bluuebunny/crossref_metadata_2025 huggingface dataset:
Characteristics of positive feedback provided by UK health service users: content analysis of examples from two databases
Authors: Lloyd Rebecca , Slade Mike , Byng Richard , Russell Alex , Ng Fiona , Stirzaker Alex , Rennick-Egglestone Stefan
Published: September 2024

Background

Most feedback received by health services is positive. Our systematic scoping review mapped all available empirical evidence for how positive patient feedback creates healthcare change. Most included papers did not provide specific details on positive feedback characteristics.

Objectives

Describe positive feedback characteristics by (1) developing heuristics for identifying positive feedback; (2) sharing annotated feedback examples; (3) describing their positive content.

Methods

200 items were selected from two contrasting databases: (1)https://careopinion.org.uk/; (2) National Health Service (NHS) Friends and Family Test data collected by an NHS trust. Preliminary heuristics and positive feedback categories were developed from a small convenience sample, and iteratively refined.

Results

Categories were identified: positive-only; mixed; narrative; factual; grateful. We propose a typology describing tone (positive-only, mixed), form (factual, narrative) and intent (grateful). Separating positive and negative elements in mixed feedback was sometimes impossible due to ambiguity. Narrative feedback often described the cumulative impact of interactions with healthcare providers, healthcare professionals, influential individuals and community organisations. Grateful feedback was targeted at individual staff or entire units, but the target was sometimes ambiguous.

Conclusion

People commissioning feedback collection systems should consider mechanisms to maximise utility by limiting ambiguity. Since being enabled to provide narrative feedback can allow contributors to make contextualised statements about what worked for them and why, then there may be trade-offs to negotiate between limiting ambiguity, and encouraging rich narratives. Groups tasked with using feedback should plan the human resources needed for careful inspection, and consider providing narrative analysis training.
Quality improvement project (QIP): evaluating a pilot suicide awareness, screening and signposting training intervention for dental care professionals in a dental teaching hospital and school
Authors: Cairns Declan , Kilgariff Julie K , Tully Vicki
Published: September 2024

Scotland’s 2022 suicide prevention strategy recommends building skills and knowledge among healthcare staff who play a role in preventing suicide. A quality improvement project (QIP) in relation to this was initiated because several patients attending dental appointments disclosed suicidal thoughts and/or plans to attempt death by suicide. Dental staff and students involved expressed feeling ill-equipped at how to manage this situation. This initial QIP aimed to establish routine screening, identification and signposting of dental outpatients identified as having an increased risk of suicide during attendance at any dental clinic within the Dental Hospital. Several Plan-Do-Study-Act (PDSA) cycles ensued. First, to understand the problem, a scoping literature search on the role of dental professionals in preventing suicide and the availability of suicide risk awareness training frameworks for non-medical healthcare staff revealed few publications and no identified training frameworks. This was PDSA1. To gain insight into the local culture in relation to the QIP aims, two further cycles were undertaken. These examined whether dental patients were routinely screened for mental health conditions, and dental staff and student attitudes. Screening activity was measured, a new medical history intervention was implemented and a significant improvement in the number of patients being screened was seen (PDSA2). At the time of writing, the newly introduced medical history form is now used routinely to screen all outpatients attending the Dental Hospital, where 60 000 outpatients’ appointments are delivered annually. PDSA3 sought dental staff and student views on whether suicide risk awareness is part of their role. This found suicide risk awareness is considered part of the dental professionals’ role, but a lack of training, and a desire for training was expressed. With no suitable training frameworks, PDSA4 aimed to design, implement and evaluate a pilot training educational intervention by a clinical psychologist. Sixteen dental care professionals attended the workshop. To measure training effectiveness, participants completed pre-training (baseline) and post-training questionnaires to assess their self-efficacy around suicide awareness. Improvements in self-efficacy following training occurred across all domains, demonstrating a successful intervention which can be upscaled.
Neurodevelopmental functions and activities of the KAT3 class of lysine acetyltransferases
Authors: Shahib Ashraf K. , Rastegar Mojgan , van Wijnen Andre J. , Davie James R.
Published: September 2024

The human lysine acetyltransferases KAT3A ( CREBBP) and KAT3B ( EP300) are essential enzymes in gene regulation in the nucleus. Their ubiquitous expression in metazoan cell types controls cell proliferation and differentiation during development. This comprehensive review delves into the biological roles of KAT3A and KAT3B in neurodevelopment, shedding light on how alterations in their regulation or activity can potentially contribute to a spectrum of neurodegenerative diseases (e.g., Huntington's and Alzheimer's). We explore the pathophysiological implications of KAT3 function loss in these disorders, considering their conserved protein domains and biochemical functions in chromatin regulation. The discussion also underscores the crucial role of KAT3 proteins and their substrates in supporting the integration of key cell signaling pathways. Furthermore, the narrative highlights the interdependence of KAT3-mediated lysine acetylation with lysine methylation and arginine methylation. From a cellular perspective, KAT3-dependent signal integration at subnuclear domains is mediated by liquid–liquid phase separation in response to KAT3-mediated lysine acetylation. The disruption of these finely tuned regulatory processes underscores their pathological roles in neurodegeneration. This review also points to the exciting potential for future research in this field, inspiring further investigation and discovery in the area of neurodevelopment and neurodegenerative diseases.
A harm reduction approach to improving peer review by acknowledging its imperfections
Authors: Cooke Steven J. , Young Nathan , Peiman Kathryn S. , Roche Dominique G. , Clements Jeff C. , Kadykalo Andrew N. , Provencher Jennifer F. , Raghavan Rajeev , DeRosa Maria C. , Lennox Robert J. , Robinson Fayek Aminah , Cristescu Melania E. , Murray Stuart J. , Quinn Joanna , Cobey Kelly D. , Browman Howard I.
Published: September 2024

