bluuebunny/crossref_metadata_2025 huggingface dataset:
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning
Authors: Zhang Xinyi , Chang Zhuo , Wu Hong , Li Yang , Chen Jia , Tan Jian , Li Feifei , Cui Bin
Published: June 2023

Recently using machine learning (ML) based techniques to optimize the performance of modern database management systems (DBMSs) has attracted intensive interest from both industry and academia. With an objective to tune a specific component of a DBMS (e.g., index selection, knobs tuning), the ML-based tuning agents have shown to be able to find better configurations than experienced database administrators (DBAs). However, one critical yet challenging question remains unexplored -- how to make those ML-based tuning agents work collaboratively. Existing methods do not consider the dependencies among the multiple agents, and the model used by each agent only studies the effect of changing the configurations in a single component. To tune different components for DBMS, a coordinating mechanism is needed to make the multiple agents be cognizant of each other. Also, we need to decide how to allocate the limited tuning budget (e.g., time and resources) among the agents to maximize the performance. Such a decision is difficult to make since the distribution of the reward (i.e., performance improvement) corresponding to each agent is unknown and non-stationary. In this paper, we study the above question and present a unified coordinating framework to efficiently utilize existing ML-based agents. First, we propose a message propagation protocol that specifies the collaboration behaviors for agents and encapsulates the global tuning messages in each agent's model. Second, we combine Thompson Sampling, a well-studied reinforcement learning algorithm with a memory buffer so that our framework can allocate the tuning budget judiciously in a non-stationary environment. Our framework defines the interfaces adapted to a broad class of ML-based tuning agents, yet simple enough for integration with existing implementations and future extensions. Based on extensive evaluations, we show that this framework can effectively utilize different ML-based agents and find better configurations with 1.4~14.1x speedups on the workload execution time compared with baselines.
WISK: A Workload-aware Learned Index for Spatial Keyword Queries
Authors: Sheng Yufan , Cao Xin , Fang Yixiang , Zhao Kaiqi , Qi Jianzhong , Cong Gao , Zhang Wenjie
Published: June 2023

Spatial objects often come with textual information, such as Points of Interest (POIs) with their descriptions, which are referred to as geo-textual data. To retrieve such data, spatial keyword queries that take into account both spatial proximity and textual relevance have been extensively studied. Existing indexes designed for spatial keyword queries are mostly built based on the geo-textual data without considering the distribution of queries already received. However, previous studies have shown that utilizing the known query distribution can improve the index structure for future query processing. In this paper, we propose WISK, a learned index for spatial keyword queries, which self-adapts for optimizing querying costs given a query workload. One key challenge is how to utilize both structured spatial attributes and unstructured textual information during learning the index. We first divide the data objects into partitions, aiming to minimize the processing costs of the given query workload. We prove the NP-hardness of the partitioning problem and propose a machine learning model to find the optimal partitions. Then, to achieve more pruning power, we build a hierarchical structure based on the generated partitions in a bottom-up manner with a reinforcement learning-based approach. We conduct extensive experiments on real-world datasets and query workloads with various distributions, and the results show that WISK outperforms all competitors, achieving up to 8× speedup in querying time with comparable storage overhead.
PolarDB-IMCI: A Cloud-Native HTAP Database System at Alibaba
Authors: Wang Jianying , Li Tongliang , Song Haoze , Yang Xinjun , Zhou Wenchao , Li Feifei , Yan Baoyue , Wu Qianqian , Liang Yukun , Ying ChengJun , Wang Yujie , Chen Baokai , Cai Chang , Ruan Yubin , Weng Xiaoyi , Chen Shibin , Yin Liang , Yang Chengzhong , Cai Xin , Xing Hongyan , Yu Nanlong , Chen Xiaofei , Huang Dapeng , Sun Jianling
Published: June 2023

Cloud-native databases have become the de-facto choice for mission-critical applications on the cloud due to the need for high availability, resource elasticity, and cost efficiency. Meanwhile, driven by the increasing connectivity between data generation and analysis, users prefer a single database to efficiently process both OLTP and OLAP workloads, which enhances data freshness and reduces the complexity of data synchronization and the overall business cost.

In this paper, we summarize five crucial design goals for a cloud-native HTAP database based on our experience and customers' feedback, i.e., transparency, competitive OLAP performance, minimal perturbation on OLTP workloads, high data freshness, and excellent resource elasticity. As our solution to realize these goals, we present PolarDB-IMCI, a cloud-native HTAP database system designed and deployed at Alibaba Cloud. Our evaluation results show that PolarDB-IMCI is able to handle HTAP efficiently on both experimental and production workloads; notably, it speeds up analytical queries up to ×149 on TPC-H (100GB). PolarDB-IMCI introduces low visibility delay and little performance perturbation on OLTP workloads (<5%), and resource elasticity can be achieved by scaling out in tens of seconds.
Deep Learning Models for Serendipity Recommendations: A Survey and New Perspectives
Authors: Fu Zhe , Niu Xi , Maher Mary Lou
Published: June 2023

