bluuebunny/crossref_metadata_2025 huggingface dataset:
Identities with b-generalized derivations and generalized skew derivations on prime rings
Authors: Singh Lovepreet , De Filippis Vincenzo , Tiwari S. K.
Published: October 2024

Let [Formula: see text] be a prime ring of characteristic different from [Formula: see text], [Formula: see text] be the right Martindale quotient ring of [Formula: see text], [Formula: see text] the extended centroid of [Formula: see text], [Formula: see text] be a noncentral Lie ideal of [Formula: see text], [Formula: see text] and [Formula: see text] be two nonzero [Formula: see text]-generalized derivations of [Formula: see text]. Suppose there exist fixed integers [Formula: see text] such that [Formula: see text], for all [Formula: see text], then either [Formula: see text] satisfies the standard identity [Formula: see text] or there is [Formula: see text] such that [Formula: see text], [Formula: see text], for any [Formula: see text], and one of the following holds:

(a) there exists [Formula: see text], (b) [Formula: see text] and [Formula: see text] are [Formula: see text]-linearly dependent.

Then, in the second part of the paper we prove a similar result in the case [Formula: see text] and [Formula: see text] are generalized skew derivations of [Formula: see text] such that [Formula: see text], for all [Formula: see text].
On study of some bounds for fault-tolerant metric dimension and adjacency fault-tolerant resolving set of corona product graphs
Authors: Shahzad Muhammad Asif , Ali Nasir , Abdallah Suhad Ali Osman , Abd El-Gawaad N. S.
Published: October 2024

In this paper, we investigate bounds for the fault-tolerant metric dimension and adjacency fault-tolerant resolving set of corona product graphs. Let [Formula: see text] and [Formula: see text] be two graphs with orders [Formula: see text] and [Formula: see text], respectively. The corona product of the graphs [Formula: see text] and [Formula: see text], denoted by [Formula: see text], is constructed by taking one copy of [Formula: see text] and [Formula: see text] copies of [Formula: see text], connecting each vertex of the [Formula: see text]th copy of [Formula: see text] to the [Formula: see text]th vertex of [Formula: see text] by an edge. For any integer [Formula: see text], we recursively define the graph [Formula: see text] as [Formula: see text]. We present several results on the fault-tolerant metric dimension and the adjacency fault-tolerant resolving set of corona product graphs. Additionally, we explore the relationship between the fault-tolerant metric dimension and the adjacency fault-tolerant metric dimension of a graph [Formula: see text]. Finally, we determine the adjacency fault-tolerant metric dimension of path, cycle, complete, complete bipartite, and star graphs.
Multi-Objective Crop and Livestock Allocation Modeling (MOCLAM) for Sustainable Agriculture: A Case Study of Semi-Arid India
Authors: Chand Prem , Jain Rajni , Pal Suresh , Agarwal Priyanka
Published: October 2024

Sustainable cropping patterns and a systems approach in farming are crucial for the conservation of natural resources and the long-term livelihood of farmers. Achieving agricultural sustainability goals relies on adopting a comprehensive system approach involving developing a comprehensive model for optimal crop and allied enterprise planning. In this study, a multi-objective crop and livestock allocation model (MOCLAM) was devised and evaluated with a case study of the semi-arid and drought-prone Bundelkhand region of Central India. The primary aims of the model were to enhance input efficiency, maximize income and self-sufficiency and minimize water usage and other environmental impacts. The uniqueness of the proposed model lies in three key aspects: First, the model adopts a systemic view of agriculture by simultaneous optimization of both crops and livestock, second, MOCLAM introduces a quasi-dynamic framework and third, the model comprehensively incorporates water considerations from both surface and groundwater sources. The findings of the case study demonstrated that optimal resource allocation can significantly increase farmers’ net economic margins, conserve water and effectively utilize vast monsoon-season (locally termed as kharif) fallow lands in the region. By adopting microirrigation techniques and improved sowing methods, water savings can be more than doubled without compromising economic margins. Compensating farmers for potential lower yields of sesame, a low-water-requiring and stray-cattle-resistant crop, would encourage the adoption of these water-saving practices. Increasing water availability by 24% through water harvesting can boost farmers’ returns by up to 62%. This study suggests that farmers may be reluctant to adopt agroforestry practices, such as integrating trees with field crops, unless they are incentivized for the social benefits these systems provide. It also requires the development of an adequate timber marketing mechanism that is crucial for wider adoption.
Natural hydrogen exploration within Western European and the eastern Mediterranean ophiolites and ultramafic complexes
Authors: Donzé Frédéric-Victor , Lefeuvre Nicolas , Truche Laurent , Yao Yan , Vujevíc Ivan , Dutoit Hugo
Published: October 2024

