The Characteristics of Long-Wave Irregularities in High-Speed Railway Vertical Curves and Method for Mitigation.

Track geometry measurements (TGMs) are a critical methodology for assessing the quality of track regularities and, thus, are essential for ensuring the safety and comfort of high-speed railway (HSR) operations. TGMs also serve as foundational datasets for engineering departments to devise daily maintenance and repair strategies. During routine maintenance, S-shaped long-wave irregularities (SLIs) were found to be present in the vertical direction from track geometry cars (TGCs) at the beginning and end of a vertical curve (VC). In this paper, we conduct a comprehensive analysis and comparison of the characteristics of these SLIs and design a long-wave filter for simulating inertial measurement systems (IMSs). This simulation experiment conclusively demonstrates that SLIs are not attributed to track geometric deformation from the design reference. Instead, imperfections in the longitudinal profile's design are what cause abrupt changes in the vehicle's acceleration, resulting in the measurement output of SLIs. Expanding upon this foundation, an additional investigation concerning the quantitative relationship between SLIs and longitudinal profiles is pursued. Finally, a method that involves the addition of a third-degree parabolic transition curve (TDPTC) or a full-wave sinusoidal transition curve (FSTC) is proposed for a smooth transition between the slope and the circular curve, designed to eliminate the abrupt changes in vertical acceleration and to mitigate SLIs. The correctness and effectiveness of this method are validated through filtering simulation experiments. These experiments indicate that the proposed method not only eliminates abrupt changes in vertical acceleration, but also significantly mitigates SLIs.

Ultrabroadband two-beam coherent anti-Stokes Raman scattering and spontaneous Raman spectroscopy of organic fluids: A comparative study.

Spontaneous Raman spectroscopy is a well-established diagnostic tool, allowing for the identification of all Raman active species with a single measurement. Yet, it may suffer from low-signal intensity and fluorescent background. In contrast, coherent anti-Stokes Raman scattering (CARS) offers laser-like signals, but the traditional approach lacks the multiplex capability of spontaneous Raman spectroscopy. We present an ultrabroadband CARS setup which aims at exciting the full spectrum (300-3700 cm-1) of biological molecules. A dual-output optical parametric amplifier provides a ~7 fs pump/Stokes and a ~700 fs probe pulse. CARS spectra of DMSO, ethanol, and methanol show great agreement with spontaneous Raman spectroscopy and superiority in fluorescent environments. The spectral resolution proves sufficient to differentiate between the complex spectra of L-proline and hydroxyproline. Moreover, decay constants in the sub picosecond range are determined for individual Raman transitions, providing an additional approach for sample characterization.

Hyperspectal imaging technology for phenotyping iron and boron deficiency in Brassica napus under greenhouse conditions.

Introduction: The micronutrient deficiency of iron and boron is a common issue affecting the growth of rapeseed (Brassica napus). In this study, a non-destructive diagnosis method for iron and boron deficiency in Brassica napus (genotype: Zhongshuang 11) using hyperspectral imaging technology was established. Methods: The recognition accuracy was compared using the Fisher Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) recognition models. Recognition results showed that Multiple Scattering Correction (MSC) could be applied for the full band hyperspectral data processing, while the LDA models presented better performance on establishing the leaf iron and boron deficiency symptom recognition than the SVM models. Results: The recognition accuracy of the training set reached 96.67%, and the recognition rate of the prediction set could be 91.67%. To improve the model accuracy, the Competitive Adaptive Reweighted Sampling algorithm (CARS) was added to construct the MSC-CARS-LDA model. 33 featured wavelengths were selected via CARS. The recognition accuracy of the MSC-CARS-LDA training set was 100%, while the recognition accuracy of the MSC-CARS-LDA prediction set was 95.00%. Discussion: This study indicates that, it is capable to identify the iron and boron deficiency in rapeseed using hyperspectral imaging technology.

Utilizing X-ray diffraction in conjunction with competitive adaptive reweighted sampling (CARS) and principal component analysis for the discrimination of medicinal pearl powder and nacre powder.

