Open-Nanogap-Induced Strong Electromagnetic Enhancement in Au/AgAu Monolayer as a Stable and Uniform SERS Substrate for Ultrasensitive Detection.

Nanogap-based plasmonic metal nanocrystals have been applied in surface-enhanced Raman scattering detection, while the closed and insufficient electromagnetic fields as well as the nonreproducible Raman signal of the substrate greatly restrict the actual application. Herein, a highly uniform Au/AgAu monolayer with abundant nanogaps and huge electromagnetic enhancement is prepared, which shows ultrasensitive and reproducible SERS detection. Au/AgAu with an inner nanogap is first prepared based on Au nanotriangles, and the nanogap is opened from the three tips via a subsequent etching process. The open-gap Au/AgAu displays much higher SERS efficiency than Au and Au/AgAu with an inner nanogap on detecting crystal violet due to the open-gap induced electromagnetic enhancement and improved molecular absorption. Furthermore, the open-gap Au/AgAu monolayer is prepared via interfacial self-assembly, which shows further improved SERS due to the dense and strong hotspots in the nanocavities induced by the electromagnetic coupling between adjacent open gaps. The monolayer possesses excellent signal stability, uniformity, and reproducibility. The analytic enhancement factor and relative standard deviation reach to 2.12 × 108 and 4.65% on detecting crystal violet, respectively. Moreover, the monolayer achieves efficient detection of thiram in apple juice, biphenyl-4-thiol, 4-mercaptobenzoic, melamine, and a mixed solution of four different molecules, showing great promise in practical detection.

Transcriptomic and metabolomic data reveal key genes that are involved in the phenylpropanoid pathway and regulate the floral fragrance of Rhododendron fortunei.

BACKGROUND: To reveal the key genes involved in the phenylpropanoid pathway, which ultimately governs the fragrance of Rhododendron fortunei, we performed a comprehensive transcriptome and metabolomic analysis of the petals of two different varieties of two alpine rhododendrons: the scented R. fortunei and the unscented Rhododendron 'Nova Zembla'. RESULTS: Our transcriptomic and qRT-PCR data showed that nine candidate genes were highly expressed in R. fortunei but were downregulated in Rhododendron 'Nova Zembla'. Among these genes, EGS expression was significantly positively correlated with various volatile benzene/phenylpropanoid compounds and significantly negatively correlated with the contents of various nonvolatile compounds, whereas CCoAOMT, PAL, C4H, and BALDH expression was significantly negatively correlated with the contents of various volatile benzene/phenylpropanoid compounds and significantly positively correlated with the contents of various nonvolatile compounds. CCR, CAD, 4CL, and SAMT expression was significantly negatively correlated with the contents of various benzene/phenylpropanoid compounds. The validation of RfSAMT showed that the RfSAMT gene regulates the synthesis of aromatic metabolites in R. fortunei. CONCLUSION: The findings of this study indicated that key candidate genes and metabolites involved in the phenylpropanoid biosynthesis pathway may govern the fragrance of R. fortunei. This lays a foundation for further research on the molecular mechanism underlying fragrance in the genus Rhododendron.

Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children.

BACKGROUND: Moderate and late preterm (MLPT) birth accounts for the vast majority of preterm births, which is a global public health problem. The association between MLPT and neurobehavioral developmental delays in children and the underlying biological mechanisms need to be further revealed. The "placenta-brain axis" (PBA) provides a new perspective for gene regulation and risk prediction of neurodevelopmental delays in MLPT children. METHODS: The authors performed multivariate logistic regression models between MLPT and children's neurodevelopmental outcomes, using data from 129 MLPT infants and 3136 full-term controls from the Ma'anshan Birth Cohort (MABC). Furthermore, the authors identified the abnormally regulated PBA-related genes in MLPT placenta by bioinformatics analysis of RNA-seq data and RT-qPCR verification on independent samples. Finally, the authors established the prediction model of neurodevelopmental delay in children with MLPT using multiple machine learning models. RESULTS: The authors found an increased risk of neurodevelopmental delay in children with MLPT at 6 months, 18 months, and 48 months, especially in boys. Further verification showed that APOE and CST3 genes were significantly correlated with the developmental levels of gross-motor domain, fine-motor domain, and personal social domain in 6-month-old male MLPT children. CONCLUSIONS: These findings suggested that there was a sex-specific association between MLPT and neurodevelopmental delays. Moreover, APOE and CST3 were identified as placental biomarkers. The results provided guidance for the etiology investigation, risk prediction, and early intervention of neurodevelopmental delays in children with MLPT.

