bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shear Wave Elastography Evaluation of Testes in Patients With Varicocele
Authors: Erdogan Hasan , Durmaz Mehmet Sedat , Arslan Serdar , Gokgoz Durmaz Funda , Cebeci Hakan , Ergun Osman , Sogukpinar Karaagac Seda 
Published: February 2019

Abstract
We aimed to determine histological damage in patients with varicocele by comparing the elasticity of their affected testes with that of their normal contralateral testes as well as normal testes of control subjects without varicocele using shear wave elastography (SWE). In total, 48 patients with varicocele (96 testes) and 52 control subjects (104 testes) were included in this study. Shear wave elastography values were measured in the longitudinal plane using an oval region of interest that covered as much of the testicular contours as possible. Fifty testes with varicocele were classified as group A, 46 normal contralateral testes of the same patients as group B, and 104 normal testes of control subjects as group C. The normal group C testes were randomly chosen from patients who had applied for ultrasonography for any reason and agreed to participate in the study. The testicular volume and SWE values were compared between these 3 groups. The average age of the patients was 28.45 years, and no significant difference in age was found between the 3 groups (P = 0.665). A significant difference in the testicular volume was found between groups A and C (P = 0.014). The SWE values were significantly higher in group A than in groups B and C (P < 0.001). No significant correlation was observed between the testicular volume and SWE values in any of the groups. Our results showed that SWE can be used as an effective technique to assess testicular stiffness in patients with varicocele to predict interstitial fibrosis and the severity of histological damage.
Sonographic Appearances of Portal Vein Abnormalities
Authors: Kulkarni Naveen M. , Griffin Michael O. , O'Connor Stacy D. , Sudakoff Gary 
Published: February 2019

Abstract
Portal venous system evaluation is required in many clinical circumstances, as substantial morbidity and mortality can be associated with a spectrum of portal vein abnormalities. Portal venous system pathologies can be congenital or acquired, and the knowledge of their imaging appearances will allow for a confident diagnosis and appropriate treatment options. In addition, a firm understanding of anatomical variants is important for planning surgical procedures and percutaneous interventions of the liver. This article will review various imaging appearances of portal venous systems abnormalities.
High Central Venous-to-Arterial CO2 Difference is Associated With Poor Outcomes in Patients After Cardiac Surgery: A Propensity Score Analysis
Authors: Chen Tao , Pan Tuo , Luo Xuan , Wang Dongjin 
Published: February 2019

Abstract

Purpose:
In contrast to arterial lactate, previous studies have proposed central venous-to-arterial CO2 difference (P (v-a)CO2) as a more useful guide for categorizing patients at risk of developing septic shock. It is worthwhile studying P (v-a)CO2 in determining whether it could serve as a useful predictor for poor postoperative outcomes in patients undergoing cardiac surgery. We investigated the ability of P(v-a)CO2 to predict poor outcomes of patients with postoperative cardiogenic shock.

Methods:
In total, 1,672 patients were enrolled in this study from January 1, 2014 to June 1, 2017. Of these patients, 143 exhibited complicated and poor outcomes. To address any bias, we derived a propensity score predicting the functions of P(v-a)CO2 on poor outcomes and matched 114 cases to 114 controls with a similar risk profile. In this cohort study, poor outcomes were defined as the occurrence of any adverse complications, including sudden death, cardiac arrest, extracorporeal membrane oxygenation, oliguria, and the administration of a large amount of vasoactive-inotropic drugs.

Results:
In propensity-matched patients, significant differences in P(v-a)CO2 (6.11 ± 2.94 mm Hg vs. 11.21 ± 5.22 mm Hg, P < 0.001) were noted between the control group and poor outcome group. The area under the receiver operating characteristic curve of P(v-a)CO2 (AUC: 0.837, 95% CI: 0.782–0.892) for the detection of poor outcomes was significantly better compared to that of the central venous oxygen saturation and arterial lactate. Additionally, there was a negative correlation between cardiac index and P(v-a)CO2 (R= −0.68, P < 0.001).

