bluuebunny/crossref_metadata_2025 huggingface dataset:
Including transgender populations in mathematical models for HIV treatment and prevention: current barriers and policy implications
Authors: Tordoff Diana M. , Restar Arjee , Minalga Brian , Fernandez Atlas , Dimitrov Dobromir , Duerr Ann ,   the Seattle Trans and Nonbinary Sexual Health (STARS) Advisory Board
Published: June 2024

Introduction

Mathematical models of HIV have been uniquely important in directing and evaluating HIV policy. Transgender and nonbinary people are disproportionately impacted by HIV; however, few mathematical models of HIV transmission have been published that are inclusive of transgender and nonbinary populations. This commentary discusses current structural challenges to developing robust and accurate trans‐inclusive models and identifies opportunities for future research and policy, with a focus on examples from the United States.

Discussion

As of April 2024, only seven published mathematical models of HIV transmission include transgender people. Existing models have several notable limitations and biases that limit their utility for informing public health intervention. Notably, no models include transgender men or nonbinary individuals, despite these populations being disproportionately impacted by HIV relative to cisgender populations. In addition, existing mathematical models of HIV transmission do not accurately represent the sexual network of transgender people. Data availability and quality remain a significant barrier to the development of accurate trans‐inclusive mathematical models of HIV. Using a community‐engaged approach, we developed a modelling framework that addresses the limitations of existing model and to highlight how data availability and quality limit the utility of mathematical models for transgender populations.

Conclusions

Modelling is an important tool for HIV prevention planning and a key step towards informing public health interventions, programming and policies for transgender populations. Our modelling framework underscores the importance of accurate trans‐inclusive data collection methodologies, since the relevance of these analyses for informing public health decision‐making is strongly dependent on the validity of the model parameterization and calibration targets. Adopting gender‐inclusive and gender‐specific approaches starting from the development and data collection stages of research can provide insights into how interventions, programming and policies can distinguish unique health needs across all gender groups. Moreover, in light of the data structure limitations, designing longitudinal surveillance data systems and probability samples will be critical to fill key research gaps, highlight progress and provide additional rigour to the current evidence. Investments and initiatives like Ending the HIV Epidemic in the United States can be further expanded and are highly needed to prioritize and value transgender populations across funding structures, goals and outcome measures.
Effectiveness and safety of elexacaftor/tezacaftor/ivacaftor treatment in children aged 6‐11 years with cystic fibrosis in a real‐world setting
Authors: Daccò Valeria , Rosazza Chiara , Mariani Alessandra , Rizza Carmela , Ingianni Nicolò , Nazzari Erica , Terlizzi Vito , Blasi Francesco Arturo , Alicandro Gianfranco
Published: June 2024

Background

Elexacaftor‐tezacaftor‐ivacaftor (ETI) is a highly effective cystic fibrosis (CF) transmembrane conductance regulator (CFTR) modulating therapy for people with CF and at least one F508del variant. However, there is limited data about the safety and efficacy of this therapy in pediatric populations and in real‐world settings. This study aimed at evaluating the effectiveness, tolerability, and safety of ETI in children with CF.

Methods

This was a prospective observational study including all children aged 6–11 years who initiated ETI therapy between October 2022 and March 2023 at the Pediatric CF Center of Milan (Italy). Study outcomes included changes in sweat chloride concentration, FEV1, LCI2.5, body mass index (BMI), tolerance, and safety. Mean changes in study outcomes from baseline through 24 weeks were estimated using mixed‐effects regression models.

Results

The study included 34 children with CF (median age: 8.3 years). At Week 12, we observed an average decrease in LCI2.5 of 2.3 units (95% confidence interval [CI]: −3.1; −1.5). At Week 24, sweat chloride concentration decreased by 63 mEq/L (95% CI: −69; −58), FEV1 increased by 8.8 percentage point (95% CI: 3.7; 13.9) and BMI increased by 0.15 standard deviation scores (95% CI: 0.04; 0.25). Skin rashes appeared in 6 patients which spontaneously resolved within a few days. One month after treatment initiation, one patient experienced an elevation in liver function test results, which subsequently decreased during follow‐up visits without necessitating discontinuation of therapy.

Conclusions

Our data indicate that ETI therapy is well tolerated by children with CF and is effective in improving signs of lung function abnormalities from early childhood.
EXTENDED COMMENTARY—Navigating the labyrinth of youth return to deoccupied territories in Ukraine: Stakeholders, strategies, and ethical imperatives
Authors: Bohdanov Ihor , Suchikova Yana
Published: June 2024

The war in Ukraine has been ongoing for over two years. As territories that were captured at the beginning of the conflict are being deoccupied, the pressing issue of repopulating these areas emerges, especially concerning the youth. In this commentary, we critically examine the tripartite cooperation among universities, governments, and local self‐government bodies as a critical mechanism for encouraging the return of young people to Ukraine's deoccupied territories. Considering the inevitable exodus of youth due to occupation, we underscore the importance of early strategy conceptualization for their return. The discussion analyzes the roles and responsibilities of all key stakeholders, the necessity to balance national directives with local autonomy, and the ethical imperatives that should guide such endeavors. Although centered on the Ukrainian context, the insights from this research may prove valuable for other regions encountering similar challenges amidst globalization.
Evaluation of geographic variations in appendicectomy outcomes within Western Australia assessing the impact of surgical wait times and rate of negative appendicectomies in both urban and rural locations statewide
Authors: Scaddan Beau , Al Asedy Balsam , Lee Samantha , Lari Parsa Rastegar
Published: June 2024

