bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative analysis of antigen-presenting cells in gingival tissues in healthy and periodontitis patients
Authors: Pejcic Ana , Andjelkovic Zlatibor , Marjanovic Dragan , Minic Ivan , Matvijenko Vladimir , Arsic Zoran , Jovanovic Radovan , Subaric Ljiljana 
Published: July 2023

AimsMicrobial flora of dental plaque trigger innate and adaptive immune responses. The function of antigen-presenting cells (APCs) is to bridge the innate and adaptive immune systems. The human immune system contains three main types of APCs: dendritic cells (DC) (Langerhans cells (LCs) and interstitial DCs, IDCs), macrophages and B lymphocytes. In this study, the distribution and density of all APCs in healthy and inflamed human gingival tissue were comparatively analysed.MethodsResearch was conducted on gingival biopsy specimens obtained from 55 patients and classified in three groups: healthy gingiva (control group, n=10), moderate periodontal disease (PD) (n=21) and severe PD (n=24). For APCs’ identification antibodies raised against CD1a(for LCs), S100protein (for iDCs), CD68(for macrophages) and CD20(for B lymphocytes) were used.ResultsIncreased density of IDCs, macrophages and B lymphocytes in lamina propria and reduced density of LCs in the gingival epithelium were found in patients with periodontitis. Simultaneously, it was noticed an increased concentration of macrophages and B cells in the gingival epithelium in patients with PD. No statistically significant difference in the distribution and density of APC was found among patients with moderate and advanced periodontitis.ConclusionsIt was hypothesised that in the periodontitis the role of antigen presentation was largely taken from LCs by the DCs, macrophages and B cells. These APCs are thought to have less protective and tolerogenic potential than LCs and this is a significant reason for alveolar bone destruction in periodontitis.
Texture zeros of quark mass matrices at fixed point $$\tau =\omega $$ in modular flavor symmetry
Authors: Kikuchi Shota , Kobayashi Tatsuo , Tanimoto Morimitsu , Uchida Hikaru 
Published: July 2023

AbstractWe study systematically derivation of the specific texture zeros, that is the nearest neighbor interaction (NNI) form of the quark mass matrices at the fixed point $$\tau =\omega $$

τ
=
ω

in modular flavor symmetric models. We present models that the NNI forms of the quark mass matrices are simply realized at the fixed point $$\tau =\omega $$

τ
=
ω

in the $$A_4$$

A
4

modular flavor symmetry by taking account multi-Higgs fields. Such texture zero structure originates from the ST charge of the residual symmetry $$Z_3$$

Z
3

of SL(2, Z). The NNI form can be realized at the fixed point $$\tau = \omega $$

τ
=
ω

in $$A_4$$

A
4

and $$S_4$$

S
4

modular flavor models with two pairs of Higgs fields when we assign properly modular weights to Yukawa couplings and $$A_4$$

A
4

and $$S_4$$

S
4

representations to three generations of quarks. We need four pairs of Higgs fields to realize the NNI form in $$A_5$$

A
5

modular flavor models.
Uncovering tau leptons-enriched semi-visible jets at the LHC
Authors: Beauchesne Hugues , Cazzaniga Cesare , de Cosa Annapaola , Doglioni Caterina , Fitschen Tobias , di Cortona Giovanni Grilli , Zhou Ziyuan 
Published: July 2023

AbstractThis Letter proposes a new signature for confining dark sectors at the Large Hadron Collider. Under the assumption of a QCD-like hidden sector, hadronic jets containing stable dark bound states could manifest in proton-proton collisions. We present a simplified model with a $$Z'$$

Z
′

boson yielding the production of jets made up of dark bound states and subsequently leading to the decays of those that are unstable to $$\tau $$
τ
leptons and Standard Model quarks. The resulting signature is characterised by non-isolated $$\tau $$
τ
lepton pairs inside semi-visible jets. We estimate the constraints on our model from existing CMS and ATLAS analyses. We propose a set of variables that leverage the leptonic content of the jet and exploit them in a supervised jet tagger to enhance the signal-to-background separation. Furthermore, we discuss the performance and limitations of current triggers for accessing sub-TeV $$Z'$$

