Miracle-dz/UniFAR-FTUs huggingface dataset:
Mice Lacking Inducible Nitric Oxide Synthase Demonstrate Impaired Killing of Porphyromonas gingivalis

ABSTRACT Porphyromonas gingivalis is a primary etiological agent of generalized severe periodontitis, and emerging data suggest the importance of reactive oxygen and nitrogen species in periodontal tissue damage, as well as in microbial killing. Since nitric oxide (NO) released from inducible NO synthase (iNOS) has been shown to possess immunomodulatory, cytotoxic, and antibacterial effects in experimental models, we challenged iNOS-deficient (iNOS−/−) mice with P. gingivalis by using a subcutaneous chamber model to study the specific contribution of NO to host defense during P. gingivalis infection. iNOS−/− mice inoculated with P. gingivalis developed skin lesions and chamber rejection with higher frequency and to a greater degree than similarly challenged C57BL/6 wild-type (WT) mice. Chamber fluid from iNOS−/− mice possessed significantly more P. gingivalis than that of WT mice. The immunoglobulin G responses to P. gingivalis in serum was similar in WT and iNOS−/− mice, and the inductions of tumor necrosis factor alpha, interleukin-1β and interleukin-6, and prostaglandin E2 were comparable between the two mouse strains. Although no differences in total leukocyte counts in chamber fluids were observed between iNOS−/− and WT mice, the percentage of dead polymorphonuclear leukocytes (PMNs) was significantly greater in iNOS−/− mouse chamber fluids than that of WT samples. Interestingly, casein-elicited PMNs from iNOS−/− mice released more superoxide than did WT PMNs when stimulated with P. gingivalis. These results indicate that modulation of superoxide levels is a mechanism by which NO influences PMN function and that NO is an important element of the host defense against P. gingivalis.
United States Acculturation and Cancer Patients’ End-of-Life Care

Background Culture shapes how people understand illness and death, but few studies examine whether acculturation influences patients’ end-of-life treatment preferences and medical care. Methods and Findings In this multi-site, prospective, longitudinal cohort study of terminally-ill cancer patients and their caregivers (n = 171 dyads), trained interviewers administered the United States Acculturation Scale (USAS). The USAS is a 19-item scale developed to assess the degree of “Americanization” in first generation or non-US born caregivers of terminally-ill cancer patients. We evaluated the internal consistency, concurrent, criterion, and content validity of the USAS. We also examined whether caregivers’ USAS scores predicted patients’ communication, treatment preferences, and end-of-life medical care in multivariable models that corrected for significant confounding influences (e.g. education, country of origin, English proficiency). The USAS measure was internally consistent (Cronbach α = 0.98); and significantly associated with US birthplace (r = 0.66, P<0.0001). USAS scores were predictive of patients’ preferences for prognostic information (AOR = 1.31, 95% CI:1.00–1.72), but not comfort asking physicians’ questions about care (AOR 1.23, 95% CI:0.87–1.73). They predicted patients’ preferences for feeding tubes (AOR = 0.68, 95% CI:0.49–0.99) and wish to avoid dying in an intensive care unit (AOR = 1.36, 95% CI:1.05–1.76). Scores indicating greater acculturation were also associated with increased odds of patient participation in clinical trials (AOR = 2.20, 95% CI:1.28–3.78), compared with lower USAS scores, and greater odds of patients receiving chemotherapy (AOR = 1.59, 95% CI:1.20–2.12). Conclusion The USAS is a reliable and valid measure of “Americanization” associated with advanced cancer patients’ end-of-life preferences and care. USAS scores indicating greater caregiver acculturation were associated with increased odds of patient participation in cancer treatment (chemotherapy, clinical trials) compared with lower scores. Future studies should examine the effects of acculturation on end-of-life care to identify patient and provider factors that explain these effects and targets for future interventions to improve care (e.g., by designing more culturally-competent health education materials).
Modeling Human Inference Process for Textual Entailment Recognition

