Sensitive Dual-Signal ELISA Based on Specific Phage-Displayed Double Peptide Probes with Internal Filtering Effect to Assay Monkeypox Virus Antigen.

The global spread of monkeypox has become a worldwide public healthcare issue. Therefore, there is an urgent need for accurate and sensitive detection methods to effectively control its spreading. Herein, we screened by phage display two peptides M4 (sequence: DPCGERICSIAL) and M6 (sequence: SCSSFLCSLKVG) with good affinity and specificity to monkeypox virus (MPXV) B21R protein. To simulate the state of the peptide in the phage and to avoid spatial obstacles of the peptide, GGGSK was added at the C terminus of M4 and named as M4a. Molecular docking shows that peptide M4a and peptide M6 are bound to different epitopes of B21R by hydrogen bonds and salt-bridge interactions, respectively. Then, peptide M4a was selected as the capture probe, phage M6 as the detection probe, and carbonized polymer dots (CPDs) as the fluorescent probe, and a colorimetric and fluorescent double-signal capture peptide/antigen/signal peptide-displayed phage sandwich ELISA triggered by horseradish peroxidase (HRP) through a simple internal filtration effect (IFE) was constructed. HRP catalyzes H2O2 to oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to generate blue oxidized TMB, which can further quench the fluorescence of CPDs through IFE, enabling to detect MPXV B21R in colorimetric and fluorescent modes. The proposed simple immunoassay platform shows good sensitivity and reliability in MPXV B21R detection. The limit of detection for colorimetric and fluorescent modes was 27.8 and 9.14 pg/mL MPXV B21R, respectively. Thus, the established double-peptide sandwich-based dual-signal immunoassay provides guidance for the development of reliable and sensitive antigen detection capable of mutual confirmation, which also has great potential for exploring various analytical strategies for other respiratory virus surveillance.

Meta-analysis of microbial source tracking for the identification of fecal contamination in aquatic environments based on data-mining.

Microbial source tracking (MST) technology represents an innovative approach employed to trace fecal contamination in environmental water systems. The performance of primers may be affected by amplification techniques, target primer categories, and regional differences. To investigate the influence of these factors on primer recognition performance, a meta-analysis was conducted on the application of MST in water environments using three databases: Web of Science, Scopus, and PubMed (n = 2291). After data screening, 46 studies were included in the final analysis. The investigation encompassed Polymerase Chain Reaction (PCR)/quantitative PCR (qPCR) methodologies, dye-based (SYBR)/probe-based (TaqMan) techniques, and geographical differences of a human host-specific (HF183) primer and other 21 additional primers. The results indicated that the primers analyzed were capable of differentiating host specificity to a certain degree. Nonetheless, by comparing sensitivity and specificity outcomes, it was observed that virus-based primers exhibited superior specificity and recognition capacity, as well as a stronger correlation with human pathogenicity in water environments compared to bacteria-based primers. This finding highlights an important direction for future advancements. Moreover, within the same category, qPCR did not demonstrate significant benefits over conventional PCR amplification methods. In comparing dye-based and probe-based techniques, it was revealed that the probe-based method's advantage lay primarily in specificity, which may be associated with the increased propensity of dye-based methods to produce false positives. Furthermore, the heterogeneity of the HF183 primer was not detected in China, Canada, and Singapore respectively, indicating a low likelihood of regional differences. The variation among the 21 other primers may be attributable to regional differences, sample sources, detection techniques, or alternative factors. Finally, we identified that economic factors, climatic conditions, and geographical distribution significantly influence primer performance.

Salvianolic acid B ameliorates neuroinflammation and neuronal injury via blocking NLRP3 inflammasome and promoting SIRT1 in experimental subarachnoid hemorrhage.

