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The United Nations Agenda 2030 for Sustainable Development has induced the empirics to find the factors that can contribute to sustainable development. However, limited empirical evidence has estimated the impact of forest trade, bioenergy, and economic policy uncertainty on sustainable development. This study fills the gap by analyzing the impact of forest trade, bioenergy, and economic policy uncertainty on sustainable development in China and the USA using the ARDL and QARDL approaches. The findings of the ARDL model suggest that forest trade helps boost both short- and long-run sustainable development in China and the USA, while bioenergy fosters sustainable development in the short and long run only in China and in the USA, bioenergy improves sustainable development only in the long run. In contrast, economic policy uncertainty hurts sustainable development in the short and long run in China, while in the USA, only the long-run negative association between the two variables is observed. Thus, policymakers in China and the USA need to focus on enhancing trade in forest products, fostering bioenergy generation, and reducing uncertainties in economic policy to promote sustainable development.

Environmental sustainability is the primary objective of policymakers all around the globe. The most viable option to deal with this situation is to increase the use of renewable energy sources, particularly bioenergy, a carbon-neutral energy source. Trading activities in clean and green products can also enhance environmental performance. The literature on the impact of bioenergy and trade in environmental goods on ecological sustainability is growing. However, the empirical literature has not shed light on the impact of forest products trade (FPT) and rural bioenergy on environmental sustainability, leaving a significant gap in the literature. To address this gap, this analysis examines the impact of FPT and rural bioenergy on environmental sustainability using 23 economies from 2000 to 2022. Empirical estimates of the model are obtained by applying several estimation techniques, such as fixed effects (FE), random effects (RE), two-stage least squares (2SLS), generalized method of moments (GMM), and cross-sectional autoregressive distributed lag (CS-ARDL). The findings confirm that FPT and rural bioenergy reduce CO2 emissions and contribute to environmental sustainability. The estimates of control variables of economic growth, industrialization, technological development, urbanization, and financial development are positively significant, confirming that these factors increase carbon footprints and thus hurt environmental sustainability. In contrast, political stability negatively impacts carbon emissions and thus promotes environmental sustainability. In light of these findings, policymakers should encourage forest products trade and rural bioenergy to achieve environmental sustainability.

Background: The potential role of probiotics in mitigating hyperlipidemia has garnered increasing evidence, yet the specific mechanisms warrant further investigation. Objective: This study aimed to examine the alterations in short-chain fatty acids (SCFAs), a hypothesized lipid-lowering mechanism of probiotics, in animal models and to evaluate the lipid-lowering effects of probiotics on hyperlipidemic animal models through a meta-analysis of preclinical experiments. Methods: A comprehensive search of PubMed, Web of Science, EMBASE, Cochrane Library and Google Scholar up to June 2024 yielded nine studies that met the inclusion criteria (INPLASY registration number: No. CRD42024559937). Result: The analysis revealed that mice receiving probiotics exhibited a significant increase in SCFA levels compared with control mice (acetic acid: standard mean difference [SMD] = 1.26, 95% confidence interval [CI] 0.80 to 1.72, P

Objective: With the Polygonatum sibiricum as raw material, to develop a process for the combined extraction of Polygonatum sibiricum sponins (PSSs) and polysaccharides (PSPs), and the inhibitory activities of the extract and their complexes (PSSs-PSPs) on α-glucosidase and α-amylase were investigated. Methods: PSSs and PSPs were performed using ultrasound combined with enzymatic hydrolysis. The effects of solid-liquid ratio, ultrasonic time, and ultrasonic temperature on the yield of PSSs, the types of multi-enzymes, the proportion of complex enzymes, enzymolysis time, enzyme dosage, solid-liquid ratio, hot water extraction time, and hot water extraction temperature on the yield of PSPs were investigated, and the Box-Behnken experiment design was used to optimize the extraction of PSSs and PSPs. Results: The optimum extraction parameters of PSSs and PSPs were as follows: ultrasonic temperature was 50 ℃, ultrasonic time was 50 min, ultrasonic solid-liquid ratio was 1∶25 (g/mL), enzymolysis time was 2 h, enzyme dosage was 3 053 U/g, solid-liquid ratio was 1∶25 (g/mL), hot water extraction temperature was 80 ℃, and hot water extraction time was 1 h. Under the control of these conditions, the total yield of PSSs and PSPs was 12.22% and the 27.07%. The inhibitory activities of the extract and their complexes (PSSs-PSPs) on α-glucosidase and α-amylase were verified, and their complexes also have a good inhibitory effect on those enzymes. Conclusion: The process conditions for the efficient synergistic extraction of polygonatin and polysaccharide were obtained after optimization. Compared with a single component, the hypoglycemic activity of their complexes was improved.

