Truman State University

Lung and colon cancers are among the leading causes of cancer-related mortality worldwide. Early and accurate detection of these cancers is crucial for effective treatment and improved patient outcomes. False or incorrect detection is harmful. Accurately detecting cancer in a patient’s tissue is crucial to their effective treatment. While analyzing tissue samples is complicated and time-consuming, deep learning techniques have made it possible to complete this process more efficiently and accurately. As a result, researchers can study more patients in a shorter amount of time and at a lower cost. Much research has been conducted to investigate deep learning models that require great computational ability and resources. However, none of these have had a 100% accurate detection rate for these life-threatening malignancies. Misclassified or falsely detecting cancer can have very harmful consequences. This research proposes a new lightweight, parameter-efficient, and mobile-embedded deep learning model based on a 1D convolutional neural network with squeeze-and-excitation layers for efficient lung and colon cancer detection. This proposed model diagnoses and classifies lung squamous cell carcinomas and adenocarcinoma of the lung and colon from digital pathology images. Extensive experiment demonstrates that our proposed model achieves 100% accuracy for detecting lung, colon, and lung and colon cancers from the histopathological (LC25000) lung and colon datasets, which is considered the best accuracy for around 0.35 million trainable parameters and around 6.4 million flops. Compared with the existing results, our proposed architecture shows state-of-the-art performance in lung, colon, and lung and colon cancer detection.

Mood and anxiety disorders involve defining symptoms (e.g., dysphoria, anhedonia) that can impair psychosocial functioning (e.g., self-care, work, social relationships). The present study evaluated the validity of the Inventory of Depression and Anxiety Symptoms-II (IDAS-II; Watson et al., 2012) via convergence with a semistructured interview assessing mood and anxiety disorder symptoms and, moreover, prediction of psychosocial functioning. Community-dwelling adults (N = 601) completed the self-report IDAS-II, a semistructured diagnostic interview, and self-report and interview measures of psychosocial functioning. A retest subsample (ns = 497–501) completed the functioning measures again, on average 8 months later. Supporting our hypotheses, the IDAS-II converged robustly with interview-assessed symptoms and predicted psychosocial functioning significantly, both concurrently and prospectively. Moreover, the IDAS-II predicted functioning significantly better than did the diagnostic interview. These findings support use of the IDAS-II in research and clinical settings to assess mood and anxiety symptoms and their connections to psychosocial impairment.

The Partnership for Undergraduate Life Sciences Education (PULSE) is a non-profit educational organization committed to promoting the transformation of undergraduate STEM education by supporting departments in removing barriers to access, equity, and inclusion and in adopting evidence-based teaching and learning practices. The PULSE Ambassadors Campus Workshop program enables faculty and staff members of host departments to 1) develop communication, shared leadership, and inclusion skills for effective team learning; 2) implement facilitative leadership skills (e.g., empathic listening and collaboration); 3) create a shared vision and departmental action plan; and 4) integrate diversity, equity, and inclusion practices in the department and curriculum. From the first workshop in 2014, teams of trained Ambassadors conducted workshops at 58 institutions, including associate, bachelor, master, and doctoral institutions. In their workshop requests, departments cited several motivations: desire to revise and align their curriculum with Vision and Change recommendations, need for assistance with ongoing curricular reform, and wish for external assistance with planning processes and communication. Formative assessments during and immediately following workshops indicated that key outcomes were met. Post-workshop interviews of four departments confirm progress achieved on action items and development of individual department members as agents of change. The PULSE Ambassadors program continues to engage departments to improve undergraduate STEM education and prepare departments for the challenges and uncertainties of the changing higher education landscape.

