Context. Large spectroscopic Galactic surveys imply a selection function in the way they performed their target selection. Aims. We investigate here the effect of the selection function on the ...metallicity distribution function (MDF) and on the vertical metallicity gradient by studying similar lines of sight using four different spectroscopic surveys (APOGEE, LAMOST, RAVE, and Gaia-ESO), which have different targeting strategies and therefore different selection functions. Methods. We use common fields between the spectroscopic surveys of APOGEE, LAMOST, RAVE (ALR) and APOGEE, RAVE, Gaia-ESO (AGR) and use two stellar population synthesis models, GALAXIA and TRILEGAL, to create mock fields for each survey. We apply the selection function in the form of colour and magnitude cuts of the respective survey to the mock fields to replicate the observed source sample. We make a basic comparison between the models to check which best reproduces the observed sample distribution. We carry out a quantitative comparison between the synthetic MDF from the mock catalogues using both models to understand the effect of the selection function on the MDF and on the vertical metallicity gradient. Results. Using both models, we find a negligible effect of the selection function on the MDF for APOGEE, LAMOST, and RAVE. We find a negligible selection function effect on the vertical metallicity gradients as well, though GALAXIA and TRILEGAL have steeper and shallower slopes, respectively, than the observed gradient. After applying correction terms on the metallicities of RAVE and LAMOST with respect to our reference APOGEE sample, our observed vertical metallicity gradients between the four surveys are consistent within 1σ. We also find consistent gradient for the combined sample of all surveys in ALR and AGR. We estimated a mean vertical metallicity gradient of − 0.241 ± 0.028 dex kpc-1. There is a significant scatter in the estimated gradients in the literature, but our estimates are within their ranges. Conclusions. We have shown that there is a negligible selection function effect on the MDF and the vertical metallicity gradients for APOGEE, RAVE, and LAMOST using two stellar population synthesis models. Therefore, it is indeed possible to combine common fields of different surveys in studies using MDF and metallicity gradients provided their metallicities are brought to the same scale.
Context. With the existing and upcoming large multifibre low-resolution spectrographs, the question arises of how precise stellar parameters such as Teff and Fe/H can be obtained from low-resolution ...K-band spectra with respect to traditional photometric temperature measurements. Until now, most of the effective temperatures in Galactic bulge studies come directly from photometric techniques. Uncertainties in interstellar reddening and in the assumed extinction law could lead to large systematic errors (>200 K). Aims. We obtain and calibrate the relation between Teff and the 12CO first overtone bands for M giants in the Galactic bulge covering a wide range in metallicity. Methods. We used low-resolution spectra for 20 M giants with well-studied parameters from photometric measurements covering the temperature range 3200 <Teff< 4500 K and a metallicity range from 0.5 dex down to −1.2 dex and study the behaviour of Teff and Fe/H on the spectral indices. Results. We find a tight relation between Teff and the 12CO(2−0) band with a dispersion of 95 K and between Teff and the 12CO(3−1) with a dispersion of 120 K. We do not find any dependence of these relations on the metallicity of the star, which makes them attractive for Galactic bulge studies. This relation is also not sensitive to the spectral resolution, which allows this relation to be applied in a more general way. We also find a correlation between the combination of the Na i, Ca i, and the 12CO band with the metallicity of the star. However, this relation is only valid for subsolar metallicities. Conclusions. We show that low-resolution spectra provide a powerful tool for obtaining effective temperatures of M giants. We show that this relation does not depend on the metallicity of the star within the investigated range and is also applicable to different spectral resolutions making this relation in general useful for deriving effective temperatures in high-extinction regions where photometric temperatures are not reliable.
Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease prone to widespread metastatic dissemination and characterized by a desmoplastic stroma that contributes to poor outcomes. Fibroblast ...activation protein (FAP)-expressing Cancer-Associated Fibroblasts (CAFs) are crucial components of the tumor stroma, influencing carcinogenesis, fibrosis, tumor growth, metastases, and treatment resistance. Non-invasive tools to profile CAF identity and function are essential for overcoming CAF-mediated therapy resistance, developing innovative targeted therapies, and improved patient outcomes. We present the design of a multicenter phase 2 study (clinicaltrials.gov identifier NCT05262855) of 68GaFAPI-46 PET to image FAP-expressing CAFs in resectable or borderline resectable PDAC.
We will enroll up to 60 adult treatment-naïve patients with confirmed PDAC. These patients will be eligible for curative surgical resection, either without prior treatment (Cohort 1) or after neoadjuvant therapy (NAT) (Cohort 2). A baseline PET scan will be conducted from the vertex to mid-thighs approximately 15 minutes after administering 5 mCi (±2) of 68GaFAPI-46 intravenously. Cohort 2 patients will undergo an additional PET after completing NAT but before surgery. Histopathology and FAP immunohistochemistry (IHC) of initial diagnostic biopsy and resected tumor samples will serve as the truth standards. Primary objective is to assess the sensitivity, specificity, and accuracy of 68GaFAPI-46 PET for detecting FAP-expressing CAFs. Secondary objectives will assess predictive values and safety profile validation. Exploratory objectives are comparison of diagnostic performance of 68GaFAPI-46 PET to standard-of-care imaging, and comparison of pre- versus post-NAT 68GaFAPI-46 PET in Cohort 2.