Nacre powder, often utilized to counterfeit medicinal pearl powder due to their similar chemical composition and appearance, poses a challenge in product authentication. This study introduces a rapid and efficient method for distinguishing between medicinal pearl powder and nacre powder using X-ray diffraction in conjunction with principal component analysis (PCA). The X-ray diffraction pattern underwent preprocessing techniques including smoothing denoising (Savitzky-Golay filter, 5-point) and second-order derivative analysis. Subsequently, PCA was employed for dimensionality reduction modeling. The CARS method was applied to select optimal variables for model refinement, determining the data preprocessing approach and key modeling variables. This method demonstrates the capability to accurately differentiate between pearl powder, nacre powder, and even counterfeit samples containing up to 90% pearl powder. With a high accuracy rate, swift operational speed, and potential for automation, this approach shows promise for practical implementation in the realm of pearl powder quality control.

The clinical effects of Orff music therapy on children with autism spectrum disorder: a comprehensive evaluation.

Objective: This study aimed to investigate the clinical effects of Orff music therapy on children with Autism Spectrum Disorder (ASD) from the perspectives of parents, evaluators, and therapists. Methods: 93 children with ASD aged 3-6 years participated in the study. They were divided into an observation group (n = 48) receiving comprehensive rehabilitation intervention including Orff music therapy, and a control group (n = 45) receiving only comprehensive rehabilitation intervention. The Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), and Psycho-educational Profile-3rd edition (PEP-3) were used for assessments before and after the intervention. Results: There were no significant demographic differences between the two groups. Both groups showed significant improvements in Sensory, Relating, Language, CVP, EL, RL, VMI, AE, SR, and CARS scores at T1, T2, and T3 (T1 vs. T2, T2 vs. T3, T1 vs. T3) (all p < 0.05). The observation group demonstrated significant changes in Body and Object use and FM, while the control group showed some changes in these domains. Social and self-help, GM, CMB, and CVB also significantly improved in both groups after 6 months of intervention (all p < 0.05). In terms of different time intervals, the observation group showed greater improvements in Sensory, Relating, Language, CARS scores, EL, RL, and SR compared to the control group (all p < 0.05). The improvement levels in Body and Object use, CVP, FM, VMI, and AE did not differ significantly between the two groups in the T1-T2 interval, but were significantly higher in the observation group in the T2-T3 and T1-T3 intervals (all p < 0.05). The magnitude of changes in Social and self-help, GM, CMB, and CVB did not differ significantly between the groups. Conclusion: Orff music therapy showed significant improvements in language expression, language comprehension, social skills, cognitive abilities, imitation abilities, emotional expression and fine motor in children with ASD. These findings provide support for the use of Orff music therapy as an effective intervention for children with ASD.

A Cysteinyl-tRNA Synthetase Mutation Causes Novel Autosomal-Dominant Inheritance of a Parkinsonism/Spinocerebellar-Ataxia Complex.

This study aimed to identify possible pathogenic genes in a 90-member family with a rare combination of multiple neurodegenerative disease phenotypes, which has not been depicted by the known neurodegenerative disease. We performed physical and neurological examinations with International Rating Scales to assess signs of ataxia, Parkinsonism, and cognitive function, as well as brain magnetic resonance imaging scans with seven sequences. We searched for co-segregations of abnormal repeat-expansion loci, pathogenic variants in known spinocerebellar ataxia-related genes, and novel rare mutations via whole-genome sequencing and linkage analysis. A rare co-segregating missense mutation in the CARS gene was validated by Sanger sequencing and the aminoacylation activity of mutant CARS was measured by spectrophotometric assay. This pedigree presented novel late-onset core characteristics including cerebellar ataxia, Parkinsonism, and pyramidal signs in all nine affected members. Brain magnetic resonance imaging showed cerebellar/pons atrophy, pontine-midline linear hyperintensity, decreased rCBF in the bilateral basal ganglia and cerebellar dentate nucleus, and hypo-intensities of the cerebellar dentate nuclei, basal ganglia, mesencephalic red nuclei, and substantia nigra, all of which suggested neurodegeneration. Whole-genome sequencing identified a novel pathogenic heterozygous mutation (E795V) in the CARS gene, meanwhile, exhibited none of the known repeat-expansions or point mutations in pathogenic genes. Remarkably, this CARS mutation causes a 20% decrease in aminoacylation activity to charge tRNACys with L-cysteine in protein synthesis compared with that of the wild type. All family members carrying a heterozygous mutation CARS (E795V) had the same clinical manifestations and neuropathological changes of Parkinsonism and spinocerebellar-ataxia. These findings identify novel pathogenesis of Parkinsonism-spinocerebellar ataxia and provide insights into its genetic architecture.

