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Abstract The prevalence of osteoporosis has drastically increased recently. It is not only the most frequent but is also a major global public health problem due to its high morbidity. There are many risk factors associated with osteoporosis were identified. However, most studies have used the traditional multiple linear regression (MLR) to explore their relationships. Recently, machine learning (Mach-L) has become a new modality for data analysis because it enables machine to learn from past data or experiences without being explicitly programmed and could capture nonlinear relationships better. These methods have the potential to outperform conventional MLR in disease prediction. In the present study, we enrolled a Chinese post-menopause cohort followed up for 4 years. The difference of T-score (δ-T score) was the dependent variable. Information such as demographic, biochemistry and life styles were the independent variables. Our goals were: (1) Compare the prediction accuracy between Mach-L and traditional MLR for δ-T score. (2) Rank the importance of risk factors (independent variables) for prediction of δ T-score. Totally, there were 1698 postmenopausal women were enrolled from MJ Health Database. Four different Mach-L methods namely, Random forest (RF), eXtreme Gradient Boosting (XGBoost), Naïve Bayes (NB), and stochastic gradient boosting (SGB), to construct predictive models for predicting δ-BMD after four years follow-up. The dataset was then randomly divided into an 80% training dataset for model building and a 20% testing dataset for model testing. A 10-fold cross-validation technique for hyperparameter tuning was used. The model with the lowest root mean square error for the validation dataset was viewed as the best model for each ML method. The averaged metrics of the RF, SGB, NB, and XGBoost models were used to compare the model performance of the benchmark MLR model that used the same training and testing dataset as the Mach-L methods. We defined that the priority demonstrated in each model ranked 1 as the most critical risk factor and 22 as the last selected risk factor. For Pearson correlation, age, education, BMI, HDL-C, and TSH were positively and plasma calcium level, and baseline T-score were negatively correlated with δ-T score. All four Mach-L methods yielded lower prediction errors than the MLR method and were all convincing Mach-L models. From our results, it could be noted that education level is the most important factor for δ-T Score, followed by DBP, smoking, SBP, UA, age, and LDL-C. All four Mach-L outperformed traditional MLR. By using Mach-L, the most important six risk factors were selected which are, from the most important to the least: DBP, SBP, UA, education level, TG and sleeping hour. δ T score was positively related to SBP, education level, UA and TG and negatively related to DBP and sleeping hour in postmenopausal Chinese women.

Abstract Two‐photon high‐speed fluorescence calcium imaging stands as a mainstream technique in neuroscience for capturing neural activities with high spatiotemporal resolution. However, challenges arise from the inherent tradeoff between acquisition speed and image quality, grappling with a low signal‐to‐noise ratio (SNR) due to limited signal photon flux. Here, a contrast‐enhanced video‐rate volumetric system, integrating a tunable acoustic gradient (TAG) lens‐based high‐speed microscopy with a TAG‐SPARK denoising algorithm is demonstrated. The former facilitates high‐speed dense z‐sampling at sub‐micrometer‐scale intervals, allowing the latter to exploit the spatial redundancy of z‐slices for self‐supervised model training. This spatial redundancy‐based approach, tailored for 4D (xyzt) dataset, not only achieves >700% SNR enhancement but also retains fast‐spiking functional profiles of neuronal activities. High‐speed plus high‐quality images are exemplified by in vivo Purkinje cells calcium observation, revealing intriguing dendritic‐to‐somatic signal convolution, i.e., similar dendritic signals lead to reverse somatic responses. This tailored technique allows for capturing neuronal activities with high SNR, thus advancing the fundamental comprehension of neuronal transduction pathways within 3D neuronal architecture.

Abstract By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma.

