bluuebunny/crossref_metadata_2025 huggingface dataset:
USP4 promotes the proliferation and glucose metabolism of gastric cancer cells by upregulating PKM2
Authors: Chen Yuanyuan , Guo Yunfei , Yuan Mei , Guo Song , Cui Shuaishuai , Chen Dahu
Published: August 2023

Background

The pyruvate kinase enzyme PKM2 catalyzes the final step in glycolysis and converts phosphoenolpyruvate (PEP) to pyruvate. PKM2 is often overexpressed in cancer and plays a role in the Warburg effect. The expression of PKM2 can be regulated at different levels. While it has been proven that PKM2 can be regulated by ubiquitination, little is known about its de-ubiquitination regulation.

Methods

Immunoprecipitation was applied to identify the PKM2 interaction protein and to determine the interaction region between PKM2 and USP4. Immunofluorescence was performed to determine the cellular localization of USP4 and PKM2. The regulation of PKM2 by USP4 was examined by western blot and ubiquitination assay. MTT assays, glucose uptake, and lactate production were performed to analyze the biological effects of USP4 in gastric cancer cells.

Results

USP4 interacts with PKM2 and catalyzes the de-ubiquitination of PKM2. Overexpression of USP4 promotes cell proliferation, glucose uptake, and lactate production in gastric cancer cells. Knockdown of USP4 reduces PKM2 levels and results in a reduction in cell proliferation and the glycolysis rate.

Conclusions

USP4 plays a tumor-promoting role in gastric cancer cells by regulating PKM2.
Maternal metabolic status and in-vitro culture conditions during embryonic genome activation deregulate the expression of energy-related genes in the bovine 16-cells embryo
Authors: Rabaglino Maria B. , Forde Niamh , Besenfelder Urban , Havlicek Vitezslav , Blum Helmut , Graf Alexander , Wolf Eckhard , Lonergan Patrick
Published: August 2023

The molecular consequences of the metabolic stress caused by milk production of dairy cows in the early embryo are largely unknown. The objective was to determine the impact of dam metabolic status or in vitro culture during embryonic genome activation (EGA) on the transcriptomic profiles of bovine 16-cell stage embryos. Two days after synchronized oestrus, in vitro produced 2- to 4-cell stage embryos were endoscopically transferred in pools of 50 into the oviduct ipsilateral to the corpus luteum of lactating (LACT, n = 3) or nonlactating (i.e. dried off immediately at calving; DRY, n = 3) dairy cows. On Day 4, the oviducts were flushed to recover the embryos. Pools of five Day-2 embryos (n = 5) and Day-4 16-cell stage embryos obtained in vitro (n = 3) or from LACT or DRY cows were subjected to RNAseq. Temporally differentially expressed genes (DEG; FDR<0.05) between Day-2 and Day-4 embryos were determined considering the differences between the three conditions under which EGA occurred. Also, DEG between Day-4 embryos derived from the three conditions were identified. Functional analysis of the temporal DEG demonstrated that genes involved in ribosome, translation and oxidative phosphorylation in the mitochondria were strongly more expressed in Day-4 than Day-2 embryos. Comparison of Day-4 embryos that underwent EGA in vitro, or in LACT or DRY cows, identified DEG enriching for mitochondrial respiration and protein translation, including the mTOR pathway. In conclusion, exposure of the embryo to an unfavourable maternal metabolic status during EGA influences its transcriptome and potentially the competence for pregnancy establishment.
Direction and distance dependency of reaching movements of lower limb
Authors: Oku Kyosuke , Tanaka Shinsuke , Kida Noriyuki
Published: August 2023

Efficient body movement is required in our daily lives, as it facilitates responding to the external environment and producing movements in various directions and distances. While numerous studies have reported on goal-directed movements in the frontal direction during gait initiation, there is limited research on the efficient movement of the lower limbs in multiple directions and distances. Therefore, we aimed to examine changes in the kinematics of lower-limb reaching movements to determine skilled motor ability in terms of direction and distance. Sixteen adults (10 male participants) were requested to reach targets projected on the floor in seven directions and at three distances for a total of 21 points. The reaching time slowed down for the contralateral side (right foot to left-sided target) and was caused by a slower start of the toe movement. To identify the cause of this delay, we analyzed the onset of movement at each joint and found that movement to the contralateral side starts from the hip, followed by the knee, and subsequently the toe. The time-to-peak velocity was also calculated, and the motion required to reach the target in the shortest time varied depending on direction and distance. These results suggested that movement kinematics vary with direction and distance, resulting in a slower reaching time on the contralateral side. The results of our study hold promise for potential applications in sports and rehabilitation.
Healthcare utilization during the first two waves of the COVID-19 epidemic in South Africa: A cross-sectional household survey
Authors: Wolter Nicole , Tempia Stefano , von Gottberg Anne , Bhiman Jinal N. , Walaza Sibongile , Kleynhans Jackie , Moyes Jocelyn , Aitken Sue , Magni Sarah , Yun Jessica , Fellows Tamika , Makamadi Tetelo , Weiner Renay , Cawood Cherie , Martinson Neil , Lebina Limakatso , Cohen Cheryl
Published: August 2023

