bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evolution of a plant sex chromosome driven by expanding pericentromeric recombination suppression
Authors: Filatov Dmitry A. 
Published: January 2024

AbstractRecombination suppression around sex-determining gene(s) is a key step in evolution of sex chromosomes, but it is not well understood how it evolves. Recently evolved sex-linked regions offer an opportunity to understand the mechanisms of recombination cessation. This paper analyses such a region on Silene latifolia (Caryophyllaceae) sex chromosomes, where recombination was suppressed in the last 120 thousand years ("stratum 3"). Locating the boundaries of the stratum 3 in S. latifolia genome sequence revealed that this region is far larger than assumed previously—it is about 14 Mb long and includes 202 annotated genes. A gradient of X:Y divergence detected in the stratum 3, with divergence increasing proximally, indicates gradual recombination cessation, possibly caused by expansion of pericentromeric recombination suppression (PRS) into the pseudoautosomal region. Expansion of PRS was also the likely cause for the formation of the older stratum 2 on S. latifolia sex chromosomes. The role of PRS in sex chromosome evolution has been underappreciated, but it may be a significant factor, especially in the species with large chromosomes where PRS is often extensive.
Baseline imaging characteristics and early structural changes in macula on rhegmatogenous retinal detachment
Authors: Quarta Alberto , Gironi Matteo , Ruggeri Maria Ludovica , Aharrh-Gnama Agbeanda , Porreca Annamaria , D’Aloisio Rossella , Toto Lisa , Di Nicola Marta , Mastropasqua Rodolfo 
Published: January 2024

AbstractAnimal models have demonstrated that structural changes affect the macula during peripheral rhegmatogenous retinal detachment. This study aimed to assess photoreceptors, retinal and choriocapillaris perfusion in non-macula involving rhegmatogenous retinal detachment by analyzing en-face images from structural OCTA segmented at the ellipsoid zone (EZ) level, calculating (1) “normalized” reflectivity as a surrogate biomarker of photoreceptor damage (2) perfusion density (PD), vessel length density (VLD) and vessel diameter index (VDI) of superficial capillary plexus (SCP) and deep capillary plexus (DCP) (3) perfusion density of choriocapillaris (PDCC). Twenty-one eyes affected by macula-on rhegmatogenous retinal detachment (RRD) were enrolled at the University “G. d’Annunzio”, Chieti-Pescara. The fellow unaffected eye was used as control. The mean age at the onset of RRD was 60.09 ± 10.22 (range 34–83). Compared with fellow eyes, we found lower EZ “normalized” reflectivity in macula-on (0.42 ± 0.15 in fellow eyes and 0.31 ± 0.09 in macula on p = 0.004). The affected eye was also characterized by impaired perfusion in SCP (17.26 ± 3.34% in macula on and 20.56 ± 3.62% in the fellow eye p = 0.004) and CC (50.21 ± 6.20% in macula on the eye and 57.43 ± 6.20% in the fellow eye p = 0.004). Macula-on rhegmatogenous retinal detachment has subclinical changes in photoreceptors, SCP, and CC. Future longitudinal studies should evaluate if early changes could impact post-operative macular function.
Prediction of sentinel lymph node metastasis in breast cancer patients based on preoperative features: a deep machine learning approach
Authors: Shahriarirad Reza , Meshkati Yazd Seyed Mostafa , Fathian Ramin , Fallahi Mohammadmehdi , Ghadiani Zahra , Nafissi Nahid 
Published: January 2024

AbstractSentinel lymph node (SLN) biopsy is the standard surgical approach to detect lymph node metastasis in breast cancer. Machine learning is a novel tool that provides better accuracy for predicting positive SLN involvement in breast cancer patients. This study obtained data from 2890 surgical cases of breast cancer patients from two referral hospitals in Iran from 2000 to 2021. Patients whose SLN involvement status was identified were included in our study. The dataset consisted of preoperative features, including patient features, gestational factors, laboratory data, and tumoral features. In this study, TabNet, an end-to-end deep learning model, was proposed to predict SLN involvement in breast cancer patients. We compared the accuracy of our model with results from logistic regression analysis. A total of 1832 patients with an average age of 51 ± 12 years were included in our study, of which 697 (25.5%) had SLN involvement. On average, the TabNet model achieved an accuracy of 75%, precision of 81%, specificity of 70%, sensitivity of 87%, and AUC of 0.74, while the logistic model demonstrated an accuracy of 70%, precision of 73%, specificity of 65%, sensitivity of 79%, F1 score of 73%, and AUC of 0.70 in predicting the SLN involvement in patients. Vascular invasion, tumor size, core needle biopsy pathology, age, and FH had the most contributions to the TabNet model. The TabNet model outperformed the logistic regression model in all metrics, indicating that it is more effective in predicting SLN involvement in breast cancer patients based on preoperative data.
Investigating robust associations between functional connectivity based on graph theory and general intelligence
Authors: Metzen Dorothea , Stammen Christina , Fraenz Christoph , Schlüter Caroline , Johnson Wendy , Güntürkün Onur , DeYoung Colin G. , Genç Erhan 
Published: January 2024