The nucleotide-binding oligomerization domain (NOD)-like receptor family pyrin domain containing 3 (NLRP3) inflammasome-mediated immuno-inflammatory response plays a critical role in exacerbating early brain injury (EBI) after subarachnoid hemorrhage (SAH). Salvianolic acid B (SalB) has previously been shown to suppress neuroinflammatory responses in many disorders. Meanwhile, a previous study has demonstrated that SalB mitigated oxidative damage and neuronal degeneration in a prechiasmatic injection model of SAH. However, the therapeutic potential of SalB on immuno-inflammatory responses after SAH remains unclear. In the present study, we explored the therapeutic effects of SalB on neuroinflammatory responses in an endovascular perforation SAH model. We observed that SalB ameliorated SAH-induced functional deficits. Additionally, SalB significantly mitigated microglial activation, pro-inflammatory cytokines release, and neuronal injury. Mechanistically, SalB inhibited NLRP3 inflammasome activation and increased sirtuin 1 (SIRT1) expression after SAH. Administration of EX527, an inhibitor of SIRT1, abrogated the anti-inflammatory effects of SalB against SAH and further induced NLRP3 inflammasome activation. In contrast, MCC950, a potent and selective NLRP3 inflammasome inhibitor, reversed the detrimental effects of SIRT1 inhibition by EX527 on EBI. These results indicated that SalB effectively repressed neuroinflammatory responses and neuronal damage after SAH. The action of SalB appeared to be mediated by blocking NLRP3 inflammasome and promoting SIRT1 signaling.

Sensitive Lateral Flow Immunoassay Based on Specific Peptide and Superior Oxidase Mimics with a Universal Dual-Mode Significant Signal Amplification.

Rapid and sensitive antigen detection using a lateral flow immunoassay (LFIA) is crucial for diagnosing infectious diseases due to its simplicity, speed, and user-friendly features. However, it remains a critical issue to explore specific biorecognition elements and powerful signal amplification. In this study, taking SARS-CoV-2 as a proof of concept, a specific peptide, WFLNDSELIML, binding to the SARS-CoV-2 spike (S) antigen was identified by a nonamplified biopanning method, which exhibited high affinity to the target, with a dissociation constant of 9.29 ± 1.55 nM. Molecular docking analysis reveals that this peptide binds to the N-terminal domain of the SARS-CoV-2 S antigen. Then, using this peptide as a capture probe and angiotensin-converting enzyme 2 as a detection probe, a peptide-based lateral flow immunoassay (pLFIA) for the sensitive detection of the SARS-CoV-2 S antigen without any antibody was developed, for which a polydopamine nanosphere (PDA)@MnO2 nanocomposite with excellent oxidase-like activity was used as a colorimetric label, exhibiting dual-mode remarkable signal amplification of natural melanin and on-demand nanozyme catalytic enhancement. The PDA@MnO2-based pLFIA is capable of detecting the SARS-CoV-2 S antigen with a limit of detection of 8.01 pg/mL, which is 18.7 times lower than that of a conventional pLFIA tagged with gold nanoparticles. Additionally, the as-proposed PDA@MnO2-based pLFIA can detect up to 150 transduction units/mL SARS-CoV-2 pseudoviruses spiked in saliva samples. Given the outstanding analytical performance, the proposed PDA@MnO2-based pLFIA may offer a reliable option for the rapid diagnosis of SARS-CoV-2.

Unilateral sublingual nerve paralysis after laryngeal mask airway in a patient with congenital heart disease: a case report.

Laryngeal masks are widely used by anesthesiologists in clinical practice because of their advantages of no tracheal injury, minimal airway stimulation, limited airway tissue invasion, and easy implantation and airway establishment. We herein describe a patient with congenital heart disease who developed unilateral sublingual nerve paralysis after application of a laryngeal mask airway. The patient reported perioral numbness and exhibited unclear speech and slight right deviation of the tip of the tongue after surgery. On physical examination, the patient had normal muscle strength, symmetrical frontal lines, normal occlusion, and a normal nasolabial groove. We performed head computed tomography and computed tomography angiography to rule out cerebrovascular disease, and no abnormalities were found. The patient's imaging findings and clinical symptoms suggested unilateral right sublingual nerve palsy. After active treatment, the patient's symptoms improved by 75% on the third postoperative day and by 90% on the fifth postoperative day. Despite the extremely low incidence of sublingual nerve palsy after application of a laryngeal mask airway, anesthesiologists should be aware of this complication. Although the nerve palsy can resolve spontaneously, the nerve damage may be permanent.

