bluuebunny/crossref_metadata_2025 huggingface dataset:
When View- and Conflict-Robustness Coincide for Multiversion Concurrency Control
Authors: Vandevoort Brecht , Ketsman Bas , Neven Frank
Published: May 2024

A DBMS allows trading consistency for efficiency through the allocation of isolation levels that are strictly weaker than serializability. The robustness problem asks whether, for a given set of transactions and a given allocation of isolation levels, every possible interleaved execution of those transactions that is allowed under the provided allocation, is always safe. In the literature, safe is interpreted as conflict-serializable (to which we refer here as conflict-robustness). In this paper, we study the view-robustness problem, interpreting safe as view-serializable. View-serializability is a more permissive notion that allows for a greater number of schedules to be serializable and aligns more closely with the intuitive understanding of what it means for a database to be consistent. However, view-serializability is more complex to analyze (e.g., conflict-serializability can be decided in polynomial time whereas deciding view-serializability is NP-complete). While conflict-robustness implies view-robustness, the converse does not hold in general. In this paper, we provide a sufficient condition for isolation levels guaranteeing that conflict- and view-robustness coincide and show that this condition is satisfied by the isolation levels occurring in Postgres and Oracle: read committed (RC), snapshot isolation (SI) and serializable snapshot isolation (SSI). It hence follows that for these systems, widening from conflict- to view-serializability does not allow for more sets of transactions to become robust. Interestingly, the complexity of deciding serializability within these isolation levels is still quite different. Indeed, deciding conflict-serializability for schedules allowed under RC and SI remains in polynomial time, while we show that deciding view-serializability within these isolation levels remains NP-complete.
Join Size Bounds using l
p
-Norms on Degree Sequences
Authors: Abo Khamis Mahmoud , Nakos Vasileios , Olteanu Dan , Suciu Dan
Published: May 2024

Estimating the output size of a query is a fundamental yet longstanding problem in database query processing. Traditional cardinality estimators used by database systems can routinely underestimate the true output size by orders of magnitude, which leads to significant system performance penalty. Recently, upper bounds have been proposed that are based on information inequalities and incorporate sizes and max-degrees from input relations, yet their main benefit is limited to cyclic queries, because they degenerate to rather trivial formulas on acyclic queries.

We introduce a significant extension of the upper bounds, by incorporating l
p
-norms of the degree sequences of join attributes. Our bounds are significantly lower than previously known bounds, even when applied to acyclic queries. These bounds are also based on information theory, they come with a matching query evaluation algorithm, are computable in exponential time in the query size, and are provably tight when all degrees are ''simple''.
Layered List Labeling
Authors: Bender Michael A. , Conway Alex , Farach-Colton Martin , Komlós Hanna , Kuszmaul William
Published: May 2024

The list-labeling problem is one of the most basic and well-studied algorithmic primitives in data structures, with an extensive literature spanning upper bounds, lower bounds, and data management applications. The classical algorithm for this problem, dating back to 1981, has amortized cost O(log bn). Subsequent work has led to improvements in three directions: low-latency (worst-case) bounds; high-throughput (expected) bounds; and (adaptive) bounds for important workloads.

Perhaps surprisingly, these three directions of research have remained almost entirely disjoint---this is because, so far, the techniques that allow for progress in one direction have forced worsening bounds in the others. Thus there would appear to be a tension between worst-case, adaptive, and expected bounds. List labeling has been proposed for use in databases at least as early as PODS'99, but a database needs good throughput, response time, and needs to adapt to common workloads (e.g., bulk loads), and no current list-labeling algorithm achieve good bounds for all three.

We show that this tension is not fundamental. In fact, with the help of new data-structural techniques, one can actually combine any three list-labeling solutions in order to cherry-pick the best worst-case, adaptive, and expected bounds from each of them.
When is Shapley Value Computation a Matter of Counting?
Authors: Bienvenu Meghyn , Figueira Diego , Lafourcade Pierre
Published: May 2024

The Shapley value provides a natural means of quantifying the contributions of facts to database query answers. In this work, we seek to broaden our understanding of Shapley value computation (SVC) in the database setting by revealing how it relates to Fixed-size Generalized Model Counting (FGMC), which is the problem of computing the number of sub-databases of a given size and containing a given set of assumed facts that satisfy a fixed query. Our focus will be on explaining the difficulty of SVC via FGMC, and to this end, we identify general conditions on queries which enable reductions from FGMC to SVC. As a byproduct, we not only obtain alternative explanations for existing hardness results for SVC, but also new complexity results. In particular, we establish FP-#P complexity dichotomies for constant-free unions of connected CQs and connected homomorphism-closed graph queries. We also consider some variants of the SVC problem, by disallowing assumed facts or quantifying the contributions of constants rather than facts.
Public-Private Powerplays in Generative AI Era: Balancing Big Tech Regulation Amidst Global AI Race
Authors: Zhang Hongzhou , Khanal Shaleen , Taeihagh Araz
Published: May 2024

