bluuebunny/crossref_metadata_2025 huggingface dataset:
Behavioral Modeling and its Association with PrEP and ART Use in Ugandan HIV-Serodifferent Couples
Authors: Wang Liying , Muwonge Timothy R. , Simoni Jane M. , Nambi Florence , Nakabugo Lylianne , Kibuuka Joseph , Thomas Dorothy , Katz Ingrid T. , Feutz Erika , Thomas Katherine K. , Ware Norma C. , Wyatt Monique A. , Kadama Herbert , Mujugira Andrew , Heffron Renee ,   For the Partners PrEP Program Study Team
Published: February 2024

Integrating Pre-Exposure Prophylaxis (PrEP) delivery into Antiretroviral Therapy (ART) programs bridges the Human Immunodeficiency Virus (HIV) prevention gap for HIV-serodifferent couples prior to the partner living with HIV achieving viral suppression. Behavioral modeling is one mechanism that could explain health-related behavior among couples, including those using antiretroviral medications, but few tools exist to measure the extent to which behavior is modeled. Using a longitudinal observational design nested within a cluster randomized trial, this study examined the factor structure and assessed the internal consistency of a novel 24-item, four-point Likert-type scale to measure behavioral modeling and the association of behavioral modeling with medication-taking behaviors among heterosexual, cis-gender HIV-serodifferent couples. In 149 couples enrolled for research, a five-factor model provided the best statistical and conceptual fit, including attention to partner behavior, collective action, role modeling, motivation, and relationship quality. Behavioral modeling was associated with medication-taking behaviors among members of serodifferent couples. Partner modeling of ART/PrEP taking could be an important target for assessment and intervention in HIV prevention programs for HIV serodifferent couples.
Energy-efficient scheduling model and method for assembly blocking permutation flow-shop in industrial robotics field
Authors: Kong Min , Wu Peng , Zhang Yajing , Wang Weizhong , Deveci Muhammet , Kadry Seifedine
Published: February 2024

Implementing green and sustainable development strategies has become essential for industrial robot manufacturing companies to fulfill their societal obligations. By enhancing assembly efficiency and minimizing energy consumption in workshops, these enterprises can differentiate themselves in the fiercely competitive market landscape and ultimately bolster their financial gains. Consequently, this study focuses on examining the collaborative assembly challenges associated with three crucial parts: the body, electrical cabinet, and pipeline pack, within the industrial robot manufacturing process. Considering the energy consumption during both active and idle periods of the industrial robot workshop assembly system, this paper presents a multi-stage energy-efficient scheduling model to minimize the total energy consumption. Two classes of heuristic algorithms are proposed to address this model. Our contribution is the restructuring of the existing complex mathematical programming model, based on the structural properties of scheduling sub-problems across multiple stages. This reformation not only effectively reduces the variable scale and eliminates redundant constraints, but also enables the Gurobi solver to tackle large-scale problems. Extensive experimental results indicate that compared to traditional workshop experience, the constructed green scheduling model and algorithm can provide more precise guidance for the assembly process in the workshop. Regarding total energy consumption, the assembly plans obtained through our designed model and algorithm exhibit approximately 3% lower energy consumption than conventional workshop experience-based approaches.
Sex-steroid hormones and risk of postmenopausal estrogen receptor-positive breast cancer: a case–cohort analysis
Authors: Albers Frances E. M. , Lou Makayla W. C. , Dashti S. Ghazaleh , Swain Christopher T. V. , Rinaldi Sabina , Viallon Vivian , Karahalios Amalia , Brown Kristy A. , Gunter Marc J. , Milne Roger L. , English Dallas R. , Lynch Brigid M.
Published: February 2024

Purpose

Sex-steroid hormones are associated with postmenopausal breast cancer but potential confounding from other biological pathways is rarely considered. We estimated risk ratios for sex-steroid hormone biomarkers in relation to postmenopausal estrogen receptor (ER)-positive breast cancer, while accounting for biomarkers from insulin/insulin-like growth factor-signaling and inflammatory pathways.

Methods

This analysis included 1208 women from a case–cohort study of postmenopausal breast cancer within the Melbourne Collaborative Cohort Study. Weighted Poisson regression with a robust variance estimator was used to estimate risk ratios (RRs) and 95% confidence intervals (CIs) of postmenopausal ER-positive breast cancer, per doubling plasma concentration of progesterone, estrogens, androgens, and sex-hormone binding globulin (SHBG). Analyses included sociodemographic and lifestyle confounders, and other biomarkers identified as potential confounders.

Results

Increased risks of postmenopausal ER-positive breast cancer were observed per doubling plasma concentration of progesterone (RR: 1.22, 95% CI 1.03 to 1.44), androstenedione (RR 1.20, 95% CI 0.99 to 1.45), dehydroepiandrosterone (RR: 1.15, 95% CI 1.00 to 1.34), total testosterone (RR: 1.11, 95% CI 0.96 to 1.29), free testosterone (RR: 1.12, 95% CI 0.98 to 1.28), estrone (RR 1.21, 95% CI 0.99 to 1.48), total estradiol (RR 1.19, 95% CI 1.02 to 1.39) and free estradiol (RR 1.22, 95% CI 1.05 to 1.41). A possible decreased risk was observed for SHBG (RR 0.83, 95% CI 0.66 to 1.05).

