Nonmetric Trait Correlation: A Look at Environmental and Biological Influences on Third Trochanter Formation Among Pre-Contact Upper Midwest Populations

Nonmetric traits of the human skeleton are thought to correlate with genetic and/or environmental influences; however, to what extent each may affect the presence of nonmetric traits has not been clearly substantiated in the literature. Nonmetric traits as defined by Larsen are, discrete or quasi-continuous anatomical entities often expressed as gradations from absence to full expression (1997:305). More precisely, nonmetric traits are anomalies that express themselves in the skeleton and are recorded as absent or present. A third trochanter is one of many nonmetric traits present in the femur and is defined by Finnegan as, a rounded tubercle that can be found at the superior end of the gluteal crest of the femur (1978:25). The third trochanter is considered an enthesopathy as well as a nonmetric trait because it is the insertion point of the gluteus maximus muscle, the most superficial muscle in the gluteal region (Gray 1918:426). Recent studies (Hawkey and Merbs 1995, Knusel 2000) indicate that enthesopathies are closely linked to patterns of subsistence, habitual activities and geographic location. It should also be noted that enthesopathies have been directly related to pathology, trauma, biological diversity, age, hormonal, and rheumatic conditions (Hawkey and Merbs 1995, Jurmain 1999). This research will examine the correlation between sex, age, pathology, and environmental influences on the presence of third trochanters in pre-contact populations of the Upper Midwest region of the United States

Research Progress of the International Carbon Tariff: A Review

Under the constraints of the target peak carbon dioxide emissions and carbon neutrality, how the international carbon tariff can be levied have become an important question for scholars and research institutions all over the world. This paper aimed to comprehensively sort the relevant literature on the Carbon Border Adjustment Mechanism from an economic perspective. Based on defining the concept connotation and extension of carbon tariff, we summarized and determined the price mechanism, institutional mechanism, and coordination mechanism of the carbon tariff, and analyzed the impact of carbon tariff on the economic environment and other fields. Further, this paper makes an international comparison of the existing reasonably operable carbon tariff, points out the focus and direction of the next research, and strives to provide valuable experience and theoretical reference for the innovative practice of building the international Carbon Border Adjustment Mechanism. Keywords: carbon tariff, border tax adjustment, connotation and extension, mechanism design, economic impac

Astrocytes from the contused spinal cord inhibit oligodendrocyte differentiation of adult oligodendrocyte precursor cells by increasing the expression of bone morphogenetic proteins.

Promotion of remyelination is an important therapeutic strategy to facilitate functional recovery after traumatic spinal cord injury (SCI). Transplantation of neural stem cells (NSCs) or oligodendrocyte precursor cells (OPCs) has been used to enhance remyelination after SCI. However, the microenvironment in the injured spinal cord is inhibitory for oligodendrocyte (OL) differentiation of NSCs or OPCs. Identifying the signaling pathways that inhibit OL differentiation in the injured spinal cord could lead to new therapeutic strategies to enhance remyelination and functional recovery after SCI. In the present study, we show that reactive astrocytes from the injured rat spinal cord or their conditioned media inhibit OL differentiation of adult OPCs with concurrent promotion of astrocyte differentiation. The expression of bone morphogenetic proteins (BMP) is dramatically increased in the reactive astrocytes and their conditioned media. Importantly, blocking BMP activity by BMP receptor antagonist, noggin, reverse the effects of active astrocytes on OPC differentiation by increasing the differentiation of OL from OPCs while decreasing the generation of astrocytes. These data indicate that the upregulated bone morphogenetic proteins in the reactive astrocytes are major factors to inhibit OL differentiation of OPCs and to promote its astrocyte differentiation. These data suggest that manipulation of BMP signaling in the endogenous or grafted NSCs or OPCs may be a useful therapeutic strategy to increase their OL differentiation and remyelination and enhance functional recovery after SCI

SiDA: Sparsity-Inspired Data-Aware Serving for Efficient and Scalable Large Mixture-of-Experts Models

