bluuebunny/crossref_metadata_2025 huggingface dataset:
LKB1 suppresses KSHV reactivation and promotes primary effusion lymphoma progression
Authors: Li Guanya , Li Yinan , Tang Xinyu , Wang Lijie , Yue Shusheng , He Shanping , Li Tingting
Published: August 2024

Viruses normally reprogram the host cell metabolic pathways as well as metabolic sensors to facilitate their persistence. The serine-threonine liver kinase B1 (LKB1) is a master upstream kinase of 5′-AMP-activated protein kinase (AMPK) that senses the energy status and therefore regulates the intracellular metabolic homeostasis. Previous studies showed that AMPK restricts Kaposi’s sarcoma-associated herpesvirus (KSHV) lytic replication in endothelial cells during primary infection and promotes primary effusion lymphoma (PEL) cell survival. However, the role of LKB1 in KSHV lytic reactivation and KSHV-associated malignancies is unclear. In this study, we found that LKB1 is phosphorylated or activated in KSHV-positive PEL cells. Mechanistically, KSHV-encoded vCyclin mediated LKB1 activation in PEL cells, as vCyclin knockout ablated, while vCyclin overexpression enhanced LKB1 activation. Furthermore, knockdown of LKB1 inactivated AMPK and induced KSHV reactivation, as indicated by the increased expression of viral lytic genes and the increased virions in supernatants. Accordingly, AMPK inhibition by functional knockdown or a pharmacologic inhibitor, Compound C, promoted KSHV reactivation in PEL cells. Furthermore, inhibition of either LKB1 or AMPKα1 efficiently induced cell death by apoptosis of PEL cells both
in vitro
and
in vivo
. Together, these results identify LKB1 as a vulnerable target for PEL, which could be potentially exploited for treating other virus-associated diseases.

IMPORTANCE

Kaposi’s sarcoma-associated herpesvirus (KSHV) is an oncogenic virus associated with several human cancers, such as primary effusion lymphoma (PEL). Here, we showed that serine-threonine liver kinase B1 (LKB1), upstream of 5
'
AMP-activated protein kinase (AMPK), is activated by KSHV-encoded vCyclin and maintains KSHV latency in PEL cells. Inhibition of either LKB1 or AMPK enhances KSHV lytic replication from latency, which at least partially accounts for PEL cell death by apoptosis. Compound C, a potent AMPK inhibitor, induced KSHV reactivation and efficiently inhibited PEL progression
in vivo
. Thus, our work revealed that LKB1 is a potential therapeutic target for KSHV-associated cancers.
miR-451-targeted PSMB8 promotes PRRSV infection by degrading IRF3
Authors: Li Sihan , Guo Shuyuan , Liu Fang , Yao Yao , Zhu Yingqi , Feng Wen-hai
Published: August 2024

Porcine respiratory and reproductive syndrome (PRRS) is one of the most devastating infectious diseases of pigs, causing reproductive failures in sows and severe respiratory symptoms in piglets and growing pigs. MicroRNAs (miRNAs) are reported to play an essential role in virus–host interactions. In this study, we demonstrated that miR-451 enhanced type I interferon (IFN-I) production through targeting proteasome subunit β8 (PSMB8), therefore restricting PRRS virus (PRRSV) replication. We showed that the expression of PSMB8 was upregulated by PRRSV infection, and knockdown of PSMB8 inhibited PRRSV replication by promoting IFN-I production. Moreover, we demonstrated that PSMB8 interacted with the regulatory domain of IRF3 to mediate K48-linked polyubiquitination and degradation of IRF3. Also, importantly, we showed that PSMB8, as a target gene of miR-451, negatively regulated IFN-I production by promoting IRF3 degradation, which is a previously unknown mechanism for PSMB8 to modulate innate immune responses.

IMPORTANCE

Porcine respiratory and reproductive syndrome virus (PRRSV), as a huge threat to the swine industry, is a causative agent that urgently needs to be solved. The dissecting of PRRSV pathogenesis and understanding of the host–pathogen interaction will provide insights into developing effective anti-PRRSV strategies. In this study, we showed that miR-451 dramatically inhibited PRRSV replication by targeting proteasome subunit β8 (PSMB8), a subunit of the immunoproteasome. Mutation of PSMB8 is often related to autoinflammatory diseases due to the elevated IFN production. We revealed that PSMB8 downregulated IFN production by promoting IRF3 degradation. In addition, we showed that PRRSV infection upregulated PSMB8 expression. Taken together, our findings reveal that miR-451 is a negative regulator of PRRSV replication, and PSMB8, a target gene of miR-451, negatively regulates IFN-I production by promoting IRF3 degradation, which is a previously unknown mechanism for PSMB8 to regulate innate immune responses.
Coenzyme A biosynthesis in
Bacillus subtilis
: discovery of a novel precursor metabolite for salvage and its uptake system
Authors: Warneke Robert , Herzberg Christina , Klein Moritz , Elfmann Christoph , Dittmann Josi , Feussner Kirstin , Feussner Ivo , Stülke Jörg
Published: August 2024

