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Objective: Systemic lupus erythematosus (SLE) is a chronic inflammatory disease associated with vascular derangement [1]. Leptin and adiponectin are adipokines with immunomodulatory and vascular functions [2]. We studied the association between arterial stiffness and plasma leptin and adiponectin levels in SLE patients in Ghana. Methods: In a case control design involving 80 SLE patients and 90 non-SLE controls, arterial stiffness was assessed by cardio-ankle vascular index (CAVI) and heart-ankle pulse wave velocity (haPWV) using Vasera 1500N. Circulating levels of leptin, adiponectin, insulin and C-reactive protein (CRP) were measured by ELISA. Results: Compared to non-SLE controls, SLE patients had higher levels of CAVI (7.3±1.1 vs 6.1±1, p < 0.001), haPWV (7.7±1.3 vs 6.5±0.8 m/s, p =

Abstract Introduction and aims Retroperitoneal fibrosis (RPF) is a fibroinflammatory disease in which patients may suffer obstructive uropathy (OU). The optimum treatment strategy for RPF with secondary OU is currently unclear, and the aim of this literature review is to assess the methods used to treat this patient cohort. Methods Medline, Embase, Cinahl, the Cochrane Library and PubMed were systematically searched to find studies assessing treatment outcomes in this patient cohort. After reviewing the studies' titles, abstracts and full texts, 12 were found that matched our search aims. Data from these publications were analysed and reported. Results The demographic and symptomatic features of patients across the 12 studies were representative of the general RPF population. No randomised control trials (RCTs) were found, and just one study formally compared outcomes between patients who underwent different treatment strategies. Many of the studies concluded that using medical and surgical methods in combination led to positive outcomes; whereas, others found positive outcomes following a variety of regimens. Many studies also highlighted, however, that significant minorities required further treatment after initial therapy. Conclusions regarding optimum treatment methods were limited as most publications did not formally compare outcomes following different strategies and had an observational study design. Conclusion Although positive outcomes were commonly seen following medical, surgical and a combination of treatments, the literature currently lacks research formally comparing outcomes after assigning specific treatment protocols to groups of RPF patients. More research is therefore required to determine how to best manage RPF leading to secondary OU.

Papua New Guinea’s health system faces ongoing challenges in the provision of maternal and child health and has some of the poorest health indicators in the world. In this paper, we describe the impact of COVID-19 on maternal and child health, as examples of primary health care services. We conducted 131 semi-structured interviews with different population groups in seven provinces (Jul–Nov 2021). A deductive analysis focused on identifying the impact of COVID-19 using the World Health Organization building blocks framework. An inductive analysis explored these impacts for maternal and child health services specifically. We identified three broad themes: service disruption, challenges in access to care and service provision. Service disruption included the closure, suspension and relocation of services and workforce challenges due to healthcare worker absences, redeployment and working within an already constrained health system. Access to care was difficult due to lockdowns and restricted movement. Service provision continued despite the fear staff had of COVID-19. Investing in pandemic preparedness, including an adequately trained and resourced healthcare workforce and facilities able to withstand sustained provision of essential services should be integrated with locally appropriate, and timely community-based information to allay fears and mistrust within the healthcare system.

Background: A patient-specific, 3-dimensional-printed, custom glenoid baseplate can be utilized to address severe glenoid deficiency in reverse total shoulder arthroplasty (rTSA). Indications: A 73-year-old woman with right shoulder pain, weakness, and decreased range of motion in the setting of glenohumeral arthritis with severe glenoid bone loss. Additionally, this implant system was used in a 77-year-old man undergoing conversion to rTSA in the setting of glenoid erosion following prior failed total shoulder arthroplasty. Technique Description: A standard deltopectoral approach is utilized. In the revision setting, prior components are removed. Adequate glenoid exposure is obtained to allow for positioning and implantation of the custom glenoid baseplate. The glenoid is prepared utilizing patient-specific guides and trials before the custom glenoid component is seated within the glenoid vault and fixated with locking screws. Compatible glenosphere and humeral components are utilized for the remainder of the surgical procedure, as performed standardly. Results: There were no immediate complications following surgery. Surgical management led to improvement in the patient's pain and shoulder function. Discussion/Conclusion: Patient-specific, 3-dimensional-printed, custom glenoid baseplates may be used to manage severe glenoid deformity and bone loss in patients indicated for primary or revision rTSA. Patient Consent Disclosure Statement: The author(s) attests that consent has been obtained from any patient(s) appearing in this publication. If the individual may be identifiable, the author(s) has included a statement of release or other written form of approval from the patient(s) with this submission for publication.

Several factors, such as human error, environmental factors, and maintenance practices, contribute to the degradation of real-world industrial systems. Predicting system dynamics is challenging and necessitates high user confidence, as these factors contribute to both aleatoric uncertainty (inherent system variability) and epistemic uncertainty (due to limited information). Decision-making and risk assessment are frequently hindered by the inability of current artificial intelligence methods to generate interpretable uncertainty estimates. To address these constraints, we propose an analysis that employs Deep Gaussian Processes (DGPs), a robust framework for generating interpretable uncertainty distributions and capturing system variability. A rigorous mathematical foundation is essential to our approach, because it enables the selection of metrics that effectively capture the system’s degradation aspects. In addition to predicting the remaining useful life, these metrics, when used in conjunction with DGPs, facilitate the creation of a degradation model that is both accurate and dependable. This model also contributes to the improvement of system reliability and proactive maintenance. We demonstrate our approach’s practical efficacy by validating it on a real-world industrial semolina plant with four mills.

