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The impact of disability on people’s lives is often underestimated because the extra costs of living with a disability are not accounted for. This paper analyzes several different methodologies for estimating those costs and explores their usefulness in designing inclusive social policies. For example, one approach is to measure what is currently being spent, while another is to estimate what would need to be spent for equal participation. These can be measured using statistical techniques or through a more qualitative methodology. Each of these methods has its advantages and disadvantages. The paper concludes with recommendations for which methodology fits which purpose, and how they can be used together to obtain a full accounting of the extra costs incurred by people with disabilities.

Lifecycle assessment (LCA) quantified changes in environmental impact categories (global warming, eutrophication, etc.) from 2021 to 2030 due to genetic trends in (re)production traits in pig lines of the breeding company Genus-PIC. The 2030 levels were projected with selection index theory based on weightings of traits in the breeding goals and genetic covariances among them. The projected improvement was 0.9% annually for most impact categories. Another LCA compared the impacts of 2021 North American pig production based on PIC genetics versus the industry average. Software openLCA converted material and energy flows to impact categories of frameworks ReCiPe-2016, PEF-3.1, and IPCC-2021. Flows came from data recorded by customers (1.1/4.7 million sows/finishing pigs) and by subscribers to a third-party data aggregator (1.3/9.1 million). PIC genetics have a 7–8% better impact than industry average for 13/18 categories of ReCiPe-2016, 19/25 of PEF-3.1, and all categories of IPCC-2001. Pig breeding delivers positive environmental outcomes as correlated responses to selection for profitability-oriented breeding goals. This trend is additive; technology development will increase it. Different investment levels in breeding population structure and technology and different operational efficiencies of breeding companies cause substantial differences in the environmental impact of pig production.

Issues of chronology are central to inferences pertaining to relationships between both contemporaneous and successive prehistoric typo-technological entities (i.e., archaeological cultures), culture–environment relationships, and ultimately the mechanisms at play behind cultural changes observed through time in the archaeological record. We refine the chronology of Upper Paleolithic archaeological cultures between 35–18 calibrated kiloanni before the present in present-day France by incorporating recently published radiocarbon data along with new 14C ages that we obtained from several Gravettian archaeological contexts. We present the results of a Bayesian age model that includes these new radiometric data and that, more importantly, separates Gravettian contexts in regions north of the Garonne River into two successive cultural phases: The Northern Noaillian and the Rayssian, respectively. This new age model places the beginning of the Noaillian during Greenland Stadial 5.2. The appearance of contexts containing assemblages associated with the Rayssian lithic technical system occurs immediately prior to the termination of Greenland Interstadial 5.1, and it is present throughout Heinrich Event 3 (GS-5.1) and into the following GI-4 climatic amelioration. Despite the Rayssian’s initial appearance during the brief and relatively weakly expressed Greenland Interstadial 5.1, its duration suggests that Rayssian lithic technology was well-suited to the environmental conditions of Greenland Stadial 5.1.

Oxyspirura petrowi is a heteroxenous nematode that infects the harderian gland and other ocular tissues in birds. High-intensity infections often cause damage to the infected tissues. Due to the nature of the infection sites, treatment of O. petrowi in these hosts can be difficult. Fenbendazole (FBZ) is a common anthelmintic used to treat birds for helminth infections; however, little information exists as to the efficacy of the drug on O. petrowi infections. The present study aims to estimate lethal concentrations of FBZ to O. petrowi. Adult O. petrowi were maintained in vitro and exposed to doses of 5, 50, 100, and 200 µM concentrations of FBZ and included both negative and vehicle controls. Exposure lasted 7.5 days and lethality was determined for each treatment. Negative and vehicle controls did not differ, and both had 75% survival at the end of the treatment period. The percentage survivorship in ascending order of concentration, corrected for the controls, was 66.67%, 44.44%, 33.33%, and 0%. LC10, LC50, and LC90 estimates were 7.5 ± 0.26, 49.1 ± 1.69, and 163.2 ± 5.63 µM, respectively. In the context of known pharmacokinetics of FBZ in birds, a single oral dose of FBZ can achieve exposure levels that are lethal to O. petrowi, but the drug does not stay in the system long enough. Thus, treatment of O. petrowi infections will require multiple oral doses over several days.

Background: Malnutrition is a significant and prevalent issue in hospital settings, associated with increased morbidity and mortality, longer hospital stays, higher readmission rates, and greater healthcare costs. Despite the potential impact of nutritional interventions on patient outcomes, there is a paucity of research focusing on their economic evaluation in the hospital setting. This study aims to fill this gap by conducting a cost–consequence analysis (CCA) of nutritional interventions targeting malnutrition in the hospital setting. Methods: We performed a CCA using data from recent systematic reviews and meta-analyses, focusing on older adult patients with or at risk of malnutrition in the hospital setting. The analysis included outcomes such as 30-day, 6-month, and 12-month mortality; 30-day and 6-month readmissions; hospital complications; length of stay; and disability-adjusted life years (DALYs). Sensitivity analyses were conducted to evaluate the impact of varying success rates in treating malnutrition and the proportions of malnourished patients seen by dietitians in SingHealth institutions. Results: The CCA indicated that 28.15 DALYs were averted across three SingHealth institutions due to the successful treatment or prevention of malnutrition by dietitians from 1 April 2021 to 31 March 2022, for an estimated 45,000 patients. The sensitivity analyses showed that the total DALYs averted ranged from 21.98 (53% success rate) to 40.03 (100% of malnourished patients seen by dietitians). The cost of implementing a complex nutritional intervention was USD 218.72 (USD 104.59, USD 478.40) per patient during hospitalization, with additional costs of USD 814.27 (USD 397.69, USD 1212.74) when the intervention was extended for three months post-discharge and USD 638.77 (USD 602.05, USD 1185.90) for concurrent therapy or exercise interventions. Conclusion: Nutritional interventions targeting malnutrition in hospital settings can have significant clinical and economic benefits. The CCA provides valuable insights into the costs and outcomes associated with these interventions, helping healthcare providers and policymakers to make informed decisions on resource allocation and intervention prioritization.

Our journal, C—Journal of Carbon Research (https://www.mdpi.com/journal/carbon), is an international, scientific, peer-reviewed, open access journal on carbon research, published quarterly online by MDPI [...]

Escherichia coli is listed as a priority 1 pathogen on the World Health Organization (WHO) priority pathogen list. For this list of pathogens, new antibiotics are urgently needed to control the emergence and spread of multidrug-resistant strains. This study assessed eighteen metal ions, graphene, and graphene oxide for their antimicrobial efficacy against E. coli in both planktonic and biofilm growth states and the potential synergy between metal ions and graphene-based compounds. Molybdenum and tin ions exhibited the greatest antimicrobial activity against the planktonic states of the isolates with minimal inhibitory concentrations (MIC) ranging between 13 mg/L and 15.6 mg/L. Graphene oxide had no antimicrobial effect against any of the isolates, while graphene showed a moderate effect against E. coli (MIC, 62.5 mg/L). Combinations of metal ions and graphene-based compounds including tin–graphene, tin–graphene oxide, gold–graphene, platinum–graphene, and platinum–graphene oxide exhibited a synergistic antimicrobial effect (FIC ≤ 0.5), inhibiting the planktonic and biofilm formation of the isolates regardless of their antibiotic-resistant profiles. The bactericidal effect of the metal ions and the synergistic effects when combined with graphene/graphene oxide against medically relevant pathogens demonstrated that the antimicrobial efficacy was increased. Hence, such agents may potentially be used in the production of novel antimicrobial/antiseptic agents.