This candid perspective written by scholars from diverse disciplinary backgrounds is intended to advance conversations about the realities of peer review and its inherent limitations. Trust in a process or institution is built slowly and can be destroyed quickly. Trust in the peer review process for scholarly outputs (i.e., journal articles) is being eroded by high-profile scandals, exaggerated news stories, exposés, corrections, retractions, and anecdotes about poor practices. Diminished trust in the peer review process has real-world consequences and threatens the uptake of critical scientific advances. The literature on “crises of trust” tells us that rebuilding diminished trust takes time and requires frank admission and discussion of problems, creative thinking that addresses rather than dismisses criticisms, and planning and enacting short- and long-term reforms to address the root causes of problems. This article takes steps in this direction by presenting eight peer review reality checks and summarizing efforts to address their weaknesses using a harm reduction approach, though we recognize that reforms take time and some problems may never be fully rectified. While some forms of harm reduction will require structural and procedural changes, we emphasize the vital role that training editors, reviewers, and authors has in harm reduction. Additionally, consumers of science need training about how the peer review process works and how to critically evaluate research findings. No amount of self-policing, transparency, or reform to peer review will eliminate all bad actors, unscrupulous publishers, perverse incentives that reward cutting corners, intentional deception, or bias. However, the scientific community can act to minimize the harms from these activities, while simultaneously (re)building the peer review process. A peer review system is needed, even if it is imperfect.
Cascaded Adaptive Dilated Temporal Convolution Network-Based Efficient Sentiment Analysis Model from Social Media Posts
Authors: Liya B. S. , Indumathy P. , Hemlathadhevi A. , Dharaniya R.
Published: September 2024

Sentimental analysis is one of the most complicated tasks in text mining. It is the process of converting unstructured text to structural text to identify the meaningful pattern of data. Different kinds of sentiments in social media posts are classified into positive and negative. Natural Language Processing (NLP) plays an imperative task in examining sentiments on social media. Sentimental analysis techniques frequently use text data to help to monitor customer feedback about products and understand the needs of customers in the field of business. The text data are gathered from social media comments that lead to several drawbacks such as spelling errors, noise, and unstructured data, and some of the data are in abbreviation form in which abbreviations are hard to understand from the text data. Therefore, the innovative sentiment analysis method is implemented to identify the kinds of sentiments from the collected social media posts. At first, the text data are assembled from the social media posts. The collected text data are subjected to text preprocessing techniques to improve the data quality. NLP techniques such as a bag of n-grams, glove embedding, and Bidirectional Encoder Representations from Transformers (BERT) are applied to separate the features from the text data. The removed features from these techniques are given to the fusion of the optimal feature stage, where the weight optimization takes place via the Mutated Random Parameter-based Serval Optimization Algorithm (MRP-SOA). The attained optimal weighted fused features contain the most relevant information, and it is fed to the classifier for analyzing the sentiments. For analyzing the sentiments, the Cascaded Adaptive Dilated Temporal Convolutional Network (CADTCN) is utilized, and the parameters from ADTCN are optimized with the same to get higher classification outcomes. The analysis outcomes are compared with the traditional sentiment analysis models in terms of various metrics to show the success of the advanced design.
Relationship between plantar pressure distribution and sagittal spinal curvatures among handball players: A cross-sectional study
Authors: Abdel-aziem Amr A. , Ameer Mariam A. , Al Abbad Ammar M. , Mahdi Maher A.
Published: September 2024

Background:

Handball affects the spinal anterior–posterior curvatures and disturbs the foot plantar pressure which provides insights into alterations in an individual’s posture. However, little is known about how the mal-alignment affects the distribution of plantar pressure.

Objective:

To investigate the relationship between the thoracic kyphosis angle, and plantar pressure distribution among handball players.

Methods:

Sixty male handball players were distributed into two groups based on their thoracic kyphosis angles. Group A: 28 handball players with an angle greater than 44∘ (kyphotic group), and group B: 32 handball players with an angle equal to or less than 44∘ (normal group). The Formetric III 4D spine and DIERS Pedoscan devices were used to measure the trunk anthropometry and plantar pressure distribution. The Pearson correlation test was used to explore the relationship between the kyphosis angle and plantar pressure distribution.

Results:

Group A was significantly taller, had longer trunk length, greater lumbar lordosis angles, and forefoot plantar pressure (FPP), and less rearfoot plantar pressure (RPP) than group B ([Formula: see text]). They showed a highly significant positive correlation between the thoracic kyphosis angle and FPP, and a highly significant negative correlation with the RPP ([Formula: see text], [Formula: see text], respectively). There was no correlation between the lumbar lordosis angle and FPP or RPP ([Formula: see text], [Formula: see text], respectively).