To prepare an evaluation dataset for textual entailment (TE) recognition, human annotators label rich linguistic phenomena on text and hypothesis expressions. These phenomena illustrate implicit human inference process to determine the relations of given text-hypothesis pairs. This paper aims at understanding what human think in TE recognition process and modeling their thinking process to deal with this problem. At first, we analyze a labelled RTE-5 test set which has been annotated with 39 linguistic phenomena of 5 aspects by Mark Sammons et al . , and find that the negative entailment phenomena are very effective features for TE recognition. Then, a rule-based method and a machine learning method are proposed to extract this kind of phenomena from text-hypothesis pairs automatically. Though the systems with the machine-extracted knowledge cannot be comparable to the systems with human-labelled knowledge, they provide a new direction to think TE problems. We further annotate the negative entailment phenomena on Chinese text-hypothesis pairs in NTCIR-9 RITE-1 task, and conclude the same findings as that on the English RTE-5 datasets.
Single-item predictive validity of the Short-Term Assessment of Risk and Treatability (START) for violent behaviour in outpatient forensic psychiatry

ABSTRACT The single-item predictive validity of the Short-Term Assessment of Risk and Treatability (START) has not been thoroughly investigated, although this has great clinical relevance for the selection of treatment targets. Furthermore, it remains unclear whether the characteristic START additions of scoring strengths next to vulnerabilities and selecting key items, add incremental predictive validity. Finally, predictive validity has primarily been studied in inpatient settings and included mainly patients with a psychotic disorder. We analysed data from a mixed diagnostic sample of 195 forensic psychiatric outpatients with a 3-month and 170 patients with a 6-month follow-up period, using logistic regression analysis. The occurrence of violent or criminal behaviour was established based on the case manager’s recordings in the patient’s file. Only 5 of the 20 START items were found to have predictive validity: Impulse Control, Attitudes, Material Resources, Rule Adherence and Conduct. The last three were the only items for which incremental predictive validity was found with respect to scoring it as a strength and a vulnerability. Selection of key items did not add to the predictive validity. While possibly having therapeutic significance, the scoring of strength next to vulnerability and the selection of key items, may not be beneficial for risk assessment.
Cash flow, earnings, and dividends: A comparison between different valuation methods for Brazilian companies

This paper compares three valuation models – discounted dividends, discounted cash flow, and residual earnings – using financial and accounting data from Brazilian companies, during the period of 1995 to 2004. These approaches should be theoretically equivalent when the respective companies' payoffs are predicted to infinity, but in practice they require predictions over finite horizons. So, the objective of the present study is to assess how these three models perform in finite horizon analysis and in a different financial and economic context. The conclusion was that, among the three models, the cash flow approach presented the best accuracy and explanatory power, having the current stock price as the parameter of comparison. It also had the largest number of valuations considered acceptable. This conclusion diverges from that obtained by some studies performed in other countries like the U.S. (Francis et al., 2000, Penman and Sougiannis, 1998, and Courteau et al., 2000).
GRB060614: a "fake" short GRB from a merging binary system

