Classical generalized constant coupling model for geometrically frustrated antiferromagnets

A generalized constant coupling approximation for classical geometrically frustrated antiferromagnets is presented. Starting from a frustrated unit we introduce the interactions with the surrounding units in terms of an internal effective field which is fixed by a self consistency condition. Results for the magnetic susceptibility and specific heat are compared with Monte Carlo data for the classical Heisenberg model for the pyrochlore and kagome lattices. The predictions for the susceptibility are found to be essentially exact, and the corresponding predictions for the specific heat are found to be in very good agreement with the Monte Carlo results.Comment: 4 pages, 3 figures, 2 columns. Discussion about the zero T value of the pyrochlore specific heat correcte

Design and Characterization of a Hypervelocity Expansion Tube Facility

We report on the design and characterization of a 152 mm diameter expansion tube capable of accessing a range of high enthalpy test conditions with Mach numbers up to 7.1 for aerodynamic studies. Expansion tubes have the potential to offer a wide range of test flow conditions as gas acceleration is achieved through interaction with an unsteady expansion wave rather than expansion through a fixed area ratio nozzle. However, the range of test flow conditions is in practice limited by a number of considerations such as short test time and large amplitude flow disturbances. We present a generalized design strategy for small-scale expansion tubes. As a starting point, ideal gas dynamic calculations for optimal facility design to maximize test time at a given Mach number test condition are presented, together with a correction for the expansion head reflection through a non-simple region. A compilation of practical limitations that have been identified for expansion tube facilities such as diaphragm rupture and flow disturbance minimization is then used to map out a functional design parameter space. Experimentally, a range of test conditions have been verified through pitot pressure measurements and analysis of schlieren images of flow over simple geometries. To date there has been good agreement between theoretical and experimental results

Serum IGF-1 is insufficient to restore skeletal size in the total absence of the growth hormone receptor

States of growth hormone (GH) resistance, such those observed in Laron dwarf patients, are characterized by mutations in the GH receptor (GHR), decreased serum and tissue IGF-1 levels, impaired glucose tolerance, and impaired skeletal acquisition. IGF-1 replacement therapy in such patients increases growth velocity but does not normalize growth. Herein we combined the GH-resistant (GHR knockout [GHRKO]) mouse model with mice expressing the hepatic Igf-1 transgene (HIT) to generate the GHRKO-HIT mouse model. In GHRKO-HIT mice, serum IGF-1 levels were restored via transgenic expression of Igf-1, allowing us to study how endocrine IGF-1 affects growth, metabolic homeostasis, and skeletal integrity. We show that in a GH-resistant state, normalization of serum IGF-1 improved body adiposity and restored glucose tolerance but was insufficient to support normal skeletal growth, resulting in an osteopenic skeletal phenotype. The inability of serum IGF-1 to restore skeletal integrity in the total absence of GHR likely resulted from reduced skeletal Igf-1 gene expression, blunted GH-mediated effects on the skeleton that are independent of serum or tissue IGF-1, and poor delivery of IGF-1 to the tissues. These findings are consistent with clinical data showing that IGF-I replacement therapy in patients with Laron syndrome does not achieve full skeletal growth.Fil: Wu, Yingjie. University Of New York; Estados UnidosFil: Sun, Hui. University Of New York; Estados UnidosFil: Basta Pljakic, Jelena. City College of New York; Estados UnidosFil: Cardoso, Luis. City College of New York; Estados UnidosFil: Kennedy, Oran D.. City College of New York; Estados UnidosFil: Jasper, Hector Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas; ArgentinaFil: Domene, Horacio Mario. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas; ArgentinaFil: Karabatas, Liliana Margarita. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas; ArgentinaFil: Guida, María Clara. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones Endocrinológicas; ArgentinaFil: Schaffler, Mitchell B.. City College of New York; Estados UnidosFil: Rosen, Clifford J.. Maine Medical Center Research Institute; Estados UnidosFil: Yakar, Shoshana. University Of New York; Estados Unido

