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Femtosecond laser filamentation is a unique nonlinear optical phenomenon when high-power ultrafast laser propagation in all transparent optical media. During filamentation in the atmosphere, the ultrastrong field of 1013–1014 W/cm2 with a large distance ranging from meter to kilometers can effectively ionize, break, and excite the molecules and fragments, resulting in characteristic fingerprint emissions, which provide a great opportunity for investigating strong-field molecules interaction in complicated environments, especially remote sensing. Additionally, the ultrastrong intensity inside the filament can damage almost all the detectors and ignite various intricate higher order nonlinear optical effects. These extreme physical conditions and complicated phenomena make the sensing and controlling of filamentation challenging. This paper mainly focuses on recent research advances in sensing with femtosecond laser filamentation, including fundamental physics, sensing and manipulating methods, typical filament-based sensing techniques and application scenarios, opportunities, and challenges toward the filament-based remote sensing under different complicated conditions.

Background Ischemic stroke (IS) remains a leading cause of mortality and disability, with limited therapeutic options due to poor drug delivery to ischemic lesions. To address this challenge, an engineered Salmonella based therapeutic method for targeted drug delivery and long-term treatment is herein designed to mitigate ischemic damage. Methods We engineered an attenuated luminescent Salmonella typhimurium ( S.t -ΔpG) strain with an L-arabinose-inducible pBAD system to secrete bioactive FGF21. C57BL/6 mice were used to to measure neuron apoptosis and the activity of immune cells following IS induction plus S.t -ΔpG injection. Bioluminescence imaging was applied for bacterial colonization. ELISA and glucose uptake assays were performed to detect FGF21 secretion and the bioactivity. Neurological tests, TTC staining, and TUNEL labeling were used to assess the therapeutic effects of barterially secreted FGF21. Immunofluorescence assay of FGF21/FGFR1 dominant pathway was explored to investigate neuroprotective mechanism, while IBA-1 staining, CD3/CD68 immunostaining, cytokine profiling, and hepatorenal histopathology were detected to evaluate biosecurity. Results S.t -ΔpG FGF21 selectively colonized peri-infarct regions and secreted functional FGF21, reducing neurologic deficits (48%) and infarct volume (46%) versus controls ( p  < 0.01). Mechanistically, immunofluorescence demonstrated that bacterially secreted FGF21 activated neuronal FGFR1/AMPK/mTOR pathway to enhance autophagy, whereas autophagy inhibition abolished its neuroprotection. Further, bacterial exclusion from neuron was validated via MAP2/NeuN plus Salmonella co-staining in primary neuron cells and brain tissue. Critically, CD3/CD68 immunostaining, serum cytokine profiling, and hepatorenal histopathology confirmed the long-term biosafety of this approach. Conclusion Our study presents a novel, Salmonella - based platform for targeted and sustained FGF21 delivery, offering a promising therapeutic strategy for ischemic stroke with robust efficacy and minimal systemic toxicity.

Forest is the largest vegetation carbon pool in the global terrestrial ecosystem. The spatial distribution and change of forest biomass are of importance to reveal the surface spatial variation and driving factors, to analyze and evaluate forest productivity, and to evaluate ecological function of forest. In this study, broad-leaved forests located in a typical state nature reserve in northern subtropics were selected as the study area. Based on ground survey data and high-resolution remote sensing images, three machine learning models were used to identify the best remote sensing quantitative inversion model of forest biomass. The biomass of broad-leaved forest with 30-m resolution in the study area from 1998 to 2016 was estimated by using the best model about every two years. With the estimated biomass, multiple leading factors to cause biomass temporal change were then identified from dozens of remote sensing factors by investigating their nonlinear correlations. Our results showed that the artificial neural network (ANN) model was the best (R2 = 0.8742) among the three, and its accuracy was also much higher than that of the traditional linear or nonlinear models. The mean biomass of the broad-leaved forest in the study area from 1998 to 2016 ranged from 90 to 145 Mg ha−1, showing an obvious temporal variation. Instead of biomass, biomass change (BC) was studied further in this research. Significant correlations were found between BC in broad-leaved forest and three climate factors, including average daily maximum surface temperature, maximum precipitation, and maximum mean temperature. It was also found that BC has a strong correlation with the biomass at the previous time (i.e., two years ago). Those quantitative correlations were used to construct a linear model of BC with high accuracy (R2 = 0.8873), providing a new way to estimate the biomass change of two years later based on the observations of current biomass and the three climate factors.