Z
′

masses, as well as possible strategies that can be adopted by experiments to access such low mass regions. We estimate that with the currently available triggers, a high mass search can claim a $$5 \sigma $$

5
σ

discovery (exclusion) of the $$Z'$$

Z
′

boson with a mass up to 4.5 TeV (5.5 TeV) with the full Run 2 data of the LHC when the fraction of unstable dark hadrons decaying to $$\tau $$
τ
lepton pairs is around $$50\%$$

50
%

, and with a coupling of the $$Z'$$

Z
′

to right-handed up-type quarks of 0.25. Furthermore, we show that, with new trigger strategies for Run 3, it may be possible to access $$Z'$$

Z
′

masses down to 700 GeV, for which the event topology is still composed of two resolved semi-visible jets.
Investigating the effects of Lorentz Invariance Violation on the CP-sensitivities of the Deep Underground Neutrino Experiment
Authors: Sarker Arnab , Medhi Abinash , Devi Moon Moon 
Published: July 2023

AbstractThe phenomena of neutrino oscillations offer a great potential for probing new-physics beyond the Standard Model. Any additional effects on neutrino oscillations can help understand the nature of the non-standard effects. The violation of fundamental symmetries may appear as a probe for new-physics in various neutrino experiments. Lorentz symmetry is one such fundamental symmetry in nature and the breakdown of spacetime is a possible motivation for a departure from the standard Lorentz symmetry picture. The Lorentz invariance violation (LIV) is intrinsic in nature and its effects exist even in a vacuum. Neutrinos can be an intriguing probe for exploring such violations of Lorentz symmetry. The effect of violation of Lorentz invariance can be explored through its impact on the neutrino oscillation probabilities. The effect of LIV is treated as a perturbation to the standard neutrino Hamiltonian considering the Standard Model Extension (SME) framework. In this work, we have probed the effects of LIV on the measurement of neutrino oscillation parameters considering Deep Underground Neutrino Experiment (DUNE) as a case study. The inclusion of LIV affects the measurements of various neutrino oscillation parameters as it modifies the standard neutrino oscillation probabilities. We looked into the capability of DUNE in constraining the LIV parameters and then explored the impact of CPT-violating LIV terms on the mass-induced neutrino oscillation probabilities. We have also probed the impact of LIV parameters on the CP-measurement sensitivities at DUNE.
EVaDe: Efficient and Lightweight Mirai Variants Detection via Approximate Largest Submatrix Search
Authors: Wang Xuguo , Chen Ligeng , Wang Yuyang , Huang Hao , Mao Bing 
Published: July 2023

The Mirai botnet, notorious for launching significant Distributed Denial of Service (DDoS) attacks and crippling portions of internet services in late 2016, has emerged as a significant threat. Its threat is magnified by the open-source nature of the original Mirai code, which enables a propagation and evolution rate that surpasses traditional malware and frequently defies common sense. As the primary targets of Mirai attacks, Internet of Things (IoT) devices must promptly adapt to the evolving variations of the Mirai threat scenario. In practice, however, IoT devices are frequently constrained by insufficient security detection resources. Therefore, there is an urgent need for a lightweight framework capable of handling Mirai variants and dynamically updating its rule set in order to effectively counter the threat. In response to these challenges, we present Efficient and lightweight Mirai Variants Detection (EVaDe), a novel, lightweight framework for detecting Mirai. EVaDe unleashes the power of sample function mining to efficiently automate the generation of detection rules, requiring limited hardware resources while maintaining effectiveness against Mirai and its numerous variants. In addition, to improve the efficacy of rule generation, we propose a sophisticated algorithm designed to optimize the maximum submatrix problem, thereby facilitating the efficient and rapid extraction of malicious rules from the sample group. We validated the experiments on actual IoT devices with significantly compressed performance overheads. An average sample detection time of 5 ms to make sure the system can be deployed in real production. According to the result, the approach has an average detection rate of 95% for Mirai and its variants, which beats every other well-known piece of commercial antivirus software on the market by 3% to 56%.
Games with filters I
Authors: Foreman Matthew , Magidor Menachem , Zeman Martin 
Published: July 2023

