Free-space coupled, large-active-area superconducting microstrip single-photon detector for photon-counting time-of-flight imaging.

Numerous applications at the photon-starved regime require a free-space coupling single-photon detector with a large active area, low dark count rate (DCR), and superior time resolutions. Here, we developed a superconducting microstrip single-photon detector (SMSPD), with a large active area of 260 µm in diameter, a DCR of ∼5k c p s, and a low time jitter of ∼171p s, operated at a near-infrared of 1550 nm and a temperature of ∼2.0K. As a demonstration, we applied the detector to a single-pixel galvanometer scanning system and successfully reconstructed the object information in depth and intensity using a time-correlated photon counting technology.

LARP7 overexpression alleviates aortic senescence and atherosclerosis.

Atherosclerosis, characterized by the accumulation of lipid plaques on the inner walls of arteries, is the leading cause of heart attack, stroke and severe ischemic injuries. Senescent cells have been found to accumulate within atherosclerotic lesions and contribute to the progression of atherosclerosis. In our previous study, we discovered that suppressing Larp7 accelerates senescence by inhibiting Sirt1 activity, resulting in increased atherosclerosis in high-fat diet (HFD) fed and ApoE deficient (ApoEKO) mice. However, there has been no direct evidence demonstrating Larp7 per se could attenuate atherosclerosis. To this end, we generated a tetO-controlled and Cre-activated Larp7 gain-of-function mouse. Through RT-PCR and western blotting, we confirmed Larp7 overexpression in the aortas of HFD-fed ApoEKO; Larp7tetO mice. Larp7 overexpression led to increased Sirt1 activity and decreased cellular senescence signals mediated by p53/p65 in the aortas. Additionally, Larp7 overexpression reduced the presence of p16-positive senescent cells in the aortic lesions. Furthermore, Larp7 overexpression resulted in a decrease in pro-inflammatory macrophages and SASP factors. Consequently, Larp7 overexpression led to a reduction in the area of atherosclerotic lesions in HFD-fed ApoEKO; Larp7tetO mice. In summary, our study provides evidence that Larp7 overexpression holds promise as an approach to inhibit cellular senescence and prevent atherosclerosis.

In Situ Atomic Reconstruction Engineering Modulating Graphene-Like MXene-Based Multifunctional Electromagnetic Devices Covering Multi-Spectrum.

With the diversified development of big data, detection and precision guidance technologies, electromagnetic (EM) functional materials and devices serving multiple spectrums have become a hot topic. Exploring the multispectral response of materials is a challenging and meaningful scientific question. In this study, MXene/TiO2 hybrids with tunable conduction loss and polarization relaxation are fabricated by in situ atomic reconstruction engineering. More importantly, MXene/TiO2 hybrids exhibit adjustable spectral responses in the GHz, infrared and visible spectrums, and several EM devices are constructed based on this. An antenna array provides excellent EM energy harvesting in multiple microwave bands, with |S11| up to - 63.2 dB, and can be tuned by the degree of bending. An ultra-wideband bandpass filter realizes a passband of about 5.4 GHz and effectively suppresses the transmission of EM signals in the stopband. An infrared stealth device has an emissivity of less than 0.2 in the infrared spectrum at wavelengths of 6-14 µm. This work can provide new inspiration for the design and development of multifunctional, multi-spectrum EM devices.

Reactive oxygen species (ROS) modulate nitrogen signaling using temporal transcriptome analysis in foxtail millet.

Reactive oxygen species (ROS) is a chemically reactive chemical substance containing oxygen and a natural by-product of normal oxygen metabolism. Excessive ROS affect the growth process of crops, which will lead to the decrease of yield. Nitrogen, as a critical nutrient element in plants and plays a vital role in plant growth and crop production. Nitrate is the primary nitrogen source available to plants in agricultural soil and various natural environments. However, the molecular mechanism of ROS-nitrate crosstalk is still unclear. In this study, we used the foxtail millet (Setaria italica L.) as the material to figure it out. Here, we show that excessive NaCl inhibits nitrate-promoted plant growth and nitrogen use efficiency (NUE). NaCl induces ROS accumulation in roots, and ROS inhibits nitrate-induced gene expression in a short time. Surprisingly, low concentration ROS slight promotes and high concentration of ROS inhibits foxtail millet growth under long-term H2O2 treatment. These results may open a new perspective for further exploration of ROS-nitrate signaling pathway in plants.

