bluuebunny/crossref_metadata_2025_split huggingface dataset:
Floristic diversity and its relationships with human land use varied regionally during the Holocene
Authors: Gordon Jonathan D. , Fagan Brennen , Milner Nicky , Thomas Chris D. 
Published: July 2024

AbstractHumans have caused growing levels of ecosystem and diversity changes at a global scale in recent centuries but longer-term diversity trends and how they are affected by human impacts are less well understood. Analysing data from 64,305 pollen samples from 1,763 pollen records revealed substantial community changes (turnover) and reductions in diversity (richness and evenness) in the first ~1,500 to ~4,000 years of the Holocene epoch (starting 11,700 years ago). Turnover and diversity generally increased thereafter, starting ~6,000 to ~1,000 years ago, although the timings, magnitudes and even directions of these changes varied among continents, biomes and sites. Here, modelling these diversity changes, we find that most metrics of biodiversity change are associated with human impacts (anthropogenic land-cover change estimates for the last 8,000 years), often positively but the magnitudes, timings and sometimes directions of associations differed among continents and biomes and sites also varied. Once-forested parts of the world tended to exhibit biodiversity increases while open areas tended to decline. These regionally specific relationships between humans and floristic diversity highlight that human–biodiversity relationships have generated positive diversity responses in some locations and negative responses in others, for over 8,000 years.
Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction
Authors: Yun Taedong , Cosentino Justin , Behsaz Babak , McCaw Zachary R. , Hill Davin , Luben Robert , Lai Dongbing , Bates John , Yang Howard , Schwantes-An Tae-Hwi , Zhou Yuchen , Khawaja Anthony P. , Carroll Andrew , Hobbs Brian D. , Cho Michael H. , McLean Cory Y. , Hormozdiari Farhad 
Published: July 2024

AbstractAlthough high-dimensional clinical data (HDCD) are increasingly available in biobank-scale datasets, their use for genetic discovery remains challenging. Here we introduce an unsupervised deep learning model, Representation Learning for Genetic Discovery on Low-Dimensional Embeddings (REGLE), for discovering associations between genetic variants and HDCD. REGLE leverages variational autoencoders to compute nonlinear disentangled embeddings of HDCD, which become the inputs to genome-wide association studies (GWAS). REGLE can uncover features not captured by existing expert-defined features and enables the creation of accurate disease-specific polygenic risk scores (PRSs) in datasets with very few labeled data. We apply REGLE to perform GWAS on respiratory and circulatory HDCD—spirograms measuring lung function and photoplethysmograms measuring blood volume changes. REGLE replicates known loci while identifying others not previously detected. REGLE are predictive of overall survival, and PRSs constructed from REGLE loci improve disease prediction across multiple biobanks. Overall, REGLE contain clinically relevant information beyond that captured by existing expert-defined features, leading to improved genetic discovery and disease prediction.
Proteomics shows that brain metastases of lung adenocarcinoma overexpress ribosomal proteins in response to gamma knife radiosurgery
Authors: Tong Luqing , Ye Ke , Chen Qun , Wang Xiaoxi , Hu Chi , Xu Qingsheng , Zhou Lihui , Zhan Renya , Tong Ying 
Published: July 2024

AbstractGamma knife radiosurgery (GKRS) is recommended as the first-line treatment for brain metastases of lung adenocarcinoma (LUAD) in many guidelines, but its specific mechanism is unclear. We aimed to study the changes in the proteome of brain metastases of LUAD in response to the hyperacute phase of GKRS and further explore the mechanism of differentially expressed proteins (DEPs). Cancer tissues were collected from a clinical trial for neoadjuvant stereotactic radiosurgery before surgical resection of large brain metastases (ChiCTR2000038995). Five brain metastasis tissues of LUAD were collected within 24 h after GKRS. Five brain metastasis tissues without radiotherapy were collected as control samples. Proteomics analysis showed that 163 proteins were upregulated and 25 proteins were downregulated. GO and KEGG enrichment analyses showed that the DEPs were closely related to ribosomes. Fifty-three of 70 ribosomal proteins were significantly overexpressed, while none of them were underexpressed. The risk score constructed from 7 upregulated ribosomal proteins (RPL4, RPS19, RPS16, RPLP0, RPS2, RPS26 and RPS25) was an independent risk factor for the survival time of LUAD patients. Overexpression of ribosomal proteins may represent a desperate response to lethal radiotherapy. We propose that targeted inhibition of these ribosomal proteins may enhance the efficacy of GKRS.
Genome wide identification of novel DNA methylation driven prognostic markers in colorectal cancer
Authors: Ma Yuhua , Li Yuanxin , Wen Zhahong , Lai Yining , Kamila Kulaixijiang , Gao Jing , Xu Wang-yang , Gong Chengxiang , Chen Feifan , Shi Liuqing , Zhang Yunzhi , Chen Hanzhang , Zhu Min 
Published: July 2024

