Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitochondria DNA Change and Oxidative Damage in Clinically Stable Patients with Major Depressive Disorder

Background To compare alterations of mitochondria DNA (mtDNA) copy number, single nucleotide polymorphisms (SNPs), and oxidative damage of mtDNA in clinically stable patients with major depressive disorder (MDD). Methods Patients met DSM-IV diagnostic criteria for MDD were recruited from the psychiatric outpatient clinic at Changhua Christian Hospital, Taiwan. They were clinically stable and their medications had not changed for at least the preceding two months. Exclusion criteria were substance-induced psychotic disorder, eating disorder, anxiety disorder or illicit substance abuse. Comparison subjects did not have any major psychiatric disorder and they were medically healthy. Peripheral blood leukocytes were analyzed to compare copy number, SNPs and oxidative damage of mtDNA between the two groups. Results 40 MDD patients and 70 comparison subjects were collected. The median age of the subjects was 42 years and 38 years in MDD and comparison groups, respectively. Leukocyte mtDNA copy number of MDD patients was significantly lower than that of the comparison group (p = 0.037). MDD patients had significantly higher mitochondrial oxidative damage than the comparison group (6.44 vs. 3.90, p<0.001). After generalized linear model adjusted for age, sex, smoking, family history, and psychotropic use, mtDNA copy number was still significantly lower in the MDD group (p<0.001). MtDNA oxidative damage was positively correlated with age (p<0.001) and MDD (p<0.001). Antipsychotic use was negatively associated with mtDNA copy number (p = 0.036). Limitations The study is cross-sectional with no longitudinal follow up. The cohort is clinically stable and generalizability of our result to other cohort should be considered. Conclusions Our study suggests that oxidative stress and mitochondria may play a role in the pathophysiology of MDD. More large-scale studies are warranted to assess the interplay between oxidative stress, mitochondria dysfunction and MDD.
Atomic spectrometry update. Environmental analysis

This is the twentieth annual review published in JAAS of the application of atomic spectrometry to the chemical analysis of environmental samples. In the analysis of air, there is ongoing development of instrumentation for continuous emission monitoring and as a means of interrogating the composition of individual airborne particulates. Developments in mass spectrometry applications continue to be an active area of research where the advantages of low detection limits and abilities to perform isotopic measurements are being exploited. There is growing interest in performing speciation measurements in water and this is being aided by the development of hyphenated techniques, most notably via the coupling of chromatographic systems to ICP-MS. Dominant themes in the analysis of soils include the optimization of preconcentration (and matrix separation) techniques, development of speciation protocols, notably arsenic and the increased use of portable XRF systems for in situ analysis. In geological analysis, laser ablation as an analytical tool is attracting a wider audience. Multi-collector ICP-MS is increasingly being used in a number of geological facilities to perform high precision isotope ratio measurements.
Overexpressing Breast Cancer Cells − 3-Gallate in Her-2 / neu Resistance to the Green Tea Polyphenol Epigallocatechin Mitogen-Activated Protein Kinase Signaling as a Mediator of Microarray-Assisted Pathway Analysis Identifies

Overexpression of the epidermal growth factor receptor family member Her-2/neu in breast cancer leads to autophosphorylation of the receptor and induction of multiple downstream signaling pathways, including the Akt kinase to nuclear factor-nB (NF-nB) cascade that is associated with poor prognosis. Previously, we showed that the green tea polyphenol epigallocatechin 3-gallate (EGCG) inhibits growth of NF639 Her-2/neu–driven breast cancer cells via reducing receptor autophosphorylation and downstream Akt and NF-nB activities. Interestingly, upon prolonged culture in the presence of EGCG, cells resistant to the polyphenol could be isolated. Here, we report that resistant cells have lost tyrosine phosphorylation on the Her-2/neu receptor. Surprisingly, they displayed elevated NF-nB activity, and inhibition of this activity sensitized cells to EGCG. Data from microarray studies of the original and resistant NF639 populations of cells were subjected to Gene Set Enrichment Analysis pathway assessment, which revealed that the mitogen activated protein kinase (MAPK) pathway was activated in the resistant cells. Treatment of the resistant cells with the MAPK inhibitor U0216 reduced growth in soft agar and invasive phenotype, whereas the combination of EGCG and U0216 resulted in cells with a cobblestone epithelial phenotype. Thus, activation of the MAPK pathway mediates resistance to EGCG. (Cancer Res 2006; 66(10): 5322-9)
Improved side-chain modeling by coupling clash-detection guided iterative search with rotamer relaxation