Conclusion:
We have shown a correlation between P(v-a)CO2 to cardiac output which may be used as an alternative metric to predict the poor outcomes of patients with postoperative cardiogenic shock.
Treatment of Poststroke Pathologic Laughing With Duloxetine: A Case Series
Authors: Shin Sang Hoon , Kim Yong Wook , Kim Na Young 
Published: February 2019

Objectives
Pathologic laughing is characterized by episodes of uncontrollable laughter caused by underlying neurologic disturbances, such as stroke. Several types of medication, including selective serotonin reuptake inhibitors, have demonstrated only limited success at treating the condition. Duloxetine, a dual serotonin-norepinephrine reuptake inhibitor, is reportedly effective in treating the symptoms of mood disorders. We herein introduce a prospective consecutive sample of stroke patients with pathologic laughing treated with duloxetine.

Methods
We enrolled patients without a history of psychological illness who exhibited poststroke pathologic laughter. Duloxetine administration was commenced at an initial dose of 30 mg once daily. The dose was increased to 60 mg once daily within 2 weeks for all patients except 2. The effect of the treatment was assessed by means of the Pathological Laughter and Crying Scale.

Results
A total of 7 patients were included in the study. Improvements were observed within an average of 10 days after duloxetine administration. Pathological Laughter and Crying Scale score decreased after duloxetine administration in all patients, and 4 patients demonstrated a decrease in score of more than 50%. All patients reported subjective improvement of symptoms, and no adverse effects were observed.

Conclusions
This case series demonstrates that duloxetine could attenuate pathologic laughing exhibited by stroke patients; however, further randomized controlled studies are necessary to validate our findings.
VEF: a Variant Filtering tool based on Ensemble methods
Authors: Zhang Chuanyi , Ochoa Idoia 
Published: February 2019

AbstractMotivationVariant discovery is crucial in medical and clinical research, especially in the setting of personalized medicine. As such, precision in variant identification is paramount. However, variants identified by current genomic analysis pipelines contain many false positives (i.e., incorrectly called variants). These can be potentially eliminated by applying state-of-the-art filtering tools, such as the Variant Quality Score Recalibration (VQSR) or the Hard Filtering (HF), both proposed by GATK. However, these methods are very user-dependent and fail to run in some cases. We propose VEF, a variant filtering tool based on ensemble methods that overcomes the main drawbacks of VQSR and the HF. Contrary to these methods, we treat filtering as a supervised learning problem. This is possible by using for training variant call data for which the set of “true” variants is known, i.e., agold standardexists. Hence, we can classify each variant in the training VCF file as true or false using the gold standard, and further use the annotations of each variant as features for the classification problem. Once trained, VEF can be directly applied to filter the variants contained in a given VCF file. Analysis of several ensemble methods revealed random forest as offering the best performance, and hence VEF uses a random forest for the classification task.ResultsAfter training VEF on a Whole Genome Sequencing (WGS) Human dataset of sampleNA12878, we tested its performance on a WGS Human dataset of sampleNA24385. For these two samples, the set of high-confident variants has been produced and made available. Results show that the proposed filtering tool VEF consistently outperforms VQSR and HF. In addition, we show that VEF generalizes well even when some features have missing values, and when the training and testing datasets differ either in coverage or in the sequencing machine that was used to generate the data. Finally, since the training needs to be performed only once, there is a significant saving in running time when compared to VQSR (50 minutes versus 4 minutes approximately for filtering the SNPs of WGS Human sample NA24385). Code and scripts available at:github.com/ChuanyiZ/vef.
Phylogenomics clarifies biogeographic and evolutionary history, and conservation status of West Indian tremblers and thrashers (Aves: Mimidae)
Authors: DaCosta Jeffrey M. , Miller Matthew J. , Mortensen Jennifer L. , Reed J. Michael , Curry Robert L. , Sorenson Michael D. 
Published: February 2019

