Search

Objective The C4 is the transition point between the upper and lower cervical vertebrae and plays a pivotal role in the middle of the cervical spine. Currently, there are limited reports on large‐scale sample studies regarding C4 anatomy in children, and a scarcity of experience exists in pediatric cervical spine surgery. The current study addresses the dearth of anatomical measurements of the C4 vertebral arch and lateral mass in a substantial sample of children. This study aims to measure the imaging anatomy of the C4 vertebral arch and lateral mass in children under 14 years of age across various age groups, investigate the growth and development of these structures. Methods We measured 12 indicators, including the size (D1, D2, D3, D4, D5, D6, D7, and D8) and angle (A, C, D, and E) of the C4 vertebral arch and lateral mass, in 513 children who underwent cervical CT examinations at our hospital. We employed the aggregate function for statistical analysis, conducted t‐tests for difference statistics, and utilized the least squares method for regression analysis. Results Overall, as age increased, there was a gradual increase in the size of the vertebral arch and lateral mass. Additionally, the medial inclination angle of the vertebral arch decreased, and the lateral mass flattened gradually. The rate of change decreased gradually with age. The mean value of D1 increased from 2.31 mm to 3.88 mm, of D2 from 16.75 mm to 29.2 mm, of D3 from 2.21 mm to 4.92 mm, and of D4 from 7.34 mm to 11.84 mm. Meanwhile, the mean value of D5 increased from 5.2 mm to 9.71 mm, of D6 from 10.19 mm to 16.16 mm, of D7 from 2.53 mm to 5.67 mm, and of D8 from 6.11 mm to 11.45 mm. Angle A ranged from 49.12° to 54.97°, angle C from 15.28° to 19.83°, angle D from 39.91° to 53.7°, and angle E from 18.63° to 28.08°. Conclusion Prior to cervical spine surgery in children, meticulous CT imaging anatomical measurements is essential. The imaging data serves as a reference for posterior C4 internal fixation, aids in designing posterior cervical screws for pediatric patients, and offer morphological anatomical references for posterior cervical spine surgery and screw design in pediatric patients.

Abstract Background Academic paper writing holds significant importance in the education of medical students, and poses a clear challenge for those whose first language is not English. This study aims to investigate the effectiveness of employing large language models, particularly ChatGPT, in improving the English academic writing skills of these students. Methods A cohort of 25 third-year medical students from China was recruited. The study consisted of two stages. Firstly, the students were asked to write a mini paper. Secondly, the students were asked to revise the mini paper using ChatGPT within two weeks. The evaluation of the mini papers focused on three key dimensions, including structure, logic, and language. The evaluation method incorporated both manual scoring and AI scoring utilizing the ChatGPT-3.5 and ChatGPT-4 models. Additionally, we employed a questionnaire to gather feedback on students’ experience in using ChatGPT. Results After implementing ChatGPT for writing assistance, there was a notable increase in manual scoring by 4.23 points. Similarly, AI scoring based on the ChatGPT-3.5 model showed an increase of 4.82 points, while the ChatGPT-4 model showed an increase of 3.84 points. These results highlight the potential of large language models in supporting academic writing. Statistical analysis revealed no significant difference between manual scoring and ChatGPT-4 scoring, indicating the potential of ChatGPT-4 to assist teachers in the grading process. Feedback from the questionnaire indicated a generally positive response from students, with 92% acknowledging an improvement in the quality of their writing, 84% noting advancements in their language skills, and 76% recognizing the contribution of ChatGPT in supporting academic research. Conclusion The study highlighted the efficacy of large language models like ChatGPT in augmenting the English academic writing proficiency of non-native speakers in medical education. Furthermore, it illustrated the potential of these models to make a contribution to the educational evaluation process, particularly in environments where English is not the primary language.

Abstract Background Bacterial nanocellulose (BNC), a natural polymer material, gained significant popularity among researchers and industry. It has great potential in areas, such as textile manufacturing, fiber-based paper, and packaging products, food industry, biomedical materials, and advanced functional bionanocomposites. The main current fermentation methods for BNC involved static culture, as the agitated culture methods had lower raw material conversion rates and resulted in non-uniform product formation. Currently, studies have shown that the production of BNC can be enhanced by incorporating specific additives into the culture medium. These additives included organic acids or polysaccharides. γ-Polyglutamic acid (γ-PGA), known for its high polymerization, excellent biodegradability, and environmental friendliness, has found extensive application in various industries including daily chemicals, medicine, food, and agriculture. Results In this particular study, 0.15 g/L of γ-PGA was incorporated as a medium additive to cultivate BNC under agitated culture conditions of 120 rpm and 30 ℃. The BNC production increased remarkably by 209% in the medium with 0.15 g/L γ-PGA and initial pH of 5.0 compared to that in the standard medium, and BNC production increased by 7.3% in the medium with 0.06 g/L γ-PGA. The addition of γ-PGA as a medium additive resulted in significant improvements in BNC production. Similarly, at initial pH levels of 4.0 and 6.0, the BNC production also increased by 39.3% and 102.3%, respectively. To assess the characteristics of the BNC products, scanning electron microscopy, Fourier transform infrared spectroscopy, and thermogravimetric analysis were used. The average diameter of BNC fibers, which was prepared from the medium adding 0.15 g/L γ-PGA, was twice thicker than that of BNC fibers prepared from the control culture medium. That might be because that polyglutamic acid relieved the BNC synthesis from the shear stress from the agitation. Conclusions This experiment held great significance as it explored the use of a novel medium additive, γ-PGA, to improve the production and the glucose conversion rate in BNC fermentation. And the BNC fibers became thicker, with better thermal stability, higher crystallinity, and higher degree of polymerization (DPv). These findings lay a solid foundation for future large-scale fermentation production of BNC using bioreactors.

