bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coupling Deep Learning and Physically Based Hydrological Models for Monthly Streamflow Predictions
Authors: Xu Wenxin , Chen Jie , Corzo Gerald , Xu Chong‐Yu , Zhang Xunchang John , Xiong Lihua , Liu Dedi , Xia Jun 
Published: February 2024

AbstractThis study proposes a new hybrid model for monthly streamflow predictions by coupling a physically based distributed hydrological model with a deep learning (DL) model. Specifically, a simplified hydrological model is first developed by optimally selecting grid cells from a distributed hydrological model according to their soil moisture characteristics. It is then driven by bias corrected general circulation model (GCM) predictions to generate soil moistures for the forecasting months. Finally, model‐simulated soil moisture along with other predictors from multiple sources are used as inputs of the DL model to predict future monthly streamflows. The proposed hybrid model, using the simplified Variable Infiltration Capacity (VIC) as the hydrological model and the combination of Convolutional Neural Network and Gated Recurrent Unit (CNN‐GRU) as the DL model, is applied to predict 1‐, 3‐, and 6‐month ahead reservoir inflows for the Danjiangkou Reservoir in China. The results show that the hybrid model consistently performs better than VIC and CNN‐GRU models with great improvement in Kling‐Gupta efficiency (KGE) values for lead times up to 6 months. Additional tests indicate that hybrid models based on CNN‐GRU outperform those based on LASSO, XGBoost, CNN, and GRU models. Moreover, compared with the distributed hydrological model, the hybrid model greatly reduces the computation burden of rolling prediction. It also saves decision‐makers the time and effort of trying different combinations of predictors, which is indispensable when building DL models. Overall, the new hybrid model demonstrates great potential for monthly streamflow prediction where training data are limited.
Urbanization and Water Management Control Stream Water Quality Along a Mountain to Plains Transition
Authors: Murphy S. F. , Runkel R. L. , Stets E. G. , Nolan A. J. , Repert D. A. 
Published: February 2024

AbstractUrbanization can have substantial effects on water quality due to altered hydrology and introduction of constituents to water bodies. In arid and semi‐arid environments, streams are further stressed by dewatering as a result of diversions. We conducted a high‐resolution synoptic survey of two streams in Colorado, USA that transition abruptly from granitic/metamorphic forested mountains to sedimentary urbanized plains and are both highly managed for water supply, yet differ in degree of urbanization. A synoptic mass balance approach developed for mine drainage applications was adapted to elucidate effects of urbanization, geology, and diversions on stream chemistry during baseflow conditions. Urbanization was a more important driver of stream concentrations than geology. The urban area was a strong source of bromide, calcium, chloride, and manganese, while lanthanum and dissolved organic carbon were primarily sourced from the mountains. A majority of streamflow was removed by diversions near the mountains/plains interface. Groundwater accounted for 31% of the subsequent flow increase to the urbanized stream, and delivered at least 33% of chloride loading. Constituents that were primarily urban‐derived (bromide, calcium, chloride, and manganese) were 2–3 times higher in the urban region due to diversions; without diversions, stream water quality would have largely retained characteristics of forested streams through the urban reach. This study provides insights into processes that affect water quality in highly managed streams of the semi‐arid western USA.
Robustness of cancer microbiome signals over a broad range of methodological variation
Authors: Sepich-Poore Gregory D. , McDonald Daniel , Kopylova Evguenia , Guccione Caitlin , Zhu Qiyun , Austin George , Carpenter Carolina , Fraraccio Serena , Wandro Stephen , Kosciolek Tomasz , Janssen Stefan , Metcalf Jessica L. , Song Se Jin , Kanbar Jad , Miller-Montgomery Sandrine , Heaton Robert , Mckay Rana , Patel Sandip Pravin , Swafford Austin D. , Korem Tal , Knight Rob 
Published: February 2024

