Implementing Total Quality Management in a College of Business

Today, a wide range of organizations are involved in what is commonly referred to as total quality management (TQM). Implementation and associated research have primarily been focused in the business community; however, over the past decade, faced with dwindling enrollment and increased competition, the educational community has also started to embrace TQM at differing levels in a wide variety of settings across the nation, ranging from doctoral granting institutions to community colleges to elementary schools. This descriptive case study examined the implementation of a TQM process at a College of Business in a large state university on the west coast. Using the methodology of participant observation, the researcher was able to document the successful, yet difficult struggle to implement TQM in the College. This study also examined the influence patterns which occurred among team members, the level of training necessary, which TQM tools were the most effective, and what aspects of the process the participants believed were worthwhile. Results indicated that significant quality improvements were made within the College by some of the teams. As a result of the team process, many indirect gains occurred in the areas of job satisfaction, improved co-worker relationships, and office harmony. Although TQM can be successfully implemented within an educational setting, it is difficult because the most salient principles necessary to the TQM model are virtually unknown in higher education. Thus, ideally the overall zeitgeist of administration and faculty must be changed to reflect an emphasis on customer focus and process orientation. Further, the change effort must be built on the principles of empowerment and mutual trust because without these, the participants will maintain the status-quo

High-Performance Atomically-Thin Room-Temperature NO2 Sensor.

The development of room-temperature sensing devices for detecting small concentrations of molecular species is imperative for a wide range of low-power sensor applications. We demonstrate a room-temperature, highly sensitive, selective, stable, and reversible chemical sensor based on a monolayer of the transition-metal dichalcogenide Re0.5Nb0.5S2. The sensing device exhibits a thickness-dependent carrier type, and upon exposure to NO2 molecules, its electrical resistance considerably increases or decreases depending on the layer number. The sensor is selective to NO2 with only minimal response to other gases such as NH3, CH2O, and CO2. In the presence of humidity, not only are the sensing properties not deteriorated but also the monolayer sensor shows complete reversibility with fast recovery at room temperature. We present a theoretical analysis of the sensing platform and identify the atomically sensitive transduction mechanism

Sculpting Liquids with Two-Dimensional Materials: The Assembly of Ti3C2Tx MXene Sheets at Liquid–Liquid Interfaces

The self-assembly of nanoscale materials at the liquid–liquid interface allows for fabrication of three-dimensionally structured liquids with nearly arbitrary geometries and tailored electronic, optical, and magnetic properties. Two-dimensional (2D) materials are highly anisotropic, with thicknesses on the order of a nanometer and lateral dimensions upward of hundreds of nanometers to micrometers. Controlling the assembly of these materials has direct implications for their properties and performance. We here describe the interfacial assembly and jamming of Ti3C2Tx MXene nanosheets at the oil–water interface. Planar, as well as complex, programmed three-dimensional all-liquid objects are realized. Our approach presents potential for the creation of all-liquid 3D-printed devices for possible applications in all-liquid electrochemical and energy storage devices and electrically active, all-liquid fluidics that exploits the versatile structure, functionality, and reconfigurability of liquids

Department of Pathology, Thomas Jefferson University, Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors.

BACKGROUND: Although numerous mouse models of breast carcinomas have been developed, we do not know the extent to which any faithfully represent clinically significant human phenotypes. To address this need, we characterized mammary tumor gene expression profiles from 13 different murine models using DNA microarrays and compared the resulting data to those from human breast tumors. RESULTS: Unsupervised hierarchical clustering analysis showed that six models (TgWAP-Myc, TgMMTV-Neu, TgMMTV-PyMT, TgWAP-Int3, TgWAP-Tag, and TgC3(1)-Tag) yielded tumors with distinctive and homogeneous expression patterns within each strain. However, in each of four other models (TgWAP-T121, TgMMTV-Wnt1, Brca1Co/Co;TgMMTV-Cre;p53+/- and DMBA-induced), tumors with a variety of histologies and expression profiles developed. In many models, similarities to human breast tumors were recognized, including proliferation and human breast tumor subtype signatures. Significantly, tumors of several models displayed characteristics of human basal-like breast tumors, including two models with induced Brca1 deficiencies. Tumors of other murine models shared features and trended towards significance of gene enrichment with human luminal tumors; however, these murine tumors lacked expression of estrogen receptor (ER) and ER-regulated genes. TgMMTV-Neu tumors did not have a significant gene overlap with the human HER2+/ER- subtype and were more similar to human luminal tumors. CONCLUSION: Many of the defining characteristics of human subtypes were conserved among the mouse models. Although no single mouse model recapitulated all the expression features of a given human subtype, these shared expression features provide a common framework for an improved integration of murine mammary tumor models with human breast tumors

Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors

Comparison of mammary tumor gene-expression profiles from thirteen murine models using microarrays and with that of human breast tumors showed that many of the defining characteristics of human subtypes were conserved among mouse models

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.