Interactions between Plasmonic Nanoantennas and Vortex Beams.

The orbital angular momentum (OAM) of light offers a new degree of freedom for light-matter interactions, yet how to control such interactions with this physical dimension remains open. Here, by developing a numerical method enabling optical OAM simulations, we provide insights into complex plasmon behaviors with the physical dimension of OAM, and we prove in theory that plasmonic nanostructures can function as efficient antennas to intercept and directionally reradiate the power of OAM beams. The interplay between optical OAM and spin angular momentum (SAM) generates novel particle polarizations and radiations, which were inaccessible before. For arrayed nanoparticles, coherent surface plasmons with specific phase retardations determined by OAM of the beams enable directional power radiations, making a phased array antenna. These findings expand our knowledge of nanoplasmonics in the OAM area and are promising for quantum information processing and dynamic sensing of ultraweak biosignals.

mPGES-1 Inhibitor Discovery Based on Computer-Aided Screening: Pharmacophore Models, Molecular Docking, ADMET, and MD Simulations.

mPGES-1 is an enzyme, which, when activated by inflammatory factors, can cause prostaglandin E synthesis. Traditional non-steroidal anti-inflammatory drugs are capable of inhibiting prostaglandin production, yet they can also cause gastrointestinal reactions and coagulation disorders. mPGES-1, the enzyme at the conclusion of prostaglandin production, does not cause any adverse reactions when inhibited. Numerous studies have demonstrated that mPGES-1 is more abundant in cancerous cells than in healthy cells, indicating that decreasing the expression of mPGES-1 could be a potential therapeutic strategy for cancer. Consequently, the invention of mPGES-1 inhibitors presents a fresh avenue for the treatment of inflammation and cancer. Incorporating a database of TCM compounds, we collected a batch of compounds that had an inhibitory effect on mPGES-1 and possessed IC50 value. Firstly, a pharmacophore model was constructed, and the TCM database was screened, and the compounds with score cut-off values of more than 1 were retained. Then, the compounds retained after being screened via the pharmacodynamic model were screened for docking at the mPGES-1 binding site, followed by high-throughput virtual screening [HTVS] and standard precision [SP] and super-precision [XP] docking, and the compounds in the top 20% of the XP docking score were selected to calculate the total free binding energy of MM-GBSA. The best ten compounds were chosen by comparing their score against the reference ligand 4U9 and the MM-GBSA_dG_Bind score. ADMET analysis resulted in the selection of ten compounds, three of which had desirable medicinal properties. Finally, the binding energy of the target protein mPGES-1 and the candidate ligand compound was analyzed using a 100 ns molecular dynamics simulation of the reference ligand 4U9 and three selected compounds. After a gradual screening study and analysis, we identified a structure that is superior to the reference ligand 4U9 in all aspects, namely compound 15643. Taken together, the results of this study reveal a structure that can be used to inhibit mPGES-1 compound 15643, thereby providing a new option for anti-inflammatory and anti-tumor drugs.

SPP standing waves within plasmonic nanocavities.

Surface plasmons usually take two forms: surface plasmon polaritons (SPP) and localized surface plasmons (LSP). Recent experiments demonstrate an interesting plasmon mode within plasmonic gaps, showing distinct characters from the two usual forms. In this investigation, by introducing a fundamental concept of SPP standing wave and an analytical model, we reveal the nature of the recently reported plasmon modes. The analytical model includes SPP propagating and SPP reflection within a metal-insulator-metal (MIM) cavity, which is rechecked and supplemented by numerical simulations. We systematically analyze SPP standing waves within various nanocavities. During the discussion, some unusual phenomena have been explained. For example, the hot spot of a nanodimer could be off-tip, depending on the order of standing wave mode; and that a nanocube on metal film can be viewed as a nanocube dimer with the same separation. And many other interesting phenomena have been discussed, such as dark mode of SPP standing wave and extraordinary optical transmission. The study gives a comprehensive understanding of SPP standing waves, and may promote the applications of cavity plasmons in ultrasensitive bio-sensings.

