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We report on the fabrication of Cu2+-sensing thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) microgels labeled with metal-chelating acceptor and fluorescent reporter moieties. Cu2+ detection sensitivity can be considerably enhanced via thermo-induced collapse of the sensing matrix, which can easily optimize the relative spatial distribution of Cu2+-binding sites and fluorescence readout functionalities. A novel picolinamine-containing monomer with Cu2+-binding capability, N-(2-(2-oxo-2-(pyridine 2-yl-methylamino)ethylamino)ethyl)acrylamide (PyAM, 3), was synthesized at first. Nearly monodisperse Cu2+-sensing microgels were prepared via emulsion polymerization of N-isopropylacrylamide (NIPAM) in the presence of a nonionic surfactant, N,N'-Methylene-bis(acrylamide) (BIS), PyAM (3), and fluorescent dansylaminoethyl- acrylamide (DAEAM, 5) monomers at around neutral pH and 70 degrees C. At 20 degrees C, as-synthesized microgels in their swollen state can selectively bind Cu2+ over other metal ions (Hg2+, Mg2+, Zn2+, Pb2+, Ag+, and Al3+), leading to prominent quenching of fluorescence emission intensity. Above the volume phase transition temperature, P(NIPAM-co-PyAM-co-DAEAM) microgels exhibit increased fluorescence intensity. It was observed that Cu2+ detection sensitivity can be dramatically enhanced via thermo-induced microgel collapse at elevated temperatures. At a microgel concentration of 3.0x10(-6) g/mL, the detection limit drastically improved from approximately 46 nM at 20 degrees C to approximately 8 nM at 45 degrees C. The underlying mechanism for this novel type of sensor with thermotunable detection sensitivity was tentatively proposed.

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Breast cancer is a heterogeneous disease with increasing incidence and mortality and represents one of the most common cancer types worldwide. Low-density lipoprotein (LDL) is a complex particle composed of several proteins and lipids, which carries cholesterol into peripheral tissues and also affects the metabolism of fatty acids. Recent reports have indicated an emerging role of LDL in breast cancer, affecting cell proliferation and migration, thereby facilitating disease progression. However, controversy still exists among distinct types of breast cancer that can be affected by LDL. Classical therapeutic approaches, such as radiotherapy, chemotherapy, and lipid-lowering drugs were also reported as affecting LDL metabolism and content in breast cancer patients. Therefore, in this review we summarized and discussed the role of LDL in the development and treatment of breast cancer.

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Because of their locality preservation properties, Space-Filling Curves (SFC) have been widely used in massive point dataset management. However, the completeness, universality, and scalability of current SFC implementations are still not well resolved. To address this problem, a generic n-dimensional (nD) SFC library is proposed and validated in massive multiscale nD points management. The library supports two well-known types of SFCs (Morton and Hilbert) with an object-oriented design, and provides common interfaces for encoding, decoding, and nD box query. Parallel implementation permits effective exploitation of underlying multicore resources. During massive point cloud management, all xyz points are attached an additional random level of detail (LOD) value l. A unique 4D SFC key is generated from each xyzl with this library, and then only the keys are stored as flat records in an Oracle Index Organized Table (IOT). The key-only schema benefits both data compression and multiscale clustering. Experiments show that the proposed nD SFC library provides complete functions and robust scalability for massive points management. When loading 23 billion Light Detection and Ranging (LiDAR) points into an Oracle database, the parallel mode takes about 10 h and the loading speed is estimated four times faster than sequential loading. Furthermore, 4D queries using the Hilbert keys take about 1~5 s and scale well with the dataset size.

Background: Knee osteoarthritis (KOA) is more common in middle-aged and elderly people, and seriously affects the quality of life of those affected. Traditional Chinese medicine (TCM) treatment of KOA has been widely recognized. In recent years, warm needling acupuncture (WNA) has been used to treat KOA and has achieved good results. However, there is a lack of comparison of the efficacy of WNA and other TCM treatments for KOA.Methods: We conducted a search for reports of WNA and/or TCM treatment of KOA in English-and Chinese-language databases. The data was retrieved from inception of the database until October 2021. The Cochrane risk of bias tool was used to evaluate the quality of the included studies, and the network metaanalysis was performed using the software RevMan 5.20.Results: A total of 8 articles met the inclusion criteria, including 399 patients treated with WNA (WNA group), and 396 patients treated with other TCM (TCM group). The results of meta-analysis showed that compared with patients in the TCM group, the effective rate [relative risk (RR)] was 1.18, 95% confidence interval (CI): 1.06 to 1.33, the last follow-up osteoarthritis index [mean difference (MD)] was −6.93, 95% CI: −12.14 to −1.72, and the last follow-up knee pain visual analogue scale (VAS) MD was −1.06, 95% CI: −1.61 to −0.51, which were all statistically significant. However, the difference in daily activities (MD: −4.31, 95% CI: −10.90 to 2.28) was not statistically significant.Discussion: Compared with other TCM treatments for KOA, WNA has better overall patient efficacy. However, further randomized controlled studies are needed to compare WNA and other TCM treatments individually to confirm the efficacy of WNA.