The Gram-positive model bacterium
Bacillus subtilis
is used for many biotechnological applications, including the large-scale production of vitamins. For vitamin B5, a precursor for coenzyme A synthesis, there is so far no established fermentation process available, and the metabolic pathways that involve this vitamin are only partially understood. In this study, we have elucidated the complete pathways for the biosynthesis of pantothenate and coenzyme A in
B. subtilis
. Pantothenate can not only be synthesized but also be taken up from the medium. We have identified the enzymes and the transporter involved in the pantothenate biosynthesis and uptake. High-affinity vitamin B5 uptake in
B. subtilis
requires an ATP-driven energy coupling factor transporter with PanU (previously YhfU) as the substrate-specific subunit. Moreover, we have identified a salvage pathway for coenzyme A acquisition that acts on complex medium even in the absence of pantothenate synthesis. This pathway requires rewiring of sulfur metabolism resulting in the increased expression of a cysteine transporter. In the salvage pathway, the bacteria import cysteinopantetheine, a novel naturally occurring metabolite, using the cystine transport system TcyJKLMN. This work lays the foundation for the development of effective processes for vitamin B5 and coenzyme A production using
B. subtilis
.

IMPORTANCE

Vitamins are essential components of the diet of animals and humans. Vitamins are thus important targets for biotechnological production. While efficient fermentation processes have been developed for several vitamins, this is not the case for vitamin B5 (pantothenate), the precursor of coenzyme A. We have elucidated the complete pathway for coenzyme A biosynthesis in the biotechnological workhorse
Bacillus subtilis
. Moreover, a salvage pathway for coenzyme A synthesis was found in this study. Normally, this pathway depends on pantetheine; however, we observed activity of the salvage pathway on complex medium in mutants lacking the pantothenate biosynthesis pathway even in the absence of supplemented pantetheine. This required rewiring of metabolism by expressing a cystine transporter due to acquisition of mutations affecting the regulation of cysteine metabolism. This shows how the hidden “underground metabolism” can give rise to the rapid formation of novel metabolic pathways.
Slow clearance of histidine-rich protein-2 in Gabonese with uncomplicated malaria
Authors: Lamsfus Calle Carlos , Schaumburg Frieder , Rieck Thorsten , Nkoma Mouima Anne Marie , Martinez de Salazar Pablo , Breil Saskia , Behringer Johannes , Kremsner Peter G. , Mordmüller Benjamin , Fendel Rolf
Published: August 2024

Malaria rapid diagnostic tests (RDTs), which detect
Plasmodium falciparum
(Pf)-specific histidine-rich protein-2 (HRP2), have increasing importance for the diagnosis and control of malaria, especially also in regions where routine diagnosis by microscopy is not available. HRP2-based RDTs have a similar sensitivity to expert microscopy, but their reported low specificity can lead to high false positivity rates, particularly in high-endemic areas. Despite the widespread use of RDTs, models investigating the dynamics of HRP2 clearance following Pf treatment focus rather on short-term clearance of the protein. The goal of this observational cohort study was to determine the long-term kinetic of HRP2-levels in peripheral blood after treatment of uncomplicated malaria cases with Pf mono-infection using a 3-day course of artesunate/amodiaquine. HRP2 levels were quantified at enrollment and on days 1, 2, 3, 5, 7, 12, 17, 22, and 28 post-treatment initiation. The findings reveal an unexpectedly prolonged clearance of HRP2 after parasite clearance from capillary blood. Terminal HRP2 half-life was estimated to be 9 days after parasite clearance using a pharmacokinetic two-compartmental elimination model. These results provide evidence that HRP2 clearance has generally been underestimated, as the antigen remains detectable in capillary blood for up to 28 days following successful treatment, influencing RDT-based assessment following a malaria treatment for weeks. A better understanding of the HRP2 clearance dynamics is critical for guiding the diagnosis of malaria when relying on RDTs.

IMPORTANCE

Detecting
Plasmodium falciparum
, the parasite responsible for the severest form of malaria, typically involves microscopy, polymerase chain reaction (PCR), or rapid diagnostic tests (RDTs) targeting the histidine-rich protein 2 or 3 (HRP2/3). While microscopy and PCR quickly turn negative after the infection is cleared, HRP2 remains detectable for a prolonged period. The exact duration of HRP2 persistence had not been well defined. Our study in Gabon tracked HRP2 levels over 4 weeks, resulting in a new model for antigen clearance. We discovered that a two-compartment model accurately predicts HRP2 levels, revealing an initial rapid reduction followed by a much slower elimination phase that can take several weeks. These findings are crucial for interpreting RDT results, as lingering HRP2 can lead to false positives, impacting malaria diagnosis and treatment decisions.
Desertic siliciclastic stromatolites in the Upper Jurassic Guará Formation from southwestern Gondwana: Trapping and binding in a non-marine setting
Authors: Angonese Bruno S. , Scherer Claiton M.S. , De Ros Luiz F. , Michel Rossano D.L. , Sipp Gabriel S. , Ferronato João P.F.
Published: August 2024