Introduction: Malnutrition is a widespread and intricate issue among hospitalized adults, necessitating a wide variety of nutritional strategies to address its root causes and repercussions. The primary objective of this study is to systematically categorize nutritional interventions into simple or complex, based on their resource allocation, strategies employed, and predictors of intervention complexity in the context of adult malnutrition in hospital settings. Methods: A conceptual evaluation of 100 nutritional intervention studies for adult malnutrition was conducted based on data from a recent umbrella review (patient population of mean age > 60 years). The complexity of interventions was categorized using the Medical Research Council 2021 Framework for Complex Interventions. A logistic regression analysis was employed to recognize variables predicting the complexity of interventions. Results: Interventions were divided into three principal categories: education and training (ET), exogenous nutrient provision (EN), and environment and services (ES). Most interventions (66%) addressed two or more of these areas. A majority of interventions were delivered in a hospital (n = 75) or a hospital-to-community setting (n = 25), with 64 studies being classified as complex interventions. The logistic regression analysis revealed three variables associated with intervention complexity: the number of strategies utilized, the targeted areas, and the involvement of healthcare professionals. Complex interventions were more likely to be tailored to individual needs and engage multiple healthcare providers. Conclusions: The study underlines the importance of considering intervention complexity in addressing adult malnutrition. Findings advocate for a comprehensive approach to characterizing and evaluating nutritional interventions in future research. Subsequent investigations should explore optimal balances between intervention complexity and resource allocation, and assess the effectiveness of complex interventions across various settings, while considering novel approaches like telehealth.

Botrytis cinerea, the causative agent of gray mold disease (GMD), invades plants to obtain nutrients and disseminates through airborne conidia in nature. Bacillus amyloliquefaciens strain GD4a, a beneficial bacterium isolated from switchgrass, shows great potential in managing GMD in plants. However, the precise mechanism by which GD4a confers benefits to plants remains elusive. In this study, an A. thaliana-B. cinerea-B. amyloliquefaciens multiple-scale interaction model was used to explore how beneficial bacteria play essential roles in plant growth promotion, plant pathogen suppression, and plant immunity boosting. Arabidopsis Col-0 wild-type plants served as the testing ground to assess GD4a’s efficacy. Additionally, bacterial enzyme activity and targeted metabolite tests were conducted to validate GD4a’s potential for enhancing plant growth and suppressing plant pathogens and diseases. GD4a was subjected to co-incubation with various bacterial, fungal, and oomycete pathogens to evaluate its antagonistic effectiveness in vitro. In vivo pathogen inoculation assays were also carried out to investigate GD4a’s role in regulating host plant immunity. Bacterial extracellular exudate (BEE) was extracted, purified, and subjected to untargeted metabolomics analysis. Benzocaine (BEN) from the untargeted metabolomics analysis was selected for further study of its function and related mechanisms in enhancing plant immunity through plant mutant analysis and qRT-PCR analysis. Finally, a comprehensive model was formulated to summarize the potential benefits of applying GD4a in agricultural systems. Our study demonstrates the efficacy of GD4a, isolated from switchgrass, in enhancing plant growth, suppressing plant pathogens and diseases, and bolstering host plant immunity. Importantly, GD4a produces a functional bacterial extracellular exudate (BEE) that significantly disrupts the pathogenicity of B. cinerea by inhibiting fungal conidium germination and hypha formation. Additionally, our study identifies benzocaine (BEN) as a novel small molecule that triggers basal defense, ISR, and SAR responses in Arabidopsis plants. Bacillus amyloliquefaciens strain GD4a can effectively promote plant growth, suppress plant disease, and boost plant immunity through functional BEE production and diverse gene expression.

Endoscopy is the gold standard for the diagnosis of cancers and cancer precursors in the oesophagus and stomach. Early detection of upper GI cancers requires high-quality endoscopy and awareness of the subtle features these lesions carry. Endoscopists performing surveillance of high-risk patients including those with Barrett’s oesophagus, previous squamous neoplasia or chronic atrophic gastritis should be familiar with endoscopic features, classification systems and sampling techniques to maximise the detection of early cancer. In this article, we review the current approach to diagnosis of these conditions and the latest advanced imaging and diagnostic techniques.

The oral cavity is a niche for diverse microbes, including viruses. Members of the Herpesviridae family, comprised of dsDNA viruses, as well as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an ssRNA virus, are among the most prevalent viruses infecting the oral cavity, and they exhibit clinical manifestations unique to oral tissues. Viral infection of oral mucosal epithelia triggers an immune response that results in prolonged inflammation. The clinical and systemic disease manifestations of HHV have been researched extensively, and several recent studies have illuminated the relationship between HHV and oral inflammatory diseases. Burgeoning evidence suggests the oral manifestation of SARS-CoV-2 infection includes xerostomia, dysgeusia, periodontal disease, mucositis, and opportunistic viral and bacterial infections, collectively described as oral post-acute sequelae of COVID-19 (PASC). These diverse sequelae could be a result of intensified immune responses initially due to the copious production of proinflammatory cytokines: the so-called “cytokine storm syndrome”, facilitating widespread oral and non-oral tissue damage. This review explores the interplay between HHV, SARS-CoV-2, and oral inflammatory diseases such as periodontitis, endodontic disease, and peri-implantitis. Additionally, the review discusses proper diagnostic techniques for identifying viral infection and how viral diagnostics can lead to improved overall patient health.

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder that has been diagnosed in an increasing number of children around the world. The existing data suggest that early diagnosis and intervention can improve ASD outcomes. The causes of ASD remain complex and unclear, and there are currently no clinical biomarkers for autism spectrum disorder. There is an increasing recognition that ASD might be associated with oxidative stress through several mechanisms including abnormal metabolism (lipid peroxidation) and the toxic buildup of reactive oxygen species (ROS). Glutathione acts as an antioxidant, a free radical scavenger and a detoxifying agent. This open-label pilot study investigates the tolerability and effectiveness of oral supplementation with OpitacTM gluthathione as a treatment for patients with ASD. The various aspects of glutathione OpitacTM glutathione bioavailability were examined when administered by oral routes. The absorption of glutathione from the gastrointestinal tract has been recently investigated. The results of this case series suggest that oral glutathione supplementation may improve oxidative markers, but this does not necessarily translate to the observed clinical improvement of subjects with ASD. The study reports a good safety profile of glutathione use, with stomach upset reported in four out of six subjects. This article discusses the role of the gut microbiome and redox balance in ASD and notes that a high baseline oxidative burden may make some patients poor responders to glutathione supplementation. In conclusion, an imbalance in redox reactions is only one of the many factors contributing to ASD, and further studies are necessary to investigate other factors, such as impaired neurotransmission, immune dysregulation in the brain, and mitochondrial dysfunction.

Hybrids between the critically endangered Siamese crocodile (Crocodylus siamensis) and least-concern saltwater crocodile (C. porosus) in captive populations represent a serious challenge for conservation and reintroduction programs due to the impact of anthropogenic activities. A previous study used microsatellite and mitochondrial DNA data to establish the criteria for identifying species and their hybrids; however, the results may have been influenced by biased allelic frequencies and genetic drift within the examined population. To overcome these limitations and identify the true signals of selection, alternative DNA markers and a diverse set of populations should be employed. Therefore, this study used DArT sequencing to identify genome-wide single nucleotide polymorphisms (SNPs) in both species and confirm the genetic scenario of the parental species and their hybrids. A population of saltwater crocodiles from Australia was used to compare the distribution of species-diagnostic SNPs. Different analytical approaches were compared to diagnose the level of hybridization when an admixture was present, wherein three individuals had potential backcrossing. Approximately 17.00–26.00% of loci were conserved between the Siamese and saltwater crocodile genomes. Species-diagnostic SNP loci for Siamese and saltwater crocodiles were identified as 8051 loci and 1288 loci, respectively. To validate the species-diagnostic SNP loci, a PCR-based approach was used by selecting 20 SNP loci for PCR primer design, among which 3 loci were successfully able to differentiate the actual species and different hybridization levels. Mitochondrial and nuclear genetic information, including microsatellite genotyping and species-diagnostic DNA markers, were combined as a novel method that can compensate for the limitations of each method. This method enables conservation prioritization before release into the wild, thereby ensuring sustainable genetic integrity for long-term species survival through reintroduction and management programs.

