Sintilimab plus bevacizumab and CapeOx (BBCAPX) on first-line treatment in patients with RAS mutant, microsatellite stable, metastatic colorectal cancer: study protocol of a randomized, open-label, multicentric study.

BACKGROUND: Rat sarcoma viral oncogene homolog (RAS) gene mutation is a common molecular event in colorectal cancer (CRC). The prognosis of mCRC (metastatic colorectal cancer) patients with RAS mutation is poor and capecitabine and oxaliplatin (CapeOx) plus bevacizumab has shown to be one of the standard therapeutic regimens as first line for these patients with objective response rate (ORR) of ~ 50% and median progression-free survival (mPFS) of 8-9 months. Immunotherapy, especially anti-programmed death 1 (PD-1) monoclonal antibody has demonstrated ground-breaking results in deficient mismatch repair (dMMR) / microsatellite instability-high (MSI-H) mCRC patients. However, the response rate of in microsatellite stable (MSS) patients is extremely low. In addition, preclinical studies have demonstrated that anti-Vascular endothelial growth factor (VEGF) agents, such as bevacizumab, can induce tumor vascular normalization and enhance antitumor immunity. Previous study indicated the combination of chemotherapy, anti-VEGF agents (bevacizumab) with immune checkpoint inhibitors may have promising clinical activity in RAS mutant, MSS refractory mCRC patients. Based on these evidences, we will explore the combination of CapeOx with bevacizumab and sintilimab (anti-PD-1 monoclonal antibody) in RAS mutant, MSS mCRC patients as first-line therapy. METHODS: This is a randomized, open-label, multicentric clinical trial. In the sintilimab arm, patients will receive sintilimab in combination with CapeOx and bevacizumab. In the control arm, patients will receive CapeOx and bevacizumab. This trial will recruit 494 patients from 20 centers and randomly (1:1) disseminated into two groups. The primary endpoint is the PFS. The secondary endpoints include overall survival, safety, ORR, and disease control rate. DISCUSSION: This study may provide new ideas for optimizing oncology treatment planning for RAS mutant, MSS mCRC patients in the first-line set. TRIAL REGISTRATION: This study is short for BBCAPX and has been registered at clinicaltrials.gov registry with identifier NCT05171660.

A novel approach to quantify calcifications of thyroid nodules in US images based on deep learning: predicting the risk of cervical lymph node metastasis in papillary thyroid cancer patients.

OBJECTIVE: Based on ultrasound (US) images, this study aimed to detect and quantify calcifications of thyroid nodules, which are regarded as one of the most important features in US diagnosis of thyroid cancer, and to further investigate the value of US calcifications in predicting the risk of lymph node metastasis (LNM) in papillary thyroid cancer (PTC). METHODS: Based on the DeepLabv3+ networks, 2992 thyroid nodules in US images were used to train a model to detect thyroid nodules, of which 998 were used to train a model to detect and quantify calcifications. A total of 225 and 146 thyroid nodules obtained from two centers, respectively, were used to test the performance of these models. A logistic regression method was used to construct the predictive models for LNM in PTCs. RESULTS: Calcifications detected by the network model and experienced radiologists had an agreement degree of above 90%. The novel quantitative parameters of US calcification defined in this study showed a significant difference between PTC patients with and without cervical LNM (p < 0.05). The calcification parameters were beneficial to predicting the LNM risk in PTC patients. The LNM prediction model using these calcification parameters combined with patient age and other US nodular features showed a higher specificity and accuracy than the calcification parameters alone. CONCLUSIONS: Our models not only detect the calcifications automatically, but also have value in predicting cervical LNM risk of PTC patients, thereby making it possible to investigate the relationship between calcifications and highly invasive PTC in detail. CLINICAL RELEVANCE STATEMENT: Due to the high association of US microcalcifications with thyroid cancers, our model will contribute to the differential diagnosis of thyroid nodules in daily practice. KEY POINTS: • We developed an ML-based network model for automatically detecting and quantifying calcifications within thyroid nodules in US images. • Three novel parameters for quantifying US calcifications were defined and verified. • These US calcification parameters showed value in predicting the risk of cervical LNM in PTC patients.

MS-Net: Learning to assess the malignant status of a lung nodule by a radiologist and her peers.

