Georgia State University

Artificial intelligence is increasingly advancing both fundamental research and clinical applications in schizophrenia. This review surveys recent literature on artificial intelligence driven approaches for schizophrenia diagnosis, treatment, management, and characterization, using multiple data modalities such as neuroimaging, electrophysiology, electronic health records, and genomic data. Recent work shows substantial progress in leveraging machine learning and deep learning for diagnostic label prediction, treatment response modeling, and brain network characterization. While many studies continue to improve feature extraction and classification methods within single modalities, there is a growing trend to utilize multiple data sources to capture the complexity of schizophrenia from a comprehensive perspective. Emerging themes include multimodal fusion methodologies to identify linked correlates of schizophrenia, as well as data-driven approaches to learn subgroups, brain networks, and psychosis continua. The rise of large-scale multimodal datasets, foundation models, and mechanistic interpretability methods holds promise for scalable symptom assessment and biomarker identification, thereby better supporting early intervention and personalized treatment. Current literature highlights a shift from unimodal prediction to holistic, multimodal characterization of schizophrenia. Transforming these artificial intelligence models into clinical tools, however, requires careful attention to patient privacy and data bias, alongside rigorous validation across diverse populations and settings.

Micro-multinationals from emerging markets (mEMNEs) face significant challenges in establishing social legitimacy in foreign markets due to resource constraints and limited knowledge of local societal issues. This study examines how mEMNEs leverage partnerships with non-governmental organizations (NGOs) to develop dynamic capabilities for social innovation and, ultimately, to build social legitimacy in other emerging markets. Drawing on survey data from 143 Pakistani mEMNEs operating internationally, we find that NGO coupling positively influences the development of dynamic capabilities. These effects amplify when NGO salience and activism are high. Furthermore, social innovation mediates the relationship between NGO coupling, dynamic capabilities, and social legitimacy. Our findings extend dynamic capabilities theory into the social domain and contribute to understanding how resource-constrained multinationals from emerging markets can overcome legitimacy deficits through strategic stakeholder engagement. We also provide practical insights for managers on leveraging NGO partnerships and offer policy recommendations for facilitating cross-border social innovation initiatives.

Background/Objectives: Young adulthood is a critical developmental period during which lifestyle behaviors may shape intrinsic brain network dynamics that support cognition. This pilot longitudinal intervention study examined whether variability in physical activity and sedentary behavior during an 8-week exercise and/or cognitive intervention protocol was associated with changes in intrinsic brain dynamics and cognitive and mood outcomes in undergraduate young adults. Methods: Participants (n = 32) completed resting-state functional magnetic resonance imaging (rs-fMRI) at baseline (T1) and post-intervention (T2). Dynamic functional network connectivity (dFNC) was estimated from 53 intrinsic connectivity networks derived using spatially constrained independent component analysis (ICA). Ten recurring dynamic connectivity states were identified and individualized using constrained dynamic double functional independent primitives (c-ddFIPs). State occupancy and dynamic convergence and divergence metrics were computed to characterize network flexibility. Results: Greater moderate-to-vigorous physical activity was modestly but consistently associated with increased occupancy of integrative higher-order states, particularly States 6 and 7, and reduced occupancy of more segregated configurations. More physically active individuals also demonstrated greater divergence between integrative and low-engagement states, whereas greater sedentary time corresponded to increased similarity among segregated configurations. Working memory performance showed parallel associations with more integrative and better-differentiated dynamic patterns. Conclusions: These findings suggest that dynamic functional network reconfiguration may represent a neurobiological mechanism linking lifestyle behaviors and cognitive health in young adulthood. Furthermore, they highlight the translational promise of engagement-driven, low-burden programs for college-aged young adults, showing that even modest variability in habitual physical activity corresponds to greater engagement and differentiation of integrative connectivity states linked to executive and broader cognitive functions.

