Utilize multi-metabolic parameters as determinants for prediction of skeletal muscle mass quality in elderly type2 diabetic Chinese patients.

BACKGROUND: Sarcopenia, an age-related disorder characterized by loss of skeletal muscle mass and function, is recently recognized as a complication in elderly patients with type 2 diabetes mellitus (T2DM). Skeletal muscles play a crucial role in glycemic metabolism, utilizing around 80% of blood glucose. Accordingly, we aimed to explore the relationship between glucose metabolism and muscle mass in T2DM. METHODS: We employed the AWGS 2019 criteria for diagnosing low muscle mass and 1999 World Health Organization (WHO) diabetes diagnostic standards. This study included data of 191 individuals aged 60 and above with T2DM of Shanghai Pudong Hospital from November 2021 to November 2022. Fasting C-peptide (FPCP), fasting plasma glucose (FPG), 2-hour postprandial plasma glucose (PPG) and postprandial 2-hour C-peptide (PPCP), glycated hemoglobin A1c (HbA1c), glycated albumin (GA), serum lipids spectrum, renal and hepatic function, hemoglobin, and hormone were measured. Based on the findings of univariate analysis, logistic regression and receiver operating characteristic (ROC) curves were established. RESULTS: Participants with low muscle mass had significantly lower alanine and aspartate aminotransferase, and both FPCP and PPCP levels (P < 0.05). Compared with those without low muscle mass, low muscle mass group had significantly higher FPG, HbA1c, GA levels (P < 0.05). Body fat (BF, OR = 1.181) was an independent risk factor for low muscle mass. PPCP (OR = 0.497), BMI (OR = 0.548), and female (OR = 0.050) were identified as protective factors for low skeletal muscle. The AUC of BMI was the highest, followed by the PPCP, gender and BF (0.810, 0.675, 0.647, and 0.639, respectively), and the AUC of the combination of the above four parameters reached 0.895. CONCLUSIONS: In this cross-sectional study, BMI, Female, and PPCP associated with T2DM were protective factors for low muscle mass. BF was associated with T2DM and risk factor for low muscle mass.

Two Birds with one Stone: Dual-mode immunoassay constructed using a novel emitter ethylene glycol-induced perylene diimide and a multifunctional ANS probe.

Perylene diimide (PDI) is a readily reducible electron-deficient dye that exhibits strong photoluminescent properties, providing new opportunities for synthesizing novel electrochemiluminescence (ECL) emitters. In this study, ethylene glycol (EG) was used to induce the self-assembly of PDI supramolecules for the preparation of ultrathin EG-PDI nanosheets characterized by low crystallinity and weak stacking interaction. Notably, EG-PDI integrates luminescent and catalytic functions into one device, accelerating the interfacial electron transfer and the faster charge transfer kinetics of EG-PDI with K2S2O8. Furthermore, the narrow band gap of EG-PDI facilitates its excitation at an ultra-low potential (-0.3 V). To improve the efficiency of tumor marker analysis, multifunctional Au nanostars (ANS) was introduced both as an energy acceptor of the ECL system and a probe for the photothermal system. Dual-mode immunoassay have demonstrated superior analytical performance in detecting alpha-fetoprotein (AFP), meeting the requirements of modern clinical diagnostics in resource-limited environments.

Driving model of land use change on the evolution of carbon stock: a case study of Chongqing, China.

Terrestrialecosystems are significant carbon sinks and are crucial for understanding the regional and global carbon cycles, energy flow, and climate change. As land use change is a significant process affecting ecosystem carbon stocks and striving for land degradation neutrality (LDN), studying it is essential for comprehending the evolution of regional carbon sink functions and achieving sustainable development goals. The drastically diverse land use patterns in each of the study area's regions resulted in significant differences in carbon stock. This study explores the evolution traits of carbon stocks based on land use data and their driving mechanisms in Chongqing during the past 30 years by using spatial analysis, the InVEST model, and geographic probes. The results demonstrate that from 1990 to 2020, land degradation in Chongqing was made worse by the demand for land for construction land, but the strategy of converting cropland back to forests raised the carbon stock of forest land. The overall result is a decrease in total carbon stocks of 5.1078 Tg or 1.5%. The main pathway for carbon loss pathway in the evolution of carbon stock is the conversion of cropland to construction land, and the primary carbon compensation pathway is the conversion of grassland and cropland to forest land, with a spatial distribution characterized by "higher in the whole area and obvious local differences." The land use intensity index has the most significant influence on the evolution of carbon stock. Moreover, the interaction of pairwise factors played a more important role in affecting the evolution of carbon stocks than did each factor individually. The case study in this paper shows that land use change is a significant driving mechanism for the evolution of carbon stock, and the development of a driving model theory is appropriate for deciphering the trajectory of carbon stock evolution and offering research suggestions for other regions.