[This corrects the article DOI: 10.1371/journal.pbio.3000324.].

There is a need to improve and expand mitochondrial base editing tools. Here the authors identify a DddA homolog from Simiaoa sunii (Ddd_Ss) which can efficiently deaminate cytosine in dsDNA; they develop cytosine base editors and introduce mutations at multiple mitochondrial DNA loci.

Background: To explore the correlation of pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) with the occurrence of birth defects. Methods: Clinical data of pregnant women were collected in Zhuzhou Central Hospital from January 2019 to December 2021. A total of 10,086 newborns, including 175 newborns with birth defects. Birth defect cases were identified, and 350 cases of pregnant women without birth defects were randomly selected as the control group by control case matching (1:2). Clinical baseline data were compared between the two groups, and logistic single-factor analysis was performed to examine the correlation between pre-pregnancy BMI, GWG, and birth defects. Results: The study consisted of a total of 175 cases of birth defects, including circulatory system 114 (65.14%) cases, musculoskeletal system 34 (19.43%) cases, urinary system 15 (8.57%) cases, and 12 (6.86%) cases of other birth defects. There were no statistical differences in parity between the two groups (p > 0.05). However, statistically significant differences were observed in maternal age, pre-pregnancy medication history, and the perinatal TORCH (Toxoplass, Other (Syphilis, Hepatitis B), Rubivirus, Cytomegalovirus, Herpesvirus) (p < 0.05). Logistic single-factor analysis revealed that the proportion of birth defects in obese women was significantly higher than that in the control group (5.14% vs. 1.14%, p = 0.013). In the birth defect group, the distribution of inadequate, appropriate, and excessive GWG was 9.71%, 34.86%, and 55.43%, respectively. However, no statistical differences were found in the types of birth defects based on maternal BMI and GWG. Conclusion: The primary focus on addressing birth defects should center around the prevention and control of congenital heart disease. Abnormal pre-pregnancy BMI is a risk factor for birth defects. Effective control of GWG contributes to preventing adverse outcomes in newborns. Therefore, both women of childbearing age and pregnant women need to pay attention to weight management.

Parkinson’s disease (PD), the second most common neurodegenerative disease worldwide, often occurs in middle-aged and elderly individuals. The pathogenesis of PD is complex and includes mitochondrial dysfunction, and oxidative stress. Recently, natural products with multiple structures and their bioactive components have become one of the most important resources for small molecule PD drug research targeting mitochondrial dysfunction. Multiple lines of studies have proven that natural products display ameliorative benefits in PD treatment by regulating mitochondrial dysfunction. Therefore, a comprehensive search of recent published articles between 2012 and 2022 in PubMed, Web of Science, Elesvier, Wliey and Springer was carried out, focusing on original publications related to natural products against PD by restoring mitochondrial dysfunction. This paper presented the mechanisms of various kinds of natural products on PD-related mitochondrial dysfunction regulation and provided evidence that natural products are promising to be developed as drugs for PD therapeutics.

Cancer is currently the most important problem endangering human health. As antitumor drugs have always been the most common methods for treating cancers, searching for new antitumor agents is of great significance. Brusatol, a quassinoid from the seeds of Brucea javanica, exhibits a potent tumor-suppressing effect with improved disease outcome. Studies have shown that brusatol not only shows potential tumor inhibition through multiple pharmacological effects, such as promoting apoptosis and inhibiting metastasis but also exhibits significant synergistic antitumor effects in combination with chemotherapeutic agents and overcoming chemical resistance in a wide range of cancer types. In this paper, the antitumor effects and mechanisms of brusatol were reviewed to provide evidence that brusatol has the exact antitumor efficacy of chemotherapeutic agents and show the potential of brusatol to be developed as a promising antitumor drug.

Cancer is still considered a “hopeless case”, which seriously endangers human health. Therefore, it is of great significance to research and develop novel anticancer drugs. Active natural products play an important role in anticancer drug discovery by providing lead compounds. Halofuginone (HF), as a derivative of febrifugine, an alkaloid originally isolated from the plant Dichroa febrifuga, is used for the prevention and treatment of coccidiosis and malaria in poultry. In recent years, HF has shown excellent anticancer activity and great clinical potential for treating various cancers. Despite enormous progress, a thorough elaboration of the proposed mechanism and mode of action is absent. Herein, we provide a comprehensive review of the most recent anticancer studies reported for HF and a rationale for further exploring the potential application of HF in overcoming cancer in the future.

