bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic assessment of long-read RNA-seq methods for transcript identification and quantification
Authors: Pardo-Palacios Francisco J. , Wang Dingjie , Reese Fairlie , Diekhans Mark , Carbonell-Sala Sílvia , Williams Brian , Loveland Jane E. , De María Maite , Adams Matthew S. , Balderrama-Gutierrez Gabriela , Behera Amit K. , Gonzalez Martinez Jose M. , Hunt Toby , Lagarde Julien , Liang Cindy E. , Li Haoran , Meade Marcus Jerryd , Moraga Amador David A. , Prjibelski Andrey D. , Birol Inanc , Bostan Hamed , Brooks Ashley M. , Çelik Muhammed Hasan , Chen Ying , Du Mei R. M. , Felton Colette , Göke Jonathan , Hafezqorani Saber , Herwig Ralf , Kawaji Hideya , Lee Joseph , Li Jian-Liang , Lienhard Matthias , Mikheenko Alla , Mulligan Dennis , Nip Ka Ming , Pertea Mihaela , Ritchie Matthew E. , Sim Andre D. , Tang Alison D. , Wan Yuk Kei , Wang Changqing , Wong Brandon Y. , Yang Chen , Barnes If , Berry Andrew E. , Capella-Gutierrez Salvador , Cousineau Alyssa , Dhillon Namrita , Fernandez-Gonzalez Jose M. , Ferrández-Peral Luis , Garcia-Reyero Natàlia , Götz Stefan , Hernández-Ferrer Carles , Kondratova Liudmyla , Liu Tianyuan , Martinez-Martin Alessandra , Menor Carlos , Mestre-Tomás Jorge , Mudge Jonathan M. , Panayotova Nedka G. , Paniagua Alejandro , Repchevsky Dmitry , Ren Xingjie , Rouchka Eric , Saint-John Brandon , Sapena Enrique , Sheynkman Leon , Smith Melissa Laird , Suner Marie-Marthe , Takahashi Hazuki , Youngworth Ingrid A. , Carninci Piero , Denslow Nancy D. , Guigó Roderic , Hunter Margaret E. , Maehr Rene , Shen Yin , Tilgner Hagen U. , Wold Barbara J. , Vollmers Christopher , Frankish Adam , Au Kin Fai , Sheynkman Gloria M. , Mortazavi Ali , Conesa Ana , Brooks Angela N. 
Published: June 2024

AbstractThe Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.
Field experiment on the effect of musical street performance/busking on public space perception as mediated by street audience experience
Authors: Ho Robbie , Szubielska Magdalena 
Published: June 2024

AbstractStreet performance or busking is common in public spaces. The literature highlights two psychological issues: the effect of street performance on public space perception and the complexity of the appreciation of street performance, regarded as street audience experience (SAE). The present study aims at verifying the effect of street performance on public space perception, while examining SAE as a mediator of this effect. We conducted a between-subjects field experiment (a quasi-experiment; N = 292) in Hong Kong. Participants assessed a public space without (control) or with (experimental) musical busking on essentialism, anti-essentialism, sonic restorativeness, and overall liking. In the experimental condition, unengaged passersby and engaged audience further evaluated SAE factors of emotion, intellect, novelty, place, interaction, and technique, and outcomes of overall satisfaction and donation worth. The public space with busking was perceived as significantly more sonically restorative. Engaged audience perceived the space as significantly more essentialist, anti-essentialist, sonically restorative, and likeable. Engaged audience also experienced more positive SAE and outcome variables. SAE fully mediated the effects of street performance on public space perception and outcome variables, respectively. These findings support the positive impact of street performance, which may enhance city inhabitants’ well-being.
Systemic inflammation, oxidative damage and neurocognition predict telomere length in a transdiagnostic sample stratified by global DNA methylation levels
Authors: Sánchez-Ortí Joan Vicent , Correa-Ghisays Patricia , Balanzá-Martínez Vicent , Macías Saint-Gerons Diego , Berenguer-Pascual Ester , Romá-Mateo Carlos , Victor Víctor M. , Forés-Martos Jaume , San-Martin Constanza , Selva-Vera Gabriel , Tabarés-Seisdedos Rafael 
Published: June 2024

