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High Stakes: Exploring the Impact of Traditional, Live, and Parlay Sports Betting on Young Adults
Get PDFThis study explores how young men experience and are affected by three distinct types of online sports betting: traditional pregame betting, live betting, and parlay betting. Drawing on in-depth interviews with fifteen male participants aged 21–25, the study investigates how different bet structures influence mental and emotional well-being, everyday activities, and decision-making behaviors. Using thematic analysis and a scale-based engagement intensity matrix, the study identifies key divergences in risk perception, impulsivity, emotional volatility, and financial behavior across betting types. While traditional pregame betting is largely associated with calculated decision-making and reduced emotional reactivity, live and parlay betting elicits stronger emotional swings, greater impulsivity, and higher perceived entertainment value. The findings suggest that different sports betting formats pose distinct behavioral risks and should not be treated uniformly in research or regulation. This work contributes to the literature on gambling psychology, digital betting environments, and youth behavioral health, and concludes with evidence-based policy recommendations aimed at mitigating harms
Structural basis of voltage-dependent gating in BK channels
Get PDFThe allosteric communication between the pore domain, voltage sensors, and Ca2+ binding sites in the calcium- and voltage-activated K+ channel (BK) underlies its physiological role as the preeminent signal integrator in excitable systems. BK displays shallow voltage sensitivity with very fast gating charge kinetics, yet little is known about the molecular underpinnings of this distinctive behavior. Here, we explore the mechanistic basis of coupling between voltage-sensing domains (VSDs) and calcium sensors in Aplysia BK by locking the VSDs in their activated (R196Q and R199Q) and resting (R202Q) states, with or without calcium. Cryo-EM structures of these mutants reveal unique tilts at the S4 C-terminal end, together with large side-chain rotameric excursions of the gating charges. Notably, the VSD resting structure (R202Q) also revealed BK in its elusive, fully closed state, highlighting the reciprocal relation between calcium and voltage sensors. These structures provide a plausible path where voltage and Ca2+ binding couple energetically and define the conformation of the pore domain and, thus, BK’s full functional range
A machine learning model using clinical notes to identify physician fatigue
Get PDFClinical notes should capture important information from a physician-patient encounter, but they may also contain signals indicative of physician fatigue. Using data from 129,228 emergency department (ED) visits, we train a model to identify notes written by physicians who are likely to be tired: those who worked ED shifts on at least 5 of the prior 7 days. In a hold-out set, the model accurately identifies notes written by such high-workload physicians. It also flags notes written in other settings with high fatigue: overnight shifts and high patient volumes. When the model identifies signs of fatigue in a note, physician decision-making for that patient appears worse: yield of testing for heart attack is 19% lower with each standard deviation increase in model-predicted fatigue. A key feature of notes written by fatigued doctors is the predictability of the next word, given the preceding context. Perhaps unsurprisingly, because word prediction is the core of how large language models (LLMs) work, we find that predicted fatigue of LLM-written notes is 74% higher than that of physician-written ones, highlighting the possibility that LLMs may introduce distortions in generated text that are not yet fully understood
Methodological Frontiers in Intergenerational Mobility Research
Get PDFThis special issue of Sociological Methods & Research presents a collection of papers that develop a range of new statistical approaches and empirical insights on intergenerational mobility. The papers in the special issue involve four broad themes: the development of new statistics to characterize mobility, the exploration of methods to establish causal explanations, the enrichment of statistical models to better characterize heterogeneity in mobility across families, and the development and application of ways to employ machine learning tools to enrich mobility analysis. These papers demonstrate the excitement of the methodological frontier in mobility research
Symmetric Instability in a Boussinesq Fluid on a Rotating Planet
Get PDFSymmetric instability has broad applications in geophysical and planetary fluid dynamics. It plays a crucial role in the formation of mesoscale rainbands at mid‐latitudes on Earth, instability in the ocean's mixed layer, and slantwise convection on gas giants and icy moon oceans. Here, we apply linear instability analysis to an arbitrary zonally symmetric Boussinesq flow on a rotating spherical planet, with applicability to icy moon oceans. We divide the instabilities into three types: (a) gravitational instability, occurring when stratification is unstable along angular momentum surfaces, (b) inertial instability, occurring when angular momentum shear is unstable along buoyancy surfaces, and (c) a mixed symmetric instability, occurring when neither of the previous conditions are fulfilled, but the potential vorticity has the opposite sign to planetary rotation. We note that N2 z sinθ0 z is the stratification along the planetary rotation axis and θ0 is the local latitude, is always sufficient for instability and also necessary in the low Rossby number limit. In this limit, relevant for deep convection in icy moon oceans, the most unstable mode is slantwise convection parallel to the planetary rotation axis. This slantwise convection differs from the parameterized convection in existing general circulation models, whose convection schemes parameterize convection in the direction of gravity. Our results suggest that convection schemes in global ocean models must be revised before being applied to icy moon oceans
