Evaluation of force pain thresholds to ensure collision safety in worker-robot collaborative operations

With the growing demand for robots in the industrial field, robot-related technologies with various functions have been introduced. One notable development is the implementation of robots that operate in collaboration with human workers to share tasks, without the need of any physical barriers such as safety fences. The realization of such collaborative operations in practice necessitates the assurance of safety if humans and robots collide. Thus, it is important to establish criteria for such collision scenarios to ensure robot safety and prevent injuries. Collision safety must be ensured in both pinching (quasi-static contact) and impact (transient contact) situations. To this end, we measured the force pain thresholds associated with impacts and evaluated the biomechanical limitations. This measurements were obtained through clinical trials involving physical collisions between human subjects and a device designed for generating impacts, and the force pain thresholds associated with transient collisions between humans and robots were analyzed. Specifically, the force pain threshold was measured at two different locations on the bodies of 37 adults aged 19-32 years, using two impactors with different shapes. The force pain threshold was compared with the results of other relevant studies. The results can help identify biomechanical limitations in a precise and reliable manner to ensure the safety of robots in collaborative applications.

The value of T2-weighted MRI contrast ratio combined with DWI in evaluating the pathological grade of solid lung adenocarcinoma

AIM

To assess the predictive value of T2-weighted (T2W) magnetic resonance imaging (MRI) in combination with diffusion-weighted imaging (DWI) for determining the pathological grading of solid lung adenocarcinoma.

MATERIALS AND METHODS

The clinical and imaging data from 153 cases of solid lung adenocarcinoma (82 men, 71 women, mean age 63.2 years) confirmed at histopathology in The First Affiliated Hospital of Xi'an Jiaotong University from January 2017 to May 2022 were analysed retrospectively. Adenocarcinomas were classified into low-grade (G1 and G2) and high-grade (G3) groups following the 2020 pathological grading system proposed by the International Association for the Study of Lung Cancer. The T2-weighted contrast ratio (T2CR), calculated as the T2 signal intensity of the lung mass/nodule divided by the T2 signal intensity of the right rhomboid muscle was utilised. Two experienced radiologists reviewed the MRI images independently, measured the T2CR, and obtained apparent diffusion coefficient (ADC) values. The Mann-Whitney U-test was used to compare general characteristics (sex, age, maximum diameter), T2CR, and ADC values between the low-grade and high-grade groups. The non-parametric Kruskal-Wallis test determined differences in T2CR and ADC values among the five adenocarcinoma subtypes. Receiver characteristic curve (ROC) analysis, along with area under the curve (AUC) calculation, assessed the effectiveness of each parameter in distinguishing the pathological grade of lung adenocarcinoma. A Z-test was used to compare the AUC values.

RESULTS

Among the 153 patients with adenocarcinoma, 103 had low-grade adenocarcinoma, and 50 had high-grade adenocarcinoma. The agreement between T2CR and ADC observers was good (0.948 and 0.929, respectively). None of the parameters followed a normal distribution (p<0.05). The ADC value was lower in the high-grade adenocarcinoma group compared to the low-grade adenocarcinoma group (p=0.004), while the T2CR value was higher in the high-grade group (p=0.011). Statistically significant differences were observed in maximum diameter and gender between the two groups (p<0.001 and p=0.005, respectively), while no significant differences were noted in age (p=0.980). Among the five adenocarcinoma subtypes, only the lepidic and micropapillary subtypes displayed statistical differences in ADC values (p=0.047), with the remaining subtypes showing no statistical differences (p>0.05). The AUC values for distinguishing high-grade adenocarcinoma from low-grade adenocarcinoma were 0.645 for ADC and 0.627 for T2CR. Combining T2CR, ADC, sex, and maximum diameter resulted in an AUC of 0.778, sensitivity of 70%, and specificity of 75%. This combination significantly improved diagnostic efficiency compared to T2CR and ADC alone (p=0.008, z = 2.624; p=0.007, z = 2.679).

CONCLUSION

The MRI quantitative parameters are useful for distinguishing the pathological grades of solid lung adenocarcinoma, offering valuable insights for precise lung cancer treatment.

