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Abstract Artificial Intelligence (AI) techniques have made great advances in assisting antibody design. However, antibody design still heavily relies on isolating antigen-specific antibodies from serum, which is a resource-intensive and time-consuming process. To address this issue, we propose a Pre-trained Antibody generative large Language Model (PALM-H3) for the de novo generation of artificial antibodies heavy chain complementarity-determining region 3 (CDRH3) with desired antigen-binding specificity, reducing the reliance on natural antibodies. We also build a high-precision model antigen-antibody binder (A2binder) that pairs antigen epitope sequences with antibody sequences to predict binding specificity and affinity. PALM-H3-generated antibodies exhibit binding ability to SARS-CoV-2 antigens, including the emerging XBB variant, as confirmed through in-silico analysis and in-vitro assays. The in-vitro assays validate that PALM-H3-generated antibodies achieve high binding affinity and potent neutralization capability against spike proteins of SARS-CoV-2 wild-type, Alpha, Delta, and the emerging XBB variant. Meanwhile, A2binder demonstrates exceptional predictive performance on binding specificity for various epitopes and variants. Furthermore, by incorporating the attention mechanism inherent in the Roformer architecture into the PALM-H3 model, we improve its interpretability, providing crucial insights into the fundamental principles of antibody design.

Increasing the proportion of bainite and martensite phases is one of the effective ways to enhance the toughness of medium-carbon low-alloy steel(42CrMo). In this paper, the surface heat treatment of 42CrMo steel is carried out by using a laser heat source to achieve complete austenitization, then with electromagnetic induction heating for several times to implement insulation, and eventually to promote bainite phase transformation. In conjunction with the temperature history curves, OM, SEM, and EBSD are used to characterize the bainite morphology and percentage of bainite via different parameters of the hybrid process. The results demonstrate that the hybrid process combined with twice electromagnetic induction heating can yield a considerable proportion of bainite phase in 42CrMo steel. The resulting duplex structure, consisting of bainite and a minor fraction of martensite, exhibits a significant increase (81.1%) in tensile strength, while maintaining similar impact toughness. The elongation after fracture only has a slight reduction of 5.5% compared to that of the substrate. This innovative process provides a practical alternative to traditional bainite isothermal treatment method which must perform in a heat treatment furnace. Therefore, it is presented as a promising solution for enhancing the mechanical properties of medium-carbon low-alloy high strength steels.

Laser cladding is a promising surface modification and repair technology for fabricating Inconel 718 parts. However, laser cladding may produce coarse grains and brittle Laves phase, leading to a significant decrease in performance. The application of high-intensity ultrasonic vibration in laser cladding is able to refine grain and reduce Laves phase. This study investigates the distribution characteristics and the evolution mechanism of the grains and Laves phase in laser cladding with high-intensity ultrasonic vibration. The effects of high-intensity ultrasonic vibration on alteration of grain characteristics and the reduction of Laves phase were analyzed and discussed through ultrasonic vibration-assisted laser cladding experiments. Results indicate that high-intensity ultrasonic vibration promoted a columnar-to-equiaxed transition, and reduced the grain size from 75.6 μm to 48.8 μm. Furthermore, the Laves phase had a decrease of 47.1% in the volume fraction, and transformed from a long-striped shape into a fine granular shape, leading to a more homogeneous distribution of elements in Laves phase. The change in the grains and the Laves phase is attributed to dendrite fragmentation and inhibition of element segregation by nonlinear effects of ultrasound including cavitation and acoustic streaming. The findings of this study confirm the significant benefits of applying high-intensity ultrasonic vibration in laser cladding and provide insight into the underlying evolution mechanisms of high-intensity ultrasonic vibration for grains and Laves phase.

Abstract Control of exposed crystal facets in nanostructures is scientifically important, but technically challenging due to the inherent difficulty in manipulating surface energy of crystals. Here, laser‐induced periodic surface structures (LIPSS) induced by femtosecond laser is applied to produce periodic subwavelength 1D nanostructures with high index crystal facets on epitaxial CoFe2O4 surfaces, providing an efficient, maskless, cost‐effective “top‐down” method for nanostructure fabrication. Homogenous 1D LIPSSs (1D‐LIPSSs) with a period of 131 ± 15 nm and a depth of 90 ± 5 nm are obtained. The orientation of LIPSS nanostructures is finely controlled by tuning the polarization of fs laser beam, therefore flexibly producing 1D‐LIPSSs along various crystallographic orientations. Gas sensing performance evaluation shows that the fabrication of 1D‐LIPSSs on CoFe2O4 enlarges its surface area and contributes to enhanced gas sensing response. Compared to CoFe2O4 with LIPSSs faceted along {100} orientation, CoFe2O4 with LIPSSs faceted along high‐index {110} facets exhibits further improved gas sensing performance, suggesting the critical role of high‐index crystal facets in promoting surface reactivity and sensing sensitivity. The development of a laser‐based nanostructure fabrication route with high controllability of exposed crystal facets provides a novel solution for high‐density film‐based gas sensing applications.

ABSTRACTA comprehensive control methodology has been developed to address challenges such as temperature fluctuations, inconsistent depth penetration, and compositional integrity variations during laser-induction hybrid strengthening performed with consistent power parameters. This approach synergistically integrates a fuzzy controller and a decoupling compensator. In the initial part of this study, a temperature field model was utilized to investigate the effects of different process factors on temperature profiles. The analysis of step response data facilitated the development of mathematical models that delineate the correlation between the input factors and output responses. Subsequently, a decoupling compensation technique was used to reduce the coupling effects between temperature and its rate of change. A fuzzy controller was then developed to reduce the system's reliance on mathematical models, hence improving the accuracy of the control strategy. The results indicate that the application of fuzzy PI control and the implementation of decoupling compensation, the control strategy successfully improves the performance of the controller by minimizing parameter interactions. This strategy also incorporates real-time adjustment of PI parameters. Compared to conventional PI control, this method offers improved response speed and reduced overshoot. The laser-induction hybrid strengthening technique ensures superior temperature control, maintaining steady-state temperature precision within a 1% tolerance.

Element segregation and texture control are two prominent challenges for Inconel 718 repairing via laser cladding. Hence, the electromagnetic field was introduced in the laser cladding of Inconel 718 in this paper. The effect of thermal-electromagnetic convection, magnetic torque, and electromigration induced by electromagnetic field on element segregation and texture of Inconel 718 was studied. Results show element segregation is suppressed due to thermal-electromagnetic convection and electromigration. More Nb and Ti are solid-dissolved into the γ matrix. The average fraction of the Laves phase reduces from 6.44 % to 4.04 %, while the morphology of the Laves phase is modified from long-chain-like to discrete wormlike and exhibits smaller size, owing to modified element segregation. Moreover, magnetic torque drives the rod crystal to rotate with the applied electromagnetic field and thereby the long axis of the rod crystal deviates from direction. The maximum multiple of uniform density decreases from 7.54 to 2.97. This study provides a promising method to weaken texture and element segregation in laser additive manufacturing.