This study investigates the potential for natural hydrogen (H
2
) production across western continental Europe and the eastern Mediterranean, focusing on ophiolitic and ultramafic massifs. Our approach integrates geophysical, geological and geochemical parameters to identify regions where serpentinization could be a key natural process for H
2
generation. Based on these parameters, we have developed a comprehensive probabilistic model to assess the likelihood of abiotic H
2
production at depth. This model incorporates parameters such as geothermal heat flux, magnetic anomalies and the existence of hyperalkaline springs, each weighted according to their possible influence on serpentinization. This weighting is derived from a case study in Albania, where H
2
degassing has been observed. The model has been applied to several ophiolitic and ultramafic complexes, including the Ordenes (Spain), the Alter-do-Chão (Portugal), the Ronda (Spain), the northwestern Alps, the Apennine (Italy), the Dinarides, the Hellenides (e.g. Vourinos and Pindos ophiolites in Greece), Troodos (Cyprus), Kızıldağ, Bassit, Hatay (Turkey) and Leka (Norway). A ranking has been proposed in terms of the probability of finding H
2
at these locations. Subsequently, in order to underscore the potential need for region-specific adaptations of the model, the model was applied to the well-documented Samail Ophiolite in Oman, where H
2
seepages are observed. While the model provides a framework for H
2
-targeted exploration, it also acknowledges its current limitations, emphasizing the necessity for continuous refinement and validation against new observations. The inherent uncertainties in geological processes call for a dynamic modelling strategy to accurately predict and explore geological H
2
resources.
Ethics, Governance, and User Mental Models for Large Language Models in Computing Education
Authors: Zhou Kyrie Zhixuan , Kilhoffer Zachary , Sanfilippo Madelyn Rose , Underwood Ted , Gumusel Ece , Wei Mengyi , Choudhry Abhinav , Xiong Jinjun
Published: October 2024

Large language models like ChatGPT are disrupting many industries, including computing education. How should policy evolve to improve learning outcomes?
Rethinking Supervised Learning based Neural Combinatorial Optimization for Routing Problem
Authors: Yao Shunyu , Lin Xi , Wang Jiashu , Zhang Qingfu , Wang Zhenkun
Published: October 2024

Neural combinatorial optimization (NCO) is a promising learning-based approach to solving complex combinatorial optimization problems such as the traveling salesman problem (TSP), the vehicle routing problem (VRP), and the orienteering problem (OP). However, how to efficiently train a powerful NCO solver for routing problems remains a crucial challenge. The widely used reinforcement learning method suffers from sparse rewards and low data efficiency, while the supervised learning approach requires a large number of high-quality solutions (i.e., labels) that could be costly to obtain. In this work, we find that simple data augmentation operations can drastically reduce the number of required high-quality solutions for supervised learning. Moreover, simple boosting strategies that leverage the property of multiple optima can significantly improve training efficiency. With only a small set of

\(50,000\)

labeled instances, supervised learning can achieve a competitive in-distribution performance with the widely-used reinforcement learning counterpart. Furthermore, we also investigate the generalization ability for larger out-of-distribution problems. We believe the findings from this work may lead to a rethinking of the value of data-efficient supervised learning for NCO solver training.
Improving Source Code Pre-Training via Type-Specific Masking
Authors: Zou Wentao , Li Qi , Li Chuanyi , Ge Jidong , Chen Xiang , Huang LiGuo , Luo Bin
Published: October 2024

The Masked Language Modeling (MLM) task is widely recognized as one of the most effective pre-training tasks and currently derives many variants in the Software Engineering (SE) field. However, most of these variants mainly focus on code representation without distinguishing between different code token types, while some focus on a specific type, such as code identifiers. Indeed, various code token types exist, and there is no evidence that only identifiers can improve PTMs. Thus, to improve PTMs through different types, we conducted an extensive study to evaluate how different type-specific masking tasks can affect PTMs. First, we extract five code token types, convert them into type-specific masking tasks, and generate their combinations. Second, we pre-train CodeBERT and PLBART using combinations and fine-tuned them on four SE downstream tasks. Experimental results show that type-specific masking tasks can enhance CodeBERT and PLBART on all downstream tasks. Furthermore, we discuss topics related to low-resource datasets, conflicting PTMs that original pre-training tasks conflict with our methods, the cost and performance of our methods, factors that impact the performance of our methods, and applying our methods on state-of-the-art PTMs. These discussions comprehensively analyze the strengths and weaknesses of different type-specific masking tasks.
Artificial Intelligence to Support the Training and Assessment of Professionals: A Systematic Literature Review
Authors: Albaladejo-González Mariano , Ruipérez-Valiente José A. , Gmez Mármol Félix
Published: October 2024

Advances in Artificial Intelligence (AI) and sensors are significantly impacting multiple areas, including education and workplaces. Following the PRISMA methodology, this review explores the current status of using AI to support the training and assessment of professionals. We examined 83 research papers, analyzing (1) the targeted professionals, (2) the skills assessed, (3) the AI algorithms utilized, (4) the data and devices employed, (5) data fusion techniques utilized, (6) the architecture of the proposed platforms, (7) the management of ethics and privacy, and (8) validations of the proposals. The review highlights a trend in evaluating healthcare professionals (especially surgeons) motivated by the critical role of hands-on training in these professions. Besides, the review reveals that data fusion techniques and certain technologies, like transfer learning and explainable AI, are not widely utilized despite their huge potential. Finally, the review underscores that most proposals remain within the research domain, lacking the integration and maturity needed for sustained use in real-world environments. Therefore, most of the proposals are not currently available to support the training of professionals. The insights of this review can guide researchers aiming to improve the training of professionals and, consequently, their education.
Surrogate Modeling to Address the Absence of Protected Membership Attributes in Fairness Evaluation
Authors: Kadıoğlu Serdar , Thielbar Melinda
Published: October 2024