BACKGROUND: Automatically assessing the malignant status of lung nodules based on CTscan images can help reduce the workload of radiologists while improving their diagnostic accuracy. PURPOSE: Despite remarkable progress in the automatic diagnosis of pulmonary nodules by deep learning technologies, two significant problems remain outstanding. First, end-to-end deep learning solutions tend to neglect the empirical (semantic) features accumulated by radiologists and only rely on automatic features discovered by neural networks to provide the final diagnostic results, leading to questionable reliability, and interpretability. Second, inconsistent diagnosis between radiologists, a widely acknowledged phenomenon in clinical settings, is rarely examined and quantitatively explored by existing machine learning approaches. This paper solves these problems. METHODS: We propose a novel deep neural network called MS-Net, which comprises two sequential modules: A feature derivation and initial diagnosis module (FDID), followed by a diagnosis refinement module (DR). Specifically, to take advantage of accumulated empirical features and discovered automatic features, the FDID model of MS-Net first derives a range of perceptible features and provides two initial diagnoses for lung nodules; then, these results are fed to the subsequent DR module to refine the diagnoses further. In addition, to fully consider the individual and panel diagnosis opinions, we propose a new loss function called collaborative loss, which can collaboratively optimize the individual and her peers' opinions to provide a more accurate diagnosis. RESULTS: We evaluate the performance of the proposed MS-Net on the Lung Image Database Consortium image collection (LIDC-IDRI). It achieves 92.4% of accuracy, 92.9% of sensitivity, and 92.0% of specificity when panel labels are the ground truth, which is superior to other state-of-the-art diagnosis models. As a byproduct, the MS-Net can automatically derive a range of semantic features of lung nodules, increasing the interpretability of the final diagnoses. CONCLUSIONS: The proposed MS-Net can provide an automatic and accurate diagnosis of lung nodules, meeting the need for a reliable computer-aided diagnosis system in clinical practice.

The Evolution and Disparities of Online Attitudes Toward COVID-19 Vaccines: Year-long Longitudinal and Cross-sectional Study.

BACKGROUND: Due to the urgency caused by the COVID-19 pandemic worldwide, vaccine manufacturers have to shorten and parallel the development steps to accelerate COVID-19 vaccine production. Although all usual safety and efficacy monitoring mechanisms remain in place, varied attitudes toward the new vaccines have arisen among different population groups. OBJECTIVE: This study aimed to discern the evolution and disparities of attitudes toward COVID-19 vaccines among various population groups through the study of large-scale tweets spanning over a whole year. METHODS: We collected over 1.4 billion tweets from June 2020 to July 2021, which cover some critical phases concerning the development and inoculation of COVID-19 vaccines worldwide. We first developed a data mining model that incorporates a series of deep learning algorithms for inferring a range of individual characteristics, both in reality and in cyberspace, as well as sentiments and emotions expressed in tweets. We further conducted an observational study, including an overall analysis, a longitudinal study, and a cross-sectional study, to collectively explore the attitudes of major population groups. RESULTS: Our study derived 3 main findings. First, the whole population's attentiveness toward vaccines was strongly correlated (Pearson r=0.9512) with official COVID-19 statistics, including confirmed cases and deaths. Such attentiveness was also noticeably influenced by major vaccine-related events. Second, after the beginning of large-scale vaccine inoculation, the sentiments of all population groups stabilized, followed by a considerably pessimistic trend after June 2021. Third, attitude disparities toward vaccines existed among population groups defined by 8 different demographic characteristics. By crossing the 2 dimensions of attitude, we found that among population groups carrying low sentiments, some had high attentiveness ratios, such as males and individuals aged ≥40 years, while some had low attentiveness ratios, such as individuals aged ≤18 years, those with occupations of the 3rd category, those with account age <5 years, and those with follower number <500. These findings can be used as a guide in deciding who should be given more attention and what kinds of help to give to alleviate the concerns about vaccines. CONCLUSIONS: This study tracked the year-long evolution of attitudes toward COVID-19 vaccines among various population groups defined by 8 demographic characteristics, through which significant disparities in attitudes along multiple dimensions were revealed. According to these findings, it is suggested that governments and public health organizations should provide targeted interventions to address different concerns, especially among males, older people, and other individuals with low levels of education, low awareness of news, low income, and light use of social media. Moreover, public health authorities may consider cooperating with Twitter users having high levels of social influence to promote the acceptance of COVID-19 vaccines among all population groups.

Isolation, purification and structural characterization of two pectin-type polysaccharides from Coreopsis tinctoria Nutt. and their proliferation activities on RAW264.7 cells.

