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Bone minerals may be more complex than the prevailing opinion suggests. Understanding its biomaterial properties in health and disease may address fundamental geo/biomorphological ambiguities recurrent within its calcified cancellous hierarchy of macro-, micro-, and nano-skeletal networks. (i) There is evidence that the outer mineral macroskeleton of interconnected trabeculae (150 µm diameter) is modulated according to axes of tensile stress by permeating arrays of periosteal Sharpey's fibres (collagen type III/VI, 5–25 µm thick) studded with tenascin organiser protein. (ii) Its substructural mineral microskeleton is a reticulation of bridged and deformable calcium phosphate/carbonate microspheres (about 1 µm diameter). These organically enshrouded (e.g., bone sialoprotein, osteocalcin, osteopontin) objects, configured by the adhesive organiser protein fibronectin and tempered by trace elements (e.g., Si, Mg, Fe, Al), display differential histochemistry (e.g., acid phosphatase, carbonic anhydrase) and anomalous traits (tetracycline binding, gram-positive microbial staining and nucleic acid staining affinity). The calcified microspheres are intracellular fabrications of osteocyte cohorts developed within "switched on" Golgi cisternae prior to aggregation at the extracellular calcification front in chains and looped assemblies. (iii) Within each microsphere, a less dense centre is encircled by a mineral nanoskeleton of beaded filaments (5 nm in diameter) transmutable in electron density, with a trait for lateral fusion into ladder-like struts, stays and senescent fenestrated plates, constituting domains of microparticle slip and crystal fracture. The evidence suggests a bone mineral biosystem of integrated complexity within which a particulate assemblage at the animate: inanimate calcification front resembles a colonial construct of prokaryote-like, Golgi-fabricated objects calcified with phosphate and harbouring a resident biochemistry. A self-contained "Petrified Microbiome" is proposed to be orchestrated according to a biodynamic primordial paradigm. [ABSTRACT FROM AUTHOR]

Background/Objectives: Healthcare-associated infections involving surgical sites, skin trauma, and devices penetrating the skin are a frequent source of increased expense, hospitalization periods, and adverse outcomes. Medical adhesives are often employed to help protect compromised skin from infection and to secure medical devices, but adhesives can become contaminated by pathogens, exposing wounds, surgical sites, and medical devices to colonization. We aimed to incorporate ceragenins, a class of antimicrobial agents, into silicone- and polyacrylate-based adhesives with the goal of reducing adhesive contamination and subsequent infections. Methods: Three adhesives were developed and evaluated for the release of ceragenins, antimicrobial efficacy, adhesive strength, and dermal irritation. Results: Elution profiles over two weeks showed a high initial release followed by steady, long-term release. Standard microbial challenges of the adhesives by methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, or Candida albicans demonstrated microbial reduction for 6 to 68 days. Lap shear adhesive strength was not reduced for polyacrylate adhesives containing ceragenins, and no dermal irritation was observed in an in vivo model. Conclusions: Ceragenin-containing adhesive materials appear well suited for prevention of bacterial and fungal infections associated with medical devices and bandages. [ABSTRACT FROM AUTHOR]

Background/Objectives: GPT-3.5 and GPT-4 has shown promise in assisting healthcare professionals with clinical questions. However, their performance in real-time clinical scenarios remains underexplored. This study aims to evaluate their precision and reliability compared to board-certified emergency department attendings, highlighting their potential in improving patient care. We hypothesized that board-certified emergency department attendings at Maimonides Medical Center exhibit higher accuracy and reliability than GPT-3.5 and GPT-4 in generating differentials based on history and physical examination for patients presenting to the emergency department. Methods: Real-time patient data from Maimonides Medical Center's emergency department, collected from 1 January 2023 to 1 March 2023 were analyzed. Demographic details, symptoms, medical history, and discharge diagnoses recorded by emergency room attendings were examined. AI algorithms (ChatGPT-3.5 and GPT-4) generated differential diagnoses, which were compared with those by attending physicians. Accuracy was determined by comparing each rater's diagnoses with the gold standard discharge diagnosis, calculating the proportion of correctly identified cases. Precision was assessed using Cohen's kappa coefficient and Intraclass Correlation Coefficient to measure agreement between raters. Results: Mean age of patients was 49.12 years, with 57.3% males and 42.7% females. Chief complaints included fever/sepsis (24.7%), gastrointestinal issues (17.7%), and cardiovascular problems (16.4%). Diagnostic accuracy against discharge diagnoses was highest for ChatGPT-4 (85.5%), followed by ChatGPT-3.5 (84.6%) and ED attendings (83%). Cohen's kappa demonstrated moderate agreement (0.7) between AI models, with lower agreement observed for ED attendings. Stratified analysis revealed higher accuracy for gastrointestinal complaints with Chat GPT-4 (87.5%) and cardiovascular complaints with Chat GPT-3.5 (81.34%). Conclusions: Our study demonstrates that Chat GPT-4 and GPT-3.5 exhibit comparable diagnostic accuracy to board-certified emergency department attendings, highlighting their potential to aid decision-making in dynamic clinical settings. The stratified analysis revealed comparable reliability and precision of the AI chat bots for cardiovascular complaints which represents a significant proportion of the high-risk patients presenting to the emergency department and provided targeted insights into rater performance within specific medical domains. This study contributes to integrating AI models into medical practice, enhancing efficiency and effectiveness in clinical decision-making. Further research is warranted to explore broader applications of AI in healthcare. [ABSTRACT FROM AUTHOR]

Patellofemoral instability is a common condition in children, with an annual incidence of approximately 50 cases per 100,000 children. Instability of the patella involves a number of structures, such as the medial patellofemoral ligament and the vastus medialis obliquus, which can be used for patellar realignment in soft tissue, physeal-sparing procedures. In this rapid review, we aim to review the surgical interventions, post-operative outcomes, and associated surgical complications of global soft tissue procedures in the management of patellofemoral instability. A search of the Medline database was conducted to identify studies evaluating the treatment and outcomes of global treatment of pediatric patellofemoral instability. The included studies analyzed the surgical management of patellofemoral instability in pediatric patients, utilizing soft tissue global procedures and reported functional outcomes, return to sport or play, and post-operative complications. A total of eight studies were included, comprising a cohort of 270 pediatric and adolescent patients and 334 knees. The average patient age was 10.6 years, with 60.4% (163/270) patients being female, and the mean follow-up duration was 58.4 months. Of the eight studies, two examined the three-in-one procedure, three examined the four-in-one procedure, one examined a combination of medial and lateral release, and two examined the Galeazzi procedure. This review underscores the variety of global physeal-sparing surgical procedures available for treating patellofemoral instability. While outcomes are generally favorable, with high rates of return to sport, recurrent residual instability and recurrent dislocation remain significant challenges, with residual instability affecting nearly half of patients. Future research should focus on exploring long-term outcomes, optimizing patient selection, and identifying the causes of recurrent instability to further enhance patient outcomes and reduce complication rates. [ABSTRACT FROM AUTHOR]

The accurate quantification of Campylobacter jejuni in poultry samples is critical for ensuring food safety and compliance with regulatory standards. This study evaluated the performance of three enrichment media—Mueller–Hinton Broth (MHB), Bolton's Blood-Free Broth 2x (BFBB2x), and Buffered Peptone Water (BPW)—in supporting C. jejuni detection and quantification using the BAX® Q7-RT PCR system and traditional plate count methods. Results demonstrated high reliability across all media types, with BFBB2x and MHB showing the strongest correlations (R2 = 0.99) for the BAX® system. BFBB2x exhibited the lowest RMSE (0.13), while MHB balanced precision (RMSE = 0.4) with sensitivity. For plate counts, MHB and BPW achieved the highest correlations (R2 = 0.99) and precision (RMSE = 0.26), with MHB demonstrating the lowest detection limit (2.56 log10 CFU/mL) compared to BFBB2x (2.93 log10 CFU/mL) and BPW (3.31 log10 CFU/mL). The findings underscore MHB's robustness as an enrichment medium, offering consistent performance across both molecular and culture-based methods. The current study supports MHB as the more effective medium for the reliable and precise quantification of C. jejuni in poultry-associated matrices, highlighting its utility in minimizing contamination risks and enhancing food safety. Future research should explore its applicability in diverse poultry products and production environments. [ABSTRACT FROM AUTHOR]