AbstractThe West Indian avifauna has provided fundamental insights into island biogeography, taxon cycles, and the evolution of avian behavior. Our interpretations, however, rely on robust hypotheses of evolutionary relationships and consistent conclusions about taxonomic status in groups with many endemic island populations. Here we present a phylogenetic study of the West Indian thrashers, tremblers, and allies, an assemblage of at least 5 species found on 29 islands, which is considered the archipelago’s only avian radiation. We improve on previous phylogenetic studies of this group by using double-digest restriction site-associated DNA sequencing (ddRAD-seq) to broadly sample loci scattered across the nuclear genome. A variety of analyses, based on either nucleotide variation in 2,223 loci that were recovered in all samples or on 13,282 loci that were confidently scored as present or absent in all samples, converged on a single well-supported phylogenetic hypothesis. In contrast to previous studies, we found that the resident West Indian taxa form a monophyletic group, exclusive of the Neotropical–Nearctic migratory Gray CatbirdDumetella carolinensis, which breeds in North America. Earlier studies indicated that the Gray Catbird was nested within a clade of island resident species. Instead, our findings imply a single colonization of the West Indies without the need to invoke a subsequent ‘reverse colonization’ of the mainland by West Indian taxa. Furthermore, our study is the first to sample both endemic subspecies of the endangered White-breasted ThrasherRamphocinclus brachyurus. We find that these subspecies have a long history of evolutionary independence with no evidence of gene flow, and are as genetically divergent from each other as other genera in the group. These findings support recognition ofR. brachyurus(restricted to Martinique) and the Saint Lucia ThrasherR. sanctaeluciaeas two distinct, single-island endemic species, and indicate the need to re-evaluate conservation plans for these taxa. Our results demonstrate the utility of phylogenomic datasets for generating robust systematic hypotheses.
Mechanistic Insights into Specific G Protein Interactions with Adenosine Receptors Revealed by Accelerated Molecular Simulations
Authors: Wang Jinan , Miao Yinglong 
Published: February 2019

AbstractCoupling between G-protein-coupled receptors (GPCRs) and the G proteins is a key step in cellular signaling. Despite extensive experimental and computational studies, the mechanism of specific GPCR-G protein coupling remains poorly understood. This has greatly hindered effective drug design of GPCRs that are primary targets of ~1/3 of currently marketed drugs. Here, we have employed all-atom molecular simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method to decipher the mechanism of the GPCR-G protein interactions. Adenosine receptors (ARs) were used as model systems based on very recently determined cryo-EM structures of the A1AR and A2AAR coupled with the Gi and Gs proteins, respectively. Changing the Gi protein to the Gs led to increased fluctuations in the A1AR and agonist adenosine (ADO), while agonist 5’-N-ethylcarboxamidoadenosine (NECA) binding in the A2AAR could be still stabilized upon changing the Gs protein to the Gi. Free energy calculations identified one stable low-energy conformation for each of the ADO-A1AR-Gi and NECA-A2AAR-Gs complexes as in the cryo-EM structures, similarly for the NECA-A2AAR-Gi complex. In contrast, the ADO agonist and Gs protein sampled multiple conformations in the ADO-A1AR-Gs system. GaMD simulations thus indicated that the ADO-bound A1AR preferred to couple with the Gi protein to the Gs, while the A2AAR could couple with both the Gs and Gi proteins, being highly consistent with experimental findings of the ARs. More importantly, detailed analysis of the atomic simulations showed that the specific AR-G protein coupling resulted from remarkably complementary residue interactions at the protein interface, involving mainly the receptor transmembrane 6 helix and the Gα α5 helix and α4-β6 loop. In summary, the GaMD simulations have provided unprecedented insights into the dynamic mechanism of specific GPCR-G protein interactions at an atomistic level, which is expected to facilitate future drug design efforts of the GPCRs.
The potential role of collagens in congenital Zika syndrome: A systems biology approach
Authors: Aguiar Renato S , Pohl Fabio , Morais Guilherme L , Nogueira Fabio CS , Carvalho Joseane B , Guida Letícia , Arge Luis WP , Melo Adriana , Moreira Maria EL , Cunha Daniela P , Gomes Leonardo , Portari Elyzabeth A , Velasquez Erika , Melani Rafael D , Pezzuto Paula , Castro Fernanda L de , Geddes Victor EV , Gerber Alexandra L , Azevedo Girlene S , Schamber-Reis Bruno L , Gonçalves Alessandro L , Junqueira-de-Azevedo Inácio , Nishiyama Milton Y , Ho Paulo L , Schanoski Alessandra S , Schuch Viviane , Tanuri Amilcar , Chimelli Leila , Vasconcelos Zilton FM , Domont Gilberto B , Vasconcelos Ana TR , Nakaya Helder I 
Published: February 2019