Statistical and machine learning analysis for the application of microbially induced carbonate precipitation as a physical barrier to control seawater intrusion.

Seawater intrusion in coastal aquifers is a significant problem that can be addressed through the construction of subsurface dams or physical cut-off barriers. An alternative method is the use of microbially induced carbonate precipitation (MICP) to reduce the hydraulic conductivity of the porous medium and create a physical barrier. However, the effectiveness of this method depends on various factors, and the scientific literature presents conflicting results, making it challenging to generalise the findings. To overcome this challenge, a statistical and machine learning (ML) approach is employed to infer the causes for the reduction in hydraulic conductivity and identify the optimum MICP parameters for preventing seawater intrusion. The study involves data curation, exploratory analysis, and the development of various models to fit the input data (k-Nearest Neighbours - kNN, Support Vector Regression - SVR, Random Forests - RF, Gradient Boosting - XgBoost, Linear model with interaction terms, Ensemble learning algorithms with weighted averages - EnL-WA and stacking - EnL-Stack). The models performed reasonably well in the region where permeability reduction is sensitive to carbonate increase capturing the permeability reduction profile with respect to cementation level while demonstrating that they can be used in initial assessments of the specific conditions (e.g., soil properties). The best performing algorithms were the EnL-Stack and RF followed by XgBoost and SVR. The MICP method is effective in reducing hydraulic conductivity provided that the various biochemical parameters are optimised. Critical biochemical parameters for successful MICP formulations are the bacterial optical density, the urease activity, calcium chloride concentration and flow rate as well as the interaction terms across the properties of the porous media and the biochemical parameters. The models were used to identify the optimum MICP formulation for various porous media properties and the maximum permeability reduction profiles across cementation levels have been derived.

Chemiluminescent Conjugated Polymer Nanoparticles for Deep-Tissue Inflammation Imaging and Photodynamic Therapy of Cancer.

Deep-tissue optical imaging and photodynamic therapy (PDT) remain a big challenge for the diagnosis and treatment of cancer. Chemiluminescence (CL) has emerged as a promising tool for biological imaging and in vivo therapy. The development of covalent-binding chemiluminescence agents with high stability and high chemiluminescence resonance energy transfer (CRET) efficiency is urgent. Herein, we design and synthesize an unprecedented chemiluminescent conjugated polymer PFV-Luminol, which consists of conjugated polyfluorene vinylene (PFV) main chains and isoluminol-modified side chains. Notably, isoluminol groups with chemiluminescent ability are covalently linked to main chains by amide bonds, which dramatically narrow their distance, greatly improving the CRET efficiency. In the presence of pathologically high levels of various reactive oxygen species (ROS), especially singlet oxygen (1O2), PFV-Luminol emits strong fluorescence and produces more ROS. Furthermore, we construct the PFV-L@PEG-NPs and PFV-L@PEG-FA-NPs nanoparticles by self-assembly of PFV-Luminol and amphiphilic copolymer DSPE-PEG/DSPE-PEG-FA. The chemiluminescent PFV-L@PEG-NPs nanoparticles exhibit excellent capabilities for in vivo imaging in different inflammatory animal models with great tissue penetration and resolution. In addition, PFV-L@PEG-FA-NPs nanoparticles show both sensitive in vivo chemiluminescence imaging and efficient chemiluminescence-mediated PDT for antitumors. This study paves the way for the design of chemiluminescent probes and their applications in the diagnosis and therapy of diseases.

Undaria pinnatifida gel inks for food 3D printing are developed based on the colloidal properties of Undaria pinnatifida slurry and protein/colloidal/starch substances.

