bluuebunny/crossref_metadata_2025 huggingface dataset:
Maxwell equations in Schwarzschild black hole with topological defects and the gravitational magnetoelectric effect
Authors: Kurbah Meshwa Garnet , Ahmed Faizuddin
Published: November 2024

In this study, our primary focus lies in addressing the characteristics of the electromagnetic field tensor within the context of a curved spacetime engendered by a spherically symmetric black hole accompanied by topological defects. Specifically, we scrutinize the Schwarzschild model of a black hole, renowned for its spherically symmetric attributes, while incorporating the additional complexity of a cosmic string traversing the symmetry axis. Our investigation entails deriving the electromagnetic field tensor and subsequently formulating Maxwell vacuum equations, which govern the electric and magnetic fields within this distinctive scenario. Furthermore, we consider a topologically charged spherically symmetric black hole and investigate the same problem within this geometry. The principal findings of our study unveil notable deviations in both the electromagnetic field tensor and the Maxwell equations when compared with outcomes obtained in the conventional Minkowski flat space. Particularly noteworthy is the introduction of a cosmic string and global monopole in our analysis, which introduces supplementary modifications to the results. Moreover, we study the gravitational magnetoelectric effects within these spacetimes’ background and analyze the results.
PACMNET, V2, CoNEXT4, December 2024 Editorial
Authors: Mellia Marco , Steenkiste Peter , Qazi Ihsan Ayyub , Tyson Gareth
Published: November 2024

The Proceedings of the ACM on Networking (PACMNET) series showcases top-tier research in emerging computer networks and their applications. We welcome submissions introducing new technologies, innovative experiments, creative applications of networking technologies, and fresh insights gained through analysis. Supported by the ACM Special Interest Group on Communications and Computer Networks (SIGCOMM), the journal is backed by a distinguished Editorial Board composed of leading researchers in the field.

This issue concludes the second volume of PACMNET which in total published 32 articles, with a growth of 25% compared to the first volume. This issue features 18 articles, all submitted by the June 2024 deadline when a total of 121 submissions were received. Each submission underwent a thorough review process involving over 80 Editors, coordinated by two Associate Editors. In the initial phase, every article received a minimum of three reviews. Following an online discussion, roughly half of the submissions were rejected, while the other half advanced to a second review phase. In this phase, Editors produced at least two additional reviews per article. After a further discussion and remote Editors' meeting, 18 articles were chosen for publication and appear in this issue.

Topics include network measurement, security, and privacy of both traditional and novel networking technologies. From a methodological perspective, machine learning and artificial intelligence-based solutions are predominant. All papers include a thorough set of experiments to validate the proposed solutions.

We would like to express our gratitude to all those who contributed to this issue of PACMNET, especially the Authors for submitting their finest work and the Associate Editors for offering valuable feedback in their reviews and engaging in the discussions. Our thanks also go to the SIGCOMM Executive Committee Chair and the CoNEXT Steering Committee members for their continued support and guidance, providing essential suggestions and insights throughout the article selection process.
A Systematic Comparison of Large Language Models Performance for Intrusion Detection
Authors: Bui Minh-Thanh , Boffa Matteo , Valentim Rodolfo Vieira , Navarro Jose Manuel , Chen Fuxing , Bao Xiaosheng , Houidi Zied Ben , Rossi Dario
Published: November 2024

We explore the capabilities of Large Language Models (LLMs) to assist or substitute devices (i.e., firewalls) and humans (i.e., security experts) respectively in the detection and analysis of security incidents. We leverage transformer-based technologies, from relatively small to foundational sizes, to address the problem of correctly identifying the attack severity (and accessorily identifying and explaining the attack type). We contrast a broad range of LLM techniques (prompting, retrieval augmented generation, and fine-tuning of several models) using state-of-the-art machine learning models as a baseline. Using proprietary data from commercial deployment, our study provides an unbiased picture of the strengths and weaknesses of LLM for intrusion detection.
SetD4: Sets With Deletions and Decay in the Data Plane
Authors: Diamant Jonathan , Landau Feibish Shir
Published: November 2024

Sets are a fundamental data type in Computer Science. Data structures used to maintain sets need to enable the insertion and deletion of keys from the set and support a lookup operation to check if a key belongs to the set. Recent advances in programmable networks allow performing fine-grained network telemetry and other network functions right in the data plane, many of which utilize sets. One of the most common data structure in use for maintaining sets in the data plane is the Bloom Filter (BF). Existing implementations of BFs in the data plane support key insertion and lookup, yet due to the harsh processing restrictions of the data plane, they do
not
support deletions. We present SetD4, the first data structure for maintaining sets in the data plane that supports insertion, lookup
and deletion.
SetD4 maintains a modified BF, which holds the set, as well as two auxiliary structures that allow the safe removal of keys from the set. In addition, we present a variant of SetD4 that also supports decay, which allows the automatic removal of keys from the structure after a predefined time interval. We analyze SetD4 and show precise error rates for both the decaying and non-decaying structures. We have implemented SetD4 on the Tofino programmable switch and show that it can achieve high accuracy with limited overhead when compared to the current state-of-the-art set-membership data structures in the data plane with better false-positive and false-negative error rates.
Practically High Performant Neural Adaptive Video Streaming
Authors: Patel Sagar , Zhang Junyang , Narodystka Nina , Jyothi Sangeetha Abdu
Published: November 2024

Despite offering early promise, Deep Reinforcement Learning (DRL) suffers from several challenges in adaptive bitrate streaming stemming from the uncertainty and noise in network conditions. However, in this paper, we find that although these challenges complicate the training process, in practice, we can substantially mitigate their effects by addressing a key overlooked factor: the skewed input trace distribution in DRL training datasets.