The aim of this study was to evaluate prediction equations to estimate 1RM in different exercises in older men and women with osteopenia/osteoporosis. Forty well-trained older women and men (73 ± 8 years) with osteopenia/osteoporosis performed 1RM dynamic and isometric maximum strength tests on resistance devices. In addition, each participant performed repetitions-to-fatigue (RTF) in the 5–8RM, 9–12RM, and 13–16RM zones. After evaluating the predictive performance of available 1RM prediction equations from the literature, new prediction equations were developed for all seven exercises. One of the available equations that focus on postmenopausal women already acceptably predicted 1RM from RTF for all but one exercise. Nevertheless, new exercise-specific prediction equations based on a cubic polynomial most accurately predict 1RM from RTF in the 5–8 reps range with mean absolute differences between predicted and actual 1RM of 3.7 ± 3.7% (leg-press) to 6.9 ± 5.5% (leg flexion) that is roughly within the acceptable coefficient of variation. For some exercises, the inclusion of the isometric maximum strength tests slightly increases the prediction performance of the 5–8RM. In conclusion, the present prediction equation accurately estimates 1RM in trained, older women and men with osteopenia/osteoporosis. Further evaluation of this new equation is warranted to determine its applicability to different age groups and populations.

We aimed to determine and compare the longitudinal predictive power of Diagnostic and Statistical Manual of Mental Disorders, fifth edition’s (DSM-5) two models of personality disorder (PD) for multiple clinically relevant outcomes. A sample of 600 community-dwelling adults—half recruited by calling randomly selected phone numbers and screening-in for high-risk for personality pathology and half in treatment for mental health problems—completed an extensive battery of self-report and interview measures of personality pathology, clinical symptoms, and psychosocial functioning. Of these, 503 returned for retesting on the same measures an average of 8 months later. We used Time 1 interview data to assess DSM-5 personality pathology, both the Section-II PDs and the alternative (DSM-5) model of personality disorder’s (AMPD) Criterion A (impairment) and Criterion B (adaptive-to-maladaptive-range trait domains and facets). We used these measures to predict 20 Time 2 functioning outcomes. Both PD models significantly predicted functioning-outcome variance, albeit modestly—averaging 12.6% and 17.9% (Section-II diagnoses and criterion counts, respectively) and 15.2% and 23.2% (AMPD domains and facets, respectively). Each model significantly augmented the other in hierarchical regressions, but the AMPD domains (6.30%) and facets (8.62%) predicted more incremental variance than the Section-II diagnoses (3.74%) and criterion counts (3.31%), respectively. Borderline PD accounted for just over half of Section II’s predictive power, whereas the AMPD’s predictive power was more evenly distributed across components. We note the predictive advantages of dimensional models and articulate the theoretical and clinical advantages of the AMPD’s separation of personality functioning impairment from how this is manifested in personality traits.

The primary objective of this study was to explore posttraumatic growth in adults who lived alone during the shelter‐in‐place (SIP) phase of the pandemic. Semistructured interviews were conducted with nine adults between the ages of 33 and 56 several weeks into SIP. Transcripts were analyzed using thematic analysis. Five themes emerged from participant interviews: connection, prior recent hardship, gratitude, spiritual practice, and relationship with self. By exploring the experiences of those who thrived while living alone during the SIP phase, this study aimed to provide a nuanced understanding of the psychological processes underlying positive adaptation amidst crisis. Our findings highlight the importance of fostering connections, both interpersonal and intrapersonal, as a means of promoting resilience and growth during times of crisis. The themes of gratitude, spiritual practice, and a positive relationship with self underscore the significance of existential and humanistic concepts, such as meaning‐making, self‐reflection, and personal growth.

A strong professional identity (PI), seeing oneself as a member of a professional community of practice, is important for student academic and motivational outcomes during transition from college to the work setting. Many educational strategies have been successfully used in medical and other health professions education to support student PI formation. The purpose of this study was to determine the scope and sequence of pedagogical and extra-curricular strategies used by undergraduate public health programs to support student PI formation. An online survey was created and distributed to public health program chairs/directors from all CEPH-accredited undergraduate United States public health programs. Results generally confirmed that the PI formation strategies of curricular training, work-integrated learning, and role-modeling were being implemented in respondents’ accredited undergraduate programs. However, some areas for improvement in offerings and their sequencing were identified. It is recommended that all PI formation strategies be introduced early in the program and constantly emphasized and reinforced so students continually view themselves as part of a professional community of practice. Analysis of the types and timing of PI formation strategies can provide insight on focus areas for improvements that may impact public health student academic achievement, satisfaction, and retention in the program.

