Increasing Student-Teacher Interactions at an Urban Commuter Campus through Instant Messaging and Online Office Hours

Encouraging first year undergraduate students in large lecture-hall classes to seek out and actively engage their professors is a perennial problem in science education. This problem is especially acute for commuter and minority populations. Thus, because personal relationships between students and professors are well known to promote student learning and academic success, fostering new ways to connect students and faculty is essential for reducing attrition at inner-city colleges. In the current study, we demonstrate that the use of instant messaging (IM) is highly effective in fostering student-teacher interactions in the lecture-hall setting of an introductory major-level biology course at John Jay College of Criminal Justice, a senior college within The City University of New York. We found that not only did the use of IM allow more students to directly contact their professors through the internet, but also formed the basis for a personal relationship, leading to increased in-person interaction during office hours. This argues that new internet-based communication technologies can help break down barriers between students and professors at the undergraduate level. We also discuss some of the further enhancements that are possible given these preliminary successes with IM. Clearly, increased use and development of Instant Messaging can play a vital role in the active engagement of students in the learning process

Cultivating Minority Scientists: Undergraduate Research Increases Self-Efficacy and Career Ambitions for Underrepresented Students in STEM

In this study, Social Cognitive Career Theory (SCCT) is used to explore changes in the career intentions of students in an undergraduate research experience (URE) program at a large public minority-serving college. Our URE model addresses the challenges of establishing an undergraduate research program within an urban, commuter, underfunded, Minority-Serving Institution (MSI). However, our model reaches beyond a focus on retention and remediation toward scholarly contributions and shifted career aspirations. From a student’s first days at the College to beyond their graduation, we have encouraged them to explore their own potential as scientists in a coordinated, sequential, and self-reflective process. As a result, while the program’s graduates have traditionally pursued entry-level STEM jobs, graduates participating in mentored research are increasingly focused on professional and academic STEM career tracks involving post-graduate study. In addition to providing an increasingly expected experience and building students’ skills, participation in undergraduate research is seen to have a transformative effect on career ambitions for many students at MSIs. While undergraduate research is often thought of in context of majority-serving institutions, we propose that it serves as a powerful equalizer at MSIs. Building on the institutional characteristics that drive diversity, our students produce scholarly work and pursue graduate degrees, in order to address the long-standing under-representation of minorities in the sciences

A Machine Learning Approach for Using the Postmortem Skin Microbiome to Estimate the Postmortem Interval

Research on the human microbiome, the microbiota that live in, on, and around the human person, has revolutionized our understanding of the complex interactions between microbial life and human health and disease. The microbiome may also provide a valuable tool in forensic death investigations by helping to reveal the postmortem interval (PMI) of a decedent that is discovered after an unknown amount of time since death. Current methods of estimating PMI for cadavers discovered in uncontrolled, unstudied environments have substantial limitations, some of which may be overcome through the use of microbial indicators. In this project, we sampled the microbiomes of decomposing human cadavers, focusing on the skin microbiota found in the nasal and ear canals. We then developed several models of statistical regression to establish an algorithm for predicting the PMI of microbial samples. We found that the complete data set, rather than a curated list of indicator species, was preferred for training the regressor. We further found that genus and family, rather than species, are the most informative taxonomic levels. Finally, we developed a k-nearest- neighbor regressor, tuned with the entire data set from all nasal and ear samples, that predicts the PMI of unknown samples with an average error of ±55 accumulated degree days (ADD). This study outlines a machine learning approach for the use of necrobiome data in the prediction of the PMI and thereby provides a successful proof-of- concept that skin microbiota is a promising tool in forensic death investigations

Direct intra-tumoral injection of zinc-acetate halts tumor growth in a xenograft model of prostate cancer

Intracellular levels of zinc have shown a strong inverse correlation to growth and malignancy of prostate cancer. To date, studies of zinc supplementation in prostate cancer have been equivocal and have not accounted for bioavailability of zinc. Therefore, we hypothesized that direct intra-tumoral injection of zinc could impact prostate cancer growth. In this study, we evaluated the cytotoxic properties of the pH neutral salt zinc acetate on the prostate cancer cell lines PC3, DU145 and LNCaP. Zinc acetate killed prostate cancer cell lines in vitro, independent of androgen sensitivity, in a dose-dependent manner in a range between 200 and 600 μM. Cell death occurred rapidly with 50% cell death by six hours and maximal cell death by 18 hours. We next established a xenograft model of prostate cancer and tested an experimental treatment protocol of direct intra-tumoral injection of zinc acetate. We found that zinc treatments halted the growth of the prostate cancer tumors and substantially extended the survival of the animals, whilst causing no detectable cytoxicity to other tissues. Thus, our studies form a solid proof-of-concept that direct intra-tumoral injection of zinc acetate could be a safe and effective treatment strategy for prostate cancer

Cultivating Minority Scientists: Undergraduate Research Increases Self-Efficacy and Career Ambitions for Underrepresented Students in STEM

