Archeological Investigations for Fort Stabilization and Restoration, For McKavett State Historical Park, Menard County, Texas: 1978-1990 Seasons

The U.S. Army occupations at Fort McKavett from 1853 until 1859 and from 1868 until 1883 were part of Texas\u27s frontier defense. During the Civil War and from 1883 until the present, civilians have inhabited and used the fort buildings, creating the small town of Fort McKavett. The Texas Parks and Wildlife Department developed part of the town as a state historical park, restoring this property to its appearance during the second military occupation. Archeological investigations at the park between 1978 and 1990 focused on recovering architectural data and artifacts to support restoration, stabilization, and interpretation of the military occupations. The archeological work varied from surface collection to large-scale excavations, the latter generally confined to Officers\u27 Quarters 4, but the most common approach was limited testing in building foundations and suspected architectural features. Work took place in 16 structures. Most of the archeological work focused on officers\u27 quarters, although a few enlisted mens\u27 barracks and other buildings also were tested. Relatively few temporally diagnostic artifacts were recovered in the vicinity of walls, fireplaces, and other architectural features, and only sparse military and military-period artifacts were found. The 372 military and military-period artifacts recovered from the post-1977 work at Fort McKavett and described in this report represent less than 0.01 percent of the total artifact assemblage and likely represent only a small proportion of the trash generated by the military occupations. Much of that trash probably was disposed of and possibly burned off-site or, if on-site, in pit latrines or other deep features not excavated during the 1978-1990 work. Military conduct, discipline, and policing may have functioned in keeping public spaces at this frontier military fort relatively litter free and thus artifact poor

Identifying Personalized Metabolic Signatures in Breast Cancer.

Cancer cells are adept at reprogramming energy metabolism, and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of 1156 breast normal and tumor samples from The Cancer Genome Atlas (TCGA) and integrated this information with a genome-scale reconstruction of human metabolism to generate personalized, context-specific metabolic networks. Using this approach, we classified the samples into four distinct groups based on their metabolic profiles. Enrichment analysis of the subsystems indicated that amino acid metabolism, fatty acid oxidation, citric acid cycle, androgen and estrogen metabolism, and reactive oxygen species (ROS) detoxification distinguished these four groups. Additionally, we developed a workflow to identify potential drugs that can selectively target genes associated with the reactions of interest. MG-132 (a proteasome inhibitor) and OSU-03012 (a celecoxib derivative) were the top-ranking drugs identified from our analysis and known to have anti-tumor activity. Our approach has the potential to provide mechanistic insights into cancer-specific metabolic dependencies, ultimately enabling the identification of potential drug targets for each patient independently, contributing to a rational personalized medicine approach

A Cell-Surface Membrane Protein Signature for Glioblastoma.

We present a systems strategy that facilitated the development of a molecular signature for glioblastoma (GBM), composed of 33 cell-surface transmembrane proteins. This molecular signature, GBMSig, was developed through the integration of cell-surface proteomics and transcriptomics from patient tumors in the REMBRANDT (n = 228) and TCGA datasets (n = 547) and can separate GBM patients from control individuals with a Matthew\u27s correlation coefficient value of 0.87 in a lock-down test. Functionally, 17/33 GBMSig proteins are associated with transforming growth factor β signaling pathways, including CD47, SLC16A1, HMOX1, and MRC2. Knockdown of these genes impaired GBM invasion, reflecting their role in disease-perturbed changes in GBM. ELISA assays for a subset of GBMSig (CD44, VCAM1, HMOX1, and BIGH3) on 84 plasma specimens from multiple clinical sites revealed a high degree of separation of GBM patients from healthy control individuals (area under the curve is 0.98 in receiver operating characteristic). In addition, a classifier based on these four proteins differentiated the blood of pre- and post-tumor resections, demonstrating potential clinical value as biomarkers

Longitudinal analysis reveals transition barriers between dominant ecological states in the gut microbiome.