AbstractColorectal cancer (CRC) stands as a major contributor to cancer-related fatalities within China. There is an urgent need to identify accurate biomarkers for recurrence predicting in CRC. Reduced representation bisulfite sequencing was used to perform a comparative analysis of methylation profiles in tissue samples from 30 recurrence to 30 non-recurrence patients with CRC. Least absolute shrinkage and selection operator method was performed to select the differential methylation regions (DMRs) and built a DNA methylation classifier for predicting recurrence. Based on the identified top DMRs, a methylation classifier was built and consisted of eight hypermethylated DMRs in CRC. The DNA methylation classifier showed high accuracy for predicting recurrence with an area under the receiver operator characteristic curve of 0.825 (95% CI 0.680–0.970). The Kaplan–Meier survival analysis demonstrated that CRC patients with high methylation risk score, evaluated by the DNA methylation classifier, had poorer survival than low risk score (Hazard Ratio 4.349; 95% CI 1.783–10.61, P = 0.002). And only CRC patients with low methylation risk score could acquire benefit from adjuvant therapy. The DNA methylation classifier has been proved as crucial biomarkers for predicting recurrence and exhibited promising prognostic value after curative surgery in patients with CRC.
Emotion regulation skills as a mediator of STEM teachers’ stress, well-being, and burnout
Authors: Farhi Moran , Rubinsten Orly 
Published: July 2024

AbstractThe teaching profession highly stressful, and teachers are often faced with challenging situations. This is particularly the case in STEM (science, technology, engineering, and math) education, which is a uniquely demanding and challenging field. This study examined the role of emotional regulation (ER) skills in STEM teachers’ stress, well-being, and burnout. The sample included 165 STEM teachers in middle and high schools who completed standard online questionnaires on ER, stress, well-being, and burnout. They were also asked to comment on three videos depicting authentic mathematical and pedagogical situations. The results indicated that contrary to popular belief, seniority was not linked with levels of stress, difficulties in ER, lower levels of well-being, or higher levels of burnout. A structural equation model and bootstrapping analysis showed teachers’ levels of stress predicted their well-being, and this link between stress and well-being was mediated by teachers’ level of difficulty in ER. The study highlights the importance of STEM teachers’ well-being and suggests the need to reduce stress and burnout by providing tools for teachers to regulate their emotions in the classroom.
Domestication and exposure to human social stimuli are not sufficient to trigger attachment to humans: a companion pig-dog comparative study
Authors: Gábor Anna , Pérez Fraga Paula , Gácsi Márta , Gerencsér Linda , Andics Attila 
Published: July 2024

AbstractDogs exhibit human-analogue attachment to their owners, with similar function and mechanisms to that of infant-mother bond, but its origin is unclear. Comparative studies on socialised wolves and dogs emphasise genetic influence in dogs' preparedness for attachment to humans. We aimed to reveal if this genetic effect stems from general domestication or artificial selection that increased dogs' dependence on humans. We assessed and compared behavioural patterns of young companion pigs and dogs using a Strange Situation Test. Dogs but not pigs exhibited distinct behaviours towards their owner and a stranger along attachment-specific variables, so only dogs’ relevant behaviours fulfilled attachment criteria. From the observed behaviours, three factors were formed: Attachment (to the owner), Anxiety (in a strange situation), and Acceptance (of a stranger). Results indicate (1) higher Attachment scores in dogs than pigs, (2) greater Acceptance scores in pigs, (3) positive correlation of Attachment and Anxiety in both, (4) similar time tendency of pigs' Attachment and Acceptance scores. These suggest that in pigs, domestication and early exposure to human social stimuli did not trigger attachment to humans. Thus, along with species predispositions, the unique dog-owner attachment can be facilitated by artificial selection that increased dogs' dependence on humans.
Urea production via photocatalytic coupling of mixed gases (CO2/NH3) using Mo(MnO4)5 supported on Ce-BTC as nano-composite catalyst
Authors: El-Shahat Mahmoud , Abdelhameed Reda M. 
Published: July 2024