Effects of salt stress on soil enzyme activities and rhizosphere microbial structure in salt-tolerant and -sensitive soybean

Salt is recognized as one of the most major factors that limits soybean yield in acidic soils. Soil enzyme activity and bacterial community have a critical function in improving the tolerance to soybean. Our aim was to assess the activities of soil enzyme, the structure of bacteria and their potential functions for salt resistance between Salt-tolerant (Salt-T) and -sensitive (Salt-S) soybean genotypes when subject to salt stress. Plant biomass, soil physicochemical properties, soil catalase, urease, sucrase, amylase, and acid phosphatase activities, and rhizosphere microbial characteristics were investigated in Salt-T and Salt-S soybean genotypes under salt stress with a pot experiment. Salt stress significantly decreased the soil enzyme activities and changed the rhizosphere microbial structure in a genotype-dependent manner. In addition, 46 ASVs which were enriched in the Salt-T geotype under the salt stress, such as ASV19 (Alicyclobacillus), ASV132 (Tumebacillus), ASV1760 (Mycobacterium) and ASV1357 (Bacillus), which may enhance the tolerance to soybean under salt stress. Moreover, the network structure of Salt-T soybean was simplified by salt stress, which may result in soil bacterial communities being susceptible to external factors. Salt stress altered the strength of soil enzyme activities and the assembly of microbial structure in Salt-T and Salt-S soybean genotypes. Na+, NO3--N, NH4+-N and Olsen-P were the most important driving factors in the structure of bacterial community in both genotypes. Salt-T genotypes enriched several microorganisms that contributed to enhance salt tolerance in soybeans, such as Alicyclobacillus, Tumebacillus, and Bacillus. Nevertheless, the simplified network structure of salt-T genotype due to salt stress may render its bacterial community structure unstable and susceptible.

[Expert consensus on the biobank development of oral genetic diseases and rare diseases and storage codes of related biological samples from craniofacial and oral region]

The biological samples of oral genetic diseases and rare diseases are extremely precious. Collecting and preserving these biological samples are helpful to elucidate the mechanisms and improve the level of diagnose and treatment of oral genetic diseases and rare diseases. The standardized construction of biobanks for oral genetic diseases and rare diseases is important for achieving these goals. At present, there is very little information on the construction of these biobanks, and the standards or suggestions for the classification and coding of biological samples from oral and maxillofacial sources, and this is not conducive to the standardization and information construction of biobanks for special oral diseases. This consensus summarizes the background, necessity, principles, and key points of constructing the biobank for oral genetic diseases and rare diseases. On the base of the group standard "Classification and Coding for Human Biomaterial" (GB/T 39768-2021) issued by the National Technical Committee for Standardization of Biological Samples, we suggest 76 new coding numbers for different of biological samples from oral and maxillofacial sources. We hope the consensus may promote the standardization, and smartization on the biobank construction as well as the overall research level of oral genetic diseases and rare diseases in China.

[Measurement and analysis of the crown conical degree of maxillary incisors in patients with congenital tooth agenesis caused by different gene mutations]

Objective: To measure the crown conical degree of the remaining maxillary incisors in patients with congenital tooth agenesis, and to analyze the influence of different gene mutations on the crown conical degree of patients. Methods: Whole exome sequencing was performed on 85 patients with congenital tooth agenesis (50 males, 35 females, median age 19 years old) who visited the Department of Prosthodontics, Peking University School and Hospital of Stomatology from January 2019 to January 2023. The pathogenic gene was identified. The width of the crowns of the maxillary central and lateral incisors at the incisal 1/3 and gingival 1/3 were measured on the panoramic radiograph, and the ratio was defined as the crown conical degree. The smaller the ratio is, the more likely is the crown to be peg shaped teeth. The control group was matched by age and gender with 85 other patients with intact maxillary permanent incisors who were treated in the Department of Prosthodontics, Peking University School and Hospital of Stomatology from January 2019 to January 2023. The conical degree of the tooth agenesis group was compared with the control group by t-test, and the differences in the crown conical degree in different gene mutation groups were compared using one-way analysis of variance, and the multiple comparisons among gene groups were carried out using the LSD method. Results: Among the 85 tooth agenesis patients, the numbers of patients in each gene mutation group were 20 in ectodysplasin A (EDA) group, 8 in ectodysplasin A receptor (EDAR) group, 15 in wingless-type MMTV integration site family, member 10A (WNT10A) group, 16 in paired box 9 (PAX9) group, 10 in Msh homeobox 1 (MSX1) group, 10 in low-density lipoprotein receptor related protein 6 (LRP6) group, and 6 in bone morphogenetic protein4 (BMP4) group. The number of missing teeth were 1-27, median number 15 among the tooth agenesis patients. There was no significant difference in the conical degree between the left and right homonymous teeth in the congenital tooth agenesis group and the control group (P>0.05). The crown conical degree of maxillary central incisor and lateral incisor in the congenital missing teeth group (0.95±0.24, 0.90±0.22) was significantly smaller than that in the control group (1.12±0.09, 1.13±0.09) (t=-8.50, P<0.001; t=-11.47, P<0.001). In WNT10A mutants, the conical degree of lateral incisors (0.89±0.18) was less than that of central incisors (1.07±0.15)(t=3.68, P<0.001). The conical degree of central incisors and lateral incisors (0.70±0.23, 0.57±0.15) of EDA mutants was significantly lower than that in patients with other gene mutations (P>0.05). Conclusions: Compared with the normal control group, the remaining maxillary central and lateral incisors of the seven gene mutation groups of patients with congenital tooth agenesis all had different degrees of conical crown. Among them, the crown conical degree of maxillary central and lateral incisors of the EDA mutation was the most severe, and the WNT10A mutation affected the maxillary lateral incisors more specifically.