AbstractIn 2020, we identified cancer-specific microbial signals in The Cancer Genome Atlas (TCGA) [1]. Multiple peer-reviewed papers independently verified or extended our findings [2–12]. Given this impact, we carefully considered concerns by Gihawi et al. [13] that batch correction and database contamination with host sequences artificially created the appearance of cancer type-specific microbiomes. (1) We tested batch correction by comparing raw and Voom-SNM-corrected data per-batch, finding predictive equivalence and significantly similar features. We found consistent results with a modern microbiome-specific method (ConQuR [14]), and when restricting to taxa found in an independent, highly-decontaminated cohort. (2) Using Conterminator [15], we found low levels of human contamination in our original databases (~1% of genomes). We demonstrated that the increased detection of human reads in Gihawi et al. [13] was due to using a newer human genome reference. (3) We developed Exhaustive, a method twice as sensitive as Conterminator, to clean RefSeq. We comprehensively host-deplete TCGA with many human (pan)genome references. We repeated all analyses with this and the Gihawi et al. [13] pipeline, and found cancer type-specific microbiomes. These extensive re-analyses and updated methods validate our original conclusion that cancer type-specific microbial signatures exist in TCGA, and show they are robust to methodology.
Oral lichen planus and lichenoid lesions - challenges and pitfalls for the general dental practitioner
Authors: Binnie Rebecca , Dobson Marianne Louise , Chrystal Anna , Hijazi Karolin 
Published: February 2024

AbstractLichen planus is a chronic, mucocutaneous inflammatory condition which, due to its prevalence, will be familiar to the dental profession. However, diverse forms of presentation, important differential diagnosis, potential malignant change and monitoring requirements often result in challenges for those in primary care. This paper looks to examine these challenges and provide information to support those who are involved in recognition and management of patients with lichen planus.
Biological therapies and management of oral mucosal disease
Authors: Healy Claire M. , Galvin Sheila 
Published: February 2024

AbstractBiologic drugs are drugs made by living organisms and the term is usually limited to monoclonal antibodies or receptors targeting specific cytokines or cells that have been developed in recent decades. These drugs have had an enormous impact on the management of cancers, including head and neck cancers, and immune-mediated inflammatory conditions, for example, rheumatoid arthritis and inflammatory bowel disease. General dental practitioners will routinely be managing patients who are on these medications for a wide range of systemic conditions. These drugs also have a limited role in the management of immune-mediated oral mucosal disease. In this article, we will introduce the range of biological agents and their systemic indications and then elaborate on their use in oral mucosal disease and the disadvantages associated with their use.
Direct linearly polarized electroluminescence from perovskite nanoplatelet superlattices
Authors: Ye Junzhi , Ren Aobo , Dai Linjie , Baikie Tomi K. , Guo Renjun , Pal Debapriya , Gorgon Sebastian , Heger Julian E. , Huang Junyang , Sun Yuqi , Arul Rakesh , Grimaldi Gianluca , Zhang Kaiwen , Shamsi Javad , Huang Yi-Teng , Wang Hao , Wu Jiang , Koenderink A. Femius , Torrente Murciano Laura , Schwartzkopf Matthias , Roth Stephen V. , Müller-Buschbaum Peter , Baumberg Jeremy J. , Stranks Samuel D. , Greenham Neil C. , Polavarapu Lakshminarayana , Zhang Wei , Rao Akshay , Hoye Robert L. Z. 
Published: February 2024

AbstractPolarized light is critical for a wide range of applications, but is usually generated by filtering unpolarized light, which leads to substantial energy losses and requires additional optics. Here we demonstrate the direct emission of linearly polarized light from light-emitting diodes made of CsPbI3perovskite nanoplatelet superlattices. The use of solvents with different vapour pressures enables the self-assembly of the nanoplatelets with fine control over their orientation (either face-up or edge-up) and therefore their transition dipole moment. As a result of the highly uniform alignment of the nanoplatelets, as well as their strong quantum and dielectric confinement, large exciton fine-structure splitting is achieved at the film level, leading to pure red light-emitting diodes with linearly polarized electroluminescence exhibiting a high degree of polarization of 74.4% without any photonic structures. This work demonstrates the potential of perovskite nanoplatelets as a promising source of linearly polarized light, opening up the development of next-generation three-dimensional displays and optical communications from a highly versatile, solution-processable system.
A novel ferroptosis-related gene signature for overall survival prediction in patients with gastric cancer
Authors: Wen Fang , Zhao Fan , Huang Wenjie , Liang Yan , Sun Ruolan , Lin Yize , Zhang Weihua 
Published: February 2024

