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Abstract To explore the multiparameter precursor characteristics of pre- and post-coal burst. Based on a coal burst of LW 1305 in the Zhaolou Coal Mine, an early warning method combining stress‒strain curve and microseismic multiparameter is proposed. The research results show that coal burst was induced by the intrinsic static high-stress concentration and the strong external impact loading generated by fracturing of the key stratum. The precursors mainly characterize the enhancement trend of the S value, the sudden and sharp increase in the A(t) value, the continuous and abnormal decrease in the b value, the increasing absolute value of Z sharply and larger than 2, the continuous and abnormal decrease in the Qt value, and the dominant frequency moving to the low-frequency band. Essentially, many micro-fissures inside the key stratum initiated, converged and connected to form macro-fractures, which was verified by the attenuation rate of the K value. Considering the time-varying effect of the overlying stratum movement, the curves of the six parameters agree well with those of stress vs. strain, which indicates that it is reasonable to take the observed zone as a whole system to investigate the variation in the multiple parameters and fracturing of the key stratum. The research results can be applied to the monitoring, early warning and control of coal burst so that effective safety measures can be taken in real time.

Textile-based sensors have emerged as a promising technology for enabling low-burden, personalized, and on-body biometrics. However, current textile sensors often lack multimodal or multipositional sensing capabilities, are challenging to fabricate at scale, and are not seamlessly integrated into textile-borne readout systems. We report textile-integrated, laser-induced graphene (LIG) sensors for multiparametric biometrics monitoring. The LIG sensors are designed with custom patterns specific to different stimulistrain, humidity, and temperature demonstrated hereinand exhibit tunable sensitivity through control of the pattern geometry and the laser power used during LIG conversion. These sensors are highly sensitive to changes in resistance, rapidly respond to stimuli (<5 s), and exhibit remarkable stability for at least 1000 cycles. Lastly, such sensors are synthesized alongside magnetic metamaterials and are seamlessly coupled with flexible near-field communication systems directly on textile. This enables fully integrated "smart" clothing capable of battery-free, wireless monitoring of cross-body metrics. Such protocols represent a straightforward, accessible strategy for directly incorporating multiple sensor and network elements into on-demand textiles for advanced human body measurements. [ABSTRACT FROM AUTHOR]

Objectives: A questionnaire was designed to survey veterinarians and veterinary nurses/technicians on blood pressure (BP) assessment in cats, including ocular examination, encompassing current methodology, indications, uptake and barriers. Methods: An online questionnaire was produced and promoted to more than 2000 veterinary professionals, of whom 545 answered all questions and 85 answered most questions. Results: Of the participants, 572 (90.8%) were based in the UK and almost all (n = 613, 97.3%) had access to a BP monitor. Of those that had a monitor, most (n = 550, 88.4%) participants had access to a Doppler monitor; 367 (59.0%) participants had access to multiparameter monitors; fewer (n = 202, 32.5%) had access to oscillometric BP monitors. Where applicable, Doppler monitors were most commonly chosen for conscious cat measurements (n = 337, 72.2%) due to the greater 'trust' and 'reliability' of these compared with oscillometric machines. Conscious BP measurement typically involved two members of staff (n = 391, 62.9%). Only 156 (29.1%) participants recommended BP assessment at least several times a week in their interactions with cat owners. BP assessment was routinely recommended in cats with ocular target organ damage (n = 365, 87.7%), chronic kidney disease (n = 346, 78.6%), proteinuria (n = 255, 63.0%) and hyperthyroidism (n = 266, 60.9%). Common equipment-related barriers included 'cuff frustration' and difficulties hearing the pulse signal for Doppler users (72.2% and 71.6%, respectively), and oscillometric machines failing to give a reading at least some of the time (52.8%). Situational hypertension concerns affected many (n = 507, 92.0%), as did lack of time to do the procedure (n = 402, 73.0%). Significant owner barriers included difficulties persuading the owner to bring their cat in for BP checks (n = 475, 86.2%) and concerns over costs (n = 445, 80.8%). Most participants had access to a direct ophthalmoscope (n = 527, 96.5%); however, 399 (73.1%) reported that they struggled to interpret ocular findings. Conclusions and relevance: Significant barriers exist to successful BP assessment in cats. Education and support of clinics should focus on improving confidence with equipment and eye examination. [ABSTRACT FROM AUTHOR]

Autonomous underwater vehicle (AUV) with towed magnetic anomaly detection (MAD) system is a reliable technique for detecting underwater magnetic targets. However, arranging too many magnetometers in the towed MAD system is not suitable, and the key lies in their reasonable arrangement. As a result, this letter proposes a new MAD system equipped with two scalar and one vector magnetometers, along with the corresponding multiparameter magnetic target localization method. By using two scalar magnetometers and the geometric relationship with vector magnetometer, the time when the vector magnetometer reaches the closest point approach (CPA) on the trajectory and the value range of the shortest distance are obtained. The value range of the shortest distance is cleverly set as the search boundary for the improved particle swarm optimization algorithm in this dimension, which greatly mitigates the randomness of the optimization algorithm and enhances the accuracy of the solution. Subsequently, the unique solution for the magnetic target parameters can be easily obtained by using the vector magnetometer. The combination of scalar and vector magnetometers proves to be both economical and effective. Numerical simulation and field experiments show that this method provides a new idea for static magnetic target detection. [ABSTRACT FROM AUTHOR]

Abstract Objective To evaluate the diagnostic value of a multiparameter model based on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) metabolic parameters and clinical variables in differentiating nonmetastatic gallbladder cancer (GBC) from cholecystitis. Patients and methods In total, 122 patients (88 GBC nonmetastatic patients and 34 cholecystitis patients) with gallbladder space-occupying lesions who underwent 18F-FDG PET/CT were included. All patients received surgery and pathology, and baseline characteristics and clinical data were also collected. The metabolic parameters of 18F-FDG PET, including SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), SUVpeak (peak standard uptake value), MTV (metabolic tumour volume), TLG (total lesion glycolysis) and SUVR (tumour-to-normal liver standard uptake value ratio), were evaluated. The differential diagnostic efficacy of each independent parameter and multiparameter combination model was evaluated using the receiver operating characteristic (ROC) curve. The improvement in diagnostic efficacy using a combination of the above multiple parameters was evaluated by integrated discriminatory improvement (IDI), net reclassification improvement (NRI) and bootstrap test. Decision curve analysis (DCA) was used to evaluate clinical efficacy. Results The ROC curve showed that SUVR had the highest diagnostic ability among the 18F-FDG PET metabolic parameters (area under the curve [AUC] = 0.698; sensitivity = 0.341; specificity = 0.971; positive predictive value [PPV] = 0.968; negative predictive value [NPV] = 0.363). The combined diagnostic model of cholecystolithiasis, fever, CEA > 5 ng/ml and SUVR showed an AUC of 0.899 (sensitivity = 0.909, specificity = 0.735, PPV = 0.899, NPV = 0.758). The diagnostic efficiency of the model was improved significantly compared with SUVR. The clinical efficacy of the model was confirmed by DCA. Conclusions The multiparameter diagnostic model composed of 18F-FDG PET metabolic parameters (SUVR) and clinical variables, including patient signs (fever), medical history (cholecystolithiasis) and laboratory examination (CEA > 5 ng/ml), has good diagnostic efficacy in the differential diagnosis of nonmetastatic GBC and cholecystitis.

