bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular simulation studies on a zwitterionic peptide-dendrimer conjugate for integrin αvβ3 binding
Authors: Lin Xiaowei , Xu Nan , Li Chen , Wu Zhiyu , Chen Shengfu , Shi Yao , He Yi
Published: May 2023

Zwitterionic dendrimer is an effective carrier, which can restore the natural conformation of peptide segments for high bioaffinity by a hydrogen bond-induced conformational constraint approach. However, it is still unknown whether the approach is applicable for the dendrimers with different geometric sizes. Therefore, the characteristics of conjugates made from zwitterionic poly(amidoamine) (PAM) and the arginine-glycine-aspartic acid (RGD) peptide were examined to elucidate the effects of the geometric sizes of the PAM dendrimer on the conformational structure and stability of the peptide. The results show that the RGD fragments had almost the same structure and stability when conjugated with PAM(G3, G4, or G5) dendrimers. However, when conjugated with PAM(G1 or G2) dendrimers, the structural stability of these fragments was found to be much worse. Also, the structure and stability of RGD segments conjugated with PAM(G3, G4, or G5) were not affected when additional EK segments were inserted. Moreover, we observed that RGD fragments conjugated with PAM(G3, G4, or G5) dendrimers were structurally stable and similar when the concentration of NaCl was 0.15 and 0.5M. Furthermore, we show that PAM(G3, G4, or G5)-RGD conjugates bind strongly to integrin αvβ3.
Global Effects of the Developmental Regulator BldB in Streptomyces venezuelae
Authors: Avramova Marieta M. , Stevenson Clare E. M. , Chandra Govind , Holmes Neil A. , Bush Matthew J. , Findlay Kim C. , Buttner Mark J.
Published: May 2023

To reproduce and disperse, the filamentous bacteriumStreptomycesdevelops specialized reproductive structures called aerial hyphae. The formation of these structures is controlled by thebld(bald) genes, many of which encode transcription factors whose functions have been characterized.
Concordance between Genotypic and Phenotypic Drug-Resistant Profiles of
Shigella
Isolates from Taiyuan City, Shanxi Province, China, 2005 to 2016
Authors: Kong Mimi , Liu Chunmei , Xu Yang , Wang Jitao , Jin Dong
Published: May 2023

Antimicrobial resistance in
Shigella
spp. has become a global public health concern. In this study, we identified the antimicrobial susceptibility testing (AST) characteristics based on genomic sequences of 218
Shigella
isolates and analyzed the correlation between genotypic and phenotypic antibiotic resistance profiles of
Shigella
spp., especially for fluoroquinolone, macrolides, and third-generation cephalosporins.
Stable tungsten isotopic composition of seawater over the past 80 million years
Authors: Yang Ruiyu , Stubbs Daniel , Elliott Tim , Li Tao , Chen Tianyu , Paytan Adina , Kemp David B. , Ling Hongfei , Chen Jun , Hein James R. , Coath Christopher D. , Li Gaojun
Published: May 2023

The isotopic composition of seawater provides valuable information on how the Earth system has evolved. Here we present the stable tungsten isotopic composition (δ186/184W) of seawater recorded in three ferromanganese (Fe-Mn) crusts spanning the past 80 million years in the Pacific. The δ186/184W of Fe-Mn crusts displays a pronounced decrease of ∼0.2‰ from 60 Ma to 40 Ma followed by a stable value of ∼0‰ since ca. 40 Ma. Multiple lines of evidence indicate an invariable equilibrium isotopic fractionation between Fe-Mn crusts and seawater. The consistent variations in δ186/184W in the three Fe-Mn crusts also indicate limited alteration by deposition regime or diagenetic overprinting. Thus, the δ186/184W of Fe-Mn crusts reflects mainly that of seawater. A simple mass-balance calculation and comparison to other proxies suggest that the early Cenozoic decrease of seawater δ186/184W was most likely caused by decreased W isotopic fractionation between seawater and W sinks linked to shifting sedimentation regimes. We propose that increased burial of organics and decreased Fe-Mn oxide (FMO) sedimentation may result in a smaller isotopic fractionation associated with W sinks by limiting the adsorption of W from the water column onto FMOs in openocean sediments. Our results demonstrate the potential of δ186/184W as a novel paleo-proxy for global biogeochemical cycling.
Risk stratified monitoring for methotrexate toxicity in immune mediated inflammatory diseases: prognostic model development and validation using primary care data from the UK
Authors: Nakafero Georgina , Grainge Matthew J , Williams Hywel C , Card Tim , Taal Maarten W , Aithal Guruprasad P , Fox Christopher P , Mallen Christian D , van der Windt Danielle A , Stevenson Matthew D , Riley Richard D , Abhishek Abhishek
Published: May 2023

Objective

To develop and validate a prognostic model to inform risk stratified decisions on frequency of monitoring blood tests during long term methotrexate treatment.

Design

Retrospective cohort study.

Setting

Electronic health records within the UK’s Clinical Practice Research Datalink (CPRD) Gold and CPRD Aurum.

Participants

Adults (≥18 years) with a diagnosis of an immune mediated inflammatory disease who were prescribed methotrexate by their general practitioner for six months or more during 2007-19.