Conclusion

Progesterone, estrogens and androgens likely increase postmenopausal ER-positive breast cancer risk, whereas SHBG may decrease risk. These findings strengthen the causal evidence surrounding the sex-hormone-driven nature of postmenopausal breast cancer.
Effects of UV irradiation of TEMPO-oxidized cellulose nanofibril/water dispersions on chemical structure, molar mass, and morphology
Authors: Ning Ruizhi , Ono Yuko , Isogai Akira
Published: February 2024

A commercial TEMPO-oxidized cellulose (TOC) and three laboratory-made TOC samples prepared under different conditions were converted to aqueous 0.4% dispersions of TEMPO-oxidized cellulose nanofibrils (TEMPO-CNFs) by high-pressure homogenization in water under the same conditions. The obtained TEMPO-CNF/water dispersions were irradiated with ultraviolet (UV) light for 0–48 h using a high-pressure mercury lamp at a main wavelength of 365 nm. The changes in the light transmittance, viscosity, pH, zeta-potential, and average particle size of the dispersions, and mass recovery ratio, molar mass, and carboxylate content of the acid-insoluble and freeze-dried fractions separated and isolated from the UV-irradiated dispersions were investigated. The results were analyzed in terms of the UV-irradiation time. The dispersion pH, and the mass recovery ratio, carboxylate content, and mass-average degree of polymerization (DPw) of the acid-soluble fraction decreased with increasing UV-irradiation time. This shows that some acid-soluble acidic compounds were formed from the TEMPO-CNFs via UV-induced depolymerization, degradation, and removal of carboxylate groups from the TEMPO-CNFs in water, depending on the UV-irradiation time. The average CNF length, which was determined from atomic force microscopy images, decreased with increasing UV-irradiation time. After UV irradiation of dispersions of the laboratory-made TEMPO-CNFs for 12 h, the average CNF lengths were 130–150 nm and their length distributions were narrower. UV irradiation of TEMPO-CNF/water dispersions is therefore a promising method for efficiently decreasing the dispersion viscosity, DPw, and average CNF length, depending on the TEMPO-CNF properties and UV-irradiation conditions.

Graphical abstract
Roles of HOTAIR Long Non-coding RNA in Gliomas and Other CNS Disorders
Authors: Ahmad Faraz , Sudesh Ravi , Ahmed A. Toufeeq , Haque Shafiul
Published: February 2024

HOX transcript antisense intergenic RNA (HOTAIR) is a long non-coding RNA (lncRNA) which is increasingly being perceived as a tremendous molecular mediator of brain pathophysiology at multiple levels. Epigenetic regulation of target gene expression carried out by HOTAIR is thorough modulation of chromatin modifiers; histone methyltransferase polycomb repressive complex 2 (PRC2) and histone demethylase lysine-specific demethylase 1 (LSD1). Incidentally, HOTAIR was the first lncRNA shown to elicit sponging of specific microRNA (miRNA or miR) species in a trans-acting manner. It has been extensively studied in various cancers, including gliomas and is regarded as a prominent pro-tumorigenic and pro-oncogenic lncRNA. Indeed, the expression of HOTAIR may serve as glioma grade predictor and prognostic biomarker. The objective of this timely review is not only to outline the multifaceted pathogenic roles of HOTAIR in the development and pathophysiology of gliomas and brain cancers, but also to delineate the research findings implicating it as a critical regulator of overall brain pathophysiology. While the major focus is on neuro-oncology, wherein HOTAIR represents a particularly potent underlying pathogenic player and a suitable therapeutic target, mechanisms underlying the regulatory actions of HOTAIR in neurodegeneration, traumatic, hypoxic and ischemic brain injuries, and neuropsychiatric disorders are also presented.

Graphical Abstract

HOTAIR-mediated epigenetic DNA regulation and molecular sponging of target miRNAs. While the 5′ end of HOTAIR regulates the H3K27 trimethylation activity of the catalytic subunit enhancer of Zeste homolog 2 (EZH2) of the polycomb repressive complex 2 (PRC2), its 3′ end modulates the H3K4 demethylation activity of lysine-specific demethylase 1 (LSD1). HOTAIR also binds to and competitively inhibits the functions of target miRNAs, altering the expression of downstream genes.
Healing Landscapes and Grieving Eco-Warriors: Climate Activism in Children’s Literature
Authors: Murphy Emily
Published: February 2024

Children, we are told, are becoming more anxious. But what are they anxious about? Recent studies on “climate anxiety” suggest that the current climate crisis is at the top of children and young people’s concerns and is being expressed in the form of grief. This essay considers a growing body of climate fiction for children that links personal grief to planetary grief as a way of developing children’s ecological consciousness and putting them on the path towards climate activism. It examines Sarah Baughman’s The Light in the Lake (2019) while tracing the historical and literary roots of this trend in literature for the young. Drawing on research in the interdisciplinary field of ecopsychology, the author argues that children’s authors are increasingly drawing on tropes of ecological fiction in order to respond to the current climate crisis and offer young readers models of activism that will address this major global issue.
Routine Sensitive Enquiry of Adult Interpersonal Trauma in Community Mental Health Teams: An Audit of the Initial Assessment Tool
Authors: Hill Natasha , Graham Nicholas , Forrester Rebecca L.
Published: February 2024