Healthcare utilization surveys contextualize facility-based surveillance data for burden estimates. We describe healthcare utilization in the catchment areas for sentinel site healthcare facilities during the first year of the COVID-19 pandemic. We conducted a cross-sectional healthcare utilization survey in households in three communities from three provinces (KwaZulu-Natal, Western Cape and North West). Field workers administered structured questionnaires electronically with the household members reporting influenza-like illness (ILI) in the past 30 days or severe respiratory illness (SRI) since March 2020. Multivariable logistic regression was used to identify factors associated with healthcare utilization among individuals that reported illness. From November 2020 through April 2021, we enrolled 5804 households and 23,003 individuals. Any respiratory illness was reported by 1.6% of individuals; 0.7% reported ILI only, 0.8% reported SRI only, and 0.1% reported both ILI and SRI. Any form of medical care was sought by 40.8% (95% CI 32.9% - 49.6%) and 71.3% (95% CI 63.2% - 78.6%) of individuals with ILI and SRI, respectively. On multivariable analysis, respiratory illness was more likely to be medically attended for individuals at the Pietermaritzburg site (aOR 3.2, 95% CI 1.1–9.5, compared to Klerksdorp), that were underweight (aOR 11.5, 95% CI 1.5–90.2, compared to normal weight), with underlying illness (aOR 3.2, 95%CI 1.2–8.5), that experienced severe illness (aOR 4.8, 95% CI 1.6–14.3) and those with symptom duration of ≥10 days (aOR 7.9, 95% CI 2.1–30.2, compared to <5 days). Less than half of ILI episodes and only 71% of SRI episodes were medically attended during the first two COVID-19 waves in South Africa. Facility-based data may underestimate disease burden during the COVID-19 pandemic.
Germline-encoded specificities and the predictability of the B cell response
Authors: Vieira Marcos C. , Palm Anna-Karin E. , Stamper Christopher T. , Tepora Micah E. , Nguyen Khoa D. , Pham Tho D. , Boyd Scott D. , Wilson Patrick C. , Cobey Sarah
Published: August 2023

Antibodies result from the competition of B cell lineages evolving under selection for improved antigen recognition, a process known as affinity maturation. High-affinity antibodies to pathogens such as HIV, influenza, and SARS-CoV-2 are frequently reported to arise from B cells whose receptors, the precursors to antibodies, are encoded by particular immunoglobulin alleles. This raises the possibility that the presence of particular germline alleles in the B cell repertoire is a major determinant of the quality of the antibody response. Alternatively, initial differences in germline alleles’ propensities to form high-affinity receptors might be overcome by chance events during affinity maturation. We first investigate these scenarios in simulations: when germline-encoded fitness differences are large relative to the rate and effect size variation of somatic mutations, the same germline alleles persistently dominate the response of different individuals. In contrast, if germline-encoded advantages can be easily overcome by subsequent mutations, allele usage becomes increasingly divergent over time, a pattern we then observe in mice experimentally infected with influenza virus. We investigated whether affinity maturation might nonetheless strongly select for particular amino acid motifs across diverse genetic backgrounds, but we found no evidence of convergence to similar CDR3 sequences or amino acid substitutions. These results suggest that although germline-encoded specificities can lead to similar immune responses between individuals, diverse evolutionary routes to high affinity limit the genetic predictability of responses to infection and vaccination.
AJL's Sydney Taylor Awards for Children's Literature
Authors: Barancik Sue
Published: August 2023

This past year, I have had the privilege of serving once again as Chairman of the Sydney Taylor Book Award Committee, having chaired this committee in 1983 and 1984. In the space of these few short years, I have marveled at the growth in quality of Judaica for children. Although there were certainly excellent books during my earlier stint as chairman, the 46 books that my committee and I reviewed this year showed a delightfully marked increase in quality of illustrations, uniqueness of topic, and sophistication in format.
Felicity Meakins and Patrick McConvell. 2021. A grammar of Gurindji as spoken by Violet Wadrill, Ronnie Wavehill, Dandy Danbayarri, Biddy Wavehill, Topsy Dodd Ngarnjal, Long Johnny Kijngayarri, Banjo Ryan, Pincher Nyurrmiari and Blanche Bulngari
Authors: Majewicz Alfred F.
Published: August 2023

Review of: Felicity Meakins and Patrick McConvell. 2021. A grammar of Gurindji as spoken by Violet Wadrill, Ronnie Wavehill, Dandy Danbayarri, Biddy Wavehill, Topsy Dodd Ngarnjal, Long Johnny Kijngayarri, Banjo Ryan, Pincher Nyurrmiari and Blanche Bulngari (Mouton Grammar Library 91) Berlin–Boston: De Gruyter Mouton, pp. xxxii + 746
Lotan: Bridging the Gap between GNNs and Scalable Graph Analytics Engines
Authors: Zhang Yuhao , Kumar Arun
Published: August 2023

Recent advances in Graph Neural Networks (GNNs) have changed the landscape of modern graph analytics. The complexity of GNN training and the scalability challenges have also sparked interest from the systems community, with efforts to build systems that provide higher efficiency and schemes to reduce costs. However, we observe that many such systems basically "reinvent the wheel" of much work done in the database world on scalable graph analytics engines. Further, they often tightly couple the scalability treatments of graph data processing with that of GNN training, resulting in entangled complex problems and systems that often do not scale well on one of those axes.