Siliciclastic stromatolites are rare in the geologic record, and their occurrence recorded in the literature is restricted to marine and coastal environments. The Upper Jurassic Guará Formation, from the Paraná Basin in southern Brazil, hosts unique non-marine siliciclastic stromatolites, providing a rare opportunity to study trapping and binding mechanisms by microbial mats in a continental setting. These microbialites occur interbedded with eolian and fluvial facies. The structural layering of the stromatolite domes is formed by the intercalation of sandy layers, resulting from trapping and binding of siliciclastic grains by microbial mats and in situ precipitation of amorphous to cryptocrystalline silica, which directly replaced the microbial colonies. The silica layers contain partially preserved spherical to ovoid bodies interpreted as colonies of coccoid microorganisms. These siliciclastic stromatolites were formed due to a specific balance of environmental factors, namely water chemistry and sediment supply, which enhanced the processes of trapping and binding and in situ precipitation. They record the presence of microbial life in a non-marine, silica-rich, fluvial-eolian environment in which there were no previous published occurrences of agglutinated stromatolites. These specimens record macroscopically identifiable evidence of microbial life in a continental environment that must be accounted for in the search for ancient life on Earth and Mars.
Gut Microbiota Regulation by Acupuncture and Moxibustion: A Systematic Review and Meta-Analysis
Authors: Bae Sun-Jeong , Jang Yumi , Kim Yejin , Park Ji-Han , Jang Jae-Hwan , Oh Ju-Young , Jang Sun-Young , Ahn Sora , Park Hi-Joon
Published: August 2024

There have been numerous studies investigating the impact of acupuncture and/or moxibustion on the gut microbiota, but the results have been inconclusive. Therefore, we conducted a systematic review and meta-analysis that included both preclinical and clinical studies to assess the current evidence regarding the effects of acupuncture on gut microbiota changes. We collected relevant studies from EMBASE and PubMed, collected outcomes including diversity and relative abundance measures of the gut microbiome, and the summarized effect estimates were calculated using the ratio of means (ROM) with 95% confidence intervals. Our analysis identified three clinical studies and 20 preclinical studies, encompassing various diseases and models, including colitis and obesity. The pooled results indicated no significant difference in alpha diversity changes between treatment groups and controls, except for the Simpson index measure, which was significantly higher in the treatment groups. Additionally, the pooled results showed an increase in the Firmicutes and a decrease in the Bacteroidetes in the treatment groups, along with increases in the Lactobacillus and Ruminococcus genera. These findings suggest acupuncture treatment can target the modification of specific phyla and genera of gut microbiota. However, it is important to note that the effects of acupuncture on the gut microbiome are heterogeneous across studies, particularly in different disease models.
Liquiritigenin, an Active Ingredient of Liquorice, Alleviates Acute Kidney Injury by VKORC1-Mediated Ferroptosis Inhibition
Authors: Guo Run-Zhi , Li Jia , Pan Shao-Kang , Hu Ming-Yang , Lv Lin-Xiao , Feng Qi , Qiao Ying-Jin , Duan Jia-Yu , Liu Dong-Wei , Liu Zhang-Suo
Published: August 2024

Acute kidney injury (AKI) is a major public health problem worldwide that still lacks effective treatments. Recent studies have suggested that ferroptosis is a key mediator of AKI due to its activation of lipid peroxidation. Therefore, we hypothesized that antiferroptosis agents might be a novel potential therapeutic strategy for AKI. Herein, we demonstrated that liquiritigenin (LG), an active ingredient of liquorice, improves renal function by inhibiting vitamin K epoxide reductase complex subunit 1 (VKORC1)-mediated ferroptosis, both in vivo and in vitro. In a folic acid-induced murine AKI model, after a single pre-treatment intravenous injection, LG markedly alleviated the loss of renal function through suppressing ferroptosis induced by iron accumulation. LG prevented mitochondrial morphological changes and upregulated glutathione and glutathione peroxidase 4 levels, while downregulating malonaldehyde and divalent iron levels. An in vitro RNA-sequence analysis suggested that the protective role of LG may involve upregulation of VKORC1. Moreover, knockdown of VKORC1 diminished the renal protective and antiferroptosis roles of LG. Collectively, our findings demonstrated that LG protected against AKI by inhibiting VKORC1-mediated ferroptosis. This suggests that inhibiting ferroptosis might be a novel therapeutic approach in the future.
On the measurements in quantum gravity
Authors: Carrasco-Martinez Juanca
Published: August 2024

In this essay, we argue that certain aspects of the measurement require revision in Quantum Gravity. Using entropic arguments, we propose that the number of measurement outcomes and the accuracy (or the range) of the measurement are limited by the entropy of the black hole associated with the observer’s scale. This also implies the necessity of modifying the algebra of commutation relationships to ensure a finite representation of observables, changing the Heisenberg Uncertainty Principle in this manner.
MODELING A REHAB–RECOVERY–RELAPSE CYCLE WITH COMMUNITY DEPENDENCE VIA ODES
Authors: BULAI IULIA MARTINA , TEIXEIRA ANDREIA SOFIA
Published: August 2024

In this paper, we introduce a rehab–recovery–relapse cycle model to study the interaction between healthy individuals, individuals that might develop substance use disorders (SUD), which for simplicity here we will call susceptible individuals, individuals with SUD, and individuals recovered in a rehab community. We measure the community’s health through a system defined by four non-linear ordinary differential equations in which we include a rehab community. After computing the SUD-free and coexistence equilibrium points, we find the feasibility and stability conditions of an equivalent and reduced system obtained by nondimensionalizing the equations of the original model. We have numerically investigated the importance of the parameter values on the model’s outcome via a one- and two-strain parameter analysis. From the numerical results, we observe that an efficient rehab community can be characterized by (i) a high recovery rate (the individuals stay in that community as little time as possible) and (ii) permanent rehabilitation being preferred at the expense of a low recovery rate.
Data discretization impact on deep learning for missing value imputation of continuous data
Authors: Kumar Talluri Sunil , Neelakantan P. , Reddy G. Suresh , Gangappa Malige , Rajasekar M.
Published: August 2024

