Glaucoma Diagnostic Performance of Macular Ganglion Cell Complex Thickness Using Regular and Long Axial Length Normative Databases

The risks of misdiagnosing a healthy individual as glaucomatous or vice versa may be high in a population with a large majority of highly myopic individuals, due to considerable morphologic variability in high myopic fundus. This study aims to compare the diagnostic ability of the regular and long axial length databases in the RS-3000 Advance SD-OCT (Nidek) device to correctly diagnose glaucoma with high myopia. Patients with high myopia (axial length ≥ 26.0 mm) in Chang Gung Memorial Hospital, Taiwan between 2015 and 2020 were included. Glaucoma was diagnosed based on glaucomatous discs, visual field defects and corresponding retinal nerve fiber layer defects. The sensitivity, specificity, diagnostic accuracy and likelihood ratios of diagnosing glaucoma via mGCC thickness in both superior/inferior and GChart mapping using the regular and long axial length normative databases. The specificity and diagnostic accuracy of mGCC thickness for distinguishing glaucomatous eyes from nonglaucomatous eyes among highly myopic eyes were significantly improved using the long axial length database (p=0.046). There were also significant proportion changes in S/I mapping as well as GChart mapping (37.3% and 48.0%, respectively; p<0.01) from abnormal to normal in the myopic normal eye group when using the long axial length normative database. The study revealed that clinicians could utilize a long axial length database to effectively decrease the number of false-positive diagnoses or to correctly identify highly myopic normal eyes misdiagnosed as glaucomatous eyes.

Osteopontin as a Tumor Marker in Ovarian Cancer

Introduction: Ovarian cancer is associated with high morbidity and mortality. This is due to the nonspecific symptoms and no effective screening methods. Currently CA 125 is used as a tumor biomarker for the diagnosis of ovarian cancer, but it has its own limitations. So, there is need for other tumor biomarkers for the diagnosis of ovarian cancer. To determine the diagnostic test characteristics of plasma osteopontin (OPN) in detecting ovarian malignancy and comparing its performance with carbohydrate antigen-125 (CA 125). Methods: This is a prospective cross-sectional diagnostic test evaluation. Women with adnexal mass detected by clinical or radiological examination were enrolled as suspected cases. Women who presented with other gynecological conditions were enrolled as controls. OPN and CA 125 levels were measured in all enrolled subjects. Results: Among 106 women enrolled, 26 were ovarian cancer, 31 had benign ovarian masses and 49 were controls. Median plasma CA 125 levels were higher in subjects with ovarian cancer (298 U/ml; IQR 84-1082 U/ml vs. 37.5U/ml; IQR 17.6-82.9U/ml; P<0.001).CA 125 sensitivity, specificity, positive and negative likelihood ratios were 88.5%, 61.3%,2.10 and 0.19 respectively. Median plasma OPN levels were higher in subjects with ovarian cancer (63.1 ng/ml; IQR 39.3-137 ng/ml vs. 27ng/ml; IQR 20-52ng/ml; P=0.001). Sensitivity, specificity, positive and negative likelihood ratios of OPN were 50%,87%,2.58 and 0.62, respectively. Conclusion: OPN levels were higher in ovarian cancer than in the benign ovarian mass and had better specificity than CA125. OPN can better differentiate between benign and malignant ovarian mass as compared to CA125.

Learning to discover: expressive Gaussian mixture models for multi-dimensional simulation and parameter inference in the physical sciences

We show that density models describing multiple observables with (i) hard boundaries and (ii) dependence on external parameters may be created using an auto-regressive Gaussian mixture model. The model is designed to capture how observable spectra are deformed by hypothesis variations, and is made more expressive by projecting data onto a configurable latent space. It may be used as a statistical model for scientific discovery in interpreting experimental observations, for example when constraining the parameters of a physical model or tuning simulation parameters according to calibration data. The model may also be sampled for use within a Monte Carlo simulation chain, or used to estimate likelihood ratios for event classification. The method is demonstrated on simulated high-energy particle physics data considering the anomalous electroweak production of a $Z$ boson in association with a dijet system at the Large Hadron Collider, and the accuracy of inference is tested using a realistic toy example. The developed methods are domain agnostic; they may be used within any field to perform simulation or inference where a dataset consisting of many real-valued observables has conditional dependence on external parameters.

Combination of extramural venous invasion and lateral lymph node size detected with magnetic resonance imaging is a reliable biomarker for lateral lymph node metastasis in patients with rectal cancer

Purpose Pathological extramural venous invasion (EMVI) is defined as the active invasion of malignant cells into veins beyond the muscularis propria in colorectal cancer. It is associated with poor prognosis and increases the risk of disease recurrence. Specific findings on MRI (termed MRI-EMVI) are reportedly associated with pathological EMVI. In this study, we aimed to identify risk factors for lateral lymph node (LLN) metastasis related to rectal cancer and to evaluate whether MRI-EMVI could be a new and useful imaging biomarker to help LLN metastasis diagnosis besides LLN size. Methods We investigated 67 patients who underwent rectal resection and LLN dissection for rectal cancer. We evaluated MRI-EMVI grading score and examined the relationship between MRI-EMVI and LLN metastasis. Results Pathological LLN metastasis was detected in 18 cases (26.9%), and MRI-EMVI was observed in 32 cases (47.8%). Patients were divided into two cohorts, according to LLN metastasis. Multivariate analyses demonstrated that higher risk of LLN metastasis was significantly associated with MRI-EMVI (P = 0.0112) and a short lateral lymph node axis (≥ 5 mm) (P = 0.0002). The positive likelihood ratios of MRI-EMVI alone, LLN size alone, and the combination of both factors were 2.12, 4.84, and 16.33, respectively. Patients negative for both showed better 2-year relapse-free survival compared to other patients (84.4% vs. 62.1%, P = 0.0374). Conclusions MRI-EMVI was a useful imaging biomarker for identifying LLN metastasis in patients with rectal cancer. The combination of MRI-EMVI and LLN size can improve diagnostic accuracy.