Machine Learning Using Presentation CT Perfusion Imaging for Predicting Clinical Outcomes in Patients With Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND. Prediction of outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) is challenging using current clinical predictors. OBJECTIVE. The purpose of our study was to evaluate the utility of machine learning (ML) models incorporating presentation clinical and CT perfusion imaging (CTP) data in predicting delayed cerebral ischemia (DCI) and poor functional outcome in patients with aSAH. METHODS. This study entailed retrospective analysis of data from 242 patients (mean age, 60.9 ± 11.8 [SD] years; 165 women, 77 men) with aSAH who, as part of a prospective trial, underwent CTP followed by standardized evaluation for DCI during initial hospitalization and poor 3-month functional outcome (i.e., modified Rankin scale score ≥ 4). Patients were randomly divided into training (n = 194) and test (n = 48) sets. Five ML models (k-nearest neighbor [KNN], logistic regression [LR], support vector machine [SVM], random forest [RF], and category boosting [CatBoost]) were developed for predicting outcomes using presentation clinical and CTP data. The least absolute shrinkage and selection operator method was used for feature selection. Ten-fold cross-validation was performed in the training set. Traditional clinical models were developed using stepwise LR analysis of clinical, but not CTP, data. RESULTS. Qualitative CTP analysis was identified as the most impactful feature for both outcomes. In the test set, the traditional clinical model, KNN, LR, SVM, RF, and CatBoost showed AUC for predicting DCI of 0.771, 0.812, 0.824, 0.908, 0.930, and 0.949, respectively, and AUC for predicting poor 3-month functional outcome of 0.863, 0.858, 0.879, 0.908, 0.926, and 0.958. CatBoost was selected as the optimal model. In the test set, AUC was higher for CatBoost than for the traditional clinical model for predicting DCI (p = .004) and poor 3-month functional outcome (p = .04). In the test set, sensitivity and specificity for predicting DCI were 92.3% and 60.0% for the traditional clinical model versus 92.3% and 85.7% for CatBoost, and sensitivity and specificity for predicting poor 3-month functional outcome were 100.0% and 65.8% for the traditional clinical model versus 90.0% and 94.7% for CatBoost. A web-based prediction tool based on CatBoost was created. CONCLUSION. ML models incorporating presentation clinical and CTP data outperformed traditional clinical models in predicting DCI and poor 3-month functional outcome. CLINICAL IMPACT. ML models may help guide early management of patients with aSAH.

Stratospheric aerosol lidar with a 300†µm diameter superconducting nanowire single-photon detector at 1064†nm.

Stratospheric aerosols play an important role in the atmospheric chemical and radiative balance. To detect the stratospheric aerosol layer, a 1064 nm lidar with high resolution and large dynamic range is developed using a superconducting nanowire single-photon detector (SNSPD). Measurements are typically performed at 1064 nm for its sensitivity to aerosol, whereas detectors are limited by low efficiency and high dark count rate (DCR). SNSPDs are characterized by high efficiency in the infrared wavelength domain, as well as low noise and dead time, which can significantly enhance the signal quality. However, it is still challenging to build an SNSPD with both large active area and high count rate. To improve the maximal count rate (MCR) so as to avoid saturation in the near range, a 16-pixel interleaved SNSPD array and a multichannel data acquisition system are developed. As a reference, a synchronous system working at 532 nm is applied. In a continuous comparison experiment, backscatter ratio profiles are retrieved with resolutions of 90 m/3 min, and the 1064 nm system shows better performance, which is sensitive to aerosols and immune to the contamination of the ozone absorption and density of molecule change in the lower stratosphere.

