Indiana University Bloomington

This “Introduction” situates the chapters in the third part of Palgrave Handbook of Philosophy and Money on the Roman era. Money—both as a practical instrument and as an abstract idea—was nearly ubiquitous in the Roman world. And yet, ubiquity was not uniformity. Not only, for example, did numerous varied local and regional coinages and monetary instruments persist until the third century AD, but this monetary diversity influenced or was influenced by a wide range of aspects of the Roman experience: mythology, law, politics, religion, and social relationships. Developments are thus impossible to adequately summarize. In this part of the Handbook, scholars instead offer snapshots of key developments in what might be broadly termed philosophical considerations of money. Such snapshots include the following themes: the origins of coinage in Roman myth; Cicero on property; Seneca on the uses of money; the treatment of money in Pliny’s Natural History; money and coinage in Roman jurists’ thought; imperial Roman law; Rabbinic thought and Jewish solidarity; monetary themes in the writing of the Christian Bible; and philosophies of money in early Christian thought. It is the collective hope that these chapters, taken together, give shape and clarity to an otherwise tangled milieu.

In the quest to model neuronal function amid gaps in physiological data, a promising strategy is to develop a normative theory that interprets neuronal physiology as optimizing a computational objective. This study extends current normative models, which primarily optimize prediction, by conceptualizing neurons as optimal feedback controllers. We posit that neurons, especially those beyond early sensory areas, steer their environment toward a specific desired state through their output. This environment comprises both synaptically interlinked neurons and external motor sensory feedback loops, enabling neurons to evaluate the effectiveness of their control via synaptic feedback. To model neurons as biologically feasible controllers which implicitly identify loop dynamics, infer latent states, and optimize control we utilize the contemporary direct data-driven control (DD-DC) framework. Our DD-DC neuron model explains various neurophysiological phenomena: the shift from potentiation to depression in spike-timing-dependent plasticity with its asymmetry, the duration and adaptive nature of feedforward and feedback neuronal filters, the imprecision in spike generation under constant stimulation, and the characteristic operational variability and noise in the brain. Our model presents a significant departure from the traditional, feedforward, instant-response McCulloch–Pitts–Rosenblatt neuron, offering a modern, biologically informed fundamental unit for constructing neural networks.

Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult. Computational approaches can aid in carbohydrate structure prediction, structure determination, and design. In this work, we developed a glycan-modeling algorithm, GlycanTreeModeler , that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. GlycanTreeModeler was benchmarked on a test set of glycan structures of varying lengths, or “trees”. Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. We employed these tools to design de novo glycan trees into a protein nanoparticle vaccine to shield regions of the scaffold from antibody recognition, and experimentally verified shielding. This work will inform glycoprotein model prediction, glycan masking, and further aid computational methods in experimental structure determination and refinement.

Adults with type 1 diabetes (T1D) have an elevated risk for cardiovascular disease (CVD) compared with the general population. HbA1c is the primary modifiable risk factor for CVD in T1D. Fewer than 1% of patients achieve euglycemia (<5.7%HbA1c). Ketogenic diets (KD; ≤50g carbohydrate/day) may improve glycemia and downstream vascular dysfunction in T1D by reducing HbA1c and insulin load. However, there are concerns regarding the long-term CVD risk from a KD. Therefore, we compared data collected in a 60-day window in an adult with T1D on exogenous insulin who consumed a KD for 10 years versus normative values in those with T1D (T1D norms). The participant achieved euglycemia with an HbA1c of 5.5%, mean glucose of 98[5]mg/dL(median[IQR]), and 90[11]%time-in-range 70-180mg/dL (T1D norms: 1 st percentile for all); and low insulin requirements of 0.38±0.03IU/kg/day (T1D norms: 8 th percentile). Seated systolic blood pressure (SBP) was 113mmHg (T1D norms: 18 th percentile) while ambulatory awake SBP was 132±15mmHg (T1D target: <130mmHg), blood triglycerides were 69mg/dL (T1D norms: 34 th percentile), low-density lipoprotein was 129mg/dL (T1D norms: 60 th percentile), heart rate was 56bpm (T1D norms: >1SD below the mean), carotid-femoral pulse wave velocity was 7.17m/s (T1D norms: lowest quartile of risk), flow-mediated dilation was 12.8% (T1D norms: >1SD above mean), and cardiac vagal baroreflex gain was 23.5ms/mmHg (T1D norms: >1SD above mean). Finally, there was no indication of left ventricular diastolic dysfunction from echocardiography. Overall, these data demonstrate below-average CVD risk relative to T1D norms despite concerns regarding the long-term impact of a KD on CVD risk.

