Pulsed Microfluid Force-Based On-Chip Modular Fabrication for Liver Lobule-Like 3D Cellular Models

In vitro three-dimensional (3D) cellular models with native tissue-like architectures and functions have potential as alternatives to human tissues in regenerative medicine and drug discovery. However, it is difficult to replicate liver constructs that mimic in vivo microenvironments using current approaches in tissue engineering because of the vessel-embedded 3D structure and complex cell distribution of the liver. This paper reports a pulsed microflow-based on-chip 3D assembly method to construct 3D liver lobule-like models that replicate the spatial structure and functions of the liver lobule. The heterogeneous cell-laden assembly units with hierarchical cell distribution are fabricated through multistep photopatterning of different cell-laden hydrogels. Through fluid force interaction by pulsed microflow, the hierarchical assembly units are driven to a stack, layer by layer, and thus spatially assemble into 3D cellular models in the closed liquid chamber of the assembly chip. The 3D models with liver lobule-like hexagonal morphology and radial cell distribution allow the dynamic perfusion culture to maintain high cell viability and functional expression during long-term culture in vitro. These results demonstrate that the fabricated 3D liver lobule-like models are promising for drug testing and the study of individual diagnoses and treatments.

Identification and validation of a hub gene prognostic index for hepatocellular carcinoma

Aims: We aim to provide new insights into the mechanisms of hepatocellular carcinoma (HCC) and identify key genes as biomarkers for the prognosis of HCC. Materials & methods: Differentially expressed genes between HCC tissues and normal tissues were identified via the Gene Expression Omnibus tool. The top ten hub genes screened by the degree of the protein nodes in the protein-protein interaction network also showed significant associations with overall survival in HCC patients. Results: A prognostic model containing a five-gene signature was constructed to predict the prognosis of HCC via multivariate Cox regression analysis. Conclusion: This study identified a novel five-gene signature (CDK1, CCNB1, CCNB2, BUB1 and KIF11) as a significant independent prognostic factor.

XPG gene polymorphisms and glioma susceptibility: a two-centre case-control study

Background: Glioma, the most common tumour in children next to leukaemia, is difficult to treat, with a poor prognosis and high recurrence rate. Xeroderma pigmentosum group G (XPG) plays a key role in the nucleotide excision repair pathway, which may modulate individual susceptibility to developing cancer. We hypothesized links between XPG variants and glioma in children.Methods: We tested our hypothesis in a study comparing 171 glioma cases with 228 age and sex matched controls, determining XPG polymorphisms rs2094258 C > T, rs751402 C > T, rs2296147 T > C, rs1047768 T > C, rs873601 G > A by standard molecular genetic methods.Results: rs2094258 C > T was associated with a decreased glioma risk, but carrying the rs1047768 C or rs873601 A allele brought an increased risk. Subjects carrying 5 risk genotypes had a significantly increased glioma risk at an adjusted odds ratio of 1.97 (95% confidence Interval 1.26-3.08)(p = 0.003) when compared with those carrying 0-4 risk genotypes. Furthermore, children with 5 risk genotypes had a higher glioma risk when aged >60 months, were more likely to be male, and with subtypes of astrocytic tumours, and low-grade clinical stage, when compared to those with 0-4 risk genotypes. Preliminary functional exploration suggested that rs2094258 is linked with the expression of its surrounding genes in the expression quantitative trait locus analysis.Conclusion: Certain variants of XPG are risk factors for paediatric glioma, and so may be useful in early diagnosis.

The role of liver metabolism in compensatory-growth piglets induced by protein restriction and subsequent protein realimentation