Fiber-reinforced plastic (FRP) composites are utilized extensively in various high-end industries. Therefore, developing a proper sensing and monitoring system is crucial to monitor the production and post-production in-service structural behaviors of composite materials. This paper provides a comprehensive literature review focusing on Fiber Bragg Grating (FBG) as a multiparameter sensor in FRP composite materials. The review is mainly divided into two main themes, namely, embedded FBGs and surface-attached FBGs, followed by further sub-themes according to the application of the FBGs. Contemporary issues regarding FBGs as sensors in composite materials are also discussed. Subsequently, a comparative analysis between the embedded and surface-attached techniques from various perspectives is presented before further recommendation for the ideal embedding conditions and techniques is provided. This review is summarized with a projected view on the future of FBGs as a sensor, generally, and in composite laminates, specifically.

Abstract Pre-stack seismic inversion is an effective method to estimate multiparameter from seismic reflection data in the oil–gas reservoir exploration. In order to get a reliable inverted parameter result, a constrained model is commonly used to reduce the multi-solution in the seismic inversion. However, it is hard to get an appropriate constrained model by conventional well-log data interpolation or velocity field in offshore oil–gas exploration with sparse wells. Envelope inversion has been successfully applied to get a good initial model with low-frequency components in full-waveform inversion. In order to fully exploit the rich information contained in seismic data, we introduce envelope inversion into background modeling based on convolution theory and propose a multiparameter pre-stack seismic inversion with envelope prior constraint. Both inversion results of the model and field data indicate the effectiveness and adaptability of the proposed method in multiparameter estimation.

Abstract An accurate prediction of prognosis is important for clinical treatments of glioma. In this study, a multiparameter radiomic model is proposed for accurate prognostic prediction of glioma. Three kinds of region of interest were extracted from preoperative postcontrast T1‐weighted images and T2 fluid‐attenuated inversion recovery images acquired from 140 glioma patients. Radiomics score (Radscore) was calculated and the conventional image features and clinical molecular characteristics that may be related to progression‐free survival (PFS) were evaluated. Five uniparameter and various combinations of biparameter and multiparameter models based on above characteristics were built. The performance of these models was evaluated by concordance index (C index), and the nomogram of the multiparameter radiomic model was constructed. The results show that the proposed multiparameter radiomic model has a better prediction performance than other models. In the training and validation sets, the calibration curves of the multiparameter radiomic model for the 1‐, 2‐, and 3‐year PFS probability demonstrate a high consistence between predictions and observations. In conclusion, this study demonstrates that the multiparameter radiomic model based on Radscore, conventional image features and clinical molecular characteristics can improve the prediction accuracy of glioma prognosis, which could be informative for individualized treatments.

Abstract Objective To evaluate the diagnostic performance of combined multiparametric 18F-fluorodeoxyglucose positron emission tomography (18FDG PET) with clinical characteristics in differentiating thymic epithelial tumors (TETs) from thymic lymphomas. Patients and methods A total of 173 patients with 80 TETs and 93 thymic lymphomas who underwent 18F-FDG PET/CT before treatment were enrolled in this retrospective study. All patients were confirmed by pathology, and baseline characteristics and clinical data were also collected. The semi-parameters of 18F-FDG PET/CT, including lesion size, SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), TLG (total lesion glycolysis), MTV (metabolic tumor volume) and SUVR (tumor-to-normal liver standard uptake value ratio) were evaluated. The differential diagnostic efficacy was evaluated using the receiver operating characteristic (ROC) curve. Integrated discriminatory improvement (IDI) and net reclassification improvement (NRI), and Delong test were used to evaluate the improvement in diagnostic efficacy. The clinical efficacy was evaluated by decision curve analysis (DCA). Results Age, clinical symptoms, and metabolic parameters differed significantly between patients with TETs and thymic lymphomas. The ROC curve analysis of SUVR showed the highest differentiating diagnostic value (sensitivity = 0.763; specificity = 0.888; area under the curve [AUC] = 0.881). The combined diagnostics model of age, clinical symptoms and SUVR resulted in the highest AUC of 0.964 (sensitivity = 0.882, specificity = 0.963). Compared with SUVR, the diagnostic efficiency of the model was improved significantly. The DCA also confirmed the clinical efficacy of the model. Conclusions The multiparameter diagnosis model based on 18F-FDG PET and clinical characteristics had excellent value in the differential diagnosis of TETs and thymic lymphomas.

Objective: To evaluate the diagnostic value of a multiparameter model based on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) metabolic parameters and clinical variables in differentiating nonmetastatic gallbladder cancer (GBC) from cholecystitis. Patients and methods: In total, 122 patients (88 GBC nonmetastatic patients and 34 cholecystitis patients) with gallbladder space-occupying lesions who underwent 18F-FDG PET/CT were included. All patients received surgery and pathology, and baseline characteristics and clinical data were also collected. The metabolic parameters of 18F-FDG PET, including SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), SUVpeak (peak standard uptake value), MTV (metabolic tumour volume), TLG (total lesion glycolysis) and SUVR (tumour-to-normal liver standard uptake value ratio), were evaluated. The differential diagnostic efficacy of each independent parameter and multiparameter combination model was evaluated using the receiver operating characteristic (ROC) curve. The improvement in diagnostic efficacy using a combination of the above multiple parameters was evaluated by integrated discriminatory improvement (IDI), net reclassification improvement (NRI) and bootstrap test. Decision curve analysis (DCA) was used to evaluate clinical efficacy. Results: The ROC curve showed that SUVR had the highest diagnostic ability among the 18F-FDG PET metabolic parameters (area under the curve [AUC] = 0.698; sensitivity = 0.341; specificity = 0.971; positive predictive value [PPV] = 0.968; negative predictive value [NPV] = 0.363). The combined diagnostic model of cholecystolithiasis, fever, CEA > 5 ng/ml and SUVR showed an AUC of 0.899 (sensitivity = 0.909, specificity = 0.735, PPV = 0.899, NPV = 0.758). The diagnostic efficiency of the model was improved significantly compared with SUVR. The clinical efficacy of the model was confirmed by DCA. Conclusions: The multiparameter diagnostic model composed of 18F-FDG PET metabolic parameters (SUVR) and clinical variables, including patient signs (fever), medical history (cholecystolithiasis) and laboratory examination (CEA > 5 ng/ml), has good diagnostic efficacy in the differential diagnosis of nonmetastatic GBC and cholecystitis. [ABSTRACT FROM AUTHOR]