The past decades have seen unbridled growth in the economic, social and political influence of large technology corporations (Big Tech) in the United States. The rising popularity of Generative Artificial Intelligence (GenAI) is likely to further consolidate the power of these companies. The rapid expansion of Big Tech in various domains has triggered a wide range of economic, ethical, and political concerns. However, the US Government is also engaged in a growing technology and AI race with China. As a result, the US government now faces the challenges of balancing the external goal of winning the AI race through close collaboration with the Big Tech and the internal objective of regulating the Big Tech. In this paper, we argue that this intersection of interest has been the primary motivator of US policy on the governance of Big Tech. By exploring the evolution of AI policy in the US, we highlight the role internal and external pressures have played in its approach to AI governance.
PerFedRec++: Enhancing Personalized Federated Recommendation with Self-Supervised Pre-Training
Authors: Luo Sichun , Xiao Yuanzhang , Zhang Xinyi , Liu Yang , Ding Wenbo , Song Linqi
Published: May 2024

Federated recommendation systems employ federated learning techniques to safeguard user privacy by transmitting model parameters instead of raw user data between user devices and the central server. Nevertheless, the current federated recommender system faces three significant challenges: (1)
data heterogeneity:
the heterogeneity of users’ attributes and local data necessitates the acquisition of personalized models to improve the performance of federated recommendation; (2)
model performance degradation:
the privacy-preserving protocol design in the federated recommendation, such as pseudo item labeling and differential privacy, would deteriorate the model performance; (3)
communication bottleneck:
the standard federated recommendation algorithm can have a high communication overhead. Previous studies have attempted to address these issues, but none have been able to solve them simultaneously. In this article, we propose a novel framework, named
PerFedRec++
, to enhance the personalized federated recommendation with self-supervised pre-training. Specifically, we utilize the privacy-preserving mechanism of federated recommender systems to generate two augmented graph views, which are used as contrastive tasks in self-supervised graph learning to pre-train the model. Pre-training enhances the performance of federated models by improving the uniformity of representation learning. Also, by providing a better initial state for federated training, pre-training makes the overall training converge faster, thus alleviating the heavy communication burden. We then construct a collaborative graph to learn the client representation through a federated graph neural network. Based on these learned representations, we cluster users into different user groups and learn personalized models for each cluster. Each user learns a personalized model by combining the global federated model, the cluster-level federated model, and its own fine-tuned local model. Experiments on three real-world datasets show that our proposed method achieves superior performance over existing methods.
Fair Projections as a Means toward Balanced Recommendations
Authors: Anagnostopoulos Aris , Becchetti Luca , Böhm Matteo , Fazzone Adriano , Leonardi Stefano , Menghini Cristina , Schwiegelshohn Chris
Published: May 2024

The goal of recommender systems is to provide to users suggestions that match their interests, with the eventual goal of increasing their satisfaction, as measured by the number of transactions (clicks, purchases, and so forth). Often, this leads to providing recommendations that are of a particular type. For some contexts (e.g., browsing videos for information) this may be undesirable, as it may enforce the creation of filter bubbles. This is because of the existence of underlying bias in the input data of prior user actions.

Reducing hidden bias in the data and ensuring fairness in algorithmic data analysis has recently received significant attention. In this article, we consider both the densest subgraph and the

\(k\)

-clustering problem, two primitives that are being used by some recommender systems. We are given a coloring on the nodes, respectively the points, and aim to compute a
fair
solution

\(S\)

, consisting of a subgraph or a clustering, such that none of the colors is disparately impacted by the solution.

Unfortunately, introducing fair solutions typically makes these problems substantially more difficult. Unlike the unconstrained densest subgraph problem, which is solvable in polynomial time, the fair densest subgraph problem is NP-hard even to approximate, which means that with the standard computational model it is probably impossible to solve (or even approximate it sufficiently well) in polynomial time. For

\(k\)

-clustering, the fairness constraints make the problem very similar to capacitated clustering, which is a notoriously hard problem to even approximate.

Despite such negative premises, we are able to provide positive results in important use cases. In particular, we are able to prove that a suitable spectral embedding allows recovery of an almost optimal, fair, dense subgraph hidden in the input data, whenever one is present, a result that is further supported by experimental evidence.

We also show a polynomial-time,

\(2\)

-approximation algorithm to the problem of fair densest subgraph, assuming that there exist only two colors and both colors occur equally often in the graph. This result turns out to be optimal assuming the small set expansion hypothesis. For fair

\(k\)

-clustering, we show that we can recover high quality fair clusterings effectively and efficiently. For the special case of

\(k\)

-median and

\(k\)

-center, we offer additional, fast and simple approximation algorithms as well as new hardness results.

The above theoretical findings drive the design of heuristics, which we experimentally evaluate on a scenario based on real data, in which our aim is to strike a good balance between diversity and highly correlated items from Amazon co-purchasing graphs and Facebook contacts. We additionally evaluated our algorithmic solutions for the fair

\(k\)

-median problem through experiments on various real-world datasets.
Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning
Authors: Cai Miaomiao , Hou Min , Chen Lei , Wu Le , Bai Haoyue , Li Yong , Wang Meng
Published: May 2024

Collaborative Filtering (CF) plays a crucial role in modern recommender systems, leveraging historical user-item interactions to provide personalized suggestions. However, CF-based methods often encounter biases due to imbalances in training data. This phenomenon makes CF-based methods tend to prioritize recommending popular items and performing unsatisfactorily on inactive users. Existing works address this issue by rebalancing training samples, reranking recommendation results, or making the modeling process robust to the bias. Despite their effectiveness, these approaches can compromise accuracy or be sensitive to weighting strategies, making them challenging to train. Therefore, exploring how to mitigate these biases remains in urgent demand.