AbstractThe global diagnosis rate and mortality of gastric cancer (GC) are among the highest. Ferroptosis and iron-metabolism have a profound impact on tumor development and are closely linked to cancer treatment and patient’s prognosis. In this study, we identified six PRDEGs (prognostic ferroptosis- and iron metabolism-related differentially expressed genes) using LASSO-penalized Cox regression analysis. The TCGA cohort was used to establish a prognostic risk model, which allowed us to categorize GC patients into the high- and the low-risk groups based on the median value of the risk scores. Our study demonstrated that patients in the low-risk group had a higher probability of survival compared to those in the high-risk group. Furthermore, the low-risk group exhibited a higher tumor mutation burden (TMB) and a longer 5-year survival period when compared to the high-risk group. In summary, the prognostic risk model, based on the six genes associated with ferroptosis and iron-metabolism, performs well in predicting the prognosis of GC patients.
NLCECA score: a serum inflammatory-tumor biomarker score to predict survival of advanced perihilar cholangiocarcinoma after hepatic arterial infusion chemotherapy
Authors: Fu Shjie , Li Jie , Fan Hua , Zheng Kanglian , Leng Boyu , Cao Guang , Xu Liang , Zhong Yujie , Niu Chuanxin , Wang Xiaodong 
Published: February 2024

AbstractPrognostic features in advanced perihilar cholangiocarcinoma (pCCA) patients who received first-line hepatic arterial infusion chemotherapy (HAIC) are unknown. The purpose of our study was to develop an applicable score based on serum inflammatory-tumor biomarkers to predict the survival of advanced pCCA patients who received first-line HAIC. In total, 106 advanced pCCA patients were enrolled as the training cohort. The optimal cutoff values of baseline variables were defined by the receiver operating characteristic method or according to previous publications. According to the results of Cox regression analysis, baseline neutrophil-to-lymphocyte ratio (NLR) > 3.19, carcinoembryonic antigen (CEA) > 10 ng/mL, and carbohydrate antigen 19-9 (CA19-9) > 200 U/mL were identified as independent survival predictors, which were used to develop the NLCECA score (NLR, CEA, and CA19-9). When including the NLCECA score in the multivariate analysis, the NLCECA score was the only independent predictor of survival. The risk of survival decreased by 111.9% for each 1-point increase in the NLCECA score. Additionally, the NLCECA score could also predict survival in another 33 patients in the validation cohort (P < 0.001). In summary, the NLCECA score is a potential biomarker system for predicting the survival of advanced pCCA patients who received first-line HAIC.
Enhancement of the mechanical properties in ultra-low weight SWCNT sandwiched PDMS composites using a novel stacked architecture
Authors: Ananthasubramanian Pavithra , Sahay Rahul , Raghavan Nagarajan 
Published: February 2024

AbstractThis study focuses on enhancing the mechanical properties of thin, soft, free-standing films via a layer-by-layer (LBL) fabrication process called LBL-FP. Soft polymer nanocomposite (PNC) thin films, combining polydimethylsiloxane (PDMS) and single-walled carbon nanotubes (SWCNT) at ultra-low loadings using a unique bottom-up LBL-FP, are examined. Two different structures of layered composites, (i) LBL PNCs- Layered composites with alternating layers of PDMS and SWCNT, (ii) Bulk PNCs- Layered composites with SWCNT dispersed in the bulk of PDMS, are comparatively investigated for their structural and mechanical properties. Silane-functionalized SWCNT strengthens the chemical bonding with PDMS, improving adhesion and dispersion. Mechanical analysis using nanoindentation, delamination, and dynamic analysis highlights the advantages of LBL PNCs with alternating layers of PDMS and SWCNT. Notably, LBL PNC (0.5 wt%) exhibits significant improvements, such as 2.6X increased nanoindentation resistance, 3X improved viscoelasticity, and (2–5)X enhanced tensile properties in comparison with neat PDMS. Due to this, LBL PNCs offer potential for soft, lightweight applications like wearables, electromagnetic interference shielding materials, and strain sensors while advancing composite thin film mechanics. The study emphasizes using a stacked architecture to produce PDMS-SWCNT multilayered PNCs with improved mechanics utilizing ultra-low concentrations of SWCNT. This first-of-its-kind stack design facilitates possibilities for lightweight composites utilizing less fillers. The LBL assembly involves the stacking of alternating layers of different materials, each contributing specific properties to enhance the overall strength and toughness of the structure.
In vivo evaluation of a nanotechnology-based microshunt for filtering glaucoma surgery
Authors: Gniesmer Stefanie , Sonntag Svenja Rebecca , Gapeeva Anna , Cojocaru Ala , Kaps Sören , Adelung Rainer , Sewing Judith , Tura Aysegül , Grisanti Salvatore , Grisanti Swaantje 
Published: February 2024

