bluuebunny/crossref_metadata_2025_split huggingface dataset:
An open-access dashboard to interrogate the genetic diversity of Mycobacterium tuberculosis clinical isolates
Authors: Phelan Jody , Van den Heede Klaas , Masyn Serge , Verbeeck Rudi , Lamprecht Dirk A. , Koul Anil , Wall Richard J. 
Published: October 2024

AbstractTuberculosis (TB) remains one of the leading infectious disease killers in the world. The ongoing development of novel anti-TB medications has yielded potent compounds that often target single sites with well-defined mechanisms of action. However, despite the identification of resistance-associated mutations through target deconvolution studies, comparing these findings with the diverse Mycobacterium tuberculosis populations observed in clinical settings is often challenging. To address this gap, we constructed an open-access database encompassing genetic variations from > 50,000 clinical isolates, spanning the entirety of the M. tuberculosis protein-encoding genome. This resource offers a valuable tool for investigating the prevalence of target-based resistance mutations in any drug target within clinical contexts. To demonstrate the practical application of this dataset in drug discovery, we focused on drug targets currently undergoing phase II clinical trials. By juxtaposing genetic variations of these targets with resistance mutations derived from laboratory-adapted strains, we identified multiple positions across three targets harbouring resistance-associated mutations already present in clinical isolates. Furthermore, our analysis revealed a discernible correlation between genetic diversity within each protein and their predicted essentiality. This meta-analysis, openly accessible via a dedicated dashboard, enables comprehensive exploration of genetic diversity pertaining to any drug target or resistance determinant in M. tuberculosis.
A hybrid approach of vision transformers and CNNs for detection of ulcerative colitis
Authors: Shah Syed Abdullah , Taj Imran , Usman Syed Muhammad , Hassan Shah Syed Nehal , Imran Ali Shariq , Khalid Shehzad 
Published: October 2024

AbstractUlcerative Colitis is an Inflammatory Bowel disease caused by a variety of factors that lead to a serious impact on the quality of life of the patients if left untreated. Due to complexities in the identification procedures of this disease, the treatment timeline and quality can be severely affected, leading to further consequences for the sufferer. The difficulties in identification are due to high patients to healthcare professionals ratio. Researchers have proposed variety of machine/deep learning methods for automated detection of ulcerative colitis, however, several challenges exists including class imbalance problem, comprehensive feature extraction and accurate classification. We propose a novel method for accurate detection of ulcerative colitis with augmentation techniques to overcome class imbalance issue, a comprehensive feature vector extraction using custom architecture of Vision Transformer (ViT) and accurate classification using customized Convolutional Neural Network (CNN). We used the TMC-UCM and LIMUC datasets in this research for training and testing of proposed method and achieved accuracy of 90% with AUC-ROC scores of 0.91, 0.81, 0.94, and 0.94 for the endoscopic classes of Mayo 0, Mayo 1, Mayo 2, and Mayo 3 respectively. We have compared the proposed method with existing state of the art methods and conclude that the proposed method outperforms the existing methods.
Empowering consumers to purchase safe ready-to-eat chicken from street restaurants in Ouagadougou, Burkina Faso: impact of a multi-media behavior change campaign
Authors: Madjdian Donya S. , van Asseldonk Marcel , Talsma Elise F. , Dione Michel , Ilboudo Guy , Roesel Kristina , Grace Delia , Knight-Jones Theodore J.D. , de Vet Emely 
Published: October 2024

AbstractFoodborne disease resulting from food sold at urban informal markets is a major public health challenge in Sub-Saharan Africa. This study assessed the impact of an innovative nine-months multi-media campaign engaging a key influencer, aimed at empowering consumers to choose safer ready-to-eat chicken meat at informal street restaurants in Ouagadougou, Burkina Faso. A two-wave panel study assessed associations between recall of TV, radio, billboard, and social media advertisements, and self-reported behavior regarding purchasing and consumption of ready-to-eat chicken at outlets, consumer intentions, knowledge, attitudes, norms, and agency. A panel of randomly selected adult consumers (n = 852) were interviewed pre- and post-campaign, 12 months apart. 60% recalled at least one of the campaign channels when prompted. Mixed-effects models showed associations between prompted recall and feeling better informed about food safety (aOR 1.449) and increased knowledge (0.132 unit increase on total score). Social media recall was associated with higher perceived access to information (aOR 1.449) and knowledge. Billboard recall increased odds of higher perceived health benefits of paying attention to food safety behaviors when purchasing chicken (aOR 2.046). TV ad recall was associated with a 0.159 unit decrease in the gap between consumers’ intentions and behavior. An engaging consumer food safety multimedia campaign that engages key influencers improved food safety awareness and knowledge, ultimately supporting consumers to choose safer chicken at markets.
Significant role of secondary electrons in the formation of a multi-body chemical species spur produced by water radiolysis
Authors: Kai Takeshi , Toigawa Tomohiro , Matsuya Yusuke , Hirata Yuho , Tezuka Tomoya , Tsuchida Hidetsugu , Yokoya Akinari 
Published: October 2024