This paper introduces and describes a method for extracting, processing, and analyzing large amounts of track geometrical data. It allows for a more accurate description of the orbital deterioration correlations than currently applied procedures, and it seems to be more valuable and efficient in practice. The initial data were the track geometry measurement and classification data for the whole national network provided by the Hungarian State Railways, i.e., the MÁV PLC. The MÁV provided data for the whole Hungarian railway network for 27 half-years, measured and recorded by the FMK-004 type special diesel locomotive (i.e., track geometry measuring car). The paper discusses the development of a procedure to automatically compute important condition ratings from the available data set of millions of units according to the algorithms created for railway industry colleagues, thus helping the maintenance and renewal decision-making process. Functions have been developed to classify the track geometry condition of a given railway line, to predict how long the service level can be maintained without intervention (i.e., e.g., lining, leveling, and tamping with a mechanized maintenance train), to determine the time of the necessary maintenance intervention, the time of the upgrade (rehabilitation or modernization), and to develop a track geometry prediction procedure that makes full use of the mathematical and computational possibilities of the present day.

It is fundamental to obtain accurate land surface temperature (LST) to study surface energy process. Infrared thermal imagers are commonly used for deriving LST on the basis of radiance measurements. However, when deriving LST from brightness temperature of a blackbody in thermal imagers, thermal imagers only allow setting a fixed land surface emissivity (LSE). This causes uncertainty in retrieving thermal infrared (TIR) temperature from heterogeneous surfaces with varied LSE, such as those covered in vegetation. Corrections can be made using the Normalized Vegetation Index (NDVI). However, commercial thermal imagers provide only red (R), green (G), and blue (B) bands without a near infrared band so NDVI cannot be calculated on the same instrument and is commonly not available. We propose an alternative method to estimate LSE using RGB-based vegetation index. Thereafter the estimated LSE was used to correct the TIR temperature derived from the fixed LSE. An experiment was conducted to validate the proposed correcting method. The results show that 1) the corrected LST values were closer to the ground truth, with a mean absolute error (MAE) of 0.41 ± 0.34 °C, whereas the MAE was 0.75 ± 0.56 °C for the uncorrected LST; 2) the more heterogeneous the surface, the greater the difference between the corrected and uncorrected LST values, indicating the necessity of LST correction when applying thermal imagers over heterogeneous surface.

Abstract Background Manual analysis of (mini-)rhizotron (MR) images is tedious. Several methods have been proposed for semantic root segmentation based on homogeneous, single-source MR datasets. Recent advances in deep learning (DL) have enabled automated feature extraction, but comparisons of segmentation accuracy, false positives and transferability are virtually lacking. Here we compare six state-of-the-art methods and propose two improved DL models for semantic root segmentation using a large MR dataset with and without augmented data. We determine the performance of the methods on a homogeneous maize dataset, and a mixed dataset of > 8 species (mixtures), 6 soil types and 4 imaging systems. The generalisation potential of the derived DL models is determined on a distinct, unseen dataset. Results The best performance was achieved by the U-Net models; the more complex the encoder the better the accuracy and generalisation of the model. The heterogeneous mixed MR dataset was a particularly challenging for the non-U-Net techniques. Data augmentation enhanced model performance. We demonstrated the improved performance of deep meta-architectures and feature extractors, and a reduction in the number of false positives. Conclusions Although correction factors are still required to match human labelled root lengths, neural network architectures greatly reduce the time required to compute the root length. The more complex architectures illustrate how future improvements in root segmentation within MR images can be achieved, particularly reaching higher segmentation accuracies and model generalisation when analysing real-world datasets with artefacts—limiting the need for model retraining.

Applications of artificial intelligence (AI) and machine learning (ML) have become pervasive in our everyday lives. These applications range from the mundane (asking ChatGPT to write a thank you note) to high-end science (predicting future weather patterns in the face of climate change), but, because they rely on human-generated or mediated data, they also have the potential to perpetuate systemic oppression and racism. For museums and other cultural heritage institutions, there is great interest in automating the kinds of applications at which AI and ML can excel, for example, tasks in computer vision including image segmentation, object recognition (labelling or identifying objects in an image) and natural language processing (e.g. named-entity recognition, topic modelling, generation of word and sentence embeddings) in order to make digital collections and archives discoverable, searchable and appropriately tagged.A coalition of staff, Fellows and interns working in digital spaces at the Smithsonian Institution, who are either engaged with research using AI or ML tools or working closely with digital data in other ways, came together to discuss the promise and potential perils of applying AI and ML at scale and this work results from those conversations. Here, we present the process that has led to the development of an AI Values Statement and an implementation plan, including the release of datasets with accompanying documentation to enable these data to be used with improved context and reproducibility (dataset cards). We plan to continue releasing dataset cards and for AI and ML applications, model cards, in order to enable informed usage of Smithsonian data and research products.