We introduce a generalized framework,
Plume
, to automatically identify and balance the skew using a three-stage process. First, we identify the critical features that determine the behavior of the traces. Second, we classify the traces into clusters. Finally, we prioritize the salient clusters to improve the
overall
performance of the controller. We implement our ideas with a novel ABR controller,
Gelato
, and evaluate the performance against state-of-the-art controllers in the real world for more than a year, streaming 59 stream-years of television to over 280,000 users on the live streaming platform Puffer. Gelato trained with Plume outperforms all baseline solutions and becomes the first controller on the platform to deliver statistically significant improvements in both video quality and stalling, decreasing stalls by as much as 75%.
RECC: Joint Congestion Control Based on RTT and ECN for High-speed RDMA Networks
Authors: Wan Zirui , Zhang Jiao , Wei Haoran , Jiang Zhuo , Zhong Xiaolong , Wu Wenfei , Zhou Huaping , Pan Tian , Huang Tao
Published: November 2024

Together with the construction of RDMA networks for data center applications, the RDMA-coupled DCQCN dominates the RDMA Congestion Control (CC). However, DCQCN suffers severe performance problems in high-speed RDMA networks with modern high-performance distributed applications such as machine learning training. This paper presents RECC, inspired by both the latest emerging programmability of RDMA NICs (RNICs) and limitations in existing RDMA congestion control mechanisms. RECC comprehensively leverages RTT and ECN events from RNICs to handle congestion timely and precisely, along with a History-aware Burst Smooth mechanism to avoid wrong rate decisions under various traffic patterns. We implement RECC completely based on commercial RNICs without any modifications to switches, RDMA protocol stack, and applications. The results of microbenchmark testbed experiments and real Machine Learning (ML) workload experiments with hundreds of 200G RNICs show that RECC can significantly reduce network tail latency and pause duration by up to 64.4% and 95%, respectively, compared with DCQCN. In addition, large-scale simulations with realistic workloads demonstrate that RECC achieves comparable performance with HPCC.
Saving Private WAN: Using Internet Paths to Offload WAN Traffic in Conferencing Services
Authors: Kataria Bhaskar , LNU Palak , Bothra Rahul , Gandhi Rohan , Bhattacherjee Debopam , Padmanabhan Venkata N. , Atov Irena , Ramakrishnan Sriraam , Chaturmohta Somesh , Kotipalli Chakri , Liang Rui , Sueda Ken , He Xin , Hinton Kevin
Published: November 2024

Large-scale video conferencing services incur significant network cost while serving surging global demands. Our work systematically explores the opportunity to offload a fraction of this traffic to the Internet, a cheaper routing option offered already by cloud providers, from WAN without drop in application performance. First, with a large-scale latency measurement study with 3.5 million data points per day spanning 241K source cities and 21 data centers across the globe, we demonstrate that Internet paths perform comparable to or better than the private WAN for parts of the world (e.g., Europe and North America). Next, we present Titan, a live (12+ months) production system that carefully moves a fraction of the conferencing traffic to the Internet using the above observation. Finally, we propose
Titan-Next
- a research prototype that jointly assigns the conferencing server and routing option (Internet or WAN) for individual calls. With 5 weeks of production data, we show Titan-Next reduces the sum of peak bandwidth on WAN links that defines the operational network cost by up to 61% compared to state-of-the-art baselines.
SPARC: Spatio-Temporal Adaptive Resource Control for Multi-site Spectrum Management in NextG Cellular Networks
Authors: Ghosh Ushasi , Chiejina Azuka , Stephenson Nathan , Shah Vijay K , Shakkottai Srinivas , Bharadia Dinesh
Published: November 2024

This work presents SPARC (Spatio-Temporal Adaptive Resource Control), a novel approach for multi-site spectrum management in NextG cellular networks. SPARC addresses the challenge of limited licensed spectrum in dynamic environments. We leverage the O-RAN architecture to develop a multi-timescale RAN Intelligent Controller (RIC) framework, featuring an xApp for near-real-time interference detection and localization, and a xApp for real-time intelligent resource allocation. By utilizing base stations as spectrum sensors, SPARC enables efficient and fine-grained dynamic resource allocation across multiple sites, enhancing signal-to-noise ratio (SNR) by up to 7dB, spectral efficiency by up to 15%, and overall system throughput by up to 20%. Comprehensive evaluations, including emulations and over-the-air experiments, demonstrate the significant performance gains achieved through SPARC, showcasing it as a promising solution for optimizing resource efficiency and network performance in NextG cellular networks.
MLTL Multi-type: A Typed Logic for Cyber-Physical Systems
Authors: Hariharan Gokul , Kempa Brian , Wongpiromsarn Tichakorn , Jones Phillip , Rozier Kristin
Published: November 2024