Coreopsis tinctoria Nutt. (C.tinctoria) is an annual herb of the Compositae family with many health benefits, such as clearing heat, antioxidant and anticancer activity. In this paper, two polysaccharides were isolated from C.tinctoria, named CTAP-1 and CTAP-2, respectively. Structure of CTAP-1and CTAP-2 were elucidated by high-performance gel permeation chromatography, chemical derivative analyses, GC-MS and NMR techniques. Results reveal that they both CTAP-1 and CTAP-2 consisted of predominant amounts of galacturonic acid residues along with small amounts of arabinose, rhamnose and galactose.Both them contain homogalacturonan and rhammnogalcturan I regions in different ratio, suggesting their pectin-type features. The proliferation activities of CTAP-1 and CTAP-2 on RAW264.7 cells in vitro were detected. Results show both them have the significant proliferation effect on RAW264.7 cells when the concentration from 40 to 200 µg/mL. Given their structural characteristics and proliferation activities, the pectins are expected to be potential natural immune modulators, which need further study.

Adaboost-Based Machine Learning Improved the Modeling Robust and Estimation Accuracy of Pear Leaf Nitrogen Concentration by In-Field VIS-NIR Spectroscopy.

Different cultivars of pear trees are often planted in one orchard to enhance yield for its gametophytic self-incompatibility. Therefore, an accurate and robust modelling method is needed for the non-destructive determination of leaf nitrogen (N) concentration in pear orchards with mixed cultivars. This study proposes a new technique based on in-field visible-near infrared (VIS-NIR) spectroscopy and the Adaboost algorithm initiated with machine learning methods. The performance was evaluated by estimating leaf N concentration for a total of 1285 samples from different cultivars, growth regions, and tree ages and compared with traditional techniques, including vegetation indices, partial least squares regression, singular support vector regression (SVR) and neural networks (NN). The results demonstrated that the leaf reflectance responded to the leaf nitrogen concentration were more sensitive to the types of cultivars than to the different growing regions and tree ages. Moreover, the AdaBoost.RT-BP had the best accuracy in both the training (R2 = 0.96, root mean relative error (RMSE) = 1.03 g kg-1) and the test datasets (R2 = 0.91, RMSE = 1.29 g kg-1), and was the most robust in repeated experiments. This study provides a new insight for monitoring the status of pear trees by the in-field VIS-NIR spectroscopy for better N managements in heterogeneous pear orchards.

An investigation of vitamin D nutritional status in children after outbreak of coronavirus disease 2019. / æ–°åž‹å† çŠ¶ç— æ¯’è‚ºç‚Žç–«æƒ åŽå„¿ç«¥ç»´ç”Ÿç´ Dè¥å »çŠ¶å†µè°ƒæŸ¥.

OBJECTIVES: To investigate vitamin D nutritional status in children after outbreak of coronavirus disease 2019 (COVID-19), as well as the effect of strict epidemic prevention and control measures for the COVID-19 epidemic on vitamin D nutritional status in children. METHODS: A total of 7 460 children who underwent routine physical examinations from February to August, 2020 and had normal results were retrospectively enrolled as the observation group, and 10 102 children who underwent routine physical examinations from February to August, 2019 (no epidemic of COVID-19) and had normal results were enrolled as the control group. The serum level of 25-hydroxy vitamin D [25(OH)D] was compared between the two groups. The children in the observation and control groups who underwent physical examinations in March and April were selected as the epidemic prevention subgroup (n=1 710) and non-epidemic subgroup (n=2 877) respectively. The subjects were divided into five age groups (infancy, early childhood, preschool, school age and adolescence), and serum 25(OH)D levels of children of all ages were compared between the epidemic prevention and non-epidemic subgroups. RESULTS: The observation group had a lower serum level of 25(OH)D than the control group in March and April (P<0.001). The epidemic prevention subgroup had a lower serum level of 25(OH)D than the non-epidemic subgroup in all age groups (P<0.001). The vitamin D sufficiency rate in early childhood, preschool, school and adolescent children from the epidemic prevention subgroup was lower than the non-epidemic subgroup (P<0.001), with a reduction of 10.71%, 18.76%, 59.63% and 56.29% respectively. CONCLUSIONS: Strict prevention and control measures for the COVID-19 epidemic may lead to a significant reduction in vitamin D level in children, especially school-aged and adolescent children. It is recommended to timely monitor vitamin D level in children, take vitamin D supplements, and increase the time of outdoor sunshine as far as possible under the premise of adherence to epidemic prevention regulations.