CAR-T-Cell-Based Cancer Immunotherapies: Potentials, Limitations, and Future Prospects.

Cancer encompasses various elements occurring at the cellular and genetic levels, necessitating an immunotherapy capable of efficiently addressing both aspects. T cells can combat cancer cells by specifically recognizing antigens on them. This innate capability of T cells has been used to develop cellular immunotherapies, but most of them can only target antigens through major histocompatibility complexes (MHCs). New gene-editing techniques such as clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein 9 (CRISPR-cas9) can precisely edit the DNA sequences. CRISPR-cas9 has made it possible to generate genetically engineered chimeric antigen receptors (CARs) that can overcome the problems associated with old immunotherapies. In chimeric antigen receptor T (CAR-T) cell therapy, the patient's T cells are isolated and genetically modified to exhibit synthetic CAR(s). CAR-T cell treatment has shown remarkably positive clinical outcomes in cancers of various types. Nevertheless, there are various challenges that reduce CAR-T effectiveness in solid tumors. It is required to address these challenges in order to make CAR-T cell therapy a better and safer option. Combining CAR-T treatment with other immunotherapies that target multiple antigens has shown positive outcomes. Moreover, recently generated Boolean logic-gated advanced CARs along with artificial intelligence has expanded its potential to treat solid tumors in addition to blood cancers. This review aims to describe the structure, types, and various methods used to develop CAR-T cells. The clinical applications of CAR-T cells in hematological malignancies and solid tumours have been described in detail. In addition, this discussion has addressed the limitations associated with CAR-T cells, explored potential strategies to mitigate CAR-T-related toxicities, and delved into future perspectives.

Coordination dynamics between fuel cell and battery technologies in the transition to clean cars.

Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry's transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry's markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms.

Fully equipped CARs to address tumor heterogeneity, enhance safety, and improve the functionality of cellular immunotherapies.

Although adoptive transfer of chimeric antigen receptor (CAR)-engineered T cells has achieved unprecedented response rates in patients with certain hematological malignancies, this therapeutic modality is still far from fulfilling its remarkable potential, especially in the context of solid cancers. Antigen escape variants, off-tumor destruction of healthy tissues expressing tumor-associated antigens (TAAs), poor CAR-T cell persistence, and the occurrence of functional exhaustion represent some of the most prominent hurdles that limit CAR-T cell ability to induce long-lasting remissions with a tolerable adverse effect profile. In this review, we summarize the main approaches that have been developed to face such bottlenecks, including the adapter CAR (AdCAR) system, Boolean-logic gating, epitope editing, the modulation of cell-intrinsic signaling pathways, and the incorporation of safety switches to precisely control CAR-T cell activation. We also discuss the most pressing issues pertaining to the selection of co-stimulatory domains, with a focus on strategies aimed at promoting CAR-T cell persistence and optimal antitumor functionality.

The inclusion of e-cigarettes and heated tobacco products in smoke-free home and car rules: A cross-sectional survey of adults in Armenia and Georgia.

