bluuebunny/crossref_metadata_2025 huggingface dataset:
The application of machine learning for demand prediction under macroeconomic volatility: a systematic literature review
Authors: Muth Manuel , Lingenfelder Michael , Nufer Gerd
Published: June 2024

In a contemporary context characterised by shifts in macroeconomic conditions and global uncertainty, predicting the future behaviour of demanders is critical for management science disciplines such as marketing. Despite the recognised potential of Machine Learning, there is a lack of reviews of the literature on the application of Machine Learning in predicting demanders’ behaviour in a volatile environment. To fill this gap, the following systematic literature review provides an interdisciplinary overview of the research question: “How can Machine Learning be effectively applied to predict demand patterns under macroeconomic volatility?” Following a rigorous review protocol, a literature sample of studies (n = 64) is identified and analysed based on a hybrid methodological approach. The findings of this systematic literature review yield novel insights into the conceptual structure of the field, recent publication trends, geographic centres of scientific activity, as well as leading sources. The research also discusses whether and in which ways Machine Learning can be used for demand prediction under dynamic market conditions. The review outlines various implementation strategies, such as the integration of forward-looking data with economic indicators, demand modelling using the Coefficient of Variation, or the application of combined algorithms and specific Artificial Neural Networks for accurate demand predictions.
Development of a trash classification system to map potential Aedes aegypti breeding grounds using unmanned aerial vehicle imaging
Authors: Rosser Joelle I. , Tarpenning Morgan S. , Bramante Juliet T. , Tamhane Anoushka , Chamberlin Andrew J. , Mutuku Paul S. , De Leo Giulio A. , Ndenga Bryson , Mutuku Francis , LaBeaud Angelle Desiree
Published: June 2024

Aedes aegypti mosquitos are the primary vector for dengue, chikungunya, and Zika viruses and tend to breed in small containers of water, with a propensity to breed in small piles of trash and abandoned tires. This study piloted the use of aerial imaging to map and classify potential Ae. aegypti breeding sites with a specific focus on trash, including discarded tires. Aerial images of coastal and inland sites in Kenya were obtained using an unmanned aerial vehicle. Aerial images were reviewed for identification of trash and suspected trash mimics, followed by extensive community walk-throughs to identify trash types and mimics by description and ground photography. An expert panel reviewed aerial images and ground photos to develop a classification scheme and evaluate the advantages and disadvantages of aerial imaging versus walk-through trash mapping. A trash classification scheme was created based on trash density, surface area, potential for frequent disturbance, and overall likelihood of being a productive Ae. aegypti breeding site. Aerial imaging offers a novel strategy to characterize, map, and quantify trash at risk of promoting Ae. aegypti proliferation, generating opportunities for further research on trash associations with disease and trash interventions.
Mathematical vs. machine learning models for particle size distribution in fragile soils of North-Western Himalayas
Authors: Bashir Owais , Bangroo Shabir Ahmad , Shafai Shahid Shuja , Shah Tajamul Islam , Kader Shuraik , Jaufer Lizny , Senesi Nicola , Kuriqi Alban , Omidvar Negar , Naresh Kumar Soora , Arunachalam Ayyanadar , Michael Ruby , Ksibi Mohamed , Spalevic Velibor , Sestras Paul , Marković Slobodan B. , Billi Paolo , Ercişli Sezai , Hysa Artan
Published: June 2024

Purpose

Particle size distribution (PSD) assessment, which affects all physical, chemical, biological, mineralogical, and geological properties of soil, is crucial for maintaining soil sustainability. It plays a vital role in ensuring appropriate land use, fertilizer management, crop selection, and conservation practices, especially in fragile soils such as those of the North-Western Himalayas.

Materials and methods

In this study, the performance of eleven mathematical and three Machine Learning (ML) models used in the past was compared to investigate PSD modeling of different soils from the North-Western Himalayan region, considering that an appropriate model must fit all PSD data.

Results and discussion

Our study focuses on the significance of evaluating the goodness of fit in particle size distribution modeling using the coefficient of determination (R2adj = 0.79 to 0.45), the Akaike information criterion (AIC = 67 to 184), and the root mean square error (RMSE = 0.01 to 0.09). The Fredlund, Weibull, and Rosin Rammler models exhibited the best fit for all samples, while the performance of the Gompertz, S-Curve, and Van Genutchen models was poor. Of the three ML models tested, the Random Forest model performed the best (R2 = 0.99), and the SVM model was the lowest (R2 = 0.95). Thus, the PSD of the soil can be best predicted by ML approaches, especially by the Random Forest model.