Conventional and genetic evidence on alcohol and vascular disease aetiology: a prospective study of 500 000 men and women in China.

BACKGROUND: Moderate alcohol intake has been associated with reduced cardiovascular risk in many studies, in comparison with abstinence or with heavier drinking. Studies in east Asia can help determine whether these associations are causal, since two common genetic variants greatly affect alcohol drinking patterns. We used these two variants to assess the relationships between cardiovascular risk and genotype-predicted mean alcohol intake in men, contrasting the findings in men with those in women (few of whom drink). METHODS: The prospective China Kadoorie Biobank enrolled 512 715 adults between June 25, 2004, and July 15, 2008, from ten areas of China, recording alcohol use and other characteristics. It followed them for about 10 years (until Jan 1, 2017), monitoring cardiovascular disease (including ischaemic stroke, intracerebral haemorrhage, and myocardial infarction) by linkage with morbidity and mortality registries and electronic hospital records. 161 498 participants were genotyped for two variants that alter alcohol metabolism, ALDH2-rs671 and ADH1B-rs1229984. Adjusted Cox regression was used to obtain the relative risks associating disease incidence with self-reported drinking patterns (conventional epidemiology) or with genotype-predicted mean male alcohol intake (genetic epidemiology-ie, Mendelian randomisation), with stratification by study area to control for variation between areas in disease rates and in genotype-predicted intake. FINDINGS: 33% (69 897/210 205) of men reported drinking alcohol in most weeks, mainly as spirits, compared with only 2% (6245/302 510) of women. Among men, conventional epidemiology showed that self-reported alcohol intake had U-shaped associations with the incidence of ischaemic stroke (n=14 930), intracerebral haemorrhage (n=3496), and acute myocardial infarction (n=2958); men who reported drinking about 100 g of alcohol per week (one to two drinks per day) had lower risks of all three diseases than non-drinkers or heavier drinkers. In contrast, although genotype-predicted mean male alcohol intake varied widely (from 4 to 256 g per week-ie, near zero to about four drinks per day), it did not have any U-shaped associations with risk. For stroke, genotype-predicted mean alcohol intake had a continuously positive log-linear association with risk, which was stronger for intracerebral haemorrhage (relative risk [RR] per 280 g per week 1·58, 95% CI 1·36-1·84, p<0·0001) than for ischaemic stroke (1·27, 1·13-1·43, p=0·0001). For myocardial infarction, however, genotype-predicted mean alcohol intake was not significantly associated with risk (RR per 280 g per week 0·96, 95% CI 0·78-1·18, p=0·69). Usual alcohol intake in current drinkers and genotype-predicted alcohol intake in all men had similarly strong positive associations with systolic blood pressure (each p<0·0001). Among women, few drank and the studied genotypes did not predict high mean alcohol intake and were not positively associated with blood pressure, stroke, or myocardial infarction. INTERPRETATION: Genetic epidemiology shows that the apparently protective effects of moderate alcohol intake against stroke are largely non-causal. Alcohol consumption uniformly increases blood pressure and stroke risk, and appears in this one study to have little net effect on the risk of myocardial infarction. FUNDING: Chinese Ministry of Science and Technology, Kadoorie Charitable Foundation, National Natural Science Foundation of China, British Heart Foundation, Cancer Research UK, GlaxoSmithKline, Medical Research Council, and Wellcome Trust.

Transcriptome Analysis of Pyrus betulaefolia Seedling Root Responses to Short-Term Potassium Deficiency.

