bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hemihamate Arthroplasty Revisited
Authors: Doucet Véronique M. , Clark Tod A. , Giuffre Jennifer L. 
Published: December 2022

Purpose
Proximal interphalangeal joint (PIPJ) fracture dislocations are complex injuries that can result in persistent pain, stiffness, and angulation. Hemihamate arthroplasty (HHA) can be used to reconstruct the base of the middle phalanx in cases of unstable PIPJ fracture dislocations. Despite previous case series describing good outcomes with HHA, it has not gained widespread use. The purpose of this study is to describe our straightforward, reproducible technique and to demonstrate the benefit in motion after the procedure in chronic unstable PIPJ fracture dislocations.

Methods
All patients with chronic, unstable PIPJ fracture dislocations requiring joint resurfacing of greater than 40% of the base of the middle phalanx treated with HHA were retrospectively reviewed. Patient demographics, injury features, surgical technique, preoperative and postoperative PIPJ range of motion and arc of motion, time to surgery, and complications were reviewed. Any fracture amenable to fixation or cases with radiographic evidence of arthritis or injury to the head of the proximal phalanx were excluded.

Results
Eleven cases were reviewed. The mean patient age was 35 years. The mean time from injury to surgery was 6 months. The mean joint surface involved was 64%. The mean PIPJ arc of motion was 17 degrees preoperatively and 63 degrees postoperatively. The mean bone block size required was 8 × 8 × 8 mm. The mean follow-up was 26 months. Postoperative pain at the PIPJ on the visual analog scale was 0.4 (scale of 0 to 10). Complications included 2 patients requiring tenolysis.

Conclusions
Despite the lack of a perfect geometric recreation of the base of the middle phalanx with the hamate, patients recover acceptable PIPJ motion and have minimal pain. Hemihamate arthroplasty is a good option for any patient with minimal motion of their PIPJ and a chronic, unstable fracture dislocation.
An update to the critical appraisal of Milwaukee protocol
Authors: Arslan Ferhat , Vahaboglu Haluk 
Published: December 2022

AbstractRabies is a highly fatal encephalitis. Currently, there is no approved treatment. Inducing therapeutic coma during the first week of symptomatic rabies patient, called Milwaukee protocol, had been suggested as promising. However, recent evidence failed to support the use of the Milwaukee protocol. This mini-review analyzed the reports of patients managed with therapeutic coma since 2014 to provide an update for the critical appraisal of this protocol.
Profile-Wise Analysis: A profile likelihood-based workflow for identifiability analysis, estimation, and prediction with mechanistic mathematical models
Authors: Simpson Matthew J. , Maclaren Oliver J. 
Published: December 2022

AbstractInterpreting data using mechanistic mathematical models provides a foundation for discovery and decision-making in all areas of science and engineering. Developing mechanistic insight by combining mathematical models and experimental data is especially critical in mathematical biology as new data and new types of data are collected and reported. Key steps in using mechanistic mathematical models to interpret data include: (i) identifiability analysis; (ii) parameter estimation; and (iii) model prediction. Here we present a systematic, computationally-efficient workflow we callProfile-Wise Analysis(PWA) that addresses all three steps in a unified way. Recently-developed methods for constructing ‘profile-wise’ prediction intervals enable this workflow and provide the central linkage between different workflow components. These methods propagate profile-likelihood-based confidence sets for model parameters to predictions in a way that isolates how different parameter combinations affect model predictions. We show how to extend these profile-wise prediction intervals to two-dimensional interest parameters. We then demonstrate how to combine profile-wise prediction confidence sets to give an overall prediction confidence set that approximates the full likelihood-based prediction confidence set well. Our three case studies illustrate practical aspects of the workflow, focusing on ordinary differential equation (ODE) mechanistic models with both Gaussian and non-Gaussian noise models. While the case studies focus on ODE-based models, the workflow applies to other classes of mathematical models, including partial differential equations and simulation-based stochastic models. Open-source software on GitHub can be used to replicate the case studies.
Cell Tree Rings: the structure of somatic evolution as a human aging timer
Authors: Csordas Attila , Sipos Botond , Kurucova Terezia , Volfova Andrea , Zamola Frantisek , Tichy Boris , Hicks Damien G 
Published: December 2022