AbstractEpigenetic mechanisms contribute to the maintenance of both type 2 diabetes mellitus (T2DM) and psychiatric disorders. Emerging evidence suggests that molecular pathways and neurocognitive performance regulate epigenetic dynamics in these disorders. The current combined and transdiagnostic study investigated whether inflammatory, oxidative stress, adhesion molecule, neurocognitive and functional performance are significant predictors of telomere dynamics in a sample stratified by global DNA methylation levels. Peripheral blood inflammation, oxidative stress and adhesion molecule biomarkers and neurocognitive function were assessed twice over a 1-year period in 80 individuals, including 16 with schizophrenia (SZ), 16 with bipolar disorder (BD), 16 with major depressive disorder (MDD), 15 with T2DM, and 17 healthy controls (HCs). Leukocyte telomere length (LTL) was measured by qRT-PCR using deoxyribonucleic acid (DNA) extracted from peripheral blood samples. A posteriori, individuals were classified based on their global methylation score (GMS) at baseline into two groups: the below-average methylation (BM) and above-average methylation (AM) groups. Hierarchical and k-means clustering methods, mixed one-way analysis of variance and linear regression analyses were performed. Overall, the BM group showed a significantly higher leukocyte telomere length (LTL) than the AM group at both time points (p = 0.02; η2p = 0.06). Moreover, the BM group had significantly lower levels of tumor necrosis factor alpha (TNF-α) (p = 0.03; η2p = 0.06) and C-reactive protein (CRP) (p = 0.03; η2p = 0.06) than the AM group at the 1-year follow-up. Across all participants, the regression models showed that oxidative stress (reactive oxygen species [ROS]) (p = 0.04) and global cognitive score [GCS] (p = 0.02) were significantly negatively associated with LTL, whereas inflammatory (TNF-α) (p = 0.04), adhesion molecule biomarkers (inter cellular adhesion molecule [ICAM]) (p = 0.009), and intelligence quotient [IQ] (p = 0.03) were significantly positively associated with LTL. Moreover, the model predictive power was increased when tested in both groups separately, explaining 15.8% and 28.1% of the LTL variance at the 1-year follow-up for the AM and BM groups, respectively. Heterogeneous DNA methylation in individuals with T2DM and severe mental disorders seems to support the hypothesis that epigenetic dysregulation occurs in a transdiagnostic manner. Our results may help to elucidate the interplay between epigenetics, molecular processes and neurocognitive function in these disorders. DNA methylation and LTL are potential therapeutic targets for transdiagnostic interventions to decrease the risk of comorbidities.
In silico design of peptide inhibitors for Dengue virus to treat Dengue virus-associated infections
Authors: Ajmal Amar , Shahab Muhammad , Waqas Muhammad , Zheng Guojun , Zulfat Maryam , Bin Jardan Yousef A. , Wondmie Gezahign Fentahun , Bourhia Mohammed , Ali Ijaz 
Published: June 2024

AbstractDengue virus is a single positive-strand RNA virus that is composed of three structural proteins including capsid, envelope, and precursor membrane while seven non-structural proteins (NS1, NS2A, NS2B, NS3A, NS3B, NS4, and NS5). Dengue is a viral infection caused by the dengue virus (DENV). DENV infections are asymptomatic or produce only mild illness. However, DENV can occasionally cause more severe cases and even death. There is no specific treatment for dengue virus infections. Therapeutic peptides have several important advantages over proteins or antibodies: they are small in size, easy to synthesize, and have the ability to penetrate the cell membranes. They also have high activity, specificity, affinity, and less toxicity. Based on the known peptide inhibitor, the current study designs peptide inhibitors for dengue virus envelope protein using an alanine and residue scanning technique. By replacing I21 with Q21, L14 with H14, and V28 with K28, the binding affinity of the peptide inhibitors was increased. The newly designed peptide inhibitors with single residue mutation improved the binding affinity of the peptide inhibitors. The inhibitory capability of the new promising peptide inhibitors was further confirmed by the utilization of MD simulation and free binding energy calculations. The molecular dynamics simulation demonstrated that the newly engineered peptide inhibitors exhibited greater stability compared to the wild-type peptide inhibitors. According to the binding free energies MM(GB)SA of these developed peptides, the first peptide inhibitor was the most effective against the dengue virus envelope protein. All peptide derivatives had higher binding affinities for the envelope protein and have the potential to treat dengue virus-associated infections. In this study, new peptide inhibitors were developed for the dengue virus envelope protein based on the already reported peptide inhibitor.
Cell-specific models of hiPSC-CMs developed by the gradient-based parameter optimization method fitting two different action potential waveforms
Authors: Zhang Yixin , Toyoda Futoshi , Himeno Yukiko , Noma Akinori , Amano Akira 
Published: June 2024