Main outcome measure

Discontinuation of methotrexate owing to abnormal monitoring blood test result. Patients were followed-up from six months after their first prescription for methotrexate in primary care to the earliest of outcome, drug discontinuation for any other reason, leaving the practice, last data collection from the practice, death, five years, or 31 December 2019. Cox regression was performed to develop the risk equation, with bootstrapping used to shrink predictor effects for optimism. Multiple imputation handled missing predictor data. Model performance was assessed in terms of calibration and discrimination.

Results

Data from 13 110 (854 events) and 23 999 (1486 events) participants were included in the development and validation cohorts, respectively. 11 candidate predictors (17 parameters) were included. In the development dataset, the optimism adjusted R2was 0.13 and the optimism adjusted Royston D statistic was 0.79. The calibration slope and Royston D statistic in the validation dataset for the entire follow-up period was 0.94 (95% confidence interval 0.85 to 1.02) and 0.75 (95% confidence interval 0.67 to 0.83), respectively. The prognostic model performed well in predicting outcomes in clinically relevant subgroups defined by age group, type of immune mediated inflammatory disease, and methotrexate dose.

Conclusion

A prognostic model was developed and validated that uses information collected during routine clinical care and may be used to risk stratify the frequency of monitoring blood test during long term methotrexate treatment.
Fecal microbiota transplantation ameliorates type 2 diabetes via metabolic remodeling of the gut microbiota in db/db mice
Authors: Chen Lijuan , Guo Lin , Feng Susu , Wang Congcong , Cui Zhicheng , Wang Sijing , Lu Qingmiao , Chang Hang , Hang Bo , Snijders Antoine M , Mao Jian-Hua , Lu Yibing , Ding Dafa
Published: May 2023

Introduction

Gut microbiome (GM) deregulation has been implicated in major conditions such as obesity and type 2 diabetes (T2DM). Our previous prospective study indicated that fecal microbiota transplantation (FMT) successfully improved patients with T2DM. We hypothesized that FMT may be a potential therapeutic method for T2DM, but its precise mechanisms in T2DM remains to be elucidated.

Research design and methods

Eight db/m mice were FMT donors and control mice, and 16 genetically diabetic db/db mice were equally divided into two groups (db/db+phosphate-buffered saline (PBS) group, db/db+FMT group). The db/db+FMT group was administered fresh fecal suspension (0.2 mL/mice) daily for 4 weeks. Analysis of the GM and serum metabolome was carried out by 16S ribosomal RNA sequencing and liquid chromatogram-mass spectrometry, respectively. Effects of FMT on the gut barrier and pancreas were assessed using protein assays, messenger RNA, immunohistology and clinical indicators testing.

Results

Our results showed that FMT treatment of db/db mice relieves a series of clinical indicators, including fasting plasma glucose, serum insulin and oral glucose tolerance test among others. Compared with non-diabetic control mice, db/db+PBS mice exhibited decreased abundance of Ruminococaceae, Porphyromonadaceae and increased abundance of Rikenellaceae and Lactobacillaceae. FMT treatment reversed this effect on the microbiome. Eleven metabolites were changed between the db/db+PBS and db/db+FMT groups. Correlation analysis showed that the structural changes of the GM were correlated with host metabolite levels. We further showed that FMT treatment of db/db mice improved intestinal barrier function, reduced inflammation and caused an alteration in the number of circulating immune cells.

Conclusions

FMT-mediated changes in the GM, serum metabolites, intestinal epithelial barrier, inflammation and circulating immune cells play an important role in the efficacy of FMT on T2DM disease progression.
Obstacles to the deceased donor transplantation in Pakistan
Authors: Ullah Kaleem , Dogar Abdul Wahab , Ochani Sidhant , Shoaib Azam , Shah Hussain Haider , Ur Rehman Mohammad Ebad
Published: May 2023

Introduction

Transplantation in many Asian countries is moulded by socioeconomic, religious, cultural and health indicators. In most Asian countries, the living-related donation is the common most organ donation. Due to the limited deceased organ donation, live donor programmes flourished in many Asian countries. Another apparent reason for this tremendous growth of living-related programmes in Asian countries is their larger serving population. Several centres from Asia, including Pakistan and India from Southeast Asia and Egypt in Middle East Asia, on the one hand, have recently emerged as leading living donor transplant programmes. On the other hand, a few Asian countries, including Iran and China, have established some of the world’s largest deceased donor programmes.

Discussion

In Pakistan, thousands of patients die from end-stage organ failure annually, seeking organ transplants for survival. The exact statics are not available, but over 50 000 people are estimated to die each year as a result of end-stage organ failure without getting a transplant, about 15 000–18 000 from kidney failure, and 10 000 from liver failure and the National Centre for Health Statistics labelled organ failure as a leading cause of death. Despite all these efforts, the knowledge of organ donation among Pakistani people was determined to be around 60%. In Pakistan, the lack of deceased organ donation programmes and the unwillingness of people to deceased organ donation contributes to an increased demand for living organ donation and patients continue to rely on living donors. We discuss various obstacles to deceased organ donation comprising various challenges that form a unique combination, including religious, economic, social, demographic and political factors.