Purpose

Surgery wait times after diagnosis of appendicitis are an important factor influencing the success of a patient’s treatment. The proposed study will be a quantitative multicenter retrospective cohort design with the primary aim of assessing the difference between appendicectomy wait times between rural and urban hospitals in Western Australia and the effect of this on operative outcomes. Selected outcome measures will be examined by time from initial presentation at an emergency department to the patient being diagnosed and then time of diagnosis to surgery being performed. The secondary aim is to compare rates of negative appendicectomies between hospitals.

Methods

Appendicectomy patients will be identified from operating room register by medical student data collectors; then, each respective hospital’s emergency room data collection will subsequently be accessed to complete case report forms based on demographics and clinical findings, pre-operative investigations, and management and follow-up. Case report forms with > 95% completeness will be accepted for pooled analysis. The expected duration of retrospective data collection will be 8 months. This study RGS6483 has received HREC approval by the Royal Perth Hospital HREC Ethics Committee, with a waiver of consent obtained and the HREC was notified of amendments to the protocol made on April 21, 2024.

Dissemination of results.

Data will be collected and stored online through a secure server running the Research Electronic Data Capture (REDCap) web application. No patient-identifiable data will be entered into the system. Results will subsequently be shared via scientific journal publication and presentation at relevant meetings.
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction
Authors: Demir Selçuk , Sahin Emrehan Kutlug
Published: June 2024

In the field of data engineering in machine learning (ML), a crucial component is the process of scaling, normalization, and standardization. This process involves transforming data to make it more compatible with modeling techniques. In particular, this transformation is essential to ensure the suitability of the data for subsequent analysis. Despite the application of many conventional and relatively new approaches to ML, there remains a conspicuous lack of research, particularly in the geotechnical discipline. In this study, ML-based prediction models (i.e., RF, SVR, Cubist, and SGB) were developed to estimate the undrained shear strength (UDSS) of cohesive soil from the perspective of a wide range of data-scaling and transformation methods. Therefore, this work presents a novel ML framework based on data engineering approaches and the Cubist regression method to predict the UDSS of cohesive soil. A dataset including six different features and one target variable were used for building prediction models. The performance of ML models was examined considering the impact of the data pre-processing issue. For that purpose, data scaling and transformation methods, namely Range, Z-Score, Log Transformation, Box-Cox, and Yeo-Johnson, were used to generate the models. The results were then systematically compared using different sampling ratios to understand how model performance varies as various data scaling/transformation methods and ML algorithms were combined. It was observed that data transformation or data sampling methods had considerable or limited effects on the UDSS model performance depending on the algorithm type and the sampling ratio. Compared to RF, SVR, and SGB models, Cubist models provided higher performance metrics after applying the data pre-processing steps. The Box-Cox transformed Cubist model yielded the best prediction performance among the other models with an R2 of 0.87 for the 90% training set. Also, the UDSS prediction model generally yielded the best performance metrics when it was used with the transformed-based models (i.e., Box-Cox, Log, and Yeo-Johnson) than that of scaled-based (i.e., Range and Z-Score) models. The results show that the Cubist model has a higher potential for UDSS prediction, and data pre-processing methods have impacts on the predictive capacity of the evaluated regression models.
Approaches for the production of reference materials with qualitative properties—The new International Standard ISO 33406
Authors: Trapmann Stefanie , Ellison Stephen L. R. , Davis W. Clay , Possolo Antonio , Zheng Jiang , Botha Angelique
Published: June 2024

The number of reference materials (RMs), including certified reference materials (CRMs) characterized for qualitative properties, has steadily increased in recent years. In response, the Technical Committee for Reference Materials of the International Organization for Standardization, ISO/TC 334, developed ISO 33406 to provide guidance to reference material producers (RMPs) on producing qualitative RMs. ISO 33406 builds on the general requirements in ISO 17034:2016 for RMP competence and offers specific guidance on value assignment, assessment of homogeneity and stability, statement of metrological traceability, and measurement uncertainty evaluation for RMs with qualitative property values.
Effect of surface treatment strategies on bond strength of additively and subtractively manufactured hybrid materials for permanent crowns
Authors: Mao Zhen , Schmidt Franziska , Beuer Florian , Yassine Jamila , Hey Jeremias , Prause Elisabeth
Published: June 2024

Objectives

The purpose of this study is to evaluate the bond strength of different computer-aided design / computer-aided manufacturing (CAD/CAM) hybrid ceramic materials following different pretreatments.