Serendipitous recommendations have emerged as a compelling approach to deliver users with unexpected yet valuable information, contributing to heightened user satisfaction and engagement. This survey presents an investigation of the most recent research in serendipity recommenders, with a specific emphasis on deep learning recommendation models. We categorize these models into three types, distinguishing their integration of the serendipity objective across distinct stages: pre-processing, in-processing, and post-processing. Additionally, we provide a review and summary of the serendipity definition, available ground truth datasets, and evaluation experiments employed in the field. We propose three promising avenues for future exploration: (1) leveraging user reviews to identify and explore serendipity, (2) employing reinforcement learning to construct a model for discerning appropriate timing for serendipitous recommendations, and (3) utilizing cross-domain learning to enhance serendipitous recommendations. With this review, we aim to cultivate a deeper understanding of serendipity in recommender systems and inspire further advancements in this domain.
Hydrodynamical Simulations of the Galaxy Population: Enduring Successes and Outstanding Challenges
Authors: Crain Robert A. , van de Voort Freeke
Published: June 2023

We review the progress in modeling the galaxy population in hydrodynamical simulations of the ΛCDM cosmogony. State-of-the-art simulations now broadly reproduce the observed spatial clustering of galaxies; the distributions of key characteristics, such as mass, size, and SFR; and scaling relations connecting diverse properties to mass. Such improvements engender confidence in the insight drawn from simulations. Many important outcomes, however, particularly the properties of circumgalactic gas, are sensitive to the details of the subgrid models used to approximate the macroscopic effects of unresolved physics, such as feedback processes. We compare the outcomes of leading simulation suites with observations, and with each other, to identify the enduring successes they have cultivated and the outstanding challenges to be tackled with the next generation of models. Our key conclusions include the following:▪Realistic galaxies can be reproduced by calibrating the ill-constrained parameters of subgrid feedback models. Feedback is dominated by stars and black holes in low-mass and high-mass galaxies, respectively.▪Adjusting or disabling the processes implemented in simulations can elucidate their impact on observables, but outcomes can be degenerate.▪Similar galaxy populations can emerge in simulations with dissimilar feedback implementations. However, these models generally predict markedly different gas flow rates into, and out of, galaxies and their halos. CGM observations are thus a promising means of breaking this degeneracy and guiding the development of new feedback models.
Regulation of TORC2 Function and Localization in Yeast
Authors: Emmerstorfer-Augustin Anita , Thorner Jeremy
Published: June 2023

Every eukaryotic cell contains two distinct multisubunit protein kinase complexes that each contain a TOR (target of rapamycin) protein as the catalytic subunit. These ensembles, designated TORC1 and TORC2, serve as nutrient and stress sensors, signal integrators, and regulators of cell growth and homeostasis, but they differ in their composition, localization, and function. TORC1, activated on the cytosolic surface of the vacuole (or, in mammalian cells, on the cytosolic surface of the lysosome), promotes biosynthesis and suppresses autophagy. TORC2, located primarily at the plasma membrane (PM), maintains the proper levels and bilayer distribution of all PM components (sphingolipids, glycerophospholipids, sterols, and integral membrane proteins), which are needed for the membrane expansion that accompanies cell growth and division and for combating insults to PM integrity. This review summarizes our current understanding of the assembly, structural features, subcellular distribution, and function and regulation of TORC2, obtained largely through studies conducted with Saccharomyces cerevisiae.
Global Risk, Non-Bank Financial Intermediation, and Emerging Market Vulnerabilities
Authors: Chari Anusha
Published: June 2023

Over the last two decades, the unprecedented increase in non-bank financial intermediation, particularly the rise of open-end mutual funds and exchange-traded funds, accounts for nearly half of the external financing flows to emerging markets, exceeding cross-border lending by global banks. Evidence suggests that investment fund flows enhance risk sharing across borders and provide emerging markets access to more diverse forms of financing. However, a growing body of evidence also indicates that investment funds are inherently more vulnerable to liquidity and redemption risks during periods of global financial market stress, increasing the volatility of capital flows to emerging markets. Benchmark-driven investments, namely passive funds, appear particularly sensitive to global risk shocks, such as tightening US dollar funding conditions, compared to their active fund counterparts. The procyclicality of investment fund flows to emerging markets during times of global stress poses financial stability concerns, with implications for the role of macroprudential policy.
Lessons from US–China Trade Relations
Authors: Caliendo Lorenzo , Parro Fernando
Published: June 2023

We review theoretical and empirical work on the economic effects of the United States and China trade relations during the past 20 years. We first discuss the origins of the China shock and its measurement and present methods used to study its economic effects on different outcomes. We then focus on the recent US–China trade war. We review methods used to evaluate its effects, describe its economic effects, and analyze whether this increase in trade protectionism reverted the effects of the China shock. The main lessons learned in this review are that (a) the aggregate gains from US–China trade created winners and losers; (b) China's trade expansion seems not to be the main cause of the decline in US manufacturing employment during the same period; and (c) the recent trade war generated welfare losses, had small employment effects, and was ineffective in reversing the distributional effects due to the China shock.
Fiscal Capacity: An Asset Pricing Perspective
Authors: Jiang Zhengyang , Lustig Hanno , Van Nieuwerburgh Stijn , Xiaolan Mindy Z.
Published: June 2023

This review revisits the literature on fiscal capacity using modern tools from asset pricing. We find that properly accounting for aggregate risk substantially reduces fiscal capacity. In this environment, the gap between the risk-free rate and the expected growth rate is not a sufficient statistic for fiscal capacity. To borrow at the risk-free rate when aggregate growth is risky, governments need to ask taxpayers to insure bondholders against aggregate risk, but governments in advanced economies tend to insure taxpayers against aggregate risk. We use this asset pricing perspective to review alternative mechanisms to boost fiscal capacity that have been explored in the literature.
Food Losses in Agrifood Systems: What We Know
Authors: Delgado Luciana , Schuster Monica , Torero Maximo
Published: June 2023