AbstractPrevious research investigating relations between general intelligence and graph-theoretical properties of the brain’s intrinsic functional network has yielded contradictory results. A promising approach to tackle such mixed findings is multi-center analysis. For this study, we analyzed data from four independent data sets (total N > 2000) to identify robust associations amongst samples between g factor scores and global as well as node-specific graph metrics. On the global level, g showed no significant associations with global efficiency or small-world propensity in any sample, but significant positive associations with global clustering coefficient in two samples. On the node-specific level, elastic-net regressions for nodal efficiency and local clustering yielded no brain areas that exhibited consistent associations amongst data sets. Using the areas identified via elastic-net regression in one sample to predict g in other samples was not successful for local clustering and only led to one significant, one-way prediction across data sets for nodal efficiency. Thus, using conventional graph theoretical measures based on resting-state imaging did not result in replicable associations between functional connectivity and general intelligence.
Prognostic significance of pretreatment albumin–bilirubin (ALBI) grade and platelet–albumin–bilirubin (PALBI) grade in patients with small cell lung cancer
Authors: Kut Engin , Menekse Serkan 
Published: January 2024

AbstractSmall cell lung cancer (SCLC) is a common cancer among the world’s lung cancers. Despite advances in diagnosis and treatment, the prognosis is still poor. There is no effective biomarker other than stage in daily practice. However, in daily practice, patients may have different features and survival times even though they have the same stage. Previously, albumin–bilirubin (ALBI) grade, platelet–albumin–bilirubin (PALBI) grade were used to determine the prognosis of acute-chronic liver failure and acute upper gastrointestinal bleeding in liver cirrhosis. In subsequent studies, they were found to be associated with prognosis in hepatocellular carcinoma (HCC) and other solid cancers. However, the prognostic relationship between ALBI grade, PALBI grade, and SCLC is unknown. Therefore, we conducted this study to examine the relationship between ALBI grade and PALBI grade and prognosis in SCLC patients. Data of 138 patients with advanced SCLC at diagnosis between 2009 and 2020 were analyzed retrospectively. The results of the multivariate analysis were as follows: ALBI grade 1 vs 2, hazard ratio (HR) = 1.608, p = 0.002 for OS and HR = 1.575, p = 0.002 for PFS; ALBI grade 1 vs 3, HR = 2.035, p < 0.001 for OS and HR = 2.675, p < 0.001 for PFS; PALBI grade 1 vs 2, HR = 1.302, p = 0.006 for OS and HR = 1.674, p = 0.002 for PFS; and PALBI grade 1 vs 3, HR = 1.725, p < 0.001 for OS and HR = 2.675, p < 0.001 for PFS. In conclusion, the ALBI and PALBI grades were determined to be associated with the prognosis of SCLC, and they can be used as easy, inexpensive, and practical markers in determining the follow-up treatment and prognosis of SCLC patients.
Resolving acne with optimized adapalene microspongeal gel, in vivo and clinical evaluations
Authors: Yehia Rania M. , Teaima Mahmoud H. , Ragaie Maha H. , Elmazar Mohamed M. , Attia Dalia A. , El-Nabarawi Mohamed A. 
Published: January 2024