This study presents the development of thiol–maleimide/thiol–thiol double self-crosslinking hyaluronic acid-based (dscHA) hydrogels for use as dermal fillers. Hyaluronic acid with varying degrees of maleimide substitution (10%, 20%, and 30%) was synthesized and characterized, and dscHA hydrogels were fabricated using two molecular weights of four-arm polyethylene glycol (PEG10K/20K)–thiol as crosslinkers. The six resulting dscHA hydrogels demonstrated solid-like behavior with distinct physical and rheological properties. SEM analysis revealed a decrease in porosity with higher crosslinker MW and maleimide substitution. The swelling ratios of the six hydrogels reached equilibrium at approximately 1 h and ranged from 20% to 35%, indicating relatively low swelling. Degradation rates decreased with increasing maleimide substitution, while crosslinker MW had little effect. Higher maleimide substitution also required greater injection force. Elastic modulus (G′) in the linear viscoelastic region increased with maleimide substitution and crosslinker MW, indicating enhanced firmness. All hydrogels displayed similar creep-recovery behavior, showing instantaneous deformation under constant stress. Alternate-step strain tests indicated that all six dscHA hydrogels could maintain elasticity, allowing them to integrate with the surrounding tissue via viscous deformation caused by the stress exerted by changes in facial expression. Ultimately, the connection between the clinical performance of the obtained dscHA hydrogels used as dermal filler and their physicochemical and rheological properties was discussed to aid clinicians in the selection of the most appropriate hydrogel for facial rejuvenation. While these findings are promising, further studies are required to assess irritation, toxicity, and in vivo degradation before clinical use. Overall, it was concluded that all six dscHA hydrogels show promise as dermal fillers for various facial regions.

The China Seismo-Electromagnetic Satellite (CSES-01) is the first satellite of the space-based observational platform for the earthquake (EQ) monitoring system in China. It aims to monitor the ionospheric disturbances related to EQ activities by acquiring global electromagnetic fields, ionospheric plasma, energy particles, etc., opening a new path for innovative explorations of EQ prediction. This study analyzed 47 shallow strong EQ cases (Ms ≥ 7 and depth ≤ 100 km) recorded by CSES-01 from its launch in February 2018 to February 2023. The results show that: (1) For the majority (90%) of shallow strong EQs, at least one payload onboard CSES-01 recorded discernible abnormal signals before the mainshocks, and for over 65% of EQs, two or three payloads simultaneously recorded ionospheric disturbances; (2) the majority of anomalies recorded by different payloads onboard CSES-01 predominantly manifest within one week before or on the mainshock day, or occasionally about 11–15 days or 20–25 days before the mainshock; (3) typically, the abnormal signal detected by CSES-01 does not directly appear overhead the epicenter, but rather hundreds of kilometers away from the epicenter, and more preferably toward the equatorward direction; (4) the anomaly recognition rate of each payload differs, with the highest rate reaching more than 70% for the Electric Field Detector (EFD), Search-Coil Magnetometer (SCM), and Langmuir Probe (LAP); (5) for the different parameters analyzed in this study, the plasma density from LAP, and electromagnetic field in the ULF band recorded by EFD and SCM, and energetic electrons from the High-Energy Particle Package (HEPP) show a relatively high occurrence of abnormal phenomena during the EQ time. Although CSES-01 has recorded prominent ionospheric anomalies for a significant portion of EQ cases, it is still challenging to accurately extract and confirm the real seismic precursor signals by relying solely on a single satellite. The combination of seismology, electromagnetism, geodesy, geochemistry, and other multidisciplinary means is needed in the future’s exploration to get infinitely closer to addressing the global challenge of EQ prediction.

Abstract The canonical studies on Mie scattering unravel strong electric/magnetic optical responses in nanostructures, laying foundation for emerging meta-photonic applications. Conventionally, the morphology-sensitive resonances hinge on the normalized frequency, i.e. particle size over wavelength, but non-paraxial incidence symmetry is overlooked. Here, through confocal reflection microscopy with a tight focus scanning over silicon nanostructures, the scattering point spread functions unveil distinctive spatial patterns featuring that linear scattering efficiency is maximal when the focus is misaligned. The underlying physical mechanism is the excitation of higher-order multipolar modes, not accessible by plane wave irradiation, via displacement resonance, which showcases a significant reduction of nonlinear response threshold, sign flip in all-optical switching, and spatial resolution enhancement. Our result fundamentally extends the century-old light scattering theory, and suggests new dimensions to tailor Mie resonances.

Tissue-clearing and labeling techniques have revolutionized brain-wide imaging and analysis, yet their application to clinical formalin-fixed paraffin-embedded (FFPE) blocks remains challenging. We introduce HIF-Clear, a novel method for efficiently clearing and labeling centimeter-thick FFPE specimens using elevated temperature and concentrated detergents. HIF-Clear with multi-round immunolabeling reveals neuron circuitry regulating multiple neurotransmitter systems in a whole FFPE mouse brain and is able to be used as the evaluation of disease treatment efficiency. HIF-Clear also supports expansion microscopy and can be performed on a non-sectioned 15-year-old FFPE specimen, as well as a 3-month formalin-fixed mouse brain. Thus, HIF-Clear represents a feasible approach for researching archived FFPE specimens for future neuroscientific and 3D neuropathological analyses.