AbstractUrea used in fertilization and feed supplement, as well as a starting material for the manufacture of plastics and drugs. Urea is most commonly produced by reacting carbon dioxide with ammonia at high temperature. Photocatalysis has gained attention as a sustainable pathway for performing urea. This work focus on designing very active photocatalysts based on cerium organic framework (Ce-BTC) doped with metal oxide nanoparticles (molybdenum permanganate, Mo(MnO4)5) for production of urea from coupling of ammonia with carbon dioxide. The prepared materials were characterized using different spectral analysis and the morphology was analysed using microscopic data. The effect of catalyst loading on the production rate of urea was investigated and the obtained results showed speed rate of urea production with high production yield at low temperature. The recyclability tests confirmed the sustainability of the prepared photocatlysts (Mo(MnO4)5@Ce-BTC) which supported the beneficial of the photocatalysis process in urea production.
Human health risk assessment of heavy metals in vegetables of Bangladesh
Authors: Chowdhury Akibul Islam , Shill Lincon Chandra , Raihan M. Maruf , Rashid Rumana , Bhuiyan Md. Nizamul Hoque , Reza Sompa , Alam Mohammad Rahanur 
Published: July 2024

AbstractThis study aims to evaluate the heavy metal concentration in fifteen species of vegetables as well as associated health risk. Atomic absorption spectrometry is used to assess heavy metals. The mean concentrations of Pb, Cd, Cr, Ni and Fe in vegetables were 4.78, 0.713, 9.266, 0.083, 5.06 mg/kg/fw exceeding the reference value of FAO/WHO indicating unsafe to consumption. Based on principal component analysis, the Pb, Cr, Ni and Fe are from same sources. Health risk was estimated in terms of estimated daily intake (EDI), target hazard quotient, hazard index (HI) and cancer risk (CR). The EDI values of metals except Cr were found to be lower than maximum tolerable daily intake (MTDI). The total THQs of metals were > 1 indicating non-carcinogenic health risk. The individual HI values for vegetables except potato (0.831) and total HI values were found to be > 1 (94.747). The TCR of Pb, Cd and Cr were > 1.0E−04 which indicating carcinogenic risk. Fruit and pod vegetables contribute much in carcinogenic risk for Pb and Cr whereas fruit, root and stems vegetables for Cd. The study revealed potential human health risk associated with the consumption of different types of vegetables in Bangladeshi adult population that might assist the regulatory bodies to develop new strategies to minimize the risk to human.
Urolithin A-mediated augmentation of intestinal barrier function through elevated secretory mucin synthesis
Authors: Yasuda Takeshi , Takagi Tomohisa , Asaeda Kohei , Hashimoto Hikaru , Kajiwara Mariko , Azuma Yuka , Kitae Hiroaki , Hirai Yasuko , Mizushima Katsura , Doi Toshifumi , Inoue Ken , Dohi Osamu , Yoshida Naohisa , Uchiyama Kazuhiko , Ishikawa Takeshi , Konishi Hideyuki , Ukawa Yuichi , Kohara Akiko , Kudoh Masatake , Inoue Ryo , Naito Yuji , Itoh Yoshito 
Published: July 2024

AbstractMaintaining the mucus layer is crucial for the innate immune system. Urolithin A (Uro A) is a gut microbiota-derived metabolite; however, its effect on mucin production as a physical barrier remains unclear. This study aimed to elucidate the protective effects of Uro A on mucin production in the colon. In vivo experiments employing wild-type mice, NF-E2-related factor 2 (Nrf2)-deficient mice, and wild-type mice treated with an aryl hydrocarbon receptor (AhR) antagonist were conducted to investigate the physiological role of Uro A. Additionally, in vitro assays using mucin-producing cells (LS174T) were conducted to assess mucus production following Uro A treatment. We found that Uro A thickened murine colonic mucus via enhanced mucin 2 expression facilitated by Nrf2 and AhR signaling without altering tight junctions. Uro A reduced mucosal permeability in fluorescein isothiocyanate-dextran experiments and alleviated dextran sulfate sodium-induced colitis. Uro A treatment increased short-chain fatty acid-producing bacteria and propionic acid concentration. LS174T cell studies confirmed that Uro A promotes mucus production through the AhR and Nrf2 pathways. In conclusion, the enhanced intestinal mucus secretion induced by Uro A is mediated through the actions of Nrf-2 and AhR, which help maintain intestinal barrier function.
Immunomodulatory of sesquiterpenoids and sesquiterpenoid dimers-based toll-like receptor 4 (TLR4) from Dysoxylum parasiticum stem bark
Authors: Naini Al Arofatus , Mayanti Tri , Hilmayanti Erina , Huang Xuhao , Kabayama Kazuya , Shimoyama Atsushi , Manabe Yoshiyuki , Fukase Koichi , Supratman Unang 
Published: July 2024