In this article, we deeply analyze the causes and effects of the biases and propose a framework to alleviate biases in recommendation from the perspective of representation distribution, namely Group-Alignment and Global-Uniformity Enhanced Representation Learning for Debiasing Recommendation (AURL). Specifically, we identify two significant problems in the representation distribution of users and items, namely group-discrepancy and global-collapse. These two problems directly lead to biases in the recommendation results. To this end, we propose two simple but effective regularizers in the representation space, respectively named group-alignment and global-uniformity. The goal of group-alignment is to bring the representation distribution of long-tail entities closer to that of popular entities, while global-uniformity aims to preserve the information of entities as much as possible by evenly distributing representations. Our method directly optimizes both the group-alignment and global-uniformity regularization terms to mitigate recommendation biases. Please note that AURL applies to arbitrary CF-based recommendation backbones. Extensive experiments on three real datasets and various recommendation backbones verify the superiority of our proposed framework. The results show that AURL not only outperforms existing debiasing models in mitigating biases but also improves recommendation performance to some extent.
Better Differentially Private Approximate Histograms and Heavy Hitters using the Misra-Gries Sketch
Authors: Janos Lebeda Christian , Tetek Jakub
Published: May 2024

We consider the problem of computing differentially private approximate histograms and heavy hitters in a stream of elements. In the non-private setting, this is often done using the sketch of Misra and Gries [Science of Computer Programming, 1982]. Chan, Li, Shi, and Xu [PETS 2012] describe a differentially private version of the Misra-Gries sketch, but the amount of noise it adds can be large and scales linearly with the size of the sketch; the more accurate the sketch is, the more noise this approach has to add. We present a better mechanism for releasing a Misra-Gries sketch under (ε, δ)-differential privacy. It adds noise with magnitude independent of the size of the sketch; in fact, the maximum error coming from the noise is the same as the best known in the private non-streaming setting, up to a constant factor. Our mechanism is simple and likely to be practical. In the full version of the paper we also give a simple post-processing step of the Misra-Gries sketch that does not increase the worst-case error guarantee. It is sufficient to add noise to this new sketch with less than twice the magnitude of the non-streaming setting. This improves on the previous result for "-differential privacy where the noise scales linearly to the size of the sketch.
Allocating Isolation Levels to Transactions in a Multiversion Setting
Authors: Vandevoort Brecht , Ketsman Bas , Neven Frank
Published: May 2024

A serializable concurrency control mechanism ensures consistency for OLTP systems at the expense of a reduced transaction throughput. A DBMS therefore usually offers the possibility to allocate lower isolation levels for some transactions when it is safe to do so. However, such trading of consistency for efficiency does not come with any safety guarantees. In this paper, we study the mixed robustness problem which asks whether, for a given set of transactions and a given allocation of isolation levels, every possible interleaved execution of those transactions that is allowed under the provided allocation is always serializable. That is, whether the given allocation is indeed safe. While robustness has already been studied in the literature for the homogeneous setting where all transactions are allocated the same isolation level, the heterogeneous setting that we consider in this paper, despite its practical relevance, has largely been ignored. We focus on multiversion concurrency control and consider the isolation levels that are available in Postgres and Oracle: read committed (RC), snapshot isolation (SI) and serializable snapshot isolation (SSI). We show that the mixed robustness problem can be decided in polynomial time. In addition, we provide a polynomial time algorithm for computing the optimal robust allocation for a given set of transactions, prioritizing lower over higher isolation levels. The present results therefore establish the groundwork to automate isolation level allocation within existing databases supporting multiversion concurrency control.
From Binary Join to Free Join
Authors: Remy Wang Yisu , Willsey Max , Suciu Dan
Published: May 2024

Over the last decade, worst-case optimal join (WCOJ) algorithms have emerged as a new paradigm for one of the most fundamental challenges in query processing: computing joins efficiently. Such an algorithm can be asymptotically faster than traditional binary joins, all the while remaining simple to understand and implement. However, they have been found to be less efficient than the old paradigm, traditional binary join plans, on the typical acyclic queries found in practice. In an effort to unify and generalize the two paradigms, we proposed a new framework, called Free Join, in our SIGMOD 2023 paper. Not only does Free Join unite the worlds of traditional and worst-case optimal join algorithms, it uncovers optimizations and evaluation strategies that outperform both.

In this article, we approach Free Join from the traditional perspective of binary joins, and re-derive the more general framework via a series of gradual transformations. We hope this perspective from the past can help practitioners better understand the Free Join framework, and find ways to incorporate some of the ideas into their own systems.
Learning to Restructure Tables Automatically
Authors: Hellerstein Joseph M.
Published: May 2024

By now, it is widely-accepted folk wisdom that "half of the time in any data analysis project is spent wrangling the data". Analytic algorithms and tools-built on mathematical foundations of matrices and relations-require their data to be lined up in particular rows and columns. In the relational model (known in data science circles as "tidy data"), each row is an independent observation, and each column is a distinct attribute of the phenomenon described by the data. While there are many thorny aspects to data wrangling, perhaps none is more basic than the challenge of getting data reorganized, positionally, into the right form for analysis.
DBSP: Incremental Computation on Streams and Its Applications to Databases
Authors: Budiu Mihai , Chajed Tej , McSherry Frank , Ryzhyk Leonid , Tannen Val
Published: May 2024