The Pioneer 100 Wellness Project involved quantitatively profiling 108 participants\u27 molecular physiology over time, including genomes, gut microbiomes, blood metabolomes, blood proteomes, clinical chemistries, and data from wearable devices. Here, we present a longitudinal analysis focused specifically around the Pioneer 100 gut microbiomes. We distinguished a subpopulation of individuals with reduced gut diversity, elevated relative abundance of the genus Prevotella, and reduced levels of the genus Bacteroides We found that the relative abundances of Bacteroides and Prevotella were significantly correlated with certain serum metabolites, including omega-6 fatty acids. Primary dimensions in distance-based redundancy analysis of clinical chemistries explained 18.5% of the variance in bacterial community composition, and revealed a Bacteroides/Prevotella dichotomy aligned with inflammation and dietary markers. Finally, longitudinal analysis of gut microbiome dynamics within individuals showed that direct transitions between Bacteroides-dominated and Prevotella-dominated communities were rare, suggesting the presence of a barrier between these states. One implication is that interventions seeking to transition between Bacteroides- and Prevotella-dominated communities will need to identify permissible paths through ecological state-space that circumvent this apparent barrier

A wellness study of 108 individuals using personal, dense, dynamic data clouds.

Personal data for 108 individuals were collected during a 9-month period, including whole genome sequences; clinical tests, metabolomes, proteomes, and microbiomes at three time points; and daily activity tracking. Using all of these data, we generated a correlation network that revealed communities of related analytes associated with physiology and disease. Connectivity within analyte communities enabled the identification of known and candidate biomarkers (e.g., gamma-glutamyltyrosine was densely interconnected with clinical analytes for cardiometabolic disease). We calculated polygenic scores from genome-wide association studies (GWAS) for 127 traits and diseases, and used these to discover molecular correlates of polygenic risk (e.g., genetic risk for inflammatory bowel disease was negatively correlated with plasma cystine). Finally, behavioral coaching informed by personal data helped participants to improve clinical biomarkers. Our results show that measurement of personal data clouds over time can improve our understanding of health and disease, including early transitions to disease states

High resolution time-course mapping of early transcriptomic, molecular and cellular phenotypes in Huntington\u27s disease CAG knock-in mice across multiple genetic backgrounds.

Huntington\u27s disease is a dominantly inherited neurodegenerative disease caused by the expansion of a CAG repeat in the HTT gene. In addition to the length of the CAG expansion, factors such as genetic background have been shown to contribute to the age at onset of neurological symptoms. A central challenge in understanding the disease progression that leads from the HD mutation to massive cell death in the striatum is the ability to characterize the subtle and early functional consequences of the CAG expansion longitudinally. We used dense time course sampling between 4 and 20 postnatal weeks to characterize early transcriptomic, molecular and cellular phenotypes in the striatum of six distinct knock-in mouse models of the HD mutation. We studied the effects of the HttQ111 allele on the C57BL/6J, CD-1, FVB/NCr1, and 129S2/SvPasCrl genetic backgrounds, and of two additional alleles, HttQ92 and HttQ50, on the C57BL/6J background. We describe the emergence of a transcriptomic signature in HttQ111/+  mice involving hundreds of differentially expressed genes and changes in diverse molecular pathways. We also show that this time course spanned the onset of mutant huntingtin nuclear localization phenotypes and somatic CAG-length instability in the striatum. Genetic background strongly influenced the magnitude and age at onset of these effects. This work provides a foundation for understanding the earliest transcriptional and molecular changes contributing to HD pathogenesis

Scansion No. 23 -_Thursday_27 January_ 1955

In this issue I intend to depart somewhat from the general editorial policy by attacking everyone, instead of confining my attack to one or two individuals. I say that science fiction fandom has had its day, it has lost its crusading appeal, it has remained unchanged while it has changed other things (like Allah)

Scansion No. 38 – Thursday, 8th December, 1955

It seems to be generally accepted, all over the world, that science fiction fandom is on the decline. The enthusiasm of the old days is gone. No longer does one feel anything out of the ordinary in being a science fiction fan

Ageotypes: Distinct Biomolecular Trajectories in Human Aging.

Many studies have demonstrated that biological age (BA) varies significantly among individuals of similar chronological age. A recent study by Ahadi et al. used longitudinal and deep multi-omic profiling to identify individuals with distinct BA phenotypes or \u27ageotypes\u27. These ageotypes open new avenues to creating diagnostic and treatment strategies that may slow the aging process based on the unique biochemistry of each individual

Unpacking the Racial Disparity in Crime from a Racialized General Strain Theory Perspective

Criminologists have long theorized the relationship between race and crime using traditional criminological theories, suggesting that Blacks simply experience more factors conducive to crime than Whites. Race scholars have criticized this “add and stir” approach and, instead, argue for race-based explanations. Racialized General Strain Theory (RGST) is the first traditional approach to address this call to action. To date, however, little research has fully assessed RGST’s propositions. Using the Project on Human Development in Chicago Neighborhoods, we find mixed support for RGST. Findings also suggest racial differences in experiences and responses to strain are much more complicated than originally theorized