Modern cyber-physical systems-of-systems (CPSoS) operate in complex systems-of-systems that must seamlessly work together to control safety- or mission-critical functions. Linear Temporal Logic (LTL) and Mission-time Linear Temporal logic (MLTL) intuitively express CPSoS requirements for automated system verification and validation. However, both LTL and MLTL presume that all signals populating the variables in a formula are sampled over the same rate and type (e.g., time or distance), and agree on a standard “time” step. Formal verification of cyber-physical systems-of-systems needs validate-able requirements expressed over (sub-)system signals of different types, such as signals sampled at different timescales, distances, or levels of abstraction, expressed in the same formula. Previous works developed more expressive logics to account for types (e.g., timescales) by sacrificing the intuitive simplicity of LTL. However, a legible direct one-to-one correspondence between a verbal and formal specification will ease validation, reduce bugs, increase productivity, and linearize the workflow from a project’s conception to actualization. Validation includes both transparency for human interpretation, and tractability for automated reasoning, as CPSoS often run on resource-limited embedded systems. To address these challenges, we introduced Mission-time Linear Temporal Logic Multi-type (Hariharan et al., Numerical Software Verification Workshop, 2022), a logic building on MLTL. MLTLM enables writing formal requirements over finite input signals (e.g., sensor signals and local computations) of different types, while maintaining the same simplicity as LTL and MLTL. Furthermore, MLTLM maintains a direct correspondence between a verbal requirement and its corresponding formal specification. Additionally, reasoning a formal specification in the intended type (e.g., hourly for an hourly rate, and per second for a seconds rate) will use significantly less memory in resource-constrained hardware. This article extends the previous work with (1) many illustrated examples on types (e.g., time and space) expressed in the same specification, (2) proofs omitted for space in the workshop version, (3) proofs of succinctness of MLTLM compared to MLTL, and (4) a minimal translation to MLTL of optimal length.
AI-powered Fraud Detection in Decentralized Finance: A Project Life Cycle Perspective
Authors: Luo Bingqiao , Zhang Zhen , Wang Qian , Ke Anli , Lu Shengliang , He Bingsheng
Published: November 2024

Decentralized finance (DeFi) represents a novel financial system but faces significant fraud challenges, leading to substantial losses. Recent advancements in artificial intelligence (AI) show potential for complex fraud detection. Despite growing interest, a systematic review of these methods is lacking. This survey correlates fraud types with DeFi project stages, presenting a taxonomy based on the project life cycle. We evaluate AI techniques, revealing notable findings, such as the superiority of tree-based and graph-related models. Based on these insights, we offer recommendations and outline future research directions to aid researchers, practitioners, and regulators in enhancing DeFi security.
Developmental and Genetic Aspects of Desert Crops
Authors: Smet Wouter , Blilou Ikram
Published: November 2024

Deserts are hostile environments to plant life due to exposure to abiotic stresses, including high temperature, heat, high light, low water availability, and poor soil quality. Desert plants have evolved to cope with these stresses, and for thousands of years humans have used these plants as sources of food, fiber, and medicine. Due to desertification, the amount of arable land is reduced every year; hence, the usage of these species as substitutes for some crops might become one of the solutions for food production and land remediation. Additionally, increasing our understanding of how these plants have adapted to their environment could aid in the generation of more resistant staple crops. In this review, we examine three desert plant species and discuss their developmental aspects, physiological adaptations, and genetic diversity and the related genomic resources available to date. We also address major environmental challenges and threats faced by these species as well as their potential use for improving food security through stimulating stress resistance in crops.
An Aqueous High-Voltage Chloride Ion Battery Utilizing MoS2 for Chlorine Storage
Authors: Xu Shuailiang , Li Mingqiang , Weng Haochen , Li Jingwen
Published: November 2024

Chloride-ion batteries (CIBs) are considered potential alternatives to Lithium-ion batteries (LIBs). Here, we report a novel CIB composed of a molybdenum disulfide (MoS2) cathode, a zinc (Zn) anode, and a “water-in-salt” electrolyte. Leveraging MoS2’s exceptional chloride-ion storage capability, we achieved a high specific capacity of 258.1 mAh g−1 and retained 86.4% of the maximum discharge capacity after 1700 cycles. Additionally, the “water-in-salt” electrolyte provides a high discharge voltage platform of 2.2 V for aqueous CIBs. We investigated the principle and demonstrated reversible absorption/desorption of Cl− by the MoS2 cathode.
Latency and amplitude of catch-up saccades to accelerating targets
Authors: Doré Sydney , Coutinho Jonathan , Khan Aarlenne Z. , Lefèvre Philippe , Blohm Gunnar
Published: November 2024

When visually tracking object motion, humans combine smooth pursuit and saccadic eye movements to maintain the target image on the fovea. Retinal position and velocity errors are known to determine catch-up saccade amplitude and latency, however, it is unknown if retinal acceleration error is also used to predict future target position. This study provides evidence of a small but statistically significant contribution of retinal acceleration error in determining saccade amplitude and latency.
Regulation of cardiac function by the autonomic nervous system
Authors: Hafez Omar A. , Chang Rui B.
Published: November 2024

The autonomic nervous system is critical for regulating cardiovascular physiology. The neurocardiac axis encompasses multiple levels of control, including the motor circuits of the sympathetic and parasympathetic nervous systems, sensory neurons that contribute to cardiac reflexes, and the intrinsic cardiac nervous system that provides localized sensing and regulation of the heart. Disruption of these systems can lead to significant clinical conditions. Recent advances have enhanced our understanding of the autonomic control of the heart, detailing the specific neuronal populations involved and their physiologic roles. In this review, we discuss this research at each level of the neurocardiac axis. We conclude by discussing the clinical field of neurocardiology and attempts to translate this new understanding of neurocardiac physiology to the clinic. We highlight the contributions of autonomic dysfunction in prevalent cardiovascular diseases and assess the current status of novel neuroscience-based treatment approaches.
Optimization of Aerodynamic Design of a Winged UAV Through Genetic Algorithms and Large Eddy Simulation
Authors: Ebrahimi Mohammad Javad , Pasandidehfard Mahmoud , Esmaeili Ali , Moghimi Esfandabadi Mohammad Hossein
Published: November 2024