The aim of this work was to study the role of hepatic metabolism of compensatory growth in piglets induced by protein restriction and subsequent protein realimentation. Thirty-six weaned piglets were randomly distributed in a control group and a treatment group. The control group piglets were fed with a normal protein level diet (18.83% CP) for the entire experimental period (day 1-28). The treatment group piglets were fed with a protein-restriction diet (13.05% CP) for day 1 to day 14, and the diet was restored to normal protein level diet for day 15 to day 28. RNA-seq is used to analyze samples of liver metabolism on day 14 and day 28, respectively. Hepatic RNA-sequencing analysis revealed that some KEGG signaling pathways involved in glycolipid metabolism (eg, "AMPK signaling pathway," "insulin signaling pathway," and "glycolysis or gluconeogenesis") were significantly enriched on day 14 and day 28. On day 14, protein restriction promoted hepatic lipogenesis by increasing the genes expression level of ACACA, FASN, GAPM, and SREBP1C, decreasing protein phosphorylation levels of AMPKɑ and ACC in AMPK signaling pathway. In contrast, on day 28, protein realimentation promoted hepatic gluconeogenesis by increasing the concentration of G6Pase and PEPCK, decreasing protein phosphorylation levels of IRS1, Akt, and FoXO1 in insulin signaling pathway. In addition, protein realimentation activated the GH-IGF1 axis between the liver and skeletal muscle. Overall, these findings revealed the importance of liver metabolism in achieving compensatory growth.

Triboelectric Nanogenerators and Hybridized Systems for Enabling Next-Generation IoT Applications

In the past few years, triboelectric nanogenerator-based (TENG-based) hybrid generators and systems have experienced a widespread and flourishing development, ranging among almost every aspect of our lives, e.g., from industry to consumer, outdoor to indoor, and wearable to implantable applications. Although TENG technology has been extensively investigated for mechanical energy harvesting, most developed TENGs still have limitations of small output current, unstable power generation, and low energy utilization rate of multisource energies. To harvest the ubiquitous/coexisted energy forms including mechanical, thermal, and solar energy simultaneously, a promising direction is to integrate TENG with other transducing mechanisms, e.g., electromagnetic generator, piezoelectric nanogenerator, pyroelectric nanogenerator, thermoelectric generator, and solar cell, forming the hybrid generator for synergetic single-source and multisource energy harvesting. The resultant TENG-based hybrid generators utilizing integrated transducing mechanisms are able to compensate for the shortcomings of each mechanism and overcome the above limitations, toward achieving a maximum, reliable, and stable output generation. Hence, in this review, we systematically introduce the key technologies of the TENG-based hybrid generators and hybridized systems, in the aspects of operation principles, structure designs, optimization strategies, power management, and system integration. The recent progress of TENG-based hybrid generators and hybridized systems for the outdoor, indoor, wearable, and implantable applications is also provided. Lastly, we discuss our perspectives on the future development trend of hybrid generators and hybridized systems in environmental monitoring, human activity sensation, human-machine interaction, smart home, healthcare, wearables, implants, robotics, Internet of things (IoT), and many other fields.

Hidden Quantum Hall Stripes in Al_{x}Ga_{1-x}As/Al_{0.24}Ga_{0.76}As Quantum Wells

We report on transport signatures of hidden quantum Hall stripe (hQHS) phases in high (N>2) half-filled Landau levels of Al_{x}Ga_{1-x}As/Al_{0.24}Ga_{0.76}As quantum wells with varying Al mole fraction x<10^{-3}. Residing between the conventional stripe phases (lower N) and the isotropic liquid phases (higher N), where resistivity decreases as 1/N, these hQHS phases exhibit isotropic and N-independent resistivity. Using the experimental phase diagram, we establish that the stripe phases are more robust than theoretically predicted, calling for improved theoretical treatment. We also show that, unlike conventional stripe phases, the hQHS phases do not occur in ultrahigh mobility GaAs quantum wells but are likely to be found in other systems.

Deep learning enabled smart mats as a scalable floor monitoring system

Toward smart building and smart home, floor as one of our most frequently interactive interfaces can be implemented with embedded sensors to extract abundant sensory information without the video-taken concerns. Yet the previously developed floor sensors are normally of small scale, high implementation cost, large power consumption, and complicated device configuration. Here we show a smart floor monitoring system through the integration of self-powered triboelectric floor mats and deep learning-based data analytics. The floor mats are fabricated with unique "identity" electrode patterns using a low-cost and highly scalable screen printing technique, enabling a parallel connection to reduce the system complexity and the deep-learning computational cost. The stepping position, activity status, and identity information can be determined according to the instant sensory data analytics. This developed smart floor technology can establish the foundation using floor as the functional interface for diverse applications in smart building/home, e.g., intelligent automation, healthcare, and security.