In 2015, the United Nations and the G20 put food loss and food waste on the global agenda. While progress has been made since then, the scale of the problem persists because food loss and food waste are measured together, not separately. The paucity of data also poses a challenge. This article reviews the measurements, causes, and determinants of food loss as well as the interventions to reduce it. The review finds that food loss is considered in isolation, even though it is one of the causes and results of how agrifood systems function. The review calls for improved microdata collection and standardized measurements to separate food loss from food waste. Such efforts would help integrate feedback loops and cascading effects across the value chain with agrifood systems to identify intervention hot spots, trade-offs, and synergies of interventions as well as the effects of food loss reduction on socioeconomic, environmental, and food security goals.
The Effects of Temperature on Labor Productivity
Authors: Lai Wangyang , Qiu Yun , Tang Qu , Xi Chen , Zhang Peng
Published: June 2023

This article reviews recent economic studies on the causal effects of temperature on labor productivity. The negative effects of extreme temperatures are widespread, and the magnitudes of the impact differ across social and economic factors. In addition to physical outputs, extreme temperatures also impair mental productivity, including cognition and learning. In utero exposure to extreme temperatures has profound effects on human development. Although the literature has detected various adaptation strategies, the conclusions are mixed. We discuss some limitations of existing studies and propose several directions for future research.
Advances in Causal Inference at the Intersection of Air Pollution and Health Outcomes
Authors: Brewer Dylan , Dench Daniel , Taylor Laura O.
Published: June 2023

This article provides an overview of the recent economics literature analyzing the effect of air pollution on health outcomes. We review the common approaches to measuring and modeling air pollution exposures and the epidemiological and biological literature on health outcomes that undergird federal air regulations in the United States. The article contrasts the methods used in the epidemiology literature with the causal inference framework used in economics. In particular, we review the common sources of estimation bias in epidemiological approaches that the economics literature has sought to overcome with research designs that take advantage of natural experiments. We review new promising research designs for estimating concentration-response functions and identify areas for further research.
Sensitivity Analysis of Al0.3Ga0.7N/GaN Dielectric Modulated MOSHEMT Biosensor
Authors: Dastidar Ananya , Patra Tapas Kumar , Mohapatra Sushanta Kumar , Braim Mona , Pandiaraj Saravanan , Alshammari Abeer , Alodhayb Abdullah N.
Published: June 2023

Emerging and newly proposed devices integrate various materials at different scales (from nano to submicron), which reveals sensor response. Prefab simulation is in great demand to elucidate fundamental biosensor phenomena that are based on transistors. Numerous HEMT-based biosensors have been developed, however, MOSHEMT deserves to be further investigated. The sensitivity analysis with neutral and charged biomolecules is thus carried out in this research using a single gate high-κ dielectric MOSHEMT through Technology Computer Aided Design simulation. The device performance is evaluated through the shift (sensing action) of device parameters like Two-Dimensional Electron Gas, on-current, transconductance, drain current and output conductance due to the immobilization of biomolecules in the cavity created under the gate. For the neutral biomolecule (

κ
=
8

), the fluctuation in on-current, transconductance, drain current, and output conductance is determined to be 330.3 μA μm−1, 102.0 μS μm−1, 319.0 μA μm−1, and 534.9 μS μm−1, respectively. Positively charged biomolecules were more sensitive to the device than negatively charged ones. Analysis is done on the response to the fill rates of the biomolecules in the cavity. For the vertical, horizontal, and tapered profiles, the transconductance sensitivities are 0.65, 0.17, and 0.32 and the drain current sensitivities are 0.25, 0.16, and 0.27 at the lowest fill (25%). In light of this, the AlGaN/GaN dielectric modulated MOSHEMT assures that the device can be used in sensitive intelligent biomedical applications.
Differential sensitivity to Wnt signaling gradients in human gastric organoids derived from corpus and antrum
Authors: McGowan Kevin P. , Delgado Elizabeth , Hibdon Elise S. , Samuelson Linda C.
Published: June 2023

This study demonstrates that human gastric corpus organoids have a lower Wnt signaling threshold to drive optimal growth relative to patient-matched antral organoids. Paradoxically, supramaximal Wnt levels suppress corpus organoid proliferation, yet promote differentiation toward deep glandular cell types while simultaneously enhancing progenitor cell function. These findings provide novel insights into how Wnt signaling differentially regulates homeostasis in the human gastric corpus and antrum and contextualizes patterns of Wnt activation diseases.
Thoracoabdominal asynchrony in a virtual preterm infant: computational modeling and analysis
Authors: Foster Richard R. , Smith Bradford , Ellwein Fix Laura
Published: June 2023

A novel model of thoracoabdominal asynchrony incorporates literature-derived mechanics and simulates the impact of risk factors on a virtual preterm infant. Sensitivity analyses were performed to determine the influence of model parameters on TAA and respiratory volume. Predicted phase angles are consistent with prior experimental and clinical results, and influential parameters are associated with clinical scenarios that significantly alter phase angle, motivating further investigation into the use of computational modeling for assessing and managing thoracoabdominal asynchrony.
A Weak-Coupling Flow-Power Forecasting Method for Small Hydropower Station Group
Authors: Chen Biyun , Long Yujia , Wei Hua , Li Bin , Zhang Yongjun , Deng Wenyang , Li Canbing
Published: June 2023