A novel approach for converting non-edible plant biomass into single-cell protein and oil (SCPO) via consolidated bioprocessing has been established, leveraging aerotolerant thermophilic cellulolytic consortia consisting mainly of Thermoanaerobacterium thermosaccharolyticum, Sporolactobacillus spp. and Clostridium sensu stricto to achieve the rapid and complete conversion of crystalline cellulose into a consistent cocktail of lactate, acetate and ethanol. This cocktail is an excellent substrate for cultivating organisms for SCPO production and food and feed applications, including Cyberlindnera jadinii, Yarrowia lipolytica and Corynebacterium glutamicum. Cultivation on this cocktail resulted in yields (YX/S) of up to 0.43 ± 0.012 g/g, indicating a yield from cellulose (YX/Cellulose) of up to 0.27 ± 0.007 g/g (dwb). The resulting SCPO was rich in protein (42.5% to 57.9%), essential amino acids (27.8% to 43.2%) and lipids (7.9% to 8.4%), with unsaturated fatty acid fractions of up to 89%. Unlike fermentation feedstocks derived from easily digested feedstocks (i.e., food waste), this approach has been applied to cellulosic biomass, and this mixed-culture bioconversion can be carried out without adding expensive enzymes. This two-stage cellulosic bioconversion can unlock non-edible plant biomass as an untapped feedstock for food and feed production, with the potential to strengthen resiliency and circularity in food systems. [ABSTRACT FROM AUTHOR]

Health checks aim to improve the health of the population by identifying individuals with risk factors earlier and intervening to prevent disease. The role of commissioners is to ensure health checks provide as much benefit as possible for taxpayer funds invested into them. As such, evidence of the potential impacts of different commissioning choices is beneficial in this decision-making process. System dynamics modelling can be used to provide this evidence by modelling the health check programme using a pre-existing cohort model of a given population. This modelling considers local data, literature findings, and stakeholder views, from which nine different scenarios of a local health check programme have been tested. These scenarios found that extending the duration of health checks to 20 years and improving treatment uptake for those with high blood pressure or high cholesterol reduced rates of cardiovascular disease, improved healthy life expectancy and reduced years lived in ill health. In contrast, improving attendance in the most deprived quintile of the population made very little change to the health of the population overall, although a larger effect was observed in the most deprived areas. These findings helped guide local commissioning decisions by showing the long-term impact of different health check scenarios. [ABSTRACT FROM AUTHOR]

Lipases are enzymes that catalyze the hydrolysis of carboxylic esters at a lipid–water interface and are able to catalyze reactions such as alcoholysis, esterification, transesterification, and enantioselective synthesis in organic media. They are important biocatalysts for biotechnological and industrial applications—such as in the food and flavor industry—and in the production of biopharmaceuticals, biofuels, biopolymers, and detergents. A desirable property of lipases is stereoselectivity for the production of chemicals with high optical purity. In this work, we report the improvement of the enantioselective capabilities of the Geobacillus thermoleovorans CCR11 lipase. By means of a rational design and bioinformatic approaches, six amino acids of the catalytic cavity of the lipase LipTioCCR11 were substituted resulting in an increase in the optimum temperature of the enzyme and in the resistance to the presence of organic solvents in hydrolytic reactions, and in the promotion of the enantioselective recognition of R isomers of carboxylic acids with importance for the pharmaceutical and food industries. [ABSTRACT FROM AUTHOR]

With the vast majority of global trade volume and value reliant on maritime transport, accurate prediction of vessel estimated time of arrival (ETA) is crucial for optimizing supply chain efficiency and managing logistical complexities in port operations. This review paper systematically examines the current state of research and practices in the field of vessel ETA prediction, highlighting significant trends, methodologies, and technologies. It explores various approaches, including classical methods, machine learning and deep learning algorithms, and hybrid methods, developed to enhance the accuracy and reliability of vessel travel time and arrival time predictions. Additionally, this paper categorizes key influencing factors and metrics, and identifies open issues and challenges within current prediction models. Concluding with proposed future research directions aimed at addressing the identified gaps and leveraging technological advancements, this review emphasizes the importance of fostering innovation in maritime ETA prediction systems, particularly within the framework of Intelligent Transportation Systems (ITSs) and maritime logistics. By applying a systematic literature review (SLR) methodology and conducting an in-depth evaluation, the results provide a comprehensive overview of vessel ETA prediction for researchers, practitioners, and policy makers involved in maritime transport and logistics, and offer insights into the potential for improved efficiency, safety, and environmental sustainability in waterway networks. [ABSTRACT FROM AUTHOR]

Background/Objectives: Streptococcus pneumoniae with, or following, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been associated with increased mortality, particularly in older adults. However, vaccination can be an effective preventative measure. This Phase 3 study (NCT05158140) assessed the immunogenicity and safety of co-administering the SARS-CoV-2 vaccine mRNA-1273 with the 23-valent pneumococcal polysaccharide vaccine (PPSV23) or the 15-valent pneumococcal conjugate vaccine (PCV15). Methods: Participants were healthy adults ≥50 years of age who had previously received a two-dose primary series of mRNA-1273 ≥5 months before the first study visit and may have received a booster dose of mRNA-1273 ≥4 months prior to the first study visit. Participants were randomized (1:1:1:1) to receive mRNA-1273 concomitantly with PPSV23 or PCV15 on Day 1 followed by placebo on Day 30, or sequentially with mRNA-1273 and placebo on Day 1 and PPSV23 or PCV15 on Day 30. The primary study endpoints were pneumococcal-serotype-specific opsonophagocytic activity (OPA) geometric mean titers (GMTs) and SARS-CoV-2-specific binding antibody GMTs at 30 days after vaccination, as well as safety and tolerability following vaccination. Results: In total, 850 adults participated in the study. Serotype-specific OPA GMTs at 30 days post-vaccination with PPSV23 or PCV15 were generally comparable between the concomitant and sequential groups. SARS-CoV-2-specific GMTs increased in all groups from pre-vaccination to 30 days post-vaccination with mRNA-1273, with a consistent response between concomitant and sequential groups. Safety profiles were comparable across study groups. Conclusions: Co-administration of mRNA-1273 with PPSV23 or PCV15 in healthy adults ≥50 years of age was immunogenic and well tolerated. [ABSTRACT FROM AUTHOR]

Background/Objectives: Human papillomavirus (HPV) is linked to multiple cancers that can be prevented through vaccination. While the optimal age for vaccination is in childhood and adolescence, vaccination recommendations include adults through age 26 who missed childhood/adolescent vaccination. There are limited data about disparities among adults eligible for catch-up HPV vaccination. We conducted a comprehensive examination of HPV vaccination among US young adults, disaggregating the group by race/ethnicity and nativity status to identify subgroups that may require additional interventions. Methods: We analyzed 2019 and 2022 data of individuals aged 18–26 years from the National Health Interview Survey. Generalized linear models using Poisson regression with log link were used to examine the receipt of 1+ dose of HPV vaccine, race/ethnicity, and nativity (i.e., US- versus foreign-born) status. Results: The overall receipt of 1+ doses of HPV vaccine was 47.5%. The vaccination rate among the US-born group was 49.7% versus 31.9% among the foreign-born group with an adjusted prevalence ratio (APR) of 0.72; (95% CI, 0.62–0.82). Foreign-born non-Hispanic (NH) Black individuals (APR 0.31; 95% CI, 0.13–0.70) were less likely to be vaccinated against HPV than foreign-born NH White individuals, while US-born NH Asians (APR 1.27; 95% CI, 1.09–1.48) had a higher prevalence of the vaccination than the US-born NH White group. Additionally, foreign-born NH Asian (APR 0.60; 95% CI, 0.46–0.77), NH Black (APR 0.27; 95% CI, 0.12–0.61), and Hispanic (APR 0.76; 95% CI, 0.60–0.97) populations were less likely to be vaccinated than their respective US-born counterparts. Conclusion: Profound HPV vaccination inequalities exist among US young adults with particularly low vaccine coverage among racially and ethnically minoritized immigrant populations. [ABSTRACT FROM AUTHOR]