This paper proposes the use of machine learning models to predict one's risk of having hypertension in the future using their routine health checkup data of their current and past visits to a health checkup center. The large-scale and high-dimensional dataset used in this study comes from MJ Health Research Foundation in Taiwan. The training data for models is separated into 5 folds and used to train 5 models in a 5-fold cross validation manner. While predicting the results for the test set, the voted result of 5 models is used as the final prediction. Experimental results show that our models achieve 69.59% of precision, 77.90% of recall, and 73.51% of F1-score, which outperforms a baseline using only the blood pressure of visitors' last visits. Experiments also show that a visitor who performs a health checkup more often can be predicted better, and models trained with selected important factors achieve better results than those trained with Framingham risk score. We also demonstrate the possibility of using our models to suggest visitors for weight control by adding virtual visits that assume their body weight can be reduced in the near future to model input. Experimental results show that around 5.48% of the people who are with high Body Mass Index of the true positive cases are rejudged as negative, and a rising trend appears when adding more virtual visits, which may be used to suggest visitors that controlling their body weight for a longer time lead to lower probability of having hypertension in the future.

Abstract Immunoproteasomes (IP) serve as an important modulator of immune responses to pathogens and other pathological factors. LMP7/β5i, one of the IP subunits, plays a critical role in autoimmune diseases by downregulating inflammation. Rhinovirus (RV) infection is a major risk factor in the exacerbations of respiratory inflammatory diseases, but whether LMP7 regulates RV-mediated inflammation in the lung particularly in the airway epithelium, the first line of defense against RV infection, remains unclear. In this study, we determined whether airway epithelial LMP7 promotes the resolution of RV-mediated lung inflammation. Inducible airway epithelial-specific LMP7-deficient (conditional knockout, CKO) mice were generated to reveal the in vivo anti-inflammatory and antiviral functions of LMP7. By using LMP7-deficient primary human airway epithelial cells generated by CRISPR-Cas9, we confirmed that airway epithelial LMP7 decreased pro-inflammatory cytokines and viral load during RV infection. Additionally, airway epithelial LMP7 enhanced the expression of a negative immune regulator A20/TNFAIP3 during viral infection that may contribute to the anti-inflammatory function of LMP7. We also discovered that induction of LMP7 by a low dose of polyinosinic:polycytidylic acid (PI:C) reduced RV-mediated inflammation in our CKO mice infected with RV. Our findings suggest that airway epithelial LMP7 has anti-inflammatory and antiviral functions that is critical to the resolution of RV-mediated lung inflammation. Induction of airway epithelial LMP7 may open a novel avenue for therapeutic intervention against RV infection.

Abstract The Aurignacian is one of the first cultural-technological traditions commonly associated with the expansion of Homo sapiens in Europe. Early Homo sapiens demographics across the continent are therefore typically inferred using the distribution of Aurignacian assemblages. Western Romania has been used as a tie-point to connect the well-researched lithic assemblages from the eastern Mediterranean and Western Europe through its early Homo sapiens fossils. However, Romania’s archeological record remains underexplored thereby hindering our ability to directly connect better understood regions through time and space. Here we report on excavations from the open-air Middle/Upper Paleolithic site of Româneș ti-Dumbrăvița I in southwestern Romania. Three stratified Paleolithic assemblages were extensively excavated within a 1-m-thick eolian-deposited sequence. Spatial, geochemical, raw material, techno-typological, and use-wear analysis of the site reveal patterns of artifact configuration, resource exploitation, fire history, knapping objectives, and functionality. Taken together, Românești-Dumbrăvița I is the first well-contextualized archeological site in close spatiotemporal proximity to many early, well-preserved human fossils and in East-Central Europe.

The Ryukyu Trench is located in the northern Philippine Sea. The subduction of the Philippine Sea Plate to the Eurasia Plate along the Ryukyu Trench in the NNW direction leads to extremely complex tectonic processes such as subduction, collision, accretion, and back-arc expansion. It is of great significance to obtain the crustal structure of the Ryukyu Trench for understanding the crustal deformation characteristics, subduction direction and the scale of the Philippine Sea Plate. The ocean bottom seismometer (OBS) could provide important information on the deep structure of the oceanic area, and the wide coverage of gravity anomaly can provide more constraints for the regional crustal structure. In this study, we put the time-delay term of the sedimentary layer into the H-κ stacking formula, which eliminates the influence of the sedimentary layer in traditional H-κ stacking. Based on the accurate crustal thickness at OBS locations, a gravity inversion method is proposed to solve the problem of non-uniqueness in gravity data and limited distribution of OBSs. By using this method, we obtain a crustal structure with higher resolution than Crust1.0 model in Ryukyu Trench. The results show that the crustal thickness in the Ryukyu Trench region thickens along the NNW subduction direction, revealing that the Philippine Plate’s subduction direction towards the Eurasian Plate is in the NNW direction.