Identification of disease-associated spectral alterations of oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMD) is critical to improving patient outcomes. Protein structural changes in serum can be investigated using a minimally invasive, potential adjunctive analytical method. This preliminary, exploratory study aimed to explore the ability of attenuated total reflection–Fourier transform infrared (ATR-FTIR) spectroscopy to characterize disease-associated serum protein structural alterations in OSCC and OPMDs relative to healthy controls (HCs). A laboratory-based analytical study was conducted using 110 serum samples from clinically and histopathologically confirmed cases: OSCC (n = 22), oral leukoplakia (OLK) (n = 22), oral lichen planus (OLP) (n = 22), oral submucous fibrosis (OSF) (n = 22), and HCs (n = 22). Spectral data were obtained with a FTIR over the 400–4000 cm⁻¹ range. Protein secondary structure alterations were analyzed using spectral deconvolution and Gaussian curve fitting. The relevance of specific wavenumbers was evaluated, and sensitivity and specificity were calculated to describe their ability to differentiate diseased groups from HCs in an exploratory manner. Alterations in the Amide I region were evident in serum samples from OSCC and OLK compared with controls, although no direct statistical comparison between disease groups was performed. Ten wavenumbers (1372, 1381, 1390, 1398, 1412, 1421, 1609, 1635, 1665, and 1683 cm⁻¹) showed statistically significant disease-associated differences between diseased groups and healthy controls. Among the evaluated spectral features, the wavenumber 1390 cm⁻¹ showed the highest sensitivity and specificity values for distinguishing OSCC from HCs (77.3% sensitivity, 86.4% specificity) and OLK from HCs (86.4% sensitivity, 77.3% specificity). ATR-FTIR spectroscopy revealed distinct protein structural alterations in serum samples from patients with OSCC and OPMD when compared with healthy individuals. Specific spectral features, particularly at 1381 cm⁻¹ and 1683 cm⁻¹, demonstrated consistent disease-associated alterations compared with HCs, indicating their potential utility as minimally invasive serum-based spectral markers in exploratory studies of oral cancer and OPMD.

Most ROS-sensitive cleavable linkers rely on their broad reactivity toward all ROS. However, individual ROS have very specialized functions in various pathologies. For example, HOCl/OCl- is primarily produced in response to infection and/or inflammation by certain immune cells that express myeloperoxidase (MPO). We herein describe a novel HOCl/OCl--selective prodrug approach through an oxidation-initiated Cascade Reaction with Kinetic Tunability (CReKT) for drug release. Specifically, HOCl/OCl- oxidation of a phenylthioether is used to trigger prodrug activation via enhancing the nucleophilicity of the S-connected carbon for condensation-based payload release. The reactivity of the S-connected carbon is further augmented by tethering to an electron-withdrawing group (EWG) and by creating synergy with proximity effects. Tunability of release kinetics can be achieved by varying the EWG, substitution on the phenyl ring, and entropic factors. This approach offers new tools and sets a new direction in designing species-selective ROS-sensitive prodrugs.

Numerous peptide hormones regulate feeding and metabolism via the brain and alimentary canal. Many of these peptides are also expressed, along with their cognate receptors, in the taste buds of the lingual epithelium. Among those present in the rodent oral cavity are peptides and receptors in the neuropeptide Y (NPY) family. Previous studies suggest that manipulation of NPY family peptide signaling can impact upon taste-related behavior, but it remains unclear whether these are mediated by changes in taste information processed by taste bud cells (TBCs), the primary sensory organs of the gustatory system, and whether human taste buds are similarly impacted by NPY family peptide signaling. In this report, we identify a complex modulatory role for NPY family peptides in shaping the tastant-evoked responses of human TBCs. Using a human fungiform taste bud cell line, we show that NPY and peptide YY (PYY), along with NPY receptor subtypes 1 and 2 (NPY1R and NPY2R), are expressed in TBCs. Importantly, NPY and PYY modulated the functional responses (assessed by calcium imaging and measurements of neurotransmitter release) of TBCs to bitter and fatty acid stimuli. The nature of modulation (i.e., enhancement or diminishment) was dependent not only on the peptide but also on the taste modality in question. Application of NPY1R and NPY2R antagonists indicated that the differential impacts of these peptides on TBC response parameters were mediated by differential NPY receptor activation. These data suggest that NPY family peptides directly and intricately modify gustatory sensory input by shaping TBC signaling.NEW & NOTEWORTHY The conventional view of feeding regulation by metabolic peptides largely comprises "top-down" peptidergic signaling via the hypothalamus incorporating pre- and postprandial information via the gut-brain axis. Here, we suggest a role for these peptides adjusting "bottom-up" taste information streams that impact food choice and intake. This novel dimension of peptidergic modulation may provide a more comprehensive understanding of taste, feeding, and metabolism that better informs diagnostic and therapeutic developments related to feeding and metabolic regulation.

Abstract While many Americans identify as politically “independent,” conventional wisdom suggests most are covert partisans, especially “leaners.” However, we argue that independents exhibit distinct attitudes toward political parties. Analyzing American National Election Studies open‐ended responses from 1984 to 2020, we employ structural topic models and support vector machines to explore differences in how independents and partisans express “dislikes” about the major parties. Our results show that leaning independents differ significantly from self‐identified partisans in their language and align more closely with pure independents. Furthermore, we find that independents are more likely than partisans to mention issues related to “politics”—such as political cynicism, concern about special interests, or distaste for partisan conflict—when discussing their “dislikes.” These findings suggest that independents have meaningful distinctions from partisans beyond voting behavior, cautioning against overlooking the nuances between these groups.