AbstractZika virus (ZIKV) infection during pregnancy could cause a set of severe abnormalities in the fetus known as congenital Zika syndrome (CZS). Experiments using animal models and in vitro systems significantly contributed to our understanding of the physiopathology of ZIKV infection. However, the molecular basis of CZS is not yet studied in humans. Here, we used a systems biology approach to integrate transcriptomic, proteomic and genomic data from post-mortem brains of neonates with CZS. We observed that collagen genes were greatly reduced in CZS brains at both the RNA and protein levels and that neonates with CZS have several polymorphisms in collagen genes associated with osteogenesis imperfect and arthrogryposis. These findings were validated using immunohistochemistry and collagen staining of ZIKV infected and non-infected samples. Additionally, it was found that cell adhesion genes that are essential for neurite outgrowth and axon guidance were up-regulated and thereby confirmed the neuronal migration defects observed. This work provided new insights into the underlying mechanisms of CZS and revealed host genes associated with CZS susceptibility.
Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis
Authors: Bernardo-Faura Marti , Rinas Melanie , Wirbel Jakob , Pertsovskaya Inna , Pliaka Vicky , Messinis Dimitris E , Vila Gemma , Sakellaropoulos Theodore , Faigle Wolfgang , Stridh Pernilla , Behrens Janina R. , Olsson Tomas , Martin Roland , Paul Friedemann , Alexopoulos Leonidas G , Villoslada Pablo , Saez-Rodriguez Julio 
Published: February 2019

AbstractSignal transduction deregulation is a hallmark of many complex diseases, including Multiple Sclerosis (MS). Here, we performed ex vivo multiplexed phosphoproteomic assays in PBMCs from 180 MS patients either untreated or treated with fingolimod, natalizumab, interferon-beta, glatiramer acetate or the experimental therapy epigallocatechin gallate (EGCG), and from 60 matched healthy controls. Fitting a bespoke literature-derived network of MS-related pathways using logic modeling yielded a signaling network specific for each patient. Patient models were merged to characterize healthy-, disease- and drug-specific signaling networks. We defined a co-druggability score based on the topology for each drug’s network. We used this score to identify kinase interactions whose activity could be reverted to a "healthy-like" status by combination therapy. We predicted several combinations with approved MS drugs. Specifically, TAK1 kinase, involved in TGF-B, toll-like receptor, B-cell receptor and response to inflammation pathways was found to be highly deregulated and co-druggable with four MS drugs. One of these predicted combinations, Fingolimod with a TAK1 inhibitor, was validated in an animal model of MS. Our approach based on patient-specific signaling networks enables prediction of targets for combination therapy for MS and other complex diseases.One sentence summaryA new approach to predict combination therapies based on modeling signaling architecture using phosphoproteomics from patients with Multiple Sclerosis characterizes deregulated signaling pathways and reveals new therapeutic targets and drug combinations.
Emergence of hierarchical organization in memory for random material
Authors: Naim Michelangelo , Katkov Mikhail , Recanatesi Stefano , Tsodyks Misha 
Published: February 2019

Structured information is easier to remember and recall than random one. In real life, information exhibits multi-level hierarchical organization, such as clauses, sentences, episodes and narratives in language. Here we show that multi-level grouping emerges even when participants perform memory recall experiments with random sets of words. To quantitatively probe brain mechanisms involved in memory structuring, we consider an experimental protocol where participants perform ‘final free recall’ (FFR) of several random lists of words each of which was first presented and recalled individually. We observe a hierarchy of grouping organizations of FFR, most notably many participants sequentially recalled relatively long chunks of words from each list before recalling words from another list. More-over, participants who exhibited strongest organization during FFR achieved highest levels of performance. Based on these results, we develop a hierarchical model of memory recall that is broadly compatible with our findings. Our study shows how highly controlled memory experiments with random and meaningless material, when combined with simple models, can be used to quantitatively probe the way meaningful information can efficiently be organized and processed in the brain, so to be easily retrieved.Significance StatementInformation that people communicate to each other is highly structured. For example, a story contains meaningful elements of various degrees of complexity (clauses, sentences, episodes etc). Recalling a story, we are chiefly concerned with these meaningful elements and not its exact wording. Here we show that people introduce structure even when recalling random lists of words, by grouping the words into ‘chunks’ of various sizes. Doing so improves their performance. The so formed chunks closely correspond in size to story elements described above. This suggests that our memory is trained to create a structure that resembles the one it typically deals with in real life, and that using random material like word lists can be used to quantitatively probe these memory mechanisms.
Structured event memory: a neuro-symbolic model of event cognition
Authors: Franklin Nicholas T. , Norman Kenneth A. , Ranganath Charan , Zacks Jeffrey M. , Gershman Samuel J. 
Published: February 2019