A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.

An IA is an abnormal swelling of cerebral vessels, and a subset of these IAs can rupture causing aneurysmal subarachnoid hemorrhage (aSAH), often resulting in death or severe disability. Few studies have used an appropriate method of feature selection combined with machine learning by analyzing transcriptomic sequencing data to identify new molecular biomarkers. Following gene ontology (GO) and enrichment analysis, we found that the distinct status of IAs could lead to differential innate immune responses using all 913 differentially expressed genes, and considering that there are numerous irrelevant and redundant genes, we propose a mixed filter- and wrapper-based feature selection. First, we used the Fast Correlation-Based Filter (FCBF) algorithm to filter a large number of irrelevant and redundant genes in the raw dataset, and then used the wrapper feature selection method based on the he Multi-layer Perceptron (MLP) neural network and the Particle Swarm Optimization (PSO), accuracy (ACC) and mean square error (MSE) were then used as the evaluation criteria. Finally, we constructed a novel 10-gene signature (YIPF1, RAB32, WDR62, ANPEP, LRRCC1, AADAC, GZMK, WBP2NL, PBX1, and TOR1B) by the proposed two-stage hybrid algorithm FCBF-MLP-PSO and used different machine learning models to predict the rupture status in IAs. The highest ACC value increased from 0.817 to 0.919 (12.5% increase), the highest area under ROC curve (AUC) value increased from 0.87 to 0.94 (8.0% increase), and all evaluation metrics improved by approximately 10% after being processed by our proposed gene selection algorithm. Therefore, these 10 informative genes used to predict rupture status of IAs can be used as complements to imaging examinations in the clinic, meanwhile, this selected gene signature also provides new targets and approaches for the treatment of ruptured IAs.

Suppression of crosstalk in coding CDWL by active FOV modulation with a deformable mirror.

Coding technology provides new ideas for spatial resolution enhancement of coherent Doppler wind lidar (CDWL). To improve the performance of coding CDWL for ultra-fine-wind field detection, the crosstalk between neighboring laser pulses is analyzed in theory. The strong backscattered signal from aerosols in near field region will interfere with the weak atmospheric signal, making the accuracy of Doppler shift estimation deteriorate seriously. Considering the formation mechanism of crosstalk, a solution based on adaptive field of view (FOV) modulation is proposed to suppress the crosstalk which is validated by numerical simulation and experiment. Dynamic range of the backscatter intensity is controlled from 10 dB to 2 dB within the distance of 50 m to 300 m, thus the crosstalk is accordingly suppressed.

Comparison of Enterprise stent 2 with 1 in assisting coiling of ruptured aneurysms: a real-world study.

Aim: To investigate the effectiveness and safety of the Enterprise 2 (E2) stent versus the Enterprise 1 (E1) stent in treating ruptured intracranial aneurysms (RIAs) in China. Materials & methods: The authors conducted an electronic medical record analysis for patients with RIAs who underwent E1/E2 deployment. The main outcomes were immediate complete occlusion (ICO), patient functional outcomes, complications and aneurysm recurrence. Results: Stent deployment was successful in all patients (E2: 90; E1: 270). ICO and patients with good functional outcomes at discharge were similar between E2 and E1 (80.0% vs 75.1% and 78.7% vs 81.1%, respectively). The E2 group had a significantly lower complication rate compared with the E1 group (7.8% vs 16.4%; odds ratio: 0.36; 95% CI: 0.15-0.91; p = 0.031). By 6 months post-discharge, the two groups had comparable patient functional outcomes and aneurysm recurrence (E2 vs E1: 80.2% vs 81.9% and 13.3% vs 14.9%). Conclusion: Compared with the E1 stent, the E2 stent had similar effectiveness but a lower complication risk in treating RIAs.

Effect of sodium hypochlorite on biofilm of Klebsiella pneumoniae with different drug resistance.