The extraction, processing and transport of crude oil in the Niger Delta region of Nigeria has long been associated with collateral environmental damage to the largest mangrove ecosystem in Africa. Oil pollution is impacting not only one of the planet's most ecologically diverse regions but also the health, livelihoods, and social cohesion of the Delta region inhabitants. Quantifying and directly associating localised oil pollution events to specific petrochemical infrastructure is complicated by the difficulty of monitoring such vast and complex terrain, with documented concerns regarding the thoroughness and impartiality of reported oil pollution events. Earth Observation (EO) offers a means to deliver such a monitoring and assessment capability using Normalised Difference Vegetation Index (NDVI) measurements as a proxy for mangrove biomass health. However, the utility of EO can be impacted by persistent cloud cover in such regions. To overcome such challenges here, we present a workflow that leverages EO-derived high-resolution (10 m) synthetic aperture radar data from the Sentinel-1 satellite constellation combined with machine learning to conduct observations of the spatial land cover changes associated with oil pollution-induced mangrove mortality proximal to pipeline networks in a 9000 km2 region of Rivers State located near Port Harcourt. Our analysis identified significant deforestation from 2016–2024, with an estimated mangrove mortality rate of 5644 hectares/year. Using our empirically derived Pipeline Impact Indicator (PII), we mapped the oil pipeline network to 1 km resolution, highlighting specific pipeline locations in need of immediate intervention and restoration, and identified several new pipeline sites showing evidence of significant oil spill damage that have yet to be formally reported. Our findings emphasise the critical need for the continuous and comprehensive monitoring of oil extractive regions using satellite remote sensing to support decision-making and policies to mitigate environmental and societal damage from pipeline oil spills, particularly in ecologically vulnerable regions such as the Niger Delta. [ABSTRACT FROM AUTHOR]

The influence of machine learning (ML) on scientific domains continues to grow, and the number of publications at the intersection of ML, CO2 capture, and material science is growing rapidly. Approaches for building ML models vary in both objectives and the methods through which materials are represented (i.e., featurised). Featurisation based on descriptors, being a crucial step in building ML models, is the focus of this review. Metal organic frameworks, ionic liquids, and other materials are discussed in this paper with a focus on the descriptors used in the representation of CO2-capturing materials. It is shown that operating conditions must be included in ML models in which multiple temperatures and/or pressures are used. Material descriptors can be used to differentiate the CO2 capture candidates through descriptors falling under the broad categories of charge and orbital, thermodynamic, structural, and chemical composition-based descriptors. Depending on the application, dataset, and ML model used, these descriptors carry varying degrees of importance in the predictions made. Design strategies can then be derived based on a selection of important features. Overall, this review predicts that ML will play an even greater role in future innovations in CO2 capture. [ABSTRACT FROM AUTHOR]

State-of-the-art hydrogeological investigations use transient calibrated numerical flow and transport models for multiple scenario analyses. However, the transient calibration of numerical flow and transport models still requires consistent long-term groundwater time series, which are often not available or contain data gaps, thus reducing the robustness and confidence of the numerical model. This study presents a data-driven approach for the reconstruction and prediction of gaps in a discontinuous groundwater level time series at a monitoring station in the Allertal (Saxony-Anhalt, Germany). Deep Learning and classical machine learning (ML) approaches (artificial neural networks (TensorFlow, PyTorch), the ensemble method (Random Forest), boosting method (eXtreme gradient boosting (XGBoost)), and Multiple Linear Regression) are used. Precipitation and groundwater level time series from two neighboring monitoring stations serve as input data for the prediction and reconstruction. A comparative analysis shows that the input data from one measuring station enable the reconstruction and prediction of the missing groundwater levels with good to satisfactory accuracy. Due to a higher correlation between this station and the station to be predicted, its input data lead to better adapted models than those of the second station. If the time series of the second station are used as model inputs, the results show slightly lower correlations for training, testing and, prediction. All machine learning models show a similar qualitative behavior with lower fluctuations during the hydrological summer months. The successfully reconstructed and predicted time series can be used for transient calibration of numerical flow and transport models in the Allertal (e.g., for the overlying rocks of the Morsleben Nuclear Waste Repository). This could lead to greater acceptance, reliability, and confidence in further numerical studies, potentially addressing the influence of the overburden acting as a barrier to radioactive substances. [ABSTRACT FROM AUTHOR]

Due to cyanobacterial toxin (cyanotoxin) contamination issues in 2018, the city of Salem, Oregon, issued a 33-day do-not-drink advisory for vulnerable people among the 200,000 residents. After the incident, the state of Oregon put in place drinking water rules to require the routine testing of raw water, as well as finished water, in cases where the raw water cyanotoxin concentrations exceeded trigger values. The United States Environmental Protection Agency (EPA) total microcystins drinking water health advisory level (HAL) for small children is 0.3 µg/L. This is equivalent to the minimum reporting level (MRL) for EPA Method 546. Consequently, there was no ability to provide early warnings via toxin testing for total microcystins using the EPA method. In this study, we performed a comparison of the precision and accuracy of the enzyme-linked immunosorbent assay (ELISA) described in the EPA method to a more sensitive assay, the Streptavidin-enhanced Sensitivity (SAES) assay. Based on these precision and accuracy studies and quantitation limit determinations and confirmations, the EPA Office of Ground Water and Drinking Water (OGWDW) has concluded the SAES kit meets the requirements of EPA Method 546. With an MRL that is one-third of the original concentration, the new kit provides a small but critical window for identifying early warnings. Challenges remain with providing early warnings due to the variability in bloom dynamics; however, the new MRL allowed Oregon to lower the trigger level for susceptible systems, thereby providing an additional early warning. [ABSTRACT FROM AUTHOR]

Bottlenecks reduce both traffic safety and efficiency, resulting in congestion and collisions. The introduction of connected autonomous vehicles (CAVs) has had a significant impact on road networks and can improve traffic efficiency at bottlenecks. This paper proposes a microscopic traffic model to investigate CAV behavior at bottlenecks and examine the effect of cyberattacks. The model is developed using data collected from a roadside sensor node. It is implemented in MATLAB using the Euler scheme to simulate a platoon of vehicles on a circular road of length 1 km. The performance is compared with the intelligent driver (ID) model. The results obtained indicate that the road capacity with the proposed model is 1.4 times higher than with the ID model. Further, the proposed model results in nearly constant speeds with small variations, which is realistic. Conversely, the ID model produces large speed variations that are unrealistic. In addition, the proposed model results in less acceleration and deceleration, which leads to lower vehicle emissions and pollution. The efficiency is better than with the ID model due to CAV communication and coordination, so queues dissipate faster. The traffic flow with the proposed model increases as the density decreases, which is consistent with traffic dynamics. It is also shown that the proposed model can characterize CAV behavior under cyberattacks that cause disruptions in the data. Thus, it can be employed for traffic control and forecasting when bottleneck conditions exist and there is malicious behavior. [ABSTRACT FROM AUTHOR]

As processor performance advances, the cache has become an essential component of computer architecture. Moreover, the rapid digital transformation of daily life has resulted in electronic devices storing greater amounts of sensitive information. Thus, device users are becoming more concerned about the security of their personal information, so improving processor performance is no longer the sole priority. Hardware vulnerabilities are generally more difficult to detect and address compared to software viruses and related threats. A common technique for exploiting hardware vulnerabilities is through side-channel attacks. They can bypass software security to extract personal information directly from hardware components like the cache or registers. This paper introduces a novel architecture for the arithmetic logic unit (ALU) and associated memory controller (MC) based on the RISC-V microarchitecture to mitigate side-channel attacks. The proposed approach employs hardware-generated random numbers and has minimal design costs, negligible impact on the original system structure, seamless integration, and easy modification of internal components. Results are presented that show it is effective against side-channel attacks. [ABSTRACT FROM AUTHOR]