This audit aimed to evaluate the utility of the Initial Assessment Tool (IAT) in documenting routine sensitive enquiry of adult interpersonal trauma within three Community Mental Health Teams (CMHTs) in North-East Glasgow. In addition, it sought to evaluate if disclosures informed patient risk assessments and if patients were signposted to additional support services. 57% of 90 IATs had evidence of routine sensitive enquiry. Of 51 casefiles with evidence of routine sensitive enquiry, 61% had evidence of the information informing their risk assessments and 14% had documented recommendations of support organisations. The IAT appeared able to assist clinicians with routine sensitive enquiry in adulthood. However, there may be advantage in supporting staff understanding of how to ask questions to specific populations and to use this information to inform treatment planning. Given the prevalence of adult interpersonal trauma experienced by patients presenting to CMHTs, trauma-informed approaches to care should be implemented.
Constructing Optimal Portfolio Rebalancing Strategies with a Two-Stage Multiresolution-Grid Model
Authors: Dai Tian-Shyr , Chen Bo-Jen , Sun You-Jia , Yang Dong-Yuh , Wu Mu-En
Published: February 2024

Sophisticated predetermined ratios are used to allocate portfolio asset weights to strike a good trade-off between profitability and risk in trading. Rebalancing these weights due to market fluctuations without incurring excessive transaction costs and tracking errors is a vital financial engineering problem. Rebalancing strategies can be modeled by discretely enumerating portfolio weights to form a grid space and then optimized via the Bellman equation. Discretization errors are reduced by increasing the grid resolution at the cost of increased computational time. To minimize errors with constrained computational resources (e.g., grid nodes), we vary the grid resolution according to the probability distribution of asset weights. Specifically, a grid space is first divided into several areas, and each area’s probability is estimated. Then, the discretization error’s upper bound is minimized by inserting an adequate number of grid nodes determined by Lagrange multipliers in a non-uniform fashion. In experiments, the proposed multiresolution rebalancing outperforms traditional uniform-resolution rebalancing and popular benchmark strategies such as the periodic, tolerance-band, and buy-and-hold strategies.
Novel adaptive quantization methodology for 8-bit floating-point DNN training
Authors: Hassani Sadi Mohammad , Sudarshan Chirag , Wehn Norbert
Published: February 2024

There is a high energy cost associated with training Deep Neural Networks (DNNs). Off-chip memory access contributes a major portion to the overall energy consumption. Reduction in the number of off-chip memory transactions can be achieved by quantizing the data words to low data bit-width (E.g., 8-bit). However, low-bit-width data formats suffer from a limited dynamic range, resulting in reduced accuracy. In this paper, a novel 8-bit Floating Point (FP8) data format quantized DNN training methodology is presented, which adapts to the required dynamic range on-the-fly. Our methodology relies on varying the bias values of FP8 format to fit the dynamic range to the required range of DNN parameters and input feature maps. The range fitting during the training is adaptively performed by an online statistical analysis hardware unit without stalling the computation units or its data accesses. Our approach is compatible with any DNN compute cores without any major modifications to the architecture. We propose to integrate the new FP8 quantization unit in the memory controller. The FP32 data from the compute core are converted to FP8 in the memory controller before writing to the DRAM and converted back after reading the data from DRAM. Our results show that the DRAM access energy is reduced by 3.07$$\times $$
×
while using an 8-bit data format instead of using 32-bit. The accuracy loss of the proposed methodology with 8-bit quantized training is $$\approx 1\%$$

≈
1
%

for various networks with image and natural language processing datasets.
Profiling with trust: system monitoring from trusted execution environments
Authors: Eichler Christian , Röckl Jonas , Jung Benedikt , Schlenk Ralph , Müller Tilo , Hönig Timo
Published: February 2024

Large-scale attacks on IoT and edge computing devices pose a significant threat. As a prominent example, Mirai is an IoT botnet with 600,000 infected devices around the globe, capable of conducting effective and targeted DDoS attacks on (critical) infrastructure. Driven by the substantial impacts of attacks, manufacturers and system integrators propose Trusted Execution Environments (TEEs) that have gained significant importance recently. TEEs offer an execution environment to run small portions of code isolated from the rest of the system, even if the operating system is compromised. In this publication, we examine TEEs in the context of system monitoring and introduce the Trusted Monitor (TM), a novel anomaly detection system that runs within a TEE. The TM continuously profiles the system using hardware performance counters and utilizes an application-specific machine-learning model for anomaly detection. In our evaluation, we demonstrate that the TM accurately classifies 86% of 183 tested workloads, with an overhead of less than 2%. Notably, we show that a real-world kernel-level rootkit has observable effects on performance counters, allowing the TM to detect it. Major parts of the TM are implemented in the Rust programming language, eliminating common security-critical programming errors.
Fair concordance between Google Trends and Danish ornithologists in the assessment of temporal trends in Danish bird populations highlights the informational value of big data
Authors: Jensen Per M. , Danielsen Finn , Jacobsen Stine K. , Vikstrøm Thomas
Published: February 2024