AbstractBiological age is typically estimated using biomarkers whose states have been observed to correlate with chronological age. A persistent limitation of such aging clocks is that it is difficult to establish how the biomarker states are related to the mechanisms of aging. Somatic mutations could potentially form the basis for a more fundamental aging clock since the mutations are both markers and drivers of aging and have a natural timescale. Cell lineage trees inferred from these mutations reflect the somatic evolutionary process and thus, it has been conjectured, the aging status of the body. Such a timer has been impractical thus far, however, because detection of somatic variants in single cells presents a significant technological challenge. Here we show that somatic mutations detected using single-cell RNA sequencing (scRNA-seq) from thousands of cells can be used to construct a cell lineage tree whose structure correlates with chronological age. De novo single-nucleotide variants (SNVs) are detected in human peripheral blood mononuclear cells using a modified protocol. A default model based on penalized multiple regression of chronological age on 31 metrics characterizing the phylogenetic tree gives a Pearson correlation of 0.81 and a median absolute error of ∼4 years between predicted and chronological age. Testing of the model on a public scRNA-seq dataset yields a Pearson correlation of 0.85. In addition, cell tree age predictions are found to be better predictors of certain clinical biomarkers than age alone, for instance glucose, albumin levels and leukocyte count. The geometry of the cell lineage tree records the structure of somatic evolution in the individual and represents a new modality of aging timer. In addition to providing a numerical estimate of ‘Cell Tree Age’, it unveils a temporal history of the aging process, revealing how clonal structure evolves over life span. Cell Tree Rings complements existing aging clocks and may help reduce the current uncertainty in the assessment of geroprotective trials.
Cellular and Fibrillar Collagen Analyses in an Animal Model of Retinal Detachment-Related Proliferative Vitreoretinopathy Reveals a Defined Transition to Chronic Fibrosis
Authors: Peterson Cornelia , Santiago Clayton P. , Lu Yuchen , Price Antoinette , McNally Minda M. , Schubert William , Blackshaw Seth , Eberhart Charles G. , Singh Mandeep S. 
Published: December 2022

AbstractPurposeProliferative vitreoretinopathy (PVR) is the most common cause of failure of surgically repaired rhegmatogenous retinal detachment (RRD). Chemically-induced and cell-injection PVR models do not fully simulate the clinical characteristics of PVR in the post-RRD context. There is an unmet need for translational models in which to study mechanisms and treatments specific to RRD-PVR.MethodsRRD-PVR was induced in adult Dutch Belted rabbits. Posterior segments of enucleated globes were fixed or processed for RNA-Seq at 6 hours and 2, 7, 14, and 35 days post-induction. Histochemical staining and immunolabeling for glial fibrillary acidic protein (GFAP), alpha smooth muscle actin (αSMA), vascular endothelial growth factor receptor 2 (VEGFR2), CD68, and retinal pigment epithelium 65 kDa protein (RPE65) were performed, and labeling intensity was scored. Single cell RNA sequencing was performed.ResultsAcute histopathologic changes included intravitreal and intraretinal hemorrhage, leukocytic vitritis, chorioretinitis, and retinal rarefaction. Chronic lesions showed retinal atrophy, gliosis, fibrotic subretinal membranes, and epiretinal fibrovascular proliferation. Fibrillar collagen was present in the fibrocellular and fibrovascular membranes in chronic lesions. Moderate to strong labeling of glia and vasculature was detected in chronic lesions. At day 14, most cells profiled by single cell sequencing were identified as Müller glia and microglia, consistent with immunolabeling. Expression of several fibrillar collagen genes were upregulated in chronic lesions.ConclusionsHistologic and transcriptional features of this rabbit model simulate important features of human RRD-PVR, including the transition to chronic intra and periretinal fibrosis. This high-fidelityin vivomodel of RRD-PVR will enable further research on targeted treatment interventions.
Bayesian methods for optimizing deep brain stimulation to enhance cognitive control
Authors: Nagrale Sumedh S , Yousefi Ali , Netoff Theoden I , Widge Alik S 
Published: December 2022

