s growth, serving as a form of primitive lactation.

IntroductionSubstantial response heterogeneity is commonly seen in dietary intervention trials. In larger datasets, this variability can be exploited to identify predictors, for example genetic and/or phenotypic baseline characteristics, associated with response in an outcome of interest.ObjectiveUsing data from a placebo-controlled crossover study (the FINGEN study), supplementing with two doses of long chain n-3 polyunsaturated fatty acids (LC n-3 PUFAs), the primary goal of this analysis was to develop models to predict change in concentrations of plasma triglycerides (TG), and in the plasma phosphatidylcholine (PC) LC n-3 PUFAs eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA), after fish oil (FO) supplementation. A secondary goal was to establish if clustering of data prior to FO supplementation would lead to identification of groups of participants who responded differentially.MethodsTo generate models for the outcomes of interest, variable selection methods (forward and backward stepwise selection, LASSO and the Boruta algorithm) were applied to identify suitable predictors. The final model was chosen based on the lowest validation set root mean squared error (RMSE) after applying each method across multiple imputed datasets. Unsupervised clustering of data prior to FO supplementation was implemented using k-medoids and hierarchical clustering, with cluster membership compared with changes in plasma TG and plasma PC EPA + DHA.ResultsModels for predicting response showed a greater TG-lowering after 1.8 g/day EPA + DHA with lower pre-intervention levels of plasma insulin, LDL cholesterol, C20:3n-6 and saturated fat consumption, but higher pre-intervention levels of plasma TG, and serum IL-10 and VCAM-1. Models also showed greater increases in plasma PC EPA + DHA with age and female sex. There were no statistically significant differences in PC EPA + DHA and TG responses between baseline clusters.ConclusionOur models established new predictors of response in TG (plasma insulin, LDL cholesterol, C20:3n-6, saturated fat consumption, TG, IL-10 and VCAM-1) and in PC EPA + DHA (age and sex) upon intervention with fish oil. We demonstrate how application of statistical methods can provide new insights for precision nutrition, by predicting participants who are most likely to respond beneficially to nutritional interventions.

Abstract Background Diagnosis of a chronic illness, such as cancer may influence health behavior changes, such as smoking cessation. The present analyses examine associations between a cancer diagnosis (i.e., yes or no) and response to an opt‐out smoking cessation bedside intervention provided to hospitalized patients. It was hypothesized that patients with a past or present cancer diagnosis would report higher motivation and engagement with quitting smoking, and higher rates of smoking abstinence after hospital discharge, compared to those without a cancer diagnosis. Methods Chart review was conducted on 5287 inpatients who accepted bedside treatment from a counselor and opted‐in to automated follow‐up calls from July 2014 to December 2019. Results At the time of inpatient assessment, those with a past or present cancer diagnosis (n = 419, 7.9%) endorsed significantly higher levels of importance of quitting than those without a cancer diagnosis (3.92/5 vs. 3.77/5), and were more likely to receive smoking cessation medication upon discharge (17.9% vs. 13.3%). Follow‐up data from 30‐days post‐discharge showed those with a cancer diagnosis endorsed higher rates of self‐reported abstinence (20.5%) than those without a cancer diagnosis (10.3%; p

Abstract The research presented in this paper provides an insight into the behavioral ecology of mountain hares on heather moorland in the Lammermuir Hills of southeast Scotland. We examine the seasonal and diel activity patterns using camera traps over a period of 12 months. The rate of camera detections was calculated for the different divisions of the 24‐hr cycle (daylight, dusk, night, and dawn). During autumn and winter (October–February), the activity pattern was crepuscular with greater activity at dusk than at dawn. Daylight activity was relatively low, and there was a regular pattern of small peaks of activity during the night. In spring and summer (March–September), peaks of crepuscular activity remained evident but daylight activity was much more prevalent than during autumn and winter, and night activity was lower. We discuss the problematic definition of twilight and present an explanation for seasonal changes in the pattern of diel activity that is linked to the reproductive cycle of the mountain hare.