Classical Hodgkin lymphoma (cHL) is the most common type of HL that occurs mainly in people aged between 15–30 and over 55 years. Although its general prognosis is favorable, 10%–30% of patients with cHL will ultimately develop relapsed or refractory disease (r/r cHL). Improving the cure rate of r/r cHL has proven to be challenging. Some novel agents, such as brentuximab vedotin and immune checkpoint inhibitors, which have been used in conventional regimens for patients with r/r cHL in the past decade, have been shown to have good curative effects. This paper reviews the conventional regimens for patients with r/r cHL and focuses on the newest clinical trials and treatment measures to prolong prognosis and reduce adverse events. The evaluation of prognosis plays a vital role in analyzing the risk of relapse or disease progression; thus, finding new predictive strategies may help treat patients with r/r cHL more efficaciously.

Schizophrenia is a serious mental illness characterized by a disconnection between brain regions. Transcranial magnetic stimulation is a non-invasive brain intervention technique that can be used as a new and safe treatment option for patients with schizophrenia with drug-refractory symptoms, such as negative symptoms and cognitive impairment. However, the therapeutic effects of transcranial magnetic stimulation remain unclear and would be investigated using non-invasive tools, such as functional connectivity (FC). A longitudinal design was adopted to investigate the alteration in FC dynamics using a dynamic functional connectivity (dFC) approach in patients with schizophrenia following high-frequency repeated transcranial magnetic stimulation (rTMS) with the target at the left dorsolateral prefrontal cortex (DLPFC). Two groups of schizophrenia inpatients were recruited. One group received a 4-week high-frequency rTMS together with antipsychotic drugs (TSZ, n = 27), while the other group only received antipsychotic drugs (DSZ, n = 26). Resting-state functional magnetic resonance imaging (fMRI) and psychiatric symptoms were obtained from the patients with schizophrenia twice at baseline (t1) and after 4-week treatment (t2). The dynamics was evaluated using voxel- and region-wise FC temporal variability resulting from fMRI data. The pattern classification technique was used to verify the clinical application value of FC temporal variability. For the voxel-wise FC temporary variability, the repeated measures ANCOVA analysis showed significant treatment × time interaction effects on the FC temporary variability between the left DLPFC and several regions, including the thalamus, cerebellum, precuneus, and precentral gyrus, which are mainly located within the cortico-thalamo-cerebellar circuit (CTCC). For the ROI-wise FC temporary variability, our results found a significant interaction effect on the FC among CTCC. rTMS intervention led to a reduced FC temporary variability. In addition, higher alteration in FC temporal variability between left DLPFC and right posterior parietal thalamus predicted a higher remission ratio of negative symptom scores, indicating that the decrease of FC temporal variability between the brain regions was associated with the remission of schizophrenia severity. The support vector regression (SVR) results suggested that the baseline pattern of FC temporary variability between the regions in CTCC could predict the efficacy of high-frequency rTMS intervention on negative symptoms in schizophrenia. These findings confirm the potential relationship between the reduction in whole-brain functional dynamics induced by high-frequency rTMS and the improvement in psychiatric scores, suggesting that high-frequency rTMS affects psychiatric symptoms by coordinating the heterogeneity of activity between the brain regions. Future studies would examine the clinical utility of using functional dynamics patterns between specific brain regions as a biomarker to predict the treatment response of high-frequency rTMS.

High-strength engineered cementitious composite (HS-ECC) reinforced with polyethylene (PE) fiber characterizes wider crack widths than the conventional polyvinyl alcohol fiber-reinforced ECC (PVA-ECC), weakening the self-healing potential of HS-ECC. The properties of HS-ECC are tailored by introducing crumb rubber (CR), as artificial flaws can lower the matrix toughness and the crack width, leading to an enhanced self-healing potential of HS-ECC. In this study, CR is used to entirely replace silica sand (SS) with three equivalent aggregate-to-binder ratios of 0.2, 0.4, and 0.6, and two CR particle sizes (i.e., CR1 and CR2) are also considered to investigate the effects on density, compressive properties, and tensile performances of HS-ECC. Although CR substitution of SS influences adversely the mechanical strengths of HS-ECC, it can reduce the HS-ECC matrix fracture toughness, activate more microcracks, and reduce the crack width. Moreover, CR-modified HS-ECC specimens featuring the smallest crack width were preloaded to three specific strain levels, including 0.5%, 1.0%, and 2.0%, and then experienced wet–dry conditioning to exhibit effective mechanical and non-mechanical property recovery. The further hydration of binder materials enhances the interfacial bond stress and thus retains the mechanical performances of self-healed HS-ECC, which is expected to improve the practical application and benefit the sustainability of HS-ECC.