INTRODUCTION: Understanding who includes e-cigarettes and heated tobacco products (HTPs) in smoke-free home or car rules could inform public health interventions, particularly in countries with high smoking prevalence and recently implemented national smoke-free laws, like Armenia and Georgia. METHODS: In 2022, we conducted a cross-sectional survey among 1468 adults in 28 Armenian and Georgian communities (mean age=42.92 years; 51.4% female, 31.6% past-month smoking). Multilevel regression (accounting for clustering within communities; adjusted for sociodemographics and cigarette use) examined e-cigarette/HTP perceptions (risk, social acceptability) and use intentions in relation to: 1) including e-cigarettes/HTPs in home and car rules among participants with home and car rules, respectively (logistic regressions); and 2) intention to include e-cigarettes/HTPs in home rules (linear regression, 1 = 'not at all' to 7 = 'extremely') among those without home rules. RESULTS: Overall, 72.9% (n=1070) had home rules, 86.5% of whom included e-cigarettes/HTPs; 33.9% (n=498) had car rules, 81.3% of whom included e-cigarettes/HTPs. Greater perceived e-cigarette/HTP risk was associated with including e-cigarettes/HTPs in home rules (AOR=1.28; 95% CI: 1.08-1.50) and car rules (AOR=1.46; 95% CI: 1.14-1.87) and next-year intentions to include e-cigarettes/HTPs in home rules (ß=0.38; 95% CI: 0.25-0.50). Lower e-cigarette/HTP use intentions were associated with including e-cigarettes/HTPs in home rules (AOR=0.75; 95% CI: 0.63-0.88). While perceived social acceptability was unassociated with the outcomes, other social influences were: having children and no other household smokers was associated with including e-cigarettes/HTPs in car rules, and having children was associated with intent to include e-cigarettes/HTPs in home rules. CONCLUSIONS: Interventions to address gaps in home and car rules might target e-cigarette/HTP risk perceptions.

Degradation and Recondensation of Metal Oxide Nanoparticles in Laminar Premixed Flames.

The behavior of technical nanoparticles at high temperatures was measured systematically to detect morphology changes under conditions relevant to the thermal treatment of end-of-life products containing engineered nanomaterials. The focus of this paper is on laboratory experiments, where we used a Bunsen-type burner to add titania and ceria particles to a laminar premixed flame. To evaluate the influence of temperature on particle size distributions, we used SMPS, ELPI and TEM analyses. To measure the temperature profile of the flame, we used coherent anti-Stokes Raman spectroscopy (CARS). The comprehensible data records show high temperatures by measurement and equilibrium calculation for different stoichiometries and argon admixtures. With this, we show that all technical metal oxide nanoparticle agglomerates investigated reform in flames at high temperatures. The originally large agglomerates of titania and ceria build very small nanoparticles (<10 nm/"peak 2") at starting temperatures of <2200 K and <1475 K, respectively (ceria: Tmelt = 2773 K, Tboil = 3873 K/titania: Tmelt = 2116 K, Tboil = 3245 K). Since the maximum flame temperatures are below the evaporation temperature of titania and ceria, enhanced vaporization of titania and ceria in the chemically reacting flame is assumed.

A study of the effects of screen exposure on the neuropsychological development in children with autism spectrum disorders based on ScreenQ.

PURPOSE: To investigate the relationship between multi-dimensional aspects of screen exposure and autistic symptoms, as well as neuropsychological development in children with ASD. METHODS: We compared the ScreenQ and Griffiths Development Scales-Chinese Language Edition (GDS-C) of 636 ASD children (40.79 ± 11.45 months) and 43 typically developing (TD) children (42.44 ± 9.61 months). Then, we analyzed the correlations between ScreenQ and Childhood Autism Rating Scale (CARS), and GDS-C. We further used linear regression model to analyze the risk factors associated with high CARS total scores and low development quotients (DQs) in children with ASD. RESULTS: The CARS of children with ASD was positively correlated with the ScreenQ total scores and "access, frequency, co-viewing" items of ScreenQ. The personal social skills DQ was negatively correlated with the "access, frequency, content, co-viewing and total scores" of ScreenQ. The hearing-speech DQ was negatively correlated with the "frequency, content, co-viewing and total scores" of ScreenQ. The eye-hand coordination DQ was negatively correlated with the "frequency and total scores" of ScreenQ. The performance DQ was negatively correlated with the "frequency" item of ScreenQ. CONCLUSION: ScreenQ can be used in the study of screen exposure in children with ASD. The higher the ScreenQ scores, the more severe the autistic symptoms tend to be, and the more delayed the development of children with ASD in the domains of personal-social, hearing-speech and eye-hand coordination. In addition, "frequency" has the greatest impact on the domains of personal social skills, hearing-speech, eye-hand coordination and performance of children with ASD.