Comparing the Salt Tolerance of Different Spring Soybean Varieties at the Germination Stage

Salinization is a global agricultural problem with many negative effects on crops, including delaying germination, inhibiting growth, and reducing crop yield and quality. This study compared the salt tolerance of 20 soybean varieties at the germination stage to identify soybean germplasm with a high salt tolerance. Germination tests were conducted in Petri dishes containing 0, 50, 100, 150, and 200 mmol L-1 NaCl. Each Petri dish contained 20 soybean seeds, and each treatment was repeated five times. The indicators of germination potential, germination rate, hypocotyl length, and radicle length were measured. The salt tolerance of 20 soybean varieties was graded, and the theoretical identification concentration was determined by cluster analysis, the membership function method, one-way analysis of variance, and quadratic equation analysis. The relative germination rate, relative germination potential, relative root length, and relative bud length of the 20 soybean germplasms decreased when the salt concentration was >50 mmol L-1, compared with that of the Ctrl. The half-lethal salt concentration of soybean was 164.50 mmol L-1, and the coefficient of variation was 18.90%. Twenty soybean varieties were divided into three salt tolerance levels following cluster analysis: Dongnong 254, Heike 123, Heike 58, Heihe 49, and Heike 68 were salt-tolerant varieties, and Xihai 2, Suinong 94, Kenfeng 16, and Heinong 84 were salt-sensitive varieties, respectively. This study identified suitable soybean varieties for planting in areas severely affected by salt and provided materials for screening and extracting parents or genes to breed salt-tolerant varieties in areas where direct planting is impossible. It assists crop breeding at the molecular level to cope with increasingly serious salt stress.

[Development and validation of prognostic nomogram for malignant pleural mesothelioma]

Objective: To development the prognostic nomogram for malignant pleural mesothelioma (MPM). Methods: Two hundred and ten patients pathologically confirmed as MPM were enrolled in this retrospective study from 2007 to 2020 in the People's Hospital of Chuxiong Yi Autonomous Prefecture, the First and Third Affiliated Hospital of Kunming Medical University, and divided into training (n=112) and test (n=98) sets according to the admission time. The observation factors included demography, symptoms, history, clinical score and stage, blood cell and biochemistry, tumor markers, pathology and treatment. The Cox proportional risk model was used to analyze the prognostic factors of 112 patients in the training set. According to the results of multivariate Cox regression analysis, the prognostic prediction nomogram was established. C-Index and calibration curve were used to evaluate the model's discrimination and consistency in raining and test sets, respectively. Patients were stratified according to the median risk score of nomogram in the training set. Log rank test was performed to compare the survival differences between the high and low risk groups in the two sets. Results: The median overall survival (OS) of 210 MPM patients was 384 days (IQR=472 days), and the 6-month, 1-year, 2-year, and 3-year survival rates were 75.7%, 52.6%, 19.7%, and 13.0%, respectively. Cox multivariate regression analysis showed that residence (HR=2.127, 95% CI: 1.154-3.920), serum albumin (HR=1.583, 95% CI: 1.017-2.464), clinical stage (stage Ⅳ: HR=3.073, 95% CI: 1.366-6.910) and the chemotherapy (HR=0.476, 95% CI: 0.292-0.777) were independent prognostic factors for MPM patients. The C-index of the nomogram established based on the results of Cox multivariate regression analysis in the training and test sets were 0.662 and 0.613, respectively. Calibration curves for both the training and test sets showed moderate consistency between the predicted and actual survival probabilities of MPM patients at 6 months, 1 year, and 2 years. The low-risk group had better outcomes than the high-risk group in both training (P=0.001) and test (P=0.003) sets. Conclusion: The survival prediction nomogram established based on routine clinical indicators of MPM patients provides a reliable tool for prognostic prediction and risk stratification.

Salt altered rhizosphere fungal community and induced soybean recruit specific species to ameliorate salt stress

Different crop genotypes showed different adaptability to salt stress, which is partly attributable to the microorganisms in the rhizosphere. Yet, knowledge about how fungal communities of different genotypes in soybean respond to salt stress is limited. Here, qPCR and ITS sequencing were used to assess the response of rhizobial fungal communities of resistant and susceptible soybean to salt stress. Moreover, we isolated two fungal species recruited by resistant soybeans for validation. The assembly of fungal community structure might be strongly linked to alterations in fungal abundance and soil physicochemical properties. Salt stress derived structural differences in fungal communities of resistant and susceptible genotypes. The salt-resistant genotype appeared to recruit some fungal taxa to the rhizosphere to help mitigating salt stress. An increase of fungal taxa with predicted saprotrophic lifestyles might help promoting plant growth by increasing nutrient availability to the plants. Compared with the susceptible genotypes, the resistant genotypes had more stronger network structure of fungi. Lastly, we verified that recruited fungi, such as Penicillium and Aspergillus, can soybean adapt to salt stress. This study provided a promising approach for rhizospheric fungal community to enhance salt tolerance of soybean from the perspective of microbiology and ecology.