[Effect of Porphyromonas gingivalis infection on atherosclerosis in apolipoprotein-E knockout mice]

OBJECTIVE

Studies have indicated that periodontal pathogen Porphyromonas gingivalis (P. gingivalis) infection may contributed to accelerate the development of atherosclerosis. The aim of this study was to investigate the effect of inflammation, oxidative stress and the mechanism on atherosclerosis in apolipoprotein-E knockout (ApoE-/-) mice with P. gingivalis infection.

METHODS

Eight-week-old male ApoE-/- mice (C57BL/6) were maintained under specific pathogen-free conditions and fed regular chow and sterile water after 1 weeks of housing. The animals were randomly divided into two groups: (a) ApoE-/- + PBS (n=8); (b) ApoE-/- + P.gingivalis strain FDC381 (n=8). Both of the groups received intravenous injections 3 times per week for 4 weeks since 8 weeks of age. The sham control group received injections with phosphate buffered saline only, while the P. gingivalis-challenged group with P.gingivalis strain FDC381at the same time. After 4 weeks, oxidative stress mediators and inflammation cytokines were analyzed by oil red O in heart, Enzyme linked immunosorbent assay (ELISA) in serum, quantitative real-time PCR and Western blot in aorta.

RESULTS

In our study, we found accelerated development of atherosclerosis and plaque formation in aorta with oil red O staining, increased oxidative stress markers [8-hydroxy-2-deoxyguanosine (8-OHdG), NADPH oxidase (NOX)-2 and NOX-4], as well as increased inflammation cytokines [interleukin (IL)-1β, IL-6 and tumor necrosis factor-α (TNF-α)] in the serum and aorta of the P. gingivalis-infected ApoE-/- mice. Compared with the control group, there was a significant increase protein level of nuclear factor-kappa B (NF-κB) in aorta after P. gingivalis infection.

CONCLUSIONS

Our results suggest that chronic intravenous infection of P. gingivalis in ApoE-/- mice could accelerate the development of atherosclerosis by disturbing the lipid profile and inducing oxidative stress and inflammation. The NF-κB signaling pathway might play a potential role in the P. gingivalis-accelerated atherogenesis.

Wearable Triboelectric/Aluminum Nitride Nano-Energy-Nano-System with Self-Sustainable Photonic Modulation and Continuous Force Sensing

Wearable photonics offer a promising platform to complement the thriving complex wearable electronics system by providing high-speed data transmission channels and robust optical sensing paths. Regarding the realization of photonic computation and tunable (de)multiplexing functions based on system-level integration of abundant photonic modulators, it is challenging to reduce the overwhelming power consumption in traditional current-based silicon photonic modulators. This issue is addressed by integrating voltage-based aluminum nitride (AlN) modulator and textile triboelectric nanogenerator (T-TENG) on a wearable platform to form a nano-energy-nano-system (NENS). The T-TENG transduces the mechanical stimulations into electrical signals based on the coupling of triboelectrification and electrostatic induction. The self-generated high-voltage from the T-TENG is applied to the AlN modulator and boosts its modulation efficiency regardless of AlN's moderate Pockels effect. Complementarily, the AlN modulator's capacitive nature enables the open-circuit operation mode of T-TENG, providing the integrated NENS with continuous force sensing capability which is notably uninfluenced by operation speeds. Furthermore, a physical model is proposed to describe the coupled AlN modulator/T-TENG system. With the enhanced photonic modulation and the open-circuit operation mode enabled by synergies between the AlN modulator and the T-TENG, optical Morse code transmission and continuous human motion monitoring are demonstrated for practical wearable applications.

Wearable Triboelectric-Human-Machine Interface (THMI) Using Robust Nanophotonic Readout

With the rapid advances in wearable electronics and photonics, self-sustainable wearable systems are desired to increase service life and reduce maintenance frequency. Triboelectric technology stands out as a promising versatile technology due to its flexibility, self-sustainability, broad material availability, low cost, and good scalability. Various triboelectric-human-machine interfaces (THMIs) have been developed including interactive gloves, eye blinking/body motion-triggered interfaces, voice/breath monitors, and self-induced wireless interfaces. Nonetheless, THMIs conventionally use electrical readout and produce pulse-like signals due to the transient charge flows, leading to unstable and lossy transfer of interaction information. To address this issue, we propose a strategy by equipping THMIs with robust nanophotonic aluminum nitride (AlN) modulators for readout. The electrically capacitive nature of AlN modulators enables THMIs to work in the open-circuit condition with negligible charge flows. Meanwhile, the interaction information is transduced from THMIs' voltage to AlN modulators' optical output via the electro-optic Pockels effect. Thanks to the negligible charge flow and the high-speed optical information carrier, stable, information-lossless, and real-time THMIs are achieved. Leveraging the design flexibility of THMIs and nanophotonic readout circuits, various linear sensitivities independent of force speeds are achieved in different interaction force ranges. Toward practical applications, we develop a smart glove to realize continuous real-time robotics control and virtual/augmented reality interaction. Our work demonstrates a generic approach for developing self-sustainable HMIs with stable, information-lossless, and real-time features for wearable systems.