We describe DBSP, a framework for incremental computation. Incremental computations repeatedly evaluate a function on some input values that are "changing". The goal of an efficient implementation is to "reuse" previously computed results. Ideally, when presented with a new change to the input, an incremental computation should only perform work proportional to the size of the changes of the input, rather than to the size of the entire dataset.
Construction and validation of a rat model of acute necrotizing pancreatitis-associated intestinal injury
Authors: Jiang Haojie , Xie Weidong , Chen Qinbo , Li Yiling , Yu Zhen , Liu Naxin
Published: May 2024

We constructed a rat model of acute necrotizing pancreatitis-associated intestinal injury and verified its feasibility. In addition, we identified the mechanism by which necrotic pancreatic tissue and pancreatitis-associated ascites fluid (PAAF) cause intestinal injury through the HIPPO signaling pathway.
Diacylglycerol kinase is a keystone regulator of signaling relevant to the pathophysiology of asthma
Authors: Hernandez-Lara Miguel A. , Richard Joshua , Deshpande Deepak A.
Published: May 2024

Signal transduction by G protein-coupled receptors (GPCRs), receptor tyrosine kinases (RTKs) and immunoreceptors converge at the activation of phospholipase C (PLC) for the hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) into inositol 1,4,5-trisphosphate (IP3) and diacylglycerol (DAG). This is a point for second-messenger bifurcation where DAG via protein kinase C (PKC) and IP3 via calcium activate distinct protein targets and regulate cellular functions. IP3 signaling is regulated by multiple calcium influx and efflux proteins involved in calcium homeostasis. A family of lipid kinases belonging to DAG kinases (DGKs) converts DAG to phosphatidic acid (PA), negatively regulating DAG signaling and pathophysiological functions. PA, through a series of biochemical reactions, is recycled to produce new molecules of PIP2. Therefore, DGKs act as a central switch in terminating DAG signaling and resynthesis of membrane phospholipids precursor. Interestingly, calcium and PKC regulate the activation of α and ζ isoforms of DGK that are predominantly expressed in airway and immune cells. Thus, DGK forms a feedback and feedforward control point and plays a crucial role in fine-tuning phospholipid stoichiometry, signaling, and functions. In this review, we discuss the previously underappreciated complex and intriguing DAG/DGK-driven mechanisms in regulating cellular functions associated with asthma, such as contraction and proliferation of airway smooth muscle (ASM) cells and inflammatory activation of immune cells. We highlight the benefits of manipulating DGK activity in mitigating salient features of asthma pathophysiology and shed light on DGK as a molecule of interest for heterogeneous diseases such as asthma.
Study on Pretightening Loss Effect of Bolt Support in Deep Soft Rock Roadway
Authors: Yu Fenghai , Sun Bo , Wang Qingduo , Fang Ping , Zhang Tao , Chen Jianchong , Zhao Xin , Zhu Dehe
Published: May 2024

The magnitude of pretension force serves as an important indicator of the effectiveness of anchor bolt active support and is one of the significant factors influencing the stability of tunnel surrounding rock. Therefore, in practical engineering, it is crucial to establish the relationship between pretension torque and pretension force. However, current research in this field has some limitations. With a specific mine in western China as the engineering background, this paper first analyzed the influence factors of surrounding rock deformation and failure, established a mechanical model for pretension structure of anchor bolt support, and derived the quantitative relationship between pretension torque and pretension force based on hypothetical conditions. Finally, it proposed the loss effect of anchor bolt support and modified the pretightening loss coefficient for engineering application. The research results show that the actual pretightening force of anchor support is lower due to the influence of deep soft coal seam, which leads to failure of coal pillar under mining stress. The loss effect of surrounding rock on pretightening force was represented by a coefficient k, and the modified value of the coefficient was calculated as 0.19∼0.43. By applying the modified relationship between pretightening torque and pretightening force, it was found that the actual pretightening torque of 300 Nm applied to 11307 return air roadway effectively controlled surrounding rock deformation and failure, with coal pillar displacement less than 120 mm.
Feasibility Study of Earthquake‐Induced Damage Assessment for Structures by Utilizing Images from Surveillance Cameras
Authors: Zhou Jing , Huo Linsheng , Huang Chen , Yang Zhuodong , Li Hongnan
Published: May 2024

Rapid and accurate structural damage assessment after an earthquake is important for efficient emergency management. The widespread application of surveillance cameras provides a new possibility for improving the efficiency of assessment. However, it is still challenging to directly assess the structural seismic damage based on videos captured by indoor surveillance cameras during earthquakes. In this study, we elaborate on the concept of estimating the structural natural frequency based on the relative pixel displacement of inter‐stories. Furthermore, we propose a strategy for post‐earthquake structural damage assessment that integrates the computer vision and time‐frequency analysis. This approach aims to navigate the difficulties inherent in earthquake damage assessment and improve emergency responses. The relative pixel displacement between the camera and the fixed features on the floor is extracted from videos by using the Harris corner detection and Kanade–Lucas–Tomasi algorithms. The structural natural frequency is estimated using the synchroextracting transform‐enhanced empirical wavelet transform. The natural frequency shift‐related seismic damage index is defined and calculated for damage assessment. A shake table experiment of a small‐scale steel model is conducted to verify the accuracy and feasibility of the approach, and the practicality of the proposed approach is further verified by utilizing the data from a full‐scale reinforced concrete benchmark model experiment. The results demonstrate that the approach can accurately and efficiently evaluate the structural damage after an earthquake based on the video captured by surveillance cameras during the earthquake. The error of the acquired damage index is less than 0.1. We will apply more advanced algorithms in the future to alleviate this problem.
Images Inpainting Quality Evaluation Using Structural Features and Visual Saliency
Authors: Ma Shuang , Liu Jinhe
Published: May 2024