Purpose The objective of this study was to determine how to optimize implementation of tobacco cessation treatment interventions in cancer care by (1) investigating the feasibility and acceptability of a multi-level approach to tobacco cessation treatment intervention, (2) identifying barriers and facilitators to implementation, and (3) eliciting additional strategies to improve implementation of the intervention. Methods We conducted qualitative interviews with oncologists ( n = 15) from one large academic health center in the Southeastern United States. We asked about their knowledge, attitudes, and current practices regarding tobacco use screening and treatment. We also asked about two proposed strategies to support implementation of tobacco cessation treatment: (1) developing a registry of tobacco users in collaboration with the state-run tobacco cessation program, and (2) providing on-site tobacco cessation counseling from trained professionals. Results Oncologists saw addressing tobacco use as valuable; however, they felt restricted from consistently addressing tobacco use by multi-level barriers such as workload, electronic health record (EHR) design, patient anxiety, and low self-efficacy for treating tobacco dependence. Oncologists responded positively to on-site treatment and felt this strategy would increase treatment accessibility and enhance engagement. Reaction to developing a registry of tobacco users was mixed, with concerns regarding lack of oncologist involvement and patient privacy expressed. Other suggested strategies for supporting implementation of tobacco cessation treatment included reducing referral complexity, establishing financial or quality incentives for oncologists, and leveraging existing EHR tools to facilitate integration of cessation interventions into clinic workflows. Conclusions We identified several challenges to implementing tobacco use treatment in cancer care; however, we considered strategies to overcome these barriers that were viewed as feasible and acceptable. Our work highlights the importance of engaging stakeholders in implementation efforts. Future work should explore the impact of the implementation strategies identified in this study. Plain Language Summary Tobacco cessation significantly improves cancer patients’ treatment outcomes, quality of life, and chances of survival; however, tobacco cessation interventions are not routinely delivered in oncology care. Interviews with oncologists identified barriers to delivering tobacco cessation interventions at multiple levels. Suggested strategies for overcoming these barriers included simplifying cessation intervention processes, establishing incentives for oncologists to address tobacco use, and using the electronic health record to support intervention activities. Oncologists generally supported implementing on-site tobacco cessation counseling for cancer patients. Although there was support for developing a registry of tobacco users with an external tobacco cessation program, more reservations were expressed. Our work identifies several stakeholder-endorsed strategies for implementing tobacco cessation interventions in cancer care. Future research should test the effectiveness of these strategies.

Abstract Background The Cancer Center Cessation Initiative (C3I) was launched in 2017 as a part of the NCI Cancer Moonshot program to assist NCI-designated cancer centers in developing tobacco treatment programs for oncology patients. Participating centers have implemented varied evidence-based programs that fit their institutional resources and needs, offering a wide range of services including in-person and telephone-based counseling, point of care, interactive voice response systems, referral to the quitline, text- and web-based services, and medications. Methods We used a mixed methods comparative case study design to evaluate system-level implementation costs across 15 C3I-funded cancer centers that reported for at least one 6-month period between July 2018 and June 2020. We analyzed operating costs by resource category (e.g., personnel, medications) concurrently with transcripts from semi-structured key-informant interviews conducted during site visits. Personnel salary costs were estimated using Bureau of Labor Statistics wage data adjusted for area and occupation, and non-wage benefits. Qualitative findings provided additional information on intangible resources and contextual factors related to implementation costs. Results Median total monthly operating costs across funded centers were $11,045 (range: $5129–$20,751). The largest median operating cost category was personnel ($10,307; range: $4122–$19,794), with the highest personnel costs attributable to the provision of in-person program services. Monthly (non-zero) cost ranges for other categories were medications ($17–$573), materials ($6–$435), training ($96–$516), technology ($171–$2759), and equipment ($10–$620). Median cost-per-participant was $466 (range: $70–$2093) and cost-per-quit was $2688 (range: $330–$9628), with sites offering different combinations of program components, ranging from individually-delivered in-person counseling only to one program that offered all components. Site interviews provided context for understanding variations in program components and their cost implications. Conclusions Among most centers that have progressed in tobacco treatment program implementation, cost-per-quit was modest relative to other prevention interventions. Although select centers have achieved similar average costs by offering program components of various levels of intensity, they have varied widely in program reach and effectiveness. Evaluating implementation costs of such programs alongside reach and effectiveness is necessary to provide decision makers in oncology settings with the important additional information needed to optimize resource allocation when establishing tobacco treatment programs.