AbstractIn recent decades, the interest in natural products with immunomodulatory properties has increased due to their therapeutic potential. These products have a wider range of pharmacological activities and demonstrate lower toxicity levels when compared to their synthetic counterparts. Therefore, this study aimed to investigate the immunomodulatory effects of sesquiterpenoids (SQs) and sesquiterpenoid dimers (SQDs) isolated from Dysoxylum parasiticum (Osbeck) Kosterm. stem bark on human and murine cells, particularly focusing on toll-like receptor 4 (TLR4). Utilizing the secreted alkaline phosphatase (SEAP) assay on engineered human and murine TLR4 of HEK-Blue cells, antagonist TLR4 compounds were identified, including SQs 6, 9, and 10, as well as SQDs 17 and 22. The results showed that 10-hydroxyl-15-oxo-α-cadinol (9) had a potent ability to reduce TLR4 activation induced by LPS stimulation, with minimal toxicity observed in both human and murine cells. The SEAP assay also revealed diverse immune regulatory effects for the same ligand. For instance, SQs 12, 14, and 16 transitioned from antagonism on human to murine TLR4. The SQs (4, 7, 11, and 15) and SQDs (18–20) offered partial antagonist effect exclusively on murine TLR4. Furthermore, these selected SQs and SQDs were assessed for their influence on the production of proinflammatory cytokines TNF-α, IL-1α, IL-1β, and IL-6 of the NF-κB signaling pathway in human and murine macrophage cell lines, showing a dose-dependent manner. Additionally, a brief discussion on the structure-activity relationship was presented.
Combination immunohistochemistry for CK5/6, p63, GATA6, and HNF4a predicts clinical outcome in treatment-naïve pancreatic ductal adenocarcinoma
Authors: Shibayama Takahiro , Hayashi Akimasa , Toki Masao , Kitahama Keiichiro , Ho Yu-Jui , Kato Kenichiro , Yamada Takahiro , Kawamoto Sho , Kambayashi Komei , Ochiai Kazushige , Gondo Koichi , Okano Naohiro , Melchor Jerry P. , Iacobuzio-Donahue Christine A. , Sakamoto Yoshihiro , Hisamatsu Tadakazu , Shibahara Junji 
Published: July 2024

AbstractAlthough sequence-based studies show that basal-like features lead to worse prognosis and chemotherapy-resistance compared to the classical subtype in advanced pancreatic ductal adenocarcinoma (PDAC), a surrogate biomarker distinguishing between these subtypes in routine diagnostic practice remains to be identified. We aimed to evaluate the utility of immunohistochemistry (IHC) expression subtypes generated by unsupervised hierarchical clustering based on staining scores of four markers (CK5/6, p63, GATA6, HNF4a) applied to endoscopic ultrasound-guided fine needle aspiration biopsy (EUS-FNAB) materials. EUS-FNAB materials taken from 190 treatment-naïve advanced PDAC patients were analyzed, and three IHC patterns were established (Classical, Transitional, and Basal-like pattern). Basal-like pattern (high co-expression of CK5/6 and p63 with low expression of GATA6 and HNF4a) was significantly associated with squamous differentiation histology (p < 0.001) and demonstrated the worst overall survival among our cohort (p = 0.004). IHC expression subtype (Transitional, Basal vs Classical) was an independent poor prognosticator in multivariate analysis [HR 1.58 (95% CI 1.01–2.38), p = 0.047]. Furthermore, CK5/6 expression was an independent poor prognostic factor in histological glandular type PDAC [HR 2.82 (95% CI 1.31–6.08), p = 0.008]. Our results suggest that IHC expression patterns successfully predict molecular features indicative of the Basal-like subgroup in advanced PDAC. These results provide the basis for appropriate stratification for therapeutic selection and prognostic estimation of advanced PDAC in a simplified manner.
The discovery of the church of Rungholt, a landmark for the drowned medieval landscapes of the Wadden Sea World Heritage
Authors: Wilken Dennis , Hadler Hanna , Majchczack Bente Sven , Blankenfeldt Ruth , Auge Oliver , Bäumler Sarah , Bienen-Scholt Dirk , Ickerodt Ulf , Klooß Stefanie , Reiß Antonia , Willershäuser Timo , Rabbel Wolfgang , Vött Andreas 
Published: July 2024