In this paper, we ask a fundamental question: How far can we push existing systems for scalable graph analytics and deep learning (DL) instead of building custom GNN systems? Are compromises inevitable on scalability and/or runtimes? We propose Lotan, the first scalable and optimized data system for full-batch GNN training with
decoupled scaling
that bridges the hitherto siloed worlds of graph analytics systems and DL systems. Lotan offers a series of technical innovations, including re-imagining GNN training as query plan-like dataflows, execution plan rewriting, optimized data movement between systems, a GNN-centric graph partitioning scheme, and the first known GNN model batching scheme. We prototyped Lotan on top of GraphX and PyTorch. An empirical evaluation using several real-world benchmark GNN workloads reveals a promising nuanced picture: Lotan significantly surpasses the scalability of state-of-the-art custom GNN systems, while often matching or being only slightly behind on time-to-accuracy metrics in some cases. We also show the impact of our system optimizations. Overall, our work shows that the GNN world can indeed benefit from building on top of scalable graph analytics engines. Lotan's new level of scalability can also empower new ML-oriented research on ever-larger graphs and GNNs.
Analyzing Vectorized Hash Tables across CPU Architectures
Authors: Böther Maximilian , Benson Lawrence , Klimovic Ana , Rabl Tilmann
Published: August 2023

Data processing systems often leverage vector instructions to achieve higher performance. When applying vector instructions, an often overlooked data structure is the hash table, even though it is fundamental in data processing systems for operations such as indexing, aggregating, and joining. In this paper, we characterize and evaluate three fundamental vectorized hashing schemes, vectorized linear probing (VLP), vectorized fingerprinting (VFP), and bucket-based comparison (BBC). We implement these hashing schemes on the x86, ARM, and Power CPU architectures, as modern database systems must provide efficient implementations for multiple platforms due to the continuously increasing hardware heterogeneity. We present various implementation variants and platform-specific optimizations, which we evaluate for integer keys, string keys, large payloads, skewed distributions, and multiple threads. Our extensive evaluation and comparison to three scalar hashing schemes on four servers shows that BBC outperforms scalar linear probing by a factor of more than 2x, while also scaling well to high load factors. We find that vectorized hashing schemes come with caveats that need to be considered, such as the increased engineering overhead, differences between CPUs, and differences between vector ISAs, such as AVX and AVX-512, which impact performance. We conclude with key findings for vectorized hashing scheme implementations.
Exploiting Cloud Object Storage for High-Performance Analytics
Authors: Durner Dominik , Leis Viktor , Neumann Thomas
Published: August 2023

Elasticity of compute and storage is crucial for analytical cloud database systems. All cloud vendors provide disaggregated object stores, which can be used as storage backend for analytical query engines. Until recently, local storage was unavoidable to process large tables efficiently due to the bandwidth limitations of the network infrastructure in public clouds. However, the gap between remote network and local NVMe bandwidth is closing, making cloud storage more attractive. This paper presents a blueprint for performing efficient analytics directly on cloud object stores. We derive cost- and performance-optimal retrieval configurations for cloud object stores with the first in-depth study of this foundational service in the context of analytical query processing. For achieving high retrieval performance, we presentAnyBlob, a novel download manager for query engines that optimizes throughput while minimizing CPU usage. We discuss the integration of high-performance data retrieval in query engines and demonstrate it by incorporatingAnyBlobin our database systemUmbra.Our experiments show that even without caching,Umbrawith integratedAnyBlobachieves similar performance to state-of-the-art cloud data warehouses that cache data on local SSDs while improving resource elasticity.
WALTZ: Leveraging Zone Append to Tighten the Tail Latency of LSM Tree on ZNS SSD
Authors: Lee Jongsung , Kim Donguk , Lee Jae W.
Published: August 2023

We propose WALTZ, an LSM tree-based key-value store on the emerging Zoned Namespace (ZNS) SSD. The key contribution of WALTZ is to leverage the
zone append
command, which is a recent addition to ZNS SSD specifications, to provide tight tail latency. The long tail latency problem caused by the merging process of multiple parallel writes, called
batch-group
writes, is effectively addressed by the internal synchronization mechanism of ZNS SSD. To provide fast failover when the active zone becomes full for a write-ahead log (WAL) file during parallel append, WALTZ introduces a mechanism for WAL zone replacement and reservation. Finally, lazy metadata management allows a put query to be processed fast without requiring any other synchronizations to enable lock-free execution of individual append commands. For evaluation we use both mi-crobenchmarks (db_bench) with varying read/write ratios and key skewnesses, and realistic social-graph workloads (MixGraph from Facebook). Our evaluation demonstrates geomean reduction of tail latency by 2.19× and 2.45× for db_bench and MixGraph, respectively, with a maximum reduction of 3.02× and 4.73×. As a side effect of eliminating the overhead of batch-group writes, WALTZ also improves the query throughput (QPS) by up to 11.7%.
QueryBooster: Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting
Authors: Bai Qiushi , Alsudais Sadeem , Li Chen
Published: August 2023