Due to the need for rural revitalization and renewable energy utilization, a large quantity of small hydropower stations is emerging, with weak-coupling flow-power features. However, a weak spatial coupling exists between the distribution of small hydropower station groups (SHSGs) and gaging stations since the small hydropower stations are usually located in remote areas lacking hydrographic facilities. That may cause weak or no coupling between the hydroregime and the power output of small hydropower plants in the target basin, thus hindering accurate power forecasting. To meet the need for short-term power generation prediction for SHSGs in intensive management areas, we propose a data-driven power-forecasting model which can mine the correlation information of weakly coupled basins while transferring hydrological knowledge to uncoupled basins. First, to make the task data domains before and after migration more similar, a similar watershed matching algorithm based on the nonlinear dimensionality reduction algorithm (Isomap) and the

k

-means++ algorithm is proposed; then a short-term interpretable runoff prediction model is pretrained, and features are extracted in the source basin using the temporal fusion transformer (TFT) network. After that, a heuristic ensemble fine-tuning model based on the

k

-fold cross-validation fine-tuning method and heuristic ensemble algorithm is proposed to transfer the public knowledge of the source basin to the uncoupled basin. Then, a TFT network is used to mine the weak-coupling relationship between the hydrological regime and the output power of an SHSG. Finally, the validity of the model is verified with an example from a European region. After considering the weakly coupled flow-power characteristics, the mean absolute percentage error (MAPE) of three SHSGs’ power prediction by the proposed method is on average 34.8% lower than that of the method without considering the hydrological information.
A Cold-Inducible RNA Binding Protein Gene from Acanthopagrus schlegelii: Molecular Characterization, Expression, and Association with Apoptosis to Low-Temperature Stress
Authors: Mingliang Wei , Mingjun Shen , Yue Wang , Bo Gao , Ruijian Sun , Yali Qin , Jianbin Jiang , Jianlou Zhou , Jing Shen , Xiaojian Tang , Zhiyong Zhang , Zhiwei Zhang
Published: June 2023

In this study, the complete cDNA sequence (1552 bp) of the cold-inducible RNA binding protein gene (cirbp gene) was successfully cloned from the liver in Acanthopagrus schlegelii (initial weight: 15.0 ± 2.3 g). Results showed that Ascirbp (cirbp gene from A. schlegelii) gene has 24 phosphorylation sites, no signal peptide, and no transmembrane helix structure. AsCIRBP, with a molecular weight of 18.84 ku and an isoelectric point of 9.04 was a stable protein that encodes 182 amino acids. Subcellular localization analysis of this protein showed that it was located in the nucleus. Sequence alignment results showed that the AsCIRBP amino acid sequences of various fishes including black porgy were highly conserved, especially the RNA recognition motif (RRM). Those results of real-time quantitative PCR (qRT-PCR) demonstrated that Ascirbp gene was specifically expressed in the liver tissue of black porgy and its expression was significantly increased under cold stress or cold acclimation. The RNA interference experiment results showed that Ascirbp-dsRNA could suppress the expression of Ascirbp gene in the liver of black porgy through intraperitoneal injection. After silencing the expression of Ascirbp gene, RNAi groups were more severely damaged in the structure of the liver tissue and more prone to apoptosis under cold stress than control groups. The results of the study on the linkage between Ascirbp gene expression and mitochondrial apoptosis pathways showed that changes in the expression of the Ascirbp gene had a significant effect on the expression of key genes of apoptosis. The most striking result from silencing the expression of the Ascirbp gene was that expressions of the bcl-2 and apaf-1 gene in the liver of black porgy decreased significantly, which can block the normal apoptotic process. After the disruption of the normal apoptotic process, the expressions of p53, bax, cyto-c, caspase-9, caspase-3, diablo, and caspase-1 gene were significantly affected. These results suggest that Ascirbp gene can inhibit apoptosis and protect tissue structure in the liver tissue of black porgy at low temperatures.
Modelling the Potential Human Exposure to Japanese Encephalitis Virus (JEV) in Case of Introduction into Reunion Island
Authors: Ladreyt Héléna , Garros Claire , Habchi-Hanriot Nausicaa , Dupraz Marlène , Baldet Thierry , Chevalier Véronique , Durand Benoit
Published: June 2023

Japanese encephalitis virus (JEV) is a vector-borne zoonotic virus and the leading cause of human acute encephalitis in Asia. Continuous human and commercial exchanges between Southeast Asia where JE is endemic and Reunion Island increase the risk of introducing JEV on the island, where putative vectors of JEV such as Culex quinquefasciatus and amplifying hosts such as pigs are present. Each of the 255 Reunionese pig farms was assumed to harbor a Cx. quinquefasciatus population and, together with the competent hosts: pigs and poultry and noncompetent hosts: humans, dogs, and cattle, located within a radius of 1 km, formed an epidemiological unit. We used a deterministic compartmental model to investigate whether these epidemiological units could be invaded by JEV in the event of an introduction. Since the vector population size changes seasonally, we computed the basic reproduction number (R0) using vector population sizes ranging from 100 to 100,000 vectors for each of the 255 epidemiological units. The size of the potentially exposed human population was calculated in the case where the virus would be introduced in a single epidemiological unit and in the extreme case where the virus would have spread over the whole island. For a vector population of 1,000 vectors per unit, 2 out of 255 units had an R0 ≥ 1. With 50,000 vectors per unit, more than 75% (193/255) of the units had an estimated R0 ≥ 1, representing a median of approximately 2,500 potentially exposed people if JEV was introduced in a single unit, and about 140,000 potentially exposed people if JEV had expanded throughout the island. The unit located a few kilometers from the large port area of Reunion Island had an estimated R0 ≥ 1 with at least 10,000 vectors, making it a potential gateway to JEV given a virus introduction of infected vectors.
Design and Implementation of Nonisolated High Step-Up DC-DC Converter
Authors: Zamani Mehdi , Aghaie Amir , Zamani Ali , Tari Rana , Abarzadeh Mostafa , Hosseini Seyed Hossein
Published: June 2023