Despite the extensive research on developing robust image inpainting algorithms in recent years, there are almost no objective metrics for the quality assessment of inpainted images currently. Inspired by the feature coherence in the inpainted image and the human visual perception mechanism, this paper proposes an image inpainting quality assessment (IIQA) that takes into account both visual saliency and structural features. First, the quality issues associated with image inpainting are categorized into three aspects: incoherent structure, unreasonable texture, and other results that are inconsistent with human visual perception. These quality problems are further expressed as “regions of interest” and extracted by the visual saliency method using the natural statistics model. Subsequently, the structural features are computed based on the nonlinear diffusion of the horizontal and vertical gradient field of the inpainted image. Finally, the IIQA metric incorporates brightness, gradient similarity, structural similarity, and visual saliency is established. The quality evaluation process is conducted by comparing each patch within the inpainted region with its best match from the known region. The quantitative experimental results demonstrate the effectiveness of the proposed method, especially for images with structural discontinuity. A comparative study also shows that the Spearman rank order correlation coefficient of our method achieves 0.875 on certain databases, which outperforms existing IIQA metrics.
Recycling Mode Choice in a Textile and Apparel Closed‐Loop Supply Chain considering Blockchain
Authors: Zhu Jianfeng , Hang Tao , Zheng Haodong , Zhang Xuemei
Published: May 2024

The development of the textile and apparel (T&A) industry has led to an increasing focus on recycling used products. Remanufactured product quality raises consumer concerns, and blockchain can effectively solve this problem. We establish a closed‐loop supply chain (CLSC) in which a manufacturer, a retailer, or a third‐party recycler collects used T&A products to examine the most efficient recycling mode with and without blockchain and the impact of blockchain on CLSC decisions. The results show that (1) if the manufacturer’s recycling cost coefficient is relatively low, used T&A products are collected directly by the manufacturer. Otherwise, the responsibility for recycling used T&A products falls to the retailer or the third‐party recycler. It is noteworthy that the manufacturer’s choice of recycling mode remains unchanged whether a blockchain is implemented or not. (2) The implementation of blockchain by the manufacturer and the retailer can increase profits and consumers also benefit when the cost of validating blockchain units remains below a certain threshold. (3) When the recycling cost coefficient exceeds a certain threshold, the implementation of blockchain increases prices and recycling rates. These findings offer CLSC members’ management insights into how to select the optimal recycling mode and the consequences of implementing blockchain.
Therapeutic Potential of Withaferin-A and Propolis Combinational Drug Therapy for Breast Cancer: An In Vivo Interpretation for Validating the Antiproliferative Efficacy and Ameliorative Potential in Benzo[a]pyrene-Induced Breast Metastasis
Authors: T. S. Meghalatha , Suresh Arumugam , Natrajan Muninathan , Baskaran Kuppusamy , Sampath Shobana , Perumal Elumalai , Madhav E. , Z. Ahmed Mohammad , S. Alqahtani Ali , Kazmi Shadab , Perumal Asaithambi
Published: May 2024

Cancer is a serious health problem, with a rising trend in its occurrence documented globally. Female breast cancer is the most common type of cancer worldwide with treatment consisting of different strategies like mastectomy, chemotherapy, and radiotherapy. Anticancer property has been studied in withaferin-A (WA), a bioactive compound of Withania somnifera. Another natural substance derived from bees, propolis, has been investigated for many beneficial effects on human diseases. The current study aims to investigate the ameliorative efficacy and antiproliferative potential of combinational drug therapy of withaferin-A and propolis on breast cancer cells. By evaluating the levels of glycoproteins, nucleic acids, and the marker enzymes in benzo[a]pyrene-induced breast cancer-bearing female Wistar rats, the pharmacodynamic effects of withaferin-A and propolis drug combination were examined. Biochemical analysis of DNA, RNA, and protein levels in the liver demonstrated typical results after propolis therapy. Withaferin-A and propolis drug combination treatment significantly decreased nucleic acid synthesis, indicating that combination chemotherapy has increased breast tumoricidal efficiency. The pharmacological combination therapy exhibited the capacity to control glycoproteins associated with tumor growth (hexose, hexosamine, and sialic acid), with a considerable decrease in their levels detected. Histopathological analysis of the mammary glands demonstrated a decrease in hyperplasia and cell proliferation, indicating that the treatment has the ability to reverse architectural and morphological abnormalities associated with breast cancer. This study found that natural drug compounds in combination have shown regenerative and regulating effects when given to rats carrying the breast cancer gene.
Bystander Effects, Pharmacokinetics, and Linker-Payload Stability of EGFR-Targeting Antibody-Drug Conjugates Losatuxizumab Vedotin and Depatux-M in Glioblastoma Models
Authors: Jain Sonia , Griffith Jessica I. , Porath Kendra A. , Rathi Sneha , Le Jiayan , Pasa Tugce I. , Decker Paul A. , Gupta Shiv K. , Hu Zeng , Carlson Brett L. , Bakken Katrina , Burgenske Danielle M. , Feldsien Thomas M. , Lefebvre Didier R. , Vaubel Rachael A. , Eckel-Passow Jeanette E. , Reilly Edward B. , Elmquist William F. , Sarkaria Jann N.
Published: May 2024