AbstractObjectiveDeep brain stimulation (DBS) of the ventral internal capsule/striatum (VCVS) is a potentially effective treatment for several mental health disorders when conventional therapeutics fail. Its effectiveness, however, depends on correct programming to engage VCVS sub-circuits. VCVS programming is currently an iterative, time-consuming process, with weeks between setting changes and reliance on noisy, subjective self-reports. An objective measure of circuit engagement might allow individual settings to be tested in seconds to minutes, reducing the time to response and increasing patient and clinician confidence in the chosen settings. Here, we present an approach to measuring and optimizing that circuit engagement.ApproachWe leverage prior results showing that effective VCVS DBS engages circuits of cognitive control, that this engagement depends primarily on which contact(s) are activated, and that circuit engagement can be tracked through a state space modeling framework. We combine this framework with an adaptive optimizer to perform a principled exploration of electrode contacts and identify the contacts that maximally improve cognitive control.Main resultsUsing behavioral simulations directly derived from patient data, we show that an Upper Confidence Bound (UCB1) algorithm outperforms other optimizers (roughly 80% probability of convergence to a global optimum).SignificanceWe show that the optimization can converge even with lag between stimulation and effect, and that a complete optimization can be done in a clinically feasible timespan (a few hours). Further, the approach requires no specialized recording or imaging hardware, and thus could be a scalable path to expand the use of DBS in psychiatric and other non-motor applications.
Improving theCOIDNA barcoding library for Neotropical phlebotomine sand flies (Diptera, Psychodidae)
Authors: Posada-López Laura , Rodrigues Bruno Leite , Velez Ivan Dario , Uribe Sandra 
Published: December 2022

AbstractA fragment of the mitochondrialcytochrome c oxidase subunit I(COI) gene was used to generate 156 new barcode sequences for sand flies from different countries of the Neotropical region, mainly Colombia, which had been identified morphologically as 43 species. The sequencing of theCOIgene allowed the detection of cryptic diversity within species and correctly associated isomorphic females with males identified by morphology. The maximum intraspecific genetic distances ranged from 0 to 8.32% and 0 to 8.92% using uncorrectedpdistances and the K2P model, respectively. The minimum interspecific distance (nearest neighbor) for each species ranged from 1.5 to 14.14% and 1.51 to 15.7% using p and K2P distances, respectively. Three species had more than 3% maximum intraspecific distance:Psychodopygus panamensis, Micropygomyia cayennensis cayennensis, andPintomyia evansi. They also were splitted into at least two MOTUs each, using different species delimitation algorithms. Regarding interspecific genetic distances, the species of the generaNyssomyiaandTrichophoromyiagenerated values lower than 3% (exceptNy. ylephiletorandNy. trapidoi). However, the maximum intraspecific distances did not exceed these values, indicating the presence of a barcode gap despite their proximity. Also, nine sand fly species were DNA barcoded for the first time:Evandromyia georgii, Lutzomyia sherlocki, Ny. ylephiletor, Ny. yuilli pajoti, Psathyromyia punctigeniculata, Sciopemyia preclara, Trichopygomyia triramula, Trichophoromyia howardi, andTh. velezbernali. Thus, theCOIDNA barcode analysis allowed the correct delimitation of several Neotropical sand fly species from South and Central America and raised questions about the presence of cryptic species for some taxa, which should be further assessed.
Combination drug screen targeting glioblastoma core vulnerabilities reveals pharmacological synergisms
Authors: Ariey-Bonnet Jérémy , Berges Raphael , Montero Marie-Pierre , Mouysset Baptiste , Piris Patricia , Muller Kevin , Pinna Guillaume , Failes Tim W. , Arndt Greg M. , Baeza-Kallee Nathalie , Colin Carole , Chinot Olivier , Braguer Diane , Morelli Xavier , André Nicolas , Carré Manon , Tabouret Emeline , Figarella-Branger Dominique , Grand Marion Le , Pasquier Eddy 
Published: December 2022

