Advances of Hydrogel-Based Bioprinting for Cartilage Tissue Engineering

Bioprinting has gained immense attention and achieved the revolutionized progress for application in the multifunctional tissue regeneration. On account of the precise structural fabrication and mimicking complexity, hydrogel-based bio-inks are widely adopted for cartilage tissue engineering. Although more and more researchers have reported a number of literatures in this field, many challenges that should be addressed for the development of three-dimensional (3D) bioprinting constructs still exist. Herein, this review is mainly focused on the introduction of various natural polymers and synthetic polymers in hydrogel-based bioprinted scaffolds, which are systematically discussed via emphasizing on the fabrication condition, mechanical property, biocompatibility, biodegradability, and biological performance for cartilage tissue repair. Further, this review describes the opportunities and challenges of this 3D bioprinting technique to construct complex bio-inks with adjustable mechanical and biological integrity, and meanwhile, the current possible solutions are also conducted for providing some suggestive ideas on developing more advanced bioprinting products from the bench to the clinic.

Developing Longer-Lived Single Molecule Junctions with a Functional Flexible Electrode

Creating single-molecule junctions with a long-lived lifetime at room temperature is an open challenge. Finding simple and efficient approaches to increase the durability of single-molecule junction is also of practical value in molecular electronics. Here it is shown that a flexible gold-coated nanopipette electrode can be utilized in scanning tunneling microscope (STM) break-junction measurements to efficiently enhance the stability of molecular junctions by comparing with the measurements using conventional solid gold probes. The stabilizing effect of the flexible electrode displays anchor group dependence, which increases with the binding energy between the anchor group and gold. An empirical model is proposed and shows that the flexible electrode could promote stable binding geometries at the gold-molecule interface and slow down the junction breakage caused by the external perturbations, thereby extending the junction lifetime. Finally, it is demonstrated for the first time that the internal conduit of the flexible STM tip can be utilized for the controlled molecule delivery and molecular junction formation.

Artificial intelligence in echocardiography: detection, functional evaluation, and disease diagnosis

Ultrasound is one of the most important examinations for clinical diagnosis of cardiovascular diseases. The speed of image movements driven by the frequency of the beating heart is faster than that of other organs. This particularity of echocardiography poses a challenge for sonographers to diagnose accurately. However, artificial intelligence for detection, functional evaluation, and disease diagnosis has gradually become an alternative for accurate diagnosis and treatment using echocardiography. This work discusses the current application of artificial intelligence in echocardiography technology, its limitations, and future development directions.

Risk and Influencing Factors for Subsequent Primary Lung Cancer After Treatment of Breast Cancer: A Systematic Review and Two Meta-Analyses Based on Four Million Cases

INTRODUCTION

To compare the risk of developing lung cancer between patients with breast cancer and the general population and explore the risk factors for the development of primary lung cancer after treatment for breast cancer.

METHODS

The PubMed, EMBASE, and Web of Science databases were searched from the establishment date to October 11, 2020. Two separate meta-analyses were performed: one focused on studies reporting the risk of subsequent lung cancer after breast cancer and one focused on studies exploring the risk factors for subsequent lung cancer in patients with breast cancer. The standardized incidence ratios with 95% confidence intervals were combined to compare the risk of developing lung cancer between patients with breast cancer and the general population. The relative risks (RRs) or ORs with 95% confidence intervals were combined to assess the association of clinicopathological parameters with the risk of developing lung cancer after breast cancer. All statistical analyses were conducted by STATA 12.0.

RESULTS

A total of 15 studies involving 1,161,979 patients were eventually included in the first meta-analysis, and the pooled results indicated that female patients with breast cancer revealed a significantly higher risk of developing subsequent lung cancer (standardized incidence ratio = 1.25, p < 0.001). In addition, a total of 22 articles involving 3,090,620 patients were included in the second meta-analysis. The pooled results indicated that smoking (OR = 9.73, p < 0.001) and radiotherapy (RR = 1.40, p < 0.001) were risk factors for developing subsequent lung cancer in patients with breast cancer, and chemotherapy (RR = 0.69, p = 0.002), positive estrogen receptor status (RR = 0.93, p = 0.014) and positive progesterone receptor status (RR = 0.86, p < 0.001) were protective factors. Meanwhile, subgroup analysis based on the relative position of the breast and lung cancers (ipsilateral versus contralateral) was conducted, which indicated that radiotherapy only increased the risk of ipsilateral lung cancer in patients with breast cancer (RR = 1.27, p = 0.001).

