RADICAL POLYMERIZATION: CHEMISTRIES, APPLICATIONS, DEVELOPMENTS, AND PERSPECTIVES

Radical polymerization is one of most versatile and easily implemented chain-growth polymerization methods for obtaining polymers, copolymers and polymer composites. As a synthetic process with over seventy years of investigation, it has enabled the production of materials that enriched the daily lives of humankind. The polymerization mechanism involves the fundamental steps of initiation, propagation, and termination events. This radical-based synthetic route provides many advantages, such as the reaction conditions are usually not as demanding as ionic and coordination-insertion polymerizations regarding the tolerance of water, chemical functionalities and impurities. This polymerization technique can be applied to a wide variety of monomers. The major challenge during the early development of controlled radical polymerization resulted from the presence of radical combination, atom transfer and abstraction reactions, which bring difficulties in understanding polymerization kinetics and achieving well-defined polymer structures. Thereby, industrial and academic effort has been focusing on developing techniques that offered the prospect of control over radical polymerization. The seeds were laid for the major growth of controlled radical polymerization techniques in the 1990s. These approaches allow for the facile production of polymer architectures with complexities, from simple chains with narrow dispersity to di-block, tri-block and multi-block copolymers. In Chapters 2 and 4 of this dissertation, radical addition fragmentation chain transfer (RAFT) polymerization was utilized to investigated well-defined polymer structures, enabling subsequent structure-property relationship investigations of polyelectrolyte solutions and multi-block copolymer membranes. In Chapter 3, nitroxide mediated polymerization (NMP) was performed to prepare polyisoprene that was successfully chain extended with chloromethyl styrene. The resulting diblock copolymer was quaternized for ionomer preparation. The analysis of their bulk as well as surface morphology was investigated. Cyclic ketene acetals (CKA) can be polymerized through concomitant radical rearrangement and ring-opening mechanisms, to yield ester-based scission points on the resultant polymer backbone. An aliphatic and an aromatic CKAs were investigated in Chapter 5 to develop a fundamental understanding of CKA radical-mediated polymerization and charge transfer as a main competitive reaction. Chapter 6 concludes on the areas of research and development that I believe will lead to further progress in the future

Insulin Attenuates Beta-Amyloid-Associated Insulin/Akt/EAAT Signaling Perturbations in Human Astrocytes

The excitatory amino acid transporters 1 and 2 (EAAT1 and EAAT2), mostly located on astrocytes, are the main mediators for glutamate clearance in humans. Malfunctions of these transporters may lead to excessive glutamate accumulation and subsequent excitotoxicity to neurons, which has been implicated in many kinds of neurodegenerative disorders including Alzheimer’s disease (AD). Yet, the specific mechanism of the glutamate system dysregulation remains vague. To explore whether the insulin/protein kinase B (Akt)/EAAT signaling in human astrocytes could be disturbed by beta-amyloid protein (Aβ) and be protected by insulin, we incubated HA-1800 cells with varying concentrations of Aβ1–42 oligomers and insulin. Then the alterations of several key substrates in this signal transduction pathway were determined. Our results showed that expressions of insulin receptor, phospho-insulin receptor, phospho-protein kinase B, phospho-mammalian target of rapamycin, and EAAT1 and EAAT2 were decreased by the Aβ1–42 oligomers in a dose-dependent manner (p 0.05), and the mRNA levels of EAAT1 and EAAT2 were also unchanged (p > 0.05). Taken together, this study indicates that Aβ1–42 oligomers could cause disturbances in insulin/Akt/EAAT signaling in astrocytes, which might be responsible for AD onset and progression. Additionally, insulin can exert protective functions to the brain by modulating protein modifications or expressions

Probabilistic Constellation Shaping for OFDM-Based ISAC Signaling

Integrated Sensing and Communications (ISAC) has garnered significant attention as a promising technology for the upcoming sixth-generation wireless communication systems (6G). In pursuit of this goal, a common strategy is that a unified waveform, such as Orthogonal Frequency Division Multiplexing (OFDM), should serve dual-functional roles by enabling simultaneous sensing and communications (S&C) operations. However, the sensing performance of an OFDM communication signal is substantially affected by the randomness of the data symbols mapped from bit streams. Therefore, achieving a balance between preserving communication capability (i.e., the randomness) while improving sensing performance remains a challenging task. To cope with this issue, in this paper we analyze the ambiguity function of the OFDM communication signal modulated by random data. Subsequently, a probabilistic constellation shaping (PCS) method is proposed to devise the probability distributions of constellation points, which is able to strike a scalable S&C tradeoff of the random transmitted signal. Finally, the superiority of the proposed PCS method over conventional uniformly distributed constellations is validated through numerical simulations

