bluuebunny/crossref_metadata_2025_split huggingface dataset:
An efficient CRISPR/Cas9 genome editing system based on a multiple sgRNA processing platform in Trichoderma reesei for strain improvement and enzyme production
Authors: Zhang Jiaxin , Li Kehang , Sun Yu , Yao Cheng , Liu Weifeng , Liu Hong , Zhong Yaohua 
Published: February 2024

Abstract
Background
The CRISPR/Cas9 technology is being employed as a convenient tool for genetic engineering of the industrially important filamentous fungus Trichoderma reesei. However, multiplex gene editing is still constrained by the sgRNA processing capability, hindering strain improvement of T. reesei for the production of lignocellulose-degrading enzymes and recombinant proteins.

Results
Here, a CRISPR/Cas9 system based on a multiple sgRNA processing platform was established for genome editing in T. reesei. The platform contains the arrayed tRNA−sgRNA architecture directed by a 5S rRNA promoter to generate multiple sgRNAs from a single transcript by the endogenous tRNA processing system. With this system, two sgRNAs targeting cre1 (encoding the carbon catabolite repressor 1) were designed and the precise deletion of cre1 was obtained, demonstrating the efficiency of sgRNAs processing in the tRNA−sgRNA architecture. Moreover, overexpression of xyr1-A824V (encoding a key activator for cellulase/xylanase expression) at the ace1 (encoding a repressor for cellulase/xylanase expression) locus was achieved by designing two sgRNAs targeting ace1 in the system, resulting in the significantly enhanced production of cellulase (up to 1- and 18-fold on the Avicel and glucose, respectively) and xylanase (up to 11- and 41-fold on the Avicel and glucose, respectively). Furthermore, heterologous expression of the glucose oxidase gene from Aspergillus niger ATCC 9029 at the cbh1 locus with the simultaneous deletion of cbh1 and cbh2 (two cellobiohydrolase coding genes) by designing four sgRNAs targeting cbh1 and cbh2 in the system was acquired, and the glucose oxidase produced by T. reesei reached 43.77 U/mL. Besides, it was found the ER-associated protein degradation (ERAD) level was decreased in the glucose oxidase-producing strain, which was likely due to the reduction of secretion pressure by deletion of the major endogenous cellulase-encoding genes.

Conclusions
The tRNA−gRNA array-based CRISPR-Cas9 editing system was successfully developed in T. reesei. This system would accelerate engineering of T. reesei for high-level production of enzymes including lignocellulose-degrading enzymes and other recombinant enzymes. Furthermore, it would expand the CRISPR toolbox for fungal genome editing and synthetic biology.
Mapping the distribution of Amblyomma americanum in Georgia, USA
Authors: Bellman Stephanie , Fausett Ellie , Aeschleman Leah , Long Audrey , Roeske Isabella , Pilchik Josie , Piantadosi Anne , Vazquez-Prokopec Gonzalo 
Published: February 2024

Abstract
Background
Amblyomma americanum, the lone star tick, is an aggressive questing species that harbors several pathogens dangerous to humans in the United States. The Southeast in particular has large numbers of this tick due to the combined suitable climate and habitats throughout the region. No studies have estimated the underlying distribution of the lone star tick across the state of Georgia, a state where it is the dominant species encountered.

Methods
Ticks were collected by flagging 198 transects of 750 m2 at 43 state parks and wildlife management areas across the state from March to July of 2022. A suite of climate, landscape, and wildlife variables were assembled, and a logistic regression model was used to assess the association between these environmental factors and the presence of lone star ticks and to predict the distribution of these ticks across the state.

Results
A total of 59/198 (30%) transects sampled contained adult or nymph A. americanum, with the majority of transects containing these ticks (54/59, 91.5%) in forested habitats. The presence of A. americanum was associated with elevation, normalized difference vegetation index (NDVI) on January 1, isothermality, temperature seasonality, and precipitation in the wettest quarter. Vast regions of central, eastern, and southern coastal Georgia (57% of the state) were categorized as suitable habitat for the lone star tick.

Conclusions
This study describes the distribution of the lone star tick across the state of Georgia at a finer scale than the current county-level information available. It identifies specific variables associated with tick presence and provides a map that can be used to target areas for tick prevention messaging and awareness.

Graphical Abstract
Molecular map of disulfidptosis-related genes in lung adenocarcinoma: the perspective toward immune microenvironment and prognosis
Authors: Zhao Fangchao , Su Lei , Wang Xuefeng , Luan Jiusong , Zhang Xin , Li Yishuai , Li Shujun , Hu Ling 
Published: February 2024

Abstract
Background
Disulfidptosis is a recently discovered form of programmed cell death that could impact cancer development. Nevertheless, the prognostic significance of disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD) requires further clarification.