In this study, we introduce the Multiparameter Eddy Significance Index (MESI) for use in conjunction with mesoscale eddy tracking to estimate the impact of mesoscale eddies on the upper ocean and marine ecosystems. MESI combines blended satellite observations of sea level anomalies, sea surface temperature, sea surface salinity, and ocean color chlorophyll‐a and is a normalized index. When used in conjunction with mesoscale eddy tracking, MESI can highlight those eddies which extend into the deeper ocean and have a greater effect on nutrient cycling. Preliminary analysis in the Gulf Stream region of the western North Atlantic shows that MESI covaries with model estimates of nitrate, phosphate, iron, and pH with cross‐correlation values between 76% and 95%. These results suggest that when MESI is used in concert with eddy tracking, it can be used as an indicator of eddies and areas that are more likely to impact nutrient cycling in the upper ocean. An additional analysis of MESI values inside eddies during Hurricane Dorian (2019) along the Carolina coast further suggests that MESI is most effective when used to enhance eddy tracking as it provides valuable insight into mesoscale eddy activity and the upper ocean circulation. Plain Language Summary: A Multiparameter Eddy Significance Index (MESI) is introduced in an effort to begin to quantify the potential impact mesoscale eddies have on the upper ocean circulation, nutrient cycling, and biological productivity. MESI is calculated using satellite observations of sea level anomalies, sea surface temperature and salinity, ocean color derived chlorophyll‐a, and eddy kinetic energy and is a normalized index that maintains the integrity of the eddy circulation type. Analysis of MESI values in conjunction with multiparameter mesoscale eddy tracking results for a period from August 2019–July 2021 suggest that eddies with higher amplitude MESI values penetrate deeper into the upper ocean than eddies with lower amplitude MESI values. In comparing MESI values with nitrate, phosphate, iron, and pH, it was found that MESI covaries with nutrient values with cross‐correlations between 76% and 95%, suggesting that MESI can be used as an indicator for nutrient cycling potential within tracked mesoscale eddies. When MESI is paired with eddy tracking, our results suggest that the index can provide valuable insight into eddy activity and impact on the upper ocean, especially during hurricanes and other large storms. Key Points: A multiparameter index is introduced that estimates the impact of mesoscale eddies on the upper ocean circulation and nutrient cyclingMultiparameter Eddy Significance Index (MESI) is most effective when coupled with multiparameter mesoscale eddy trackingMESI is shown to be closely related to nutrient values with a cross‐correlation of 76%–95% in the Northwestern Atlantic Ocean in 2019–2021 [ABSTRACT FROM AUTHOR]

Pre-stack seismic inversion is an effective method to estimate multiparameter from seismic reflection data in the oil–gas reservoir exploration. In order to get a reliable inverted parameter result, a constrained model is commonly used to reduce the multi-solution in the seismic inversion. However, it is hard to get an appropriate constrained model by conventional well-log data interpolation or velocity field in offshore oil–gas exploration with sparse wells. Envelope inversion has been successfully applied to get a good initial model with low-frequency components in full-waveform inversion. In order to fully exploit the rich information contained in seismic data, we introduce envelope inversion into background modeling based on convolution theory and propose a multiparameter pre-stack seismic inversion with envelope prior constraint. Both inversion results of the model and field data indicate the effectiveness and adaptability of the proposed method in multiparameter estimation. [ABSTRACT FROM AUTHOR]

Thermodynamic properties of homogeneous fluids in the metastable and unstable regions are needed to describe confined fluids, interfaces, nucleating embryos and estimate critical mass flow rates. The most accurate equations of state (EoS) called multiparameter EoS, have a second, non-physical Maxwell loop that renders predictions unreliable in these regions. We elaborate how information from the stable region can be used to reconstruct the metastable and unstable regions. For a simple interaction potential, comparison to results from molecular simulations reveals that isochoric expansion of the pressure from stable states reproduces simulation results in the metastable regions. By constructing a dome that extends above the critical point, we obtain an extrapolated pressure from multiparameter EoS that is free of second Maxwell loops. A reconstructed EoS is developed next, by integrating the extrapolated pressure from a stable state to obtain the Helmholtz energy. The consistency of the reconstructed EoS is gauged by computing phase equilibrium densities, pressures, and enthalpies of evaporation, which are in reasonable agreement with experimental values. Combined with density gradient theory, the reconstructed EoS yields surface tensions of water, carbon dioxide, ammonia, hydrogen and propane that deviate, on average, 4.4%, 1.6%, 6.0%, 0.7% and 5.4% from experimental values respectively. The results reveal a potential to develop more accurate extrapolation protocols, which can be leveraged to obtain prediction of metastable properties, surface properties or used as constraints in fitting multiparameter EoS. [ABSTRACT FROM AUTHOR]

Several studies have demonstrated that antimicrobial resistance (AMR) can result from natural mutations or the acquisition of foreign antimicrobial resistance genes. Many environmental parameters are known to affect AMR, including trace antibiotic concentrations in water, pH, hydraulic retention time, and nutrient concentration, among others. However, most analyses that investigate these parameters analyze them independently. This study investigated the development of natural resistance in Salmonella sp., and the horizontal transfer of resistance genes from an imipenem- resistant (IR) E. coli strain under varying environmental conditions. An automated continuous-culture device was employed to investigate the effect of external parameters of relevance to wastewater treatment plants and to conduct a multiparametric analysis to determine the relative importance of the different variables. In terms of mutation-driven resistance, hydraulic retention time, trace antibiotic concentration, and initial cell concentrations are the leading factors contributing to higher IR in Salmonella spp. In the case of acquired resistance, the initial trace antibiotic concentrations, and hydraulic retention times were also important, but pH, initial nutrient concentration, and, very importantly, the initial concentration of IR E. coli , were the leading factors contributing to IR in Salmonella spp. These results point out some important factors that need to be considered during the design and operation of wastewater treatment plants to minimize the appearance and transmission of antibiotic resistance. [Display omitted] • Used continuous-culture device for multiparametric study of AMR. • Mutation resistance is driven by HRT, trace antibiotic, and bacteria concentration. • Acquired resistance is driven by pH, trace antibiotic, and AMR gene donor. • Emphasized the importance of removing trace antibiotic concentrations in Wastewater. [ABSTRACT FROM AUTHOR]

Full-polarimetric ground penetrating radar (FP-GPR) can measure the ability of an object to change the polarization of electromagnetic waves. Compared to the traditional GPR, it has a stronger capability to identify underground objects. In recent years, a series of polarization decomposition methods have been applied to the FP-GPR data processing to obtain the polarimetric attributes and enhance the capability of targets identification. Different polarimetric attributes characterize different features of a target but there is still no effective way to integrate these attributes and take their respective advantages for target classification. In this article, we propose a particle center AdaBoost (PCAD) method and achieve the multiparameter adaptive target identification. The experimental results indicate that the PCAD method can automatically select suitable parameters during the training process for different targets. Compared to the single-parameter classification and the AdaBoost methods based on the traditional average and Bagging method, the PCAD method presents higher correct rates in classification. Finally, the proposed method is applied to landmine detection. The results demonstrate that the landmine is a composite scatterer that can generate surface scattering signals on its surface and dipole and volume scattering signals from its interior; based on the color-coded two-dimensional image by PCAD, we can distinguish landmines from other targets.