SQL query performance is critical in database applications, and query rewriting is a technique that transforms an original query into an equivalent query with a better performance. In a wide range of database-supported systems, there is a unique problem where both the application and database layer are black boxes, and the developers need to use their knowledge about the data and domain to rewrite queries sent from the application to the database for better performance. Unfortunately, existing solutions do not give the users enough freedom to express their rewriting needs. To address this problem, we propose QueryBooster, a novel middleware-based service architecture for human-centered query rewriting, where users can use its expressive and easy-to-use rule language (called VarSQL) to formulate rewriting rules based on their needs. It also allows users to express rewriting intentions by providing examples of the original query and its rewritten query. QueryBooster automatically generalizes them to rewriting rules and suggests high-quality ones. We conduct a user study to show the benefits of VarSQL to formulate rewriting rules. Our experiments on real and synthetic workloads show the effectiveness of the rule-suggesting framework and the significant advantages of using QueryBooster for human-centered query rewriting to improve the end-to-end query performance.
Saibot: A Differentially Private Data Search Platform
Authors: Huang Zezhou , Liu Jiaxiang , Alabi Daniel Gbenga , Fernandez Raul Castro , Wu Eugene
Published: August 2023

Recent data search platforms use ML task-based utility measures rather than metadata-based keywords, to search large dataset corpora. Requesters submit a training dataset, and these platforms search for
augmentations
---join or union-compatible datasets---that, when used to augment the requester's dataset, most improve model (e.g., linear regression) performance. Although effective, providers that manage personally identifiable data demand differential privacy (DP) guarantees before granting these platforms data access. Unfortunately, making data search differentially private is nontrivial, as a single search can involve training and evaluating datasets hundreds or thousands of times, quickly depleting privacy budgets.

We present
Saibot
, a differentially private data search platform that employs Factorized Privacy Mechanism (FPM), a novel DP mechanism, to calculate sufficient semi-ring statistics for ML over different combinations of datasets. These statistics are privatized once, and can be freely reused for the search. This allows Saibot to scale to arbitrary numbers of datasets and requests, while minimizing the amount that DP noise affects search results. We optimize the sensitivity of FPM for common augmentation operations, and analyze its properties with respect to linear regression. Specifically, we develop an unbiased estimator for many-to-many joins, prove its bounds, and develop an optimization to redistribute DP noise to minimize the impact on the model. Our evaluation on a real-world dataset corpus of 329 datasets demonstrates that
Saibot
can return augmentations that achieve model accuracy within 50--90% of non-private search, while the leading alternative DP mechanisms (TPM, APM, shuffling) are several orders of magnitude worse.
SlabCity: Whole-Query Optimization Using Program Synthesis
Authors: Dong Rui , Liu Jie , Zhu Yuxuan , Yan Cong , Mozafari Barzan , Wang Xinyu
Published: August 2023

Query rewriting is often a prerequisite for effective query optimization, particularly for poorly-written queries. Prior work on query rewriting has relied on a set of "rules" based on syntactic pattern-matching. Whether relying on manual rules or auto-generated ones, rule-based query rewriters are inherently limited in their ability to handle new query patterns. Their success is limited by the quality and quantity of the rules provided to them.

To our knowledge, we present the first
synthesis-based
query rewriting technique, SlabCity, capable of
whole-query optimization
without relying on any rewrite rules. SlabCity directly searches the space of SQL queries using a novel query synthesis algorithm that leverages a new concept called
query dataflows.
We evaluate SlabCity on four workloads, including a newly curated benchmark with more than 1000 real-life queries. We show that not only can SlabCity optimize more queries than state-of-the-art query rewriting techniques, but interestingly, it also leads to queries that are significantly faster than those generated by rule-based systems.
Scaling Up Structural Clustering to Large Probabilistic Graphs Using Lyapunov Central Limit Theorem
Authors: Howie Joseph , Srinivasan Venkatesh , Thomo Alex
Published: August 2023

Structural clustering is one of the most widely used graph clustering frameworks. In this paper, we focus on structural clustering of probabilistic graphs, which comes with significant computational challenges and has, so far, resisted efficient solutions that are able to scale to large graphs, e.g. the state-of-art can only handle graphs with a few million edges. We address the main bottleneck step of probabilistic structural clustering, computing the structural similarity of vertices based on their Jaccard similarity over the set of possible worlds of a given probabilistic graph. The state-of-art used Dynamic Programming, a quadratic run-time algorithm, that does not scale to pairs of vertices of high degree. In this paper we present a novel approach based on Lyapunov Central Limit Theorem. By using a carefully chosen set of random variables we are able to cast the computation of structural similarity to computing a one-tailed area under the Normal Distribution. Our approach has linear runtime as opposed to quadratic, and as such, it scales to much larger inputs. Extensive experiments show that our approach can handle massive graphs at web-scale which the state-of-art cannot.
Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching
Authors: Shahbazi Nima , Danevski Nikola , Nargesian Fatemeh , Asudeh Abolfazl , Srivastava Divesh
Published: August 2023

Entity matching (EM) is a challenging problem studied by different communities for over half a century. Algorithmic fairness has also become a timely topic to address machine bias and its societal impacts. Despite extensive research on these two topics, little attention has been paid to the fairness of entity matching.