Methods
This study systematically explores the genetic and transcriptional variability, prognostic relevance, and expression profiles of DRGs. Clusters related to disulfidptosis were identified through consensus clustering. We used single-sample gene set enrichment analysis and ESTIMATE to assess the tumor microenvironment (TME) in different subgroups. We conducted a functional analysis of differentially expressed genes between subgroups, which involved gene ontology, the Kyoto encyclopedia of genes and genomes, and gene set variation analysis, in order to elucidate their functional status. Prognostic risk models were developed using univariate Cox regression and the least absolute shrinkage and selection operator regression. Additionally, single-cell clustering and cell communication analysis were conducted to enhance the understanding of the importance of signature genes. Lastly, qRT-PCR was employed to validate the prognostic model.

Results
Two clearly defined DRG clusters were identified through a consensus-based, unsupervised clustering analysis. Observations were made concerning the correlation between changes in multilayer DRG and various clinical characteristics, prognosis, and the infiltration of TME cells. A well-executed risk assessment model, known as the DRG score, was developed to predict the prognosis of LUAD patients. A high DRG score indicates increased TME cell infiltration, a higher mutation burden, elevated TME scores, and a poorer prognosis. Additionally, the DRG score showed a significant correlation with the tumor mutation burden score and the tumor immune dysfunction and exclusion score. Subsequently, a nomogram was established for facilitating the clinical application of the DRG score, showing good predictive ability and calibration. Additionally, crucial DRGs were further validated by single-cell sequencing data. Finally, crucial DRGs were further validated by qRT-PCR and immunohistochemistry.

Conclusion
Our new DRG signature risk score can predict the immune landscape and prognosis of LUAD. It also serves as a reference for LUAD's immunotherapy and chemotherapy.
Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters
Authors: Wen Youjia , Song Zuhua , Li Qian , Zhang Dan , Li Xiaojiao , Yu Jiayi , Li Zongwen , Ren Xiaofang , Zhang Jiayan , Liu Qian , Huang Jie , Zeng Dan , Tang Zhuoyue 
Published: February 2024

Abstract
Objective
To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC).

Materials and methods
Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT–Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve.

Results
Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT–Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT–Radiology nomogram was established based on the DECT–Radiology model, which showed the highest net benefit and satisfactory consistency.

Conclusions
The DECT–Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients.

Critical relevance statement
The DECT–Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression.

Key points
• Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC).
• The DECT–Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression.
• The nomogram may help screen out PDAC patients with high Ki-67 expression.

Graphical Abstract
Deep learning enables the quantification of browning capacity of human adipose samples
Authors: Wang Yuxin , Zuo Shiman , Yang Nanfei , Jian Ani , Zheng Wei , Hua Zichun , Shen Pingping 
Published: February 2024

Abstract
Background
The recruitment of thermogenic adipocytes in human fat depots markedly improves metabolic disorders such as type 2 diabetes mellitus (T2DM). However, identification and quantification of thermogenic cells in human fats, especially in metabolic disorders patients, remains a major challenge. Here, we aim to provide a stringent validation of human thermogenic adipocyte signature genes, and construct transcriptome-based models to quantify the browning degree of human fats.

Methods
Evidence from RNA-seq, microarray analyses and experimental approaches were integrated to isolate robust human brown-like fat signature genes. Meta-analysis was employed to validate the performance of known human brown-like fat marker genes. Autoencoder was used to reveal the browning levels of human adipose samples for supervised machine learning. Ensemble machine learning was applied to devised molecular metrics for quantifying browning degree of human fats. Obesity and T2DM datasets were used to validate the performance of the molecular metrics in adipose-related metabolic disorders.

Results
Human brown-like adipocytes were heterogeneous populations which showed distinct transcriptional patterns and biological features. Only DHRS11, REEP6 and STX11 were robust signature genes that were consistently up-regulated in different human brown-like fats, especially in creatine-induced UCP1-independent adipocytes. The molecular metrices based on the expression patterns of the three signature genes, named human browning capacity index (HBI) and absolute HBI (absHBI), were superior to 26 traditional human brown-like fat marker genes and previously reported browning classifier in prediction of browning levels of human adipocytes and adipose tissues as well as primary cell cultures upon various physiological and pharmacological stimuli. Notably, these molecular metrics also reflected the insulin sensitivity and glucose-lipid metabolic activity of human adipose samples from obesity and T2DM patients.

Conclusions
In summary, this study provides promising signatures and computational tools for evaluating browning levels of human adipose samples in response to physiological and medical intervention. The metrices construction pipeline provides an alternative approach for training machine learning models using unlabeled samples.
The Mental Health of Elite-Level Coaches: A Systematic Scoping Review
Authors: Frost Joshua , Walton Courtney C. , Purcell Rosemary , Fisher Krista , Gwyther Kate , Kocherginsky Michael , Rice Simon M. 
Published: February 2024

Abstract
Background
Elite-level coaches are exposed to multiple performance, organisational and personal stressors which may contribute to reduced mental health and wellbeing. This systematic scoping review examined the current body of evidence to explore what is known about the mental health of elite-level coaches (i.e. wellbeing and mental ill-health), the risk and protective factors that influence coach mental health, and the relationship between mental health and coaching effectiveness.