AbstractScientific insights into water photolysis and radiolysis are essential for estimating the direct and indirect effects of deoxyribonucleic acid (DNA) damage. Secondary electrons from radiolysis intricately associated with both effects. In our previous paper, we simulated the femtosecond (1 × 10− 15 s) dynamics of secondary electrons ejected by energy depositions of 11−19 eV into water via high-energy electron transport using a time-dependent simulation code. The results contribute to the understanding of simple “intra-spur” chemical reactions of tree-body chemical species (hydrated electrons, hydronium ion and OH radical) in subsequent chemical processes. Herein, we simulate the dynamics of the electrons ejected by energy depositions of 20−30 eV. The present results contribute to the understanding of complex “inter-spur” chemical reactions of the multi-body chemical species as well as for the formation of complex DNA damage with redox site and strand break on DNA. The simulation results present the earliest formation mechanism of an unclear multi-body chemical species spur when secondary electrons induce further ionisations or electronic excitations. The formation involves electron–water collisions, i.e. ionisation, electronic excitation, molecular excitation and elastic scattering. Our simulation results indicate that (1) most secondary electrons delocalise to ~ 12 nm, and multiple collisions are sometimes induced in a water molecule at 22 eV deposition energy. (2) The secondary electrons begin to induce diffuse band excitation of water around a few nm from the initial energy deposition site and delocalise to ~ 8 nm at deposition energies ~ 25 eV. (3) The secondary electron can cause one additional ionisation or electronic excitation at deposition energies > 30 eV, forming a multi-body chemical species spur. Thus, we propose that the type and density of chemical species produced by water radiolysis strongly depend on the deposition energy. From our results, we discuss formation of complex DNA damage.
Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces
Authors: Pun Tsam Kiu , Khoshnevis Mona , Hosman Tommy , Wilson Guy H. , Kapitonava Anastasia , Kamdar Foram , Henderson Jaimie M. , Simeral John D. , Vargas-Irwin Carlos E. , Harrison Matthew T. , Hochberg Leigh R. 
Published: October 2024

AbstractIntracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method, “MINDFUL”, to measure instabilities in neural data for useful long-term iBCI, without needing labels of user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed decoders to control a computer cursor spanning 142 days and 28 days, respectively. We demonstrate a measure of instability that correlates with changes in closed-loop cursor performance solely based on the recorded neural activity (Pearson r = 0.93 and 0.72, respectively). This result suggests a strategy to infer online iBCI performance from neural data alone and to determine when recalibration should take place for practical long-term use.
Forecasting trends in food security with real time data
Authors: Herteux Joschka , Raeth Christoph , Martini Giulia , Baha Amine , Koupparis Kyriacos , Lauzana Ilaria , Piovani Duccio 
Published: October 2024

AbstractEarly warning systems are an essential tool for effective humanitarian action. Advance warnings on impending disasters facilitate timely and targeted response which help save lives and livelihoods. In this work we present a quantitative methodology to forecast levels of food consumption for 60 consecutive days, at the sub-national level, in four countries: Mali, Nigeria, Syria, and Yemen. The methodology is built on publicly available data from the World Food Programme’s global hunger monitoring system which collects, processes, and displays daily updates on key food security metrics, conflict, weather events, and other drivers of food insecurity. In this study we assessed the performance of various models including Autoregressive Integrated Moving Average (ARIMA), Extreme Gradient Boosting (XGBoost), Long Short Term Memory (LSTM) Network, Convolutional Neural Network (CNN), and Reservoir Computing (RC), by comparing their Root Mean Squared Error (RMSE) metrics. Our findings highlight Reservoir Computing as a particularly well-suited model in the field of food security given both its notable resistance to over-fitting on limited data samples and its efficient training capabilities. The methodology we introduce establishes the groundwork for a global, data-driven early warning system designed to anticipate and detect food insecurity.
Osmotic signaling releases PP2C-mediated inhibition of Arabidopsis SnRK2s via the receptor-like cytoplasmic kinase BIK1
Authors: Li Guo-Jun , Chen Kong , Sun Shujing , Zhao Yang 
Published: October 2024