Towards addressing this gap, we perform an extensive experimental evaluation of a variety of EM techniques in this paper. We generated two social datasets from publicly available datasets for the purpose of auditing EM through the lens of fairness. Our findings underscore potential unfairness under two common conditions in real-world societies: (i) when some demographic groups are over-represented, and (ii) when names are more similar in some groups compared to others. Among our many findings, it is noteworthy to mention that while various fairness definitions are valuable for different settings, due to EM's class imbalance nature, measures such as positive predictive value parity and true positive rate parity are, in general, more capable of revealing EM unfairness.
How Large Language Models Will Disrupt Data Management
Authors: Fernandez Raul Castro , Elmore Aaron J. , Franklin Michael J. , Krishnan Sanjay , Tan Chenhao
Published: August 2023

Large language models (LLMs), such as GPT-4, are revolutionizing software's ability to understand, process, and synthesize language. The authors of this paper believe that this advance in technology is significant enough to prompt introspection in the data management community, similar to previous technological disruptions such as the advents of the world wide web, cloud computing, and statistical machine learning. We argue that the disruptive influence that LLMs will have on data management will come from two angles. (1) A number of hard database problems, namely, entity resolution, schema matching, data discovery, and query synthesis, hit a ceiling of automation because the system does not fully understand the semantics of the underlying data. Based on large training corpora of natural language, structured data, and code, LLMs have an unprecedented ability to ground database tuples, schemas, and queries in real-world concepts. We will provide examples of how LLMs may completely change our approaches to these problems. (2) LLMs blur the line between predictive models and information retrieval systems with their ability to answer questions. We will present examples showing how large databases and information retrieval systems have complementary functionality.
Equitable Data Valuation Meets the Right to Be Forgotten in Model Markets
Authors: Xia Haocheng , Liu Jinfei , Lou Jian , Qin Zhan , Ren Kui , Cao Yang , Xiong Li
Published: August 2023

The increasing demand for data-driven machine learning (ML) models has led to the emergence of model markets, where a broker collects personal data from data owners to produce high-usability ML models. To incentivize data owners to share their data, the broker needs to price data appropriately while protecting their privacy. Forequitable data valuation, which is crucial in data pricing,Shapley valuehas become the most prevalent technique because it satisfies all four desirable properties in fairness: balance, symmetry, zero element, and additivity. Forthe right to be forgotten, which is stipulated by many data privacy protection laws to allow data owners to unlearn their data from trained models, thesharded structurein ML model training has become a de facto standard to reduce the cost of future unlearning by avoiding retraining the entire model from scratch. In this paper, we explore how the sharded structure for the right to be forgotten affects Shapley value for equitable data valuation in model markets. To adapt Shapley value for the sharded structure, we propose S-Shapley value, a sharded structure-based Shapley value, which satisfies four desirable properties for data valuation. Since we prove that computing S-Shapley value is #P-complete, two sampling-based methods are developed to approximate S-Shapley value. Furthermore, to efficiently update valuation results after data owners unlearn their data, we present two delta-based algorithms that estimate the change of data value instead of the data value itself. Experimental results demonstrate the efficiency and effectiveness of the proposed algorithms.
Cross Modal Data Discovery over Structured and Unstructured Data Lakes
Authors: Eltabakh Mohamed Y. , Kunjir Mayuresh , Elmagarmid Ahmed K. , Ahmad Mohammad Shahmeer
Published: August 2023

Organizations are collecting increasingly large amounts of data for data-driven decision making. These data are often dumped into a centralized repository, e.g., a data lake, consisting of thousands of structured and unstructured datasets. Perversely, such mixture makes the problem of
discovering
tables or documents that are relevant to a user's query very challenging. Despite the recent efforts in
data discovery
, the problem remains widely open especially in the two fronts of (1) discovering relationships and relatedness across structured and unstructured datasets-where existing techniques suffer from either scalability, being customized for a specific problem type (e.g., entity matching or data integration), or demolishing the structural properties on its way, and (2) developing a holistic system for integrating various similarity measurements and sketches in an effective way to boost the discovery accuracy.

In this paper, we propose a new data discovery system, named CMDL, for addressing these two limitations. CMDL supports the data discovery process over both structured and unstructured data while retaining the structural properties of tables. As a result, CMDL is the only system to date that empowers end-users to seamlessly pipeline the discovery tasks across the two modalities. We propose a novel multi-modal embedding representation that captures the similarities between text documents and tabular columns. The model training relies on labeled datasets generated though
weak supervision
, and thus the system is domain agnostic and easily generalizable. We evaluate CMDL on three real-world data lakes with diverse applications and show that our system is significantly more effective for cross-modality discovery compared to the search-based baseline techniques. Moreover, CMDL is more accurate and robust to different data types and distributions compared to the state-of-the-art systems that are limited to only the structured datasets.
Administrative Discretion in U. S. Banking Regulation
Authors: Tarullo Daniel K.
Published: August 2023

992U.S. banking regulators have considerable discretion in developing and enforcing prudential rules. Regulators have also enjoyed wide discretion in exercising supervisory authority over banks, in order to guard against potential safety and soundness risks that are not covered by the rules. However, recent developments in U.S. administrative law may create some conflict with that broad discretion. Whether or not this conflict comes to pass, a form of judicial review that focuses less on individual supervisory actions, and more on the overall framework within which the supervisory function is carried out, is a more promising way to achieve the administrative law aims of fairness and consistency.
Novel PAX4 variant in a child and family with diabetes mellitus – case report and review of the literature
Authors: Lee Yee-Lin , Ting Tzer-Hwu , Lim Chong-Teik , Arrumugam-Arthini Crystal , Karuppiah Thilakavathy , Ling King-Hwa
Published: August 2023

Objectives

PAX4 (Paired box 4), a transcription factor crucial in pancreatic beta cell development and function, is a rare cause of maturity-onset diabetes of the young (MODY). What is new? A novel PAX4 variant is verified by family segregation study to be likely pathogenic. A child below 10 years of age diagnosed to have PAX4-MODY, differing from previously reported paediatric cases diagnosed in adolescence.