S-CdIn2S4: A novel near-infrared emitter triggered by low potential for constructing a dual-mode immunosensing platform.

CdIn2S4 is an interesting ternary metal sulfide whose narrow band gap and tunable optical properties offer new opportunities for the development of novel ECL emitters. Here, we use a simple hydrothermal synthesis to obtain hollow spindle CdIn2S4 (S-CIS), which exhibits strong near-infrared electrochemiluminescence (ECL) emission with K2S2O8 as a coreactant at a low excitation potential (-1.3 V), which is encouraging. The lower excitation potential of S-CIS is probably due to the low band gap energy, which makes the excitation potential positively shift. This lower excitation potential reduces the side-reactions caused by high voltages, effectively avoiding irreversible damage to biomolecules, and protecting the biological activity of antigens and antibodides. In this work, new features of S-CIS in ECL studies are also presented, demonstrating that the ECL emission mechanism of S-CIS is generated by surface state transitions and that S-CIS exhibits excellent near-infrared (NIR) characteristics. Importantly, we introduced S-CIS into electrochemical impedance spectroscopy (EIS) and ECL to the construct a dual-mode sensing platform to achieve AFP detection. The two models with intrinsic reference calibration and high accuracy showed outstanding analytical performance in AFP detection. The detection limits were 0.862 pg mL-1 and 16.8 fg mL-1, respectively. This study demonstrates the key role and great application potential of S-CIS as a novel NIR emitter with easy preparation, low cost and great performance in the development of a simple, efficient and ultrasensitive dual-mode response sensing platform for early clinical use.

Compact breast shape acquisition system for improving diffuse optical tomography image reconstructions.

Diffuse optical tomography (DOT) has been investigated for diagnosing malignant breast lesions, but its accuracy relies on model-based image reconstructions, which in turn depends on the accuracy of breast shape acquisition. In this work, we have developed a dual-camera structured light imaging (SLI) breast shape acquisition system tailored for a mammography-like compression setting. Illumination pattern intensity is dynamically adjusted to account for skin tone differences, while thickness-informed pattern masking reduces artifacts due to specular reflections. This compact system is affixed to a rigid mount that can be installed into existing mammography or parallel-plate DOT systems without the need for camera-projector re-calibration. Our SLI system produces sub-millimeter resolution with a mean surface error of 0.26 mm. This breast shape acquisition system results in more accurate surface recovery, with an average 1.6-fold reduction in surface estimation errors over a reference method via contour extrusion. Such improvement translates to 25% to 50% reduction in mean squared error in the recovered absorption coefficient for a series of simulated tumors 1-2 cm below the skin.

The coupling effect of socio-economic and eco-environment and land use transformation in mountainous areas-a case of the Fengjie County in the Three Gorges Reservoir Area, China.

Revealing the general laws of land use transformation (LUT) under the coupling evolution of different socio-economic and eco-environment (SE-EE) in mountainous areas is of great significance for rational use of land resources, regional socio-economic development, and eco-environment protection. This paper constructs a research framework of LUT under the coupling evolution of SE-EE and takes Fengjie County as an example to conduct a case study. The results show (1) the socio-economic development level and eco-environment quality showed an overall growth trend from 2000 to 2020, showed the distribution pattern of high in the Yangtze River valley and low in the mountainous areas, and low in the Yangtze River valley and high in the mountainous areas respectively. (2) The coupling evolution of SE-EE showed five types: synchronous development of SE-EE, socio-economic development and ecological retarded, socio-economic retarded and ecological restoration, low socio-economic development level, and low eco-environment quality. (3) The transformation of land use quantity, structure, and function corresponded to the coupling evolution of SE-EE. Cultivated land was reduced when the socio-economic development level was relatively high, and the function changed from production to ecological and eco-economic. When the eco-environment quality was high, cultivated land was reduced, and the function changed from production to ecological. (4) The framework constructed in this paper is universal to the mountainous areas represented by the Three Gorges Reservoir Area (TGRA) and the plain areas where the LUT and SE-EE evolution are different from the mountainous areas.