Background/Objectives: Immune thrombotic thrombocytopenic purpura (iTTP) is a rare, chronically relapsing disorder that causes life-threatening thrombotic microangiopathy. Many survivors in clinical remission show evidence of ongoing silent cerebral infarction and neurocognitive deficits. Prospective longitudinal studies of this population are needed to acquire a complete understanding of the mechanism behind this ongoing neurologic injury. We aimed to assess the feasibility of a multicenter prospective study of neuropsychological and cognitive function in iTTP survivors in remission and examine novel biomarkers. Methods: We aimed to enroll 50 iTTP patients across three USTMA consortium sites between 2019 and 2022 in a 24-month longitudinal study. Clinical, cognitive, and biomarker assessments, including ADAMTS13 activity, were performed. Results: Despite the COVID-19 pandemic, we enrolled 38 subjects, and 31 (81.6%) completed closeout evaluations at 24 months. Upon the participants' enrollment in the study, we confirmed previous findings, including high rates of moderate to severe neurocognitive and psychiatric sequelae (anxiety, 47%; depression, 45%; and headaches, 55%). Changes in cognitive function were measurable and included decreased immediate memory and visuospatial abilities. Over this two-year study, we did not see a significant change in neurocognitive findings. There was no association between cognitive function and ADAMTS13 activity; however, we found that the level of soluble thrombomodulin (CD141) was significantly correlated with cognitive impairment. Conclusions: We conclude that a more extensive study is feasible, and at least 5–10 years may be required to detect trends in neurocognitive function. Soluble thrombomodulin is a promising biomarker for cognitive impairment in survivors of iTTP, and it is worthy of additional study. [ABSTRACT FROM AUTHOR]

This work presents a machine learning (ML) approach to volume-tracking for computational simulations of multiphase flow. It is an alternative to a commonly used procedure in the volume-of-fluid (VOF) method for volume tracking, in which the phase interfaces are reconstructed for flux calculation followed by volume advection. Bypassing the computationally expensive steps of interface reconstruction and flux calculation, the proposed ML approach performs volume advection in a single step, directly predicting the volume fractions at the next time step. The proposed ML function is two-dimensional and has eleven inputs. It was trained using MATLAB's (R2021a) Deep Learning Toolbox with a grid search method to find an optimal neural network configuration. The performance of the ML function is assessed using canonical test cases, including translation, rotation, and vortex tests. The errors in the volume fraction fields obtained by the ML function are compared with those of the VOF method. In ideal conditions, the ML function speeds up the computations four times compared to the VOF method. However, in terms of overall robustness and accuracy, the VOF method remains superior. This study demonstrates the potential of applying ML methods to multiphase flow simulations while highlighting areas for further improvement. [ABSTRACT FROM AUTHOR]

Simple Summary: Metastatic prostate cancer with high metastatic burden is challenging for treatment. Based on existing literature, it remains unclear whether external beam radiation therapy on the prostate can bring prognostic benefit in this scenario. In this retrospective cohort study using propensity score matching, we compared 50 patients who were treated with standard hormonal and chemotherapy treatments to 50 patients who, in addition to standard treatments, received external beam radiation therapy on the prostate. We found that patients who received radiotherapy had longer overall survival and longer biochemical progression-free survival. These results suggest that adding radiotherapy to the treatment plan may improve survival and other outcomes. Further research should be performed to investigate if this treatment approach is broadly applicable. Background: Retrospective studies suggest that local radiotherapy on the prostate improves overall survival in the metastatic setting, but its benefit in patients with high-burden metastatic disease is still uncertain. Methods: We conducted a retrospective study of 100 high-metastatic-burden prostate cancer patients at Hadassah Ein Karem Medical Center from 2004 to 2021. Patients receiving local RT alongside standard treatment were compared to those receiving standard treatment alone. Prostate RT involved EBRT to the prostate/seminal vesicles with/without pelvic lymph nodes, delivering 54–60 Gy in up to 3 Gy fractions. The standard treatment used was ADT including or excluding chemotherapy. Subsequently, we performed 1:1 propensity score matching on 50 patients for further analysis. Results: The cohort had 100 patients split evenly between the RT and NRT groups. The RT group had higher Overall Survival than NRT (p < 0.046), remaining significant after Propensity Score Matching (PSM) (p < 0.034). Biochemical progression-free survival was also higher in RT vs. NRT (p < 0.033), maintaining significance after PSM (p < 0.042). RT patients reported longer symptom-free time vs. NRT (p < 0.017), though this difference did not persist post-PSM (p < 0.249). Post-PSM analysis showed higher loco-regional progression-free survival in the RT group vs. NRT (p < 0.049). Conclusions: Our study shows improved overall survival in the high-metastatic-burden group when adding RT to the standard treatment of choice, which persists after propensity score matching. The RT group in the entire cohort also demonstrated a reduction in progressing urinary symptoms and biochemical progression-free survival. These findings highlight radiotherapy's potential as a viable treatment in these patients. However, prospective studies with comprehensive data collection are needed to fully address this topic. [ABSTRACT FROM AUTHOR]

Simple Summary: Cirrhosis is the precursor to most cases of hepatocellular carcinoma (HCC). HCC incidence and mortality have increased rapidly over the past two decades in the US, with a <20% 5-year survival rate. Understanding the mechanisms of this transition and identifying biomarkers is vital for effective screening and reducing HCC-related mortality. This study evaluated genome-wide DNA methylation patterns in the buffy coats of cirrhosis patients who developed HCC and those who remained HCC-free during an average four-year follow-up. We then identified differentially methylated sites, distinguishing cirrhosis with HCC from cirrhosis without HCC. The findings support the theory that buffy coat-derived DNA methylation markers could be implementable to stratify cirrhosis patients at high risk before clinical symptoms appear. Background/Objectives: Cirrhosis is the precursor to most cases of hepatocellular carcinoma (HCC). Understanding the mechanisms leading to the transition from cirrhosis to HCC and identifying key biomarkers is crucial to developing effective screening strategies and reducing HCC-related mortality. DNA methylation is associated with gene inactivation and plays an important role in physiological and pathological processes; however, its role in cirrhosis progression to HCC is unknown. Methods: We performed genome-wide DNA methylation profiling using Illumina Infinium MethylationEPI BeadChip in pre-diagnostic samples from 22 cirrhosis patients who subsequently developed HCC and 22 cirrhosis patients who remained HCC-free during an average 4-year follow-up. In a secondary analysis, we examined a subset of patients without hepatitis C virus (HCV) infection. Results: We identified three differentially methylated positions (DMPs) located in ADAM12 (cg13674437) and PSD3 (cg06758847 and cg24595678) that show a strong association with HCC risk (lower median vs. higher median hazards ratio (HR): HR cg13674437 = 0.34, 95% CI = 0.14–0.83; HR cg06758847 = 4.89, 95% CI = 1.79–13.33; HR cg24595678 = 11.19, 95% CI = 3.27–38.35). After excluding all HCV-active patients from our analysis, the HR for the DMPs remained significant. Conclusions: In conclusion, the findings in this study support the theory that buffy coat-derived DNA methylation markers could be used to identify biomarkers among cirrhosis patients at high risk for HCC before clinical symptoms appear. A further study with a large prospective cohort is required to validate these findings. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer treatment can be improved by using tiny particles, called nanoparticles, to deliver drugs directly to cancer cells. To understand how these drug-loaded nanoparticles work in the body, researchers create mathematical models that predict their behavior. These models help us understand how different factors—like the size and makeup of nanoparticles, the characteristics of tumors, and the body's own responses—affect the treatment's success. However, current models sometimes make assumptions that may not match what happens in real-life scenarios, causing us to overestimate the treatment's effectiveness. This research aims to refine these mathematical models by incorporating more realistic data and advanced artificial intelligence techniques. These improvements may lead to more accurate predictions and ultimately make nanoparticle-based cancer treatments more successful in clinical settings, benefiting patients and advancing the field of cancer therapy. Mathematical models are crucial for predicting the behavior of drug conjugate nanoparticles and optimizing drug delivery systems in cancer therapy. These models simulate interactions among nanoparticle properties, tumor characteristics, and physiological conditions, including drug resistance and targeting specificity. However, they often rely on assumptions that may not accurately reflect in vivo conditions. In vitro studies, while useful, may not fully capture the complexities of the in vivo environment, leading to an overestimation of nanoparticle-based therapy effectiveness. Advancements in mathematical modeling, supported by preclinical data and artificial intelligence, are vital for refining nanoparticle-based therapies and improving their translation into effective clinical treatments. [ABSTRACT FROM AUTHOR]