Case presentation

A child with diabetes diagnosed at age 8 years, harbored a PAX4 variant, c.890G>A (p.Gly297Asp), initially classified as variant of uncertain significance. Eleven family members (7 adults and 4 children) with and without diabetes across 3 generations were genotyped. The variant co-segregated with diabetes or prediabetes across 3 generations of the family. The variant is reclassified as likely pathogenic according to standard guidelines.

Conclusions

Genetic testing is essential to confirm PAX4-MODY as the presentation is variable even within the same family. PAX4 mutation needs to be considered in MODY genetic testing in Asian patients.
The effect of problem-solving skills on blood glucose regulation and disease management in children with type 1 diabetes mellitus
Authors: Mutluer Tuba , Aslan Genç Herdem , Demir Tuana , Demirel Çağrı , Bakır Çiçek Nur , Necef Işıl , Muradoğlu Serra , Yeşiltepe Mutlu Gül , Hatun Şükrü
Published: August 2023

Objectives

This cross-sectional study examined the relationship between problem-solving skills, glucose regulation, and disease management in children with type 1 diabetes mellitus (T1DM) as well as the role of depression in this association.

Methods

The participants (n=54) were recruited from a diabetes camp. Problem-solving inventory (PSI), Beck depression inventory (BDI), and diabetes self-management profile (DSMP) were administered as tests. Forty-six participants who have been diagnosed with T1DM for at least a year and completed the survey were included in the analyses. Participants were categorized into high and low depression groups based on the median split. Student’s t-test was used to detect demographic differences in groups. Linear regression models were used to examine the association between PSI, HbA1c, and DSMP. Regressions for PSI and DSMP were repeated in low and high-depression groups.

Results

Of the 46 participants with T1DM, 52 % were female, with a mean age of 13.96 ± 1.94 (range 10–17). Avoidant and monitoring style of problem solving as well as the total score of PSI significantly predicted HbA1c levels. Impulsive and avoidant style of problem solving, problem-solving confidence, and total scores of PSI significantly predicted DSMP (p<0.05). The high depression group had a significantly higher DSMP score than the low depression group (p=0.001), with no difference in HbA1c levels (p=0.968). When the DSMP regressions were repeated, no significant associations were seen in the low depression group. Avoidant style of problem solving, problem-solving confidence, and the total score of PSI significantly predicted DSMP in the high depression group (p<0.005).

Conclusions

Problem solving-skills are essential in children with T1DM for a successful disease management. Depression modulates the association between the problem-solving and self-management profile.
Bioprocess intensification with model-assisted DoE-strategies for the production of biopharmaceuticals
Authors: Möller Johannes , Kuchemüller Kim B. , Pörtner Ralf
Published: August 2023

The demand for highly effective biopharmaceuticals and the need to reduce manufacturing costs are increasing the pressure to develop productive and efficient bioprocesses. For this purpose, model-based process design concepts have been developed. Although first approaches were proposed, model-based process designs are still not state-of-the-art for cell culture processes during development or manufacturing. This highlights a need for improved methods and tools for optimal experimental design, optimal and robust process design and process optimization for the purposes of monitoring and control during manufacturing. In this review, an overview of the state of the art of model-based methods, their applications, further challenges, possible solutions and specific case studies for intensification of process development for production of biopharmaceuticals is presented. As a special focus, problems related to data generation (culture systems, process mode, specifically designed experiments) will be addressed.
Effect of different boron sources on the copper borates in solid-state synthesis
Authors: Senberber Dumanli Fatma Tugce , Kavci Karaagac Sibel , Kipcak Azmi Seyhun , Moroydor Derun Emek
Published: August 2023

The copper borate of CuB2O4 in tetragonal form was successfully synthesized as a single-phase by using a solid-state method without using any modifying agent. For the designed experimental procedure, the optimized reaction conditions were estimated as a reaction temperature of 950 °C, reaction time of 240 min, argon atmosphere and Cu:B ratio of 1:5. The possible reaction mechanism estimated for both boron sources of boric acid and boron oxide. In both sets, the lower ratios of Cu:B supported CuB2O4 formation. In the use of boric acid as a boron source, higher reaction yield percentages (98 %) and lower particle sizes were determined. The micron-scale rounded particles were observed in morphological analyses and the particles were shaped in homogeneity in the use of boron oxide as a boron source. The specific FT-IR peaks were observed at the band values of 1190, 1035, 988, 945, 890, 695, 631, 540 and 479 cm−1. The experimental results highlighted the probable use of solid-state in the copper borate synthesis.
Optimal LDL cholesterol levels in young and old patients with type 2 diabetes for secondary prevention of cardiovascular diseases are different
Authors: Jeong Chaiho , Kim Bongseong , Kim Jinyoung , Baek Hansang , Kim Mee Kyoung , Sohn Tae-Seo , Baek Ki-Hyun , Song Ki-Ho , Son Hyun-Shik , Han Kyungdo , Kwon Hyuk-Sang
Published: August 2023

Objective

Real-world-based population data about the optimal low-density lipoprotein cholesterol (LDL-C) level for preventing cardiovascular disease in very high-risk populations is scarce.