This paper focuses on the optimization of a winged UAV airframe utilizing a preliminary configuration and the combination of the Taguchi experimental design method and the evolutionary genetic optimization algorithm, along with computational fluid dynamics. Simulations were carried out based on the Reynolds‐averaged Navier–Stokes (RANS) equations and SST k‐ω turbulence model and the large eddy simulation (LES) for a speed of 50 m/s and a Reynolds number of 1.6 million. Optimization was conducted for six variables in a single stage, with 25 tests performed. The tested case is a winged UAV with a Lambda‐shaped airframe design named SACCON, featuring wings with a tilt angle of 53°. The objective function in this study is the ratio of lift to drag specified. A genetic algorithm is used in conjunction with an initial configuration to create a new aircraft. Ultimately, the newly designed airframe demonstrates a 14% improvement in aerodynamic efficiency compared to the default state, and the lift‐to‐drag ratio increases by 55%, successfully concluding the optimization process.
Parameter Optimization Method for Predictor–Corrector Guidance With Impact Angle Constraint
Authors: Kong Xinwan , Zhang Cheng
Published: November 2024

With the applications of predictor–corrector guidance technology on hypersonic vehicles, the stability and robustness of the predictor–corrector algorithm have become issues of concern. Currently, the key parameters of predictor–corrector guidance law often rely on the designer’s experience and trial‐and‐error selection. It requires a significant amount of time for comprehensive testing to verify its reliability, lacking a theoretical basis for stability and robustness analysis. In this paper, a nonlinear model is proposed to describe the prediction process. Based on this model, the stability and stability margin of the predictor–corrector guidance system can be calculated using the Nyquist stability theory. The upper bounds of the key parameters in the algorithm of corrector can be deduced according to the requirement for the system’s stability margin. Additionally, an uncertainty factor is proposed to describe the model uncertainty in the predictor–corrector guidance algorithm. Based on the uncertainty factor, the impact of uncertainty and external disturbances on prediction accuracy is derived, and the propagation of prediction error to the miss distance is analyzed using the adjoint method. The lower bounds of key parameters can be deduced by the requirement for the guidance precision index. Finally, this paper proposes a parameter optimization algorithm that can satisfy the requirements of stability and guidance precision. A Monte Carlo simulation has verified its effectiveness and reliability.
Identification of the hsa_circ_0001314‐Related ceRNA Network in Breast Cancer With Bioinformatics Analysis
Authors: Ma Yuge , Zhang Bing , Wang Liping , Rong Wei , Liu Ting
Published: November 2024

Circular RNA (circRNA) serves as a competitive endogenous RNA (ceRNA) that plays a pivotal role in the initiation and progression of breast cancer (BC). However, compared to other noncoding RNAs (ncRNAs), research on circRNA in BC is still in its infancy. Through the analysis of circRNA datasets in the GEO database, hsa_circ_0001314, which is upregulated in BC, was selected as the focus of this study. RT‐qPCR analysis showed that hsa_circ_0001314 was significantly upregulated in BC tissues and cells. Subsequently, the biological functions of hsa_circ_0001314 in BC cells were examined through CCK‐8, wound healing, transwell invasion, and flow cytometry analyses. The research demonstrated that knocking down the expression level of hsa_circ_0001314 significantly inhibited cell proliferation, migration, and invasion abilities while notably promoting cell apoptosis. Bioinformatics methods were used to predict downstream miRNAs and mRNAs that may interact with hsa_circ_0001314, constructing a ceRNA regulatory network related to hsa_circ_0001314. RT‐qPCR confirmed that hsa_circ_0001314 functions as a sponge for hsa‐miR‐548aj‐3p, competitively binding to hsa‐miR‐548aj‐3p to activate the MAPK signaling pathway and regulate the expression of MAPK8 and MAP3K1. The findings uncover the potential of hsa_circ_0001314 as a novel prognostic biomarker and therapeutic target for BC patients.
Molluscicidal Activity of Extracts and Fractions From Hagenia abyssinica, Rosa abyssinica, and Cucumis ficifolius Against Biomphalaria and Bulinus Snails
Authors: Basha Hirut , Debella Asfaw , Endale Milkyas , Debebe Eyob , Mathewos Meharu , Biftu Tesfaye , Mamo Hassen
Published: November 2024

Background: Schistosomiasis continues to be a major public health concern in Ethiopia. Eliminating the intermediate host snails is an effective and cost‐efficient strategy for preventing and controlling schistosomiasis transmission. However, chemical molluscicides have limitations due to their toxicity to nontarget aquatic organisms, environmental concerns, and the development of resistance. Plant‐based molluscicides are biodegradable, less toxic, safe, and cost‐effective.

Objective: This study is aimed at evaluating the molluscicidal activity of Hagenia abyssinica flowers, Rosa abyssinica fruits, and Cucumis ficifolius roots against Biomphalaria and Bulinus species.