BACKGROUND: Biofilm formation is a major factor in the resistance mechanism of Klebsiella pneumoniae. This study aimed to evaluate the effects of sodium hypochlorite on the biofilm of K. pneumoniae with different drug resistance. METHODS: We collected 3 different types of K. pneumoniae respectively. The growth trend of biofilms of different drug-resistant K. pneumoniae was quantified by measuring the OD590 for 7 consecutive days using crystal violet staining. Scanning confocal fluorescence microscopy was used to observe biofilm morphology. RESULTS: After adding sodium hypochlorite, there were significant differences between the OD590 value of the 200, 500, and 1,000 µg/mL groups and the positive control group (all P < .05) on the fifth day. Concentrations of 2,000 and 5,000 µg/mL sodium hypochlorite were added after the biofilm had matured. In the 5,000 µg/mL sodium hypochlorite group, the OD590 of K. pneumoniae biofilm in the 3 groups decreased significantly compared with the blank control group (all P < .05). CONCLUSIONS: Sodium hypochlorite inhibited and cleared the biofilm of K. pneumoniae with different drug resistance, and the effect was enhanced with the increase of concentration in the range of bacteriostatic and bactericidal concentration.

SIRT1 Promotes M2 Microglia Polarization via Reducing ROS-Mediated NLRP3 Inflammasome Signaling After Subarachnoid Hemorrhage.

Mounting evidence has suggested that modulating microglia polarization from pro-inflammatory M1 phenotype to anti-inflammatory M2 state might be a potential therapeutic approach in the treatment of subarachnoid hemorrhage (SAH) injury. Our previous study has indicated that sirtuin 1 (SIRT1) could ameliorate early brain injury (EBI) in SAH by reducing oxidative damage and neuroinflammation. However, the effects of SIRT1 on microglial polarization and the underlying molecular mechanisms after SAH have not been fully illustrated. In the present study, we first observed that EX527, a potent selective SIRT1 inhibitor, enhanced microglial M1 polarization and nod-like receptor pyrin domain-containing 3 (NLRP3) inflammasome activation in microglia after SAH. Administration of SRT1720, an agonist of SIRT1, significantly enhanced SIRT1 expression, improved functional recovery, and ameliorated brain edema and neuronal death after SAH. Moreover, SRT1720 modulated the microglia polarization shift from the M1 phenotype and skewed toward the M2 phenotype. Additionally, SRT1720 significantly decreased acetylation of forkhead box protein O1, inhibited the overproduction of reactive oxygen species (ROS) and suppressed NLRP3 inflammasome signaling. In contrast, EX527 abated the upregulation of SIRT1 and reversed the inhibitory effects of SRT1720 on ROS-NLRP3 inflammasome activation and EBI. Similarly, in vitro, SRT1720 suppressed inflammatory response, oxidative damage, and neuronal degeneration, and improved cell viability in neurons and microglia co-culture system. These effects were associated with the suppression of ROS-NLRP3 inflammasome and stimulation of SIRT1 signaling, which could be abated by EX527. Altogether, these findings indicate that SRT1720, an SIRT1 agonist, can ameliorate EBI after SAH by shifting the microglial phenotype toward M2 via modulation of ROS-mediated NLRP3 inflammasome signaling.

Hemodynamic Characteristics Associated with Recurrence of Middle Cerebral Artery Bifurcation Aneurysms After Total Embolization.

