bluuebunny/crossref_metadata_2025_split huggingface dataset:
Scale-up of 99DOTS for tuberculosis treatment supervision in Uganda: An interrupted time series analysis
Authors: Crowder Rebecca , Nakasendwa Suzan , Kityamuwesi Alex , Musoke Muhammad , Nannozi Joyce , Waswa Joseph , Sanyu Agnes Nakate , Lamunu Maureen , Twinamasiko Amon , Tinka Lynn Kunihira , Oyuku Denis , Babirye Diana , Berger Christopher , Thompson Ryan , Turyahabwe Stavia , Dowdy David , Katamba Achilles , Cattamanchi Adithya , Kiwanuka Noah 
Published: January 2024

ABSTRACTBackgroundDigital adherence technologies like 99DOTS are being scaled-up for tuberculosis (TB) treatment despite limited evidence of their effectiveness and concerns about accessibility. We evaluated the reach and effectiveness of 99DOTS during its scale-up in Uganda.MethodsWe included all adults initiating drug-susceptible pulmonary TB treatment between August 2019 and June 2021 at 12 99DOTS-naïve health facilities (n=3,526). Using an interrupted time series design, we compared the proportion with treatment success (primary outcome) and enrolled on 99DOTS in the 9 months before and 12 months after implementing an ‘enhanced 99DOTS’ intervention. This included providing low-cost phones to people with TB when needed, task shifting monitoring and support to community health workers, and automated task lists. Treatment data were derived from routine TB treatment registers.ResultsThe proportion enrolled on 99DOTS post-intervention was high (87.2%) and had a slight upward trend (proportion ratio 1.01, 95% CI 1.00-1.01). Treatment completion remained similar across periods (89.8% post-intervention vs. 87.1% pre-intervention). There was no immediate level or slope change in treatment success following the intervention.ConclusionsWith appropriate implementation supports, 99DOTS can have high uptake without negatively impacting treatment outcomes. Equity in access should be prioritized during implementation
Machine Learning-Based Prediction of Pediatric Ulcerative Colitis Treatment Response using Diagnostic Histopathology
Authors: Liu Xiaoxuan , Walters Thomas , Siddiqui Iram , Lopez-Nunez Oscar , Prasath Surya , Denson Lee A ,   PROTECT consortium, Dhaliwal Jasbir 
Published: January 2024

ABSTRACTBackground and AimsWe previously reported clinical features associated with outcomes in pediatric ulcerative colitis (UC). Here we developed a histopathology model to predict corticosteroid-free remission (CSFR) on mesalamine therapy alone.MethodsPre-treatment rectal biopsy slides were digitized in training and validation groups of 292 and 113 pediatric UC patients, respectively. Whole slide images (WSI) underwent pre-processing. Thirteen machine learning (ML) models were trained using 250 histomic features including texture, color, histogram, and nuclei. Feature importance was determined by the Gini index with the classifier re-trained using the top features.Results187571 informative patches from 292 training group patients (Male:53%; Age:13y (IQR:11-15); CSFR:41%) were trained on 13 ML classifiers. The best model was random forest (RF). Eighteen optimal histomic features were identified and trained, and the corresponding WSI AUROC was 0.89 (95%CI:0.71, 0.96), accuracy of 90% for CSFR. Features were re-trained on an independent real-world dataset of 113 patients and the model WSI AUROC was 0.85 (95%CI:0.75, 0.95), accuracy of 85%.ConclusionRoutine histopathology obtained at diagnosis contains histomic features associated with UC treatment response.
Artificial intelligence-enabled reconstruction of the right ventricular pressure curve using the peak pressure value: a proof-of-concept study
Authors: Szijártó Ádám , Nicoara Alina , Podgoreanu Mihai , Tokodi Márton , Fábián Alexandra , Merkely Béla , Sárkány András , Tősér Zoltán , Lakatos Bálint , Kovács Attila 
Published: January 2024