The ongoing depletion of natural systems and associated biodiversity decline is of growing international concern. Climate change is expected to exacerbate anthropogenic impacts on wild populations. The scale of impact on ecosystems and ecosystem services will be determined by the impact on a multitude of species and functional groups, which due to their biology and numbers are difficult to monitor. The IPCC has argued that surveillance or monitoring is critical and proposed that monitoring systems should be developed, which not only track developments but also function as “early warning systems.” Human populations are already generating large continuous datasets on multiple taxonomic groups through internet searches. These time series could in principle add substantially to current monitoring if they reflect true changes in the natural world. We here examined whether information on internet search frequencies delivered by the Danish population and captured by Google Trends (GT) appropriately informs on population trends in 106 common Danish bird species. We compared the internet search activity with independent equivalent population trend assessments from the Danish Ornithological Society (BirdLife Denmark/DOF). We find a fair concordance between the GT trends and the assessments by DOF. A substantial agreement can be obtained by omitting species without clear temporal trends. Our findings suggest that population trend proxies from internet search frequencies can be used to supplement existing wildlife population monitoring and to ask questions about an array of ecological phenomena, which potentially can be integrated into an early warning system for biodiversity under climate change.
A Practical Approach for Employing Tensor Train Decomposition in Edge Devices
Authors: Kokhazadeh Milad , Keramidas Georgios , Kelefouras Vasilios , Stamoulis Iakovos
Published: February 2024

Deep Neural Networks (DNN) have made significant advances in various fields including speech recognition and image processing. Typically, modern DNNs are both compute and memory intensive, therefore their deployment in low-end devices is a challenging task. A well-known technique to address this problem is Low-Rank Factorization (LRF), where a weight tensor is approximated by one or more lower-rank tensors, reducing both the memory size and the number of executed tensor operations. However, the employment of LRF is a multi-parametric optimization process involving a huge design space where different design points represent different solutions trading-off the number of FLOPs, the memory size, and the prediction accuracy of the DNN models. As a result, extracting an efficient solution is a complex and time-consuming process. In this work, a new methodology is presented that formulates the LRF problem as a (FLOPs vs. memory vs. prediction accuracy) Design Space Exploration (DSE) problem. Then, the DSE space is drastically pruned by removing inefficient solutions. Our experimental results prove that the design space can be efficiently pruned, therefore extract only a limited set of solutions with improved accuracy, memory, and FLOPs compared to the original (non-factorized) model. Our methodology has been developed as a stand-alone, parameterized module integrated into T3F library of TensorFlow 2.X.
Pattern electroretinography response in amblyopic adults
Authors: Fernandes Andresa , Pinto Nuno , Tuna Ana Rita , Brardo Francisco Miguel , Pato Maria Vaz
Published: February 2024

Introduction

Amblyopia is generally a unilateral disorder, defined by at least a difference of two lines of visual acuity between both eyes with the best-corrected visual acuity, a decrease in contrast sensitivity, and a decrease in stereopsis. Pattern electroretinogram (PERG) is a noninvasive technique that provides a retinal biopotential and is a highly sensitive indicator of changes in the macular area. Our aim was to evaluate if there are differences in the retinal response of an amblyopic eye compared with a normal eye (NE).

Methods

We evaluated twenty-four adult volunteers, twelve amblyopes (mean 43.42 ± 12.72 years old), and twelve subjects with NE (mean 35.58 ± 12.85 years old). None of the subjects in the two groups had comorbidities. A complete optometric examination was performed including parameters such as visual acuity (VA) by far and near with ETDRS chart, eye alignment with cover test, and evaluation of retinal cells response with PERG.

Results

The refractive error found in the NE group of subjects had a mean of − 0.95 ± 1.65D, while the amblyopic group showed a mean of − 2.03 ± 4.29D. The VA in amblyopic eyes had a mean of 0.38 ± 0.20 logMAR. Analyzing PERG data, we observed significant differences in the P50-N95 amplitudes of the amblyopic group compared with the NE group (p < 0.0001–amblyopic eye vs. NE; p = 0.039–fellow eye vs. NE).

Discussion

These findings suggest that amblyopic patients may also present other impairments beyond the visual cortex. PERGs seem to be an important complementary examination in the diagnosis of other impairments in amblyopia.
Molecule auto-correction to facilitate molecular design
Authors: Kerstjens Alan , De Winter Hans
Published: February 2024

Ensuring that computationally designed molecules are chemically reasonable is at best cumbersome. We present a molecule correction algorithm that morphs invalid molecular graphs into structurally related valid analogs. The algorithm is implemented as a tree search, guided by a set of policies to minimize its cost. We showcase how the algorithm can be applied to molecular design, either as a post-processing step or as an integral part of molecule generators.