To facilitate the clinical translation of 68GaFAPI-46 in PDAC, the current study seeks to implement a coherent strategy to mitigate risks and increase the probability of meeting FDA requirements and stakeholder expectations. The findings from this study could potentially serve as a foundation for a New Drug Application to the FDA.
@ClinicalTrials.gov identifier NCT05262855.
Context.
The nuclear stellar disc (NSD) is, together with the nuclear star cluster (NSC) and the central massive black hole, one of the main components in the central parts of our Milky Way. However, ...until recently, only a few studies of the stellar content of the NSD have been obtained owing to extreme extinction and stellar crowding.
Aims.
We study the kinematics and global metallicities of the NSD based on the observations of K/M giant stars via a dedicated KMOS (VLT, ESO) spectroscopic survey.
Methods.
We traced radial velocities and metallicities, which were derived based on spectral indices (Na I and CO) along the NSD, and compared those with a Galactic bulge sample of APOGEE (DR16) and data from the NSC.
Results.
We find that the metallicity distribution function and the fraction of metal-rich and metal-poor stars in the NSD are different from the corresponding distributions and ratios of the NSC and the Galactic bulge. By tracing the velocity dispersion as a function of metallicity, we clearly see that the NSD is kinematically cool and that the velocity dispersion decreases with increasing metallicity contrary to the inner bulge sample of APOGEE (|
b
|< 4°). Using molecular gas tracers (H
2
CO, CO(4−3)) of the central molecular zone (CMZ), we find an astonishing agreement between the gas rotation and the rotation of the metal-rich population. This agreement indicates that the metal-rich stars could have formed from gas in the CMZ. On the other hand, the metal-poor stars show a much slower rotation profile with signs of counter-rotation, thereby indicating that these stars have a different origin.
Conclusions.
Coupling kinematics with global metallicities, our results demonstrate that the NSD is chemically and kinematically distinct with respect to the inner bulge, which indicates a different formation scenario.
Baade’s window and APOGEE Schultheis, M; Rojas-Arriagada, A; Perez, A E Garcia ...
Astronomy and astrophysics (Berlin),
04/2017, Volume:
600
Journal Article
Peer reviewed
Open access
Context. Baade's window (BW) is one of the most observed Galactic bulge fields in terms of chemical abundances. Owing to its low and homogeneous interstellar absorption it is considered the perfect ...calibration field for Galactic bulge studies. Aims. In the era of large spectroscopic surveys, calibration fields such as BW are necessary for cross calibrating the stellar parameters and individual abundances of the APOGEE survey. Methods. We use the APOGEE BW stars to derive the metallicity distribution function (MDF) and individual abundances for alpha- and iron-peak elements of the APOGEE ASPCAP pipeline (DR13), as well as the age distribution for stars in BW. Results. We determine the MDF of APOGEE stars in BW and find a remarkable agreement with that of the Gaia-ESO survey (GES). Both exhibit a clear bimodal distribution. We also find that the Mg-metallicity planes of the two surveys agree well, except for the metal-rich part (Fe/H > 0.1), where APOGEE finds systematically higher Mg abundances with respect to the GES. The ages based on the C/N ratio reveal a bimodal age distribution, with a major old population at ~ 10 Gyr, with a decreasing tail towards younger stars. A comparison of stellar parameters determined by APOGEE and those determined by other sources reveals detectable systematic offsets, in particular for spectroscopic surface gravity estimates. In general, we find a good agreement between individual abundances of O, Na, Mg, Al, Si, K, Ca, Cr, Mn, Co, and Ni from APOGEE with that of literature values. Conclusions. We have shown that in general APOGEE data show a good agreement in terms of MDF and individual chemical abundances with respect to literature works. Using the C/N ratio we found a significant fraction of young stars in BW.
The aims of our case-control study were (1) to develop an automated 3-dimensional (3D) Convolutional Neural Network (CNN) for detection of pancreatic ductal adenocarcinoma (PDA) on diagnostic ...computed tomography scans (CTs), (2) evaluate its generalizability on multi-institutional public data sets, (3) its utility as a potential screening tool using a simulated cohort with high pretest probability, and (4) its ability to detect visually occult preinvasive cancer on prediagnostic CTs.
