Hasil untuk "Medicine"

L. Grossman

The George Washington University School of Medicine and Health Sciences seeks to graduate “Physician Citizens” committed to local, national, and global public service through excellent patient care, leadership, advocacy for change and innovation, and scholarly inquiry. This goal will be achieved through a robust and flexible curriculum and by leveraging the School’s unique position as part of a major university located in the heart of the nation’s capital surrounded by major institutions and leading authorities in domestic and international health.

C. Pechura

J. Lefkovits, E. Plow, E. Topol

R. P. Sloan, E. Bagiella, Tia Powell

V. Podgorelec, P. Kokol, B. Stiglic et al.

M. Roco

Christine Hughes Mcsp BPhil

H. Burstein, S. Gelber, E. Guadagnoli et al.

C. Fattman, L. Schaefer, T. Oury

Simon Noë, Seyed Amir Zaman Pour, Ahmadreza Rezaei et al.

Scattered coincidences introduce quantitative bias in positron emission tomography (PET) and must be compensated during reconstruction. Conventional scatter estimates typically rely on simplified cylindrical scanner models that omit detector physics. Incorporating detector sensitivities for scatter is challenging because scattered events exhibit less constrained properties, such as incidence angles, compared to true coincidences. We integrated a 5D single-photon detection probability lookup table (LUT) accounting for photon energy, incidence angle, and detector location into the simulator logic. The resulting scatter sinogram is scaled by a precomputed, LUT-specific scatter sensitivity sinogram. Scatter was simulated using MCGPU-PET, a fast Monte Carlo (MC) simulator with a simplified scanner model, and applied to phantom data from a simulated GE Signa PET/MR in GATE. We evaluated three scenarios: (1) high-count MC simulations from a known activity distribution; (2) limited-count simulations; and (3) joint estimation of activity and scatter under low-count conditions. The method was also tested on two real Signa PET/MR acquisitions. In scenario 1, scatter-compensated reconstructions achieved <1% global bias in all active regions. In scenario 2, noisy scatter estimates caused positive bias, but Gaussian smoothing restored accuracy to scenario 1 levels. In scenario 3, joint estimation maintained <1% bias in nearly all regions. For real scans, the MC-based scatter estimate closely matched the vendor-provided scatter estimate. This proof-of-concept demonstrates that scatter sensitivity modeling can enhance simulators by incorporating detector physics. It supports the feasibility of using fast MC simulations for real scans, offering improved accuracy and robustness to acquisition noise in clinical PET reconstruction.

Gernot Fiala, Markus Plass, Robert Harb et al.

A Whole Slide Image (WSI) is a high-resolution digital image created by scanning an entire glass slide containing a biological specimen, such as tissue sections or cell samples, at multiple magnifications. These images are digitally viewable, analyzable, and shareable, and are widely used for Artificial Intelligence (AI) algorithm development. WSIs play an important role in pathology for disease diagnosis and oncology for cancer research, but are also applied in neurology, veterinary medicine, hematology, microbiology, dermatology, pharmacology, toxicology, immunology, and forensic science. When assembling cohorts for AI training or validation, it is essential to know the content of a WSI. However, no standard currently exists for this metadata, and such a selection has largely relied on manual inspection, which is not suitable for large collections with millions of objects. We propose a general framework to generate 2D index maps (tissue maps) that describe the morphological content of WSIs using common syntax and semantics to achieve interoperability between catalogs. The tissue maps are structured in three layers: source, tissue type, and pathological alterations. Each layer assigns WSI segments to specific classes, providing AI-ready metadata. We demonstrate the advantages of this standard by applying AI-based metadata extraction from WSIs to generate tissue maps and integrating them into a WSI archive. This integration enhances search capabilities within WSI archives, thereby facilitating the accelerated assembly of high-quality, balanced, and more targeted datasets for AI training, validation, and cancer research.