Abstract Background Large language models like ChatGPT have revolutionized the field of natural language processing with their capability to comprehend and generate textual content, showing great potential to play a role in medical education. This study aimed to quantitatively evaluate and comprehensively analysis the performance of ChatGPT on three types of national medical examinations in China, including National Medical Licensing Examination (NMLE), National Pharmacist Licensing Examination (NPLE), and National Nurse Licensing Examination (NNLE). Methods We collected questions from Chinese NMLE, NPLE and NNLE from year 2017 to 2021. In NMLE and NPLE, each exam consists of 4 units, while in NNLE, each exam consists of 2 units. The questions with figures, tables or chemical structure were manually identified and excluded by clinician. We applied direct instruction strategy via multiple prompts to force ChatGPT to generate the clear answer with the capability to distinguish between single-choice and multiple-choice questions. Results ChatGPT failed to pass the accuracy threshold of 0.6 in any of the three types of examinations over the five years. Specifically, in the NMLE, the highest recorded accuracy was 0.5467, which was attained in both 2018 and 2021. In the NPLE, the highest accuracy was 0.5599 in 2017. In the NNLE, the most impressive result was shown in 2017, with an accuracy of 0.5897, which is also the highest accuracy in our entire evaluation. ChatGPT’s performance showed no significant difference in different units, but significant difference in different question types. ChatGPT performed well in a range of subject areas, including clinical epidemiology, human parasitology, and dermatology, as well as in various medical topics such as molecules, health management and prevention, diagnosis and screening. Conclusions These results indicate ChatGPT failed the NMLE, NPLE and NNLE in China, spanning from year 2017 to 2021. but show great potential of large language models in medical education. In the future high-quality medical data will be required to improve the performance.

Abstract O-Sulfation is a vital post-translational modification in bioactive molecules, yet there are significant challenges with their synthesis. Dialkyl sulfates, such as dimethyl sulfate and diisopropyl sulfate are commonly used as alkylation agents in alkaline conditions, and result in the formation of sulfate byproducts. We report herein a general and robust approach to O-sulfation by harnessing the tunable reactivity of dimethyl sulfate or diisopropyl sulfate under tetrabutylammonium bisulfate activation. The versatility of this O-sulfation protocol is interrogated with a diverse range of alcohols, phenols and N-OH compounds, including carbohydrates, amino acids and natural products. The enhanced electrophilicity of the sulfur atom in dialkyl sulfates, facilitated by the interaction with bisulfate anion (HSO4 -), accounts for this pioneering chemical reactivity. We envision that our method will be useful for application in the comprehension of biological functions and discovery of drugs.

Abstract. Background:. Bladder cancer, characterized by a high potential of tumor recurrence, has high lifelong monitoring and treatment costs. To date, tumor cells with intrinsic softness have been identified to function as cancer stem cells in several cancer types. Nonetheless, the existence of soft tumor cells in bladder tumors remains elusive. Thus, our study aimed to develop a micro-barrier microfluidic chip to efficiently isolate deformable tumor cells from distinct types of bladder cancer cells. Methods:. The stiffness of bladder cancer cells was determined by atomic force microscopy (AFM). The modified microfluidic chip was utilized to separate soft cells, and the 3D Matrigel culture system was to maintain the softness of tumor cells. Expression patterns of integrin β8 (ITGB8), protein kinase B (AKT), and mammalian target of rapamycin (mTOR) were determined by Western blotting. Double immunostaining was conducted to examine the interaction between F-actin and tripartite motif containing 59 (TRIM59). The stem-cell-like characteristics of soft cells were explored by colony formation assay and in vivo studies upon xenografted tumor models. Results:. Using our newly designed microfluidic approach, we identified a small fraction of soft tumor cells in bladder cancer cells. More importantly, the existence of soft tumor cells was confirmed in clinical human bladder cancer specimens, in which the number of soft tumor cells was associated with tumor relapse. Furthermore, we demonstrated that the biomechanical stimuli arising from 3D Matrigel activated the F-actin/ITGB8/TRIM59/AKT/mTOR/glycolysis pathways to enhance the softness and tumorigenic capacity of tumor cells. Simultaneously, we detected a remarkable up-regulation in ITGB8, TRIM59, and phospho-AKT in clinical bladder recurrent tumors compared with their non-recurrent counterparts. Conclusions:. The ITGB8/TRIM59/AKT/mTOR/glycolysis axis plays a crucial role in modulating tumor softness and stemness. Meanwhile, the soft tumor cells become more sensitive to chemotherapy after stiffening, that offers new insights for hampering tumor progression and recurrence.

Abstract Captive pandas are suffering from intestinal infection due to intestinal microbiota characterized by a high abundance of Enterobacteriaceae induced by long-term captivity. Probiotic supplements showed improvement in intestinal barrier function and inflammation. However, the effects of panda-derived probiotics on the intestinal epithelium and inflammation have not been elucidated. In the present study, lipopolysaccharide (LPS) impaired Caco-2 and RAW264.7 inflammatory models were applied to assess the protection of Lactiplantibacillus plantarum BSG201683 (L. plantarum G83) on barrier disruption and inflammation. The results showed that treatment with L. plantarum G83 significantly decreased the paracellular permeability to fluorescein isothiocyanate conjugated dextran (MW 4000, FITC-D4) after LPS induction. Meanwhile, L. plantarum G83 alleviated the reduction in tight junction (TJ) proteins and downregulated proinflammatory cytokines caused by LPS in Caco-2 cells. L. plantarum G83 also significantly decreased the expression and secretion of pro-inflammatory cytokines in LPS-induced RAW264.7 cells. In addition, the IL-10 increased in both Caco-2 and RAW264.7 cells after L. plantarum G83 treatment. The phagocytosis activity of RAW264.7 cells was significantly increased after L. plantarum G83 treatment. Toll-like receptor 4/ nuclear factor kappa-B (TLR4/NF-κB) signaling pathways were significantly down-regulated after L. plantarum G83 intervention, and the phosphorylation of NF-κB/p65 was consistent with this result. Our findings suggest that L. plantarum G83 improves intestinal inflammation and epithelial barrier disruption in vitro.