Conclusion

The Fredlund model exhibited the best fit among mathematical models while random forest performed best among the machine learning models. As the number of parameters in the model increased better was the accuracy.
Integrating subject-generic and subject-specific teaching frameworks: searching for stages of teaching in mathematics
Authors: Kyriakides Leonidas , Charalambous Charalambos Y. , Antoniou Panayiotis
Published: June 2024

Currently there is an attempt to combine subject-generic and subject-specific teaching frameworks to comprehensively capture teaching quality. This study explores the possibility of integrating two widely used and validated frameworks, the subject-generic Dynamic Model of Educational Effectiveness (DMEE) and the subject-specific Mathematical Quality of Instruction (MQI). Toward this end, we drew on data from 38 upper-grade primary school teachers, each observed in six mathematics lessons, which were coded using both frameworks. Data were analyzed using the Extended Logistic model of Rasch to explore whether a common scale of teaching quality with good psychometric properties could be developed. Saltus was then utilized to investigate the possibility of forming levels of effective teaching in mathematics. A common scale encompassing both subject-generic and subject-specific teaching aspects, which had good psychometric properties, was developed. The subject-generic and subject-specific teaching aspects of these frameworks were clustered in five distinct levels. With the exception of the top level that included only subject-generic aspects, all other levels included teaching aspects from both frameworks, thus providing support to the assumption that it is possible to develop levels of effective teaching that combine related subject-generic and subject-specific aspects. In discussing the study findings, we consider their implications for developing an integrated framework of teaching quality and for developing professional development programs that combine subject-generic and subject-specific teaching aspects.
Primary Intranodal Epithelioid Haemangioendothelioma in the Submandibular Region: A Case Report
Authors: Shukla Khilan , Taheri Touraj , Baghaie Hooman , Breik Omar
Published: June 2024

Epithelioid haemangioendothelioma (EHE) is a rare vascular tumour that primarily affects the liver, lungs and bone. It is very rarely described in the head and neck region, and is exceptionally uncommon within the submandibular region. We report a very rare case of EHE originating in a lymph node within the submandibular salivary gland of a 54-year-old female patient. The tumour was resected and the patient was regularly followed up, with no recurrence of disease at 24 months postoperatively. A review of existing literature, clinical and immunohistopathological features are discussed, which highlight the diagnostic dilemma, absence of consensus for management and appropriate surveillance method associated with EHE.
Towards a personalized prediction, prevention and therapy of insomnia: gut microbiota profile can discriminate between paradoxical and objective insomnia in post-menopausal women
Authors: Barone Monica , Martucci Morena , Sciara Giuseppe , Conte Maria , Medina Laura Smeldy Jurado , Iattoni Lorenzo , Miele Filomena , Fonti Cristina , Franceschi Claudio , Brigidi Patrizia , Salvioli Stefano , Provini Federica , Turroni Silvia , Santoro Aurelia
Published: June 2024

Background

Insomnia persists as a prevalent sleep disorder among middle-aged and older adults, significantly impacting quality of life and increasing susceptibility to age-related diseases. It is classified into objective insomnia (O-IN) and paradoxical insomnia (P-IN), where subjective and objective sleep assessments diverge. Current treatment regimens for both patient groups yield unsatisfactory outcomes. Consequently, investigating the neurophysiological distinctions between P-IN and O-IN is imperative for devising novel precision interventions aligned with primary prediction, targeted prevention, and personalized medicine (PPPM) principles.

Working hypothesis and methodology.

Given the emerging influence of gut microbiota (GM) on sleep physiology via the gut-brain axis, our study focused on characterizing the GM profiles of a well-characterized cohort of 96 Italian postmenopausal women, comprising 54 insomniac patients (18 O-IN and 36 P-IN) and 42 controls, through 16S rRNA amplicon sequencing. Associations were explored with general and clinical history, sleep patterns, stress, hematobiochemical parameters, and nutritional patterns.

Results

Distinctive GM profiles were unveiled between O-IN and P-IN patients. O-IN patients exhibited prominence in the Coriobacteriaceae family, including Collinsella and Adlercreutzia, along with Erysipelotrichaceae, Clostridium, and Pediococcus. Conversely, P-IN patients were mainly discriminated by Bacteroides, Staphylococcus, Carnobacterium, Pseudomonas, and respective families, along with Odoribacter.

Conclusions

These findings provide valuable insights into the microbiota-mediated mechanism of O-IN versus P-IN onset. GM profiling may thus serve as a tailored stratification criterion, enabling the identification of women at risk for specific insomnia subtypes and facilitating the development of integrated microbiota-based predictive diagnostics, targeted prevention, and personalized therapies, ultimately enhancing clinical effectiveness.
Explicit expression for water permeation flux in forward osmosis desalination process
Authors: Al-Mutaz Ibrahim S. , Alalawi Abdulrahman , Bin Darwish Nawaf
Published: June 2024

Forward osmosis (FO) is a membrane process of water separation and purification. FO uses the osmotic pressure difference across a semipermeable membrane. The effective osmotic pressure at the membrane–solution interface on both the feed and permeate sides of the membrane is the main driving force for the generation of the water flux. The major hindrance to the permeation of the water flux is the prevalence of concentration polarization on both sides of the membrane. Concentration polarization inhibits permeate flux by increasing the osmotic pressure at the membrane active layer interface on the feed side of the membrane. This work focused on the development of a mathematical model for water flux in the FO process. Combined film theory model and diffusion transport through the membrane were utilized. The effect of internal concentration polarization and external concentration polarization on the flux was studied. Both internal and external concentration polarization were taken into consideration in both membrane orientations, i.e., active layer facing the feed solution and active layer facing the draw solution. The obtained explicit expression for water permeation flux in forward osmosis desalination process shows excellent agreement with the literature data.
MXene Key Composites: A New Arena for Gas Sensors
Authors: Wang Yitong , Wang Yuhua , Jian Min , Jiang Qinting , Li Xifei
Published: June 2024