This paper investigates the impact of natural gas pipeline congestion on the integrated gas–electricity market in Peru, focusing on short-term market dynamics. By simulating congestion by reducing the primary natural gas pipeline’s capacity, the study reveals significant patterns in production costs and load flows within the electrical network. The research highlights the critical interdependencies between natural gas and electricity systems, emphasizing how constraints in one network can directly affect the other. The findings underscore the importance of coordinated management of these interconnected systems to optimize economic dispatch and ensure the reliability of both gas and electricity grids. The study also proposes strategic public policy interventions to mitigate the financial and physical impacts of pipeline congestion, contributing to more efficient and resilient energy market operations.

Abstract Lateral wander of autonomous truck can be further improved by optimizing the uniform wander. Increase in available lane width for the autonomous trucks can increase the performance efficiency of this mode. This research is based on finding the optimum, combination of lane width increment and asphalt layer thickness reduction among different scenarios. Therefore, In this research with assumed maximum lane width of 4.35 m, difference combination of lane width and asphalt layer thickness scenarios have been analyzed using finite element modelling in ABAQUS. Considering the base pavement width of 3.75 m, increment for each scenario is 15 cm and reduction in asphalt layer thickness is at 2 cm. Performance efficiency of each scenario is conducted while considering the initial construction costs and damage assessment for each scenario. Moreover, life cycle cost analysis (LCCA) is conducted for the base scenario and selected optimum scenario. Results show that increase in pavement width beyond 4.2 m, renders the scenarios uneconomical and thus, the scenario consisting of 4.2 m lane width and 16 cm asphalt layer thickness yield a maximum performance efficiency of 20% among all other alternatives. LCCA analysis shows that a difference in salvage value of 42 million Euros exists when compared with the base scenario. By selecting the optimum lane width of 4.2 m and asphalt layer thickness of 16 cm, Pavement lifetime can be further increased by 13 years with full depth reclamation used as maintenance intervention.

Abstract Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Summary: Synapses preferentially respond to particular temporal patterns of activity with a large degree of heterogeneity that is informally or tacitly separated into classes. Yet, the precise number and properties of such classes are unclear. Do they exist on a continuum and, if so, when is it appropriate to divide that continuum into functional regions? In a large dataset of glutamatergic cortical connections, we perform model-based characterization to infer the number and characteristics of functionally distinct subtypes of synaptic dynamics. In rodent data, we find five clusters that partially converge with transgenic-associated subtypes. Strikingly, the application of the same clustering method in human data infers a highly similar number of clusters, supportive of stable clustering. This nuanced dictionary of functional subtypes shapes the heterogeneity of cortical synaptic dynamics and provides a lens into the basic motifs of information transmission in the brain.

Unintended adolescent pregnancy is a public health priority in Papua New Guinea (PNG), where national policies specify need for easier access to reliable modern contraceptives. To reduce young people's experiences of unintended pregnancy in PNG, improved understandings of use of modern and other forms of contraception within young people's relationships is required to support the development of new sexual and reproductive health (SRH) programs and policies. The aim of this paper is to understand young men's use of modern and other contraceptives. This qualitative study involved semi-structured interviews with 35 sexually active young men aged 15-24 years, who were sampled purposively from the general population within community-based settings. Data were analysed using inductive thematic analysis techniques. Our analysis of young men's everyday experiences of using condoms and other contraceptives highlights clear drivers of unintended adolescent pregnancies. Across three settings, these included non-use of any modern method at first sex or during early sexual experiences; inconsistent use of condoms, often only after first pregnancy experiences; difficulties accessing condoms from health service providers, pharmacies and stores; a lack of understanding of other modern contraceptive strategies; inconsistent use of the withdrawal method; and inconsistent and incorrect use of calendar approaches due to misunderstandings about women's fertile period. Ten young men had never used any form of contraception. These occurred largely because young men's sexual agency is constrained within sexual and peer relationships, and community, school and health service settings, in ways that inhibit pregnancy prevention. It is important to engage meaningfully with young men to build sexual and reproductive health policies and programs that pay honest, respectful attention to young people's everyday sexual and social lives. Young men's everyday stories provide a unique lens through which we can identify mechanisms of change required to address the health and social inequities associated with unintended pregnancy among young men and young women in PNG and beyond.

Abstract The olivocerebellar projection is organized into an intricate topographical connection from the inferior olive (IO) subdivisions to the longitudinally-striped compartments of cerebellar Purkinje Cells (PCs), to play an essential role in cerebellar coordination and learning. However, the central mechanisms for forming topography need to be clarified. IO neurons and PCs are generated during overlapping periods of a few days in embryonic development. Therefore, we examined whether their neurogenic timing is specifically involved in the olivocerebellar topographic projection relationship. First, we mapped neurogenic timing in the entire IO by using the neurogenic-tagging system of neurog2-CreER (G2A) mice and specific labeling of IO neurons with FoxP2. IO subdivisions were classified into three groups depending on their neurogenic timing range. Then, we examined the relationships in the neurogenic-timing gradient between IO neurons and PCs by labeling topographic olivocerebellar projection patterns and PC neurogenic timing. Early, intermediate, and late groups of IO subdivisions projected to late, intermediate, and early groups of the cortical compartments, respectively, except for a few particular areas. The results indicated that the olivocerebellar topographic relationship is essentially arranged according to the reverse neurogenic-timing gradients of the origin and target.