Insights into the Modifying Effect of Ga on Cu-Based Catalysts for Hydrogenation of Hydroxypivalaldehyde to Neopentyl Glycol

Cu-based catalysts, modified by gallium addition via the stepwise co-precipitation method, were studied for the liquid phase hydrogenation of hydroxypivalaldehyde (HPA) to neopentyl glycol (NPG). Through physico-chemical techniques, the effects of gallium introduction on the Cu trimetallic catalyst performance and the reaction mechanism of HPA hydrogenation were discussed. The characterization results showed that gallium introduction can influence the dispersion, reduction, and distribution of active Cu species, as well as their reactivity. Herein, the catalyst with 2 wt% gallium addition exhibited excellent catalytic performance with HPA conversion rate and NPG selectivity of 93.5% and 95.5%, at a reaction pressure of 3 MPa, temperature of 110 °C, hydrogen-aldehyde ratio (molar ratio) 10:1, and liquid space-time at a speed of 8.4 h−1. The good performance could be attributed to gallium doping tending to dynamically tune the interaction between the components, increasing Cu dispersion and the distributions of Cu+ and Cu0 species on the catalyst surfaces.

Detection of type III effector-induced transcription factors that regulate phytohormone content during symbiosis establishment in soybean

Soybean is a pivotal protein and oil crop that utilizes atmospheric nitrogen via symbiosis with rhizobium soil bacteria. Rhizobial type III effectors (T3Es) are essential regulators during symbiosis establishment. However, how the transcription factors involved in the interaction between phytohormone synthesis and type III effectors are connected is unclear. To detect the responses of phytohormone and transcription factor genes to rhizobial type III effector NopAA and type III secretion system, the candidate genes underlying soybean symbiosis were identified using RNA sequencing (RNA-seq) and phytohormone content analysis of soybean roots infected with wild-type Rhizobium and its derived T3E mutant. Via RNA-seq analysis the WRKY and ERF transcription factor families were identified as the most differentially expressed factors in the T3E mutant compared with the wild-type. Next, qRT-PCR was used to confirm the candidate genes Glyma.09g282900, Glyma.08g018300, Glyma.18g238200, Glyma.03g116300, Glyma.07g246600, Glyma.16g172400 induced by S. fredii HH103, S. fredii HH103ΩNopAA, and S. fredii HH103ΩRhcN. Since the WRKY and ERF families may regulate abscisic acid (ABA) content and underlying nodule formation, we performed phytohormone content analysis at 0.5 and 24 h post-inoculation (hpi). A significant change in ABA content was found between wild Rhizobium and type III effector mutant. Our results support that NopAA can promote the establishment of symbiosis by affecting the ABA signaling pathways by regulating WRKY and ERF which regulate the phytohormone signaling pathway. Specifically, our work provides insights into a signaling interaction of prokaryotic effector-induced phytohormone response involved in host signaling that regulates the establishment of symbiosis and increases nitrogen utilization efficiency in soybean plants.

A Video Target Tracking and Correction Model with Blockchain and Robust Feature Location

In this paper, a cutting-edge video target tracking system is proposed, combining feature location and blockchain technology. The location method makes full use of feature registration and received trajectory correction signals to achieve high accuracy in tracking targets. The system leverages the power of blockchain technology to address the challenge of insufficient accuracy in tracking occluded targets, by organizing the video target tracking tasks in a secure and decentralized manner. To further enhance the accuracy of small target tracking, the system uses adaptive clustering to guide the target location process across different nodes. In addition, the paper also presents an unmentioned trajectory optimization post-processing approach, which is based on result stabilization, effectively reducing inter-frame jitter. This post-processing step plays a crucial role in maintaining a smooth and stable track of the target, even in challenging scenarios such as fast movements or significant occlusions. Experimental results on CarChase2 (TLP) and basketball stand advertisements (BSA) datasets show that the proposed feature location method is better than the existing methods, achieving a recall of 51% (27.96+) and a precision of 66.5% (40.04+) in the CarChase2 dataset and recall of 85.52 (11.75+)% and precision of 47.48 (39.2+)% in the BSA dataset. Moreover, the proposed video target tracking and correction model performs better than the existing tracking model, showing a recall of 97.1% and a precision of 92.6% in the CarChase2 dataset and an average recall of 75.9% and mAP of 82.87% in the BSA dataset, respectively. The proposed system presents a comprehensive solution for video target tracking, offering high accuracy, robustness, and stability. The combination of robust feature location, blockchain technology, and trajectory optimization post-processing makes it a promising approach for a wide range of video analytics applications, such as surveillance, autonomous driving, and sports analysis.

