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Stimulated Raman scattering (SRS) has attracted increasing attention in bio-imaging because of the ability toward background-free molecular-specific acquisitions without fluorescence labeling. Nevertheless, the corresponding sensitivity and specificity remain far behind those of fluorescence techniques. Here, we demonstrate SRS spectro-microscopy driven by a multiple-plate continuum (MPC), whose octave-spanning bandwidth (600-1300 nm) and high spectral energy density (∼1 nJ/cm-1) enable spectroscopic interrogation across the entire Raman active region (0-4000 cm-1), SRS imaging of a Drosophila brain, and electronic pre-resonance (EPR) detection of a fluorescent dye. We envision that utilizing MPC light source will substantially enhance the sensitivity and specificity of SRS by implementing EPR mode and spectral multiplexing via accessing three or more coherent wavelengths.

Purpose: To investigate whether hydrogen-oxygen (67%–33%) therapy could improve the postoperative pulmonary function, recovery, complications, inflammatory reactions, and oxidative stress in patients undergoing lung surgery.Methods: We performed a prospective, randomized, single-blind, controlled clinical trial between December 2020 and December 2021. Eligible patients received either a lobectomy or sublobar resection. Postoperatively, they had 2-hour hydrogen-oxygen therapy (group H) or oxygen therapy (group C) daily, for three consecutive days. The pulmonary functions, recovery, pain intensity, oxygen saturation, inflammatory cytokines, and anti-oxidative markers were documented.Results: A total of 66 patients were analyzed, with 33 patients in each group. Both groups had decreased postoperative pulmonary functions, but group H had significantly better postoperative pulmonary functions than group C (forced vital capacities were 1.4±0.5 and 1.0±0.4 L and forced expiratory volumes in the first second were 1.1±0.3 and 0.9±0.3 L in group H and C, respectively (both PConclusion: Hydrogen-oxygen therapy could improve postoperative pulmonary functions, decrease pain intensity, accelerate recovery, and shorten the length of the hospital stay in patients who have undergone lung resection, which may be related to its anti-inflammatory and anti-oxidative effects. Trial registration: The Chinese Clinical Trial Registry (registration number ChiCTR2100042101)，the date of registration was January,13,2021.

Diabetes is an independent risk factor for stroke and amplifies inflammation. Diabetic stroke is associated with a higher risk of death and worse neural function. The identification of effective anti-inflammatory molecules with translational advantages is particularly important to promote perioperative neurorestorative effects. Applying molecular hydrogen, we measured blood glucose levels before and after middle cerebral artery occlusion (MCAO), 48-h cerebral oedema and infarct volumes, as well as 28-day weight, survival and neurological function. We also measured the levels of TLR4, NF-κB p65, phosphorylated NF-κB p65, catecholamines, acetylcholine and inflammatory factors. All measurements comprehensively showed the positive effect and translational advantage of molecular hydrogen on diabetic stroke. Molecular hydrogen improved the weight, survival and long-term neurological function of rats with diabetic stroke and alleviated changes in blood glucose levels before and after middle cerebral artery occlusion (MCAO), but no difference in circadian rhythm was observed. Molecular hydrogen inhibited the phosphorylation of NF-κB and significantly reduced inflammation. Molecular hydrogen mediates neurorestorative effects after stroke in diabetic rats. The effect is independent of circadian rhythms, indicating translational advantages. The molecular mechanism is related to the TLR4/NF-κB pathway and inflammation. Graphical abstract Molecular hydrogen (H2) affects outcomes of ischemic stroke with diabetes mellitus (DM).

Background: Age-related macular degeneration (AMD) is a leading cause of blindness in the elderly. Choroidal neovascularization (CNV) is the major pathologic feature of neovascular AMD. Oxidative damages and the ensuing chronic inflammation are representative of trigger events. Hydrogen gas (H2) has been demonstrated as an antioxidant and plays a role in the regulation of oxidative stress and inflammation. This experiment aimed to investigate the influence of H2 inhalation on a mouse model of CNV. Methods: Laser was used to induce CNV formation. C57BL/6J mice were divided into five groups: the control group, the laser-only group, and the 2 h, 5 h, and 2.5 h/2.5 h groups that received laser and H2 inhalation (21% oxygen, 42% hydrogen, and 37% nitrogen mixture) for 2 h, 5 h, and 2.5 h twice every day, respectively. Results: The severity of CNV leakage on fluorescence angiography showed a significant decrease in the H2 inhalation groups. The mRNA expression of hypoxia-inducible factor 1 alpha and its immediate downstream target vascular endothelial growth factor (VEGF) showed significant elevation after laser, and this elevation was suppressed in the H2 inhalation groups in an inhalation period length-related manner. The mRNA expression of cytokines, including tumor necrosis factor alpha and interlukin-6, also represented similar results. Conclusion: H2 inhalation could alleviate CNV leakage in a laser-induced mouse CNV model, and the potential mechanism might be related to the suppression of the inflammatory process and VEGF-driven CNV formation.