The effective welding of a 6 mm thick TA2 pure titanium medium-thickness plate was achieved by laser–arc hybrid welding (LAHW) with helium–argon mixed shielding gas. Conducted research on the influence of helium–argon mixed shielding gas on plasma and arc characteristics during welding, and its further impact on the microstructure, internal porosity defects, tensile properties, and corrosion resistance of welded joints was explored. The study demonstrated that under the shielding gas with 75% helium, the arc width narrowed significantly from 6.96 mm to 2.61 mm, achieving a 63% reduction, which enhanced the concentration of arc heat flux density. Achieved a well-formed weld with no surface spatter and significantly reduced the internal porosity rate from 3.02% to 0.47%, which is an 84% decrease. Tensile fractures are located in the base material, all exhibiting plastic failure. The corrosion resistance of the welded joint initially increased and then decreased with the increase of helium content in the shielding gas, peaking at 75% helium content.

Разом з режимами обробки, властивостями матеріалу деталі та порошку та інш., від якості «фокусування» газопорошкового струменя (ГПС) в зону дії лазерного випромінювання цілком та повністю залежить продуктивність, якість та економічні показники лазерного газопорошкового наплавлення (ЛГПН), швидкого виготовлення виробів по технології направленого лазерного плавлення та легування поверхні виробів. На жаль, в літературі майже не висвітлено етапи та методи проектування систем подачі ГПС в зону дії сфокусованого лазерного випромінювання, прості методи вимірювання його параметрів та контролю. Розробка методики проектування та створення систем подачі ГПС в зону дії сфокусованого лазерного випромінювання, які задіяні при реалізації процесів ЛГПН та простих методів контролю параметрів ГПС. При досягнені поставленої мети (крім евристичних) використовуються чисельні методи векторної оптики, газової динаміки та методи обробки відеозображень. Розроблені оригінальні системи для реалізації ЛГПН, що забезпечують підвищення продуктивність операції, яка виконується за рахунок зменшення масових витрат порошкового матеріалу. Встановлено, що в просторі проектування, багатоканальні системи подачі ГПС в зону дії сфокусованого лазерного випромінювання (в порівнянні з одноканальними або коаксіальними системами) забезпечують підвищення продуктивності операції, яка виконується (особливо при обробці поверхонь, які лежать під кутом до горизонту) та дозволяють подавати в зону обробки порошкові суміші різного хімічного складу.

Some disinfection by-products (DBPs) in drinking water present a potential safety concern. This study focuses on the elements influencing DBPs formation. A total of 120 water samples were collected from 10 different drinking water facilities spanning 5 counties within Huzhou, Zhejiang Province, China. Concentrations of trihalomethanes (THMs) and haloacetic acids (HAAs) were observed to be 14.5 and 27.4 μg/L, respectively, constituting 34 and 64% of the total DBPs. Seasonal fluctuations demonstrated that HAAs, THMs, halonitromethanes (HNMs), and haloacetonitriles (HANs) followed a similar pattern with higher levels in summer or autumn compared to spring. Importantly, the concentrations of HAAs and THMs were markedly higher in Taihu-sourced water compared to other sources. Geographically, Nanxun exhibited the highest levels of total DBPs, HAAs, and THMs, while Deqing and Changxing demonstrated significantly lower levels. Correlation studies between water quality parameters and DBPs revealed that factors such as chloride content, temperature, and residual chlorine positively influenced DBPs formation, whereas turbidity negatively affected it. Principal component analysis suggested similar formation processes for HANs, haloketones (HKs), HNMs, and THMs. Factors such as temperature, chemical oxygen demand (COD), and residual chlorine were identified as significant contributors to the prevalence of HAAs. HIGHLIGHTS Twenty classes of DBPs and eight kinds of water quality parameters were monitored.; The impacts of water source and season were different between DBP species.; The temperature and COD played important roles in HAAs occurrence.;

Many microRNAs (miRNAs) have been identified as being involved in diabetes; however, the question of which ones may be the most promising therapeutical targets still needs more investigation. This study aims to understand the overall development tendency and identify a specific miRNA molecule to attenuate diabetes. We developed a combined analysis method based on bibliometrics and bioinformatics to visualize research institutions, authors, cited references, and keywords to identify a promising target for diabetes. Our data showed that diabetes-related miRNA is receiving continuously increasing attention, with a large number of publications, indicating that this is still a hot topic in diabetes research. Scientists from different institutions are collaborating closely in this field. miR-21, miR-146a, miR-155, and miR-34a are frequently mentioned as high-frequency keywords in the related references. Moreover, among all the above miRNAs, bioinformatics analysis further strengthens the argument that miR-21 is the top significantly upregulated molecule in diabetes patients and plays an important role in the pathogenesis of diabetes. Our study may provide a way to identify targets and promote the clinical translation of miRNA-related therapeutical strategies for diabetes, which could also indicate present and future directions for research in this area.

Abstract The objective of our study is to develop a deep learning model based on clinicopathological data and digital pathological image of core needle biopsy specimens for predicting breast cancer lymph node metastasis. We collected 3701 patients from the Fourth Hospital of Hebei Medical University and 190 patients from four medical centers in Hebei Province. Integrating clinicopathological data and image features build multi-modal and multi-instance (MMMI) deep learning model to obtain the final prediction. For predicting with or without lymph node metastasis, the AUC was 0.770, 0.709, 0.809 based on the clinicopathological features, WSI and MMMI, respectively. For predicting four classification of lymph node status (no metastasis, isolated tumor cells (ITCs), micrometastasis, and macrometastasis), the prediction based on clinicopathological features, WSI and MMMI were compared. The AUC for no metastasis was 0.770, 0.709, 0.809, respectively; ITCs were 0.619, 0.531, 0.634, respectively; micrometastasis were 0.636, 0.617, 0.691, respectively; and macrometastasis were 0.748, 0.691, 0.758, respectively. The MMMI model achieved the highest prediction accuracy. For prediction of different molecular types of breast cancer, MMMI demonstrated a better prediction accuracy for any type of lymph node status, especially in the molecular type of triple negative breast cancer (TNBC). In the external validation sets, MMMI also showed better prediction accuracy in the four classification, with AUC of 0.725, 0.757, 0.525, and 0.708, respectively. Finally, we developed a breast cancer lymph node metastasis prediction model based on a MMMI model. Through all cases tests, the results showed that the overall prediction ability was high.

Warpage deformation inevitably occurs when laser powder bed fusion (LPBF) is applied on an overhanging structure. An effective support added to the system can mitigate warpage and improve the accuracy of formed parts. Four types of support structures are designed, and sheet tensile specimens and overhanging structures with different support structures are fabricated in this study. The tensile failure behavior and warpage suppression ability of different support structures are investigated, with the relation of the support influence to the design of support structure analyzed. The results show that the support with reinforcement can effectively restrain warpage deformation of the overhanging structure. During the process of tension, the main failure area of the support structure is located on the top of the support structure, close to the overhanging solid body. Increasing the change ratio of the support cross-sectional area is helpful to improve the constraint ability of the support. This design provides a new method for accurate forming of overhanging structures via LPBF and evaluating the restrain ability of support structures.

Li dendrites penetration through solid electrolytes (SEs) challenges the development of solid‐state Li batteries (SSLBs). To date, significant efforts are devoted to understand the mechanistic dynamics of Li dendrites nucleation, growth, and propagation in SEs, and various strategies that aim to alleviate and even inhibit Li dendrite formation have been proposed. Nevertheless, most of these conventional strategies require either additional material processing steps or new materials/layers that eventually increase battery cost and complexity. In contrast, using external fields, such as mechanical force, temperature physical field, electric field, pulse current, and even magnetic field to regulate Li dendrites penetration through SEs, seems to be one of the most cost‐effective strategies. This review focuses on the current research progress of utilizing external physical fields in regulating Li dendrites growth in SSLBs. For this purpose, the mechanical properties of Li and SEs, as well as the experimental results that visually track Li penetration dynamics, are reviewed. Finally, the review ends with remaining open questions in future studies of Li dendrites growth and penetration in SEs. It is hoped this review can shed some light on understanding the complex Li dendrite issues in SSLBs and potentially guide their rational design for further development.