Context. GRB060614 observations by VLT and by Swift have infringed the traditionally accepted gamma-ray burst (GRB) collapsar scenario that purports the origin of all long duration GRBs from supernovae (SN). GRB060614 is the first nearby long durat ion GRB clearly not associated with a bright Ib/c SN. Moreover, its duration (T90 ∼ 100 s) makes it hardly classifiable as a short GRB. It presents strong similarities with GRB970228, the prototype of a new class of “fake” short GRBs that appear to originate from the coalescence of binary neutron stars or white dwarfs spiraled out into the galactic halo. Aims. Within the “canonical” GRB scenario based on the “fireshell” model, we test if GRB060614 can be a “fake” or “disguised” short GRB. We model the traditionally termed “prompt emission” and discriminate the signal originating from the gravitational collapse leading to the GRB from the process occurring in the circumburst medium (CBM). Methods. We fit GRB060614 light curves in Swift’s BAT (15 − 150 keV) and XRT (0.2− 10 keV) energy bands. Within the fireshell model, light curves are formed by two well defined and different components: the proper-GRB (P-GRB), emitted when the fireshell becomes transparent, and the extended afterglow, due to the interaction between the leftover accelerated baryonic and leptonic shell and the CBM. Results. We determine the two free parameters describing the GRB source within the fireshell model: the total e ± plasma energy (E e ± tot = 2.94× 10 51 erg) and baryon loading (B = 2.8× 10 −3 ). A small average CBM density∼ 10 −3 particles/cm 3 is inferred, typical of galactic halos. The first spikelike emission is identified with the P-GRB and the following prolonged emission with the extended afterglow peak. We obtain very good agreement in the BAT (15− 150 keV) energy band, in what is traditionally called “prompt emission”, and in the XRT (0.2− 10 keV) one. Conclusions. The anomalous GRB060614 finds a natural interpretation within our canonic al GRB scenario: it is a “disguised” short GRB. The total time-integrated extended afterglow luminosity is greater than the P-GRB one, but its peak luminosity is smaller since it is deflated by the peculiarly low average CBM density of gal actic halos. This result points to an old binary system, like ly formed by a white dwarf and a neutron star, as the progenitor of GRB060614 and well justifies the absence of an associated SN Ib /c. Particularly important for further studies of the final merging process ar e the temporal structures in the P-GRB down to 0.1 s.
A reconfigurable mostly-digital ΔΣ ADC with a worst-case FOM of 160dB

A 0.075 mm<sup>2</sup> 65 nm CMOS VCO-based ΔΣ modulator ADC that operates from a single 0.9-1.2 V supply is presented. Its sample-rate, f<sub>s</sub>, is tunable from 1.3-2.4 GHz over which the SNDR spans 70-75 dB, the bandwidth spans 5-37.5 MHz, and the minimum SNDR + 10 log(bandwidth/power dissipation) figure of merit (FOM) is 160 dB.
When Less is Heard than Meets the Ear: Change Deafness in a Telephone Conversation

During a conversation, we hear the sound of the talker as well as the intended message. Traditional models of speech perception posit that acoustic details of a talker's voice are not encoded with the message whereas more recent models propose that talker identity is automatically encoded. When shadowing speech, listeners often fail to detect a change in talker identity. The present study was designed to investigate whether talker changes would be detected when listeners are actively engaged in a normal conversation, and visual information about the speaker is absent. Participants were called on the phone, and during the conversation the experimenter was surreptitiously replaced by another talker. Participants rarely noticed the change. However, when explicitly monitoring for a change, detection increased. Voice memory tests suggested that participants remembered only coarse information about both voices, rather than fine details. This suggests that although listeners are capable of change detection, voice information is not continuously monitored at a fine-grain level of acoustic representation during natural conversation and is not automatically encoded. Conversational expectations may shape the way we direct attention to voice characteristics and perceive differences in voice.
Epidemics on Interconnected Networks

Populations are seldom completely isolated from their environment. Individuals in a particular geographic or social region may be considered a distinct network due to strong local ties but will also interact with individuals in other networks. We study the susceptible-infected-recovered process on interconnected network systems and find two distinct regimes. In strongly coupled network systems, epidemics occur simultaneously across the entire system at a critical infection strength β(c), below which the disease does not spread. In contrast, in weakly coupled network systems, a mixed phase exists below β(c) of the coupled network system, where an epidemic occurs in one network but does not spread to the coupled network. We derive an expression for the network and disease parameters that allow this mixed phase and verify it numerically. Public health implications of communities comprising these two classes of network systems are also mentioned.
Empirical Study on Social Media Marketing Based on Sina Microblog

Social media is a new media platform based on Web2.0, Sina Microblog is the most mature one among the domestic social media platforms. In order to find out the problems and difficulties when using microblog for marketing, 100 enterprises' official accounts were selected as examples. By collecting and analyzing the data of each enterprise, many problems have been found. Many small and medium enterprises didn't take a full advantage of social media, and how to have quality interaction with fans didn't receive enough attention by most enterprises. In the meantime, the corresponding problem-solving methods have been presented: mark, management, measure, moderate, which is very useful for social media marketing.
Monetizing Social Value Creation – A Business Model Approach