With the development of science and technology, the scale of industrial production continues to grow, and the types and quantities of gas raw materials used in industrial production and produced during the production process are also constantly increasing. These gases include flammable and explosive gases, and even contain toxic gases. Therefore, it is very important and necessary for gas sensors to detect and monitor these gases quickly and accurately. In recent years, a new two-dimensional material called MXene has attracted widespread attention in various applications. Their abundant surface functional groups and sites, excellent current conductivity, tunable surface chemistry, and outstanding stability make them promising for gas sensor applications. Since the birth of MXene materials, researchers have utilized the efficient and convenient solution etching preparation, high flexibility, and easily functionalize MXene with other materials to prepare composites for gas sensing. This has opened a new chapter in high-performance gas sensing materials and provided a new approach for advanced sensor research. However, previous reviews on MXene-based composite materials in gas sensing only focused on the performance of gas sensing, without systematically explaining the gas sensing mechanisms generated by different gases, as well as summarizing and predicting the advantages and disadvantages of MXene-based composite materials. This article reviews the latest progress in the application of MXene-based composite materials in gas sensing. Firstly, a brief summary was given of the commonly used methods for preparing gas sensing device structures, followed by an introduction to the key attributes of MXene related to gas sensing performance. This article focuses on the performance of MXene-based composite materials used for gas sensing, such as MXene/graphene, MXene/Metal oxide, MXene/Transition metal sulfides (TMDs), MXene/Metal–organic framework (MOF), MXene/Polymer. It summarizes the advantages and disadvantages of MXene composite materials with different composites and discusses the possible gas sensing mechanisms of MXene-based composite materials for different gases. Finally, future directions and inroads of MXenes-based composites in gas sensing are presented and discussed.
Willingness to experience unpleasant thoughts, emotions, and bodily sensations at admission does not predict treatment outcome in inpatients with obsessive–compulsive disorder
Authors: Zisler Eva M. , Meule Adrian , Koch Stefan , Voderholzer Ulrich
Published: June 2024

Background

Some persons with obsessive–compulsive disorder (OCD) refuse or drop out of treatment because of the aversive nature of exposure and response prevention therapy when they have to face and tolerate unpleasant thoughts, emotions, and bodily sensations. Indeed, one study suggested that a higher willingness to experience unpleasant thoughts, emotions, and bodily sensations (WTE) predicts a better treatment outcome, but this finding has not been replicated yet.

Methods

We examined whether WTE at admission predicted treatment outcome in a sample of 324 inpatients with OCD who received a multimodal treatment that included cognitive-behavioral therapy with exposure and response prevention sessions.

Results

Obsessive–compulsive symptoms (based on OCD-specific self-report questionnaires) decreased with medium-to-large effect sizes (all ps < 0.001) and global functioning (based on therapist ratings) increased with a large effect size (d = 1.3, p < 0.001) from admission to discharge. In contrast to previous findings, however, WTE did not predict treatment outcome (all ps > 0.005). The effect of WTE on treatment outcome remained non-significant when controlling for any comorbidity, age, sex, length of stay, and antidepressant medication and was not moderated by these variables.

Conclusions

Results indicate that higher WTE at the beginning of inpatient treatment does not facilitate improvements in obsessive–compulsive symptoms from admission to discharge. However, they also indicate that lower WTE at the beginning of inpatient treatment does not adversely affect treatment outcome, that is, even patients who indicate that they are unwilling to face the negative experiences associated with exposure and response prevention can still achieve considerable symptom reductions.
Analysis of Prevalence, Socioeconomic and Disease Trends of Non-Melanoma Skin Cancer in New Zealand from 2008 to 2022
Authors: Paul Sharad , Chen Yipan , Mohaghegh Mahsa
Published: June 2024

Background

Skin cancer shows geographic and ethnic variation. New Zealand—with a predominantly fair-skinned populations, high UV indices and outdoor lifestyles—has high rates of skin cancer. However, population prevalence data is lacking. This study aimed to determine the demographics and socioeconomic disease trends of non-melanoma skin cancer prevalence in New Zealand from a large targeted-screening study.

Methods

A targeted screening programme was conducted among 32,839 individuals, Fitzpatrick Skin Types I to IV in Auckland, New Zealand during the 2008–2022 period. This data was analyzed retrospectively. Linear regression models were used to assess statistical trends of skin cancer prevalence over time, along with associated factors that included demographics, disease trends and overall prevalence.

Results

A total of 32,839 individuals were screened and 11,625 skin cancers were detected. 16,784 individuals were females who had 4,378 skin cancers. 16,055 individuals were males who had 5,777 skin cancers. 54 males and 65 females had multiple skin cancers. The article presents detailed descriptions of tumour types and subtypes detected, age groups, demographic and socioeconomic information. regarding the non-melanoma skin cancers detected.