Summary: Although numerous susceptibility loci are nominated for nicotine dependence (ND), no report showed any association of ARVCF with ND. Through genome-wide sequencing analysis, we first identified genetic variants associated nominally with ND and then replicated them in an independent sample. Of the six replicated variants, rs148582811 in ARVCF located in the enhancer-associated marker peak is attractive. The effective-median-based Mendelian randomization analysis indicated that ARVCF is a causal gene for ND. RNA-seq analysis detected decreased ARVCF expression in smokers compared to nonsmokers. Luciferase reporter assays indicated that rs148582811 and its located DNA fragment allele-specifically regulated ARVCF expression. Immunoprecipitation analysis revealed that transcription factor X-ray repair cross-complementing protein 5 (XRCC5) bound to the DNA fragment containing rs148582811 and allele-specifically regulated ARVCF expression at the mRNA and protein levels. With the Arvcf knockout mouse model, we showed that Arvcf deletion not only impairs hippocampus-dependent learning and memory, but also alleviated nicotine-induced memory deficits.

BackgroundsTobacco smoking is an important risk factor for coronary artery disease (CAD), but the genetic mechanisms linking smoking to CAD remain largely unknown.MethodsWe analyzed summary data from the genome-wide association study (GWAS) of the UK Biobank for CAD, plasma lipid concentrations (n = 184,305), and smoking (n = 337,030) using different biostatistical methods, which included LD score regression and Mendelian randomization (MR).ResultsWe identified SNPs shared by CAD and at least one smoking behavior, the genes where these SNPs are located were found to be significantly enriched in the processes related to lipoprotein metabolic, chylomicron-mediated lipid transport, lipid digestion, mobilization, and transport. The MR analysis revealed a positive correlation between smoking cessation and decreased risk for CAD when smoking cessation was considered as exposure (p = 0.001), and a negative correlation between the increased risk for CAD and smoking cessation when CAD was considered as exposure (p = 2.95E-08). This analysis further indicated that genetic liability for smoking cessation increased the risk of CAD.ConclusionThese findings inform the concomitant conditions of CAD and smoking and support the idea that genetic liabilities for smoking behaviors are strongly associated with the risk of CAD.

This paper analyzes the OBL strategy’s impact on optimizing the GWO algorithm and identifies three shortcomings. the specific limitations of the OBL optimization approach. To address these three shortcomings and enhance both global optimization and local exploration capabilities of GWO, this paper introduces a follow-controlled opposition learning strategy. then, the paper analyzes the control parameter C of the grey wolf algorithm to investigate its impact on global optimization and local exploration. Based on these properties, a new control parameter C is proposed. The proposed learning strategy and control parameter C are introduced into the traditional grey wolf algorithm to obtain the FCGWO algorithm. Finally, this paper conducts a comparative analysis of the FCGWO algorithm in comparison to other meta-heuristic algorithms, as well as the enhanced grey wolf algorithm, utilizing 23 benchmark test functions and 2 engineering problems. The results indicate that FCGWO effectively avoids the shortcomings of the traditional OBL, while also outperforming other algorithms significantly in terms of solution quality.

Abstract Background The research of the sensitivity and specificity point-of-care testing (POCT) of D-dimer as a diagnostic protocol for differential diagnosis of Stanford Type A aortic syndrome (hereafter as TAAS) mimicking ST-elevated myocardial infarction (STEMI) with regular STEMI in the emergency department is limited. Methods Full medical information of 32 patients confirmed TAAS and 527 patients confirmed STEMI from January 1st, 2016 to October 1st, 2021 were retrospectively analyzed in Shanghai Tenth People’s Hospital of Tongji University. Results The baseline characteristics of two groups of patients were well-balanced post propensity score matching (PSM) analysis, and each group had 32 patients enrolled. Patients in the STEMI group had higher positive cardiac troponin I (cTNI) (0.174 ng/ml vs. 0.055 ng/ml, P = 0.008) results but lower D-dimer (0.365μg/ml vs. 31.50μg/ml, P

Comprehensive annotating of cell types in spatially resolved transcriptomics to understand biological processes at the single cell level remains challenging. Here the authors introduce Spatial-ID, a supervision-based cell typing method, that combines the existing knowledge of reference single-cell RNA-seq data and the spatial information of spatially resolved transcriptomics data.

Methods that analyse heterogeneity and compare tissue microenvironments using spatial omics data are challenging to develop. Here, the authors present SOTIP, a method that can perform spatial heterogeneity, spatial domain, and differential microenvironment analyses across multiple spatial omics modalities.

Abstract Objectives Lymphangioleiomyomatosis (LAM) patients with severe lung disease may be considered for lung transplantation. Clinical, physiologic, and quality of life data are usually employed for referral. The aim of this study was to determine whether computed tomographic measurement of lung volume occupied by cysts (cyst score) complemented clinical and physiologic data in supporting referral for transplantation. Methods Forty-one patients were studied. Pre-referral clinical data, pulmonary function tests, exercise testing, and high-resolution computed tomography (HRCT) scans were obtained. From HRCT, a computer-aided diagnostic program was employed to calculate cyst scores. These data were compared to those of 41 age-matched LAM patients not referred for lung transplantation. Results Cyst score, and % predicted FEV1 and DLCO were respectively, 48.1 ± 9.4%, 36.5 ± 9.1%, and 35.0 ± 10.7%. For the control group, cyst score, FEV1, and DLCO were respectively, 14.8 ± 8.3%, 77.2 ± 20.3%, and 66.7 ± 19.3%. Cyst score values showed a normal distribution. However, the frequency distribution of FEV1 was skewed to the right while the distribution of DLCO was bimodal. Correlations between cyst score and FEV1 and DLCO for the study group were respectively, r = − 0.319 and r = − 0.421. Conclusions LAM patients referred for lung transplantation had nearly 50% of lungs occupied by cysts. Correlations between cyst score and FEV1 or DLCO were weak; as shown previously, DLCO was better related to cyst number while FEV1 had a better association with cyst size. Given its normal distribution, cyst score measurements may assist in evaluation of pre-transplant severity of lung disease before referral for transplantation.

Abstract Inhibition of pathological cardiac hypertrophy is recognized as an important therapeutic strategy for heart failure, although effective targets are still lacking in clinical practice. Homeodomain interacting protein kinase 1 (HIPK1) is a conserved serine/threonine kinase that can respond to different stress signals, however, whether and how HIPK1 regulates myocardial function is not reported. Here, it is observed that HIPK1 is increased during pathological cardiac hypertrophy. Both genetic ablation and gene therapy targeting HIPK1 are protective against pathological hypertrophy and heart failure in vivo. Hypertrophic stress‐induced HIPK1 is present in the nucleus of cardiomyocytes, while HIPK1 inhibition prevents phenylephrine‐induced cardiomyocyte hypertrophy through inhibiting cAMP‐response element binding protein (CREB) phosphorylation at Ser271 and inactivating CCAAT/enhancer‐binding protein β (C/EBPβ)‐mediated transcription of pathological response genes. Inhibition of HIPK1 and CREB forms a synergistic pathway in preventing pathological cardiac hypertrophy. In conclusion, HIPK1 inhibition may serve as a promising novel therapeutic strategy to attenuate pathological cardiac hypertrophy and heart failure.