The Inhibitors of CDK4/6 from a Library of Marine Compound Database: A Pharmacophore, ADMET, Molecular Docking and Molecular Dynamics Study.

BACKGROUND: CDK4/6 (Cyclin-dependent kinases 4/6) are the key promoters of cell cycle transition from G1 phase to S phase. Thus, selective inhibition of CDK4/6 is a promising cancer treatment. METHODS: A total of 52,765 marine natural products were screened for CDK4/6. To screen out better natural compounds, pharmacophore models were first generated, then the absorption, distribution, metabolism, elimination, and toxicity (ADMET) were tested, followed by molecular docking. Finally, molecular dynamics simulation was carried out to verify the binding characteristics of the selected compounds. RESULTS: Eighty-seven marine small molecules were screened based on the pharmacophore model. Then, compounds 41369 and 50843 were selected according to the ADMET and molecular docking score for further kinetic simulation evaluation. Finally, through molecular dynamics analysis, it was confirmed that compound 50843 maintained a stable conformation with the target protein, so it has the opportunity to become an inhibitor of CDK4/6. CONCLUSION: Through structure-based pharmacophore modeling, ADMET, the molecular docking method and molecular dynamics (MD) simulation, marine natural compound 50843 was proposed as a promising marine inhibitor of CDK4/6.

Chronic inflammation as a potential mediator between phthalate exposure and depressive symptoms.

BACKGROUND: A few studies have reported phthalate exposure as a risk factor for depressive symptoms, but the results have been inconsistent. Whether chronic inflammation mediates the relationship between phthalates (PAEs) and depressive symptoms remains unclear. In this study, we establish mediating models of inflammatory factors and explore the mediating role of chronic inflammation in the association between PAEs exposure and depressive symptoms. METHODS: The sample included 989 participants from the Study on Health and Environment of the Elderly in Lu'an City, Anhui Province. Geriatric depression scale (GDS-30) was used to screen depressive symptoms of the elderly. The levels of seven kinds of PAEs in urine samples and four inflammatory factors in serum of the elderly were measured. To establish the mediating effect of inflammatory factors to explore the potential effect of PAEs exposure on the increased odds of depressive symptoms. RESULTS: Adjusted for multiple variables, the highest tertiles of Mono (2-ethylhexyl) phthalate (MEHP) (95%CI = 1.051-2.112), Mono benzyl phthalate (MBzP) (95%CI = 1.016-2.082) and Mono butyl phthalate (MBP) (95%CI = 1.102-2.262) were positively correlated with depressive symptoms. The mediating effect of IL-6 and generalized inflammation factor between MEHP exposure and depressive symptoms were 15.96% (95%CI=0.0288-0.1971) and 14.25% (95%CI = 0.0167-0.1899). CONCLUSIONS: High levels of MEHP, MBzP and MBP increased the odds of depressive symptoms in the elderly, and chronic inflammation had a partial mediating effect on the increased odds of depressive symptoms due to MEHP exposure.

Tunable Size Dependence of Quantum Plasmon of Charged Gold Nanoparticles.

The quantum behavior of surface plasmons has received extensive attention, benefiting from the development of exquisite nanotechnology and the diverse applications. Blueshift, redshift, and nonshift of localized surface plasmon resonances (LSPRs) have all been reported as the particle size decreases and enters the quantum size regime, but the underlying physical mechanism to induce these controversial size dependences is not clear. Herein, we propose an improved semiclassical model for modifying the dielectric function of metal nanospheres by combining the intrinsic quantized electron transitions and surface electron injection or extraction to investigate the plasmon shift and LSPR size dependence of the charged Au nanoparticles. We experimentally observe that the nonmonotonic blueshift of LSPRs with size for Au nanoparticles is turned into an approximately monotonic blueshift by increasing the electron donor concentration in the reduction solution, and it can also be transformed to an approximately monotonic redshift after surface passivation by ligand molecules. Moreover, we demonstrate controlled blueshift and redshift for the electron and hole plasmons in Cu_{2-x}S@Au core-shell nanoparticles by injecting electrons. The experimental observations and the theoretical calculations clarify the controversial size dependences of LSPR reported in the literature, reveal the critical role of surface electron injection or extraction in the transformation between the different size dependences of LSPRs, and are helpful for understanding the nature of surface plasmons in the quantum size regime.