In various fields of information examination, for example, AI, profoundly getting the hang of missing information is a typical issue. Missing qualities should be tended to since they can adversely affect the exactness and adequacy of prescient models. This research investigates how data discretization affects deep learning methods for filling the missing values in datasets with continuous features. They provide a unique method for imputing missing values using deep neural networks (DNNs) called extravagant expectation maximization-deep neural network (EEM-DNN). This approach discretizes continuous features into separate intervals initially. This is justified by treating the issue of missing value imputation as a classification work, with the missing values being considered a distinct class. A DNN, designed explicitly for imputation, is then trained using the discretized data. The expectation maximization concepts are incorporated into the network architecture, and as a result, the network iteratively improves its imputation predictions. They run comprehensive experiments on several datasets from different fields to gauge the efficacy of the suggested strategy. The effectiveness of EEM-DNN is compared to that of other imputation approaches, such as traditional imputation techniques and deep learning methods without data discretization. Our findings show that data discretization significantly enhances imputation accuracy. In terms of imputation accuracy and prediction performance on downstream tasks, the EEM-DNN method regularly performs better than alternative methods. It also examines if various discretization techniques affect the overall imputation process. They find that the trade-off between bias and variance in imputed data depends on the discretization method selected. This highlights the significance of choosing a suitable discretization approach depending on the unique properties of the dataset.
WHEN AND HOW GREEN TRANSFORMATIONAL LEADERSHIP LEADS TO GREEN TECHNOLOGY INNOVATION: THE MEDIATION EFFECT OF GREEN INNOVATION CAPABILITY
Authors: WAQAS M. , KHAN A. RASHID , TAHIR A. HASEEB
Published: August 2024

Realising the customers’ demands for green products, green technology innovation (GTI) serves as the way for businesses to grow, seek continued profit, and attain a competitive edge. Based on a paper-based survey of 337 respondents from Chinese hi-tech companies, this study utilised PROCESS Macro to analyse the impact of green transformational leadership (GTL) style on GTI through green innovation capability (GIC). Also, the study examined the adjustment effect of green market orientation (GMO). The findings indicated a statistically significant and favorable relationship between GTL and GTI through GIC. It also provided evidence to support the notion that GMO has a constructive role in moderating the association between GIC and GTI. These findings provide valuable insights into sustainable practises within Chinese high-tech enterprises, thereby enhancing our comprehension of this subject. Additionally, the study offers practical implications for leadership tactics that promote green innovation.
Towards a theory of Inc-compatible term orders in polynomial rings in infinitely many variables
Authors: Bilal Hafiz Muhammad , Ahmad Sarfraz
Published: August 2024

Monomial ordering is the process of putting single polynomial terms, or monomials, in a certain order depending on predefined principles. It facilitates the systematic grouping and comparison of monomials, as well as the division and factorization of polynomials and other algebraic operations. Let [Formula: see text], be a polynomial ring over arbitrary field [Formula: see text], where [Formula: see text] is any fixed natural number. In this paper, we have defined different orderings like lexicographical, degree lexicographical and reverse degree lexicographical ordering on polynomial ring. We have discussed the infinitely many Inc-compatible term ordering on polynomial ring [Formula: see text] with respect to two different weight vectors [Formula: see text] and [Formula: see text]
On connectivity polynomial of graphs
Authors: Oboudi Mohammad Reza
Published: August 2024

In this paper we introduce a new graph polynomial, say connectivity polynomial. Let [Formula: see text] be a simple graph of order [Formula: see text]. The connectivity polynomial of [Formula: see text], denoted by [Formula: see text], is [Formula: see text], where [Formula: see text] and [Formula: see text] (for [Formula: see text]) is the number of connected induced subgraphs of [Formula: see text] with order [Formula: see text]. We investigate some properties of the connectivity polynomial. We find the connectivity polynomial of disjoint union and join of graphs. Finally, we find the coefficients of this polynomial in terms of the vertex connectivity and the order of graphs.
Deep Consistent-Inherent Learning for Cross-Modal Subspace Clustering
Authors: Feng Yuzhuo , Zhou Demin
Published: August 2024

Deep cross-modal clustering has been developing at a rapid pace and attracted great attention. It aims to pursue a consistent subspace from different modalities by conventional neural network and achieve remarkable clustering performance. However, most existing deep cross-modal clustering methods do not simultaneously take care of the inherently different information for each modality and local geometric structure for all cross-modal data, which inevitably results in the degradation of clustering performance. In this paper, we propose a novel method named Deep Consistent-Inherent Cross-Modal Subspace Clustering (i.e. DCCSC) to tackle these problems of cross-modal clustering. Our method can preserve the inherent independence of each modality while exploring the consistent information amongst different modalities. Meanwhile, a neighbor graph is embedded into the proposed deep cross-modal subspace clustering framework to maintain the local geometry structure of the original data and learn a shared subspace representation. Therefore, we integrate the consistent-inherent learning and the local structure learning into a unified deep framework to significantly improve the cross-modal subspace clustering performance. Experimental results demonstrate that our proposed method can achieve the superior clustering performance compared with the state-of-the-art methods on four benchmark datasets.
SPORT: A Subgraph Perspective on Graph Classification with Label Noise
Authors: Yin Nan , Shen Li , Chen Chong , Hua Xian-Sheng , Luo Xiao
Published: August 2024