CONCLUSIONS

Patients with breast cancer are more likely to develop lung cancer than the general population, and the risk of developing primary lung cancer after breast cancer is affected by smoking, radiotherapy, chemotherapy, estrogen receptor status and progesterone receptor status.

Prognostic Characteristics of Operated Breast Cancer Patients with Second Primary Lung Cancer: A Retrospective Study

Background and Purpose

The number of breast cancer patients with second primary lung cancer is increasing year by year. The aim of this study was to explore the prognostic characteristics of these multiple primary breast and lung cancer patients.

Methods

Operated breast cancer patients with subsequent lung cancer who were admitted to our hospital from January, 2010 to August, 2020 were retrospectively analyzed. The univariate and multivariate Cox regression analyses were conducted to explore the prognostic risk factors of such patients. Meanwhile, the propensity score match (PSM) method was applied to compare the prognosis between lung cancer patients with and without the history of breast cancer.

Results

A total of 137 cases were included and most of them (94.9%) were asynchronous multiple primary carcinomas. The median interval between the diagnoses of breast cancer and lung cancer was 60 months (2-456 months), median age at the diagnosis of breast cancer was 49.5 (28-81) years old and median age at the diagnosis of lung cancer was 58 (31-84) years old. Univariate and multivariate Cox regression analysis indicated that poor differentiation [hazard ratio (HR)=6.372, 95% confidence interval (CI): 2.441-16.633, P<0.001] and pTNM stage III/IV (HR=5.830, 95% CI: 2.295-14.813, P<0.001) of lung cancer were independent prognostic risk factors for these patients. Before and after the PSM, the overall survival (OS) of lung cancer patients with breast cancer was significantly worse than that of single primary lung cancer patients (P<0.001, P=0.002).

Conclusion

Differentiation status and pTNM stage were independent prognostic factors in operated breast cancer patients with second primary lung cancer. Meanwhile, the prognosis of this group of patients was worse than single primary lung cancer patients, which indicated that the medical history of breast cancer was also a prognostic risk factor of female lung cancer patients.

Direct Observation of Amide Bond Formation in a Plasmonic Nanocavity Triggered by Single Nanoparticle Collisions

The real-time observation of chemical bond formation at the single-molecule level is one of the great challenges in the fields of organic and biomolecular chemistry. Valuable information can be gleaned that is not accessible using ensemble-average measurements. Although remarkably sophisticated techniques for monitoring chemical reactions have been developed, the ability to detect the specific formation of a chemical bond in situ at the single-molecule level has remained an elusive goal. Amide bonds are routinely formed from the aminolysis of N-hydroxysuccinimide (NHS) esters by primary amines, and the protocol is widely used for the synthesis, cross-linking, and labeling of peptides and proteins. Herein, a plasmonic nanocavity was applied to study aminolysis reaction for amide bond formation, which was initiated by single nanoparticle collision events between suitably functionalized free-moving gold nanoparticles and a gold nanoelectrode in an aqueous buffer. By means of simultaneous surface enhanced Raman spectroscopy (SERS) and single-entity electrochemistry (EC) measurements, we have probed the dynamic evolution of amide bond formation in the aminolysis reaction with 10 s of millisecond time resolution. Hence, we demonstrate that single-entity EC-SERS is a valuable and sensitive technique by which chemical reactions can be studied at the single-molecule level.