In this work, the surface of long-period fiber grating (LPFG) and polarization maintaining fiber (PMF) is functionalized based on the interaction between the resonance wavelength and external environment. LPFG coated with a 150 nm ZnSe/Co film is fixed on a hollow bracket, prestressed, and annealed many times. A highly sensitive liquid level sensor with adjustable sensitivity, an adjustable measurement range, and a high liquid level early warning is prepared. The waveguide layer controlled by humidity is constructed by filling poly-(3,4-ethylenedioxythiophene)/poly-(styrene sulfonate) (PEDOT/PSS) in a periodically etched PMF. The surface is coated with a poly-(vinyl alcohol) (PVA) and carbon nanotube (CNT) composite polymer. After laser processing, a honeycomb porous film is obtained, and the humidity sensor with wavelength modulation is prepared. The pH-sensitive polymer is successively adsorbed on the surface of PMF coated with a 120 nm indium tin oxide (ITO) film by electrostatic self-assembly (ESA). Poly-(allylamine hydrochloride) (PAH), poly-(acrylic acid) (PAA), and poly-(styrene sulfonate) (PSS) constitute a composite film with rapid deposition and high permeability that is covered with polyaniline/poly-(methyl methacrylate) (PMMA) as the protective layer. After laser processing, a fluffy porous film structure is formed. The pH sensor is obtained and the preparation steps are greatly reduced. Finally, based on the wavelength division multiplexing (WDM) and multiwavelength matrix (MWM), the problem of crosstalk is solved. An integrated sensor is constructed to realize the simultaneous measurement of temperature, liquid level, humidity, and pH. It has been successfully applied to monitor the overall environment of a chemical waste liquid storage tank. The sensor has the advantages of remote monitoring, safety, efficiency, and labor-saving. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: To construct a multiparameter radiomics nomogram based on ultrasound (US) to predict the aggressiveness of thyroid papillary carcinoma (PTC)., Materials and Methods: In total, 471 consecutive patients from three institutions were included in this study. Among them, patients from institution 1 were used for training (n = 294) and internal validation (n = 92), while 85 patients from institution 2 and institution 3 were used for external validation. Radiomics features were extracted from the conventional US. The least absolute shrinkage was employed to select the most relevant features for the aggressiveness of PTC, along with the maximum relevance minimum redundancy algorithm and selection operator. These features were then used to construct the radiomics signature (RS). Subsequently, relevant multiparameter ultrasound (MPUS) features from shear-wave elastic (SWE) and strain elastography (SE) will be extracted using multivariable logistic regression. The final radionics nomogram was conducted using the RS, clinical information, and conventional US and MPUS features. The receiver operating characteristic (ROC), calibration, and decision curves were used to evaluate the performance of the nomogram., Results: Multivariable logistic regression analysis indicated that age, nodule size, capsule abutment, SWV tumor, and RS were independent predictors of the aggressiveness of PTC. The radiomics nomogram, utilizing these characteristics, displayed impressive performance with an AUC of 0.920 [95% CI, 0.889-0.950], 0.901 [95% CI, 0.839-0.963], and 0.896 [95% CI, 0.823-0.969] in the training, internal, and external validation cohort. It outperformed the clinical US, MPUS, and RS models (p < 0.05). The decision curve analysis indicated that the nomogram offered valuable clinical utility., Conclusion: The nomogram incorporated MPUS and radiomics have good diagnostic performance in predicting the aggressiveness of PTC which may help in the selection of the surgical modality., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Rong Wu reports financial support was provided by the National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Background: There is a need for better noninvasive remote monitoring solutions that prevent hospitalizations through the early prediction and management of heart failure (HF). SurveillanCe and Alert-Based Multiparameter Monitoring to ReducE Worsening Heart Failure Events (SCALE-HF 1) evaluated the performance of a novel congestion index that alerts to fluid accumulation preceding HF events., Methods and Results: SCALE-HF 1 was a multicenter, prospective, observational study investigating HF event prediction using data from the cardiac scale. Participants with HF took measurements at home by standing barefoot on the scale for approximately 20 seconds each day. The congestion index was applied retrospectively, and an alert was generated when the index exceeded a fixed threshold established in prior studies. HF events were defined as unplanned administration of IV diuretics or admissions with a primary diagnosis of HF. Sensitivity was defined as the ratio of correctly identified HF events to the total number of HF events. We enrolled 329 participants (mean age 64 ± 14 years; 43% women; 32% Black; 56% with reduced ejection fraction) across 8 sites with 238 participant-years of follow-up and 69 usable HF events. The congestion index predicted 48 of the 69 HF events (70%) at 2.58 alerts per participant-year. In contrast, the standard weight rule (weight gain of >3 lb in 1 day or >5 lb in 7 days) predicted only 24 of the 69 HF events (35%) at 4.18 alerts per participant-year. The congestion index alerts had a significantly higher sensitivity (P < .01) at a lower alert rate than the standard weight rule., Conclusions: The congestion index alerts demonstrated sensitive prediction of HF events at a low alert rate, significantly exceeding the performance of weight-based monitoring., Gov Identifier: NCT04882449., Competing Interests: Disclosures Dr. Fudim was supported by the National Heart, Lung, and Blood Institute (NHLBI) (K23HL151744), the American Heart Association (20IPA35310955), the Doris Duke Foundation, Bayer, Bodyport, and Verily. He receives consulting fees from Abbott, Alio Health, Alleviant, Audicor, AxonTherapies, Bayer, Bodyguide, Bodyport, Boston Scientific, Cadence, Coridea, CVRx, Daxor, Deerfield Catalyst, Edwards LifeSciences, EKO, Feldschuh Foundation, Fire1, Gradient, Intershunt, Medtronic, NIMedical, NXT Biomedical, Pharmacosmos, PreHealth, ReCor, Shifamed, Splendo, Sumacor, SyMap, Verily, Vironix, Viscardia, and Zoll. Dr. Sauer reports consulting for Bodyport, Abbott, Amgen, Bayer, Medtronic, Edwards Lifesciences, Boston Scientific, Impulse Dynamics, Acorai, Story Health, 35Pharma, Regeneron, and General Prognostics. Dr. Sauer also reports significant research funding from Abbott, Bayer, CSL Vifor, Pfizer, Rivus, Story Health, General Prognostics, and Impulse Dynamics and serves on clinical trial steering committees for Rivus, Bayer, Boston Scientific, Biotronik, Abbott, Impulse Dynamics, Story Health, and General Prognostics. Dr. Sauer also owns stock in ISHI, a privately held digital health company, for his role as a senior advisor. Dr. Lopes reports research grants or contracts from Amgen, Bristol-Myers Squibb, GlaxoSmithKline, Medtronic, Pfizer, and Sanofi-Aventis; funding for educational activities or lectures from Pfizer, Daiichi Sankyo, and Novo Nordisk; and funding for consulting or other services from Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, and Novo Nordisk. Dr. Ozonat is a current employee at Bodyport Inc. Sarah Smith and Corey Centen are founders and employees of Bodyport Inc. Dr. Pandit is a clinical advisor to Bodyport. Dr. DeVore reports research funding through his institution from the American Heart Association, Biofourmis, Bodyport, Cytokinetics, American Regent, Inc., the NHLBI, Novartis, and Story Health. He also provides consulting services for and/or receives honoraria from Abiomed, AstraZeneca, Cardionomic, InnaMed, LivaNova, Natera, Novartis, Procyrion, Story Health, Vifor, and Zoll. He has also received nonfinancial support from Abbott for educational and research activities., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: To evaluate the diagnostic performance of combined multiparametric 18F-fluorodeoxyglucose positron emission tomography (18FDG PET) with clinical characteristics in differentiating thymic epithelial tumors (TETs) from thymic lymphomas.Patients and Methods: A total of 173 patients with 80 TETs and 93 thymic lymphomas who underwent 18F-FDG PET/CT before treatment were enrolled in this retrospective study. All patients were confirmed by pathology, and baseline characteristics and clinical data were also collected. The semi-parameters of 18F-FDG PET/CT, including lesion size, SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), TLG (total lesion glycolysis), MTV (metabolic tumor volume) and SUVR (tumor-to-normal liver standard uptake value ratio) were evaluated. The differential diagnostic efficacy was evaluated using the receiver operating characteristic (ROC) curve. Integrated discriminatory improvement (IDI) and net reclassification improvement (NRI), and Delong test were used to evaluate the improvement in diagnostic efficacy. The clinical efficacy was evaluated by decision curve analysis (DCA).Results: Age, clinical symptoms, and metabolic parameters differed significantly between patients with TETs and thymic lymphomas. The ROC curve analysis of SUVR showed the highest differentiating diagnostic value (sensitivity = 0.763; specificity = 0.888; area under the curve [AUC] = 0.881). The combined diagnostics model of age, clinical symptoms and SUVR resulted in the highest AUC of 0.964 (sensitivity = 0.882, specificity = 0.963). Compared with SUVR, the diagnostic efficiency of the model was improved significantly. The DCA also confirmed the clinical efficacy of the model.Conclusions: The multiparameter diagnosis model based on 18F-FDG PET and clinical characteristics had excellent value in the differential diagnosis of TETs and thymic lymphomas. [ABSTRACT FROM AUTHOR]