First Identification and Phylogenetic Analysis of Porcine Circovirus Type 4 in Fur Animals in Hebei, China.

A novel circovirus called porcine circovirus type 4 (PCV4) was recently detected in pigs suffering from severe clinical diseases in Hunan province, China. There are few reports on the origin and evolution of PCV4, although some researchers have conducted epidemiological investigations of PCV4 and found that PCV4 is widespread in pigs. Based on the previous study, we detected PCV2 in farmed foxes and raccoon dogs with reproductive failure. To explore whether the PCV4 genome also exists in fur animals, we detected 137 cases admitted from fur animal farms in Hebei China between 2015 and 2020, which were characterized by inappetence, lethargy, depression, abortion, and sterility. The overall infection rate of PCV4 was 23.36% (32/137), including 20.37% (22/108) for raccoon dogs, 18.75% (3/16) for foxes, and 53.85% (7/13) for minks. Finally, five raccoon dog-origin PCV4 strains and one fox-origin PCV4 strain were sequenced in our study, whose nucleotide identities with other representative PCV4 strains varied from 96.5% to 100%. Phylogenetic analysis based on the complete genomes of PCV4 strains indicated a close relationship with those of PCV4 strains identified from pigs. To our knowledge, this is the first study to detect PCV4 in fur animals. Interestingly, we also identified PCV4 in a mixed farm (feeding pigs and raccoon dogs at the same time). In summary, our findings extend the understanding of the molecular epidemiology of PCV4 and provide new evidence for its cross-species transmission.

Effects of Atmospheric Cold Plasma Treatment on the Storage Quality and Chlorophyll Metabolism of Postharvest Tomato.

Atmospheric cold plasma (ACP) is a potential green preservation technology, but its preservation mechanism is still unclear, and the effects of different plasma intensities on postharvest tomatoes are little studied. In this study, the effects of different ACP treatments (0 kV, 40 kV, 60 kV, and 80 kV) on the sensory quality, physiological indexes, key enzyme activities, and gene expression related to the chlorophyll metabolism of postharvest tomatoes were investigated during the storage time. The results showed that compared with the control group, the tomatoes in the plasma treatment group had a higher hardness and total soluble solid (TSS) and titratable acid (TA) contents, a lower respiratory intensity and weight loss rate, a higher brightness, and a lower red transformation rate, especially in the 60 kV treatment group. In addition, chlorophyll degradation, carotenoid accumulation, and chlorophyllase and pheophorbide a mono-oxygenase (PAO) enzyme activities in the postharvest tomatoes were inhibited in the 60 kV treatment group, and the expressions of three key genes related to chlorophyll metabolism, chlorophyll (CLH1), pheophytinase (PPH), and red chlorophyll catabolic reductase (RCCR) were down-regulated. The results of the correlation analysis also confirmed that the enzyme activity and gene expression of the chlorophyll metabolism were regulated by the ACP treatment, aiming to maintain the greenness of postharvest tomatoes.

AI-2/Lux-S Quorum Sensing of Lactobacillus plantarum SS-128 Prolongs the Shelf Life of Shrimp (Litopenaeus vannamei): From Myofibril Simulation to Practical Application.

Retarding the protein deterioration of shrimp during storage is important for maintaining its quality. Lactobacillus plantarum SS-128 (L. plantarum SS-128) is a biocontrol bacterium that can effectively maintain the fresh quality of food. This research establishes a myofibril simulation system and refrigerated control system to explore the impact of L. plantarum SS-128 on the quality and shelf life of refrigerated shrimp (Litopenaeus vannamei). Through the bacterial growth assay and AI-2 signal molecule measurement, the effect of the AI-2/LuxS quorum sensing (QS) system of L. plantarum SS-128 and shrimp spoilage bacteria was established. In the myofibril simulation system, a study on protein degradation (dimer tyrosine content, protein solubility, sulfhydryl content, and carbonyl content) showed that adding L. plantarum SS-128 effectively slowed protein degradation by inhibiting the growth of food pathogens. The application to refrigerated shrimp indicated that the total volatile basic nitrogen (TVB-N) value increased more slowly in the group with added L. plantarum SS-128, representing better quality. The total viable count (TVC) and pH results exhibited similar trends. This study provides theoretical support for the application of L. plantarum SS-128 in storing aquatic products.