AbstractParameter optimization (PO) methods to determine the ionic current composition of experimental cardiac action potential (AP) waveform have been developed using a computer model of cardiac membrane excitation. However, it was suggested that fitting a single AP record in the PO method was not always successful in providing a unique answer because of a shortage of information. We found that the PO method worked perfectly if the PO method was applied to a pair of a control AP and a model output AP in which a single ionic current out of six current species, such as IKr, ICaL, INa, IKs, IKur or IbNSC was partially blocked in silico. When the target was replaced by a pair of experimental control and IKr-blocked records of APs generated spontaneously in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), the simultaneous fitting of the two waveforms by the PO method was hampered to some extent by the irregular slow fluctuations in the Vm recording and/or sporadic alteration in AP configurations in the hiPSC-CMs. This technical problem was largely removed by selecting stable segments of the records for the PO method. Moreover, the PO method was made fail-proof by running iteratively in identifying the optimized parameter set to reconstruct both the control and the IKr-blocked AP waveforms. In the lead potential analysis, the quantitative ionic mechanisms deduced from the optimized parameter set were totally consistent with the qualitative view of ionic mechanisms of AP so far described in physiological literature.
Leukocyte filtration and leukocyte modulation therapy during extracorporeal cardiopulmonary resuscitation in a porcine model of prolonged cardiac arrest
Authors: VanZalen Jensyn J. , Nakashima Takahiro , Phillips Annie , Hill Joseph E. , Westover Angela J. , Lou Liandi , Liao Jinhui , Mergos Joshua , Fogo Garrett , Sanderson Thomas H. , Stacey William C. , Tiba Mohamad Hakam , Humes David H. , Bartlett Robert H. , Rojas-Peña Alvaro , Neumar Robert W. 
Published: June 2024

AbstractExtracorporeal cardiopulmonary resuscitation (ECPR) is emerging as a feasible and effective rescue strategy for prolonged cardiac arrest (CA). However, prolonged total body ischemia and reperfusion can cause microvascular occlusion that prevents organ reperfusion and recovery of function. One hypothesized mechanism of microvascular “no-reflow” is leukocyte adhesion and formation of neutrophil extracellular traps. In this study we tested the hypothesis that a leukocyte filter (LF) or leukocyte modulation device (L-MOD) could reduce NETosis and improve recovery of heart and brain function in a swine model of prolonged cardiac arrest treated with ECPR. Thirty-six swine (45.5 ± 2.5 kg, evenly distributed sex) underwent 8 min of untreated ventricular fibrillation CA followed by 30 min of mechanical CPR with subsequent 8 h of ECPR. Two females were later excluded from analysis due to CPR complications. Swine were randomized to standard care (Control group), LF, or L-MOD at the onset of CPR. NET formation was quantified by serum dsDNA and citrullinated histone as well as immunofluorescence staining of the heart and brain for citrullinated histone in the microvasculature. Primary outcomes included recovery of cardiac function based on cardiac resuscitability score (CRS) and recovery of neurologic function based on the somatosensory evoked potential (SSEP) N20 cortical response. In this model of prolonged CA treated with ECPR we observed significant increases in serum biomarkers of NETosis and immunohistochemical evidence of microvascular NET formation in the heart and brain that were not reduced by LF or L-MOD therapy. Correspondingly, there were no significant differences in CRS and SSEP recovery between Control, LF, and L-MOD groups 8 h after ECPR onset (CRS = 3.1 ± 2.7, 3.7 ± 2.6, and 2.6 ± 2.6 respectively; p = 0.606; and SSEP = 27.9 ± 13.0%, 36.7 ± 10.5%, and 31.2 ± 9.8% respectively, p = 0.194). In this model of prolonged CA treated with ECPR, the use of LF or L-MOD therapy during ECPR did not reduce microvascular NETosis or improve recovery of myocardial or brain function. The causal relationship between microvascular NETosis, no-reflow, and recovery of organ function after prolonged cardiac arrest treated with ECPR requires further investigation.
Oxidative modification of miR-30c promotes cardiac fibroblast proliferation via CDKN2C mismatch
Authors: Chang Wenguang , Xiao Dandan , Fang Xinyu , Wang Jianxun 
Published: June 2024