Purpose:

Antibody-drug conjugates (ADC) are targeted therapies with robust efficacy in solid cancers, and there is intense interest in using EGFR-specific ADCs to target EGFR-amplified glioblastoma (GBM). Given GBM’s molecular heterogeneity, the bystander activity of ADCs may be important for determining treatment efficacy. In this study, the activity and toxicity of two EGFR-targeted ADCs with similar auristatin toxins, Losatuxizumab vedotin (ABBV-221) and Depatuxizumab mafodotin (Depatux-M), were compared in GBM patient-derived xenografts (PDX) and normal murine brain following direct infusion by convection-enhanced delivery (CED).

Experimental Design:

EGFRviii-amplified and non-amplified GBM PDXs were used to determine in vitro cytotoxicity, in vivo efficacy, and bystander activities of ABBV-221 and Depatux-M. Nontumor-bearing mice were used to evaluate the pharmacokinetics (PK) and toxicity of ADCs using LC-MS/MS and immunohistochemistry.

Results:

CED improved intracranial efficacy of Depatux-M and ABBV-221 in three EGFRviii-amplified GBM PDX models (Median survival: 125 to >300 days vs. 20–49 days with isotype control AB095). Both ADCs had comparable in vitro and in vivo efficacy. However, neuronal toxicity and CD68+ microglia/macrophage infiltration were significantly higher in brains infused with ABBV-221 with the cell-permeable monomethyl auristatin E (MMAE), compared with Depatux-M with the cell-impermeant monomethyl auristatin F. CED infusion of ABBV-221 into the brain or incubation of ABBV-221 with normal brain homogenate resulted in a significant release of MMAE, consistent with linker instability in the brain microenvironment.

Conclusions:

EGFR-targeting ADCs are promising therapeutic options for GBM when delivered intratumorally by CED. However, the linker and payload for the ADC must be carefully considered to maximize the therapeutic window.
Perivascular NOTCH3+ Stem Cells Drive Meningioma Tumorigenesis and Resistance to Radiotherapy
Authors: Choudhury Abrar , Cady Martha A. , Lucas Calixto-Hope G. , Najem Hinda , Phillips Joanna J. , Palikuqi Brisa , Zakimi Naomi , Joseph Tara , Birrueta Janeth O. , Chen William C. , Oberheim Bush Nancy A. , Hervey-Jumper Shawn L. , Klein Ophir D. , Toedebusch Christine M. , Horbinski Craig M. , Magill Stephen T. , Bhaduri Aparna , Perry Arie , Dickinson Peter J. , Heimberger Amy B. , Ashworth Alan , Crouch Elizabeth E. , Raleigh David R.
Published: May 2024

Meningiomas are the most common primary intracranial tumors. Treatments for patients with meningiomas are limited to surgery and radiotherapy, and systemic therapies remain ineffective or experimental. Resistance to radiotherapy is common in high-grade meningiomas and the cell types and signaling mechanisms that drive meningioma tumorigenesis and resistance to radiotherapy are incompletely understood. Here, we report that NOTCH3 drives meningioma tumorigenesis and resistance to radiotherapy and find that perivascular NOTCH3+ stem cells are conserved across meningiomas from humans, dogs, and mice. Integrating single-cell transcriptomics with lineage tracing and imaging approaches in genetically engineered mouse models and xenografts, we show NOTCH3 drives tumor-initiating capacity, cell proliferation, angiogenesis, and resistance to radiotherapy to increase meningioma growth and reduce survival. To translate these findings to patients, we show that an antibody stabilizing the extracellular negative regulatory region of NOTCH3 blocks meningioma tumorigenesis and sensitizes meningiomas to radiotherapy, reducing tumor growth and improving survival.

Significance: There are no effective systemic therapies to treat meningiomas, and meningioma stem cells are poorly understood. Here, we report perivascular NOTCH3+ stem cells to drive meningioma tumorigenesis and resistance to radiotherapy. Our results identify a conserved mechanism and a therapeutic vulnerability to treat meningiomas that are resistant to standard interventions.
Table S1 from Identification of MUC1-C as a Target for Suppressing Progression of Head and Neck Squamous Cell Carcinomas
Authors: Nakashoji Ayako , Haratake Naoki , Bhattacharya Atrayee , Mao Weipu , Xu Kangjie , Wang Keyi , Daimon Tatsuaki , Ozawa Hiroki , Shigeta Keisuke , Fushimi Atsushi , Yamashita Nami , Morimoto Yoshihiro , Shimokawa Mototsugu , Saito Shin , Egloff Ann Marie , Uppaluri Ravindra , Long Mark D. , Kufe Donald
Published: May 2024