Abstract Epigenetic imprinting is important for neurogenesis and brain function. Hippocampal volumes and brain hyperintensities in late life have been associated with early life circumstances. Epigenetic imprinting may underpin these associations. Methylation was measured at 982 sites in 13 imprinted locations in blood samples from a longitudinal cohort by bisulphite amplicon sequencing. Hippocampal volumes and hyperintensities were determined at age 64y and 72y using MRI. Hyperintensities were determined in white matter, grey matter and infratentorial regions. Permutation methods were used to adjust for multiple testing. At 64y, H19/IGF2 and NESPAS methylation predicted hippocampal volumes. PEG3 predicted hyperintensities in hippocampal grey matter, and white matter. GNASXL predicted grey matter hyperintensities. Changes with age were predicted for hippocampal volume (MEST1, KvDMR, L3MBTL, GNASXL), white matter (MEST1, PEG3) and hippocampal grey matter hyperintensities (MCTS2, GNASXL, NESPAS, L3MBTL, MCTS2, SNRPN, MEST1). Including childhood cognitive ability, years in education, or socioeconomic status as additional explanatory variables in regression analyses did not change the overall findings. Imprinting methylation in multiple genes predicts brain structures, and their change over time. These findings are potentially relevant to the development of novel tests of brain structure and function across the life-course, strategies to improve cognitive outcomes, and our understanding of early influences on brain development and function.

Due to their success at synthesising highly realistic images, many claims have been made about optimality and convergence in generative adversarial networks (GANs). But what of vanishing gradients, saturation, and other numerical problems noted by AI practitioners? Attempts to explain these phenomena have so far been based on purely empirical studies or differential equations, valid only in the limit. We take a fresh look at these questions using explicit, low-dimensional models. We revisit the well known optimal discriminator result and, by construction of a counterexample, show that it is not valid in the case of practical interest: when the dimension of the latent variable is less than that of the data: ${\mathrm{ dim}}({\mathbf{z}}) < {\mathrm{ dim}}({\mathbf{x}})$ . To examine convergence issues, we consider a 1-D least squares (LS) GAN with exponentially distributed data, a Rayleigh distributed latent variable, a square law generator and a discriminator of the form $D(x)=(1+ {\text {erf}}(x))/2$ where erf is the error function. We obtain explicit representations of the cost (or loss) function and its derivatives. The representation is exact down to the evaluation of a well-behaved 1-D integral. We present analytical numerical examples of 2D and 4D parameter trajectories for gradient-based minimax optimisation. Although the cost function has no saddle points, it generally has a minimum, maximum and plateaux areas. The gradient algorithms typically converge to a plateau, where the gradients vanish and the cost function saturates. This is an undesirable setting with no implications of optimality for either the generator or discriminator. The analytical method is compared with stochastic gradient optimisation and proven to be a very accurate predictor of the latter’s performance. The quasi-deterministic framework we develop is a powerful analytical tool for understanding convergence behaviour of low-dimensional GANs based on least-squares cost criteria.