This article presents a novel structure for a high step-up DC-DC converter. The proposed converter offers several advantages, including a simple structure, high voltage gain, high efficiency, reduced voltage stress on the semiconductors, and fewer components. A two-winding coupled inductor has been employed to enhance the output voltage level in this topology. The suggested structure has only one power switch with low ON-state resistance (RDS-ON), reducing power losses. Moreover, the zero-voltage switching (ZVS) and zero-current switching (ZCS) features of the diodes of the proposed converter result have improved overall efficiency. To evaluate and ascertain the enhanced performance of this configuration, the study of different modes of operation, steady-state investigation, and a comparative study between the proposed and other relevant topologies are presented. A laboratory prototype is designed and implemented with an input voltage of 12 V, an output voltage of 150 V, and a 200 W rated power level under a 50 kHz switching frequency. The maximum efficiency of the recommended topology is measured at the rated output power, equal to 96.98%. Also, for an output power range from 50 W to 350 W, the efficiency is obtained higher than 95%.
Impact of Food Environments on Obesity Rates: A State-Level Analysis
Authors: Cerceo Elizabeth , Sharma Elena , Boguslavsky Anne , Rachoin Jean-Sebastien
Published: June 2023

Introduction. Limited access to healthy food in areas that are predominantly food deserts or food swamps may be associated with obesity. Other unhealthy behaviors may also be associated with obesity and poor food environments. Methods. We calculated Modified Retail Food Environment Index (mRFEI) to assess food retailers. Using data collected from the Behavioral Risk Factor Surveillance System (BRFSS) survey, the NJ Department of Health (NJDOH), and the US Census Bureau, we conducted a cross-sectional analysis of the interaction of obesity with the food environment and assessed smoking, leisure-time physical activity (LPA), and poor sleep. Results. There were 17.9% food deserts and 9.3% food swamps in NJ. There was a statistically significant negative correlation between mRFEI and obesity rate (Pearson’s r −0.13,

p
<
0.001

), suggesting that lack of access to healthy food is associated with obesity. Regression analysis was significantly and independently associated with increased obesity prevalence (adjusted R square 0.74 and

p
=
0.008

). Obesity correlated positively with unhealthy behaviors. Each unhealthy behavior was negatively correlated with mRFEI. The mean prevalence for smoking, LPA, and sleep <7 hours was 15.4 (12.5–18.6), 26.5 (22.5–32.3), and 37.3 (34.9–40.4), respectively. Conclusion. Obesity tracks with food deserts and especially food swamps. It is also correlated with other unhealthy behaviors (smoking, LPA, and poor sleep).
Effects of Oat Bran Addition on the Growth Performance and Intestinal Health of Nile Tilapia (Oreochromis niloticus) Exposed to Copper Ions
Authors: Guo Chunze , Zhang Yingchao , Wang Xuekai , Ni Kuikui , Hao Qiang , Zhang Zhen , Zhou Zhigang , Yang Fuyu
Published: June 2023

This study investigated the effects of the oat bran addition on the growth performance and intestinal health of Nile tilapia (Oreochromis niloticus) exposed to copper ions. Four groups of diets containing 0%, 5%, 10%, and 20% oat bran were fed to Nile tilapia for four weeks. The results showed that oat bran had a dose-dependent effect on the growth performance of Nile tilapia. The addition of oat bran can increase the relative abundance of Delftia, which is capable of degrading heavy metals in the intestinal tract and alleviating the intestinal damage caused by copper ion stress. Compared to the control group, the 5% oat bran group had an increased intestinal antioxidant capacity. The relative gene expression of proinflammatory factors (NF-κB, IL-1β) was significantly downregulated in the 5% oat bran group (

P
<
0.05

), and the relative gene expression of anti-inflammatory factors (TGF-β), HIF-1α, occludin, and claudin was significantly upregulated (

P
<
0.05

). In conclusion, we suggest that 5% oat bran should be added to the diet to improve the growth performance of Nile tilapia and alleviate the negative effects of copper ion stress on intestinal health.
Role of Extracellular microRNAs in Sepsis-Induced Acute Lung Injury
Authors: Xiong Chenlu , Huang Xuan , Chen Shibiao , Li Yong
Published: June 2023