Graph neural networks (GNNs) have achieved great success recently on graph classification tasks using supervised end-to-end training. Unfortunately, extensive noisy graph labels could exist in the real world because of the complicated processes of manual graph data annotations, which may significantly degrade the performance of GNNs. Therefore, we investigate the problem of graph classification with label noise, which is demanding because of the complex graph representation learning issue and serious memorization of noisy samples. In this work, we present a novel approach called
S
ubgra
p
h Set Netw
or
k with Sample Selection and Consis
t
ency Learning (SPORT) for this problem. To release the overfitting of GNNs, SPORT proposes to characterize each graph as a set of subgraphs generated by certain predefined stratagems, which can be viewed as samples from its underlying semantic distribution in graph space. Then we develop an equivariant network to encode the subgraph set with the consideration of the symmetry group. To further release the influences of noisy examples, we leverage the predictions of subgraphs to measure the likelihood of a sample being clean or noisy, followed by effective label updating. In addition, we propose a joint loss to advance the model generalizability by introducing consistency regularization. Comprehensive experiments on a wide range of graph classification datasets demonstrate the effectiveness of our SPORT. Specifically, SPORT outperforms the most competing baseline by up to 6.4%.
SeSMR: Secure and Efficient Session-based Multimedia Recommendation in Edge Computing
Authors: Li Fengyin , Liu Hongzhe , Li Guangshun , Wang Yilei , Zhou Huiyu , Cao Shanshan , Li Tao
Published: August 2024

Session-based multimedia recommendation in edge computing remains an important issue for boosting the utilization of services since service composition has increasingly attracted attention. Existing session-based recommendations (SBRs) model the session sequence with multilevel feature extraction in graph neural networks (GNNs). However, multilevel feature extraction in disentangled graph neural networks causes over-smoothing and privacy leakage. To address the aforementioned problems, Secure and Efficient Session-based Multimedia Recommendation (SeSMR) model is proposed. In the proposed SeSMR model, based on BGV homomorphic encryption, a ciphertext training submodel is proposed to address the privacy leakage, ensuring the security in session-based recommendation. Furthermore, based on the reinforcement of feature activation, a residual attention mechanism is proposed to mitigate over-smoothing while maintaining the independence of multiple features. Finally, based on location coding, a soft attention mechanism is proposed to improve the recommendation accuracy, by introducing the position difference information between items into intra-session and inter-session scenarios. Experiments demonstrate that both Recall and MRR metrics exhibit nearly 2%∼5% improvement.
Cross-Modal Face Super-Resolution Based on Quasi-Siamese Domain Transfer Fusion Network
Authors: Wen Jiaxing , Shen Aohong , Han Zhen , Wang Zhongyuan , Chen Liang
Published: August 2024

In this paper, we propose a Cross-Modal Face Super-Resolution (CMFSR) method to construct high-resolution (HR) facial images from low-resolution (LR) cross-modal facial images captured respectively by disjoint visible light (VIS) and near-infrared (NIR) cameras. Due to the coupling of modality transformation and information fusion, CMFSR is more difficult to obtain HR reconstructed results compared with traditional super-resolution. To solve this problem, a Quasi-Siamese Domain Transfer Fusion Network (QSDTFN) for CMFSR is proposed in this paper, whose two branches transfer two LR face modality to HR face modality by domain transfer respectively. Different from two completely independent branches in the traditional pseudo-siamese network, only the HR-to-LR face transfer processes of the two branches in our quasi-siamese network are independent, while the LR-to-HR face transfer processes are coupled. This coupled module called the Adaptive Weighted Domain Transfer Fusion Module (AWDTFM) disentangles the modality and identity information in the two LR faces, thus achieving modality transformation and identity information fusion simultaneously. In order to strengthen the optimization on the process of CMFSR, this method further introduces the backward QSDTFN to form a higher-level bidirectional structure with the forward QSDTFN, and specifically designs two types of losses: intra-network loss and inter-network loss, to constrain the modality and identity consistencies within one QSDTFN and between two QSDTFNs respectively. The experimental results on the challenging LR cross-modal face datasets demonstrate that the proposed method performs favorably against the state-of-the-art methods.
Denoising and Augmented Negative Sampling for Collaborative Filtering
Authors: Zhao Yuhan , Chen Rui , Lai Riwei , Han Qilong , Song Hongtao , Chen Li
Published: August 2024

Negative sampling plays a crucial role in implicit-feedback-based collaborative filtering, where it leverages massive unlabeled data to generate negative signals for guiding supervised learning. The current state-of-the-art approaches focus on utilizing hard negative samples that contain more information to establish a better decision boundary. To strike a balance between efficiency and effectiveness, most existing methods adopt a two-pass approach: in the first pass, a fixed number of unobserved items are sampled using a simple static distribution, while, in the second pass, a more sophisticated negative sampling strategy is employed to select the final negative items. However, selecting negative samples solely from the original items in a dataset is inherently restricted due to the limited available choices, and thus may not be able to effectively contrast positive samples. In this paper, we empirically validate this observation through meticulously designed experiments and identify three major limitations of existing solutions: ambiguous trap, information discrimination, and false negative samples.