Conclusion:

Handball players with greater thoracic kyphosis angle have greater lumbar lordosis angle. Increasing the thoracic kyphosis angle is strongly associated with increased FPP and decreased RPP. While there is no relationship between the lumbar lordosis angle and FPP or RPP.
Automatic Identification of Game Stuttering via Gameplay Videos Analysis
Authors: Guglielmi Emanuela , Bavota Gabriele , Oliveto Rocco , Scalabrino Simone
Published: September 2024

Modern video games are extremely complex software systems and, as such, they might suffer from several types of post-release issues. A particularly insidious issue is constituted by drops in the frame rate (i.e., stuttering events), which might have a negative impact on the user experience. Stuttering events are frequently documented in the million of hours of gameplay videos shared by players on platforms such as Twitch or YouTube. From the developers’ perspective, these videos represent a free source of documented “testing activities.” However, especially for popular games, the quantity and length of these videos make impractical their manual inspection. We introduce HASTE, an approach for the automatic detection of stuttering events in gameplay videos that can be exploited to generate candidate bug reports. HASTE firstly splits a given video into visually coherent slices, with the goal of filtering-out those that not representing actual gameplay (e.g., navigating the game settings). Then, it identifies the subset of pixels in the video frames which actually show the game in action excluding additional elements on screen such as the logo of the YouTube channel, on-screen chats, and so forth. In this way, HASTE can exploit state-of-the-art image similarity metrics to identify candidate stuttering events, namely subsequent frames being almost identical in the pixels depicting the game. We evaluate the different steps behind HASTE on a total of 105 videos showing that it can correctly extract video slices with a 76% precision, and can correctly identify the slices related to gameplay with a recall and precision higher than 77%. Overall, HASTE achieves 71% recall and 89% precision for the identification of stuttering events in gameplay videos.
Proven Distributed Memory Parallelization of Particle Methods
Authors: Pahlke Johannes , Sbalzarini Ivo F.
Published: September 2024

We provide a mathematically proven parallelization scheme for particle methods on distributed-memory computer systems. Particle methods are a versatile and widely used class of algorithms for computer simulations and numerical predictions in various applications, ranging from continuum fluid dynamics to discrete granular flows and molecular dynamics simulations. Particle methods naturally lend themselves to implementation on parallel computing systems. So far, however, a mathematical proof of correctness and equivalence to sequential implementations has only been available for shared-memory parallelism. Here, we leverage a formal definition of the algorithmic class of particle methods to provide a proven parallelization scheme for distributed-memory computers. We prove that thus parallelized particle methods on distributed-memory computers are formally equivalent to their sequential counterpart for a well-defined class of particle methods, and we provide analytical expressions for the speedup and scalability bounds of this class of algorithms in function of their parameters. The parallelization scheme analyzed here is the basis of many real-world software designs for parallel particle methods. The present analysis is, therefore, of direct relevance to existing and new parallel implementations of particle methods and places them on solid theoretical grounds, rationalizing best practices and providing useful scalability and speedup bounds for benchmarking.
A Survey on Video Diffusion Models
Authors: Xing Zhen , Feng Qijun , Chen Haoran , Dai Qi , Hu Han , Xu Hang , Wu Zuxuan , Jiang Yu-Gang
Published: September 2024

The recent wave of AI-generated content (AIGC) has witnessed substantial success in computer vision, with the diffusion model playing a crucial role in this achievement. Due to their impressive generative capabilities, diffusion models are gradually superseding methods based on GANs and auto-regressive Transformers, demonstrating exceptional performance not only in image generation and editing, but also in the realm of video-related research. However, existing surveys mainly focus on diffusion models in the context of image generation, with few up-to-date reviews on their application in the video domain. To address this gap, this article presents a comprehensive review of video diffusion models in the AIGC era. Specifically, we begin with a concise introduction to the fundamentals and evolution of diffusion models. Subsequently, we present an overview of research on diffusion models in the video domain, categorizing the work into three key areas: video generation, video editing, and other video understanding tasks. We conduct a thorough review of the literature in these three key areas, including further categorization and practical contributions in the field. Finally, we discuss the challenges faced by research in this domain and outline potential future developmental trends. A comprehensive list of video diffusion models studied in this survey is available athttps://github.com/ChenHsing/Awesome-Video-Diffusion-Models.
Rewriting the Infinite Chase for Guarded TGDs
Authors: Benedikt Michael , Buron Maxime , Germano Stefano , Kappelmann Kevin , Motik Boris
Published: September 2024

Guarded tuple-generating dependencies
(GTGDs) are a natural extension of description logics and referential constraints. It has long been known that queries over GTGDs can be answered by a variant of the
chase
—a quintessential technique for reasoning with dependencies. However, there has been little work on concrete algorithms and even less on implementation. To address this gap, we revisit
Datalog rewriting
approaches to query answering, where a set of GTGDs is transformed to a Datalog program that entails the same base facts on each base instance. We show that a rewriting consists of “shortcut” rules that circumvent certain chase steps, we present several algorithms that compute a rewriting by deriving such “shortcuts” efficiently, and we discuss important implementation issues. Finally, we show empirically that our techniques can process complex GTGDs derived from synthetic and real benchmarks and are thus suitable for practical use.
A Blockchain-Based Privacy-Preserving Charging Station Reservation and Payment Scheme for Electric Vehicles
Authors: Danish Syed Muhammad , Shabir Muhammad Muneem , Zhang Kaiwen , Jacobsen Hans-Arno , Hassan Syed Ali
Published: September 2024