Acute lung injury (ALI) is a life-threatening pathological disease characterized by the damage of pulmonary endothelial cells and epithelial cell barriers by uncontrolled inflammation. During sepsis-induced ALI, multiple cells cooperate and communicate with each other to respond to the stimulation of inflammatory factors. However, the underlying mechanisms of action have not been fully identified, and the modes of communication therein are also being investigated. Extracellular vesicles (EVs) are a heterogeneous population of spherical membrane structures released by almost all types of cells, containing various cellular components. EVs are primary transport vehicles for microRNAs (miRNAs), which play essential roles in physiological and pathological processes in ALI. EV miRNAs from different sources participated in regulating the biological function of pulmonary epithelial cells, endothelial cells, and phagocytes by transferring miRNA through EVs during ALI induced by sepsis, which has great potential diagnostic and therapeutic values. This study aims to summarize the role and mechanism of extracellular vesicle miRNAs from different cells in the regulation of sepsis-induced ALI. It provides ideas for further exploring the role of extracellular miRNA secreted by different cells in the ALI induced by sepsis, to make up for the deficiency of current understanding, and to explore the more optimal scheme for diagnosis and treatment of ALI.
The Potential Nexus between Helminths and SARS-CoV-2 Infection: A Literature Review
Authors: Al-kuraishy Hayder M. , Al-Gareeb Ali I. , Alkazmi Luay , El-Bouseary Maisra M. , Hamad Rabab S. , Abdelhamid Mahmoud , Batiha Gaber El-Saber
Published: June 2023

Chronic helminth infections (CHIs) can induce immunological tolerance through the upregulation of regulatory T cells. In coronavirus disease 2019 (COVID-19), abnormal adaptive immune response and exaggerated immune response may cause immune-mediated tissue damage. Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) and CHIs establish complicated immune interactions due to SARS-CoV-2-induced immunological stimulation and CHIs-induced immunological tolerance. However, COVID-19 severity in patients with CHIs is mild, as immune-suppressive anti-inflammatory cytokines counterbalance the risk of cytokine storm. Since CHIs have immunomodulatory effects, therefore, this narrative review aimed to clarify how CHIs modulate the immunoinflammatory response in SARS-CoV-2 infection. CHIs, through helminth-derived molecules, may suppress SARS-CoV-2 entry and associated hyperinflammation through attenuation of the inflammatory signaling pathway. In addition, CHIs may reduce the COVID-19 severity by reducing the SARS-CoV-2 entry points in the initial phase and immunomodulation in the late phase of the disease by suppressing the release of pro-inflammatory cytokines. In conclusion, CHIs may reduce the severity of SARS-CoV-2 infection by reducing hyperinflammation and exaggerated immune response. Thus, retrospective and prospective studies are recommended in this regard.
Advances in Zebrafish as a Comprehensive Model of Mental Disorders
Authors: Wang Lei , Liu Fan , Fang Yimeng , Ma Jiahui , Wang Jiawei , Qu Linkai , Yang Qinsi , Wu Wei , Jin Libo , Sun Da
Published: June 2023

As an important part in international disease, mental disorders seriously damage human health and social stability, which show the complex pathogenesis and increasing incidence year by year. In order to analyze the pathogenesis of mental disorders as soon as possible and to look for the targeted drug treatment for psychiatric diseases, a more reasonable animal model is imperious demands. Benefiting from its high homology with the human genome, its brain tissue is highly similar to that of humans, and it is easy to realize whole-body optical visualization and high-throughput screening; zebrafish stands out among many animal models of mental disorders. Here, valuable qualified zebrafish mental disorders models could be established through behavioral test and sociological analysis, which are simulated to humans, and combined with molecular analyses and other detection methods. This review focuses on the advances in the zebrafish model to simulate the human mental disorders; summarizes the various behavioral characterization means, the use of equipment, and operation principle; sums up the various mental disorder zebrafish model modeling methods; puts forward the current challenges and future development trend, which is to contribute the theoretical supports for the exploration of the mechanisms and treatment strategies of mental disorders.
Exploring the Solubility and Bioavailability of Sodium Salt and Its Free Acid Solid Dispersions of Dolutegravir
Authors: Yarlagadda Dani Lakshman , Nayak Akshatha M. , Brahmam Bheemisetty , Bhat Krishnamurthy
Published: June 2023

Amorphous salt solid dispersion (ASSD) of Dolutegravir amorphous salt (DSSD) was generated using quench cooling and compared to its Dolutegravir free acid solid dispersion (DFSD) to improve the solubility and bioavailability. Soluplus (SLP) was used as a polymeric carrier in both solid dispersions. The prepared DSSD and DFSD, physical mixtures, and individual compounds were characterized by employing DSC, XRPD, and FTIR to assess the formation of the single homogenous amorphous phase and the existence of intermolecular interactions. Partial crystallinity was observed for DSSD, unlike DFSD, which is completely amorphous. No intermolecular interactions were observed between the Dolutegravir sodium (DS)/Dolutegravir free acid (DF) and SLP from the FTIR spectra of DSSD and DFSD. Both DSSD and DFSD improved the solubility of Dolutegravir (DTG) to 5.7 and 4.54 folds compared to the pure forms. Similarly, drug release from DSSD and DFSD was 2 and 1.5 folds higher than that in the pure form, owing to the rapid dissolution of the drug from the formulations. The permeability of DSSD and DFSD was estimated using the dialysis membrane, which enhanced the DTG permeability. The improvement in in vitro studies was translated into in vivo pharmacokinetic profiles of DSSD and DFSD, where 4.0 and 5.6 folds, respectively, improved the Cmax of DTG.
Development and External Validation of Machine Learning-Based Models for Predicting Lung Metastasis in Kidney Cancer: A Large Population-Based Study
Authors: Yi Xinglin , Zhang Yuhan , Cai Juan , Hu Yu , Wen Kai , Xie Pan , Yin Na , Zhou Xiangdong , Luo Hu
Published: June 2023