AbstractHumans spontaneously organize a continuous experience into discrete events and use the learned structure of these events to generalize and organize memory. We introduce theStructured Event Memory(SEM) model of event cognition, which accounts for human abilities in event segmentation, memory, and generalization. SEM is derived from a probabilistic generative model of event dynamics defined over structured symbolic scenes. By embedding symbolic scene representations in a vector space and parametrizing the scene dynamics in this continuous space, SEM combines the advantages of structured and neural network approaches to high-level cognition. Using probabilistic reasoning over this generative model, SEM can infer event boundaries, learn event schemata, and use event knowledge to reconstruct past experience. We show that SEM can scale up to high-dimensional input spaces, producing human-like event segmentation for naturalistic video data, and accounts for a wide array of memory phenomena.
Deep learning reveals cancer metastasis and therapeutic antibody targeting in whole body
Authors: Pan Chenchen , Schoppe Oliver , Parra-Damas Arnaldo , Cai Ruiyao , Todorov Mihail Ivilinov , Gondi Gabor , Neubeck Bettina von , Ghasemi Alireza , Reimer Madita Alice , Coronel Javier , Garvalov Boyan K. , Menze Bjoern , Zeidler Reinhard , Ertürk Ali 
Published: February 2019

SUMMARYReliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipeline for automated quantification of cancer metastases and therapeutic antibody targeting, named DeepMACT. First, we enhanced the fluorescent signal of tumor cells more than 100-fold by applying the vDISCO method to image single cancer cells in intact transparent mice. Second, we developed deep learning algorithms for automated quantification of metastases with an accuracy matching human expert manual annotation. Deep learning-based quantifications in a model of spontaneous metastasis using human breast cancer cells allowed us to systematically analyze clinically relevant features such as size, shape, spatial distribution, and the degree to which metastases are targeted by a therapeutic monoclonal antibody in whole mice. DeepMACT can thus considerably improve the discovery of effective therapeutic strategies for metastatic cancer.Graphical AbstractSupplementary Movies and deep learning algorithms of DeepMACT are available at http://discotechnologies.org/DeepMACT/
Tumor establishment requires tumor autonomous and non-autonomous deregulation of homeostatic feedback control
Authors: Ngo Sang , Liang Jackson , Su Yu-Han , O’Brien Lucy Erin 
Published: February 2019

SummaryIn healthy adult organs, robust feedback mechanisms control cell turnover to enforce homeostatic equilibrium between cell division and death [1, 2]. Nascent tumors must subvert these mechanisms to achieve cancerous overgrowth [3–7]. Elucidating the nature of this subversion can reveal how cancers become established and may suggest strategies to prevent tumor progression. In adultDrosophilaintestine, a well-studied model of homeostatic cell turnover, the linchpin of cell equilibrium is feedback control of the EGF protease Rhomboid (Rho). Expression of Rho in apoptotic cells enables them to secrete EGFs, which stimulate nearby stem cells to undergo replacement divisions [8]. As in mammals, loss ofadenomatous polyposis coli(APC) causesDrosophilaintestinal stem cells to form adenomas [9]. Here we demonstrate thatDrosophila APC−/−tumors trigger widespread Rho expression in non-apoptotic cells, resulting in chronic EGF signaling. Initially, nascentAPC−/−tumors inducerhoin neighbor wild-type cells via acute, non-autonomous activation of JNK. During later growth and multilayering,APC−/−tumors inducerhoin tumor cells by autonomous downregulation of E-cadherin (E-cad) and consequent activity of p120-catenin. This sequential dysregulation of tumor non-autonomous and -autonomous EGF signaling converts tissue-level feedback into feed-forward activation that drives cancerous overgrowth. Since Rho, EGFR, and E-cad are associated with colorectal cancer in humans [10–17], our findings may shed light on how human colorectal tumors progress.