Methods
The review adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A systematic search was undertaken and updated in September 2022 using six electronic databases.

Results
12,376 studies were identified and screened, with 42 studies satisfying the inclusion criteria. Despite the paucity of high-quality research, findings indicated that 40% of the included studies examined themes connected to wellbeing, with 76% assessing the nature or prevalence of mental ill-health in elite-level coaches. Among studies exploring mental ill-health, coach burnout was the primary focus, while scant research examined symptoms associated with clinical disorders (e.g. anxiety and depression). Overall, psychological outcomes for elite-level coaches were shaped by risk and protective factors operating at the individual, interpersonal, organisational and societal level. Preliminary evidence was also found to suggest that poor mental health may contribute to reduced coaching effectiveness. It is proposed that coaching effectiveness could therefore be employed as a ‘hook’ to engage elite-level coaches in greater consideration of their mental health needs.

Conclusion
Alongside the development of methodologically robust research, there is a need to examine dynamic individual (e.g. psychological skills), interpersonal (e.g. strong social supports) and organisational (e.g. workload) factors that aim to preserve the mental health and optimise the efficacy of elite-level coaches.
A deep learning approach for projection and body-side classification in musculoskeletal radiographs
Authors: Fink Anna , Tran Hien , Reisert Marco , Rau Alexander , Bayer Jörg , Kotter Elmar , Bamberg Fabian , Russe Maximilian F. 
Published: February 2024

Abstract
Background
The growing prevalence of musculoskeletal diseases increases radiologic workload, highlighting the need for optimized workflow management and automated metadata classification systems. We developed a large-scale, well-characterized dataset of musculoskeletal radiographs and trained deep learning neural networks to classify radiographic projection and body side.

Methods
In this IRB-approved retrospective single-center study, a dataset of musculoskeletal radiographs from 2011 to 2019 was retrieved and manually labeled for one of 45 possible radiographic projections and the depicted body side. Two classification networks were trained for the respective tasks using the Xception architecture with a custom network top and pretrained weights. Performance was evaluated on a hold-out test sample, and gradient-weighted class activation mapping (Grad-CAM) heatmaps were computed to visualize the influential image regions for network predictions.

Results
A total of 13,098 studies comprising 23,663 radiographs were included with a patient-level dataset split, resulting in 19,183 training, 2,145 validation, and 2,335 test images. Focusing on paired body regions, training for side detection included 16,319 radiographs (13,284 training, 1,443 validation, and 1,592 test images). The models achieved an overall accuracy of 0.975 for projection and 0.976 for body-side classification on the respective hold-out test sample. Errors were primarily observed in projections with seamless anatomical transitions or non-orthograde adjustment techniques.

Conclusions
The deep learning neural networks demonstrated excellent performance in classifying radiographic projection and body side across a wide range of musculoskeletal radiographs. These networks have the potential to serve as presorting algorithms, optimizing radiologic workflow and enhancing patient care.

Relevance statement
The developed networks excel at classifying musculoskeletal radiographs, providing valuable tools for research data extraction, standardized image sorting, and minimizing misclassifications in artificial intelligence systems, ultimately enhancing radiology workflow efficiency and patient care.

Key points
• A large-scale, well-characterized dataset was developed, covering a broad spectrum of musculoskeletal radiographs.
• Deep learning neural networks achieved high accuracy in classifying radiographic projection and body side.
• Grad-CAM heatmaps provided insight into network decisions, contributing to their interpretability and trustworthiness.
• The trained models can help optimize radiologic workflow and manage large amounts of data.

Graphical Abstract
The association of p21, inhibin, and Tob-1 expression with the clinicopathological characteristics of benign and malignant colorectal lesions
Authors: Moussa Mona , Abdullah Aya Mohamed , Youssef Mohieldin Magdy , Elwi Dalal , Helal Noha Said 
Published: February 2024

Abstract
Background
Worldwide, colorectal cancer (CRC) is the third most common cancer and the second most common cause of cancer-related deaths. p21, inhibin, and Tob-1 are tumor suppressors that play a role in the development and progression of several cancers, however, their role in CRC is not well-established. This study aims to evaluate the expression of these proteins by immunohistochemistry and correlate their expression with the clinicopathological characteristics of CRCs and preneoplastic lesions [adenomas and ulcerative colitis] to study the potential for their use as targeted therapies. The study was performed on sections of 30 CRCs, 30 adenomas, 30 UC, 30 chronic colitis, and 20 controls.