AbstractOsmotic stress and abscisic acid (ABA) signaling are important for plant growth and abiotic stress resistance. Activation of osmotic and ABA signaling downstream of the PYL-type ABA receptors requires the release of SnRK2 protein kinases from the inhibition imposed by PP2Cs. PP2Cs are core negative regulators that constantly interact with and inhibit SnRK2s, but how osmotic signaling breaks the PP2C inhibition of SnRK2s remains unclear. Here, we report that an Arabidopsis receptor-like cytoplasmic kinase, BIK1, releases PP2C-mediated inhibition of SnRK2.6 via phosphorylation regulation. The dominant abi1-1 ABA-signaling mutation (G180D) disrupts PYL-PP2C interactions and disables PYL-initiated release of SnRK2s; in contrast, BIK1 releases abi1-1-mediated inhibition of SnRK2.6. BIK1 interacts with and phosphorylates SnRK2.6 at two tyrosine residues, which are critical for SnRK2.6 activation and function. Phosphorylation of the two tyrosine residues may affect the docking of the tryptophan “lock” of PP2C into SnRK2.6. Moreover, the bik1 mutant is defective in SnRK2 activation, stress-responsive gene expression, ABA accumulation, growth maintenance, and water loss under osmotic stress. Our findings uncover the critical role of BIK1 in releasing PP2C-mediated inhibition of SnRK2s under osmotic stress.
Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning
Authors: Akhoundzadeh Pouya , Mirjalily Ghasem 
Published: October 2024

AbstractIn this paper, with the promising assumption of using adaptive directional microstrip antenna on user equipment, the problem of joint antenna selection, spectrum assignment, and transmit power allocation for mm‐wave device‐to‐device communications underlying cellular networks is tackled, with the goal of enhancing system throughput and energy efficiency. To address the complexity of this problem, a method based on multi‐agent distributed deep reinforcement learning in which an autonomous intelligent agent is deployed for each user equipment is proposed. The performance evaluation demonstrates its superiority over existing strategies, resulting in improved system performance, reduced outage probability, and enhanced energy efficiency.
Artificial intelligence‐driven insights: Precision tracking of power plant carbon emissions using satellite data
Authors: Zhang Zeqi , Leng Di , Li Yingjie , Gui Xuanang , Cheng Yuheng , Zhao Junhua , Zhang Zhengwen , Ghias Amer M. Y. M. 
Published: October 2024

AbstractHuman activities have been driving massive greenhouse gas emissions, causing global warming, and triggering increasingly frequent extreme weather events that severely threaten the environment. Power generation is the leading contributor to anthropogenic emissions, making precise, real‐time measurement and monitoring of power plant carbon emissions crucial in reducing climate change. This study uses a new sophisticated pipeline that combines tropospheric monitoring instrument satellite data, power plant attributes, and advanced artificial intelligence algorithms to build a predictive carbon emission model. The approach utilizes multimodal data processing, encoding, and model optimisation. Experimental results confirm that this pipeline can automatically extract and utilize vast amounts of relevant data, thereby enabling the artificial intelligence model to accurately predict power plant carbon emissions and providing a vital tool for reducing global warming.
A high efficiency wideband co‐polarised metalens antenna
Authors: Liang JiaJun , Wu Zhao , Li Long , Huang YanHu 
Published: October 2024

