Attitudes Toward Marriage and Long-term Relationships across Emerging Adulthood

The current study expands upon existing developmental research on marital attitude change by examining how attitudes toward marriage and long-term relationships may vary across emerging adulthood. Utilizing five waves of data from the Center on Young Adult Health and Development’s College Life Study, discrete-time survival analysis and latent basis growth curve analysis are employed to assess the change—and predictors of such change—in three measures of relationship attitudes (desire for marriage, desire for long-term relationships, and importance of marriage and long-term relationships) of over 900 college students. Results indicate positive change in all three measures of attitudes, with most emerging adults desiring and placing importance on marriage and long-term relationships from the very beginning of college. Predictors of attitude change included sex, race, experience of parental death, student status, educational aspirations, and total number of sex partners. Results suggest a need for more longitudinal research in this area

The intellectual and moral integrity of bioethics: response to commentaries on A case study in unethical transgressive bioethics: \u27Letter of concern from bioethicists\u27 about the prenatal administration of dexamethasone .

In our target article we showed that the Letter of Concern (LoC) fails to meet accepted standards for presenting empirical data for the purpose of supplementing a normative claim and for argument-based normative ethics. The LoC fails to meet the standards of evidence-based reasoning by making false claims, failing to reference data that undermine its key premises, and misrepresenting and misinterpreting the scientific publications it selectively references. The LoC fails to meet the standards of argument-based reasoning by treating as settled matters what are, instead, ongoing controversies, offering “mere opinion” as a substitute for argument, and making contradictory claims. The LoC is methodologically defective and thus a case study in unethical transgressive bioethics. Not withdrawing the LoC will damage the field of bioethics, making this case study in unethical transgressive bioethics important for the entire field

Mycotoxins in Corn Distillers Grains A Concern in Ruminants?

The main fungi that produce toxins during storage belong to three genera: Aspergillus, Fusarium, and Penicillium. When dealing with cattle diets, it is not easy to correlate the presence of mycotoxins to that of molds. The same types of molds can produce different types of toxins, and different types of molds can produce the same mycotoxin. When addressing mycotoxicosis, the fact that multiple ingredients usually make up a dairy cattle diet can be viewed both positively and negatively. On the one hand, multiple feeds dilute the toxins from any given feed, resulting in a safer diet. On the other hand, because the effect of toxins can be additive, if there are multiple contaminated feeds, the toxic effect of the feeds will be compounded. The primary toxins of concern are aflatoxin, zearalenone, trichothecene, fumonisin, ochratoxin, and patulin

Sulfur in Distillers Grains for Dairy Cattle

Sulfur is an essential element needed by animals for many functions. About 0.15% of body weight is sulfur. It is found in the amino acids methionine, cysteine, cystine, homocysteine, and taurine; in chondroitin sulfate of cartilage; and in the B-vitamins thiamin and biotin. Methionine, thiamin, and biotin cannot be synthesized in cattle tissues, so they must be supplied in the diet or synthesized by ruminal microbes. The sulfur content of most feed sources reflects the sulfur amino acid content of the proteins in the feed. See table 1 for example sulfur concentrations for various feed ingredients

A case study in unethical transgressive bioethics: Letter of concern from bioethicists about the prenatal administration of dexamethasone.

On February 3, 2010, a Letter of Concern from Bioethicists, organized by fetaldex.org, was sent to report suspected violations of the ethics of human subjects research in the off-label use of dexamethasone during pregnancy by Dr. Maria New. Copies of this letter were submitted to the FDA Office of Pediatric Therapeutics, the Department of Health and Human Services (DHHS) Office for Human Research Protections, and three universities where Dr. New has held or holds appointments. We provide a critical appraisal of the Letter of Concern and show that it makes false claims, misrepresents scientific publications and websites, fails to meet standards of evidence-based reasoning, makes undocumented claims, treats as settled matters what are, instead, ongoing controversies, offers mere opinion as a substitute for argument, and makes contradictory claims. The Letter of Concern is a case study in unethical transgressive bioethics. We call on fetaldex.org to withdraw the letter and for co-signatories to withdraw their approval of it

Use of Glucagon to Prevent and Treat Fatty Liver in Transition Dairy Cows

Because of the relationship of fatty liver to increase health problems and decreased productive and reproductive performance, scientists can improve the profitability of dairy farmers by developing nutritional and management technologies for preventing and treating fatty liver. Our research group has demonstrated that glucagon shows much promise for use in preventing and treating fatty liver in transition cows. Moreover, we have data to indicate that ultrasound technology can be used to estimate the incidence of fatty liver within a dairy herd. The development of a slow-release form of glucagon would seem necessary before adoption of our proposed glucagon technology is adopted by the dairy industry

Visualization of the Genesis and Fate of Isotype-switched B Cells during a Primary Immune Response

The life history of isotype-switched B cells is unclear, in part, because of an inability to detect rare antigen-specific B cells at early times during the immune response. To address this issue, a small population of B cells carrying targeted antibody transgenes capable of class switching was monitored in immunized mice. After contacting helper T cells, the first switched B cells appeared in follicles rather than in the red pulp, as was expected. Later, some of the switched B cells transiently occupied the red pulp and marginal zone, whereas others persisted in germinal centers (GCs). Antigen-experienced IgM B cells were rarely found in GCs, indicating that these cells switched rapidly after entering GCs or did not persist in this environment

miQC : An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data

Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a 'low-quality' cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected. Current best practices use these QC metrics independently with either arbitrary, uniform thresholds (e.g. 5%) or biological context-dependent (e.g. species) thresholds, and fail to jointly model these metrics in a data-driven manner. Current practices are often overly stringent and especially untenable on certain types of tissues, such as archived tumor tissues, or tissues associated with mitochondrial function, such as kidney tissue [1]. We propose a data-driven QC metric (miQC) that jointly models both the proportion of reads mapping to mtDNA genes and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses. Our software package is available at https://bioconductor.org/packages/miQC. Author summary We developed the miQC package to predict the low-quality cells in a given scRNA-seq dataset by jointly modeling both the proportion of reads mapping to mitochondrial DNA (mtDNA) genes and the number of detected genes using mixture models in a probabilistic framework. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses.Peer reviewe

Skunk River Review September 1993, vol 5

https://openspace.dmacc.edu/skunkriver/1008/thumbnail.jp