Photon upconversion through high harmonic generation, multiphoton absorption, Auger recombination and phonon scattering performs a vital role in energy conversion and renormalization. Considering the reduced dielectric screening and enhanced Coulomb interactions, semiconductor monolayers provide a promising platform to explore photon upconversion at room temperature. Additionally, two-photon upconversion was recently demonstrated as an emerging technique to probe the excitonic dark states due to the extraordinary selection rule compared with conventional excitation. However, highly efficient two-photon upconversion still remains challenging due to the limited multiphoton absorption efficiency and long radiative lifetimes. Here, a 2440-fold enhancement of two-photon luminescence (TPL) is achieved in doubly resonant plasmonic nanocavities due to the amplified light collection, enhanced excitation rate, and increased quantum efficiency. To gain more insight into the attractive doubly resonant enhancement in such a plasmon−exciton coupling system, the intriguing thermally tuned excitonic upconversion and optimized amplification factor >3000 are realized at 350 K. Meanwhile, the single resonance enhanced photoluminescence (PL) (~890-fold) and second-harmonic generation (SHG) (~134-fold) are elaborately demonstrated. These results establish a foundation for developing cost-effective, high-performance nonlinear photonic devices and probing fine excitonic states via configuring plasmonic nanocavities. Two-photon upconversion of 2D exciton was enhanced by 2440-fold in doubly-resonant nanocavity due to combined field localization and Purcell effect.

Two-dimensional excitons, characterized by high binding energy and valley pseudospin, are key to advancing photonic and electronic devices through controlled spatiotemporal dynamics of exciton flux. However, optimizing excitonic transport and emission dynamics, considering potential disorder and phonon scattering, requires further research. This study systematically investigates the effects of hexagonal boron nitride (hBN) encapsulation on semiconductor monolayers. Time-resolved photoluminescence (TRPL) and femtosecond pump-probe techniques reveal that encapsulation reduces excitonic radiative lifetime and enhances exciton-exciton annihilation, due to increased dielectric screening, which enlarges the Bohr radius and decreases binding energy. It also manages phonon scattering and thermal fluctuations, confirming non-monotonic temperature effects on emission and diffusion. The reduced disorder by hBN leads to a lowered optimized temperature from 250 K to 200 K, concurrently resulting in a doubled enhancement of the effective exciton diffusion coefficient. These findings highlight the importance of thermal and dielectric environmental control for ultrafast 2D exciton-based devices.

Cell fate and proliferation ability can be transformed through reprogramming technology. Reprogramming glioblastoma cells into neuron-like cells holds great promise for glioblastoma treatment, as it induces their terminal differentiation. NeuroD4 (Neuronal Differentiation 4) is a crucial transcription factor in neuronal development and has the potential to convert astrocytes into functional neurons. In this study, we exclusively employed NeuroD4 to reprogram glioblastoma cells into neuron-like cells. In vivo, the reprogrammed glioblastoma cells demonstrated terminal differentiation, inhibited proliferation, and exited the cell cycle. Additionally, NeuroD4 virus-infected xenografts exhibited smaller sizes compared to the GFP group, and tumor-bearing mice in the GFP+NeuroD4 group experienced prolonged survival. Mechanistically, NeuroD4 overexpression significantly reduced the expression of SLC7A11 and Glutathione peroxidase 4 (GPX4). The ferroptosis inhibitor ferrostatin-1 effectively blocked the NeuroD4-mediated process of neuron reprogramming in glioblastoma. To summarize, our study demonstrates that NeuroD4 overexpression can reprogram glioblastoma cells into neuron-like cells through the SLC7A11-GSH-GPX4 signaling pathway, thus offering a potential novel therapeutic approach for glioblastoma.

Background and aims Several malignant solid tumors have been reported to have an abnormal expression of the long non-coding RNA CASC15 (lncRNA CASC15 ). However, the clinicopathologic and prognostic importance of CASC15 in solid tumors are unknown. As a result, we examined the interrelationship between CASC15 , overall survival length, and clinicopathological attributes of cancers affecting humans by analyzing various studies and The Cancer Genome Atlas (TCGA) data related to CASC15 expression. Methods Web of Science, PubMed, Cochrane Library, Embase, Chinese WanFang, and Chinese CNKI databases were used to conduct a literature search. Hazard ratios (HRs) and Pooled odds ratios (ORs) were calculated taking 95% confidence intervals (CIs). The results of the current meta-analysis were further validated using TCGA datasets. Results A total of 12 eligible studies enrolling 767 patients were included in this meta-analysis. Findings of the analysis showed that CASC15 expression had a significant relation to the metastasis of lymph node (OR = 3.30, 95%CI = 1.88–5.81, p  < 0.001), distant metastasis (OR = 2.64, 95%CI = 1.24–5.63, p  = 0.012), and high TNM/clinical stage (OR = 2.67, 95%CI = 1.34–5.32, p  = 0.005). Additionally, we found that a poor outcome for overall survival (OS) was predicted by an elevation in CASC15 expression (HR = 2.01, 95%CI = 1.71–2.36, p  < 0.001). Further investigation of the TCGA dataset revealed that CASC15 had abnormal expression in many cancers, which at least partially validated the findings of the current meta-analysis. Conclusions According to the latest meta-analysis and systematic review, high expression levels of CASC15 are associated with poor survival outcomes for solid tumor patients, and the use of CASC15 as a solid tumor prognostic predictor has a solid theoretical foundation.

