bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic identification of the role of gut microbiota in mental disorders: a TwinsUK cohort study
Authors: Delanote Julie , Correa Rojo Alejandro , Wells Philippa M. , Steves Claire J. , Ertaylan Gökhan 
Published: February 2024

AbstractMental disorders are complex disorders influenced by multiple genetic, environmental, and biological factors. Specific microbiota imbalances seem to affect mental health status. However, the mechanisms by which microbiota disturbances impact the presence of depression, stress, anxiety, and eating disorders remain poorly understood. Currently, there are no robust biomarkers identified. We proposed a novel pyramid-layer design to accurately identify microbial/metabolomic signatures underlying mental disorders in the TwinsUK registry. Monozygotic and dizygotic twins discordant for mental disorders were screened, in a pairwise manner, for differentially abundant bacterial genera and circulating metabolites. In addition, multivariate analyses were performed, accounting for individual-level confounders. Our pyramid-layer study design allowed us to overcome the limitations of cross-sectional study designs with significant confounder effects and resulted in an association of the abundance of genus Parabacteroides with the diagnosis of mental disorders. Future research should explore the potential role of Parabacteroides as a mediator of mental health status. Our results indicate the potential role of the microbiome as a modifier in mental disorders that might contribute to the development of novel methodologies to assess personal risk and intervention strategies.
FMO-guided design of darunavir analogs as HIV-1 protease inhibitors
Authors: Chuntakaruk Hathaichanok , Hengphasatporn Kowit , Shigeta Yasuteru , Aonbangkhen Chanat , Lee Vannajan Sanghiran , Khotavivattana Tanatorn , Rungrotmongkol Thanyada , Hannongbua Supot 
Published: February 2024

AbstractThe prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19–0–14–3, 19–8–10–0, and 19–8–14–3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.
Validation of computational fluid dynamics of shake flask experiments at moderate viscosity by liquid distributions and volumetric power inputs
Authors: Dinter Carl , Gumprecht Andreas , Menze Matthias Alexander , Azizan Amizon , Niehoff Paul-Joachim , Hansen Sven , Büchs Jochen 
Published: February 2024

AbstractComputational fluid dynamics (CFD) has recently become a pivotal tool in the design and scale-up of bioprocesses. While CFD has been extensively utilized for stirred tank reactors (STRs), there exists a relatively limited body of literature focusing on CFD applications for shake flasks, almost exclusively concentrated on fluids at waterlike viscosity. The importance of CFD model validation cannot be overstated. While techniques to elucidate the internal flow field are necessary for model validation in STRs, the liquid distribution, caused by the orbital shaking motion of shake flasks, can be exploited for model validation. An OpenFOAM CFD model for shake flasks has been established. Calculated liquid distributions were compared to suitable, previously published experimental data. Across a broad range of shaking conditions, at waterlike and moderate viscosity (16.7 mPa∙s), the CFD model's liquid distributions align excellently with the experimental data, in terms of overall shape and position of the liquid relative to the direction of the centrifugal force. Additionally, the CFD model was used to calculate the volumetric power input, based on the energy dissipation. Depending on the shaking conditions, the computed volumetric power inputs range from 0.1 to 7 kW/m3 and differed on average by 0.01 kW/m3 from measured literature data.
Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease
Authors: Rocque Brittany , Guion Kate , Singh Pranay , Bangerth Sarah , Pickard Lauren , Bhattacharjee Jashdeep , Eguizabal Sofia , Weaver Carly , Chopra Shefali , Zhou Shengmei , Kohli Rohit , Sher Linda , Akbari Omid , Ekser Burcin , Emamaullee Juliet A. 
Published: February 2024