Potassium (K) plays a crucial role in multiple physiological and developmental processes in plants. Its deficiency is a common abiotic stress that inhibits plant growth and reduces crop productivity. A better understanding of the mechanisms involved in plant responses to low K could help to improve the efficiency of K use in plants. However, such responses remain poorly characterized in fruit tree species such as pears (Pyrus sp). We analyzed the physiological and transcriptome responses of a commonly used pear rootstock, Pyrus betulaefolia, to K-deficiency stress (0 mM). Potassium deprivation resulted in apparent changes in root morphology, with short-term low-K stress resulting in rapidly enhanced root growth. Transcriptome analyses indicated that the root transcriptome was coordinately altered within 6 h after K deprivation, a process that continued until 15 d after treatment. Potassium deprivation resulted in the enhanced expression (up to 5-fold) of a putative high-affinity K+ transporter, PbHAK5 (Pbr037826.1), suggesting the up-regulation of mechanisms associated with K+ acquisition. The enhanced root growth in response to K-deficiency stress was associated with a rapid and sustained decrease in the expression of a transcription factor, PbMYB44 (Pbr015309.1), potentially involved in mediating auxin responses, and the increased expression of multiple genes associated with regulating root growth. The concentrations of several phytohormones including indoleacetic acid (IAA), ABA, ETH, gibberellin (GA3), and jasmonic acid (JA) were higher in response to K deprivation. Furthermore, genes coding for enzymes associated with carbon metabolism such as SORBITOL DEHYDROGENASE (SDH) and SUCROSE SYNTHASE (SUS) displayed greatly enhanced expression in the roots under K deprivation, presumably indicating enhanced metabolism to meet the increased energy demands for growth and K+ acquisition. Together, these data suggest that K deprivation in P. betulaefolia results in the rapid re-programming of the transcriptome to enhance root growth and K+ acquisition. These data provide key insights into the molecular basis for understanding low-K-tolerance mechanisms in pears and in other related fruit trees and identifying potential candidates that warrant further analyses.

Study on Structural Evolution, Thermochemistry and Electron Affinity of Neutral, Mono- and Di-Anionic Zirconium-Doped Silicon Clusters ZrSin0/-/2- (n = 6-16).

We have carried out a global search of systematic isomers for the lowest energy of neutral and Zintl anionic Zr-doped Si clusters ZrSin0/-/2- (n = 6-16) by employing the ABCluster global search method combined with the mPW2PLYP double-hybrid density functional. In terms of the evaluated energies, adiabatic electron affinities, vertical detachment energies, and agreement between simulated and experimental photoelectron spectroscopy, the true global minimal structures are confirmed. The results reveal that structural evolution patterns for neutral ZrSin clusters prefer the attaching type (n = 6-9) to the half-cage motif (n = 10-13), and finally to a Zr-encapsulated configuration with a Zr atom centered in a Si cage (n = 14-16). For Zintl mono- and di-anionic ZrSin-/2-, their growth patterns adopt the attaching configuration (n = 6-11) to encapsulated shape (n = 12-16). The further analyses of stability and chemical bonding make it known that two extra electrons not only perfect the structure of ZrSi15 but also improve its chemical and thermodynamic stability, making it the most suitable building block for novel multi-functional nanomaterials.

[Epidemic characteristics of central obesity among adults in Gansu Province in 2013-2014].

OBJECTIVE: To analyze waist circumference level and the prevalence of central obesity among adults aged 18 years and above in Gansu Province. METHODS: The data from Chinese adult chronic diseases and their risk factors monitoring in 2013 was obtained by multi-stage stratified cluster random sampling method. The waist circumference level and epidemiologic characteristics of central obesity of 7607 adults aged 18 years and above in Gansu Province were analyzed. RESULTS: The waist circumference was(84.7±10.3)cm and(81.3±9.5)cm for adult men and women in Gansu Province, respectively. With the increase of age, waist circumference level of women showed a gradual increase trend from 78.6 cm in the group of 18-44 years to 83.5 cm in the group above 60 years; with improvement of education level, the average waist circumference of men gradually increased from 82.7 cm in illiterate/semi-literate group to 87.6 cm in group of junior college and above(P<0.001), but the value of women gradually reduced from 81.9 cm in illiterate/semi-literate group to 77.6 cm in group of junior college and above group(P<0.001); the higher the average annual income of family, the higher the waist circumference of the men from 83.0 cm in the group below 5000 yuan to 85.9 cm in the group above 18 000 yuan; among the occupational group, the highest waist circumference(88.9 cm) was the men engaged in enterprises and institutions and in contrast the women were the lowest in this occupation(79.0 cm). The prevalence of central obesity was 32.6%(standardized rate 28.8%) and men(33.9%)(standardized rate 28.8%) was higher than women(30.9%)(standardize rate 28.8%). The pre-obesity rate was 18.1%(standardized rate 17.6%), and that of women and men was 19.5%(standardized rate 18.5%) and 16.2%(standardized rate 16.0%), respectively. With the age increase, the central obesity rate of women showed a gradually increasing trend from 22.6% in the group of 18-44 years to 45.3% in the group above 60 years. With the increase of education level, the prevalence of central obesity showed increasing trend from 23.0% in illiterate/semi-literate group to 42.5% in group of college and above in men(P<0.001), but the prevalence of women gradually reduced from 36.1% in illiterate/semi-literate group to 20.1% in group of college and above group(P<0.001); with the increase in per capita annual income of the family, the prevalence of male central obesity increased from 23.8% in the group below 5000 yuan to 35.5% in the group above 18 000 yuan; among the professional groups, men predisposed central obesity(48.5%, P<0.001) and women had lowest prevalence(25.8%, P<0.001) in enterprises and institutions. Among the groups of overweight and obesity, the waist circumference was(88.3±7.4) cm and(98.8±8.3) cm in men, respectively, while the waist was(84.4±6.7)cm and(94.5±8.1)cm in women, respectively; the prevalence of central obesity was 43.3% and 87.7% in men and 47.3% and 93.9% in women between overweight and obese groups. However, the rate of central obesity in the groups without overweight/obesity(BMI<24.0) was only 6.0% in men and 9.8% in women. CONCLUSION: The central obesity is widely prevalence in adults of Gansu Province, and the averaged waist circumference level in men and women is close to or more than the cut-off point predicating pre-central obesity and the prevalence for this type of obesity is higher than that of the national level which indicates that using cut-off point of waist circumference. The subjects with obesity are more likely susceptible to central obesity.

