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Mid-infrared spectroscopy probes molecular vibrations to identify chemical species and functional groups. Therefore, mid-infrared hyperspectral imaging is one of the most powerful and promising candidates for chemical imaging using optical methods. Yet high-speed and entire bandwidth mid-infrared hyperspectral imaging has not been realized. Here we report a mid-infrared hyperspectral chemical imaging technique that uses chirped pulse upconversion of sub-cycle pulses at the image plane. This technique offers a lateral resolution of 15 µm, and the field of view is adjustable between 800 µm × 600 µm to 12 mm × 9 mm. The hyperspectral imaging produces a 640 × 480 pixel image in 8 s, which covers a spectral range of 640–3015 cm –1 , comprising 1069 wavelength points and offering a wavenumber resolution of 2.6–3.7 cm –1 . For discrete frequency mid-infrared imaging, the measurement speed reaches a frame rate of 5 kHz, the repetition rate of the laser. As a demonstration, we effectively identified and mapped different components in a microfluidic device, plant cell, and mouse embryo section. The great capacity and latent force of this technique in chemical imaging promise to be applied to many fields such as chemical analysis, biology, and medicine. The authors present a fast mid-infrared hyperspectral chemical imaging technique that uses chirped pulse upconversion of sub-cycle pulses at the image plane, with lateral resolution of 15 µm and an adjustable field of view and large spectral range. They demonstrate identification and mapping different components in a microfluidic device, plant cell, and mouse embryo.

Near infrared energy remains untapped toward the maneuvering of entire solar spectrum harvesting for fulfilling the nuts and bolts of solar hydrogen production. We report the use of Au@Cu 7 S 4 yolk@shell nanocrystals as dual-plasmonic photocatalysts to achieve remarkable hydrogen production under visible and near infrared illumination. Ultrafast spectroscopic data reveal the prevalence of long-lived charge separation states for Au@Cu 7 S 4 under both visible and near infrared excitation. Combined with the advantageous features of yolk@shell nanostructures, Au@Cu 7 S 4 achieves a peak quantum yield of 9.4% at 500 nm and a record-breaking quantum yield of 7.3% at 2200 nm for hydrogen production in the absence of additional co-catalysts. The design of a sustainable visible- and near infrared-responsive photocatalytic system is expected to inspire further widespread applications in solar fuel generation. In this work, the feasibility of exploiting the localized surface plasmon resonance property of self-doped, nonstoichiometric semiconductor nanocrystals for the realization of wide-spectrum-driven photocatalysis is highlighted. Near infrared energy remains untapped toward the maneuvering of entire solar spectrum harvesting for fulfilling nuts and bolts of solar hydrogen production. Here, the authors report the use of Au@Cu 7 S 4 yolk@shell nanocrystals for hydrogen production from untapped near infrared energy.

Introduction: Diabetic nephropathy (DN) is a serious complication of diabetes mellitus and is considered to be a sterile inflammatory disease. Increasing evidence suggest that pyroptosis and subsequent inflammatory response play a key role in the pathogenesis of DN. However, the underlying cellular and molecular mechanisms responsible for pyroptosis in DN are largely unknown. Methods: The rat models of DN were successfully established by single 65 mg/kg streptozotocin treatment. Glomerular mesangial cells were exposed to 30 mmol/L high glucose media for 48 h to mimic the DN environment in vitro. Gene and protein expressions were determined by quantitative real-time PCR and Western blot. Cell viability and pyroptosis were measured by MTT assay and flow cytometry analysis, respectively. The relationship between lncRNA NEAT1, miR-34c, and Nod-like receptor protein-3 (NLRP3) was confirmed by luciferase reporter assay. Results: We found that upregulation of NEAT1 was associated with the increase of pyroptosis in DN models. miR-34c, as a target gene of NEAT1, mediated the effect of NEAT1 on pyroptosis in DN by regulating the expression of NLRP3 as well as the expressions of caspase-1 and interleukin-1β. Either miR-34c inhibition or NLRP3 overexpression could reverse the accentuation of pyroptosis and inflammation by sh-NEAT1 transfection in the in vitro model of DN. Conclusions: Our findings suggested NEAT1 and its target gene miR-34c regulated cell pyroptosis via mediating NLRP3 in DN, providing new insights into understanding the molecular mechanisms of pyroptosis in the pathogenesis of DN.