Traditional field vegetation plot surveys are critical for monitoring ecosystem restoration performance and include visual observations to quantitatively measure plants (e.g., species composition and abundance). However, surveys can be costly, time-consuming, and only provide data at discrete locations, leaving potential data gaps across a site. Uncrewed aircraft system (UAS) technology can help fill data gaps between high-to-moderate spatial resolution (e.g., 1–30 m) satellite imagery, manned airborne data, and traditional field surveys, yet it has not been thoroughly evaluated in a virtual capacity as an alternative to traditional field vegetation plot surveys. This study assessed the utility of UAS red-green-blue (RGB) and low-altitude imagery for virtually surveying vegetation plots in a web application and compared to traditional field surveys at two coastal marsh restoration sites in southeast Louisiana, USA. Separate expert botanists independently observed vegetation plots in the field vs. using UAS imagery in a web application to identify growth form, species, and coverages. Taxa richness and assemblages were compared between field and virtual vegetation plot survey results using taxa resolution (growth-form and species-level) and data collection type (RGB imagery, Anafi [low-altitude] imagery, or field data) to assess accuracy. Virtual survey results obtained using Anafi low-altitude imagery compared better to field data than those from RGB imagery, but they were dependent on growth-form or species-level resolution. There were no significant differences in taxa richness between all survey types for a growth-form level analysis. However, there were significant differences between each survey type for species-level identification. The number of species identified increased by approximately two-fold going from RGB to Anafi low-altitude imagery and another two-fold from Anafi low-altitude imagery to field data. Vegetation community assemblages were distinct between the two marsh sites, and similarity percentages were higher between Anafi low-altitude imagery and field data compared to RGB imagery. Graminoid identification mismatches explained a high amount of variance between virtual and field similarity percentages due to the challenge of discriminating between them in a virtual setting. The higher level of detail in Anafi low-altitude imagery proved advantageous for properly identifying lower abundance species. These identifications included important taxa, such as invasive species, that were overlooked when using RGB imagery. This study demonstrates the potential utility of high-resolution UAS imagery for increasing marsh vegetation monitoring efficiencies to improve ecosystem management actions and outcomes. Restoration practitioners can use these results to better understand the level of accuracy for identifying vegetation growth form, species, and coverages from UAS imagery compared to field data to effectively monitor restored marsh ecosystems. [ABSTRACT FROM AUTHOR]

The safety screening of manufactured nanomaterials (MNMs) is essential for their adoption by consumers and the marketplace. Lately, animal-based testing has been replaced by mechanistically informative in vitro assays due to the requirements of regulatory agencies. Cell viability assays are widely employed for manufactured nanomaterial hazard screening as a first-tier approach. Critical parts of such assays are positive and negative controls that serve as measurement benchmarks. We present the cellular viability and corresponding particle characterization obtained with eight different cell lines that were exposed to Au-PEI and Au-PEG-COOH nanoparticles. We showed that polyethyleneimine- and carboxylate-polyethylene-glycol-conjugated gold nanoparticles (AuPEI and Au-PEG-COOH) qualified for positive and negative controls in the in vitro cell viability assays used for MNM toxicological screening. [ABSTRACT FROM AUTHOR]

Simple Summary: The Affordable Care Act's Medicaid expansion aimed to increase healthcare access for low-income individuals by providing Medicaid coverage to more non-elderly adults. This study examines the impact of Medicaid expansion on melanoma diagnosis, treatment, and outcomes, focusing on whether the expansion has led to earlier tumor detection and improved survival rates. By analyzing data from the National Cancer Database, the study reveals that Medicaid expansion is associated with earlier melanoma diagnosis and a decrease in advanced-stage melanoma cases. These findings highlight the importance of public health policies in reducing health disparities and improving cancer care for vulnerable populations. Background: This study addresses the lack of research on Medicaid expansion's impact on melanoma staging, treatment utilization, and outcomes by evaluating its effects under the Affordable Care Act (ACA), particularly focusing on staging at diagnosis, treatment use, and 3-year mortality outcomes. The objective is to determine whether Medicaid expansion led to earlier melanoma diagnosis and improved survival rates among non-elderly adults (ages 40–64) by analyzing data from the National Cancer Database (NCDB). Methods: A total of 12,667 patients, aged 40–64, diagnosed with melanoma from 2010 to 2020 were identified using the NCDB. Difference-in-difference (DID) analysis was performed to analyze tumor staging at presentation between Medicaid expansion states and non-Medicaid expansion states both prior to the expansion and after the expansion. Results: Of the total patients, 2307 were from the pre-expansion time period residing in Medicaid expansion states (MES) and 1804 in non-Medicaid expansion states. In the post-expansion time period there were 5571 residing in the MES and 2985 in the non-MES. DID analysis revealed a decrease in stage IV melanoma at diagnosis (DID −0.222, p < 0.001) between MES and non-MES before and after Medicaid expansion. After expansion, in stage IV, the occurrence of primary surgery was 0.42 in non-MES and 0.44 (difference 0.02); DID analysis was not statistically significant. The use of immunotherapy in MES was significantly higher than in non-MES after expansion (p < 0.001), although DID analysis did not reveal a statistically significant difference. DID analysis showed a statistically significant decrease in 3-year mortality (DID −0.05, p = 0.001) between MES and non-MES before and after Medicaid expansion. Conclusions: This study revealed the positive impact of the ACA's Medicaid expansion on melanoma stage at presentation, highlighting the importance of public health policies in reducing disparities in mortality rates and early-stage diagnoses. Future research should explore additional barriers to care and evaluate the long-term outcomes of Medicaid expansion to optimize cancer care for vulnerable populations. [ABSTRACT FROM AUTHOR]

Background: Low-density lipoprotein cholesterol (LDL-C) is a well-established risk factor for cardiovascular disease, and it plays a causal role in the development of atherosclerosis. Genome-wide association studies (GWASs) have successfully identified hundreds of genetic variants associated with LDL-C. Most of these risk loci fall in non-coding regions of the genome, and it is unclear how these non-coding variants affect circulating lipid levels. One hypothesis is that genetically mediated variation in transcript abundance, detected via the analysis of expressed quantitative trait loci (eQTLs), is key to the biologic function of causal variants. Here, we investigate the hypothesis that non-coding GWAS risk variants affect the homeostatic expression of a nearby putatively causal gene for serum LDL-C levels. Methods: We establish a set of twenty-one expert-curated and validated genes implicated in hypercholesterolemia via dose-dependent pharmacologic modulation in human adults, for which the relevant tissue type has been established. We show that the expression of these LDL-C genes is impacted by eQTLs in relevant tissues and that there are significant genomic-risk loci in LDL-GWAS near these causal genes. We evaluate, using statistical colocalization, whether a single variant or set of variants in each genetic locus is responsible for the GWAS and eQTL signals. Results: Genome-wide association study results for serum LDL-C levels demonstrate that the 402 identified genomic-risk loci for LDL-C are highly enriched for known causal genes for LDL-C (OR 527, 95% CI 126–5376, p < 2.2 × 10−16). However, we find limited evidence for colocalization between GWAS signals near validated hypercholesterolemia genes and eQTLs in relevant tissues (colocalization rate of 26% at a locus-level colocalization probability > 50%). Conclusions: Our results highlight the complexity of genetic regulatory effects for causal hypercholesterolemia genes; we suggest that context-responsive eQTLs may explain the effects of non-coding GWAS hits that do not overlap with standard eQTLs. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to compare microwave ablation (MWA) with and without prior placement of an intra-arterial catheter for the purpose of application of contrast medium (CM). Methods: 148 patients (45 female, 65.1 ± 14.9 years) with liver tumors who underwent CT-guided MWA were included. Of these, 25 patients had an IA catheter placed in the hepatic artery. Results: 37 patients underwent planning imaging for MWA without CM. A total of 86 patients received a standard dose of 80 mL intravenous (IV) CM for the planning scans. The patients with an IA catheter (n = 25) received an IA application of 10 mL CM. A total of 29 patients received contrast-enhanced scans in the PV phase for control of needle positioning after IV application of a standard dose of 80 mL CM. In patients with an IA catheter, control of the needle position was performed by single-slice scans. IA CM application during the ablation enabled monitoring of the ablation zone. Over the entire intervention, patients with IA catheters received less CM as compared to patients without an IA catheter (39.1 ± 10.4 mL vs. 141 ± 39.69 mL; p < 0.001). Conclusions: IA catheter placement was associated with a significant decrease of the amount of CM during MWA and enabled monitoring of the ablation zone. [ABSTRACT FROM AUTHOR]