Abstract Circulating circular RNAs (circRNAs) are emerging as novel biomarkers for cardiovascular diseases (CVDs). Machine learning can provide optimal predictions on the diagnosis of diseases. Here we performed a proof‐of‐concept study to determine if combining circRNAs with an artificial intelligence approach works in diagnosing CVD. We used acute myocardial infarction (AMI) as a model setup to prove the claim. We determined the expression level of five hypoxia‐induced circRNAs, including cZNF292, cAFF1, cDENND4C, cTHSD1, and cSRSF4, in the whole blood of coronary angiography positive AMI and negative non‐AMI patients. Based on feature selection by using lasso with 10‐fold cross validation, prediction model by logistic regression, and ROC curve analysis, we found that cZNF292 combined with clinical information (CM), including age, gender, body mass index, heart rate, and diastolic blood pressure, can predict AMI effectively. In a validation cohort, CM + cZNF292 can separate AMI and non‐AMI patients, unstable angina and AMI patients, acute coronary syndromes (ACS), and non‐ACS patients. RNA stability study demonstrated that cZNF292 was stable. Knockdown of cZNF292 in endothelial cells or cardiomyocytes showed anti‐apoptosis effects in oxygen glucose deprivation/reoxygenation. Thus, we identify circulating cZNF292 as a potential biomarker for AMI and construct a prediction model “CM + cZNF292.”

BackgroundPrevious epidemiological studies have reported controversial results on the relationship between smoking and Alzheimer’s disease (AD). Therefore, we sought to assess the association using Mendelian randomization (MR) analysis.MethodsWe used single nucleotide polymorphisms (SNPs) associated with smoking quantity (cigarettes per day, CPD) from genome-wide association studies (GWAS) of Japanese population as instrumental variables, then we performed two-sample MR analysis to investigate the association between smoking and AD in a Chinese cohort (1,000 AD cases and 500 controls) and a Japanese cohort (3,962 AD cases and 4,074 controls), respectively.ResultsGenetically higher smoking quantity showed no statistical causal association with AD risk (the inverse variance weighted (IVW) estimate in the Chinese cohort: odds ratio (OR) = 0.510, 95% confidence interval (CI) = 0.149–1.744, p = 0.284; IVW estimate in the Japanese cohort: OR = 1.170, 95% confidence interval CI = 0.790–1.734, p = 0.434).ConclusionThis MR study, for the first time in Chinese and Japanese populations, found no significant association between smoking and AD.

Electrochemical machining (ECM) has become more prevalent in titanium alloy processing. However, the presence of the passivation layer on the titanium alloys significantly impacts the performance of ECM. In an attempt to overcome the passivation effects, a high-temperature electrolyte or the addition of halogen ions to the electrolyte has been used. Still, it often results in compromised machining accuracy and surface roughness. This study applied laser and shaped tube electrolytic machining (Laser-STEM) for titanium alloy drilling, where the laser was guided to the machining zone via total internal reflection. The performance of Laser-STEM using different types of electrolytes was compared. Further, the effects of laser power and pulse voltage on the machining side gap, material removal rate (MRR), and surface roughness were experimentally studied while drilling small holes in titanium alloy. The results indicated that the use of passivating electrolytes improved the machining precision, while the MRR decreased with an increase in laser power during Laser-STEM. The MRR showed an increase while using aggressive electrolytes; however, at the same time, the machining precision deteriorated with the increase in laser power. Particularly, the maximum feeding rate of 6.0 mm/min for the tool electrode was achieved using NaCl solution as the electrolyte during Laser-STEM, marking a 100% increase compared to the rate without the use of a laser. Moreover, the model and equivalent circuits were also established to illustrate the material removal mechanisms of Laser-STEM in different electrolytes. Lastly, the processing of deep small holes with a diameter of 1.5 mm, a depth of 38 mm, and a surface roughness of Ra 2 µm was achieved via Laser-STEM without the presence of a recast layer and heat-affected zones. In addition, the cross-inner flow channels in the titanium alloys were effectively processed.

The extremely harsh environment of the high temperature plasma imposes strict requirements on the construction materials of the first wall in a fusion reactor. In this work, a refractory alloy system, WTaVTiZrx, with low activation and high entropy, was theoretically designed based on semi-empirical formula and produced using a laser cladding method. The effects of Zr proportions on the metallographic microstructure, phase composition, and alloy chemistry of a high-entropy alloy cladding layer were investigated using a metallographic microscope, XRD (X-ray diffraction), SEM (scanning electron microscope), and EDS (energy dispersive spectrometer), respectively. The high-entropy alloys have a single-phase BCC structure, and the cladding layers exhibit a typical dendritic microstructure feature. The evolution of microstructure and mechanical properties of the high-entropy alloys, with respect to annealing temperature, was studied to reveal the performance stability of the alloy at a high temperature. The microstructure of the annealed samples at 900 °C for 5–10 h did not show significant changes compared to the as-cast samples, and the microhardness increased to 988.52 HV, which was higher than that of the as-cast samples (725.08 HV). When annealed at 1100 °C for 5 h, the microstructure remained unchanged, and the microhardness increased. However, after annealing for 10 h, black substances appeared in the microstructure, and the microhardness decreased, but it was still higher than the matrix. When annealed at 1200 °C for 5–10 h, the microhardness did not increase significantly compared to the as-cast samples, and after annealing for 10 h, the microhardness was even lower than that of the as-cast samples. The phase of the high entropy alloy did not change significantly after high-temperature annealing, indicating good phase stability at high temperatures. After annealing for 10 h, the microhardness was lower than that of the as-cast samples. The phase of the high entropy alloy remained unchanged after high-temperature annealing, demonstrating good phase stability at high temperatures.

Drying is the main technical means of fruit and vegetable processing and storage; freeze drying is one of the best dehydration processes for fruit and vegetables, and the quality of the final product obtained is the highest. The process is carried out under vacuum and at low temperatures, which inhibits enzymatic activity and the growth and multiplication of micro-organisms, and better preserves the nutrient content and flavor of the product. Despite its many advantages, freeze drying consumes approximately four to ten times more energy than hot-air drying, and is more costly, so freeze drying can be assisted by means of highly efficient physical fields. This paper reviews the definition, principles and steps of freeze drying, and introduces the application mechanisms of several efficient physical fields such as ultrasonic, microwave, infrared radiation and pulsed electric fields, as well as the application of efficient physical fields in the freeze drying of fruits and vegetables. The application of high efficiency physical fields with freeze drying can improve drying kinetics, increase drying rates and maintain maximum product quality, providing benefits in terms of energy, time and cost. Efficient physical field and freeze drying technologies can be well linked to sustainable deep processing of fruit and vegetables and have a wide range of development prospects.

