bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mock samples resolve biases in diversity estimates and quantitative interpretation of zooplankton metabarcoding data
Authors: Ershova Elizaveta , Wangensteen Owen S. , Falkenhaug Tone 
Published: April 2023

Abstract
Metabarcoding is a rapidly developing tool in marine zooplankton ecology, although most zooplankton surveys continue to rely on visual identification for monitoring purposes. We attempted to resolve some of the biases associated with metabarcoding by sequencing a 313 b.p. fragment of the COI gene in 34 “mock” samples from the North Sea which were pre-sorted to species level, with biomass and abundance estimates obtained for each species and taxonomic group. The samples were preserved either in 97% ethanol or dried for 24 hours in a drying oven at 65° C (the routine way of preserving samples for dry weight measurements). The visual identification yielded a total of 59 unique holoplanktonic and 16 meroplanktonic species/taxa. Metabarcoding identified 86 holoplanktonic and 124 meroplanktonic species/taxa, which included all but 3 of the species identified visually as well as numerous species of hard-to-identify crustaceans, hydrozoan jellyfish and larvae of benthic animals. On a sample-to-sample basis, typically 90–95% of visually registered species were recovered, but the number of false positives was also high. We demonstrate robust correlations of relative sequence abundances to relative biomass for most taxonomic groups and develop conversion factors for different taxa to account for sequencing biases. We then combine the adjusted sequencing data with a single bulk biomass measurement for the entire sample to produce a quantitative parameter akin to species biomass. When examined with multivariate statistics, this parameter, which we call BWSR (Biomass weighed sequence reads) showed very similar trends to species biomass and comparable patterns to species abundance, highlighting the potential of metabarcoding not only for biodiversity estimation and mapping of presence/absence of species, but also for quantitative assessment of zooplankton communities.
Sequential Labelling and DNABERT For Splice Site Prediction in Homo Sapiens DNA
Authors: Leksono Muhammad Anwari , Purwarianti Ayu 
Published: April 2023

Abstract
Background
Gene prediction on DNA has been conducted using various deep learning architectures to discover splice sites to locate intron and exon regions. However, recent predictions are carried out with models trained with a sequence which has a splice site in the middle. This case eliminates the possibility of multiple splice sites in a single sequence.
Results
This research proposes a sequential labelling model to predict splice sites regardless of their position in a sequence. A sequential labelling model named DNABERT-SL is developed on pre-trained DNABERT-3. DNABERT-SL is benchmarked against the latest sequential labelling model for mutation type and location prediction based on BiLSTM and BiGRU. While achieving F1 scores above 0.8 on validation data, BiLSTM, BiGRU, and DNABERT-SL perform poorly on test data as indicated by their respective low F1 scores (0.498 ± 0.184, 0.6 ± 0.123, 0.532 ± 0.245).
Conclusions
DNABERT-SL model cannot distinguish nucleotides acting as splice sites from normal ones. Principal component analysis on token contextual representation produced by DNABERT-SL shows that the representation is not optimal for distinguishing splice site tokens from non-splice site tokens. Splice site motif observation conducted on test and training sequences shows that an arbitrary sequence with GT-AG motif can be both splice sites in some sequences and normal nucleotides in others.
High-density NV Ensemble with Mutual Interaction of NV Centers Created in Ultra Heavily Nitrogen-doped CVD Diamond
Authors: Hayasaka Kyosuke , Kanehisa Kyotaro , Ueda Mayu , Kimura Kosuke , Tanii Takashi , Onoda Shinobu , Enomoto Shinpei , Kawarada Hiroshi 
Published: April 2023

Abstract
A nitrogen vacancy (NV) center in diamond is a promising platform for the study of quantum sensing and quantum many-body physics. It is essential for such study to realize a system in which NV centers interact with one another. This requires the fabrication of highly concentrated NV centers, as the centers must exist within a few nanometers of one another. Only a few such samples have been fabricated, because the required irradiation of several-MV electron beams over long periods makes such sample preparation difficult. Here, highly concentrated NV ensembles ([NV] = 8.5 × 1018 cm-3) were created by narrowing the electron beam of a transmission electron microscope to generate large amounts of vacancies in highly concentrated nitrogen-doped CVD diamond ([N] = 8 × 1020 cm-3). This result reduces the difficulty of producing high-concentration NV ensembles and is expected to promote the development of many-body quantum physics.
Unusual Flexibility of Transparent Poly(methylsilsesquioxane) Aerogels by Surfactant-Induced Mesoscopic Fiber Assembly
Authors: Ueoka Ryota , Hara Yosuke , Maeno Ayaka , Kaji Hironori , Nakanishi Kazuki , Kanamori Kazuyoshi 
Published: April 2023