Methods

A total of 306 CAD/CAM hybrid material specimens were manufactured, n = 102 for each material (VarseoSmile Crownplus [VSCP] by 3D-printing; Vita Enamic [VE] and Grandio Blocs [GB] by milling). Each material was randomly divided into six groups regarding different pretreatment strategies: control, silane, sandblasting (50 μm aluminum oxide particles), sandblasting + silane, etching (9% hydrofluorics acid), etching + silane. Subsequently, surface roughness (Ra) values, surface free energy (SFE) were measured. Each specimen was bonded with a dual-cured adhesive composite. Half of the specimens were subjected to thermocycling (5000 cycles, 5–55 °C). The shear bond strength (SBS) test was performed. Data were analyzed by using a two-way analysis of variance, independent t-test, and Mann-Whitney-U-test (α = 0.05).

Results

Material type (p = 0.001), pretreatment strategy (p < 0.001), and the interaction (p < 0.001) all had significant effects on Ra value. However, only etching on VSCP and VE surface increased SFE value significantly. Regarding SBS value, no significant difference was found among the three materials (p = 0.937), while the pretreatment strategy significantly influenced SBS (p < 0.05). Etching on VSCP specimens showed the lowest mean value among all groups, while sandblasting and silane result in higher SBS for all test materials.

Conclusions

The bond strength of CAD/CAM hybrid ceramic materials for milling and 3D-printing was comparable. Sandblasting and silane coupling were suitable for both millable and printable materials, while hydrofluoric etching should not be recommended for CAD/CAM hybrid ceramic materials.

Clinical relevance

Since comparable evidence between 3D-printable and millable CAD/CAM dental hybrid materials is scarce, the present study gives clear guidance for pretreatment planning on different materials.
Somatic amplification and addiction profile as risk factors for medication overuse headache with chronic migraine
Authors: Cesur Ender , Yavuz Burcu Göksan , Acar Erkan , Özdemir Zeynep , Soyukibar Tuba Erdoğan , Aydınlar Elif Ilgaz
Published: June 2024

Introduction

Overuse of analgesics can lead to medication-overuse headache (MOH) in chronic migraine (CM) patients, and is often linked to addiction. This study explores the addiction-related characteristics and somatic amplification in patients with, CM with medication overuse headache (CM+MOH), CM, and healthy controls.

Methods

73 CM patients and 70 CM+MOH, along with 63 healthy controls, participated in the study. Assessments included a Sociodemographic Form, Migraine Disability Assessment Scale (MIDAS), Addiction Profile Index (API), Addiction Profile Index-Clinical Version (API-C), and the Somatosensory Amplification Scale (SSAS).

Results

Substance use characteristics, craving, motivation for use, and addiction severity scores were higher in the CM+MOH group than in both the CM and the control group. Specifically, the SSAS scores within the CM+MOH group surpassed those of both the CM and control groups. In the CM+MOH group, SSAS scores were a strong predictor of the amount of analgesic usage. Besides, craving and motivation for substance use scores significantly predicted the number of days analgesic taken per month in the CM+MOH group

Conclusion

CM patients with MOH exhibit a pronounced association with addiction, and a heightened manifestation of somatic symptoms. Addressing addiction characteristics and psychosomatic amplification is important to ensure comprehensive management.
When rational functions meet virtual elements: the lightning virtual element method
Authors: Trezzi Manuel , Zerbinati Umberto
Published: June 2024

We propose a lightning Virtual Element Method that eliminates the stabilisation term by actually computing the virtual component of the local VEM basis functions using a lightning approximation. In particular, the lightning VEM approximates the virtual part of the basis functions using rational functions with poles clustered exponentially close to the corners of each element of the polygonal tessellation. This results in two great advantages. First, the mathematical analysis of a priori error estimates is much easier and essentially identical to the one for any other non-conforming Galerkin discretisation. Second, the fact that the lightning VEM truly computes the basis functions allows the user to access the point-wise value of the numerical solution without needing any reconstruction techniques. The cost of the local construction of the VEM basis is the implementation price that one has to pay for the advantages of the lightning VEM method, but the embarrassingly parallelizable nature of this operation will ultimately result in a cost-efficient scheme almost comparable to standard VEM and FEM.
Residual effect of commonly used fungicides in strawberries on Amblyseius swirskii, Neoseiulus cucumeris, and Neoseiulus californicus (Mesostigmata: Phytoseiidae)
Authors: Busuulwa Allan , Revynthi Alexandra M. , Liburd Oscar E. , Lahiri Sriyanka
Published: June 2024

