[Sources, Disposal Technologies, and Environmental Impact of Photopolymerization-based 3D Printing Plastic Waste].

In the 3D printing industry, photopolymerization-based 3D printing is considered to have the characteristics of high printing accuracy and mature technology. Therefore, it is of wide concern in industrial application and academic research. With the rapid development of photopolymerization-based technology, photopolymerization-based plastic waste will inevitably be produced in the process of product manufacturing and use. This kind of plastic waste is a new type of organic solid waste with an incalculable growth rate, and its impact on the environment is difficult to predict. Based on available research results, the latest research progress of sources, disposal technologies, and environmental impact of photopolymerization-based plastic waste were summarized and analyzed. The results revealed that the photopolymerization-based plastic waste was covalently crosslinked with thermosetting plastic. It had relatively higher activation energy and photo-sensitive chromogenic groups. There were some potential hazards to the environment and biosome caused by the raw material, printing process, and waste disposal process of photopolymerization-based plastic. Therefore, prospects and suggestions were proposed for the possibility of future disposal of photopolymerization-based plastic waste, in order to provide a reference for developing the photopolymerization-based 3D printing industry.

Alginate hydrogels containing different concentrations of magnesium-containing poly(lactic-co-glycolic acid) microspheres for bone tissue engineering.

The easy loss of crosslinking ions in alginate can result in structural collapse and loss of its characteristics as a bone scaffold. A novel injectable tissue engineering scaffold containing poly(lactic-co-glycolic acid) (PLGA) microspheres and alginate was fabricated to improve alginate's physiochemical and biological properties. MgCO3and MgO were loaded at a 1:1 ratio into PLGA microspheres to form biodegradable PLGA microspheres containing magnesium (PMg). Subsequently, different concentrations of PMg were mixed into a Ca2+suspension and employed as crosslinking agents for an alginate hydrogel. A pure Ca2+suspension was used as the alginate crosslinking agent in the control group. The influence of PMg on the physiochemical properties of the injectable scaffolds, including the surface morphology, degradation rate, Mg2+precipitation concentration, and the swelling rate, was investigated. MC3T3-E1 cells were seeded onto the hydrogels to evaluate the effect of the resultant alginate on osteoblastic attachment, proliferation, and differentiation. The physicochemical properties of the hydrogels, including morphology, degradation rate, and swelling ratio, were effectively tuned by PMg. Inductively coupled plasma-optical emission spectroscopy results showed that, in contrast to those in pure PMg, the magnesium ions (Mg2+) in alginate hydrogel containing PMg microspheres (Alg-PMg) were released in a dose-dependent and slow-releasing manner. Additionally, Alg-PMg with an appropriate concentration of PMg not only improved cell attachment and proliferation but also upregulated alkaline phosphatase activity, gene expression of osteogenic markers, and related growth factors. These findings indicate that PMg incorporation can regulate the physicochemical properties of alginate hydrogels. The resultant hydrogel promoted cell attachment, matrix mineralization, and bone regeneration. The hydrogel described in this study can be considered a promising injectable scaffold for bone tissue engineering.

The complete chloroplast genome of Elsholtzia fruticosa (D. Don) Rehd. (Labiatae), an ornamental plant with high medicinal value.

Elsholtzia fruticosa is an ornamental plant with high medicinal value. In this study, we sequenced and analyzed the complete chloroplast (cp) genome of the species. The complete cp sequence is 151,550 bp, including the large single-copy (LSC) region of 82,778 bp, the small single-copy (SSC) region of 17,492 bp, and a pair of invert repeats (IRs) regions of 25,640 bp. It encodes 132 unique genes in total, including 87 protein-coding genes, 37 transfer RNA genes (tRNAs), and eight ribosomal RNA genes (rRNAs). The comparative analysis of complete cp genomes showed that the genomic structure and gene order of E. fruticosa cps were conserved. The sequences of rps15, rps19, ycf1, ycf3, ycf15, psbL, psaI, trnG-UCC, trnS-GCU, trnR-UCU, trnL-UAG, trnP-UG, and trnL-UAA serve as hotspots for developing the DNA barcoding of Elsholtzia species. There are 49 SSR loci in the cp genome of E. fruticosa, among which the repeat numbers of mononucleotide, dinucleotide, trinucleotide, tetranucleotide, and pentanucleotides SSR are 37, 9, 3, 0, and 0, respectively. A total of 50 repeats were detected, including 15 forward repeats, seven reverse repeats, 26 palindromic repeats, and two complementary repeats. Phylogenetic analysis based on the complete cp genome and protein-coding DNA sequences of 26 plants indicates that E. fruticosa has a dose relationship with E. splendens and E. byeonsanensis.