GainNet: Coordinates the Odd Couple of Generative AI and 6G Networks

The rapid expansion of AI-generated content (AIGC) reflects the iteration from assistive AI towards generative AI (GAI) with creativity. Meanwhile, the 6G networks will also evolve from the Internet-of-everything to the Internet-of-intelligence with hybrid heterogeneous network architectures. In the future, the interplay between GAI and the 6G will lead to new opportunities, where GAI can learn the knowledge of personalized data from the massive connected 6G end devices, while GAI's powerful generation ability can provide advanced network solutions for 6G network and provide 6G end devices with various AIGC services. However, they seem to be an odd couple, due to the contradiction of data and resources. To achieve a better-coordinated interplay between GAI and 6G, the GAI-native networks (GainNet), a GAI-oriented collaborative cloud-edge-end intelligence framework, is proposed in this paper. By deeply integrating GAI with 6G network design, GainNet realizes the positive closed-loop knowledge flow and sustainable-evolution GAI model optimization. On this basis, the GAI-oriented generic resource orchestration mechanism with integrated sensing, communication, and computing (GaiRom-ISCC) is proposed to guarantee the efficient operation of GainNet. Two simple case studies demonstrate the effectiveness and robustness of the proposed schemes. Finally, we envision the key challenges and future directions concerning the interplay between GAI models and 6G networks.Comment: 10 pages, 5 figures, 1 tabl

Comparing glycemic traits in defining diabetes among rural Chinese older adults

The protocol of MIND-China was registered in the Chinese Clinical Trial Registry (ChiCTR, www.chictr.org.cn; registration no.: ChiCTR1800017758).Background: We sought to identify the optimal cut-off of glycated hemoglobin (HbA1c) for defining diabetes and to assess the agreements of fasting plasma glucose (FPG), fasting serum glucose (FSG), and HbA1c in defining diabetes among rural older adults in China. Methods: This population-based cross-sectional study included 3547 participants (age ≥61 years, 57.8% women) from the Multidomain Interventions to Delay Dementia and Disability in Rural China from 2018-2019; of these, 3122 had no previously diagnosed diabetes. We identified the optimal cut-off of HbA1c against FPG ≥7.0 mmol/L for defining diabetes by using receiver operating characteristic curve and Youden index. The agreements of FPG, FSG, and HbA1c in defining diabetes were assessed using kappa statistics. Results: Among participants without previously diagnosed diabetes (n = 3122), the optimal HbA1c cut-off for defining diabetes was 6.5% (48 mmol/mol), with the sensitivity of 88.9%, specificity of 93.7%, and Youden index of 0.825. The correlation coefficients were 0.845 between FPG and FSG, 0.574 between FPG and HbA1c, and 0.529 between FSG and HbA1c in the total sample (n = 3547). The kappa statistic for defining diabetes was 0.962 between FSG and FPG, and 0.812 between HbA1c and FPG. Conclusions: The optimal cut-off of HbA1c for diagnosing diabetes against FPG >7.0 mmol/L is ≥6.5% in Chinese rural-dwelling older adults. The agreement in defining diabetes using FPG, FSG, and HbA1c is nearly perfect. These results have relevant implications for diabetes research and clinical practice among older adults in China. Clinical trial registration: The protocol of MIND-China was registered in the Chinese Clinical Trial Registry (ChiCTR, www.chictr.org.cn; registration no.: ChiCTR1800017758).Y Du was supported by the major grant from the National Key R&D Program of the Ministry of Sciences and Technology of China (Grant No.: 2017YFC1310100) and by additional grants from the National Nature Science Foundation of China (Grants No.: 81861138008 and 82011530139), the Academic Promotion Program of Shandong First Medical University (2019QL020), and the Taishan Scholar Program of Shandong Province, China (Tsqn201909182). C Qiu received grants from the Swedish Research Council (Grants No.: 2017-05819 and 2020-01574), the Swedish Foundation for International Cooperation in Research and Higher Education (STINT) (Grant No.: CH2019-8320) for the Joint China-Sweden Mobility program, and the Karolinska Institutet, Stockholm, Sweden. The funding agency had no role in the study design, data collection and analysis, the writing of this manuscript, and in the decision to submit the work for publication.S