Explaining the differences of gait patterns between high and low-mileage runners with machine learning

Running gait patterns have implications for revealing the causes of injuries between higher-mileage runners and low-mileage runners. However, there is limited research on the possible relationships between running gait patterns and weekly running mileages. In recent years, machine learning algorithms have been used for pattern recognition and classification of gait features to emphasize the uniqueness of gait patterns. However, they all have a representative problem of being a black box that often lacks the interpretability of the predicted results of the classifier. Therefore, this study was conducted using a Deep Neural Network (DNN) model and Layer-wise Relevance Propagation (LRP) technology to investigate the differences in running gait patterns between higher-mileage runners and low-mileage runners. It was found that the ankle and knee provide considerable information to recognize gait features, especially in the sagittal and transverse planes. This may be the reason why high-mileage and low-mileage runners have different injury patterns due to their different gait patterns. The early stages of stance are very important in gait pattern recognition because the pattern contains effective information related to gait. The findings of the study noted that LRP completes a feasible interpretation of the predicted results of the model, thus providing more interesting insights and more effective information for analyzing gait patterns

A new method applied for explaining the landing patterns:interpretability analysis of machine learning

As one of many fundamental sports techniques, the landing maneuver is also frequently used in clinical injury screening and diagnosis. However, the landing patterns are different under different constraints, which will cause great difficulties for clinical experts in clinical diagnosis. Machine learning (ML) have been very successful in solving a variety of clinical diagnosis tasks, but they all have the disadvantage of being black boxes and rarely provide and explain useful information about the reasons for making a particular decision. The current work validates the feasibility of applying an explainable ML (XML) model constructed by Layer-wise Relevance Propagation (LRP) for landing pattern recognition in clinical biomechanics. This study collected 560 groups landing data. By incorporating these landing data into the XML model as input signals, the prediction results were interpreted based on the relevance score (RS) derived from LRP. The interpretation obtained from XML was evaluated comprehensively from the statistical perspective based on Statistical Parametric Mapping (SPM) and Effect Size. The RS has excellent statistical characteristics in the interpretation of landing patterns between classes, and also conforms to the clinical characteristics of landing pattern recognition. The current work highlights the applicability of XML methods that can not only satisfy the traditional decision problem between classes, but also largely solve the lack of transparency in landing pattern recognition. We provide a feasible framework for realizing interpretability of ML decision results in landing analysis, providing a methodological reference and solid foundation for future clinical diagnosis and biomechanical analysis

Magnetically-dressed CrSBr exciton-polaritons in ultrastrong coupling regime

The strong coupling between photons and matter excitations such as excitons, phonons, and magnons is of central importance in the study of light-matter interactions. Bridging the flying and stationary quantum states, the strong light-matter coupling enables the coherent transmission, storage, and processing of quantum information, which is essential for building photonic quantum networks. Over the past few decades, exciton-polaritons have attracted substantial research interest due to their half-light-half-matter bosonic nature. Coupling exciton-polaritons with magnetic orders grants access to rich many-body phenomena, but has been limited by the availability of material systems that exhibit simultaneous exciton resonances and magnetic ordering. Here we report magnetically-dressed microcavity exciton-polaritons in the van der Waals antiferromagnetic (AFM) semiconductor CrSBr coupled to a Tamm plasmon microcavity. Angle-resolved spectroscopy reveals an exceptionally high exciton-polariton coupling strength attaining 169 meV, demonstrating ultrastrong coupling that persists up to room temperature. Temperature-dependent exciton-polariton spectroscopy senses the magnetic order change from AFM to paramagnetism in CrSBr, confirming its magnetic nature. By applying an out-of-plane magnetic field, an effective tuning of the polariton energy is further achieved while maintaining the ultrastrong exciton-photon coupling strength, which is attributed to the spin canting process that modulates the interlayer exciton interaction. Our work proposes a hybrid quantum platform enabled by robust opto-electronic-magnetic coupling, promising for quantum interconnects and transducers.Comment: 8 pages, 4 figure

SRSF1 modulates PTPMT1 alternative splicing to regulate lung cancer cell radioresistance