This paper has two parts. The first is concerned with a variant of a family of games introduced by Holy and Schlicht, that we call Welch games. Player II having a winning strategy in the Welch game of length [Formula: see text] on [Formula: see text] is equivalent to weak compactness. Winning the game of length [Formula: see text] is equivalent to [Formula: see text] being measurable. We show that for games of intermediate length [Formula: see text], II winning implies the existence of precipitous ideals with [Formula: see text]-closed, [Formula: see text]-dense trees. The second part shows the first is not vacuous. For each [Formula: see text] between [Formula: see text] and [Formula: see text], it gives a model where II wins the games of length [Formula: see text], but not [Formula: see text]. The technique also gives models where for all [Formula: see text] there are [Formula: see text]-complete, normal, [Formula: see text]-distributive ideals having dense sets that are [Formula: see text]-closed, but not [Formula: see text]-closed.
Smartphone Screens as Astrometric Calibrators
Authors: Walk Aidan , Claveau Charles-Antoine , Bottom Michael , Chun Mark , Jacobson Shane , Service Maxwell , Lu Jessica R. 
Published: July 2023

Geometric optical distortion is a significant contributor to the astrometric error budget in large telescopes using adaptive optics. To increase astrometric precision, optical distortion calibration is necessary. We investigate using smartphone Organic Light-Emitting Diode (OLED) screens as astrometric calibrators. Smartphones are low-cost, have stable illumination, and can be quickly reconfigured to probe different spatial frequencies of an optical system’s geometric distortion. In this work, we characterize the astrometric accuracy of a Samsung S20 smartphone, with a view towards providing large format, flexible astrometric calibrators for the next generation of astronomical instruments. We find the placement error of the pixels to be 189[Formula: see text]nm ± 15[Formula: see text]nm Root Mean Square (RMS). At this level of error, milliarcsecond astrometric accuracy can be obtained on modern astronomical instruments.
Intratumoral Microbiota Composition Regulates Chemoimmunotherapy Response in Esophageal Squamous Cell Carcinoma
Authors: Wu Hong , Leng Xuefeng , Liu Qianshi , Mao Tianqin , Jiang Tao , Liu Yiqiang , Li Feifei , Cao Chenhui , Fan Jun , Chen Liang , Chen Yaqi , Yao Quan , Lu Shun , Liang Renchuan , Hu Lanlin , Liu Mingxin , Wan Yejian , Li Zhaoshen , Peng Jun , Luo Qiyu , Zhou Hang , Yin Jun , Xu Ke , Lan Mei , Peng Xinhao , Lan Haitao , Li Gang , Han Yongtao , Zhang Xia , Xiao Zhi-Xiong Jim , Lang Jinyi , Wang Guihua , Xu Chuan 
Published: July 2023

Abstract

Neoadjuvant chemoimmunotherapy (NACI) has shown promise in the treatment of resectable esophageal squamous cell carcinoma (ESCC). The microbiomes of patients can impact therapy response, and previous studies have demonstrated that intestinal microbiota influences cancer immunotherapy by activating gut immunity. Here, we investigated the effects of intratumoral microbiota on the response of patients with ESCC to NACI. Intratumoral microbiota signatures of β-diversity were disparate and predicted the treatment efficiency of NACI. The enrichment of Streptococcus positively correlated with GrzB+ and CD8+ T-cell infiltration in tumor tissues. The abundance of Streptococcus could predict prolonged disease-free survival in ESCC. Single-cell RNA sequencing demonstrated that responders displayed a higher proportion of CD8+ effector memory T cells but a lower proportion of CD4+ regulatory T cells. Mice that underwent fecal microbial transplantation or intestinal colonization with Streptococcus from responders showed enrichment of Streptococcus in tumor tissues, elevated tumor-infiltrating CD8+ T cells, and a favorable response to anti-PD-1 treatment. Collectively, this study suggests that intratumoral Streptococcus signatures could predict NACI response and sheds light on the potential clinical utility of intratumoral microbiota for cancer immunotherapy.