Methods: Adult Biomphalaria and Bulinus species were subjected to varying concentrations of aqueous and 70% ethanol extracts and solvent partitions from H. abyssinica, R. abyssinica, and C. ficifolius for 24, 48, and 72 h. The investigation involved conducting a phytochemical analysis using standard screening methods. Female mice were subjected to an acute oral toxicity test using a 70% ethanol extract of H. abyssinica, R. abyssinica, and C. ficifolius. The mortality data were then determined using GraphPad Prism 9 software.

Results: Aqueous and 70% ethanol extracts of R. abyssinica and C. ficifolius did not exhibit molluscicidal activities against Biomphalaria and Bulinus species. However, aqueous, 70% ethanol, and chloroform extracts of H. abyssinica showed significant molluscicidal activities against Biomphalaria species with 24‐h LC50 values of 39.05, 11.93, and 5.52 mg/L, respectively. Similarly, the LC50 values of the same extracts against Bulinus species after 24 h of exposure were 40.08, 12.23, and 6.13 mg/L, respectively. The plant extract’s LD50 for acute toxicity against mice was found to be over 2000 mg/kg of body weight.

Conclusion: H. abyssinica demonstrated potent molluscicidal activity, making it a potential candidate for application. Further isolation of active ingredients and field trials are necessary to determine the optimal conditions for its use in snail control.
Supplementary Figure S1 from First-In-Human Phase I Study of a Next-Generation, Oral, TGFβ Receptor 1 Inhibitor, LY3200882, in Patients with Advanced Cancer
Authors: Yap Timothy A. , Vieito Maria , Baldini Capucine , Sepúlveda-Sánchez Juan Manuel , Kondo Shunsuke , Simonelli Matteo , Cosman Rasha , van der Westhuizen Andre , Atkinson Victoria , Carpentier Antoine F. , Löhr Mario , Redman Rebecca , Mason Warren , Cervantes Andres , Le Rhun Emilie , Ochsenreither Sebastian , Warren Louise , Zhao Yumin , Callies Sophie , Estrem Shawn T. , Man Michael , Gandhi Leena , Avsar Emin , Melisi Davide
Published: November 2024

Patient disposition
Antitumor Activity and Biomarker Analysis for TROP2 Antibody–Drug Conjugate Datopotamab Deruxtecan in Patient-Derived Breast Cancer Xenograft Models
Authors: Meric-Bernstam Funda , Yuca Erkan , Evans Kurt W. , Zhao Ming , Maejima Takanori , Karibe Tsuyoshi , Raso Maria Gabriela , Tang Ximing , Zheng Xiaofeng , Rizvi Yasmeen Qamar , Akcakanat Argun , Scott Stephen M. , Wang Bailiang , Byers Lauren A. , Tripathy Debu , Okajima Daisuke , Damodaran Senthil
Published: November 2024

Purpose:

Datopotamab deruxtecan (Dato-DXd) is a humanized anti–trophoblast cell-surface antigen-2 (TROP2) IgG1 mAb linked to a potent topoisomerase I inhibitor payload (DXd). Dato-DXd has already shown antitumor activity in breast cancer; however, the determinants of response, including the importance of TROP2 expression, remain unclear. We tested the activity of Dato-DXd in a panel of breast cancer patient-derived xenografts (BCX) varying in TROP2 expression.

Experimental Design:

The antitumor activity of Dato-DXd and isotype-control-DXd (IgG-DXd) was assessed against 11 BCXs varying in TROP2 expression, 10 representing tumors postneoadjuvant chemotherapy. Pharmacodynamic effects were assessed at 24 and 72 hours. The effects of TROP2 expression on Dato-DXd activity was assessed in vitro and in vivo using viral overexpression in BCX-derived cell lines.

Results:

Models differed in their sensitivity to both Dato-DXd and IgG-DXd. Dato-DXd (10 mg/kg) led to objective response in 4 (36%) models and statistically significant prolongation of event-free survival in 8 (73%) models, whereas IgG-DXd (10 mg/kg) led to response in 1 (9%) and prolonged event-free survival in 3 (27%) models. TROP2 RNA and protein were significantly higher in Dato-DXd–sensitive models. In isogenic cell lines derived from Dato-DXd–resistant BCXs, overexpression of TROP2 conferred Dato-DXd antitumor activity in vitro and in vivo. Dato-DXd increased γH2AX and phospho-KAP1 in the two Dato-DXd–sensitive BCXs but not in a Dato-DXd–resistant BCX. In Dato-DXd–sensitive models, antitumor activity was enhanced in combination with a PARP inhibitor, olaparib.

Conclusions:

Dato-DXd is active in breast cancer models. Dato-DXd has TROP2-dependent and -independent mediators of activity; however, high TROP2 expression enhances Dato-DXd antitumor activity.
STAT5 Activation Enhances Adoptive Therapy Combined with Peptide Vaccination by Preventing PD-1 Inhibition
Authors: Fan Aaron E. , Sultan Hussein , Kumai Takumi , Fesenkova Valentyna I. , Wu Juan , Klement John D. , Bernstock Joshua D. , Friedman Gregory K. , Celis Esteban
Published: November 2024