AbstractThe response of cardiac fibroblast proliferation to detrimental stimuli is one of the main pathological factors causing heart remodeling. Reactive oxygen species (ROS) mediate the proliferation of cardiac fibroblasts. However, the exact molecular mechanism remains unclear. In vivo, we examined the oxidative modification of miRNAs with miRNA immunoprecipitation with O8G in animal models of cardiac fibrosis induced by Ang II injection or ischemia‒reperfusion injury. Furthermore, in vitro, we constructed oxidation-modified miR-30c and investigated its effects on the proliferation of cardiac fibroblasts. Additionally, luciferase reporter assays were used to identify the target of oxidized miR-30c. We found that miR-30c oxidation was modified by Ang II and PDGF treatment and mediated by excess ROS. We demonstrated that oxidative modification of G to O8G occurred at positions 4 and 5 of the 5′ end of miR-30c (4,5-oxo-miR-30c), and this modification promoted cardiac fibroblast proliferation. Furthermore, CDKN2C is a negative regulator of cardiac fibroblast proliferation. 4,5-oxo-miR-30c misrecognizes CDKN2C mRNA, resulting in a reduction in protein expression. Oxidized miR-30c promotes cardiac fibroblast proliferation by mismatch mRNA of CDKN2C.
Effects of (S)-3,4-DCPG, an mGlu8 receptor agonist, on hippocampal long-term potentiation at perforant pathway-dentate gyrus synapses in prenatal valproic acid-induced rat model of autism
Authors: Gholipour Parsa , Ebrahimi Zahra , Mohammadkhani Reihaneh , Ghahremani Reza , Salehi Iraj , Sarihi Abdolrahman , Komaki Alireza , Karimi Seyed Asaad 
Published: June 2024

AbstractAutism spectrum disorder (ASD) is a pervasive neurodevelopmental condition characterized by social interaction deficits, communication impairments, repetitive behaviors, and sensory sensitivities. While the etiology of ASD is multifaceted, abnormalities in glutamatergic neurotransmission and synaptic plasticity have been implicated. This study investigated the role of metabotropic glutamate receptor 8 (mGlu8) in modulating long-term potentiation (LTP) in a rat model of ASD induced by prenatal valproic acid (VPA) exposure. To induce an animal model with autism-like characteristics, pregnant rats received an intraperitoneal injection of 500 mg/kg of sodium valproate (NaVPA) on embryonic day 12.5. High-frequency stimulation was applied to the perforant path-dentate gyrus (PP-DG) synapse to induce LTP, while the mGlu8 receptor agonist (S)-3,4-dicarboxyphenylglycine (DCPG) was administered into the DG. The results revealed that VPA-exposed rats exhibited reduced LTP compared to controls. DCPG had contrasting effects, inhibiting LTP in controls and enhancing it in VPA-exposed rats. Moreover, reduced social novelty preference index (SNPI) in VPA-exposed rats was reversed by intra-DG administration of S-3,4-DCPG. In conclusion, our study advances our understanding of the complex relationship between glutamatergic neurotransmission, synaptic plasticity, and VPA-induced autism model. The findings suggest that mGlu8 receptor dysfunction plays a role in the impaired synaptic plasticity seen in ASD.
Potential therapeutic targets of gastric cancer explored under endogenous network modeling of clinical data
Authors: Zhang Xile , Chen Yong-Cong , Yao Mengchao , Xiong Ruiqi , Liu Bingya , Zhu Xiaomei , Ao Ping 
Published: June 2024