Background Catheter ablation of premature ventricular contractions (PVCs) that trigger polymorphic ventricular tachycardia (PVT) or ventricular fibrillation has been reported as a novel therapy to reduce the syncope events in patients with catecholaminergic PVT, whereas the long‐term ablation outcome and its value in improving exercise‐induced ventricular arrhythmias remain unclear. Methods and Results Fourteen consecutive selected patients with catecholaminergic PVT (mean±SD age, 16±6 years; 43% male patients) treated with maximum β‐blockers with no possibility of adding flecainide were prospectively enrolled for catheter ablation. The primary end point was syncope recurrence, and the secondary end point was the reduction of the ventricular arrhythmia score during exercise testing. Twenty‐six PVT/ventricular fibrillation–triggering PVCs were identified for ablation. The trigger beats arose from the left ventricle in 50% of the cases and from both ventricles in 36% of the cases. Purkinje potentials were observed at 27% of the targets. After a mean follow‐up of 49 months after ablation, 8 (57%) patients were free from syncope recurrence. Ablation of trigger beat significantly reduced the syncope frequency (mean±SD, 4.3±1.6 to 0.5±0.8 events per year; P

Key errors of machine tools have a significant impact on their accuracy, however accurately and quickly measuring the geometric errors of machine tools is essential for key error identification. Fortunately, a quick and direct laser measurement method and system for 21 geometric errors of three linear axes of machine tools were proposed previously, which enables the measurement of all 21 geometric errors via a one-step installation and a three-step automated measurement process. Based on this, to efficiently identify the key error factors, this paper first utilizes the 21 geometric errors obtained from the proposed measurement system to evaluate the contribution of each error to the volumetric errors of machine tools, leading to the building of a 21-geometric-error sensitivity analysis model. Then, experiments are carried out on the vertical machining tool TH5656, and all 21 geometric errors are obtained in 5 min. After this, the volumetric error distribution in the machining workspace is mapped according to the relationship between the geometric errors and the machining errors, and the key error factors affecting the manufacturing and machining accuracy of the TH5656 are ultimately determined. Thus, this new method provides a way to quickly identify key errors of the three linear axes of machine tools, and offers guidance for the machine tool configuration design, machining technology determination, and geometric error compensation.

This study evaluated the co-production of pigment and bacterial nanocellulose (BNC) from S. salsa biomass. The extraction of the beet red pigment reduced the salts and flavonoids contents by 82.7%–100%, promoting the efficiencies of enzymatic saccharification of the biomass and the fermentation of BNC from the hydrolysate. SEM analysis revealed that the extraction process disrupted the lignocellulosic fiber structure, and the chemical analysis revealed the lessened cellulase inhibitors, consequently facilitating enzymatic saccharification for 10.4 times. BNC producing strains were found to be hyper-sensitive to NaCl stress, produced up to 400.4% more BNC from the hydrolysate after the extraction. The fermentation results of BNC indicated that the LDU-A strain yielded 2.116 g/L and 0.539 g/L in ES-M and NES-M, respectively. In comparison to the control, the yield in ES-M increased by approximately 20.0%, while the enhancement in NES-M was more significant, reaching 292.6%. After conducting a comprehensive characterization of BNC derived from S. salsa through Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and Thermogravimetric Analysis (TGA), the average fiber diameter distribution of these four BNC materials ranges from 22.23 to 33.03 nanometers, with a crystallinity range of 77%–90%. Additionally, they exhibit a consistent trend during the thermal degradation process, further emphasizing their stability in high-temperature environments and similar thermal properties. Our study found an efficient co-production approach of pigment and BNC from S. salsa biomass. Pigment extraction made biomass more physically and chemically digestible to cellulase, and significantly improved BNC productivity and quality.

Background: Deep learning methods are increasingly applied in the medical field; however, their lack of interpretability remains a challenge. Captum is a tool that can be used to interpret neural network models by computing feature importance weights. Although Captum is an interpretable model, it is rarely used to study medical problems, and there is a scarcity of data regarding MRI anatomical measurements for patients with prostate cancer after undergoing Robotic-Assisted Radical Prostatectomy (RARP). Consequently, predictive models for continence that use multiple types of anatomical MRI measurements are limited. Methods: We explored the energy efficiency of deep learning models for predicting continence by analyzing MRI measurements. We analyzed and compared various statistical models and provided reference examples for the clinical application of interpretable deep-learning models. Patients who underwent RARP at our institution between July 2019 and December 2020 were included in this study. A series of clinical MRI anatomical measurements from these patients was used to discover continence features, and their impact on continence was primarily evaluated using a series of statistical methods and computational models. Results: Age and six other anatomical measurements were identified as the top seven features of continence by the proposed model UINet7 with an accuracy of 0.97, and the first four of these features were also found by primary statistical analysis. Conclusions: This study fills the gaps in the in-depth investigation of continence features after RARP due to the limitations of clinical data and applicable models. We provide a pioneering example of the application of deep-learning models to clinical problems. The interpretability analysis of deep learning models has the potential for clinical applications.