Florida’s strawberry industry is currently valued at $511 million annually but faces challenges from pathogens and arthropod pests especially Tetranychus urticae Koch (twospotted spider mite) and Scirtothrips dorsalis Hood (chilli thrips). Predatory mites, particularly Neoseiulus cucumeris Oudemans, Neoseiulus californicus McGregor, and Amblyseius swirskii Athias-Henriot, play a crucial role in pest management. However, there are concerns regarding how these biological control agents are affected by fungicides used in current pathogen management strategies. This study assessed the residual effects of commonly used fungicides in strawberries on the survival, feeding, and oviposition of these predatory mites. Commercially sourced predatory mites were reared on S. dorsalis larvae, and gravid female predators placed on fungicide treated strawberry leaf discs in a Munger cell for 120 h. Fungicides tested included two formulations of Captan, hydrogen peroxide + peroxyacetic acid, cyprodinil + fludioxonil, tetramethylthiuram disulfide, cyflufenamid and a control. All fungicides tested had an impact on the survival, feeding, and oviposition of the predators. Among the fungicide treatments, the lowest predator survival was observed in the cyprodinil + fludioxonil treatment, while the highest was observed in the hydrogen peroxide + peroxyacetic acid and tetramethylthiuram disulfide treatments. In all treatments, feeding and oviposition greatly varied among predators; specifically, N. cucumeris and A. swirskii had the lowest prey consumption, while N. californicus had the highest. These findings highlight the potential incompatibility between fungicides and predatory mites and demonstrate the need for the development of a fungicide rotation program tailored to the different susceptibilities of predators to fungicides.
Behavioral Inhibition and Social Anxiety Disorder as Predictors of Long-Term Outcomes of Cognitive Behavioral Therapy for Youth Anxiety Disorders
Authors: Skumsnes Toril , Fjermestad Krister W. , Wergeland Gro Janne , Aalberg Marianne , Heiervang Einar R. , Kodal Arne , Ingul Jo Magne
Published: June 2024

The temperamental trait behavioral inhibition (BI) is related to the development and maintenance of anxiety, particularly much so to social anxiety disorder. We investigated if BI and social anxiety disorder predicted cognitive behavioral therapy (CBT) outcomes for youth anxiety. Youth (N = 179; Mage = 11.6 years) were assessed 4 years following a randomized controlled CBT effectiveness trial. BI was measured by the parent-reported Behavioral Inhibition Questionnaire at baseline. The outcomes were diagnostic recovery, youth- and parent-reported anxiety symptoms, and clinical severity at post-treatment, 1-year, and 4-year follow-up. Having social anxiety disorder negatively predicted diagnostic recovery and predicted higher clinical severity at all assessment points and was the only significant predictor of outcomes at 4-year follow-up. Higher BI negatively predicted diagnostic recovery and predicted higher clinical severity and parent-reported symptom levels at post-treatment and 1-year follow-up, and predicted higher youth-reported anxiety levels at 1-year follow-up. Higher BI was the only predictor of youth- and parent-reported anxiety symptoms. BI and social anxiety disorder seem to be unique predictors of CBT outcomes among youth with anxiety disorders. CBT adaptations may be indicated for youth with high BI and social anxiety disorder.
A Model for the Coexistence of Competing Mechanisms for $$\text {Ca}^{\text {2}+}$$ Oscillations in T-lymphocytes
Authors: Castaneda Ruan Paco , Benson J. Cory , Trebak Mohamed , Kirk Vivien , Sneyd James
Published: June 2024

$$\text {Ca}^{\text {2}+}$$

Ca

2
+

is a ubiquitous signaling mechanism across different cell types. In T-cells, it is associated with cytokine production and immune function. Benson et al. have shown the coexistence of competing $$\text {Ca}^{\text {2}+}$$

Ca

2
+

oscillations during antigen stimulation of T-cell receptors, depending on the presence of extracellular $$\text {Ca}^{\text {2}+}$$

Ca

2
+

influx through the $$\text {Ca}^{\text {2}+}$$

Ca

2
+

release-activated $$\text {Ca}^{\text {2}+}$$

Ca

2
+

channel (Benson in J Biol Chem 29:105310, 2023). In this paper, we construct a mathematical model consisting of five ordinary differential equations and analyze the relationship between the competing oscillatory mechanisms.. We perform bifurcation analysis on two versions of our model, corresponding to the two oscillatory types, to find the defining characteristics of these two families.
Glucocorticoid Therapy in Acute Lymphoblastic Leukemia: Navigating Short-Term and Long-Term Effects and Optimal Regimen Selection
Authors: Pourhassan Hoda , Murphy Lindsey , Aldoss Ibrahim
Published: June 2024

Purpose of Review

Glucocorticoids are a mainstay in acute lymphoblastic leukemia treatment and lack of early response is predictive for overall disease prognosis. Given the vital position of glucocorticoids and well known long and short-term side effects associated with differing glucocorticoids, we aim to highlight the wide breadth of historical and more contemporary data to describe the current landscape of glucocorticoid use in this arena.

Recent Findings

Emerging studies aim to overcome issues such as steroid resistance and to optimize the antileukemic effects of glucocorticoids while aiming to mitigate the risks and side effects associated with their exposure.

Glucocorticoids have and likely always will be a fundamental component of acute lymphoblastic leukemia treatment and understanding how to navigate short- and long-term effects and how to optimize regimens is at the heart of continued treatment success.
Sports governance after the superleague judgment: going into extra time?
Authors: Poiares Maduro Miguel
Published: June 2024

This paper argues that the Superleague Judgment creates the conditions necessary for the political process to step in and do its part in providing a much-needed regulatory framework for transnational sports organizations to exercise their powers in an accountable manner and in accordance with the values usually attributed to the European Sports model. Indeed, the key issues raised in cases such as the Superleague, ISU and Royal Antwerp, as well as in past cases, often require a regulatory follow up and implementation that courts are unfit to undertake. The Court Judgments highlight systemic flaws in the governance of sports that require a public framework regulating both the scope and nature of the powers of transnational sports organisations and ensure the democratic scrutiny and accountability of their regulatory powers. This can only be properly addressed at the political level. That should have been clear by now. Let’s hope that the Superleague, ISU and Royal Antwerp judgments will make it so.
On using machine learning algorithms for motorcycle collision detection
Authors: Rodegast Philipp , Maier Steffen , Kneifl Jonas , Fehr Jörg
Published: June 2024