The geo-structures embedded in the multiple variable strata could be significantly affected by the geological uncertainty. The quantitative evaluation of geological uncertainty and its influence on the structural safety of embedded tunnels are seldom studied in the past. This paper aims to analyse the effect of geological uncertainty on the structural performance of tunnel using the proposed stochastic geological modelling framework. The geological uncertainty is characterized using an improved coupled Markov chain model based on sparse limited boreholes. A mapping approach is presented to solve the mesh asymmetry problem between the simulated strata and the numerical tunnel model. The tunnel structural performance analysis is then conducted based on the combined model considering the geological uncertainty and tunnel structure. A geological uncertainty index (GUI) is proposed to quantitatively evaluate the level of uncertainty of each borehole and the whole site. The effect of the borehole layout scheme on uncertainty evaluation of factor of safety of tunnel structure is investigated by a large number of stratigraphic realizations. Boreholes collected from Norway with relatively more considerable variability and from Shanghai with relatively more minor variability are adopted as case studies to illustrate the proposed probabilistic analysis framework. The results show that the boreholes with larger GUI values and closer to tunnel locations have a greater weight to affect the embedded tunnel structural performance in uncertain geological strata.

Soft structured clays usually exhibit complex behaviors, which can lead to difficulties in the determination of parameters and high testing costs. This paper aims to propose an efficient optimization method for identifying the parameters of advanced constitutive model for soft structured clays from only limited conventional triaxial tests. First, a new real-coded genetic algorithm (RCGA) is proposed by combining two new crossover and mutation operators for improving the performance of optimization. A newly developed elastic–viscoplastic model accounting for anisotropy, destructuration and creep features is enhanced with the cross-anisotropy of elasticity and is adopted for test simulations during optimization. Laboratory tests on soft Wenzhou marine clay are selected, with three of them being used as objectives for optimization and others for validation. The optimization process, using the new RCGA with a uniform sampling initialization method, is carried out to obtain the soil parameters. A classic genetic algorithm (NSGA-II)-based optimization is also conducted and compared to the RCGA for estimating the performance of the new RCGA. Finally, the optimal parameters are validated by comparing with other measurements and test simulations on the same clay. All comparisons demonstrate that a reliable solution can be obtained by the new RCGA optimization combined with the appropriate soil model, which is practically useful with a reduction in testing costs.

The scale of fluctuation (SOF) is the critical parameter to describe the soil spatial variability, which significantly influences the embedded geostructures. Due to the limited data in the horizontal direction, horizontal SOF estimation is relatively challenging and not well studied yet. This paper aims to develop an efficient convolutional neural network (CNN)-based approach for estimating the horizontal SOF by coupling random field and limited CPT data. Two or three columns (i.e. pseudo-CPT) were selected from the simulated 2D random field with prescribed SOF at the same spacing and combined into a two-dimensional matrix as input data to train the CNN model, namely CNN2 and CNN3 models. The dataset of CNN2 and CNN3 models contains 196,670 and 149,420 samples. Results on the training and testing datasets show that the trained CNN model has a good estimation performance as the mean squared error value is less than 0.1 and the correlation coefficient value is larger than 0.99. The effectiveness of trained CNN models was further verified by the new simulated CPT data with untrained SOF from the random field and CPT data from real site in Hollywood, South Carolina. The excellent agreement indicates that the trained CNN model has the ability to capture the horizontal SOF for limited CPT data from the actual project. Finally, the collected CPT data from the Shanghai site was applied for application. The COV of the estimated results of CNN3 and CNN2 models for the Shanghai site is 0.09 and 0.40, indicating the estimation performance of the CNN3 model has less variability than the CNN2 model. The proposed method provides the potential to characterize the soil spatial variability using very limited CPT data.

Flaviviruses, including Dengue virus (DENV), Zika virus (ZIKV) and Japanese encephalitis virus (JEV), remain major global health threats, and currently, there are no widely available vaccines for humans. The fusion loop region of the flavivirus envelope protein plays a crucial role in eliciting neutralizing antibodies and providing protection against secondary DENV infections. However, these antibodies often exhibit dual functionalities, with both neutralizing and enhancing activities, posing a challenge for vaccine development. In this study, we focused on optimizing the fusion loop epitope as the primary immunogen and incorporated the adjacent bc loop which we had reported previously as a complementary element, aiming to enhance the immunogen capable of robust neutralization and protection without inducing the risk of antibody-dependent enhancement (ADE). This newly designed immunogen was named as muBCFL which comprises sequences spanning from amino acid 69 to 116 primarily on DENV-2 envelope protein, along with four specific mutations (T76A, W101A, G106Q, and L107D). The synthesized muBCFL peptide elicited neutralizing antibodies against all four DENV serotypes, ZIKV, and JEV, with particularly strong neutralization activity against DENV-2, ZIKV, and JEV. Besides, compared to pre-immune sera, muBCFL-immune sera significantly reduced viremia levels in DENV- or ZIKV-infected AG129 mice and increased the survival rates of JEV-challenged ICR mice. Furthermore, in vitro and in vivo ADE assays validated that muBCFL-immune sera did not induce ADE compared with the control 4G2 monoclonal antibody. These findings indicated that the muBCFL sequence holds great potential as a safe and effective immunogen for developing a flavivirus vaccine in the future.