Construction of engineered Saccharomyces cerevisiae strain to improve that whole-cell biocatalytic production of melibiose from raffinose.

There are excessive by-products in the biocatalysis process of this whole-cell biocatalytic production of melibiose from raffinose with current Saccharomyces cerevisiae strains. To solve this problem, we constructed engineered strains based on a liquor yeast (S. cerevisiae) via gene deletion (mel1 gene), heterologous integration (fsy1 or/and ffzi1 gene from Candida magnoliae), and gene overexpression (gcr1 gene). Functional verification showed that deletion of the mel1 gene led to elimination of the reactions catalyzed by α-galactosidase, as well as elimination of the degradation of melibiose and the formation of galactose by-product. Insertion of the fsy1 or/and ffzi1 gene and overexpression of the gcr1 gene could contribute to fructose transport for enhancing the biopurification rate of the fructose by-product. Compared with the wild-type strain, the optimal engineered strain of MP8 (Δmel1::fsy1 cm ::ffzi1 cm ::gcr1 sc ) had improved about 30% on yield, 31% on productivity, and 36% on purity of the melibiose product.

Non-Destructive Evaluation of the Leaf Nitrogen Concentration by In-Field Visible/Near-Infrared Spectroscopy in Pear Orchards.

Non-destructive and timely determination of leaf nitrogen (N) concentration is urgently needed for N management in pear orchards. A two-year field experiment was conducted in a commercial pear orchard with five N application rates: 0 (N0), 165 (N1), 330 (N2), 660 (N3), and 990 (N4) kg·N·ha-1. The mid-portion leaves on the year's shoot were selected for the spectral measurement first and then N concentration determination in the laboratory at 50 and 80 days after full bloom (DAB). Three methods of in-field spectral measurement (25° bare fibre under solar conditions, black background attached to plant probe, and white background attached to plant probe) were compared. We also investigated the modelling performances of four chemometric techniques (principal components regression, PCR; partial least squares regression, PLSR; stepwise multiple linear regression, SMLR; and back propagation neural network, BPNN) and three vegetation indices (difference spectral index, normalized difference spectral index, and ratio spectral index). Due to the low correlation of reflectance obtained by the 25° field of view method, all of the modelling was performed on two spectral datasets-both acquired by a plant probe. Results showed that the best modelling and prediction accuracy were found in the model established by PLSR and spectra measured with a black background. The randomly-separated subsets of calibration (n = 1000) and validation (n = 420) of this model resulted in high R² values of 0.86 and 0.85, respectively, as well as a low mean relative error (<6%). Furthermore, a higher coefficient of determination between the leaf N concentration and fruit yield was found at 50 DAB samplings in both 2015 (R² = 0.77) and 2014 (R² = 0.59). Thus, the leaf N concentration was suggested to be determined at 50 DAB by visible/near-infrared spectroscopy and the threshold should be 24-27 g/kg.

Risks and Population Burden of Cardiovascular Diseases Associated with Diabetes in China: A Prospective Study of 0.5 Million Adults.