Three different Ti addition routes were used to prepare an Al–5Ti–B Master Alloy: the halide salt route, the Ti-sponge route, and the partial Ti-sponge route. In the halide salt route, the raw materials were Al + KBF4 + K2TiF6; K2TiF6 was completely replaced by pure titanium for the Ti-sponge route versus the halide salt route; in the partial Ti-sponge route, K2TiF6 was partially replaced by pure titanium. Here, 30% Ti-sponge or 60% Ti-sponge route means that 30% or 60% K2TiF6 was replaced by pure titanium, respectively. The above Ti addition routes have a significant influence on the growth pattern and morphological evolution of TiAl3 and TiB2, which greatly affect the refining performance of Al–Ti–B Master Alloy. When using the halide salt route, a streamlined “rich Ti, B area” exists in the aluminum melt, which is a complex compound of (Tix, Al1−x) By. The “rich Ti, B area” is essential for the nucleation and growth of TiAl3 and TiB2. Blocky TiAl3 was obtained and its average size was 4.7 μm based on the halide salt route. In the Ti-sponge route, the nucleation of TiAl3 mainly depends on the mutual diffusion of Al and Ti, and TiAlx forms around pure Ti particles, i.e., the so-called Ti–TiAlx mechanism. The average size of the blocky TiAl3 was 9.8 μm based on the Ti–TiAlx mechanism. For the partial Ti-sponge route, the “rich Ti, B area” gradually decreases with the increase in Ti powder’s contents, and large TiAl3 coexists with the small TiAl3. Compared with the Ti-sponge route, the halide salt route can form smaller TiAl3. In the Ti-sponge route, there is a small amount of “rich Ti, B area” due to the influence of the Ti–TiAlx mechanism, which does not meet the requirements of TiB2 growth. In the halide salt route, there is sufficient “rich Ti, B area”, which is conducive to the formation of TiB2. Both the crystal defects and the crowded growth environment caused by the “rich Ti, B area” are fundamental reasons for the fragility and the irregular shape of the TiB2. The refining effect of the Al–Ti–B Master Alloy prepared by the halide salt route is better than the Ti-sponge route. The refining effect of 30% Ti-sponge route is better than that of Ti-sponge route and worse than that of halide salt route.

This paper presents an approach to predict the depression self-rating scale of Patient Health Questions-9 (PHQ-9) values from pupil-diameter data based on the graph attention network (GAT). The pupil diameter signal was derived from the eye information collected synchronously while the subjects were viewing the virtual reality emotional scene, and then the scores of PHQ-9 depression self-rating scale were collected for depression level. The chebyshev distance based GAT (Chebyshev-GAT) was constructed by extracting pupil-diameter change rate, emotional bandwidth, information entropy and energy, and their statistical distribution. The results show that, the error (MAE and SMRE)of the prediction results using Chebyshev-GAT is smaller then the traditional regression prediction model.

With the rapid development of information technology and biomedical engineering, people can get more and more information. At the same time, they begin to study how to apply the advanced technology in biomedical information. The main research of this paper is to optimize the machine learning method by particle swarm optimization (PSO) and apply it in the classification of biomedical data. In order to improve the performance of the classification model, we compared the different inertia weight strategies and mutation strategies and their combinations with PSO, and obtained the best inertia weight strategy without mutation, the best mutation strategy without inertia weight and the best combination of the two. Then, we used the three PSO algorithms to optimize the parameters of support vector machine in the classification of biomedical data. We found that the PSO algorithm with the combination of inertia weight and mutation strategy and the inertia weight strategy that we proposed could improve the classification accuracy. This study has an important reference value for the prediction of clinical diseases.

We undertook a comparative study of the leaf venation characteristics of Dioscorea species from all seven sections distributed in China (33 species, 1 subspecies and 3 varieties). We established that leaf venation has a taxonomic significance in Dioscorea. The sections Combili, Opsophyton Lasiophyton and Shannicorea all show consistent acrodromous venation (a subtype of palmate venation), with Botryosicyos exhibiting consistent pinnate venation. However, sections Stenophora and Enantiophyllum show obvious intrasectional differences. For example, D. simulans and D. biformifolia of section Stenophora have acrodromously veined middle leaflets, whereas the side leaflets are pinnately veined; D. cirrhosa and D. cirrhosa var. cylindrica of section Enantiophyllum show dichotomous veinlets. Other species in the same section show either one-branched veinlets or multiple branched veinlets. In addition to the discrepancy in venation patterns, differences in many other important morphological characteristics and chemical components were also observed. Therefore, D. simulans and D. biformifolia can be reasonably excluded from section Stenophora, and section Illigerestrum can be rebuilt using these two species. In addition, D. cirrhosa and D. cirrhosa var. cylindrica should be removed from section Enantiophyllum and placed into another new section. D. simulans and D. biformifolia show pinnate venation, and the complexity of their leaf organization (with both simple and compound leaves) also points to variations between the pinnate and acrodromous veins in Dioscorea. The repeated presence of palmate and pinnate venation in multiple angiosperm clades also suggests that the formation and evolution of venation are likely the result of evolutionary adaptation to ecological environments.