Contact-based biometric applications primarily use prints from a finger or a palm for a single instance in different applications. For access control, there is an enrollment process using one or more templates which are compared with verification images. In forensics applications, randomly located, partial, and often degraded prints acquired from a crime scene are compared with the images captured from suspects or existing fingerprint databases, like AFIS. In both scenarios, if we need to use handprints which include segments from the finger and palm, what would be the solution? The motivation behind this is the concept of one single algorithm for one hand. Using an algorithm that can incorporate both prints in a common processing framework can be an alternative which will have advantages like scaling to larger existing databases. This work proposes a method that uses minutiae or minutiae-like features, Delaunay triangulation and graph matching with invariant feature representation to overcome the effects of rotation and scaling. Since palm prints have a large surface area with degradation, they tend to have many false minutiae compared to fingerprints, and the existing palm print algorithms fail to tackle this. The proposed algorithm constructs Delaunay triangulated graphs (DTG) using minutiae where Delaunay triangles form from minutiae, and initiate a collection of base triangles for opening the matching process. Several matches may be observed for a single triangle match when two images are compared. Therefore, the set of initially matched triangles may not be a true set of matched triangles. Each matched triangle is then used to extend as a sub-graph, adding more nodes to it until a maximum graph size is reached. When a significant region of the template image is matched with the test image, the highest possible order of this graph will be obtained. To prove the robustness of the algorithm to geometrical variations and working ability with extremely degraded (similar to latent prints) conditions, it is demonstrated with a subset of partial-quality and extremely-low-quality images from the FVC (fingerprint) and the THUPALMLAB (palm print) databases with and without geometrical variations. The algorithm is useful when partial matches between template and test are expected, and alignment or geometrical normalization is not accurately possible in pre-processing. It will also work for cross-comparisons between images that are not known a priori.

Cu2+ and Co2+ are metals known to increase DNA damage in the presence of hydrogen peroxide through a Fenton-type reaction. We hypothesized that these metals could increase DNA damage following irradiations of increasing LET values as hydrogen peroxide is a product of the radiolysis of water. The reaction mixtures contain either double- or single-stranded DNA in solution with Cu2+ or Co2+ and were irradiated either with X-ray, carbon-ion or iron-ion beams, or they were treated with hydrogen peroxide or bleomycin at increasing radiation dosages or chemical concentrations. DNA damage was then assessed via gel electrophoresis followed with a band intensity analysis. DNA damage was the greatest when DNA in the solution with either metal was treated with only hydrogen peroxide followed by the DNA damage of DNA in the solution with either metal post irradiation of low-LET (X-Ray) or high-LET (carbon-ion and iron-ion), respectively, and demonstrated the least damage after treatment with bleomycin. Cu2+ portrayed greater DNA damage than Co2+ following all experimental conditions. The metals’ effect caused more DNA damage and was observed to be LET-dependent for single-strand break formation but inversely dependent for double-strand break formation. These results suggest that Cu2+ is more efficient than Co2+ at inducing both DNA single-strand and double-strand breaks following all irradiations and chemical treatments.

Opioid use among pregnant and postpartum women and people (PPWP) has significant health repercussions. This study explores how substance-use behaviors may vary by stage in recovery among PPWP with opioid use disorder (OUD). We recruited 29 PPWP with OUD. “High-risk” participants self-identified as “not being engaged in treatment” or “new or early in their recovery” (n = 11); “low-risk” participants self-identified as being “well-established” or “in long-term recovery” (n = 18). Participants were queried regarding sociodemographic, mental health, and drug-misuse factors; urine drug screens were collected at baseline. Univariate group comparisons between high-risk and low-risk PPWP were conducted. High-risk PPWP were more likely to self-identify as non-Hispanic African American and more likely to report current opioid use, other illicit drugs, and tobacco. High-risk PPWP had higher opioid cravings versus low-risk PPWP. High-risk PPWP were more likely to screen positive on urine tests for non-opioid drugs and on concurrent use of both non-opioid drugs and opioids versus low-risk participants. PPWP earlier in recovery are at higher-risk for opioid and other illicit drug misuse but are willing to disclose aspects of their recent use. PPWP early in recovery are an ideal population for interventions that can help facilitate recovery during the perinatal period and beyond.

Drug-loaded perfluorocarbon nanodroplets (NDs) can be activated non-invasively by focused ultrasound (FUS) and allow for precise drug-delivery. Anesthetic-loaded NDs and transcranial FUS have previously achieved targeted neuromodulation. To assess the clinical potential of anesthetic-loaded NDs, in depth physical characterization and investigation of storage strategies and triggered-activation is necessary. Pentobarbital-loaded decafluorobutane nanodroplets (PBNDs) with a Definity-derived lipid shell (237 nm; 4.08 × 109 particles/mL) were fabricated and assessed. Change in droplet stability, concentration, and drug-release efficacy were tested for PBNDs frozen at −80 °C over 4 weeks. PBND diameter and the polydispersity index of thawed droplets remained consistent up to 14 days frozen. Cryo-TEM images revealed NDs begin to lose circularity at 7 days, and by 14 days, perfluorocarbon dissolution and lipid fragmentation occurred. The level of acoustic response and drug release decreases through prolonged storage. PBNDs showed no hemolytic activity at clinically relevant concentrations and conditions. At increasing sonication pressures, liquid PBNDs vaporized into gas microbubbles, and acoustic activity at the second harmonic frequency (2 f0) peaked at lower pressures than the subharmonic frequency (1/2 f0). Definity-based PBNDs have been thoroughly characterized, cryo-TEM has been shown to be suitable to image the internal structure of volatile NDs, and PBNDs can be reliably stored at −80 °C for future use up to 7 days without significant degradation, loss of acoustic response, or reduction in ultrasound-triggered drug release.

Research on the neuroprotective effect of pituitary adenylate cyclase-activating polypeptide (PACAP) and its use as a therapeutic agent has grown over the past 30 years. Both in vitro and in vivo experiments have shown that PACAP exerts a strong neuroprotective effect in many central and peripheral neuronal diseases. Various delivery routes have been employed from intravenous (IV) injections to intracerebroventricular (ICV) administration, leading either to systemic or topical delivery of the peptide. Over the last decade, a growing interest in the use of intranasal (IN) administration of PACAP and other therapeutic agents has emerged as an alternative delivery route to target the brain. The aim of this review is to summarize the findings on the neuroprotective effect of PACAP and to discuss how the IN administration of PACAP could contribute to target the effects of this pleiotropic peptide.

The status and sustainability of Poaceae crops, wheat and barley, were examined in an Atlantic zone climate. Intensification had caused yield to rise 3-fold over the last 50 years but had also degraded soil and biodiversity. Soil carbon and nitrogen were compared with current growth and yield of crops. The yield gap was estimated and options considered for raising yield. Organic carbon stores in the soil (C-soil) ranged from 4% in low-input, short-season barley and grass. Carbon acquisition by crops (C-crop) was driven mainly by length of season and nitrogen input. The highest C-crop was 8320 kg ha−1 C in long-season wheat supported by >250 kg ha−1 mineral N fertiliser and the lowest 1420 kg ha−1 in short-season barley fertilised by livestock grazing. Sites were quantified in terms of the ratio C-crop to C-soil, the latter estimated as the mass of carbon in the upper 0.25 m of soil. C-crop/C-soil was 10% in high-input wheat, indicating vulnerability of the soil to continued severe annual disturbance. The yield gap between the current average and the highest attainable yield was quantified in terms of the proportion of grain sink that was unfilled. Intensification had raised yield through a 3- to 4-fold increase in grain number per unit field area, but the potential grain sink was still much higher than the current average yield. Filling the yield gap may be possible but could only be achieved with a major rise in applied nitrogen. Sustainability in Poaceae cropping now faces conflicting demands: (a) conserving and regenerating soil carbon stores in high-input systems, (b) reducing GHG emissions and other pollution from N fertiliser, (c) maintaining the yield or closing the yield gap, and (d) readjusting production among food, feed, and alcohol markets. Current cropping systems are unlikely to satisfy these demands. Transitions are needed to alternative systems based on agroecological management and biological nitrogen fixation.