Conclusion

Overall men have more non-melanoma skin cancer (NMSC) than females; however females develop more BCC on the lips. BCC is three times more common in the 31-50 age group, whereas SCC are significantly more prevalent after age 80. Prevalence of BCC has not changed over the 15-year timeframe of the study but SCC has increased. Older ages and higher incomes are associated with higher rates of NMSC in New Zealand.
Embolization of a splenic artery aneurysm: a case report
Authors: Verde Caterina , Tarotto Luca , Stilo Salvatore , D’Angelo Roberto , Fiore Francesco
Published: June 2024

Splenic artery aneurysm (SAA) is the most common aneurysm of the visceral arteries. SAA can be silent and asymptomatic; rupture is a rare but serious complication that can manifest as acute diffuse abdominal pain and hypovolemic shock with a high risk of mortality. Surgery is the traditional treatment, but has the disadvantage of severe surgical injuries, a high risk of complications and a high mortality rate. We present the case of a 58-year-old woman with a saccular aneurysm of the middle segment of the splenic artery; she was treated by coiling embolization using the sandwich technique. Contrast-enhanced computed tomography (CECT) controls at one month, four months and one year showed progressive reduction and complete devascularization of the aneurysmal sac. Embolization of the splenic artery aneurysm is an effective and safe treatment.
Working with Network Data
Authors: Bagrow James , Ahn Yong‐Yeol
Published: June 2024

Drawing examples from real-world networks, this essential book traces the methods behind network analysis and explains how network data is first gathered, then processed and interpreted. The text will equip you with a toolbox of diverse methods and data modelling approaches, allowing you to quickly start making your own calculations on a huge variety of networked systems. This book sets you up to succeed, addressing the questions of what you need to know and what to do with it, when beginning to work with network data. The hands-on approach adopted throughout means that beginners quickly become capable practitioners, guided by a wealth of interesting examples that demonstrate key concepts. Exercises using real-world data extend and deepen your understanding, and develop effective working patterns in network calculations and analysis. Suitable for both graduate students and researchers across a range of disciplines, this novel text provides a fast-track to network data expertise.
Religious Humanitarianism during the World Wars, 1914–1945
Authors: Houlihan Patrick J.
Published: June 2024

The history of modern war has focused on destruction; however, practices of saving lives and rebuilding societies have received far less scrutiny. The world wars reconfigured geopolitics on a sacred-secular spectrum dominated by the USA and the USSR. In these events, the motivations of humanitarian actors are disputed as either secular or religious, evoking approval or censure. Although modern global humanitarianism emerged during the world wars, it is often studied in a Euro-centric framework that does not engage the conflicts' globality. The effects of humanitarianism during the Second World War look toward the post-1945 era with not enough reflection on the pre-1945 history of humanitarianism. Thus, what is needed is a critical history beyond moralizing, bringing synchronic and diachronic expansion to study questions of continuity and change. A global history of religious humanitarianism during both world wars places faith-based humanitarianism on a spectrum of belief and unbelief.
Dissipation Rates of Mesospheric Stratified Turbulence From Multistatic Meteor‐Radar Observations
Authors: Vierinen J. , Poblet F. L. , Chau J. L. , Avsarkisov V. , Pécseli H. L. , Tsutsumi M. , Nozawa S. , Johnsen M. G. , Latteck R. , Gulbrandsen N.
Published: June 2024

Stratified turbulence (ST) has been proposed as a model for the dynamics of the mesosphere‐lower thermosphere (MLT) region. This theory postulates that for horizontal mesoscales (∼1–400 km), the kinetic energy of horizontal winds dissipates from large to small scales with an approximately mean constant rate. In this investigation, dissipation rates are quantified using meteor‐radar observations conducted in Northern Norway. The observed seasonal variability of dissipation rates exhibits maxima during the summer and winter, and minima near the equinoxes, between 80 and 95 km altitude. The results are compared with model predictions and earlier medium frequency radar, rocket, lidar, and satellite observations of MLT turbulence. The findings suggest that multi‐static meteor radar measurements of ST can provide a novel way to continuously monitor turbulent dissipation rates in the MLT region.
Dust Accumulation and Lifting at the Landing Site of the Mars 2020 Mission, Jezero Crater, as Observed From MEDA
Authors: Vicente‐Retortillo A. , Lemmon M. T. , Martinez G. M. , Toledo D. , Apéstigue V. , Arruego I. , Bertrand T. , Lorenz R. , Sebastián E. , Hueso R. , Newman C. , Smith M. D. , Rodriguez‐Manfredi J. A.
Published: June 2024

We quantify the effect of dust accumulation at Jezero crater by means of a Dust Correction Factor (DCF) for the solar radiation measured by the photodiodes of the Radiation and Dust Sensor of the Mars 2020 mission. After one Mars Year, dust on the photodiode surface attenuated 25%–30% of the incoming solar radiation. The DCF did not decrease monotonically; we use a model to reproduce its evolution and to derive dust deposition and lifting rates, showing that dust removal is 9 times larger at Jezero crater than at InSight's location in western Elysium Planitia. The model fit obtained using observed opacities is further improved when fed with dust sedimentation rates simulated by a GCM that considers a particle size distrtibution. Projections show seasonal net dust removal, being encouraging for the long‐term survival of solar‐powered missions to Jezero or similarly active dust lifting regions.
Simulation of Compound Flooding Using River‐Ocean Two‐Way Coupled E3SM Ensemble on Variable‐Resolution Meshes
Authors: Feng Dongyu , Tan Zeli , Engwirda Darren , Wolfe Jonathan D. , Xu Donghui , Liao Chang , Bisht Gautam , Benedict James J. , Zhou Tian , Li Hong‐Yi , Leung L. Ruby
Published: June 2024