Proton transport enabled by a field-induced metallic state in a semiconductor heterostructure

Tuning a semiconductor to function as a fast proton conductor is an emerging strategy in the rapidly developing field of proton ceramic fuel cells (PCFCs). The key challenge for PCFC researchers is to formulate the proton-conducting electrolyte with conductivity above 0.1 siemens per centimeter at low temperatures (300 to 600°C). Here we present a methodology to design an enhanced proton conductor by means of a Na _x CoO₂/CeO₂ semiconductor heterostructure, in which a field-induced metallic state at the interface accelerates proton transport. We developed a PCFC with an ionic conductivity of 0.30 siemens per centimeter and a power output of 1 watt per square centimeter at 520°C. Through our semiconductor heterostructure approach, our results provide insight into the proton transport mechanism, which may also improve ionic transport in other energy applications.

Machine Learning Glove Using Self-Powered Conductive Superhydrophobic Triboelectric Textile for Gesture Recognition in VR/AR Applications

The rapid progress of Internet of things (IoT) technology raises an imperative demand on human machine interfaces (HMIs) which provide a critical linkage between human and machines. Using a glove as an intuitive and low-cost HMI can expediently track the motions of human fingers, resulting in a straightforward communication media of human-machine interactions. When combining several triboelectric textile sensors and proper machine learning technique, it has great potential to realize complex gesture recognition with the minimalist-designed glove for the comprehensive control in both real and virtual space. However, humidity or sweat may negatively affect the triboelectric output as well as the textile itself. Hence, in this work, a facile carbon nanotubes/thermoplastic elastomer (CNTs/TPE) coating approach is investigated in detail to achieve superhydrophobicity of the triboelectric textile for performance improvement. With great energy harvesting and human motion sensing capabilities, the glove using the superhydrophobic textile realizes a low-cost and self-powered interface for gesture recognition. By leveraging machine learning technology, various gesture recognition tasks are done in real time by using gestures to achieve highly accurate virtual reality/augmented reality (VR/AR) controls including gun shooting, baseball pitching, and flower arrangement, with minimized effect from sweat during operation.

[Comparisons of clinical characteristics and prognosis between patients with primary and secondary thyroid lymphoma]

Objective: To compare clinical characteristics and prognosis between patients with primary (PTL) and secondary thyroid lymphoma (STL) . Methods: A retrospective analysis was performed on 46 patients with thyroid lymphoma (PTL 19, STL 27) from January 2002 to October 2018. Results: ①PTL group included 4 males and 15 females, with a median age of 57 years. The STL group included 10 males and 17 females, with a median age of 61 years. Diffuse large B-cell lymphoma (DLBCL) was the main pathological subtype in both PTL and STL groups, with 14 cases (73.7%) and 20 cases (74.1%) respectively. In terms of clinical manifestations, goiter was the most common symptom in PTL patients 100.0% (19/19) , while 29.6% (8/27) STL had goiter (P<0.001) . The incidences of increased thyroglobulin antibody (TRAb) /thyroid peroxidase antibody (TPO) were 81.3% (13/16) in PTL group and 43.8% (7/16) in STL group (P=0.028) respectively. Concerning the clinical features of patients, only two PTL patients (10.5%) with advanced Ann Arbor stage (Ⅲ/Ⅳ) , while 21 (77.8%) STL experienced advanced Ann Arbor stage (P<0.001) . Elevated serum β(2)-MG were appeared in 1 (7.1%) PTL and 9 (47.4%) STL patients (P=0.013) , and advanced IPI score (3-5) was more common in STL than PTL (59.3% vs 5.3%, P<0.001) . ②Among the 17 PTL patients who received treatments, 15 (88.2%) achieved remission; as for STL patients received treatments, 23/25 (92.0%) were in remission. The 5-year overall survival (OS) rates of PTL (n=17) and STL groups (n=25) were (87.4±8.4) % and (70.0±13.1) % (P=0.433) respectively. ③The 5-year OS rate in 41 patients with B-cell thyroid lymphoma was (81.1±7.5) %. Univariate analysis showed that IPI score of 3-5 (P=0.040) and high level of serum IL-8 (P=0.022) were significantly associated with poor outcome. Conclusion: DLBCL was the most common subtype in both PTL and STL, and goiter was the major symptom in PTL. IPI score of 3-5 and high level of serum IL-8 were unfavorable prognostic factors for patients with B-cell thyroid lymphoma.