Abstract
We report a new synthetic strategy to realize highly transparent aerogels with outstanding bending flexibility. Taking poly(methylsilsesquioxane) (PMSQ) aerogels as an example, surfactant-induced fiber-like mesoscopic assembly of PMSQ and poly(ethylene oxide)-block-poly(propylene oxide)-block-poly(ethylene oxide) (PEO-b-PPO-b-PEO, so-called Pluronics) has been demonstrated. The obtained PMSQ aerogels possessed a characteristic branched fibrous structure in the mesoscale. With employing various kinds of PEO-b-PPO-b-PEO as the structure determining agent, optimization of the mesoscale structure of PMSQ gels has realized highly transparent aerogels with outstanding bendability compared to those reported in previous works. This approach provides a novel way to thermally superinsulating flexible devices with glasslike transparency.
Chemotherapy for Cancer Treatment: An L1 Optimal Control Approach
Authors: Rautela Akansha , Neetish  , Bora Riddhi Mohan , Dey Bhabani Shankar , Paul Chayan Kumar 
Published: April 2023

Abstract
Chemotherapy as a cancer treatment has garnered much scientific interest in recent years. Chemotherapy is essential for the elimination of cancer cells to the greatest extent possible. Clinical studies demonstrate a predictable trajectory of tumor volume after chemotherapy. However, the standard dose regimens often utilized in chemotherapy have substantial toxicity and little therapeutic value. Consequently, optimum drug dosage is crucial for effectively reducing the tumor size to a defined level while tracking a predefined course. This work establishes optimum control theory with L1-norm based cost function to discover the inputs that decrease the difference between real tumor growth and goal size to improve treatment efficacy while minimizing the side effects. Because of the bang-off nature of the L1-norm control profile, intermittent drug dosing is possible. This study also compares and contrasts the findings with the cost function based on L2-norm. Simulation findings validate the performance of the proposed control scheme for chemotherapy. Further study is needed to confirm the procedures in clinical situations and optimize the regimens for individual patients.
Comprehensive evaluation of serum nutritional markers in predicting prognosis among cancer patients with cachexia
Authors: Huang Jiaxin , Zhang Xi , Tang Meng , Zhang Qi , Deng Li , Song Chunhua , Li Wei , Shi Hanping , Cong Ming-Hua 
Published: April 2023

Abstract
Purpose
Our objective is to comprehensively assess the prognostic value of three serum nutritional markers including albumin, prealbumin, and transferrin in patients with cancer cachexia.
Methods
Concordance index and receiver operating characteristic curves were applied to compare the prognostic performance of different markers. The primary outcome was overall survival (OS), with comprehensive survival analyses were performed. The second outcomes were short-term survival and quality of life.
Results
This multicenter prospective cohort study included 1303 cancer cachexia patients, with 592 death cases during a median follow-up of 20.23 months. Albumin was the most accurate prognostic predictor, followed by transferrin and prealbumin. Multivariate Cox analysis confirmed that low albumin (hazard ratio = 1.55, 95% confidence interval = 1.31–1.84, P < 0.001), prealbumin (HR = 1.33, 95%CI = 1.11–1.59, P = 0.002), and transferrin (HR = 1.46, 95%CI = 1.22–1.74, P < 0.001) were independent risk factors associated with survival in cancer cachexia patients. The prognostic value of low albumin was significant in patients with upper gastrointestinal, hepatobiliary and pancreatic and colorectal cancers; low prealbumin was significant in colorectal cancer; and low transferrin was significant in patients with upper gastrointestinal and colorectal cancer. All three nutritional markers were valuable in predicting survival for patients in advanced stages. The risks of short-term mortalit and poor quality of life were significantly increased in patients with low serum nutritional markers.
Conclusion
Low albumin, prealbumin, and transferrin levels were all independent prognostic factors for patients with cancer cachexia, especially in advanced stages.
Epidemiology of Polypharmacy, Drug-drug Interaction, and Potentially Inappropriate Medication Among Metabolic Syndrome Patients in Iran: A National, Cross-sectional, Multi-level Study
Authors: Daneshmand Mojdeh , Jamshidi Hamidreza , Malekpour Mohammad-Reza , Ghasemi Erfan , Moghaddam Sahar Saeedi , Mortazavi Seyede Salehe , Shati Mohsen , Farjoo Mohammad Hadi , Farzadfar Farshad 
Published: April 2023