Coastal zone compound flooding (CF) can be caused by the interactive fluvial and oceanic processes, particularly when coastal backwater propagates upstream and interacts with high river discharge. The modeling of CF is limited in existing Earth System Models (ESMs) due to coarse mesh resolutions and one‐way coupled river‐ocean components. In this study, we present a novel multi‐scale coupling framework within the Energy Exascale Earth System Model (E3SM), integrating global atmosphere and land with interactively coupled river and ocean models using different meshes with refined resolutions near the coastline. To evaluate this framework, we conducted ensemble simulations of a CF event (Hurricane Irene in 2011) in a Mid‐Atlantic estuary. The results demonstrate that the novel E3SM configuration can reasonably reproduce river discharge and sea surface height variations. The two‐way river‐ocean coupling improves the representation of coastal backwater effects at the terrestrial‐aquatic interface that are caused by the combined actions of tide and storm surge during the CF event, thus providing a valuable modeling tool for better understanding the river‐estuary‐ocean dynamics in extreme events under climate change. Notably, our results show that the most significant CF impacts occur when the highest storm surge generated by a tropical cyclone meets with a moderate river discharge. This study highlights the state‐of‐the‐art advancements developed within E3SM for simulating multi‐scale coastal processes.
Observational Constraints and Attribution of Global Plant Transpiration Changes Over the Past Four Decades
Authors: Cui Jiangpeng , Ding Jinzhi , Lian Xu , Wei Zhongwang , Li Shijie , Peng Jian , Poyatos Rafael , Wang Tao , Piao Shilong
Published: June 2024

Accurate estimation and attribution of large‐scale changes in plant transpiration are critical to understand the impacts of vegetation dynamics on the terrestrial hydrological cycle. However, these aspects remain poorly understood due to the limited reliability of global transpiration products. Here we compile data from 101 site‐based transpiration measurements across the globe and use them to constrain three biophysically based data‐driven transpiration products. The constrained transpiration reveals a prominent increasing trend of 0.61–0.79 mm yr−2 during 1980–2021, which is overestimated by 8%–32% in unconstrained transpiration. We further find that the global transpiration increase is mainly driven by leaf area index increase (40%), followed by climate change (19%), though offset partly by CO2‐induced stomatal closure (−38%) and land use and cover change (−3%). Our refined estimates indicate a less substantial increase of global transpiration than previously thought, improving the understanding of transpiration change impact on global hydrological cycle.
Timescales of Autogenic Noise in River Bedform Evolution and Stratigraphy
Authors: Ganti Vamsi , Kelley Madeline M. , Das Debsmita , Mahon Robert C.
Published: June 2024

Bedform evolution and preserved cross strata are known to respond to floods. However, it is unclear if autogenic dynamics mask the flood signal in bedform evolution and cross strata. To address this, we characterize the temporal structure of autogenic noise in steady‐state bedform evolution in a physical experiment. Results reveal the existence of bedform groups—quasi‐stable collections of bedforms—that migrate at a similar speed as bedforms. We find that bedform and bedform‐group turnover timescales are the key autogenic timescales of bed evolution that set the transition time‐periods between different noise regimes in bedform evolution. Results suggest that bedform‐group turnover timescale sets the lower limit for detecting flood signals in bedform evolution, and floods with duration shorter than bedform turnover timescale can be severely degraded in bedform evolution and cross strata. Our work provides a new framework for interrogating fluvial cross strata for reconstruction of past floods.
ETV6::RUNX1 Acute Lymphoblastic Leukemia: how much therapy is needed for cure?
Authors: Østergaard Anna , Fiocco Marta , de Groot-Kruseman Hester , Moorman Anthony V. , Vora Ajay , Zimmermann Martin , Schrappe Martin , Biondi Andrea , Escherich Gabriele , Stary Jan , Imai Chihaya , Imamura Toshihiko , Heyman Mats , Schmiegelow Kjeld , Pieters Rob
Published: June 2024

Recent trials show 5-year survival rates >95% for ETV6::RUNX1 Acute Lymphoblastic Leukemia (ALL). Since treatment has many side effects, an overview of cumulative drug doses and intensities between eight international trials is presented to characterize therapy needed for cure. A meta-analysis was performed as a comprehensive summary of survival outcomes at 5 and 10 years. For drug dose comparison in non-high risk trial arms, risk group distribution was applied to split the trials into two groups: trial group A with ~70% (range: 63.5–75%) of patients in low risk (LR) (CCLSG ALL2004, CoALL 07-03, NOPHO ALL2008, UKALL2003) and trial group B with ~45% (range: 38.7–52.7%) in LR (AIEOP-BFM ALL 2000, ALL-IC BFM ALL 2002, DCOG ALL10, JACLS ALL-02). Meta-analysis did not show evidence of heterogeneity between studies in trial group A LR and medium risk (MR) despite differences in treatment intensity. Statistical heterogeneity was present in trial group B LR and MR. Trials using higher cumulative dose and intensity of asparaginase and pulses of glucocorticoids and vincristine showed better 5-year event-free survival but similar overall survival. Based on similar outcomes between trials despite differences in therapy intensity, future trials should investigate, to what extent de-escalation is feasible for ETV6::RUNX1 ALL.
Theta burst stimulation for depression: a systematic review and network and pairwise meta-analysis
Authors: Kishi Taro , Ikuta Toshikazu , Sakuma Kenji , Hatano Masakazu , Matsuda Yuki , Wilkening Jonas , Goya-Maldonado Roberto , Tik Martin , Williams Nolan R. , Kito Shinsuke , Iwata Nakao
Published: June 2024