Graphical abstract
Recombinant IFN-γ1b Treatment in a Patient with Inherited IFN-γ Deficiency
Authors: Rosain Jérémie , Kiykim Ayca , Michev Alexandre , Kendir-Demirkol Yasemin , Rinchai Darawan , Peel Jessica N. , Li Hailun , Ocak Suheyla , Ozdemir Pinar Gokmirza , Le Voyer Tom , Philippot Quentin , Khan Taushif , Neehus Anna-Lena , Migaud Mélanie , Soudée Camille , Boisson-Dupuis Stéphanie , Marr Nico , Borghesi Alessandro , Casanova Jean-Laurent , Bustamante Jacinta
Published: February 2024

Purpose

Inborn errors of IFN-γ immunity underlie Mendelian susceptibility to mycobacterial disease (MSMD). Twenty-two genes with products involved in the production of, or response to, IFN-γ and variants of which underlie MSMD have been identified. However, pathogenic variants of IFNG encoding a defective IFN-γ have been described in only two siblings, who both underwent hematopoietic stem cell transplantation (HCST).

Methods

We characterized a new patient with MSMD by genetic, immunological, and clinical means. Therapeutic decisions were taken on the basis of these findings.

Results

The patient was born to consanguineous Turkish parents and developed bacillus Calmette-Guérin (BCG) disease following vaccination at birth. Whole-exome sequencing revealed a homozygous private IFNG variant (c.224 T > C, p.F75S). Upon overexpression in recipient cells or constitutive expression in the patient’s cells, the mutant IFN-γ was produced within the cells but was not correctly folded or secreted. The patient was treated for 6 months with two or three antimycobacterial drugs only and then for 30 months with subcutaneous recombinant IFN-γ1b plus two antimycobacterial drugs. Treatment with IFN-γ1b finally normalized all biological parameters. The patient presented no recurrence of mycobacterial disease or other related infectious diseases. The treatment was well tolerated, without the production of detectable autoantibodies against IFN-γ.

Conclusion

We describe a patient with a new form of autosomal recessive IFN-γ deficiency, with intracellular, but not extracellular IFN-γ. IFN-γ1b treatment appears to have been beneficial in this patient, with no recurrence of mycobacterial infection over a period of more than 30 months. This targeted treatment provides an alternative to HCST in patients with complete IFN-γ deficiency or at least an option to better control mycobacterial infection prior to HCST.
Enrichment of Immune Dysregulation Disorders in Adult Patients with Human Inborn Errors of Immunity
Authors: Segura-Tudela Alejandro , López-Nevado Marta , Nieto-López Celia , García-Jiménez Sandra , Díaz-Madroñero María J. , Delgado Ángeles , Cabrera-Marante Oscar , Pleguezuelo Daniel , Morales Pablo , Paz-Artal Estela , Gil-Niño Jorge , Marco Francisco M. , Serrano Cristina , González-Granado Luis I. , Quesada-Espinosa Juan F. , Allende Luis M.
Published: February 2024

Human inborn errors of immunity (IEI) comprise a group of diseases resulting from molecular variants that compromise innate and adaptive immunity. Clinical features of IEI patients are dominated by susceptibility to a spectrum of infectious diseases, as well as autoimmune, autoinflammatory, allergic, and malignant phenotypes that usually appear in childhood, which is when the diagnosis is typically made. However, some IEI patients are identified in adulthood due to symptomatic delay of the disease or other reasons that prevent the request for a molecular study. The application of next-generation sequencing (NGS) as a diagnostic technique has given rise to an ever-increasing identification of IEI-monogenic causes, thus improving the diagnostic yield and facilitating the possibility of personalized treatment. This work was a retrospective study of 173 adults with IEI suspicion that were sequenced between 2005 and 2023. Sanger, targeted gene-panel, and whole exome sequencing were used for molecular diagnosis. Disease-causing variants were identified in 44 of 173 (25.43%) patients. The clinical phenotype of these 44 patients was mostly related to infection susceptibility (63.64%). An enrichment of immune dysregulation diseases was found when cohorts with molecular diagnosis were compared to those without. Immune dysregulation disorders, group 4 from the International Union of Immunological Societies Expert Committee (IUIS), were the most prevalent among these adult patients. Immune dysregulation as a new item in the Jeffrey Model Foundation warning signs for adults significantly increases the sensitivity for the identification of patients with an IEI-producing molecular defect.
Post-transplant Inflammatory Bowel Disease Associated with Donor-Derived TIM-3 Deficiency
Authors: Baldrich Adrian , Althaus Dominic , Menter Thomas , Hirsiger Julia R. , Köppen Julius , Hupfer Robin , Juskevicius Darius , Konantz Martina , Bosch Angela , Drexler Beatrice , Gerull Sabine , Ghosh Adhideb , Meyer Benedikt J. , Jauch Annaise , Pini Katia , Poletti Fabio , Berkemeier Caroline M. , Heijnen Ingmar , Panne Isabelle , Cavelti-Weder Claudia , Niess Jan Hendrik , Dixon Karen , Daikeler Thomas , Hartmann Karin , Hess Christoph , Halter Jörg , Passweg Jakob , Navarini Alexander A. , Yamamoto Hiroyuki , Berger Christoph T. , Recher Mike , Hruz Petr
Published: February 2024