The emergence of SARS-CoV-2 variants has raised concerns about the sustainability of vaccine-induced immunity. Little is known about the long-term humoral responses and spike-specific T cell memory to Omicron variants, with specific attention to BA.4/5, BQ.1.1, and XBB.1. We assessed immune responses in 50 uninfected individuals who received varying three-dose vaccination combinations (2X AstraZeneca + 1X Moderna, 1X AstraZeneca + 2X Moderna, and 3X Moderna) against wild-type (WT) and Omicron variants at eight months post-vaccination. The serum antibody titers were analyzed by enzyme-linked immunosorbent assays (ELISA), and neutralizing activities were examined by pseudovirus and infectious SARS-CoV-2 neutralization assays. T cell reactivities and their memory phenotypes were determined by flow cytometry. We found that RBD-specific antibody titers, neutralizing activities, and CD4+ T cell reactivities were reduced against Omicron variants compared to WT. In contrast, CD8+ T cell responses, central memory, effector memory, and CD45RA+ effector memory T cells remained unaffected upon stimulation with the Omicron peptide pool. Notably, CD4+ effector memory T cells even exhibited a higher proportion of reactivity against Omicron variants. Furthermore, participants who received three doses of the Moderna showed a more robust response regarding neutralization and CD8+ T cell reactions than other three-dose vaccination groups. Reduction of humoral and CD4+ T cell responses against Omicron variants in vaccinees suggested that vaccine effectiveness after eight months may not have sufficient protection against the new emerging variants, which provides valuable information for future vaccination strategies such as receiving BA.4/5 or XBB.1-based bivalent vaccines.

Sarcopenia, an age-related disease characterized by loss of muscle strength and muscle mass, has attracted the attention of medical experts due to its severe morbidity, low living quality, high expenditure of health care, and mortality. Traditionally, persistent aerobic exercise (PAE) is considered as a valid way to attenuate muscular atrophy. However, nowadays, high intensity interval training (HIIT) has emerged as a more effective and time-efficient method to replace traditional exercise modes. HIIT displays comprehensive effects on exercise capacity and skeletal muscle metabolism, and it provides a time-out for the recovery of cardiopulmonary and muscular functions without causing severe adverse effects. Studies demonstrated that compared with PAE, HIIT showed similar or even higher effects in improving muscle strength, enhancing physical performances and increasing muscle mass of elder people. Therefore, HIIT might become a promising way to cope with the age-related loss of muscle mass and muscle function. However, it is worth mentioning that no study of HIIT was conducted directly on sarcopenia patients, which is attributed to the suspicious of safety and validity. In this review, we will assess the effects of different training parameters on muscle and sarcopenia, summarize previous papers which compared the effects of HIIT and PAE in improving muscle quality and function, and evaluate the potential of HIIT to replace the status of PAE in treating old people with muscle atrophy and low modality; and point out drawbacks of temporary experiments. Our aim is to discuss the feasibility of HIIT to treat sarcopenia and provide a reference for clinical scientists who want to utilize HIIT as a new way to cope with sarcopenia.

A novel five-surface phosphor-in-glass (FS-PiG) structure for high illumination and excellent color uniformity in large-view scale LEDs for sensor light source application is demonstrated. YAG phosphor (Y3Al5O12:Ce3+) was uniformly mixed with ceramic and sintered at 680 °C to form a phosphor wafer. Sophisticated laser engraving was employed on the phosphor wafer to form saddle-shaped large-view scale FS-PiG LEDs. The performance of the FS-PiG LEDs exhibited an illumination of 401 lm, average color temperature (CCT) of 5488 K ± 110 K, and color coordinates (CIE) of (0.3179 ± 0.003, 0.3352 ± 0.003). In contrast to convention single-surface phosphor-in-glass (SS-PiG) LEDs, the performance exhibited an illumination of 380 lm, average CCT of 5830 K ± 758 K, and CIE of (0.3083 ± 0.07, 0.3172 ± 0.07). These indicated that the performance of the FS-PiG LEDs was higher than the SS-PiG LEDs for illumination, CCT, and CIE by 1.7, 7, and 23 times, respectively. Furthermore, the FS-PiG LEDs demonstrate a lower lumen loss of 2% and a reduced chromaticity shift of 5.4 × 10−3 under accelerated aging at 350 °C for 1008 h, owing to the high ceramic melting temperature of up to 510 °C. In this study, the proposed FS-PiG large-view scale LEDs with excellent optical performance and high reliability may be promising candidates to replace the conventional phosphor-in-organic silicone material used in high-power LEDs for the next generation of sensor light sources, display, and headlight applications.