Conclusion:Every single effort should be made to initiate and establish multiple deceased donor programmes in Pakistan. Developing the deceased donor programmes in the country will be vital to counter the countrywide increasing organ shortage. The mainstay transplant activities like organ procurement and distribution systems need to be adequately developed. It will help achieve national self-sufficiency and decrease living donors’ burden. With education, the behaviour of healthcare professionals and common people can be changed and a positive attitude toward deceased organ donation can be obtained. As healthcare professionals, we should come forward and take responsibility by enrolling ourselves in deceased donors’ registration. Public awareness, medical community interest and government support are essential in initiating and establishing deceased donor programmes in Pakistan.
Cluster analysis of dietary patterns associated with colorectal cancer derived from a Moroccan case–control study
Authors: Qarmiche Noura , El Kinany Khaoula , Otmani Nada , El Rhazi Karima , Chaoui Nour El Houda
Published: May 2023

Introduction

Colorectal cancer (CRC) is a global public health problem. There is strong indication that nutrition could be an important component of primary prevention. Dietary patterns are a powerful technique for understanding the relationship between diet and cancer varying across populations.

Objective

We used an unsupervised machine learning approach to cluster Moroccan dietary patterns associated with CRC.

Methods

The study was conducted based on the reported nutrition of CRC matched cases and controls including 1483 pairs. Baseline dietary intake was measured using a validated food-frequency questionnaire adapted to the Moroccan context. Food items were consolidated into 30 food groups reduced on 6 dimensions by principal component analysis (PCA).

Results

K-means method, applied in the PCA-subspace, identified two patterns: ‘prudent pattern’ (moderate consumption of almost all foods with a slight increase in fruits and vegetables) and a ‘dangerous pattern’ (vegetable oil, cake, chocolate, cheese, red meat, sugar and butter) with small variation between components and clusters. The student test showed a significant relationship between clusters and all food consumption except poultry. The simple logistic regression test showed that people who belong to the ‘dangerous pattern’ have a higher risk to develop CRC with an OR 1.59, 95% CI (1.37 to 1.38).

Conclusion

The proposed algorithm applied to the CCR Nutrition database identified two dietary profiles associated with CRC: the ‘dangerous pattern’ and the ‘prudent pattern’. The results of this study could contribute to recommendations for CRC preventive diet in the Moroccan population.
Mapping health service coverage inequalities in Africa: a scoping review protocol
Authors: Karamagi Humphrey Cyprian , Ben Charif Ali , Afriyie Doris Osei , SY Sokona , Kipruto Hillary , Oyelade Taiwo , Droti Benson
Published: May 2023

Introduction

Addressing inequities in health service coverage is a global priority, especially with the resurgence of interest in universal health coverage. However, in Africa, which has the lowest health service coverage index, there is limited information on the progress of countries in addressing inequalities related to health services. Thus, we seek to map the evidence on inequalities in health service coverage in Africa.

Methods and analysis

We will conduct a scoping review following the Joanna Briggs Institute Manual for Evidence Synthesis. We preregistered this protocol with the Open Science Framework on 26 July 2022 (https://osf.io/zd5bt). We will consider any empirical research that assesses inequalities in relation to services for reproductive, maternal, newborn and child health (eg, family planning), infectious diseases (eg, tuberculosis treatment) and non-communicable diseases (eg, cervical cancer screening) in Africa. We will search MEDLINE, Embase, Web of Science, CINAHL, PsycINFO and Cochrane Library from their inception onwards. We will also hand-search Google and Global Index Medicus, and screen reference lists of relevant studies. We will evaluate studies for eligibility and extract data from included studies using pre-piloted and standardised forms. We will further extract a core set of health service coverage indicators, which are disaggregated by place of residence, race/ethnicity/culture, occupation, gender, religion, education, socioeconomic status and social capital plus equity stratifiers. We will summarise data using a narrative approach involving thematic syntheses and descriptive statistics. We will report our findings according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist.

Ethics and dissemination

Ethical approval is not required as primary data will not be collected. This work will contribute to identifying knowledge gaps in the evidence of inequalities in health service coverage in Africa, and propose strategies that could help overcome current challenges. We will disseminate our findings to knowledge users through a publication in a peer-reviewed journal and organisation of workshops.
Patient–clinician dynamics in remote consultations: a qualitative study of cardiology and rheumatology outpatient clinics in the UK
Authors: Grey Elisabeth , Brown Frankie , Smith Paula , Springett Daniella , Augustine Dan , Sengupta Raj , Peacock Oliver , Gillison Fiona
Published: May 2023

Objective

Explore the experiences of patients and clinicians in rheumatology and cardiology outpatient clinics during the first year of the COVID-19 pandemic, focusing on the impact of remote consultations on interpersonal dynamics.

Design

Qualitative study using semistructured interviews, conducted between February and June 2021.

Setting

The rheumatology and cardiology departments of a general hospital in England, UK.

Participants

All clinicians and a convenience sample of 100 patients in each department who had taken part in a remote consultation in the past month were invited to take part. Twenty-five interviews were conducted (13 with patients, 12 with clinicians).