Abstract Selection of optimum platoon pattern based on types of trucks inside the platoon, the number of trucks in the platoon, headway distance, interplatoon distance as well as the use of different lateral wander modes for autonomous trucks has been analyzed. The objective of this research is to study the impacts of axle configurations, truck grouping, headway distance and lateral wander options on the performance of truck platoons. Four different headway distances from 2 to 5 m are compared. The first platoon PT-1 only consists of semi trailers, the second platoon PT-2 only consists of rigid body trucks and the third platoon PT-3 consists of equally distributed random traffic mix. Analysis has been conducted using the dload subroutine for projecting zero wander and uniform wander movements for each truck in the platoon on a three layered pavement crossection at vehicle speeds of 90 km/h for a total of 15 years of pavement lifetime consisting of 1.4 million equivalent single axle loads in finite element software ABAQUS. Results show that PT-3 platoon yields the minimum accumulation of damaging strains when compared against other platoon types. A headway distance of 5 m is suggested when using a zero wander mode and 3 m when using a uniform wander mode. In case of zero wander mode, fatigue life of the pavement decreases by 1.2 years and the use of uniform wander mode delays the rutting by 1.6 years, thereby increasing lifetime of the pavement.

Autonomous trucks can bring changes in transport infrastructure in terms of sustainability based on the type of lateral wander mode used. In this research, two lateral wander modes, a zero wander and a uniform wander mode, are analysed based on their applicability for sustainability in terms of CO2 emissions. Life cycle analysis has been performed for the analysis period of 30 y for the pavement section of 10 km, along with fatigue predictions. Results show that zero wander mode generates more emissions as a result of premature fatigue damage under channelized loading. The uniform wander mode yields 20 % fewer emissions. Moreover, the use of full-depth reclamation during the pavement's Life Cycle improves the CO2 emissions by 15 % when compared to traditional removal and reconstruction methods. Therefore, the uniform wander mode is favourable for the improvement of pavement sustainability in terms of CO2 emissions.

This qualitative study examined employability, also referred to as workplace readiness strengths in this article, for American Millennial health administration baccalaureates. The primary researcher used data collected from focus groups and interviews conducted at two certified Association of University Programs in Health Administration (AUPHA) programs in California, USA. Participants (n = 71) belonged to one of 4 distinct groups: (a) health administration faculty, (b) internship preceptors, (c) alumni, and (d) undergraduate students (interns) enrolled in their internship program. Thematic content analysis was used to evaluate the collected qualitative data, after which descriptive statistics was applied to calculate the frequencies of emergent themes. The National Association of Colleges and Employers (NACE) Career Readiness Competencies, an employer and university validated list of Career Readiness Competencies for a Career-Ready Workforce, was used as a comparative framework for the workplace readiness strengths provided in the qualitative data. Six strength-based themes emerged, two of which comparatively aligned with two of the NACE Career Readiness Competencies. However, respondents indicated that the rest of the NACE Career Competencies were not overtly expressed by Millennials as workplace strengths and should be embedded into the health administration curriculum. This invaluable information can be used to update the AUPHA health administration curriculum and help their undergraduate students increase their employability index scores.

Microrobotics is an emerging technology with wide implications for medical fields, such as assisted reproduction. Here the authors show how the key challenges regarding materials, processes and engineering as well as ethical and regulatory implications can be addressed towards a clinical adoption.

There is growing recognition of the need for long-duration energy storage to cope with low frequency (i.e. seasonal to multi-annual) variability in renewable energy supplies. Recent analysis for the UK has estimated that 60–100 TWh of hydrogen storage could be required to provide zero-carbon backup for renewable energy supplies in 2050. However, the analysis did not consider the potential role of green energy imports as a supplement to domestic energy storage. Using a global spatially-explicit model of green hydrogen/ammonia production and shipping we estimate the lowest import costs for green ammonia to the UK, and compare them with the levelized costs of energy storage across scenarios of varying domestic renewable energy production. The results indicate that imported green ammonia could offer a cost-comparable alternative to domestic hydrogen production, storage and power generation, whilst increasing energy system resilience through supply diversification, at a similar or cheaper delivered energy cost compared to a hydrogen-only storage system. In countries lacking the geological potential for low-cost hydrogen storage, green ammonia imports could have an even more significant role.

Scientific and technical progress is driven particularly by the ability to “look” into new areas [...]