Currently, people eat Undaria pinnatifida (UP) in a single way, and processing homogeneity is serious. However, UP has not gained any traction in the 3D printing industry to date. This study explored the incorporation of soy protein isolate (SPI), pea protein (PP), xanthan gum (XG), guar gum (GG), corn starch (CS), and potato starch (PS) into UP slurry liquid, the primary component of the study, to formulate a UP gel ink. The UP gel 3D printing ink system based on UP paste was established and characterized. The results show that hydrogen bonds are formed, and three-dimensional gel network structure is formed in all UP gel inks. UP gel inks containing high concentrations of SPI and GG exhibited good texture and rheological qualities and good 3D printing effect, with storage modulus (G') values of 8440.405 ± 3.893 and 8111.730 ± 3.585 Pa. The loss of modulus (G″) values were 1409.107 ± 3.524 and 1071.673 ± 3.669 Pa. Unfortunately, the properties of other UP gel inks are not suitable, resulting in poor 3D printing results. The food 3D printing method developed in this study provides valuable insights for expanding food 3D printing material choices and achieving high-value applications of UP.

Classification of subtypes and identification of dysregulated genes in sepsis.

Background: Sepsis is a clinical syndrome with high mortality. Subtype identification in sepsis is meaningful for improving the diagnosis and treatment of patients. The purpose of this research was to identify subtypes of sepsis using RNA-seq datasets and further explore key genes that were deregulated during the development of sepsis. Methods: The datasets GSE95233 and GSE13904 were obtained from the Gene Expression Omnibus database. Differential analysis of the gene expression matrix was performed between sepsis patients and healthy controls. Intersection analysis of differentially expressed genes was applied to identify common differentially expressed genes for enrichment analysis and gene set variation analysis. Obvious differential pathways between sepsis patients and healthy controls were identified, as were developmental stages during sepsis. Then, key dysregulated genes were revealed by short time-series analysis and the least absolute shrinkage and selection operator model. In addition, the MCPcounter package was used to assess infiltrating immunocytes. Finally, the dysregulated genes identified were verified using 69 clinical samples. Results: A total of 898 common differentially expressed genes were obtained, which were chiefly related to increased metabolic responses and decreased immune responses. The two differential pathways (angiogenesis and myc targets v2) were screened on the basis of gene set variation analysis scores. Four subgroups were identified according to median expression of angiogenesis and myc target v2 genes: normal, myc target v2, mixed-quiescent, and angiogenesis. The genes CHPT1, CPEB4, DNAJC3, MAFG, NARF, SNX3, S100A9, S100A12, and METTL9 were recognized as being progressively dysregulated in sepsis. Furthermore, most types of immune cells showed low infiltration in sepsis patients and had a significant correlation with the key genes. Importantly, all nine key genes were highly expressed in sepsis patients. Conclusion: This study revealed novel insight into sepsis subtypes and identified nine dysregulated genes associated with immune status in the development of sepsis. This study provides potential molecular targets for the diagnosis and treatment of sepsis.

High-efficiency broadband fiber-to-chip coupler using a 3D nanoprinting microfiber.

We propose a method for coupling a tapered optical fiber to an inverted tapered SiN waveguide by fabricating a microfiber using 3D nanoprinting lithography. The microfiber consists of three parts: a tapered cladding cap, an S-bend, and a straight part, all composed of high-refractive-index material. Light is adiabatically coupled from the tapered fiber to the printed microfiber through the cladding cap. The light is then transmitted through the S-bend and the straight part with low loss and is finally coupled to the waveguide through the evanescent field. In the simulation, our design can achieve a high coupling efficiency (TE mode) of ∼97% at a wavelength of 1542 nm with a wide bandwidth of ∼768n m at the 1-dB cutoff criterion.

Classification of Glomerular Pathology Images in Children Using Convolutional Neural Networks with Improved SE-ResNet Module.