In clinical practice, theta burst stimulation (TBS) presents as a more efficient and potentially more effective therapeutic modality than conventional repetitive transcranial magnetic stimulation (rTMS), as it allows for the delivery of more stimuli in less time and at similar intensities. To date, accelerated treatment plans according to various continuous (cTBS) and intermittent TBS (iTBS) protocols for depression have been proposed. To investigate which of the TBS protocols provided a favorable risk-benefit balance for individuals with depression, this systematic review and random-effects model network meta-analysis was conducted. The study outcomes included response rate (primary), depression symptom improvement, remission rate, all-cause discontinuation rate, incidence of switch to mania, and incidence of headache/discomfort at treatment site. In this meta-analysis, a total of 23 randomized controlled trials (n = 960, mean age = 41.88 years, with 60.78% females) were included. Approximately 69.57% of the trials included individuals with an exclusive diagnosis of major depressive disorder. The following six TBS protocols (target) were evaluated: cTBS (right-dorsolateral prefrontal cortex [R-DLPFC]), cTBS (R-DLPFC) + iTBS (left-DLPFC [L-DLPFC]), iTBS (L-DLPFC), iTBS (L-DLPFC) + iTBS (R-DLPFC), iTBS (left-dorsomedial prefrontal cortex) + iTBS (right-dorsomedial prefrontal cortex), and iTBS (occipital lobe). Compared to sham, cTBS (R-DLPFC) + iTBS (L-DLPFC), iTBS (L-DLPFC), and iTBS (occipital lobe) had a higher response rate (k = 23); cTBS (R-DLPFC) + iTBS (L-DLPFC) and iTBS (L-DLPFC) dominated in the depression symptom improvement (k = 23); and iTBS (L-DLPFC) had a higher remission rate (k = 15). No significant differences were found for all-cause discontinuation rate (k = 17), incidence of switch to mania (k = 7), and incidence of headache/discomfort at treatment site (k = 10) between any TBS protocols and sham. Thus, cTBS (R-DLPFC) + iTBS (L-DLPFC) and iTBS (L-DLPFC) demonstrate favorable risk-benefit balance for the treatment of depression.
From real world data to real world evidence to improve outcomes in neuro-ophthalmology
Authors: Colman Blake D. , Zhu Zhuoting , Qi Ziyi , van der Walt Anneke
Published: June 2024

Real-world data (RWD) can be defined as all data generated during routine clinical care. This includes electronic health records, disease-specific registries, imaging databanks, and data linkage to administrative databases. In the field of neuro-ophthalmology, the intersection of RWD and clinical practice offers unprecedented opportunities to understand and treat rare diseases. However, translating RWD into real-world evidence (RWE) poses several challenges, including data quality, legal and ethical considerations, and sustainability of data sources. This review explores existing RWD sources in neuro-ophthalmology, such as patient registries and electronic health records, and discusses the challenges of data collection and standardisation. We focus on research questions that need to be answered in neuro-ophthalmology and provide an update on RWE generated from various RWD sources. We review and propose solutions to some of the key barriers that can limit translation of a collection of data into impactful clinical evidence. Careful data selection, management, analysis, and interpretation are critical to generate meaningful conclusions.
The hippocampus dissociates present from past and future goals
Authors: Montagrin Alison , Croote Denise E. , Preti Maria Giulia , Lerman Liron , Baxter Mark G. , Schiller Daniela
Published: June 2024

Our brain adeptly navigates goals across time frames, distinguishing between urgent needs and those of the past or future. The hippocampus is a region known for supporting mental time travel and organizing information along its longitudinal axis, transitioning from detailed posterior representations to generalized anterior ones. This study investigates the role of the hippocampus in distinguishing goals over time: whether the hippocampus encodes time regardless of detail or abstraction, and whether the hippocampus preferentially activates its anterior region for temporally distant goals (past and future) and its posterior region for immediate goals. We use a space-themed experiment with 7T functional MRI on 31 participants to examine how the hippocampus encodes the temporal distance of goals. During a simulated Mars mission, we find that the hippocampus tracks goals solely by temporal proximity. We show that past and future goals activate the left anterior hippocampus, while current goals engage the left posterior hippocampus. This suggests that the hippocampus maps goals using timestamps, extending its long axis system to include temporal goal organization.
Calcite carbonate sinks low-density plastic debris in open oceans
Authors: Sun Xiang-Fei , Zhang Yanxu , Xie Meng-Yi , Mai Lei , Zeng Eddy Y.
Published: June 2024