EV charging infrastructures traditionally rely on untrusted centralized infrastructures that pose several privacy and security threats to EVs’ personal information. Targeted advertisements, privacy leaks, selling data to third parties, are among the threats to privacy and security. By utilizing blockchain-based solutions, recent work address the security and privacy problems associated with EV charging protocols. Most of them are geared toward maintaining EV anonymity rather than preserving end-to-end privacy. As EV owners’ charging histories and payment information are associated with their wallet address on the blockchain, any threat of linkability of these blockchain addresses to physical identities can pose a serious risk to their privacy. In this paper, we propose a ring signature based privacy-preserving end-to-end charging station (CS) reservation and payment protocol, which provides EV owners with the ability to reserve and pay for a charging slot privately, without sharing private information or exposing their identity or addresses at CS locations. Additionally, we provide EV owners with a decentralized charging slot information verification protocol with the help of secure multiparty computation (SMC), which allows them to verify available slots. A dispute resolution mechanism is also proposed that handles disputes between EVs and CSs and penalizes them accordingly by utilizing trusted execution environment (TEE). Results show that the proposed protocol ensures end-to-end EV owners’ privacy with low blockchain transaction and computation overhead.
A Multi-Mechanism Fusion Method for Robust State of Charge Estimation via Bidirectional Long Short-Term Memory Model with Mixture Kernel Mean p-Power Error Loss Optimized by Golden Jackal Optimization Algorithm
Authors: Ma Wentao , Lei Yiming , Yang Bo , Guo Peng
Published: September 2024

Accurate state of charge (SOC) estimation is crucial for effective battery management in various applications. The bidirectional long short-term memory (BiLSTM) as an outstanding nonlinear regression model can be used for SOC estimation. This work develops a novel multi-mechanism fusion method based on BiLSTM to further enhance its estimation performance for SOC, in which the convolutional neural network (CNN), attention mechanism, and mixture kernel mean p-power error (MKMPE) loss are introduced into the BiLSTM framework for addressing different issues. First, the introduction of CNN components aims to extract essential features from battery data, enhancing the model’s comprehension of complex information. Then, the attention mechanism is used to further refine the model’s perceptual ability and a robust MKMPE loss is introduced into the BiLSTM framework to replace its original mean squared error loss, and a novel robust model is developed to suppress non-Gaussian noise interference. Finally, some key hyperparameters of the proposed model are fine-tuned using the golden jackal optimization algorithm, resulting in improved estimation performance. Comparative numerical experiments are meticulously conducted in various cases to evaluate the performance of the proposed method, and the experiment results demonstrate that it can perform outstanding effectiveness in handling non-Gaussian noise scenarios.
Interplay of Interfacial Adhesion and Mechanical Degradation in Anode-Free Solid-State Batteries
Authors: Shozib Imtiaz Ahmed , Cúñez Fernando David , Ganter Matthew , Leggiero Anthony , Liu Rui , Tu Qingsong Howard
Published: September 2024

Anode-free solid-state batteries (AFSSBs) with an Ag-C interlayer are an innovative architecture because of their high energy density compared to conventional Li metal solid-state batteries. This work introduces simple methods to enhance the interfacial adhesion strength between the Ag-C interlayer and the solid electrolyte (SE) for better initial capacity of the cell, by controlling the cell assembling pressure to place together all components of the cell. Through contact angle experiments, our study unveils how the variation in the assembling pressure can significantly influence the contact angle between SE (at different assembling pressures) and Li metal, affecting their adhesion energy. Our electrochemical tests evidence that raising the assembling pressure from 350 to 530 MPa outcomes an increment of more than 50% in initial capacity due to higher adhesion energies, with the corresponding energy density of 410 Wh kg−1. Nonetheless, SE separator tends to crack beyond a critical assembling pressure of 530 MPa that might cause a dramatic decrease of the cell performance. Our findings show that increasing the interfacial adhesion through different methods can prevent interface degradation and increase energy density of AFSSBs, affirming the vital role of interfacial adhesion between the Ag-C interlayer and SE separators, holding significant advances in anode free architectures.
Mass Transport in Confined Micro Geometry in Reciprocating Paddle Plating Cell by Numerical Simulation and Neural Network Analysis
Authors: Huang Q.
Published: September 2024

The mass transport in confined geometry in a paddle plating cell is studied using numerical simulation with an attempt to extrapolate an explicit correlation to understand the transport physics and to predict the electrodeposition rate of metal microstructures. A moving boundary in conjunction with mapped mesh is used to allow the reciprocating movement of the flow. A correlation is obtained based on a generalized additive model using multivariant linear regression. Neural networks are also used to analyze the efficacy of such correlation and to determine the descriptor characterizing the error in prediction. A two-step convectional mass transport process, one in the bulk electrolyte outside the patterns and the other inside the micro-trenches, is demonstrated to better describe the overall transport physics and improve the correlation.
On the Volume Expansion of Lithium Ion Battery Electrodes (I) after Wetting, and (II) Selection of the Right Amount of Electrolyte
Authors: Pritzlaff Lars , Winter Martin , Niehoff Philip
Published: September 2024

