Simulation of inference test performance for minimum inhibitory concentration censored data

The estimation of the minimum inhibitory concentration is usually performed by a method of serial dilutions by a factor of 2, introducing the overestimation of antimicrobial efficacy, quantified by a simulation model that shows that the variability of the bias is higher for the standard deviation, being dependent on the metric distance to the values of the concentrations used. We use a methodological approach through modeling and simulation for the measurement error of physical variables with censored information, proposing a new inference method based on the calculation of the exact probability for the set of possible samples from nmeasurements that allows quantifying the p-value in one or two independent sample tests for the comparison of censored data means. Tests based on exact probability methods offer a reasonable solution for small sample sizes, with statistical power varying according to the hypothesis evaluated, providing insight into the limitations of censored data analysis and providing a tool for decision making in the diagnosis of antimicrobial efficacy.

Exact site-percolation probability on the square lattice

We present an algorithm to compute the exact probability $R_{n}(p)$ for a site percolation cluster to span an $n\times n$ square lattice at occupancy $p$. The algorithm has time and space complexity $O(\lambda^n)$ with $\lambda \approx 2.6$. It allows us to compute $R_{n}(p)$ up to $n=24$. We use the data to compute estimates for the percolation threshold $p_c$ that are several orders of magnitude more precise than estimates based on Monte-Carlo simulations.

Transient adverse events after REGN-CoV2 administration for mild COVID-19 patients and their potential predictive factors: a single center analysis

Background The efficacy of REGN-COV2 in preventing severe COVID-19 has been proven, and its use in outpatient and home settings is expanding. Adverse events such as fever and decreased oxygen saturation, which are often seen after REGN-COV2 administration, are generally transient, but predicting these events is useful in developing a monitoring plan for patients. Methods We performed a retrospective analysis of 76 patients who received REGN-CoV2 between August and September 2021. The clinical course of the patients' fever and oxygen administration was collected from their medical records, and the patients were divided into two groups based on the presence or absence of these adverse events, and the underlying pathology and blood sampling data were compared. Parameters that showed significant differences were further examined by Fisher's exact probability test to see if the use of appropriate thresholds would significantly correlate with the occurrence of adverse events. Findings Of the 76 patients, 47 had fever of 38.5°C or higher within 24 hours after administration, and 27 of these patients had a body temperature of 37.5°C or lower before administration. Oxygen was required in 14 cases, 5 of which required oxygen more than 24 hours after administration of REGN-COV2, and additional treatment such as dexamethasone was given as a transition to moderate disease. Among the parameters analyzed, except for fever before administration, lymphocyte count and IFNλ3 showed significant differences between the fever and non-fever groups. There was also a significant difference in ferritin and CRP between the oxygen required and non-required groups. This was also the case in the comparison excluding patients who had fever before administration. In addition to IFNλ3, ferritin, and CRP, there was a significant difference in LDH between the group that required additional treatment and the group that did not. Fisher's exact test was used to examine the prediction threshold for fever and non-fever groups. The sensitivity and specificity were 55% and 79%, respectively with odds ratio 4.746 (95% CI: 1.666 to 14.12) when lymphocytes counts <950/μL was used (p=0.004). Similarly, when IFNλ3>5.0 was used as the cutoff, sensitivity 72%, specificity 76%, odds ratio 8.220 (2.857 to 22.22; p<0.0001). Interpretations Fever and decreased oxygen saturation after administration of REGN-Cov2 were found to correlate with the severity factors of COVID-19 itself. Evaluation of these items at the time of administration is useful not only for predicting the severity of illness but also for the development of adverse events in patients.

Pigmentary Complications after Non-Medical Male Circumcision

Objectives: A wide spectrum of complications are reported after male circumcision (MC), the non-aesthetic complications are well known, but the pigmentary complications scale are not reported precisely. Methods: This is a prospective cohort study of 550 circumcised boys, who were examined and appropriately investigated for the incidence of pigmentary complications after circumcision. Most diagnoses were clinically, but dermoscopy was done for 17 case and a skin biopsy for 14 cases. Patients with personal or family history of vitiligo, or congenital nevi were excluded. Available hospital records details and parents' statements were revised. The main outcome measures are the incidence of different pigmentary complications and circumcision details; data were analyzed by Fisher’s exact probability test, two tailed, and non-parametric tests including the Mann-Whitney U test. Results: 69 cases had 72 confirmed pigmentary complications discovered at 2 to 36 months after commencement of circumcision (mean 18). 48 cases had pigmentary complications directly related to MC, 11 cases were probably related and 10 unrelated to MC. The most common lesion is the circular hyperpigmented scar (29 cases); liner hyperpigmented scar in 13, spotted exogenous melanosis in 18 cases, melanocytic nevi (7), hypopigmentation diagnosed in 3 cases, but kissing nevus is the rarest finding (2). Topical corticosteroid was tried in 15 cases, surgical excision of pigmented scar were done for 19 cases, local laser used for 4 resistant cases and reassurance with follow up for the rest. Conclusion: Pigmentary complications after male circumcision are not rare and its management is challenging.