Structure-Based Pharmacophore Modeling, Virtual Screening, Molecular Docking, ADMET, and Molecular Dynamics (MD) Simulation of Potential Inhibitors of PD-L1 from the Library of Marine Natural Products.

BACKGROUND: In the past decade, several antibodies directed against the PD-1/PD-L1 interaction have been approved. However, therapeutic antibodies also exhibit some shortcomings. Using small molecules to regulate the PD-1/PD-L1 pathway may be another way to mobilize the immune system to fight cancer. METHOD: 52,765 marine natural products were screened against PD-L1(PDBID: 6R3K). To identify natural compounds, a structure-based pharmacophore model was generated, following by virtual screening and molecular docking. Then, the absorption, distribution, metabolism, and excretion (ADME) test was carried out to select the most suitable compounds. Finally, molecular dynamics simulation was also performed to validate the binding property of the top compound. RESULTS: Initially, 12 small marine molecules were screened based on the pharmacophore model. Then, two compounds were selected for further evaluation based on the molecular docking scores. After ADME and toxicity studies, molecule 51320 was selected for further verification. By molecular dynamics analysis, molecule 51320 maintains a stable conformation with the target protein, so it has the chance to become an inhibitor of PD-L1. CONCLUSIONS: Through structure-based pharmacophore modeling, virtual screening, molecular docking, ADMET approaches, and molecular dynamics (MD) simulation, the marine natural compound 51320 can be used as a small molecule inhibitor of PD-L1.

Di-(2-ethylhexyl) phthalate inhibits expression and internalization of transthyretin in human placental trophoblastic cells.

During pregnancy, fetal thyroid hormones (THs) are dependent on maternal placental transport and their physiological level is crucial for normal fetal neurodevelopment. Earlier research has shown that Di-(2-ethylhexyl) phthalate (DEHP) disrupts thyroid function and THs homeostasis in pregnant women and fetuses, and affects placental THs transport. However, the underlying mechanisms are poorly understood. The present study, therefore, aimed to systematically investigate the potential mechanisms of DEHP-induced disruption in the placental THs transport using two human placental trophoblastic cells, HTR-8/SVneo cells and JEG-3 cells. While the exposure of DEHP at the doses of 0-400 µM for 24 h did not affect cell viability, we found reduced consumption of T3 and T4 in the culture medium of HTR-8/Svneo cells treated with DEHP at 400 µM. DEHP treatment did not affect T3 uptake and the expression of monocarboxylate transporters 8 (MCT8) and organic anion transporters 1C1 (OATP1C1). However, DEHP significantly inhibited transthyretin (TTR) internalization, down-regulated TTR, deiodinase 2 (DIO2), and thyroid hormone receptors mRNA expression and protein levels, and up-regulated deiodinase 3 (DIO3) protein levels in a dose-dependent manner. These results indicate that DEHP acts on placental trophoblast cells, inhibits its TTR internalization, down-regulates TTR expression and affects the expression of DIO2, DIO3, and thyroid hormone receptor. These may be the mechanisms by which PAEs affects THs transport through placental.

A review of therapeutic agents and Chinese herbal medicines against SARS-COV-2 (COVID-19).

The epidemic of pneumonia (COVID-19) caused by novel coronavirus (SARS-CoV-2) infection has been listed as a public health emergency of international concern by the World Health Organization (WHO), and its harm degree is defined as a global "pandemic". At present, the efforts of various countries focus on the rapid diagnosis and isolation of patients, as well as to find a treatment that can combat the most serious impact of the disease. The number of reported COVID-19 virus infections is still increasing. Unfortunately, no drugs or vaccines have been approved for the treatment of human coronaviruses, but there is an urgent need for in-depth research on emerging human infectious coronaviruses. Clarification transmission routes and pathogenic mechanisms, and identification of potential drug treatment targets will promote the development of effective prevention and treatment measures. In the absence of confirmed effective treatments, due to public health emergencies, it is essential to study the possible effects of existing approved antivirals drugs or Chinese herbal medicines for SARS-CoV-2. This review summarizes the epidemiological characteristics, pathogenesis, virus structure and targeting strategies of COVID-19. Meanwhile, this review also focus on the re-purposing of clinically approved drugs and Chinese herbal medicines that may be used to treat COVID-19 and provide new ideas for the discovery of small molecular compounds with potential therapeutic effects on novel COVID-19.