InsT-ALLing CD7 chimeric antigen receptors before transplantation.

In their paper, the authors present their experience with the use of chimeric antigen receptor T cells targeting CD7 as a bridge to allogeneic haematopoietic cell transplantation in patients with relapsed/refractory T-cell acute lymphoblastic leukaemia/lymphoblastic lymphoma. Commentary on: Cao et al. A safety and efficacy study of allogeneic haematopoietic stem cell transplantation for refractory and relapsed T-cell acute lymphoblastic leukaemia/lymphoblastic lymphoma patients who achieved complete remission after autologous CD7 chimeric antigen receptor T-cell therapy. Br J Haematol 2024;204:2351-2364.

Novel Genetic and Biochemical Insights into the Spectrum of NEFL-Associated Phenotypes.

Background: NEFL encodes for the neurofilament light chain protein. Pathogenic variants in NEFL cause demyelinating, axonal and intermediate forms of Charcot-Marie-Tooth disease (CMT) which present with a varying degree of severity and somatic mutations have not been described yet. Currently, 34 different CMT-causing pathogenic variants in NEFL in 174 patients have been reported. Muscular involvement was also described in CMT2E patients mostly as a secondary effect. Also, there are a few descriptions of a primary muscle vulnerability upon pathogenic NEFL variants. Objectives: To expand the current knowledge on the genetic landscape, clinical presentation and muscle involvement in NEFL-related neurological diseases by retrospective case study and literature review. Methods: We applied in-depth phenotyping of new and already reported cases, molecular genetic testing, light-, electron- and Coherent Anti-Stokes Raman Scattering-microscopic studies and proteomic profiling in addition to in silico modelling of NEFL-variants. Results: We report on a boy with a muscular phenotype (weakness, myalgia and cramps, Z-band alterations and mini-cores in some myofibers) associated with the heterozygous p.(Phe104Val) NEFL-variant, which was previously described in a neuropathy case. Skeletal muscle proteomics findings indicated affection of cytoskeletal proteins. Moreover, we report on two further neuropathic patients (16 years old girl and her father) both carrying the heterozygous p.(Pro8Ser) variant, which has been identified as 15% somatic mosaic in the father. While the daughter presented with altered neurophysiology,neurogenic clump feet and gait disturbances, the father showed clinically only feet deformities. As missense variants affecting proline at amino acid position 8 are leading to neuropathic manifestations of different severities, in silico modelling of these different amino acid substitutions indicated variable pathogenic impact correlating with disease onset. Conclusions: Our findings provide new morphological and biochemical insights into the vulnerability of denervated muscle (upon NEFL-associated neuropathy) as well as novel genetic findings expanding the current knowledge on NEFL-related neuromuscular phenotypes and their clinical manifestations. Along this line, our data show that even subtle expression of somatic NEFL variants can lead to neuromuscular symptoms.

Non-invasive methods of monitoring Fe3O4 magnetic nanoparticle toxicity in human liver HepaRG cells using impedance biosensing and Coherent anti-Stokes Raman spectroscopic (CARS) microscopy.