M. A. Rasel, Sameem Abdul Kareem, Zhenli Kwan et al.

In dermoscopic images, which allow visualization of surface skin structures not visible to the naked eye, lesion shape offers vital insights into skin diseases. In clinically practiced methods, asymmetric lesion shape is one of the criteria for diagnosing melanoma. Initially, we labeled data for a non-annotated dataset with symmetrical information based on clinical assessments. Subsequently, we propose a supporting technique, a supervised learning image processing algorithm, to analyze the geometrical pattern of lesion shape, aiding non-experts in understanding the criteria of an asymmetric lesion. We then utilize a pre-trained convolutional neural network (CNN) to extract shape, color, and texture features from dermoscopic images for training a multiclass support vector machine (SVM) classifier, outperforming state-of-the-art methods from the literature. In the geometry-based experiment, we achieved a 99.00% detection rate for dermatological asymmetric lesions. In the CNN-based experiment, the best performance is found with 94% Kappa Score, 95% Macro F1-score, and 97% Weighted F1-score for classifying lesion shapes (Asymmetric, Half-Symmetric, and Symmetric).

Cristina Dolciotti, Paolo Andre, Maria Paola Tramonti Fantozzi et al.

In 16 healthy volunteers (age 42-69 years, 8 females) we investigated chewing effects on postural learning. Initially, the Centre of Pressure (CoP) position in bipedal stance was recorded (1 minute) in 4 conditions: Hard support (HS)-Open Eyes (OE), HS-Closed Eyes (CE), Soft Support (SS)-OE, SS-CE. Following 2 minutes of Chewing (C, n = 8 subjects, 4 females) or rhythmic Hand Grip (HG, n = 8 subjects, 4 females), 10 unipedal stance test (1 minute) were performed for 30 minutes in both groups in HS-OE, with a progressive decrease in CoP Velocity and Path Length. Since the 95% Area of body sway decreased only in the HG group, the Length in Function of Surface (LFS, indicative of balance energy expenditure), increased in the HG and remained constant in the C group. Soon after and 5 hours post-training, bipedal stance tests were performed for 8 minutes, in the same order as before. In both groups, the changes in unipedal stance parameters were found persistent 5 hours post-training. In SS-OE condition of bipedal stance, CoP Velocity was reduced and 95% Area increased by postural training, in the HG and C group, respectively. These modifications were significantly correlated to the corresponding changes in unipedal stance and led to a LSF decrease in the C group. In conclusion, the CoP Velocity during unipedal training was not affected by the previous motor activities. Chewing allowed for a larger compliance concerning the extent of CoP oscillation. Postural training in unipedal stance seem to favour the development of modifications in bipedal stance, according to the conditioning activity. Chewing before a postural training promotes a postural strategy characterized by a constant and a lower energy cost in unipedal and bipedal stance, respectively. Further experiments are necessary to verify whether such a change may promote a more secure balance in trained people.

Guillaume Barbalat, Ariane Guilbert, Lucie Adelaïde et al.

Abstract Background A number of negative developmental outcomes in response to extreme temperature have been documented. Yet, to our knowledge, environmental research has left the question of the effect of temperature on human neurodevelopment largely unexplored. Here, we aimed to investigate the effect of ambient temperature on linguistic development at the age of 2 years-old. Methods We used data from the prospective national French birth cohort ELFE (N = 12,163) and highly-resolved exposure models with daily temporal resolution and 200 m to 1 km spatial resolution. We investigated the effect of weekly averages of overall, daytime and night-time temperature in the prenatal (first 30 weeks of gestation) and postnatal (91 weeks after birth) period on vocabulary production scores from the MacArthur-Bates Communicative Development Inventories (MB-CDI) at 2 years-old. Exposure-response and lag-response relationships were modeled with confounder-adjusted distributed lag non-linear models. Results Scores at the MB-CDI decreased by 3.2% (relative risk (RR) 0.968, 95% confidence interval (CI): 0.939–0.998) following exposure to severe night-time heat of 15.6 °C (95th percentile) vs. 8.3 °C (median) throughout gestational weeks 14 to 19. In the postnatal period, scores at the MB-CDI decreased by 14.8% (RR 0.852; 95% CI: [0.756–0.96]) for severe overall heat of 21.9 °C (95th percentile) vs. 11.5 °C (median) throughout weeks 1 to 28. Consistent results were found for daytime and night-time heat. We observed positive effects of overall and night-time heat in the first few weeks of pregnancy. Night-time cold in the pre-natal period also resulted in improved scores at the MB-CDI. Adjusting our models for air pollutants (PM2.5, PM10 and NO2) tended to confirm these observations. Finally, there were no significant differences in temperature effects between boys and girls. Conclusion In this large cohort study, we showed a negative impact of hot temperatures during pregnancy and after birth on language acquisition. Positive associations observed in the first few weeks of pregnancy are likely the results of methodological artifacts. Positive associations with night-time cold during the prenatal period are likely truly protective, as colder temperatures may encourage staying indoors at a comfortable temperature. Policymakers should consider neurodevelopment impairments as a deleterious effect of climate change.