The molecular mechanism controlling the zygotic genome activation (ZGA) in mammals remains poorly understood. The 2-cell (2C)-like cells spontaneously emerging from cultures of mouse embryonic stem cells (ESCs) share some key transcriptional and epigenetic programs with 2C-stage embryos. By studying the transition of ESCs into 2C-like cells, we identified developmental pluripotency associated 2 and 4 (Dppa2/4) as important regulators controlling zygotic transcriptional program through directly up-regulating the expression of double homeobox (Dux). In addition, we found that DPPA2 protein is sumoylated and its activity is negatively regulated by small ubiquitin-like modifier (Sumo) E3 ligase protein inhibitor of activated STAT 4 (PIAS4). PIAS4 is down-regulated during ZGA process and during transitioning of ESCs into 2C-like cells. Depleting Pias4 or overexpressing Dppa2/4 is sufficient to activate 2C-like transcriptional program, whereas depleting Dppa2/4 or forced expression of Pias4 or Sumo2-Dppa2 inhibits 2C-like transcriptional program. Furthermore, ectopic expression of Pias4 or Sumo2-Dppa2 impairs early mouse embryo development. In summary, our study identifies key molecular rivals consisting of transcription factors and a Sumo2 E3 ligase that regulate zygotic transcriptional program upstream of Dux.

Goethite is a stable and widespread mineral present in soil with many uses, and it affects the transportation and immobilization of heavy metals in solution. Nanogoethite was synthesized by a chemical precipitation method and used to batch adsorb U(VI) in solution. Adsorption experiments were used to understand the role of nanogoethite in controlling the U(VI) adsorption behavior in soil. The morphology and the crystallinity of nanogoethite were characterized by scanning electron microscopy and wide-angle X-ray powder diffractometry, respectively. The results showed that the crystallinity of nanogoethite after the adsorption of uranium did not change, but small particles appeared on the surface of the scales. The surface area was determined from N 2 adsorption–desorption experiments using the Brunauer–Emmett–Teller to be 81.86 m 2 /g. The effects of factors such as the contact time, pH, adsorbent dosage, and the initial concentration of uranium on the adsorption of U(VI) were investigated. The experimental results showed that nanogoethite removed over 85% of the U(VI) in an aqueous 5.0 mg/L U(VI) solution at pH 4.0 and at 298 K. The pseudo-second-order model was used to simulate the adsorption process. The results show that chemisorption plays a major role in the adsorption process. The results of this study suggest that nanogoethite may play a significant role in controlling the migration and transfer of U(VI) in the soil, thus controlling the presence of U(VI) in soil.

To reduce the navigation control cost, this paper proposes a mechanical guidance control scheme that uses a cam-link mechanism as a steering control mechanism for an automated guided vehicle with a fixed driving path. According to the steering principle, a mathematical model of the steering system and the driving trajectory are established. By setting the boundary conditions, the vehicle trajectory is modeled using a quintic polynomial. The contour of the directional control cam is obtained based on the equation of the vehicle trajectory. Because errors occur in actual machining and assembly processes, errors will be classified based on their impact on the trajectory. The effects of various errors on the trajectory are quantitatively determined by using simulation methods with different parameters. Furthermore, an error compensation approach is designed to reduce the influence of the error on the trajectory directly or indirectly. Finally, experiment results illustrate that the adjustment accuracy of the proposed automated guided vehicle trajectory is 2 mm.

At present, the clinical diagnosis of depression is mainly through structured interviews by psychiatrists, which is lack of objective diagnostic methods, so it causes the higher rate of misdiagnosis. In this paper, a method of depression recognition based on SVM and particle swarm optimization algorithm mutation is proposed. To address on the problem that particle swarm optimization (PSO) algorithm easily trap in local optima, we propose a feedback mutation PSO algorithm (FBPSO) to balance the local search and global exploration ability, so that the parameters of the classification model is optimal. We compared different PSO mutation algorithms about classification accuracy for depression, and found the classification accuracy of support vector machine (SVM) classifier based on feedback mutation PSO algorithm is the highest. Our study promotes important reference value for establishing auxiliary diagnostic used in depression recognition of clinical diagnosis.