In this paper, a metal–insulator–metal (MIM) surface plasmon waveguide structure is proposed and numerically investigated. It is composed of a square-ring cavity with a silver baffle, an isosceles triangle cavity, and a bus waveguide with a silver baffle. The results show that the structure can produce triple Fano resonances that can be independently tuned by changing the structural parameters. The detection of refractive indexes at different positions in the structure was also accomplished, with a maximum sensitivity of 2259.56 nm/RIU. On the basis of this, the simultaneous measurement of multiple parameters (plasma concentration and glucose concentration) was performed. The numerical simulation results are beneficial to the applications of MIM waveguide structure in nanosensing and biosensing with time-sharing or simultaneous measurement of multiple parameters. [ABSTRACT FROM AUTHOR]

The diversity of magnetic field information obtained in marine geomagnetic measurements is of great relevance to defining detailed features of the targets. In this article, a solution algorithm based on the combination of scalar and vector fields is proposed. The magnetic direction of the geomagnetic field was obtained by repeatedly applying bias fields, and the multiparameter integrated measurement is realized based on the geometric relationship of the geomagnetic parameters. To make an instrument feasible for undersea measurement, a miniaturized multiparameter magnetometer was constructed within the limited space of a pressure tank, using an Overhauser scalar sensor and a spherical coil for generating bias fields. Test platforms were built to evaluate the scalar sensor and spherical coil. Results from a nonmagnetic laboratory showed that the expanded uncertainty of the scalar sensor was 0.11 nT, whereas the magnetic field generated by the spherical coil had 97% uniformity and completely engulfed the scalar sensor. Moreover, field experiments indicated that the standard deviation of prototype instrument in magnetic direction (3 $^{\prime \prime }$) was close to that of declination–inclination magnetometer, whereas its standard deviation in Z-component of 0.24 nT was better than that of a commercial fluxgate magnetometer. It also had markedly better measurement stability, with no temperature drift. [ABSTRACT FROM AUTHOR]

The multiparameter 2 × n LC complex impedance network is one of the difficult problems of the resistor network problem. In this study, the equivalent complex impedance problem of the four‐parameter 2 × n LC network model has been considered, where the network model contains four arbitrary L and C parameters. Our study involves four main steps: Firstly, a general difference equation model with current parameters has been established by utilizing Kirchhoff's law. Secondly, the general solution of the difference equation model has been obtained by matrix transformation. Thirdly, a matrix equation with boundary current parameters has been established, and the special solution of the boundary current has been obtained by substituting the general solution in the previous step. Finally, based on Ohm's law, the equivalent complex impedance formula has been obtained by using the special solution of the boundary current. The analysis of the derived equivalent complex impedances, Zab(n) and Zac(n), shows that they have different characteristics in different frequency ranges, and their variation is related to the mesh number n. The results of this study offer a theoretical basis for the related applied research. [ABSTRACT FROM AUTHOR]

In this paper, the equations and systems of Monge-Ampère with parameters are considered. We first show the uniqueness of of nontrivial radial convex solution of Monge-Ampère equations by using sharp estimates. Then we analyze the existence and nonexistence of nontrivial radial convex solutions to Monge-Ampère systems, which includes some new ingredients in the arguments. Furthermore, the asymptotic behavior of nontrivial radial convex solutions for Monge-Ampère systems is also considered. Finally, as an application, we obtain sufficient conditions for the existence of nontrivial radial convex solutions of the power-type system of Monge-Ampère equations.

Abstract Background Flow cytometry is a powerful tool for the multiparameter analysis of leukocyte subsets on the single cell level. Recent advances have greatly increased the number of fluorochrome-labeled antibodies in flow cytometry. In particular, an increase in available fluorochromes with distinct excitation and emission spectra combined with novel multicolor flow cytometers with several lasers have enhanced the generation of multidimensional expression data for leukocytes and other cell types. However, these advances have mainly benefited the analysis of human or mouse cell samples given the lack of reagents for most animal species. The flow cytometric analysis of important veterinary, agricultural, wildlife, and other animal species is still hampered by several technical limitations, even though animal species other than the mouse can serve as more accurate models of specific human physiology and diseases. Results Here we present time-tested approaches that our laboratory regularly uses in the multiparameter flow cytometric analysis of ovine leukocytes. The discussed approaches will be applicable to the analysis of cells from most animal species and include direct modification of antibodies by covalent conjugation or Fc-directed labeling (Zenon™ technology), labeled secondary antibodies and other second step reagents, labeled receptor ligands, and antibodies with species cross-reactivity. Conclusions Using refined technical approaches, the number of parameters analyzed by flow cytometry per cell sample can be greatly increased, enabling multidimensional analysis of rare samples and giving critical insight into veterinary and other less commonly analyzed species. By maximizing information from each cell sample, multicolor flow cytometry can reduce the required number of animals used in a study.