AbstractTo carry out the preclinical and histological evaluation of a novel nanotechnology-based microshunt for drainage glaucoma surgery. Twelve New Zealand White rabbits were implanted with a novel microshunt and followed up for 6 weeks. The new material composite consists of the silicone polydimethylsiloxane (PDMS) and tetrapodal Zinc Oxide (ZnO-T) nano-/microparticles. The microshunts were inserted ab externo to connect the subconjunctival space with the anterior chamber. Animals were euthanized after 2 and 6 weeks for histological evaluation. Ocular health and implant position were assessed at postoperative days 1, 3, 7 and twice a week thereafter by slit lamp biomicroscopy. Intraocular pressure (IOP) was measured using rebound tonometry. A good tolerability was observed in both short- and medium-term follow-up. Intraocular pressure was reduced following surgery but increased to preoperative levels after 2 weeks. No clinical or histological signs of inflammatory or toxic reactions were seen; the fibrotic encapsulation was barely noticeable after two weeks and very mild after six weeks. The new material composite PDMS/ZnO-T is well tolerated and the associated foreign body fibrotic reaction quite mild. The new microshunt reduces the IOP for 2 weeks. Further research will elucidate a tube-like shape to improve and prolong outflow performance and longer follow-up to exclude medium-term adverse effects.
Knowledge, attitude, and practice toward cochlear implants among deaf patients who received cochlear implants
Authors: Li Kunjun , Zhou Ruhuan , Zheng Wenwen , Zhang Yanbing , Qiu Jianxin 
Published: February 2024

AbstractDespite the growing use of cochlear implants in deaf patients, there is a lack of data on their knowledge, attitude, and practice (KAP) toward cochlear implants. This study aimed to investigate the KAP toward cochlear implants among deaf patients who received cochlear implants. A web-based cross-sectional study was conducted between August 2022 and December 2022 among deaf patients who had received cochlear implants. A self-administered questionnaire was used to collect demographic characteristics and KAP scores. A total of 526 participants were enrolled; 54.18% were female, 65.40% were above 60 years old, and 61.03% were surveyed at less than 3 years after implantation. The mean knowledge, attitude, and practice scores were 8.15 ± 2.18 (possible range: 0–10), 43.63 ± 6.98 (possible range: 12–60), and 41.11 ± 7.42 (possible range: 11–55), respectively, indicating good knowledge, moderate attitude and practice. Multivariable logistic regression analysis showed that attitude [odd ratio (OR) = 1.24, 95% confidence interval (CI) 1.18–1.29, P < 0.001] and unemployment (OR = 0.33, 95% CI 0.17–0.63, P = 0.001) were independently associated with practice. Path analysis showed that knowledge directly influenced attitude (β = 0.93, 95% CI 0.61–1.19, P < 0.001), attitude directly influenced practice (β = 0.53, 95% CI 0.46–0.61, P < 0.001), and knowledge directly (β = 0.77, 95% CI 0.53–1.01, P < 0.001) and indirectly (β = 0.50, 95% CI 0.34–0.66, P < 0.001) influenced practice. Deaf patients who received cochlear implants showed good knowledge, moderate attitude and practice toward cochlear implants. Knowledge should be strengthened to improve attitude and practice toward cochlear implants, which could translate into realistic expectations toward cochlear implants devices and proper care and maintenance.
Periodicity, Elliott waves, and fractals in the NFT market
Authors: Christopher Westland J. 
Published: February 2024