Primers used for qRT-PCR analysis.
FIGURE 4 from Identification of MUC1-C as a Target for Suppressing Progression of Head and Neck Squamous Cell Carcinomas
Authors: Nakashoji Ayako , Haratake Naoki , Bhattacharya Atrayee , Mao Weipu , Xu Kangjie , Wang Keyi , Daimon Tatsuaki , Ozawa Hiroki , Shigeta Keisuke , Fushimi Atsushi , Yamashita Nami , Morimoto Yoshihiro , Shimokawa Mototsugu , Saito Shin , Egloff Ann Marie , Uppaluri Ravindra , Long Mark D. , Kufe Donald
Published: May 2024

MUC1-C/STAT1 signaling regulates ∆Np63 expression. A, CAL27/tet-MUC1shRNA cells treated with vehicle or DOX for 7 days were analyzed for ∆Np63 gene transcription (left) and mRNA (right) levels. The results (mean ± SD of four determinations) are expressed as relative levels compared with that obtained for vehicle-treated cells (assigned a value of 1). B, CAL27/CshRNA and CAL27/STAT1shRNA cells were analyzed for ∆Np63 gene transcription (left) and mRNA (right) levels. The results (mean ± SD of four determinations) are expressed as relative levels compared with that obtained for vehicle-treated cells (assigned a value of 1). C, Schema of the ∆Np63 gene with highlighting localization of the PLS region that contains potential STAT1 binding motifs. D, Soluble chromatin from CAL27/tet-MUC1shRNA cells treated with vehicle or DOX for 7 days was precipitated with anti-MUC1-C and anti-STAT1. The DNA samples were amplified by qPCR with primers for the ∆Np63 PLS region. The results (mean ± SD of three determinations) are expressed as percentage of the input DNA for each sample. E, CAL27 cells expressing the indicated vectors were treated with vehicle or DOX for 7 days. Lysates were immunoblotted with antibodies against the indicated proteins. F, Lysates from CAL27/CshRNA and CAL27/STAT1shRNA cells were immunoblotted with antibodies against the indicated proteins.
S-Nitrosoglutathione Attenuates Oxidative Stress and Improves Retention Memory Dysfunctions in Intra-Cerebroventricular-Streptozotocin Rat Model of Sporadic Alzheimer’s Disease via Activation of BDNF and Nuclear Factor Erythroid 2-Related Factor-2 Antioxidant Signaling Pathway
Authors: Dubey Harikesh , Ray Arunabha , Dubey Anamika , Gulati Kavita
Published: May 2024

Introduction: The brain-derived neurotrophic factor (BDNF) and transcription nuclear factor erythroid 2-related factor-2 (NRF-2) play an important role in Alzheimer’s disease (AD). However, the interactive involvement of BDNF and NRF-2 in respect to antioxidant mechanisms in different parts of the AD brain is still unclear. Considering the above condition, used S-nitrosoglutathione (GSNO) to examine whether it modulates the BDNF and NRF-2 levels to activate signaling pathway to promote antioxidant levels in AD brains. Method: AD was induced by intracerebroventricular infusion of streptozotocin (ICV-STZ, 3 mg/kg) in Wistar rats. The effect of GSNO was analyzed by evaluating the retention of memory in months 1, 2, and 3. After the behavior study, rats were sacrificed and accessed the amyloid beta (Aβ)-40, Aβ42, glutathione (GSH), BDNF, and NRF-2 levels in the hippocampus, cortex, and amygdala tissue. Results: Pretreatment with GSNO (50 µg/kg/intraperitoneal/day) restored the BDNF, and NRF-2 levels toward normalcy as compared with ICV-STZ + saline-treated animals. Also, GSNO treatment reversed the oxidative stress and increased the GSH levels toward normal levels. Further, reduced Aβ levels and neuronal loss in different brain regions. As a result, GSNO treatment improved the cognitive deficits in ICV-STZ-treated rats. Conclusion: The results showed that endogenous nitric oxide donor GSNO improved the cognitive deficits and ICV-STZ-induced AD pathological conditions, possibly via attenuating the oxidative stress. Hence, the above finding supported that GSNO treatment may activate BDNF and NRF-2 antioxidant signaling pathways in the AD brain to normalize oxidative stress, which is the main causative factor for ICV-STZ-induced AD pathogenesis.
Objective and Subjective Dysphagia Assessment in Inflammatory Bowel Diseases
Authors: Tahir Emel , Ustaoğlu Müge
Published: May 2024