An effective spatial relational reasoning networks for visual question answering

Visual Question Answering (VQA) is a method of answering questions in natural language based on the content of images and has been widely concerned by researchers. The existing research on the visual question answering model mainly focuses on the point of view of attention mechanism and multi-modal fusion. It only pays attention to the visual semantic features of the image in the process of image modeling, ignoring the importance of modeling the spatial relationship of visual objects. We are aiming at the existing problems of the existing VQA model research. An effective spatial relationship reasoning network model is proposed, which can combine visual object semantic reasoning and spatial relationship reasoning at the same time to realize fine-grained multi-modal reasoning and fusion. A sparse attention encoder is designed to capture contextual information effectively in the semantic reasoning module. In the spatial relationship reasoning module, the graph neural network attention mechanism is used to model the spatial relationship of visual objects, which can correctly answer complex spatial relationship reasoning questions. Finally, a practical compact self-attention (CSA) mechanism is designed to reduce the redundancy of self-attention in linear transformation and the number of model parameters and effectively improve the model's overall performance. Quantitative and qualitative experiments are conducted on the benchmark datasets of VQA 2.0 and GQA. The experimental results demonstrate that the proposed method performs favorably against the state-of-the-art approaches. Our best single model has an overall accuracy of 71.18% on the VQA 2.0 dataset and 57.59% on the GQA dataset.

[Sero-epidemiological characteristics of the hepatitis D virus infection among hepatitis B virus infected-patients at a single center in Xinjiang region]

Objective: To investigate the sero-epidemiological characteristics of the hepatitis D virus (HDV) infection among hepatitis B virus (HBV)-infected patients in Xinjiang region. Methods: A single-center cross-sectional analysis method was used to select 264 cases of hepatitis B virus infection who were hospitalized in the Center for Infectious Diseases and Liver Diseases of the First Affiliated Hospital of Xinjiang Medical University from August 2021 to January 2022. All patients were tested for HDV Ag, HDV IgM, HDV IgG, and HDV RNA. The infection status of hepatitis D virus was analyzed by grouping according to their clinical type, HBV viral load, and HBsAg level. A paired t-test was used for data with measurement data conforming to normal distribution. A paired rank sum test was used for data that did not conform to normal distribution before and after treatment. Results: A total of 36 cases (13.64%) and 26 cases (9.85%) were positive for HDV serological markers and HDV RNA. According to clinical type grouping, the positive rates of HDV serum markers in patients with chronic hepatitis B, hepatitis B-related cirrhosis, liver cancer, and liver failure were 13.46%, 12.43%, and 20.83%, respectively, and there was no statistically significant difference among the three groups (χ²=0.86, P=0.649). The positive rates of HDV RNA were 11.54%, 8.11%, and 20.83%, respectively, and there was no statistically significant difference among the three groups (χ²=4.015, P=0.134). According to HBV viral load grouping, the positive rates of HDV serum markers among patients with viral loads <20, 20-2 000, and >2 000 IU/ml were 17.15%, 7.81%, and 6.67%, respectively, and the difference was not statistically significant among the three groups (χ²=4.846, P=0.089). The positive rates of HDV RNA were 9.47%, 10.94%, and 10%, respectively, and the difference was not statistically significant among the three groups (χ²=0.113, P=0.945). According to HBsAg level grouping, the positive rates of HDV serum markers in HBsAg<0.05, 0.05~250, and >250 IU/ml were 14.29%, 16.67%, and 10.85%, respectively, and there was no statistically significance between the three groups (χ²=1.745, P=0.418). The positive rates of HDV RNA were 4.76%, 8.77%, and 11.63%, respectively, and there was no statistically significant difference among the three groups (χ²=1.221, P=0.543). Clinical outcome, disease course, HBV DNA, serological markers of viral hepatitis, routine blood test, biochemical indicators, coagulation function, and other laboratory indicators were compared between HDV serum marker and/or nucleic acid positive and negative patients, and there was no statistically significant difference (P>0.05). Conclusion: The positive rate of HDV serological markers and HDV RNA is 13.64% and 9.85%, respectively, at a single center in the Xinjiang region, and there is still a high HDV infection rate among the HBV-infected patients with low levels of viral load and HBsAg.