Passive microwave data have been extensively used for snow depth (SD) inversion, but their accuracy has large error in the Qinghai-Tibet Plateau (QTP). Thus, there is still room for improvement in regional SD inversion. Ground-measured SD data combined with elevation, longitude, and land cover data were used to develop a multifactor SD inversion model based on Advanced Microwave Scanning Radiometer 2 (AMSR2) over the QTP. The SD inversion model and the AMSR2 SD product were validated and compared using the meteorological stations and ground-measured SD over the QTP at the same time. The results show that the root-mean-square error (RMSE) of the novel model developed in this study is approximately 5 cm, which is much better than the accuracy of the AMSR2 SD product (11-13 cm) released by the Japan Aerospace Exploration Agency. When the ground-measured SD is less than 30 cm, the RMSE and the mean absolute error of the developed model are below 7 and 6 cm, respectively, and the BIAS is approximately 1 cm. The SD inversion results are poor in the western part of the plateau due to the complex terrain and thick snow cover, and its RMSE is greater than 15 cm. In conclusion, this novel SD inversion model is more applicable and accurate than the AMSR2 SD products.

Elastic least-squares reverse-time migration (ELSRTM) yields subsurface high-resolution elastic images from multicomponent seismic data. For ocean bottom seismic (OBS) acquisitions, both pressure and displacement components are measured using four-component (4C) modern receivers. However, these 4C data cannot be effectively simulated and migrated using conventional ELSRTM approaches due to the limitation of the standard elastic wave equation. For this reason, we propose a new ELSRTM method based on a modified acoustic-elastic coupled (AEC) equation. Owing to this equation, either the prediction or the migration of OBS 4C data can be implemented using a one-time wavefield simulation. Incorporation with a perturbation imaging condition, the proposed method can invert for P- and S-wave velocity and density and generate amplitude-preserving images. Besides, it can provide subsurface impedance reflectivity models by stacking the obtained multi-parameter images. In the least-squares migration, a preconditioned conjugate gradient algorithm is implemented based on a multi-parameter diagonal Hessian. Numerical experiments on an uncorrelated layer model and a portion of the Southern Yellow China sea model can demonstrate the effectiveness of this method on improving imaging resolution and accelerating convergence rate. [ABSTRACT FROM AUTHOR]

In this article, we improved the nonlinear weight of the classical third‐order WENO scheme by using the limiter of the MUSCL scheme and got a new WENO scheme, the WENO‐F scheme, and developed three new nonlinear multiple‐parameter weight functions by improving the nonlinear weight of WENO‐JS, WENO‐Z, and WENO‐Z+ schemes. After selecting appropriate parameters of these new weight functions, three new high‐resolution schemes are comparing with three kinds of classical WENO schemes. Theoretical analysis and numerical results show that the new scheme with these multiparameter functional weights can achieve third‐order convergence in smooth regions. And the new scheme has lower dissipation and better resolution than the classical third‐order WENO schemes for smooth and discontinuous solutions. [ABSTRACT FROM AUTHOR]

Autonomous aerial refueling (AAR) can improve the aircraft’s combat effectiveness, and drogue visual tracking is one of the key technologies for the success of AAR. Target tracking is challenging as high-speed drogue often undergo abrupt motions, leaving the vision field, and significant hollow background variation over time. To address these challenges, a tracker based on multiparameter adaptive adjustment is proposed. First, we propose a background awareness module to perceive the hollow background of the drogue, which contributes to fully utilize background information. Second, the parameter and feature adaptation module is proposed to optimize the parameters and features by combining the information of drogue motion and the changing background. Finally, the tracking result is determined by the designed adaptive fusion module that conduces to the elevation of the tracking accuracy. The three modules are effectively merged, allowing our system to track the hollow object robustly and leading to superior results on the drogue videos experiment in the sky compared with state-of-the-art trackers. [ABSTRACT FROM AUTHOR]

On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst, the research progress and shortcomings in understanding the rockburst phenomenon have been comprehensively investigated. This study focuses on the occurrence mechanism and monitoring and early warning technology for rockburst in coal mines. Results showed that the prevention and control of rockburst had made significant progress. However, with the increasing mining depth, several unresolved concerns remain challenging. From the in-depth research and analysis, it can be inferred that rockburst disasters involve three main problems, i.e., the induction factors are complicated, the mechanism is still unclear, and the accuracy of the monitoring equipment and multi-source stereo monitoring technology is insufficient. The monitoring and warning standards of rockburst need to be further clarified and improved. Combined with the Internet of Things, cloud computing, and big data, a study of the trend of rockburst needs to be conducted. Furthermore, the mechanism of multiphase and multi-field coupling induced by rockburst on a large scale needs to be explored. A multisystem and multiparameter integrated monitoring and early warning system and remote monitoring cloud platform for rockburst should be explored and developed. High-reliability sensing technology and equipment and perfect monitoring and early warning standards are considered to be the development direction of rockburst in the future. This research will help experts and technicians adopt effective measures for controlling rockburst disasters. [ABSTRACT FROM AUTHOR]

Metasurface provides subwavelength structures for manipulating wavefronts of light. The benefits of subwavelength components offer a continuous modulation of amplitude, phase, and polarization, thus eliminating the production of higher-order images and improving the utilization of light intensity. Despite the rapid progress in this field, multiparameter control of light using single layer metasurface is rarely reported. In fact, multiparameter control of light helps to improve information storage capacity and image fidelity. With simultaneous manipulation of polarization and amplitude at each pixel, it is possible to encode two separate images into one metasurface and reconstruct them under proper conditions. In a proof of concept experiment, we demonstrate an independent display of two binary images at the same position with polarization de-multiplexing from a single metasurface. This unique technology of encoding two images through amplitude and polarization manipulation provides a new opportunity for various applications in, such as encryption, information storage, polarization holograms, optical communications and fundamental physics.

An optical method for measuring soot volume fraction, flame temperature, and concentration of combustion products in a diffusion flame based on time-division multiplexed tunable diode laser absorption spectroscopy technique is presented in this article. By moving the slot burner with an electric platform, two-dimensional profile of soot volume fraction, flame temperature, and gas concentrations along the flame sheet with 1-mm spatial resolution were obtained simultaneously. The flame temperature and soot volume fraction were simultaneously on-line monitored using one distributed feedback diode laser with a center wavelength at 1397.83 nm. Tunable diode laser absorption spectroscopy based temperature measurements in the flame were carried out by two-line thermometry of H2O and compared with the thermocouple technique. The attenuation of tunable diode laser intensity caused by soot extinction and gas absorption after transmitting through the diffusion flame was detected. And the soot volume fraction was determined quantitatively with laser extinction based on Rayleigh limit assumption. Two tunable distributed feedback diode lasers with center wavelength at 2001.6 and 2302 nm were used to determine the CO2 concentration and CO concentration, respectively. The experimental results of soot volume fraction, flame temperature, and the mole fraction of combustion products by varying concentrations of CO2 added in the diffusion flame were analyzed.