BackgroundBisphenol A (BPA), bisphenol S (BPS), and bisphenol F (BPF) are widely used in various consumer products. They are environmental contaminants with estrogenic properties that have been linked to various health outcomes. Understanding their impact on body composition is crucial for identifying potential health risks and developing preventive strategies. However, most current studies have only focused on their relationship with BMI. ObjectiveThis study aimed to investigate the association between urinary levels of BPA, BPS, and BPF and body composition, including BMI, lean mass, and fat mass, in a large population-based sample. MethodsWe conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey 2003-2016. Body composition data were assessed using dual-energy X-ray absorptiometry, which provided precise measurements of lean mass, fat mass, and other indicators. We used multivariate linear regression models to estimate the associations, adjusting for potential confounders such as age, gender, race, socioeconomic factors, and lifestyle variables. ResultsThe results revealed significant associations between bisphenol exposure and body composition. After adjusting for covariates, BPS showed a positive association with BMI, with quartiles 3 and 4 having 0.91 (95% CI 0.34-1.48) and 1.15 (95% CI 0.55-1.74) higher BMI, respectively, compared with quartile 1 (P

Abstract Background Bisphenol A (BPA) exposure and its structural analogs (BPS and BPF) might cause endocrine alterations and adverse physiological effects. Few studies to date have directly explored the association between its structural analogs (BPS, BPF) and sex hormones in adult male participants. Therefore, we aimed to assess the associations between BPA, BPS, BPF, and sex hormones in American adult men. Methods We used data from the U.S. National Health and Nutrition Examination Survey 2011–2016. We excluded participants without data available on sex hormones and urinary bisphenols. Furthermore, participants consuming sex hormone medications were excluded. Multivariable regression models were performed to assess the association between bisphenols and sex hormones. Results In this study, 2367 participants were included. Of 2367, in 1575 participants, the data on BPS and BPF were available. We found that a per unit increase in BPF was associated with 0.575 ng/dL higher total testosterone (TT) (Model 2: 95% CI: 0.047, 1.103, P = 0.033). However, there was no significant association between BPA or BPS and TT. Furthermore, increased BPA and BPS levels were associated with higher levels of sex hormone-binding globulin (SHBG) (Model 2: β = 0.364, 95% CI: 0.158, 0.571; β = 0.25, 95% CI: 0.071, 0.429, respectively). Additionally, participants in the highest BPA exposure quartile (quartile 4) had 4.072 nmol/L higher levels of SHBG than those in quartile 1 (Model 2: 95% CI: 0.746, 7.397, P = 0.017; P for trend =0.005). Both BPA and BPS were negatively associated with free testosterone (FT, nmol/L) after full adjustment (Model 2, β = − 0.01%, P = 0.0211, P = 0.0211; Model 2, β = − 0.01%, P = 0.0258, respectively). However, BPF was positively associated with FT (Model 2, β = 0.0029%, P = 0.0028). Conclusion Our study indicated that exposure to both BPA and its substitutions could alter sex hormone levels. This finding supports the possibility that human exposure to bisphenols at environmental levels might affect the endogenous hormone balance.

Highlights 1. klotho deficiency linked to multiple premature-aging syndromes and a short lifespan 2. Proinflammatory cytokines, including TNF-α, IFN-γ, and IL-6, downregulate α-Klotho gene expression 3. Dietary Inflammatory Index was developed as a tool to determine the inflammatory potential of diet 4. We found that there was a dose–response relationship between DII and circulating concentrations of klotho in a nationally representative population of American adults.

Video question answering (VideoQA) is a typical task that integrates language and vision. The key for VideoQA is to extract relevant and effective visual information for answering a specific question. Information selection is believed to be necessary for this task due to the large amount of irrelevant information in the video, and explicitly learning an attention model can be a reasonable and effective solution for the selection. Herein, a novel VideoQA model called Text‐Assisted Spatial and Temporal Attention Network (TASTA) is proposed, which shows the great potential of explicitly modeling attention. TASTA is made to be simple, small, clean, and efficient for clear performance justification and possible easy extension. Its success is mainly from two new strategies of better using the textual information. Experimental results on a large and most representative dataset, TGIF‐QA, show the significant superiority of TASTA w.r.t. the state‐of‐the‐art and demonstrate the effectiveness of its key components via ablation studies.

Laser-based measurement and sensing technology has been paid more and more attention by academia and industry because of its incomparable advantages, such as high sensitivity, fast response, and no contact [...]

BackgroundIt has been reported for several years that polycyclic aromatic hydrocarbons (PAHs) could disturb human endocrine function. However, there is still a short of consistent conclusion about the relationship between PAH exposure and levels of sexual hormones. The aim of our study is to explore whether exposure to PAHs and how PAHs affect the levels of serum testosterone (T) and estradiol (E2) in adults, hoping to fulfill the knowledge gap.Materials and methodsThis study included adults aged 20 and above who participated in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016. We included 10 PAH metabolites in this study. The levels of urinary PAH metabolites were log-transformed and divided into quartiles. The associations between PAH metabolites and both serum T levels of males and E2 levels of females were investigated using multivariate regression models. We furtherly calculated PAHs scores by sum of ranks across 10 PAHs metabolites, which represented the exposure levels of PAHs mixtures, and the association between PAHs scores and serum T and E2 levels were analyzed.ResultsA total of 4,654 subjects were included in this study, including 2,460 males and 2,194 females. After adjusting for confounders, 2-hydroxynapthalene and 3-hydroxyfluorene were positively associated with serum T levels of males (p-value for trend=0.047, and p-value for trend=0.006, respectively), while 1-hydroxyphenanthrene was positively associated with serum E2 levels of females (p-value for trend=0.013). In the adjusted models, no significant association was found between PAHs scores and either T levels of males or E2 levels of females (p-value for trend=0.615, and p-value for trend=0.241, respectively).ConclusionsThis study showed urinary 2-hydroxynapthalene and 3-hydroxyfluorene were associated with increased T levels of males, and urinary 1-hydroxyphenanthrene was associated with increased E2 levels of females. The observed association indicated disrupting effects of PAH exposure on reproductive health.