BACKGROUND: In China, diabetes prevalence is rising rapidly, but little is known about the associated risks and population burden of cardiovascular diseases. We assess associations of diabetes with major cardiovascular diseases and the relevance of diabetes duration and other modifiable risk factors to these associations. METHODS AND FINDINGS: A nationwide prospective study recruited 512,891 men and women aged 30-79 y between 25 June 2004 and 15 July 2008 from ten diverse localities across China. During ~7 y of follow-up, 7,353 cardiovascular deaths and 25,451 non-fatal major cardiovascular events were recorded among 488,760 participants without prior cardiovascular disease at baseline. Cox regression yielded adjusted hazard ratios (HRs) comparing disease risks in individuals with diabetes to those without. Overall, 5.4% (n = 26,335) of participants had self-reported (2.7%) or screen-detected (2.7%) diabetes. Individuals with self-reported diabetes had an adjusted HR of 2.07 (95% CI 1.90-2.26) for cardiovascular mortality. There were significant excess risks of major coronary event (2.44, 95% CI 2.18-2.73), ischaemic stroke (1.68, 95% CI 1.60-1.77), and intracerebral haemorrhage (1.24, 95% CI 1.07-1.44). Screen-detected diabetes was also associated with significant, though more modest, excess cardiovascular risks, with corresponding HRs of 1.66 (95% CI 1.51-1.83), 1.62 (95% CI 1.40-1.86), 1.48 (95% CI 1.40-1.57), and 1.17 (95% CI 1.01-1.36), respectively. Misclassification of screen-detected diabetes may have caused these risk estimates to be underestimated, whilst lack of data on lipids may have resulted in residual confounding of diabetes-associated cardiovascular disease risks. Among individuals with diabetes, cardiovascular risk increased progressively with duration of diabetes and number of other presenting modifiable cardiovascular risk factors. Assuming a causal association, diabetes now accounts for ~0.5 million (489,676, 95% CI 335,777-681,202) cardiovascular deaths annually in China. CONCLUSIONS: Among Chinese adults, diabetes is associated with significantly increased risks of major cardiovascular diseases. The increasing prevalence and younger age of onset of diabetes foreshadow greater diabetes-attributable disease burden in China.

Biosynthesis of 2-deoxysugars using whole-cell catalyst expressing 2-deoxy-D-ribose 5-phosphate aldolase.

2-Deoxy-D-ribose 5-phosphate aldolase (DERA) accepts a wide variety of aldehydes and is used in de novo synthesis of 2-deoxysugars, which have important applications in drug manufacturing. However, DERA has low preference for non-phosphorylated substrates. In this study, DERA from Klebsiella pneumoniae (KDERA) was mutated to increase its enzyme activity and substrate tolerance towards non-phosphorylated polyhydroxy aldehyde. Mutant KDERA(K12) (S238D/F200I/ΔY259) showed a 3.15-fold improvement in enzyme activity and a 1.54-fold increase in substrate tolerance towards D-glyceraldehyde compared with the wild type. Furthermore, a whole-cell transformation strategy using resting cells of the BL21(pKDERA12) strain, containing the expressed plasmid pKDERA12, resulted in increase in 2-deoxy-D-ribose yield from 0.41 mol/mol D-glyceraldehyde to 0.81 mol/mol D-glyceraldehyde and higher substrate tolerance from 0.5 to 3 M compared to in vitro assays. With further optimization of the transformation process, the BL21(pKDERA12) strain produced 2.14 M (287.06 g/L) 2-deoxy-D-robose (DR), with a yield of 0.71 mol/mol D-glyceraldehyde and average productivity of 0.13 mol/L·h (17.94 g/L·h). These results demonstrate the potential for large-scale production of 2-deoxy-D-ribose using the BL21(pKDERA12) strain. Furthermore, the BL21(pKDERA12) strain also exhibited the ability to efficiently produce 2-deoxy-D-altrose from D-erythrose, as well as 2-deoxy-L-xylose and 2-deoxy-L-ribose from L-glyceraldehyde.

Structural Growth Pattern, Electronic Configurations, and Spectral and Thermochemistry Properties of ZrSnn0/-/2- (n = 4-17) Nanoscale Compounds: A Systematic Study Using Density Functional Theory.