Graphics-processing-unit-accelerated Monte Carlo simulation of polarized light in complex three-dimensional media.

SIGNIFICANCE: Monte Carlo (MC) methods have been applied for studying interactions between polarized light and biological tissues, but most existing MC codes supporting polarization modeling can only simulate homogeneous or multi-layered domains, resulting in approximations when handling realistic tissue structures. AIM: Over the past decade, the speed of MC simulations has seen dramatic improvement with massively parallel computing techniques. Developing hardware-accelerated MC simulation algorithms that can accurately model polarized light inside three-dimensional (3D) heterogeneous tissues can greatly expand the utility of polarization in biophotonics applications. APPROACH: Here, we report a highly efficient polarized MC algorithm capable of modeling arbitrarily complex media defined over a voxelated domain. Each voxel of the domain can be associated with spherical scatters of various radii and densities. The Stokes vector of each simulated photon packet is updated through photon propagation, creating spatially resolved polarization measurements over the detectors or domain surface. RESULTS: We have implemented this algorithm in our widely disseminated MC simulator, Monte Carlo eXtreme (MCX). It is validated by comparing with a reference central-processing-unit-based simulator in both homogeneous and layered domains, showing excellent agreement and a 931-fold speedup. CONCLUSION: The polarization-enabled MCX offers biophotonics community an efficient tool to explore polarized light in bio-tissues, and is freely available at http://mcx.space/.

Exploring complex water stress-gross primary production relationships: Impact of climatic drivers, main effects, and interactive effects.

The dominance of vapor pressure deficit (VPD) and soil water content (SWC) for plant water stress is still under debate. These two variables are strongly coupled and influenced by climatic drivers. The impacts of climatic drivers on the relationships between gross primary production (GPP) and water stress from VPD/SWC and the interaction between VPD and SWC are not fully understood. Here, applying statistical methods and extreme gradient boosting models-Shapley additive explanations framework to eddy-covariance observations from the global FLUXNET2015 data set, we found that the VPD-GPP relationship was strongly influenced by climatic interactions and that VPD was more important for plant water stress than SWC across most plant functional types when we removed the effect of main climatic drivers, e.g. air temperature, incoming shortwave radiation and wind speed. However, we found no evidence for a significant influence of elevated CO2 on stress alleviation, possibly because of the short duration of the records (approximately one decade). Additionally, the interactive effect between VPD and SWC differed from their individual effect. When SWC was high, the SHAP interaction value of SWC and VPD on GPP was decreased with increasing VPD, but when SWC was low, the trend was the opposite. Additionally, we revealed a threshold effect for VPD stress on GPP loss; above the threshold value, the stress on GPP was flattened off. Our results have important implications for independently identifying VPD and SWC limitations on plant productivity, which is meaningful for capturing the magnitude of ecosystem responses to water stress in dynamic global vegetation models.

An electrochemiluminescence immunosensor based on Ag-Ti3C2 MXene and CNNVs with multiple signal amplification strategies.

In electrochemical immunoassays, great breakthroughs have been made in ultrasensitive detection of tumor markers by amplifying signals with coreaction accelerators. Herein, carbon nitrides with nitrogen vacancies (CNNVs) are proposed as emitter, due to the introduction of nitrogen vacancies this emitter has better ECL efficiency, the phenomena of interface electron transfer and electrode passivation are improved. At the same time, it can also promote the electrochemical reduction of coreactant, making it an attractive and potential emitter. The electrode was modified with Ag-Ti3C2 MXene. It not only accelerates electron transfer and increases the effective working area of the electrode, but also acts as a coreaction accelerator to promote the electrochemical reduction of the coreactant K2S2O8, resulting in a strong ECL signal. The immunosensor showed a good linear relationship in the range of 10-5-100 ng/mL with a detection limit of 0.36 fg/mL. In addition, the excellent properties of good specificity and ultra-high stability provide an effective method for ultra-sensitive immunoassays.

