bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilizing 3D Printing for the Surgical Management of Orbital Floor Fractures
Authors: Mukai Sakurako , Tsuge Takuya , Akaishi Satoshi , Ogawa Rei , Kuwahara Hiroaki 
Published: November 2023

Summary:
We present a technique for treating orbital floor fractures using three-dimensional (3D) printing technology and a preoperative template based on the mirror image of the unaffected orbit. Our patient, a 56-year-old man, experienced persistent diplopia in the upward direction and left enophthalmos after previous open reduction internal fixation surgery. To address these complications, we used a simulation of the ideal orbital floor from computed tomography images and used a 3D printer to create a template. Subsequently, an absorbable plate was molded intraoperatively based on this template. Notably, the plate fit seamlessly into the fracture site without requiring any adjustment, reducing the operation time. Postoperative computed tomography scans confirmed successful reduction, improved visual function, and the absence of complications. Our method offers a precise and efficient approach to reconstructing fractured orbital floors. By leveraging 3D printing technology and preoperative templates, surgeons can enhance postoperative outcomes and minimize patient burden. Further investigations are warranted to assess the long-term effectiveness and cost-effectiveness of this technique. Our findings highlight the potential of this approach to improve treatment strategies for patients with orbital floor fractures.
Incorporation of protein induced by vitamin K absence or antagonist-II into transplant criteria expands beneficiaries of liver transplantation for hepatocellular carcinoma: A multi-center retrospective cohort study in China
Authors: Wang Kai , Dong Libin , Lu Qian , Yang Zhe , Fan Xiaoli , Gao Fengqiang , Ge Wenwen , Wang Zhoucheng , Zhou Zhisheng , Lu Di , Wei Xuyong , Wei Qiang , Zhuang Li , Qin Lunxiu , Ye Qifa , Yang Jiayin , Dong Jiahong , Zheng Shusen , Xu Xiao 
Published: November 2023

Introduction:
In order to maximize the utilization of precious donor liver, precisely determining potential hepatocellular carcinoma (HCC) candidates who will benefit from liver transplantation (LT) is essential. As a crucial diagnostic biomarker for HCC, protein induced by vitamin K absence or antagonist-II (PIVKA-II) has become one of the key indicators for assessing tumor recurrence risk after LT. This study aims to investigate the role of PIVKA-II in recipient selection and prognostic stratification.

Methods:
The clinicopathologic data of HCC patients undergoing LT from 2015 to 2020 in 6 Chinese transplant centers were collected. Univariate and multivariate analyses were performed to determine risk factors for disease-free survival (DFS). Based on these risk factors, survival analysis was made by Kaplan-Meier method and their value in prognostic stratification was assessed.

Results:
A total of 522 eligible HCC patients with pre-LT PIVKA-II records were finally included in this study. Tumor burden>8 cm, AFP>400 ng/mL, histopathologic grade III and PIVKA-II>240 mAU/mL were identified as independent risk factors for DFS. DFS of patients with PIVKA-II≤240 mAU/mL (N=288) were significantly higher than those with PIVKA-II>240 mAU/mL (N=234) (1-, 3- and 5-year DFS: 83.2%, 77.3% and 75.9% vs. 75.1%, 58.5% and 50.5%; P<0.001). Compared with Hangzhou criteria (N=305), incorporating PIVKA-II into Hangzhou criteria (including tumor burden, AFP, histopathologic grade) increased the number of patients with eligibility for LT by 21.6% but achieved comparable DFS and OS.

Conclusions:
Incorporating PIVKA-II into existing LT criteria could increase the number of eligible HCC patients without compromising post-LT outcomes.
Artificial intelligence-aided detection for prostate cancer with multi-modal routine health check-up data: an Asian multi-center study
Authors: Song Zijian , Zhang Wei , Jiang Qingchao , Deng Longxin , Du Le , Mou Weiming , Lai Yancheng , Zhang Wenhui , Yang Yang , Jasmine Lim , Liu Kang , Park Jae Young , Chi-Fai Ng , Aik Ong Teng , Wei Qiang , Li Lei , Wei Xuedong , Chen Ming , Cao Zhixing , Wang Fubo , Chen Rui 
Published: November 2023

Background:
The early detection of high-grade prostate cancer (HGPCa) is of great importance. However, the current detection strategies result in a high rate of negative biopsies and high medical costs. In this study, we aimed to establish an Asian Prostate Cancer Artificial intelligence (APCA) score with no extra cost other than routine health check-ups to predict the risk of HGPCa.