The electrolyte is necessary for transport of lithium ions between the negative and positive electrode within the battery cell. The lower the amount of electrolyte, the higher the energy density and specific energy. Hence, it is important to understand which cell parameters are relevant to determine the right amount of electrolyte. Here, three different cell designs in 1 to 5 Ah pouch cells where investigated for cell impedance after filling, cell capacity after formation, C-rate performance, and capacity retention for up to 3,000 full cycles. Wetting the cell with electrolyte, the cell pore volume changed between 25%–35% due to changes of 6%–16% in the thickness of the anode and cathode. Although electrolyte volumes >0.85 times the wet cell pore volume showed minimal resistance before formation, only electrolyte volumes of 1.08 times the wet cell pore volume were sufficient for a successful formation process. For long-term cycling, a minimum electrolyte volume of 1.19 times the wet cell pore volume was required to improve long-term cycling performance. Future experiments will investigate the correlation of capacity fade with electrolyte consumption for different electrolytes.
Processing of Zirconium Oxide Raw Materials to Produce Zirconium Silicides via Electrolysis of KCl-K2SiF6-ZrO2 Melt
Authors: Gorshkov Leonid , Suzdaltsev Andrey , Gevel Timofey , Zaikov Yury
Published: September 2024

The possibility of electrochemical synthesis of zirconium silicides by electrolysis of KCl-K2SiF6 melt with ZrO2 additives at 790 °C has been studied. To determine the synthesis parameters, the kinetics and some features of the mechanism of the cathodic process in the investigated melt on glassy carbon were studied by cyclic chronovoltammetry and chronoamperometry. It was shown that the electroreduction of silicon ions in the KCl-K2SiF6 melt takes place at potentials from 0 to −0.2 V. Additional peaks at more negative potentials were obtained on the voltametric dependences, presumably related to the reduction of zirconium ions and the co-reduction of silicon and zirconium ions. Electrolysis of KCl-K2SiF6 melt with additions of 0.33 and 0.66 wt% ZrO2 in galvanostatic mode at cathodic current density of 20 mA cm−2 was performed in order to check assumptions. Cathode deposits were obtained, which were analyzed by X-ray diffraction and scanning electron microscopy after separation of salt residues. It is shown that the precipitates were represented by zirconium silicides (ZrSi2, ZrSi) as well as oxides (SiO2, ZrO2).
Exploring Deep Learning–Based Models for Sociocultural African Food Recognition System
Authors: Ataguba Grace , Alhasani Mona , Daniel James , Ogbuju Emeka , Orji Rita
Published: September 2024

Food recognition, a field under food computing, has significantly promoted people’s dietary decision‐making and culinary customs. We present the design and evaluation of a sociocultural app for African food recognition using deep learning models such as transfer learning. Deep learning models have multiple processing layers that make them robust in image recognition. Based on this capability of deep learning models, we explored them in this study. A total of 3142 food image datasets were collected from three African countries: Nigeria, Ghana, and Cameroon. Using the datasets, we developed and trained a deep learning model for recognizing African foods. The model attained a test accuracy of 94.5%. The model was further deployed in a food recognition app. To evaluate the predictive ability of the app, we recruited 16 participants who were interviewed and subsequently used the app in the wild for 7 days. In a comparative evaluation between the app and human recognition capabilities, we found that the app recognized 71% of the instances of food images generated by the participants and tested with the app, while the human evaluators (participants) could only recognize 56% of the food datasets. Participants were mostly able to recognize some foods from their own country. Furthermore, participants suggested some design features for the app. In view of this, we offer design recommendations for researchers and designers of sociocultural food recognition systems.
Controllability of Functional and Structural Brain Networks
Authors: Moradi Amani Ali , Tahmassebi Amirhessam , Stadlbauer Andreas , Meyer-Baese Uwe , Noblet Vincent , Blanc Frederic , Malberg Hagen , Meyer-Baese Anke
Published: September 2024

Normal and aberrant cognitive functions are the result of the dynamic interplay between large‐scale neural circuits. Describing the nature of these interactions has been a challenging task yet important for neurodegenerative disease evolution. Fusing modern dynamic graph network theory techniques and control theory applied on complex brain networks creates a new framework for neurodegenerative disease research by determining disease evolution at the subject level, facilitating a predictive treatment response and revealing key mechanisms responsible for disease alterations. It has been shown that two types of controllability—the average and the modal controllability—are relevant for the mechanistic explanation of how the brain navigates between cognitive states. The average controllability favors highly connected areas which move the brain to easily reachable states, while the modal controllability favors weakly connected areas representative for difficult‐to‐reach states. We propose two different techniques to achieve these two types of controllability: a centrality measure based on a sensitivity analysis of the Laplacian matrix is employed to determine the average controllability, while graph distances form the basis of the modal controllability. The concepts of “choosing the best driver set” and “graph distances” are applied to measure the average controllability and the modal controllability, respectively. Based on these new techniques, we obtain important disease descriptors that visualize alterations in the disease trajectory by revealing densely connected hubs or sparser areas. Our results suggest that these two techniques can accurately describe the different node roles in controlling trajectories of brain networks.
Performance Evaluation and Stability of Maize (Zea mays L.) Genotypes for Grain Yield Using AMMI and GGE Biplot
Authors: Daemo Berhanu Bilate , Wolancho Getahun Bore , Arke Zeleke Ashango , Wakalto Dawit Dalga , Onu Mesele Haile
Published: September 2024