Ground-penetrating radar (GPR) full-waveform inversion (FWI) is an emerging near-surface high-resolution imaging technology that has been widely used in GPR 2-D imaging to better quantitatively evaluate the permittivity and conductivity of the subsurface. However, the 2-D imaging method limits the applicability and accuracy of FWI for the 3-D object cases. In this letter, we develop a 3-D FWI algorithm involving permittivity and conductivity for GPR in the frequency domain. The method employs the edge-based finite element method to solve the forward problem and the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method to solve the inverse problem, which avoids the calculation of the Hessian matrix. In particular, by using the parameter scaling and scaling factor, it is convenient to carry out the simultaneous inversion of permittivity and conductivity with high efficiency. In addition, a modified total variation regularization scheme is utilized for ensuring the stability of the inversion, as well as identifying the abnormal body boundary more effectively. As a demonstration, a synthetic 3-D model experiment is presented to test the proposed algorithm. The results show that the proposed inversion strategy can accurately reconstruct the permittivity structure together with the conductivity distribution from the 3-D on-ground GPR data. [ABSTRACT FROM AUTHOR]

Previous studies have revealed that gas compositions of fluid samples collected from southwestern Taiwan, where many hot springs and mud volcanoes are distributed along with tectonic structures, show significant variation before and after some disaster seismic events. Such variations, including radon activity, CH4/CO2, and 3He/4He ratios of gas compositions, are considered precursors of earthquakes in this area. An automatic system for continuous on-line gas monitoring and groundwater sampling was established at Yun-Shui (YS), where an artesian well located at an active fault zone in SW Taiwan, to validate the relationship between fluid compositions and seismicity. It is equipped with a quadrupole mass spectrometer (QMS) and a radon detector for in-situ measurement of the dissolved gas composition. Variations of dissolved gas compositions are transmitted to the laboratory through the internet. Furthermore, a syringe pump apparatus for the retrieval and temporal analysis of helium (SPARTAH) is also installed for off-line laboratory analysis for obtaining the detailed time-series records of helium, hydrogen, oxygen, and dissolved inorganic carbon (DIC) isotopic compositions as well as dissolved inorganic carbon and chloride concentration of water samples at this station. After continuous monitoring for several months, two substantial anomalies of multiparameter were observed prior to the significant earthquakes. This automated system has been demonstrated to be feasible for long-term continuous seismo-geochemical research in this area.

In this paper, a metal–insulator–metal (MIM) surface plasmon waveguide structure is proposed and numerically investigated. It is composed of a square-ring cavity with a silver baffle, an isosceles triangle cavity, and a bus waveguide with a silver baffle. The results show that the structure can produce triple Fano resonances that can be independently tuned by changing the structural parameters. The detection of refractive indexes at different positions in the structure was also accomplished, with a maximum sensitivity of 2259.56 nm/RIU. On the basis of this, the simultaneous measurement of multiple parameters (plasma concentration and glucose concentration) was performed. The numerical simulation results are beneficial to the applications of MIM waveguide structure in nanosensing and biosensing with time-sharing or simultaneous measurement of multiple parameters.

Full waveform inversion (FWI) is a powerful tool to understand the real complicated earth model. As FWI is a highly nonlinear problem and depends strongly on the initial model, how to effectively retrieve the large-scale background model is critical for the success of FWI. For elastic FWI (EFWI), the inversion challenge increases because the P-wave and S-wave are coupled together if no mode separation technologies are applied. In this article, we develop a new EFWI strategy, where we simultaneously implement the angle decomposition and mode separation for the wavefield. Based on the analysis of radiation patterns of different parameters and the fact that small scattering angles correspond to large-scale model perturbations, we can retrieve the large-scale background model of the P-wave velocity with pure small scattering angle P-P mode wavefield. On the other hand, the pure small scattering angle S-S, S-P, and P-S mode wavefields are used to estimate the large-scale background model of the S-wave velocity. The correctly retrieved large-scale background models further guarantee the success of subsequent fine structure retrieving for the P- and S-wave velocity models by using different wave modes. The proposed method is able to reduce the cycle-skipping problem and the multiparameter crosstalk problem simultaneously. Numerical examples show that the proposed method provides much improved inversion results than the conventional EFWI, which demonstrates the validity of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the equations and systems of Monge-Ampère with parameters are considered. We first show the uniqueness of of nontrivial radial convex solution of Monge-Ampère equations by using sharp estimates. Then we analyze the existence and nonexistence of nontrivial radial convex solutions to Monge-Ampère systems, which includes some new ingredients in the arguments. Furthermore, the asymptotic behavior of nontrivial radial convex solutions for Monge-Ampère systems is also considered. Finally, as an application, we obtain sufficient conditions for the existence of nontrivial radial convex solutions of the power-type system of Monge-Ampère equations. [ABSTRACT FROM AUTHOR]

A novel traveltime tomographic approach is applied to anisotropic media, limited to 2D geometry at present. A general anisotropic Eikonal solver based on a discontinuous Galerkin method is combined with an efficient adjoint formulation for multiparameter least‐squares inversion. This new approach is tested considering synthetic crosshole ground‐penetrating radar data. The configuration of the ground‐penetrating radar survey is inspired by a real experiment done on layered carbonate media disturbed by the presence of a deep gallery, which induces a localized high‐electromagnetic contrast. This made it possible to define a well‐adapted general workflow in this context. We notably show that, under the elliptical anisotropic assumption, the parametrization based on vertical and horizontal velocities provides less biased results than those obtained by considering the vertical velocity and the relevant Thomsen parameter ε. The initial vertical and horizontal velocity models are identical and built from an isotropic inversion. The presence of the high‐contrast gallery generates a weak diffraction pattern, which is taken into account in our tomography approach. It also creates potential artefacts due to the model discretization, which are mitigated by a model regularization term within the definition of the misfit function. This general workflow is then applied to the real experiment dataset. The vertical and horizontal velocity images provide similar structures as those previously obtained by isotropic full waveform inversion, complemented by an image of a rather weak elliptical anisotropy. [ABSTRACT FROM AUTHOR]