Adoptive cell therapy (ACT) using retrovirally transduced T cells represents a promising strategy for enhancing antitumor responses. When used with TriVax, a peptide vaccination strategy, this approach synergistically expands antigen-specific cell populations. STAT5 plays a vital role as a transcription factor in regulating T-cell proliferation and their differentiation into effector and memory T cells. We aimed to explore the combination therapy using CD8 T cells engineered to express constitutively active STAT5 (CA-STAT5) with vaccines. CD8 T cells were transduced with a retrovirus (RV) encoding the mouse gp100 T-cell receptor (TCR). In certain treatment groups, cells were also co-transduced with RV encoding CA-STAT5. We assessed transduction efficiency and functional activity through flow cytometry and various functional assays. B16F10 tumor-bearing mice were treated with ACT using RV-transduced CD8 T cells and subsequently vaccinated with TriVax. We demonstrate that TriVax selectively enhanced the expansion of ACT cell populations bearing gp100-specific TCRs. T cells engineered to express CA-STAT5 showed not only increased expansion and polyfunctionality but also reduced PD-1 expression, leading to decreased cellular exhaustion. In a B16F10 melanoma mouse model, our approach yielded a potent antitumor effect, with CA-STAT5 further amplifying this response. We found that CA-STAT5 improved antitumor activities, in part, by attenuating the PD-1/PD-L1 inhibitory pathway. These findings indicate that TCR-transduced CD8 T cells can undergo antigen-dependent expansion when exposed to TriVax. Additionally, the expression of CA-STAT5 enhances T-cell proliferation and persistence, partly by promoting resistance to PD-1/PD-L1–mediated inhibition in antitumor T cells.
Nuclear Focal Adhesion Kinase Protects against Cisplatin Stress in Ovarian Carcinoma
Authors: Zhang Yichi , Ojalill Marjaana , Boyer Antonia , Chen Xiao Lei , Tahon Elise , Thivolle Lioux Gaëtan , Xia Marvin , Abbas Maryam , Soylu Halime Meryem , Flieder Douglas B. , Connolly Denise C. , Molinolo Alfredo A. , McHale Michael T. , Stupack Dwayne G. , Schlaepfer David D.
Published: November 2024

Tumor chemotherapy resistance arises frequently and limits high-grade serous ovarian cancer (HGSOC) patient survival. Focal adhesion kinase (FAK) is an intracellular protein–tyrosine kinase encoded by PTK2, a gene that is often gained in HGSOC. Canonically, FAK functions at the cell periphery. However, FAK also transits to the nucleus to modulate gene expression. We find that FAK is tyrosine-phosphorylated and nuclear-localized in tumors of patients with HGSOC surviving neoadjuvant platinum–paclitaxel chemotherapy and that FAK nuclear accumulation occurs upon subcytotoxic cisplatin exposure to ovarian tumor cells in vitro. FAK nuclear localization sequence (NLS) mutational inactivation resulted in tumor cell sensitization to cisplatin in vitro and in vivo relative to wild-type FAK-reconstituted ovarian tumor cells. Cisplatin cytotoxicity was associated with elevated ERK MAPK activation in FAK NLS− cells, cisplatin-stimulated ERK activation was also enhanced upon loss of FAK activity or expression, and cisplatin-stimulated cell death was prevented by an inhibitor of ERK signaling. MAPK phosphastase-1 (MKP1) negatively regulates ERK signaling, and cisplatin-induced MKP1 levels were significantly elevated in wild-type FAK compared with FAK NLS− ovarian tumor cells. Notably, small-molecule MKP1 inhibition enhanced both cisplatin-stimulated ERK phosphorylation and ovarian tumor cell death. Together, our results show that FAK expression, activity, and nuclear localization limit cisplatin cytotoxicity in part by regulating MKP1 levels and preventing noncanonical ERK/MAPK activation.

Significance:

FAK inhibitors are in combinatorial clinical testing with agents that prevent Ras–Raf–MAPK pathway activation in various cancers. This study suggests that nuclear FAK limits ERK/MAPK activation in supporting HGSOC cell survival to cisplatin stress. Overall, it is likely that targets of FAK-mediated survival signaling may be tumor type– and context-dependent.
The lung-brain axis: genetic evidence for causal effects of asthma, allergic rhinitis, and chronic rhinosinusitis on brain structure
Authors: Guo Tao , Jia Guobing , Wang Jingjing , Deng Xinxing , Liu Dehong , Xie Hui
Published: November 2024

Background: Previous studies have indicated Asthma, allergic rhinitis (AR) and chronic rhinosinusitis (CRS) may influence brain structure. However, it remains unclear whether these three airway conditions cause brain structural changes and which specific brain regions are affected.
Methods: We conducted a Mendelian randomization (MR) to explore the causal effect of AR, CRS, and asthma on brain structure. Reverse MR was conducted to investigate potential impact of changes in brain structure on AR, CRS, and asthma. Additionally, to enhance our understanding of the lung-brain axis, we examined bidirectional relationships between Alzheimer’s disease, Parkinson’s disease, insomnia, major depression, neuroticism, attention deficit hyperactivity disorder and these three respiratory disorders
Findings: The genetically predicted CRS could reduce the surface area in the banks of the superior temporal sulcus, paracentral, and superior frontal. Asthma had an association with a decrease in the surface area of the entorhinal, fusiform, and temporal pole, as well as a reduction in the volume of amygdala. Asthma could also increase the thickness of pericalcarine. Reverse MR showed that changes in the surface area of pars opercularis and thickness of entorhinal cortex had a potential effect on CRS. Besides, bidirectional MR between 3 airway disorders and 6 neuropsychiatric disorders indicated neuroticism could raised risk for asthma, and major depression could increased the risk of CRS and asthma
Conclusion: Our MR analysis revealed a potential causal relationship among CRS, asthma, and atrophy in specific functional areas of the human brain, supporting the existence of a lung-brain axis.
Transcatheter Interventions in Adults With Fontan Palliation
Authors: Flores-Umanzor Eduardo , Luna-López Raquel , Cepas-Guillen Pedro , Montserrat Sílvia , Alshehri Bandar , Keshvara Rajesh , Abrahamyan Lusine , Carretero Bellón Juan M. , Alonso-Gonzalez Rafael , Osten Mark , Freixa Xavier , Rodes-Cabau Josep , Benson Lee , Horlick Eric
Published: November 2024