AbstractThe UNESCO World Heritage Wadden Sea holds remains of a medieval cultural landscape shaped by interactions between man and natural forces. From the Netherlands to Denmark, human efforts of cultivating low-lying areas created a unique coastal landscape. Since the Middle Ages, storm floods widely drowned embanked cultural land and especially affected North Frisia (Germany), where once fertile marshland was permanently turned into tidal flats. One key region, the Edomsharde, was widely destroyed in 1362 AD. Medieval settlement remains still occur in the tidal flats around the island Hallig Südfall and are commonly associated with Edomsharde’s trading centre Rungholt—ever since a symbol for the region’s drowned landscapes and focus of this study. We present a first-time comprehensive reconstruction of this medieval settlement by means of new geophysical, geoarchaeological and archaeological data. Our results reveal remains of up to 64 newly found and rectified dwelling mounds, abundant drainage ditches, a seadike, and especially the discovery of Edomshardes’s main church as important landmark in this former cultural landscape. These finds together with the documented imported goods confirm a thriving society, involved in transregional trade and thereby close a significant gap in medieval history not only for North Frisia, but the entire Wadden Sea region.
Functional data geometric morphometrics with machine learning for craniodental shape classification in shrews
Authors: Pillay Aneesha Balachandran , Pathmanathan Dharini , Dabo-Niang Sophie , Abu Arpah , Omar Hasmahzaiti 
Published: July 2024

AbstractThis work proposes a functional data analysis approach for morphometrics in classifying three shrew species (S. murinus, C. monticola, and C. malayana) from Peninsular Malaysia. Functional data geometric morphometrics (FDGM) for 2D landmark data is introduced and its performance is compared with classical geometric morphometrics (GM). The FDGM approach converts 2D landmark data into continuous curves, which are then represented as linear combinations of basis functions. The landmark data was obtained from 89 crania of shrew specimens based on three craniodental views (dorsal, jaw, and lateral). Principal component analysis and linear discriminant analysis were applied to both GM and FDGM methods to classify the three shrew species. This study also compared four machine learning approaches (naïve Bayes, support vector machine, random forest, and generalised linear model) using predicted PC scores obtained from both methods (a combination of all three craniodental views and individual views). The analyses favoured FDGM and the dorsal view was the best view for distinguishing the three species.
Climate change will lead to range shifts and genetic diversity losses of dung beetles in the Gobi Desert and Mongolian Steppe
Authors: Lim Changseob , Kang Ji Hyoun , Bayartogtokh Badamdorj , Bae Yeon Jae 
Published: July 2024

AbstractDesertification is known to be a major threat to biodiversity, yet our understanding of the consequent decline in biodiversity remains insufficient. Here, we predicted climate change-induced range shifts and genetic diversity losses in three model dung beetles: Colobopterus erraticus, Cheironitis eumenes, and Gymnopleurus mopsus, distributed across the Gobi Desert and Mongolian Steppe, areas known for desertification. Phylogeographic analyses of mitochondrial COI sequences and species distribution modeling, based on extensive field investigations spanning 14 years, were performed. Species confined to a single biome were predicted to contract and shift their distribution in response to climate change, whereas widespread species was predicted to expand even if affected by range shifts. We indicated that all species are expected to experience significant haplotype losses, yet the presence of high singleton frequencies and low genetic divergence across geographic configurations and lineages mitigate loss of genetic diversity. Notably, Cheironitis eumenes, a desert species with low genetic diversity, appears to be the most vulnerable to climate change due to the extensive degradation in the Gobi Desert. This is the first study to predict the response of insects to desertification in the Gobi Desert. Our findings highlight that dung beetles in the Gobi Desert and Mongolian Steppe might experience high rates of occupancy turnover and genetic loss, which could reshuffle the species composition.