Preoperative image-guided identification of response to neoadjuvant chemoradiotherapy in esophageal cancer (PRIDE):a multicenter observational study

BACKGROUND: Nearly one third of patients undergoing neoadjuvant chemoradiotherapy (nCRT) for locally advanced esophageal cancer have a pathologic complete response (pCR) of the primary tumor upon histopathological evaluation of the resection specimen. The primary aim of this study is to develop a model that predicts the probability of pCR to nCRT in esophageal cancer, based on diffusion-weighted magnetic resonance imaging (DW-MRI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and (18)F-fluorodeoxyglucose positron emission tomography with computed tomography ((18)F-FDG PET-CT). Accurate response prediction could lead to a patient-tailored approach with omission of surgery in the future in case of predicted pCR or additional neoadjuvant treatment in case of non-pCR. METHODS: The PRIDE study is a prospective, single arm, observational multicenter study designed to develop a multimodal prediction model for histopathological response to nCRT for esophageal cancer. A total of 200 patients with locally advanced esophageal cancer - of which at least 130 patients with adenocarcinoma and at least 61 patients with squamous cell carcinoma - scheduled to receive nCRT followed by esophagectomy will be included. The primary modalities to be incorporated in the prediction model are quantitative parameters derived from MRI and (18)F-FDG PET-CT scans, which will be acquired at fixed intervals before, during and after nCRT. Secondary modalities include blood samples for analysis of the presence of circulating tumor DNA (ctDNA) at 3 time-points (before, during and after nCRT), and an endoscopy with (random) bite-on-bite biopsies of the primary tumor site and other suspected lesions in the esophagus as well as an endoscopic ultrasonography (EUS) with fine needle aspiration of suspected lymph nodes after finishing nCRT. The main study endpoint is the performance of the model for pCR prediction. Secondary endpoints include progression-free and overall survival. DISCUSSION: If the multimodal PRIDE concept provides high predictive performance for pCR, the results of this study will play an important role in accurate identification of esophageal cancer patients with a pCR to nCRT. These patients might benefit from a patient-tailored approach with omission of surgery in the future. Vice versa, patients with non-pCR might benefit from additional neoadjuvant treatment, or ineffective therapy could be stopped. TRIAL REGISTRATION: The article reports on a health care intervention on human participants and was prospectively registered on March 22, 2018 under ClinicalTrials.gov Identifier: NCT03474341

Chest CT Imaging Signature of Coronavirus Disease 2019 Infection In Pursuit of the Scientific Evidence:in pursuit of the scientific evidence

BACKGROUND: Chest CT may be used for the diagnosis of coronavirus disease 2019 (COVID-19), but clear scientific evidence is lacking. Therefore, we systematically reviewed and meta-analyzed the chest CT imaging signature of COVID-19.RESEARCH QUESTION: What is the chest CT imaging signature of COVID-19 infection?STUDY DESIGN AND METHODS: A systematic literature search was performed for original studies on chest CT imaging findings in patients with COVID-19. Methodologic quality of studies was evaluated. Pooled prevalence of chest CT imaging findings were calculated with the use of a random effects model in case of between-study heterogeneity (predefined as I-2 =50); otherwise, a fixed effects model was used.RESULTS: Twenty-eight studies were included. The median number of patients with COVID-19 per study was 124 (range, 50-476), comprising a total of 3,466 patients. Median prevalence of symptomatic patients was 99% (range, &gt;76.3%-100%). Twenty-seven of the studies (96%) had a retrospective design. Methodologic quality concerns were present with either risk of or actual referral bias (13 studies), patient spectrum bias (eight studies), disease progression bias (26 studies), observer variability bias (27 studies), and test review bias (14 studies). Pooled prevalence was 10.6% for normal chest CT imaging findings. Pooled prevalences were 90.0% for posterior predilection, 81.0% for ground-glass opacity, 75.8% for bilateral abnormalities, 73.1% for left lower lobe involvement, 72.9% for vascular thickening, and 72.2% for right lower lobe involvement. Pooled prevalences were 5.2% for pleural effusion, 5.1% for lymphadenopathy, 4.1% for airway secretions/tree-in-bud sign, 3.6% for central lesion distribution, 2.7% for pericardial effusion, and 0.7% for cavitation/cystic changes. Pooled prevalences of other CT imaging findings ranged between 10.5% and 63.2%.INTERPRETATION: Studies on chest CT imaging findings in COVID-19 suffer from methodologic quality concerns. More high-quality research is necessary to establish diagnostic CT criteria for COVID-19. Based on the available evidence that requires cautious interpretation, several chest CT imaging findings appear to be suggestive of COVID-19, but normal chest CT imaging findings do not exclude COVID-19, not even in symptomatic patients.</p