It is imperative to ensure that artificial intelligence models perform well for all groups including those from underprivileged populations. By comparing the performance of models for the protected group with respect to the rest of the population, we can uncover and prevent unwanted bias. However, a significant drawback of such binary fairness evaluation is its dependency on protected group membership attributes. In various real-world scenarios, protected status for individuals is sparse, unavailable, or even illegal to collect. This paper extends the previous work on binary fairness metrics to relax the requirement on deterministic membership to its surrogate counterpart under a probabilistic setting. We show how to conduct binary fairness evaluation when exact protected attributes are not available, but their surrogates as likelihoods are accessible. In theory, we prove that inferred metrics calculated from surrogates are valid under standard statistical assumptions. In practice, we demonstrate the effectiveness of our approach using publicly available data from the Home Mortgage Disclosure Act and simulated benchmarks that mimic real-world conditions under different levels of model disparity. We extend the results from previous work to include comparisons with alternative model-based methods and we develop further practical guidance based on our extensive simulation. Finally, we embody our method in open-source software that is readily available for use in other applications.
Fuzzing and Symbolic Execution for Multipath Malware Tracing: Bridging Theory and Practice via Survey and Experiments
Authors: Botacin Marcus
Published: October 2024

In real life, distinct runs of the same artifact lead to the exploration of different paths, due to either system’s natural randomness or malicious constructions. These variations might completely change execution outcomes (extreme case). Thus, to analyze malware beyond theoretical models, we must consider the execution of multiple paths. The academic literature presents many approaches for multipath analysis (e.g., fuzzing, symbolic, and concolic executions), but it still fails to answer
What’s the current state of multipath malware tracing?
This work aims to answer this question and also to point out
What developments are still required to make them practical?
Thus, we present a literature survey and perform experiments to bridge theory and practice. Our results show that (i) natural variation is frequent; (ii) fuzzing helps to discover more paths; (iii) fuzzing can be guided to increase coverage; (iv) forced execution maximizes path discovery rates; (v) pure symbolic execution is impractical, and (vi) concolic execution is promising but still requires further developments.
On Efficient Training of Large-Scale Deep Learning Models
Authors: Shen Li , Sun Yan , Yu Zhiyuan , Ding Liang , Tian Xinmei , Tao Dacheng
Published: October 2024

The field of deep learning has witnessed significant progress in recent times, particularly in areas such as computer vision (CV), natural language processing (NLP), and speech. The use of large-scale models trained on vast amounts of data holds immense promise for practical applications, enhancing industrial productivity and facilitating social development. However, it suffers extremely from the unstable training process and stringent requirements of computational resources. With the increasing demands on the adaption of computational capacity, though numerous studies have explored the efficient training field to a certain extent, a comprehensive summarization/guideline on those general acceleration techniques of training large-scale deep learning models is still much anticipated. In this survey, we present a detailed review of the general techniques for training acceleration. We consider the fundamental update formulation and split its basic components into five main perspectives: (1) “data-centric,” including dataset regularization, data sampling, and data-centric curriculum learning techniques, which can significantly reduce the computational complexity of the data samples; (2) “model-centric,” including acceleration of basic modules, compression training, model initialization, and model-centric curriculum learning techniques, which focus on accelerating the training via reducing the calculations on parameters and providing better initialization; (3) “optimization-centric,” including the selection of learning rate, the employment of large batch size, the designs of efficient objectives, and model average techniques, which pay attention to the training policy and improving the generality for the large-scale models; (4) “budgeted training,” including some distinctive acceleration methods on source-constrained situations, e.g., for limitation on the total iterations; and (5) “system-centric,” including some efficient distributed frameworks and open source libraries that provide adequate hardware support for the implementation of the above-mentioned acceleration algorithms. By presenting this comprehensive taxonomy, our survey presents a comprehensive review to understand the general mechanisms within each component and their joint interaction. Meanwhile, we further provide a detailed analysis and discussion of future works on the development of general acceleration techniques, which could inspire us to re-think and design novel efficient paradigms. Overall, we hope that this survey will serve as a valuable guideline for general efficient training.
Development of a Versatile and Reversible Multi-Stack Solid Oxide Cell System Towards Operation Strategies Optimization
Authors: Cubizolles Géraud , Bosio Félix , Fantin Sébastien , Tantolin Christian , Alamome Simon , Champelovier Lucas , Gonzalez Brigitte , Aicart Jérôme
Published: October 2024

