A novel bearing current signal diagnosis method combining variational modal decomposition and improved random forests.

A new fault diagnosis approach based on bearing current signals is proposed in this paper. First, in view of strong background noise of the current signal, the variational modal decomposition method is applied to decompose the bearing current signal to obtain multiple intrinsic mode functions, and then the intrinsic mode functions are constructed as the input feature vector according to the kurtosis. Second, to avoid the influence of random forest parameters on the random forest classifier, a random forest faulty bearing diagnostic model optimized by the whale algorithm is established. Finally, the accuracy rate and confusion matrix are adopted to evaluate the prediction effects of both established and traditional models. The classification accuracy of the real damaged bearing fault type can reach 95.11%. The fault diagnosis accuracy of manually damaged bearings can reach 93.83%. The results show that the method proposed in this paper has high accuracy and good generalization ability for bearing fault diagnosis.

Analysis of serum metabolome of laborers exposure to welding fume.

OBJECTIVE: Welding fume exposure is inevitable of welding workers and poses a severe hazard to their health since welding is a necessary industrial process. Thus, preclinical diagnostic symptoms of worker exposure are of great importance. The aim of this study was to screen serum differential metabolites of welding fume exposure based on UPLC-QTOF-MS/MS. METHODS: In 2019, 49 participants were recruited at a machinery manufacturing factory. The non-target metabolomics technique was used to clarify serum metabolic signatures in people exposed to welding fume. Differential metabolites were screened by OPLS-DA analysis and Student's t-test. The receiver operating characteristic curve evaluated the discriminatory power of differential metabolites. And the correlations between differential metabolites and metal concentrations in urine and whole blood were analyzed utilizing Pearson correlation analysis. RESULTS: Thirty metabolites were increased significantly, and 5 metabolites were decreased. The differential metabolites are mainly enriched in the metabolism of arachidonic acid, glycero phospholipid, linoleic acid, and thiamine. These results observed that lysophosphatidylcholine (20:1/0:0) and phosphatidylglycerol(PGF1α/16:0) had a tremendous anticipating power with relatively increased AUC values (AUC > 0.9), and they also presented a significant correlation of Mo concentrations in whole blood and Cu concentrations in urine, respectively. CONCLUSION: The serum metabolism was changed significantly after exposure to welding fume. Lysophosphatidylcholine (20:1/0:0) and phosphatidylglycerol (PGF1α/16:0) may be a potential biological mediator and biomarker for laborers exposure to welding fume.

Challenges and perspectives of multi-virus biosensing techniques: A review.

In the context of globalization, individuals have an increased chance of being infected by multiple viruses simultaneously, thereby highlighting the importance of developing multiplexed devices. In addition to sufficient sensitivity and rapid response, multi-virus sensing techniques are expected to offer additional advantages including high throughput, one-time sampling for parallel analysis, and full automation with data visualization. In this paper, we review the optical, electrochemical, and mechanical platforms that enable multi-virus biosensing. The working mechanisms of each platform, including the detection principle, transducer configuration, bio-interface design, and detected signals, are reviewed. The advantages and limitations, as well as the challenges in implementing various detection strategies in real-life scenarios, were evaluated. Future perspectives on multiplexed biosensing techniques are critically discussed. Earlier access to multi-virus biosensors will efficiently serve for immediate pandemic control, such as in emerging SARS-CoV-2 and monkeypox cases.

A high-throughput fully automatic biosensing platform for efficient COVID-19 detection.

We propose a label-free biosensor based on a porous silicon resonant microcavity and localized surface plasmon resonance. The biosensor detects SARS-CoV-2 antigen based on engineered trimeric angiotensin converting enzyme-2 binding protein, which is conserved across different variants. Robotic arms run the detection process including sample loading, incubation, sensor surface rinsing, and optical measurements using a portable spectrometer. Both the biosensor and the optical measurement system are readily scalable to accommodate testing a wide range of sample numbers. The limit of detection is 100 TCID50/ml. The detection time is 5 min, and the throughput of one single robotic site is up to 384 specimens in 30 min. The measurement interface requires little training, has standard operation, and therefore is suitable for widespread use in rapid and onsite COVID-19 screening or surveillance.