MOTIVATION Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy. RESULTS We present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling. AVAILABILITY CIS-RR is available to non-commercial users at our website: http://jianglab.ibp. ac.cn/lims/cisrr/cisrr.html.
Generation of purified oligodendrocyte progenitors from embryonic stem cells

Demyelination is a key component in the pathogenesis of many neurological disorders. Transplantation of myelinating cells may offer a therapeutic approach to restore neurological function in these diseases. Recent findings suggest that pluripotent embryonic stem (ES) cells can serve as an unlimited donor source for neural transplantation. The clinical application of ES cells for myelin repair will depend critically on the ability to enrich oligodendroglial progenitors in high purity. Combining controlled differentiation in the presence of growth factors and genetic lineage selection, we devised a cell culture protocol yielding highly purified oligodendrocyte progenitors. Murine ES cell clones stably transfected with a construct encoding the β‐ galactosidase‐neomycine phosphotransferase fusion protein (βgeo) under control of the 2′3′‐ cyclic nucleotide 3′‐phosphodiesterase (CNP) promoter were differentiated into bipotential glial precursors. Subsequent induction of a CNP‐positive stage and selection in neomycine resulted in a homogenous cell population with a pre‐oligodendrocyte phenotype. The selected cells continued to proliferate in the presence of FGF‐2 and PDGF and, upon growth factor withdrawal, differentiated into mature galactocerebroside (GalC)‐positive oligodendrocytes. Transplantation studies in myelin‐deficient (md) rats indicate that ES cell‐derived oligodendrocyte progenitors generated with this method may serve as an attractive donor source for myelin repair.
Parameter Identifiability of Monostatic MIMO Chaotic Radar Using Compressed Sensing

Compressed sensing (CS) has attracted significant attention in the radar community. The better understanding of CS theory has led to substantial improvements over existing methods in CS radar. But there are also some challenges that should be resolved in order to benefit the most from CS radar, such as radar signal with low signal to noise ratio (Low-SNR). In this paper, we will focuses on monostatic chaotic multiple-inputmultiple-output (MIMO) radar systems and analyze theoretically and numerically the performance of sparsityexploiting algorithms for the parameter estimation of targets at LowSNR. The novelty of this paper is that it capitalizes on chaotic coded waveform to construct measurement operator incoherent with noise and singular value decomposition (SVD) to suppress noise. In order to improve the robustness of azimuth estimation interpolation method is applied to construction of sparse bases. The gradient pursuit (GP) algorithm for reconstruction is implemented at Low-SNR. Finally, the conclusions are all demonstrated by simulation experiments.
Multivariate Probit Analysis of Binary Time Series Datawith Missing

SUMMARY The development of adequate models for binary time series data with covariate adjustment has been an active research area in the last years. In the case, where interest is focused on marginal and association parameters, generalized estimating equations (GEE) (see for example Lipsitz, Laird and Harrington (1991) and Liang, Zeger and Qaqish (1992)) and likelihood (see for example Fitzmaurice and Laird (1993) and Molenberghs and Lesaare (1994)) based methods have been proposed. The number of parameters required for the full speciication of these models grows exponentially with the length of the binary time series. Therefore, the analysis is often focused on marginal and rst order parameters. In this case, the multivariate probit model (Ashford and Sowden (1970)) becomes an attractive alternative to the above models. The application of the multivariate probit model has been hampered by the intractability of the maximum likelihood estimator, when the length of the binary time series is large. This paper shows that this diiculty can be overcome by the use of Markov Chain Monte Carlo methods. This analysis also allows for valid point and interval estimates of the parameters in small samples. In addition, the analysis is adopted to handle the case of missing at random responses. The approach is illustrated on data involving binary responses measured at unequally spaced time points. Finally, this data analysis is compared to a GEE analysis given in Fitzmaurice and Lipsitz (1995).
Measuring School–Family Conflict and Enrichment in University Student Parents: A Measurement Validation Study

The purpose of this study was to extend work–family research to the school–family context by adapting Carlson and colleagues’ Work–Family Conflict and Enrichment scales. Using two samples of student parents primarily from Canadian universities, the adapted scales were assessed for reliability, construct validity, and factor structure. The measures had three factors for school–family conflict (school-to-family conflict, behaviour-based conflict, and family-to-school conflict) and five for school–family enrichment (school-to-family growth and affect; and family-to-school development, affect, and efficiency). The two adapted scales were confirmed to be reliable and valid for use with university student parents. Data from the confirmatory factor analysis provided strong support for the factor structure of the School–Family Enrichment Scale, but suggested that additional testing and development of the School–Family Conflict Scale may be required.
Named Entity Tagging a Very Large Unbalanced Corpus: Training and Evaluating NE Classifiers