Globally, motorcycles attract vast and varied users. However, since the rate of severe injury and fatality in motorcycle accidents far exceeds that of passenger car accidents, efforts have been directed towards increasing passive safety systems. Impact simulations show that the risk of severe injury or death in the event of a motorcycle-to-car impact can be greatly reduced if the motorcycle is equipped with passive safety measures such as airbags and seat belts. For the passive safety systems to be activated, a collision must be detected within milliseconds for a wide variety of impact configurations, but under no circumstances may it be falsely triggered. For the challenge of reliably detecting impending collisions, this paper presents an investigation towards the applicability of machine learning algorithms. First, a series of simulations of accidents and driving operation is introduced to collect data to train machine learning classification models. Their performance is henceforth assessed and compared via multiple representative and application-oriented criteria.
Optimisation of the depth range of UIV on cohesive sediment (fluid mud) flows
Authors: Brouwers Bart , van Beeck Jeroen , Lataire Evert
Published: June 2024

Ultrasound Image Velocimetry (UIV) is a technique that enables the monitoring of flows in natural high-density cohesive sediments, also known as fluid mud. Using conventional medical ultrasound imaging equipment, the depth range of UIV in mud is however too limited. This manuscript discusses how this depth range can be improved based on the results of experimental UIV measurements in fluid mud. The results show that the depth range limitation is determined by the pixel brightness of the generated speckle pattern images. Since pixel brightness is a measure of the intensity of the backscattered signals, it degrades with increasing depth due to the attenuation of the ultrasound radiation by the mud. The rate at which ultrasound is attenuated by fluid mud is constant and is governed by the density of the mud and the applied ultrasound frequency. A greater depth range can thus be achieved by reducing attenuation and increasing the intensity of the emitted ultrasound. The former was confirmed by the results of experiments with variable mud density and ultrasound frequency. Flexibility of both parameters is however restricted, allowing only a limited increase in depth range. Another experiment confirmed an additional increase in depth range when a higher ultrasound intensity is applied. Patient safety measures of medical ultrasound imaging equipment, however restrict the intensity of the emitted ultrasound. To increase the depth range even further, potential solutions are therefore suggested, such as the use of high-power non-medical ultrasound imaging equipment or a novel procedure for processing the acquired acoustic data.
A Concrete Syntax Transformation Approach for Software Language Processing
Authors: Lano Kevin , Xue Qiaomu , Haughton Howard
Published: June 2024

In this paper we present an approach for software language processing tasks such as code generation, reverse-engineering and refactoring, based upon text-to-text (T2T) transformations expressed using theconcrete syntaxof the source and target software languages. The goal of the approach is to provide simpler and more usable techniques for specifying such tasks, compared to model-to-model (M2M) or model-to-text (M2T) transformation approaches. We evaluate the approach on language processing tasks of domain-specific language (DSL) tool support, software abstraction, model transformation, reverse engineering and program translation, and show that it can be effective for these tasks.
Clinically proven natural products in aid of treating Parkinson's disease: a comprehensive review
Authors: Roni Md Abul Hasan , Jami Md. Abu Bakar Siddique , Hoque Sajidul , Al Hasibuzzaman Md. , Banu Kazi Hamida , Rozina  , Ansari Farzana , Sohel Md , Ashifuzzaman Md. , Joy Ferdous-Ul-Haque , Hossain Md. Solaiman , Huda Nazmul , Mostaq Md. Saqline , Amin Mohammad Nurul , Yunus Mohd Yusri Bin Mohd
Published: June 2024

Parkinson's disease (PD) is a neurodegenerative disorder that is caused by degeneration of nerve cells in the part of the brain called the substantia nigra, which controls movement. Although there is some considerable evidence with conventional drugs for PD, treating patients becomes increasingly difficult due to their short- and long-term adverse effects and other restrictions. This dire circumstance emphasizes the need for an innovative, strong alternative treatment for PD. Plants and natural products are considered one of the most important sources of bioactive molecules against a wide range of health disorders. With mechanistic insights, this systematic review explains the efficacy of clinically proven natural products in managing PD. This review is based on comprehensive literature searches from PubMed, Science Direct, Scopus, and Google Scholar databases using the keywords- “plants or natural products in Parkinson's”, “plants or herbs used in Parkinson's treatment”, or keywords that are similar to those. Natural products that have been clinically proven for their anti-Parkinson effect have only been selected for this study, and the products are- Mucuna pruriens, Caffeine, Camellia sinensis or green tea leaves, and a traditional Chinese herbal called Jiawei-Liujunzi Tang. In comparison to currently available medications, we firmly feel that the mentioned clinically proven natural products would be more effective at treating PD while having fewer adverse effects. However, further study is required to confirm their exact mechanism of action.
Properties of concrete using water from the Padma River and the Shitalakshya River, Bangladesh
Authors: Hasan Md. Mahmudul , Adnan Raofur , Shafiquzzaman Md. , Azad Md. Izharul Haque , Pial Md. Asaduzzaman , Rahman Shohanur , Tonmoy Zakaria Hassan , Roy Nayan , Islam Tony
Published: June 2024