Detecting Individual Bond Switching within Amides in a Tunneling Junction

Amides are essential in the chemistry of life. Detecting the chemical bond states within amides could unravel the nature of amide stabilization and planarity, which is critical to the structure and reactivity of such molecules. Yet, so far, no work has been reported to detect or measure the bond changes at the single-molecule level within amides. Here, we show that a transition between single and double bonds between N and C atoms in an amide can be monitored in real time in a nanogap between gold electrodes via the generation of distinctive conductance features. Density functional theory simulations show that the switching between amide isomers proceeds via a proton transfer process facilitated by a water molecule bridge, and the resulting molecular junctions display bimodal conductance states with a difference as much as nine times.

A Combined sEMG and Accelerometer System for Monitoring Functional Activity in Stroke

Remote monitoring of physical activity using bodyworn sensors provides an alternative to assessment of functional independence by subjective, paper-based questionnaires. This study investigated the classification accuracy of a combined surface electromyographic (sEMG) and accelerometer (ACC) sensor system for monitoring activities of daily living in patients with stroke. sEMG and ACC data were recorded from 10 hemi paretic patients while they carried out a sequence of 11 activities of daily living (Identification tasks), and 10 activities used to evaluate misclassification errors (non-Identification tasks). The sEMG and ACC sensor data were analyzed using a multilayered neural network and an adaptive neuro-fuzzy inference system to identify the minimal sensor configuration needed to accurately classify the identification tasks, with a minimal number of misclassifications from the non-Identification tasks. The results demonstrated that the highest sensitivity and specificity for the identification tasks was achieved using a subset of 4 ACC sensors and adjacent sEMG sensors located on both upper arms, one forearm, and one thigh, respectively. This configuration resulted in a mean sensitivity of 95.0 %, and a mean specificity of 99.7 % for the identification tasks, and a mean misclassification error of < 10% for the non-Identification tasks. The findings support the feasibility of a hybrid sEMG and ACC wearable sensor system for automatic recognition of motor tasks used to assess functional independence in patients with stroke.

Genome-wide expression changes mediated by A-to-I RNA editing correlate with hepatic oncogenesis

Background

Adenosine-to-inosine (A-to-I) RNA editing is one of the most prevalent RNA modifications in the animal kingdom. Since inosine is recognized as guanosines, the A-to-I process mimics A-to-G DNA mutations but can be controlled in a more flexible manner compared to DNA alterations.

Methods

We parsed the transcriptomes and translatomes of liver cancer and normal tissues from ten patients. We profiled the landscape of the A-to-I RNA editome in these samples and interrogated whether the A-to-I processes participated in the gene expression regulation in oncogenesis.

Results

Globally, editing activity was enhanced in all tumor samples compared to that in normal samples. Accordingly, expression of the gene encoding the RNA editing enzyme ADAR (adenosine deaminase acting on RNA) was elevated. Two intronic self-editing sites in ADAR mRNAs controlled its splicing pattern and may regulate its translation efficiency (TE). Moreover, the expression of oncogenes was generally upregulated in tumors, whereas tumor suppressor genes (TSG) were downregulated, possibly due to alterations to microRNA binding sites or RNA splicing defects caused by A-to-I editing.

Conclusions

A-to-I RNA editing plays a crucial role in the oncogenesis of liver cancer. ADAR regulates its own expression via self-editing, and it also affects global transcriptomes and translatomes involving cancer-related genes by RNA editing and changing their expression patterns.

Retrieving the deleterious mutations before extinction: genome-wide comparison of shared derived mutations in liver cancer and normal population

STUDY PURPOSE

Deleterious mutations would be rapidly purged from natural populations along with the extinction of their carriers. The currently observed mutations in existing species are mostly neutral. The inaccessibility of deleterious mutations impedes the functional studies on how these mutations affect the fitness at individual level.

STUDY DESIGN

The connection between the deleterious genotype and the non-adaptive phenotype could be bridged by sequencing the genome before extinction. Although this approach is no longer feasible for evolutionary biologists, it is feasible for cancer biologists by profiling the mutations in tumour samples which are so deleterious that the carriers hardly live.

RESULTS

By comparing the derived mutation profile between normal populations and patients with liver cancer, we found that the shared mutations, which are highly deleterious, are suppressed to low allele frequencies in normal populations and tissues, but show remarkably high frequency in tumours. The density of shared mutations is negatively correlated with gene conservation and expression levels.