AbstractConventional echocardiographic parameters of right ventricular (RV) function are heavily afterload-dependent. Therefore, the incorporation of the RV pressure curve may enable the formulation of new parameters that reflect intrinsic RV function more accurately. Accordingly, we sought to develop an artificial intelligence-based method that can reconstruct the RV pressure curve based on the peak RV pressure.We invasively acquired RV pressure in 29 heart failure patients before and after the implantation of a left ventricular (LV) assist device. Using these tracings, we trained various machine learning models to reconstruct the RV pressure curve of the entire cardiac cycle solely based on the peak value of the invasively acquired curve. The best-performing model was compared with the performance of two other methods that estimated RV pressure curves based on a reference LV and RV pressure curve, respectively.Among the evaluated algorithms, the multilayer perceptron (MLP) achieved the best performance with an R2of 0.887 [0.834 – 0.941]. The RV and LV reference curve-based methods achieved R2values of 0.879 [0.815 – 0.943] and 0.636 [0.500 – 0.771], respectively. The MLP and the RV reference curve-based estimation showed good agreement with the invasive RV pressure curves (mean bias: -0.38 mmHg and -0.73 mmHg, respectively), whereas the LV reference curve-based estimation exhibited a high mean bias (+3.93 mmHg).The proposed method enables the reconstruction of the RV pressure curve, using only the peak value as input. Thus, it may serve as a fundamental component for developing new echocardiographic tools targeting the afterload-adjusted assessment of RV function.Graphical abstractKey question. Can artificial intelligence be useful in the reconstruction of the right ventricular pressure curve of the entire cardiac cycle using only the peak value as input?Key findings. Multilayer Perceptron predicted instantaneous pressure values with a balanced, low bias throughout the cardiac cycle, even slightly outperforming the reference curve creation methods.Take-home message. Accurate prediction of the right ventricular pressure curve may enable formulation of new echocardiographic parameters targeting the afterload-adjusted assessment of RV function.LV: left ventricular, PVC: pulmonary valve closure, PVO: pulmonary valve opening, RV: right ventricular, TVC: tricuspid valve closure, TVO: tricuspid valve opening
Comprehensive Benchmarking of CNN-Based Tumor Segmentation Methods Using Multimodal MRI Data
Authors: Kundal Kavita , Rao K Venkateswara , Majumdar Arunabha , Kumar Neeraj , Kumar Rahul 
Published: January 2024

AbstractMagnetic resonance imaging (MRI) is become an essential and a frontline technique in the detection of brain tumor. However, manual segmentation of tumor from MRI scans is a time-consuming and labour-intensive process. There is a prevalent trend in employing fully automated methods for accurate tumor segmentation using MRI scans. The precision in brain tumor segmentation is essential for the better diagnosis, treatment and prognosis. This study focuses on benchmarking and evaluating the performance of four widely used convolutional neural network (CNN) based brain tumor segmentation methods CaPTk, 2DVNet, EnsembleUNets, and ResNet50. We used 1251 multimodal MRI scans from the BraTS2021 dataset, which encompasses T1, T2, T1ce, and Flair imaging modalities. We compared the performance of these CNN-based methods against a reference set of previously segmented images obtained with the assistance of radiologists. The evaluation encompasses direct utilization of segmented outputs and also by employing radiomic features. Performance evaluation with direct segments method using Dice Similarity Coefficient score (DSC) and Hausdorff Distance (HD) suggested better performance of EnsembleUNets with DSC and HD of 0.93 and 18 respectively, outperforming the other methods. Comparative analysis using radiomics features also revealed that EnsembleUNets is the most precise segmentation method as compared to CaPTk, 2DVNet, and ResNet50. EnsembleUNets achieved Concordance Correlation Coefficient (CCC), Total Deviation Index (TDI), and Root Mean Square Error (RMSE) of 0.79, 1.14 and 0.53 respectively and outperformed its counterparts. These findings contribute valuable insight into the comparative efficacy of EnsembleUNets, facilitating informed decision for accurate brain tumor segmentation.
Relationship between sleep and progression of Parkinson’s disease – A Mendelian randomization study
Authors: Mahjoub Mahiar , Matar Elie 
Published: January 2024

AbstractBackgroundSleep disturbances are common in Parkinson’s disease (PD) and growing evidence suggests a bidirectional relationship between sleep disruption and neurodegeneration.ObjectivesTo study the causal relationship between sleep and rate of PD progression using two-sample Mendelian randomisation (MR).MethodsGenetic variants linked to sleep duration and insomnia were analysed within a GWAS combining 12 longitudinal cohorts of patients with PD(n=4093 patients) examining motor and cognitive progression.ResultsGenetic liability to insomnia was associated with greater cognitive decline measured by MMSE. Consistent trends across MR estimates suggested a protective effect of increased sleep duration, and detrimental effect of insomnia on motor decline measured using UPDRS-III. Sensitivity analyses reinforced these relationships. The strength of causality among these associations was limited by heterogeneity and balanced pleiotropy.ConclusionSleep related variables may alter the trajectory of cognitive and motor progression in PD and warrants further study.
A phenome-wide association study of tandem repeat variation in 168,554 individuals from the UK Biobank
Authors: Manigbas Celine A. , Jadhav Bharati , Garg Paras , Shadrina Mariya , Lee William , Martin-Trujillo Alejandro , Sharp Andrew J. 
Published: January 2024

