Hominid butchers and biting crocodiles in the African Plio-Pleistocene.

Zooarchaeologists have long relied on linear traces and pits found on the surfaces of ancient bones to infer ancient hominid behaviors such as slicing, chopping, and percussive actions during butchery of mammal carcasses. However, such claims about Plio-Pleistocene hominids rely mostly on very small assemblages of bony remains. Furthermore, recent experiments on trampling animals and biting crocodiles have shown each to be capable of producing mimics of such marks. This equifinality-the creation of similar products by different processes-makes deciphering early archaeological bone assemblages difficult. Bone modifications among Ethiopian Plio-Pleistocene hominid and faunal remains at Asa Issie, Maka, Hadar, and Bouri were reassessed in light of these findings. The results show that crocodiles were important modifiers of these bone assemblages. The relative roles of hominids, mammalian carnivores, and crocodiles in the formation of Oldowan zooarchaeological assemblages will only be accurately revealed by better bounding equifinality. Critical analysis within a consilience-based approach is identified as the pathway forward. More experimental studies and increased archaeological fieldwork aimed at generating adequate samples are now required

Ecogeographic Variation in Neandertal Dietary Habits: Evidence From Microwear Texture Analysis

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METHOD OF MOMENTS FOR EXPONENTIAL RANDOM GRAPH MODEL SELECTION

Collaboration has become crucial in solving scientific problems in biomedical and health sciences. There is a growing interest in applying social network analysis to professional associations aiming to leverage expertise and resources for optimal synergy. As a set of computational and statistical methods for analyzing social networks, Exponential Random Graph Models (ERGMs) examine complex collaborative networks due to their uniqueness of allowing for non-independent variables in network modeling. This study took a review approach to collect and analyze ERGM applications in health sciences by following the protocol of a systematic review. We included a total of 30 studies. We observed five types of ERGMs for network modeling (standard ERGM and its extensions such as Bayesian ERGM, Temporal ERGM, Separable Temporal ERGM, and Multilevel ERGM). Most studies (80%) used the standard ERGM, which possesses only endogenous and exogenous variables examining either micro- (individual-based) or macro-level (organization-based) collaborations without exploring how the links between individuals and organizations contribute to the overall network structure. Our findings help researchers (a) understand the extant research landscape of ERGM applications in health sciences, (b) learn to control and predict connection occurrence in a collaborative network, and (c) better design ERGM-applied studies to examine com-plex relations and social system structure, which is native to professional collaborations. This dissertation introduces a novel methodology for endogenous variable selection in Exponential Random Graph Models (ERGMs) to enhance the analysis of social networks across various scientific disciplines. Addressing critical challenges such as ERGM degeneracy and computational complexity, our method integrates a systematic stepwise feature selection process. This approach effectively manages the intractable normalizing constants characteristic of ERGMs, ensuring the generation of accurate and non-degenerate network models. An empirical application to ten real-life binary networks demonstrates the method's effectiveness in accommodating network dependencies and providing meaningful insights into complex network interactions. Particularly notable is the adaptability of this methodology to both directed and undirected networks, overcoming the limitations of traditional ERGMs in capturing realistic network structures. The findings contribute significantly to network analysis, offering a robust framework for modeling and interpreting social networks and laying a foundation for future advancements in statistical network analysis techniques.Doctor of Philosoph

Stochastic Step-wise Feature Selection for Exponential Random Graph Models (ERGMs)

Statistical analysis of social networks provides valuable insights into complex network interactions across various scientific disciplines. However, accurate modeling of networks remains challenging due to the heavy computational burden and the need to account for observed network dependencies. Exponential Random Graph Models (ERGMs) have emerged as a promising technique used in social network modeling to capture network dependencies by incorporating endogenous variables. Nevertheless, using ERGMs poses multiple challenges, including the occurrence of ERGM degeneracy, which generates unrealistic and meaningless network structures. To address these challenges and enhance the modeling of collaboration networks, we propose and test a novel approach that focuses on endogenous variable selection within ERGMs. Our method aims to overcome the computational burden and improve the accommodation of observed network dependencies, thereby facilitating more accurate and meaningful interpretations of network phenomena in various scientific fields. We conduct empirical testing and rigorous analysis to contribute to the advancement of statistical techniques and offer practical insights for network analysis.Comment: 23 pages, 6 tables and 18 figure

CCR2 mediates Helicobacter pyloriâ induced immune tolerance and contributes to mucosal homeostasis