Combining underwater communication and detection can reduce system size and power consumption as well as improve secrecy. This paper presents a waveform that integrates continuous phase modulation (CPM) for data communication with linear frequency modulation (LFM) for detection. It is shown that the velocity ambiguity and range performance with this waveform are similar to those with only LFM. An integrated underwater acoustic system is also proposed to achieve simultaneous communication and detection. A symbol suffix (SS) is introduced into the signal frame at the transmitter and a two-step algorithm is employed at the receiver for frequency and phase offset estimation. Results are presented, showing that this decreases the sensitivity to CPM and reduces the range ambiguity side lobes. Further, the proposed system can effectively recover the data from the received signal. The bit error rate (BER) is shown to be better than that of traditional systems without a symbol suffix. With changes in the signal-to-noise ratio (SNR), the bit error rate (BER) in underwater acoustic environments is comparable to that in an additive white Gaussian noise (AWGN) channel, indicating a significant improvement in communication performance within the underwater acoustic channel. [ABSTRACT FROM AUTHOR]

This study assesses and characterizes six woody biomass (WB) species commonly harvested in the Republic of Congo: Millettia laurentii (WB1), Millettia eetveldeana (WB2), Hymenocardia ulmoides (WB3), Markhamia tomentosa (WB4), Pentaclethra eetveldeana (WB5), and Hymenocardia acida (WB6). Characterization was performed using proximate analysis with a Thermo Gravimetric Analyser (TGA), ultimate analysis with a CHNS Analyser, higher heating value (HHV) determination, metal content analysis by X-ray fluorescence (XRF), and aboveground biomass (AGB) estimation. The proximate analysis results showed that volatile matter varied between 74.6% and 77.3%, while the ultimate analysis indicated that carbon content ranged from 43% to 46%, with low nitrogen content. XRF analysis revealed low levels of heavy metals in all samples. The HHV results, using three models (Dulong's equation, Friedl, and proximate analysis), showed higher values with Friedl's method (17.3–18.2 MJ/kg) and proximate analysis (15.26–19.23 MJ/kg) compared to Dulong's equation (13.9–14.9 MJ/kg). Savannah biomass (WB6) exhibited high AGB (7.28 t), 14.55 t/ha, and carbon stock (7.28 t). Compared to forest biomass, savannah biomass presents a higher potential for bioenergy production. Minimal statistical analysis of wood biomass showed that parameters such as volatile matter (VM), carbon (C), hydrogen (H), and calculated HHV have low variability, suggesting the biomass is relatively homogeneous. However, moisture and nitrogen showed significant standard deviations, indicating variability in storage conditions or sample nature. Statistical analysis of forest biomass estimation revealed different mean values for diameter, AGB (t and t/ha), and carbon stock, with high standard deviations, indicating a heterogeneous forest with both young and mature trees. These analyses and estimates indicate that these WB species are suitable for biofuel and bioenergy production using gasification, pyrolysis, and combustion processes. Among these thermochemical processes, gasification is the most efficient compared to combustion and pyrolysis. [ABSTRACT FROM AUTHOR]

Background/Objectives: Idecabtagene vicleucel (ide-cel), an anti-B-cell maturation chimeric antigen receptor T-cell therapy, represents an unprecedented treatment option for relapsed/refractory multiple myeloma (R/R MM). Nevertheless, given its limitations, including the risk of adverse effects and unclear durability of efficacy, there remains a need to report the real-world clinical outcomes of ide-cel therapy in patients with R/R MM, as well as explore host predictive factors for therapy. Methods: We performed a single-center retrospective analysis of 25 adult patients with R/R MM who received ide-cel between 2021 and 2023 at the University of California San Diego Health. Data on baseline characteristics, efficacy, safety, and post-relapse outcomes were collected. Treatment responses were assessed using the International Myeloma Working Group criteria while survival analyses were conducted using the Kaplan–Meier and Cox proportional hazards methods. Results: The median age was 65. Twelve patients (48%) were male. Patients received a median of six lines of prior therapy with four patients (16%) receiving prior BCMA-targeted therapy. Six patients (24%) had high-risk cytogenetics while ten patients (40%) had extramedullary disease. The incidence of cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome incidence was 92% and 12%, respectively. All grade infection occurred in 11 patients (44%). Cytomegalovirus (CMV) reactivation occurred in 9 of 19 patients (47%) who were CMV IgG positive prior to CAR T-cell therapy. The objective response rate (ORR) was 84%; stringent complete response was seen in 14 patients (56%). After a median follow-up of 13 months, median progression-free survival (PFS) was 13.9 months (95% CI: 9.21 months—not reached [NR]); median overall survival (OS) was not reached (95% CI: 19.5 months—NR). Among the 11 patients (44%) who progressed after ide-cel therapy, median OS2 was 13.7 months; especially poor outcomes (median OS2 of 1.74 months) were observed in four patients who did not respond to ide-cel. Six of these eleven patients remained alive at time of data cutoff. Univariate and multivariate analysis revealed no significant predictors of ORR, PFS, or OS. Conclusions: Overall, ide-cel had comparable efficacy and safety to the KarMMa-1 trial and other reported real-world experiences. [ABSTRACT FROM AUTHOR]

The majority of US Black social movement organizations during the second half of the twentieth century had explicit ties to either Christian or Islamic religious institutions. The Black Panther Party (BPP) was a notable outlier in its secularism. Through the lens of radicalization, this paper examines the place of violence in the Party's ideological platform and political practice relative to the Party's secularism and experience of state repression. Drawing on newly available archival materials, we examine how Party members conceptualized their own programs, made sense of, and responded to the repressive intervention of state actors and institutions in their attempts to create social change. [ABSTRACT FROM AUTHOR]

A parallelized field-programmable gate array (FPGA) architecture is proposed to realize an ultra-fast, compact, and low-cost dual-channel ultra-wideband (UWB) pulsed-radar system. This approach resolves the main shortcoming of current FPGA-based radars, namely their low processing throughput, which leads to a significant loss of data provided by the radar receiver. The architecture is integrated with an in-house UWB pulsed radar operating at a sampling rate of 20 gigasamples per second (GSa/s). It is demonstrated that the FPGA data-processing speed matches that of the radar output, thus eliminating data loss. The radar system achieves a remarkable speed of over 9000 waveforms per second on each channel. The proposed architecture is scalable to accommodate higher sampling rates and various waveform periods. It is also multi-functional since the FPGA controls and synchronizes two transmitters and a dual-channel receiver, performs signal reconstruction on both channels simultaneously, and carries out user-defined averaging, trace windowing, and interference suppression for improving the receiver's signal-to-noise ratio. We also investigate the throughput rate while offloading radar data onto an external device through an Ethernet link. Since the radar data rate significantly exceeds the Ethernet link capacity, we show how the FPGA-based averaging and windowing functions are leveraged to reduce the amount of offloaded data while fully utilizing the radar output. [ABSTRACT FROM AUTHOR]

Semantic segmentation algorithms, such as UNet, that rely on convolutional neural network (CNN)-based architectures, due to their ability to capture local textures and spatial context, have shown promise for anthropogenic geomorphic feature extraction when using land surface parameters (LSPs) derived from digital terrain models (DTMs) as input predictor variables. However, the operationalization of these supervised classification methods is limited by a lack of large volumes of quality training data. This study explores the use of transfer learning, where information learned from another, and often much larger, dataset is used to potentially reduce the need for a large, problem-specific training dataset. Two anthropogenic geomorphic feature extraction problems are explored: the extraction of agricultural terraces and the mapping of surface coal mine reclamation-related valley fill faces. Light detection and ranging (LiDAR)-derived DTMs were used to generate LSPs. We developed custom transfer parameters by attempting to predict geomorphon-based landforms using a large dataset of digital terrain data provided by the United States Geological Survey's 3D Elevation Program (3DEP). We also explored the use of pre-trained ImageNet parameters and initializing models using parameters learned from the other mapping task investigated. The geomorphon-based transfer learning resulted in the poorest performance while the ImageNet-based parameters generally improved performance in comparison to a random parameter initialization, even when the encoder was frozen or not trained. Transfer learning between the different geomorphic datasets offered minimal benefits. We suggest that pre-trained models developed using large, image-based datasets may be of value for anthropogenic geomorphic feature extraction from LSPs even given the data and task disparities. More specifically, ImageNet-based parameters should be considered as an initialization state for the encoder component of semantic segmentation architectures applied to anthropogenic geomorphic feature extraction even when using non-RGB image-based predictor variables, such as LSPs. The value of transfer learning between the different geomorphic mapping tasks may have been limited due to smaller sample sizes, which highlights the need for continued research in using unsupervised and semi-supervised learning methods, especially given the large volume of digital terrain data available, despite the lack of associated labels. [ABSTRACT FROM AUTHOR]