CONCLUSIONS

Deleterious mutations are suppressed in functionally important genes as well as in normal populations. This work deepened our understanding on how natural selection act on deleterious mutations by analogising the cancer evolution to species evolution, which are essentially the same molecular process but at different time scales.

Synonymous mutations that regulate translation speed might play a non-negligible role in liver cancer development

Background

Synonymous mutations do not change the protein sequences. Automatically, they have been regarded as neutral events and are ignored in the mutation-based cancer studies. However, synonymous mutations will change the codon optimality, resulting in altered translational velocity.

Methods

We fully utilized the transcriptome and translatome of liver cancer and normal tissue from ten patients. We profiled the mutation spectrum and examined the effect of synonymous mutations on translational velocity.

Results

Synonymous mutations that increase the codon optimality significantly enhanced the translational velocity, and were enriched in oncogenes. Meanwhile, synonymous mutations decreasing codon optimality slowed down translation, and were enriched in tumor suppressor genes. These synonymous mutations significantly contributed to the translational changes in tumor samples compared to normal samples.

Conclusions

Synonymous mutations might play a role in liver cancer development by altering codon optimality and translational velocity. Synonymous mutations should no longer be ignored in the genome-wide studies.

The positive effects of the alpine cushion plant Arenaria polytrichoides on insect dynamics are determined by both physical and biotic factors

Cushion plants' significant role for alpine biodiversity has been demonstrated in particular through their positive effects on plant diversity. However, their effects on higher trophic levels (e.g. insects) remain largely unclear. In this study, by field sampling in the Hengduan Mountains (HDM) in southwestern China, we evaluated the effects of an alpine gynodioecious cushion species, Arenaria polytrichoides (Carophyllaceae), on insect richness, abundance and population dynamics at two different elevations (4427 m vs. 4732 m) separately at two time periods (day vs. night) and in two growing seasons (early vs. late). The results showed that the total insect diversity decreases from low to high elevation sites. Some insect species were exclusively detected within A. polytrichoides cushions, leading to an increase in local insect richness from 7% to 35%. The positive effects of cushions on insect diversity could be attributed to unique biotic properties provided by cushions. Firstly, the effects were determined by the sexual dimorphism of the cushion with hermaphroditic cushions supporting higher insect diversity than female cushions. This could be because hermaphroditic cushions provide more resources, such as nectar and pollen grains, for insects than female cushions. Secondly, the cushions' associated beneficiary plants can also provide extra resources for attracting more insects, but this effect was mediated by the micro-environmental conditions. Finally, the magnitude of cushions' positive effects on insect dynamics were stronger under higher than under lower environmental stress. This study confirmed that facilitation by A. polytrichoides cushions in HDM plays an important role in constructing the alpine insect community and further regulating its dynamics. Moreover, the positive effects of cushions on insect dynamics increase with increasing environmental stress. Therefore, the distribution range of insects would quite possibly be expanded into higher elevation under future climate changes, which will induce new challenges for the local alpine ecosystems.

Programmable Transformations of DNA Origami Made of Small Modular Dynamic Units

Dynamic DNA origami has been employed for generating a rich repository of molecular nanomachines that are capable of sensing various cues and changing their conformations accordingly. The common design principle of the existing DNA origami nanomachines is that each dynamic DNA origami is programmed to transform in a specific manner, and the nanomachine needs to be redesigned to achieve a different form of transformation. However, it remains challenging to enable a multitude of controlled transformations in a single design of dynamic DNA nanomachine. Here we report a modular design method to programmatically tune the shapes of a DNA origami nanomachine. The DNA origami consists of small, modular DNA units, and the length of each unit can be selectively changed by toehold-mediated strand displacement. By use of different combinations of trigger DNA strands, modular DNA units can be selectively transformed, leading to the programmable reconfiguration of the overall dimensions and curvatures of DNA origami. The modular design of programmable shape transformation of DNA origami can find potential applications in more sophisticated molecular nanorobots and smart drug delivery nanocarriers.