Artificial Intelligence as an emerging technology in a large number of applications at the same time gradually revealed many ethical issues. Artificial Intelligence ethics education has become an important initiative and a key link in the implementation of the fundamental task of moral education in Chinese higher education institutions, however, Artificial Intelligence ethics education in professional courses often lags behind the education of course knowledge and skills, and it is difficult to achieve the integration of the three educational requirements. This paper proposes that Artificial Intelligence ethics education in professional courses should meet the requirements of the progression of course teaching objectives and adapt to the changes of educational traits from explicit and implicit to integration, and puts forward a practical path of Artificial Intelligence ethics education in professional courses that is consistent with the objectives, adapted to the traits, and constructed with multiple synergies according to the progression of the educational objectives of the professional course system and the changes of the educational traits. This paper also proposes the following suggestions for ethical education in professional courses: in order to achieve the goals of ethical teaching, it is necessary to establish connections between courses at different stages of cultivation, so that each course forms a hierarchical, collaborative, and supportive relationship. After the relationship is established, it is necessary to strengthen the collaborative participation of various subjects and corresponding practical guarantees in the specific teaching practice. This helps to form a system of Artificial Intelligence ethics education throughout the whole process, which in turn improves students' Artificial Intelligence ethics literacy.

Sterol regulatory element-binding protein （SREBP） transcription factors are master regulators of cellular lipid homeostasis in mammals and oxygen-responsive regulators of hypoxic adaptation in fungi. SREBP C-terminus binds to the WD40 domain of SREBP cleavage-activating protein （SCAP）, which confers sterol regulation by controlling the ER-to-Golgi transport of the SREBP-SCAP complex and access to the activating proteases in the Golgi. Here, we biochemically and structurally show that the carboxyl terminal domains （CTD） of Srel and Scpl, the fission yeast SREBP and SCAP, form a functional 4：4 oligomer and SreI-CTD forms a dimer of dimers. The crystal structure of Sre1-CTD at 3.5 A and cryo-EM structure of the complex at 5.4 A together with in vitro biochemical evidence eluci- date three distinct regions in SreI-CTD required for Scpl binding, SreI-CTD dimerization and tetrameric formation. Finally, these structurally identified domains are validated in a cellular context, demonstrating that the proper 4：4 oligomeric complex formation is required for Srel activation.

The thrust of the thesis work is to investigate and determine the fracture parameters of interface cracks. Both the oscillatory model and the contact model are used to study the fracture behavior of interface cracks for small scale contact condition and large contact condition with friction, respectively. For interface cracks with their surfaces in small scale contact, the existing solutions for interfacial cracks in bimaterial media obtained from the contact model and oscillatory model were compared. The oscillatory neartip stress field was found to agree very well with that of the contact model except for the extremely small contact zone. Using the oscillatory solution, Mode I and Mode II \"strain energy release rates\" for finite crack extensions were obtained in terms of the stress intensity factors and the assumed crack extension $\\Delta a$ for interface cracks lying between three different kinds of media, i.e.. two dissimilar isotropic materials; two dissimilar general orthotropic media with one plane of material symmetry in $x\\sb1 - x\\sb2$ plane; and two dissimilar monoclinic media. Finite elements in conjunction with the crack closure method were used to calculate these \"strain energy release rates\" from which accurate stress intensity factors were obtained. An alternative method based on crack surface displacement ratio was also introduced to obtain stress intensity factors. Numerical examples were studied to show their accuracy and implementation. For interface cracks with friction, the concept of strain energy release rate for interfacial cracks in the presence of friction is reexamined. A finite element based numerical procedure is introduced to calculate the strain energy release rate and energy dissipation due to friction for a finite crack extension. Thus, the finite extension strain energy release rate with a fixed crack extension can be used to represent the magnitude of the singular stress field and, therefore, to quantitatively characterize the intrinsic fracture toughness. For numerical examples, a center crack in an infinite bimaterial media under pure shear and combined compression and shear were studied to understand the neartip singularity nature and concept of strain energy release rates. Both fiber pull-out and push-out tests were simulated for illustration of this application.