AbstractNon-fungible tokens (NFTs) are unique digital assets that exist on a blockchain and have provided new revenue streams for creators. This research investigates NFT market inefficiencies to identify claimed cyclic behavior and cryptocurrency influences on NFT prices. The research found that while linear models are not useful in modeling NFT price series, models that extract periodic behavior can provide explanations and predictions of price behavior. The investigation of autocycles in cryptocurrency and NFT markets did not support the existence of Elliott Wave behavior in any of these blockchain enabled assets. Rather NFT price behavior is strongly tied to the underlying asset and its community of fans. These fans commit to periodic bouts of idiosyncratic trading which cools for a while, and then restarts. The research found no evidence supporting whole market effects across the full price series of individual NFTs. The research strongly supports prior findings that the offsetting movements significantly influence NFT prices and trading volume in Bitcoin and Ether. The research found NFT markets exhibit characteristics resembling a social media platform rather than more traditional asset markets like stock exchanges. It found that traditional linear econometric models cannot predict or explain NFT price series, only that NFT price and volume were weakly correlated. Fractal models consistent with Elliott wave theory do explain some of NFT price behavior, but are not consistent or stable over time. This research confirmed prior research findings that Bitcoin and Ether price movements are correlated with general NFT price and volume series in periods of between 24 and 48 h, with significant numbers of trades into and out of cryptocurrencies at 2 and 8 h.
Expression of the checkpoint kinase BUB1 is a predictor of response to cancer therapies
Authors: Cicirò Ylenia , Ragusa Denise , Sala Arturo 
Published: February 2024

AbstractThe identification of clinically-relevant biomarkers is of upmost importance for the management of cancer, from diagnosis to treatment choices. We performed a pan-cancer analysis of the mitotic checkpoint budding uninhibited by benzimidazole 1 gene BUB1, in the attempt to ascertain its diagnostic and prognostic values, specifically in the context of drug response. BUB1 was found to be overexpressed in the majority of cancers, and particularly elevated in clinically aggressive molecular subtypes. Its expression was correlated with clinico-phenotypic features, notably tumour staging, size, invasion, hypoxia, and stemness. In terms of prognostic value, the expression of BUB1 bore differential clinical outcomes depending on the treatment administered in TCGA cancer cohorts, suggesting sensitivity or resistance, depending on the expression levels. We also integrated in vitro drug sensitivity data from public projects based on correlation between drug efficacy and BUB1 expression to produce a list of candidate compounds with differential responses according to BUB1 levels. Gene Ontology enrichment analyses revealed that BUB1 overexpression in cancer is associated with biological processes related to mitosis and chromosome segregation machinery, reflecting the mechanisms of action of drugs with a differential effect based on BUB1 expression.
Epistasis arises from shifting the rate-limiting step during enzyme evolution of a β-lactamase
Authors: Fröhlich Christopher , Bunzel H. Adrian , Buda Karol , Mulholland Adrian J. , van der Kamp Marc W. , Johnsen Pål J. , Leiros Hanna-Kirsti S. , Tokuriki Nobuhiko 
Published: February 2024

AbstractEpistasis, the non-additive effect of mutations, can provide combinatorial improvements to enzyme activity that substantially exceed the gains from individual mutations. Yet the molecular mechanisms of epistasis remain elusive, undermining our ability to predict pathogen evolution and engineer biocatalysts. Here we reveal how directed evolution of a β-lactamase yielded highly epistatic activity enhancements. Evolution selected four mutations that increase antibiotic resistance 40-fold, despite their marginal individual effects (≤2-fold). Synergistic improvements coincided with the introduction of super-stochiometric burst kinetics, indicating that epistasis is rooted in the enzyme’s conformational dynamics. Our analysis reveals that epistasis stemmed from distinct effects of each mutation on the catalytic cycle. The initial mutation increased protein flexibility and accelerated substrate binding, which is rate-limiting in the wild-type enzyme. Subsequent mutations predominantly boosted the chemical steps by fine-tuning substrate interactions. Our work identifies an overlooked cause for epistasis: changing the rate-limiting step can result in substantial synergy that boosts enzyme activity.