Radical Love: Love all, Serve all

 A quick scan of any major news outlet will show America's unending fascination with crisis.  We are engulfed in information about these events, yet we continue with our lives as usual.  If the problem is a patriarchal system, as Johnson (2004) suggests, that is interested in maintaining a status quo of existing understandings of social and power relationships, then the solution we suggest is one of radical love to love all and serve all.   The love we speak of is more than an individual or even familial feeling.  This idea of radical love is love over force, fear, and apathy.   This love should not be conflated with altruistic generosity since the intention behind this action is motivated by sincerity.  Radical love has the potential to happen individual-to-individual, individual to group, as well as between groups and institutions.  It looks like simple acts of kindness, balanced policy making, and honest concern for all of those around us.   This radical love is the power for change.

Nuclear localization of clathrin involves a labile helix outside the trimerization domain

AbstractClathrin is a trimeric protein involved in receptor-mediated-endocytosis, but can function as a non-trimer outside of endocytosis. We have discovered that the subcellular distribution of a clathrin cysteine mutant we previously studied is altered and a proportion is also localized to nuclear spaces. MALS shows C1573A hub is a mixture of trimer-like and detrimerized molecules. The X-ray structure of the trimerization domain reveals that without light chains, a helix harboring cysteine-1573 is reoriented. We propose clathrin has a detrimerization switch, which suggests clathrin topology can be altered naturally for new functions

Hemophagocytic Macrophages Harbor Salmonella enterica during Persistent Infection

Salmonella enterica subspecies can establish persistent, systemic infections in mammals, including human typhoid fever. Persistent S. enterica disease is characterized by an initial acute infection that develops into an asymptomatic chronic infection. During both the acute and persistent stages, the bacteria generally reside within professional phagocytes, usually macrophages. It is unclear how salmonellae can survive within macrophages, cells that evolved, in part, to destroy pathogens. Evidence is presented that during the establishment of persistent murine infection, macrophages that contain S. enterica serotype Typhimurium are hemophagocytic. Hemophagocytic macrophages are characterized by the ingestion of non-apoptotic cells of the hematopoietic lineage and are a clinical marker of typhoid fever as well as certain other infectious and genetic diseases. Cell culture assays were developed to evaluate bacterial survival in hemophagocytic macrophages. S. Typhimurium preferentially replicated in macrophages that pre-phagocytosed viable cells, but the bacteria were killed in macrophages that pre-phagocytosed beads or dead cells. These data suggest that during persistent infection hemophagocytic macrophages may provide S. Typhimurium with a survival niche

Towards the identification of the soil microbiome community associated with Longleaf Pine

This project is part of a larger study looking at the restoration of the Long-leaf Pine ecosystem in certain Wildlife Management Areas (WMA) in Northwest Georgia. As part of this larger study another group of researchers has been looking at changes in the plant community in the same plots used for this soil microbiome research. Our long-term aim is to look for potential associations between the above and below-ground community structures. Although research has shown that the health and composition of the microbiome surrounding the roots of plants has a significant impact on the ability of plants to fight and survive various stressors (Wei et al. 2019), the full extent of the complex system of feedback mechanisms between the rhizosphere and soil microbiome, and the above ground plant communities is not yet understood. We collected soil samples from six plots located in the Sheffield WMA located in Paulding County, GA. Except for two plots at the savanna site, with slopes south or west facing; soil samples were collected from either north or south facing hillsides. Within each plot, samples were collected in sterile plastic tubes at the center of the plot and 10 m above and below from the center. Five random sub samples were taken from each tube for DNA extraction using a commercially available kit. Given that plant communities appear to differ between north and south facing slopes, we hypothesize that the soil microbiome will also differ significantly in north versus south facing areas. We also hypothesize that the microbiome in the savanna plots, which are actively being restored for Longleaf pine, will be distinct from all others

Hexacoordinate Ru-based olefin metathesis catalysts with pH-responsive N-heterocyclic carbene (NHC) and N-donor ligands for ROMP reactions in non-aqueous, aqueous and emulsion conditions

Three new ruthenium alkylidene complexes (PCy3)Cl2(H2ITap)Ru=CHSPh (9), (DMAP)2Cl2(H2ITap)Ru=CHPh (11) and (DMAP)2Cl2(H2ITap)Ru=CHSPh (12) have been synthesized bearing the pH-responsive H2ITap ligand (H2ITap = 1,3-bis(2’,6’- dimethyl-4’-dimethylaminophenyl)-4,5-dihydroimidazol-2-ylidene). Catalysts 11 and 12 are additionally ligated by two pH-responsive DMAP ligands. The crystal structure was solved for complex 12 by X-ray diffraction. In organic, neutral solution, the catalysts are capable of performing standard ring-opening metathesis polymerization (ROMP) and ring closing metathesis (RCM) reactions with standard substrates. The ROMP with complex 11 is accelerated in the presence of two equiv of H3PO4, but is reduced as soon as the acid amount increased. The metathesis of phenylthiomethylidene catalysts 9 and 12 is sluggish at room temperature, but their ROMP can be dramatically accelerated at 60 °C. Complexes 11 and 12 are soluble in aqueous acid. They display the ability to perform RCM of diallylmalonic acid (DAMA), however, their conversions are very low amounting only to few turnovers before decomposition. However, both catalysts exhibit outstanding performance in the ROMP of dicyclopentadiene (DCPD) and mixtures of DCPD with cyclooctene (COE) in acidic aqueous microemulsion. With loadings as low as 180 ppm, the catalysts afforded mostly quantitative conversions of these monomers while maintaining the size and shape of the droplets throughout the polymerization process. Furthermore, the coagulate content for all experiments staye