Energy saving is an important measure for the sustainable of opencast mining industry. However, the energy saving operation of crushing station is affected by vibration and collision in the process of open pit mining. This research aims to explore a novel strategy to reduce the high energy consumption of crushing station. Discrete element method (DEM), particle contact model and multiscale viscous particle model were used to analyse the operation process of crushing station. A multiparameter coupling coordinated speed regulation crushing strategy was proposed combined with the crusher model and simulation parameters. The practical application of this strategy in the crushing station of Shenbao energy open pit mine has been verified. The application results showed that compared with the manual operation control, the crushing efficiency of the crushing station is increased by 21.80%, the powder passing rate is reduced by 53.35%, and the operation energy saving of the crushing station is about 41.00%. The energy saving effect of multiparameter optimization is better than that of single parameter. This research provides a new theoretical basis for energy saving operation of crushing station in open pit mine. [ABSTRACT FROM AUTHOR]

Background: Flow cytometry is a powerful tool for the multiparameter analysis of leukocyte subsets on the single cell level. Recent advances have greatly increased the number of fluorochrome-labeled antibodies in flow cytometry. In particular, an increase in available fluorochromes with distinct excitation and emission spectra combined with novel multicolor flow cytometers with several lasers have enhanced the generation of multidimensional expression data for leukocytes and other cell types. However, these advances have mainly benefited the analysis of human or mouse cell samples given the lack of reagents for most animal species. The flow cytometric analysis of important veterinary, agricultural, wildlife, and other animal species is still hampered by several technical limitations, even though animal species other than the mouse can serve as more accurate models of specific human physiology and diseases. Results: Here we present time-tested approaches that our laboratory regularly uses in the multiparameter flow cytometric analysis of ovine leukocytes. The discussed approaches will be applicable to the analysis of cells from most animal species and include direct modification of antibodies by covalent conjugation or Fc-directed labeling (Zenon™ technology), labeled secondary antibodies and other second step reagents, labeled receptor ligands, and antibodies with species cross-reactivity. Conclusions: Using refined technical approaches, the number of parameters analyzed by flow cytometry per cell sample can be greatly increased, enabling multidimensional analysis of rare samples and giving critical insight into veterinary and other less commonly analyzed species. By maximizing information from each cell sample, multicolor flow cytometry can reduce the required number of animals used in a study. [ABSTRACT FROM AUTHOR]

Background: Splenic marginal zone lymphoma (SMZL) is a low-grade disorder that regularly presents with peripheral blood (PB) involvement. A precise description of clinical, laboratory features and immunophenotypic characterization of SMZL are still lacking. Here, we reviewed 34 patients presenting with SMZL to describe the clinical, hematologic features, and flow cytometry immunophenotypic findings of this type of lymphoma at diagnosis. Objectives: The aim of this study is to confirm that SMZL has a specific immunologic profile which enables the hematopathologist and clinician to differentiate this low-grade B-cell lymphoma from other B-cell lymphoproliferative disorder, especially chronic lymphocytic leukemia and hairy cell leukemia, which could sometimes stimulate SMZL morphologically and to emphasize that a correlation of immunophenotypic findings, clinical, and hematologic features of patients plus careful morphological examination of PB and/or bone marrow (BM) aspirate can lead confidently to the correct diagnosis. Materials And Methods: Flow cytometry immunophenotypic findings of 34 cases of SMZL were reviewed. The analysis was performed by BD FACS Calibur™ and FACSCanto II flow cytometers. B lymphocytes were identified according to their Side-Scattered (SSC)/CD19 distribution. A marker was considered positive when expressed in more than 20% of cells above the control. Results: Median age was 60 years, range (35–84 years), both sexes were affected equally. All patients presented with splenomegaly, 71% of patients had absolute lymphocytosis and 88% of patients showed PB involvement. Seventy-four percent of patients had anemia and (53%) of them had thrombocytopenia. Cells from all cases expressed pan B-cell antigens (CD19, CD20), 74% of cases expressed CD79b and Human Leukocyte Antigen – antigen D Related (HLA-DR) expressed in nearly almost all cases (97%). Half of the patients expressed CD11c and SIgD, 41% expressed CD5 and FMC7 while CD25 and CD103 showed positivity in less than 5% of cases. Preferential expression of Kappa light chain was demonstrated, CD10 and CD38, SIgG were negative. Conclusion: SMZL has a distinct immunologic profile which if correlated with morphologic findings of PB or BM aspirates, clinical and hematologic features can help to make the accurate diagnosis and lessens the need of further invasive diagnostic procedure.

Rationale : Multimodal imaging provides important pharmacokinetic and dosimetry information during nanomedicine development and optimization. However, accurate quantitation is time-consuming, resource intensive, and requires anatomical expertise. Methods : We present NanoMASK: a 3D U-Net adapted deep learning tool capable of rapid, automatic organ segmentation of multimodal imaging data that can output key clinical dosimetry metrics without manual intervention. This model was trained on 355 manually-contoured PET/CT data volumes of mice injected with a variety of nanomaterials and imaged over 48 hours. Results : NanoMASK produced 3-dimensional contours of the heart, lungs, liver, spleen, kidneys, and tumor with high volumetric accuracy (pan-organ average %DSC of 92.5). Pharmacokinetic metrics including %ID/cc, %ID, and SUV max achieved correlation coefficients exceeding R = 0.987 and relative mean errors below 0.2%. NanoMASK was applied to novel datasets of lipid nanoparticles and antibody-drug conjugates with a minimal drop in accuracy, illustrating its generalizability to different classes of nanomedicines. Furthermore, 20 additional auto-segmentation models were developed using training data subsets based on image modality, experimental imaging timepoint, and tumor status. These were used to explore the fundamental biases and dependencies of auto-segmentation models built on a 3D U-Net architecture, revealing significant differential impacts on organ segmentation accuracy. Conclusions : NanoMASK is an easy-to-use, adaptable tool for improving accuracy and throughput in imaging-based pharmacokinetic studies of nanomedicine. It has been made publicly available to all readers for automatic segmentation and pharmacokinetic analysis across a diverse array of nanoparticles, expediting agent development., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

The human primed pluripotent state is maintained by a complex balance of several signaling pathways governing pluripotency maintenance and commitment. Here, we explore a multiparameter approach using a full factorial design and a simple well-defined culture system to assess individual and synergistic contributions of Wnt, FGF and TGFβ signaling to pluripotency and lineage specification of human induced pluripotent stem cells (hiPSC). Hierarchical clustering and quadratic models highlighted a dominant effect of Wnt signaling over FGF and TGFβ signaling, drawing hiPSCs towards mesendoderm lineages. In addition, a synergistic effect between Wnt signaling and FGF was observed to have a negative contribution to pluripotency maintenance and a positive contribution to ectoderm and mesoderm commitment. Furthermore, FGF and TGFβ signaling only contributed significantly for negative ectoderm scores, suggesting that the effect of both factors for pluripotency maintenance resides in a balance of inhibitory signals instead of proactive stimulation of hiPSC pluripotency. Overall, our dry-signaling multiparameter modeling approach can contribute to elucidate individual and synergistic inputs, providing an additional degree of comprehension of the complex regulatory mechanisms of human pluripotency and commitment. [ABSTRACT FROM AUTHOR]