AbstractSingle cell and spatially resolved ‘omic’ techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict individual cell types within each transcriptome ‘spot’ on tissue sections. In this study, we performed spatial transcriptomics and single nucleus RNA sequencing (snRNAseq) on matched specimens from patients with either histologically normal or advanced fibrosis to establish important aspects of tissue handling, data processing, and downstream analyses of biobanked liver samples. We observed that tissue preservation technique impacts transcriptomic data, especially in fibrotic liver. Single cell mapping of the spatial transcriptome using paired snRNAseq data generated a spatially resolved, single cell dataset with 24 unique liver cell phenotypes. We determined that cell–cell interactions predicted using ligand–receptor analysis of snRNAseq data poorly correlated with cellular relationships identified using spatial transcriptomics. Our study provides a framework for generating spatially resolved, single cell datasets to study gene expression and cell–cell interactions in biobanked clinical samples with advanced liver disease.
Sequential Bayesian-optimized graphene synthesis by direct solar-thermal chemical vapor deposition
Authors: Alghfeli Abdalla , Fisher Timothy S. 
Published: February 2024

AbstractThis work reports the use of a high-flux solar simulator that mimics the solar spectrum and a cold-wall CVD reactor to demonstrate the feasibility of utilizing a renewable energy resource in synthesizing graphene under various conditions. A parametric study of process parameters was conducted using a probabilistic approach. Gaussian process regression serves as a surrogate to establish a prior for Bayesian optimization, and an information acquisition function is employed to identify conditions that yield high-quality products. Backscattered electron images and Raman mapping were used to assess the effects of growth conditions on graphene characteristic sizes, film quality, and uniformity. We report the synthesis of high-quality single-layer graphene (SLG) and AB-stacked bilayer graphene films in a one-step, short-time process with $$I_{D}/I_{G}$$

I
D

/

I
G

ratios of 0.21 and 0.14, respectively. Electron diffraction analysis shows peak intensities that resemble SLG and AB-bilayer graphene with up to 5 and 20 $${\upmu }$$
μ
m grain sizes, respectively. The optical transmissivities of SLG and AB-bilayer graphene fall between 0.959–0.977 and 0.929–0.953, whereas the sheet resistances measured by a 4-point probe with 1 mm spacing are 15.5 ± 4.6 and 3.4 ± 1.5 k$$\Omega$$
Ω
/sq, respectively. Further scale-up of the optimized graphene growth area was achieved by flattening the insolation profile, leading to spatial uniformity up to 13 mm in radius. Direct solar capture for CVD synthesis enable a practical and sustainable option for synthesizing graphene films applicable for photonic and electronic applications.
Concordance of movements and songs enhances receiver responses to multimodal display in the starling
Authors: Rusiecki Stanisław , Ręk Paweł 
Published: February 2024

AbstractMany animals produce signals that consist of vocalizations and movements to attract mates or deter rivals. We usually consider them as components of a single multimodal signal because they are temporally coordinated. Sometimes, however, this relationship takes on a more complex spatiotemporal character, resembling choreographed music. Timing is important for audio-visual integration, but choreographic concordance requires even more skill and competence from the signaller. Concordance should therefore have a strong impact on receivers; however, little is known about its role in audio-visual perception during natural interactions. We studied the effects of movement and song type concordance in audio-visual displays of the starling, Sturnus vulgaris. Starlings produce two types of movements that naturally appear in specific phrases of songs with a similar temporal structure and amplitude. In an experiment with a taxidermic robotic model, males responded more to concordant audio-visual displays, which are also naturally preferred, than to discordant displays. In contrast, the effect of concordance was independent of the specific combination of movement and song types in a display. Our results indicate that the concordance of movements and songs was critical to the efficacy of the display and suggest that the information that birds gained from concordance could not be obtained by adding information from movements and songs.
Isolation and identification of metallotolerant bacteria with a potential biotechnological application
Authors: Parades-Aguilar Jonathan , Calderon Kadiya , Agustin-Salazar Sarai , Cerruti Pierfrancesco , Ambrogi Veronica , Gamez-Meza Nohemi , Medina-Juarez Luis Angel 
Published: February 2024