This study aimed to determine the agreement between fat-free mass (FFM) estimates from bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) and their use in estimating resting metabolic rate (RMR) in men undergoing resistance training. Thirty healthy resistance-trained men (22.7 ± 4.4 years, 70.0 ± 8.7 kg, 174.6 ± 6.7 cm, and 22.9 ± 2.3 kg/m2) were evaluated. The equation developed by Tinsley et al. (RMR = 25.9 x fat-free mass [FFM] + 284) was adopted to calculate the RMR. DXA was used as the reference method for FFM. Furthermore, FFM was also estimated by BIA using a spectral device. No significant difference (P > 0.05) was observed between DXA (1884.2 ± 145.5 kcal) and BIA (1849.4 ± 167.7 kcal) to estimate RMR. A positive and significant correlation (r = 0.89, P < 0.05) was observed between DXA and BIA estimates of RMR. The mean difference between methods indicated that BIA presented a bias of -34.8 kcal. These findings suggest that using FFM derived from DXA or BIA results in similar RMR estimates in resistance-trained men.

Alzheimer’s disease (AD) is closely associated with obstructive sleep apnea (OSA). Such hypoxic insults trigger glutamate release of chemoafferents into the nucleus tractus solitarii (nTS), an important upstream center of the chemoreflex. Potential alterations of glutamate handling in the nTS may lead to the respiratory dysfunction seen in AD patients. Using the streptozotocin (STZ)-induced rat model — an effective proxy for human AD — we studied the functional consequences of nTS glutamate stress on respiration. STZ-AD was induced in 6-week-old male Sprague Dawley rats via intracerebroventricular injections of 2 - 2.25 mg/kg STZ. After two weeks, EMG recordings of diaphragm activity served as surrogate for respiratory responses to glutamate microinjections (20 nL of 40 mM) into the caudal nTS. In a subset of rats, chemoafferent terminals were labeled with the fluorescent tracer DiI to permit patch clamp recordings of identified 2nd order nTS neurons participating in the chemoreflex loop. Evoked glutamatergic excitatory postsynaptic currents (TS-EPSCs) were generated via tractus solitarii stimulation at frequencies (10 - 40 Hz) typical for afferent discharge during hypoxia. Acute glutamate injections into the caudal nTS increased respiratory frequency by 15 - 20 breaths per minute. The response magnitude was similar between CTL and STZ-AD animals. Excitatory stress with repeated glutamate injections (5 min. apart) evoked a reliable respiratory response in CTL that slowly declined to ~65% from its maximum over the course of 10 injections. In contrast, the decline of respiratory response in STZ-AD was more pronounced and occurred significantly earlier than in CTL, indicating altered glutamate handling in the caudal nTS of STZ-AD rats. Next, we used patch clamp electrophysiology to analyze increased glutamate release of chemoafferents onto 2nd order nTS neurons. High frequency stimulation of chemoafferents induced a successive depression of TS-EPSC amplitude in nTS neurons. TS-EPSC depression was significantly stronger in STZ-AD and may be due to altered glutamate handling at the synapse. Western Blot analysis of STZ-AD brainstem tissue including the nTS revealed a significant increase in glial fibrillary acidic protein (GFAP) expression and a decrease of excitatory amino acid transporters (EAATs) expression, suggesting astrocyte involvement in compromised nTS glutamate handling in STZ-AD. In summary, the STZ-AD model showed reduced respiratory responses to glutamate stress in the caudal nTS. The altered stress response may come from enhanced depression of TS-EPSC amplitude at nTS neurons in the chemoreflex. Altered astrocytic glutamate removal from the synaptic cleft may contribute to TS-EPSC depression. Together, altered glutamate handling in a respiratory brainstem center may contribute to OSA in AD patients. NIH R15AG065927 (TDO & DO), KCOM Biomedical Graduate Program (RKT &TDO), ATSU Research Support (SKRC). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.