Research on the Related Factors of the Second Molar Dislocation and Orthodontic Erect Method

The second molar dislocation is more common clinically.To investigate the related factors of the second permanent molar dislocation,and provide reference for the clinical diagnosis and treatment of orthodontics.From the current clinical research,the clinical methods of orthodontic erect secondary molars are also diverse and clinical.The narrower first molar alveolar arch width,smaller ANB angle,and crowded maxillary posterior segment arch are the factors that cause the maxillary second permanent molar dislocation.The narrow alveolar arch width,the smaller SNB angle,the larger ANB angle,and the crowded lower mandibular arch are the factors leading to the dislocation of the mandibular second permanent molar.In addition,for the second mandibular molar malposition,it is particularly important to select the corrective treatment plan.It is especially important to improve the treatment.

Artificial intelligence reinforced upconversion nanoparticle-based lateral flow assay via transfer learning

The combination of upconverting nanoparticles(UCNPs)and immunochromatography has become a widely used and promising new detection technique for point-of-care testing(POCT).However,their low luminescence efficiency,non-specific adsorption,and image noise have always limited their progress toward practical applications.Recently,artificial intelligence(AI)has demonstrated powerful representational learning and generalization capabilities in computer vision.We report for the first time a combination of AI and upconversion nanoparticle-based lateral flow assays(UCNP-LFAs)for the quantitative detection of commercial internet of things(IoT)devices.This universal UCNPs quantitative detection strategy combines high accuracy,sensitivity,and applicability in the field detection environment.By using transfer learning to train AI models in a small self-built database,we not only significantly improved the accuracy and robustness of quantitative detection,but also efficiently solved the actual problems of data scarcity and low computing power of POCT equipment.Then,the trained AI model was deployed in IoT devices,whereby the detection process does not require detailed data preprocessing to achieve real-time inference of quantitative results.We validated the quantitative detection of two detectors using eight transfer learning models on a small dataset.The AI quickly provided ultra-high accuracy prediction results(some models could reach 100%accuracy)even when strong noise was added.Simultaneously,the high flexibility of this strategy promises to be a general quantitative detection method for optical biosensors.We believe that this strategy and device have a scientific significance in revolutionizing the existing POCT technology landscape and providing excellent commercial value in the in vitro diagnostics(IVD)industry.

DropLab:an automated magnetic digital microfluidic platform for sample-to-answer point-of-care testing—development and application to quantitative immunodiagnostics

In point-of-care testing(POCT),tests are performed near patients and results are given rapidly for timely clinical decisions.Immunodiagnostic assays are one of the most important analyses for detecting and quantifying protein-based biomarkers.However,existing POCT immunodiagnostics mainly rely on the lateral flow assay(LFA),which has limited sensitivity or quantification capability.Although other immunodiagnostic assays,such as enzyme-linked immunosorbent assays(ELISAs),offer more sensitive and quantitative results,they require complex liquid manipulations that are difficult to implement in POCT settings by conventional means.Here,we show the development of DropLab,an automated sample-in-answer-out POCT immunodiagnostic platform based on magnetic digital microfluidic(MDM)technology.DropLab performs microbead-based ELISA in droplets to offer more sensitive and quantitative testing results.The intricate liquid manipulations required for ELISA are accomplished by controlling droplets with magnetic microbeads using MDM technology,which enables us to achieve full automation and easy operations with DropLab.Four ELISAs(the sample in triplicates and a negative control)can be run in parallel on the thermoformed disposable chip,which greatly improves the throughput and accuracy compared to those of other POCT immunodiagnostic devices.DropLab was validated by measuring two protein targets and one antibody target.The testing results showed that the limit of detection(LOD)of DropLab matched that of the conventional ELISA in a microwell plate.DropLab brings MDM one step closer to being a viable medical technology that is ready for real-world POCT applications.

Preparation and application of microfluidic SERS substrate:Challenges and future perspectives

Surface-enhanced Raman spectroscopy(SERS),as a highly sensitive molecular analysis technique,can realize fast and non-destructive detection of the information of molecular bonds to identify the component of analytes by"fingerprint"identification.The preparation of SERS substrates plays an extremely important role in the development of SERS technology and the application of SERS detection.By integrating SERS enhancement substrates into microfluidic chips,researchers have developed the microfluidic SERS chips which expand the function of microfluidic chips and provide an efficient platform for on-site biochemical analysis equipped with the powerful sensing capability of SERS technique.In this paper,we will first briefly give a review of the current microfluidic SERS-active substrates preparation technology and present the perspective on the application prospects of microfluidic SERS-active substrates.And then the challenges in the preparation of microfluidic SERS-active substrates will be pointed out,as well as realistic issues of using this technology for biochemical application.