In this study, Social Cognitive Career Theory (SCCT) is used to explore changes in the career intentions of students in an undergraduate research experience (URE) program at a large public minorityserving college. Our URE model addresses the challenges of establishing an undergraduate research program within an urban, commuter, underfunded, Minority-Serving Institution (MSI). However, our model reaches beyond a focus on retention and remediation toward scholarly contributions and shifted career aspirations. From a student’s first days at the College to beyond their graduation, we have encouraged them to explore their own potential as scientists in a coordinated, sequential, and self-reflective process. As a result, while the program’s graduates have traditionally pursued entry-level STEM jobs, graduates participating in mentored research are increasingly focused on professional and academic STEM career tracks involving post-graduate study. In addition to providing an increasingly expected experience and building students’ skills, participation in undergraduate research is seen to have a transformative effect on career ambitions for many students at MSIs. While undergraduate research is often thought of in context of majority-serving institutions, we propose that it serves as a powerful equalizer at MSIs. Building on the institutional characteristics that drive diversity, our students produce scholarly work and pursue graduate degrees, in order to address the long-standing under-representation of minorities in the sciences

Phosphatidylinositol 3-Kinase Regulates Macrophage Responses to Double-Stranded RNA and Encephalomyocarditis Virus

Virus infection of macrophages stimulates the expression of proinflammatory and antiviral genes interleukin-1 (IL-1), inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). In this study, we show that phosphatidylinositol 3-kinase (PI3K) is required for the inflammatory response of macrophages to virus infection. When macrophages are infected with encephalomyocarditis virus (EMCV) there is a rapid and transient activation of PI3K and phosphorylation of its downstream target Akt. Inhibitors of PI3K attenuate EMCV- and double-stranded RNA-induced iNOS, COX-2 and IL-1β expression in RAW264.7 cells and mouse peritoneal macrophages. The attenuation of inflammatory gene expression in response to PI3K inhibition correlates with the induction of macrophage apoptosis. The morphology of macrophages shifts from activation in response to EMCV infection to apoptosis in the cells treated with PI3K inhibitors and EMCV. These morphological changes are accompanied by the activation of caspase-3. These findings suggest that PI3K plays a central role in the regulation of macrophage responses to EMCV infection. When PI3K is activated, it participates in the regulation of inflammatory gene expression; however, if PI3K is inhibited macrophages are unable to mount an inflammatory antiviral response and die by apoptosis

A Machine Learning Approach for Using the Postmortem Skin Microbiome to Estimate the Postmortem Interval.

Research on the human microbiome, the microbiota that live in, on, and around the human person, has revolutionized our understanding of the complex interactions between microbial life and human health and disease. The microbiome may also provide a valuable tool in forensic death investigations by helping to reveal the postmortem interval (PMI) of a decedent that is discovered after an unknown amount of time since death. Current methods of estimating PMI for cadavers discovered in uncontrolled, unstudied environments have substantial limitations, some of which may be overcome through the use of microbial indicators. In this project, we sampled the microbiomes of decomposing human cadavers, focusing on the skin microbiota found in the nasal and ear canals. We then developed several models of statistical regression to establish an algorithm for predicting the PMI of microbial samples. We found that the complete data set, rather than a curated list of indicator species, was preferred for training the regressor. We further found that genus and family, rather than species, are the most informative taxonomic levels. Finally, we developed a k-nearest- neighbor regressor, tuned with the entire data set from all nasal and ear samples, that predicts the PMI of unknown samples with an average error of ±55 accumulated degree days (ADD). This study outlines a machine learning approach for the use of necrobiome data in the prediction of the PMI and thereby provides a successful proof-of- concept that skin microbiota is a promising tool in forensic death investigations

Pocket Protein Complexes Are Recruited to Distinct Targets in Quiescent and Proliferating Cells

Biochemical and genetic studies have determined that retinoblastoma protein (pRB) tumor suppressor family members have overlapping functions. However, these studies have largely failed to distinguish functional differences between the highly related p107 and p130 proteins. Moreover, most studies pertaining to the pRB family and its principal target, the E2F transcription factor, have focused on cells that have reinitiated a cell cycle from quiescence, although recent studies suggest that cycling cells exhibit layers of regulation distinct from mitogenically stimulated cells. Using genome-wide chromatin immunoprecipitation, we show that there are distinct classes of genes directly regulated by unique combinations of E2F4, p107, and p130, including a group of genes specifically regulated in cycling cells. These groups exhibit both distinct histone acetylation signatures and patterns of mammalian Sin3B corepressor recruitment. Our findings suggest that cell cycle-dependent repression results from recruitment of an unexpected array of diverse complexes and reveals specific differences between transcriptional regulation in cycling and quiescent cells. In addition, factor location analyses have, for the first time, allowed the identification of novel and specific targets of the highly related transcriptional regulators p107 and p130, suggesting new and distinct regulatory networks engaged by each protein in continuously cycling cells