Purpose This study aimed to investigate the changes in serum Anti-Müllerian Hormone (AMH) levels, sex hormone levels, follicle-stimulating hormone (FSH)/luteinizing hormone (LH) ratio in patients with celiac disease (CeD), and their correlation with clinical characteristics and nutrient levels. Methods This cross-sectional study collected clinical and biochemical data from a total of 67 females diagnosed with CeD and 67 healthy females within the reproductive age range of 18–44 years. The study was conducted at a tertiary hospital between September 2016 and January 2024. Both groups underwent comprehensive clinical and laboratory assessments. Serum levels of AMH and sex hormones were quantified using chemiluminescence immunoassay, and their associations with CeD clinical features and nutrient levels were thoroughly analyzed. Results The study included 67 patients and 67 controls with a mean age of 36.7±7.6 years. No statistically significant differences were found between the two groups in mean age, BMI, FSH, LH, E2, P levels, FSH/LH, menstrual irregularities, abortions history, parity, and gravidity (all P>0.05). However, AMH, T, FER, FA, Zn, and Se levels were significantly lower, and PRL levels were higher in the CeD group (all P<0.05). Spearman’s correlation analysis showed that AMH levels were negatively correlated with age, tTG level, disease duration, and Marsh grading (P<0.05). Conclusions This study highlights the association between impaired ovarian function in CeD patients and disease severity and nutrient levels. Early detection and intervention for ovarian function abnormalities are imperative to enhance fertility potential in CeD patients.

Human learning varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing microstructure of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in learning a sensorimotor task, and further, if the mapping between tract microstructure and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then practiced drawing a set of 40 unfamiliar symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and measured visual recognition learning for the symbols using an old/new 2-AFC task. Results demonstrated that tract microstructure selectively predicted learning outcomes, with left hemisphere pArc and SLF3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated using repeat, held-out data and supported with complementary analyses. Results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes.

Tumor hypoxia has been shown to predict poor patient outcomes in several cancer types, partially because it reduces radiation’s ability to kill cells. We hypothesized that some of the clinical effects of hypoxia could also be due to its impact on the tumor microbiome. Therefore, we examined the RNA-seq data from the Oncology Research Information Exchange Network (ORIEN) database of colorectal cancer (CRC) patients treated with radiotherapy. We identified microbial RNAs for each tumor and related them to the hypoxic gene expression scores calculated from host mRNA. Our analysis showed that the hypoxia expression score predicted poor patient outcomes and identified tumors enriched with certain microbes such as Fusobacterium nucleatum. The presence of other microbes, such as Fusobacterium canifelinum, predicted poor patient outcomes, suggesting a potential interaction between hypoxia, the microbiome, and radiation response. To experimentally investigate this concept, we implanted CT26 CRC cells into immune-competent BALB/c and immune-deficient athymic nude mice. After growth, where tumors passively acquired microbes from the gastrointestinal tract, we harvested tumors, extracted nucleic acids, and sequenced host and microbial RNAs. We stratified tumors based on their hypoxia score and performed a metatranscriptomic analysis of microbial gene expression. In addition to hypoxia-trophic and -phobic microbial populations, analysis of microbial gene expression at the strain level showed expression differences based on the hypoxia score. Thus, hypoxia appears to associate with different microbial populations and elicit an adaptive transcriptional response in intratumoral microbes, potentially influencing clinical outcomes.

This study investigates leadership ambition and focuses this with a simple, yet necessary perspective, the focus of race/ethnicity and gender. Many public organizations may not consider how gendered and racialized aspects of organizations can influence leadership ambition for diverse individuals. We ask: (a) How is gender and race/ethnicity related to leadership ambition? and (b) Are social networks related to leadership ambition based on gender and racial/ethnic differences? Using a 2011 national survey of STEM faculty in U.S. research-based universities, we find significant leadership ambition differences for people of color and that social networks are beneficial for women’s leadership ambition.

Despite hundreds of studies examining belief in conspiracy theories, it is still unclear who—demographically—is most likely to believe such theories. To remedy this knowledge gap, we examine survey data containing various operationalizations of conspiracism across diverse sociopolitical contexts. Study 1 employs a 2021 U.S. survey (n = 2021) to examine associations between sociodemographic characteristics and beliefs in 39 conspiracy theories. Study 2 similarly employs a survey of 20 countries (n = 26,416) and 11 conspiracy theory beliefs. Study 3 reports results from a 2020 U.S. survey (n = 2015) measuring perceptions about which groups are engaging in conspiracies. Study 4 interrogates data from nine U.S. surveys (2012–2022; n = 14,334) to examine the relationships between sociodemographic characteristics and generalized conspiracy thinking. Study 5 synchronizes studies 1–4 to provide an intersectional analysis of conspiracy theory belief. Across studies, we observe remarkably consistent patterns: education, income, age (older), and White identification are negatively related to conspiracism, while Black identification is positively related. We conclude by discussing why conspiracy theories may appeal most to historically marginalized groups and how our findings can inform efforts to mitigate the negative effects of conspiracy theories.

Here, we report the characterization of cholesterol levels on membrane fluidity with a twisted intramolecular charge transfer (TICT) membrane dye, namely DI-8-ANEPPS, using fluorescence lifetime techniques such as time-correlated single...