AbstractIn our pursuit of enhancing acne treatment while minimizing side effects, we developed tailored Adapalene microsponges (MS) optimized using a Box–Behnken design 33. The independent variables, Eudragit RS100 percentage in the polymer mixture, organic phase volume, and drug to polymer percentage, were explored. The optimized formulation exhibited remarkable characteristics, with a 98.3% ± 1.6 production yield, 97.3% ± 1.64 entrapment efficiency, and a particle size of 31.8 ± 1.1 µm. Notably, it achieved a 24 h cumulative drug release of 75.1% ± 1.4. To delve deeper into its efficacy, we evaluated the optimized microspongeal-gel in vitro, in vivo, and clinically. It demonstrated impressive retention in the pilosebaceous unit, a target for acne treatment. Comparative studies between our optimized Adapalene microspongeal gel and marketed Adapalene revealed superior performance. In vivo studies on Propionibacterium acnes-infected mice ears showed a remarkable 97% reduction in ear thickness, accompanied by a significant decrease in inflammatory signs and NF-κB levels, as confirmed by histopathological and histochemical examination. Moreover, in preliminary clinical evaluation, it demonstrated outstanding effectiveness in reducing comedonal lesions while causing fewer irritations. This not only indicates its potential for clinical application but also underscores its ability to enhance patient satisfaction, paving the way for future commercialization.
Interactive effects of long-term management of crop residue and phosphorus fertilization on wheat productivity and soil health in the rice–wheat
Authors: Gupta Rajeev Kumar , Sraw Paramjit Kaur , Kang Jasjit Singh , Kaur Jagroop , Sharma Vivek , Pathania Neemisha , Kalia Anu , Al-Ansari Nadhir , Alataway Abed , Dewidar Ahmed Z. , Mattar Mohamed A. 
Published: January 2024

AbstractIn the context of degradation of soil health, environmental pollution, and yield stagnation in the rice–wheat system in the Indo-Gangetic Plains of South Asia, an experiment was established in split plot design to assess the long-term effect of crop residue management on productivity and phosphorus requirement of wheat in rice–wheat system. The experiment comprised of six crop residue management practices as the main treatment factor with three levels (0, 30 and 60 kg P2O5 ha–1) of phosphorus fertilizer as sub-treatments. Significant improvement in soil aggregation, bulk density, and infiltration rate was observed under residue management (retention/incorporation) treatments compared to residue removal or residue burning. Soil organic carbon (SOC), available nutrient content (N, P, and K), microbial count, and enzyme activities were also significantly higher in conservation tillage and residue-treated plots than without residue/burning treatments. The residue derived from both crops when was either retained/incorporated improved the soil organic carbon (0.80%) and resulted in a significant increase in SOC (73.9%) in the topsoil layer as compared to the conventional practice. The mean effect studies revealed that crop residue management practices and phosphorus levels significantly influenced wheat yield attributes and productivity. The higher grain yield of wheat was recorded in two treatments, i.e. the basal application of 60 kg P2O5 ha–1 without residue incorporation and the other with half the P-fertilizer (30 kg P2O5 ha–1) with rice residue only. The grain yield of wheat where the rice and wheat residue were either retained/incorporated without phosphorus application was at par with 30 and 60 kg P2O5ha–1. Phosphorus levels also significantly affected wheat productivity and available P content in the soil. Therefore, results suggested that crop residue retention following the conservation tillage approach improved the yield of wheat cultivated in the rice–wheat cropping system.
Early detection of liver injuries by the Serum enhanced binding test sensitive to albumin post-transcriptional modifications
Authors: El Balkhi Souleiman , Rahali Mohamad Ali , Lakis Roy , Sauvage François Ludovic , Martin Marving , Janaszkiewicz Angelika , Lawson Roland , Goncalves Ruben , Carrier Paul , Loustaud-Ratti Veronique , Guyot Anne , Marquet Pierre , Di Meo Florent , Saint-Marcoux Franck 
Published: January 2024

