Flow Measurement: An Inverse Problem Formulation

This paper proposes a new mathematical formulation for flow measurement based on the inverse source problem for wave equations with partial boundary measurement. Inspired by the design of acoustic Doppler current profilers (ADCPs), we formulate an inverse source problem that can recover the flow field from the observation data on a few boundary receivers. To our knowledge, this is the first mathematical model of flow measurement using partial differential equations. This model is proved well-posed, and the corresponding algorithm is derived to compute the velocity field efficiently. Extensive numerical simulations are performed to demonstrate the accuracy and robustness of our model. Our formulation is capable of simulating a variety of practical measurement scenarios

Traceability of Water Pollution: An Inversion Scheme Via Dynamic Complex Geometrical Optics Solutions

We investigate the identification of the time-dependent source term in the diffusion equation using boundary measurements. This facilitates tracing back the origins of environmental pollutants. Employing the concept of dynamic complex geometrical optics (CGO) solutions, a variational formulation of the inverse source problem is analyzed, leading to a proof of uniqueness result. Our proposed two-step reconstruction algorithm first determines the point source locations and subsequently reconstructs the Fourier components of the emission concentration functions. Numerical experiments on simulated data are conducted. The results demonstrate that the proposed two-step reconstruction algorithm can reliably reconstruct multiple point sources and accurately reconstruct the emission concentration functions. Additionally, by partitioning the algorithm into online and offline computations, and concentrating computational demand offline, real-time pollutant traceability becomes feasible. This method, applicable in various fields - especially those related to water pollution, can identify the source of a contaminant in the environment, thus serving as a valuable tool in environmental protection

Identification and Characterization of Key Chemical Constituents in Processed Gastrodia elata Using UHPLC-MS/MS and Chemometric Methods

© The Author(s) 2019. Background. Obesity is a major medical issue nationally, with rates continually increasing. In obese patients, minimal data exist for appropriate dosing of acyclovir to decrease the rates of nephrotoxicity. The purpose of this study was to determine the prevalence of and risk factors associated with acyclovir-induced nephrotoxicity. Methods. A retrospective case-control of patients who received intravenous acyclovir for \u3e48 hours at University of Mississippi Medical Center over a 4-year period were evaluated to elucidate the prevalence of acyclovir-induced nephrotoxicity. Additionally, risk factors for the development of nephrotoxicity, including the effect of obesity and dosing strategy, were assessed. Results. One hundred fifteen patients were included in the study. A total of 24 (21%) patients developed nephrotoxicity after acyclovir exposure and were in the Risk (9.6%), Injury (4.3%), and Failure (7%) categories, defined by the RIFLE criteria. Neither acyclovir dosage, fluid status, nor baseline characteristics, other than obesity, varied between those who developed nephrotoxicity vs those who did not. Independent predictors of nephrotoxicity were obesity (odds ratio [OR], 3.2; 95% confidence interval [CI], 1.19-8.67) and receipt of vancomycin (OR, 4.73; 95% CI, 1.57-14.25). No differences in vancomycin dosing or concentrations were observed between the patients who developed nephrotoxicity and those who did not. Conclusions. In this study, nephrotoxicity occurred in 21% of patients receiving acyclovir. Concomitant vancomycin receipt and obesity led to higher rates of toxicity. Efforts should be made to target obese patients on acyclovir plus vancomycin and discontinue therapy in patients not warranting antiviral coverage to minimize chances of toxicity

Effects of stellate ganglion block on perimenopausal hot flashes: a randomized controlled trial