Our response to such limitations is to introduce “denoised” and “augmented” negative samples that may not exist in the original dataset. This direction renders a few substantial technical challenges. First, constructing augmented negative samples may introduce excessive noise that eventually distorts the decision boundary. Second, the scarcity of supervision signals hampers the denoising process. To this end, we introduce a novel generic denoising and augmented negative sampling (DANS) paradigm and provide a concrete instantiation. First, we disentangle the hard and easy factors of negative items. Then, we regulate the augmentation of easy factors by carefully considering the direction and magnitude. Next, we propose a reverse attention mechanism to learn a user’s negative preference, which allows us to perform a dimension-level denoising procedure on hard factors. Finally, we design an advanced negative sampling strategy to identify the final negative samples, taking into account both the score function used in existing methods and a novel metric called synthesization gain. Through extensive experiments on real-world datasets, we demonstrate that our method substantially outperforms state-of-the-art baselines. Our code is publicly available at https://github.com/Asa9aoTK/ANS-Recbole.
Synergistic effects of glucose tolerance and BMI on cardiovascular events and all-cause mortality in a healthy population: CA.ME.LI.A study 7 years follow-up
Authors: Bignotto Monica , Bianco Elena , Centofanti Lucia , Russo Antonio , Dei Cas Michele , Zermiani Paola , Morano Camillo , Samartin Federica , Bertolini Emanuela , Bifari Francesco , Berra Cesare , Zuin Massimo , Paroni Rita , Battezzati Pier Maria , Folli Franco
Published: August 2024

For the first time, the combined effects of glucose tolerance and BMI have been investigated in an apparently healthy large population sample of a city in the north of Italy. We found that there are synergistic effects of glucose levels with BMI to increase not only cardiovascular events and deaths but also cancer-related deaths and all-cause mortality.
Intermittent fasting increases fat oxidation and promotes metabolic flexibility in lean mice but not obese type 2 diabetic mice
Authors: Conn Meghan O. , Marko Daniel M. , Schertzer Jonathan D.
Published: August 2024

We show that a 5:2 intermittent fasting regimen can increase lipid oxidation without altering body mass in lean mice. Therefore, repeated intermittent fasting can increase metabolic flexibility without the need for (or prior to) weight loss. Intermittent fasting did not increase lipid oxidation in mice with obesity and type 2 diabetes, highlighting that obesity and/or type 2 diabetes limit changes in metabolic flexibility and mitigate increased fatty acid oxidation without weight loss during intermittent fasting.
Secreted GDF15 maintains transcriptional responses during DNA damage-mediated senescence in human beta cells
Authors: Rampazzo Morelli Nayara , Préfontaine Camille , Pipella Jasmine , Thompson Peter J.
Published: August 2024

Beta cell senescence is an emerging contributor to the pathogenesis of type 1 diabetes, but candidate therapeutic targets have not been identified in human beta cells. In this study, we examined the role of a secreted factor, GDF15, and found that although it is not required to maintain viability during senescence, it is required to fine-tune gene expression programs involved in the senescence response during DNA damage in human beta cells.
On the genesis and unique functions of zinc neuromodulation
Authors: Bizup Brandon , Tzounopoulos Thanos
Published: August 2024

In addition to the essential structural and catalytic functions of zinc, evolution has adopted synaptic zinc as a neuromodulator. In the brain, synaptic zinc is released primarily from glutamatergic neurons, notably in the neocortex, hippocampus, amygdala, and auditory brainstem. In these brain areas, synaptic zinc is essential for neuronal and sensory processing fine-tuning. But what niche does zinc fill in neural signaling that other neuromodulators do not? Here, we discuss the evolutionary history of zinc as a signaling agent and its eventual adoption as an essential neuromodulator in the mammalian brain. We then attempt to describe the unique roles that zinc has carved out of the vast and diverse landscape of neuromodulators.
Predictors of Mortality, Drug Resistance, and Determinants among Carbapenem‐Resistant Enterobacterales Infections in Chinese Elderly Patients
Authors: Zhang Yufei , Zou Chengyun , Qin Jie , Li Muyi , Wang Xing , Wei Tian , Wang Haiying
Published: August 2024

Elderly patients with carbapenem‐resistant Enterobacterales (CRE) infections represent considerable mortality rates. But data on the risk factors for the death of elderly patients following such infection remain limited. We aimed to assess the clinical outcomes, identify mortality‐associated risk factors, and determine the antibiotic resistance and resistance genes of isolates for these patients. Hospitalized patients aged ≥65 years with CRE infection from January 2020 to December 2020 were retrospectively reviewed. Isolates identification and molecular characterization of CRE were carried out. Logistic regression analysis was applied to assess the potential factors associated with mortality. Of the 123 elderly patients with CRE infection included in our study, the all‐cause mortality rate was 39.8% (49/123). The most prevalent pathogen was carbapenem‐resistant Klebsiella pneumoniae (CRKP, 116 of 123). The overall rates of multidrug‐resistant (MDR) and extensively drug‐resistant (XDR) were 100.0% and 66.7%. All CRE isolates exclusively harbored a singular variant of carbapenemase gene, such as blaKPC−2, blaIMP−4, blaNDM−5, or blaOXA−48, while 98.4% of isolates harbored more than one β‐lactamase gene, of which 106 (86.2%) isolates harbored blaCTX−M, 121 (98.4%) isolates harbored blaTEM, and 116 (94.3%) isolates harbored blaSHV. Multivariable logistic regression analysis revealed that mechanical ventilation (adjusted odds ratio (AOR) = 33.607, 95% confidence interval (CI): 4.176‐270.463, P < 0.001), use of tigecycline during hospitalization (AOR = 5.868, 95% CI: 1.318‐26.130, P = 0.020), and APACHE II score (AOR = 1.305, 95% CI: 1.161–1.468, P < 0.001) were independent factors associated with increasing the mortality of patients with CRE infection, while admission to intensive care unit (ICU) during hospitalization (AOR = 0.046, 95% CI: 0.004–0.496, P = 0.011) was a protective factor. CRE‐infected elderly patients with mechanical ventilation, use of tigecycline during hospitalization, and high APACHE II score were related to poor outcomes. The isolates carried various antibiotic genes and presented high antibiotic resistance. These findings provide crucial guidance for clinicians to devise appropriate strategies for treatment.
Rolling Bearings Fault Diagnosis under Variable Speed Conditions Based on Multitime‐Frequency Ridge Extraction
Authors: Xiong Qing , Li Yixuan , Qiu Xiaoli , Yu Dong , Zhang Weihua , Chen Qingze
Published: August 2024