The levels of phthalate exposure and associations with obesity in an elderly population in China.

BACKGROUND: Few epidemiological studies on the correlation between phthalate exposure and elderly obesity in China are available. The purpose of the present study is to assess phthalate exposure levels and explore the connections between exposure to phthalates and obesity using a sample of Chinese community-dwelling elderly individuals. METHODS: Data were acquired from the baseline survey of the Cohort of Health of Elderly and Controllable Factors of Environment, which was established in Lu'an, Anhui province, China, from June to September in 2016. Urine samples were obtained to analyze the concentrations of seven phthalate metabolites, utilizing a high-performance liquid chromatography-tandem mass spectrometry method. General obesity was determined based on body mass index, and abdominal obesity based on waist circumference. Binary logistic regression models were utilized to analyze the associations of creatinine-corrected phthalate metabolite concentrations (categorized into quartiles) with general and abdominal obesity in elderly people. Moreover, a stratified analysis was performed to explore the difference between genders. RESULTS: Of 942 elderly individuals, 52.9% were defined as generally obese and 75.5% as abdominally obese. The detection rates of seven phthalate metabolites ranged from 90.07% to 99.80%. The highest median concentration was 44.08 µg/l (for MBP), and the lowest was 0.55 µg/l (for MEHP). The level of exposure to LMW(low-molecular-weight) PAEs is higher than that to HMW(high-molecular-weight) PAEs. After adjustment for confounding variables, we found a significant association between urinary MEOHP (mono-2-ethyl-5-oxohexyl phthalate), MEHP (mono-2-ethylhexyl phthalate), MBP (mono-n-butyl phthalate), MEP (mono-ethyl phthalate), and MMP (mono-methyl phthalate) levels and general obesity. MBP levels were also correlated with abdominal obesity. When stratified by gender, higher urinary levels of MEOHP, MBP, MEP, and MMP were associated with general obesity in males, whereas MBP and MMP levels were eminently correlated with general obesity in females. Higher urinary MBP levels were associated with increased abdominal obesity rates in males, but not in females. CONCLUSIONS: In conclusion, higher phthalate metabolite concentrations were correlated with obesity in the elderly. Moreover, a gender difference was observed in these associations.

Chemical composition and pharmacological mechanism of shenfu decoction in the treatment of novel coronavirus pneumonia (COVID-19).

PURPOSE: Shenfu decoction has outstanding curative effects in the treatment of COVID-19. This study aimed to explore the material basis and molecular mechanism of Shenfu Decoction through network pharmacology and molecular mechanisms, to provide a research basis for clinical medication and clues for subsequent research. METHODS: The active components and targets of Shenfu decoction were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the COVID-19-associated genes were collected using the Gene Cards platform. The target protein-protein interaction network map was constructed by mapping two genes, and the 'drug-active ingredient-target' network was constructed using Cytoscape software. The Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the mapping targets were analyzed. RESULT: Based on Traditional Chinese medicine, Shenfu Decoction can take effect in the lung, spleen, kidney and heart. Considering oral bioavailability (OB) ≥ 30% and drug-like (DL) ≥ 0.18 as the standard, 43 active compounds were screened and 114 Shenfu decoction action targets were collected. The key targets were CASP3, MAPK8, PTGS2, IL1B, PPARG, ICAM1, IFNG, RELA, NOS2, NOS3, HMOX1, CASP8, STAT1, and TGFB1. According to the standard of p < .05, GO function was enriched in 108 biological processes, 16 cell processes and 27 molecular processes. Sixty-three signaling pathways were enriched by KEGG, which can be divided into four types: viral infection pathways, signal pathways, biological process pathways and different disease pathways. The comparison of negative and positive prescriptions further reflects the positive effect of Shenfu decoction against COVID-19. Finally, the effective ingredients with the high degree were molecular docked with Mpro, Rdrp and Spro proteins to further confirm the intervention effect of Shenfu Decoction on COVID-19. CONCLUSION: Shenfu decoction played an important role in regulating the anti-virus process, regulating immunity, inhibiting inflammation and regulating apoptosis through the interrelated regulation mechanism of multi-components and multi-targets, to treat patients with severe COVID-19.