Significance:
Analysis of intratumoral microbiota in patients with esophageal cancer identifies a microbiota signature that is associated with chemoimmunotherapy response and reveals that Streptococcus induces a favorable response by stimulating CD8+ T-cell infiltration.
See related commentary by Sfanos, p. 2985
Clec4A4 Acts as a Negative Immune Checkpoint Regulator to Suppress Antitumor Immunity
Authors: Uto Tomofumi , Fukaya Tomohiro , Mitoma Shuya , Nishikawa Yotaro , Tominaga Moe , Choijookhuu Narantsog , Hishikawa Yoshitaka , Sato Katsuaki 
Published: July 2023

Abstract
Clec4A4 is a C-type lectin receptor (CLR) exclusively expressed on murine conventional dendritic cells (cDC) to regulate their activation status. However, the functional role of murine Clec4A4 (mClec4A4) in antitumor immunity remains unclear. Here, we show that mClec4A4 serves as a negative immune checkpoint regulator to impair antitumor immune responses. Deficiency of mClec4A4 lead to a reduction in tumor development, accompanied by enhanced antitumor immune responses and amelioration of the immunosuppressive tumor microenvironment (TME) mediated through the enforced activation of cDCs in tumor-bearing mice. Furthermore, antagonistic mAb to human CLEC4A (hCLEC4A), which is the functional orthologue of mClec4A4, exerted protection against established tumors without any apparent signs of immune-related adverse events in hCLEC4A-transgenic mice. Thus, our findings highlight the critical role of mClec4A4 expressed on cDCs as a negative immune checkpoint molecule in the control of tumor progression and provide support for hCLEC4A as a potential target for immune checkpoint blockade in tumor immunotherapy.
Impact of Diabetes on Myocardial Fibrosis in Patients With Hypertension: The REMODEL Study
Authors: Pua Chee Jian , Loo Germaine , Kui Michelle , Moy Wai Lun , Hii An-An , Lee Vivian , Chin Chee-Tang , Bryant Jennifer A. , Toh Desiree-Faye , Lee Chi-Hang , Cook Stuart A. , Richards A. Mark , Le Thu-Thao , Chin Calvin W.L. 
Published: July 2023

BACKGROUND:
Compared with patients with hypertension only, those with hypertension and diabetes (HTN/DM) have worse prognosis. We aimed to characterize morphological differences between hypertension and HTN/DM using cardiovascular magnetic resonance; and compare differentially expressed proteins associated with myocardial fibrosis using high throughput multiplex assays.

METHODS:
Asymptomatic patients underwent cardiovascular magnetic resonance: 438 patients with hypertension (60±8 years; 59% males) and 167 age- and sex-matched patients with HTN/DM (60±10 years; 64% males). Replacement myocardial fibrosis was defined as nonischemic late gadolinium enhancement on cardiovascular magnetic resonance. Extracellular volume fraction was used as a marker of diffuse myocardial fibrosis. A total of 184 serum proteins (Olink Target Cardiovascular Disease II and III panels) were measured to identify unique signatures associated with myocardial fibrosis in all patients.

RESULTS:

Despite similar left ventricular mass (
P
=0.344) and systolic blood pressure (
P
=0.086), patients with HTN/DM had increased concentricity and worse multidirectional strain (
P
<0.001 for comparison of all strain measures) compared to hypertension only. Replacement myocardial fibrosis was present in 28% of patients with HTN/DM compared to 16% of those with hypertension (
P
<0.001). NT-proBNP (N-terminal pro-B-type natriuretic peptide) was the only protein differentially upregulated in hypertension patients with replacement myocardial fibrosis and independently associated with extracellular volume. In patients with HTN/DM, GDF-15 (growth differentiation factor 15) was independently associated with replacement myocardial fibrosis and extracellular volume. Ingenuity Pathway Analysis demonstrated a strong association between increased inflammatory response/immune cell trafficking and myocardial fibrosis in patients with HTN/DM.