The vibration signals of rolling bearings under variable speed conditions exhibit time‐varying, nonstationary, and nonlinear characteristics, making it challenging to extract fault features. A fast path optimization‐based multitime‐frequency ridge extraction (FPOMRE) method is proposed in this paper to address the problem. First, the time‐frequency representation of the fault signal is obtained through the adaptive short‐time Fourier transform (STFT), and then the FPOMRE algorithm is used to extract additional ridges below the lowest time‐frequency ridge multiple times. The frequency ratio of each ridge to the additional ridge, the average value of the ratio, and the variance of the ratio are calculated, respectively, and finally, the matching degree between the average ratio and the fault feature coefficient is compared with the diagnosis of the bearing fault. The simulation and experimental results show that the FPOMRE method can effectively diagnose the bearing fault under constant speed and variable speed conditions, and the extraction accuracy of time‐frequency ridges under constant speed is higher than that under variable speed, and the extraction accuracy under high speed is higher than that under low speed. The relative error of extracting rotation frequency under constant speed and variable speed is 0.5% and 1.3%, respectively. In addition, comparing the FPOMRE with the maximum amplitude method (MAM), both FPOMRE and MAM can effectively extract the instantaneous shaft rotation frequency at a constant speed. However, under variable speed conditions, the ridge extracted by FPOMRE has a higher accuracy and lower average processing time than that extracted by MAM.
The Impact of Artificial Intelligence Applications on Digital Banking in Turkish Banking Industry
Authors: Demirel Serkan , Topcu Murat
Published: August 2024

This paper presents the effects of chat box (C.B.) and video call (V.C.) artificial intelligence applications, which are becoming increasingly common in the banking system in parallel with the development of information systems on the number of digital banking users, and the relationship between the variables is investigated. The data set of the variables consists of a total of 44 observation points between the 1st quarter of 2012 and the 4th quarter of 2022. The cointegration relationship between the variables is examined using the ARDL cointegration test. According to the F statistic results for cointegration hypothesis testing, there is a statistically significant relationship between the variables at a 1% significance level. In the long run, a 1% increase in Chat Box users causes an increase of approximately 0.2% in the number of mobile banking users. A 1% increase in Chat Box users in the short term increases the number of mobile banking users in the current period by approximately 0.03%. A 1% increase in video call users in the long term causes an increase of approximately 0.04% in the number of mobile banking users. A 1% increase in the number of video calls in the current period increases current period mobile banking applications by approximately 0.005%. It has been determined that the effect of chat box applications on mobile banking is higher than that of video call applications. In addition, there is a close correlation between mobile banking and the independent variable chat box, no correlation between mobile banking and video calling, and a moderate correlation between chat box and video calling. All findings mean that artificial intelligence applications positively contribute to the expansion of mobile banking.
Figure 5 from Characterizing Relationships between T-cell Inflammation and Outcomes in Patients with High-Risk Neuroblastoma According to Mesenchymal and Adrenergic Signatures
Authors: Kaufman Maria E. , Vayani Omar R. , Moore Kelley , Chlenski Alexandre , Wu Tong , Lee Sang Mee , Desai Ami V. , He Chuan , Cohn Susan L. , Applebaum Mark A.
Published: August 2024

Inflammation score may be associated with for OS in high-risk, adrenergic tumors. A, OS was significantly better for TCI tumors than NI tumors in ADRN patients in the Discovery cohort and B, trended similarly in the Validation cohort. C, There was no difference in survival for patients with MES tumors according to TCI status in the Discovery cohort. D, the MES patients in the Validation also had no difference in OS according to the TCI status.
Effects of a pH-Regulating Emollient Cream in Mild Atopic Dermatitis Patients with Moderate Localized Lesions
Authors: Ng Sue Phay , Bielfeldt Stephan , Laing Sabrina , Danby Simon , Cork Michael J. John
Published: August 2024