Background: Clostridioides difficile infection (CDI) often recurs in patients aged ≥65 years and those with comorbidities. Clinical trials often exclude patients with history of immunosuppression, malignancy, renal insufficiency, or other comorbidities. In a phase 3 trial (ECOSPOR III), SER-109 was superior to placebo in reducing recurrent CDI (rCDI) risk at week 8 and was well tolerated. We report integrated safety data for SER-109 in a broad patient population through week 24 from phase 3 studies: ECOSPOR III and ECOSPOR IV. Methods: ECOSPOR III was a double-blind, placebo-controlled trial conducted in participants with ≥2 CDI recurrences randomized 1:1 to placebo or SER-109. ECOSPOR IV was an open-label, single-arm study conducted in 263 patients with rCDI enrolled in 2 cohorts: (1) rollover participants from ECOSPOR III with on-study recurrence and (2) participants with ≥1 CDI recurrence, inclusive of the current episode. In both studies, the investigational product was administered as 4 oral capsules over 3 days. Treatment-emergent adverse events (TEAEs) were collected through week 8; serious TEAEs and TEAEs of special interest (ie, bacteremia, abscess, meningitis) were collected through week 24. Results: In total, 349 participants received SER-109 in ECOSPOR III and/or ECOSPOR IV (mean age 64.2; 68.8% female). Chronic diseases included cardiac disease (31.2%), immunocompromised or immunosuppressed (21.2%), diabetes (18.9% ), and renal impairment or failure (13.2%). Overall, 221 (63.3%) of 349 participants who received SER-109 experienced TEAEs through week 24. Most were mild to moderate and gastrointestinal. The most common (>5% of participants) treatment related TEAEs were flatulence, abdominal pain and distension, decreased appetite, constipation, nausea, fatigue, and diarrhea. No participants experienced a treatment-related TEAE leading to study withdrawal. Invasive infections were observed in 28 participants (8%); those with identified pathogens were unrelated to SER-109 species, and all were deemed unrelated to treatment by the investigators. There were 11 deaths (3.2%) and 48 participants (13.8%) with serious TEAEs, none of which were deemed treatment related. There were no clinically important differences in the safety profile across subgroups of sex, race, prior antibiotic regimen, or number of CDI recurrences. No safety signals were observed in participants with renal impairment or failure, diabetes, cardiac disease, or immunocompromised or immunosuppressed individuals. Conclusions: In this integrated analysis of phase 3 trials, SER-109, an investigational microbiome therapeutic, was well tolerated in this vulnerable patient population with prevalent comorbidities. No infections, nor those with identified pathogens, were attributed to SER-109 or product species. This safety profile might be expected because this purified product is composed of spore-forming Firmicutes normally abundant in the healthy microbiome.

Az Európai Bizottság 2014 óta méri a digitális gazdaság és társadalom fejlettségét a DESI mutatóval. A 2020-as DESI jelentés rámutat arra, hogy a Covid-19 járvány hatására még fontosabbak lettek a digitális eszközök az országok gazdasága számára. Hazánk a 28 Európai Uniós tagállam közül a 21. helyen szerepel a digitális gazdaságot és társadalmi fejlettséget mérő mutatón. A magyar vállalatok versenyképességének javulása a nemzetközi piacon nagymértékben függ a digitalizációjuk mértékétől. A kutatás célja egy áttekintést nyújtani a hazai vállalatok emelt szintű digitalizációs rendszerek bevezetését elősegítő pénzügyi eszközökről és forrásokról a mögöttünk álló Európai Uniós költségvetési időszakból. Az emelt szintű digitalizációval összefüggésbe hozhatóan két pályázati felhívás volt elérhető a 2014-2020-as pályázati ciklusban Magyarországon: GINOP 1.2.8-17 és a GINOP 3.2.6-8.2.4-17. A pályázatok közötti regionális összehasonlító elemzés nem volt megvalósítható, mert a támogatási intenzitás az elszámolható költségekre eltérő a két pályázat esetében, ezért a pályázati felhívások értékelése különállóan történt meg. Az elemzés során megállapításra került, hogy az alacsony pályázati hajlandóság okai között feltételezhetően megjelenik a hiányzó gazdasági és társadalmi potenciál a vidéki térségekben, ezek között kiemelve a beruházásra fordítandó saját forrás és a megfelelő digitális készségekkel rendelkező munkaerő hiánya.

This roundtable discussion brings together four prominent scholars from equine studies (Susanna Forrest, Richard Nash, Karen Raber, and Jeannette Vaught) to discuss how we have historically shaped the equine body (and mind) when we breed and train horses, and how taking this history into account might allow us to imagine new ways of living with horses. Three core concerns are addressed from multidisciplinary perspectives: How do human representations, desires, and fantasies inform our interactions with horses? How have equine bodies and minds been shaped by us over time? How do the stories we tell ourselves about equine bodies in turn shape how we relate to horses—and how might we do this differently?

Tuberculosis (TB) is a major public health issue in Papua New Guinea, with incidence rates particularly high in the South Fly District of Western Province. We present three case studies, along with additional vignettes, that were derived from interviews and focus groups carried out between July 2019 and July 2020 of people living in rural areas of the remote South Fly District depicting their challenges accessing timely TB diagnosis and care; most services within the district are only offered offshore on Daru Island. The findings detail that rather than ‘patient delay’ attributed to poor health seeking behaviours and inadequate knowledge of TB symptoms, many people were actively trying to navigate structural barriers hindering access to and utilisation of limited local TB services. The findings highlight a fragile and fragmented health system, a lack of attention given to primary health services, and undue financial burdens placed on people living in rural and remote areas associated with costly transportation to access functioning health services. We conclude that a person-centred and effective decentralised model of TB care as outlined in health policies is imperative for equitable access to essential health care services in Papua New Guinea.