Patients and methods:
A total of 7476 patients with routine health checkup data who underwent prostate biopsies from January 2008 to December 2021 in eight referral centers in Asia were screened. After data pre-processing and cleaning, 5037 patients and 117 features were analyzed. Seven AI-based algorithms were tested for feature selection and seven AI-based algorithms were tested for classification, with the best combination applied for model construction. The APAC score was established in the CH cohort and validated in a multi-center cohort and in each validation cohort to evaluate its generalizability in different Asian regions. The performance of the models was evaluated using area under the receiver operating characteristic curve (ROC), calibration plot, and decision curve analyses.

Results:
Eighteen features were involved in the APCA score predicting HGPCa, with some of these markers not previously used in prostate cancer diagnosis. The area under the curve (AUC) was 0.76 (95% CI:0.74-0.78) in the multi-center validation cohort and the increment of AUC (APCA vs. PSA) was 0.16 (95% CI:0.13-0.20). The calibration plots yielded a high degree of coherence and the decision curve analysis yielded a higher net clinical benefit. Applying the APCA score could reduce unnecessary biopsies by 20.2% and 38.4%, at the risk of missing 5.0% and 10.0% of HGPCa cases in the multi-center validation cohort, respectively.

Conclusions:
The APCA score based on routine health checkups could reduce unnecessary prostate biopsies without additional examinations in Asian populations. Further prospective population-based studies are warranted to confirm these results.
Comparison of the postoperative outcome with and without intraoperative leak testing for sleeve gastrectomy: a systematic review and meta-analysis of 469,588 cases
Authors: Ma Longyin , Gao Zhenguo , Luo Heng , Kou Shien , Lei Yu , Jia Victor , Lan Ke , Sankar Subbiah , Hu Jiani , Tian Yunhong 
Published: November 2023

Objective:
Postoperative staple line leakage after sleeve gastrectomy is a rare but serious complication. Many surgeons routinely test anastomosis with an intraoperative leak test as part of the sleeve gastrectomy procedure. This meta-analysis aims to determine whether an intraoperative leak test plays a role in reducing the rate of postoperative staple line related complications in patients who underwent sleeve gastrectomy.

Methods:
We searched the PubMed, Web of science, the Cochrane Library and Clinical Trials.gov databases for clinical studies assessing the application of intraoperative leak test (IOLT) in sleeve gastrectomy. The primary endpoint was the development of postoperative staple line leakage. Secondary endpoints included the postoperative bleeding, 30 days mortality rates, and 30 days readmission rates.

Results:
Six studies totaling 469,588 patients met the inclusion criteria. Our review found that the Staple line leakage (SLL) rate was 0.38% (1,221/ 324,264) in the IOLT group and 0.31% (453/ 145,324) in the no intraoperative leak test (NIOLT) group. Postoperative staple line leakage decreased in the NIOLT group compared with the IOLT group (OR=1.27; 95%CI 1.14 to 1.42, P=0.000). Postoperative bleeding was fewer in the IOLT group than that in the NIOLT group (OR 0.79; 95% CI 0.72 to 0.87, P=0.000). There was no significant difference between the IOLT group and the NIOLT group regarding 30 days mortality rates and 30 days readmission rates (P＞0.05).

Conclusion:
IOLT was correlated with an increase in staple line leakage when included as a part of the sleeve gastrectomy procedure. However, IOLT was associated with a lower rate of postoperative bleeding. Thus, IOLT should be considered in sleeve gastrectomy in the situation of suspected postoperative bleeding.
Effect of endometrial thickness on the risk of ectopic pregnancy for frozen embryo transfer
Authors: Huang Li-Juan , Zheng Qu , Wang Xue-Jiao , Zhong Zhao-Hui , Fu Li-Juan , Lv Xing-Yu , Geng Li-Hong , Tang Xiao-Jun , Ding Yu-Bin , Wan Qi 
Published: November 2023

Objective:
Few studies have explored the suitability of endometrial thickness (EMT) as a predictor of ectopic pregnancy (EP) in frozen embryo transfer (FET) cycles. Our study aimed to investigate the association between EMT and EP and explore the cutoff value of EMT to predict EP.