The imperative of achieving net zero carbon emissions is driving the transition to renewable energy sources. However, this often leads to carbon tunnel vision by narrowly focusing on carbon metrics and overlooking broader sustainability impacts. To enable these broader impacts to be considered, we have developed a generic approach and a freely available assessment tool on GitHub that not only facilitate the high-level sustainability assessment of renewable energy projects but also indicate whether project-level decisions have positive, negative, or neutral impacts on each of the sustainable development goals (SDGs). This information highlights potential problem areas and which actions can be taken to increase the sustainability of renewable energy projects. The tool is designed to be accessible and user-friendly by developing it in MS Excel and by only requiring yes/no answers to approximately 60 diagnostic questions. The utility of the approach and tool are illustrated via three desktop case studies performed by the authors. The three illustrative case studies are located in Australia and include a large-scale solar farm, biogas production from wastewater plants, and an offshore wind farm. Results show that the case study projects impact the SDGs in different and unique ways and that different project–level decisions are most influential, highlighting the value of the proposed approach and tool to provide insight into specific projects and their sustainability implications, as well as which actions can be taken to increase project sustainability. [ABSTRACT FROM AUTHOR]

Laboratory-based high-sensitivity cardiac troponin testing has been the pillar for emergency stratification of suspected acute coronary syndrome for well over a decade. Point-of-care troponin assays achieving the requisite analytical sensitivity have recently been developed and could accelerate such assessment. This review summarises the latest assays and describes their potential diverse clinical utility in the emergency department, community healthcare, pre-hospital, and other hospital settings. It outlines the current clinical data but also highlights the evidence gap, particularly the need for clinical trials using whole blood, that must be addressed for safe and successful implementation of point-of-care troponin analysis into daily practice. Additionally, how point-of-care troponin testing can be coupled with advances in biosensor technology, cardiovascular screening, and triage algorithms is discussed. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) is a technique that employs strong magnetic fields and radio frequencies to generate detailed images of the body's interior. In oncology patients, gadolinium-based contrast agents (GBCAs) are frequently administered to enhance the visualization of tumors. Those contrast agents are gadolinium chelates, characterized by high stability that prevents the release of the toxic gadolinium ion into the body. This work is part of the research for alternative nanoscaled GBCAs. Following the synthesis and characterization of zinc hexacyanoferrate nanoparticles, gadolinium ions were successfully incorporated into a hexacyanoferrate-based matrix, deposited on FTO-coated glass used as working electrode in a gadolinium salt solution, by applying a fixed potential determined through cyclic voltammetry studies. The presence of gadolinium inside the matrix was confirmed by EDX. [ABSTRACT FROM AUTHOR]

This paper examines Connected Smart Green Buildings (CSGBs) in Burnaby, BC, Canada, with a focus on townhouses with one to four bedrooms. The proposed model integrates sustainable materials and smart components such as recycled insulation, Photovoltaic (PV) solar panels, smart meters, and high-efficiency systems. These elements improve energy efficiency and promote sustainability. Operating in island mode, CSGBs can function independently of the grid, providing resilience during power outages and reducing reliance on external energy sources. Real data on electricity, gas, and water consumption are used to optimize load management under isolated conditions. Electric Vehicles (EVs) are also considered in the system. They serve as energy storage devices and, through Vehicle-to-Grid (V2G) technology, can supply power when needed. A hybrid Machine Learning (ML) model combining Long Short-Term Memory (LSTM) and a Convolutional Neural Network (CNN) is proposed to improve the performance. The metrics considered include accuracy, efficiency, emissions, and cost. The performance was compared with several well-known models including Linear Regression (LR), CNN, LSTM, Random Forest (RF), Gradient Boosting (GB), and hybrid LSTM–CNN, and the results show that the proposed model provides the best results. For a four-bedroom Connected Smart Green Townhouse (CSGT), the Mean Absolute Percentage Error (MAPE) is 4.43%, the Root Mean Square Error (RMSE) is 3.49 kWh, the Mean Absolute Error (MAE) is 3.06 kWh, and R 2 is 0.81. These results indicate that the proposed model provides robust load optimization, particularly in island mode, and highlight the potential of CSGBs for sustainable urban living. [ABSTRACT FROM AUTHOR]

Additive manufacturing is an attractive technology due to its versatility in producing parts with diverse properties from a single material. However, the process often generates plastic waste, particularly from failed prints, making sustainability a growing concern. Recycling this waste material presents a potential solution for reducing environmental impact while creating new, functional parts. In this study, the feasibility of creating printable filaments from recycled polylactic acid (PLA) waste and virgin PLA pellets was explored. Filaments were manufactured in the lab using a single-screw desktop extruder with four temperature zones, with compositions ranging from 100% virgin PLA to 100% recycled PLA in 10% composition increments. Test samples were 3D printed using a Material Extrusion 3D printer and subjected to tensile testing in conjunction with digital image correlation to evaluate their ultimate tensile strength, yield strength, Young's modulus, ductility, toughness, and strain distribution. The results indicated that the optimal mechanical properties were observed in specimens made from 100% virgin PLA, 100% recycled PLA, and a 50% virgin/50% recycled PLA blend. Additionally, comparisons with a commercially produced PLA filament revealed that 100% virgin and 100% recycled blends have a 50.33% and 48% higher tensile strength than commercial filament, respectively. However, commercial filaments exhibited higher ductility and toughness than the lab-made extruded filament. [ABSTRACT FROM AUTHOR]

Psychoactive drugs are compounds that alter the function of the central nervous system, resulting in changes in perception, mood, cognition, and behavior. A subclass of psychoactive drugs, psychedelics, are hallucinogenic drugs that can trigger psychedelic experiences and possible changes in mental perception. The potential use of psychedelics as a therapeutic has led to an increase in clinical research focusing on the treatment of mental disorders including anxiety and depression. There are numerous species belonging to Psychotria and Banisteriopsis which have been reported to contain psychedelic and psychoactive compounds; however, there is a lack of validated analytical methods for raw plant material, which is crucial if these plants are to be commercially cultivated for medicines. This study provides a fully validated method using ultra-high performance liquid chromatography (UHPLC) coupled to mass spectrometry (MS) for the following six compounds: tryptamine, N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), tetrahydroharmine (THH), harmaline, and harmine. The validated method was used to determine the psychoactive concentrations in Psychotria viridis, Psychotria carthagenensis, Banisteriopsis caapi, and Alicia anisopetala. Validation parameters were established; linearity (R2 = 0.988–0.999), limit of detection (LOD) (0.06–0.11 ng/mL), limit of quantitation (LOQ) (0.18–0.34 ng/mL), accuracy, precision, extraction efficiency (>98%), recovery (74.1–111.6%), and matrix effect (70.6–109%) were all evaluated. All six compounds eluted within nine minutes, with a total analysis time of 20 min including column equilibration. This method establishes a high-throughput method for the robust analysis of psychedelics which may see future use in agricultural research and industry. [ABSTRACT FROM AUTHOR]