Results

Three themes were developed through the analysis: adapting to the dynamics of remote consultations, impact on the patient’s experience and impact on the clinician’s experience. The majority of remote consultations experienced by both patients and clinicians had been via telephone. Both clinicians and patients found remote consultations to be more business-like and focused, with the absence of pauses restricting time for reflection. For patients with stable, well-managed conditions, remote consultations were felt to be appropriate and could be more convenient than in-person consultations. However, the loss of visual cues meant some patients felt they could not give a holistic view of their condition and limited clinicians’ ability to gather and convey information. Clinicians adjusted their approach by asking more questions, checking understanding more frequently and expressing empathy verbally, but felt patients still shared fewer concerns remotely than in person; a perception with which patients concurred.

Conclusions

These findings highlight the importance of ensuring, for each patient, that remote care is appropriate. Future research should focus on developing ways to support both clinicians and patients to gather and provide all information necessary during remote consultations, to enhance communication and trust.
Ethical considerations for psychedelic-assisted therapy in military clinical settings
Authors: Hoener Scott , Wolfgang Aaron , Nissan David , Howe Edmund
Published: May 2023

Psychedelic treatments, particularly 3,4-methylenedioxymethamphetamine (MDMA)-assisted and psilocybin-assisted therapies, have recently seen renewed interest in their clinical potential to treat various mental health conditions. Clinical trials for both MDMA-assisted and psilocybin-assisted therapies have shown to be highly efficacious for post-traumatic stress disorder and major depression. Recent research trials for psychedelic-assisted therapies (PAT) have demonstrated that although they are resource-intensive, their effects are rapid-acting, durable and cost-effective. These results have generated enthusiasm among researchers seeking to investigate psychedelic therapies in active-duty service members of the US military, particularly those with treatment refractory mental health conditions. At the same time, psychedelics remain in early stages of clinical investigation, have not yet achieved regulatory approval for general clinical use and may confer unique psychological and neurobiological effects that could raise novel ethical considerations when treating active-duty service members. Should psychedelics achieve regulatory approval, military relevant considerations may include issues of access to these treatments, appropriate procedures for informed consent, confidentiality standards, and possible unanticipated mental health risks and other psychological sequelae. A service member’s deployability, as well as their ability to return to full military duty following PAT, may also be of unique concern. The authors argue that MDMA-assisted therapy currently represents a promising treatment that should be more rapidly investigated as a clinical therapy for service members while still taking a measured approach that accounts for the many military-specific uncertainties that remain.
Effectiveness of adding motivational interviewing or a stratified
vocational advice intervention to usual case management on return to work
for people with musculoskeletal disorders: the MI-NAV randomised controlled
trial
Authors: Aanesen Fiona , Grotle Margreth , Rysstad Tarjei Langseth , Tveter Anne Therese , Tingulstad Alexander , Løchting Ida , Småstuen Milada C , van Tulder Maurits W , Berg Rigmor , Foster Nadine E , Wynne-Jones Gwenllian , Sowden Gail , Fors Egil , Bagøien Gunnhild , Hagen Roger , Storheim Kjersti , Øiestad Britt Elin
Published: May 2023

Objectives

To evaluate if adding motivational interviewing (MI) or a stratified
vocational advice intervention (SVAI) to usual case management (UC),
reduced sickness absence over 6 months for workers on sick leave due to
musculoskeletal disorders.

Methods

We conducted a three-arm parallel pragmatic randomised controlled
trial including 514 employed workers (57% women, median age 49 (range
24–66)), on sick leave for at least 50% of their contracted work hours
for ≥7 weeks. All participants received UC. In addition, those
randomised to UC+MI were offered two MI sessions from social insurance
caseworkers and those randomised to UC+SVAI were offered vocational
advice from physiotherapists (participants with low/medium-risk for
long-term sickness absence were offered one to two sessions, and those
with high-risk were offered three to four sessions).

Results

Median sickness absence was 62 days, (95% CI 52 to 71) in the UC arm
(n=171), 56 days (95% CI 43 to 70) in the UC+MI arm (n=169) and 49 days
(95% CI 38 to 60) in the UC+SVAI arm (n=169). After adjusting for
predefined potential confounding factors, the results showed seven fewer
days in the UC+MI arm (95% CI −15 to 2) and the UC+SVAI arm (95% CI −16
to 1), compared with the UC arm. The adjusted differences were not
statistically significant.

Conclusions

The MI-NAV trial did not show effect on return to work of adding MI
or SVAI to UC. The reduction in sickness absence over 6 months was
smaller than anticipated, and uncertain due to wide CIs.