MCX Cloud-a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing.

SIGNIFICANCE: Despite the ample progress made toward faster and more accurate Monte Carlo (MC) simulation tools over the past decade, the limited usability and accessibility of these advanced modeling tools remain key barriers to widespread use among the broad user community. AIM: An open-source, high-performance, web-based MC simulator that builds upon modern cloud computing architectures is highly desirable to deliver state-of-the-art MC simulations and hardware acceleration to general users without the need for special hardware installation and optimization. APPROACH: We have developed a configuration-free, in-browser 3D MC simulation platform-Monte Carlo eXtreme (MCX) Cloud-built upon an array of robust and modern technologies, including a Docker Swarm-based cloud-computing backend and a web-based graphical user interface (GUI) that supports in-browser 3D visualization, asynchronous data communication, and automatic data validation via JavaScript Object Notation (JSON) schemas. RESULTS: The front-end of the MCX Cloud platform offers an intuitive simulation design, fast 3D data rendering, and convenient simulation sharing. The Docker Swarm container orchestration backend is highly scalable and can support high-demand GPU MC simulations using MCX over a dynamically expandable virtual cluster. CONCLUSION: MCX Cloud makes fast, scalable, and feature-rich MC simulations readily available to all biophotonics researchers without overhead. It is fully open-source and can be freely accessed at http://mcx.space/cloud.

Distal tibial tubercle-high tibial osteotomy with assistance of modifiable spreader in the treatment of varus knee osteoarthritis: A retrospective observational study.

As one of the knee preservation surgical approaches, good clinical outcomes of high tibial osteotomy were reported. Aims of this study were to analyze the clinical outcome and pre- and postoperative radiographical parameter and knee functional score between distal tibial tubercle high tibial osteotomy (DTTHTO) and open wedge- high tibial osteotomy (OWHTO) in patients with varus knee osteoarthritis after more than 1 year following-up. A total of 194 consecutive patients in our joint center from March 2016 to October 2021 were enrolled, according to the surgical method, patients were divided into DDTHTO and OWHTO groups. Radiographic parameters of Kellgren-Lawrence grading, hip-knee-ankle angle, weight bearing line ratio and medial tibial plateau angle, knee functional score of American knee society (AKS) score, western Ontario and McMaster universities arthritis index (WOMAC) score, visual analogue score (VAS) were introduced to evaluate clinical outcome for patients who received DDTHTO and OWHTO. There were 103 knees and 89 knees in the OWHTO and DTTHTO group, respectively. Mean weight bearing line ratio for OWHTO and DTTHTO were 25.1 ±â€…11.7 and 25.2 ±â€…12.0% respectively, medial tibial plateau angle and hip-knee-ankle angle angle demonstrated that all patients in the present study inherited a varus angle ranges from 3.4° to 9.5°. Preoperative AKS, WOMAC and VAS were 68.4 ±â€…5.7 versus 69.0 ±â€…5.9, 109.3 ±â€…15.0 versus 107.7 ±â€…14.0 and 6.8 ±â€…1.0 versus 6.9 ±â€…0.8, and there was no significant difference between 2 groups (P > .05). Mean postoperative AKS and WOMAC score for patients in both OWHTO and DTTHTO group were significantly improved, moreover, postoperative VAS of DTTHTO patients was lower than that in OWHTO group (P < .05). When comparing the operation time, intraoperative blood loss and bone union time, DHHTO group shows a superiority in these variables over patients in OWHTO (121 ±â€…29.6 vs 145.7 ±â€…35.2 minutes, 115.0 ±â€…20.8 vs 103.3 ±â€…17.3 mL, 13.7 ±â€…4.1 vs 12.0 ±â€…2.8 weeks; P < .005) and incidence of complication was lower for DTTHTO group. DTTHTO in patients with varus knee osteoarthritis has good clinical outcomes, and it can achieve a better postoperative alignment. Operation time and surgical trauma were also less in patients who underwent DTTHTO.

Reassortment with dominant chicken H9N2 influenza virus contributed to the fifth H7N9 virus human epidemic.