Methods:
This retrospective cohort study included women aged 20–45 years undergoing FET between March 2015 and September 2021. The primary outcomes and measured variables were EP and EMT, respectively. The threshold effect of EMT on EP was calculated based on a constructed smooth curve fitting. The patients were divided into two groups based on the threshold for comparison. A subgroup analysis was conducted to examine whether the relationship between EMT and EP remained consistent across the different subgroups. Additionally, a generalized linear model was used to analyze the interactions between the treatment factors and EMT in EP.

Results:
In total, 27,549 FET cycles were included, with 27,086 intrauterine and 463 ectopic pregnancies. The risk of EP in the EMT ≤8.7 mm group was 3.36 times higher than that in the EMT >8.7 mm group (odds ratio [OR]: 3.36, 95% confidence interval [CI]: 2.57–4.05). Subgroup analysis further indicated that a thin EMT was a risk factor for EP, independent of other risks. We also noted that diminished ovarian reserve, tubal factor infertility, transfer of two embryos, or transfer of cleavage-stage embryos may further enhance the risk of EP in patients with thin endometrium.

Conclusions:
Thin endometrium was associated with an increased risk of EP. Patients with EMT less than 8.7 mm need close medical observation and management after embryo transfer. In addition, diminished ovarian reserve, tubal factor infertility, transfer of two embryos, or transfer of cleavage-stage embryos may significantly enhance the effect of a thin endometrium on the risk of EP.
DARDN: A deep-learning approach for CTCF binding sequence classification and oncogenic regulatory feature discovery
Authors: Cho Hyun Jae , Wang Zhenjia , Cong Yidan , Bekiranov Stefan , Zhang Aidong , Zang Chongzhi 
Published: November 2023

AbstractCharacterization of gene regulatory mechanisms in cancer is a key task in cancer genomics. CCCTC-binding factor (CTCF), a DNA binding protein, exhibits specific binding patterns in the genome of cancer cells and has a non-canonical function to facilitate oncogenic transcription programs by cooperating with transcription factors bound at flanking distal regions. Identification of DNA sequence features from a broad genomic region that distinguish cancer-specific CTCF binding sites from regular CTCF binding sites can help find oncogenic transcription factors in a cancer type. However, the long DNA sequences without localization information makes it difficult to perform conventional motif analysis. Here we present DNAResDualNet (DARDN), a computational method that utilizes convolutional neural networks (CNNs) for predicting cancer-specific CTCF binding sites from long DNA sequences and employs DeepLIFT, a method for interpretability of deep learning models that explains the model’s output in terms of the contributions of its input features [1], for identifying DNA sequence features associated with cancer-specific CTCF binding. Evaluation on DNA sequences associated with CTCF binding sites in T-cell acute lymphoblastic leukemia (T-ALL) and other cancer types demonstrates DARDN’s ability in classifying DNA sequences surrounding cancer-specific CTCF binding from control constitutive CTCF binding and identifying sequence motifs for transcription factors potentially active in each specific cancer type. We identified potential oncogenic transcription factors in T-ALL, acute myeloid leukemia (AML), breast cancer (BRCA), colorectal cancer (CRC), lung adenocarcinoma (LUAD), and prostate cancer (PRAD). Our work demonstrates the power of advanced machine learning and feature discovery approach in finding biologically meaningful information from complex high-throughput sequencing data.
Structural basis for polyuridine tract recognition by SARS-CoV-2 Nsp15
Authors: Ito Fumiaki , Yang Hanjing , Zhou Z. Hong , Chen Xiaojiang S. 
Published: November 2023

AbstractSARS-CoV-2 non-structural protein 15 (Nsp15) is critical for productive viral replication and evasion of host immunity. The uridine-specific endoribonuclease activity of Nsp15 mediates the cleavage of the polyuridine [poly(U)] tract of the negative-strand coronavirus genome to minimize the formation of dsRNA that activates the host antiviral interferon signaling. However, the molecular basis for the recognition and cleavage of the poly(U) tract by Nsp15 is incompletely understood. Here, we present cryogenic electron microscopy (cryoEM) structures of SARS-CoV-2 Nsp15 bound to viral replication intermediate dsRNA containing poly(U) tract at 2.7-3.3 Å resolution. The structures reveal one copy of dsRNA binds to the sidewall of an Nsp15 homohexamer, spanning three subunits in two distinct binding states. The target uracil is dislodged from the base-pairing of the dsRNA by amino acid residues W332 and M330 of Nsp15, and the dislodged base is entrapped at the endonuclease active site center. Up to 20 A/U base pairs are anchored on the Nsp15 hexamer, which explains the basis for a substantially shortened poly(U) sequence in the negative strand coronavirus genome compared to the long poly(A) tail in its positive strand. Our results provide mechanistic insights into the unique immune evasion strategy employed by coronavirus Nsp15.
2D versus 3D artificial intelligence-driven segmentations of airway alterations in cystic fibrosis: which one is better?
Authors: Bouzid Imene Hadj , Benlala Ilyes , Dournes Gael 
Published: November 2023