AbstractMining has led to severe environmental pollution in countries with exhaustive mining production and inadequate industrial waste regulation. Microorganisms in contaminated sites, like mine tailings, have adapted to high concentrations of heavy metals, developing the capacity of reducing or removing them from these environments. Therefore, it is essential to thoroughly characterize bacteria present in these sites to find different ways of bioremediation. In this regard, in this study, an enrichment and isolation procedure were performed to isolate bacteria with lower nutritional requirements and high tolerance to Cu(II) and Fe(II) from two Sonoran River basin mining tails. Two Staphylococcus species and a Microbacterium ginsengisoli strain were isolated and identified from the San Felipe de Jesús mining tail. Also, three strains were isolated from the Nacozari de García mining tail: Burkholderia cenocepacia, Sphingomonas sp. and Staphylococcus warneri. Significant microbiological differences were found between the two sites. All these species exhibited tolerance up to 300 mg/L for Cu (II)–Fe (II) solutions, indicating their capacity to grow in these conditions. Moreover, a consortium of isolated bacteria was immobilized in two different biocomposites and the biocomposite with larger pore size achieved greater bacterial immobilization showcasing the potential of these bacteria in biotechnological applications.
Age at onset of type 1 diabetes between puberty and 30 years old is associated with increased diabetic nephropathy risk
Authors: Lin Yen-Bo ,   Taiwan Diabetes Registry Study Group, Sheu Wayne Huey-Herng , Lo Su-Huey , Yeh Yen-Po , Huang Chien-Ning , Hwu Chii-Min , Hsieh Chang-Hsun , Ou Horng-Yi , Chuang Lee-Ming , Chen Jung-Fu , Chen Yu-Cheng , Peng Yun-Hsing , Chen Szu-Tah , Hsu Shang-Ren , Hsieh Yi-Ling , Chu Chih-Hsun , Lu Chieg-Hsiang , Lee Yau-Jiunn , Chen Hua-Fen , Chen Ching-Chu , Lee Chun-Chuan , Hsiao Pi-Jung , Tsai Shih-Tzer , Chen Samuel , Su Ching-Chieh , Lin Yu-Ling , Bau Cho-Tsan , Liao Chung-Chia , Kuo Tsung-yung , Chen Huey-Jen , Wang Chih-Chien , Cheng Chiu-Jung , Lin Yung-Lung , Chen Shin-Chueh , Chen Chung-Yuan , Huang Hsin-Yang , Chen Jiunn-Rong , Lo Hsiao-Jung , Yu Neng-Chun , Liu Wen-Cheng , Wu Chun-Han , Chen Deng-Wang , Shen De-Chung , Chung Wei-Chen , Chang Tien-Jyun 
Published: February 2024

AbstractDiabetic nephropathy is a critical complication of patients with type 1 diabetes, while epidemiological studies were scarce among Asian countries. We conducted a cross-sectional study to identify factors associated with diabetic nephropathy by questionnaires, using student’s t-test, chi-square test, and multivariable logistic regression. Among 898 participants, 16.7% had diabetic nephropathy. Compared with non-diabetic nephropathy patients, the patients with diabetic nephropathy had significantly higher percentage with onset age of type 1 diabetes between puberty and under 30 years old (female ≥ 12 or male ≥ 13 years old to 29 years old), longer diabetes duration, having family history of diabetes and diabetic nephropathy, accompanied with hypertension, hyperlipidemia, or coronary artery disease (CAD). Compared with patients with onset age before puberty, the odds of diabetic nephropathy occurrence increased to 1.61 times in patients with onset age between puberty and under 30 years old (p = 0.012) after adjusting diabetes duration. Age of diabetes onset between puberty and under 30 years old, diabetes duration, HbA1c, hospital admission within 3 years, diabetic retinopathy, hypertension, systolic blood pressure (SBP), triglyceride levels, and use of angiotensin converting enzyme inhibitor (ACEI) and/or angiotensin receptor blockers (ARB) were independent factors associated with diabetic nephropathy Screening for proteinuria is important in daily clinical practice and should be part of diabetes self-management education for patients with type 1 diabetes.
Comparing surface electroenterography measurements between patients suffering from Hirschsprung’s disease and controls: a feasibility study
Authors: Rolleman Nick , Klein Willemijn , Nagtegaal Iris , van Putten Michel , de Blaauw Ivo , Botden Sanne 
Published: February 2024