AbstractWe measured MRI network progression in mesial temporal lobe epilepsy (mTLE) patients as a function of healthy brain architecture. Resting-state functional MRI and diffusion-weighted MRI were acquired in 40 unilateral mTLE patients and 70 healthy controls. Data were used to construct region-to-region functional connectivity, structural connectivity, and streamline length connectomes per subject. Three models of distance from the presumed seizure focus in the anterior hippocampus in the healthy brain were computed using the average connectome across controls. A fourth model was defined using regions of transmodal (higher cognitive function) to unimodal (perceptual) networks across a published functional gradient in the healthy brain. These models were used to test whether network progression in patients increased when distance from the anterior hippocampus or along a functional gradient in the healthy brain decreases. Results showed that alterations of structural and functional networks in mTLE occur in greater magnitude in regions of the brain closer to the seizure focus based on healthy brain topology, and decrease as distance from the focus increases over duration of disease. Overall, this work provides evidence that changes across the brain in focal epilepsy occur along healthy brain architecture.

Most of our understanding of the ecology and evolution of avian influenza A virus (AIV) in wild birds is derived from studies conducted in the northern hemisphere on waterfowl, with a substantial bias towards dabbling ducks. However, relevant environmental conditions and patterns of avian migration and reproduction are substantially different in the southern hemisphere. Through the sequencing and analysis of 333 unique AIV genomes collected from wild birds collected over 15 years we show that Australia is a global sink for AIV diversity and not integrally linked with the Eurasian gene pool. Rather, AIV are infrequently introduced to Australia, followed by decades of isolated circulation and eventual extinction. The number of co-circulating viral lineages varies per subtype. AIV haemagglutinin (HA) subtypes that are rarely identified at duck-centric study sites (H8-12) had more detected introductions and contemporary co-circulating lineages in Australia. Combined with a lack of duck migration beyond the Australian-Papuan region, these findings suggest introductions by long-distance migratory shorebirds. In addition, on the available data we found no evidence of directional or consistent patterns in virus movement across the Australian continent. This feature corresponds to patterns of bird movement, whereby waterfowl have nomadic and erratic rainfall-dependant distributions rather than consistent intra-continental migratory routes. Finally, we detected high levels of virus gene segment reassortment, with a high diversity of AIV genome constellations across years and locations. These data, in addition to those from other studies in Africa and South America, clearly show that patterns of AIV dynamics in the Southern Hemisphere are distinct from those in the temperate north. Author summary A result of the ever-growing poultry industry is a dramatic global increase in the incidence of high pathogenicity avian influenza virus outbreaks. In contrast, wild birds are believed to be the main reservoir for low pathogenic avian influenza A virus. Due to intensive research and surveillance of AIV in waterfowl in the Northern Hemisphere, we have a better understanding of AIV ecology and evolution in that region compared to the Southern Hemisphere, which are characterised by different patterns of avian migration and ecological conditions. We analysed 333 unique AIV genomes collected from wild birds in Australia to understand how Australia fits into global AIV dynamics and how viruses are maintained and dispersed within the continent of Australia. We show that the Southern Hemisphere experiences differing evolutionary dynamics to those seen in Northern Hemisphere with Australia representing a global sink for AIV.

Ranaviral infections have been associated with mass mortality events in captive and wild amphibian, fish, and reptile populations globally. In Australia, two distinct types of ranaviruses have been isolated: epizootic haematopoietic necrosis virus in fish and a Frog virus 3-like ranavirus in amphibians. Experimental studies and serum surveys have demonstrated that several Australian native fish, amphibian, and reptile species are susceptible to infection and supported the theory that ranavirus is naturally circulating in Australian herpetofauna. However, ranaviral infections have not been detected in captive or wild lizards in Australia. Oral-cloacal swabs were collected from 42 wild lizards from northern Queensland and 83 captive lizards from private collections held across three states/territories. Samples were tested for ranaviral DNA using a quantitative PCR assay. This assay detected ranaviral DNA in 30/83 (36.1%) captive and 33/42 (78.6%) wild lizard samples. This is the first time molecular evidence of ranavirus has been reported in Australian lizards.