AbstractMost genetic association studies focus on binary variants. To identify the effects of multi-allelic variation of tandem repeats (TRs) on human traits, we performed direct TR genotyping and phenome-wide association studies in 168,554 individuals from the UK Biobank, identifying 47 TRs showing causal associations with 73 traits. We replicated 23 of 31 (74%) of these causal associations in the All of Us cohort. While this set included several known repeat expansion disorders, novel associations we found were attributable to common polymorphic variation in TR length rather than rare expansions and includee.g.a coding polyhistidine motif inHRCT1influencing risk of hypertension and a poly(CGC) in the 5’UTR ofGNB2influencing heart rate. Causal TRs were strongly enriched for associations with local gene expression and DNA methylation. Our study highlights the contribution of multi-allelic TRs to the “missing heritability” of the human genome.
Diverse competitor B cell responses to a germline-targeting priming immunogen in human Ig loci transgenic mice
Authors: Schiffner Torben , Palser Anne , Jardine Joseph G. , Liguori Alessia , Menis Sergey , Raemisch Sebastian , Hu Xiaozhen , Kulp Daniel W. , Wang Xiaoning , Diedrich Jolene K. , Groschel Bettina , Kalyuzhniy Oleksandr , Tingle Ryan , Le Khoa , Georgeson Erik , Adachi Yumiko , Kubitz Michael , Landais Elise , Yates John R. , Paulson James C. , Sok Devin , Kellam Paul , Schief William R. 
Published: January 2024

AbstractBroadly neutralizing antibodies (bnAbs) have promise to protect against HIV infection, but induction of bnAbs by immunization is an unsolved vaccine design challenge. Germline-targeting priming immunogens aim to initiate the induction of bnAbs by specifically activating rare bnAb-precursor B cells that can subsequently be matured using suitable heterologous boosting and shepherding immunogens. Several pre-clinical studies, and the IAVI G001 human clinical trial, have demonstrated the ability of a germline-targeting priming immunogen, eOD-GT8 60mer, to induce precursors of the VRC01 class of bnAbs. However, much less is known about B cells induced against other epitopes of the immunogen. Here, we performed unbiased analysis of B cells induced by eOD-GT8 60mers in Intelliselect Transgenic mice (Kymice) that are transgenic for the human Ig loci and produce human-like BCRs. B cells isolated with intact eOD-GT8 60mer nanoparticles showed a large diversity of non-VRC01-class B cells, with 38% unique clonotypes and only 5% of BCRs belonging to public lineages shared among all animals. We found that many competitors recognize epitopes in close proximity to or overlapping with the VRC01 epitope. These results indicate that optimal boosting of VRC01-class bnAb-precursor B cells primed by eOD-GT8 60mer might require a first-boost immunogen that minimizes recognition of competitor B cells, and such competitors isolated from Kymice could serve as valuable reagents for boost development.
Identification of Family-Specific Features in Cas9 and Cas12 Proteins: A Machine Learning Approach Using Complete Protein Feature Spectrum
Authors: Madugula Sita Sirisha , Pujar Pranav , Bharani Nammi , Wang Shouyi , Jayasinghe-Arachchige Vindi M. , Pham Tyler , Mashburn Dominic , Artilis Maria , Liu Jin 
Published: January 2024