ABSTRACTSynergistic drug combinations are an attractive anticancer strategy but prove challenging to identify. Here we present a stepwise approach consisting in revealing core cancer vulnerabilities and exploiting them through drug combination screen to uncover synergistic treatments for glioblastoma patients.MethodsWe established an innovative method, based on high-throughput screening, target deconvolution and functional genomics, to reveal core vulnerabilities in glioblastoma. Combination drug screen targeting these vulnerabilities was then designed to unveil synergistic associations. The therapeutic potential of the top drug combination was validated in two different clinically-relevant models: an organotypicex vivomodel and a syngeneic orthotopic mouse model of glioblastoma.ResultsLarge-scale monotherapy drug screening identified 83 potent anti-glioblastoma compounds. Target deconvolution using public chemoinformatic databases uncovered 1,100 targets and interactors of the hit compounds. Screening of a focused siRNA library targeting the top 292 drug interactors revealed 22 targetable vulnerabilities, 9 of which were confirmed as core glioblastoma vulnerabilities by mining the CRISPR screen cohort data from the online Cancer Dependency Map portal. Six selective inhibitors of the core vulnerabilities were then screened in combination with a custom-made library of 88 compounds and synergies amongst the 528 tested pairwise combinations were predicted. The combinations of CHK1 / MEK and AURKA / BET inhibitors were highlighted and validated in 3D tumor spheroids. Using an organotypicex vivomodel and a syngeneic orthotopic mouse model, we definitively ascertained the efficacy of dual AURKA / BET inhibition in glioblastoma.ConclusionsCollectively, we uncovered that dual inhibition of BET proteins and aurora kinase A is highly synergistic against GBM. Moreover, our study indicates that our approach to exploit drug poly-pharmacology for the rational design of drug combination screens represent a valuable strategy to discover synergistic treatments against refractory cancers.
The necessity of considering enzymes as compartments in constraint-based genome-scale metabolic models
Authors: Yang Xue , Mao Zhitao , Huang Jianfeng , Wang Ruoyu , Dong Huaming , Zhang Yanfei , Ma Hongwu 
Published: December 2022

AbstractAs the most widespread and practical digital representations of living cells, metabolic network models have become increasingly precise and accurate. By integrating cellular resources and abiotic constraints, the prediction functions were significantly expanded in recent years. However, we found that if unreasonable modeling methods were adopted due to the lack of consideration of biological knowledge, the conflicts between stoichiometric and other constraints, such as thermodynamic feasibility and enzyme resource availability, would lead to distorted predictions. In this work, we investigated a prediction anomaly of EcoETM, a constraints-based metabolic network model, and introduced the idea of enzyme compartmentalization into the analysis process. Through rational combination of reactions, we avoid the false prediction of pathway feasibility caused by the unrealistic assumption of free intermediate metabolites. This allowed us to correct the pathway structures of L-serine and L-tryptophan. Specific analysis explains the application method of EcoETM-like model, demonstrating its potential and value in correcting the prediction results in pathway structure by resolving the conflict between different constraints and incorporating the evolved roles of enzymes as reaction compartments. Notably, this work also reveals the trade-off between product yield and thermodynamic feasibility. Finally, we provide a preliminary comparison of the thermodynamic feasibility of ammonia and glutamine as amino donors, which revealed that the direct utilization of ammonia does not have a decisive impact on the thermodynamic feasibility of the anthranilate pathway. Our work is of great value for the structural improvement of constraints-based models.
Host Immunity toMycobacterium tuberculosisInfection is Similar in Simian Immunodeficiency Virus (SIV)-infected, Antiretroviral Therapy-treated and SIV-naïve Juvenile Macaques
Authors: Larson Erica C. , Ellis Amy L. , Rodgers Mark A. , Gubernat Abigail K. , Gleim Janelle L. , Moriarty Ryan V. , Balgeman Alexis J. , Menezes Yonne K. , Ameel Cassaundra L. , Fillmore Daniel J. , Pergalske Skyler M. , Juno Jennifer A. , Maiello Pauline , White Alexander G. , Borish H. Jacob , Godfrey Dale I. , Kent Stephen J. , Ndhlovu Lishomwa C. , O’Connor Shelby L. , Scanga Charles A. 
Published: December 2022