Solid oxide cell technology is currently rapidly industrializing. To investigate operational strategies, CEA-Liten has designed and assembled a four-stack reversible solid oxide cell (rSOC) toolbox system. Each stack comprised 25 cathode-supported cells with a 100 cm2 active area, amounting to a nominal electrolysis module power of approximately 13 kWDC at −1 A cm−2. Most of the present work reports on preliminary functional validation carried out in a two-stack configuration. Thermal losses have been quantified and their sources identified. While the hotbox is showing high intrinsic performances, the overall losses increased twofold when pass-through piping and current connections are taken into account. Module fluid distribution was verified to be homogeneous, and did not affect nominal stack operation. A test sequence of 3.5 kh is presented. Over the first 1.1 kh, the stacks behavior was similar to that of stack tested on a bench, indicating adequate control of the system. However, continued testing highlighted that stack degradation was significantly increased. A detailed analysis of efficiency was then conducted after thermal stabilization and in the nominal four-stack configuration. A maximum efficiency of 79%LHV was recorded when steam generation was excluded.
Carbonaceous C@FeS Flow Electrode for Electrochemcal Capacitive Deionization Application
Authors: Zhou Juan , Yang Ze-Qin , Yang Kang , Yuan Xia-Yue , Feng Jie , Liu Jun-Hu , Ma Xue-Jing , Zhang Wei-Bin
Published: October 2024

FeS has attracted much attention in the field of capacitive deionisation of flow electrodes due to its high theoretical specific capacity and wide range of sources. However, it usually exhibits frustrating performance due to its inherent low conductivity and volume expansion during charging and discharging. Herein, we successfully prepared calcium alginate-coated FeS carbon spheres (C@FeS) with a hollow nanosphere structure by a combination of sol-gel and solid-phase sintering using sodium alginate as a carbon source. This unique hollow structure provides enough space for the expansion of FeS and enhances the stability of the sulfide; meanwhile, the internal “surface-line-surface” structure not only facilitates the migration and charge transfer of ions inside, but also provides more active electrosorption sites. When assembled as the flow electrode of the flow electrode capacitive deionisation (FCDI) system, the desalination capacity of the electrode was improved from 25.32 mg g−1 to 53.12 mg g−1. Therefore, the C@FeS composite is expected to provide a new candidate electrode material for the FCDI system, which will make the future desalination process more cost-effective and efficient.
Cross‐Layer Greedy‐Based Routing in VANETs: Virtual Multibackbones Approach
Authors: Nabil Mohamed , El Kafhali Said , Hajami Abdelmajid , Haqiq Abdelkrim
Published: October 2024

An efficient data packet delivery in a vehicular ad hoc network (VANET) is still a challenging task because of the rapid changes in the network topology and the instability of link quality, especially for nonsafety applications. Several routing schemes are proposed to improve the reliability of data delivery between vehicles. These protocols still suffer from the growth of the data packet delivery delay, the lost data packets, and the control packets. For this reason, we propose a novel cross‐layer routing protocol, which is the first that uses virtual multibackbones and combines them with the quality of the link to choose the next forwarder vehicle. The next candidate forwarders, among neighbors, are those that keep a minimum of link quality during the data packet delivery delay. Then, among these candidates, we select that is closest to the destination vehicle to receive and forward the data. In addition, our proposal gives priority to those that travel toward the destination vehicle avoiding the forwarding of data several times by the same vehicle. The substantial simulations show that our protocol outperforms certain of the well‐known existing schemes in the VANET area by varying the vehicle density on the highway. It exhibits an improvement of 6.72% in the average end‐to‐end delay of data delivery, 14.44% in the packet delivery ratio, 11.2% in the throughput, and 6.4% in the control overhead as compared to other schemes.
SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors
Authors: Liu Xinyi , Tang Gongyu , Chen Yuhao , Li Yuanxiang , Li Hua , Wang Xiaowei
Published: October 2024

The rapid development of spatial transcriptomics (ST) technologies has enabled transcriptome-wide profiling of gene expression in tissue sections. Despite the emergence of single-cell resolution platforms, most ST sequencing studies still operate at a multicell resolution. Consequently, deconvolution of cell identities within the spatial spots has become imperative for characterizing cell-type–specific spatial organization. To this end, we developed Spatial Deconvolution Explorer (SpatialDeX), a regression model–based method for estimating cell-type proportions in tumor ST spots. SpatialDeX exhibited comparable performance to reference-based methods and outperformed other reference-free methods with simulated ST data. Using experimental ST data, SpatialDeX demonstrated superior performance compared with both reference-based and reference-free approaches. Additionally, a pan-cancer clustering analysis on tumor spots identified by SpatialDeX unveiled distinct tumor progression mechanisms both within and across diverse cancer types. Overall, SpatialDeX is a valuable tool for unraveling the spatial cellular organization of tissues from ST data without requiring single-cell RNA-seq references.

Significance: The development of a reference-free method for deconvolving the identity of cells in spatial transcriptomics datasets enables exploration of tumor architecture to gain deeper insights into the dynamics of the tumor microenvironment.
Association between Immune-Related Adverse Events and Atezolizumab in Previously Treated Patients with Unresectable Advanced or Recurrent Non–Small Cell Lung Cancer
Authors: Hayashi Hidetoshi , Nishio Makoto , Akamatsu Hiroaki , Goto Yasushi , Miura Satoru , Gemma Akihiko , Yoshino Ichiro , Misumi Toshihiro , Kijima Takashi , Takase Naoto , Fujita Masaki , Tasaka Sadatomo , Mouri Atsuto , Kondo Tetsuro , Takamura Kei , Kawashima Yosuke , Imaizumi Kazuyoshi , Iwasawa Shunichiro , Nakagawa Shintaro , Mitsudomi Tetsuya
Published: October 2024

Purpose:

Real-world, large-scale studies on the association between immune-related adverse events (irAE) and immune checkpoint inhibitor therapy effectiveness are limited. We evaluated overall survival (OS) and progression-free survival based on the occurrence and grade of irAEs.