AbstractCurrent diagnostics in Hirschsprung’s disease are often challenging and invasive. This study aims to investigate whether surface electroenterography can non-invasively discern healthy subjects from subjects suffering from Hirschsprung’s disease. Nine healthy subjects (seven children, two adults) and eleven subjects suffering from surgically untreated Hirschsprung’s disease (nine children, two adults) underwent an electroenterography procedure. This procedure consisted of ultrasound-guided placement of surface electrodes on the abdomen covering all parts of the colon, fasting and two 20-min electroenterography measurements separated by a meal. The dominant frequency, magnitude and relative increase (pre- to postprandial) of colonic activity were compared between both groups. The results showed that in the pediatric group, no significant differences in dominant frequency, colonic activity and relative power increase were observed between controls and patients. The adult patients showed decreased colonic motility and relative power increase in the electrodes closest to the distal colon, both when compared to the same electrodes in controls and to the more proximal electrodes of themselves. To conclude, electroenterography measurements in young children is challenging, but the results in adults demonstrate that these measurements can possibly distinguish between controls and Hirschsprung’s patients. Therefore, optimization of electroenterography measurements in young children is necessary.
Deep learning predicts prevalent and incident Parkinson’s disease from UK Biobank fundus imaging
Authors: Tran Charlie , Shen Kai , Liu Kang , Ashok Akshay , Ramirez-Zamora Adolfo , Chen Jinghua , Li Yulin , Fang Ruogu 
Published: February 2024

AbstractParkinson’s disease is the world’s fastest-growing neurological disorder. Research to elucidate the mechanisms of Parkinson’s disease and automate diagnostics would greatly improve the treatment of patients with Parkinson’s disease. Current diagnostic methods are expensive and have limited availability. Considering the insidious and preclinical onset and progression of the disease, a desirable screening should be diagnostically accurate even before the onset of symptoms to allow medical interventions. We highlight retinal fundus imaging, often termed a window to the brain, as a diagnostic screening modality for Parkinson’s disease. We conducted a systematic evaluation of conventional machine learning and deep learning techniques to classify Parkinson’s disease from UK Biobank fundus imaging. Our results suggest Parkinson’s disease individuals can be differentiated from age and gender-matched healthy subjects with 68% accuracy. This accuracy is maintained when predicting either prevalent or incident Parkinson’s disease. Explainability and trustworthiness are enhanced by visual attribution maps of localized biomarkers and quantified metrics of model robustness to data perturbations.
Targeting yeast topoisomerase II by imidazo and triazoloacridinone derivatives resulting in their antifungal activity
Authors: Rząd Kamila , Gabriel Iwona , Paluszkiewicz Ewa , Kuplińska Aleksandra , Olszewski Mateusz , Chylewska Agnieszka , Dąbrowska Aleksandra M. , Kozłowska-Tylingo Katarzyna 
Published: February 2024

AbstractFungal pathogens are considered as serious factors for deadly diseases and are a case of medical concern. Invasive fungal infections also complicate the clinical course of COVID-19, leading to a significant increase in mortality. Furthermore, fungal strains' multidrug resistance has increased the demand for antifungals with a different mechanism of action. The present study aimed to identify antifungal compounds targeting yeast topoisomerase II (yTOPOII) derived from well-known human topoisomerase II (hTOPOII) poisons C-1305 and C-1311. Two sets of derivatives: triazoloacridinones (IKE1-8) and imidazoacridinones (IKE9-14) were synthetized and evaluated with a specific emphasis on the molecular mechanism of action. Our results indicated that their effectiveness as enzyme inhibitors was not solely due to intercalation ability but also as a result of influence on catalytic activity by the formation of covalent complexes between plasmid DNA and yTOPOII. Lysine conjunction increased the strength of the compound's interaction with DNA and improved penetration into the fungal cells. Triazoloacridinone derivatives in contrast to starting compound C-1305 exhibited moderate antifungal activity and at least twice lower cytotoxicity. Importantly, compounds (IKE5-8) were not substrates for multidrug ABC transporters whereas a derivative conjugated with lysine (IKE7), showed the ability to overcome C. glabrata fluconazole-resistance (MIC 32–64 µg mL−1).
Applying the new multi-objective algorithms for the operation of a multi-reservoir system in hydropower plants
Authors: Samare Hashemi Syed Mohsen , Robati Amir , Kazerooni Mohammad Ali 
Published: February 2024