Classification of glomerular pathology based on histology sections is the key to diagnose the type and degree of kidney diseases. To address problems in the classification of glomerular lesions in children, a deep learning-based complete glomerular classification framework was designed to detect and classify glomerular pathology. A neural network integrating Resnet and Senet (RS-INet) was proposed and a glomerular classification algorithm implemented to achieve high-precision classification of glomerular pathology. SE-Resnet was applied with improvement by transforming the convolutional layer of the original Resnet residual block into a convolutional block with smaller parameters as well as reduced network parameters on the premise of ensuring network performance. Experimental results showed that our algorithm had the best performance in differentiating mesangial proliferative glomerulonephritis (MsPGN), crescent glomerulonephritis (CGN), and glomerulosclerosis (GS) from normal glomerulus (Normal) compared with other classification algorithms. The accuracy rates were 0.960, 0.940, 0.937, and 0.968, respectively. This suggests that the classification algorithm proposed in the present study is able to identify glomerular lesions with a higher precision, and distinguish similar glomerular pathologies from each other.

Decomposition of drivers and identification of decoupling states for the evolution of carbon emissions from energy consumption in China.

As the largest energy consumer, China's control of carbon emissions from energy consumption plays a pivotal role in world climate governance. However, few studies have been conducted to explore the emission reduction pathways that promote a high level of synergy between China's economic growth and the " carbon peaking and carbon neutrality " goal from the perspective of energy consumption. Based on the measurement of energy consumption carbon emissions, this paper reveals the spatial and temporal distribution and evolution trends of carbon emissions in China at the national-provincial level. The multi-dimensional socio-economic factors such as R&D and urbanization are taken into account, and the LMDI model is used to decompose the driving effects of energy consumption carbon emissions at the national-provincial levels. Further, this paper combines the Tapio decoupling index with the LMDI model to decompose the decoupling states of China year by year and at the provincial level in four periods to explore the reasons for the change of carbon decoupling states. The results show that: (1) China's energy consumption carbon emissions grew at a high rate before 2013, and slowed down after that. There are significant differences in the scale and growth rate of carbon emissions among provinces, which can be classified into four types accordingly. (2) The R&D scale effect, urbanization effect, and population scale effect are the factors driving the growth of China's carbon emissions; while the energy structure effect, energy consumption industry structure effect, energy intensity effect, and R&D efficiency effect inhibit the growth of China's carbon emissions. (3) Weak decoupling is the most dominant decoupling state in China from 2003 to 2020, and the decoupling state varies significantly among provinces. According to the conclusions, this paper proposes targeted policy recommendations based on China's energy endowment.

The chemokine monocyte chemoattractant protein-1/CCL2 is a promoter of breast cancer metastasis.

Breast cancer is the most prevalent cancer worldwide, and metastasis is the leading cause of death in cancer patients. Human monocyte chemoattractant protein-1 (MCP-1/CCL2) was isolated from the culture supernatants of not only mitogen-activated peripheral blood mononuclear leukocytes but also malignant glioma cells based on its in vitro chemotactic activity toward human monocytes. MCP-1 was subsequently found to be identical to a previously described tumor cell-derived chemotactic factor thought to be responsible for the accumulation of tumor-associated macrophages (TAMs), and it became a candidate target of clinical intervention; however, the role of TAMs in cancer development was still controversial at the time of the discovery of MCP-1. The in vivo role of MCP-1 in cancer progression was first evaluated by examining human cancer tissues, including breast cancers. Positive correlations between the level of MCP-1 production in tumors and the degree of TAM infiltration and cancer progression were established. The contribution of MCP-1 to the growth of primary tumors and metastasis to the lung, bone, and brain was examined in mouse breast cancer models. The results of these studies strongly suggested that MCP-1 is a promoter of breast cancer metastasis to the lung and brain but not bone. Potential mechanisms of MCP-1 production in the breast cancer microenvironment have also been reported. In the present manuscript, we review studies in which the role of MCP-1 in breast cancer development and progression and the mechanisms of its production were examined and attempt to draw a consensus and discuss the potential use of MCP-1 as a biomarker for diagnosis.