Patients and Methods:

We used data from Japanese patients with unresectable advanced or recurrent non–small cell lung cancer (NSCLC) who received atezolizumab and were enrolled in J-TAIL, a multicenter, prospective, single-arm observational study.

Results:

Among the 1,002 patients, 190 (19.0%) developed irAEs. The most common irAEs were skin disorders (3.8%) of any grade and interstitial lung disease (1.5%) of grade ≥3. Patients who developed irAEs within 4 or 6 weeks of treatment initiation had higher baseline C-reactive protein levels than those without irAEs. OS was longer in patients with irAEs [HR, 0.66; 95% confidence interval (CI), 0.54–0.82], particularly in those with low-grade irAEs (HR, 0.45; 95% CI, 0.33–0.62), than in patients without irAEs. The HR (95% CI) for OS in patients with low-grade and high-grade skin or endocrine disorder–related irAEs was 0.42 (0.28–0.64) and 0.37 (0.15–0.88), respectively. The HR (95% CI) for OS in patients with low-grade and high-grade irAEs other than skin or endocrine disorders was 0.44 (0.30–0.65) and 1.27 (0.96–1.69), respectively.

Conclusions:

In patients with unresectable advanced or recurrent NSCLC treated with atezolizumab in real-world settings, irAEs are associated with a clinical benefit except in those with high-grade irAEs other than skin and endocrine disorders.

Significance:

Immune checkpoint inhibitors are useful for treating NSCLC but can cause life-threatening irAEs. This study had a large sample size and stratified the analysis by irAE type and grade. The results suggest that improved management of irAEs may improve the therapeutic effect of atezolizumab.
Genomic Features of Newly Diagnosed Large B-cell Lymphoma with or without Subsequent Disease Progression
Authors: Landsburg Daniel J. , Morrissette Jennifer J.D. , Nasta Sunita D. , Barta Stefan K. , Schuster Stephen J. , Chong Elise A. , Svoboda Jakub , Barlev Ashley , Bagg Adam , Priore Salvatore F.
Published: October 2024

Genomic analysis has the potential to both risk-stratify and inform management of patients diagnosed with large B-cell lymphomas (LBCL). We analyzed cases of patients with newly diagnosed LBCL treated with standard immunochemotherapy from three publicly available cohorts of patients on which FISH and next-generation sequencing were performed to determine the frequency of genomic alterations based upon the development of disease progression. Cases from 698 patients were analyzed, with 201 experiencing disease progression and 497 experiencing no disease progression by 24 months after diagnosis. When analyzing for the presence of MYC rearrangement and MYC–BCL2 dual-rearrangement/double-hit status, as well as variants predicted to result in alterations in protein function in 15 genes common to next-generation sequencing panels from all three cohorts, only MYC rearrangement and TP53 mutation were associated with significantly higher odds of disease progression on multivariate analysis. Additionally, cases from patients who experienced disease progression demonstrated a high frequency of specific genomic alterations when analyzed by cohort or cell-of-origin classification by IHC when available. Individual genomic features of LBCL cases may predict for the development of disease progression in newly diagnosed patients treated with standard therapies, as well as occur at higher frequencies in cases of disease progression based upon geographic region and/or cell-of-origin status. These novel findings support efforts to evaluate genomic features as biomarkers for response to specific therapies in subsets of patients with LBCL who experience disease progression, which may lead to discovery of more effective treatment options.

Significance:

Genomic features of LBCL that can be detected by clinical laboratory assays may predict for resistance to first-line immunochemotherapy, as well as support the exploration of genomic features as biomarkers of response to therapies which could be offered to patients who experience disease progression.
Development and in vitro Evaluation of Cannabidiol Mucoadhesive Buccal Film Formulations Using Hot-Melt Extrusion Technology
Authors: Taha Iman E. , ElSohly Mahmoud A. , Radwan Mohamed M. , Omari Sundus , Repka Michael A. , Ashour Eman A.
Published: October 2024

Introduction: Cannabidiol (CBD) has sparked considerable interest because of its wide range of pharmacological uses and the fact that it does not induce psychoactive effects. CBD formulation development presents significant challenges due to its limited water solubility and susceptibility to first-pass metabolism, both of which restrict its overall bioavailability. The current research aimed to use hot-melt extrusion (HME) technology to develop mucoadhesive buccal films to improve CBD solubility and reduce first-pass metabolism. Methods: Five formulations containing 10% w/w CBD were extruded using a counter-rotating twin-screw extruder (Haake Minilab II, Thermo Fisher Scientific). Different characterization studies were conducted on the developed formulations. Results: Differential scanning calorimetry (DSC) revealed that the CBD endothermic peak disappeared in some of the developed films, indicating that CBD was converted from crystalline to amorphous form. A bio-adhesion study showed that the formulations containing Carbopol® (BF2, BF3, BF4, and BF5) had higher adhesiveness properties. In vitro release and solubility studies showed an increase in CBD release and water solubility in the developed formulations when compared to pure CBD. Stability studies revealed that CBD content and release in the lead formulation (BF2) was stable over 15 months. Conclusion: The current study demonstrates that HME was successfully used as an approach to develop CBD mucoadhesive buccal films and CBD solubility was enhanced.
Picking a Side: Preferential Laterality in Scalp Hair Density
Authors: Duong Amanda N. , Kincaid Colin , Phong Celine , Babadjouni Arash , Mesinkovska Natasha Atanaskova
Published: October 2024