Abstract

Purpose
The prevalence of metabolic syndrome is 4.8% in adults worldwide. In the treatment process, Polypharmacy which is defined as concomitant use of ≥ 5 medications in a prescription is common and it may lead to untoward Drug-drug interactions.
Methods
A population-based, cross sectional study was conducted following joining the data from Iranians Health Insurance Service prescriptions in 2015 and 2016 with patients data from STEPwise approach to risk factor Surveillance 2016 survey in Iran. Epidemiology of polypharmacy was evaluated among Metabolic syndrome patients, and association between polypharmacy and individual and sociodemographic factors was assessed with polypharmacy being the dependent variable. Potentially Inappropriate Medication was evaluated among the ≥ 60 year-olds and, as the dependent variable, its association with individual and sociodemographic factors as well as polypharmacy was evaluated. Drug-drug interactions were assessed using LexiComp® software. Logistic regression analysis was used to analyze the associations.
Results
Out of 2075 patients, 10.3% had polypharmacy. There was significant association between polypharmacy with age and area of living (p < 0.001). Potentially Inappropriate Medication was 13.2% and its association with area of living was significant (p < 0.001). Among patients with polypharmacy, 91.4% in 2015, and 90.1% in 2016 had drug-drug interactions. Prevalence of C, D, and X risk category and prescriptions with 3 kinds of risk categories (C + D + X) was more among patients with polypharmacy.
Impact of the OncotypeDX score and HER2 RNA PCR levels on HER-low IHC levels in primary and metastasized tumors
Authors: Feldman Didi , Sinberger Liat Anabel , Salmon-Divon Mali , Ben-Dror Judith , Shachar Shlomit Strulov , Sonnenblick Amir 
Published: April 2023

Abstract
Purpose One-half of hormone receptor-positive (HR+) breast cancer (BC) patients have low expressions of HER2 (HER2-low) and may benefit from Trastuzumab Deruxtecan (TDxd). This study aimed to identify parameters associated with HER2 low levels in primary and metastatic tumors. We specifically sought to determine whether OncotypeDX and HER2 mRNA levels could identify patients that would otherwise be considered HER2 negative (HER2-) by immunohistochemistry (IHC).
Methods This retrospective analysis of all consecutive HR+ patients who underwent OncotypeDX from January 2004 to December 2020 was conducted in a single medical center (n=1429). A HER2 positivity cutoff of >10% stained cells was applied. We divided HER2- cases into HER2-low (IHC=1 or 2 and non-amplified fluorescent situ hybridization) and HER2- (IHC=0). HER2-RT-PCR was evaluated from the OncotypeDX results.
Results HER2-low cases reached higher HER2 RT-PCR scores (p=2.1e-9), expressed higher ER levels (p=0.0114) and were larger than the HER2- cases, (>2 cm; 36.6% versus 22.1%, respectively, p<0.00001). Primary tumors >2 cm are more likely to be HER2-low (OR=2.07, 95 % CI: 1.6317 to 2.6475, p< 0.0001). Of the 274 tumors with HER2-RT-PCR scores >10, 74% were classified as HER2-low. Metastatic BCs expressed higher HER2 IHC scores compared with primary BCs (Wilcoxon signed-rank, p=0.046). HER2 IHC scores were higher for low-risk vs. medium-risk OncotypeDX (p=0.0067). No other clinical or pathological parameters were associated with the increase of HER2 levels in the metastatic samples.
Conclusion It might be beneficial using clinical data from the primary tumor, including the HER2-RT-PCR score, to determine a HER2-low status.
Feature Representation in Pretrained Deep Metric Embeddings
Authors: Furlong Ryan , O'Brien Vincent , Garland James , Alonso Daniel Palacios , Mateos Francisco Dominguez 
Published: April 2023