Genome-Wide Identification of Candidate Genes Underlying Soluble Sugar Content in Vegetable Soybean (Glycine max L.) via Association and Expression Analysis

Soluble sugar is a major indicator of the intrinsic quality of vegetable soybean [Glycine max (L.) Merr. ]. The improvement of soluble sugar content in soybean is very important due to its healthcare functions for humans. The genetic mechanism of soluble sugar in soybean is unclear. In this study, 278 diverse soybean accessions were utilized to identify the quantitative trait nucleotides (QTNs) for total soluble sugar content in soybean seeds based on a genome-wide association study (GWAS). A total of 25,921 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) ≥ 5% and missing data ≤ 10% were selected for GWAS. Totally, thirteen QTNs associated with total soluble sugar content were identified, which were distributed on ten chromosomes. One hundred and fifteen genes near the 200-kb flanking region of these identified QTNs were considered candidate genes associated with total soluble sugar content in soybean seed. Gene-based association analysis and haplotype analysis were utilized to further identify the effect of candidate genes on total soluble sugar content. Totally, 84 SNPs from seventeen genes across four chromosomes were significantly associated with the total soluble sugar content. Among them, three SNPs from Glyma.02G292900 were identified at two locations, and other eighty-one SNPs from sixteen genes were detected at three locations. Furthermore, expression level analysis of candidate genes revealed that Glyma.02G293200 and Glyma.02G294900 were significantly positively associated with soluble sugar content and Glyma.02G294000 was significantly negatively associated with soluble sugar content. Six genes (i.e., Glyma.02G292600, Glyma.02G292700, Glyma.02G294000, Glyma.02G294300, Glyma.02G294400, and Glyma.15G264200) identified by GWAS were also detected by the analysis of differential expression genes based on soybean germplasms with higher and lower soluble sugar content. Among them, Glyma.02G294000 is the only gene that was identified by gene-based association analysis with total soluble sugar content and was considered an important candidate gene for soluble sugar content. These candidate genes and beneficial alleles would be useful for improving the soluble sugar content of soybean.

MRI-based radiomics analysis in differentiating solid non-small-cell from small-cell lung carcinoma: a pilot study

AIM

To investigate the ability of a T2-weighted (W) magnetic resonance imaging (MRI)-based radiomics signature to differentiate solid non-small-cell lung carcinoma (NSCLC) from small-cell lung carcinoma (SCLC).

MATERIALS AND METHODS

The present retrospective study enrolled 152 eligible patients (NSCLC = 125, SCLC = 27). All patients underwent MRI using a 3 T scanner and radiomics features were extracted from T2W MRI. The least absolute shrinkage and selection operator (LASSO) logistic regression model was used to identify the optimal radiomics features for the construction of a radiomics model to differentiate solid NSCLC from SCLC. Threefold cross validation repeated 10 times was used for model training and evaluation. The conventional MRI morphology features of the lesions were also evaluated. The performance of the conventional MRI morphological features, and the radiomics signature model and nomogram model (combining radiomics signature with conventional MRI morphological features) was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Five optimal features were chosen to build a radiomics signature. There was no significant difference in age, gender, and the largest diameter. The radiomics signature and conventional MRI morphological features (only pleural indentation and lymph node enlargement) were independent predictive factors for differentiating solid NSCLC from SCLC. The area under the ROC curves (AUCs) for MRI morphological features, and the radiomics model, and nomogram model was 0.69, 0.85, and 0.90 (ROC), respectively.

CONCLUSIONS

The T2W MRI-based radiomics signature is a potential non-invasive approach for distinguishing solid NSCLC from SCLC.

Pre-training Model Based on Parallel Cross-Modality Fusion Layer

Visual Question Answering (VQA) is a learning task that combines computer vision with natural language processing. In VQA, it is important to understand the alignment between visual concepts and linguistic semantics. In this paper, we proposed a Pre-training Model Based on Parallel Cross-Modality Fusion Layer (P-PCFL) to learn the fine-grained relationship between vision and language. The P-PCFL model is composed of three Encoders: Object Encoder, Language Encoder, and Parallel Cross-Modality Fusion Encoder, with Transformer as the core. We use four different Pre-training missions, namely, Cross-Modality Mask Language Modeling, Cross-Modality Mask Region Modeling, Image-Text Matching, and Image-Text Q&A, to pre-train the P-PCFL model and improve its reasoning and universality, which help to learn the relationship between Intra-modality and Inter-modality. Experimental results on the platform of Visual Question Answering dataset VQA v2.0 show that the Pre-trained P-PCFL model has a good effect after fine-tuning the parameters. In addition, we also conduct ablation experiments and provide some results of Attention visualization to verify the effectiveness of P-PCFL model.

Tuning product selectivity in the MTO reaction over Zn-modified SSZ-13 catalysts

In this work, Zn-modified SSZ-13 catalysts with different spatial distributions of zinc species were prepared by ion exchange (IE), wet impregnation (WI) and in situ synthesis (IS) methods employed for the methanol-to-olefin (MTO) reaction.