Inflammatory bowel disease (IBD) occurring following allogeneic stem cell transplantation (aSCT) is a very rare condition. The underlying pathogenesis needs to be better defined. There is currently no systematic effort to exclude loss- or gain-of-function mutations in immune-related genes in stem cell donors. This is despite the fact that more than 100 inborn errors of immunity may cause or contribute to IBD. We have molecularly characterized a patient who developed fulminant inflammatory bowel disease following aSCT with stable 100% donor-derived hematopoiesis. A pathogenic c.A291G; p.I97M HAVCR2 mutation encoding the immune checkpoint protein TIM-3 was identified in the patient’s blood-derived DNA, while being absent in DNA derived from the skin. TIM-3 expression was much decreased in the patient’s serum, and in vitro-activated patient-derived T cells expressed reduced TIM-3 levels. In contrast, T cell-intrinsic CD25 expression and production of inflammatory cytokines were preserved. TIM-3 expression was barely detectable in the immune cells of the patient’s intestinal mucosa, while being detected unambiguously in the inflamed and non-inflamed colon from unrelated individuals. In conclusion, we report the first case of acquired, “transplanted” insufficiency of the regulatory TIM-3 checkpoint linked to post-aSCT IBD.
A critical view on using “life not worth living” in the bioethics of assisted reproduction
Authors: Kandlbinder Agnes Elisabeth
Published: February 2024

This paper critically engages with how life not worth living (LNWL) and cognate concepts are used in the field of beginning-of-life bioethics as the basis of arguments for morally requiring the application of preimplantation genetic diagnosis (PGD) and/or germline genome editing (GGE). It is argued that an objective conceptualization of LNWL is largely too unreliable in beginning-of-life cases for deriving decisive normative reasons that would constitute a moral duty on the part of intending parents. Subjective frameworks are found to be more suitable to determine LNWL, but they are not accessible in beginning-of-life cases because there is no subject yet. Conceptual and sociopolitical problems are additionally pointed out regarding the common usage of clear case exemplars. The paper concludes that a moral requirement for the usage of PGD and GGE cannot be derived from the conceptual base of LNWL, as strong reasons that can be reliably determined are required to limit reproductive freedom on moral grounds. Educated predictions on prospective well-being might still be useful regarding the determination of moral permissibility of PGD and/or GGE. It is suggested that due to the high significance of subjective experience in the normativity of beginning-of-life bioethics, the discipline is called to more actively realize the inclusion of people with disabilities. This regards for instance research design, citation practices, and language choices to increase the accessibility of societal debates on the reproductive ethics of genetic technologies.
Pectolinarigenin regulates the tumor-associated proteins in AGS-xenograft BALB/c nude mice
Authors: Lee Ho Jeong , Kwon Young Sang , Lee Ju Hong , Moon Yeon Gyu , Choi Jungil , Hyun Moonjung , Tak Tae Kil , Kim Je-Hein , Heo Jeong Doo
Published: February 2024

Background

Pectolinarigenin (PEC) is a flavone extracted from Cirsium, and because it has anti-inflammatory properties, anti-cancer research is also being conducted. The objective of this work was to find out if PEC is involved in tumor control and which pathways it regulates in vivo and in vitro.

Methods

AGS cell lines were xenografted into BALB/c nude mice to create tumors, and PEC was administered intraperitoneally to see if it was involved in tumor control. Once animal testing was completed, tumor proteins were isolated and identified using LC–MS analysis, and gene ontology of the found proteins was performed.

Results

Body weight and hematological measurements on the xenograft mice model demonstrated that PEC was not harmful to non-cancerous cells. We found 582 proteins in tumor tissue linked to biological reactions such as carcinogenesis and cell death signaling. PEC regulated 6 out of 582 proteins in vivo and in vitro in the same way.

Conclusion

Our findings suggested that PEC therapy may inhibit tumor development in gastric cancer (GC), and proteomic research gives fundamental information about proteins that may have great promise as new therapeutic targets in GC.
The development of a custom RNA-sequencing panel for the identification of predictive and diagnostic biomarkers in glioma
Authors: Shirai Yukina , Ueno Toshihide , Kojima Shinya , Ikeuchi Hiroshi , Kitada Rina , Koyama Takafumi , Takahashi Fumiyuki , Takahashi Kazuhisa , Ichimura Koichi , Yoshida Akihiko , Sugino Hirokazu , Mano Hiroyuki , Narita Yoshitaka , Takahashi Masamichi , Kohsaka Shinji
Published: February 2024

Purpose

Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA.

Methods

A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets.

Results

Among 55 glioblastoma cases, gene fusions were detected in 11 cases (20%), including novel MET fusions. Seven tyrosine kinase genes were found to be overexpressed in 15 cases (27.3%). In contrast to isocitrate dehydrogenase (IDH) wild-type glioblastoma, IDH-mutant tumors, including astrocytomas and oligodendrogliomas, barely harbor fusion genes or gene overexpression. Of the 34 overexpressed tyrosine kinase genes, MDM2 and CDK4 in glioblastoma, 22 copy number amplifications (64.7%) were observed. When comparing astrocytomas and oligodendrogliomas in gene set enrichment analysis, the gene sets related to 1p36 and 19q were highly enriched in astrocytomas, suggesting that regional genomic DNA copy number alterations can be evaluated by gene expression analysis.