Results
p21 expression was lower in CRCs and adenomas compared to inflammatory lesions (chronic colitis and UC). High-grade CRCs, adenomas with high-grade dysplasia, and UC with dysplasia showed insignificantly lower expression compared to their counterparts. Inhibin expression was absent in CRCs; however, its expression was higher in chronic colitis than in UC and adenomas. Adenomas with high-grade dysplasia and UC with dysplasia showed insignificantly higher expression than their counterparts. Tob-1 expression increased significantly from chronic colitis to UC to adenomas to CRCs. High-grade CRCs, adenomas with high-grade dysplasia, and UC with dysplasia showed higher expression compared to their counterparts.

Conclusions
Decreased p21 and increased inhibin and Tob-1 expressions are associated with the progression of adenomas and UC to more dysplastic lesions, then possibly to CRC. Despite being tumor suppressors, the studied proteins may potentially have tumor-promoting properties. They can be useful targets for therapeutic intervention.
A Quantitative Assessment of ChatGPT as a Neurosurgical Triaging Tool
Authors: Ward Max , Unadkat Prashin , Toscano Daniel , Kashanian Alon , Lynch Daniel G. , Horn Alexander C. , D'Amico Randy S. , Mittler Mark , Baum Griffin R. 
Published: February 2024

BACKGROUND AND OBJECTIVES:
ChatGPT is a natural language processing chatbot with increasing applicability to the medical workflow. Although ChatGPT has been shown to be capable of passing the American Board of Neurological Surgery board examination, there has never been an evaluation of the chatbot in triaging and diagnosing novel neurosurgical scenarios without defined answer choices. In this study, we assess ChatGPT’s capability to determine the emergent nature of neurosurgical scenarios and make diagnoses based on information one would find in a neurosurgical consult.

METHODS:
Thirty clinical scenarios were given to 3 attendings, 4 residents, 2 physician assistants, and 2 subinterns. Participants were asked to determine if the scenario constituted an urgent neurosurgical consultation and what the most likely diagnosis was. Attending responses provided a consensus to use as the answer key. Generative pretraining transformer (GPT) 3.5 and GPT 4 were given the same questions, and their responses were compared with the other participants.

RESULTS:
GPT 4 was 100% accurate in both diagnosis and triage of the scenarios. GPT 3.5 had an accuracy of 92.59%, slightly below that of a PGY1 (96.3%), an 88.24% sensitivity, 100% specificity, 100% positive predictive value, and 83.3% negative predicative value in triaging each situation. When making a diagnosis, GPT 3.5 had an accuracy of 92.59%, which was higher than the subinterns and similar to resident responders.

CONCLUSION:
GPT 4 is able to diagnose and triage neurosurgical scenarios at the level of a senior neurosurgical resident. There has been a clear improvement between GPT 3.5 and 4. It is likely that the recent updates in internet access and directing the functionality of ChatGPT will further improve its utility in neurosurgical triage.
THE CULTURAL HERITAGE OF THE OLD BELIEVERS IN THE SOCIO-CULTURAL SPACE OF TRANSBAIKALIA
Authors: Mishina Tatiana V. , Kondakova Natalia S. 
Published: February 2024

Background. The socio-cultural space of Transbaikalia is represented by a wide ethno-cultural diversity, which was formed historically under the influence of various factors. Subsequently, each of the cultures that appeared in Transbaikalia contributed to the cultural space of the region. However, today there is a change in the importance of traditional cultures, new values appear that are more in demand in modern conditions, hence the loss of traditional culture, the disappearance of cultural heritage. The issue of preservation and transmission of traditional culture is becoming urgent.
In the context of the analysis of cultural heritage, the concepts of M. Halbvaks, E. Hobsbaum, P. Nor, G. Peckham, Lisitsky A.V., Mamaeva O.B., Kuchmaeva V.A., Kopsergenova A.A. are studied. Old Believers in Transbaikalia were studied by Bolonev F.F., Gavrilova E.A. et al.
Materials and methods. The appeal to theoretical concepts in the field of cultural heritage shows the close interconnectedness of cultural heritage and memory. The concepts of M. Halbwax, E. Hobsbawm, P. Nor, G. Peckham, Lisitsky A.V., Mamaeva O.B., Kuchmaeva V.A., Kopsergenova A.A. fix the interdependence of cultural heritage and cultural memory. The work uses general scientific methods: analysis, synthesis, comparison.
Results and conclusions. Cultural heritage, while remaining “alive”, allows it to be reproduced and remains relevant in modern times, however, the transformation of heritage into memory leads to its restoration, the invention of tradition, consolidation in places of memory, restoration due to demand in the field of economics and tourism. Within the framework of state projects, tourist requests, there is a revival of this tradition in folklore, material elements, but the question remains open about the revival of the spiritual tradition of the Old Believers.