Mixture-of-Experts (MoE) has emerged as a favorable architecture in the era of large models due to its inherent advantage, i.e., enlarging model capacity without incurring notable computational overhead. Yet, the realization of such benefits often results in ineffective GPU memory utilization, as large portions of the model parameters remain dormant during inference. Moreover, the memory demands of large models consistently outpace the memory capacity of contemporary GPUs. Addressing this, we introduce SiDA (Sparsity-inspired Data-Aware), an efficient inference approach tailored for large MoE models. SiDA judiciously exploits both the system's main memory, which is now abundant and readily scalable, and GPU memory by capitalizing on the inherent sparsity on expert activation in MoE models. By adopting a data-aware perspective, SiDA achieves enhanced model efficiency with a neglectable performance drop. Specifically, SiDA attains a remarkable speedup in MoE inference with up to 3.93X throughput increasing, up to 75% latency reduction, and up to 80% GPU memory saving with down to 1% performance drop. This work paves the way for scalable and efficient deployment of large MoE models, even in memory-constrained systems

Gut microbiome variation modulates the effects of dietary fiber on host metabolism

Background: There is general consensus that consumption of dietary fermentable fiber improves cardiometabolic health, in part by promoting mutualistic microbes and by increasing production of beneficial metabolites in the distal gut. However, human studies have reported variations in the observed benefits among individuals consuming the same fiber. Several factors likely contribute to this variation, including host genetic and gut microbial differences. We hypothesized that gut microbial metabolism of dietary fiber represents an important and differential factor that modulates how dietary fiber impacts the host. Results: We examined genetically identical gnotobiotic mice harboring two distinct complex gut microbial communities and exposed to four isocaloric diets, each containing different fibers: (i) cellulose, (ii) inulin, (iii) pectin, (iv) a mix of 5 fermentable fibers (assorted fiber). Gut microbiome analysis showed that each transplanted community preserved a core of common taxa across diets that differentiated it from the other community, but there were variations in richness and bacterial taxa abundance within each community among the different diet treatments. Host epigenetic, transcriptional, and metabolomic analyses revealed diet-directed differences between animals colonized with the two communities, including variation in amino acids and lipid pathways that were associated with divergent health outcomes. Conclusion: This study demonstrates that interindividual variation in the gut microbiome is causally linked to differential effects of dietary fiber on host metabolic phenotypes and suggests that a one-fits-all fiber supplementation approach to promote health is unlikely to elicit consistent effects across individuals. Overall, the presented results underscore the importance of microbe-diet interactions on host metabolism and suggest that gut microbes modulate dietary fiber efficacy. [MediaObject not available: see fulltext.]Fil: Murga Garrido, Sofia M.. Universidad Nacional Autónoma de México; México. University of Wisconsin; Estados UnidosFil: Hong, Qilin. University of Wisconsin; Estados UnidosFil: Cross, Tzu Wen L.. University of Wisconsin; Estados Unidos. Purdue University; Estados UnidosFil: Hutchison, Evan R.. University of Wisconsin; Estados UnidosFil: Han, Jessica. Wisconsin Institute for Discovery; Estados UnidosFil: Thomas, Sydney P.. Wisconsin Institute for Discovery; Estados UnidosFil: Vivas, Eugenio I.. University of Wisconsin; Estados UnidosFil: Denu, John. Wisconsin Institute for Discovery; Estados UnidosFil: Ceschin, Danilo Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; Argentina. Instituto Universitario de Ciencias Biomédicas de Córdoba; ArgentinaFil: Tang, Zheng Zheng. University of Wisconsin; Estados Unidos. Wisconsin Institute for Discovery; Estados UnidosFil: Rey, Federico E.. University of Wisconsin; Estados Unido

Multi-Omic Analysis of the Microbiome and Metabolome in Healthy Subjects Reveals Microbiome-Dependent Relationships Between Diet and Metabolites