AbstractThe recent development of CRISPR-Cas technology holds promise to correct gene-level defects for genetic diseases. The key element of the CRISPR-Cas system is the Cas protein, a nuclease that can edit the gene of interest assisted by guide RNA. However, these Cas proteins suffer from inherent limitations like large size, low cleavage efficiency, and off-target effects, hindering their widespread application as a gene editing tool. Therefore, there is a need to identify novel Cas proteins with improved editing properties, for which it is necessary to understand the underlying features governing the Cas families. In the current study, we aim to elucidate the unique protein attributes associated with Cas9 and Cas12 families and identify the features that distinguish each family from the other. Here, we built Random Forest (RF) binary classifiers to distinguish Cas12 and Cas9 proteins from non-Cas proteins, respectively, using the complete protein feature spectrum (13,495 features) encoding various physiochemical, topological, constitutional, and coevolutionary information of Cas proteins. Furthermore, we built multiclass RF classifiers differentiating Cas9, Cas12, and Non-Cas proteins. All the models were evaluated rigorously on the test and independent datasets. The Cas12 and Cas9 binary models achieved a high overall accuracy of 95% and 97% on their respective independent datasets, while the multiclass classifier achieved a high F1 score of 0.97. We observed that Quasi-sequence-order descriptors like Schneider-lag descriptors and Composition descriptors like charge, volume, and polarizability are essential for the Cas12 family. More interestingly, we discovered that Amino Acid Composition descriptors, especially the Tripeptide Composition (TPC) descriptors, are important for the Cas9 family. Four of the identified important descriptors of Cas9 classification are tripeptides PWN, PYY, HHA, and DHI, which are seen to be conserved across all the Cas9 proteins and were located within different catalytically important domains of the Cas9 protein structure. Among these four tripeptides, tripeptides DHI and HHA are well-known to be involved in the DNA cleavage activity of the Cas9 protein. We therefore propose the the other two tripeptides, PWN and PYY, may also be essential for the Cas9 family. Our identified important descriptors enhanced the understanding of the catalytic mechanisms of Cas9 and Cas12 proteins and provide valuable insights into design of novel Cas systems to achieve enhanced gene-editing properties.
Integrative Omics Uncovers Low Tumorous Magnesium Content as A Driver Factor of Colorectal Cancer
Authors: Zhang Rou , Hu Meng , Liu Yu , Li Wanmeng , Xu Zhiqiang , He Siyu , Lu Ying , Gong Yanqiu , Wang Xiuxuan , Hai Shan , Li Shuangqing , Qi Shiqian , Li Yuan , Shu Yang , Du Dan , Zhang Huiyuan , Xu Heng , Zhou Zongguang , Lei Peng , Chen Hai-Ning , Dai Lunzhi 
Published: January 2024

AbstractMagnesium (Mg) deficiency is associated with increased risk and malignancy of colorectal cancer (CRC), yet the underlying mechanisms remain elusive. Here we used genomic, proteomic, and phosphoproteomic data to elucidate the impact of Mg deficiency on CRC. Genomic analysis identified 160 genes with higher mutation frequencies in Low-Mg tumors, including key driver genes such asKMT2CandERBB3. Unexpectedly, initiation driver genes of CRC, such asTP53andAPC, displayed higher mutation frequencies in High-Mg tumors. Additionally, proteomics and phosphoproteomics indicated that low tumorous Mg content may activate epithelial-mesenchymal transition (EMT) by modulating inflammation or remodeling the phosphoproteome of cancer cells. Notably, we observed a negative correlation between the phosphorylation of DBN1 at S142 (DBN1S142p) and Mg content. A mutation in S142 to D (DBN1S142D) mimicking DBN1S142pupregulated MMP2 and enhanced cell migration, while treatment with MgCl2reduced DBN1S142p, thereby reversing this phenotype. Mechanistically, Mg2+attenuated the DBN1-ACTN4 interaction by decreasing DBN1S142p, which, in turn, enhanced the binding of ACTN4 to F-actin and promoted F-actin polymerization, ultimately reducing MMP2 expression. These findings shed new light on the crucial role of Mg deficiency in CRC progression and suggest that Mg supplementation may offer a promising preventive and therapeutic strategy for CRC.
The modified activity of prolyl 4 hydroxylases (P4Hs) reveals the effect of arabinogalactan proteins (AGPs) on changes in the cell wall during the tomato ripening process
Authors: Kutyrieva-Nowak Nataliia , Leszczuk Agata , Ezzat Lamia , Kaloudas Dimitris , Zając Adrian , Szymańska-Chargot Monika , Skrzypek Tomasz , Krokida Afroditi , Mekkaoui Khansa , Lampropoulou Evangelia , Kalaitzis Panagiotis , Zdunek Artur 
Published: January 2024

ABSTRACTArabinogalactan proteins (AGPs) are proteoglycans with an unusual molecular structure characterised by the presence of a protein part and carbohydrate chains. Their specific properties at different stages of the fruit ripening programme make AGPs unique markers of this process. An important function of AGPs is to co-form an amorphous extracellular matrix in the cell wall-plasma membrane continuum; thus, changes in the structure of these molecules can determine the presence and distribution of other components. The aim of the current work was to characterise the molecular structure and localisation of AGPs during the fruit ripening process in transgenic lines with silencing and overexpression ofSlP4H3genes. The objective was accomplished through comprehensive and comparativein situandex situanalyses of AGPs from the fruit of transgenic lines and wild-type plants at specific stages of ripening. The experiment showed that changes in P4H3 activity affected the content of AGPs and the progress in their modifications in the ongoing ripening process. The analysis of the transgenic lines confirmed the presence of AGPs with high molecular weights (120–60 kDa) at all the examined stages, but a changed pattern of the molecular features of AGPs was found in the last ripening stages, compared to WT. In addition to the AGP molecular changes, morphological modifications of fruit tissue and alterations in the spatio-temporal pattern of AGP distribution at the subcellular level were detected in the transgenic lines with the progression of the ripening process. The work highlights the irreversible impact of AGPs and their alterations on the fruit cell wall assembly and changes in AGPs associated with the progression of the ripening process.GRAPHICAL ABSTRACT
E41K Mutation Activates Bruton’s Tyrosine Kinase by Stabilizing an Inositol Hexakisphosphate dependent Invisible Dimer
Authors: Chowdhury Subhankar , Chakraborty Manas Pratim , Roy Swarnendu , Gangopadhyay Kaustav , Das Rahul 
Published: January 2024