Wild Rabbit Exposure to Leishmania infantum, Toxoplasma gondii, Anaplasma phagocytophilum and Babesia caballi Evidenced by Serum and Aqueous Humor Antibody Detection

Wild rabbits (Oryctolagus cuniculus) can be important sentinel species for the presence of zoonotic pathogens. Therefore, we collected blood samples from wild rabbits harvested by hunters during the hunting season 2019–2020 on the island of Lemnos, to determine exposure of wild rabbits to the zoonotic pathogens Leishmania infantum, Toxoplasma gondii, Anaplasma phagocytophilum and Babesia caballi, as well as aqueous humor to assess its diagnostic performance in terms of sensitivity, specificity, positive and negative likelihood ratios. Antibodies against these pathogens were detected by Indirect Immunofluorescence Antibody (IFA) assay. Out of the 72 wild rabbits included in the study, 4.2%, 5.5%, 18% and 9.7% were seropositive to L. infantum, T. gondii, A. phagocytophilum and B. caballi, respectively. Although less frequently, antibodies were also detected in aqueous humor of wild rabbits. The antibody detection in aqueous humor presented 100% specificity but decreased sensitivity compared to serum suggesting that aqueous humor could be successfully used in epidemiological studies to confirm exposure at the population level but has little diagnostic value at the individual level. This is the first report on the seropositivity of wild rabbits to A. phagocytophilum and B. caballi and the detection of antibodies against A. phagocytopylum, L. infantum, T. gondii and B. caballi in the aqueous humor.

Fair Cake Division Under Monotone Likelihood Ratios

This work develops algorithmic results for the classic cake-cutting problem in which a divisible, heterogeneous resource (modeled as a cake) needs to be partitioned among agents with distinct preferences. We focus on a standard formulation of cake cutting wherein each agent must receive a contiguous piece of the cake. Although multiple hardness results exist in this setup for finding fair/efficient cake divisions, we show that, if the value densities of the agents satisfy the monotone likelihood ratio property (MLRP), then strong algorithmic results hold for various notions of fairness and economic efficiency. Addressing cake-cutting instances with MLRP, first we develop an algorithm that finds cake divisions (with connected pieces) that are envy free, up to an arbitrary precision. The time complexity of our algorithm is polynomial in the number of agents and the bit complexity of an underlying Lipschitz constant. We obtain similar positive results for maximizing social, egalitarian, and Nash social welfare. Many distribution families bear MLRP. In particular, this property holds if all the value densities belong to any one of the following families: Gaussian (with the same variance), linear, Poisson, and exponential distributions, linear translations of any log-concave function. Hence, through MLRP, the current work obtains novel cake-cutting algorithms for multiple distribution families.

The FORCE Panel: An All-in-One SNP Marker Set for Confirming Investigative Genetic Genealogy Leads and for General Forensic Applications

The FORensic Capture Enrichment (FORCE) panel is an all-in-one SNP panel for forensic applications. This panel of 5422 markers encompasses common, forensically relevant SNPs (identity, ancestry, phenotype, X- and Y-chromosomal SNPs), a novel set of 3931 autosomal SNPs for extended kinship analysis, and no clinically relevant/disease markers. The FORCE panel was developed as a custom hybridization capture assay utilizing ~20,000 baits to target the selected SNPs. Five non-probative, previously identified World War II (WWII) cases were used to assess the kinship panel. Each case included one bone sample and associated family reference DNA samples. Additionally, seven reference quality samples, two 200-year-old bone samples, and four control DNAs were processed for kit performance and concordance assessments. SNP recovery after capture resulted in a mean of ~99% SNPs exceeding 10X coverage for reference and control samples, and 44.4% SNPs for bone samples. The WWII case results showed that the FORCE panel could predict first to fifth degree relationships with strong statistical support (likelihood ratios over 10,000 and posterior probabilities over 99.99%). To conclude, SNPs will be important for further advances in forensic DNA analysis. The FORCE panel shows promising results and demonstrates the utility of a 5000 SNP panel for forensic applications.

Cognitive screening instruments for dementia: comparing metrics of test limitation

ABSTRACT Cognitive screening instruments (CSIs) for dementia and mild cognitive impairment are usually characterized in terms of measures of discrimination such as sensitivity, specificity, and likelihood ratios, but these CSIs also have limitations. Objective: The aim of this study was to calculate various measures of test limitation for commonly used CSIs, namely, misclassification rate (MR), net harm/net benefit ratio (H/B), and the likelihood to be diagnosed or misdiagnosed (LDM). Methods: Data from several previously reported pragmatic test accuracy studies of CSIs (Mini-Mental State Examination, the Montreal Cognitive Assessment, Mini-Addenbrooke’s Cognitive Examination, Six-item Cognitive Impairment Test, informant Ascertain Dementia 8, Test Your Memory test, and Free-Cog) undertaken in a single clinic were reanalyzed to calculate and compare MR, H/B, and the LDM for each test. Results: Some CSIs with very high sensitivity but low specificity for dementia fared poorly on measures of limitation, with high MRs, low H/B, and low LDM; some had likelihoods favoring misdiagnosis over diagnosis. Tests with a better balance of sensitivity and specificity fared better on measures of limitation. Conclusions: When deciding which CSI to administer, measures of test limitation as well as measures of test discrimination should be considered. Identification of CSIs with high MR, low H/B, and low LDM, may have implications for their use in clinical practice.