OBJECTIVE: Hemodynamic parameters are associated with the recurrence of intracranial aneurysms (IAs). Studies showed that high velocity and wall shear stress (WSS) were associated with IAs recurrence after endovascular treatment; nevertheless, factors such as small sample size, locations of IAs, and types of IAs (ie, sidewall or bifurcation) were neglected. The purpose of this study was to identify the hemodynamic characteristics associated with recurrence of middle cerebral artery bifurcation aneurysms (MCABAs) after total embolization by the method of computer fluid dynamics (CFD). METHODS: Following inclusion criteria, we included 92 MCABAs treated with coils only after total embolization from January 2014 to January 2019. We segmented into recurrent and non-recurrent groups according to follow-up digital subtraction angiography (DSA). The MCABA models, including pre-operatively and immediate post-operatively, were reconstructed using 3D-DSAs. The hemodynamic parameters pre-operatively and immediately post-operatively between the groups were calculated and analyzed. RESULTS: There were no significant differences between the recurrent and non-recurrent groups for spatially averaged wall shear stress (SAWSS), maximum wall shear stress (MWSS), velocity, or oscillatory shear index (OSI) at the neck pre-operatively. In the recurrent group, the WSS (22.02±5.11 vs 37.43±8.27 pa, p < 0.001), MWSS (42.59±17.02 vs 66.98±18.61 pa, p=0.014), velocity (0.86±0.19 vs 1.44±0.61 m/s, p=0.01) preoperatively were significantly higher than postoperative values. By contrast, in the non-recurrent group, the WSS (26.53±8.18 vs 22.29±8.64pa, p=0.002), MWSS (42.71±14.01 vs 37.15±15.56 pa, p=0.013), velocity (1.08±0.43 vs 0.23 (0.52, 0.57) m/s, p < 0.001) postoperatively were significantly lower than preoperative values. The OSI, whether in the recurrent group or the non-recurrent group, did not differ significantly between groups (p=0.79 and p=0.19). CONCLUSION: Higher WSS (SAWSS, MWSS) and flow velocity at the aneurysm neck after embolization might be related to recurrence of bifurcation IAs. These might be applied to clinical post-embolization management for the evaluation of bifurcation IAs recanalization.

Hemodynamic and Morphological Parameters of Ruptured Mirror Posterior Communicating Artery Aneurysms.

Objective: Morphological and hemodynamic parameters might predict rupture of intracranial aneurysms (IAs). A practical model for the study is patients with ruptured mirror IAs in which one is ruptured and the other is unruptured. Although there have been analyses of the morphology and hemodynamics of ruptured mirror posterior communicating artery aneurysms (PComAAs), the sample sizes in these studies were small and only considered hemodynamics or morphological characters. Therefore, this study aimed to investigate the morphological and hemodynamic parameters associated with ruptured mirror PComAAs. Methods: We considered 72 patients with ruptured mirror PComAAs using computational fluid dynamics (CFDs). Ruptured mirror PComAAs were divided into ruptured and unruptured groups. Fourteen morphological and eight hemodynamic parameters were calculated and compared. Significant parameters were analyzed by the multivariate logistic regression to identify independent risk factors. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curve (AUC) was calculated for all independent risk factors to determine the predictability and identify the optimal threshold. Results: Four hemodynamic and three morphological parameters were significantly different between ruptured and unruptured groups: normalized wall shear stress (NWSS), mean WSS, low wall shear WSS area (LSA%), size, aspect ratio (AR), size ratio (SR), and inflow angle (IA). Multivariate logistic regression analysis showed that AR, SR, NWSS, mean WSS, and LSA% were all independent factors significantly associated with PComAAs rupture. The ROC analysis for independent risk factors indicated that AR (0.751), NWSS (0.755), mean WSS (0.69), and LSA (0.778) had merely acceptable AUC values. Only SR (0.803) had a high acceptable AUC value. The threshold value of SR was 1.96. Conclusions: SR (>1.96) was the most significant parameter associated with IA rupture, whereas AR, NWSS, mean WSS, and LSA independently characterized the status of IA rupture.

Interleukin-6 in Cerebrospinal Fluid Small Extracellular Vesicles as a Potential Biomarker for Prognosis of Aneurysmal Subarachnoid Haemorrhage.