This review has summarized the methods currently available for cardiac sympathetic assessment in clinical or under research, with emphasis on the principles behind these methodologies. Heart rate variability (HRV) and other methods based on heart rate pattern analysis can reflect the dominance of sympathetic nerve to sinoatrial node function and indirectly show the average activity level of cardiac sympathetic nerve in a period of time. Sympathetic neurotransmitters play a key role of signal transduction after sympathetic nerve discharges. Plasma or local sympathetic neurotransmitter detection can mediately display sympathetic nerve activity. Given cardiac sympathetic nerve innervation, i.e., the distribution of stellate ganglion and its nerve fibers, stellate ganglion activity can be recorded either directly or subcutaneously, or through the surface of the skin using a neurophysiological approach. Stellate ganglion nerve activity (SGNA), subcutaneous nerve activity (SCNA), and skin sympathetic nerve activity (SKNA) can reflect immediate stellate ganglion discharge activity, i.e., cardiac sympathetic nerve activity. These cardiac sympathetic activity assessment methods are all based on the anatomy and physiology of the heart, especially the sympathetic innervation and the sympathetic regulation of the heart. Technological advances, discipline overlapping, and more understanding of the sympathetic innervation and sympathetic regulation of the heart will promote the development of cardiac sympathetic activity assessment methods.

BackgroundThe association between grip strength and depression in elderly individuals in low- and middle-income countries (LMICs) has rarely been studied. This study aims to explore the relevance of grip strength and depression in the elderly population using data from a national large-scale population.MethodsThis study was conducted using data from seniors over 60 years old in wave 1 of the Longitudinal Aging Study in India (LASI). Grip strength is the maximum of three measurements by the dynamometer. Depression symptoms were assessed using 10 items on the Center for Epidemiologic Studies Depression Scale (CESD-10) with a 10-point boundary. Multivariate linear regression analysis, non-linear analysis, subgroup analysis, interaction tests and sensitivity analysis were performed.ResultsThere were 27,343 participants in this study, including 19,861 participants with low grip strength and 7,482 participants with normal grip strength. The results revealed that grip strength and depression were negatively correlated in elderly individuals after adequate adjustment for confounding factors [odds ratio (OR) = 1.237, 95% confidence interval (CI) 1.172–1.305, p < 0.00001]. The results remained stable after adjusting for all confounding factors (OR = 1.090, 95% CI 1.030–1.155, p = 0.00307). Regression analysis showed that physical activity (PA), comorbidities and cognition may have an impact on the correlation between grip strength and depression symptoms. Smooth curve fit suggested that grip strength and depressive symptoms were linearly related. The interaction test results of gender in the relationship between grip strength and depression were significant (p for interaction < 0.05).ConclusionGrip strength and depression were negatively correlated in older Indians, and larger prospective studies are needed in the future to determine this association.

Abstract The purpose of this study was to evaluate the association between dietary inflammatory index (DII) and urinary incontinence (UI) among a representative sample of the US women. We performed a cross-sectional analysis of women younger than 65 years using the 1999 to 2016 NHANES (National Health and Nutrition Examination Survey) populations. DII were calculated based on baseline dietary intake using 24-h dietary recalls. UI was determined and categorized by self-reported questions. Multivariable logistic regression models were used to assess the association between DII and UI. Stratified linear regression models were applied to test for interaction in prespecified subgroup of interest. A total of 13,441 women age between 20 and 65 years were included in the final analysis. Of these participants 3230 (24.03%) complained of urgency UI, 5276 (39.25%) complained of stress UI and 2028 (15.09%) complained of mixed UI. On multivariate analysis, analysis with DII categorized as quartiles revealed significantly increase odds of urgency UI in the most pro-inflammatory quartile compared to the most anti-inflammatory quartile (OR 1.24, 95% CI 1.07–1.44, P = 0.004 for trend) in full adjustment model. Similar results were observed in SUI (OR 1.14, 95% CI 1.00–1.30, P = 0.021 for trend) and MUI (OR 1.20, 95% CI 1.02−1.43, P = 0.022 for trend). More pro-inflammatory diets, as presented by higher DII scores are associated with an increased likelihood of UI in American women younger than 65 years. Further studies are needed to explore the possible physiological mechanism and evaluate the potential therapeutic implications.

Wheel flats are amongst the most common local surface defect in railway wheels, which can result in repetitive high wheel–rail contact forces and thus lead to rapid deterioration and possible failure of wheels and rails if not detected at an early stage. The timely and accurate detection of wheel flats is of great significance to ensure the safety of train operation and reduce maintenance costs. In recent years, with the increase of train speed and load capacity, wheel flat detection is facing greater challenges. This paper focuses on the review of wheel flat detection techniques and flat signal processing methods based on wayside deployment in recent years. Commonly used wheel flat detection methods, including sound-based methods, image-based methods, and stress-based methods are introduced and summarized. The advantages and disadvantages of these methods are discussed and concluded. In addition, the flat signal processing methods corresponding to different wheel flat detection techniques are also summarized and discussed. According to the review, we believe that the development direction of the wheel flat detection system is gradually moving towards device simplification, multi-sensor fusion, high algorithm accuracy, and operational intelligence. With continuous development of machine learning algorithms and constant perfection of railway databases, wheel flat detection based on machine learning algorithms will be the development trend in the future.