Introduction: Clinical examinations of the scalp have shown that patients may grow hair preferentially at higher density on one side of their scalp, yet review of the literature to date has not yield studies that directly assess differences in scalp hair density laterality. The objective of this study was to examine whether scalp hair growth occurs preferentially and on which side of the scalp, the right or left, in healthy patients. Method: Scalps of healthy subjects with no history of hair loss or scalp disease were imaged with digital trichoscopy at a university dermatology clinic. Bilateral temporal photos were uploaded to trichoscopy software for quantitative analysis. Results: Scalp hair laterality was observed in both male and female, with no trend in left or right preference. While subjects who identified as Asian or Hispanic exhibited a strong laterality preference, statistical significance was not reached among African American or Caucasian subjects. Conclusion: No overall side preference was observed in the study population, yet many of the healthy individuals tend to preferentially grow more hair on one side of their scalp. It is possible that in addition to genetics, certain behavioral or environmental factors may play a role in laterality.
Light Exposure on Alertness after Wake-Up in Healthy Men: Comparing Dim, Bright, Red, and Blue Light
Authors: Mekschrat Liza , Straßer Torsten , Ghassabei Shiwa , Schmalbach Bjarne , Niedling Mathias , Petrowski Katja
Published: October 2024

Introduction: Light is a key factor in moderating human alertness, both subjective and objective. However, the methodology applies in research on the effects of exposure to light of different wavelengths and intensities on objective and subjective alertness varies greatly and evidence on objective alertness in particular is still inconclusive. Thus, the present, highly standardized within-subject laboratory study on N = 44 healthy males explored how LED light of different intensities (dim vs. bright light) and wavelengths (red vs. blue) affected objective (reaction time/RT) as well as subjective (sleepiness) alertness in the morning after wake-up. Methods: Participants spent two separate nights in the laboratory and were exposed to either one of the two light intensities or colors for 60 min after wake-up. Additionally, they indicated their sleepiness on the Karolinska Sleepiness Scale and participated in an auditory RT task before and after light intervention. It was hypothesized that both bright and blue light would lead to greater subjective and objective alertness when compared to dim and red light, respectively. Results: Results indicated that average RTs were longer for participants in the bright light condition (p = 0.004, f2 = 0.07) and that RTs decreased post-light exposure irrespective of light being dim or bright (p = 0.026, f2 = 0.07). However, dim versus bright light and RT did not interact (p = 0.758, f2 = 0.07). Chronotype was a significant covariate in the interaction of dim versus bright light and subjective sleepiness (p = 0.008, f2 = 0.22). There was no difference in RTs when comparing exposure to red or blue light (p = 0.488, f2 = 0.01). Findings on subjective sleepiness and light of different wavelengths revealed that sleepiness was reduced after light exposure (p = 0.007, f2 = 0.06), although the wavelength of light did not appear to play a role in this effect (p = 0.817, f2 = 0.06). Conclusion: Hence, neither of the hypotheses could be confirmed. However, they indicated that evening types might benefit from exposure to bright light regarding sleepiness, but not morning types.
Evaluation of the Environmental Risk Factors and Comorbidities in Patients with Lichen Planopilaris: A Case-Control Study
Authors: Mahmoudi Fahimeh , Moravvej Hamideh , Nasiri Soheila , Pourgholi Elnaz , Yazdanshenas Atousa , Dadkhahfar Sahar
Published: October 2024

Introduction: Lichen planopilaris (LPP) is an uncommon cicatricial alopecia clinically characterized by follicular hyperkeratosis, perifollicular erythema, and permanent hair loss. The association of LPP with certain underlying diseases and environmental factors has been evaluated but there are limited data about this association. This study was designated to evaluate the environmental risk factors and comorbidities in LPP patients. Method: This case-control study was performed on LPP patients referred to two dermatology referral centers from 2019 to 2022. A group of non-LPP healthy individuals referring for cosmetic concerns was recruited as control group. Data collection was performed using two questionnaires: a general questionnaire, including demographic information, comorbidities, environmental risk factors, and disease-related information, and the lichen planopilaris activity index (LPPAI) questionnaire. Results: One hundred LPP patients as case group were compared with 100 healthy people without LPP as control group. Unemployment, history of major stressful events, thyroid disorder, history of hair dyeing, using face soaps, taking supplements, postmenopausal status, and family history of LPP or other types of alopecia had significant relationship with LPP (all p values <0.05). Conclusion: LPP has associations with environmental and non-environmental risk factors and, also, genetic component.
Preemptive Transjugular Intrahepatic Portosystemic Shunt in Variceal Bleeding: A Real-World Study in a Tertiary Hospital
Authors: Silva Andrea , Perdigoto David , Feijó Diogo , Lucas João , Oliveira Tiago , Donato Paulo , Figueiredo Pedro Narra
Published: October 2024