Methods

From 2009 to 2012, 26,922 people aged ≥ 40 years with type 2 diabetes mellitus (T2DM) who had a history of percutaneous coronary intervention (PCI) were analyzed. Data from the Korean National Health Insurance System were used. They were followed up to the date of a cardiovascular event or the time to death, or until December 31, 2018. Endpoints were recurrent PCI, newly stroke or heart failure, cardiovascular death, and all-cause death. Participants were divided into the following categories according to LDL-C level: <55 mg/dL, 55–69 mg/dL, 70–99 mg/dL, 100–129 mg/dL, 130–159 mg/dL, and ≥ 160 mg/dL.

Results

Compared to LDL-C < 55 mg/dL, the hazard ratios (HR) for re-PCI and stroke increased linearly with increasing LDL-C level in the population < 65 years. However, in ≥ 65 years old, HRs for re-PCI and stroke in LDL-C = 55–69 mg/dL were 0.97 (95% CI: 0.85–1.11) and 0.96 (95% CI: 0.79–2.23), respectively. The optimal range with the lowest HR for heart failure and all-cause mortality were LDL-C = 70–99 mg/dL and LDL-C = 55–69 mg/dL, respectively, in all age groups (HR: 0.99, 95% CI: 0.91–1.08 and HR: 0.91, 95% CI: 0.81–1.01).

Conclusion

LDL-C level below 55 mg/dL appears to be optimal in T2DM patients with established cardiovascular disease aged < 65 years, while an LDL-C level of 55–69 mg/dL may be optimal for preventing recurrent PCI and stroke in patients over 65 years old.
The effect of varnish type, glue amount, and density on the surface properties of low density particleboards produced from waste wood bark
Authors: Özlüsoylu İsmail
Published: August 2023

Particleboards, which are widely used in various fields, are commonly coated with solid and liquid surface coating materials to achieve better physical, mechanical, and aesthetic results. This study produced low-density particleboards from waste wood bark using different adhesive mixtures and densities. These particleboards were then coated with three types of varnish: water-based (Aq), polyurethane-based (Pu), and oil/wax-based (Ow). The color, gloss, and surface roughness values of the coated boards were determined to investigate the effect of varnish type, total adhesive usage, and density on these properties. In the board groups produced with the same glue ratio and density, the roughness values obtained with Ow varnish application were mostly higher compared to Aq and Pu. In the Ow varnish type, the roughness (Rmax) decreased linearly with increasing total adhesive amount in particleboards produced at low density (320 kg/m3). The highest color change (ΔE*) values for all variations were obtained in the Ow varnish type, while the highest gloss values were achieved at 85° and in the B2 (4%-420 kg/m3) board group. It was concluded that higher density should be preferred for smoother and glossier surfaces, which are important in terms of surface properties and aesthetics. Overall, these findings highlight the preference for higher density to achieve smoother and glossier surfaces in areas where surface properties and aesthetics are significant.
Az autizmus és a tehetség kapcsolata neuropszichológiai megközelítésben
Authors: Gyarmathy Éva
Published: August 2023

A tanulmány a neurológiai alapú teljesítményzavarok, kiemelten az autizmus idegrendszeri fejlődési jellemzőinek a tehetségfejlődés szempontjából történő áttekintése. Az elemzés kiterjed az autizmus és intelligencia kapcsolatára a végrehajtó funkciók, a mintázatfelismerés, a szisztematizálás és a beszéd szerepének kiemelésével és a komplex fejlesztési eljárások hatásának bemutatására. Kiemelt kérdéskör a kreativitás, amely a neuroatipikus fejlődés esetén szintén eltér a szokásostól, és kapcsolatot mutat a pszichotikus állapotokkal. A feltárt összefüggések jelzik, hogy mely tényezők tekintetében van különös gondosságra szükség, amikor az atipikus idegrendszeri fejlődés kiemelkedő képességekkel és erős fejlődésre való törekvéssel párosul. A korai beavatkozás és a környezeti tényezők döntő szerepet játszhatnak a különleges képességnek tehetség irányú fejlődésében. Az autizmus jellemzői mentén a tehetséggondozás számára konkrét lehetőségeket ismertetünk.
Diák kiégés hagyományos és alternatív pedagógiai programú oktatási intézményekben
Authors: Kóródi Kitti , Jagodics Balázs , Szabó Éva , Kunos Nóra , Fülöp Márta
Published: August 2023

Háttér és célkitűzések

A diákok iskolai kiégésének kutatása mára már bekerült a pszichológiai kutatások fókuszába. A középiskolás diákok esetében is megfigyelhető a jelenség, amit a számukra kialakított mérőeszközökkel bizonyítani is lehet. Feltáró jellegű kutatásunkban arra a kérdésre kerestük a választ, hogy az iskola egyes jellemzői összefüggést mutatnak-e a kiégés mértékével.

Módszer

Kérdőíves kutatásunkban a magyar nyelvre adaptált Diák Kiégés Kérdőívet használtuk (Salmela-Aro, Kiuru, Pietikäinen és Jokela, 2008; Salmela-Aro, Kiuru, Leskinen és Nurmi, 2009; magyar változat: Jagodics, Kóródi és Szabó, 2021). A vizsgálatba középiskolás diákokat vontunk be (N = 2,205), akik eltérő követelményeket támasztó iskolatípusokban tanulnak az iskola jellegét tekintve (szakgimnázium [N = 741]; gimnázium [N = 898]; magasan teljesítő gimnázium [N = 327]; Waldorf-gimnázium [N = 81] és egyéb alternatív gimnázium [N = 151], másrészt megkülönböztethetők hagyományos vagy alternatív pedagógiai program szerint.