The vertical settling of plastic debris in oceans is poorly understood. A large share of low-density microplastics (LDMPs) are largely absent from sea surfaces. The present study employs a model that considers the potential of an overlooked microbially induced calcium carbonate precipitation (MICP) process and new motion equations for irregular LDMPs. Here we show that the motion of LDMPs in the present model, exhibiting a damped oscillation pattern, is quite different from that in biofouling models. Furthermore, LDMPs in the size range of 10–200 µm are most likely to gain sufficient density at the biofouling/MICP stage to independently sink to the ocean floor with relatively small drag coefficients, potentially explaining the selective enrichment of LDMPs in the oceanic sediment. The size and shape exhibit strong non-linear effects on the settling patterns of LDMPs. Overall, the present study highlights the importance of calcite-mediated sinking of LDMPs in open oceans.
Central transcriptional regulator controls photosynthetic growth and carbon storage in response to high light
Authors: Steichen Seth , Deshpande Arnav , Mosey Megan , Loob Jessica , Douchi Damien , Knoshaug Eric P. , Brown Stuart , Nielsen Robert , Weissman Joseph , Carrillo L. Ruby , Laurens Lieve M. L.
Published: June 2024

Carbon capture and biochemical storage are some of the primary drivers of photosynthetic yield and productivity. To elucidate the mechanisms governing carbon allocation, we designed a photosynthetic light response test system for genetic and metabolic carbon assimilation tracking, using microalgae as simplified plant models. The systems biology mapping of high light-responsive photophysiology and carbon utilization dynamics between two variants of the same Picochlorum celeri species, TG1 and TG2 elucidated metabolic bottlenecks and transport rates of intermediates using instationary 13C-fluxomics. Simultaneous global gene expression dynamics showed 73% of the annotated genes responding within one hour, elucidating a singular, diel-responsive transcription factor, closely related to the CCA1/LHY clock genes in plants, with significantly altered expression in TG2. Transgenic P. celeri TG1 cells expressing the TG2 CCA1/LHY gene, showed 15% increase in growth rates and 25% increase in storage carbohydrate content, supporting a coordinating regulatory function for a single transcription factor.
Development and organization of the retinal orientation selectivity map
Authors: Vita Dominic J. , Orsi Fernanda S. , Stanko Nathan G. , Clark Natalie A. , Tiriac Alexandre
Published: June 2024

Orientation or axial selectivity, the property of neurons in the visual system to respond preferentially to certain angles of visual stimuli, plays a pivotal role in our understanding of visual perception and information processing. This computation is performed as early as the retina, and although much work has established the cellular mechanisms of retinal orientation selectivity, how this computation is organized across the retina is unknown. Using a large dataset collected across the mouse retina, we demonstrate functional organization rules of retinal orientation selectivity. First, we identify three major functional classes of retinal cells that are orientation selective and match previous descriptions. Second, we show that one orientation is predominantly represented in the retina and that this predominant orientation changes as a function of retinal location. Third, we demonstrate that neural activity plays little role on the organization of retinal orientation selectivity. Lastly, we use in silico modeling followed by validation experiments to demonstrate that the overrepresented orientation aligns along concentric axes. These results demonstrate that, similar to direction selectivity, orientation selectivity is organized in a functional map as early as the retina.
Microporous Zr-metal-organic frameworks based-nanocomposites for thermoelectric applications
Authors: Ebrahim Asmaa , Ghali Mohsen , El-Moneim A. A.
Published: June 2024

In the area of energy storage and conversion, Metal-Organic Frameworks (MOFs) are receiving more and more attention. They combine organic nature with long-range order and low thermal conductivity, giving them qualities to be potentially attractive for thermoelectric applications. To make the framework electrically conductive so far, thermoelectricity in this class of materials requires infiltration by outside conductive guest molecules. In this study, an in-situ polymerization of conductive polyaniline inside the porous structure of MOF-801 was conducted to synthesize PANi@MOF-801 nanocomposites for thermoelectrical applications. The growth of polyaniline chains of different loadings inside the host MOF matrix generally enhanced bulk electrical conductivity by about 6 orders of magnitude, leading to Seebeck coefficient value of -141 µVK−1 and improved thermal stability. The unusual increase in electrical conductivity was attributed to the formation of highly oriented conductive PANi chains inside the MOF pores, besides host–guest physical interaction, while the Seebeck coefficient enhancement was because of the energy filtering effect of the developed structure. Modulating the composition of PANi@MOF-801 composites by varying the aniline: MOF-801 ratio in the synthesis bath from 2:1 and 1:1 to 1:2 leads to a change in the semiconductor properties from p-type semiconductor to n-type. Among the examined composites with n-type semiconducting properties exhibited the highest ZT value, 0.015, and lowest thermal conductivity, 0.24 Wm−1 K−1. The synthesized composites have better performance than those recently reported for a similar category of thermoelectric materials related to MOF-based composites.
Active juvenile systemic lupus erythematosus is associated with distinct NK cell transcriptional and phenotypic alterations
Authors: Radziszewska Anna , Peckham Hannah , de Gruijter Nina M. , Restuadi Restuadi , Wu Wing Han , Jury Elizabeth C. , Rosser Elizabeth C. , Ciurtin Coziana
Published: June 2024