Metabolomics Based Mechanism Exploration of Pulmonary Arterial Hypertension pathogenesis: Novel Lessons from Explanted Lungs

Background: Metabolic pathways have been shown to participate in the pathogenesis of pulmonary arterial hypertension (PAH). We investigated the metabolic profile shifts to reveal molecular mechanisms underlying PAH. Methods: Explanted human lung tissues from 18 PAH patients were collected. The lung tissues far from the tumor from 16 lung cancer patients were taken as controls. Lung tissues were analyzed by LC-MS/MS based non-target metabolomics method. Pathway analysis was performed with KEGG database and MetaboAnalyst 5.0. Statistical analysis including partial least squares discriminant analysis (PLS-DA), Student’s t-test, Pearson’s correlation, Chi-square test and Fisher’s exact probability test were used. COX survival analysis model was applied to evaluate the predictive value of metabolites on prognosis. Protein expression levels were detected by Western blotting in human PAH lung tissues, rat monocrotaline-PAH lungs and hypoxia exposed human pulmonary artery smooth muscle cells (HPASMCs) to study the molecular mechanisms.Results: Significant differences in metabolites and metabolic pathways were identified among PAH subgroups and control tissues. Spermine levels were positively correlated with the patients' cardiac outputs (COs). Levels of (2e)-2,5-dichloro-4-oxo-2-hexenedioic acid were positively correlated with the patient's serum creatinine (Scr) levels. Patients with higher levels of thymine had a better prognosis. Moreover, 7 differential metabolites were associated with AKT pathway. AKT pathway inactivation was confirmed in human and rat PAH lungs and hypoxia exposed HPASMCs.Conclusions: Our findings provide the first metabolomics evidence for PAH pathogenesis by human lungs and may contribute to the improvement of therapeutic strategy.

A Distributionally Robust Chance-Constrained Unit Commitment with N-1 Security and Renewable Generation

With the increasing penetration of renewable energy generation, one of the major challenges is the problem of how to express the stochastic process of wind power and photovoltaic output as the exact probability density and distribution, in order to improve the security and accuracy of unit commitment results, a distributed robust security-constrained optimization model based on moment uncertainty is proposed, in which the uncertainty of wind and photovoltaic power is captured by two uncertain sets of first- and second-order moments, respectively. The two sets contain the probability distribution of the forecast error of the wind and photovoltaic power, and in the model, the energy storage is considered. In order to solve the model effectively, firstly, based on the traditional chance-constrained second-order cone transformation, according to the first- and second-order moments polyhedron expression of the distribution set, a cutting plane method is proposed to solve the distributed robust chance constraints. Secondly, the modified IEEE-RTS 24 bus system is selected to establish a simulation example, an improved generalized Benders decomposition algorithm is developed to solve the model to optimality. The results show that the unit commitment results with different emphasis on economy and security can be obtained by setting different conservative coefficients and confidence levels and, then, provide a reasonable decision-making basis for dispatching operation.

Histopathological validation of safe margin for nephron-sparing surgery based on individual tumor growth pattern

Background To evaluate the clinicopathologic value of morphological growth patterns of small renal cell carcinoma (sRCC) and determine the actual demand for taking a rim of healthy parenchyma to avoid positive SM. Methods Data was collected from 560 sRCC patients who underwent laparoscopic surgeries from May 2010 to October 2017. One hundred forty-nine cases received nephron-sparing surgery (NSS) and others received radical nephrectomy (RN). All specimens were analyzed separately by two uropathologists, and three morphological growth patterns were identified. The presence of pseudocapsule (PC), surgical margins (SM), and other routine variables were recorded. The relationship between growth patterns and included variables was measured by the χ2 test and Fisher’s exact probability test. Survival outcomes were evaluated by Kaplan-Meier method and the log-rank test. Results The median age of patients was 63.2 years old and the mean tumor diameter was 3.0 cm. Four hundred eighty (85.7%) cases were clear cell RCC and 541 (96.6%) cases were at the pT1a stage. Peritumoral PC was detected in 512 (92.5%) specimens, and the ratio of tumor invasion in PC in infiltration pattern increased obviously than that of the other growth patterns. Similarly, the pT stage was significantly correlated with the infiltration pattern as well. One hundred forty-nine patients underwent NSS and 3 (2.0%) of them showed positive SM after operation. Statistical differences of the 5-year overall survival (OS) and the cancer-specific survival (CSS) existed between different morphological growth patterns, PC status, and pT stages. Conclusions Morphological growth patterns of sRCC might be used as a potential biomarker to help operate NSS to avoid the risk of positive SM. How to distinguish different morphological growth patterns before operation and the effectiveness of the growth pattern as a novel proposed parameter to direct NSS in sRCC patients deserves further exploration.