AbstractThe optimal operation of the multi-purpose reservoir system is a difficult, and, sometimes, non-linear problem in multi-objective optimization. By simulating biological behavior, meta-heuristic algorithms scan the decision space and can offer a set of points as a group of solutions to a problem. Because it is essential to simultaneously optimize several competing objectives and consider relevant constraints as the main problem in many optimization problems, researchers have improved their ability to solve multi-objective problems by developing complementary multi-objective algorithms. Because the AHA algorithm is new, its multi-objective version, MOAHA (multi-objective artificial hummingbird algorithm), was used in this study and compared with two novel multi-objective algorithms, MOMSA and MOMGA. Schaffer and MMF1 were used as two standard multi-objective benchmark functions to gauge the effectiveness of the proposed method. Then, for 180 months, the best way to operate the reservoir system of the Karun River basin, which includes Karun 4, Karun 3, Karun 1, Masjed-e-Soleyman, and Gotvand Olia dams to generate hydropower energy, supply downstream demands (drinking, agriculture, industry, environmental), and control flooding was examined from September 2000 to August 2015. Four performance appraisal criteria (GD, S, Δ, and MS) and four evaluation indices (reliability, resiliency, vulnerability, and sustainability) were used in Karun's multi-objective multi-reservoir problem to evaluate the performance of the multi-objective algorithm. All three algorithms demonstrated strong capability in criterion problems by using multi-objective algorithms’ criteria and performance indicators. The large-scale (1800 dimensions) of the multi-objective operation of the Karun Basin reservoir system was another problem. With a minimum of 1441.71 objectives and an average annual hydropower energy manufacturing of 17,166.47 GW, the MOAHA algorithm demonstrated considerable ability compared to the other two. The final results demonstrated the MOAHA algorithm’s excellent performance, particularly in difficult and significant problems such as multi-reservoir systems' optimal operation under various objectives.
Integration of risk factor polygenic risk score with disease polygenic risk score for disease prediction
Authors: Jung Hyein , Jung Hae-Un , Baek Eun Ju , Kwon Shin Young , Kang Ji-One , Lim Ji Eun , Oh Bermseok 
Published: February 2024

AbstractPolygenic risk score (PRS) is useful for capturing an individual’s genetic susceptibility. However, previous studies have not fully exploited the potential of the risk factor PRS (RFPRS) for disease prediction. We explored the potential of integrating disease-related RFPRSs with disease PRS to enhance disease prediction performance. We constructed 112 RFPRSs and analyzed the association of RFPRSs with diseases to identify disease-related RFPRSs in 700 diseases, using the UK Biobank dataset. We uncovered 6157 statistically significant associations between 247 diseases and 109 RFPRSs. We estimated the disease PRSs of 70 diseases that exhibited statistically significant heritability, to generate RFDiseasemetaPRS—a combined PRS integrating RFPRSs and disease PRS—and compare the prediction performance metrics between RFDiseasemetaPRS and disease PRS. RFDiseasemetaPRS showed better performance for Nagelkerke’s pseudo-R2, odds ratio (OR) per 1 SD, net reclassification improvement (NRI) values and difference of R2 considered by variance of R2 in 31 out of 70 diseases. Additionally, we assessed risk classification between two models by examining OR between the top 10% and remaining 90% individuals for the 31 diseases; RFDiseasemetaPRS exhibited better R2, NRI and OR than disease PRS. These findings highlight the importance of utilizing RFDiseasemetaPRS, which can provide personalized healthcare and tailored prevention strategies.