Introduction: Inflammatory bowel disease (IBD) is a chronic gastrointestinal disease that is separated into two types: ulcerative colitis (UC) and Crohn’s disease (CD). Although dysphagia is a well-studied and important topic in head and neck cancers and neurological disorders, research on the relationship between IBD and swallowing problems is not yet elucidated. The aim of this study was to compare swallowing function in the UC and CD using objective and patient-reported evaluation modalities. Methods: This was a prospective cross-sectional research with 86 patients (50 UC and 36 CD) treated at the gastroenterology department. The assessment includes flexible fiberoptic endoscopic examination (FEES). The penetration-aspiration scale, the functional oral intake scale (FOIS), the functional outcome swallowing scale (FOSS), the Eating Assessment Tool-10 (EAT-10) test, the Yale Pharyngeal Residue Severity Scale for vallecula (Yale PRSS-vallecula) and pyriform sinus (Yale PRSS-PS) were all used to determine extent of dysphagia. Results: The CD group had higher EAT-10 scores than UC group (p = 0.014). In terms of PAS scores, there was no significant difference between the two groups in all three food types (water, yogurt, and crackers) (p > 0.05). There was not a statistically significant variance between the groups in terms of vallecular residue (p > 0.05) according to the Yale PRSS-vallecula. Based on the Yale PRSS-PS, the CD group had significantly more residue than the UC group with yogurt and cracker (p = 0.014 and 0.030, respectively). FOSS and FOIS scores did not vary significantly between the two groups (p > 0.05). Conclusion: CD impairs subjective and pharyngeal swallowing functions more than UC. It is obvious that swallowing should be assessed in patients with IBD.
Impact of PD-L1 Gene Polymorphisms and Interactions with Cooking with Solid Fuel Exposure on Tuberculosis
Authors: Tang Kun , Wang Jing , Zhong Hua , Wang Qiaozhi , Li Zihao , Wu Chunli , An Rongjing , Lin Ying , Tan Hongzhuan , Chen Lizhang , Wang Mian , Chen Mengshi
Published: May 2024

Introduction: Given that PD-L1 is a crucial immune checkpoint in regulating T-cell responses, the aim of this study was to explore the impact of PD-L1 gene polymorphisms and the interaction with cooking with solid fuel on susceptibility to tuberculosis (TB) in Chinese Han populations. Methods: A total of 503 TB patients and 494 healthy controls were enrolled in this case-control study. Mass spectrometry technology was applied to genotype rs2297136 and rs4143815 of PD-L1 genes. The associations between single nucleotide polymorphism (SNPs) and TB were assessed using unconditional logistic regression analysis. Marginal structural linear odds models were used to estimate the gene-environment interactions. Results: Compared with genotype CC, genotypes GG and CG+GG at rs4143815 locus were significantly associated with susceptibility to TB (OR: 3.074 and 1.506, respectively, p < 0.05). However, no statistical association was found between rs2297136 SNP and TB risk. Moreover, the relative excess risk of interaction between rs4143815 of the PD-L1 gene and cooking with solid fuel was 2.365 (95% CI: 1.922–2.809), suggesting positive interactions with TB susceptibility. Conclusion: The rs4143815 polymorphism of the PD-L1 gene was associated with susceptibility to TB in Chinese Han populations. There were significantly positive interactions between rs4143815 and cooking with solid fuel.
Precocious Puberty and GnRH Analogs: Current Treatment Practices and Perspectives among US Pediatric Endocrinologists
Authors: Breidbart Emily , Ilkowitz Jeniece , Regelmann Molly O. , Ashraf Ambika P. , Gourgari Evgenia , Kamboj Manmohan K. , Kohn Brenda , Lahoti Amit , Mehta Shilpa , Miller Ryan , Raman Vandana , Khokhar Aditi , Brar Preneet C.
Published: May 2024

Introduction: Gonadotropin releasing hormone analogs (GnRHas) are used for treatment of precocious puberty. Over the last decade, several new formulations have been approved. Methods: The Drugs and Therapeutics Subcommittee of the Pediatric Endocrine Society (PES) undertook a review to ascertain the current treatment options, prescribing behaviors, and practices of GnRHas among pediatric endocrinologists practicing within the USA. The survey consisted of four main subsections: (1) description of clinical practice; (2) self-assessment of knowledge base of pediatric and adult GnRHa formulations; (3) current practice for treating central precocious puberty (CPP); and (4) utilization of healthcare resources. Results: There were 223 survey respondents. Pediatric endocrine practitioners were most familiar with the pediatric one-monthly preparation, the 3-month preparation, and the histrelin implant (Supprelin®) (88%, 96%, and 91%, respectively), with lower familiarity for 24-week triptorelin intramuscular (Triptodur®) (65%) and 6-month subcutaneous leuprolide (Fensolvi®) (45%). Only 23% of the respondents reported being extremely familiar with the availability of adult formulations, and 25% reported being completely unaware of cost differences between pediatric and adult GnRHa preparations. The implant was the most preferred therapy (44%), but in practice, respondents reported a higher percentage of patients treated with the 3-month preparation. While family preference/ease of treatment (87%) was the key determinant for using a particular GnRHa preparation, insurance coverage also played a significant role in the decision (64%). Responses regarding assessment for efficacy of treatment were inconsistent, as were practices and criteria for obtaining an MRI. Conclusions: The survey indicated there is more familiarity with older, shorter acting GnRHas, which are prescribed in greater numbers than newer, longer acting formulations. There is lack of consensus on the need for central nervous system (CNS) imaging in girls presenting with CPP between 6 and 8 years of age and use of laboratory testing to monitor response to treatment. Insurance requirements regarding CNS imaging and laboratory monitoring are highly variable. Despite having similar constituents and bioavailability, there are substantial cost differences between the pediatric and adult formulations and lack of evidence for safe use of these formulations in children. The survey-based analysis highlights the challenges faced by prescribers while reflecting on areas where further research is needed to provide evidence-based practice guidelines for pediatric endocrinologists.