Trial registration number

NCT03871712.
Case of apparent mpox reinfection
Authors: Golden John , Harryman Lindsey , Crofts Megan , Muir Peter , Donati Matthew , Gillett Sophie , Irish Charles
Published: May 2023

We present an apparent second episode of mpox (monkeypox) genital
ulcerative disease in a non-immunosuppressed MSM (man who has sex with men)
patient who had completely recovered from a primary mpox infection 4 months
previously. The patient had also received a complete two-dose course of
smallpox vaccination between the two presentations. This case highlights the
importance of continuing to include mpox in the differential diagnoses for
individuals presenting with genital or mucosal ulceration, regardless of
assumed immunity derived from prior infection or vaccination.
Volcanogenic massive sulfide (VMS) deposits of the Dunnage Zone of the Newfoundland Appalachians: setting, styles, key advances, and future research
Authors: Piercey Stephen J. , Hinchey John G. , Sparkes Gregory W.
Published: May 2023

The Dunnage Zone of the Newfoundland Appalachians hosts diverse Cambrian–Ordovician volcanogenic massive sulfide (VMS) deposits. The peri-Laurentian Notre Dame Subzone contains Cu–Zn–Au mafic and bimodal mafic deposits in ∼501–485 Ma ophiolitic rocks and Zn–Pb–Cu–(Au–Ag) deposits in ∼471–465 Ma bimodal rifted continental arc sequences (e.g., Buchans). The peri-Gondwanan rocks of the Exploits Subzone host Zn–Pb–Cu–(Au–Ag) bimodal felsic, felsic siliciclastic, and Zn–Ag–Au hybrid bimodal felsic deposits in the ∼513–486 Ma Victoria Lake supergroup; Cu–Zn bimodal felsic to bimodal mafic deposits of the ∼486 Ma Wild Bight Group; and Cu–(Au) mafic siliciclastic deposits of the ∼466 Ma Great Burnt Lake/South Pond belt. Regardless of age or stratigraphic hosts, all VMS deposits are associated with specific magmatic assemblages and extensional tectonism (i.e., rifting). Gold-enriched deposits of the Rambler-Ming district are associated with felsic rocks that formed via slab melting and subsequent melt-mantle wedge interaction, which likely enhanced precious metal enrichment in these deposits. Whereas many deposits exhaled on the seafloor, some deposits formed via subseafloor replacement of host units or as re-sedimented sulfides generated in sediment-gravity flows. Metals in the deposits were derived from leaching of underlying footwall rocks; however, Au–Ag- and epithermal suite element-enriched deposits show evidence for metal contributions from magmatic hydrothermal fluids. Sulfur in deposits was derived predominantly from leaching of H2S from underlying footwall rocks and from thermochemical sulfate reduction of seawater sulfate, with lesser input from bacteria-derived H2S and magmatic-hydrothermal-derived H2S. Despite recent research advances and historic mining, numerous questions remain unresolved and provide opportunities for future study.
Obtaining of thin films of manganese silicides on a Si surface by the method of solid-phase deposition and investigation of their electronic structure
Authors: Umirzakov B. E. , Imanova G. T. , Bekpulatov I. R. , Turapov I. Kh.
Published: May 2023

The regularities of the formation of thin Mn/Si (111) nanofilms during solid-phase deposition of Mn on Si under conditions of ultrahigh vacuum ([Formula: see text][Formula: see text]Pa) and thin Mn4Si7/Si (111) nanofilms during annealing of the Mn/Si system have been studied. It has been established that silicon atoms diffuse into the Mn film up to a thickness of [Formula: see text]–12 monolayers, and Mn in Si up to [Formula: see text]–10 monolayers, therefore, a transition layer of nonstoichiometric MnxSiy silicide is formed at the Mn–Si interface. After heating at [Formula: see text][Formula: see text]K, the higher manganese silicide (HMS) Mn4Si7 is formed. In particular, it was found that the bandgap of Mn4Si7is [Formula: see text][Formula: see text]eV, and the electron affinity is [Formula: see text][Formula: see text]eV and in the work, the optimal thermal diffusion conditions for the formation of stoichiometric Mn4Si7 silicide are determined. It is shown that at [Formula: see text][Formula: see text]K, a partial formation of a chemical bond between manganese and silicon atoms occurs. At 1100[Formula: see text]K, a thin Mn4Si7 film with a good stoichiometric composition is formed.
About this title - Celebrating 100 Years of Female Fellowship of the Geological Society: Discovering Forgotten Histories
Authors: Burek C. V. , Higgs B. M.
Published: May 2023

The Geological Society of London was founded in 1807. At the time, membership was restricted to men, many of whom became well-known names in the history of the geological sciences. On the 21 May 1919, the first female Fellows were elected to the Society, 112 years after its formation.

This Special Publication celebrates the centenary of that important event. In doing so it presents the often untold stories of pioneering women geoscientists from across the world who navigated male-dominated academia and learned societies, experienced the harsh realities of Siberian field-exploration, or responded to the strategic necessity of the ‘petroleum girls’ in early American oil exploration and production.