By means of an expansive innervation, the serotonin (5-HT) neurons of the dorsal raphe nucleus (DRN) are positioned to enact coordinated modulation of circuits distributed across the entire brain in order to adaptively regulate behavior. Yet the network computations that emerge from the excitability and connectivity features of the DRN are still poorly understood. To gain insight into these computations, we began by carrying out a detailed electrophysiological characterization of genetically identified mouse 5-HT and somatostatin (SOM) neurons. We next developed a single-neuron modeling framework that combines the realism of Hodgkin-Huxley models with the simplicity and predictive power of generalized integrate-and-fire models. We found that feedforward inhibition of 5-HT neurons by heterogeneous SOM neurons implemented divisive inhibition, while endocannabinoid-mediated modulation of excitatory drive to the DRN increased the gain of 5-HT output. Our most striking finding was that the output of the DRN encodes a mixture of the intensity and temporal derivative of its input, and that the temporal derivative component dominates this mixture precisely when the input is increasing rapidly. This network computation primarily emerged from prominent adaptation mechanisms found in 5-HT neurons, including a previously undescribed dynamic threshold. By applying a bottom-up neural network modeling approach, our results suggest that the DRN is particularly apt to encode input changes over short timescales, reflecting one of the salient emerging computations that dominate its output to regulate behavior.

Ectomycorrhizal (ECM) fungi are among the most diverse and dominant fungal groups in temperate forests and are crucial for ecosystem functioning of forests and their resilience toward disturbance. We carried out DNA metabarcoding of ECM fungi from soil samples taken at 62 sites in the Bükk Mountains in northern Hungary. The selected sampling sites represent the characteristic Pannonian forest types distributed along elevation (i.e., temperature), pH and slope aspect gradients. We compared richness and community composition of ECM fungi among forest types and explored relationships among environmental variables and ECM fungal alpha and beta diversity. The DNA sequence data generated in this study indicated strong correlations between fungal community composition and environmental variables, particularly with pH and soil moisture, with many ECM fungi showing preference for specific zonal, topographic or edaphic forest types. Several ECM fungal genera showed significant differences in richness among forest types and exhibited strong compositional differences mostly driven by differences in environmental factors. Despite the relatively high proportions of compositional variance explained by the tested environmental variables, a large proportion of the compositional variance remained unexplained, indicating that both niche (environmental filtering) and neutral (stochastic) processes shape ECM fungal community composition at landscape level. Our work provides unprecedented insights into the diversity, landscape-level distribution, and habitat preferences of ECM fungi in the Pannonian forests of Northern Hungary.

The mechanical interaction between the fuel pellet and the cladding tube of a nuclear fuel rod is a very important for safety studies as this phenomenon could lead to fuel failure and release of radioactivity. To investigate the ductility of cladding tubes used in WWER type nuclear power plants, several mandrel tests were performed in the Centre for Energy Research (EK). This modified mandrel test was used to model the mechanical interaction between the fuel pellet and the cladding using a segmented tool. The tests were conducted at room temperature and at 300 °C with inactive as-received and hydrogenated cladding ring samples. The results show a gradual decrease in ductility as the hydrogen content increases, the ductile-brittle transition was seen above 1500 ppm hydrogen absorbed.

Abstract The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.

Abstract Background Few studies have investigated risk factor heterogeneity by molecular subtypes in indigenous African populations where prevalence of traditional breast cancer (BC) risk factors, genetic background, and environmental exposures show marked differences compared to European ancestry populations. Methods We conducted a case-only analysis of 838 pathologically confirmed BC cases recruited from 5 groups of public, faith-based, and private institutions across Kenya between March 2012 to May 2015. Centralized pathology review and immunohistochemistry (IHC) for key markers (ER, PR, HER2, EGFR, CK5-6, and Ki67) was performed to define subtypes. Risk factor data was collected at time of diagnosis through a questionnaire. Multivariable polytomous logistic regression models were used to determine associations between BC risk factors and tumor molecular subtypes, adjusted for clinical characteristics and risk factors. Results The median age at menarche and first pregnancy were 14 and 21 years, median number of children was 3, and breastfeeding duration was 62 months per child. Distribution of molecular subtypes for luminal A, luminal B, HER2-enriched, and triple negative (TN) breast cancers was 34.8%, 35.8%, 10.7%, and 18.6%, respectively. After adjusting for covariates, compared to patients with ER-positive tumors, ER-negative patients were more likely to have higher parity (OR = 2.03, 95% CI = (1.11, 3.72), p = 0.021, comparing ≥ 5 to ≤ 2 children). Compared to patients with luminal A tumors, luminal B patients were more likely to have lower parity (OR = 0.45, 95% CI = 0.23, 0.87, p = 0.018, comparing ≥ 5 to ≤ 2 children); HER2-enriched patients were less likely to be obese (OR = 0.36, 95% CI = 0.16, 0.81, p = 0.013) or older age at menopause (OR = 0.38, 95% CI = 0.15, 0.997, p = 0.049). Body mass index (BMI), either overall or by menopausal status, did not vary significantly by ER status. Overall, cumulative or average breastfeeding duration did not vary significantly across subtypes. Conclusions In Kenya, we found associations between parity-related risk factors and ER status consistent with observations in European ancestry populations, but differing associations with BMI and breastfeeding. Inclusion of diverse populations in cancer etiology studies is needed to develop population and subtype-specific risk prediction/prevention strategies.