AbstractThe traditional co‐polarised metasurface achieves 360° phase coverage only at the resonant frequency but not full phase coverage across a wide bandwidth. This paper proposes a multilayer structure metasurface, which composes of five layers of metal patch and four layers of medium, forming the Fabry–Perry resonator, using the principle of the cancellation of two polarisation conversion, which can achieve a wideband efficient co‐polarisation transmission. Based on the metasurface transmission phase principle, 360° phase coverage has been achieved by changing the geometric parameters of the intermediate metal patches. Through phase compensation arrangement, a metalens is designed using the proposed metasurface unit cell. At the same time, horn antenna is used as a feed to feed the metalens, which can significantly improve the gain of the antenna within a wideband. Simulated and measured results show that the proposed metalens antenna operates at 22–26 GHz, and the maximum measured gain of the metalens antenna reaches 24.16 dBi at 25 GHz, which is 10.85 dB higher than the horn antenna without metasurface compensation, showing good focusing performance. The proposed multilayer metasurface breaks the narrow band limit of the traditional stacked metasurface in principle, opening a way in the broadband metasurface design.
The Galactic population of canonical pulsars
Authors: Sautron Mattéo , Pétri Jérôme , Mitra Dipanjan , Dirson Ludmilla 
Published: October 2024

Context. Pulsars are highly magnetised rotating neutron stars, emitting in a broad electromagnetic energy range. These objects were discovered more than 55 years ago and are astrophysical laboratories for studying physics at extreme conditions. Reproducing the observed pulsar population helps refine our understanding of their formation and evolution scenarios, as well as their radiation processes and geometry.
Aims. In this paper, we improve our previous population synthesis by focusing on both the radio and γ-ray pulsar populations, investigating the impact of the Galactic gravitational potential and of the radio emission death line. To elucidate the necessity of a death line, we implemented our refined initial distributions of the spin period and spacial position at birth. This approach allowed us to elevate the sophistication of our simulations to the most recent state-of-the-art approaches.
Methods. The motion of each individual pulsar was tracked in the Galactic potential by a fourth-order symplectic integration scheme. Our pulsar population synthesis took into account the secular evolution of the force-free magnetosphere and magnetic field decay simultaneously and self-consistently. Each pulsar was evolved from birth to the present time. The radio and γ-ray emission locations were modelled by the polar cap geometry and striped wind model, respectively.
Results. By simulating ten million pulsars, we found that including a death line allows us to better reproduce the observational trend. However, when simulating one million pulsars, we obtained an even more realistic P−Ṗ diagram, whether or not a death line was included. This suggests that the ages of the detected pulsars might be overestimated and so, it sets the need for a death line in pulsar population studies into question. Kolmogorov-Smirnov tests confirm the statistical similarity between the observed and simulated P−Ṗ diagram. Additionally, simulations with increased γ-ray telescope sensitivities hint at a significant contribution coming from the γ-ray pulsars to the GeV excess in the Galactic centre.
Ausgeprägte Myelonkompression durch Rezidiv eines Osteochondroms 14 Jahre nach der ersten Resektion
Authors: Zolal Amir , Hares Mohammad Bader , Kirsch Matthias 
Published: October 2024

ZusammenfassungEin 39-jähriger männlicher Patient präsentierte sich mit zunehmender Gangataxie, Schwäche und Gefühlsstörungen der rechten Körperhälfte. Anamnestisch war eine Resektion eines Osteochondroms im Bereich HWK6 vor 15 Jahren bekannt. Die MRT-Aufnahmen zeigten ein Rezidiv des Tumors mit deutlicher Myelonkompression, woraufhin eine komplette Resektion mittels Laminektomie und dorsaler Osteosynthese durchgeführt wurde. Die postoperative Nachsorge ergab eine signifikante Verbesserung der Symptomatik, dokumentiert durch einen Anstieg des mJOA-Scores von 10 auf 15 Punkte. Osteochondrome sind seltene, gutartige Knochentumore, deren spinale Manifestation besonders ungewöhnlich ist und in der Regel eine chirurgische Resektion erfordert. Der vorliegende Fall unterstreicht die Bedeutung regelmäßiger Nachsorge bei Patienten nach Resektion eines Osteochondroms, um Rezidive frühzeitig zu erkennen und zu behandeln.
Therapierefraktäre generalisierte pustulöse Psoriasis – Ein deutsches Problem
Authors: Sollfrank Lukas , Kemenes Stephan , Voskens Caroline , Sticherling Michael 
Published: October 2024