AbstractPurpose or Learning ObjectiveArtificial intelligence (AI) with convolutional neural network allows fully automated detection and segmentation of bronchial changes on CT-scans of cystic fibrosis (CF). However, the superiority of two-dimensional (2D) versus three-dimensional (3D) architectures remains to be explored.Method or BackgroundCT-scans from fifty CF patients were retrospectively included at two CF reference centers. The nnUnet model was implemented in both 2D and 3D, and trained to segment five structural alterations: bronchiectasis, wall thickening, mucus plugs, bronchiolar impactions and consolidations. A semantic validation was done by using fifty CTs with a five-fold cross validation strategy, by comparing normalized Dice-Sorensen coefficient (DSC) between 2D and 3D architectures, with manual segmentations as Gold Standard.Results or FindingsThe 3D nnUnet was found able to segment the five CF main hallmarks such as bronchiectasis, wall thickening, mucus plugs, bronchiolar impactions and consolidations. Metrics obtained with the 3D architecture were superior for mucus plugs, bronchiolar impactions and consolidations (p<0.001) but not significantly different for bronchiectasis and wall thickening (p>0.05).ConclusionAI with the 3D-nnUnet model can perform fully automated segmentation of CF-related structural hallmarks on CT scans, and overcome 2D implementation. Non-invasive, holistic 3D quantifications are allowed for promising next clinical applications.
Mapping Cerebellar Anatomical Heterogeneity in Mental and Neurological Illnesses
Authors: Kim Milin , Leonardsen Esten , Rutherford Saige , Selbæk Geir , Persson Karin , Steen Nils Eiel , Smeland Olav B. , Ueland Torill , Richard Geneviève , Beckmann Christian F. , Marquand Andre F. ,   Alzheimer’s Disease Neuroimaging Initiative (ADNI), Andreassen Ole A. , Westlye Lars T. , Wolfers Thomas , Moberget Torgeir 
Published: November 2023

AbstractThe cerebellum has been linked to motor coordination, cognitive and affective processing, in addition to a wide range of clinical illnesses. To enable robust quantification of individual cerebellar anatomy relative to population norms, we mapped the normative development and aging of the cerebellum across the lifespan using brain scans of > 54k participants. We estimated normative models at voxel-wise spatial precision, enabling integration with cerebellar atlases. Applying the normative models in independent samples revealed substantial heterogeneity within five clinical illnesses: autism spectrum disorder, mild cognitive impairment, Alzheimer’s disease, bipolar disorder, and schizophrenia. Notably, individuals with autism spectrum disorder and mild cognitive impairment exhibited increased numbers of both positive and negative extreme deviations in cerebellar anatomy, while schizophrenia and Alzheimer’s disease predominantly showed negative deviations. Finally, extreme deviations were associated with cognitive scores. Our results provide a voxel-wise mapping of cerebellar anatomy across the human lifespan and clinical illnesses, demonstrating cerebellum’s nuanced role in shaping human neurodiversity across the lifespan and in different clinical illnesses.
Imaging intracellular componentsin situusing super-resolution cryo-correlative light and electron microscopy
Authors: Last Mart G. F. , Voortman Lenard M. , Sharp Thomas H. 
Published: November 2023