Sustainable finance and renewable energy: Promoters of carbon neutrality in the United States.

This investigation explores whether sustainable finance and renewable energy could facilitate U.S. carbon neutrality. We perform the time-varying parameter-stochastic volatility-vector auto-regression (TVP-SV-VAR) model to obtain the changing relations among U.S. sustainable finance (SF), renewable energy (RE) and carbon dioxide emission (CO2). The empirical outcomes reveal a short-term negative effect from RE to CO2, indicating that renewable energy consumption could promote U.S. carbon neutrality. This effect is asymmetrical, and it could be observed that RE increase has a greater effect on CO2 than RE reduction. Also, the development of sustainable finance could facilitate U.S. carbon neutrality, and the direct impact is longer and more significant than RE, but the indirect effect of SF on CO2 by influencing RE is hysteretic. Besides, the asymmetric effect reveals that the negative direct impact of SF increase on CO2 is smaller than SF reduction, and the latter's indirect effect is more rapid than the former. Against the backdrop of global warming and frequent extreme weather, the above conclusions have meaningful practical applications for the U.S. to achieve carbon neutrality targets through developing sustainable finance and renewable energy.

Maximum Entropy Principle Underlies Wiring Length Distribution in Brain Networks.

A brain network comprises a substantial amount of short-range connections with an admixture of long-range connections. The portion of long-range connections in brain networks is observed to be quantitatively dissimilar across species. It is hypothesized that the length of connections is constrained by the spatial embedding of brain networks, yet fundamental principles that underlie the wiring length distribution remain unclear. By quantifying the structural diversity of a brain network using Shannon's entropy, here we show that the wiring length distribution across multiple species-including Drosophila, mouse, macaque, human, and C. elegans-follows the maximum entropy principle (MAP) under the constraints of limited wiring material and the spatial locations of brain areas or neurons. In addition, by considering stochastic axonal growth, we propose a network formation process capable of reproducing wiring length distributions of the 5 species, thereby implementing MAP in a biologically plausible manner. We further develop a generative model incorporating MAP, and show that, for the 5 species, the generated network exhibits high similarity to the real network. Our work indicates that the brain connectivity evolves to be structurally diversified by maximizing entropy to support efficient interareal communication, providing a potential organizational principle of brain networks.

Predictive coding models for pain perception.

Pain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats-two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further use predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a phenomenological predictive coding model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a biophysical neural mass model to describe the mesoscopic neural dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new prediction about the impact of the model parameters on the physiological or behavioral read-out-thereby yielding mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.

A Predictive Coding Model for Evoked and Spontaneous Pain Perception.

Pain is a complex multidimensional experience, and pain perception is still incompletely understood. Here we combine animal behavior, electrophysiology, and computer modeling to dissect mechanisms of evoked and spontaneous pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC) of freely behaving rats during pain episodes, and develop a predictive coding model to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Our preliminary results from computational simulations support the experimental findings and provide new predictions.

A New Theory for Acupuncture: Promoting Robust Regulation.

Robustness, an ability of biological networks to uphold their functionalities in the face of perturbations, is a key characteristic of all living systems. Acupuncture is a procedure in which fine needles are inserted into an individual at discrete points and then manipulated, with the intent of preventing and curing diseases. Acupuncture does not directly eliminate pathogenic factors or pathological tissue; rather, acupuncture enhances the ability of the human body to self-medicate itself by activating complex regulatory systems and by maintaining physiological homeostasis to prevent or treat diseases. From this point of view, the effect of acupuncture on the human body is more likely a kind of regulation to promote robustness. That is to say, acupuncture has the ability to promote robustness. In this article, we review the properties and functions of acupuncture in preventing and treating diseases and in maintaining health by enhancing robustness.

[The placebo effects of acupuncture and moxibustion].

The role of placebo effect in acupuncture and moxibustion efficacy was explored. Through the analysis of multiple factors including trust, expectation, understanding, doctor-patient relationship and social cultural environment, etc. in the literature at home and abroad, it was found the placebo effects, including patient's cognition, expectation, attention, preference and communication with doctor as well as doctor's suggestion, expectation and indirect regulation of diagnosis and treatment environment on patient's psychology, were essential factors for acupuncture efficacy. Therefore, it was concluded that the placebo effect was an inseparable part of acupuncture efficacy.