Controlled gene/drug delivery via triggerable liposomes for triple negative breast cancer treatment

Triple negative breast cancer (TNBC) is a highly aggressive breast cancers with highest mortality rate and poorest outcomes. The challenges of TNBC treatment are rooted in lack of estrogen receptors (ER), progesterone receptors (PR), and human epidermal growth factor 2 (HER2), resulting endocrine therapy or receptors targeted therapies are not effective against TNBC. Clustered regularly interspaced short palindromic repeat-associated protein 9 (CRISPR/Cas9)-based gene therapy is a revolutionary strategy for TNBC treatment, while its clinical applications are limited by lack of safe and efficient non-viral delivery system. In this thesis, we developed light triggerable liposomes mediated CRISPR/Cas9 delivery for TNBC treatment. CRISPR/Cas9 was loaded inside liposomes with encapsulation efficiency higher than 70%. FDA-approved photosensitiser (PS) verteporfin was used to produce reactive oxygen species (ROS) when it was activated by external light, leading to liposome membrane destruction and thus release of CRISPR/Cas9 in cells. The knockdown of A20 gene-Exon3 by CRISPR/Cas9 in TNBC cells significantly supressed the cell proliferation and migration in vitro. CRISPR/Cas9-based gene editing via light triggerable liposomes with spatial and temporal control provides a promising option for TNBC treatment. The application of triggerable liposomes can be extended to deep tissue therapy by using X-ray as external stimuli. PS in liposomes not only works for liposome rupture, but also serves as photodynamic therapy (PDT) reagent to induce cell death through extensive ROS generation. X‑ray induced photodynamic therapy (X-PDT) via protoporphyrin IX (PPIX) & perfluorooctyl bromide (PFOB) co-loaded liposomes for in vitro TNBC treatment was developed. Relief of hypoxia in cancer cells by addition of PFOB improved ROS production with 4.9-fold of PPIX under 2Gy radiation and it turned out to induce 17% increase in cell death through either apoptosis or necrosis pathway. These findings in this thesis suggest that developed intelligent triggerable liposomes are superior to deliver CRISPR/Cas9 or photosensitisers efficiently for TNBC treatment. Future works were prospected to combine CRISPR/Cas9 gene editing with X-PDT via triggerable liposomes to achieve precise synthetic therapy

A Novel Nanowire Assembly Process for the Fabrication of CO Sensor

Nanowires have been widely studied due to their outstanding mechanical and electrical properties; however, their practical applications are limited to the lack of an effective technique for controlled assembly. In the present work, zinc oxide (ZnO) nanowire arrays were assembled via a combing process using a makeup brush and the nanodevice was fabricated. The current–voltage (I–V) and ultraviolet (UV) characteristics of the device indicate stable and repeatable electrical properties. The carbon monoxide (CO) sensing properties were tested at operating temperatures of 200, 300 and 400 °C. It was found that ZnO based sensor exhibited the highest sensitivity to CO at 300 °C due to the change of dominant oxygen species. Comparing with others result, the sensitivity of the fabricated sensor exhibits higher sensing performance. The sensing mechanism of the CO sensor is also discussed

A Sensing Peak Identification Method for Fiber Extrinsic Fabry–Perot Interferometric Refractive Index Sensing

A novel sensing peak identification method for high accuracy refractive index (RI) sensing is proposed. The implementation takes the intensity of interference maximum as the characteristic to distinguish interference peaks, tracking the sensing peak continually during a RI changes, with high measurement accuracy and simple computation. To verify the effect of the method, the extrinsic Fabry–Perot interferometer (EFPI) sensor has been fabricated using the large lateral offset splicing technique. In the RI range from 1.346 to 1.388, the measurement range of the EFPI with the proposed method reaches at least 6 times larger than that of EFPI with the wavelength tracking method and the largest measurement error is −4.47 × 10−4. The EFPI refractive index (RI) sensor identified the sensing peak is believed to play an important role in RI, concentration and density sensing, etc., for superior performance

Divergence of Desiccation-Related Traits in Sitobion avenae from Northwestern China