The creation of social value through entrepreneurial ventures occurs in various dimensions, which are often difficult to compare. From an economic standpoint, however, value creation requires resources and activities that lead to expenditures. The sustainability of social ventures, therefore, depends on how these expenditures are financed. We develop a general framework in which business models of diverse social ventures can be analyzed and categorized. Using a gallery of real-life case studies, we illustrate that social business models can be characterized and ordered by the degree to which they monetize social value creation and the level of generated market revenues in excess of expenditures. Our analysis reveals a positive correlation between the monetization of social value creation and financial output, and it shows that relatively simple changes in the business model can have a significant impact on monetization and market performance. Our framework thus yields several strategic implications for business modeling.
2′-O-Methyl RNA/Ethylene-Bridged Nucleic Acid Chimera Antisense Oligonucleotides to Induce Dystrophin Exon 45 Skipping

Duchenne muscular dystrophy (DMD) is a fatal muscle-wasting disease characterized by dystrophin deficiency from mutations in the dystrophin gene. Antisense oligonucleotide (AO)-mediated exon skipping targets restoration of the dystrophin reading frame to allow production of an internally deleted dystrophin protein with functional benefit for DMD patients who have out-of-frame deletions. After accelerated US approval of eteplirsen (Exondys 51), which targets dystrophin exon 51 for skipping, efforts are now focused on targeting other exons. For improved clinical benefits, this strategy requires more studies of the delivery method and modification of nucleic acids. We studied a nucleotide with a 2′-O,4′-C-ethylene-bridged nucleic acid (ENA), which shows high nuclease resistance and high affinity for complementary RNA strands. Here, we describe the process of developing a 2′-O-methyl RNA(2′-OMeRNA)/ENA chimera AO to induce dystrophin exon 45 skipping. One 18-mer 2′-OMeRNA/ENA chimera (AO85) had the most potent activity for inducing exon 45 skipping in cultured myotubes. AO85 was administered to mdx mice without significant side effects. AO85 transfection into cultured myotubes from 13 DMD patients induced exon 45 skipping in all samples at different levels and dystrophin expression in 11 patients. These results suggest the possible efficacy of AO-mediated exon skipping changes in individual patients and highlight the 2′-OMeRNA/ENA chimera AO as a potential fundamental treatment for DMD.
Preferential binding of K+ ions in the selectivity filter at equilibrium explains high selectivity of K+ channels

K+ channels exhibit strong selectivity for K+ ions over Na+ ions based on electrophysiology experiments that measure ions competing for passage through the channel. During this conduction process, multiple ions interact within the region of the channel called the selectivity filter. Ion selectivity may arise from an equilibrium preference for K+ ions within the selectivity filter or from a kinetic mechanism whereby Na+ ions are precluded from entering the selectivity filter. Here, we measure the equilibrium affinity and selectivity of K+ and Na+ ions binding to two different K+ channels, KcsA and MthK, using isothermal titration calorimetry. Both channels exhibit a large preference for K+ over Na+ ions at equilibrium, in line with electrophysiology recordings of reversal potentials and Ba2+ block experiments used to measure the selectivity of the external-most ion-binding sites. These results suggest that the high selectivity observed during ion conduction can originate from a strong equilibrium preference for K+ ions in the selectivity filter, and that K+ selectivity is an intrinsic property of the filter. We hypothesize that the equilibrium preference for K+ ions originates in part through the optimal spacing between sites to accommodate multiple K+ ions within the selectivity filter.
Longitudinal membrane function in functionally anuric patients treated with APD: data from EAPOS on the effects of glucose and icodextrin prescription.