Conclusions

TOP2-RNA is a highly sensitive assay for detecting fusion genes, exon skipping, and aberrant gene expression. Alterations in targetable driver genes were identified in more than 50% of glioblastoma. Molecular profiling by TOP2-RNA provides ample predictive, prognostic, and diagnostic biomarkers that may not be identified by conventional assays and, therefore, is expected to increase treatment options for individual patients with glioma.
W-FENet: Wavelet-based Fourier-Enhanced Network Model Decomposition for Multivariate Long-Term Time-Series Forecasting
Authors: Wang Hai-Kun , Zhang Xuewei , Long Haicheng , Yao Shunyu , Zhu Pengjin
Published: February 2024

Accurately predicting the future trend of a time series holds immense importance for decision-making and planning across various domains, including energy planning, weather forecasting, traffic warning, and other practical applications. Recently, deep learning methods based on transformers and time convolution networks (TCN) have achieved a surprising performance in long-term sequence prediction. However, the attention mechanism for calculating global correlation is highly complex, and TCN methods do not fully consider the characteristics of time-series data. To address these challenges, we introduce a new learning model named wavelet-based Fourier-enhanced network model decomposition (W-FENet). Specifically, we have used trend decomposition and wavelet transform to decompose the original data. This processed time-series data can then be more effectively analyzed by the model and mined for different components in the series, as well as capture the local details and overall trendiness of the series. An efficient feature extraction method, Fourier enhancement-based feature extraction (FEMEX), is introduced in our model. The mechanism converts time-domain information into frequency-domain information through a Fourier enhancement module, and the obtained frequency-domain information is better captured by the model than the original time-domain information in terms of periodicity, trend, and frequency features. Experiments on multiple benchmark datasets show that, compared with the state-of-the-art methods, the MSE and MAE of our model are improved by 11.1 and 6.36% on average, respectively, covering three applications (i.e. ETT, Exchange, and Weather).
Category-Aware Saliency Enhance Learning Based on CLIP for Weakly Supervised Salient Object Detection
Authors: Zhang Yunde , Zhang Zhili , Liu Tianshan , Kong Jun
Published: February 2024

Weakly supervised salient object detection (SOD) using image-level category labels has been proposed to reduce the annotation cost of pixel-level labels. However, existing methods mostly train a classification network to generate a class activation map, which suffers from coarse localization and difficult pseudo-label updating. To address these issues, we propose a novel Category-aware Saliency Enhance Learning (CSEL) method based on contrastive vision-language pre-training (CLIP), which can perform image-text classification and pseudo-label updating simultaneously. Our proposed method transforms image-text classification into pixel-text matching and generates a category-aware saliency map, which is evaluated by the classification accuracy. Moreover, CSEL assesses the quality of the category-aware saliency map and the pseudo saliency map, and uses the quality confidence scores as weights to update the pseudo labels. The two maps mutually enhance each other to guide the pseudo saliency map in the correct direction. Our SOD network can be trained jointly under the supervision of the updated pseudo saliency maps. We test our model on various well-known RGB-D and RGB SOD datasets. Our model achieves an S-measure of 87.6$$\%$$
%
on the RGB-D NLPR dataset and 84.3$$\%$$
%
on the RGB ECSSD dataset. Additionally, we obtain satisfactory performance on the weakly supervised E-measure, F-measure, and mean absolute error metrics for other datasets. These results demonstrate the effectiveness of our model.
Genome-wide identification, stress- and hormone-responsive expression characteristics, and regulatory pattern analysis of Scutellaria baicalensis SbSPLs
Authors: Wu Jia-wen , Zhao Zi-yi , Hu Ren-chuan , Huang Yun-feng
Published: February 2024

SQUAMOSA PROMOTER BINDING PROTEIN-LIKEs (SPLs) encode plant-specific transcription factors that regulate plant growth and development, stress response, and metabolite accumulation. However, there is limited information on Scutellaria baicalensis SPLs. In this study, 14 SbSPLs were identified and divided into 8 groups based on phylogenetic relationships. SbSPLs in the same group had similar structures. Abscisic acid-responsive (ABRE) and MYB binding site (MBS) cis-acting elements were found in the promoters of 8 and 6 SbSPLs. Segmental duplications and transposable duplications were the main causes of SbSPL expansion. Expression analysis based on transcriptional profiling showed that SbSPL1, SbSPL10, and SbSPL13 were highly expressed in roots, stems, and flowers, respectively. Expression analysis based on quantitative real-time polymerase chain reaction (RT‒qPCR) showed that most SbSPLs responded to low temperature, drought, abscisic acid (ABA) and salicylic acid (SA), among which the expression levels of SbSPL7/9/10/12 were significantly upregulated in response to abiotic stress. These results indicate that SbSPLs are involved in the growth, development and stress response of S. baicalensis. In addition, 8 Sba-miR156/157 s were identified, and SbSPL1-5 was a potential target of Sba-miR156/157 s. The results of target gene prediction and coexpression analysis together indicated that SbSPLs may be involved in the regulation of L-phenylalanine (L-Phe), lignin and jasmonic acid (JA) biosynthesis. In summary, the identification and characterization of the SbSPL gene family lays the foundation for functional research and provides a reference for improved breeding of S. baicalensis stress resistance and quality traits.
Regional and sectoral variations in the ability to attract funding from the European Union’s Seventh Framework Program and Horizon 2020
Authors: Piro Fredrik Niclas , Seeber Marco , Wang Lili
Published: February 2024