Clinical outcomes of keratinized mucosa augmentation in jaws reconstructed with fibula or iliac bone flaps

This prospective study was undertaken to evaluate the treatment outcomes of keratinized mucosa augmentation (KMA) on the buccal and palatal/lingual sides of implants in jaws reconstructed after oncological surgery. Forty-two implants in 12 patients whose jaws had been reconstructed with a fibula or iliac bone flap were included. KMA was performed at 3 months after implant placement; this included an apically displaced partial-thickness flap and a free gingival graft (FGG) around the implants to increase the keratinized mucosa width (KMW). Patients were followed up for at least 6 months post-surgery. KMW, shrinkage, and patient pain and discomfort measured on a visual analogue scale were analysed. A histological analysis was performed of tissue epithelium from two patients. The results showed that KMW was >2 mm on both the buccal and palatal/lingual sides during follow-up. Before surgery, histological analysis showed epithelium with no epithelial spikes; normal keratinized epithelial spikes were observed at 8 weeks after KMA. Greater KMW was observed around implants in reconstructed maxillae than around those in reconstructed mandibles (P < 0.001). Patients felt more pain at the donor site than at the recipient site during the first 3 days post-surgery. KMA with FGG was predictable in reconstructed jaws and may help maintain the long-term stability of implants.

LINC00174 triggers the malignant development of breast cancer by negatively regulating miR-1827 level

OBJECTIVE

Long non-coding RNAs (lncRNAs) are extensively involved in tumor development. In-depth researches on cancer-associated lncRNAs provide a theoretical basis for developing prognostic hallmarks and individualized therapeutic targets in breast cancer (BCa). This study aims to detect expression characteristics of LINC00174 in BCa and its biological role in regulating BCa cell phenotypes.

PATIENTS AND METHODS

LINC00174 levels in BCa and adjacent normal tissues were detected by quantitative real-time polymerase chain reaction (qRT-PCR). The influence of LINC00174 on pathological indicators of BCa was analyzed. In MCF-7 and MDA-MB-231 cells with LINC00174 knockdown, proliferative and migratory abilities were examined by cell counting kit-8 (CCK-8), colony formation and transwell assay, respectively. At last, molecular mechanisms of LINC00174 and its downstream gene miR-1827 in regulating BCa development were explored by Luciferase assay and rescue experiments.

RESULTS

LINC00174 was upregulated in BCa tissues than adjacent normal ones. High level of LINC00174 predicted advanced tumor staging, high metastasis rate and poor prognosis in BCa. Knockdown of LINC00174 attenuated proliferative and migratory abilities in BCa cells. MiR-1827 was the target gene binding LINC00174, showing a negative correlation between each other. Silence of miR-1827 abolished the regulatory effects of LINC00174 on proliferative and migratory abilities in BCa cells.

CONCLUSIONS

LINC00174 is upregulated in BCa samples. It is closely linked to tumor staging, metastasis and prognosis in BCa. By negatively regulating miR-1827 level, LINC00174 aggravates the malignant development of BCa.

Machine learning from quantitative coronary computed tomography angiography predicts ischemia and impaired myocardial blood flow

Background

Atherosclerotic plaque characteristics influence the hemodynamic consequences of coronary lesions. This study sought to assess the performance of a machine learning (ML) score integrating coronary computed tomography angiography (CCTA)-based quantitative plaque features for the prediction of ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by [15O]H2O positron emission tomography (PET).

Methods

This post-hoc analysis of the PACIFIC (Prospective Comparison of Cardiac PET/CT, SPECT/CT Perfusion Imaging and CT Coronary Angiography With Invasive Coronary Angiography) trial included 208 patients with suspected coronary artery disease who underwent CCTA, [15O]H2O PET, and 3-vessel invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. A boosted ensemble ML algorithm (XGBoost) trained on data from the NXT (Analysis of Coronary Blood Flow using CT Angiography: Next Steps) trial was used to develop a ML score for the prediction of per-vessel ischemia (invasive FFR ≤0.80). The performance of the ML score was evaluated in 551 vessels from the PACIFIC trial for external validation. Thereafter, we assessed the discriminative ability of the ML score for per-vessel impaired hyperemic MBF (≤2.30 mL/min/g).

Results

In total, 138 (25.0%) vessels had ischemia and 195 (35.4%) vessels had impaired hyperemic MBF. CCTA-derived quantitative percent diameter stenosis and low-density noncalcified plaque (LDNCP) volume were higher in ischemic vessels compared with non-ischemic vessels (60.8% vs. 19.9%; and 42.3 mm3 vs. 9.1 mm3; both p&lt;0.001). The ML score demonstrated a significantly higher area under the receiver-operating characteristic curve (AUC) for predicting ischemia (0.92, 95% confidence interval [CI] 0.89–0.94) compared with visual stenosis grade (0.84, 95% CI 0.80–0.87; p&lt;0.001). Overall, quantitative percent diameter stenosis and LDNCP volume had greatest feature importance for ML, followed by percent area stenosis, minimum luminal diameter, and contrast density drop (Figure 1). An individualized explanation of ML ischemia prediction is shown in Figure 2. When applied for impaired MBF discrimination, the ML score exhibited an AUC of 0.82 (95% CI 0.78–0.85) and was superior to visual stenosis grade (AUC 0.76, 95% CI 0.72–0.80; p=0.03).