Upregulated Serum Granulysin Levels in Women With Antiphospholipid Syndrome-Associated Recurrent Miscarriages Are Downregulated by Heparin Treatment

Background Antiphospholipid antibody syndrome is the major cause of recurrent pregnancy loss (RPL) and associated with inflammation. Granulysin is a cytotoxic protein secreted by cytotoxic T cells, natural killer cells, and natural killer T cells that is present in abundance in the decidua. It activates innate and cellular immunity simultaneously, and also induces miscarriage. As a treatment, heparin is widely used for the patients with RPL, and exhibits the antithrombotic and anti-inflammatory activities, and angiogenesis. Methods We hypothesized that granulysin is an important factor in inducing miscarriage. Here, we evaluated the changes of serum granulysin level before and 1 week after the commencement of heparin treatment for the patients with RPL. Results The serum granulysin levels before heparin treatment were significantly higher in women who tested positive for one or more types of antiphospholipid antibody (2.75 ± 1.03 vs. 2.44 ± 0.69; P = 0.0341 by Welch’s t-test), particularly anti-phosphatidylethanolamine antibodies (IgG: 2.98 ± 1.09 vs. 2.51 ± 0.86; P = 0.0013, IgM: 2.85 ± 1.09 vs. 2.47 ± 0.77; P = 0.0024 by Welch’s t-test). After heparin treatment for 1 week, the serum granulysin levels were reduced significantly (P = 0.0017 by paired t-test). The miscarriage rate was significantly higher in women whose serum granulysin levels were not reduced by heparin treatment (P = 0.0086 by Fisher’s exact probability test). Conclusions These results suggest that heparin may reduce the incidence of miscarriages by suppressing the serum granulysin levels.

Exact Probability Landscapes of Stochastic Phenotype Switching in Feed-Forward Loops: Phase Diagrams of Multimodality

Feed-forward loops (FFLs) are among the most ubiquitously found motifs of reaction networks in nature. However, little is known about their stochastic behavior and the variety of network phenotypes they can exhibit. In this study, we provide full characterizations of the properties of stochastic multimodality of FFLs, and how switching between different network phenotypes are controlled. We have computed the exact steady-state probability landscapes of all eight types of coherent and incoherent FFLs using the finite-butter Accurate Chemical Master Equation (ACME) algorithm, and quantified the exact topological features of their high-dimensional probability landscapes using persistent homology. Through analysis of the degree of multimodality for each of a set of 10,812 probability landscapes, where each landscape resides over 105–106 microstates, we have constructed comprehensive phase diagrams of all relevant behavior of FFL multimodality over broad ranges of input and regulation intensities, as well as different regimes of promoter binding dynamics. In addition, we have quantified the topological sensitivity of the multimodality of the landscapes to regulation intensities. Our results show that with slow binding and unbinding dynamics of transcription factor to promoter, FFLs exhibit strong stochastic behavior that is very different from what would be inferred from deterministic models. In addition, input intensity play major roles in the phenotypes of FFLs: At weak input intensity, FFL exhibit monomodality, but strong input intensity may result in up to 6 stable phenotypes. Furthermore, we found that gene duplication can enlarge stable regions of specific multimodalities and enrich the phenotypic diversity of FFL networks, providing means for cells toward better adaptation to changing environment. Our results are directly applicable to analysis of behavior of FFLs in biological processes such as stem cell differentiation and for design of synthetic networks when certain phenotypic behavior is desired.

A Logical Model for Predicting Minority Representation: Application to Redistricting and Voting Rights Cases

Understanding when and why minority candidates emerge and win in particular districts entails critical implications for redistricting and the Voting Rights Act. I introduce a quantitatively predictive logical model of minority candidate emergence and electoral success—a mathematical formula based on deductive logic that can logically explain and accurately predict the exact probability at which minority candidates run for office and win in given districts. I show that the logical model can predict about 90% of minority candidate emergence and 95% of electoral success by leveraging unique data of mayoral elections in Louisiana from 1986 to 2016 and state legislative general elections in 36 states in 2012 and 2014. I demonstrate that the logical model can be used to answer many important questions about minority representation in redistricting and voting rights cases. All applications of the model can be easily implemented via an open-source software logical.