The impact of drought on insects has become increasingly evident in the context of global climate change, but the physiological mechanisms of aphids’ responses to desiccating environments are still not well understood. We sampled the wheat aphid Sitobion avenae (Fabricius) (Hemiptera: Aphididae) from arid areas of northwestern China. Both desiccation-resistant and -nonresistant genotypes were identified, providing direct evidence of genetic divergence in desiccation resistance of S. avenae. Resistant genotypes of wingless S. avenae showed longer survival time and LT50 under the desiccation stress (i.e., 10% relative humidity) than nonresistant genotypes, and wingless individuals tended to have higher desiccation resistance than winged ones. Both absolute and relative water contents did not differ between the two kinds of genotypes. Resistant genotypes had lower water loss rates than nonresistant genotypes for both winged and wingless individuals, suggesting that modulation of water loss rates could be the primary strategy in resistance of this aphid against desiccation stress. Contents of cuticular hydrocarbons (CHC) (especially methyl-branched alkanes) showed significant increase for both resistant and nonresistant genotypes after exposure to the desiccation stress for 24 h. Under desiccation stress, survival time was positively correlated with contents of methyl-branched alkanes for resistant genotypes. Thus, the content of methyl-branched alkanes and their high plasticity could be closely linked to water loss rate and desiccation resistance in S. avenae. Our results provide insights into fundamental aspects and underlying mechanisms of desiccation resistance in aphids, and have significant implications for the evolution of aphid populations in the context of global warming

Semi-quantitative risk assessment on Listeria monocytogenes in retail Chinese salads for Shanghai residents

Objective To elucidate the prevalence of Listeria monocytogenes in Chinese salads in Shanghai, and to explore measures that can avoid cross-contamination and reduce the risk of infection caused by L. monocytogenes in salads. Methods Health risk and the influencing factors were estimated using a swift quantitative microbiological risk assessment (sQMRA) method with the prevalence of L. monocytogenes in Chinese salads collected from retail market in Shanghai, dietary consumption data and experimental data. Results The detection rate of L. monocytogenes in retail salads in Shanghai was 3.97% (6/151), the average concentration in contaminated samples was 60.53 CFU/g. For sensitive and non-sensitive people, the estimated incidence of nine different scenarios were 2.36×10-4-3.49×10-4 and 2.36×10-6-3.49×10-6, respectively, and the estimated cases were 162-431 and 6-17. Containers of different materials had different influence on the cross-contamination parameters of L. monocytogenes. The cross-contamination of the glass container was relatively high, and the estimated cases were the lowest. The cross-contamination parameters and ingestion of the ceramic containers were both low, and the estimated cases were the highest. After washing with sterile water or cleanser essence of the glass container and ceramic container, the estimated cases of L. monocytogenes infection were significantly reduced. Conclusion There was a certain risk of the contamination of L. monocytogenes in Chinese salads in Shanghai. Using glass containers and adopting cleaning measures could significantly reduce the number of cases of L. monocytogenes infection caused by cross-contamination during the preparation of Chinese salads in the kitchen

Delay and Energy-Efficiency-Balanced Task Offloading for Electric Internet of Things

With the development of the smart grid, massive electric Internet of Things (EIoT) devices are deployed to collect data and offload them to edge servers for processing. However, the task of offloading optimization still faces several challenges, such as the differentiated quality of service (QoS) requirements, decision coupling among multiple devices, and the impact of electromagnetic interference. In this paper, a low-complexity delay and energy-efficiency-balanced task offloading algorithm based on many-to-one two-sided matching is proposed for an EIoT. The proposed algorithm shows its novelty in the dynamic tradeoff between energy efficiency and delay as well as in low-complexity and stable task offloading. Specifically, we firstly formulate the minimization problem of weighted difference between delay and energy efficiency to realize the joint optimization of differentiated QoS requirements. Then, the joint optimization problem is transformed into a many-to-one two-sided matching problem. Through continuous iteration, a stable matching between devices and servers is established to cope with decision coupling among multiple devices. Finally, the effectiveness of the proposed algorithm is validated through simulations. Compared with two advanced algorithms, the weighted difference between the energy efficiency and delay of the proposed algorithm is increased by 29.01% and 45.65% when the number of devices is 120, and is increased by 11.57% and 22.25% when the number of gateways is 16