OBJECTIVE: Aneurysmal subarachnoid hemorrhage (aSAH) is a severe form of stroke characterized by high rates of mortality and disability. Identifying circulating biomarkers is helpful to improve outcomes. In this study, for the first time, we identify interleukin-6 (IL-6) in cerebrospinal fluid (CSF) small extracellular vesicles (sEVs) as potential biomarkers for prognosis of aSAH. METHODS: We extracted small extracellular vesicles from the CSF of 103 aSAH patients and 40 healthy controls in a prospective observational study. Subsequently, we measured IL-6sEVs levels using an enzyme-linked immunosorbent assay. Results were statistically analyzed to determine the function of IL-6sEVs for disease monitoring of aSAH. RESULTS: CSF IL-6 sEVs showed distinct pattern differences between healthy controls and aSAH patients. The concentration of IL-6sEVs in CSF is significantly correlated with the severity of aSAH patients. The areas under the receiver operating characteristic curves of IL-6sEVs for identifying severe aSAH patient from aSAH patients were 0.900. After multivariate logistic regression analysis, IL-6sEVs were associated with neurological outcome at 1 year. IL-6sEVs levels were greater and positively associated with disease processes and outcome. CONCLUSION: There is a neuroinflammatory cascade in aSAH patients. IL-6sEVs in CSF may be a biomarker for the progression of aSAH.

Robustness analysis and identification for an enzyme-catalytic complex metabolic network in batch culture.

Bioconversion of glycerol to 1,3-propanediol is a promising way to mitigate the shortage of energy. To maximize the production of 1,3-propanediol, it needs to control precisely microbial fermentation process. However, it might consume lots of human and material resources when conducting experimental tests many times. In this study, a nonlinear enzyme-catalytic dynamical system is developed to describe the bioconversion process of glycerol to 1,3-propanediol, especially continuous piecewise linear functions are used as identification parameters. The existence, uniqueness and continuity of solutions are also discussed. Then, considering the fact that the concentration of intracellular substances is difficult to measure in experiments, a new quantitative definition of biological robustness is introduced as a performance index to determine the identification parameters related to intracellular substances. Meanwhile, a two-phase optimization algorithm is constructed to solve the identification model. By comparison with the experimental data, it can be found that the present nonlinear dynamical system can describe the fermentation process very well. Finally, the present nonlinear dynamical system and the corresponding optimal identification parameters might be useful in future studies on the batch culture of glycerol to 1,3-propanediol.

Identifying cloud, precipitation, windshear, and turbulence by deep analysis of the power spectrum of coherent Doppler wind lidar.

Researches on the atmospheric boundary layer (ABL) need accurate measurements with high temporal and spatial resolutions from a series of different instruments. Here, a method for identifying cloud, precipitation, windshear, and turbulence in the ABL using a single coherent Doppler wind lidar (CDWL) is proposed and demonstrated. Based on deep analysis of the power spectrum of the backscattering signal, multiple lidar products, such as carrier-to-noise (CNR), spectrum width, spectrum skewness, turbulent kinetic energy dissipation rate (TKEDR), and shear intensity are derived for weather identification. Firstly, the cloud is extracted by Haar wavelet covariance transform (HWCT) algorithm based on the CNR after range correction. Secondly, since the spectrum broadening may be due to turbulence, windshear or precipitation, the spectrum skewness is introduced to distinguish the precipitation from two other conditions. Whereas wind velocity is obtained by single peak fitting in clear weather condition, the double-peak fitting is used to retrieve wind and rainfall velocities simultaneously in the precipitation condition. Thirdly, judging from shear intensity and TKEDR, turbulence and windshear are classified. As a double check, the temporal continuity is used. Stable wind variances conditions such as low-level jets are identified as windshear, while arbitrary wind variances conditions are categorized as turbulence. In the field experiment, the method is implemented on a micro-pulse CDWL to provide meteorological services for the 70th anniversary of the China's National Day, in Inner Mongolia, China (43°54'N, 115°58'E). All weather conditions are successfully classified. By comparing lidar results to that of microwave radiometer (MWR), the spectrum skewness is found be more accurate to indicate precipitation than spectrum width or vertical speed. Finally, the parameter relationships and distributions are analyzed statistically in different weather conditions.