Systematic Review and Meta-Analysis on the Value of Chest CT in the Diagnosis of Coronavirus Disease (COVID-19):Sol Scientiae, Illustra Nos

OBJECTIVE. The purpose of this article is to systematically review and meta-analyze the diagnostic accuracy of chest CT in detecting coronavirus disease (COVID-19). MATERIALS AND METHODS. MEDLINE was systematically searched for publications on the diagnostic performance of chest CT in detecting COVID-19. Methodologic quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Meta-analysis was performed using a bivariate random-effects model. RESULTS. Six studies were included, comprising 1431 patients. All six studies included patients at high risk of COVID-19, and five studies explicitly reported that they included only symptomatic patients. Mean prevalence of COVID-19 was 47.9% (range, 27.6–85.4%). High or potential risk of bias was present throughout all QUADAS-2 domains in all six studies. Sensitivity ranged from 92.9% to 97.0%, and specificity ranged from 25.0% to 71.9%, with pooled estimates of 94.6% (95% CI, 91.9–96.4%) and 46.0% (95% CI, 31.9–60.7%), respectively. The included studies were statistically homogeneous in their estimates of sensitivity (p = 0.578) and statistically heterogeneous in their estimates of specificity (p < 0.001). CONCLUSION. Diagnostic accuracy studies on chest CT in COVID-19 suffer from methodologic quality issues. Chest CT appears to have a relatively high sensitivity in symptomatic patients at high risk of COVID-19, but it cannot exclude COVID-19. Specificity is poor. These data, along with other local factors such as COVID-19 prevalence, available real-time reverse transcriptase–polymerase chain reaction tests, staff, hospital, and CT scanning capacity, can be useful to healthcare professionals and policy makers to decide on the utility of chest CT for COVID-19 detection in the hospital setting

Recommendations in Second Opinion Reports of Neurologic Head and Neck Imaging:Frequency, Referring Clinicians? Compliance, and Diagnostic Yield

BACKGROUND AND PURPOSE: Second opinion reports of neurologic head and neck imaging are requested with increased regularity, and they may contain a recommendation to the clinician. Our aim was to investigate the frequency and determinants of the presence of a recommendation and the adherence by the referring physician to the recommendation in a second opinion neurology head and neck imaging report and the diagnostic yield of these recommendations. MATERIALS AND METHODS: This retrospective study included 994 consecutive second opinion reports of neurology head and neck imaging examinations performed at a tertiary care center. RESULTS: Of the 994 second opinion reports, 12.2% (121/994) contained a recommendation. An oncologic imaging indication was significantly (P = .030) associated with a lower chance of a recommendation in the second opinion report (OR = .67; 95% CI, 0.46?0.96). Clinicians followed 65.7% (88/134) of the recommendations. None of the investigated variables (patient age, sex, hospitalization status, indication for the second opinion report, experience of the radiologist who signed the second opinion report, strength of the recommendation, and whether the recommendation was made due to apparent quality issues of the original examination) were significantly associated with the compliance of the referring physician to this recommendation. The 134 individual recommendations eventually led to the establishment of 52 (38.2%) benign diagnoses and 28 (20.6%) malignant diagnoses, while no definitive diagnosis could be established in 56 (41.2%) cases. CONCLUSIONS: Recommendations are relatively common in second opinion reports of neurology head and neck imaging examinations, though less for oncologic indications. They are mostly followed by requesting physicians, thus affecting patient management. In most cases, they also lead to the establishment of a diagnosis, hence adding value to patient care