Magnetic Plasmon-Enhanced Second-Harmonic Generation on Colloidal Gold Nanocups.

The magnetic plasmons of three-dimensional nanostructures have unique optical responses and special significance for optical nanoresonators and nanoantennas. In this study, we have successfully synthesized colloidal Au and AuAg nanocups with a well-controlled asymmetric geometry, tunable opening sizes, and normalized depths ( h/ b, where h is depth and b is the height of the templating PbS nanooctahedrons), variable magnetic plasmon resonance, and largely enhanced second-harmonic generation (SHG). The most-efficient SHG of the bare Au nanocups is experimentally observed when the normalized depth h/ b is adjusted to ∼0.78-0.79. We find that the average magnetic field enhancement is maximized at h/ b = ∼0.65 and reveal that the maximal SHG can be attributed to the joint action of the optimized magnetic plasmon resonance and the "lightning-rod effect" of the Au nanocups. Furthermore, we demonstrate for the first time that the AuAg heteronanocups prepared by overgrowth of Ag on the Au nanocups can synergize the magnetic and electric plasmon resonances for nonlinear enhancement. By the tailoring of the dual resonances at the fundamental excitation and second-harmonic wavelengths, the far-field SHG intensity of the AuAg nanocups is enhanced 21.8-fold compared to that of the bare Au nanocups. These findings provide a strategy for the design of nonlinear optical nanoantennas based on magnetic plasmon resonances and can lead to diverse applications ranging from nanophotonics to biological spectroscopy.

Pure magnetic-quadrupole scattering and efficient second-harmonic generation from plasmon-dielectric hybrid nano-antennas.

We theoretically demonstrate that pure magnetic quadrupole (MQ) scattering is achieved via the excitation of anapole modes and Fano resonance in noble metal (Au or Ag) and high refractive index dielectric (AlGaAs) hybrid nano-antennas. In Au-AlGaAs hybrid nano-antennas, electric anapole and magnetic anapole modes are observed, leading to the suppressions of electric and magnetic dipoles. Introducing gain material to AlGaAs nanodisk to increase the strength of electric quadrupole (EQ) Fano resonance leads to the suppression of EQ scattering. Then, ideal MQ scattering is achieved at the wavelength of total scattering cross-section dip. The increase of signal-to-noise ratio of MQ results in the great enhancement of near-field inside AlGaAs nanodisk. Additionally, the strong MQ resonance exhibits great capability for boosting second-harmonic generation by proper mode matching. These findings achieved in subwavelength geometries have important implications for functional metamaterials and nonlinear photonic nanodevices.

Effectiveness of posterior reduction and fixation in atlantoaxial dislocation: a retrospective cohort study of 135 patients with a treatment algorithm proposal.

PURPOSE: Surgical procedures on atlantoaxial dislocation remain controversial. The aim of this observational retrospective study was to investigate the treatment algorithm of surgical procedures. METHODS: According to CT and intraoperative evaluation during direct posterior reduction, 135 AAD cases were categorized into three groups: Group I: reducible dislocation; Group II: irreducible dislocation (Group IIa: effective decompression achieved after posterior reduction; Group IIb: no effective decompression after posterior reduction); and Group III: fixed dislocation. Group III presented with extensive bony fusions. Group I and Group IIa were treated with direct posterior reduction and fixation. Group IIb underwent posterior fixation and transoral odontoidectomy. Group III underwent transoral odontoidectomy alone. Japanese Orthopedic Association scores (JOA) were assessed to evaluate clinical status before and 6, 12 months after surgery. RESULTS: Our study included 118 Group I cases, 16 Group II cases (Group IIa: 11 cases; Group IIb: 5 cases), and one Group III case. Follow-up ranged from 12 to 36 months. PRIMARY OUTCOME: Anatomic atlantoaxial reduction was achieved in 118 of 135 patients (87.4%). Clinical improvements were seen in 96.3% (130/135) all the patients. Solid atlantoaxial fusion was shown in 134 patients. Secondary outcome: The overall complication rate was 3.7% (5/135). For Group I, the mean postoperative 6-month JOA was 14.5 versus 12.2 in preoperative patients (paired Student's t test, P < 0.01). CONCLUSIONS: This article proposes a clinical procedure that assists with therapeutic decision making and indicates the severity and difficulty of reduction of the atlantoaxial joint. These slides can be retrieved under Electronic Supplementary Material.