Using polarization-maintaining fiber (PMF) in dual-frequency heterodyne interferometry has the advantages of reducing the laser’s own drift, obtaining high-quality light spots, and improving thermal stability. Using only one single-mode PMF to achieve the transmission of dual-frequency orthogonal, linearly polarized beam requires angular alignment only once to realize the transmission of dual-frequency orthogonal, linearly polarized light, avoiding coupling inconsistency errors, so that it has the advantages of high efficiency and low cost. However, there are still many nonlinear influencing factors in this method, such as the ellipticity and non-orthogonality of the dual-frequency laser, the angular misalignment error of the PMF, and the influence of temperature on the output beam of the PMF. This paper uses the Jones matrix to innovatively construct an error analysis model for the heterodyne interferometry using one single-mode PMF, to realize the quantitative analysis of various nonlinear error influencing factors, and clarify that the main error source is the angular misalignment error of the PMF. For the first time, the simulation provides a goal for the optimization of the alignment scheme of the PMF and the improvement of the accuracy to the sub-nanometer level. In actual measurement, the angular misalignment error of the PMF needs to be smaller than 2.87° to achieve sub-nanometer interference accuracy, and smaller than 0.25° to make the influence smaller than ten picometers. It provides theoretical guidance and an effective means for improving the design of heterodyne interferometry instruments based on PMF and further reducing measurement errors.

High-performance Elliptic Curve Cryptography (ECC) implementation in encryption authentication severs has become a challenge due to the explosive growth of e-commerce’s demand for speed and security. Point multiplication (PM) is the most common and complex operation in ECC which directly determines the performance of the whole system. This article proposes a 6CC-6CC (clock cycle) dual-field PM architecture and a 6CC-4CC dual-field PM architecture based on maximizing utilization of Karatsuba multipliers and re-ordering schedule strategy in PM. The Montgomery Ladder algorithm used in PM is modified to a 4CC algorithm for better resource utilization and parallel computation. To solve the frequency drop problem while working on large finite field, the PM architectures for high and low field are carefully studied to have universal critical path length and balanced performance. Both of the architectures are implemented over GF(2571) and GF(2283) on Xilinx Virtex-5 and Virtex-7 FPGAs (Field-Programmable Gate Array) for comparison. The 6CC-6CC architecture is shown to have the best performance on GF(2571), which achieves one PM operation in $17.44~\mu s$ using 81549 LUTs (Look-Up-Table) with the frequency of 197.2 MHz on Virtex-5, and $12.55~\mu s$ using 80970 LUTs with the frequency of 274.1 MHz on Virtex-7. The 6CC-4CC architecture performs better on GF(2283) with the shortest computation time. It takes only $3.21~\mu s$ to finish one PM operation on Virtex-5 and $2.22~\mu s$ on Virtex-7, which are faster than all the previous designs. The implementation results prove that the proposed architectures have state-of-the-art performance as well as higher versatility for ECC designs.

Introduction: We aimed to develop an easy-to-use individual survival prognostication tool based on competing risk analyses to predict the risk of 5-year cancer-specific death after radical prostatectomy for patients with prostate cancer (PCa).Methods: We obtained the data from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2016). The main variables obtained included age at diagnosis, marital status, race, pathological extension, regional lymphonode status, prostate specific antigen level, pathological Gleason Score. In order to reveal the independent prognostic factors. The cumulative incidence function was used as the univariable competing risk analyses and The Fine and Gray's proportional subdistribution hazard approach was used as the multivariable competing risk analyses. With these factors, a nomogram and risk stratification based on the nomogram was established. Concordance index (C-index) and calibration curves were used for validation.Results: A total of 95,812 patients were included and divided into training cohort (n = 67,072) and validation cohort (n = 28,740). Seven independent prognostic factors including age, race, marital status, pathological extension, regional lymphonode status, PSA level, and pathological GS were used to construct the nomogram. In the training cohort, the C-index was 0.828 (%95CI, 0.812–0.844), and the C-index was 0.838 (%95CI, 0.813–0.863) in the validation cohort. The results of the cumulative incidence function showed that the discrimination of risk stratification based on nomogram is better than that of the risk stratification system based on D'Amico risk stratification.Conclusions: We successfully developed the first competing risk nomogram to predict the risk of cancer-specific death after surgery for patients with PCa. It has the potential to help clinicians improve post-operative management of patients.

Abstract Background For localized prostate cancer (PCa), radical prostatectomy (RP) and radiotherapy (RT) are two standard interventions to decrease PCa mortality. Contemporary studies contained the elderly people; analyses focusing on patients over 75 years of age were still lacking. Method In the Surveillance Epidemiology and End Results (SEER) database (2004‐2015), people over 75 years of age with cT2 stage were selected in our research. Multivariable Cox proportional hazard models were used to analyze cancer‐specific mortality (CSM) and overall mortality (OM) after adjustment. The propensity score matching was performed to assume the randomization. An instrument variate (IVA) was used to calculate the unmeasured confounders. Results Radical prostatectomy is superior to RT in OM and CSM after adjustment for covariates (HR = 0.54, 95% CI = 0.47‐0.62, P