Millimeter-scale active area superconducting microstrip single-photon detector fabricated by ultraviolet photolithography.

The effective and convenient detection of single photons via advanced detectors with a large active area is becoming significant for quantum and classical applications. This work demonstrates the fabrication of a superconducting microstrip single-photon detector (SMSPD) with a millimeter-scale active area via the use of ultraviolet (UV) photolithography. The performances of NbN SMSPDs with different active areas and strip widths are characterized. SMSPDs fabricated by UV photolithography and electron beam lithography with small active areas are also compared from the aspects of the switching current density and line edge roughness. Furthermore, an SMSPD with an active area of 1 mm × 1 mm is obtained via UV photolithography, and during operation at 0.85 K, it exhibits near-saturated internal detection efficiency at wavelengths up to 800 nm. At a wavelength of 1550 nm, the detector exhibits a system detection efficiency of ∼5% (7%) and a timing jitter of 102 (144) ps, when illuminated with a light spot of ∼18 (600) µm in diameter, respectively.

Multi-Phase Fusion for Pedestrian Localization Using Mass-Market GNSS and MEMS Sensors.

Precise pedestrian positioning based on smartphone-grade sensors has been a research hotspot for several years. Due to the poor performance of the mass-market Micro-Electro-Mechanical Systems (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors, the standalone pedestrian dead reckoning (PDR) module cannot avoid long-time heading drift, which leads to the failure of the entire positioning system. In outdoor scenes, the Global Navigation Satellite System (GNSS) is one of the most popular positioning systems, and smartphone users can use it to acquire absolute coordinates. However, the smartphone's ultra-low-cost GNSS module is limited by some components such as the antenna, and so it is susceptible to serious interference from the multipath effect, which is a main error source of smartphone-based GNSS positioning. In this paper, we propose a multi-phase GNSS/PDR fusion framework to overcome the limitations of standalone modules. The first phase is to build a pseudorange double-difference based on smartphone and reference stations, the second phase proposes a novel multipath mitigation method based on multipath partial parameters estimation (MPPE) and a Double-Difference Code-Minus-Carrier (DDCMC) filter, and the third phase is to propose the joint stride lengths and heading estimations of the two standalone modules, to reduce the long-time drift and noise. The experimental results demonstrate that the proposed multipath error estimation can effectively suppress the double-difference multipath error exceeding 4 m, and compared to other methods, our fusion method achieves a minimum error RMSE of 1.63 m in positioning accuracy, and a minimum error RMSE of 4.71 m in long-time robustness for 20 min of continuous walking.

Highly Metastatic Subpopulation of TNBC Cells Has Limited Iron Metabolism and Is a Target of Iron Chelators.

Excess iron is known to be a risk factor of carcinogenesis. Although iron chelators show anti-cancer effects, they have not been used successfully to treat cancer patients. Triple-negative breast cancer (TNBC) is a disease with poor prognosis without effective treatments. Thus, we aimed to evaluate a possibility of iron chelators as a therapy for TNBC. Deferasirox (DFX), an iron chelator, suppressed the growth of 4T1 murine TNBC cell line cells in vitro and in vivo. Lung metastasis was further significantly reduced, leading to the hypothesis that iron metabolism between metastatic and non-metastatic cells may be different. An analysis of existing database demonstrated that the expression of iron-uptake genes was significantly suppressed in TNBC cells that metastasized to lymph nodes or lungs compared to those in primary tumors. A highly metastatic clone of the murine 4T1 TNBC cells (4T1-HM) did not proliferate well under iron-rich or iron-depleted conditions by iron chelators compared to a low-metastatic clone (4T1-LM). Bulk RNA-seq analysis of RNA from 4T1-HM and 4T1-LM cells suggested that the PI3K-AKT pathway might be responsible for this difference. Indeed, DFX suppressed the proliferation via the AKT-mTOR pathway in 4T1-HM and the human MDA-MB-231 cells, a human mesenchymal-like TNBC cell line. DFX also suppressed the growth of 4T1-HM tumors in comparison to 4T1-LM tumors, and reduced lung metastases after surgical resection of primary 4T1 tumors. These results indicated, for the first time, that highly metastatic TNBC cells have limited iron metabolism, and they can be more effectively targeted by iron chelators.