Conclusions

An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and abnormal MBF by PET, outperforming standard visual CCTA interpretation.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute, United States Performance of the ML scoreIndividual explanation of ML prediction

[Trajectories of body mass index Z-score and risk of high blood pressure in late adolescence in Suzhou children]

Objective: To identify age and gender standardized body mass index among children and adolescents and explore their associations with high blood pressure (HBP) in late adolescence. Methods: The current study was based on the Health Promotion Program for Children and Adolescents, school-based surveillance successively conducted from 2012 to 2019 in Suzhou, China. A total of 11 812 children and adolescents aged 16-18 years, who had ≥4 examination records during 2012-2018 and were also involved in a surveillance program in 2019, were included. Latent class growth mixture modeling was used to identify the BMI-Z trajectories in different genders, and multivariate logistic regression was used to analyze the associations between different BMI-Z trajectories and risk of HBP in late adolescence. Results: Six distinct BMI-Z trajectories were determined for both genders:thin, slightly thin,standard, declining, overweight, and obese. Compared with the regular group, the obesity group had 94.0% (OR=1.94, 95%CI: 1.43-2.63) and 107.0% (OR=2.07, 95%CI: 1.33-3.22) increased risk of developing HBP in late adolescence in boys and girls, respectively. However, a neutral association was found between the descending group and HBP in late adolescence. Conclusions: Persistent obesity in children may increase the risk of HBP in their late adolescence. If an obese child restores normal weight before late adolescence, the risk of HBP may reduce.

Effect of radiomics from different virtual monochromatic images in dual-energy spectral CT on the WHO/ISUP classification of clear cell renal cell carcinoma

AIM

To investigate the effect of radiomics obtained from different virtual monochromatic images (VMIs) in dual-energy spectral computed tomography (CT) on the World Health Organization/International Association for Urological Pathology (WHO/ISUP) classification of clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

A retrospective study of 99 ccRCC patients who underwent contrast-enhanced dual-energy CT was undertaken. ccRCC was confirmed at surgery or biopsy and graded according to the WHO/ISUP pathological grading criteria as low grade (n=68, grade I and II) or high grade (n=31, grade III and IV). Radiomics risk scores (RRSs) for differentiating high and low grades of ccRCC were constructed from 11 sets of VMI in (40-140 keV, 10 keV interval) the cortical phase. Receiver operating characteristic (ROC) curves were drawn and the area under the curves (AUCs) was calculated to evaluate the discriminatory power of RRS for each VMI. The Hosmer-Lemeshow test was used to evaluate the goodness-of-fit of each model and the decision curve was used to analyse its net benefit to patients.

RESULTS

The AUC values for distinguishing low-from high-grade ccRCC with RRS of 40-140 keV VMIs were all >0.920. The Hosmer-Lemeshow test showed that the p-values of RRS of VMIs were >0.05, suggesting good fits. In the decision curve analysis, RRS from the 40-140 keV VMIs had similar decision curves and provided better net benefits than considering all patients either as high-grade or low-grade.

CONCLUSIONS

The RRS obtained from multiple VMIs in dual-energy spectral CT have high diagnostic efficiencies for distinguishing between low- and high-grade ccRCC with no significant differences between different VMIs.

[Research progress in studies on tooth development based on diphyodont mammals]

For decades, the molecular and cellular mechanisms that govern tooth development have been extensively investigated. However, most of the studies are based on mice, whose teeth are quite different from human teeth in morphological and developmental aspects. Mice are not the ideal model for understanding the development of permanent teeth as they have only one set of dentition. Thus, using of diphyodont mammals is a better model to study the deciduous and permanent tooth development and to understand the process of tooth replacement. Several diphyodont mammal models have been established including minipig, ferret, house shrew and rabbit. Studies based on the diphyodont mammals have characterized the morphological changes involved in tooth replacement and molecular mechanisms of tooth replacement. However, few developmental stages were studied on ferret due to the presence of seasonal estrus and the difficulty to obtain ferret embryos at the correct stage. The house shrew is limited as a model because their deciduous tooth germs become vestigial in the embryonic period. The main disadvantage of the rabbit is an incomplete dentition with the lack of canines. Compared to the above mentioned animal models, the miniature pig has proven to be a valuable animal model for diphyodont development due to its dentition similarities, including the morphology, number and size of teeth, to human's, and particularly its heterodont dentition consisting of incisors, canines, premolars and molars. The present article reviews the current knowledge on the development of the primary and successional teeth in minipig modle and briefly summarizes the studies based on other diphyodont mammal models.