H9N2 Avian influenza virus (AIV) is regarded as a principal donor of viral genes through reassortment to co-circulating influenza viruses that can result in zoonotic reassortants. Whether H9N2 virus can maintain sustained evolutionary impact on such reassortants is unclear. Since 2013, avian H7N9 virus had caused five sequential human epidemics in China; the fifth wave in 2016-2017 was by far the largest but the mechanistic explanation behind the scale of infection is not clear. Here, we found that, just prior to the fifth H7N9 virus epidemic, H9N2 viruses had phylogenetically mutated into new sub-clades, changed antigenicity and increased its prevalence in chickens vaccinated with existing H9N2 vaccines. In turn, the new H9N2 virus sub-clades of PB2 and PA genes, housing mammalian adaptive mutations, were reassorted into co-circulating H7N9 virus to create a novel dominant H7N9 virus genotype that was responsible for the fifth H7N9 virus epidemic. H9N2-derived PB2 and PA genes in H7N9 virus conferred enhanced polymerase activity in human cells at 33°C and 37°C, and increased viral replication in the upper and lower respiratory tracts of infected mice which could account for the sharp increase in human cases of H7N9 virus infection in the 2016-2017 epidemic. The role of H9N2 virus in the continual mutation of H7N9 virus highlights the public health significance of H9N2 virus in the generation of variant reassortants of increasing zoonotic potential.IMPORTANCEAvian H9N2 influenza virus, although primarily restricted to chicken populations, is a major threat to human public health by acting as a donor of variant viral genes through reassortment to co-circulating influenza viruses. We established that the high prevalence of evolving H9N2 virus in vaccinated flocks played a key role, as donor of new sub-clade PB2 and PA genes in the generation of a dominant H7N9 virus genotype (G72) with enhanced infectivity in humans during the 2016-2017 N7N9 virus epidemic. Our findings emphasize that the ongoing evolution of prevalent H9N2 virus in chickens is an important source, via reassortment, of mammalian adaptive genes for other influenza virus subtypes. Thus, close monitoring of prevalence and variants of H9N2 virus in chicken flocks is necessary in the detection of zoonotic mutations.

Light transport modeling in highly complex tissues using the implicit mesh-based Monte Carlo algorithm.

The mesh-based Monte Carlo (MMC) technique has grown tremendously since its initial publication nearly a decade ago. It is now recognized as one of the most accurate Monte Carlo (MC) methods, providing accurate reference solutions for the development of novel biophotonics techniques. In this work, we aim to further advance MMC to address a major challenge in biophotonics modeling, i.e. light transport within highly complex tissues, such as dense microvascular networks, porous media and multi-scale tissue structures. Although the current MMC framework is capable of simulating light propagation in such media given its generality, the run-time and memory usage grow rapidly with increasing media complexity and size. This greatly limits our capability to explore complex and multi-scale tissue structures. Here, we propose a highly efficient implicit mesh-based Monte Carlo (iMMC) method that incorporates both mesh- and shape-based tissue representations to create highly complex yet memory-efficient light transport simulations. We demonstrate that iMMC is capable of providing accurate solutions for dense vessel networks and porous tissues while reducing memory usage by greater than a hundred- or even thousand-fold. In a sample network of microvasculature, the reduced shape complexity results in nearly 3x speed acceleration. The proposed algorithm is now available in our open-source MMC software at http://mcx.space/#mmc.

Hybrid mesh and voxel based Monte Carlo algorithm for accurate and efficient photon transport modeling in complex bio-tissues.

Over the past decade, an increasing body of evidence has suggested that three-dimensional (3-D) Monte Carlo (MC) light transport simulations are affected by the inherent limitations and errors of voxel-based domain boundaries. In this work, we specifically address this challenge using a hybrid MC algorithm, namely split-voxel MC or SVMC, that combines both mesh and voxel domain information to greatly improve MC simulation accuracy while remaining highly flexible and efficient in parallel hardware, such as graphics processing units (GPU). We achieve this by applying a marching-cubes algorithm to a pre-segmented domain to extract and encode sub-voxel information of curved surfaces, which is then used to inform ray-tracing computation within boundary voxels. This preservation of curved boundaries in a voxel data structure demonstrates significantly improved accuracy in several benchmarks, including a human brain atlas. The accuracy of the SVMC algorithm is comparable to that of mesh-based MC (MMC), but runs 2x-6x faster and requires only a lightweight preprocessing step. The proposed algorithm has been implemented in our open-source software and is freely available at http://mcx.space.