It is a fact that the performance of most crop genotypes varies across environments due to genotype‐environment interactions. Sharing knowledge about maize genotypes that are well‐adapted and high‐yielding in specific environments is essential for smallholder farmers to boost their productivity. A field trial was established in three locations during the 2019 and 2020 growing seasons to identify and select better‐adapted high‐yielding maize genotypes for production. A total of 10 improved varieties were evaluated using a randomized complete block design with three replications. The AMMI analysis of variance showed grain yield significantly (p ≤ 0.001) influenced by genotype‐environment interaction. This suggests that different genotypes showed varying grain yield performance across environments, implying the opportunity to choose effective genotypes suitable for both specific and broad adaptability. Moreover, the combined analysis of variance showed that genotype‐environment interaction significantly influenced plant height, ear height, dry biomass yield, and hundred‐kernel weight. The sum of squares factor explained that grain yield variation was contributed by the genotype (71.22%), followed by the environment (16.54%) and the genotype‐environment interaction effect (12.24%) of the total variation. Genotypes BH‐661, BH‐549, and BH‐546 demonstrated superior performance and stability, surpassing the national maize mean productivity and indicating broad adaptability. The AMMI analysis, GSI, and GGE biplot confirmed their robustness and high yield potential, especially for BH‐661 and BH‐549, making them optimal for variable conditions. Therefore, BH‐661 and BH‐549 are selected as stable genotypes for production in all agroecologies suitable for maize in the Dawuro zone.
Table S1 from A Drug Discovery Pipeline for MAPK/ERK Pathway Inhibitors in Caenorhabditis elegans
Authors: Gorgoń Szymon , Billing Ola , Eriksson Anna U. , Hemmingsson Oskar
Published: September 2024

Supplementary table 1. All Compounds and Exclusions
Figure S3 from A Drug Discovery Pipeline for MAPK/ERK Pathway Inhibitors in Caenorhabditis elegans
Authors: Gorgoń Szymon , Billing Ola , Eriksson Anna U. , Hemmingsson Oskar
Published: September 2024

Automated scoring of vulval induction and percent larvae in the ST65 strain.
Figure 4 from A Drug Discovery Pipeline for MAPK/ERK Pathway Inhibitors in Caenorhabditis elegans
Authors: Gorgoń Szymon , Billing Ola , Eriksson Anna U. , Hemmingsson Oskar
Published: September 2024

Evaluation of pathway specificity. A, Differential interference contrast (DIC) micrographs showing overall body morphology (inlayed panels) and vulval phenotypes in untreated lin-15(n765) and lin-1(e1777) mutant adults. Arrows indicate functional vulvae, and arrowheads indicate pseudovulvae. Scale bars, 50 μm. B, Graphs indicating vulvae per adult scores (black squares) and Z-factors (red dots) after drug treatment in ST65, lin-15(n765), and lin-1(e1777) animals. Drug concentrations in μmol/L are indicated on the X-axis, the mean number of vulvae per adult on the left Y-axis, and Z-factors on the right Y-axis. Error bars show ± SDs from three independent experiments.
Figure 2 from A Drug Discovery Pipeline for MAPK/ERK Pathway Inhibitors in Caenorhabditis elegans
Authors: Gorgoń Szymon , Billing Ola , Eriksson Anna U. , Hemmingsson Oskar
Published: September 2024

Scoring of vulva tissue. A, Bar graph showing distributions of indicated phenotypes in WT N2 animals after exposure to control DMSO media (n = 244) or 10 μmol/L trametinib (n = 296). B, Nomarski and fluorescence images of the ST65 strain, expressing AJM-1::GFP in pharyngeal muscle cells (arrows) and vulva tissue (arrowhead). The pharyngeal signal is retained under trametinib treatment, but the vulva signal is lost, and the worm is Vul on Nomarski image. Scale bars, 200 μm. C, Liquid cultures of the same strain imaged using a plate reader. In the magnified panels, arrows indicate adult-sized pharynges, the asterisk indicates a larval pharynx, and the arrowhead indicates a vulva. Scale bars, 500 μm.
Figure S2 from Estrogen Receptor Blockade Potentiates Immunotherapy for Liver Metastases by Altering the Liver Immunosuppressive Microenvironment
Authors: Benslimane Yasmine , Amalfi Kevin , Lapin Sara , Perrino Stephanie , Brodt Pnina
Published: September 2024

NKT and CD8+ T cells analyses. Shown in (a) are the multiplex cytokine array results validation at the mRNA expression. Shown in (b) are the flow cytometry gating strategy for the analysis of CCL5 and CCR5 in NKT and CD8+ T cells (n=3-4).
Peroxisome Proliferator–Activated Receptor δ Suppresses the Cytotoxicity of CD8+ T Cells by Inhibiting RelA DNA-Binding Activity
Authors: Cen Bo , Wei Jie , Wang Dingzhi , DuBois Raymond N.
Published: September 2024