Abstract
In deep metric learning (DML), high-level input data are represented in a lower-level representation (embedding) space, such that samples from the same class are mapped close together, while samples from disparate classes are mapped further apart. In this lower-level representation, only a single inference sample from each known class is required to discriminate between classes accurately. The features a DML model uses to discriminate between classes and the importance of each feature in the training process are unknown. To investigate this, this study takes embeddings trained to discriminate faces (identities) and uses unsupervised clustering to identify the features involved in facial identity discrimination by examining their representation within the embedded space. This study is split into two cases; intra class sub-discrimination, where attributes that differ between a single identity are considered; such as beards and emotions; and extra class sub-discrimination, where attributes which differ between different identities/people, are considered; such as gender, skin tone and age. In the intra class scenario, the inference process distinguishes common attributes between single identities, achieving 90.0\% and 76.0\% accuracy for beards and glasses, respectively. The system can also perform extra class sub-discrimination with a high accuracy rate, notably 99.3\%, 99.3\% and 94.1\% for gender, skin tone, and age, respectively.
AutoZooMS: Integrating robotics into high-throughput ZooMS for the species identification of archaeofaunal remains at Grotte Mandrin, France
Authors: Oldfield Ellie-May , Dunstan Mark , Chowdhury Manasij Pal , Slimak Ludovic , Buckley Michael 
Published: April 2023

Abstract

As the vast majority of excavated archaeofaunal skeletal remains are fragmentary to the extent that they cannot be identified by morphological analysis alone, various molecular methods have been considered to retrieve information from an otherwise underutilised resource. The introduction of collagen fingerprinting, known as Zooarchaeology by Mass Spectrometry (ZooMS), has become one of the most popular approaches to improve taxonomic data yields from fragmentary bone. However, few studies have analysed large numbers of samples. Here we test the incorporation of liquid-handling robots to further develop ZooMS into a more automated technique using samples excavated from Grotte Mandrin, France. By increasing the faunal identifications of the B2 layer (~42-44 Ka) at Grotte Mandrin from 55 to 1037, we identified a wider range of taxa, now including bear and mammoth, as well as further remains of hominin. AutoZooMS has the capacity to investigate larger proportions of archaeofaunal assemblages rapidly and cost effectively whilst requiring little human intervention, aiming to improve our understanding of the human past.
Endoscopic Retrograde Cholangiopancreatography Outcomes in Inflammatory Bowel Disease Patients: A 12 -Year Analysis of a National Database
Authors: Deshmukh Ameya , Desai Parth M. , Chrusciel Timothy , Nwankwo Eugene , Tripathi Rohan , Cheesman Antonio R. 
Published: April 2023

Abstract
Background:
Despite inflammatory bowel’s disease’s (IBD) association with hepatobiliary disorders and the use of endoscopic retrograde cholangiopancreatography (ERCP) for both diagnostic and therapeutic evaluation of these diseases, it remains a poorly studied area within the literature. The purpose of this study is to examine the effect of IBD on the occurrence of adverse events (AE) pertaining to ERCP.
Methods:
This project utilized the National Inpatient Sample (NIS) database, the largest inpatient database in the United States. All patients 18 years or older with and without IBD undergoing ERCP were identified from 2008 to 2019. Post-ERCP AEs were analyzed using multivariate logistic or linear regression controlling for age, race, and existing comorbidities using the Charlson comorbidity index (CCI).
Results:
There was no difference in post-ERCP pancreatitis (PEP) or mortality. IBD patients were also found to have a lower risk of bleeding and decreased length of stay (LOS) despite adjustment for co-morbidities. Subgroup analysis between ulcerative colitis (UC) and Crohn’s disease (CD) did not find any significant differences in outcomes.
Conclusion:
To our knowledge, this is the largest study to date evaluating ERCP outcomes in IBD patients. After adjustment of co-variates, there was no difference in the occurrence of PEP, infections and perforation. IBD patients were less likely to experience post-ERCP bleeding, mortality and LOS.
Experimental investigation on nonlinear flow properties of fluids through rough-walled shale fractures after shear
Authors: Yu Liyuan , Ji Haoqi , Wang Xiaolin , Liu Richeng , Zhu Xinjie 
Published: April 2023