Abstract Background To explore whether the “WSI Stitcher”, a program we developed for reconstructing virtual large slide through whole slide imaging fragments stitching, can improve the efficiency and consistency of pathologists in evaluating the tumor bed after neoadjuvant treatment of breast cancer compared with the conventional methods through stack splicing of physical slides. Methods This study analyzed the advantages of using software-assisted methods to evaluate the tumor bed after neoadjuvant treatment of breast cancer. This new method is to use “WSI Stitcher” to stitch all the WSI fragments together to reconstruct a virtual large slide and evaluate the tumor bed with the help of the built-in ruler and tumor proportion calculation functions. Results Compared with the conventional method, the evaluation time of the software-assisted method was shortened by 35%(P

Balancing quality and productivity, especially deciding on the optimal matching strategy for multiple process parameters, is challenging in ultrashort laser processing. In this paper, an economical and new processing strategy was studied based on the laser scribing case. To reveal the temperature evolution under the combination of multiple process parameters in the laser scribing process, a two-temperature model involving a moving laser source was developed. The results indicated that the peak thermal equilibrium temperature between the electron and lattice increased with the increase in the laser fluence, and the temperature evolution at the initial position, influenced by subsequent pulses, was strongly associated with the overlap ratio. The thermal ablation effect was strongly enhanced with the increase in laser fluence. The groove morphology was controllable by selecting the overlap ratio at the same laser fluence. The removal volume per joule (i.e., energy utilization efficiency) and the removal volume per second (i.e., ablation efficiency) were introduced to analyze the ablation characteristics influenced by multiple process parameters. The law derived from statistical analysis is as follows; at the same laser fluence with the same overlap ratio, the energy utilization efficiency is insensitive to changes in the repetition rate, and the ablation efficiency increases as the repetition rate increases. As a result, a decision-making strategy for balancing quality and productivity was created.

Diamond/copper composite coating is promising for wear-resistant applications, owing to the extreme hardness of the diamond reinforcement. Ti-coated diamond/copper composite coatings with various laser powers were successfully fabricated employing the novel manufacturing technology of supersonic laser deposition (SLD). Ti-coated diamond, which was able to enhance the wettability between diamond and copper, was prepared at the optimal parameters via salt bath. Nano-spherical titanium carbides were uniformly distributed on the diamond’s surface to generate a favorable interface bonding with a copper matrix though mechanical interlocking and metallurgical bonding during impact. Furthermore, the results showed that the transition layer acted as a buffer, preventing the breakage of the diamond in the coating. SLD can prevent the graphitization of the diamonds in the coating due to its low processing temperature. The coordination of laser and diamond metallization significantly improved the tribological properties of the diamond/copper composite coatings with the SLD technique. The microhardness of the diamond/copper composite coating at a laser power of 1000 W reached about 172.58 HV0.1, which was clearly harder than that of the cold sprayed copper. The wear test illustrated that the diamond/copper composite coating at a laser power of 1000 W exhibited a low friction coefficient of 0.44 and a minimal wear rate of 11.85 μm3·N−1·mm−1. SLD technology shows great potential in the field of preparing wear-resistant hard reinforced phase composite coatings.

Abstract Programmed death ligand-1 (PD-L1) expression is a key biomarker to screen patients for PD-1/PD-L1-targeted immunotherapy. However, a subjective assessment guide on PD-L1 expression of tumor-infiltrating immune cells (IC) scoring is currently adopted in clinical practice with low concordance. Therefore, a repeatable and quantifiable PD-L1 IC scoring method of breast cancer is desirable. In this study, we propose a deep learning-based artificial intelligence-assisted (AI-assisted) model for PD-L1 IC scoring. Three rounds of ring studies (RSs) involving 31 pathologists from 10 hospitals were carried out, using the current guideline in the first two rounds (RS1, RS2) and our AI scoring model in the last round (RS3). A total of 109 PD-L1 (Ventana SP142) immunohistochemistry (IHC) stained images were assessed and the role of the AI-assisted model was evaluated. With the assistance of AI, the scoring concordance across pathologists was boosted to excellent in RS3 (0.950, 95% confidence interval (CI): 0.936–0.962) from moderate in RS1 (0.674, 95% CI: 0.614–0.735) and RS2 (0.736, 95% CI: 0.683–0.789). The 2- and 4-category scoring accuracy were improved by 4.2% (0.959, 95% CI: 0.953–0.964) and 13% (0.815, 95% CI: 0.803–0.827) (p

Summary: Background: Pathological cardiac hypertrophy occurs in response to numerous stimuli and precedes heart failure (HF). Therapies that ameliorate pathological cardiac hypertrophy are highly needed. Methods: The expression level of miR-30d was analyzed in hypertrophy models and serum of patients with chronic heart failure by qRT-PCR. Gain and loss-of-function experiments of miR-30d were performed in vitro. miR-30d gain of function were performed in vivo. Bioinformatics, western blot, luciferase assay, qRT-PCR, and immunofluorescence were performed to examine the molecular mechanisms of miR-30d. Findings: miR-30d was decreased in both murine and neonatal rat cardiomyocytes (NRCMs) models of hypertrophy. miR-30d overexpression ameliorated phenylephrine (PE) and angiotensin II (Ang II) induced hypertrophy in NRCMs, whereas the opposite phenotype was observed when miR-30d was downregulated. Consistently, the miR-30d transgenic rat was found to protect against isoproterenol (ISO)-induced pathological hypertrophy. Mechanistically, methyltransferase EZH2 could promote H3K27me3 methylation in the promotor region of miR-30d and suppress its expression during the pathological cardiac hypertrophy. miR-30d prevented pathological cardiac hypertrophy via negatively regulating its target genes MAP4K4 and GRP78 and inhibiting pro-hypertrophic nuclear factor of activated T cells (NFAT). Adeno-associated virus (AAV) serotype 9 mediated-miR-30d overexpression exhibited beneficial effects in murine hypertrophic model. Notably, miR-30d was reduced in serum of patients with chronic heart failure and miR-30d overexpression could significantly ameliorate pathological hypertrophy in human embryonic stem cell-derived cardiomyocytes. Interpretation: Overexpression of miR-30d may be a potential approach to treat pathological cardiac hypertrophy. Funding: This work was supported by the grants from National Key Research and Development Project (2018YFE0113500 to J Xiao), National Natural Science Foundation of China (82020108002 to J Xiao, 81900359 to J Li), the grant from Science and Technology Commission of Shanghai Municipality (20DZ2255400 and 21XD1421300 to J Xiao, 22010500200 to J Li), Shanghai Sailing Program (19YF1416400 to J Li), the “Dawn” Program of Shanghai Education Commission (19SG34 to J Xiao), the “Chen Guang” project supported by the Shanghai Municipal Education Commission and Shanghai Education Development Foundation (19CG45 to J Li).

ObjectiveThis study aimed to develop an artificial intelligence model for predicting the pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) of locally advanced rectal cancer (LARC) using digital pathological images.BackgroundnCRT followed by total mesorectal excision (TME) is a standard treatment strategy for patients with LARC. Predicting the PCR to nCRT of LARC remine difficulty.Methods842 LARC patients treated with standard nCRT from three medical centers were retrospectively recruited and subgrouped into the training, testing and external validation sets. Treatment response was classified as pCR and non-pCR based on the pathological diagnosis after surgery as the ground truth. The hematoxylin & eosin (H&E)-stained biopsy slides were manually annotated and used to develop a deep pathological complete response (DeepPCR) prediction model by deep learning.ResultsThe proposed DeepPCR model achieved an AUC-ROC of 0.710 (95% CI: 0.595, 0.808) in the testing cohort. Similarly, in the external validation cohort, the DeepPCR model achieved an AUC-ROC of 0.723 (95% CI: 0.591, 0.844). The sensitivity and specificity of the DeepPCR model were 72.6% and 46.9% in the testing set and 72.5% and 62.7% in the external validation cohort, respectively. Multivariate logistic regression analysis showed that the DeepPCR model was an independent predictive factor of nCRT (P=0.008 and P=0.004 for the testing set and external validation set, respectively).ConclusionsThe DeepPCR model showed high accuracy in predicting pCR and served as an independent predictive factor for pCR. The model can be used to assist in clinical treatment decision making before surgery.