The molecular mechanisms regulating CD8+ cytotoxic T lymphocytes (CTL) are not fully understood. Here, we show that the peroxisome proliferator–activated receptor δ (PPARδ) suppresses CTL cytotoxicity by inhibiting RelA DNA binding. Treatment of ApcMin/+ mice with the PPARδ agonist GW501516 reduced the activation of normal and tumor-associated intestinal CD8+ T cells and increased intestinal adenoma burden. PPARδ knockout or knockdown in CTLs increased their cytotoxicity against colorectal cancer cells, whereas overexpression of PPARδ or agonist treatment decreased it. Correspondingly, perforin, granzyme B, and IFNγ protein and mRNA levels were higher in PPARδ knockout or knockdown CTLs and lower in PPARδ overexpressing or agonist-treated CTLs. Mechanistically, we found that PPARδ binds to RelA, interfering with RelA–p50 heterodimer formation in the nucleus, thereby inhibiting its DNA binding in CTLs. Thus, PPARδ is a critical regulator of CTL effector function.

Significance: Here, we provide the first direct evidence that PPARδ plays a critical role in suppressing the immune response against tumors by downregulating RelA DNA-binding activity. This results in decreased expression of perforin, granzyme B, and IFNγ. Thus, PPARδ may serve as a valuable target for developing future cancer immunotherapies.
Bosutinib Treatment of Chronic Myeloid Leukemia in Lombardy
Authors: Iurlo Alessandra , Bucelli Cristina , Intermesoli Tamara , Elena Chiara , D'Adda Mariella , Agostani Elena , Fiamenghi Cristina , Maffioli Margherita , Orofino Nicola , Lunghi Francesca , Gardellini Angelo , Carraro Maria Cristina , Inzoli Alessandro , Gigli Federica , Palazzolo Roberto , Bertolli Vanda , Cattaneo Daniele , Pungolino Ester Maria , Gambacorti-Passerini Carlo
Published: September 2024

Introduction: Up to 30% of CML patients will require a therapeutic change during follow-up due to intolerance and/or resistance to first-line tyrosine kinase inhibitor (TKI) approach. In this context, bosutinib (BOS) has not only demonstrated its efficacy, but also presents a favorable safety profile, without comorbid conditions representing an absolute contraindication to its use. Methods: To gain further into BOS treatment in real life, we conducted a retrospective analysis on the outcome of CML patients receiving BOS in 18 hematological centers, all belonging to the “REL” (Lombard Hematology Network). Results: Of 546 regularly followed CML cases, a total of 132 patients were reported as being treated with BOS, most frequently (62.9%) in second line. Interestingly, most patients (63.6%) switched to BOS due to intolerance to the previous TKI, while resistance to the last treatment was reported in the remaining 36.4% of patients. Despite a permanent discontinuation rate of 18.9%, over 80% of patients achieved at least a major molecular response and seven cases were able to attempt treatment-free remission. Conclusion: Although in this survey BOS represented the preferred option especially in patients intolerant rather than resistant to previous TKIs, we confirmed that BOS represents a safe and effective therapeutic option beyond the first line in the real-life setting.
Immunotherapy plus Chemotherapy for Patients with EGFR-Mutated Non-Squamous Cell Lung Cancer for Disease Progression after EGFR Tyrosine-Kinase Inhibitor: A Meta-Analysis of Randomized Controlled Trials
Authors: Refae Ahmed A. , Abu Shakra Rafat I. , Ibrahim Ezzeldin M.
Published: September 2024

Introduction: Patients with non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations face poor outcomes after progression on tyrosine kinase inhibitors (TKIs). The efficacy of immune checkpoint inhibitors (ICIs) combined with chemotherapy in these patients remains uncertain. Methods: We searched for studies published between randomized controlled trials of ICIs in combination therapies in advanced NSCLC patients post-EGFR TKI progression. Data on progression-free survival (PFS), overall survival (OS), and objective response rate (ORR) were extracted and analyzed. Results: Six studies with a total of 2,225 patients were analyzed. The pooled hazard ratio (HR) for PFS was 0.60 (95% CI, 0.55–0.65; p < 0.0001), indicating a significant improvement in PFS with ICIs. Subgroup analysis suggested that patients with prior exposure to third-generation TKIs showed a more pronounced benefit (HR = 0.61; 95% CI, 0.49–0.76; p < 0.0001). However, no benefit was found in patients without prior exposure. The efficacy of the experimental interventions was also shown on the pooled estimates of OS (HR = 0.87; 95% CI, 0.77–0.0.99; p value = 0.04) and ORR (OR = 1.91; 95% CI, 1.32–2.76; p < 0.0001). Conclusion: ICIs may significantly benefit PFS among patients with EGFR-mutated NSCLC who have progressed on TKI treatment. Future research should continue stratifying patients based on prior treatment exposure to optimize therapeutic strategies.
Is Baricitinib Effective and Safe for Patients with Difficult-to-Treat Rheumatoid Arthritis? Comparative Data with the Rheumatoid Arthritis Group of Rheumatoid Arthritis Not Difficult to Treat
Authors: Ekin Ali , Misirci Salim , Görünen Ahmet , Coskun Belkis Nihan , Yagiz Burcu , Dalkilic Ediz , Pehlivan Yavuz
Published: September 2024