BackgroundHot flashes are common symptoms afflicting perimenopausal women. A stellate ganglion block (SGB) is believed to be an effective treatment for hot flashes; however, more evidence is needed to evaluate its safety and efficacy in relieving perimenopausal hot flashes.ObjectiveTo investigate the efficacy and safety of SGB for the treatment of perimenopausal hot flashes.MethodsA randomized controlled trial was conducted at Shanxi Bethune Hospital. Forty perimenopausal women with hot flashes were recruited from April 2022 to November 2022 and randomly assigned to receive either 6 consecutive SGB treatments or 6 consecutive saline placebo treatments. The primary outcome was the change in hot flash symptom score from baseline to 12 weeks after treatment. The secondary outcomes were the change in hot flash symptom score from baseline to 12 weeks after treatment and the post-treatment Kupperman Index (KI) and Pittsburgh Sleep Quality Index (PSQI) scores.ResultsOf the 40 randomized subjects, 35 completed the study. All the variables were significantly improved. During 12 weeks of follow-up, the hot flash scores, Kupperman Menopause Scale scores, and Pittsburgh Sleep Quality Scale scores decreased significantly. Two subjects in the SGB treatment group experienced transient hoarseness, and the incidence of related adverse events was 10%. No related adverse events occurred in the control group.ConclusionCompared to the control treatment, SGB treatment was a safe and effective nonhormone replacement therapy that significantly relieved perimenopausal hot flashes and effectively improved sleep quality. Additional studies are needed to assess the long-term efficacy of this therapy

Longitude Variation of the microRNA-497/FGF-23 Axis during Treatment and Its Linkage with Neoadjuvant/Adjuvant Trastuzumab-Induced Cardiotoxicity in HER2-Positive Breast Cancer Patients

PurposeMicroRNA-497 (miR-497) is previously reported to target fibroblast growth factor 23 (FGF-23) and regulates cardiac injury, while their value in predicting drug-induced cardiotoxicity is not reported. Thus, the current study aimed to investigate the correlation of miR-497/FGF-23 with neoadjuvant/adjuvant trastuzumab-induced cardiotoxicity in human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients.MethodsA total of 97 HER2-positive surgical breast cancer patients who received neoadjuvant/adjuvant trastuzumab contained regimens were enrolled; then, their peripheral blood mononuclear cells (PBMC) and serum were collected at baseline, after neoadjuvant treatment, at 3 months (M3), 6 months (M6), 9 months (M9), and 12 months (M12) after surgery. The PBMC was used for miR-497 measurements, and the serum was used for FGF-23 measurements. The cardiotoxicity events and incidence were recorded.ResultsA total of 24 (24.7%) patients occurred cardiotoxicity during the treatment period. MiR-497 decreased from baseline (median: 0.955) to M12 after surgery (median: 0.602) (p < 0.001), while FGF-23 increased from baseline (median: 0.390 ng/mL) to M12 after surgery (median: 0.566 ng/mL) (p < 0.001); besides, the miR-497/FGF-23 axis greatly reduced from baseline (median: 2.545) to M12 after surgery (median: 1.222) (p < 0.001). At most time points, miR-497 was negatively related to FGF-23 (all p < 0.05). Notably, the miR-497/FGF-23 axis at all time points (including baseline, postneoadjuvant treatment, M3, M6, M9, and M12) was related to a lower risk of cardiotoxicity (all p < 0.05). Furthermore, the miR-497/FGF-23 axis was also positively correlated with the left ventricular ejection fraction (LVEF) at all time points (all p < 0.01).ConclusionThe MiR-497/FGF-23 axis serves as a potential indicator predicting trastuzumab-induced cardiotoxicity in HER2-positive breast cancer patients

Large–scale genetic analysis and biological traits of two SigB factors in Listeria monocytogenes: lineage correlations and differential functions

IntroductionListeria monocytogenes is a globally distributed bacterium that exhibits genetic diversity and trait heterogeneity. The alternative sigma factor SigB serves as a crucial transcriptional regulator essential for responding to environmental stress conditions and facilitating host infection.MethodWe employed a comprehensive genetic analysis of sigB in a dataset comprising 46,921 L. monocytogenes genomes. The functional attributes of SigB were evaluated by phenotypic experiments.ResultsOur study revealed the presence of two predominant SigB factors (SigBT1 and SigBT2) in L. monocytogenes, with a robust correlation between SigBT1 and lineages I and III, as well as SigBT2 and lineage II. Furthermore, SigBT1 exhibits superior performance in promoting cellular invasion, cytotoxicity and enhancing biofilm formation and cold tolerance abilities under minimally defined media conditions compared to SigBT2.DiscussionThe functional characteristics of SigBT1 suggest a potential association with the epidemiology of lineages I and III strains in both human hosts and the natural environment. Our findings highlight the important role of distinct SigB factors in influencing the biological traits of L. monocytogenes of different lineages, thus highlighting its distinct pathogenic and adaptive attributes