This study investigates age-specific prostate-specific antigen (PSA) distributions in Taiwanese men and recommends reference ranges for this population after comparison with other studies. From January 1999 to December 2016, a total of 213,986 Taiwanese men aged above 19 years old without history of prostate cancer, urinary tract infection, or prostate infection were recruited from the Taiwan MJ cohort, an ongoing prospective cohort of health examinations conducted by the MJ Health Screening Center in Taiwan. Participants were divided into seven age groups. Simple descriptive statistical analyses were carried out and quartiles and 95th percentiles were calculated for each group as reference ranges for serum PSA in screening for prostate cancer in Taiwanese men. Serum PSA concentration correlated with age (r = 0.274, p

Introduction: Vitamin D plays a vital role in maintaining homeostasis and enhancing the absorption of calcium, an essential component for strengthening bones and preventing osteoporosis. There are many factors known to relate to plasma vitamin D concentration (PVDC). However, most of these studies were performed with traditional statistical methods. Nowadays, machine learning methods (Mach-L) have become new tools in medical research. In the present study, we used four Mach-L methods to explore the relationships between PVDC and demographic, biochemical, and lifestyle factors in a group of healthy premenopausal Chinese women. Our goals were as follows: (1) to evaluate and compare the predictive accuracy of Mach-L and MLR, and (2) to establish a hierarchy of the significance of the aforementioned factors related to PVDC. Methods: Five hundred ninety-three healthy Chinese women were enrolled. In total, there were 35 variables recorded, including demographic, biochemical, and lifestyle information. The dependent variable was 25-OH vitamin D (PVDC), and all other variables were the independent variables. Multiple linear regression (MLR) was regarded as the benchmark for comparison. Four Mach-L methods were applied (random forest (RF), stochastic gradient boosting (SGB), extreme gradient boosting (XGBoost), and elastic net). Each method would produce several estimation errors. The smaller these errors were, the better the model was. Results: Pearson’s correlation, age, glycated hemoglobin, HDL-cholesterol, LDL-cholesterol, and hemoglobin were positively correlated to PVDC, whereas eGFR was negatively correlated to PVDC. The Mach-L methods yielded smaller estimation errors for all five parameters, which indicated that they were better methods than the MLR model. After averaging the importance percentage from the four Mach-L methods, a rank of importance could be obtained. Age was the most important factor, followed by plasma insulin level, TSH, spouse status, LDH, and ALP. Conclusions: In a healthy Chinese premenopausal cohort using four different Mach-L methods, age was found to be the most important factor related to PVDC, followed by plasma insulin level, TSH, spouse status, LDH, and ALP.

Earthquakes (EQs) are a significant natural threat to humanity. In recent years, with advancements in space observation technology, it has been put forward that the electromagnetic effects of earthquakes can propagate into space in various ways, causing electromagnetic radiation and plasma disturbances in space and leading to high–energy particle precipitation. The China Seismo-Electromagnetic Satellite (CSES) is specifically designed for monitoring the space electromagnetic environment. In our study, we select 78 strong earthquakes from September 2018 to February 2023 (global earthquakes with M ⩾ 7.0 and the major seismic regions in China with M ⩾ 6.0). We focus on 10∘ of the latitude and longitude around the epicenter, spanning from 15 days before the earthquake to 5 days after, and look for anomalies in spatial evolution and temporal evolution. We present some typical cases of electron flux perturbation and summarize the anomalies of all 78 cases to look for regularity in EQ–related particle anomalies. Notably, we introduce two cases of simultaneous electromagnetic and energetic particle anomalies during earthquakes. And we propose a conjecture that the particle precipitation may be the result of wave–particle interactions triggered by seismic activity.