BackgroundWe previously demonstrated that H. pylori infection leads to increased induction of regulatory T cells in local and systemic immune compartments. Here, we investigate the role of CCR2 in the tolerogenic programing of dendritic cells in a mouse model of H. pylori infection.Materials and MethodsCCR2 deficient (CCR2KO) mice and wildâ type (Wt) mice infected with H. pylori SS1 strain were analyzed by qPCR and FACS analysis. In vitro, bone marrowâ derived DC on day 6 from CCR2KO and Wt mice cocultured with or without H. pylori were examined to determine the impact of CCR2 signaling on dendritic cells function by qPCR, ELISA, and FACS analyses.ResultsAcute H. pylori infection was associated with a threefold increase in CCR2 mRNA expression in the gastric mucosa. H. pyloriâ infected CCR2KO mice exhibited a higher degree of mucosal inflammation, that is, increased gastritis scores and proâ inflammatory cytokine mRNA levels, but lower degree of H. pylori gastric colonization compared to infected Wt mice. Peripheral H. pyloriâ specific immune response measured in the CCR2KO spleen was characterized by a higher Th17 response and a lower Treg response. In vitro, CCR2KO bone marrowâ derived DC was less mature and shown a lower Treg/Th17 ratio. Moreover, blockade of CCR2 signaling by MCPâ 1 neutralizing antibody inhibited H. pyloriâ stimulated bone marrowâ derived DC maturation.ConclusionsOur results indicate that CCR2 plays an essential role in H. pyloriâ induced immune tolerance and shed light on a novel mechanism of CCR2â dependent DC Treg induction, which appears to be important in maintaining mucosal homeostasis during H. pylori infection.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136416/1/hel12366.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136416/2/hel12366_am.pd

The application of exponential random graph models to collaboration networks in biomedical and health sciences: a review

Collaboration has become crucial in solving scientific problems in biomedical and health sciences. There is a growing interest in applying social network analysis to professional associations aiming to leverage expertise and resources for optimal synergy. As a set of computational and statistical methods for analyzing social networks, exponential random graph models (ERGMs) examine complex collaborative networks due to their uniqueness of allowing for non-independent variables in network modeling. This study took a review approach to collect and analyze ERGM applications in health sciences by following the protocol of a systematic review. We included a total of 30 studies. The bibliometric characteristics revealed significant authors, institutions, countries, funding agencies, and citation impact associated with the publications. In addition, we observed five types of ERGMs for network modeling (standard ERGM and its extensions—Bayesian ERGM, temporal ERGM, separable temporal ERGM, and multilevel ERGM). Most studies (80%) used the standard ERGM, which possesses only endogenous and exogenous variables examining either micro- (individual-based) or macro-level (organization-based) collaborations without exploring how the links between individuals and organizations contribute to the overall network structure. Our findings help researchers (a) understand the extant research landscape of ERGM applications in health sciences, (b) learn to control and predict connection occurrence in a collaborative network, and (c) better design ERGM-applied studies to examine complex relations and social system structure, which is native to professional collaborations

A Case Report: Case of Megacolon due to Bowel Intussusception in an Elderly Patient

Introduction: Intussusception is the telescoping of a proximal segment of the gastrointestinal tract into the lumen of the more distal segment. A rare but still encountered entity, bowel intussusception, is a surgical emergency that should not be taken lightly. Although it is common in those under two years of age, it is one of the less likely diagnoses in adult populations, with only 5% of all cases occurring in adults. Case Presentation: We report the case of an 86-year-old gentleman who presented to the Emergency Department (ED) complaining of abdominal distension. An abdominopelvic CT scan with IV contrast showed evidence a transition point at the level of the sigmoid, with a small bowel of normal caliber and a homogenously dilated colon reaching 16 cm in its largest diameter. An exploratory laparotomy was opted for during which a colectomy was performed. Pathology results revealed chronic sigmoidal diverticulitis causing severe luminal narrowing with moderate chronic nonspecific inflammatory changes and acting as a lead point for intussusception, thus leading to obstruction, and megacolon. Conclusion: Intussusception is a challenging entity in terms of diagnosis and treatment when it occurs in adults. Clinical symptoms are usually nonspecific and imaging features are variable, making the preoperative diagnosis often missed or delayed. Up to 20% of cases are idiopathic, with the rest being secondary to an organic cause that must be determined for proper management. Laparotomy remains the best way to diagnose adult intussusception and to determine any underlying pathology for adequate treatment