AbstractSuper-resolution cryo-correlative light and electron microscopy (SRcryoCLEM) is emerging as a powerful method to enable targetedin situstructural studies of biological samples. By combining the high specificity and localization accuracy of single-molecule localization microscopy (cryoSMLM) with the high resolution of cryo-electron tomography (cryoET), this method enables accurately targeted data acquisition and the observation and identification of biomolecules within their natural cellular context. Despite its potential, the adaptation of SRcryoCLEM has been hindered by the need for specialized equipment and expertise. In this chapter, we outline a workflow for cryoSMLM and cryoET-based SRcryoCLEM, and we demonstrate that, given the right tools, it is possible to incorporate cryoSMLM into an established cryoET workflow. Using Vimentin as an exemplary target of interest, we exemplify all stages of an SRcryoCLEM experiment: performing cryoSMLM, targeting cryoET acquisition based single-molecule localization maps, and correlation of cryoSMLM and cryoET datasets using scNodes, a software package dedicated to SRcryoCLEM. By showing how SRcryoCLEM enables the imaging of specific intracellular components in situ, we hope to facilitate the further adaptation of the technique within the field of cryoEM.
Practical Bayesian Inference in Neuroscience: Or How I Learned To Stop Worrying and Embrace the Distribution
Authors: Coventry Brandon S , Bartlett Edward L 
Published: November 2023

ABSTRACTTypical statistical practices in the biological sciences have been increasingly called into question due to difficulties in replication of an increasing number of studies, many of which are confounded by the relative difficulty of null significance hypothesis testing designs and interpretation of p-values. Bayesian inference, representing a fundamentally different approach to hypothesis testing, is receiving renewed interest as a potential alternative or complement to traditional null significance hypothesis testing due to its ease of interpretation and explicit declarations of prior assumptions. Bayesian models are more mathematically complex than equivalent frequentist approaches, which have historically limited applications to simplified analysis cases. However, the advent of probability distribution sampling tools with exponential increases in computational power now allows for quick and robust inference under any distribution of data. Here we present a practical tutorial on the use of Bayesian inference in the context of neuroscientific studies. We first start with an intuitive discussion of Bayes’ rule and inference followed by the formulation of Bayesian-based regression and ANOVA models using data from a variety of neuroscientific studies. We show how Bayesian inference leads to easily interpretable analysis of data while providing an open-source toolbox to facilitate the use of Bayesian tools.Significance StatementBayesian inference has received renewed interest as an alternative to null-significance hypothesis testing for its interpretability, ability to incorporate prior knowledge into current inference, and robust model comparison paradigms. Despite this renewed interest, discussions of Bayesian inference are often obfuscated by undue mathematical complexity and misunderstandings underlying the Bayesian inference process. In this article, we aim to empower neuroscientists to adopt Bayesian statistical inference by providing a practical methodological walkthrough using single and multi-unit recordings from the rodent auditory circuit accompanied by a well-documented and user-friendly toolkit containing regression and ANOVA statistical models commonly encountered in neuroscience.
Establishment and comprehensive characterization of a novel dark-reared zebrafish model for myopia studies
Authors: Xie Jiaheng , Goodbourn Patrick T. , Bui Bang V. , Jusuf Patricia R. 
Published: November 2023

AbstractPurposeMyopia is predicted to impact approximately 5 billion people by 2050, necessitating mechanistic understanding of its development. Myopia results from dysregulated genetic mechanisms of emmetropization, caused by over-exposure to aberrant visual environments; however, these genetic mechanisms remain unclear. Recent human genome-wide association studies have identified a range of novel myopia-risk genes. To facilitate large-scalein vivomechanistic examination of gene-environment interactions, this study aims to establish a myopia model platform that allows efficient environmental and genetic manipulations.MethodsWe established an environmental zebrafish myopia model by dark-rearing. Ocular biometrics including relative ocular refraction were quantified using optical coherence tomography images. Spatial vision was assessed using optomotor response (OMR). Retinal function was analyzed via electroretinography (ERG). Myopia-associated molecular contents or distributions were examined using RT-qPCR or immunohistochemistry.ResultsOur model produces robust phenotypic changes, showing myopia after 2 weeks of dark-rearing, which were recoverable within 2 weeks after returning animals to normal lighting. 2-week dark-reared zebrafish have reduced spatial-frequency tuning function. ERG showed reduced photoreceptor and bipolar cell function (a- andb-waves) after only 2 days of dark-rearing, which worsened after 2 weeks of dark-rearing. We also found dark-rearing-induced changes to expression of myopia-risk genes, includingegr1, vegfaa, vegfab, rbp3, gjd2aandgjd2b, inner retinal distribution of EFEMP1, TIMP2 and MMP2, as well as transiently reduced PSD95 density in the inner plexiform layer.ConclusionsCoupled with the gene editing tools available for zebrafish, our environmental myopia model provides an excellent platform for large-scale investigation of gene-environment interactions in myopia development.