Recent development regarding mixture of H2 (concentration of ~66%) with O2 (concentration of ~34%) for medical purpose, such as treatment of coronavirus disease-19 (COVID-19) patients, is introduced. Furthermore, the design principles of a hydrogen inhaler which generates mixture of hydrogen (~66%) with oxygen (~34%) for medical purpose are proposed. With the installation of the liquid blocking module and flame arresters, the air pathway of the hydrogen inhaler is divided by multiple isolation zones to prevent any unexpected explosion propagating from one zone to the other. An integrated filtering/cycling module is utilized to purify the impurity, and cool down the temperature of the electrolytic module to reduce the risk of the explosion. Moreover, a nebulizer is provided to selectively atomize the water into vapor which is then mixed with the filtered hydrogen-oxygen mix gas, such that the static electricity of a substance hardly occurs to reduce the risk of the explosion. Furthermore, hydrogen concentration detector is installed to reduce the risk of hydrogen leakage. Result shows that the hydrogen inhaler implementing the aforesaid design rules could effectively inhibit the explosion, even ignition at the outset of the hydrogen inhaler which outputs hydrogen-oxygen gas (approximately 66% hydrogen: 34% oxygen).

This paper exploits capabilities implicit in DMSP plasma and field data through which users may infer local IGRF magnetic fields ( B → 0 ), as well as components of magnetic perturbations ( δ B → ⊥ ) and plasma drift ( V → ⊥ ) vectors perpendicular to B → 0 . We use relations between V → ⊥ and δ B → ⊥ , associated with Region 2 (R-2) field-aligned currents (FACs), consistent with Faraday's law, to determine Alfvenic reflection coefficients (α). Early main-phase measurements from three DMSP satellites, F16, F17 and F18 during the 17 March 2015 storm confirm the predicted V → ⊥ and δ B → ⊥ relationships. Data also show that high-latitude limits of R-2 FACs lie close to the equatorward boundaries of precipitating auroral electrons. Measurable fluxes of down-coming, ring-current ions are restricted to the vicinity of this auroral boundary. It thus remains an open question as to what particle population is responsible for carrying the downward FACs (j||) and Poynting fluxes (S||), inferred from δ B → ⊥ measurements acquired over the full latitudinal ranges of storm-time R-2.

This report demonstrates empirically that couplings between magnetically conjugate medium-scale traveling ionospheric disturbances (MSTIDs) are electromagnetic in nature. This is accomplished by comparing plasma density, electric, and magnetic perturbations sampled simultaneously by sensors on the Communication Navigation Outage Forecasting System (CNOFS) satellite. During the period of interest on 17 February 2010, CNOFS made three consecutive orbits while magnetically conjugate to the field of view of an all-sky imager located at El Leoncito, Argentina (31.8degS, 69.3degW). Imaged 630.0 nm airglow was characterized by alternating bands of relatively bright and dark emissions that were aligned from northeast to southwest and propagated toward the northwest, characteristic of MSTIDs in the southern hemisphere. Measurable Poynting fluxes flow along the Earths magnetic field (S) from generator to load hemispheres. While S was predominantly away from the ionosphere above El Leoncito, interhemispheric energy flows were not one-way streets. Measured Poynting flux intensities diminished with time over the three CNOFS passes, suggesting that source mechanisms of MSTIDs were absent or that initial impedance mismatches between the two hemispheres approached an equilibrium status.

The present study considers effects on the topside ionosphere at high-latitude (|MLat| ≥ 60°) during the magnetic storm on 17 March 2013. We divide the day into two segments, with magnetic conditions quiet during the first 6 h and disturbed thereafter, thus allowing comparisons of differences between these two states. The COSMIC data source consisted of 272 electron density profiles (EDPs) measured by COSMIC satellites using Abel inversions that assume the absence of horizontal plasma density gradients. We compared resultant EDPs with predictions of the International; Reference Ionosphere (IRI) model for the same altitudes along individual tangent-point lines. As conditions allowed, we also compared EDPs with densities measured by nearby DMSP satellites. During the pre-storm quiet period, 65 of the sampled 68 EDPs were highly correlated with IRI predictions. The remaining 3 EDPs showed significant irregularities along parts of the 800–200 km altitude range. We divided stormtime 204 COSMIC EDPs into three morphological categories. In the first group, 130 EDPs exhibit shapes similar to IRI-predictions. Of these, 72 (9) had larger (smaller) than predicted magnitudes. The second group consisted of 37 EDPs that showed little variation in magnitude over the designated altitude range. The remaining group had another 37 EDPs marked by significant irregularities. We found that the deepest EDP irregularity resulted from GPS signals passing through a deep plasma density trough observed by DMSP. The trough extended along the equatorward boundary of the evening-side, auroral oval. We suggest that EDP irregularities reflect density gradients along or near EDP tangent point lines.