With the advent of direct-acting antiviral agents (DAA) in the recent few years, hepatitis C virus (HCV) infection has become a curable infectious disease. Successful clearance of HCV could lead to improvement of both hepatic and extrahepatic outcomes, such as complications of cirrhosis, hepatocellular carcinoma, cardiovascular diseases, and incident diabetes. However, challenges persist in reaching the HCV elimination goals of the World Health Organization by 2030. Among these challenges are identifying those already infected or undiagnosed subjects, re-linking to the care of known but untreated HCV-infected subjects, and developing strategies to enhance treatment rates and compliance in specific or high-risk populations. In addition, issues of post-DAA viral clearance, including avoiding or preventing reinfection in high-risk populations and surveillance of hepatocellular carcinoma, are important to consolidate the treatment’s short- and long-term efficacies. In the current DAA era, treatment is the most effective prevention strategy not only in its excellent efficacy and safety but also in preventing HCV spread. All of the surveillance or measures should center on DAA treatment in clinical practice.

Solar eruptions can cause violent effects on the space environment. Electromagnetic radiation from solar flares will be the first to arrive on the Earth at the speed of light, followed by solar energetic charged particles. The last to appear will be coronal mass ejections and geomagnetic storms. Based on observations of ZH-1 satellite, we report three strong disturbed space environment events, all of them with solar proton events (SPEs), and analyze the driving mechanisms: 1) On 29 November 2020, an M4.4 flare accompanied with a full halo CME caused a gradual SPE, which was mainly driven by CME shocks. 2) On 28 May 2021, a C9.4 flare brought an impulsive SPE, which was accelerated by the flare. The heliolongitude of this small flare was 63°W, near the footpoint of the magnetic field line leading from the Sun to the Earth. 3) On 28 October 2021, a full-halo CME accompanied with an X1.1 flare brought a gradual SPE. On 2 November 2021, another fast full halo CME accompanied with flare was ejected. The faster CME of November 2 caught up and swept up the slower CME of November 1, and subsequently caused a severe geomagnetic storm (minimum Dst = -101) and a high-energy electron storm on November 4. The observations of the above three space environmental events confirm that the data quality of the high-energy particle package (HEPP) from ZH-1 is highly reliable and accurate and is highly advantageous to monitoring the variation of energetic particles and X-rays in the radiation belt of the Earth during solar activities.

As a parameter that quantitatively measures the shielding effect of the Earth’s magnetic field on energetic particles, the geomagnetic cutoff rigidities will change significantly with the long-term change of geomagnetic field. In this article, by using the numerical simulation method, combined with the variation trend of the Earth’s main field International Geomagnetic Reference Field (IGRF) model and the energetic particles’ windows (EPWs), the variation characteristics of the cutoff rigidities of geomagnetic energetic particles in the vertical direction from 1965 to 2025 were studied. The study found that there is a close relationship between the cutoff latitude corresponding to the cutoff rigidities and the background magnetic field intensity, but they are not in a simple linear relationship. The changes of the cutoff rigidities and geomagnetic field in the northern and southern hemispheres are asymmetric. The weakening of the geomagnetic field will push the cutoff latitudes toward the near equatorial region in the southern hemisphere, but for northern hemisphere the phenomenon is not always credible. In the northern hemisphere, the areas of EPWs will decrease at a relative rate of 0.03%/yr, but in the southern hemisphere, it will increase at a rate of about 0.05%/yr to 0.12%/yr. The long-term trajectory of the positions of the EPWs’ central points do not correspond to geomagnetic poles, nor the magnetic dip poles, relatively speaking, its position is closer to the geomagnetic poles. The study can be used for a long-term forecasting of cutoff rigidities caused by background geomagnetic field variations.

Driven by the objective of earthquake disaster prevention and mitigation, China launched the Zhangheng mission to build a stereoscopic earthquake monitoring system from the lithosphere to space. This report briefly presents the possible seismic ionospheric disturbances recorded by the first probe of the Zhangheng mission, which is known as the China-Seismo-Electromagnetic Satellite (CSES). The routine data preprocessing and seismo-ionospheric information analysis methods are briefly introduced. The possible seismo-ionospheric disturbances that appeared during the strong shallow earthquakes (with a magnitude over 7 and a depth shallower than 30 km) are analyzed by using CSES and other multi-source data. Investigating seismo-ionospheric mechanisms requires multidisciplinary knowledge involving geophysics, atmosphere/ionosphere physics, geochemistry/atmospheric chemistry, etc. We state that the results from the CSES scientific application center are preliminary, calling for international scientists to contribute to the seismo-ionospheric perturbation phenomena, which is one of the most challenging scientific problems.