AbstractImprovement in the survival rate of gastric cancer, a prevalent global malignancy and the leading cause of cancer-related mortality calls for more avenues in molecular therapy. This work aims to comprehend drug resistance and explore multiple-drug combinations for enhanced therapeutic treatment. An endogenous network modeling clinic data with core gastric cancer molecules, functional modules, and pathways is constructed, which is then transformed into dynamics equations for in-silicon studies. Principal component analysis, hierarchical clustering, and K-means clustering are utilized to map the attractor domains of the stochastic model to the normal and pathological phenotypes identified from the clinical data. The analyses demonstrate gastric cancer as a cluster of stable states emerging within the stochastic dynamics and elucidate the cause of resistance to anti-VEGF monotherapy in cancer treatment as the limitation of the single pathway in preventing cancer progression. The feasibility of multiple objectives of therapy targeting specified molecules and/or pathways is explored. This study verifies the rationality of the platform of endogenous network modeling, which contributes to the development of cross-functional multi-target combinations in clinical trials.
Attention spotlight in V1-based cortico-cortical interactions in human visual hierarchy
Authors: Zhang Yanyu , Zhang Xilin , Lu Xincheng , Chen Nihong 
Published: June 2024

AbstractAttention is often viewed as a mental spotlight, which can be scaled like a zoom lens at specific spatial locations and features a center-surround gradient. Here, we demonstrate a neural signature of attention spotlight in signal transmission along the visual hierarchy. fMRI background connectivity analysis was performed between retinotopic V1 and downstream areas to characterize the spatial distribution of inter-areal interaction under two attentional states. We found that, compared to diffused attention, focal attention sharpened the spatial gradient in the strength of the background connectivity. Dynamic causal modeling analysis further revealed the effect of attention in both the feedback and feedforward connectivity between V1 and extrastriate cortex. In a context which induced a strong effect of crowding, the effect of attention in the background connectivity profile diminished. Our findings reveal a context-dependent attention prioritization in information transmission via modulating the recurrent processing across the early stages in human visual cortex.
Artificial intelligence-based radiographic extent analysis to predict tuberculosis treatment outcomes: a multicenter cohort study
Authors: Kim Hyung-Jun , Kwak Nakwon , Yoon Soon Ho , Park Nanhee , Kim Young Ran , Lee Jae Ho , Lee Ji Yeon , Park Youngmok , Kang Young Ae , Kim Saerom , Mok Jeongha , Kim Joong-Yub , Jeon Doosoo , Lee Jung-Kyu , Yim Jae-Joon 
Published: June 2024

AbstractPredicting outcomes in pulmonary tuberculosis is challenging despite effective treatments. This study aimed to identify factors influencing treatment success and culture conversion, focusing on artificial intelligence (AI)-based chest X-ray analysis and Xpert MTB/RIF assay cycle threshold (Ct) values. In this retrospective study across six South Korean referral centers (January 1 to December 31, 2019), we included adults with rifampicin-susceptible pulmonary tuberculosis confirmed by Xpert assay from sputum samples. We analyzed patient characteristics, AI-based tuberculosis extent scores from chest X-rays, and Xpert Ct values. Of 230 patients, 206 (89.6%) achieved treatment success. The median age was 61 years, predominantly male (76.1%). AI-based radiographic tuberculosis extent scores (median 7.5) significantly correlated with treatment success (odds ratio [OR] 0.938, 95% confidence interval [CI] 0.895–0.983) and culture conversion at 8 weeks (liquid medium: OR 0.911, 95% CI 0.853–0.973; solid medium: OR 0.910, 95% CI 0.850–0.973). Sputum smear positivity was 49.6%, with a median Ct of 26.2. However, Ct values did not significantly correlate with major treatment outcomes. AI-based radiographic scoring at diagnosis is a significant predictor of treatment success and culture conversion in pulmonary tuberculosis, underscoring its potential in personalized patient management.