Functionalized nanoparticles have been developed for use in nanomedicines for treating life threatening diseases including various cancers. To ensure safe use of these new nanoscale reagents, various assays for biocompatibility or cytotoxicity in vitro using cell lines often serve as preliminary assessments prior to in vivo animal testing. However, many of these assays were designed for soluble, colourless materials and may not be suitable for coloured, non-transparent nanoparticles. Moreover, cell lines are not always representative of mammalian organs in vivo. In this work, we use non-invasive impedance sensing methods with organotypic human liver HepaRG cells as a model to test the toxicity of PEG-Fe3O4 magnetic nanoparticles. We also use Coherent anti-Stokes Raman Spectroscopic (CARS) microscopy to monitor the formation of lipid droplets as a parameter to the adverse effect on the HepaRG cell model. The results were also compared with two commercial testing kits (PrestoBlue and ATP) for cytotoxicity. The results suggested that the HepaRG cell model can be a more realistic model than commercial cell lines while use of impedance monitoring of Fe3O4 nanoparticles circumventing the uncertainties due to colour assays. These methods can play important roles for scientists driving towards the 3Rs principle - Replacement, Reduction and Refinement.

Three Genes Involved in Different Signaling Pathways, carS, wcoA, and acyA, Participate in the Regulation of Fusarin Biosynthesis in Fusarium fujikuroi.

The phytopathogenic fungus Fusarium fujikuroi has a rich secondary metabolism which includes the synthesis of very different metabolites in response to diverse environmental cues, such as light or nitrogen. Here, we focused our attention on fusarins, a class of mycotoxins whose synthesis is downregulated by nitrogen starvation. Previous data showed that mutants of genes involved in carotenoid regulation (carS, encoding a RING finger protein repressor), light detection (wcoA, White Collar photoreceptor), and cAMP signaling (AcyA, adenylate cyclase) affect the synthesis of different metabolites. We studied the effect of these mutations on fusarin production and the expression of the fus1 gene, which encodes the key polyketide synthase of the pathway. We found that the three proteins are positive regulators of fusarin synthesis, especially WcoA and AcyA, linking light regulation to cAMP signaling. Genes for two other photoreceptors, the cryptochrome CryD and the Vivid flavoprotein VvdA, were not involved in fusarin regulation. In most cases, there was a correspondence between fusarin production and fus1 mRNA, indicating that regulation is mainly exerted at the transcriptional level. We conclude that fusarin synthesis is subject to a complex control involving regulators from different signaling pathways.

Estimation of wheat protein content and wet gluten content based on fusion of hyperspectral and RGB sensors using machine learning algorithms.

The protein content (PC) and wet gluten content (WGC) are crucial indicators determining the quality of wheat, playing a pivotal role in evaluating processing and baking performance. Original reflectance (OR), wavelet feature (WF), and color index (CI) were extracted from hyperspectral and RGB sensors. Combining Pearson-competitive adaptive reweighted sampling (CARs)-variance inflation factor (VIF) with four machine learning (ML) algorithms were used to model accuracy of PC and WGC. As a result, three CIs, six ORs, and twelve WFs were selected for PC and WGC datasets. For single-modal data, the back-propagation neural network exhibited superior accuracy, with estimation accuracies (WF > OR > CI). For multi-modal data, the random forest regression paired with OR + WF + CI showed the highest validation accuracy. Utilizing the Gini impurity, WF outweighed OR and CI in the PC and WGC models. The amalgamation of MLs with multimodal data harnessed the synergies among various remote sensing sources, substantially augmenting model precision and stability.

Major low-energy trauma results in non-specific immunoglobulin generation without evidence for specific autoantibody production: A prospective cohort study.

Cellular debris resulting from large trauma might overwhelm the scavenger mechanisms and lead to autoimmune reactions. We analysed whether a major well-defined trauma in humans induces laboratory signs of transient autoimmunity in the months after the insult. We included 50 patients with pertrochanteric femur fracture undergoing intramedullary nail osteosynthesis in a prospective cohort study and followed them at 3-4 days, 6 weeks, 12 weeks and 12 months postoperatively. By standard techniques, we assessed levels of total immunoglobulins, anti-nuclear antibodies (ANA), anti-cardiolipin antibodies, anti-dsDNA antibodies and anti-C1q antibodies, as well as antibodies against cytomegalovirus (CMV) as a control. Blood leukocyte differential and lymphocyte subpopulations were determined at baseline and in the first two postoperative samples. The mean age of the patients reached 80.1 years, and 23 (46%) completed all visits. Serum concentrations of total IgG, IgM and IgA increased at all follow-up time points. The ANA fluorescence light intensity units increased at 12 weeks and 12 months postoperatively (p < 0.0001), but the proportion of ANA-positive patients did not change (35%). The values of anti-C1q mildly increased at all follow-up visits, but not the ratio to total IgG. Anti-dsDNA remained negative in all patients, and anti-cardiolipin IgG/IgM antibodies did not change. Anti-CMV IgG antibodies increased significantly at all follow-up visits, without change in the ratio to total IgG. Flow cytometry showed an increased proportion of B-cells 3-4 days postoperatively. In conclusion, major musculoskeletal trauma in elderly patients induces a generalized non-specific increase in immunoglobulin production without laboratory signs for enhanced systemic autoimmunity.