The fingerprint is a widely adopted biometric trait in forensic and civil applications. Fingerprint biometric systems have been investigated using contact prints and latent and contactless images which range from low to high resolution. While the imaging techniques are advancing with sensor variations, the input fingerprint images also vary. A general fingerprint recognition pipeline consists of a sensor module to acquire images, followed by feature representation, matching and decision modules. In the sensor module, the image quality of the biometric traits significantly affects the biometric system’s accuracy and performance. Imaging modality, such as contact and contactless, plays a key role in poor image quality, and therefore, paying attention to imaging modality is important to obtain better performance. Further, underlying physical principles and the working of the sensor can lead to their own forms of distortions during acquisition. There are certain challenges in each module of the fingerprint recognition pipeline, particularly sensors, image acquisition and feature representation. Present reviews in fingerprint systems only analyze the imaging techniques in fingerprint sensing that have existed for a decade. However, the latest emerging trends and recent advances in fingerprint sensing, image acquisition and their challenges have been left behind. Since the present reviews are either obsolete or restricted to a particular subset of the fingerprint systems, this work comprehensively analyzes the state of the art in the field of contact-based, contactless 2D and 3D fingerprint systems and their challenges in the aspects of sensors, image acquisition and interoperability. It outlines the open issues and challenges encountered in fingerprint systems, such as fingerprint performance, environmental factors, acceptability and interoperability, and alternate directions are proposed for a better fingerprint system.

With the increase in antimicrobial resistance, there is an urgent need to find new antimicrobials. Four particulate antimicrobial compounds, graphite (G), graphene oxide (GO), silver–graphene oxide (Ag-GO) and zinc oxide–graphene oxide (ZnO-GO) were tested against Enterococcus faecium, Escherichia coli, Klebsiella pneumoniae and Staphylococcus aureus. The antimicrobial effects on the cellular ultrastructure were determined using Fourier transform infrared spectroscopy (FTIR), and selected FTIR spectral metrics correlated with cell damage and death arising from exposure to the GO hybrids. Ag-GO caused the most severe damage to the cellular ultrastructure, whilst GO caused intermediate damage. Graphite exposure caused unexpectedly high levels of damage to E. coli, whereas ZnO-GO exposure led to relatively low levels of damage. The Gram-negative bacteria demonstrated a stronger correlation between FTIR metrics, indicated by the perturbation index and the minimal bactericidal concentration (MBC). The blue shift of the combined ester carbonyl and amide I band was stronger for the Gram-negative varieties. FTIR metrics tended to provide a better assessment of cell damage based on correlation with cellular imaging and indicated that damage to the lipopolysaccharide, peptidoglycan and phospholipid bilayers had occurred. Further investigations into the cell damage caused by the GO-based materials will allow the development of this type of carbon-based multimode antimicrobials.

Background: Inpatient malnutrition is a key determinant of adverse patient and healthcare outcomes. The engagement of patients as active participants in nutrition care processes that support informed consent, care planning and shared decision making is recommended and has expected benefits. This study applied patient-reported measures to identify the proportion of malnourished inpatients seen by dietitians that reported engagement in key nutrition care processes. Methods: A subset analysis of a multisite malnutrition audit limited to patients with diagnosed malnutrition who had at least one dietitian chart entry and were able to respond to patient-reported measurement questions. Results: Data were available for 71 patients across nine Queensland hospitals. Patients were predominantly older adults (median 81 years, IQR 15) and female (n = 46) with mild/moderate (n = 50) versus severe (n = 17) or unspecified severity (n = 4) malnutrition. The median length of stay at the time of audit was 7 days (IQR 13). More than half of the patients included had two or more documented dietitian reviews. Nearly all patients (n = 68) received at least one form of nutrition support. A substantial number of patients reported not receiving a malnutrition diagnosis (n = 37), not being provided information about malnutrition (n = 30), or not having a plan for ongoing nutrition care or follow-up (n = 31). There were no clinically relevant trends between patient-reported measures and the number of dietitian reviews or severity of malnutrition. Conclusions: Malnourished inpatients seen by dietitians across multiple hospitals almost always receive nutritional support. Urgent attention is required to identify why these same patients do not routinely report receiving malnutrition diagnostic advice, receiving information about being at risk of malnutrition, and having a plan for ongoing nutrition care, regardless of how many times they are seen by dietitians.

Brain glucose hypometabolism is an early sign of Alzheimer’s disease (AD), and interventions which offset this deficit, such as ketogenic diets, show promise as AD therapeutics. Conversely, high-fat feeding may exacerbate AD risk. We analyzed the metabolomic profile of cerebrospinal fluid (CSF) in a pilot study of older adults who underwent saline and triglyceride (TG) infusions. Older adults (12 cognitively normal (CN), age 65.3 ± 8.1, and 9 with cognitive impairment (CI), age 70.9 ± 8.6) underwent a 5 h TG or saline infusion on different days using a random crossover design; CSF was collected at the end of infusion. Aqueous metabolites were measured using a targeted mass spectroscopy (MS) platform focusing on 215 metabolites from over 35 different metabolic pathways. Data were analyzed using MetaboAnalyst 4.0 and SAS. Of the 215 targeted metabolites, 99 were detectable in CSF. Only one metabolite significantly differed by treatment: the ketone body 3-hydroxybutyrate (HBA). Post hoc analyses showed that HBA levels were associated with age and markers of metabolic syndrome and demonstrated different correlation patterns for the two treatments. When analyzed by cognitive diagnosis group, TG-induced increases in HBA were over 3 times higher for those with cognitive impairment (change score CN +9.8 uM ± 8.3, CI +32.4 ± 7.4, p = 0.0191). Interestingly, individuals with cognitive impairment had higher HBA levels after TG infusion than those with normal cognition. These results suggest that interventions that increase plasma ketones may lead to higher brain ketones in groups at risk for AD and should be confirmed in larger intervention studies.

Decarbonisation of heat is essential to meeting net zero carbon targets; however, fluctuating renewable resources, such as wind or solar, may not meet peak periods of demand. Therefore, methods of underground thermal energy storage can aid in storing heat in low demand periods to be exploited when required. Borehole thermal energy storage (BTES) is an important technology in storing surplus heat and the efficiency of such systems can be strongly influenced by groundwater flow. In this paper, the effect of groundwater flow on a single deep borehole heat exchanger (DBHEs) was modelled using OpenGeoSys (OGS) software to test the impact of varying regional Darcy velocities on the performance of heat extraction and BTES. It is anticipated that infrastructure such as ex-geothermal exploration or oil and gas development wells approaching the end of life could be repurposed. These systems may encounter fluid flow in the subsurface and the impact of this on single well deep BTES has not previously been investigated. Higher groundwater velocities can increase the performance of a DBHE operating to extract heat only for a heating season of 6 months. This is due to the reduced cooling of rocks in proximity to the DBHE as groundwater flow replenishes heat which has been removed from the rock volume around the borehole (this can also be equivalently thought of as “coolth” being transported away from the DBHE in a thermal plume). When testing varying Darcy velocities with other parameters for a DBHE of 920 m length in rock of thermal conductivity 2.55 W/(m·K), it was observed that rocks with larger Darcy velocity (1e-6 m/s) can increase the thermal output by up to 28 kW in comparison to when there is no groundwater flow. In contrast, groundwater flow inhibits single well deep BTES as it depletes the thermal store, reducing storage efficiency by up to 13% in comparison to models with no advective heat transfer in the subsurface. The highest Darcy velocity of 1e-6 m/s was shown to most influence heat extraction and BTES; however, the likelihood of this occurring regionally, and at depth of around or over 1 km is unlikely. This study also tested varying temporal resolutions of charge and cyclicity. Shorter charge periods allow a greater recovery of heat (c. 34% heat injected recovered for 1 month charge, as opposed to

Polymer-coated urea (PCU) was developed to better synchronize nitrogen (N) supply with crop needs and reduce N losses. The objective of this work was to evaluate the effects of different N rates prepared using combinations of urea and ESN (PCU) on corn (Zea mays L.), grain yield, yield components, in-season nutritional status, and residual soil N. Field experiments were conducted on two sites in eastern Ontario (Canada); Kemptville (sandy loam) and Winchester (clay-loam), and repeated over three years (2011–2013). A total of ten treatments were applied using combinations of three N rates (50, 100, and 150 kg N ha−1) and three fertilizer proportions (100% urea, 75:25 urea:ESN, and 60:40 urea:ESN) for each rate. The tenth treatment consisted of a non-fertilized control (0 N). Grain yield was significantly affected by N source, N rate, site, and year. There was no significant effect of the N source in most sites/years. In the wetter season 2013, treatment 100N60:40 in the sandy site produced a similar yield to treatments receiving 150 kg N ha−1. In the clay-loam site, the 150N75:25 treatment had a yield advantage of 11–12% compared with straight urea. Chlorophyll index generally increased with the higher N application rate. The other grain parameters were little affected by the N rate or source. Soil residual mineral N tended to increase with ESN blends at 100 and 150 kg N ha−1 compared with straight urea. Our findings indicate that replacing a portion of urea with PCU might save N in lighter soils prone to leaching especially in wet years without affecting yields.