Accelerating Monte Carlo modeling of structured-light-based diffuse optical imaging via "photon sharing".

The increasing use of spatially modulated imaging and single-pixel detection techniques demands computationally efficient methods for light transport modeling. Herein, we report an easy-to-implement yet significantly more efficient Monte Carlo (MC) method for simultaneously simulating spatially modulated illumination and detection patterns accurately in 3D complex domains. We have implemented this accelerated algorithm, named "photon sharing," in our open-source MC simulators, reporting 13.6× and 5.5× speedups in mesh- and voxel-based MC benchmarks, respectively. In addition, the proposed algorithm is readily used to accelerate the solving of inverse problems in spatially modulated imaging systems by building Jacobians of all illumination-detection pattern pairs concurrently, resulting in a 12.4-fold speed improvement.

Improving model-based functional near-infrared spectroscopy analysis using mesh-based anatomical and light-transport models.

Significance: Functional near-infrared spectroscopy (fNIRS) has become an important research tool in studying human brains. Accurate quantification of brain activities via fNIRS relies upon solving computational models that simulate the transport of photons through complex anatomy. Aim: We aim to highlight the importance of accurate anatomical modeling in the context of fNIRS and propose a robust method for creating high-quality brain/full-head tetrahedral mesh models for neuroimaging analysis. Approach: We have developed a surface-based brain meshing pipeline that can produce significantly better brain mesh models, compared to conventional meshing techniques. It can convert segmented volumetric brain scans into multilayered surfaces and tetrahedral mesh models, with typical processing times of only a few minutes and broad utilities, such as in Monte Carlo or finite-element-based photon simulations for fNIRS studies. Results: A variety of high-quality brain mesh models have been successfully generated by processing publicly available brain atlases. In addition, we compare three brain anatomical models-the voxel-based brain segmentation, tetrahedral brain mesh, and layered-slab brain model-and demonstrate noticeable discrepancies in brain partial pathlengths when using approximated brain anatomies, ranging between - 1.5 % to 23% with the voxelated brain and 36% to 166% with the layered-slab brain. Conclusion: The generation and utility of high-quality brain meshes can lead to more accurate brain quantification in fNIRS studies. Our open-source meshing toolboxes "Brain2Mesh" and "Iso2Mesh" are freely available at http://mcx.space/brain2mesh.

Cervical invasion, lymphovascular space invasion, and ovarian metastasis as predictors of lymph node metastasis and poor outcome on stages I to III endometrial cancers: a single-center retrospective study.

BACKGROUND: The aim of this study is to determine pathological factors that increase the risk of LNM and indicate poor survival of patients diagnosed with endometrial cancer and treated with surgical staging. METHOD: Between January 2010 and November 2018, we enrolled 874 eligible patients who received staging surgery in the First Affiliated Hospital of Anhui Medical University. The roles of prognostic risk factors, such as age, histological subtype, tumor grade, myometrial infiltration, tumor diameter, cervical infiltration, lymphopoiesis space invasion (LVSI), CA125, and ascites, were evaluated. Multivariable logistic regression models were used to identify the predictors of LNM. Kaplan-Meier and COX regression models were utilized to study the overall survival. RESULTS: Multivariable regression analysis confirmed cervical stromal invasion (OR 3.412, 95% CI 1.631-7.141; P < 0.01), LVSI (OR 2.542, 95% CI 1.061-6.004; P = 0.04) and ovarian metastasis (OR 6.236, 95% CI 1.561-24.904; P = 0.01) as significant predictors of nodal dissemination. Furthermore, pathological pattern (P = 0.03), myometrial invasion (OR 2.70, 95% CI 1.139-6.40; P = 0.01), and lymph node metastasis (OR 9.675, 95% CI 3.708-25.245; P < 0.01) were independent predictors of decreased overall survival. CONCLUSIONS: Cervical invasion, lymphopoiesis space invasion, and ovarian metastasis significantly convey the risk of LNM. Pathological type, myometrial invasion, and lymph node metastasis are all important predictors of survival and should be scheduled for completion when possible in the surgical staging procedure.