Introduction: Increased skin pH values in patients with atopic dermatitis (AD) contribute to poor antimicrobial and permeability barrier functions of the skin. In practice, the majority of topical preparations available for dry skin conditions do not provide sufficient pH and buffering capacity for maintaining optimum skin surface conditions. To address this issue, we tested a novel zinc lactobionate preparation to determine whether the regular application would lower skin surface pH, and in doing so improve the condition of lesional skin. Methods: The assessment for local severity of AD was done with the Scoring Atopic Dermatitis Index (SCORAD) and skin dryness was assessed by capacitance measurement. Results: The results showed that the test product lowered skin pH and improved AD skin lesions from moderate to mild during 2 weeks of application. In the treated area a lowered pH of about 0.85 units was found. Together with the lowering of pH, the local SCORAD significantly improved from 8.3 on average down to 4.0, while in the untreated area, only a slight improvement (from 8.2 to 6.4) was found. Conclusion: Synergistic effects of the test product’s pH lowering and emollient properties might explain the observed improvements in clinical signs of AD and further research against a comparator would allow the specific contribution of pH modulation to these improvements to be unambiguously isolated.
Real-World Impact of Routine Addition of Antithymocyte Globulin to Standard GVHD Prophylaxis in Myeloablative Unrelated Donor Transplants: Important Gains in Graft-versus-Host Disease Prevention though No Difference in Overall Survival
Authors: Bai Ni , Limvorapitak Wasithep , Henderson Robert , Abou Mourad Yasser , Chung Shanee , Forrest Donna , Hay Kevin , Kuchenbauer Florian , Nantel Stephen , Narayanan Sujaatha , Nevill Thomas , Power Maryse , Rodrigo Judith , Roy Claudie , Sanford David , Song Kevin , Stubbins Ryan , Sutherland Heather , Toze Cynthia , White Jennifer
Published: August 2024

Introduction: Antithymocyte globulin (ATG) has been demonstrated to reduce the incidence of graft-versus-host disease (GVHD); however, it remains controversial whether these gains are offset by an increase in relapse. Methods: We conducted a retrospective historical control study consisting of patients (n = 210) who underwent myeloablative allogeneic hematopoietic stem-cell transplantation (HSCT) from 2014 to 2020. Results: The incidence of acute GVHD was lower in the ATG group (51.4%) than the non-ATG group (control) (70.0%, p = 0.010). The incidence of chronic GVHD was also lower in the ATG group at 1-year (36.4% vs. 62.9%, p < 0.001) and 2-year (40.0% vs. 65.7%, p < 0.001) post-HSCT. The mortality due to GVHD was higher in the control (18.5%) than the ATG group (4.3%; p = 0.024). The severe GVHD-relapse-free survival was higher in the ATG group (36.4%) than the control (12.9%; p < 0.001). Nevertheless, the 2-year overall survival was similar. Conclusion: Our results confirm the effectiveness of ATG in prevention of GVHD in the real-world setting and enhanced GVHD-free survival. An important result is the equalization of overall survival between the ATG and control groups at 1- and 2-year post-HSCT and implies that earlier GVHD-associated mortality may be offset by later relapse mortality producing similar overall survival over time.
Shoulder Joint Range of Motion Related to Dementia
Authors: Honjo Yasuyuki , Nagai Kuniaki , Yuri Takuma , Nakai Hideaki , Kawasaki Ippei , Harada Shun , Suganuma Ippei , Ogawa Noriyuki
Published: August 2024

Introduction: Dementia is caused by various diseases, including Alzheimer’s disease dementia (ADD) and dementia with Lewy bodies (DLB). We often encounter patients with dementia who have limited shoulder joint range of motion (ROM), especially those with behavioral and psychological symptoms of dementia (BPSD). But the relationship between the diseases of dementia and restricted shoulder joint ROM is currently unclear. Methods: We examined cognitive function and shoulder joint ROM in 234 new outpatients at 7 memory clinics in Japan. We assessed cognitive function using the Mini-Mental State Examination (MMSE) and Revised Hasegawa Dementia Scale (HDS-R) and BPSD using the Neuropsychiatric Inventory Questionnaire (NPI-Q). Patients were categorized by dementia diagnosis (ADD, DLB, other dementia, and control). Right, left, and total shoulder joint ROM was assessed using validated the Japanese Orthopaedic Association (JOA) score. Results: We found significant associations of lower right, left, and total shoulder joint ROM scores with male sex, advanced age, higher NPI-Q score, lower HDS-R, and MMSE scores. Little difference was found between right and left shoulder joint ROM scores. Restricted shoulder joint ROM was related to serial 7, verbal frequency domain scores on the HDS-R and repeat score on the MMSE. It was also related to the hallucinations, irritability/lability and nighttime disturbances scores on the NPI-Q. Furthermore, the dementia groups, especially the DLB group, showed worse shoulder joint ROM than the control group. Conclusions: Dementia was significantly related to restricted shoulder joint ROM. Maintaining communication and social interaction may help maintain shoulder joint ROM.
O Estado e a produção de convenções sociais acerca do mercado de armas de fogo no Brasil
Authors: Vieira Mateus Tobias , Jardim Maria Chaves
Published: August 2024

The article analyzes the role of the state in formulating social conventions about firearms in Brazil. We selected Law 10.826/2003, passed during the first Lula Government (2003-2006),as the empirical dispute, and also we analyzed eight presidential decrees from the first year ofthe Bolsonaro Government (2019). In the methodology, we analyzed the legal framework based on the studies of Steiner and Trespeuch, about contested markets;  Bourdieu, about the state and the concept of social convention, by Mary Douglas. The results indicate that the state has influenced the production of predispositions and that the disarmamentist social convention, produced during the Lula Government, has been  challenged, generating disputes that go  beyond the normative perspective.