Biosensors for waterborne virus detection: Challenges and strategies.

Waterborne viruses that can be harmful to human health pose significant challenges globally, affecting health care systems and the economy. Identifying these waterborne pathogens is essential for preventing diseases and protecting public health. However, handling complex samples such as human and wastewater can be challenging due to their dynamic and complex composition and the ultralow concentration of target analytes. This review presents a comprehensive overview of the latest breakthroughs in waterborne virus biosensors. It begins by highlighting several promising strategies that enhance the sensing performance of optical and electrochemical biosensors in human samples. These strategies include optimizing bioreceptor selection, transduction elements, signal amplification, and integrated sensing systems. Furthermore, the insights gained from biosensing waterborne viruses in human samples are applied to improve biosensing in wastewater, with a particular focus on sampling and sample pretreatment due to the dispersion characteristics of waterborne viruses in wastewater. This review suggests that implementing a comprehensive system that integrates the entire waterborne virus detection process with high-accuracy analysis could enhance virus monitoring. These findings provide valuable insights for improving the effectiveness of waterborne virus detection, which could have significant implications for public health and environmental management.

A Closed-Loop Approach to Fight Coronavirus: Early Detection and Subsequent Treatment.

The recent COVID-19 pandemic has caused tremendous damage to the social economy and people's health. Some major issues fighting COVID-19 include early and accurate diagnosis and the shortage of ventilator machines for critical patients. In this manuscript, we describe a novel solution to deal with COVID-19: portable biosensing and wearable photoacoustic imaging for early and accurate diagnosis of infection and magnetic neuromodulation or minimally invasive electrical stimulation to replace traditional ventilation. The solution is a closed-loop system in that the three modules are integrated together and form a loop to cover all-phase strategies for fighting COVID-19. The proposed technique can guarantee ubiquitous and onsite detection, and an electrical hypoglossal stimulator can be more effective in helping severe patients and reducing complications caused by ventilators.

Label-Free LSPR-Vertical Microcavity Biosensor for On-Site SARS-CoV-2 Detection.

Cost-effective, rapid, and sensitive detection of SARS-CoV-2, in high-throughput, is crucial in controlling the COVID-19 epidemic. In this study, we proposed a vertical microcavity and localized surface plasmon resonance hybrid biosensor for SARS-CoV-2 detection in artificial saliva and assessed its efficacy. The proposed biosensor monitors the valley shifts in the reflectance spectrum, as induced by changes in the refractive index within the proximity of the sensor surface. A low-cost and fast method was developed to form nanoporous gold (NPG) with different surface morphologies on the vertical microcavity wafer, followed by immobilization with the SARS-CoV-2 antibody for capturing the virus. Modeling and simulation were conducted to optimize the microcavity structure and the NPG parameters. Simulation results revealed that NPG-deposited sensors performed better in resonance quality and in sensitivity compared to gold-deposited and pure microcavity sensors. The experiment confirmed the effect of NPG surface morphology on the biosensor sensitivity as demonstrated by simulation. Pre-clinical validation revealed that 40% porosity led to the highest sensitivity for SARS-CoV-2 pseudovirus at 319 copies/mL in artificial saliva. The proposed automatic biosensing system delivered the results of 100 samples within 30 min, demonstrating its potential for on-site coronavirus detection with sufficient sensitivity.

Energy Solutions for Wearable Sensors: A Review.

Wearable sensors have gained popularity over the years since they offer constant and real-time physiological information about the human body. Wearable sensors have been applied in a variety of ways in clinical settings to monitor health conditions. These technologies require energy sources to carry out their projected functionalities. In this paper, we review the main energy sources used to power wearable sensors. These energy sources include batteries, solar cells, biofuel cells, supercapacitors, thermoelectric generators, piezoelectric and triboelectric generators, and radio frequency (RF) energy harvesters. Additionally, we discuss wireless power transfer and some hybrids of the above technologies. The advantages and drawbacks of each technology are considered along with the system components and attributes that make these devices function effectively. The objective of this review is to inform researchers about the latest developments in this field and present future research opportunities.