The funding from the European Union’s Framework Programs for Research and Innovation (EU FPs) is skewed across European countries and institutions. The goal of this article is to deepen our understanding of this skewness by incorporating a regional (NUTS-2) and a sectoral (higher education sector and private sector) perspective when studying the ability to attract 71.6 billion euros of research funding distributed by the EU Framework Programs between 2007 and 2020, and to explore how it changed from FP7 to Horizon 2020. We explore the ability to attract grant funding per unit of R&D personnel, and how it is affected by a region’s volume of research personnel, R&D investments, research intensity, level of development, and mediated by the amount of funding requested. In the private sector, we find that several Southern European regions are highly capable of attracting funding, primarily through a high proposal intensity, e.g., large amounts of funding requested. In the higher education sector, regions in the so-called “blue banana” are particularly able to attract funding, due to high levels of R&D investments, strong research intensity, and a high amount of funding requested. From FP7 to Horizon 2020, we observe increasing divergence in the ability to attract funding in the private sector, in favor of peripheral regions, which aligns with the aims of the European Commission's cohesion policy.
Bibliometric analysis of Sci-Hub downloads by Egyptian researchers
Authors: Osman Ismail Ragab , Ahmed Hendy Abdullah Hendy
Published: February 2024

In this study we present an in-depth bibliometric analysis of Sci-Hub downloads by Egyptian researchers based on the 2017 download log file. The study reveals that Egyptian researchers heavily rely on Sci-Hub, generating a substantial 1,357,526 download requests in 2017, with 65% of these occurring outside regular working hours. Cairo emerges as a central hub for this activity, contributing 81.58% of total downloads. Journal articles constitute the majority of downloads at 82.36%, followed by conference papers (12.89%). A discernible trend shows a preference for recent papers published between 2012 and 2017, highlighting the demand for up-to-date research. The analysis also highlights prominent publishers, including IEEE, Elsevier, Wiley, and Springer, as preferred sources for Egyptian researchers. “Journal of the American Chemical Society” and “Journal of Applied Physics” stand out among accessed journals, while IEEE-associated conferences, notably “IEEE Power and Energy Society General Meeting,” dominate conference paper downloads. Examining journal accessibility via the Egyptian Knowledge Bank (EKB) reveals that 62.84% of journals are accessible, with Science Direct as the leading provider (28.37%). However, a significant gap emerges as 87.39% of downloaded conference papers remain inaccessible through EKB. Furthermore, a semantic analysis highlights recurring themes such as “systems,” “review,” “analysis,” “treatment,” “power,” and “energy,” reflecting the key research areas of Egyptian researchers. Overall, this study offers valuable insights into Sci-Hub’s role in supplementing Egyptian researchers’ resource access and underscores the need for comprehensive resource coverage and accessibility enhancements.
Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images
Authors: López-Fandiño Javier , B. Heras Dora , Argüello Francisco
Published: February 2024

This paper proposes a parallel algorithm exploiting heterogeneous computing and edge computing for anomaly detection (AD) in remotely sensed multispectral images. These images present high spatial resolution and are captured onboard unmanned aerial vehicles. AD is applied to identify patterns within an image that do not conform to the expected behavior. In this paper, the anomalies correspond to human-made constructions that trigger alarms related to the integrity of fluvial ecosystems. An algorithm based on extracting spatial information by using extinction profiles (EPs) and detecting anomalies by using the Reed–Xiaoli (RX) technique is proposed. The parallel algorithm presented in this paper is designed to be executed on multi-node heterogeneous computing platforms that include nodes with multi-core central processing units (CPUs) and graphics processing units (GPUs) and on a mobile embedded system consisting of a multi-core CPU and a GPU. The experiments are carried out on nodes of the FinisTerrae III supercomputer and, with the objective of analyzing its efficiency under different energy consumption scenarios, on a Jetson AGX Orin.
Lying and self-defeating prophecies
Authors: Freitag Wolfgang
Published: February 2024

The paper disputes the common view which holds that to lie is, essentially, to assert a disbelieved proposition. It shows by reference to self-defeating prophecies that one can lie by asserting a believed proposition, and by reference to self-fulfilling prophecies that one can be truthful by asserting a disbelieved proposition. It concludes that lying is, essentially, asserting a proposition believed to be false conditionally on the occurrence of the assertion.
Order-of-Mutation Effects on Cancer Progression: Models for Myeloproliferative Neoplasm
Authors: Wang Yue , Shtylla Blerta , Chou Tom
Published: February 2024

In some patients with myeloproliferative neoplasms (MPN), two genetic mutations are often found: JAK2 V617F and one in the TET2 gene. Whether one mutation is present influences how the other subsequent mutation will affect the regulation of gene expression. In other words, when a patient carries both mutations, the order of when they first arose has been shown to influence disease progression and prognosis. We propose a nonlinear ordinary differential equation, the Moran process, and Markov chain models to explain the non-additive and non-commutative mutation effects on recent clinical observations of gene expression patterns, proportions of cells with different mutations, and ages at diagnosis of MPN. Combined, these observations are used to shape our modeling framework. Our key proposal is that bistability in gene expression provides a natural explanation for many observed order-of-mutation effects. We also propose potential experimental measurements that can be used to confirm or refute predictions of our models.