Haptic-feedback smart glove as a creative human-machine interface (HMI) for virtual/augmented reality applications

Human-machine interfaces (HMIs) experience increasing requirements for intuitive and effective manipulation. Current commercialized solutions of glove-based HMI are limited by either detectable motions or the huge cost on fabrication, energy, and computing power. We propose the haptic-feedback smart glove with triboelectric-based finger bending sensors, palm sliding sensor, and piezoelectric mechanical stimulators. The detection of multidirectional bending and sliding events is demonstrated in virtual space using the self-generated triboelectric signals for various degrees of freedom on human hand. We also perform haptic mechanical stimulation via piezoelectric chips to realize the augmented HMI. The smart glove achieves object recognition using machine learning technique, with an accuracy of 96%. Through the integrated demonstration of multidimensional manipulation, haptic feedback, and AI-based object recognition, our glove reveals its potential as a promising solution for low-cost and advanced human-machine interaction, which can benefit diversified areas, including entertainment, home healthcare, sports training, and medical industry.

[Analysis of selective endoscopy results during the epidemic of coronavirus disease 2019 (COVID-19)]

Objective: To explore the necessity and safety of selective endoscopy to detect gastrointestinal (GI) malignancy during the outbreak of coronavirus disease 2019 (COVID-19). Methods: A retrospective cohort study was carried out to analyze the clinical data of selective endoscopy performed at the Endoscopic Center, Zhongshan Hospital of Fudan University from February 20 to March 6, 2020. Clinical data included epidemiological questionnaire, chief complaints, endoscopic findings and biopsy pathology results, etc. All medical staff had blood test for IgM/IgG antibodies of COVID-19. Patients and their families were followed up by phone to determine whether they were infected with COVID-19. Meanwhile, the clinical data of selective endoscopy during the same period from February 20 to March 6, 2019 were collected as the control group to compare the overall results of endoscopy examinations during the epidemic and the detection rate of GI malignancy. Results: A total of 911 patients underwent endoscopy in the epidemic period group, and a total of 5746 cases in the control group, which was 6.3 times over the epidemic period group. In the epidemic period group, 544 cases received gastroscopy and 367 cases received colonoscopy, while 3433 cases received gastroscopy and 2313 cases received colonoscopy in the control group, which were both 6.3 times of epidemic period group. Gastroscopy revealed that 39 patients (7.2%) were diagnosed with upper GI malignancies in the epidemic period group and 77 patients (2.2%) in the control group with significant difference (χ(2)=40.243, P<0.001). The detection rate of gastric cancer in these two groups was 3.3% (n=18) and 1.7% (n=59) respectively with significant difference (χ(2)=6.254,P=0.012). The detection rate of esophageal cancer was 3.7% (n=20) and 0.5% (n=18) respectively with significant difference (χ(2)=49.303,P<0.001). Colonoscopy revealed that colorectal cancer was found in 32 cases (8.7%) of the epidemic period group and 88 cases (3.8%) of the control group with significant difference (χ(2)=17.888, P<0.001). During the epidemic period, no infection of medical staff was found through the blood test of IgM/IgG antibodies on COVID-19. No patient and family members were infected with COVID-19 by phone follow-up. Conclusion: Compared with the same period in 2019, the number of selective endoscopy decreases sharply during the epidemic period, while the detection rate of various GI malignant tumors increases significantly, which indicates that patients with high-risk symptoms of GI malignancies should still receive endoscopy as soon as possible. Provided strict adherence to the epidemic prevention standards formulated by the state and professional societies, it is necessary to carry out clinical diagnosis and treatment as soon as possible.