AbstractEarly and sensitive biomarkers of liver dysfunction and drug-induced liver injury (DILI) are still needed, both for patient care and drug development. We developed the Serum Enhanced Binding (SEB) test to reveal post-transcriptional modifications (PTMs) of human serum albumin resulting from hepatocyte dysfunctions and further evaluated its performance in an animal model. The SEB test consists in spiking serum ex-vivo with ligands having specific binding sites related to the most relevant albumin PTMs and measuring their unbound fraction. To explore the hypothesis that albumin PTMs occur early during liver injury and can also be detected by the SEB test, we induced hepatotoxicity in male albino Wistar rats by administering high daily doses of ethanol and CCl4 over several days. Blood was collected for characterization and quantification of albumin isoforms by high-resolution mass spectrometry, for classical biochemical analyses as well as to apply the SEB test. In the exposed rats, the appearance of albumin isoforms paralleled the positivity of the SEB test ligands and histological injuries. These were observed as early as D3 in the Ethanol and CCl4 groups, whereas the classical liver tests (ALT, AST, PAL) significantly increased only at D7. The behavior of several ligands was supported by structural and molecular simulation analysis. The SEB test and albumin isoforms revealed hepatocyte damage early, before the current biochemical biomarkers. The SEB test should be easier to implement in the clinics than albumin isoform profiling.
An intelligent LinkNet-34 model with EfficientNetB7 encoder for semantic segmentation of brain tumor
Authors: Sulaiman Adel , Anand Vatsala , Gupta Sheifali , Al Reshan Mana Saleh , Alshahrani Hani , Shaikh Asadullah , Elmagzoub M. A. 
Published: January 2024

AbstractA brain tumor is an unnatural expansion of brain cells that can’t be stopped, making it one of the deadliest diseases of the nervous system. The brain tumor segmentation for its earlier diagnosis is a difficult task in the field of medical image analysis. Earlier, segmenting brain tumors was done manually by radiologists but that requires a lot of time and effort. Inspite of this, in the manual segmentation there was possibility of making mistakes due to human intervention. It has been proved that deep learning models can outperform human experts for the diagnosis of brain tumor in MRI images. These algorithms employ a huge number of MRI scans to learn the difficult patterns of brain tumors to segment them automatically and accurately. Here, an encoder-decoder based architecture with deep convolutional neural network is proposed for semantic segmentation of brain tumor in MRI images. The proposed method focuses on the image downsampling in the encoder part. For this, an intelligent LinkNet-34 model with EfficientNetB7 encoder based semantic segmentation model is proposed. The performance of LinkNet-34 model is compared with other three models namely FPN, U-Net, and PSPNet. Further, the performance of EfficientNetB7 used as encoder in LinkNet-34 model has been compared with three encoders namely ResNet34, MobileNet_V2, and ResNet50. After that, the proposed model is optimized using three different optimizers such as RMSProp, Adamax and Adam. The LinkNet-34 model has outperformed with EfficientNetB7 encoder using Adamax optimizer with the value of jaccard index as 0.89 and dice coefficient as 0.915.
Modeling of antibody responses to COVID-19 vaccination in patients with rheumatoid arthritis
Authors: Kim Yun Kyu , Choi Yunhee , Jung Ji In , Kim Ju Yeon , Kim Mi Hyeon , Curtis Jeffrey , Lee Eun Bong 
Published: January 2024

AbstractTo construct a model of the antibody response to COVID-19 vaccination in patients with rheumatoid arthritis (RA), and to identify clinical factors affecting the antibody response. A total of 779 serum samples were obtained from 550 COVID-19-naïve RA patients who were vaccinated against COVID-19. Antibody titers for the receptor binding domain (anti-RBD) and nucleocapsid (anti-N) were measured. The time from vaccination, and the log-transformed anti-RBD titer, were modeled using a fractional polynomial method. Clinical factors affecting antibody responses were analyzed by a regression model using generalized estimating equation. The anti-RBD titer peaked at about 2 weeks post-vaccination and decreased exponentially to 36.5% of the peak value after 2 months. Compared with the first vaccination, the 3rd or 4th vaccinations shifted the peaks of anti-RBD antibody response curves significantly upward (by 28-fold [4–195] and 32-fold [4–234], respectively). However, there was no significant shift in the peak from the 3rd vaccination to the 4th vaccination (p = 0.64). Multivariable analysis showed that sulfasalazine increased the vaccine response (by 1.49-fold [1.13–1.97]), but abatacept or JAK inhibitor decreased the vaccine response (by 0.13-fold [0.04–0.43] and 0.44-fold [0.26–0.74], respectively). Age was associated with lower ln [anti-RBD] values (coefficient: − 0.03 [− 0.04 to − 0.02]). In conclusion, the anti-RBD response of RA patients peaked at 2 weeks after COVID-19 vaccination, and then decreased exponentially, with the maximum peak increase observed after the 3rd vaccination. The antibody response was affected by age and the medications used to treat RA.
Enhanced convergence in p-bit based simulated annealing with partial deactivation for large-scale combinatorial optimization problems
Authors: Onizawa Naoya , Hanyu Takahiro 
Published: January 2024