This paper introduces a novel speed-oriented architecture of point multiplication in elliptic curve cryptography. A balanced full-precision multiplier is proposed to shorten latency, and a new modular inversion architecture is integrated to reduce the total number of clock cycles in point multiplication. A modified Montgomery Ladder algorithm that takes three clock cycles to calculate one input bit is proposed to best utilize hardware resources. A mixed-pipeline technique is used to balance the delay of different paths and increase frequency. The proposed architecture is implemented on GF(2163) and GF(2571), based on Xilinx Virtex-5 and Virtex-7 FPGA. For GF(2163), the design reaches 211 MHz, with 29309 LUTs, and 547 clock cycles or $2.6~\mu \text{s}$ latency on Virtex-5; 320.5 MHz, with 28911 LUTs and $1.7~\mu \text{s}$ latency on Virtex-7. For GF(2571), the design reaches 186 MHz, with 286400 LUTs, and 1813 clock cycles or $9.6~\mu \text{s}$ latency on Virtex-5; 267 MHz, 290001 LUTs and $6.79~\mu \text{s}$ latency on Virtex-7. The proposed design achieves the lowest latency among all existing works, and its performance is also among the top. Furthermore, it is demonstrated that the proposed architecture maintains a high speed for larger binary fields, making it more suitable to be implemented in large-bit-length platforms with a higher security level. Since the multiplier and its segments work in different bit-length and refer to different fields, the proposed architecture can also be upgraded to a reconfigurable design to support multiple-field point multiplication in the future.

Solution-processed CdTe semiconductor nanocrystals (NCs) have exhibited astonishing potential in fabricating low-cost, low materials consumption and highly efficient photovoltaic devices. However, most of the conventional CdTe NCs reported are synthesized through high temperature microemulsion method with high toxic trioctylphosphine tellurite (TOP-Te) or tributylphosphine tellurite (TBP-Te) as tellurium precursor. These hazardous substances used in the fabrication process of CdTe NCs are drawing them back from further application. Herein, we report a phosphine-free method for synthesizing group II-VI semiconductor NCs with alkyl amine and alkyl acid as ligands. Based on various characterizations like UV-vis absorption (UV), transmission electron microscope (TEM), and X-ray diffraction (XRD), among others, the properties of the as-synthesized CdS, CdSe, and CdTe NCs are determined. High-quality semiconductor NCs with easily controlled size and morphology could be fabricated through this phosphine-free method. To further investigate its potential to industrial application, NCs solar cells with device configuration of ITO/ZnO/CdSe/CdTe/Au and ITO/ZnO/CdS/CdTe/Au are fabricated based on NCs synthesized by this method. By optimizing the device fabrication conditions, the champion device exhibited power conversion efficiency (PCE) of 2.28%. This research paves the way for industrial production of low-cost and environmentally friendly NCs photovoltaic devices.

SPE water electrolysis is a promising method of hydrogen production owing to its multiple strengths, including its high efficiency, high product purity and excellent adaptability. However, the overpotential of the oxygen evolution reaction process and consumption of Ir during charging in SPE water electrolysis will inevitably result in large energy loss and then high cost. Under these circumstances, we propose a novel 40IrO2/CoxSn(1−x)O2 (x = 0.1, 0.2, 0.3) anode catalyst, where the CoxSn(1−x)O2 support is synthesized by a hydrothermal method and IrO2 is synthesized by a modified Adams fusion method. After modifying the component of CoxSn(1−x)O2, the 40IrO2/CoxSn(1−x)O2 exhibits an increased specific surface area, electrical conductivity and surface active sites. Moreover, a single cell is fabricated by Pt/C as cathode catalyst, 40IrO2/CoxSn(1−x)O2 as anode catalyst and Nafion 117 membrane as electrolyte. The 40IrO2/Co0.2Sn0.8O2 exhibits the lowest overpotential (1.748 V at 1000 mA cm−2), and only 0.18 mV h−1 of voltage increased for 100 h durability test at 1000 mA cm−2. Consequently, CoxSn(1−x)O2 is a promising anode electrocatalyst support for an SPE water electrolyzer.

A novel method is proposed for measuring the six degrees-of-freedom (DOF) geometric motion errors of a rotary axis based on a polyhedral prism. An error-sensitive unit which consists of a polyhedral prism and a planar reflector, is designed to carry out measurement of all six DOF errors, including the angular positioning error, the tilt motion error around the Y axis, the tilt motion error around the X axis, the radial motion error along the X and Y axes, and the axial motion error along the Z axis. The mathematical error model, including the six DOF geometric motion errors of the rotary axis, the installation errors between the polyhedral prism and the rotary axis, the manufacturing errors of the polyhedral prism, and the position errors of the sensors, are established. The effectiveness of the proposed method and the compensation model was simulated and experimentally verified.

In order to significantly enhance the absorption capability of solar energy absorbers in the visible wavelength region, a novel monolayer molybdenum disulfide (MoS2)-based nanostructure was proposed. Local surface plasmon resonances (LSPRs) supported by Au nanocubes (NCs) can improve the absorption of monolayer MoS2. A theoretical simulation by a finite-difference time-domain method (FDTD) shows that the absorptions of proposed MoS2-based absorbers are above 94.0% and 99.7% at the resonant wavelengths of 422 and 545 nm, respectively. In addition, the optical properties of the proposed nanostructure can be tuned by the geometric parameters of the periodic Au nanocubes array, distributed Bragg mirror (DBR) and polarization angle of the incident light, which are of great pragmatic significance for improving the absorption efficiency and selectivity of monolayer MoS2. The absorber is also able to withstand a wide range of incident angles, showing polarization-independence. Similar design ideas can also be implemented to other transition-metal dichalcogenides (TMDCs) to strengthen the interaction between light and MoS2. This nanostructure is relatively simple to implement and has a potentially important application value in the development of high-efficiency solar energy absorbers and other optoelectronic devices.