Parameter estimation represents an important aspect of modeling electromagnetic systems, and a wide range of parameter estimation strategies has been explored in literature. Most parameter estimation methodologies make use of either time-domain or frequency-domain responses as measured from the terminals of the device under test. Very limited research has, however, been conducted into exploring the use of modal decomposition strategies on the time-domain waveforms for parameter estimation applications. In this paper, the use of Empirical Mode Decomposition for estimating the parameters of a three-section lumped parameter transformer model is explored. A novel approach is proposed to define the optimization cost function in terms of the intrinsic modes of simulated time-domain waveforms. The results are compared with results obtained using classical time-domain and frequency-domain approaches. It is shown through an impulse response test that weighting the modes obtained from the Inferred Empirical Mode Decomposition approach presented in this work offers advantages in terms of accurately representing the target model transfer function dynamics and can assist in interpreting the various dynamic modes associated with the target model.

Background: As technology becomes more sophisticated, more accessible methods of interpretating Big Data become essential. We have continued to develop Complexity and Entropy in Physiological Signals (CEPS) as an open access MATLAB® GUI (graphical user interface) providing multiple methods for the modification and analysis of physiological data. Methods: To demonstrate the functionality of the software, data were collected from 44 healthy adults for a study investigating the effects on vagal tone of breathing paced at five different rates, as well as self-paced and un-paced. Five-minute 15-s recordings were used. Results were also compared with those from shorter segments of the data. Electrocardiogram (ECG), electrodermal activity (EDA) and Respiration (RSP) data were recorded. Particular attention was paid to COVID risk mitigation, and to parameter tuning for the CEPS measures. For comparison, data were processed using Kubios HRV, RR-APET and DynamicalSystems.jl software. We also compared findings for ECG RR interval (RRi) data resampled at 4 Hz (4R) or 10 Hz (10R), and non-resampled (noR). In total, we used around 190–220 measures from CEPS at various scales, depending on the analysis undertaken, with our investigation focused on three families of measures: 22 fractal dimension (FD) measures, 40 heart rate asymmetries or measures derived from Poincaré plots (HRA), and 8 measures based on permutation entropy (PE). Results: FDs for the RRi data differentiated strongly between breathing rates, whether data were resampled or not, increasing between 5 and 7 breaths per minute (BrPM). Largest effect sizes for RRi (4R and noR) differentiation between breathing rates were found for the PE-based measures. Measures that both differentiated well between breathing rates and were consistent across different RRi data lengths (1–5 min) included five PE-based (noR) and three FDs (4R). Of the top 12 measures with short-data values consistently within ± 5% of their values for the 5-min data, five were FDs, one was PE-based, and none were HRAs. Effect sizes were usually greater for CEPS measures than for those implemented in DynamicalSystems.jl. Conclusion: The updated CEPS software enables visualisation and analysis of multichannel physiological data using a variety of established and recently introduced complexity entropy measures. Although equal resampling is theoretically important for FD estimation, it appears that FD measures may also be usefully applied to non-resampled data.

There exists a growing interest from the clinical practice research communities in the development of methods to automate HEp-2 stained cells classification procedure from histopathological images. Challenges faced by these methods include variations in cell densities and cell patterns, overfitting of features, large-scale data volume and stained cells. In this paper, a multi-class multilayer perceptron technique is adapted by adding a new hidden layer to calculate the variation in the mean, scale, kurtosis and skewness of higher order spectra features of the cell shape information. The adapted technique is then jointly trained and the probability of classification calculated using a Softmax activation function. This method is proposed to address overfitting, stained and large-scale data volume problems, and classify HEp-2 staining cells into six classes. An extensive experimental analysis is studied to verify the results of the proposed method. The technique has been trained and tested on the dataset from ICPR-2014 and ICPR-2016 competitions using the Task-1. The experimental results have shown that the proposed model achieved higher accuracy of 90.3% (with data augmentation) than of 87.5% (with no data augmentation). In addition, the proposed framework is compared with existing methods, as well as, the results of methods using in ICPR2014 and ICPR2016 competitions.The results demonstrate that our proposed method effectively outperforms recent methods.

Bacterial vaginosis (BV) is the most frequently occurring vaginal infection worldwide, yet it remains significantly underdiagnosed as a majority of patients are asymptomatic. Untreated BV poses a serious threat as it increases one’s risk of STI acquisition, pregnancy complications, and infertility. We aim to minimize these risks by creating a low-cost disposable sensor for at-home BV diagnosis. A clinical diagnosis of BV is most commonly made according to the Amsel criteria. In this method, a fish-like odor, caused by increased levels of trimethylamine (TMA) in vaginal fluid, is used as a key diagnostic. This paper outlines the development of a Home-Based Electrochemical Rapid Sensor (HERS), capable of detecting TMA in simulated vaginal fluid (sVF). Instead of odor-based detection of volatilized TMA, we identify TMA in trimethylammonium form by utilizing HERS and a potentiometric readout. We fabricated the ion selective electrode using a carbon-black-coated cotton string and a TMA-selective membrane consisting of calix[4]arene and sodium tetrakis[3,5-bis(trifluoromethyl)phenyl]borate. When paired with a standard reference electrode, our device was able to quantify TMA concentration in deionized (DI) water, as well as sVF samples at multiple pH levels with a clinically relevant limit of detection (8.66 µM, and theoretically expected Nernstian slope of 55.14 mV/decade).

The field of signal processing using machine and deep learning algorithms has undergone significant growth in the last few years, with a wide scope of practical applications for electroencephalography (EEG). Transcutaneous electroacupuncture stimulation (TEAS) is a well-established variant of the traditional method of acupuncture that is also receiving increasing research attention. This paper presents the results of using deep learning algorithms on EEG data to investigate the effects on the brain of different frequencies of TEAS when applied to the hands in 66 participants, before, during and immediately after 20 min of stimulation. Wavelet packet decomposition (WPD) and a hybrid Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) model were used to examine the central effects of this peripheral stimulation. The classification results were analysed using confusion matrices, with kappa as a metric. Contrary to expectation, the greatest differences in EEG from baseline occurred during TEAS at 80 pulses per second (pps) or in the ‘sham’ (160 pps, zero amplitude), while the smallest differences occurred during 2.5 or 10 pps stimulation (mean kappa 0.414). The mean and CV for kappa were considerably higher for the CNN-LSTM than for the Multilayer Perceptron Neural Network (MLP-NN) model. As far as we are aware, from the published literature, no prior artificial intelligence (AI) research appears to have been conducted into the effects on EEG of different frequencies of electroacupuncture-type stimulation (whether EA or TEAS). This ground-breaking study thus offers a significant contribution to the literature. However, as with all (unsupervised) DL methods, a particular challenge is that the results are not easy to interpret, due to the complexity of the algorithms and the lack of a clear understanding of the underlying mechanisms. There is therefore scope for further research that explores the effects of the frequency of TEAS on EEG using AI methods, with the most obvious place to start being a hybrid CNN-LSTM model. This would allow for better extraction of information to understand the central effects of peripheral stimulation.