Peer advocacy can promote HIV protective behaviors, but little is known about the concordance on prevention advocacy(PA) reports between people living with HIV(PLWH) and their social network members. We examined prevalence and correlates of such concordance, and its association with the targeted HIV protective behavior of the social network member. Data were analyzed from 193 PLWH(index participants) and their 599 social network members(alters). Kappa statistics measured concordance between index and alter reports of PA in the past 3 months. Logistic and multinomial regressions evaluated the relationship between advocacy concordance and alter condom use and HIV testing behavior and correlates of PA concordance. Advocacy concordance was observed in 0.3% of index-alter dyads for PrEP discussion, 9% for condom use, 18% for HIV testing, 26% for care engagement, and 49% for antiretroviral use discussions. Fewer indexes reported condom use(23.5% vs. 28.1%; $${ \chi }^{2}$$ =3.7, p =0.05) and HIV testing(30.5% vs. 50.5%; $${\chi }^{2}$$ =25.3, p <0.001) PA occurring. Condom advocacy concordance was higher if the index and alter were romantic partners(OR=3.50; p =0.02), and lower if the index was 10 years younger than the alter(OR=0.23; p = 0.02). Alters had higher odds of using condoms with their main partner when both reported condom advocacy compared to dyads where neither reported advocacy(OR=3.90; p <0.001) and compared to dyads where only the index reported such advocacy(OR = 3.71; p =0.01). Age difference and relationship status impact advocacy agreement, and concordant perceptions of advocacy are linked to increased HIV protective behaviors. Alters’ perceptions may be crucial for behavior change, informing strategies for improving advocacy.

The mechanisms by which older adults maintain large, complex social networks are not well understood. Prior work has primarily focused on general cognitive ability (e.g., executive function, episodic memory), largely overlooking social cognition—the ability to process, store, and remember social information. Because social cognition plays a key role in navigating social interactions and is distinct from general cognition, we examined whether general and social cognition uniquely predicted the nature of older adults’ personal social networks. Our study leveraged comprehensive measures of general cognition (executive function, episodic memory), social cognition (face memory and dynamic measures of cognitive and affective theory of mind), and a rigorous measure of personal social networks from 143 community-dwelling older adults. We found that, when modeled together and controlling for sociodemographic variables, only executive function and dynamic cognitive theory of mind positively predicted having social networks with relatively unfamiliar, loosely connected others, accounting for 17% of the unique variance in older adults’ social connectedness. Interestingly, having a social network comprised primarily of close, tightly knit relationships was negatively associated with affective theory of mind performance. Findings are discussed in the context of the social–cognitive resource framework—which suggests that social cognition may be more engaged in relatively unfamiliar, versus close, interactions. Specifically, our results show that social–cognitive processes may be relatively automatic for individuals whose primary social relationships are very close but may be more strongly engaged for individuals whose interactions include at least some relatively less close relationships.

The Multispecies Ovary Tissue Histology Electronic Repository (MOTHER) is a publicly accessible repository of ovary histology images. MOTHER includes hundreds of images from nonhuman primates, as well as ovary histology images from an expanding range of other species. Along with an image, MOTHER provides metadata about the image, and for selected species, follicle identification annotations. Ongoing work includes assisting scientists with contributing their histology images, creation of manual and automated (via machine learning) processing pipelines to identify and count ovarian follicles in different stages of development, and the incorporation of that data into the MOTHER database (MOTHER-DB). MOTHER will be a critical data repository storing and disseminating high-value histology images that are essential for research into ovarian function, fertility, and intra-species variability.

Background: Pancreatic cancer is among the most fatal human cancers and the fourth leading cause of cancer death in the United States. Evidence suggests that chronic inflammation may play a role in pancreatic carcinogenesis, and its inhibition through non-steroidal anti-inflammatory drugs (NSAIDs) may reduce pancreatic cancer incidence. Methods: We examined associations of total and individual NSAIDs with pancreatic cancer risk among postmenopausal women participating in the Women’s Health Initiative observational study and clinical trials cohorts. Among 117,452 women, ages 55-79 years, 727 incident pancreatic cancer cases were reported over 18 years of follow-up. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations between NSAIDs and pancreatic cancer risk. Results: Relative to non-use, consistent use of any NSAID was inversely associated with pancreatic cancer risk (HR 0.71, 95% CI: 0.59-0.87), primarily driven by strong associations for aspirin use (HR 0.67, 95% CI: 0.52-0.86). Use of total or individual non-aspirin NSAIDs were not associated with pancreatic cancer. Upon stratified analysis, we observed stronger associations for NSAIDs among participants with prevalent diabetes (HR 0.28, 95% CI: 0.10-0.75) relative to those without (HR 0.75, 95% CI: 0.61-0.92; P-interaction=0.03). Conclusions: Additional large prospective studies with careful measurement of NSAID type, dose, and frequency are needed to further investigate the possibility of added benefit among individuals diagnosed with diabetes. Impact: This study adds to existing evidence from prospective studies and clinical trials suggesting that use of aspirin may provide moderate benefit for pancreatic cancer prevention.