The Fontan circuit is associated with chronically elevated systemic venous pressures and decreased cardiac output, often leading to circuit failure. Managing Fontan circuit failure is complex and requires multiple therapeutic options. Transcatheter interventions have emerged as a reliable approach. They can alleviate obstructions and improve cyanosis by enhancing pulmonary blood flow and oxygen saturation. These procedures can also increase cardiac output and reduce systemic venous pressure, contributing to patient stabilization. In addition, they help mitigate volume overload and decrease the risk of bleeding during heart or combined heart and liver transplants. In recent years, percutaneous interventions have rapidly evolved and become a key therapeutic option for addressing various aspects of Fontan circuit failure. These interventions should be considered integral to the management strategy for this specific patient population.
DPABI harmonization: A toolbox for harmonizing multi-site brain imaging for big-data era
Authors: Wang Yu-Wei , Wang Han-Lin , Yan Chao-Gan
Published: November 2024

Pooling multi-site datasets is the dominant trend to expand sample sizes in neuroimaging field, thereby enhancing statistical power and reproducibility of research findings. Nevertheless, the heterogeneity derived from aggregating data from various imaging sites obstructs efficient inferences. Our recent study thoroughly assessed methods for harmonizing multi-site resting-state fMRI images, accelerating progress and providing initial application instructions. Despite this advancement, the removal of such site effects generally necessitates a certain level of programming expertise. In our effort to streamline the harmonization of site effects using advanced methodologies, we are pleased to introduce the DPABI Harmonization module. This versatile tool, allowing agnostic to specific analysis methods, integrates a range of techniques, including the state-of-the-art Subsampling Maximum-mean-distance Algorithms (SMA, recommended), ComBat/CovBat, linear models, and invariant conditional variational auto-encoder (ICVAE). It equips neuroscientists with an easy-to-use and transparent harmonization workflow, ensuring the feasibility of post-hoc analysis for multi-site studies.
Solar Market Frictions: The Role of Platforms and Policies
Authors: Dorsey Jackson
Published: November 2024

This paper estimates a structural model of the solar photovoltaic (PV) installation market using detailed data from an online platform. The model incorporates households' solar installation choices and sellers' strategic bidding. Counterfactual simulations evaluate how equilibrium outcomes respond to changes in market structure and government subsidies, yielding two main results: (1) an increase from one to five bids through the platform reduces gross installation prices by $4,000 (15.5%), and (2) the U.S. Solar Investment Tax Credit increases total surplus on the platform by $1.35 per dollar of subsidy expenditure by mitigating market power and reducing pollution externalities.
Improving Workers' Performance in Small Firms: A Randomized Experiment on Goal Setting in Ghana
Authors: Cettolin Elena , Cole Kym , Dalton Patricio S.
Published: November 2024

We report the results of a cost-effective intervention to improve workers' performance in small cassava processing firms in Ghana. We train workers to track their daily output and then randomly assign a sub-sample to set daily production goals. Achieving or missing a goal does not carry monetary consequences. Goal setting increases workers' output by 16%, their productivity by 8% and the average product of labor in firms by 13%. Goal setting is particularly effective for piece-rate workers, increasing their output by 32% and productivity by 24%. While not conclusive, evidence suggests that goals serve as a self-regulation device.
Truth in Sentencing, Incentives and Recidivism
Authors: Macdonald David C
Published: November 2024

Parole was eliminated for many US offenders by Truth-in-Sentencing (TIS) laws in the 1990s. I exploit the introduction of TIS in Arizona to explore its impact on offenders before, during, and after incarceration. TIS Offenders were assigned significantly shorter sentences, largely eliminating the intended increase in punishment. These offenders reduced their rehabilitative effort while incarcerated, with rule infractions increasing by 22% and education enrollment falling by 24%. Finally, TIS offenders became 23% more likely to return to prison for a new conviction. I argue these effects were driven by TIS removing parole incentives, given that time served remained largely unchanged.
Exploitative Contracting in a Life Cycle Savings Model
Authors: Sulka Tomasz
Published: November 2024

This paper analyses the interaction between a present-biased saver and profit-maximising financial providers. Using a tractable theoretical model, I find that a naïve present-biased agent selects an ‘ineffciently cheap’ (low-yield, low-fee) contract when the income effect of an interest rate change is sufficiently strong, and an ‘inefficiently expensive’ (high-yield, high-fee) contract otherwise. Subsequently, I embed the contract choice in a calibrated life-cycle model. Given the extent of present bias, exploitative contracting reduces the naïve agent's pension wealth by 8%, lowering expected annual consumption in retirement by 3%. The associated loss of consumer welfare corresponds to 0:23% of annual consumption.
The Effect of Franchise No-Poaching Restrictions on Worker Earnings
Authors: Callaci Brian , Gibson Matthew , Pinto Sérgio , Steinbaum Marshall , Walsh Matt
Published: November 2024