Prevalence and relevant factors of halitosis in Chinese subjects: a clinical research.

BACKGROUND: The aim of this study was to investigate the prevalence of halitosis among Chinese subjects and to analyze the associated factors that influence halitosis. METHODS: This study included subjects complaining of halitosis who came to the clinic between 2014 and 2016. Questionnaires were used to obtain general information from patients. An organoleptic test was conducted, and volatile sulfur compounds measurement was obtained to assess halitosis. In conjunction with these tests, the oral health status of each patient was recorded. RESULTS: In total, there were 205 samples entered into data analysis, and the patients' age ranged from 18 to 71 years (mean ± SD: 32.44 ± 10.31). Of these patients, 65.9% had an organoleptic score ≥ 2, and 41% of patients had a volatile sulfur compound level ≥ 110 ppb. The findings indicated that the prevalence of halitosis was higher in males than in females (55.6% vs. 44.4%, respectively, P = 0.018). Several factors including the duration of bad breath, rhinitis, tongue coating and periodontal conditions were found to be associated with the organoleptic score. Tongue coating was also associated with the volatile sulfur compound level. CONCLUSIONS: Among these subjects, 65.9% had halitosis. Oral health status was strongly associated with halitosis, and tongue coating was the most important factor.

Comparative Analysis of the Microbial Profiles in Supragingival Plaque Samples Obtained From Twins With Discordant Caries Phenotypes and Their Mothers.

Early childhood caries (ECC), the most frequent disease of oral cavity in preschool children, is the consequence of microbial, genetic, biochemical, socioeconomic, physical, environmental and health-influencing behavioral factors. To investigate the role of the oral microbiome and the impact of host and environmental factors in the occurrence and development of ECC, we studied the supragingival plaques of 14 twin pairs and a set of triplets with discordant caries phenotypes and 15 mothers, applying the Human Oral Microbe Identification using Next Generation Sequencing technique (HOMINGS). A total of 2,293,650 reads revealed 11 phyla, 116 genera, and 139 species of micromiome. Comparative analysis between the caries and caries-free group at species level revealed that the relative abundance of Streptococcus mutans, Lactobacillus fermentum, Actinomyces islaelii, Neisseria sica, and Veilonella dispar was much higher in caries group (P < 0.0001). Furthermore, monozygotic twins exhibited a higher degree of similarity than dizygotic twins. Finally, we analyzed the relationship between environmental factors and the oral microbiome, and our results indicat that the frequency of taking sweet food is associated with ECC. We conclude the following. First, the occurrence of Streptococcus mutans, Lactobacillus fermentum, Neisseria sica, and Veilonella dispar is strongly associated with the occurrence of ECC. Second, host genetic factors influence the oral microbiome composition, while environmental and behavioral factors like the frequency of taking sweet foods have an impact on the distribution of caries-related bacteria.

Acid-resistant genes of oral plaque microbiome from the functional metagenomics.

Acid resistance is one of key properties assisting the survival of cariogenic bacteria in a dental caries environment, but only a few genes conferring acid resistance have been identified to data. Functional metagenomics provides a systematic method for investigating commensal DNA to identify genes that encode target functions. Here, the host strain Escherichia coli DH10B and a constructed bidirectional transcription vector pSKII+-lacZ contributed to the construction of a metagenomic library, and 46.6 Mb of metagenomic DNA was cloned from carious supragingival plaque of 8children along with screening for lethal functionality. The screen identified 2 positive clones that exhibited a similar aciduric phenotype to that of the positive controls. Bioinformatic analysis revealed that these two genes encoded an ATP/GTP-binding protein and a malate dehydrogenase. Moreover, we also performed functional screening of Streptococcus mutans, since it is one of the predominant cariogenic strains but was not identified in our initial screening. Five positive clones were retrieved. In conclusion, our improved functional metagenomics screening method helped in the identification of important acid resistance genes, thereby providing new insights into the mechanism underlying caries formation as well as in the prevention and treatment of early childhood caries (ECC).