Choon Chiat Oh, Boon Yee Lim, Elizabeth Chun Yong Lee et al.

ABSTRACT Background Cutaneous squamous cell carcinoma (cSCC) remains poorly understood at the molecular level, both in the immunocompetent and immunosuppressed population with skin of colour. Data on the diversity of viruses found in cSCC is also lacking. Objectives We aimed to characterise the immunological and molecular profiles of cSCC in organ transplant recipients (OTR) and non‐transplant recipients in an Asian cohort (n = 53) and explore the diversity of viruses detected. Methods Gene expression analysis was performed on snap‐frozen cSCC tissues using the NanoString PanCancer IO360 panel. Viral detection was performed using the Twist Comprehensive Viral Research Panel. Results cSCC presented dysregulation of immune response pathways and tumour microenvironment remodelling compared to adjacent normal skin tissue. Cell‐type profiling based on gene expression profiles showed higher levels of exhausted CD8 cells, neutrophils, and cytotoxic cells in tumour cells. Furthermore, three distinct clusters of cSCC gene signatures could be observed, where Cluster 3 with the highest Tumour inflammation signature (TIS) scores displayed distinct upregulation of most pathways suggesting a more inflamed or “hot” tumour phenotype. cSCC of OTR exhibited greater expression of tumour markers (AQP9, SERPINA1) and reduced expression of T‐cell cytokines (CXCL10, CXCL11). Viruses were particularly enriched in tumour tissue, as compared with normal skin. In addition, there was an enrichment of detectable viruses in transplant‐associated cSCC, with several tumours harbouring multiple viruses (HPV, EBV, MCV, and TTV). Conclusions cSCC is marked by a pro‐tumorigenic immune environment with altered immune cell populations. These findings support the potential for stratified, immune‐tailored treatment approaches for cSCC, especially in OTR who have a higher disease burden. Future studies on the possible oncogenic role of the detected viruses can be undertaken.

D. Ludwig, J. Kabat‐Zinn

Marcus William Kruger, Jana du Plessis, Pravani Moodley

Introduction: Unstable pelvic fractures cause significant bleeding, morbidity, and mortality. Commercially available Pelvic Circumferential Compression Devices (PCCDs) are used in the initial resuscitation and management of these cases. In the trauma-burdened, resource limited setting of Southern Africa, the available alternative is a pelvic sheet binder (PSB). For optimal results placement should be at the greater trochanters (GTs). Prior studies have shown that practitioners are inaccurate in their placement. This study aimed to describe placement of PSBs by doctors and factors influencing placement. Methods: This was a multicentre, prospective, observational, simulation-based study. Doctors working in Emergency Departments (EDs) and Trauma Emergency Units (TEUs) in Johannesburg were asked to place a PSB on two healthy male models of differing body mass index (BMI), as simulated patients (SPs). Outcomes were based on PSB position relative to the GTs, marked using an ultraviolet pen, and photographed under ultraviolet light. Data on techniques of placement, as well as practitioner factors, were also collected to investigate their influence on accuracy. Results: In this study 147/176 (83.5 %) of the PSBs placed were correct (trochanteric). Of those placed on the normal BMI SP 71/88 (81 %) were correct and 76/88 (86 %) of those on the increased BMI SP. BMI did not appear to influence accuracy of placement. Practitioner factors that had statistically significant association with accurate placement included the following: Working in the TEU, work experience of ≥6 years, a diploma in primary emergency care (DipPEC, College of emergency medicine, South Africa), all methods of placing the PSB and inspecting to find the GTs. Conclusion: The overall accuracy of PSBs placement was high (83.5 %). Additional postgraduate training (DipPEC) and work experience improved placement accuracy. This study highlighted the importance of additional trauma training and areas of possible future research, such as optimal binder width and method of securing PSBs.