It uncovers important female role models in the history of science, and investigates why not all of these women received due recognition from their contemporaries and peers. The work has identified a number of common issues that sometimes led to original work and personal achievements being lost or unacknowledged, and as a consequence, to histories being unwritten.
Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump
Authors: Hu Sihao , Zhang Zhen , Lu Shengliang , He Bingsheng , Li Zhao
Published: May 2023

With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it becomes imperative to detect such fraudulent activities in advance to alert potentially susceptible investors. In this paper, we focus on predicting the pump probability of all coins listed in the target exchange before a scheduled pump time, which we refer to as the target coin prediction task. Firstly, we conduct a comprehensive study of the latest 709 P&D events organized in Telegram from Jan. 2019 to Jan. 2022. Our empirical analysis reveals some interesting patterns of P&Ds, such as that pumped coins exhibit intra-channel homogeneity and inter-channel heterogeneity. Here channel refers a form of group in Telegram that is frequently used to coordinate P&D events. This observation inspires us to develop a novel sequence-based neural network, dubbed SNN, which encodes a channel's P&D event history into a sequence representation via the positional attention mechanism to enhance the prediction accuracy. Positional attention helps to extract useful information and alleviates noise, especially when the sequence length is long. Extensive experiments verify the effectiveness and generalizability of proposed methods. Additionally, we release the code and P&D dataset on GitHub https://github.com/Bayi-Hu/Pump-and-Dump-Detection-on-Cryptocurrency, and regularly update the dataset.
iFlipper: Label Flipping for Individual Fairness
Authors: Zhang Hantian , Tae Ki Hyun , Park Jaeyoung , Chu Xu , Whang Steven Euijong
Published: May 2023

As machine learning becomes prevalent, mitigating any unfairness present in the training data becomes critical. Among the various notions of fairness, this paper focuses on the well-known individual fairness, which states that similar individuals should be treated similarly. While individual fairness can be improved when training a model (in-processing), we contend that fixing the data before model training (pre-processing) is a more fundamental solution. In particular, we show that label flipping is an effective pre-processing technique for improving individual fairness.

Our system iFlipper solves the optimization problem of minimally flipping labels given a limit to the individual fairness violations, where a violation occurs when two similar examples in the training data have different labels. We first prove that the problem is NP-hard. We then propose an approximate linear programming algorithm and provide theoretical guarantees on how close its result is to the optimal solution in terms of the number of label flips. We also propose techniques for making the linear programming solution more optimal without exceeding the violations limit. Experiments on real datasets show that iFlipper significantly outperforms other pre-processing baselines in terms of individual fairness and accuracy on unseen test sets. In addition, iFlipper can be combined with in-processing techniques for even better results.
SANTOS: Relationship-based Semantic Table Union Search
Authors: Khatiwada Aamod , Fan Grace , Shraga Roee , Chen Zixuan , Gatterbauer Wolfgang , Miller Renée J. , Riedewald Mirek
Published: May 2023

Existing techniques for unionable table search define unionability using metadata (tables must have the same or similar schemas) or column-based metrics (for example, the values in a table should be drawn from the same domain). In this work, we introduce the use of semantic relationships between pairs of columns in a table to improve the accuracy of the union search. Consequently, we introduce a new notion of unionability that considers relationships between columns, together with the semantics of columns, in a principled way. To do so, we present two new methods to discover the semantic relationships between pairs of columns. The first uses an existing knowledge base (KB), and the second (which we call a "synthesized KB") uses knowledge from the data lake itself. We adopt an existing Table Union Search benchmark and present new (open) benchmarks that represent small and large real data lakes. We show that our new unionability search algorithm, called SANTOS, outperforms a state-of-the-art union search that uses a wide variety of column-based semantics, including word embeddings and regular expressions. We show empirically that our synthesized KB improves the accuracy of union search by representing relationship semantics that may not be contained in an available KB. This result hints at a promising future of creating synthesized KBs from data lakes with limited KB coverage and using them for union search.
LadderFilter: Filtering Infrequent Items with Small Memory and Time Overhead
Authors: Li Yuanpeng , Wang Feiyu , Yu Xiang , Yang Yilong , Yang Kaicheng , Yang Tong , Ma Zhuo , Cui Bin , Uhlig Steve
Published: May 2023

Data stream processing is critical in streaming databases. Existing works pay a lot of attention to frequent items. To improve the accuracy for frequent items, existing solutions focus on accurately filtering infrequent items. While these solutions are effective, they keep track of all infrequent items and require multiple hash computations and memory accesses. This increases memory and time overhead. To reduce this overhead, we propose LadderFilter, which candiscard infrequent items efficiently in terms of both memory and time. To achieve memory efficiency, LadderFilter discards (approximately) infrequent items using multiple LRU queues. To achieve time efficiency, we leverage SIMD instructions to implement LRU policy without timestamps. We apply LadderFilter to four types of sketches. Our experimental results show that LadderFilter improves the accuracy by up to 60.6×, and the throughput by up to 1.37×, and can maintain high accuracy with small memory usage. All related code is provided open-source at Github.
Incremental Tabular Learning on Heterogeneous Feature Space
Authors: Liu Hanmo , Di Shimin , Chen Lei
Published: May 2023