Introduction: Several studies have highlighted the potential benefits of early prophylactic transjugular intrahepatic portosystemic shunt (preemptive TIPS) placement in reducing morbidity and mortality following variceal bleeding (VB). Baveno VII recommends its placement less than 72 h after VB (Child-Pugh class C <14 or class B >7 plus active bleeding). This study aimed to evaluate the effectiveness of preemptive TIPS compared to a control group in a referral center. Methods: The control group included cirrhotic patients with VB and Child-Pugh class C or B with active bleeding, retrospectively selected between 2016 and 2022 and divided into 2 subgroups: those that never underwent TIPS placement during the course of their illness (subgroup A) and those submitted to TIPS placement due to rebleeding (subgroup B). Additionally, patients who received preemptive TIPS placement between August 2022 and January 2024 were prospectively included into the preemptive transjugular intrahepatic portosystemic shunt (pTIPS) group. Results: A total of 47 patients were included, 19 (40.4%) in the pTIPS group and 28 (59.6%) in control group (17 in subgroup A). There were no differences in baseline characteristics between the groups, except hepatic encephalopathy that was significantly higher in the control group when compared to the pTIPS group: 19 (67.9%) versus 6 (31.6%), p = 0.014. Early rebleeding rates were significantly lower in the pTIPS group: 1 (5.3%) versus 13 (46.4%) (p = 0.002). There were no significant differences in 6-week survival between the groups: 25 (89.3%) versus 17 (89.5%), p = 0.683. Regarding hepatic encephalopathy, no significant differences were observed between the control and the pTIPS group: 6 (21.4%) versus 4 (21.1%), p = 0.632, even when comparing subgroup A (4, 23.5%) with the pTIPS group (p = 0.432). Conclusion: This real-world study highlights the potential benefits of preemptive TIPS placement in reducing early relapse of VB, thereby lowering morbidity and complications. The findings advocate for the proactive incorporation of preemptive TIPS into clinical practice to optimize patient outcomes following VB.
Ultrarare Variants in DNA Damage Repair Genes in Pediatric Acute-Onset Neuropsychiatric Syndrome or Acute Behavioral Regression in Neurodevelopmental Disorders
Authors: Cunningham Janet L. , Frankovich Jennifer , Dubin Robert A. , Pedrosa Erika , Baykara Refia Nur , Schlenk Noelle Cathleen , Maqbool Shahina B. , Dolstra Hedwig , Marino Jacqueline , Edinger Jacob , Shea Julia M. , Laje Gonzalo , Swagemakers Sigrid M.A. , Sinnadurai Siamala , Zhang Zhengdong D. , Lin Jhih-Rong , van der Spek Peter J. , Lachman Herbert M.
Published: October 2024

Introduction: Acute onset of severe psychiatric symptoms or regression may occur in children with premorbid neurodevelopmental disorders, although typically developing children can also be affected. Infections or other stressors are likely triggers. The underlying causes are unclear, but a current hypothesis suggests the convergence of genes that influence neuronal and immunological function. We previously identified 11 genes in pediatric acute-onset neuropsychiatric syndrome (PANS), in which two classes of genes related to either synaptic function or the immune system were found. Among the latter, three affect the DNA damage response (DDR): PPM1D, CHK2, and RAG1. We now report an additional 17 cases with mutations in PPM1D and other DDR genes in patients with acute onset of psychiatric symptoms and/or regression that their clinicians classified as PANS or another inflammatory brain condition. Methods: We analyzed genetic findings obtained from parents and carried out whole-exome sequencing on a total of 17 cases, which included 3 sibling pairs and a family with 4 affected children. Results: The DDR genes include clusters affecting p53 DNA repair (PPM1D, ATM, ATR, 53BP1, and RMRP), and the Fanconi Anemia Complex (FANCE, SLX4/FANCP, FANCA, FANCI, and FANCC). We hypothesize that defects in DNA repair genes, in the context of infection or other stressors, could contribute to decompensated states through an increase in genomic instability with a concomitant accumulation of cytosolic DNA in immune cells triggering DNA sensors, such as cGAS-STING and AIM2 inflammasomes, as well as central deficits on neuroplasticity. In addition, increased senescence and defective apoptosis affecting immunological responses could be playing a role. Conclusion: These compelling preliminary findings motivate further genetic and functional characterization as the downstream impact of DDR deficits may point to novel treatment strategies.
Therapeutic Drug Monitoring of Imatinib: Is There a Rationale for Also Quantifying Its Active Metabolite?
Authors: Eschalier Clara , Lafont Thierry , Marsili Sabrina , Yakoubi Malika , Brice Aurélie , Thomas Fabienne , White-Koning Mélanie , Allal Ben , Chatelut Etienne
Published: October 2024