Muhammed Fatih Tabara, Murad Atmaca, Hanefi Yıldırım et al.

It has been shown that structural changes occur in the brain in many types of addiction and can have an impact on maintaining addictive behavior, which can be improved with treatment. The study aimed to iden- tify structural changes in the brain’s reward system in alcohol use disorder. Structural magnetic resonance imaging was employed to compare the volumes of total white matter and gray matter, as well as those of the nucleus accumbens, ventral tegmental area, amygdala, and hippocampus between 15 individuals diag- nosed with alcohol use disorder and 17 healthy controls. The Michigan Alcoholism Screening Test, Severity of Alcohol Dependence Questionnaire, and Alcohol Use Disorders Identification Test were administered to the participants to reveal the pattern of alcohol use and severity of dependence. The group with alcohol use disorder exhibited a significant decrease in the volume of the right hippocampus. No differences were found between the two groups in terms of other brain regions. In conclusion, this study revealed a decrease in hip- pocampal volume in patients with alcohol use disorder. It is an indication that structural changes play a role in the etiology of cognitive impairments commonly seen in alcohol use disorder.

Radostin D. Simitev, Antesar Al Dawoud, Muhamad H. N. Aziz et al.

Current understanding of arrhythmia mechanisms and design of anti-arrhythmic drug therapies hinges on the assumption that myocytes from the same region of a single heart have similar, if not identical, action potential waveforms and drug responses. On the contrary, recent experiments reveal significant heterogeneity in uncoupled healthy myocytes both from different hearts as well as from identical regions within a single heart. In this work, a methodology is developed for quantifying the individual electrophysiological properties of large numbers of uncoupled cardiomyocytes under ion channel block in terms of the parameters values of a conceptual fast-slow model of electrical excitability. The approach is applied to a population of nearly 500 rabbit ventricular myocytes for which action potential duration (APD) before and after the application of the drug nifedipine was experimentally measured (Lachaud et al., 2022, Cardiovasc. Res.). To this end, drug action is represented by a multiplicative factor to an effective ion conductance, a closed form asymptotic expression for APD is derived and inverted to determine model parameters as functions of APD and dAPD (drug-induced change in APD) for each myocyte. Two free protocol-related quantities are calibrated to experiment using an adaptive-domain procedure based on an original assumption of optimal excitability. The explicit APD expression and the resulting set of model parameter values allow (a) direct evaluation of conditions necessary to maintain fixed APD or dAPD, (b) predictions of the proportion of cells remaining excitable after drug application, (c) predictions of stimulus period dependency and (d) predictions of dose-response curves, the latter being in agreement with additional experimental data.

Li-Chin Chen, Kuo-Hsuan Hung, Yi-Ju Tseng et al.

The inherent nature of patient data poses several challenges. Prevalent cases amass substantial longitudinal data owing to their patient volume and consistent follow-ups, however, longitudinal laboratory data are renowned for their irregularity, temporality, absenteeism, and sparsity; In contrast, recruitment for rare or specific cases is often constrained due to their limited patient size and episodic observations. This study employed self-supervised learning (SSL) to pretrain a generalized laboratory progress (GLP) model that captures the overall progression of six common laboratory markers in prevalent cardiovascular cases, with the intention of transferring this knowledge to aid in the detection of specific cardiovascular event. GLP implemented a two-stage training approach, leveraging the information embedded within interpolated data and amplify the performance of SSL. After GLP pretraining, it is transferred for TVR detection. The proposed two-stage training improved the performance of pure SSL, and the transferability of GLP exhibited distinctiveness. After GLP processing, the classification exhibited a notable enhancement, with averaged accuracy rising from 0.63 to 0.90. All evaluated metrics demonstrated substantial superiority (p < 0.01) compared to prior GLP processing. Our study effectively engages in translational engineering by transferring patient progression of cardiovascular laboratory parameters from one patient group to another, transcending the limitations of data availability. The transferability of disease progression optimized the strategies of examinations and treatments, and improves patient prognosis while using commonly available laboratory parameters. The potential for expanding this approach to encompass other diseases holds great promise.