AbstractPre-existing HIV infection increases tuberculosis (TB) risk in children. Antiretroviral therapy (ART) reduces, but does not abolish, this risk in children with HIV. The immunologic mechanisms involved in TB progression in both HIV-naïve and HIV-infected children have not been explored. Much of our current understanding is based on human studies in adults and adult animal models. In this study, we sought to model childhood HIV/Mycobacterium tuberculosis(Mtb) coinfection in the setting of ART and characterize T cells during TB progression. Macaques equivalent to 4-8 year-old children were intravenously infected with SIVmac239M, treated with ART three months later, and coinfected with Mtb three months after initiating ART. SIV-naïve macaques were similarly infected with Mtb alone. TB pathology and total Mtb burden did not differ between SIV-infected, ART-treated and SIV-naïve macaques, although lung Mtb burden was lower in SIV-infected, ART-treated macaques. No major differences in frequencies of CD4+ and CD8+ T cells and unconventional T cell subsets (Vγ9+ γδ T cells, MAIT cells, and NKT cells) in airways were observed between SIV-infected, ART-treated and SIV-naïve macaques over the course of Mtb infection, with the exception of CCR5+ CD4+ and CD8+ T cells which were slightly lower. CD4+ and CD8+ T cell frequencies did not differ in the lung granulomas obtained at necropsy, nor did they differ in the frequency of immune checkpoint and proliferative markers. Thus, ART treatment of juvenile macaques, three months after SIV infection, resulted in similar progression of Mtb and T cell responses compared to Mtb in SIV-naïve macaques.
Using in silico perturbational approach to identify critical areas in schizophrenia
Authors: Mana Ludovica , Vila − Vidal Manel , Köckeritz Charlotte , Aquino Kevin , Fornito Alex , Kringelbach Morten L. , Deco Gustavo 
Published: December 2022

ABSTRACTSchizophrenia is a debilitating neuropsychiatric disorder whose underlying correlates remain unclear despite decades of neuroimaging investigation. One contentious topic concerns the role of global signal fluctuations and how they affect more focal functional changes. Moreover, it has been difficult to pinpoint causal mechanisms of circuit disruption. Here we analysed resting-state fMRI data from 47 schizophrenia patients and 118 age-matched healthy controls and used dynamical analyses to investigate how global fluctuations and other functional metastable states are affected by this disorder. We then used in-silico perturbation of a whole-brain model to identify critical areas involved in the disease. We found that brain dynamics in the schizophrenic group were characterised by an increased probability of globally coherent states and reduced recurrence of a substate dominated by coupled activity in the default mode and limbic networks. Perturbing a set of temporoparietal sensory and associative areas in a model of the healthy brain reproduced global pathological dynamics. Healthy brain dynamics were instead restored by perturbing a set of medial fronto-temporal and cingulate regions in the model of pathology. These results highlight the relevance of global signal alterations in schizophrenia and identify a set of vulnerable areas involved in determining a shift in brain state.
Predictability of the community-function landscape in wine yeast ecosystems
Authors: Ruiz Javier , de Celis Miguel , Diaz-Colunga Juan , Vila Jean CC , Benitez-Dominguez Belen , Vicente Javier , Santos Antonio , Sanchez Alvaro , Belda Ignacio 
Published: December 2022

AbstractPredictively linking taxonomic composition and quantitative ecosystem functions is a major aspiration in microbial ecology, which must be resolved if we wish to engineer microbial consortia. Here, we have addressed this open question for an ecological function of major biotechnological relevance: alcoholic fermentation in wine yeast communities. By exhaustively phenotyping an extensive collection of naturally occurring wine yeast strains, we find that most enologically-relevant traits exhibit a strong phylogenetic signal, indicating that the most relevant functions in wine yeast communities can be predicted from taxonomy. Further, we demonstrate that the quantitative contributions of individual wine yeast strains to the community function followed simple quantitative rules. These regularities can be integrated to quantitatively predict the function of newly assembled consortia. Besides addressing a fundamental open question in functional ecology, our results and methodologies provide a blueprint for rationally managing microbial processes of biotechnological relevance.