The demand for new devices that enable the detection of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) at a relatively low cost and that are fast and feasible to be used as point-of-care is required overtime on a large scale. In this sense, the use of sustainable materials, for example, the bio-based poly (ethylene terephthalate) (Bio-PET) can be an alternative to current standard diagnostics. In this work, we present a flexible disposable printed electrode based on a platinum thin film on Bio-PET as a substrate for the development of a sensor and immunosensor for the monitoring of COVID-19 biomarkers, by the detection of L-cysteine and the SARS-CoV-2 spike protein, respectively. The electrode was applied in conjunction with 3D printing technology to generate a portable and easy-to-analyze device with a low sample volume. For the L-cysteine determination, chronoamperometry was used, which achieved two linear dynamic ranges (LDR) of 3.98−39.0 μmol L−1 and 39.0−145 μmol L−1, and a limit of detection (LOD) of 0.70 μmol L−1. The detection of the SARS-CoV-2 spike protein was achieved by both square wave voltammetry (SWV) and electrochemical impedance spectroscopy (EIS) by a label-free immunosensor, using potassium ferro-ferricyanide solution as the electrochemical probe. An LDR of 0.70−7.0 and 1.0−30 pmol L−1, with an LOD of 0.70 and 1.0 pmol L−1 were obtained by SWV and EIS, respectively. As a proof of concept, the immunosensor was successfully applied for the detection of the SARS-CoV-2 spike protein in enriched synthetic saliva samples, which demonstrates the potential of using the proposed sensor as an alternative platform for the diagnosis of COVID-19 in the future.

In this review manuscript, we discuss the effects of select common viruses on insulin sensitivity and blood–brain barrier (BBB) function and the potential overlapping and distinct mechanisms involved in these effects. More specifically, we discuss the effects of human immunodeficiency virus (HIV), herpes, hepatitis, influenza, respiratory syncytial virus (RSV), and SARS-CoV-2 viruses on insulin sensitivity and BBB function and the proposed underlying mechanisms. These viruses differ in their ability to be transported across the BBB, disrupt the BBB, and/or alter the function of the BBB. For RSV and SARS-CoV-2, diabetes increases the risk of infection with the virus, in addition to viral infection increasing the risk for development of diabetes. For HIV and hepatitis C and E, enhanced TNF-a levels play a role in the detrimental effects. The winter of 2022–2023 has been labeled as a tridemic as influenza, RSV, and COVID-19 are all of concern during this flu season. There is an ongoing discussion about whether combined viral exposures of influenza, RSV, and COVID-19 have additive, synergistic, or interference effects. Therefore, increased efforts are warranted to determine how combined viral exposures affect insulin sensitivity and BBB function.

Zero-emission hydrogen and oxygen production are critical for the UK to reach net-zero greenhouse gasses by 2050. Electrochemical techniques such as water splitting (electrolysis) coupled with renewables energy can provide a unique approach to achieving zero emissions. Many studies exploring electrocatalysts need to “electrically wire” to their material to measure their performance, which usually involves immobilization upon a solid electrode. We demonstrate that significant differences in the calculated onset potential for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) can be observed when using screen-printed electrodes (SPEs) of differing connection lengths which are immobilized with a range of electrocatalysts. This can lead to false improvements in the reported performance of different electrocatalysts and poor comparisons between the literature. Through the use of electrochemical impedance spectroscopy, uncompensated ohmic resistance can be overcome providing more accurate Tafel analysis.

Crop breeding must achieve higher rates of genetic gain in grain yield (GY) and yield stability to meet future food demands in a changing climate. Optimal contributions selection (OCS) based on an index of key economic traits should increase the rate of genetic gain while minimising population inbreeding. Here we apply OCS in a global spring oilseed rape (canola) breeding program during three cycles of S0,1 family selection in 2016, 2018, and 2020, with several field trials per cycle in Australia and Canada. Economic weights in the index promoted high GY, seed oil, protein in meal, and Phoma stem canker (blackleg) disease resistance while maintaining plant height, flowering time, oleic acid, and seed size and decreasing glucosinolate content. After factor analytic modelling of the genotype-by-environment interaction for the additive effects, the linear rate of genetic gain in GY across cycles was 0.059 or 0.087 t ha−1 y−1 (2.9% or 4.3% y−1) based on genotype scores for the first factor (f1) expressed in trait units or average predicted breeding values across environments, respectively. Both GY and yield stability, defined as the root-mean-square deviation from the regression line associated with f1, were predicted to improve in the next cycle with a low achieved mean parental coancestry (0.087). These methods achieved rapid genetic gain in GY and other traits and are predicted to improve yield stability across global spring canola environments.

Landslide susceptibility modelling in tropical climates is hindered by incomplete inventory due to rapid development and natural processes that obliterate field evidence, making validation a challenge. Susceptibility modelling was conducted in Kuala Lumpur, Malaysia using a new spatial partitioning technique for cross-validation. This involved a series of two alternating east-west linear zones, where the first zone served as the training dataset and the second zone was the test dataset, and vice versa. The results show that the susceptibility models have good compatibility with the selected landslide conditioning factors and high predictive accuracy. The model with the highest area under curve (AUC) values (SRC = 0.92, PRC = 0.90) was submitted to the City Council of Kuala Lumpur for land use planning and development control. Rainfall-induced landslides are prominent within the study area, especially during the monsoon period. An extreme rainfall event in December 2021 that triggered 122 landslides provided an opportunity to conduct retrospective validation of the model; the high predictive capability (AUC of PRC = 0.93) was reaffirmed. The findings proved that retrospective validation is vital for landslide susceptibility modelling, especially where the inventory is not of the best quality. This is to encourage wider usage and acceptance among end users, especially decision-makers in cities, to support disaster risk management in a changing climate.

Ozone (O3) is an air pollutant that primarily damages the lungs, but growing evidence supports the idea that O3 also harms the brain; acute exposure to O3 has been linked to central nervous system (CNS) symptoms such as depressed mood and sickness behaviors. However, the mechanisms by which O3 inhalation causes neurobehavioral changes are limited. One hypothesis is that factors in the circulation bridge communication between the lungs and brain following O3 exposure. In this study, our goals were to characterize neurobehavioral endpoints of O3 exposure as they relate to markers of systemic and pulmonary inflammation, with a particular focus on serum amyloid A (SAA) and kynurenine as candidate mediators of O3 behavioral effects. We evaluated O3-induced dose-, time- and sex-dependent changes in pulmonary inflammation, circulating SAA and kynurenine and its metabolic enzymes, and sickness and depressive-like behaviors in Balb/c and CD-1 mice. We found that 3 parts per million (ppm) O3, but not 2 or 1 ppm O3, increased circulating SAA and lung inflammation, which were resolved by 48 h and was worse in females. We also found that indoleamine 2,3-dioxygenase (Ido1) mRNA expression was increased in the brain and spleen 24 h after 3 ppm O3 and that kynurenine was increased in blood. Sickness and depressive-like behaviors were observed at all O3 doses (1–3 ppm), suggesting that behavioral responses to O3 can occur independently of increased SAA or neutrophils in the lungs. Using SAA knockout mice, we found that SAA did not contribute to O3-induced pulmonary damage or inflammation, systemic increases in kynurenine post-O3, or depressive-like behavior but did contribute to weight loss. Together, these findings indicate that acute O3 exposure induces transient symptoms of sickness and depressive-like behaviors that may occur in the presence or absence of overt pulmonary neutrophilia and systemic increases of SAA. SAA does not appear to contribute to pulmonary inflammation induced by O3, although it may contribute to other aspects of sickness behavior, as reflected by a modest effect on weight loss.