Erasing “bad memories”: Reversing aberrant synaptic plasticity as therapy for neurological and psychiatric disorders
Get PDFDopamine modulates corticostriatal plasticity in both the direct and indirect pathways of the cortico-striato-thalamo-cortical (CSTC) loops. These gradual changes in corticostriatal synaptic strengths produce long-lasting changes in behavioral responses. Under normal conditions, these mechanisms enable the selection of the most appropriate responses while inhibiting others. However, under dysregulated dopamine conditions, including a lack of dopamine release or dopamine signaling, these mechanisms could lead to the selection of maladaptive responses and/or the inhibition of appropriate responses in an experience-dependent and task-specific manner. In this review, we propose that preventing or reversing such maladaptive synaptic strengths and erasing such aberrant “memories” could be a disease-modifying therapeutic strategy for many neurological and psychiatric disorders. We review evidence from Parkinson’s disease, drug-induced parkinsonism, L-DOPA-induced dyskinesia, obsessive-compulsive disorder, substance use disorders, and depression as well as research findings on animal disease models. Altogether, these studies allude to an emerging theme in translational neuroscience and promising new directions for therapy development. Specifically, we propose that combining pharmacotherapy with behavioral therapy or with deep brain stimulation (DBS) could potentially cause desired changes in specific neural circuits. If successful, one important advantage of correcting aberrant synaptic plasticity is long-lasting therapeutic effects even after treatment has ended. We will also discuss the potential molecular targets for these therapeutic approaches, including the cAMP pathway, proteins involved in synaptic plasticity as well as pathways involved in new protein synthesis. We place special emphasis on RNA binding proteins and epitranscriptomic mechanisms, as they represent a new frontier with the distinct advantage of rapidly and simultaneously altering the synthesis of many proteins locally
A Primer for Evaluating Large Language Models in Social-Science Research
Get PDFAutoregressive large language models (LLMs) exhibit remarkable conversational and reasoning abilities and exceptional flexibility across a wide range of tasks. Subsequently, LLMs are being increasingly used in scientific research to analyze data, generate synthetic data, or even write scientific articles. This trend necessitates that authors follow best practices for conducting and reporting LLM research and that journal reviewers can evaluate the quality of works that use LLMs. We provide authors of social-scientific research with essential recommendations to ensure replicable and robust results using LLMs. Our recommendations also highlight considerations for reviewers, focusing on methodological rigor, replicability, and validity of results when evaluating studies that use LLMs to automate data processing or simulate human data. We offer practical advice on assessing the appropriateness of LLM applications in submitted studies, emphasizing the need for transparency in methodological reporting and the challenges posed by the nondeterministic and continuously evolving nature of these models. By providing a framework for best practices and critical review, in this primer, we aim to ensure high-quality, innovative research in the evolving landscape of social-science studies using LLMs
Dynamic coexistence driven by physiological transitions in microbial communities
Get PDFMicrobial ecosystems are commonly modeled by fixed interactions between species in steady exponential growth states. However, microbes in exponential growth often modify their environments so strongly that they are forced out of the growth state into stressed, nongrowing states. Such dynamics are typical of ecological succession in nature and serial-dilution cycles in the laboratory. Here, we introduce a phenomenological model, the Community State Model, to gain insight into the dynamic coexistence of microbes due to changes in their physiological states during cyclic succession. Our model specifies the growth preference of each species along a global ecological coordinate, taken to be the biomass density of the community, but is otherwise agnostic to specific interactions (e.g., nutrient starvation, stress, aggregation), in order to focus on self-consistency conditions on combinations of physiological states, “community states,” in a stable ecosystem. We identify three key features of such dynamical communities that contrast starkly with steady-state communities: enhanced community stability through staggered dominance of different species in different community states, increased tolerance of community diversity to fast growing species dominating distinct community states, and increased requirement of growth dominance by late-growing species. These features, derived explicitly for simplified models, are proposed here as principles aiding the understanding of complex dynamical communities. Our model shifts the focus of ecosystem dynamics from bottom–up studies based on fixed, idealized interspecies interaction to top–down studies based on accessible macroscopic observables such as growth rates and total biomass density, enabling quantitative examination of community-wide characteristics
Organizing Mistrust: How Leaders Navigate Bureaucratic Resistance on Foreign Policy