Recently, incremental learning has attracted a lot of interest in both research communities and industries. Generally, given a series of data sets sequentially, it tries to achieve good performance on the new data set while maintaining not bad performance on the old ones. Despite the recent success of incremental learning, existing works mainly assume that the coming data set is from the feature space of old ones, i.e., homogeneous feature space. And they adopt one feature extractor to forcibly project different feature spaces into one space. However, this assumption is hard to hold in real-world scenarios. Especially, the attributes of tables may sequentially increase in tabular learning. Thus, classic incremental learning models may hinder their effectiveness. In this paper, we propose a new method, incremental tabular learning on heterogeneous feature space (ILEAHE) to solve this issue. We first propose the ideas that feature extractors should be decomposed into shared and specific extractors to process the shared and specific features across different data sets respectively. Then, we propose a novel measurement named discriminative ability to measure specific extractors. Thus, two kinds of extractors can be discriminated and the specific extractor will more focus on those domain-specific features. We further demonstrate the effectiveness of ILEAHE through empirical studies.
Grouping Time Series for Efficient Columnar Storage
Authors: Fang Chenguang , Song Shaoxu , Guan Haoquan , Huang Xiangdong , Wang Chen , Wang Jianmin
Published: May 2023

Columnar storage is now an industry standard design in most open-source or commercial time series database products, making them HTAP systems. The time column of a time series serves as the key for identifying the other value column, namely single-column storage scheme. When multiple time series share a similar set of timestamps, very likely in a module of multiple sensors, it is natural to group them together, i.e., one time column identifies multiple value columns in a single-group storage scheme. While multiple value columns sharing the same time column reduce the space cost of repeating timestamps, it may introduce extra space cost for recording null values. The reason is that time series may not be exactly aligned on each timestamp, owing to missing values, distinct data collection frequencies, unsynchronized clocks and so on. The columngroups storage scheme is thus to divide columns into multiple groups, within which the value columns share the same time column. Unfortunately, the problem of finding the optimal column groups for the minimum space cost is highly challenging, NP-hard according to our analysis. Thereby, we propose a heuristic algorithm for automatically grouping time series for efficient columnar storage. The column groups storage has been deployed in Apache IoTDB, an open-source time series database. The extensive performance analysis, over real-world data from our industrial partners, demonstrates that the proposed column groups achieve near optimal storage, more concise than the storage of single-column or single-group schemes. Interestingly, both the flushing and querying time costs of column groups are comparable to those of single-column or singlegroup, i.e., without incurring extra time cost.
ClipSim: A GPU-friendly Parallel Framework for Single-Source SimRank with Accuracy Guarantee
Authors: Wu Tianhao , Cheng Ji , Zhang Chaorui , Hou Jianfeng , Chen Gengjian , Huang Zhongyi , Zhang Weixi , Han Wei , Bai Bo
Published: May 2023

SimRank is an important metric to measure the topological similarity between two nodes in a graph. In particular, single-source and top-k SimRank has numerous applications in recommendation systems, network analysis, and web mining, etc. Mathematically, given a vertex, the computation of single-machine and single-source SimRank mainly lies in matrix-matrix operations. However, it is almost impossible to directly compute on large graphs. Thus, existing works yield to two main operations: a series of random walks, and sparse matrix and dense vector multiplication operations. This brings about high computation cost for SimRank on large graphs. In real-world applications, there is always the query time and accuracy trade-off, which hinders the computation of high-precision SimRank on large-scale graphs.

To handle this problem, this paper proposesClipSim, the first GPU-friendly parallel framework that accelerates the single-source SimRank on GPU with accuracy guarantee. We design a novel data structure and GPU-friendly parallel algorithms for efficient computation of all the operations of SimRank on GPU. Moreover, our theoretical derivation enables ClipSim to largely reduce the number of random walks required for each node, while maintaining the same theoretical accuracy as the state-of-the-art algorithm, ExactSim. We conduct extensive experiments on real-world and synthetic datasets to demonstrate the accuracy and efficiency of ClipSim. The results show that compared with ExactSim, ClipSim obtains single-source SimRank vectors with the same accuracy and up to 160× faster computation time.
GitTables: A Large-Scale Corpus of Relational Tables
Authors: Hulsebos Madelon , Demiralp Çagatay , Groth Paul
Published: May 2023

The success of deep learning has sparked interest in improving relational table tasks, like data preparation and search, with table representation models trained on large table corpora. Existing table corpora primarily contain tables extracted from HTML pages, limiting the capability to represent offline database tables. To train and evaluate high-capacity models for applications beyond the Web, we need resources with tables that resemble relational database tables. Here we introduce GitTables, a corpus of 1M relational tables extracted from GitHub. Our continuing curation aims at growing the corpus to at least 10M tables. Analyses of GitTables show that its structure, content, and topical coverage differ significantly from existing table corpora. We annotate table columns in GitTables with semantic types, hierarchical relations and descriptions from Schema.org and DBpedia. The evaluation of our annotation pipeline on the T2Dv2 benchmark illustrates that our approach provides results on par with human annotations. We present three applications of GitTables, demonstrating its value for learned semantic type detection models, schema completion methods, and benchmarks for table-to-KG matching, data search, and preparation. We make the corpus and code available at https://gittables.github.io.
Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data
Authors: Kurmanji Meghdad , Triantafillou Peter
Published: May 2023

Machine Learning (ML) is changing DBs as many DB components are being replaced by ML models. One open problem in this setting is how to update such ML models in the presence of data updates. We start this investigation focusing on data insertions (dominating updates in analytical DBs). We study how to update neural network (NN) models when new data follows a different distribution (a.k.a. it is "out-of-distribution" -- OOD), rendering previously-trained NNs inaccurate. A requirement in our problem setting is that learned DB components should ensure high accuracy for tasks on old and new data (e.g., for approximate query processing (AQP), cardinality estimation (CE), synthetic data generation (DG), etc.).