The accuracy of indices widely used to evaluate lung metastasis (LM) in patients with kidney cancer (KC) is insufficient. Therefore, we aimed at developing a model to estimate the risk of developing LM in KC based on a large population size and machine learning algorithms. Demographic and clinicopathologic variables of patients with KC diagnosed between 2004 and 2017 were retrospectively analyzed. We performed a univariate logistic regression analysis to identify risk factors for LM in patients with KC. Six machine learning (ML) classifiers were established and tuned using the ten-fold cross-validation method. External validation was performed using clinicopathologic information from 492 patients from the Southwest Hospital, Chongqing, China. Algorithm performance was estimated by analyzing the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, recall, F1 score, clinical decision analysis (DCA), and clinical utility curve (CUC). A total of 52,714 eligible patients diagnosed with KC were enrolled, of whom 2,618 developed LM. Variables of age, sex, race, T stage, N stage, tumor size, histology, and grade were identified as important for the prediction of LM. The extreme gradient boosting (XGB) algorithm performed better than other models in both the internal validation (AUC: 0.913, sensitivity: 0.873, specificity: 0.809, and F1 score: 0.325) and the external validation (AUC: 0.904, sensitivity: 0.750, specificity: 0.878, and F1 score: 0.364). This study established a predictive model for LM in KC patients based on ML algorithms which showed high accuracy and applicative value. A web-based predictor was built using the XGB model to help clinicians make more rational and personalized decisions.
Video Surveillance Object Forgery Detection using PDCL Network with Residual‐based Steganalysis Feature
Authors: Gan Yan-Fen , Yang Ji-Xiang , Zhong Jun-Liu
Published: June 2023

Video surveillance has various applications in various fields and industries. However, the rapid development of video processing technology has made video surveillance information susceptible to multiple malicious attacks. At present, the state‐of‐the‐art methods, including the latest deep learning techniques, cannot get satisfactory results when addressing video surveillance object forgery detection (VSOFD) due to the following limitations: (i) lack of VSOFD‐specific features for effective processing and (ii) lack of effective deep network architecture designed explicitly for VSOFD. This paper proposes a new detection scheme to alleviate these limitations. The proposed approach first extracted VSOFD‐specific features via residual‐based steganalysis feature (RSF) from the spatial‐temporal‐frequent domain. Key clues of video frames can be more effectively learned from RSF, instead of raw frame images. Then, the RSF feature is used to form the residual‐based steganography feature vector group (RSFVG), which serves as the input of our following network. Finally, a new VSOFD‐specific deep network architecture called parallel‐DenseNet‐concatenated‐LSTM (PDCL) network is designed, which includes two improved CNN and RNN modules. The improved CNN module fuses and processes the coarse‐to‐fine feature extraction and simultaneously preserves the frame independence in video frames. The improved RNN module learns the correlation features between the adjacent frames to identify forgery frames. Experimental results show that the proposed scheme using the PDCL network with RSF can achieve high performance in test error, precision, recall, and F1 scores in our newly constructed dataset (SYSU‐OBJFORG + newly generated forgery video clips). Compared to existing SOTA methods, our framework achieves the best F1 score of 90.33%, which is greatly improved by nearly 8%.
Figure S3 from Targeting Fatty Acid Reprogramming Suppresses CARM1-expressing Ovarian Cancer
Authors: Lombardi Simona , Goldman Aaron R. , Tang Hsin-Yao , Kossenkov Andrew V. , Liu Heng , Zhou Wei , Herlyn Meenhard , Lin Jianhuang , Zhang Rugang
Published: June 2023

CARM1 reprograms lipid metabolism.
Supplementary Materials and Methods from Maternal Embryonic Leucine Zipper Kinase is Associated with Metastasis in Triple-negative Breast Cancer
Authors: Xie Xuemei , Chauhan Gaurav B. , Edupuganti Ramakrishna , Kogawa Takahiro , Park Jihyun , Tacam Moises , Tan Alex W. , Mughees Mohd , Vidhu Fnu , Liu Diane D. , Taliaferro Juliana M. , Pitner Mary Kathryn , Browning Luke S. , Lee Ju-Hyeon , Bertucci François , Shen Yu , Wang Jian , Ueno Naoto T. , Krishnamurthy Savitri , Hortobagyi Gabriel N. , Tripathy Debu , Van Laere Steven J. , Bartholomeusz Geoffrey , Dalby Kevin N. , Bartholomeusz Chandra
Published: June 2023

Supplementary Materials and Methods
Supplementary Materials and Methods from Maternal Embryonic Leucine Zipper Kinase is Associated with Metastasis in Triple-negative Breast Cancer
Authors: Xie Xuemei , Chauhan Gaurav B. , Edupuganti Ramakrishna , Kogawa Takahiro , Park Jihyun , Tacam Moises , Tan Alex W. , Mughees Mohd , Vidhu Fnu , Liu Diane D. , Taliaferro Juliana M. , Pitner Mary Kathryn , Browning Luke S. , Lee Ju-Hyeon , Shen Yu , Wang Jian , Ueno Naoto T. , Krishnamurthy Savitri , Hortobagyi Gabriel N. , Tripathy Debu , Van Laere Steven J. , Bartholomeusz Geoffrey , Dalby Kevin N. , Bartholomeusz Chandra
Published: June 2023