Assessing the impact of river water on concrete properties is an important aspect of the construction industry, especially in regions with significant exposure to riverine environments, like Bangladesh. This study investigated the applicability of river water in concrete manufacturing regarding its compressive strength and density. Water samples were collected from two major rivers (the Padma and the Shitalakshya) in Bangladesh and analyzed for thirty water quality parameters. 168-cylinder specimens were cast and tested for compressive strength after curing for 7, 14, and 28 days. The investigation was also carried out with two different coarse aggregates (brick and stone chips) in the mix design. Curing was performed with fresh and river water separately. Therefore, ten different experimental conditions were explored. The compressive strength of concrete using river water compared to freshwater decreased from 0 to 24%, except for three cases, where strength increased by 4.2%, 7.3%, and 8%. The variation in water quality between the two rivers significantly influenced the reduction in compressive strength. Higher values of pH, total suspended solids, total solids, ammonia, total hardness, alkalinity, and conductivity in the Padma River water led to a greater reduction in compressive strength than using the Shitalakshya River water. The type of coarse aggregate used also had an impact on strength. Both rivers’ water met the concrete production standards; nevertheless, a pre-treatment process is recommended. Successfully using river water in concrete production could reduce the demand for freshwater resources, contributing to the construction industry’s sustainability.
Probabilistic UK Climate Projections Conditioned on Global Warming Levels
Authors: Steptoe Hamish , Murphy James
Published: June 2024

Probabilistic projections from the UK Climate Projections 2018 are presented for four global warming levels (GWLs) at 1.5, 2, 3, and 4°C above the 1850–1900 baseline. Our results show how uncertainties associated with climate models and four representative concentration pathways (RCP) emission scenarios translate to UK regional scale changes in maximum temperature and precipitation, with data also available for minimum and mean temperatures, humidity and surface net downward shortwave radiation flux. We compare weighting the likelihood of RCPs based on (hypothetical) policy decisions, against our baseline assumption that each RCP is equally likely. Differences between weighted and unweighted GWL distributions are small, particularly in relation to the full breadth of uncertainties that are incorporated into the probabilistic projections. Finally we quantify the relative importance of scenario, model and internal variability on regional projected GWLs and show that uncertainty associated with an uncertain climate response to forcings dominates at all GWLs.
CellRank 2: unified fate mapping in multiview single-cell data
Authors: Weiler Philipp , Lange Marius , Klein Michal , Pe’er Dana , Theis Fabian
Published: June 2024

Single-cell RNA sequencing allows us to model cellular state dynamics and fate decisions using expression similarity or RNA velocity to reconstruct state-change trajectories; however, trajectory inference does not incorporate valuable time point information or utilize additional modalities, whereas methods that address these different data views cannot be combined or do not scale. Here we present CellRank 2, a versatile and scalable framework to study cellular fate using multiview single-cell data of up to millions of cells in a unified fashion. CellRank 2 consistently recovers terminal states and fate probabilities across data modalities in human hematopoiesis and endodermal development. Our framework also allows combining transitions within and across experimental time points, a feature we use to recover genes promoting medullary thymic epithelial cell formation during pharyngeal endoderm development. Moreover, we enable estimating cell-specific transcription and degradation rates from metabolic-labeling data, which we apply to an intestinal organoid system to delineate differentiation trajectories and pinpoint regulatory strategies.
Nano bio fertilizer capsules for sustainable agriculture
Authors: Hamed Rinad , Jodeh Shehdeh , Alkowni Raed
Published: June 2024

A novel nano bio-fertilizer encapsulation method was developed to crosslink chitosan and alginate with humic acid. These nanocapsules, referred to as (Ch./Alg.HA.NPK) or (Ch./Alg.HA.NPK.PGPRs), were loaded with nanoscale essential agro-nutrients (NPK) and beneficial microorganisms Pseudomonas Fluorescence abbreviated as (P.Fluorescence). Structural and morphological analyses were conducted using FourierTransform Infrared, Thermogravimetric Analysis, Scanning Electron Microscopy, Malvern Zeta NanoSizer, and Zeta potential. Encapsulation efficiency and water retention were also determined compared to control non-crosslinked nanocapsules. The sustained cumulative release of NPK over 30 days was also investigated to 33.2%, 47.8%, and 68.3%, alternatively. The release mechanism, also assessed through the kinetic module of the Korsemeyer- Peppas Mathematical model, demonstrated superior performance compared to non-crosslinked nanocapsules (chitosan/alginate). These results show the potential of the synthesized nanocapsules for environmentally conscious controlled release of NPK and PGPRs, thereby mitigating environmental impact, enhancing plant growth, and reducing reliance on conventional agrochemical fertilizers.
Shallow foundation design: a comparative study of partial safety factors and full probabilistic methods
Authors: Vořechovský Miroslav , Miča Lumír , Boštík Jiří
Published: June 2024