AbstractBruton’s tyrosine kinase (BTK) regulates diverse cellular signaling of the innate and adaptive immune system in response to microbial pathogens. Downregulation or constitutive activation of BTK is reported in patients with autoimmune diseases or various B-cell leukemias. BTK is a multidomain protein tyrosine kinase that adopts an Src-like autoinhibited conformation maintained by the interaction between the kinase and PH-TH domains. The PH-TH domain plays a central role in regulating BTK function. The BTK is activated by binding to PIP3at the plasma membrane upon stimulation by the B-cell receptor (BCR). The PIP3binding allows dimerization of the PH-TH domain and subsequent transphosphorylation of the activation loop. Alternatively, a recent study shows that the multivalent T-cell-independent (TI) antigen induces BCR response by activating BTK independently of PIP3binding. It was proposed that a transiently stable IP6-dependent PH-TH dimer may activate BTK during BCR activation by the TI antigens. However, no IP6-dependent PH-TH dimer has been identified yet. Here, we investigated a constitutively active PH-TH mutant (E41K) to determine if the elusive IP6-dependent PH-TH dimer exists. We showed that the constitutively active E41K mutation activates BTK by stabilizing the IP6-dependent PH-TH dimer. We observed that a downregulating mutation in the PH-TH domain (R28H) linked to X-linked agammaglobulinemia impairs BTK activation at the membrane and in the cytosol by preventing PH-TH dimerization. We conclude that the IP6dynamically remodels the BTK active fraction between the membrane and cytoplasm. Stimulating with IP6increases the cytosolic fraction of the activated BTK.
The interferon-ɣ inducible factor 16 (IFI16) restricts adeno-associated virus serotype 2 (AAV2) transduction in an immune-modulatory independent way
Authors: Sutter Sereina O. , Tobler Kurt , Seyffert Michael , Lkharrazi Anouk , Zöllig Joël , Schraner Elisabeth M. , Vogt Bernd , Büning Hildegard , Fraefel Cornel 
Published: January 2024

ABSTRACTWe determined the transcription profile of AAV2-infected primary human fibroblasts. Subsequent analysis revealed that cells respond to AAV infection through changes in several significantly affected pathways including cell cycle regulation, chromatin modulation, and innate immune responses. Various assays were performed to validate selected differentially expressed genes and confirmed not only the quality but also the robustness of the raw data. One of the genes upregulated in AAV2 infected cells was the interferon-ɣ inducible factor 16 (IFI16). IFI16 is known as a multifunctional cytosolic and nuclear innate immune sensor for double-stranded, as well as single-stranded DNA, exerting its effects through various mechanisms, such as interferon response, epigenetic modifications, or transcriptional regulation. IFI16 thereby constitutes a restriction factor for many different viruses amongst them, as shown here, AAV2 and thereof derived vectors. Indeed, the post-transcriptional silencing ofIFI16significantly increased AAV2 transduction efficiency, independent of the structure of the virus/vector genome. We also show that IFI16 exerts its inhibitory effect on AAV2 transduction in an immune-modulatory independent way, by interfering with Sp1-dependent transactivation of wild-type AAV2 and AAV2 vector promoters.IMPORTANCEAdeno-associated virus (AAV) vectors are among the most frequently used viral vectors for gene therapy. The lack of pathogenicity of the parental virus, the long-term persistence as episomes in non-proliferating cells, and the availability of a variety of AAV serotypes differing in their cellular tropism are advantageous features of this biological nanoparticle. To deepen our understanding of virus-host interactions, especially in terms of innate immune responses, we present here the first transcriptome analysis of AAV serotype 2 (AAV2) infected human primary fibroblasts. Our findings indicate that the interferon-ɣ inducible factor 16 (IFI16) acts as an antiviral factor in AAV2 infection and AAV2 vector-mediated cell transduction in an immune-modulatory independent way by interrupting the Sp1-dependent gene expression from viral or vector genomes.