BACKGROUND Peritoneal dialysis is associated with changes in membrane function that can lead eventually to ultrafiltration (UF) failure. Factors driving these changes are thought to include hypertonic glucose exposure, but previously reported associations are confounded by the presence of residual renal function. METHODS Longitudinal membrane function (solute transport and UF capacity) were measured annually in a prospective cohort of 177 functionally anuric patients as part of the European Automated Peritoneal Dialysis Outcomes Study (EAPOS). Subgroup analysis was performed according to glucose exposure and icodextrin use at baseline. RESULTS The whole cohort experienced an increase in solute transport and reduction in UF capacity at 12 and 24 months that could not be explained by informative censoring. These changes were accelerated and more severe in patients using either 2.27% or 3.86% glucose, or those not using icodextrin at baseline. These differences could not be explained by age, comorbidity score, previous time spent on renal replacement, differential dropout from the study, peritonitis rates, or, by definition, residual renal function. Patients using icodextrin at baseline had worse membrane function and were more likely to be diabetic. There was an association between membrane function changes and achieved 24-hour ultrafiltration over the 2-year study period. CONCLUSION Anuric automated peritoneal dialysis (APD) patients experience significant detrimental changes in membrane function over a relatively short time period. Glucose appears to enhance these changes independent of residual renal function. Icodextrin use in these circumstances is associated with less deterioration in membrane function.
Efficacy of Capecitabine Plus Oxaliplatin Combination Chemotherapy for Advanced Pancreatic Cancer after Failure of First-Line Gemcitabine-Based Therapy

Background/Aims Second-line chemotherapy in patients with advanced pancreatic ductal adenocarcinoma (PDAC) that progresses following gemcitabine-based treatment has not been established. This study aimed to investigate the efficacy and safety of second-line combination chemotherapy with capecitabine and oxaliplatin (XELOX) in these patients. Methods Between August 2011 and May 2014, all patients who received at least one cycle of XELOX (capecitabine, 1,000 mg/m2 twice daily for 14 days; oxaliplatin, 130 mg/m2 on day 1 of a 3-week cycle) combination chemotherapy for unresectable or recurrent PDAC were retrospectively recruited. The response was evaluated every 9 weeks, and the tumor response rate, progression-free survival and overall survival, and adverse events were assessed. Results Sixty-two patients were included; seven patients (11.3%) had a partial tumor response, and 20 patients (32.3%) had stable disease. The median progression-free and overall survival were 88 days (range, 35.1 to 140.9 days) and 158 days (range, 118.1 to 197.9 days), respectively. Patients who remained stable longer with frontline therapy (≥120 days) exhibited significantly longer progression-free and overall survival. The most common grade 3 to 4 adverse events in patients were vomiting (8.1%) and anorexia (6.5%). There was one treatment-related mortality caused by severe neutropenia and typhlitis. Conclusions Second-line XELOX combination chemotherapy demonstrated an acceptable response and survival rate in patients with advanced PDAC who had failed gemcitabine-based chemotherapy.
Breaking the curse of kernelization: budgeted stochastic gradient descent for large-scale SVM training

Online algorithms that process one example at a time are advantageous when dealing with very large data or with data streams. Stochastic Gradient Descent (SGD) is such an algorithm and it is an attractive choice for online Support Vector Machine (SVM) training due to its simplicity and effectiveness. When equipped with kernel functions, similarly to other SVM learning algorithms, SGD is susceptible to the curse of kernelization that causes unbounded linear growth in model size and update time with data size. This may render SGD inapplicable to large data sets. We address this issue by presenting a class of Budgeted SGD (BSGD) algorithms for large-scale kernel SVM training which have constant space and constant time complexity per update. Specifically, BSGD keeps the number of support vectors bounded during training through several budget maintenance strategies. We treat the budget maintenance as a source of the gradient error, and show that the gap between the BSGD and the optimal SVM solutions depends on the model degradation due to budget maintenance. To minimize the gap, we study greedy budget maintenance methods based on removal, projection, and merging of support vectors. We propose budgeted versions of several popular online SVM algorithms that belong to the SGD family. We further derive BSGD algorithms for multi-class SVM training. Comprehensive empirical results show that BSGD achieves higher accuracy than the state-of-the-art budgeted online algorithms and comparable to non-budget algorithms, while achieving impressive computational efficiency both in time and space during training and prediction.