Abstract
For a single fracture, the magnitude of Reynolds number (Re) is proportional to that of hydraulic gradient (J), and J is also a dimensionless parameter representing how fast a pressure drops over a given region. Therefore, J is also a practical parameter for establishing a criterion that quantifies the onset of nonlinear flow in single fractures. This study experimentally analyzed the influences of surface roughness, shear displacement and confining pressure on nonlinear flow behaviors of fluids through 3D rough-walled rock fractures. A total of 10 shale samples with different joint roughness coefficients (JRCs) were prepared after Brazil splitting tests, and the distribution of asperity height distribution for each sample was analyzed using a Gaussian function. The shear displacement (us) that ranges from 1 mm to 10 mm was assigned to generate aperture spaces. Flow tests with flow rate (Q) ranging from 1 ~ 180 ml/min were conducted under confining pressures (σ3) of 1 MPa, 3 MPa, and 5MPa, respectively. The Forchheimer equation fits the Q-J correlations by zero intercept regression well and the fitting correlation coefficients of all cases are greater than 0.99. Normalized transmissivity T/T0 first maintains a value of 1 and then gradually decreases as J increases, indicating that the fluid flow state changes from the linear region to the nonlinear region. Finally, a nonlinear curve fitting formula based on the tests database was proposed to investigate the evolutions of critical hydraulic gradient Jc with varying us and JRC. As us increases, Jc drops sharply. Then, the downward trend gradually slows down, and finally approaches a constant value of approximately 1. Jc increases slightly as JRC increases and shows an exponential growth trend with the increase of σ3.
Genetic association of C-reactive protein with periodontitis: a two-sample Mendelian randomization study
Authors: Liu Rong , Jiang Yiqin , Li Yinghua , Liang Dongliang , Luo Rui , Cui Wenjun , Yang Lan 
Published: April 2023

Abstract
Background The association between C-reactive protein (CRP) and periodontitis has been reported in several observational studies. However, those studies are prone to residual confounding , thus limiting our understanding of the causal conclusions. Therefore, we aimed to assess the relationship between CRP and periodontitis by using the two sample Mendelian randomization (MR) method.
Methods We analyzed the data from two genome-wide association studies (GWAS) of European ancestry, including CRP (204,402 individuals) and periodontitis (17353 cases and 28210 controls). We primarily used inverse variance weighted (IVW) to assess the causal effects. Pleiotropy was determined by using MR-Egger regression. Heterogeneity was examined with Cochran’s Q test. The leave-one-out analysis tested the robustness of the results.
Results We obtained 54 SNPs as instrumental variables (IVs) for CRP, and these IVs had no significant horizontal pleiotropy, heterogeneity, or bias. MR analysis revealed no obvious causal effect between CRP and periodontitis (ORIVW=1.026, 95% CI 0.998–1.055, P=0.066; ORMR-Egge=1.026, 95% CI: 0.983-1.070, p = 0.242; ORweighted median=1.030, 95% CI: 0.991-1.070, p = 0.132).
Conclusions The MR analysis indicated that CRP could not increase the risk of periodontitis in people of European ancestry.
Cooperativity in regulation of membrane protein function: phenomenological analysis of the effects of pH and phospholipids.
Authors: De Palma Gerardo Zerbetto , Angelini Álvaro A Recoulat , Vitali Victoria , Flecha F. Luis González , ALLEVA KARINA 
Published: April 2023

Abstract
Interaction between membrane proteins and ligands is key to control a wide spectrum of cellular processes. These interactions can provide a cooperative-type regulation of protein function. A wide diversity of proteins, including enzymes, channels, transporters, and receptors show cooperative behavior. The variety of possible ligands is also huge and includes specific molecules or ions that bind to an also specific binding site. In this review, we focus on the interaction of membrane proteins with ligands that present many binding sites, such as protons or membrane phospholipids. The study of the interaction that protons or lipids have with membrane proteins does not always allow a clear and classic mechanistic modeling approach. In this regard we show that, like Hill´s pioneering work on hemoglobin regulation, phenomenological modeling constitutes a powerful tool to describe relevant features of these important systems.
Degrees of relations on canonically ordered natural numbers and integers
Authors: Bazhenov Nikolay , Kalociński Dariusz , Wrocławski Michał 
Published: April 2023

Abstract

We investigate the degree spectra of computable relations on canonically ordered natural numbers (ω,<) and integers (ζ,<). As for (ω,<), we provide several criteria that fix the degree spectrum of a computable relation to all c.e. or to all Δ2 degrees; this includes the complete characterization of the degree spectra of so-called computable block functions that have only finitely many types of blocks. Compared to [1], we obtain a more general solution to the problem regarding possible degree spectra on (ω,<), answering the question whether there are infinitely many such spectra. As for (ζ,<), we prove the following dichotomy result: given an arbitrary computable relation R on (ζ,<), its degree spectrum is either trivial or it contains all c.e. degrees. This result, and the proof techniques required to solve it, extend the analogous theorem for (ω,<) obtained in [2], and provide initial insight to Wright's question whether such a dichotomy holds on computable ill-founded linear orders. This article is an extended version of [1].
MSC Classification: 03C57