We attempt to generate a definition of delayed perihematomal edema expansion (DPE) and analyze its time course, risk factors, and clinical outcomes. A multi-cohort data was derived from the Chinese Intracranial Hemorrhage Image Database (CICHID). A non-contrast computed tomography (NCCT) -based deep learning model was constructed for fully automated segmentation hematoma and perihematomal edema (PHE). Time course of hematoma and PHE evolution correlated to initial hematoma volume was volumetrically assessed. Predictive values for DPE were calculated through receiver operating characteristic curve analysis and were tested in an independent cohort. Logistic regression analysis was utilized to identify risk factors for DPE formation and poor outcomes. The test cohort’s Dice scores of lesion segmentation were 0.877 and 0.642 for hematoma and PHE, respectively. Overall, 1201 patients were enrolled for time-course analysis of ICH evolution. A total of 312 patients were further selected for DPE analysis. Time course analysis showed the growth peak of PHE approximately concentrates in 14 days after onset. The best cutoff for DPE to predict poor outcome was 3.34 mL of absolute PHE expansion from 4-7 days to 8-14 days (AUC=0.784, sensitivity=72.2%, specificity=81.2%), and 3.78 mL of absolute PHE expansion from 8-14 days to 15-21 days (AUC=0.682, sensitivity=59.3%, specificity=92.1%) in the derivation sample. Patients with DPE was associated with worse outcome (OR: 12.340, 95%CI: 6.378-23.873, P

A 2D model of laser melting consisting of heat transfer, hydrodynamic flow, surface tension, and a free surface motion was established. A physical field simulation of the laser melting process was performed, and the effect of steady magnetic field parameters on the internal flow and temperature fields of the melt pool was analyzed and validated by experiments. The results show that the steady magnetic field can suppress the melt pool flow rate, but slightly influences its temperature field, and with an increase in the magnetic field strength, the ripples on the melting surface decrease with increasing magnetic flux density. Compared with the molten pool depth experiment results, the simulation molten pool depth was 792 μm, representing a difference in value of 13.5%. The surface ripples of the molten pool fluctuated greatly in the absence of a magnetic field, while the surface ripples were suppressed when the magnetic flux density was 2T. This is consistent with the simulation results, thus effectively demonstrating the simulation model’s accuracy.

Combining the advantages of a wet chemical method and spark plasma sintering, carbide-doped materials W-1wt%TiC and W-1wt%ZrC were prepared. Microstructural evolution in W-1wt%TiC and W-1wt%ZrC under irradiation of 5 keV He+ at 600 °C to fluences up to 5.0 × 1021 ions/m2 with ion flux of about 8.8 × 1017 ions/m2s was investigated by transmission electron microscopy (TEM). The dislocation loop number density of W-1wt%TiC was higher than that of W-1wt%ZrC, but the average loop size of the W-1wt%TiC was in average smaller. There were no observable helium bubbles in W-1wt%TiC and W-1wt%ZrC, exhibiting higher radiation resistance to He+ compared to pure W. He+ pre-damaged and undamaged W-1wt%TiC and W-1wt%ZrC samples were irradiated by 5 keV D2+ to estimate the D retention in doped W materials. The irradiation damage impact of He+ on deuterium retention was examined by a method of thermal desorption spectroscopy (TDS). Compared with the undamaged samples, it was illustrated that D2 retention of W-1wt%TiC and W-1wt%ZrC increased after He+ pre-irradiation.

Objective To develop a multiwalled carbon nanotube (MSPE) method coupled with ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) by preparing a magnetic multiwall carbon nanotube composite nanoparticles modified with 3-aminobenzeneboronic acid for simultaneous determination of 9 kinds of microcystins in aquatic products. Methods Magnetic multiwall carbon nanotubes (Fe3O4/MWCNTs) composite nanoparticles were prepared by hydrothermal synthesis. Then, the 3-aminobenzeneboronic acid was modified on the prepared magnetic carbon nanotubes through the chemical oxidation method. The nanoparticles have been characterized by transmission electron microscopy and infrared spectroscopy. The main factors influencing the extraction efficiency were optimized. And then a preprocessing method with acetic acid-PBS buffer solution-methanol (2:49:49, V/V) was selected as the extraction solution, and 50 mg magnetic nanomaterials were used for extraction for 15 min, 5% ammoniated methanol was used as the eluting solvent within 10 min. Results The calibration curves of microcystins showed a good linearity in the range of 5-200 ng/mL with correlation coefficients above 0.998. The detection limits (LOD) of the method were in the range of 0.15-8.71 μg/kg. The average relative recoveries of three spiked levels ranged from 91.8% to 103.2% with the relative standard deviations of 3.1%-9.5%. Conclusion The method has the characteristics of simple pretreatment, high sensitivity and high recoveries, superior to national standard method. It could simultaneously determine 9 kinds of microcystins in aquatic products and provides a powerful technical guarantee for the monitoring of microcystins in aquatic products.

The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern and early assessment would be vital. Here, the authors show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness based on clinical characteristics at admission.

We present a novel virtual multi-probe scanning system and a new error separation method for the exact optical profile reconstruction. The system realized the multi-probe function by a single probe that fixed on a flexible hinge stage. The flexible hinge stage has a millimeter-level travel range and driven by a voice coil motor to realize the function of the multi-probe. In this work, a high accuracy profile measurement with a high lateral resolution is realized under the errors of the straightness, zero-adjustment, and yaw. The new method can obtain multiple sets of straightness error of the guideway in one scanning measurement. This novel virtual multi-probe scanning system and its corresponding method has the following benefits: (i) using a single probe to separate straightness error without reversal, and can accurately reconstruct the profile, (ii) the reconstructed profile has a very high lateral resolution, depending on the lateral resolution (μm level) of the probe, (iii) the cumulative amplification effect of zero-adjustment error can be eliminated by our method, (iv) the new method can obtain multiple sets of straightness error with higher reliability and accuracy compared with only one set. These benefits are proved by theoretical derivation and simulation. Experiments also prove that the new method can reconstruct the profile with high accuracy and lateral resolution.

Objectives: Hemorrhage expansion (HE) is a common and serious condition in patients with intracerebral hemorrhage (ICH). In contrast to the volume changes, little is known about the morphological changes that occur during HE. We developed a novel method to explore the patterns of morphological change and investigate the clinical significance of this change in ICH patients.Methods: The morphological changes in the hematomas of ICH patients with available paired non-contrast CT data were described in quantitative terms, including the diameters of each hematoma in three dimensions, the longitudinal axis type, the surface regularity (SR) index, the length and direction changes of the diameters, and the distance and direction of movement of the center of the hematoma. The patterns were explored by descriptive analysis and difference analysis in subgroups. We also established a prognostic nomogram model for poor outcomes in ICH patients using both morphological changes and clinical parameters.Results: A total of 1,094 eligible patients from four medical centers met the inclusion criteria. In 266 (24.3%) cases, the hematomas enlarged; the median absolute increase in volume was 14.0 [interquartile range (IQR), 17.9] mL. The initial hematomas tended to have a more irregular shape, reflected by a larger surface regularity index, than the developed hematomas. In subtentorial and deep supratentorial hematomas, the center moved in the direction of gravity. The distance of center movement and the length changes of the diameters were small, with median values of less than 4 mm. The most common longitudinal axis type was anterior–posterior (64.7%), and the axis type did not change between initial and repeat imaging in most patients (95.2%). A prognostic nomogram model including lateral expansion, a parameter of morphological change, showed good performance in predicting poor clinical outcomes in ICH patients.Conclusions: The present study provides a morphological perspective on HE using a novel automatic approach. We identified certain patterns of morphological change in HE, and we believe that some morphological change parameters could help physicians predict the prognosis of ICH patients.