We evaluate the nationwide impact of the Washington State Attorney General's 2018-20 enforcement campaign against no-poach clauses in franchising contracts, which prohibited worker movement across locations within a chain. Implementing a staggered difference-in-differences research design using Burning Glass Technologies job vacancies and Glassdoor salary reports from numerous industries, we estimate a 6% increase in posted annual earnings from the job vacancy data and a 4% increase in worker-reported earnings.
The Impact of Fear on Police Behavior and Public Safety
Authors: Cho Sungwoo , Gonçalves Felipe , Weisburst Emily
Published: November 2024

We examine how changes in the salience of workplace risk affect police behavior and public safety. Specifically, we investigate cases of police officer deaths while on duty. Officers respond to a peer death by decreasing arrest activity for one to two months, consistent with heightened fear. Reductions are largest for low-level arrests and are more pronounced in smaller cities. Crime does not increase on average during this period, nor do we observe crime spikes in cities with larger or longer arrest declines. While shocks to perceived fatality risk generate substantial enforcement responses, officer fear is unlikely to harm public safety.
A review of the cicada genus Mata Distant, 1906 (Hemiptera: Cicadidae) with description of one new species from China
Authors: WANG SIYUE , JIANG JINYUAN , WEI CONG
Published: November 2024

The cicada genus Mata Distant, 1906 was reviewed based on the description of one new species, Mata uncinulata sp. nov., from China. Mata kama (Distant, 1881) and Mata meghalayana Sarkar, Mahapatra, Mohapatra, Nair & Kunte, 2021 are reported for the first time in China. Morphological phylogenetic analysis reveals the relationships among related species of Mata. Partial mitochondrial COI gene (DNA barcoding) of M. uncinulata sp. nov. and M. kama rec. nov. are sequenced and uploaded to GenBank. A key to species of Mata is provided.
Faunistic and systematic studies on the Lepturini (Coleoptera: Cerambycidae, Lepturinae) in the Aegean region of Türkiye
Authors: ŞİMŞEK BURCU ŞABANOĞLU , TÜRKMEN SENEM ÖZDEMİR , SERT OSMAN
Published: November 2024

In the present study, which is part of a research project examining the Cerambycidae fauna of the Aegean Region of Türkiye (including the provinces of Afyonkarahisar, Aydın, Denizli, İzmir, Kütahya, Manisa, Muğla, Uşak, and southern Balıkesir), Lepturini species (Lepturinae: Cerambycidae) are discussed in both faunistic and systematic terms. A total of 22 species are presented, six of which are new records for the Aegean Region. Additionally, a new species, Stenurella afyoncayensis sp. nov., is described from Afyonkarahisar province. The description of the new species, including photographs of its habitus and genitalia, as well as a differential diagnosis, is provided. Previous records from the study area are compared with and evaluated against our findings. The morphological structures of seven male aedeagus and three spermathecae are described, and detailed drawings are presented for the first time. Furthermore, species identified in previous studies are compared with the current fauna, and a discussion is included regarding whether species not found in the current study may have been affected by climate change.
Description of Diduga siamensis sp. nov. and newly recorded D. scalprata (Lepidoptera, Erebidae, Arctiinae) from Thailand, with a checklist of the genus Diduga
Authors: BAYARSAIKHAN ULZIIJARGAL , HEPPNER JOHN B. , KWON HYUNG WOOK , KIM KIL WON , BAE YANG-SEOP
Published: November 2024

In this study, 11 species of the genus Diduga Moore, [1887] are recognized from Thailand, including a new species, Diduga siamensis Bayarsaikhan & Heppner sp. nov., and one newly recorded species, D. scalprata Bayarsaikhan, Li & Bae, 2020. Illustrations of adults and genitalia of the additionally examined species are provided, with a checklist of known species of the genus from this country.
How Does a Dry General Circulation Model Represent Atmospheric Blocking?
Authors: Deshmukh Vinita , Rivière Gwendal , Fromang Sébastien , Saint-Lu Marion
Published: November 2024

While dry dynamics has been a key framework for understanding blocking events, recent studies have highlighted the significant role of moist processes in blocking life cycles. However, it remains unclear whether moist processes introduce unique characteristics in the blocking life cycle that cannot be captured by dry dynamics or whether they are a source of extra energy for synoptic eddies that are needed to form realistic blocking circulations. Our approach to address the above squestion is to perform a long-term simulation of a dry general circulation model (GCM) with synoptic eddy energy and mean flow characteristics close to the winter climatology of ERA5 reanalysis. Blocking frequencies are found to be reduced by about one-third in the model compared to ERA5 using a blocking detection based on potential vorticity (PV). This moderate underestimation of blocking frequency in the dry model is due to rarer favorable conditions to initiate a blocking anticyclone. The model needs episodes of weaker eastward flows than in ERA5 to compensate for the weaker westward expansion of the blocking anticyclone associated with the smaller divergent winds. The main characteristics of the blocks (intensity, size, duration) are similar in the two datasets despite some slight structural differences: ERA5 blocks are more Ω shaped, and blocks in the dry model are more dipole shaped. Even though the origins of the air parcels forming a blocking anticyclone are very different in the two datasets, the dry model compensates for its less efficient transport of low-PV air from low levels by transporting more efficiently low-PV air from lower latitudes at upper levels.