Eredmények

Elemzéseink szerint a diákok kiégéspontszáma a szakgimnáziumban tanulók esetében a legmagasabb, míg a legalacsonyabb kiégéspontszám a Waldorf-program alapján működő iskolák tanulóira jellemző. Emellett a középiskolás lányokra magasabb kiégés jellemző, mint a középiskolás fiúkra, amely különbségek iskolatípustól függően eltérőek.

Következtetések

A kutatásunk eredménye cáfolta azt a széles körben elterjedt nézetet, hogy a magas követelményeket támasztó, országosan is kiemelkedő intézmények tanulói lennének a leginkább kiégettek. Sokkal inkább úgy tűnik, hogy a kiégettség a követelmények és erőforrások egyenlőtlenségével magyarázható, amely a szakgimnáziumokban lehet a legerőteljesebb.
Acute abdomen in patients with covid-19: an integrative review
Authors: LIMA MANUELA IZIDIO DE , FONSECA NETO OLIVAL CIRILO LUCENA DA
Published: August 2023

ABSTRACT Introduction: upon infection with SARS-CoV-2, patients presented with non-classical symptoms, such as gastrointestinal phenomena including loss of appetite, nausea, vomiting, diarrhea, and abdominal pain abdominal pain. These occurrences, typically, were found in severely affected patients with COVID-19. With this, the aim of this paper is to analyze the available knowledge on the development of acute abdomen in SARS-CoV-2 infected patients. Methodology: this is an Integrative Review in PubMed, Web of Science and VHL databases. The following descriptors were used: “Acute abdomen”, “COVID-19”, “Abdominal pain” and “SARS-CoV-2” with the Boolean operator “AND”, and articles relevant to the theme were selected. Initially, 331 articles were selected, all published between 2020 and 2023, in Portuguese and/or English. After analysis, 11 articles matched the proposed objective. Results: the relationship between tenderness in the right upper region or the presence of Murphy’s sign contributed in the association between abdominal pain and the more severe forms of COVID-19 in infected patients. The number of diagnoses for acute conditions such as cholecystitis, appendicitis, diverticulitis and pancreatitis decreased with the pandemic, but at the same time there was an increase in the duration of surgical procedures and in the length of hospital stays. These acute abdominal conditions were the result of delayed demand for hospital care, which also contributed to an increase in the conversion rate to open surgery and in the number of perforative conditions. Conclusion: the development of acute abdomen in SARS-CoV-2 infected patients was predictive of an unfavorable prognosis.
Princípio da cardinalidade: relações com questões familiares e escolares
Authors: Assis Évelin Fulginiti de , Schmidt Lucas Bogdanov , Nunes Sula Cristina Teixeira , Corso Luciana Vellinho
Published: August 2023

Resumo Este estudo tem como objetivo verificar associações entre o princípio da cardinalidade e a escolaridade familiar, a renda familiar e o Índice de Desenvolvimento da Educação Básica (Ideb). A amostra contou com alunos do primeiro ano do Ensino Fundamental, de três escolas públicas de Porto Alegre, no estado do Rio Grande do Sul. A análise dos dados foi realizada por meio do teste exato de Fisher que visou verificar a independência entre a construção da cardinalidade e as variáveis de escolaridade, renda e Ideb. Como resultados, evidenciou-se que a construção da cardinalidade não pode ser bem explicada pelo nível de renda, nem de escolaridade parental. Entretanto, com relação ao Ideb, identificou-se um alto número de sujeitos com o princípio construído, independentemente da renda e da escolaridade familiar. Dessa forma, conclui-se que a escola é um relevante espaço de desenvolvimento de aprendizagens para crianças de diferentes contextos familiares, reforçando seu papel essencial nesse processo.
Cenários experimentais em pesquisas contábeis: pontos de destaque no desenvolvimento metodológico
Authors: Lima Myrna Modolon
Published: August 2023

RESUMO O objetivo principal deste artigo consiste em guiar o pesquisador, por meio da exposição de pontos de destaque e exemplos de literaturas anteriores, no desenvolvimento de um cenário experimental para a investigação de sua pergunta de pesquisa. O estudo enfoca a utilização de cenários experimentais na pesquisa contábil, trazendo pontos de destaque específicos que devem ser observados quanto ao desenvolvimento teórico e metodológico do instrumento. Sistematizam-se pontos de destaque de caráter metodológico pertinentes à utilização de cenários experimentais que visem a investigar perguntas de pesquisa contábeis com foco no julgamento e na tomada de decisão dos indivíduos. O impacto desta pesquisa consiste em sistematizar aspectos relevantes ao desenvolvimento de cenários experimentais que podem afetar o rigor metodológico e as validades interna, de constructo e de conclusão estatística. Consiste em um trabalho de proposição de método, com exemplos trazidos por meio de uma revisão narrativa. O estudo sistematiza aspectos relevantes a serem considerados nas escolhas dos pesquisadores quanto ao desenvolvimento de cenários experimentais, como o papel da randomização, a escolha de participantes, a minimização do viés de desejabilidade social, maneiras específicas de coleta da variável dependente e possibilidades de coleta do pool de participantes. Adicionalmente, discute-se o papel da utilização dos cenários experimentais diante da natureza teórica da pergunta de pesquisa, principalmente quanto à avaliação de julgamento e tomada de decisão.