A Fast Indoor/Outdoor Transition Detection Algorithm Based on Machine Learning.

The widespread popularity of smartphones makes it possible to provide Location-Based Services (LBS) in a variety of complex scenarios. The location and contextual status, especially the Indoor/Outdoor switching, provides a direct indicator for seamless indoor and outdoor positioning and navigation. It is challenging to quickly detect indoor and outdoor transitions with high confidence due to a variety of signal variations in complex scenarios and the similarity of indoor and outdoor signal sources in the IO transition regions. In this paper, we consider the challenge of switching quickly in IO transition regions with high detection accuracy in complex scenarios. Towards this end, we analyze and extract spatial geometry distribution, time sequence and statistical features under different sliding windows from GNSS measurements in Android smartphones and present a novel IO detection method employing an ensemble model based on stacking and filtering the detection result by Hidden Markov Model. We evaluated our algorithm on four datasets. The results showed that our proposed algorithm was capable of identifying IO state with 99.11% accuracy in indoor and outdoor environment where we have collected data and 97.02% accuracy in new indoor and outdoor scenarios. Furthermore, in the scenario of indoor and outdoor transition where we have collected data, the recognition accuracy reaches 94.53% and the probability of switching delay within 3 s exceeds 80%. In the new scenario, the recognition accuracy reaches 92.80% and the probability of switching delay within 4 s exceeds 80%.

Pedestrian Stride-Length Estimation Based on LSTM and Denoising Autoencoders.

Accurate stride-length estimation is a fundamental component in numerous applications, such as pedestrian dead reckoning, gait analysis, and human activity recognition. The existing stride-length estimation algorithms work relatively well in cases of walking a straight line at normal speed, but their error overgrows in complex scenes. Inaccurate walking-distance estimation leads to huge accumulative positioning errors of pedestrian dead reckoning. This paper proposes TapeLine, an adaptive stride-length estimation algorithm that automatically estimates a pedestrian's stride-length and walking-distance using the low-cost inertial-sensor embedded in a smartphone. TapeLine consists of a Long Short-Term Memory module and Denoising Autoencoders that aim to sanitize the noise in raw inertial-sensor data. In addition to accelerometer and gyroscope readings during stride interval, extracted higher-level features based on excellent early studies were also fed to proposed network model for stride-length estimation. To train the model and evaluate its performance, we designed a platform to collect inertial-sensor measurements from a smartphone as training data, pedestrian step events, actual stride-length, and cumulative walking-distance from a foot-mounted inertial navigation system module as training labels at the same time. We conducted elaborate experiments to verify the performance of the proposed algorithm and compared it with the state-of-the-art SLE algorithms. The experimental results demonstrated that the proposed algorithm outperformed the existing methods and achieves good estimation accuracy, with a stride-length error rate of 4.63% and a walking-distance error rate of 1.43% using inertial-sensor embedded in smartphone without depending on any additional infrastructure or pre-collected database when a pedestrian is walking in both indoor and outdoor complex environments (stairs, spiral stairs, escalators and elevators) with natural motion patterns (fast walking, normal walking, slow walking, running, jumping).

A Human Activity Recognition Algorithm Based on Stacking Denoising Autoencoder and LightGBM.

Recently, the demand for human activity recognition has become more and more urgent. It is widely used in indoor positioning, medical monitoring, safe driving, etc. Existing activity recognition approaches require either the location information of the sensors or the specific domain knowledge, which are expensive, intrusive, and inconvenient for pervasive implementation. In this paper, a human activity recognition algorithm based on SDAE (Stacking Denoising Autoencoder) and LightGBM (LGB) is proposed. The SDAE is adopted to sanitize the noise in raw sensor data and extract the most effective characteristic expression with unsupervised learning. The LGB reveals the inherent feature dependencies among categories for accurate human activity recognition. Extensive experiments are conducted on four datasets of distinct sensor combinations collected by different devices in three typical application scenarios, which are human moving modes, current static, and dynamic behaviors of users. The experimental results demonstrate that our proposed algorithm achieves an average accuracy of 95.99%, outperforming other comparative algorithms using XGBoost, CNN (Convolutional Neural Network), CNN + Statistical features, or single SDAE.