This paper proposes a novel updatability framework (DDUp). DDUp can provide updatability for different learned DB system components, even based on different NNs, without the high costs to retrain the NNs from scratch. DDUp entails two components: First, a novel, efficient, and principled statistical-testing approach to detect OOD data. Second, a novel model updating approach, grounded on the principles of transfer learning with knowledge distillation, to update learned models efficiently, while still ensuring high accuracy. We develop and showcase DDUp's applicability for three different learned DB components, AQP, CE, and DG, each employing a different type of NN. Detailed experimental evaluation using real and benchmark datasets for AQP, CE, and DG detail DDUp's performance advantages.
FlexER: Flexible Entity Resolution for Multiple Intents
Authors: Genossar Bar , Shraga Roee , Gal Avigdor
Published: May 2023

Entity resolution, a longstanding problem of data cleaning and integration, aims at identifying data records that represent the same real-world entity. Existing approaches treat entity resolution as a universal task, assuming the existence of a single interpretation of a real-world entity and focusing only on finding matched records, separating corresponding from non-corresponding ones, with respect to this single interpretation. However, in real-world scenarios, where entity resolution is part of a more general data project, downstream applications may have varying interpretations of real-world entities relating, for example, to various user needs. In what follows, we introduce the problem of multiple intents entity resolution (MIER), an extension to the universal (single intent) entity resolution task. As a solution, we propose FlexER, utilizing contemporary solutions to universal entity resolution tasks to solve MIER. FlexER addresses the problem as a multi-label classification problem. It combines intent-based representations of tuple pairs using a multiplex graph representation that serves as an input to a graph neural network (GNN). FlexER learns intent representations and improves the outcome to multiple resolution problems. A large-scale empirical evaluation introduces a new benchmark and, using also two well-known benchmarks, shows that FlexER effectively solves the MIER problem and outperforms the state-of-the-art for a universal entity resolution.
Efficient Sampling Approaches to Shapley Value Approximation
Authors: Zhang Jiayao , Sun Qiheng , Liu Jinfei , Xiong Li , Pei Jian , Ren Kui
Published: May 2023

Shapley value provides a unique way to fairly assess each player's contribution in a coalition and has enjoyed many applications. However, the exact computation of Shapley value is #P-hard due to the combinatoric nature of Shapley value. Many existing applications of Shapley value are based on Monte-Carlo approximation, which requires a large number of samples and the assessment of utility on many coalitions to reach high quality approximation, and thus is still far from being efficient. Can we achieve an efficient approximation of Shapley value by smartly obtaining samples? In this paper, we treat the sampling approach to Shapley value approximation as a stratified sampling problem. Our main technical contributions are a novel stratification design and two sample allocation methods based on Neyman allocation and empirical Bernstein bound, respectively. Experimental results on several real data sets and synthetic data sets demonstrate the effectiveness and efficiency of our novel stratification design and sampling approaches.
Maximum k-Biplex Search on Bipartite Graphs: A Symmetric-BK Branching Approach
Authors: Yu Kaiqiang , Long Cheng
Published: May 2023

Enumerating maximal k-biplexes (MBPs) of a bipartite graph has been used for applications such as fraud detection. Nevertheless, there usually exists an exponential number of MBPs, which brings up two issues when enumerating MBPs, namely the effectiveness issue (many MBPs are of low values) and the efficiency issue (enumerating all MBPs is not affordable on large graphs). Existing proposals of tackling this problem impose constraints on the number of vertices of each MBP to be enumerated, yet they are still not sufficient (e.g., they require to specify the constraints, which is often not user-friendly, and cannot control the number of MBPs to be enumerated directly). Therefore, in this paper, we study the problem of finding K MBPs with the most edges called MaxBPs, where K is a positive integral user parameter. The new proposal well avoids the drawbacks of existing proposals (i.e., the number of MBPs to be enumerated is directly controlled and the MBPs to be enumerated tend to have high values since they have more edges than the majority of MBPs). We formally prove the NP-hardness of the problem. We then design two branch-and-bound algorithms, among which, the better one called FastBB improves the worst-case time complexity to O*(γkn), where O* suppresses the polynomials, γk is a real number that relies on k and is strictly smaller than 2, and n is the number of vertices in the graph. For example, for k=1, γk is equal to 1.754. We further introduce three techniques for boosting the performance of the branch-and-bound algorithms, among which, the best one called PBIE can further improve the time complexity to O*(γkd3) for large sparse graphs, where d is the maximum degree of the graph (note that d< <n for sparse graphs). We conduct extensive experiments on both real and synthetic datasets, and the results show that our algorithm is up to four orders of magnitude faster than all baselines and finding MaxBPs works better than finding all MBPs for a fraud detection application.