The human microbiome has been associated with health status, and risk of disease development. While the etiology of microbiome-mediated disease remains to be fully elucidated, one mechanism may be through microbial metabolism. Metabolites produced by commensal organisms, including in response to host diet, may affect host metabolic processes, with potentially protective or pathogenic consequences. We conducted multi-omic phenotyping of healthy subjects (N = 136), in order to investigate the interaction between diet, the microbiome, and the metabolome in a cross-sectional sample. We analyzed the nutrient composition of self-reported diet (3-day food records and food frequency questionnaires). We profiled the gut and oral microbiome (16S rRNA) from stool and saliva, and applied metabolomic profiling to plasma and stool samples in a subset of individuals (N = 75). We analyzed these multi-omic data to investigate the relationship between diet, the microbiome, and the gut and circulating metabolome. On a global level, we observed significant relationships, particularly between long-term diet, the gut microbiome and the metabolome. Intake of plant-derived nutrients as well as consumption of artificial sweeteners were associated with significant differences in circulating metabolites, particularly bile acids, which were dependent on gut enterotype, indicating that microbiome composition mediates the effect of diet on host physiology. Our analysis identifies dietary compounds and phytochemicals that may modulate bacterial abundance within the gut and interact with microbiome composition to alter host metabolism

Block-Wise Mixed-Precision Quantization: Enabling High Efficiency for Practical ReRAM-based DNN Accelerators

Resistive random access memory (ReRAM)-based processing-in-memory (PIM) architectures have demonstrated great potential to accelerate Deep Neural Network (DNN) training/inference. However, the computational accuracy of analog PIM is compromised due to the non-idealities, such as the conductance variation of ReRAM cells. The impact of these non-idealities worsens as the number of concurrently activated wordlines and bitlines increases. To guarantee computational accuracy, only a limited number of wordlines and bitlines of the crossbar array can be turned on concurrently, significantly reducing the achievable parallelism of the architecture. While the constraints on parallelism limit the efficiency of the accelerators, they also provide a new opportunity for fine-grained mixed-precision quantization. To enable efficient DNN inference on practical ReRAM-based accelerators, we propose an algorithm-architecture co-design framework called \underline{B}lock-\underline{W}ise mixed-precision \underline{Q}uantization (BWQ). At the algorithm level, BWQ-A introduces a mixed-precision quantization scheme at the block level, which achieves a high weight and activation compression ratio with negligible accuracy degradation. We also present the hardware architecture design BWQ-H, which leverages the low-bit-width models achieved by BWQ-A to perform high-efficiency DNN inference on ReRAM devices. BWQ-H also adopts a novel precision-aware weight mapping method to increase the ReRAM crossbar's throughput. Our evaluation demonstrates the effectiveness of BWQ, which achieves a 6.08x speedup and a 17.47x energy saving on average compared to existing ReRAM-based architectures.Comment: 12 pages, 13 figure

On-chip ultrasensitive and rapid hydrogen sensing based on plasmon-induced hot electron–molecule interaction

Hydrogen energy is a zero-carbon replacement for fossil fuels. However, hydrogen is highly flammable and explosive hence timely sensitive leak detection is crucial. Existing optical sensing techniques rely on complex instruments, while electrical sensing techniques usually operate at high temperatures and biasing condition. In this paper an on-chip plasmonic–catalytic hydrogen sensing concept with a concentration detection limit down to 1 ppm is presented that is based on a metal–insulator–semiconductor (MIS) nanojunction operating at room temperature and zero bias. The sensing signal of the device was enhanced by three orders of magnitude at a one-order of magnitude higher response speed compared to alternative non-plasmonic devices. The excellent performance is attributed to the hydrogen induced interfacial dipole charge layer and the associated plasmonic hot electron modulated photoelectric response. Excellent agreements were achieved between experiment and theoretical calculations based on a quantum tunneling model. Such an on-chip combination of plasmonic optics, photoelectric detection and photocatalysis offers promising strategies for next-generation optical gas sensors that require high sensitivity, low time delay, low cost, high portability and flexibility