In this study, a dual-input coupling powertrain system (DICPS) was proposed to improve the energy utilization efficiency of pure electric tractors (PETs). The working principles of the DICPS under different modes were analyzed and dynamic models were established. To study the influence of changing key parameters in the DICPS on the economic performance of PETs, a parameter-matching design method was proposed and the feasible region of the design parameters was determined according to the tractor’s dynamic performance. In addition, we put forward an energy management strategy (EMS) based on the optimal system efficiency and a dual-motor-driven electric tractor (DMET) model was built in MATLAB/Simulink. The simulation results revealed that different parameter configurations of DICPS will lead to significant changes in overall efficiency, with a maximum difference of 6.6% (under a rotary tillage cycle). We found that the optimal parameter configuration for the DMET under two typical working conditions was PDR = 0.5, k = 1.6. Compared with the single-motor powertrain system (SMPS), the DICPS with the optimal configuration of key parameters can significantly improve overall efficiency by about 9.8% (under a plowing cycle).

A novel method for simultaneously directly measuring six-degrees-of-freedom (6DOF) geometric motion errors of CNC machine tools was proposed, and a corresponding measurement system was developed. This method can not only be applied for measuring a linear axis, but also for a rotary axis. A single-mode fiber was used to separate the measuring unit from the laser source in order to ensure system thermal stability and measurement accuracy. The method has the advantages of high efficiency and good accuracy, and requires no complicated decoupling calculation. The positioning error of the linear axis and radial motion error of the rotary axis are measured by laser interferometry and other 5DOF geometric motion errors by laser collimation. A series of experiments were performed to verify the feasibility and effectiveness of the developed measurement system.

A trace acetylene (C2H2) detection system was demonstrated using the cavity-enhanced absorption spectroscopy (CEAS) technique and a near-infrared distributed feedback (NIR-DFB) laser. A Fabry⁻Perot (F⁻P) cavity with an effective optical path length of 49.7 m was sealed and employed as a gas absorption cell. Co-axis cavity alignment geometry was adopted to acquire a larger transmitted light intensity and a higher sensitivity compared with off-axis geometry. The laser frequency was locked to the cavity fundamental mode (TEM00 mode) by using the Pound⁻Drever⁻Hall (PDH) technique continuously. By introducing a cavity length-locking loop, the drift of the cavity length was suppressed, and the stability of the system was enhanced. To demonstrate the efficacy of the system, a C2H2 absorption spectrum near 6534.36 cm−1 was acquired by tuning the laser operation temperature. Measurements of C2H2 samples with different concentrations were carried out, and a good linear relationship between C2H2 concentration and the cavity-transmitted signal voltage was observed. The measurement results showed the system could work stably for more than 2 h without major fluctuations. The Allan variance analysis results demonstrated a detection limit of 9 parts-per-billion (ppb) with an averaging time of 11 s corresponding to a minimum detectable absorption coefficient of 1.1 × 10−8 cm−1.

Error measurement of a rotary axis is the key to error compensation and to improving motion accuracy. However, only a few instruments can measure all the motion errors of a rotary axis. In this paper, a device based on laser collimation and laser interferometry was introduced for simultaneous measurement of all six degrees-of-freedom motion errors of a rotary axis. Synchronous rotation of the target and reference rotary axes was achieved by developing a proportional⁻integral⁻derivative algorithm. An error model for the measuring device was established using a homogeneous transformation matrix. The influences of installation errors, manufacturing errors, and error crosstalk were studied in detail, and compensation methods for them were proposed. After compensation, the repeatability of axial and radial motion errors was significantly improved. The repeatability values of angular positioning error and of tilt motion error around the y axis and x axis were 28.0″, 2.8″, and 3.9″. The repeatability values of translational motion errors were less than 2.8 μm. The comparison experiments show that the comparison errors of angular positioning error and tilt motion error around the y axis were 2.3″ and 2.9″, respectively. These results demonstrate the effectiveness of our method and the error compensation model.

Background: Robot-assisted radical prostatectomy (RARP) has emerged as a pivotal surgical intervention for the treatment of prostate cancer (PCa). However, the complexity of clinical cases, heterogeneity of PCa, and limitations in physician expertise pose challenges to rational decision-making in RARP. To address these challenges, the authors aimed to organize the knowledge of previously complex cohorts and establish an online platform named the RARP knowledge base (RARPKB) to provide reference evidence for personalized treatment plans. Materials and methods: PubMed searches over the past two decades were conducted to identify publications describing RARP. The authors collected, classified, and structured surgical details, patient information, surgical data, and various statistical results from the literature. A knowledge-guided decision-support tool was established using MySQL, DataTable, ECharts, and JavaScript. ChatGPT-4 and two assessment scales were used to validate and compare the platform. Results: The platform comprised 583 studies, 1589 cohorts, 1 911 968 patients, and 11 986 records, resulting in 54 834 data entries. The knowledge-guided decision support tool provide personalized surgical plan recommendations and potential complications on the basis of patients' baseline and surgical information. Compared with ChatGPT-4, RARPKB outperformed in authenticity (100% vs. 73%), matching (100%vs. 53%), personalized recommendations (100% vs. 20%), matching of patients (100% vs. 0%), and personalized recommendations for complications (100% vs. 20%). Postuse, the average System Usability Scale score was 88.88 ± 15.03, and the Net Promoter Score of RARPKB was 85. The knowledge base is available at: http://rarpkb.bioinf.org.cn. Conclusions: The authors introduced the pioneering RARPKB, the first knowledge base for robot-assisted surgery, with an emphasis on PCa. RARPKB can assist in personalized and complex surgical planning for PCa to improve its efficacy. RARPKB provides a reference for the future applications of artificial intelligence in clinical practice. [ABSTRACT FROM AUTHOR]