By performing density functional theory (DFT) calculations for geometric optimization in conjunction with the artificial bee colony algorithm for cluster (ABCluster) global search approach, the ground-state structures of the neutral, anionic, and dianionic ZrSnn0/-/2- (n = 4-17) nanoscale compounds are obtained. Their structural growth evolution, spectral information, and electronic and thermochemical properties are investigated. Regarding the architectural evolution of the neutral, anion, and dianionic species, ZrSnn0/-/2- (n = 4-17) compounds possess two different stages of adsorption patterns in which, when n = 4-7 and n = 8-17, ZrSn40/-/2- and ZrSn80/-/2- compounds as the basic motif adsorb Sn atoms to become the larger clusters, respectively. The simulated photoelectron spectra (PES) of anionic compounds are in good agreement with the available experimental PES. The infrared and Raman spectra can be summarized as follows: under infrared vibrational modes, the sealed cages of ZrSnn0/-/2- compounds belong to the deformation mode, and under Raman vibrational modes, they belong to the breathing mode of the Sn cage framework. The density of states (DOS) spectra and natural population analysis (NPA) indicate that the interaction between the Zr atom and Snn frameworks of capsulated compounds has been developing stronger than for unsealed compounds. The results of thermochemical properties, molecular orbital shell (MOs) analysis, and ultraviolet-visible (UV-vis) absorption spectrum indicate that the neutral ZrSn16 nanoscale compound possesses not only both thermodynamic and chemical stability but also far-infrared sensing and optoelectronic properties and hence, is the best building block motif for new multipurpose nanoscale materials.

Introducing hafnium to atomically small- and medium-sized tin clusters (HfSnn0/-/2- (n = 4-17)): A computational investigation of geometrical and growth behavior, spectral properties, electronic configuration and thermochemistry.

The global and local minimum configurations of single Hf atom doped Sn clusters are conducted via density function theory (DFT) combined with artificial bee colony algorithm (ABCluster). Furthermore, DFT method is also used to systematically investigate on their structural growth evolution, spectral and electronic information, thermochemical properties following the size of tin clusters doped Hf atom. Structurally, the ground-state geometries of neutral, anion and di-anion are discovered that, from n = 4, the number of Sn atoms in cluster, HfSnn0/-/2- adsorb additional Sn atom on the prior architecture one by one until forming n = 17 for HfSnn-10/-, as well as forming n = 16 for HfSnn-12-. And for the HfSn110/- and HfSn102- as beginning the species veritably develop sealed architectures. The strongest vibrational modes of sealed nanoclusters are stretching modes of Hf atom with infrared actives and breathing modes of the Sn cage framework with Raman actives, respectively. The natural population analysis (NPA) elucidates the stronger relationship between the Hf atoms and the tin frameworks in sealed clusters than that in unsealed clusters. The results of thermochemical properties, molecular orbital shell (MOs), adaptive natural density partitioning (AdNDP) and ultraviolet visible absorption spectrum (UV-Vis) indicate that, the HfSn16 with high symmetry of Td exhibits thermochemical stability and optoelectronic properties, which is utilized potentially as zero-dimensional unit of self-assembling fluorescent nanomaterials.

I2U-Net: A dual-path U-Net with rich information interaction for medical image segmentation.

Although the U-shape networks have achieved remarkable performances in many medical image segmentation tasks, they rarely model the sequential relationship of hierarchical layers. This weakness makes it difficult for the current layer to effectively utilize the historical information of the previous layer, leading to unsatisfactory segmentation results for lesions with blurred boundaries and irregular shapes. To solve this problem, we propose a novel dual-path U-Net, dubbed I2U-Net. The newly proposed network encourages historical information re-usage and re-exploration through rich information interaction among the dual paths, allowing deep layers to learn more comprehensive features that contain both low-level detail description and high-level semantic abstraction. Specifically, we introduce a multi-functional information interaction module (MFII), which can model cross-path, cross-layer, and cross-path-and-layer information interactions via a unified design, making the proposed I2U-Net behave similarly to an unfolded RNN and enjoying its advantage of modeling time sequence information. Besides, to further selectively and sensitively integrate the information extracted by the encoder of the dual paths, we propose a holistic information fusion and augmentation module (HIFA), which can efficiently bridge the encoder and the decoder. Extensive experiments on four challenging tasks, including skin lesion, polyp, brain tumor, and abdominal multi-organ segmentation, consistently show that the proposed I2U-Net has superior performance and generalization ability over other state-of-the-art methods. The code is available at https://github.com/duweidai/I2U-Net.