We describe a systematic and application-oriented approach to training and evaluating named entity recognition and classification (NERC) systems, the purpose of which is to identify an optimal system and to train an optimal model for named entity tagging DeReKo, a very large general-purpose corpus of contemporary German (Kupietz et al., 2010). DeReKo ‘s strong dispersion wrt. genre, register and time forces us to base our decision for a specific NERC system on an evaluation performed on a representative sample of DeReKo instead of performance figures that have been reported for the individual NERC systems when evaluated on more uniform and less diverse data. We create and manually annotate such a representative sample as evaluation data for three different NERC systems, for each of which various models are learnt on multiple training data. The proposed sampling method can be viewed as a generally applicable method for sampling evaluation data from an unbalanced target corpus for any sort of natural language processing.
Labour Market Institutions and Unemployment in Europe and OECD – a Survey Christian Spielmann preliminary draft

There are many descriptions of how unemployment in Europe and other OECD countries evolved over time (see for example Blanchard (2005) for an overview). In this respect, Europe has been a puzzling case with high and persistent unemployment rates. In short: Unemployment in Europe was low in the 1960s and it increased in the 1970s and 80s. Since then, unemployment has become highly heterogeneous across Europe. Some countries managed to reduce their unemployment rate to lower levels, others remained on a high plateau.
TEMU: Binary Code Analysis via Whole-System Layered Annotative Execution

Dynamic binary analysis has demonstrated its strength insolving a wide-spectrum of computer security problems, suchas malware analysis, protocol reverse engineering, vulner-ability detection, diagnosis, and defense, software testing,etc. An extensible platform for dynamic binary analysisprovides a foundation for solving these problems. To enablea variety of applications, we explore a unique design space.We aim to provide a whole-system view, take an externalapproach, facilitate ﬁne-grained instrumentation, and havesuﬃcient eﬃciency. These design goals bringabout anew ar-chitecture, namely
An ultra low power LNA with 15dB gain and 4.4db NF in 90nm CMOS process for 60 GHz phase array radio

This paper presents a 60 GHz LNA designed in a 90 nm CMOS process with 6 metals Cu thick metal, and Ft/Fmax of 100 GHz/150 GHz demonstrating best known noise figure, gain, power consumption and size compared to earlier 60-GHz LNAs reported. It features 15 dB of gain, a measured noise figure (NF) of 4.4 dB, while drawing 3 mA from a 1.3-V supply. The use of spiral inductors enables a reduction in transistor size, total power consumption, and die size. The LNA die area with/without pads is 0.32times0. 44 mm2/0.14times0. 27 mm2 respectively. First pass success was achieved by proper methodology of closed ground environment for passive structures and proper layout. The paper compares different transistor core sizes and different circuit topologies showing that a common source (CS) topology with a 10times1 um transistor width gives the best performance over all other options.
Looking for query terms on search engine results pages

Understanding the behaviors people employ when using a search system is important for developing systems that better serve users. More detailed knowledge of where searchers focus their visual attention is important to understanding how searchers use search results lists when reformulating queries. While observation of visual scanning has been used in the study of relevance judgments, to our knowledge the study reported here is the first to investigate visual attention to query terms. The study presented in this paper utilized eye-tracking to investigate the frequency with which people looked at (fixated on) their query terms when the terms appeared on search engine results pages. Results show that people fixated on some of the displayed query terms; however, they fixated on other words and parts of the page more frequently.
A Network Study of Chinese Medicine Xuesaitong Injection to Elucidate a Complex Mode of Action with Multicompound, Multitarget, and Multipathway

Chinese medicine has evolved from thousands of years of empirical applications and experiences of combating diseases. It has become widely recognized that the Chinese medicine acts through complex mechanisms featured as multicompound, multitarget and multipathway. However, there is still a lack of systematic experimental studies to elucidate the mechanisms of Chinese medicine. In this study, the differentially expressed genes (DEGs) were identified from myocardial infarction rat model treated with Xuesaitong Injection (XST), a Chinese medicine consisting of the total saponins from Panax notoginseng (Burk.) F. H. Chen (Chinese Sanqi). A network-based approach was developed to combine DEGs related to cardiovascular diseases (CVD) with lines of evidence from the literature mining to investigate the mechanism of action (MOA) of XST on antimyocardial infarction. A compound-target-pathway network of XST was constructed by connecting compounds to DEGs validated with literature lines of evidence and the pathways that are functionally enriched. Seventy potential targets of XST were identified in this study, of which 32 were experimentally validated either by our in vitro assays or by CVD-related literatures. This study provided for the first time a network view on the complex MOA of antimyocardial infarction through multiple targets and pathways.
Teacher identities and English learners in mainstream classrooms: A discourse analysis