Objective. To develop an artificial intelligence method predicting lymph node metastasis (LNM) for patients with colorectal cancer (CRC). Impact Statement. A novel interpretable multimodal AI-based method to predict LNM for CRC patients by integrating information of pathological images and serum tumor-specific biomarkers. Introduction. Preoperative diagnosis of LNM is essential in treatment planning for CRC patients. Existing radiology imaging and genomic tests approaches are either unreliable or too costly. Methods. A total of 1338 patients were recruited, where 1128 patients from one centre were included as the discovery cohort and 210 patients from other two centres were involved as the external validation cohort. We developed a Multimodal Multiple Instance Learning (MMIL) model to learn latent features from pathological images and then jointly integrated the clinical biomarker features for predicting LNM status. The heatmaps of the obtained MMIL model were generated for model interpretation. Results. The MMIL model outperformed preoperative radiology-imaging diagnosis and yielded high area under the curve (AUCs) of 0.926, 0.878, 0.809, and 0.857 for patients with stage T1, T2, T3, and T4 CRC, on the discovery cohort. On the external cohort, it obtained AUCs of 0.855, 0.832, 0.691, and 0.792, respectively (T1-T4), which indicates its prediction accuracy and potential adaptability among multiple centres. Conclusion. The MMIL model showed the potential in the early diagnosis of LNM by referring to pathological images and tumor-specific biomarkers, which is easily accessed in different institutes. We revealed the histomorphologic features determining the LNM prediction indicating the model ability to learn informative latent features.

Background: Exercise can protect myocardial infarction (MI) and downregulate cardiac Homeodomain-Interacting Protein Kinase 2 (HIPK2). However, the role of HIPK2 in MI is unclear. Methods: HIPK2–/– mice and miR-222–/– rats, HIPK2 inhibitor (PKI1H) and adeno-associated virus serotype 9 (AAV9) carrying miR-222 were applied in the study. Animals were subjected to running, swimming, acute MI or post-MI remodeling. HIPK2 inhibition and P53 activator were used in neonatal rat cardiomyocytes (NRCMs) and human embryonic stem cell-derived cardiomyocytes (hESC-CMs) subjected to oxygen glucose deprivation/reperfusion (OGD/R). Serum miR-222 levels were analyzed in healthy people and MI patients that were survival or readmitted to the hospital and/or died. Findings: Cardiac HIPK2 protein levels were reduced by exercise while increased in MI. In vitro, HIPK2 suppression by lentiviral vectors or inhibitor prevented apoptosis induced by OGD/R in NRCMs and hESC-CMs. HIPK2 inhibitor-treated mice and HIPK2–/– mice reduced infarct size after acute MI, and preserved cardiac function in MI remodeling. Mechanistically, protective effect against apoptosis by HIPK2 suppression was reversed by P53 activators. Furthermore, increasing levels of miR-222, targeting HIPK2, protected post-MI cardiac dysfunction, whereas cardiac dysfunction post-MI was aggravated in miR-222–/– rats. Moreover, serum miR-222 levels were significantly reduced in MI patients, as well as in MI patients that were readmitted to the hospital and/or died compared to those not. Interpretation: Exercise-induced HIPK2 suppression attenuates cardiomyocytes apoptosis and protects MI by decreasing P-P53. Inhibition of HIPK2 represents a potential novel therapeutic intervention for MI. Funding: This work was supported by the grants from National Key Research and Development Project (2018YFE0113500 to JJ Xiao), National Natural Science Foundation of China (82020108002, 81722008, and 81911540486 to JJ Xiao, 81400647 to MJ Xu, 81800265 to YJ Liang), Innovation Program of Shanghai Municipal Education Commission (2017-01-07-00-09-E00042 to JJ Xiao), the grant from Science and Technology Commission of Shanghai Municipality (18410722200 and 17010500100 to JJ Xiao), the “Dawn” Program of Shanghai Education Commission (19SG34 to JJ Xiao), Shanghai Sailing Program (21YF1413200 to QL Zhou). JS is supported by Horizon2020 ERC-2016-COG EVICARE (725229).

Tungsten carbide based cemented carbides, often simply termed hardmetals, are established forefront materials for tools, structural components, and wear parts with stringent requirements. Several of the technological applications in which they are used include exposure to chemically aggressive media. Under these conditions, failure induced under applied load may be accelerated; and consequently, the service life may be decreased. Within this context, this work addresses the influence of corrosion-induced damage on the mechanical integrity and load-bearing capability of hardmetals at different length scales, i.e., from 100s nanometers to 1000s microns. Experimental data acquired by means of nanoindentation, pyramidal, and spherical indentation, as well as sliding contact (micro- and nanoscratch) techniques, are presented. The attained results allow for identifying guidelines for the microstructural design of these materials under combined consideration of corrosion and mechanical contact as service-like conditions. Discussion of the reported findings includes a critical analysis of corrosion effects on the evolution of microstructure-property-performance interrelations for the materials under consideration.

Vibration in ultra-precision machining is an inherent physical phenomenon and a key factor affecting surface generation. However, the influence of the vibration characteristics of aerostatic guideways on the machining morphology has not been fully studied. In this article, a diamond micro-planing experiment was carried out on an oxygen-free copper workpiece using a homemade three-axis machine tool, and a white-light interferometer was used to measure the surface topography of the planing surface. The power spectral density of the surface topography was analyzed, and the spatial wavelength components of the surface topography were extracted. Then, the vibration characteristics of the aerostatic guideway were measured in both the space domain and the time domain. A comprehensive analysis of the main components of the workpiece surface error morphology and the vibration characteristics of the guideway shows that the time-domain vibration of the aerostatic guideway is the main factor causing the surface topography error of the workpiece.

Fine-grained classification of cervical cells into different abnormality levels is of great clinical importance but remains very challenging. Contrary to the traditional classification methods that rely on hand-crafted or engineered features, convolution neural network (CNN) can classify cervical cells based on automatically learned deep features. However, CNN in previous studies does not involve cell morphological information, and it is unknown whether morphological features can be directly modeled by CNN to classify cervical cells. This paper presents a CNN-based method that combines cell image appearance with cell morphology for classification of cervical cells in Pap smear. The training of cervical cell dataset consists of adaptively re-sampled image patches coarsely centered on the nuclei. Several CNN models (AlexNet, GoogLeNet, ResNet, and DenseNet) pre-trained on ImageNet dataset were fine-tuned on the cervical dataset for comparison. The proposed method is evaluated on the Herlev cervical dataset by five-fold cross-validation at patient-level splitting. The results show that by adding cytoplasm and nucleus masks as raw morphological information into appearance-based CNN learning, higher classification accuracies can be achieved in general. Among the four CNN models, GoogLeNet fed with both morphological and appearance information obtains the highest classification accuracies of 94.5%, 71.3%, and 64.5%, for two-class (abnormal versus normal), four-class (“The Bethesda System”), and seven-class (“World Health Organization classification system”) classification tasks, respectively. Our method demonstrates that combining cervical cell morphology with appearance information can provide improved classification performance. Although the initial results are promising, deep learning-based fine-grained cervical cell classification remains a very challenging task for a high-precision diagnosis.