In the past two decades, Europe has witnessed a significant transition in the design codes used for assessing foundation structures, with the widespread adoption of the Eurocodes (EC). This shift remains a pertinent topic within the engineering community, particularly concerning the transition from traditional design methodologies to those prescribed by the Eurocodes, as well as the potential for fully probabilistic design. While the Eurocodes’ methodology is described as probabilistic, it is crucial to recognize that the achievement of the target reliability level is predominantly facilitated through a system of partial safety factors. These factors are integrated into the calculation algorithm as fixed values, rendering the process essentially deterministic. To refine these calculations for more accurate reliability estimates—expressed in terms of failure probability—a genuinely probabilistic framework is required, termed as fully probabilistic computation. This paper aims to elucidate the fully probabilistic calculation approach for the broader professional community, using the geotechnical application of shallow foundations as an illustrative example. We present a comparative analysis of this advanced approach with the standard foundation design according to EC7 and ČSN 731001, the latter being a precursor in Europe for implementing the partial safety factor method. The discussion extends to a practical demonstration of full probabilistic design juxtaposed against the conventional partial safety factor method, using a shallow foundation case study. Furthermore, the paper delves into the impact of the tail behavior of uncertain or spatially varying soil parameters on the theoretical probability of failure, underscoring its significance in foundation design.
Dynamically predicting comprehension difficulties through physiological data and intelligent wearables
Authors: Hijazi Haytham , Gomes Miguel , Castelhano João , Castelo-Branco Miguel , Praça Isabel , de Carvalho Paulo , Madeira Henrique
Published: June 2024

Comprehending digital content written in natural language online is vital for many aspects of life, including learning, professional tasks, and decision-making. However, facing comprehension difficulties can have negative consequences for learning outcomes, critical thinking skills, decision-making, error rate, and productivity. This paper introduces an innovative approach to predict comprehension difficulties at the local content level (e.g., paragraphs). Using affordable wearable devices, we acquire physiological responses non-intrusively from the autonomous nervous system, specifically pulse rate variability, and electrodermal activity. Additionally, we integrate data from a cost-effective eye-tracker. Our machine learning algorithms identify ’hotspots’ within the content and regions corresponding to a high cognitive load. These hotspots represent real-time predictors of comprehension difficulties. By integrating physiological data with contextual information (such as the levels of experience of individuals), our approach achieves an accuracy of 72.11% ± 2.21, a precision of 0.77, a recall of 0.70, and an f1 score of 0.73. This study opens possibilities for developing intelligent, cognitive-aware interfaces. Such interfaces can provide immediate contextual support, mitigating comprehension challenges within content. Whether through translation, content generation, or content summarization using available Large Language Models, this approach has the potential to enhance language comprehension.
In silico study to explore the mechanism of Toxoplasma-induced inflammation and target therapy based on sero and salivary Toxoplasma
Authors: Hassanein Faika , Fadel Hewida H. , Shehata Amany I. , Hamdy Noha Alaa , Masoud Inas M.
Published: June 2024

We aimed to assess salivary and seroprevalence of Toxoplasma immunoglobulins in risky populations and evaluate drug docking targeting TgERP. A cross-sectional study was conducted in Alexandria University hospitals’ outpatient clinics. 192 participants were enrolled from September 2022 to November 2023. Anti-Toxoplasma IgG and IgM were determined in serum and saliva by ELISA. An in-Silico study examined TgERP’s protein–protein interactions (PPIs) with pro-inflammatory cytokine receptors, anti-inflammatory cytokine, cell cycle progression regulatory proteins, a proliferation marker, and nuclear envelope integrity-related protein Lamin B1. Our findings revealed that anti-T. gondii IgG were detected in serum (66.1%) and saliva (54.7%), with 2.1% of both samples were positive for IgM. Salivary IgG had 75.59% sensitivity, 86.15% specificity, 91.40% PPV, 64.40% NPP, 79.17% accuracy and fair agreement with serum IgG. On the other hand, the sensitivity, specificity, PPV, NPV, and accuracy in detecting salivary IgM were 75.0%, 99.47%, 75.0%, 99.47%, and 98.96%. AUC 0.859 indicates good discriminatory power. Examined synthetic drugs and natural products can target specific amino acids residues of TgERP that lie at the same binding interface with LB1 and Ki67, subsequently, hindering their interaction. Hence, salivary samples can be a promising diagnostic approach. The studied drugs can counteract the pro-inflammatory action of TgERP.
Increased expression of miR-320b in blood plasma of patients in response to SARS-CoV-2 infection
Authors: de Souza Nicoletti Aline , Berlofa Visacri Marília , Regina da Silva Correa da Ronda Carla , Tiemi Siguemoto Julia , Motta Neri Carolini , Nogueira de Souza Rafael , de Souza Ventura Deise , Eguti Adriana , Ferreira de Souza Silva Lilian , Wesley Perroud Junior Mauricio , Buosi Keini , Jalalizadeh Mehrsa , Dionato Franciele , Dal Col Luciana , Giacomelli Cristiane , Leme Patrícia , Oliveira Reis Leonardo , Augusto dos Santos Luiz , Durán Nelson , José Fávaro Wagner , Luiz da Costa José , Dagli-Hernandez Carolina , Moriel Patricia , de Carvalho Pincinato Eder
Published: June 2024

Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Recent research has demonstrated how epigenetic mechanisms regulate the host–virus interactions in COVID-19. It has also shown that microRNAs (miRNAs) are one of the three fundamental mechanisms of the epigenetic regulation of gene expression and play an important role in viral infections. A pilot study published by our research group identified, through next-generation sequencing (NGS), that miR-4433b-5p, miR-320b, and miR-16–2-3p are differentially expressed between patients with COVID-19 and controls. Thus, the objectives of this study were to validate the expression of these miRNAs using quantitative real-time polymerase chain reaction (qRT-PCR) and to perform in silico analyses. Patients with COVID-19 (n = 90) and healthy volunteers (n = 40) were recruited. MiRNAs were extracted from plasma samples and validated using qRT-PCR. In addition, in silico analyses were performed using mirPath v.3 software. MiR-320b was the only miRNA upregulated in the case group com-pared to the control group. The in silico analyses indicated the role of miR-320b in the regulation of the KITLG gene and consequently in the inflammatory process. This study confirmed that miR-320b can distinguish patients with COVID-19 from control participants; however, further research is needed to determine whether this miRNA can be used as a target or a biomarker.
Australia’s 2019/20 Black Summer fire weather exceptionally rare over the last 2000 years
Authors: Udy Danielle G. , Vance Tessa R. , Kiem Anthony S. , Holbrook Neil J. , Abram Nerilie
Published: June 2024

Australia’s record-breaking 2019/20 Black Summer fire weather resulted from a combination of natural and anthropogenic climate factors, but the full range of natural variability in fire weather is unknown. We reconstruct southeast Australian fire weather over the Common Era based on an East Antarctic ice core sea-salt aerosol record. This record reflects the Southern Ocean synoptic-scale weather patterns and Antarctic stratospheric polar vortex strength that pre-condition elevated fire danger over southeast Australia. We show that the (a) intensity of the 2019/20 fire weather was unprecedented since 1950 and (b) frequency of above average fire weather seasons from 2010–2020 has only occurred once since 1950 (over 1977–1987), but there are analogues for similar extreme fire danger caused by natural variability in the 2000-year reconstruction. This highlights the need for fire risk mitigation that considers the full range of plausible natural variability in Australia’s fire weather as well as anthropogenic forcing.
Seafloor roughness reduces melting of East Antarctic ice shelves
Authors: Liu Yuhang , Nikurashin Maxim , Peña-Molino Beatriz
Published: June 2024

Heat delivered by the ocean circulation is melting the Antarctic ice sheet from below. This melt is largest where warm Circumpolar Deep Water accesses the continental shelf and reaches the ice shelf cavities. Future melt rate projections are based on ocean thermal forcing derived from climate models, which tend to be biased warm around Antarctica. The bias has been attributed to unresolved ocean processes that occur at scales poorly represented in models. Using a high-resolution model of the Denman Glacier region we show that seafloor roughness unresolved in climate models suppresses the impact of warm water on ice sheet melting. Seafloor roughness slows down the shelf circulation, reducing the presence of warm water over the shelf and the heat transport towards the ice cavities. As a result, the total meltwater discharge drops by 4 Gt year−1. Our results suggest a mechanism missing in global ocean and climate models that could reduce the spread in climate projections.
Real-time motion-enabling positron emission tomography of the brain of upright ambulatory humans
Authors: Siva Nanda K. , Bauer Christopher , Glover Colson , Stolin Alexander , Chandi Sonia , Melnick Helen , Marano Gary , Parker Benjamin , Mandich MaryBeth , Lewis James W. , Qi Jinyi , Gao Si , Nott Kaylee , Majewski Stan , Brefczynski-Lewis Julie A.
Published: June 2024

Background

Mobile upright PET devices have the potential to enable previously impossible neuroimaging studies. Currently available options are imagers with deep brain coverage that severely limit head/body movements or imagers with upright/motion enabling properties that are limited to only covering the brain surface.

Methods

In this study, we test the feasibility of an upright, motion-compatible brain imager, our Ambulatory Motion-enabling Positron Emission Tomography (AMPET) helmet prototype, for use as a neuroscience tool by replicating a variant of a published PET/fMRI study of the neurocorrelates of human walking. We validate our AMPET prototype by conducting a walking movement paradigm to determine motion tolerance and assess for appropriate task related activity in motor-related brain regions. Human participants (n = 11 patients) performed a walking-in-place task with simultaneous AMPET imaging, receiving a bolus delivery of F18-Fluorodeoxyglucose.

Results

Here we validate three pre-determined measure criteria, including brain alignment motion artifact of less than <2 mm and functional neuroimaging outcomes consistent with existing walking movement literature.

Conclusions

The study extends the potential and utility for use of mobile, upright, and motion-tolerant neuroimaging devices in real-world, ecologically-valid paradigms. Our approach accounts for the real-world logistics of an actual human participant study and can be used to inform experimental physicists, engineers and imaging instrumentation developers undertaking similar future studies. The technical advances described herein help set new priorities for facilitating future neuroimaging devices and research of the human brain in health and disease.