Reversal of oncogene transformation and suppression of tumor growth by the novel IGF1R kinase inhibitor A-928605

BACKGROUND: The insulin-like growth factor (IGF) axis is an important signaling pathway in the growth and survival of many cell and tissue types. This pathway has also been implicated in many aspects of cancer progression from tumorigenesis to metastasis. The multiple roles of IGF signaling in cancer suggest that inhibition of the pathway might yield clinically effective therapeutics. METHODS: We describe A-928605, a novel pyrazolo [3,4-d]pyrimidine small molecule inhibitor of the receptor tyrosine kinases (IGF1R and IR) responsible for IGF signal transduction. This compound was first tested for its activity and selectivity via conventional in vitro kinome profiling and cellular IGF1R autophosphorylation. Additionally, cellular selectivity and efficacy of A-928605 were analyzed in an IGF1R oncogene-addicted cell line by proliferation, signaling and microarray studies. Finally, in vivo efficacy of A-928605 was assessed in the oncogene-addicted cell line and in a neuroblastoma model as a single agent as well as in combination with clinically approved therapeutics targeting EGFR in models of pancreatic and non-small cell lung cancers. RESULTS: A-928605 is a selective IGF1R inhibitor that is able to abrogate activation of the pathway both in vitro and in vivo. This novel compound dosed as a single agent is able to produce significant growth inhibition of neuroblastoma xenografts in vivo. A-928605 is also able to provide additive effects when used in combination with clinically approved agents directed against EGFR in non-small cell lung and human pancreatic tumor models. CONCLUSION: These results suggest that a selective IGF1R inhibitor such as A-928605 may provide a useful clinical therapeutic for IGF pathway affected tumors and warrants further investigation

Patient perspectives on the use of artificial intelligence in prostate cancer diagnosis on MRI

Objectives: This study investigated patients’ acceptance of artificial intelligence (AI) for diagnosing prostate cancer (PCa) on MRI scans and the factors influencing their trust in AI diagnoses. Materials and methods: A prospective, multicenter study was conducted between January and November 2023. Patients undergoing prostate MRI were surveyed about their opinions on hypothetical AI assessment of their MRI scans. The questionnaire included nine items: four on hypothetical scenarios of combinations between AI and the radiologist, two on trust in the diagnosis, and three on accountability for misdiagnosis. Relationships between the items and independent variables were assessed using multivariate analysis. Results: A total of 212 PCa suspicious patients undergoing prostate MRI were included. The majority preferred AI involvement in their PCa diagnosis alongside a radiologist, with 91% agreeing with AI as the primary reader and 79% as the secondary reader. If AI has a high certainty diagnosis, 15% of the respondents would accept it as the sole decision-maker. Autonomous AI outperforming radiologists would be accepted by 52%. Higher educated persons tended to accept AI when it would outperform radiologists (p &lt; 0.05). The respondents indicated that the hospital (76%), radiologist (70%), and program developer (55%) should be held accountable for misdiagnosis. Conclusions: Patients favor AI involvement alongside radiologists in PCa diagnosis. Trust in AI diagnosis depends on the patient’s education level and the AI performance, with autonomous AI acceptance by a small majority on the condition that AI outperforms a radiologist. Respondents held the hospital, radiologist, and program developers accountable for misdiagnosis in descending order of accountability. Clinical relevance statement: Patients show a high level of acceptance for AI-assisted prostate cancer diagnosis on MRI, either alongside radiologists or fully autonomous, particularly if it demonstrates superior performance to radiologists alone. Key Points: Prostate cancer suspicious patients may accept autonomous AI based on performance. Patients prefer AI involvement alongside a radiologist in diagnosing prostate cancer. Patients indicate accountability for AI should be shared among multiple stakeholders.</p