Laser cladding is a promising surface modification technology to fabricate high-performance parts. However, defects such as porosity, cracks and residual tensile stress are easily produced in laser cladding, leading to significant property reduction and poor reliability. In this study, laser cladding with multidimensional high-frequency vibration was investigated. The effects of multidimensional high-frequency vibration on the improvement of microstructure and mechanical properties were analyzed and discussed based on the vibration-assisted laser cladding experiments. In addition, a numerical model was conducted to help understand the significance of the vibration on flow field and temperature field. Results show that 3D vibration led to the primary dendrite spacing reduction from 11.1 to 6.8 μm, microhardness increase from 199 to 221 HV0.2, and a nearly 110% improvement in the elongations. The findings of this study confirmed the significant benefits of multidimensional high-frequency vibration applied in laser cladding and provided a basis to uncover the underlying mechanisms of multidimensional vibration on the rapid melting and solidification.

Tobacco use is one of the leading causes of preventable disease worldwide. Genetic studies have elucidated numerous smoking-associated risk loci in American and European populations. However, genetic determinants for cigarette smoking in Chinese populations are under investigated. In this study, a whole-genome sequencing (WGS)-based genome-wide association study (GWAS) was performed in a Chinese Han population comprising 620 smokers and 564 nonsmokers. Thirteen single-nucleotide polymorphisms (SNPs) of the raftlin lipid linker 1 (RFTN1) gene achieved genome-wide significance levels (P < 5 x 10−8) for smoking initiation. The rs139753473 from RFTN1 and six other suggestively significant loci from CUB and sushi multiple domains 1 (CSMD1) gene were also associated with cigarettes per day (CPD) in an independent Chinese sample consisting of 1,329 subjects (805 smokers and 524 nonsmokers). When treating males separately, associations between smoking initiation and PCAT5/ANKRD30A, two genes involved in cancer development, were identified and replicated. Within RFTN1, two haplotypes (i.e., C-A-C-G and A-G-T-C) formed by rs796812630-rs796584733-rs796349027-rs879511366 and three haplotypes (i.e., T-T-C-C-C, T-T-A-T-T, and C-A-A-T-T) formed by rs879401109-rs879453873-rs75180423-rs541378415-rs796757175 were strongly associated with smoking initiation. In addition, we also revealed two haplotypes (i.e., C-A-G-G and T-C-T-T derived from rs4875371-rs4875372-rs17070935-rs11991366) in the CSMD1 gene showing a significant association with smoking initiation. Further bioinformatics functional assessment suggested that RFTN1 may participate in smoking behavior through modulating immune responses or interactions with the glucocorticoid receptor alpha and the androgen receptor. Together, our results may help understand the mechanisms underlying smoking behavior in the Chinese Han population.

Background: Acute myocardial infarction (AMI) is among the leading causes of death worldwide. Patients with AMI may have the risk of developing recurrent cardiovascular events leading to rehospitalization or even death. The present study aimed to investigate the prediction factors of poor prognosis (mortality and/or readmission) after AMI during a 6-month follow-up.Methods: A total of 206 consecutive patients hospitalized for the first visit with AMI were enrolled. Data collection included demographic characteristics, medical history, clinical information, laboratory results, and oral medications within 24 h of admission. At 1, 3, and 6 months after discharge, AMI patients were followed up to assess the occurrence of composite endpoint events including in-hospital and out-of-hospital death and/or readmission due to recurrent myocardial infarction (MI) or exacerbated symptoms of heart failure following MI.Results: After 6-month follow-up, a total of 197 AMI patients were available and divided in two groups according to good prognosis (n = 144) and poor prognosis (n = 53). Our data identified serum myoglobin ≥651 ng/mL, serum creatinine ≥96 μM, Killip classification 2–4, and female gender as independent predictors of 6-month mortality and/or readmission after AMI. Moreover, we demonstrated that Killip classification 2–4 combined with either myoglobin (AUCKillip class 2−4+myoglobin = 0.784, sensitivity = 69.8%, specificity = 79.9%) or creatinine (AUCKillip class 2−4+creatinine = 0.805, sensitivity = 75.5%, specificity = 77.1%) could further enhance the predictive capacity of poor 6-month prognosis among AMI patients.Conclusions: Patients with AMI ranked in the higher Killip class need to be evaluated and monitored with attention. Multibiomarker approach using Killip classification 2–4 and myoglobin or creatinine may be an effective way for 6-month prognosis prediction in AMI patients.

One of the most commonly applied methods of joining dissimilar materials is gluing. This could be mainly attributed to the applicability of this technique in various industries. The article presents a method of material surface treatment, which increases the shear strength of adhesive joints for lightweight metals such as aluminum with plastics. For this purpose, laser surface microstructuring was performed on each of the selected construction materials. As a result of the performed treatment, the active surface of the glued area was increased, which increased the adhesive strength. The picosecond laser with UV radiation used in the research is TruMicro 5325c with which material can be removed as a result of the cold ablation phenomenon. The applied parameters of the laser device did not cause thermal damage to the surface of the microstructured materials, which was confirmed by microscopic examination. Laser micromachining did not deteriorate the degree of wetting of the tested materials, either, as was confirmed by the contact angle and surface energy measurements with the use of water as the measuring liquid. In investigated cases of microstructure types, the presented method significantly increased the shear strength of the joints formed, as demonstrated by the presented strength test results. Research has shown that created joints with microstructure made according to the described method, are characterized by a significant increase in strength, up to 376%, compared to materials without microstructure. The presented results are part of a series of tests aimed at selecting the operating laser parameters for the implementation of geometric shapes of microstructures which will increase the strength of adhesive joints in selected materials.

Material properties affect the surface finishing in ultra-precision diamond cutting (UPDC), especially for aluminum alloy 6061 (Al6061) in which the cutting-induced temperature rise generates different types of precipitates on the machined surface. The precipitates generation not only changes the material properties but also induces imperfections on the generated surface, therefore increasing surface roughness for Al6061 in UPDC. To investigate precipitate effect so as to make a more precise control for the surface quality of the diamond turned Al6061, it is necessary to confirm the compositions and material properties of the precipitates. Previous studies have indicated that the major precipitate that induces scratch marks on the diamond turned Al6061 is an AlFeSi phase with the composition of Al86.1Fe8.3Si5.6. Therefore, in this paper, to study the material properties of the AlFeSi phase and its influences on ultra-precision machining of Al6061, an elastoplastic-damage model is proposed to build an elastoplastic constitutive model and a damage failure constitutive model of Al86.1Fe8.3Si5.6. By integrating finite element (FE) simulation and JMatPro, an efficient method is proposed to confirm the physical and thermophysical properties, temperature-phase transition characteristics, as well as the stress–strain curves of Al86.1Fe8.3Si5.6. Based on the developed elastoplastic-damage parameters of Al86.1Fe8.3Si5.6, FE simulations of the scratch test for Al86.1Fe8.3Si5.6 are conducted to verify the developed elastoplastic-damage model. Al86.1Fe8.3Si5.6 is prepared and scratch test experiments are carried out to compare with the simulation results, which indicated that, the simulation results agree well with those from scratch tests and the deviation of the scratch force in X-axis direction is less than 6.5%.