Image formation in radio astronomy is often posed as a problem of constructing a nonnegative function from sparse samples of its Fourier transform. We explore an alternative approach that reformulates the problem in terms of estimating the entries of a diagonal covariance matrix from Gaussian data. Maximum-likelihood estimates of the covariance cannot be readily computed analytically; hence, we investigate an iterative algorithm originally proposed by Snyder, O'Sullivan, and Miller in the context of radar imaging. The resulting maximum-likelihood estimates tend to be unacceptably rough due to the ill-posed nature of the maximum-likelihood estimation of functions from limited data, so some kind of regularization is needed. We explore penalized likelihoods based on entropy functionals, a roughness penalty proposed by Silverman, and an information-theoretic formulation of Good's roughness penalty crafted by O'Sullivan. We also investigate algorithm variations that perform a generic smoothing step at each iteration. The results illustrate that tuning parameters allow for a tradeoff between the noise and blurriness of the reconstruction. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular disease (CVD) is the leading cause of mortality and disability worldwide. While sex differences in CVD have been well documented, the physiological mechanisms of those sex differences remain unclear. As important components of the cardiovascular system, cardiac vagal control and baroreflex serve as mechanisms of sex differences in CVD and are modifiable factors for gender-specific CVD preventions. Methods: Ninety-four healthy adults (18–44 years of age; Mage = 21.09 years; 46 female) were recruited to complete the assessments of heart rate variability (HRV) at a resting baseline and the cardiac timing effect on an R-wave-locked reaction time (RT) task, which were used as the indicator of cardiac vagal control and a novel behavioral measure of baroreflex activity, respectively. HRV metrics (including the root mean square of successive R-R interval differences, high frequency and low frequency heart rate variability, and low frequency-to-high frequency ratio), the cardiac timing effect (the inhibition of RT response at the phase of cardiac systole compared to diastole), and their associations were compared between female and male participants. Results: Female participants showed higher levels of vagally mediated HRV after adjusting for basal resting heart rate. Importantly, the cardiac timing effect on RT responses was positively correlated with vagally mediated HRV among males but not among females. Conclusions: Females and males exhibited different physiological processes to regulate cardiovascular functions and behavioral outcomes. The present findings will help to reduce gender disparities in the preventive care of CVD and improve cardiovascular health for both women and men. [ABSTRACT FROM AUTHOR]

Road traffic significantly impacts global energy consumption and emissions, both of which contribute to climate change. Thus, energy conservation and emission reduction in road transportation are critical concerns, and traffic flow modeling is key to evaluating and improving these metrics. Therefore, this paper develops a microscopic traffic model to characterize energy consumption reflecting driver energy saving awareness. The well-known Intelligent Driver (ID) model cannot predict traffic dynamics within an energy saving driving environment because it is based on a fixed acceleration exponent. Simulation results are presented which demonstrate that the energy consumption in the proposed model decreases as driver energy saving awareness increases. Furthermore, traffic, in the proposed model, experiences smaller variations in flow, speed, acceleration, and density, higher speeds, and less congestion compared to the ID model. Thus, the proposed model can be employed to conserve energy and reduce emissions, thereby decreasing the overall carbon footprint of traffic and contributing to a more sustainable environment. [ABSTRACT FROM AUTHOR]

We study the collision dynamics of two Bose–Einstein condensates, with their dynamical wave functions modeled by a set of coupled, time-dependent Gross–Pitaevskii equations. In an effective one-dimensional system, we identify regimes characterized by the relationship between inter- and intra-atomic interactions and the initial configuration of the system, akin to the equilibrium phase diagram of two interacting Bose condensates. We consider a dynamical setup in which two wave packets are initially at rest, with a small separation about the center of an anisotropic harmonic trap. Upon release, we observe a rapid approach to dynamical equilibrium in the limits of very large and very small inter-particle repulsion, characterized by periodic transmission or reflection of the condensates as distinguishable units, whereas the intermediate, critical regime is characterized by extended transient dynamics, density fracturing, and dynamical mixing. [ABSTRACT FROM AUTHOR]

Background: Esophageal cancer (EC) is the sixth leading cause of cancer-related mortality worldwide, continuing to be a significant public health concern. The purpose of this study is to assess the impact of staging and histopathology of EC on associated mortality. The study also aims to further investigate clinical characteristics, prognostic factors, and survival outcomes in patients diagnosed with EC between 2010 and 2017. Furthermore, we analyzed the interaction between tumor histology and staging and the risk of mortality. Methods: A total of 24,011 patients diagnosed with EC between 2010 and 2017 in the United States were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database. Demographic parameters, tumor stage, and histologic subtypes were analyzed and associated overall mortality (OM) and cancer-specific mortality (CSM) were measured across all subgroups. Covariates reaching the level of statistical significance, demonstrable by a p-value equal to or less than 0.01, were incorporated into a multivariate Cox proportional hazards model. A hazard ratio greater than 1 was indicative of an increased risk of mortality in the presence of the variable under discussion. Additionally, the study explores the interaction between histology and tumor stage on outcomes. Results: The majority of patients were male (80.13%) and non-Hispanic white (77.87%), with a predominant age at diagnosis of between 60 and 79 years (59.86%). Adenocarcinoma was the most common tumor subtype (68.17%), and most patients were diagnosed at a distant stage (41.29%). Multivariate analysis revealed higher mortality risks for males, older patients, unmarried individuals, and those with advanced-stage tumors. Higher income, receiving radiation or chemotherapy, and undergoing surgery were associated with lower mortality. Tumor subtype significantly influenced mortality, with squamous cell carcinoma and neuroendocrine tumors showing higher hazard ratios compared to adenocarcinoma. Adenocarcinoma is linked to a poorer prognosis at advanced stages, whereas the opposite trend is observed for SCC. Conclusions: The study identifies significant demographic and clinicopathologic factors influencing mortality in esophageal cancer patients, highlighting the importance of early diagnosis and treatment intervention. Future research should focus on tailored treatment strategies to improve survival outcomes in high-risk groups and to understand the interaction between tumor histology and tumor stage. [ABSTRACT FROM AUTHOR]

Laying hens usually have 16 h of light and 8 h of darkness during egg laying, with eggshell formation primarily occurring during darkness when dietary calcium is lacking, leading to bone calcium resorption and osteoporosis. This study examined how interrupting the dark phase affects bone health in 396 Hy-line W36 hens assigned to control (C) or treatment groups (W1 and W2). All hens received 16 h of light and 8 h of darkness daily in different variations of scotophase interruption. Blood samples were taken at weeks 20, 30, 50, and 70, serum calcium was measured during darkness at two timepoints (SRT and END), and bone demineralization markers were examined using enzyme concentrations (TRACP-5b and CTX-I). Across weeks, tibias were CT-scanned for density (mg/cm3) and area (mm2), then used for breakage strength analysis (N) and ash%. No SRT Ca level differences emerged, but C hens had lower END Ca levels compared to W1 and W2 hens across all weeks, while W1 and W2 hens showed no significant differences. C hens displayed higher TRACP-5b and CTX-I concentrations across all weeks compared to W1 and W2 (all p ≤ 0.05). At week 70, C hens had the lowest cortical bone cross-sectional area and mineral density compared to W1 and W2 (all p ≤ 0.05). Tibiotarsi bone breakage strength was lower in C hens compared to W1 and W2. C hens had significantly lower ash% than treatment birds. Interrupting the scotophase period improved overall bone health in Hy-line W36 laying hens. [ABSTRACT FROM AUTHOR]

Non-muscle invasive bladder cancer (NMIBC) accounts for approximately 70–75% of all bladder cancer cases. The standard treatment for high-risk NMIBC involves transurethral tumour resection followed by intravesical Bacillus Calmette–Guerin (BCG) immunotherapy. While BCG immunotherapy is both safe and effective, it frequently leads to the development of lower urinary tract symptoms (LUTS) such as urinary urgency, frequency, dysuria, and pelvic discomfort. These symptoms can significantly diminish patients' quality of life and may result in the discontinuation of BCG treatment, adversely affecting oncological outcomes. Despite the considerable clinical impact of BCG-induced LUTS, the underlying mechanisms remain unclear, hindering the implementation or development of effective treatments. This review provides novel insights into the potential mechanisms underlying BCG-induced LUTS, focusing on the integrated roles of afferent and efferent nerves in both normal and pathological bladder sensation and function. Specifically, this review examines how the body's response to BCG—through the development of inflammation, increased urothelial permeability, and altered urothelial signalling—might contribute to LUTS development. Drawing from known mechanisms in other common urological disorders and data from successful clinical trials involving NMIBC patients, this review summarises evidence supporting the likely changes in both sensory nerve signalling and bladder muscle function in the development of BCG-induced LUTS. However, further research is required to understand the intricate mechanisms underlying the development of BCG-induced LUTS and identify why some patients are more likely to experience BCG intolerance. Addressing these knowledge gaps could have profound implications for patients' quality of life, treatment adherence, and overall outcomes in NMIBC care. [ABSTRACT FROM AUTHOR]