Remote Tracking Gas Molecular via the Standalone-Like Nanosensor-Based Tele-Monitoring System

Remote tracking the variation of air quality in an effective way will be highly helpful to decrease the health risk of human short-and long-term exposures to air pollution.However,high power consumption and poor sensing performance remain the concerned issues,thereby limiting the scale-up in deploying air quality tracking networks.Herein,we report a standalone-like smart device that can remotely track the variation of air pollutants in a power-saving way.Brevity,the created smart device demonstrated satisfactory selectivity(against six kinds of representative exhaust gases or air pollutants),desirable response magnitude(164–100 ppm),and acceptable response/recovery rate(52.0/50.5 s),as well as linear response relationship to NO2.After aging for 2 weeks,the created device exhibited relatively stable sensing performance more than 3 months.Moreover,a photoluminescence-enhanced light fidelity(Li-Fi)telecommunication technique is proposed and the Li-Fi communication distance is significantly extended.Conclusively,our reported standalone-like smart device would sever as a powerful sensing platform to construct high-performance and low-power consumption air quality wireless sensor networks and to prevent air pollutant-induced diseases via a more effective and low-cost approach.

Metal-organic frameworks based surface-enhanced Raman spectroscopy technique for ultra-sensitive biomedical trace detection

Metal-organic frameworks(MOFs)have attracted widespread interest due to their unique and unprecedented advantages in microstructures and properties.Besides,surface-enhanced Raman scattering(SERS)technology has also rapidly developed into a powerful fingerprint spectroscopic technique that can provide rapid,non-invasive,non-destructive,and ultra-sensitive detection,even down to single molecular level.Consequently,a considerable amount of researchers combined MOFs with the SERS technique to further improve the sensing performance and broaden the applications of SERS substrates.Herein,representative synthesis strategies of MOFs to fabricate SERS-active substrates are summarized and their applications in ultra-sensitive biomedical trace detection are also reviewed.Besides,relative barriers,advantages,disadvantages,future trends,and prospects are particularly discussed to give guidance to relevant researchers.

Artificial intelligence in theranostics of gastric cancer, a review

Gastric cancer (GC) is one of the commonestcancers with high morbidity and mortality in the world.How to realize precise diagnosis and therapy of GC ownsgreat clinical requirement. In recent years, artificial intelligence (AI) has been actively explored to apply to earlydiagnosis and treatment and prognosis of gastric carcinoma. Herein, we review recent advance of AI in earlyscreening, diagnosis, therapy and prognosis of stomachcarcinoma. Especially AI combined with breath screeningearly GC system improved 97.4 % of early GC diagnosisratio, AI model on stomach cancer diagnosis system of salivabiomarkers obtained an overall accuracy of 97.18 %, speci-ficity of 97.44 %, and sensitivity of 96.88 %. We also discussconcept, issues, approaches and challenges of AI applied instomach cancer. This review provides a comprehensive viewand roadmap for readers working in this field, with the aimof pushing application of AI in theranostics of stomachcancer to increase the early discovery ratio and curativeratio of GC patients.