Abstract Ecological camera traps are increasingly used by wildlife biologists to unobtrusively monitor an ecosystems animal population. However, manual inspection of the images produced is expensive, laborious, and time‐consuming. The success of deep learning systems using camera trap images has been previously explored in preliminary stages. These studies, however, are lacking in their practicality. They are primarily focused on extremely large datasets, often millions of images, and there is little to no focus on performance when tasked with species identification in new locations not seen during training. Our goal was to test the capabilities of deep learning systems trained on camera trap images using modestly sized training data, compare performance when considering unseen background locations, and quantify the gradient of lower bound performance to provide a guideline of data requirements in correspondence to performance expectations. We use a dataset provided by Parks Canada containing 47,279 images collected from 36 unique geographic locations across multiple environments. Images represent 55 animal species and human activity with high‐class imbalance. We trained, tested, and compared the capabilities of six deep learning computer vision networks using transfer learning and image augmentation: DenseNet201, Inception‐ResNet‐V3, InceptionV3, NASNetMobile, MobileNetV2, and Xception. We compare overall performance on “trained” locations where DenseNet201 performed best with 95.6% top‐1 accuracy showing promise for deep learning methods for smaller scale research efforts. Using trained locations, classifications with

The globular to fibrillar transition of proteins represents a key pathogenic event in the development of amyloid diseases. Although systemic amyloidoses share the common characteristic of amyloid deposition in the extracellular matrix, they are clinically heterogeneous as the affected organs may vary. The observation that precursors of amyloid fibrils derived from circulating globular plasma proteins led to huge efforts in trying to elucidate the structural events determining the protein metamorphosis from their globular to fibrillar state. Whereas the process of metamorphosis has inspired poets and writers from Ovid to Kafka, protein metamorphism is a more recent concept. It is an ideal metaphor in biochemistry for studying the protein folding paradigm and investigating determinants of folding dynamics. Although we have learned how to transform both normal and pathogenic globular proteins into fibrillar polymers in vitro, the events occurring in vivo, are far more complex and yet to be explained. A major gap still exists between in vivo and in vitro models of fibrillogenesis as the biological complexity of the disease in living organisms cannot be reproduced at the same extent in the test tube. Reviewing the major scientific attempts to monitor the amyloidogenic metamorphosis of globular proteins in systems of increasing complexity, from cell culture to human tissues, may help to bridge the gap between the experimental models and the actual pathological events in patients.

Main objectiveThere is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic.Study design and methodsUniversity of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission.Results and significanceThe 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months.ConclusionsMortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes.Trial registrationClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528).

Oxidized β-carotene (OxBC), a phytochemical that occurs naturally in plants, is formed by the spontaneous reaction of β-carotene with ambient oxygen. Synthetic OxBC, obtained by full oxidation of β-carotene with air, shows considerable promise as an in-feed antimicrobial alternative additive that enhances health and performance in livestock. OxBC is predominantly composed of β-carotene-oxygen copolymers that have beneficial immune-modulating effects that occur within the innate immune system by priming it to face microbial challenges and by mitigating the inflammatory response. OxBC does not have any direct anti-bacterial activity. Further, unlike traditional immune stimulants, OxBC modulates but does not stimulate and utilize the animal’s energy stores unless directly stress-challenged. These immune effects occur by mechanisms distinct from the provitamin A or antioxidant pathways commonly proposed as explanations for β-carotene’s actions. Trials in poultry, swine, and dairy cows with low parts-per-million in-feed OxBC supplementation have shown performance benefits over and above those of feeds containing regular vitamin and mineral premixes. Through its ability to enhance immune function, health, and performance, OxBC has demonstrated utility not only as a viable alternative to in-feed antimicrobials but also in its ability to provide tangible health and performance benefits in applications where antimicrobial usage is precluded.