CONCLUSIONS:
Adverse cardiac remodeling was observed in patients with HTN/DM. The novel proteomic signatures and associated biological activities of increased immune and inflammatory response may partly explain these observations.
Lessons from the Evolutionary Computation Bestiary
Authors: Campelo Felipe , Aranha Claus 
Published: July 2023

Abstract
The field of metaheuristics has a long history of finding inspiration in natural systems, starting from evolution strategies, genetic algorithms, and ant colony optimization in the second half of the 20th century. In the last decades, however, the field has experienced an explosion of metaphor-centered methods claiming to be inspired by increasingly absurd natural (and even supernatural) phenomena—several different types of birds, mammals, fish and invertebrates, soccer and volleyball, reincarnation, zombies, and gods. Although metaphors can be powerful inspiration tools, the emergence of hundreds of barely discernible algorithmic variants under different labels and nomenclatures has been counterproductive to the scientific progress of the field, as it neither improves our ability to understand and simulate biological systems nor contributes generalizable knowledge or design principles for global optimization approaches. In this article we discuss some of the possible causes of this trend, its negative consequences for the field, and some efforts aimed at moving the area of metaheuristics toward a better balance between inspiration and scientific soundness.
Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks
Authors: Kanamaru Takashi , Hensch Takao K. , Aihara Kazuyuki 
Published: July 2023

Abstract
We examine the efficiency of information processing in a balanced excitatory and inhibitory (E-I) network during the developmental critical period, when network plasticity is heightened. A multimodule network composed of E-I neurons was defined, and its dynamics were examined by regulating the balance between their activities. When adjusting E-I activity, both transitive chaotic synchronization with a high Lyapunov dimension and conventional chaos with a low Lyapunov dimension were found. In between, the edge of high-dimensional chaos was observed. To quantify the efficiency of information processing, we applied a short-term memory task in reservoir computing to the dynamics of our network. We found that memory capacity was maximized when optimal E-I balance was realized, underscoring both its vital role and vulnerability during critical periods of brain development.
Improving High-Resolution Ensemble Forecast (HREF) System Mesoscale Snowband Forecasts with Random Forests
Authors: Radford Jacob T. , Lackmann Gary M. 
Published: July 2023

Abstract
Mesoscale snowbands are impactful winter weather phenomena but are challenging to predict due to small-scale forcings and ingredients. Previous work has established that even deterministic convection-allowing models (CAMs) often struggle to represent these features with much precision and recommended the application of ingredients-based or probabilistic forecast strategies. Based on these recommendations, we develop and evaluate four different models for forecasting snowbands. The first model, referred to as the “HREF threshold probability” model, detects band development in High-Resolution Ensemble Forecast (HREF) system members’ 1000-m simulated reflectivities, then uses these detections to calculate a snowband probability. The second model is a random forest incorporating features explicitly linked to snowbands, such as the detection of bands in each HREF member and statistical summaries of simulated reflectivity and the categorical snow field. The third model is a random forest model incorporating snowband ingredients, such as midtropospheric frontogenesis, moist symmetric stability, and vertical velocity. Last, the fourth model combines the features of the explicit and implicit random forests. Binary band predictions based upon the HREF threshold probability model resulted in a critical success index 27% higher than the average HREF member. The explicit feature random forest model further improved performance by an additional 11%, with statistics of the reflectivity field holding the most predictive value. The implicit and combined random forests slightly underperformed the explicit random forest, perhaps due to a large number of noisy, correlated features. Ultimately, we demonstrate that simple probabilistic snowband forecasting strategies can yield substantial improvements over deterministic CAMs.

Significance Statement
Mesoscale snowbands have the potential for major societal impacts but are difficult to predict due to their small spatial scales. Previous work has shown that individual high-resolution numerical weather prediction (NWP) models struggle to predict whether or not a snowband will occur. In this work, we evaluate whether a probabilistic forecast strategy using high-resolution ensemble NWP output leads to improved snowband forecasts, and whether we can gain additional predictive skill by combining this output with artificial intelligence (AI) methods. AI can also help us understand the environmental factors associated with snowbands and compare environmental importance in forecasting to just using the model output snowfall forecasts explicitly.