Objective: This study investigates the efficacy and safety of baricitinib, an oral targeted synthetic disease-modifying antirheumatic drugs (DMARDs), in patients with difficult-to-treat rheumatoid arthritis (D2T RA) compared to those without, aiming to determine its potential as an alternative treatment for D2T RA. Subject and Methods: A total of 78 patients participated in this retrospective cohort study, with 33 meeting the D2T RA criteria and 45 in the non-D2T RA group. Various clinical and laboratory parameters, adverse events, and disease activity indices were assessed, alongside drug efficacy and survival rates. Results: Patients with D2T RA exhibited higher seronegativity, prior use of b-DMARDs and c-DMARDs, and longer disease duration. Both groups experienced reductions in VAS and DAS28 scores, as well as SDAI, CDAI, HAQ, CRP, and ESR levels at baseline and 3, 6, and 12 months post-baricitinib initiation, with sustained efficacy observed over 12 months. The most prevalent adverse event was infection (28.21%). Although initial drug survival rates were similar between groups, the non-D2T RA group demonstrated higher rates at 24 months (46.70% vs. 59.40%). Subgroup analyses showed comparable survival rates between D2T RA and non-D2T RA groups, whether treated with baricitinib alone or in combination with methotrexate or leflunomide. Conclusion: Despite potential treatment resistance, patients meeting the D2T RA criteria shared similar safety and efficacy profiles with those non-D2T RA. Baricitinib emerges as a promising treatment option for D2T RA patients, offering effectiveness and safety comparable to the non-D2T RA group.
IN SILICO STUDY OF THE MECHANISM OF ANTIСANCER ACTIVITY OF (E)-2-((5-(3-(2-FLUOROPHENYL)ACRYLOYL)-4-METHYLTHIAZOL-2-YL)AMINO)ISOINDOLINE-1,3-DIONE (LES-6489)
Authors: Fedusevych O.-M. V.
Published: September 2024

The aim of the work. To predict the mechanisms of antiсancer activity using modern web tools for the compound Les-6489.
Materials and Methods. Molecular docking of EGFR and HER2 tyrosine kinases was performed for compound Les-6489. To evaluate the stability of complexes with Les-6489, molecular dynamics (MD) simulations were performed using GROMACS 13, which is accessed through the SiBioLead server.
Results and Discussion. As a result of in silico studies, a mechanism of antitumor activity was predicted for the studied compound Les-6489, which is implemented by inhibiting EGFR and HER2 tyrosine kinases.
Conclusions. The obtained results may become a platform for further structural optimization of the identified thiazole-isoindole hybrid molecule in the development of modern anticancer agents.
Effects of Oral Butyrate on Blood Pressure in Patients With Hypertension: A Randomized, Placebo-Controlled Trial
Authors: Verhaar Barbara J.H. , Wijdeveld Madelief , Wortelboer Koen , Rampanelli Elena , Levels Johannes H.M. , Collard Didier , Cammenga Marianne , Nageswaran Vanasa , Haghikia Arash , Landmesser Ulf , Li Xinmin S. , DiDonato Joseph A. , Hazen Stanley L. , Garrelds Ingrid M. , Danser A.H. Jan , van den Born Bert-Jan H. , Nieuwdorp Max , Muller Majon
Published: September 2024

BACKGROUND:

The microbiota-derived short chain fatty acid butyrate has been shown to lower blood pressure (BP) in rodent studies. Nonetheless, the net effect of butyrate on hypertension in humans remains uncovered. In this study, for the first time, we aimed to determine the effect of oral butyrate on BP in patients with hypertension.

METHODS:

We performed a double-blind randomized placebo-controlled trial including 23 patients with hypertension. Antihypertensive medication was discontinued for the duration of the study with a washout period of 4 weeks before starting the intervention. Participants received daily oral capsules containing either sodium butyrate or placebo with an equivalent dosage of sodium chloride for 4 weeks. The primary outcome was daytime 24-hour systolic BP. Differences between groups over time were assessed using linear mixed models (group-by-time interaction).

RESULTS:

Study participants (59.0±3.7 years; 56.5% female) had an average baseline office systolic BP of 143.5±14.6 mm Hg and diastolic BP of 93.0±8.3 mm Hg. Daytime 24-hour systolic and diastolic BP significantly increased over the intervention period in the butyrate compared with the placebo group, with an increase of +9.63 (95% CI, 2.02–17.20) mm Hg in daytime 24-hour systolic BP and +5.08 (95% CI, 1.34–8.78) mm Hg in diastolic BP over 4 weeks. Butyrate levels significantly increased in plasma, but not in feces, upon butyrate intake, underscoring its absorption.

CONCLUSIONS:

Four-week treatment with oral butyrate increased daytime systolic and diastolic BP in subjects with hypertension. Our findings implicate that butyrate does not have beneficial effects on human hypertension, which warrants caution in future butyrate intervention studies.

REGISTRATION:

URL:
https://onderzoekmetmensen.nl/
; Unique identifier: NL8924.