Get PDFThis dissertation examines how political leaders confront an enduring dilemma: while foreign policy professionals offer critical expertise and continuity in managing inter-state relations, they can also undermine leaders’ authority through resistance, obstruction, or disloyalty. How, then, do leaders shape foreign policymaking institutions, rules, and norms to secure their policy goals in the face of potential bureaucratic resistance? I argue that leaders deploy distinct organizational strategies—combinations of formal and informal institutional tools—to adjust the degree of bureaucratic inclusion and control in foreign policymaking. These strategies reflect a balance between two core objectives: retaining the technical competence and institutional memory of the bureaucracy and securing loyalty to the leader’s agenda. Leaders who value control over competence tend to exclude or politicize the bureaucracy; those who prioritize competence promote its autonomy and neutrality. The choice between control and competence hinges on a leader’s trust in the bureaucracy, shaped by psychological processes of social identification. Leaders who see themselves as fundamentally distinct from the bureaucratic establishment experience higher levels of distrust, increasing the perceived cost of bureaucratic input. Distrustful leaders are thus more likely to adopt exclusionary or loyalty-driven strategies—purging, coopting, or restructuring bureaucracies—whereas trustful leaders are more likely to tolerate inclusion and neutrality, even amid disagreement. Significantly, these strategic choices are constrained by a leader’s domestic political strength. Leaders with fewer political rivals can afford to expend more capital battling entrenched bureaucracies. Paradoxically, the most mistrustful leaders may refrain from politicizing bureaucracies if politically weak, while trustful leaders may sideline them when integration becomes too costly. To test this theory, I employ comparative case studies across India, the United States, and Turkey. In India, Indira Gandhi moved from insulation to politicization as her political strength grew, while Manmohan Singh circumvented the bureaucracy in sensitive areas despite his inclusive style. In the U.S., Nixon insulated policymaking to avoid bureaucratic sabotage; Carter, amid conflict with the State Department, sometimes excluded it; and George H. W. Bush trusted and included bureaucratic actors. In Turkey, Recep Tayyip Erdoğan centralized and politicized foreign policy institutions as his political power solidified. Together, these cases reveal how trust, control, and political context shape the organization of foreign policymaking across regimes. <p
The Roles of Microbe-Derived Transfer RNA Modifications in Eukaryotic Cell Physiology
Get PDFAcross all kingdoms of life, transfer ribonucleic acid (tRNA) is essential for translation of mRNA into protein. These adaptor molecules, comprising 75-95 nucleotides, decode mRNA codons via base pairing and carry the amino acid dictated by the genetic code to the ribosome. The typical tRNA adopts a cloverleaf secondary structure and an L-shaped tertiary structure. This conserved conformation enables tRNA to engage with both the mRNA codon and the ribosome during translation. In eukaryotic cells, tRNAs are both the most abundant and the most extensively modified cellular RNA species. Indeed, eukaryotic tRNAs carry an average of 13 modifications per cytosolic tRNA and an average of 5 modifications per mitochondrial tRNA. Over 100 different tRNA modifications have been described to date. Though diverse in chemical structure and location, modifications are broadly important in maintaining tRNA stability and fine- tuning translational dynamics. A modification of particular interest is queuosine (Q), a hypermodified guanosine analog found at position 34 in the anticodon of cytosolic and mitochondrial tRNAs for asparagine, aspartic acid, histidine, and tyrosine. While bacteria can synthesize queuosine-tRNA (Q-tRNA) de novo, eukaryotes must import extracellular queuine (the corresponding nucleobase of Q nucleotide) sourced from the environment (i.e., gut microbiome or diet). Q-modification is implicated in modulating decoding accuracy and decoding speed of synonymous NAC/U codons. However, despite being discovered decades ago, the full biological significance of queuosine is still being actively explored. In Chapter 2, we investigate the role of Q-modification on mammalian cell physiology using proliferation experiments and multiplex small RNA-seq (MSR-seq). We report that Q-modification promotes proliferation in both HEK293T cells and murine bone marrow-derived dendritic cells (BMDCs). In both cell types, we identify a novel correlative relationship between the Q and m22G (N2,N2-methylguanosine) modifications. Our mRNA-seq results show a cell-type-specific transcriptomic response to Q- modification levels. Using the same data, we propose a codon-usage-based mechanism underlying the Q-dependent changes in transcription and proliferation. In Chapter 3, we study how preQ1, a metabolic precursor of bacterial Q-tRNA, impacts HEK293T cells and BMDCs. We find that preQ1 generally attenuates cell proliferation in a cell-cycle-independent manner, a phenotype that can be rescued by co-treatment with queuine. By conducting mRNA-seq, we also identify global changes to the BMDC transcriptome in response to preQ1 treatment. In Chapter 4, we focus on BMDCs and their cell-specific functions. Using flow cytometry, we demonstrate that both queuine and preQ1 impact the expression of MHC- II, an immune response mediator. Finally, in Chapter 5, we characterize two photoactivatable preQ1 analog probes in mammalian cell culture. We find that the probes exhibit queuine-like bioactivity and are covalently inserted into Q-modifiable tRNAs. Moreover, we present preliminary RT- qPCR results revealing a potential role for preQ1 and queuine in regulating mammalian histone mRNA levels. Together, this work sheds light on the functions of Q and its derivatives, underscoring their importance in eukaryotic cell physiology