Background: Lombardy has been the first and one of the most affected European regions during the first and second waves of the novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]). Objective: To evaluate the impact of coronavirus disease 2019 (COVID-19) on all urologic activities over a 17-wk period in the three largest public hospitals in Lombardy located in the worst hit area in Italy, and to assess the applicability of the authorities’ recommendations provided for reorganising urology practice. Design, setting, and participants: A retrospective analysis of all urologic activities performed at three major public hospitals in Lombardy (Brescia, Bergamo, and Milan), from January 1 to April 28, 2020, was performed. Outcome measurements and statistical analysis: Join-point regression was used to identify significant changes in trends for all urologic activities. Average weekly percentage changes (AWPCs) were estimated to summarise linear trends. Uro-oncologic surgeries performed during the pandemic were tabulated and stratified according to the first preliminary recommendations by Stensland et al (Stensland KD, Morgan TM, Moinzadeh A, et al. Considerations in the triage of urologic surgeries during the COVID-19 pandemic. Eur Urol 2020;77:663–6) and according to the level of priority recommended by European Association of Urology guidelines. Results and limitations: The trend for 2020 urologic activities decreased constantly from weeks 8–9 up to weeks 11–13 (AWPC range –41%, –29.9%; p

High-throughput metabolomics techniques are a useful tool to understand many disease conditions including cardiovascular disease such as valvular heart disease(s) (VHD). VHD involves damage to heart valves, mostly presenting as stenosis, regurgitation or prolapse and can be classified into degenerative, rheumatic, congenital, or prosthetic valve disease. Gaps remain in our understanding of the pathogenesis of the common VHD. It is now fitting to place into perspective the contribution of metabolomics in the mechanism of development, diagnosis, and prognosis of VHD. A structured search for metabolomics studies centred on human VHD was undertaken. Biomarkers associated with the pathogenesis of bicuspid aortic valve disease, mitral valve disease, rheumatic heart disease, and degenerative aortic valve stenosis are reviewed and discussed. In addition, metabolic biomarkers reported to prognosticate patient outcomes of post-valve repair or replacement are highlighted. Finally, we also review the pitfalls and limitations to consider when designing metabolomics studies, especially from a clinician’s viewpoint. In the future, reliable and simple metabolic biomarker(s) may supplement the existing diagnostic tools in the early diagnosis of VHD.

Introduction & objectives: We tested the role of multiparametric magnetic resonance imaging (mpMRI) in disease reclassification and whether the combination of mpMRI and clinicopathological variables could represent the most accurate approach to predict the risk of reclassification during active surveillance. Materials & methods: Three-hundred eighty-nine patients (pts) underwent mpMRI and subsequent confirmatory or follow-up biopsy according to the Prostate Cancer Research International Active Surveillance (PRIAS) protocol. Pts with negative (−) mpMRI underwent systematic random biopsy. Pts with positive (+) mpMRI [Prostate Imaging Reporting and Data System, version 2 (PI-RADS-V2) score ≥3] underwent targeted + systematic random biopsies. Multivariate analyses were used to create three models predicting the probability of reclassification [International Society of Urological Pathology ≥ Grade Group 2 (GG2)]: a basic model including only clinical variables (age, prostate-specific antigen density, and number of positive cores at baseline), an Magnetic resonance imaging (MRI) model including only the PI-RADS score, and a full model including both the previous ones. The predictive accuracy (PA) of each model was quantified using the area under the curve. Results: mpMRI negative (−) was recorded in 127 (32.6%) pts; mpMRI positive (+) was recorded in 262 pts: 72 (18.5%) had PI-RADS 3, 150 (38.6%) PI-RADS 4, and 40 (10.3%) PI-RADS 5 lesions. At a median follow-up of 12 months, 125 pts (32%) were reclassified to GG2 prostate cancer. The rate of reclassification to GG2 prostate cancer was 17%, 35%, 38%, and 52% for mpMRI (−), PI-RADS 3, 4, and 5, respectively (P

Abstract Late spontaneous in-the-bag intraocular lens (IOL) dislocation is a complication presenting 6 months or later after cataract surgery. We aimed to characterize the cells in the lens capsules (LCs) of 18 patients with spontaneous late in-the-bag IOL dislocation. Patients' average age was 82.6 ± 1.5 years (range 72–98), and most of them had pseudoexfoliation syndrome (PEX). Cells from the LCs were positive for myofibroblast (αSMA), proliferation (Ki-67, PCNA), early lens development/lens progenitor (SOX2, PAX6), chemokine receptor (CXCR4), and transmembrane (N-cadherin) markers, while negative for epithelial (E-cadherin) marker. Moreover, the cells produced abundant fibronectin, type I and type V collagen in the nearby extracellular matrix (ECM). During ex vivo cultivation of dislocated IOL-LCs in toto, the cells proliferated and likely migrated onto the IOL’s anterior side. EdU proliferation assay confirmed the proliferation potential of the myofibroblasts (MFBs) in dislocated IOL-LCs. Primary cultured lens epithelial cells/MFBs isolated from the LC of dislocated IOLs could induce collagen matrix contraction and continuously proliferated, migrated, and induced ECM remodeling. Taken together, this indicates that long-lived MFBs of dislocated IOLs might contribute to the pathogenic mechanisms in late in-the-bag IOL dislocation.