Supplementary Materials and Methods
Supplementary Figure S3 from Maternal Embryonic Leucine Zipper Kinase is Associated with Metastasis in Triple-negative Breast Cancer
Authors: Xie Xuemei , Chauhan Gaurav B. , Edupuganti Ramakrishna , Kogawa Takahiro , Park Jihyun , Tacam Moises , Tan Alex W. , Mughees Mohd , Vidhu Fnu , Liu Diane D. , Taliaferro Juliana M. , Pitner Mary Kathryn , Browning Luke S. , Lee Ju-Hyeon , Shen Yu , Wang Jian , Ueno Naoto T. , Krishnamurthy Savitri , Hortobagyi Gabriel N. , Tripathy Debu , Van Laere Steven J. , Bartholomeusz Geoffrey , Dalby Kevin N. , Bartholomeusz Chandra
Published: June 2023

Supplementary Figure S3. Top 20 master regulators that were differentially expressed in Cas9-p15 control and MELK knockout (KO) MDA-NB-231 cells.
Supplementary Figure S1 from Maternal Embryonic Leucine Zipper Kinase is Associated with Metastasis in Triple-negative Breast Cancer
Authors: Xie Xuemei , Chauhan Gaurav B. , Edupuganti Ramakrishna , Kogawa Takahiro , Park Jihyun , Tacam Moises , Tan Alex W. , Mughees Mohd , Vidhu Fnu , Liu Diane D. , Taliaferro Juliana M. , Pitner Mary Kathryn , Browning Luke S. , Lee Ju-Hyeon , Bertucci François , Shen Yu , Wang Jian , Ueno Naoto T. , Krishnamurthy Savitri , Hortobagyi Gabriel N. , Tripathy Debu , Van Laere Steven J. , Bartholomeusz Geoffrey , Dalby Kevin N. , Bartholomeusz Chandra
Published: June 2023

Figure S1. Inhibitory effect of treatment with MELK-In-17 on the expression of epithelial-to-mesenchymal transition markers in murine 4T1 triple-negative breast cancer cells.
FIGURE 4 from Maternal Embryonic Leucine Zipper Kinase is Associated with Metastasis in Triple-negative Breast Cancer
Authors: Xie Xuemei , Chauhan Gaurav B. , Edupuganti Ramakrishna , Kogawa Takahiro , Park Jihyun , Tacam Moises , Tan Alex W. , Mughees Mohd , Vidhu Fnu , Liu Diane D. , Taliaferro Juliana M. , Pitner Mary Kathryn , Browning Luke S. , Lee Ju-Hyeon , Bertucci François , Shen Yu , Wang Jian , Ueno Naoto T. , Krishnamurthy Savitri , Hortobagyi Gabriel N. , Tripathy Debu , Van Laere Steven J. , Bartholomeusz Geoffrey , Dalby Kevin N. , Bartholomeusz Chandra
Published: June 2023

Effect of inhibition of MELK signaling on tumor growth and lung metastasis in TNBC xenograft mouse models. A, MELK expression in Cas9-p15 (P15) and MELK KO MDA-MB-231 (C3 and C28) cells. α-Tubulin was used as a loading control. B–F, MELK KO significantly suppressed lung metastases in an MDA-MB-231 xenograft mouse model. Female athymic nude mice were injected intravenously with luciferase-transfected Cas9-p15 or MELK KO MDA-MB-231-Luc-GFP stable cells. Metastatic tumors were measured weekly for 7 weeks by whole-body luciferase imaging using an IVIS 100 Imaging System. Shown are mouse whole-body luciferase images (B), photon counts per area (C), lung weight per mouse measured at week 7 following cell inoculation (D), mouse OS over a period of 80 days following cell inoculation (E), and IHC staining for hematoxylin and eosin (H&E), MELK, proliferation (Ki67), and mesenchymal markers (vimentin and fibronectin; F) in mice inoculated with Cas9-p15 or MELK KO MDA-MB-231 cells. Images were taken under 200 × magnification. G, MELK-In-17 significantly suppressed tumor growth in a 4T1 xenograft mouse model (P < 0.05). Murine 4T1 TNBC cells were injected into the mammary fat pads of female BALB/c mice. When tumor size reached 75–150 mm3, grouped mice were treated with vehicle or MELK-In-17 at 5 or 10 mg/kg via intraperitoneal injections daily for 25 days. In C–G, data are presented as mean ± SD. *, P < 0.05; **, P < 0.01.
Clinicoprognostic Study of Hydroa Vacciniforme-like Lymphoproliferative Diseases: A Systematic Review
Authors: Kim Young Jae , Yang Hee Joo , Won Chong Hyun , Chang Sung Eun , Lee Mi Woo , Lee Woo Jin
Published: June 2023

Background: Limited clinicopathological and prognostic data are available on hydroa vacciniforme (HV)-like lymphoproliferative diseases (HVLPD). Methods: This systematic review searched HVLPD reports in Medline via PubMed, Embase, Cochrane, and CINAHL databases in October 2020. Results: A total of 393 patients (65 classic HV, 328 severe HV/HV-like T-cell lymphoma [HVLL]) were analyzed. Among severe HV/HVLL cases, 56.0% were Asians, whereas 3.1% were Caucasians. Facial edema, hypersensitivity to mosquito bites, the onset of skin lesion, and percentage of severe HV/HVLL differed significantly by race. Progression to systemic lymphoma was confirmed in 9.4% of HVLPD patients. Death occurred in 39.7% patients with severe HV/HVLL. Facial edema was the only risk factor associated with progression and overall survival. Mortality risk was higher in Latin Americans than in Asians and Caucasians. CD4/CD8 double-negativity was significantly associated with the worst prognosis and increased mortality. Conclusion: HVLPD is a heterogeneous entity with variable clinicopathological features associated with genetic predispositions.