AbstractThis article critically investigates the limitations of the simulated annealing algorithm using probabilistic bits (pSA) in solving large-scale combinatorial optimization problems. The study begins with an in-depth analysis of the pSA process, focusing on the issues resulting from unexpected oscillations among p-bits. These oscillations hinder the energy reduction of the Ising model and thus obstruct the successful execution of pSA in complex tasks. Through detailed simulations, we unravel the root cause of this energy stagnation, identifying the feedback mechanism inherent to the pSA operation as the primary contributor to these disruptive oscillations. To address this challenge, we propose two novel algorithms, time average pSA (TApSA) and stalled pSA (SpSA). These algorithms are designed based on partial deactivation of p-bits and are thoroughly tested using Python simulations on maximum cut benchmarks that are typical combinatorial optimization problems. On the 16 benchmarks from 800 to 5000 nodes, the proposed methods improve the normalized cut value from 0.8 to 98.4% on average in comparison with the conventional pSA.
Ab initio investigation of functionalization of titanium carbide Ti3C2 MXenes to tune the selective detection of lung cancer biomarkers
Authors: Alfalasi Wadha , Hussain Tanveer , Tit Nacir 
Published: January 2024

AbstractSelected volatile organic compounds (VOCs), such as benzene (C6H6), cyclohexane (C6H12), isoprene (C5H8), cyclopropanone (C3H4O), propanol (C3H8O), and butyraldehyde butanal (C4H8O), in exhaled human breath can act as indicators or biomarkers of lung cancer diseases. Detection of such VOCs with low density would pave the way for an early diagnosis of the disease and thus early treatment and cure. In the present investigation, the density-functional theory (DFT) is applied to study the detection of the mentioned VOCs on Ti3C2TX MXenes, saturated with the functional groups Tx = O, F, S, and OH. For selectivity, comparative sensing of other interfering air molecules from exhaled breath, such as O2, N2, CO2, and H2O is further undertaken. Three functionalization (Tx = O, F, and S) are found promising for the selective detection of the studied VOCs, in particular Ti3C2O2 MXenes has shown distinct sensor response toward the C5H8, C6H6, C6H12, and C3H4O. The relatively strong physisorption ($${E}_{ads}\cong -0.45 to-0.65 {\text{eV}}$$

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≅
-
0.45
t
o
-
0.65
eV

), triggered between VOC and MXene due to an enhancement of van der Waals interaction, is found responsible to affect the near Fermi level states, which in turn controls the conductivity and consequently the sensor response. Meanwhile, such intermediate-strength interactions remain moderate to yield small desorption recovery time (of order $$\tau \cong \mu {\text{s}}-{\text{ms}})$$

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≅
μ
s
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using visible light at room temperature. Thus, Ti3C2O2 MXenes are found promising candidate material for reusable biosensor for the early diagnosis of lung cancer diseases through the VOC detection in exhaled breath.
Light-enhanced catalytic activity of stable and large gold nanoparticles in homocoupling reactions
Authors: Hou Jian , Lartey Jemima A. , Lee Chang Yeon , Kim Jun-Hyun 
Published: January 2024

AbstractValidating the direct photocatalytic activity of colloidal plasmonic nanoparticles is challenging due to their limited stability and needed support materials that can often contribute to the chemical reactions. Stable gold nanoparticles (AuNPs) with tunable sizes are prepared across porous polymer particles without any chemical bonds where the resulting composite particles exhibit intense surface plasmon resonances (SPRs) in the visible region. These composite particles are then tested as photocatalysts under a broadband solar-simulated light source to examine the contribution degree of photothermal heating and SPR coming from the incorporated AuNPs in the C–C bond forming homocoupling reaction. Generally, the thermal and photothermal heating are the main driving force to increase the reactivity of relatively smaller AuNPs (~ 44 nm in diameter) with a narrower SPR band. However, the SPR-induced catalytic activity is much greater for the composite particles containing larger AuNPs (~ 87 nm in diameter) with a broader SPR. As the polymer particle matrix does not influence the catalytic activity (e.g., inducing charge delocalization and/or separation), the unique SPR role of the colloidal AuNPs in the catalytic reaction is assessable under light irradiation. This study experimentally demonstrates the possibility of evaluating the direct contribution of SPRs to photocatalytic chemical reactions.