The Covid-19 pandemic is still current but has been particularly well addressed, so far, in the Australian context. This article presents an analysis of management practice to describe the experience of one Primary Health Network (PHN) and its approach and response to the pandemic within its geographical region in accordance with Federal government directives. The PHN is a large geographic area that includes the Central Coast, just north of the Sydney basin, the Newcastle and Hunter Valley region and the Northwest/New England region that extends from Tamworth to the Queensland Border. The article describes the PHN function within its primary healthcare role (PHC) in respect to responding to national initiatives to address and reduce the impact Of the Covid-19 event. The article recounts the Federal Governments directive described through the ‘National Cabinet’ and the Federal Health Department and the PHN response to those directives and initiatives. The article also recounts the actual cases of Covid-19 over the period of the epidemic. The article describes the governance, leadership, and management initiatives. The article then describes the PHN approach to evaluation of its approach from the perspective of general practice and other PHC providers as well as providing perspectives from governance, management, and staff. The evaluation process identified significant impacts on providers and strong support for the continuation of telehealth measures. There were positive responses to the PHN activity and as a strong sense of trusted information, ongoing education, and general engagement.

The primary motor cortex (M1) is known to be a critical site for movement initiation and motor learning. Surprisingly, it has also been shown to possess reward-related activity, presumably to facilitate reward-based learning of new movements. However, whether reward-related signals are represented among different cell types in M1, and whether their response properties change after cue–reward conditioning remains unclear. Here, we performed longitudinal in vivo two-photon Ca2+ imaging to monitor the activity of different neuronal cell types in M1 while mice engaged in a classical conditioning task. Our results demonstrate that most of the major neuronal cell types in M1 showed robust but differential responses to both the conditioned cue stimulus (CS) and reward, and their response properties undergo cell-type-specific modifications after associative learning. PV-INs’ responses became more reliable to the CS, while VIP-INs’ responses became more reliable to reward. Pyramidal neurons only showed robust responses to novel reward, and they habituated to it after associative learning. Lastly, SOM-INs’ responses emerged and became more reliable to both the CS and reward after conditioning. These observations suggest that cue- and reward-related signals are preferentially represented among different neuronal cell types in M1, and the distinct modifications they undergo during associative learning could be essential in triggering different aspects of local circuit reorganization in M1 during reward-based motor skill learning.

Triggered activity bursts in place cells can increase and decrease the strength of some inputs.

The counter-electrode (CE) material in electrochemical metallization memory (ECM) cells plays a crucial role in the switching process by affecting the reactions at the CE/electrolyte interface. This is due to the different electrocatalytic activity of the CE material towards reduction–oxidation reactions, which determines the metal ion concentration in the electrolyte and ultimately impacts the switching kinetics. In this study, the focus is laid on Pt, TiN, and W, which are relevant in standard chip technology. For these, the influence of CE metal on the switching kinetics of Ag/HfO2-based volatile ECM cells is investigated. Rectangular voltage pulses of different amplitudes were applied, and the SET times were analyzed from the transient curves. The results show that CE material has a significant effect on the SET kinetics, with differences being observed depending on the voltage regime. The formation of interfacial oxides at the CE/electrolyte interface, particularly for non-noble metals, is also discussed in relation to the findings. Overall, this work highlights the important role of the CE material in the switching process of Ag/HfO2-based diffusive memristors and the importance of considering interfacial oxide formation in the design of these devices.

Cortical pyramidal cells (PCs) have a specialized dendritic mechanism for the generation of bursts, suggesting that these events play a special role in cortical information processing. In vivo, bursts occur at a low, but consistent rate. Theory suggests that this network state increases the amount of information they convey. However, because burst activity relies on a threshold mechanism, it is rather sensitive to dendritic input levels. In spiking network models, network states in which bursts occur rarely are therefore typically not robust, but require fine-tuning. Here, we show that this issue can be solved by a homeostatic inhibitory plasticity rule in dendrite-targeting interneurons that is consistent with experimental data. The suggested learning rule can be combined with other forms of inhibitory plasticity to self-organize a network state in which both spikes and bursts occur asynchronously and irregularly at low rate. Finally, we show that this network state creates the network conditions for a recently suggested multiplexed code and thereby indeed increases the amount of information encoded in bursts. Author summary The language of the brain consists of sequences of action potentials. These sequences often contain bursts, short “words” consisting of a few action potentials in rapid succession. Bursts appear to play a special role in the brain. They indicate whether a stimulus was perceived or missed, and they are very effective drivers of synaptic plasticity, the neural substrate of learning. Bursts occur rarely, but consistently, a condition that is thought to maximize the amount of information they can communicate. In our article, we argue that this condition is far from self-evident, but requires very special circumstances. We show that these circumstances can be reached by homeostatic inhibitory plasticity in certain inhibitory neuron types. This may sound complicated, but basically works just like a thermostat. When bursts occur too often, inhibition goes up and suppresses them. When they are too rare, inhibition goes down and thereby increases their number. In computer simulations, we show that this simple mechanism can create circumstances akin to those in the brain, and indeed allows bursts to convey information effectively. Whether this mechanism is indeed used by the brain now remains to be tested by our experimental colleagues.