Introduction: Therapeutic drug monitoring of imatinib is widely performed to individualize imatinib dosage. While N-desmethyl imatinib is an active metabolite of imatinib, its concentrations are not routinely determined. Methods: Imatinib and N-desmethyl imatinib trough plasma concentrations at steady-state were obtained from 295 patients with either chronic myeloid leukemia or gastrointestinal stromal tumor to see whether N-desmethyl imatinib provided additional information. Pharmacokinetic data were analyzed using a nonlinear mixed effect approach. Correlations between several pharmacokinetic metrics of drug exposure were evaluated. Results: The mean value of the N-desmethyl imatinib/imatinib ratio of trough concentrations was 0.31 with half of the values between 0.23 and 0.37. N-desmethyl imatinib and total (i.e., N-desmethyl imatinib plus imatinib) trough plasma concentrations or area under the curve values were closely correlated with imatinib values. The distribution of imatinib or total concentrations between patients requiring imatinib dosage adjustment, or not, was similar. Conclusion: These results do not clearly support routine N-desmethyl monitoring since it does not provide additional information to imatinib data.
Utility of 3-Dimensional Modeling in Prenatally Diagnosed Large Fetal Neck Mass
Authors: Joshi Devashish S. , Stellon Michael A. , Puricelli Michael D. , Beninati Michael J. , Garcia-Rodriguez Sylvana , Winchester Casey , Chapman Teresa , Lobeck Inna N.
Published: October 2024

Introduction: Prenatally diagnosed large fetal neck mass requires multidisciplinary consultation and evaluation of perinatal treatment options. The decision to perform ex utero intrapartum treatment (EXIT) is based on risk-benefit assessment for both the infant and mother. Though fetal ultrasound and MRI assist with operative planning, a three-dimensional anatomic model offers improved anatomic visualization and prenatal patient counseling. Case Presentation: Multiple surveillance ultrasound exams between gestational weeks 16 and 32 plus fetal MRI at 29/3 weeks were performed for fetal evaluation. A 3-dimensional model was printed (Form 3 and 3L, clear resin, Formlabs) incorporating fetal MRI (Ax SSFSE TE 100 DL and Cor SSFSE Brain DL) and using Mimics Medical and 3-matic Medical software (Materialise). A left fetal multicystic neck mass measuring 2.1 × 1.8 × 1.5 cm was diagnosed at 16/6 weeks gestation in a G8P2416. Fetal MRI performed at 29/3 weeks showed a large exophytic mixed solid-cystic cervicofacial mass, 10.3 × 9.4 × 10.6 cm arising from the left mandible, concerning for a teratoma. Prior to delivery, the model was used to educate and counsel the family regarding the complex clinical situation and the reasoning for delivery via EXIT followed by mass resection. Additionally, the model demonstrated tracheal narrowing and oropharyngeal compression, supporting airway intervention planning. The fetus was delivered at 32/3 weeks via EXIT to intubation using rigid bronchoscopy. Duration of time on placental support was 12 min. On day of life 5, the patient underwent resection of the cervical mass. Pathology revealed an immature teratoma, histologic grade 3 without yolk sac elements, and negative regional lymph nodes. Conclusion: Three-dimensional fetal modeling facilitates perinatal airway needs assessment, patient counseling, delivery, and postnatal management.
Performance of a Protein Language Model for Variant Annotation in Cardiac Disease
Authors: Hochstadt Aviram , Barbhaiya Chirag , Aizer Anthony , Bernstein Scott , Cerrone Marina , Garber Leonid , Holmes Douglas , Knotts Robert J. , Kushnir Alex , Martin Jacob , Park David , Spinelli Michael , Yang Felix , Chinitz Larry A. , Jankelson Lior
Published: October 2024

Background

Genetic testing is a cornerstone in the assessment of many cardiac diseases. However, variants are frequently classified as variants of unknown significance, limiting the utility of testing. Recently, the DeepMind group (Google) developed AlphaMissense, a unique artificial intelligence–based model, based on language model principles, for the prediction of missense variant pathogenicity. We aimed to report on the performance of AlphaMissense, accessed by VarCardio, an open web‐based variant annotation engine, in a real‐world cardiovascular genetics center.

Methods and Results

All genetic variants from an inherited arrhythmia program were examined using AlphaMissense via VarCard.io and compared with the ClinVar variant classification system, as well as another variant classification platform (Franklin by Genoox). The mutation reclassification rate and genotype–phenotype concordance were examined for all variants in the study. We included 266 patients with heritable cardiac diseases, harboring 339 missense variants. Of those, 230 (67.8%) were classified by ClinVar as either variants of unknown significance or nonclassified. Using VarCard.io, 198 variants of unknown significance (86.1%, 95% CI, 80.9–90.3) were reclassified to either likely pathogenic or likely benign. The reclassification rate was significantly higher for VarCard.io than for Franklin (86.1% versus 34.8%,
P
<0.001). Genotype–phenotype concordance was highly aligned using VarCard.io predictions, at 95.9% (95% CI, 92.8–97.9) concordance rate. For 109 variants classified as pathogenic, likely pathogenic, benign, or likely benign by ClinVar, concordance with VarCard.io was high (90.5%).

Conclusions

AlphaMissense, accessed via VarCard.io, may be a highly efficient tool for cardiac genetic variant interpretation. The engine's notable performance in assessing variants that are classified as variants of unknown significance in ClinVar demonstrates its potential to enhance cardiac genetic testing.