A 3D-CNN classification system was trained using algorithmically generated bounding boxes and pancreatic masks on a curated data set of 696 portal phase diagnostic CTs with PDA and 1080 control images with a nonneoplastic pancreas. The model was evaluated on (1) an intramural hold-out test subset (409 CTs with PDA, 829 controls); (2) a simulated cohort with a case-control distribution that matched the risk of PDA in glycemically defined new-onset diabetes, and Enriching New-Onset Diabetes for Pancreatic Cancer score ≥3; (3) multi-institutional public data sets (194 CTs with PDA, 80 controls), and (4) a cohort of 100 prediagnostic CTs (i.e., CTs incidentally acquired 3-36 months before clinical diagnosis of PDA) without a focal mass, and 134 controls.
Of the CTs in the intramural test subset, 798 (64%) were from other hospitals. The model correctly classified 360 CTs (88%) with PDA and 783 control CTs (94%), with a mean accuracy 0.92 (95% CI, 0.91-0.94), area under the receiver operating characteristic (AUROC) curve of 0.97 (95% CI, 0.96-0.98), sensitivity of 0.88 (95% CI, 0.85-0.91), and specificity of 0.95 (95% CI, 0.93-0.96). Activation areas on heat maps overlapped with the tumor in 350 of 360 CTs (97%). Performance was high across tumor stages (sensitivity of 0.80, 0.87, 0.95, and 1.0 on T1 through T4 stages, respectively), comparable for hypodense vs isodense tumors (sensitivity: 0.90 vs 0.82), different age, sex, CT slice thicknesses, and vendors (all P > .05), and generalizable on both the simulated cohort (accuracy, 0.95 95% 0.94-0.95; AUROC curve, 0.97 95% CI, 0.94-0.99) and public data sets (accuracy, 0.86 95% CI, 0.82-0.90; AUROC curve, 0.90 95% CI, 0.86-0.95). Despite being exclusively trained on diagnostic CTs with larger tumors, the model could detect occult PDA on prediagnostic CTs (accuracy, 0.84 95% CI, 0.79-0.88; AUROC curve, 0.91 95% CI, 0.86-0.94; sensitivity, 0.75 95% CI, 0.67-0.84; and specificity, 0.90 95% CI, 0.85-0.95) at a median 475 days (range, 93-1082 days) before clinical diagnosis.
This automated artificial intelligence model trained on a large and diverse data set shows high accuracy and generalizable performance for detection of PDA on diagnostic CTs as well as for visually occult PDA on prediagnostic CTs. Prospective validation with blood-based biomarkers is warranted to assess the potential for early detection of sporadic PDA in high-risk individuals.
Due to the increase in pollution, the number of deaths caused by lung disease is rising rapidly. It is essential to predict the disease in earlier stages by means of high-level knowledge and ...acquaintance. Deep learning-based lung cancer prediction plays a vital role in assisting the medical practioners for diagnosing lung cancer in earlier stage. Computer-Aided diagnosis is considered to bring a boost to the field of medicine by tying it to automated systems. In this research paper, several models are experimented by using chest X-ray image or CT scan as an input to detect a particular disease. This research work is carried out to identify the best performing deep learning techniques for lung disease prediction. The performance of the method is evaluated using various performance metrics, such as precision, recall, accuracy and Jaccard index.
Purpose
To evaluate robustness of a radiomics-based support vector machine (SVM) model for detection of visually occult PDA on pre-diagnostic CTs by simulating common variations in image acquisition ...and radiomics workflow using image perturbation methods.
Methods
Eighteen algorithmically generated-perturbations, which simulated variations in image noise levels (
σ
, 2
σ
, 3
σ
, 5
σ
), image rotation both CT image and the corresponding pancreas segmentation mask by 45° and 90° in axial plane, voxel resampling (isotropic and anisotropic), gray-level discretization bin width (BW) 32 and 64), and pancreas segmentation (sequential erosions by 3, 4, 6, and 8 pixels and dilations by 3, 4, and 6 pixels from the boundary), were introduced to the original (unperturbed) test subset (
n
= 128; 45 pre-diagnostic CTs, 83 control CTs with normal pancreas). Radiomic features were extracted from pancreas masks of these additional test subsets, and the model's performance was compared vis-a-vis the unperturbed test subset.
Results
The model correctly classified 43 out of 45 pre-diagnostic CTs and 75 out of 83 control CTs in the unperturbed test subset, achieving 92.2% accuracy and 0.98 AUC. Model's performance was unaffected by a three-fold increase in noise level except for sensitivity declining to 80% at 3
σ
(
p
= 0.02). Performance remained comparable vis-a-vis the unperturbed test subset despite variations in image rotation (
p
= 0.99), voxel resampling (
p
= 0.25–0.31), change in gray-level BW to 32 (
p
= 0.31–0.99), and erosions/dilations up to 4 pixels from the pancreas boundary (
p
= 0.12–0.34).
Conclusion
The model’s high performance for detection of visually occult PDA was robust within a broad range of clinically relevant variations in image acquisition and radiomics workflow.
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