Pollution and health-risk assessments of Cr-contaminated soils from a tannery waste lagoon, Hebei, north China: With emphasis on Cr speciation.

In this paper, heavy metals (i.e., V, Cr, Co, Cu, Zn, Cd, Pb, and Sb) in soils from a tannery waste lagoon, Hebei, north China were investigated. Element concentrates were determined by a portable X-ray fluorescence in situ and an inductively coupled plasma mass spectrometry in the lab. Two sets of indexes, including geological accumulation index, contamination factor, and pollution load index, and hazard quotient and total carcinogenic risk were adopted to evaluate the pollution and health-risk of heavy metals. A scanning electron microscopy in conjunction with an energy dispersive X-ray spectroscopy and an X-ray photoelectron spectroscopy was used to observe chromium occurrence and speciation. With an average of 6493.11 mg/kg, chromium contents in the lagoon soils reached up to 12971.19 mg/kg, 211-times higher than the threshold of Chinese soils (61.00 mg/kg). Elevated Cr contents resulted in significantly high pollution and noncarcinogenic and carcinogenic risks in the studied area. Chromium in most soils occurred predominately as Cr3+ (60-74%), and to a lesser extent, Cr6+. The mechanism responsible for decreasing Cr6+ percentages in soils with increasing depth was summarized: Cr6+ favors aqueous environment; soil moisture decreased with increasing depth; in soils especially in the lower portion, Cr6+ was reduced by Fe0 and Fe2, transforming into Cr3+ and Fe3+. In addition, the alkaline condition promoted Cr3+ to precipitate, resulting more Cr3+ absorbing in soils. The intimate association of Cr and Fe in soils (i.e., Cr mainly occurred in Fe oxides and dolomite) further confirmed our assumptions. A combined application of microorganism (e.g., Aeromonas hydrophila) and biochar (prepared from maize stalk or peanut shells) were recommended to alleviate Cr pollution in the soils.

Disease-specific data processing: An intelligent digital platform for diabetes based on model prediction and data analysis utilizing big data technology.

Background: Artificial intelligence technology has become a mainstream trend in the development of medical informatization. Because of the complex structure and a large amount of medical data generated in the current medical informatization process, big data technology to assist doctors in scientific research and analysis and obtain high-value information has become indispensable for medical and scientific research. Methods: This study aims to discuss the architecture of diabetes intelligent digital platform by analyzing existing data mining methods and platform building experience in the medical field, using a large data platform building technology utilizing the Hadoop system, model prediction, and data processing analysis methods based on the principles of statistics and machine learning. We propose three major building mechanisms, namely the medical data integration and governance mechanism (DCM), data sharing and privacy protection mechanism (DPM), and medical application and medical research mechanism (MCM), to break down the barriers between traditional medical research and digital medical research. Additionally, we built an efficient and convenient intelligent diabetes model prediction and data analysis platform for clinical research. Results: Research results from this platform are currently applied to medical research at Shanghai T Hospital. In terms of performance, the platform runs smoothly and is capable of handling massive amounts of medical data in real-time. In terms of functions, data acquisition, cleaning, and mining are all integrated into the system. Through a simple and intuitive interface operation, medical and scientific research data can be processed and analyzed conveniently and quickly. Conclusions: The platform can serve as an auxiliary tool for medical personnel and promote the development of medical informatization and scientific research. Also, the platform may provide the opportunity to deliver evidence-based digital therapeutics and support digital healthcare services for future medicine.

Effects of Gabexate Mesylate on the Gut Microbiota and Metabolomics in Rats with Sepsis.

Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. However, there is still no single drug that could reduce septic mortality. Previous studies have reported gabexate mesylate (GM) significantly reduced serum inflammatory factors, alleviated sepsis-induced lung injury and improved clinical outcomes. This study aimed to combine with microbiome sequencing and metabolomics analysis to explore the effects of GM administration in septic rats. Methods: Sixty SD rats were randomly divided into the sham control (SC), cecal ligation and puncture (CLP), and GM injection (GM) groups. The mortality was measured and colonic feces were collected to examine the gut microbiota and metabolism 24 h after the procedure. The lung tissues were collected for hematoxylin-eosin staining. Results: We observed the relative abundance of Pygmaiobacter, which contributed to short-chain fatty acids (SCFAs) promotion, Lactobacillus and Erysipelotrichaceae UCG-003 increased in the GM-treated rats, while Escherichia-Shigella and Akkermansia decreased compared to the sepsis-induced lung injury group. Furthermore, these 3 metabolites including Palmitoylethanolamide, Deoxycholic acid and Chenodeoxycholic acid correlated significantly to CLP- and GM-rich genus (P < 0.05). Besides, the lung tissues of CLP group showed more severe inflammatory infiltration and edema, and the mortality rate in the CLP group (10/20) was significantly higher than in the SC group (0/20) (P < 0.001) and GM group (4/20) (P < 0.05). Conclusion: Our findings showed that GM attenuated sepsis-induced lung injury rats and regulated metabolites related to gut microbiota, which may provide an effective treatment for sepsis patients.

Se-H-free As2Se3 fiber and its spectral applications in the mid-infrared.

The complete removal of the impurities like Se-H in Se-based chalcogenide glasses has been challenging in the development of highly transparent chalcogenide glass fiber. In this paper, several purification methods, including dynamic distillation, static distillation, and combined distillation method, were adopted with an aim of purifying arsenic selenide glass with ultra-low content of the impurities. The experimental results demonstrated that the Se-H can be completely eliminated in the arsenic selenide glass host and fiber without the introduction of any chloride. We further explored the applications of such low loss and Se-H-free chalcogenide glass fiber in the mid-infrared. It was found that, using such a Se-H free fiber, a flattened supercontinuum spectrum above the -30 dB level from 1.2 to 13 µm was generated from the Se-H free fiber with a 5.5 µm laser pumping. The sensitivity was found to be improved 5.1 times for CO2 gas in the 3 to 6 µm wavelength range.

Comparison of femoral mechanics before and after internal fixation removal and the effect of sclerosis on femoral stress: a finite element analysis.

BACKGROUND: Femoral neck fractures are a common traumatic injury. The removal of the internal fixation remains controversial, especially in terms of mechanical stability. Moreover, collapsed necrosis of the femoral head continues to occur after fracture healing. We believe that sclerotic cancellous bone (SCB) formation around the screw is associated with femoral head necrosis. We aimed to compare mechanical features before and after implant removal and determine the effect of SCB formation on stress distribution. METHODS: Cylindrical cancellous bone sections were collected from a relatively normal region and an SCB region of a necrotic femoral head, and their elastic moduli were measured. Four femoral finite element models were developed: a) femoral neck fracture healing with implants, b) fracture healing without implants, c) sclerosis around the screw with implants, and d) sclerosis around the screw without implants. RESULTS: The maximum von Mises peak stresses of models a and b were 66.643 MPa and 63.76 MPa, respectively, and were concentrated in the upper lateral femur. The main stress was scattered at the lowest screw tail, femoral calcar region, and lateral femur shaft. Moreover, coronal plane strain throughout the screw paths near the femoral head in models a and b was mostly in the range of 1000-3000 µÎµ. The maximum stress concentrations in models c and d were located at the lower femoral head and reached 91.199 MPa and 78.019 MPa, respectively. CONCLUSIONS: The stresses in the sclerotic model around the cannulated screws are more concentrated on the femoral head than in the healing model without sclerotic bone. The overall stresses in the healing femoral neck fracture model were essentially unchanged before and after removal of the internal fixation.