Background Radioresistance is the major cause of cancer treatment failure. Additionally, splicing dysregulation plays critical roles in tumorigenesis. However, the involvement of alternative splicing in resistance of cancer cells to radiotherapy remains elusive. We sought to investigate the key role of the splicing factor SRSF1 in the radioresistance in lung cancer. Methods Lung cancer cell lines, xenograft mice models, and RNA-seq were employed to study the detailed mechanisms of SRSF1 in lung cancer radioresistance. Clinical tumor tissues and TCGA dataset were utilized to determine the expression levels of distinct SRSF1-regulated splicing isoforms. KM-plotter was applied to analyze the survival of cancer patients with various levels of SRSF1-regulated splicing isoforms. Findings Splicing factors were screened to identify their roles in radioresistance, and SRSF1 was found to be involved in radioresistance in cancer cells. The level of SRSF1 is elevated in irradiation treated lung cancer cells, whereas knockdown of SRSF1 sensitizes cancer cells to irradiation. Mechanistically, SRSF1 modulates various cancer-related splicing events, particularly the splicing of PTPMT1, a PTEN-like mitochondrial phosphatase. Reduced SRSF1 favors the production of short isoforms of PTPMT1 upon irradiation, which in turn promotes phosphorylation of AMPK, thereby inducing DNA double-strand break to sensitize cancer cells to irradiation. Additionally, the level of the short isoform of PTPMT1 is decreased in cancer samples, which is correlated to cancer patients' survival. Conclusions Our study provides mechanistic analyses of aberrant splicing in radioresistance in lung cancer cells, and establishes SRSF1 as a potential therapeutic target for sensitization of patients to radiotherapy

Can the entire function of the foot be concentrated in the forefoot area during the running stance phase? A finite element study of different shoe soles

The goal of this study was to use the finite element (FE) method to compare and study the differences between bionic shoes (BS) and normal shoes (NS) forefoot strike patterns when running. In addition, we separated the forefoot area when forefoot running as a way to create a small and independent area of instability. An adult male of Chinese descent was recruited for this investigation (age: 26 years old; body height: 185 cm; body mass: 82 kg) (forefoot strike patterns). We analyzed forefoot running under two different conditions through FE analysis, and used bone stress distribution feature classification and recognition for further analysis. The metatarsal stress values in forefoot strike patterns with BS were less than with NS. Additionally, the bone stress classification of features and the recognition accuracy rate of metatarsal (MT) 2, MT3 and MT5 were higher than other foot bones in the first 5%, 10%, 20% and 50% of nodes. BS forefoot running helped reduce the probability of occurrence of metatarsal stress fractures. In addition, the findings further revealed that BS may have important implications for the prevention of hallux valgus, which may be more effective in adolescent children. Finally, this study presents a post-processing method for FE results, which is of great significance for further understanding and exploration of FE results

Sulfur resistance of Ce-Mn/TiO2 catalysts for low-temperature NH3–SCR

Ce-Mn/TiO2 catalyst prepared using a simple impregnation method demonstrated a better low-temperature selective catalytic reduction of NO with NH3 (NH3–SCR) activity in comparison with the sol-gel method. The Ce-Mn/TiO2 catalyst loading with 20% Ce had the best low-temperature activity and achieved a NO conversion rate higher than 90% at 140–260°C with a 99.7% NO conversion rate at 180°C. The Ce-Mn/TiO2 catalyst only had a 6% NO conversion rate decrease after 100ppm of SO2 was added to the stream. When SO2 was removed from the stream, the catalyst was able to recover completely. The crystal structure, morphology, textural properties and valence state of the metals involving the novel catalysts were investigated using X-ray diffraction, N2 adsorption and desorption analysis, X-ray photoelectron spectroscopy, scanning electron microscopy and energy dispersive spectroscopy, respectively. The decrease of NH3–SCR performance in the presence of 100ppm SO2 was due to the decrease of the surface area, change of the pore structure, the decrease of Ce4+ and Mn4+ concentration and the formation of the sulfur phase chemicals which blocked the active sites and changed the valence status of the elements

Occurrence Dynamics of Citrus Target Spot in Wanzhou District of Chongqing City and Compound Fungicide Screening of

To explore the occurrence dynamics and infection characteristics of citrus target spot, and screen effective fungicides and provide data support for citrus safe production. Two orchards with different altitudes and different management levels in Shuangshi community and Baiyan Village of Wanzhou District Chongqing city were selected to follow up the occurrence of citrus target spot. At the same time, the inhibition effects of 6 compound fungicides to Pseud of abraea Citricarpa (Citrus Target spot) were determined by the mycelial growth rate inhibition method. The results showed that, in December of 2021 to March of 2022, in the 2 orchards, the average disease spot, number of falling leaf showed a trend of reduce after the first rise, and incidence and disease index were characterized by rising gradually along with the passage of time. From late to the end of January, there were more rainy and foggy days, and the temperature dropped sharply, which aggravated the defoliation. Orchard 1 was with higher altitude 750 m and loose management, and the disease outbreak came more rapidly and severely. While in orchard 2, the lower altitude, higher management level and stronger tree made the disease be later and lighter than orchard 1. Further studies of compound fungicide screening showed that the EC50 against Ps. Citricarpa, from low to high, was 40% Tebuconazole·Prochloraz (0.03295)<13% Thifluzamide·Hexaconazole (0.03634)<30% Difenoconazole·Propiconazole (0.03881)<40% Difenoconazole·Pyraclostrobin (0.30849)<30% Thifluzamide·Tebuconazole (0.90167)<33 % Kasugamycin·Copper Quinoline (2.92935). These fungicides can be used for further research in the field test