The blood–brain barrier (BBB) is an interface primarily comprised of brain endothelial cells (BECs), separating the central nervous system (CNS) from the systemic circulation while carefully regulating the transport of molecules and inflammatory cells, and maintaining the required steady-state environment. Inflammation modulates many BBB functions, but the ultrastructural cytoarchitectural changes of the BBB with inflammation are understudied. Inflammation was induced in male 8–10-week-old CD-1 mice with intraperitoneal lipopolysaccharide (LPS), using a regimen (3 mg/kg at 0, 6, and 24 h) that caused robust BBB disruption but had minimal lethality at the study timepoint of 28 h. Perfusion-fixed brains were collected and the frontal cortical layer III regions were analyzed using a transmission electron microscopy (TEM). The LPS-treated mice had pronounced ultrastructural remodeling changes in BECs that included plasma membrane ruffling, increased numbers of extracellular microvesicles, small exosome formation, aberrant BEC mitochondria, increased BEC transcytosis, while tight junctions appeared to be unaltered. Aberrant pericytes were contracted with rounded nuclei and a loss of their elongated cytoplasmic processes. Surveilling microglial cells were attracted to the neurovascular unit (NVU) of BECs, and astrocyte detachment and separation were associated with the formation of a perivascular space and pericapillary edema. The LPS treatment resulted in numerous ultrastructural aberrant remodeling changes to the neurovascular unit’s BECs, microglia, pericytes, and astrocytes. In summary, a disturbance of the NVU morphology is a consequence of LPS treatment.

The influence of primary cooling and rebound temperature at C–Mn slab corner surfaces during continuous casting on ferrite film transformation and AlN precipitation was investigated. Laboratory simulations included primary cooling to minimum temperature, Tmin, rebounding to various maximum temperatures, Tmax, followed by secondary cooling. The negative effect of a low Tmin on hot ductility could not be readily reversed, even at relatively high temperatures. Quantitative metallography was employed to study the evolution of the microstructure during rebounding and secondary cooling. Following primary cooling to temperatures just above the Ar3, thin films of allotriomorphic ferrite formed on the austenite grain boundaries. These films did not completely transform to austenite during the rebound at 3 °C/s up to temperatures as high as 1130 °C and persisted during slow secondary cooling up to the simulated straightening operation. Whilst dilatometry did not indicate the presence of ferrite after high rebound temperatures, metallography provided clear evidence of its existence, albeit in very small quantities. Coincident with the ferrite at these high temperatures was the predicted (TC-PRISMA) grain boundary precipitation of AlN in bcc iron during the rebound from a Tmin of 730 °C. Importantly no thin ferrite films were observed, and AlN precipitation was not predicted to occur when Tmin was restricted to 830 °C. Cooling below this temperature promotes austenite grain boundary ferrite films and AlN precipitation, which both increase the risk of corner cracking in C–Mn steels.

Incidents to pipes cause damage in water distribution systems (WDS) and access to all parts of the WDS is a challenging task. In this paper, we propose an integrated wireless robotic system for in-pipe missions that includes an agile, maneuverable, and size-adaptable (9-in to 22-in) in-pipe robot, “SmartCrawler”, with 1.56 m/s maximum speed. We develop a two-phase motion control algorithm that enables reliable motion in straight and rotation in non-straight configurations of in-service WDS. We also propose a bi-directional wireless sensor module based on active radio frequency identification (RFID) working in 434 MHz carrier frequency and 120 kbps for up to 5 sensor measurements to enable wireless underground communication with the burial depth of 1.5 m. The integration of the proposed wireless sensor module and the two-phase motion controller demonstrates promising results for wireless control of the in-pipe robot and multi-parameter sensor transmission for in-pipe missions.

Cadaverine is a biomolecule of major healthcare importance in periodontal disease; however, current detection methods remain inefficient. The development of an enzyme biosensor for the detection of cadaverine may provide a cheap, rapid, point-of-care alternative to traditional measurement techniques. This work developed a screen-printed biosensor (SPE) with a diamine oxidase (DAO) and multi-walled carbon nanotube (MWCNT) functionalised electrode which enabled the detection of cadaverine via cyclic voltammetry and differential pulse voltammetry. The MWCNTs were functionalised with DAO using carbodiimide crosslinking with 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) and N-Hydroxysuccinimide (NHS), followed by direct covalent conjugation of the enzyme to amide bonds. Cyclic voltammetry results demonstrated a pair of distinct redox peaks for cadaverine with the C-MWCNT/DAO/EDC-NHS/GA SPE and no redox peaks using unmodified SPEs. Differential pulse voltammetry (DPV) was used to isolate the cadaverine oxidation peak and a linear concentration dependence was identified in the range of 3–150 µg/mL. The limit of detection of cadaverine using the C-MWCNT/DAO/EDC-NHS/GA SPE was 0.8 μg/mL, and the biosensor was also found to be effective when tested in artificial saliva which was used as a proof-of-concept model to increase the Technology Readiness Level (TRL) of this device. Thus, the development of a MWCNT based enzymatic biosensor for the voltammetric detection of cadaverine which was also active in the presence of artificial saliva was presented in this study.

Changing the connection length of an additively manufactured electrode (AME) has a significant impact on the electrochemical and electroanalytical response of the system. In the literature, many electrochemical platforms have been produced using additive manufacturing with great variations in how the AME itself is described. It is seen that when measuring the near-ideal outer-sphere redox probe hexaamineruthenium (III) chloride (RuHex), decreasing the AME connection length enhances the heterogeneous electrochemical transfer (HET) rate constant (k0) for the system. At slow scan rates, there is a clear change in the peak-to-peak separation (ΔEp) observed in the RuHex voltammograms, with the ΔEp shifting from 118 ± 5 mV to 291 ± 27 mV for the 10 and 100 mm electrodes, respectively. For the electroanalytical determination of dopamine, no significant difference is noticed at low concentrations between 10- and 100-mm connection length AMEs. However, at concentrations of 1 mM dopamine, the peak oxidation is shifted to significantly higher potentials as the AME connection length is increased, with a shift of 150 mV measured. It is recommended that in future work, all AME dimensions, not just the working electrode head size, is reported along with the resistance measured through electrochemical impedance spectroscopy to allow for appropriate comparisons with other reports in the literature. To produce the best additively manufactured electrochemical systems in the future, researchers should endeavor to use the shortest AME connection lengths that are viable for their designs.

The holographic space-time (HST) model of inflation has a potential explanation for dark matter as tiny primordial black holes. Motivated by a recent paper of Barrau, we propose a version of this model where some of the inflationary black holes (IBHs), whose decay gives rise to the Hot Big Bang, carry the smallest value of a discrete symmetry charge. The fraction f of IBHs carrying this charge is difficult to estimate from first principles, but we determine it by requiring that the crossover between radiation and matter domination occurs at the correct temperature Teq∼1eV=10−28MP. The fraction is small, f∼2×10−9, so we believe this gives an extremely plausible model of dark matter.

Podocytes are highly differentiated epithelial cells, and their structural and functional integrity is compromised in a majority of glomerular and renal diseases, leading to proteinuria, chronic kidney disease, and kidney failure. Traditional agonists (e.g., pioglitazone) and selective modulators (e.g., GQ-16) of peroxisome-proliferator-activated-receptor-γ (PPARγ) reduce proteinuria in animal models of glomerular disease and protect podocytes from injury via PPARγ activation. This indicates a pivotal role for PPARγ in maintaining glomerular function through preservation of podocytes distinct from its well-understood role in driving insulin sensitivity and adipogenesis. While its transcriptional role in activating adipokines and adipogenic genes is well-established in adipose tissue, liver and muscle, understanding of podocyte PPARγ signaling remains limited. We performed a comprehensive analysis of PPARγ mRNA variants due to alternative splicing, in human podocytes and compared with adipose tissue. We found that podocytes express the ubiquitous PPARγ Var 1 (encoding γ1) and not Var2 (encoding γ2), which is mostly restricted to adipose tissue and liver. Additionally, we detected expression at very low level of Var4, and barely detectable levels of other variants, Var3, Var11, VartORF4 and Var9, in podocytes. Furthermore, a distinct podocyte vs. adipocyte PPAR-promoter-response-element containing gene expression, enrichment and pathway signature was observed, suggesting differential regulation by podocyte specific PPARγ1 variant, distinct from the adipocyte-specific γ2 variant. In summary, podocytes and glomeruli express several PPARγ variants, including Var1 (γ1) and excluding adipocyte-specific Var2 (γ2), which may have implications in podocyte specific signaling and pathophysiology. This suggests that that new selective PPARγ modulators can be potentially developed that will be able to distinguish between the two forms, γ1 and γ2, thus forming a basis of novel targeted therapeutic avenues.