While adaptive immune responses have been studied extensively in SLE (systemic lupus erythematosus), there is limited and contradictory evidence regarding the contribution of natural killer (NK) cells to disease pathogenesis. There is even less evidence about the role of NK cells in the more severe phenotype with juvenile-onset (J)SLE. In this study, analysis of the phenotype and function of NK cells in a large cohort of JSLE patients demonstrated that total NK cells, as well as perforin and granzyme A expressing NK cell populations, were significantly diminished in JSLE patients compared to age- and sex-matched healthy controls. The reduction in NK cell frequency was associated with increased disease activity, and transcriptomic analysis of NK populations from active and low disease activity JSLE patients versus healthy controls confirmed that disease activity was the main driver of differential NK cell gene expression. Pathway analysis of differentially expressed genes revealed an upregulation of interferon-α responses and a downregulation of exocytosis in active disease compared to healthy controls. Further gene set enrichment analysis also demonstrated an overrepresentation of the apoptosis pathway in active disease. This points to increased propensity for apoptosis as a potential factor contributing to NK cell deficiency in JSLE.
A novel interpretable machine learning model approach for the prediction of TiO2 photocatalytic degradation of air contaminants
Authors: Schossler Rodrigo Teixeira , Ojo Samuel , Jiang Zhuoying , Hu Jiajie , Yu Xiong
Published: June 2024

Air contaminants lead to various environmental and health issues. Titanium dioxide (TiO2) features the benefits of autogenous photocatalytic degradation of air contaminants. To evaluate its performance, laboratory experiments are commonly used to determine the kinetics of the photocatalytic-degradation rate, which is labor intensive, time-consuming, and costly. In this study, Machine Learning (ML) models were developed to predict the photo-degradation rate constants of air-borne organic contaminants with TiO2 nanoparticles and ultraviolet irradiation. The hyperparameters of the ML models were optimized, which included Artificial Neural Network (ANN) with Bayesian optimization, gradient booster regressor (GBR) with Bayesian optimization, Extreme Gradient Boosting (XGBoost) with optimization using Hyperopt, and Catboost combined with Adaboost. The organic contaminant was encoded through Molecular fingerprints (MF). Imputation method was applied to deal with the missing data. A generative ML model Vanilla Gan was utilized to create synthetic data to further augment the size of available dataset and the SHapley Additive exPlanations (SHAP) was employed for ML model interpretability. The results indicated that data imputation allowed for the full utilization of the limited dataset, leading to good machine learning prediction performance and preventing common overfitting problems with small-sized data. Additionally, augmenting experimental data with synthetic data significantly improved prediction accuracy and considerably reduced overfitting issues. The results ranked the feature importance and assessed the impacts of different experimental variables on the rate of photo-degradation, which were consistent with physico-chemical laws.
Performance evaluation of different regression models: application in a breast cancer patient data
Authors: Abo El Nasr Mona Mahmoud , Abdelmegaly Alaa A. , Abdo Doaa A.
Published: June 2024

This paper provides a comprehensive analysis of linear regression models, focusing on addressing multicollinearity challenges in breast cancer patient data. Linear regression methodologies, including GAM, Beta, GAM Beta, Ridge, and Beta Ridge, are compared using two statistical criteria. The study, conducted with R software, showcases the Beta regression model’s exceptional performance, achieving a BIC of − 5520.416. Furthermore, the Ridge regression model demonstrates remarkable results with the best AIC at − 8002.647. The findings underscore the practical application of these models in real-world scenarios and emphasize the Beta regression model’s superior ability to handle multicollinearity challenges. The preference for AIC over BIC in Generalized Additive Models (GAMs) is rooted in the AIC’s calculation framework, highlighting its effectiveness in capturing the complexity and flexibility inherent in GAMs.
Predictive approach of health indicators from the physical activity habits of active youth
Authors: Moreno-Gonzalez Laura , Manzano-Carrasco Samuel , Felipe Jose Luis , Alonso-Callejo Antonio , Gallardo Leonor , Garcia-Unanue Jorge
Published: June 2024

The aim of this study is to analyse the relationship between sport modalities practiced, physical fitness, body composition, and healthy habits in an active young population, using a statistical model for prediction. A total of 2255 (1528 boys and 727 girls) children and adolescents aged 6–17 years old who were involved in extracurricular sports from rural areas of Spain participated. Physical fitness was assessed through validated field test and, body composition was determinated using bioelectrical impedance analysis. Adherence to the Mediterranean diet was assessed by KIDMED questionnaire. The general sport variable was significant in VO2max when comparing the invasion and combat modalities to the reference level (court/net). The sex and age variables revealed significant differences in all physical fitness and body composition parameters. Health parameters, such as hours of additional practice, adherence to the Mediterranean diet, and previous experience, showed significant differences. The study concludes that the sport modality variables of training, sex, age, and maturational period have an impact on body composition and fitness parameters in this population. Therefore, by focusing on factors associated with lower values in health indicators, we can prevent health problems during adulthood, such as cardiorespiratory deficits.