Prescription Stimulants in College and Medical Students: A Narrative Review of Misuse, Cognitive Impact, and Adverse Effects

Stimulants are effective in treating attention-deficit/hyperactivity disorder (ADHD). Psychiatrist Charles Bradley first made this discovery in 1937 when he found that children treated with amphetamines showed improvements in school performance and behavior. Between 1995 and 2008, stimulants to treat ADHD increased six-fold among American adults and adolescents at an annual rate of 6.5%. Stimulants without a prescription, known as nonmedical use or misuse, have also increased. The highest rates of nonmedical prescription drug misuse in the United States are seen most notably in young adults between 18 and 25 years, based on data from the Substance Abuse and Mental Health Services Administration in 2021. Aside from undergraduate students, nonmedical prescription stimulant use is prevalent among medical students worldwide. A recent literature review reported the utilization of stimulants without a prescription in 970 out of 11,029 medical students. The percentages of medical students across the country misusing stimulants varied from 5.2% to 47.4%. Academic enhancement, reported in 50% to 89% of college students with stimulant misuse, is the most common reason for nonmedical stimulant use. With the increasing use of stimulants among adolescents and adults, it is unclear what long-term outcomes will be since little data are available that describe differences in how side effects are experienced for prescribed and non-prescribed users. The present narrative review focuses on these adverse effects in this population and the reasonings behind misuse and nonmedical use

Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera

Many distribution models developed to predict the presence/absence of invasive alien species need to be fitted to a training dataset before practical use. The training dataset is characterized by the number of recorded presences/absences and by their geographical locations. The aim of this paper is to study the effect of the training dataset characteristics on model performance and to compare the relative importance of three factors influencing model predictive capability; size of training dataset, stage of the biological invasion, and choice of input variables. Nine models were assessed for their ability to predict the distribution of the western corn rootworm, Diabrotica virgifera virgifera, a major pest of corn in North America that has recently invaded Europe. Twenty-six training datasets of various sizes (from 10 to 428 presence records) corresponding to two different stages of invasion (1955 and 1980) and three sets of input bioclimatic variables (19 variables, six variables selected using information on insect biology, and three linear combinations of 19 variables derived from Principal Component Analysis) were considered. The models were fitted to each training dataset in turn and their performance was assessed using independent data from North America and Europe. The models were ranked according to the area under the Receiver Operating Characteristic curve and the likelihood ratio. Model performance was highly sensitive to the geographical area used for calibration; most of the models performed poorly when fitted to a restricted area corresponding to an early stage of the invasion. Our results also showed that Principal Component Analysis was useful in reducing the number of model input variables for the models that performed poorly with 19 input variables. DOMAIN, Environmental Distance, MAXENT, and Envelope Score were the most accurate models but all the models tested in this study led to a substantial rate of mis-classification

In-Datacenter Performance Analysis of a Tensor Processing Unit

Many architects believe that major improvements in cost-energy-performance must now come from domain-specific hardware. This paper evaluates a custom ASIC---called a Tensor Processing Unit (TPU)---deployed in datacenters since 2015 that accelerates the inference phase of neural networks (NN). The heart of the TPU is a 65,536 8-bit MAC matrix multiply unit that offers a peak throughput of 92 TeraOps/second (TOPS) and a large (28 MiB) software-managed on-chip memory. The TPU's deterministic execution model is a better match to the 99th-percentile response-time requirement of our NN applications than are the time-varying optimizations of CPUs and GPUs (caches, out-of-order execution, multithreading, multiprocessing, prefetching, ...) that help average throughput more than guaranteed latency. The lack of such features helps explain why, despite having myriad MACs and a big memory, the TPU is relatively small and low power. We compare the TPU to a server-class Intel Haswell CPU and an Nvidia K80 GPU, which are contemporaries deployed in the same datacenters. Our workload, written in the high-level TensorFlow framework, uses production NN applications (MLPs, CNNs, and LSTMs) that represent 95% of our datacenters' NN inference demand. Despite low utilization for some applications, the TPU is on average about 15X - 30X faster than its contemporary GPU or CPU, with TOPS/Watt about 30X - 80X higher. Moreover, using the GPU's GDDR5 memory in the TPU would triple achieved TOPS and raise TOPS/Watt to nearly 70X the GPU and 200X the CPU.Comment: 17 pages, 11 figures, 8 tables. To appear at the 44th International Symposium on Computer Architecture (ISCA), Toronto, Canada, June 24-28, 201