Probing delivery of a lipid nanoparticle encapsulated self-amplifying mRNA vaccine using coherent Raman microscopy and multiphoton imaging.

The COVID-19 pandemic triggered the resurgence of synthetic RNA vaccine platforms allowing rapid, scalable, low-cost manufacturing, and safe administration of therapeutic vaccines. Self-amplifying mRNA (SAM), which self-replicates upon delivery into the cellular cytoplasm, leads to a strong and sustained immune response. Such mRNAs are encapsulated within lipid nanoparticles (LNPs) that act as a vehicle for delivery to the cell cytoplasm. A better understanding of LNP-mediated SAM uptake and release mechanisms in different types of cells is critical for designing effective vaccines. Here, we investigated the cellular uptake of a SAM-LNP formulation and subsequent intracellular expression of SAM in baby hamster kidney (BHK-21) cells using hyperspectral coherent anti-Stokes Raman scattering (HS-CARS) microscopy and multiphoton-excited fluorescence lifetime imaging microscopy (FLIM). Cell classification pipelines based on HS-CARS and FLIM features were developed to obtain insights on spectral and metabolic changes associated with SAM-LNPs uptake. We observed elevated lipid intensities with the HS-CARS modality in cells treated with LNPs versus PBS-treated cells, and simultaneous fluorescence images revealed SAM expression inside BHK-21 cell nuclei and cytoplasm within 5 h of treatment. In a separate experiment, we observed a strong correlation between the SAM expression and mean fluorescence lifetime of the bound NAD(P)H population. This work demonstrates the ability and significance of multimodal optical imaging techniques to assess the cellular uptake of SAM-LNPs and the subsequent changes occurring in the cellular microenvironment following the vaccine expression.

A novel method of using sound waves and artificial intelligence for the detection of vehicle's proximity from cyclists and E-scooters.

Outdoor air pollution has been found to have a significant adverse effect on health. When the authors attempted to monitor air quality that cyclists or e-scooter users' breath during commuting in different locations for health and safety analysis, it was found that the existence of internal combustion engine (ICE) cars has a significant effect on the pollution levels and the monitoring process. To comprehensively study the effect of cars and traffic on air quality that cyclists and e-scooters users experience, a low-cost and reliable system was needed to detect the proximity of cars that have diesel or petrol engines. Video cameras can be used to visually detect vehicles, but in the modern age with the existence of many electric and hybrid vehicles and the need to reduce the cost of instrumentation, there was a need to determine the passing of vehicles near e-scooter and bike users from the combined engine and tires sounds. To address this issue, this study suggests a novel approach of using sound waves of internal combustion engines and tire sounds during the passing of cars, combined with AI techniques (neural networks), to detect the proximity of cars from cyclists and e-scooter users. Audio-visual data was collected using Go-Pro cameras in order to combine the data with GPS location and pollution levels. Geographical data maps were produced to demonstrate the density of cars that cyclists encounter when on or near the road. This method will enable air quality monitoring research to detect the existence of ICE cars for future correlation with measured pollution levels. The proposed method allows for:•The automated selection of sensitive features from sound waves to detect vehicles.•Low-cost hardware which is independent of orientation that can be integrated with other air quality and GPS sensors.•The successful application of sensor fusion and neural networks.