Predicting pneumonia during hospitalization in flail chest patients using machine learning approaches

ObjectivePneumonia is a common pulmonary complication of flail chest, causing high morbidity and mortality rates in affected patients. The existing methods for identifying pneumonia have low accuracy, and their use may delay antimicrobial therapy. However, machine learning can be combined with electronic medical record systems to identify information and assist in quick clinical decision-making. Our study aimed to develop a novel machine-learning model to predict pneumonia risk in flail chest patients.MethodsFrom January 2011 to December 2021, the electronic medical records of 169 adult patients with flail chest at a tertiary teaching hospital in an urban level I Trauma Centre in Chongqing were retrospectively analysed. Then, the patients were randomly divided into training and test sets at a ratio of 7:3. Using the Fisher score, the best subset of variables was chosen. The performance of the seven models was evaluated by computing the area under the receiver operating characteristic curve (AUC). The output of the XGBoost model was shown using the Shapley Additive exPlanation (SHAP) method.ResultsOf 802 multiple rib fracture patients, 169 flail chest patients were eventually included, and 86 (50.80%) were diagnosed with pneumonia. The XGBoost model performed the best among all seven machine-learning models. The AUC of the XGBoost model was 0.895 (sensitivity: 84.3%; specificity: 80.0%).Pneumonia in flail chest patients was associated with several features: systolic blood pressure, pH value, blood transfusion, and ISS.ConclusionOur study demonstrated that the XGBoost model with 32 variables had high reliability in assessing risk indicators of pneumonia in flail chest patients. The SHAP method can identify vital pneumonia risk factors, making the XGBoost model's output clinically meaningful

Chromosome-level reference genome assembly provides insights into the evolution of Pennisetum alopecuroides

Pennisetum alopecuroides is an important forage grass resource, which plays a vital role in ecological environment improvement. Therefore, the acquisition of P. alopecuroides genome resources is conducive to the study of the adaptability of Pennisetum species in ecological remediation and forage breeding development. Here we assembled a P. alopecuroides cv. 'Liqiu' genome at the chromosome level with a size of approximately 845.71 Mb, contig N50 of 84.83Mb, and genome integrity of 99.13% as assessed by CEGMA. A total of 833.41-Mb sequences were mounted on nine chromosomes by Hi-C technology. In total, 60.66% of the repetitive sequences and 34,312 genes were predicted. The genomic evolution analysis showed that P. alopecuroides cv. 'Liqiu' was isolated from Setaria 7.53–13.80 million years ago and from Cenchrus 5.33–8.99 million years ago, respectively. The whole-genome event analysis showed that P. alopecuroides cv. 'Liqiu' underwent two whole-genome duplication (WGD) events in the evolution process, and the duplication events occurred at a similar time to that of Oryza sativa and Setaria viridis. The completion of the genome sequencing of P. alopecuroides cv. 'Liqiu' provides data support for mining high-quality genetic resources of P. alopecuroides and provides a theoretical basis for the origin and evolutionary characteristics of Pennisetum

A Deep Learning Model for Three-Dimensional Nystagmus Detection and Its Preliminary Application

Symptoms of vertigo are frequently reported and are usually accompanied by eye-movements called nystagmus. In this article, we designed a three-dimensional nystagmus recognition model and a benign paroxysmal positional vertigo automatic diagnosis system based on deep neural network architectures (Chinese Clinical Trials Registry ChiCTR-IOR-17010506). An object detection model was constructed to track the movement of the pupil centre. Convolutional neural network-based models were trained to detect nystagmus patterns in three dimensions. Our nystagmus detection models obtained high areas under the curve; 0.982 in horizontal tests, 0.893 in vertical tests, and 0.957 in torsional tests. Moreover, our automatic benign paroxysmal positional vertigo diagnosis system achieved a sensitivity of 0.8848, specificity of 0.8841, accuracy of 0.8845, and an F1 score of 0.8914. Compared with previous studies, our system provides a clinical reference, facilitates nystagmus detection and diagnosis, and it can be applied in real-world medical practices