[1] We have analyzed measurements from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) satellites acquired during an 81 day interval in late 2007 to study total electron content (TEC) responses of the dayside ionosphere during three consecutive passes of a high-speed stream (HSS) in the solar wind by Earth. During the second encounter the HSS arrival was closely preceded by the arrival at the first Lagrange point L1 of an interplanetary coronal mass ejection (ICME). In all cases the corotating interaction region (CIR) at the HSS's leading edge was characterized by increases in both nSW and TP above predisturbance levels, and large-amplitude oscillations in all interplanetary magnetic field (IMF) components. The solar wind events induced moderate magnetic storm activity; the minimum Dst of −71 nT occurred during the second encounter. TEC enhancements appeared at low-magnetic to midmagnetic latitudes during the ICME/CIR-driven storm. Some increases exceeded quiet time values by factors of ∼110%. In the absence of local auroral electron precipitation to create new plasma in the magnetic latitude domain of COSMIC measurements, the detected TEC increases must reflect transport effects. The COSMIC main phase observations of dayside TEC enhancement are explained as being caused by an ionospheric storm time “fountain” effect driven by weak (

Past studies reported that the main electrogastrography (EEG) dynamic changes related to motion sickness (MS) were occurred in occipital, parietal, and somatosensory brain area, especially in the power increasing of the alpha band (8–13 Hz) and theta band (4–7 Hz) which had positive correlation with the subjective MS level. Depend on these main findings correlated with MS, we attempt to develop an EEG based classification system to automatically classify subject's MS level and find the suitable EEG features via common feature extraction, selection and classifiers technologies in this study. If we can find the regulations and then develop an algorithm to predict MS occurring, it would be a great benefit to construct a safe and comfortable environment for all drivers and passengers when they are cruising in the car, bus, ship or airplane. EEG is one of the best methods for monitoring the brain dynamics induced by motion-sickness because of its high temporal resolution and portability. After collecting the EEG signals and subjective MS level in a realistic driving environment, we first do the data pre-processing part including ICA, component clustering analysis and time-frequency analysis. Then we adopt three common feature extractions and two feature selections (FE/FS) technologies to extract or select the correlated features such as principal component analysis (PCA), linear discriminate analysis (LDA), nonparametric weighted feature extraction (NWFE), forward feature selections (FFS) and backward feature selections (BFS) and feed the feature maps into three classifiers (Gaussian Maximum Likelihood Classifier (ML), k-Nearest-Neighbor Classifier (kNN) and Support Vector Machine (SVM)). Experimental results show that classification performance of all our proposed technologies can be reached almost over 95%. It means it is possible to apply the effective technology combination to predict the subject's MS level in the real life applications. The better combination in this study is using LDA and Gaussian based ML classifier. This advantage can be widely used in machine learning area for developing the prediction algorithms in the future.

Growing numbers of traffic accidents had become a serious social safety problem in recent years. The main factor of the high fatalities was the obvious decline of the driver's cognitive state in their perception, recognition and vehicle control abilities while being sleepy. The key to avoid the terrible consequents is to build a detecting system for ongoing assessment of driver's cognitive state. A quickly growing research, brain-computer interface (BCI), offers a solution offering great assistance to those who require alternative communicatory and control mechanisms. In this study, we propose an alertness/drowsiness classification system based on investigating electroencephalographic (EEG) brain dynamics in lane-keeping driving experiments in a virtual reality (VR) driving environment with a motion platform. The core of the classification system is composed of dimension reduction technique and classifier learning algorithm. In order to find the suitable method for better describing the data structure, we explore the performances using different feature extraction and feature selection methods with different classifiers. Experiment results show that the accuracy is over 80% in most combinations and even near 90% under Principal Component Analysis (PCA) and Nonparametric Weighted Feature Extraction (NWFE) going with Gaussian Maximum Likelihood classifier (ML) and k-Nearest-Neighbor classifier (kNN), respectively. In addition, this developed classification system can also solve the individual brain dynamic differences caused from different subjects and overcome the subject dependent limitation. The optimized solution with better accuracy performance out of all combinations can be considered to implement in the kernel brain-computer interface.