Performance enhancement of paper-based SERS chips by shell-isolated nanoparticle-enhanced Raman spectroscopy

Paper-based flexible surface-enhanced Raman scattering(SERS) chips have been demonstrated to have great potential for future practical applications in point-of-care testing(POCT) due to the potentials of massive fabrication, low cost, efficient sample collection and short signal acquisition time. In this work,common filter paper and Ag@Si O2 core-shell nanoparticles(NP) have been utilized to fabricate SERS chips based on shell-isolated nanoparticle-enhanced Raman spectroscopy(SHINERS). The SERS performance of the chips for POCT applications was systematically investigated. We used crystal violet as the model molecule to study the influence of the size of the Ag core and the thickness of the Si O2 coating layer on the SERS activity and then the morphology optimized Ag@Si O2 core-shell NPs was employed to detect thiram. By utilizing the smartphone as a miniaturized Raman spectral analyzer, high SERS sensitivity of thiram with a detection limit of 10^-9 M was obtained. The study on the stability of the SERS chips shows that a Si O2 shell of 3 nm can effectively protect the as-prepared SERS chips against oxidation in ambient atmosphere without seriously weakening the SERS sensitivity. Our results indicated that the SERS chips by SHINERS had great potential of practical application, such as pesticide residues detection in POCT.

Liquid Metal-Based Epidermal Flexible Sensor for Wireless Breath Monitoring and Diagnosis Enabled by Highly Sensitive SnS2 Nanosheets

Real-time wireless respiratory monitoring and biomarker analysis provide an attractive vision for noninvasive telemedicine such as the timely prevention of respiratory arrest or for early diagnoses of chronic diseases.Lightweight,wearable respiratory sensors are in high demand as they meet the requirement of portability in digital healthcare management.Meanwhile,high-performance sensing material plays a crucial role for the precise sensing of specific markers in exhaled air,which represents a complex and rather humid environment.Here,we present a liquid metal-based flexible electrode coupled with SnS_(2)nanomaterials as a wearable gas-sensing device,with added Bluetooth capabilities for remote respiratory monitoring and diagnoses.The flexible epidermal device exhibits superior skin compatibility and high responsiveness(1092%/ppm),ultralow detection limits(1.32 ppb),and a good selectivity of NO gas at ppb-level concentrations.Taking advantage of the fast recovery kinetics of SnS_(2)responding to H_(2)O molecules,it is possible to accurately distinguish between different respiratory patterns based on the amount of water vapor in the exhaled air.Furthermore,based on the different redox types of H_(2)O and NO molecules,the electric signal is reversed once the exhaled NO concentration exceeds a certain threshold that may indicate the onset of conditions like asthma,thus providing an early warning system for potential lung diseases.Finally,by integrating the wearable device into a wireless cloud-based multichannel interface,we provide a proof-of-concept that our device could be used for the simultaneous remote monitoring of several patients with respiratory diseases,a crucial field in future digital healthcare management.

Nanomaterial Labels in Lateral Flow Immunoassays for Point-of-Care-Testing

Lateral flow immunoassays(LFIAs) have been developed rapidly in recent years and used in a wide range of application at point-of-care-testing(POCT),where small biomolecules can be conveniently examined on a test strip.Compared with other biochemical detection methods such as ELISA(enzyme linked immunosorbent assay) or mass spectrometry method,LFIAs have the advantages of low cost,easy operation and short time-consuming.However,it suffers from low sensitivity since conventional LFIA can only realize qualitative detection based on colorimetric signals.With the increasing demand for more accurate and sensitive determination,novel nanomaterials have been used as labels in LFIAs due to their unique advantages in physical and chemical properties.Colloidal gold,fluorescent nano particles,SERSactive nanomaterials,magnetic nanoparticles and carbon nanomaterials are utilized in LFIAs to produce different kinds of signals for quantitative or semi-quantitative detection.This review paper first gives a description of the LFIA principles,and then focuses on the state-of-the-art nanomaterial labelling technology in LFIAs.At last,the conclusion and outlook are given to inspire exploration of more advanced nanomaterials for the development of future LFIAs.

Liquid Metal-Based Epidermal Flexible Sensor for Wireless Breath Monitoring and Diagnosis Enabled by Highly Sensitive SnS_(2) Nanosheets

Real-time wireless respiratory monitoring and biomarker analysis provide an attractive vision for noninvasive telemedicine such as the timely prevention of respiratory arrest or for early diagnoses of chronic diseases.Lightweight,wearable respiratory sensors are in high demand as they meet the requirement of portability in digital healthcare management.Meanwhile,high-performance sensing material plays a crucial role for the precise sensing of specific markers in exhaled air,which represents a complex and rather humid environment.Here,we present a liquid metal-based flexible electrode coupled with SnS_(2) nanomaterials as a wearable gas-sensing device,with added Bluetooth capabilities for remote respiratory monitoring and diagnoses.The flexible epidermal device exhibits superior skin compatibility and high responsiveness(1092%/ppm),ultralow detection limits(1.32 ppb),and a good selectivity of NO gas at ppb-level concentrations.Taking advantage of the fast recovery kinetics of SnS_(2) responding to H_(2) O molecules,it is possible to accurately distinguish between different respiratory patterns based on the amount of water vapor in the exhaled air.Furthermore,based on the different redox types of H_(2) O and NO molecules,the electric signal is reversed once the exhaled NO concentration exceeds a certain threshold that may indicate the onset of conditions like asthma,thus providing an early warning system for potential lung diseases.Finally,by integrating the wearable device into a wireless cloud-based multichannel interface,we provide a proof-of-concept that our device could be used for the simultaneous remote monitoring of several patients with respiratory diseases,a crucial field in future digital healthcare management.