ABSTRACT The increasing placement of English learners (ELs) in mainstream classrooms in conjunction with scant attention given to teaching these students in preservice education and professional development suggests a need to better understand how mainstream teachers understand their professional identities as teachers of these students. The purpose of this qualitative study was to gain insight on how two mainstream teachers of ELs use language to construct their teacher identities and their engagement with EL students. Participants were interviewed multiple times and discourse analysis was employed to analyze their use of language. Overall, their teacher identities possessed a value for ELs being comfortable and welcomed in the classroom. However, participants positioned linguistic differences between ELs and themselves as barriers to learning and communication. The findings suggest a need to move beyond an inclusive disposition toward supporting mainstream teachers to recognize the development of ELs’ academic and language progress as integral to their professional identities.
The Changing Role of Teachers of Students Who are Deaf or Hard of Hearing: Consultation as an Increasing Part of the Job

ABSTRACT The majority of deaf and hard of hearing (DHH) students are educated at least part of the day in general education classrooms taught by teachers who may not have any experience working with this population. DHH students make up a unique, heterogeneous group with a wide range of communication modalities, technology utilization, early intervention experiences, and educational placements. In addition to providing direct service to support these students, teachers of students who are deaf or hard of hearing (ToDHH) collaborate and consult with classroom teachers and school staff on classroom accommodations and modifications. However, recent research shows that ToDHH often feel unprepared to engage in the consultative aspect of their role. Since the Education for All Handicapped Children Act was passed 43 years ago, the field of deaf education has increasingly called for research on consultation models to apply to their unique population and to teach in their teacher preparation programs. This article identifies the characteristics of DHH learners and synthesizes current research on consultation in the field of deaf education. Three consultation models are examined to determine their level of fit within the field of deaf education. The author ends with a call for future research that can best be met through an interdisciplinary research approach between the field of deaf education and the fields of educational and psychological consultation.
Value‐Based Routing and Preference‐Based Routing in Customer Contact Centers

Telephone call centers and their generalizations—customer contact centers—usually handle several types of customer service requests (calls). Since customer service representatives (agents) have different call‐handling abilities and are typically cross‐trained in multiple skills, contact centers exploit skill‐based routing (SBR) to assign calls to appropriate agents, aiming to respond properly as well as promptly. Established agent‐staffing and SBR algorithms ensure that agents have the required call‐handling skills and that call routing is performed so that constraints are met for standard congestion measures, such as the percentage of calls of each type that abandon before starting service and the percentage of answered calls of each type that are delayed more than a specified number of seconds. We propose going beyond traditional congestion measures to focus on the expected value derived from having particular agents handle various calls. Expected value might represent expected revenue or the likelihood of first‐call resolution. Value might also reflect agent call‐handling preferences. We show how value‐based routing (VBR) and preference‐based routing (PBR) can be introduced in the context of an existing SBR framework, based on static‐priority routing using a highly‐structured priority matrix, so that constraints are still met for standard congestion measures. Since an existing SBR framework is used to implement VBR and PBR, it is not necessary to replace the automatic call distributor (ACD). We show how mathematical programming can be used, with established staffing requirements, to find a desirable priority matrix. We select the priority matrix to use during a specified time interval (e.g., 30‐minute period) by maximizing the total expected value over that time interval, subject to staffing constraints.
Differential attentional bias in generalized anxiety disorder and panic disorder

Background Cognitive theorists relate anxiety disorders to the way in which emotional information is processed. The existing research suggests that patients with anxiety disorders tend to allocate their attention toward threat-related information selectively, and this may differ among different types of anxious subjects. The aim of this study was to explore attentional bias in patients with generalized anxiety disorder (GAD) and panic disorder (PD) using the emotional Stroop task and compare the differences between them. Methods Forty-two patients with GAD, 34 patients with PD, and 46 healthy controls performed the emotional Stroop task with four word types, ie, GAD-related words, PD-related words, neutral words, and positive words. Results Patients with GAD and those with PD were slower than healthy controls to respond to all stimuli. Patients with GAD had longer response latencies in color-naming both PD-relevant words and GAD relevant words. Patients with PD had longer response latencies only in color-naming PD-related words, similar to healthy controls. Conclusion Patients with GAD and those with PD had a different pattern of attentional bias, and there was insufficient evidence to support the existence of specific attentional bias in patients with PD.