Exosomes mediate intercellular communication, shuttling messages between cells and tissues. We explored whether exosome tissue sequestration is determined by the exosomes or the tissues using ten radiolabeled exosomes from human or murine, cancerous or noncancerous cell lines. We measured sequestration of these exosomes by the liver, kidney, spleen, and lung after intravenous injection into male CD-1 mice. Except for kidney sequestration of three exosomes, all exosomes were incorporated by all tissues, but sequestration levels varied greatly among exosomes and tissues. Species of origin (mouse vs. human) or source (cancerous vs. noncancerous cells) did not influence tissue sequestration. Sequestration of J774A.1 exosomes by liver involved the mannose-6 phosphate (M6P) receptor. Wheatgerm agglutinin (WGA) or lipopolysaccharide (LPS) treatments enhanced sequestration of exosomes by brain and lung but inhibited sequestration by liver and spleen. Response to LPS was not predictive of response to WGA. Path and heat map analyses included our published results for brain and found distinct clusters among the exosomes and the tissues. In conclusion, we found no evidence for a universal binding site controlling exosome-tissue interactions. Instead, sequestration of exosomes by tissues is differentially regulated by both exosomes and tissues and may be stimulated or inhibited by WGA and inflammation.

RNA interference (RNAi) has been widely utilised in many invertebrate models since its discovery, and in a majority of instances presents as a highly efficient and potent gene silencing mechanism. This is emphasized in crustaceans with almost all taxa having the capacity to trigger effective silencing, with a notable exception in the spiny lobsters where repeated attempts at dsRNA induced RNAi have demonstrated extremely ineffective gene knockdown. A comparison of the core RNAi machinery in transcriptomic data from spiny lobsters (Panulirus ornatus) and the closely related slipper lobsters (Thenus australiensis, where silencing is highly effective) revealed that both lobsters possess all proteins involved in the small interfering and microRNA pathways, and that there was little difference at both the sequence and domain architecture level. Comparing the expression of these genes however demonstrated that T. australiensis had significantly higher expression in the transcripts encoding proteins which directly interact with dsRNA when compared to P. ornatus, validated via qPCR. These results suggest that low expression of the core RNAi genes may be hindering the silencing response in P. ornatus, and suggest that it may be critical to enhance the expression of these genes to induce efficient silencing in spiny lobsters.

Since its initial description in 2001, and with falling costs of genotyping, genomic selection has been implemented in a wide range of species. Theory predicts that the genomic selection approach to genetic improvement offers scope both for faster progress and the opportunity to make change in traits formerly less tractable to selection (hard-to-measure traits). This paper reports a survey of organisations involved in genetic improvement, across species, countries, and roles both public and private. While there are differences across organisations in what have been the most significant outcomes to date, both the increased accuracy of breeding values that underpins potentially faster progress, and the re-balancing of genetic change to include real progress in the hard-to-measure traits, have been widely observed. Across organisations, learnings have included the increasing importance of investment in phenotyping, and opportunities to evolve business models to engage more directly with a wider range of stakeholders. Genomic selection can be considered a more modular approach to genetic improvement, and its simplicity and effectiveness can transform both genetic improvement and the effectiveness of multi-disciplinary approaches to improving livestock and plant production, enabling potentially very significant increases in agricultural productivity, profitability and sustainability.

A series of small molecules containing aminopropyltriethoxysilyl-substituted imines and amides were synthesized so that they could potentially be incorporated into self-assembled monolayers (SAMs) on metal oxide surfaces. Simple one-step imine preparations and two-step amide preparations are reported here.

This paper aims to demonstrate the research-to-application and operational use of numerical hydrologic and hydraulic modeling to (a) quantify potential flash flood risks in small urban communities with high spatial resolution; (b) assess the effectiveness of possible flood mitigation measures appropriate for such communities; and (c) construct an effective operational urban flash flood warning system. The analysis is exemplified through case studies pertaining to a small community with dense housing and steep terrain in Tegucigalpa, Honduras, through numerical simulations with a customized self-contained hydrologic and hydraulic modeling software. Issues associated with limited data and the corresponding modeling are discussed. In order to simulate the extreme scenarios, 24-h design storms with return periods from 1 to 100 years with distinctive temporal and spatial distributions were constructed using both daily and hourly precipitation for each month of the rainy season (May–October). Four flood mitigation plans were examined based on natural channel revegetation and the installation of gabion dams with detention basins. Due to limitations arising from the housing layout and budgets, a feasible plan to implement both measures in selected regions, instead of all regions, is recommended as one of the top candidates from a cost-to-performance ratio perspective. Numerical modeling, customized for the conditions of the case study, is proven to be an effective and robust tool to evaluate urban flood risks and to assess the performance of mitigation measures. The transition from hydrologic and hydraulic modeling to an effective urban flash warning operational system is demonstrated by the regional Urban Flash Flood Warning System (UFFWS) implemented in Istanbul, Turkey. With quality-controlled remotely sensed precipitation observations and forecast data, the system generates forcing in the hydrologic and hydraulic modeling network to generate both historical and forecast flow to assist forecasters in evaluating urban flash flood risks.

The concept of insulin resistance has been around since a few decades after the discovery of insulin itself. To allude to the classic Charles Dicken’s novel published 62 years before the discovery of insulin, in some ways, this is the best of times, as the concept of insulin resistance has expanded to include the brain, with the realization that insulin has a life beyond the regulation of glucose. In other ways, it is the worst of times as insulin resistance is implicated in devastating diseases, including diabetes mellitus, obesity, and Alzheimer’s disease (AD) that affect the brain. Peripheral insulin resistance affects nearly a quarter of the United States population in adults over age 20. More recently, it has been implicated in AD, with the degree of brain insulin resistance correlating with cognitive decline. This has led to the investigation of brain or central nervous system (CNS) insulin resistance and the question of the relation between CNS and peripheral insulin resistance. While both may involve dysregulated insulin signaling, the two conditions are not identical and not always interlinked. In this review, we compare and contrast the similarities and differences between peripheral and CNS insulin resistance. We also discuss how an apolipoprotein involved in insulin signaling and related to AD, apolipoprotein E (apoE), has distinct pools in the periphery and CNS and can indirectly affect each system. As these systems are both separated but also linked via the blood–brain barrier (BBB), we discuss the role of the BBB in mediating some of the connections between insulin resistance in the brain and in the peripheral tissues.

Molecular recognition has been described as the “ultimate” form of sensing and plays a fundamental role in biological processes. There is a move towards biomimetic recognition elements to overcome inherent problems of natural receptors such as limited stability, high-cost, and variation in response. In recent years, several alternatives have emerged which have found their first commercial applications. In this review, we focus on molecularly imprinted polymers (MIPs) since they present an attractive alternative due to recent breakthroughs in polymer science and nanotechnology. For example, innovative solid-phase synthesis methods can produce MIPs with sometimes greater affinities than natural receptors. Although industry and environmental agencies require sensors for continuous monitoring, the regulatory barrier for employing MIP-based sensors is still low for environmental applications. Despite this, there are currently no sensors in this area, which is likely due to low profitability and the need for new legislation to promote the development of MIP-based sensors for pollutant and heavy metal monitoring. The increased demand for point-of-use devices and home testing kits is driving an exponential growth in biosensor production, leading to an expected market value of over GPB 25 billion by 2023. A key requirement of point-of-use devices is portability, since the test must be conducted at “the time and place” to pinpoint sources of contamination in food and/or water samples. Therefore, this review will focus on MIP-based sensors for monitoring pollutants and heavy metals by critically evaluating relevant literature sources from 1993 to 2022.