ZusammenfassungDie generalisierte pustulöse Psoriasis ist eine seltene, potenziell lebensbedrohliche, autoinflammatorische Hauterkrankung, welche als Sonderform der Psoriasis vulgaris gilt. Zuletzt wurde mit dem Anti-Interleukin (IL)-36-Rezeptor-Antikörper Spesolimab erstmalig eine zielgerichtete Behandlungsmöglichkeit für diese Erkrankung zugelassen. Der Gemeinsame Bundesausschuss (G-BA) hat dieser Therapieoption jedoch einen Zusatznutzen im Vergleich zu systemischen Glukokortikoiden abgesprochen, weshalb der Wirkstoff in Deutschland aktuell nicht mehr auf dem Markt ist. Wir berichten von einer 47-jährigen Patientin, die nach monatelanger, hoch dosierter Glukokortikoidtherapie nach Antrag bei ihrer Krankenkasse mit Spesolimab erfolgreich behandelt werden konnte.
Leitlinie ICH E11A veröffentlicht
Authors: Kelber Olaf 
Published: October 2024

Zusammenfassung
Die Ausweitung der Zulassung bzw. Registrierung pflanzlicher
Arzneimittel auch auf Kinder ist in den letzten Jahren zunehmend
herausfordernder geworden. Daher gibt es Initiativen
wissenschaftlicher Fachgesellschaften, diese dadurch zu erleichtern,
dass sie sich zukünftig auch auf Real World Data
(RWD) stützen kann. Im Rahmen der deutschen Nachzulassung
und der Erstellung verschiedener HMPC-Monografien
hat sich ein solches Vorgehen schon bewährt. Die neue Leitlinie
ICH E11A zur Extrapolation von an Erwachsenen gewonnenen
Daten auf Kinder hebt zwar stark auf die Nutzung von
Pharmakokinetikdaten für die Extrapolation ab, die bei pflanzlichen
Arzneimitteln in der Regel nicht aussagekräftig sind.
Doch ist die Leitlinie grundsätzlich auch für andere Wege der
Extrapolation einschließlich RWE offen, soweit diese geeignet
sind, die Zulassungsbehörden zu überzeugen.
Serum Exosomal MiR-874 as a Potential Biomarker for Nonsmall Cell Lung Cancer Diagnosis and Prognosis
Authors: Gharib Amal F. , Al-Shehri Saad S. , Almalki Abdulraheem , Alhazmi Ayman , Allahyani Mamdouh , Alghamdi Ahmed , Alrehaili Amani A. , Bakhuraysah Maha M. , M. Althobaiti Naif Saad , Elsawy Weal H. 
Published: October 2024

AbstractLung cancer, primarily nonsmall cell lung cancer (NSCLC), is a leading cause of cancer-related fatalities globally. Due to late detection, the 5-year survival rate for NSCLC remains low. Therefore, the current research aimed to assess the diagnostic and prognostic value of serum exosomal miR-874 levels in NSCLC patients. This study involved 161 NSCLC patients and 80 control subjects. Blood samples were collected from all participants, and serum exosomal MiR-874 levels were quantified using quantitative reverse transcription-polymerase chain reaction. The study revealed a significant decrease in MiR-874 levels among NSCLC patients compared to controls. The receiver operating characteristic analysis demonstrated the diagnostic value of serum exosomal MiR-874 in effectively distinguishing NSCLC patients from controls.Furthermore, associations were observed between serum exosomal MiR-874 expression and adverse clinical factors such as young age, male sex, smoking, high tumor grade, squamous cell carcinoma histopathology, advanced tumor stage, and lymphatic involvement. Patients with high levels of MiR-874 had significantly longer overall and disease-free survival compared to those with lower levels. The study demonstrates that levels of serum exosomal miR-874 are considerably lower in NSCLC patients, indicating its potential as a diagnostic biomarker. The study's findings suggest that the expression of MiR-874 may predict the prognosis of NSCLC patients based on clinical features.
Polatuzumab Vedotin for Diffuse Large B-Cell Lymphoma: Innovation's Allure versus a Time-Honored Tradition
Authors: Singh Suvir , Arora Akriti 
Published: October 2024

AbstractChemotherapy with R-CHOP (rituximab, cyclophosphamide, Adriamycin, vincristine, prednisolone) is the standard of care for patients with diffuse large B-cell lymphoma as the first-line therapy. The recent approval of polatuzumab as the first-line therapy after demonstration of its efficacy in the Polatuzumab Vedotin in Previously Untreated Diffuse Large B-Cell Lymphoma (POLARIX) trial is the first significant change in this treatment regimen over two decades. This concise appraisal of trial evidence and clinical context highlights the limited potential for a clinically significant benefit with the addition of polatuzumab to the first-line therapy for this common hematologic malignancy.