Efficacy and safety of acupuncture in post-stroke constipation: a systematic review and meta-analysis

Background and objectivePost-stroke constipation (PSC) is a common complication of strokes that seriously affects the recovery and quality of life of patients, and effective treatments are needed. Acupuncture is a viable treatment option, but current evidence is insufficient to support its efficacy and safety. This study aims to evaluate the efficacy and safety of acupuncture in the treatment of PSC.MethodsA systematic search of eight databases was conducted to identify PSC-related randomized clinical trials from the inception of each database through May 2023. Methodological quality assessment was conducted by RoB 2.0, meta-analysis was conducted by RevMan 5.3 and Stata 15.1, and evidence quality was evaluated by GRADE. Moreover, reporting quality of acupuncture interventions was assessed using the Standards for Reporting Interventions in Clinical Trials of Acupuncture (STRICTA).ResultsThirty RCTs involving 2,220 patients were identified. We found that acupuncture was superior to conventional treatment (CT) in improving total responder rate [risk ratio (RR): 1.16, 95% confidence interval (CI): 1.09 to 1.25, p < 0.0001], decreasing constipation symptom scores [standardized mean difference (SMD): -0.65, 95% CI: −0.83 to −0.46, p < 0.00001], increasing serum P substance (SP) levels (SMD: 1.92, 95% CI: 0.47 to 3.36, p = 0.009), reducing the time to first bowel movement (BM) (SMD: -1.19, 95% CI: −2.13 to −0.25, p = 0.01), and lowing serum vasoactive intestinal peptide (VIP) levels (SMD: –2.11, 95% CI: −3.83 to −0.38, p = 0.02). Furthermore, acupuncture plus CT was superior regarding total responder rate (RR: 1.26, 95% CI: 1.17 to 1.35, p < 0.00001), serum SP levels (SMD: 2.00, 95% CI: 1.65–2.35, p < 0.00001), time to first BM (SMD: –2.08, 95% CI: −2.44 to −1.71, p < 0.00001), and serum VIP levels (SMD: –1.71, 95% CI: −2.24 to −1.18, p < 0.00001). However, regarding Bristol Stool Scale (BSS) score, acupuncture plus CT was superior to CT (SMD: -2.48, 95% CI: −3.22 to −1.73, p < 0.00001), while there was no statistically significant difference between acupuncture and CT (SMD: 0.28, 95% CI: −0.02 to 0.58, p = 0.07). Acupuncture causes fewer AEs than CT (RR: 0.13, 95% CI: 0.06 to 0.26, p < 0.00001), though there was no statistically significant difference between acupuncture plus CT vs. CT (RR: 1.30, 95% CI: 0.60 to 2.84, p = 0.51).ConclusionAcupuncture may be an effective and safe therapy for PSC. However, given the inferior quality of clinical data, additional well-designed RCTs are required to confirm these findings

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing reagents. This work was supported by the Shenzhen Basic Research Project for Excellent Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In addition, L.L. was supported by the National Natural Science Foundation of China (31900466), Y. Hou was supported by the Natural Science Foundation of Guangdong Province (2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award (419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), a Chinese Academy of Sciences–Japan Society for the Promotion of Science joint research project (GJHZ2093), the National Natural Science Foundation of China (92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075). M.L. was supported by the National Key Research and Development Program of China (2021YFC2600200).S

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

A Game Analysis of Farmland Expropriation Conflict in China under Multi-Dimensional Preference: Cooperation or Resistance?

The process of urbanization in China has been accompanied by the conflict of land expropriation, which is not conducive to social stability. Different from the previous angles and methods of studying the conflict of agricultural land expropriation, this study puts forward a new behavioral perspective on the basis of game theory, and constructs an evolutionary game model of the conflict of agricultural land expropriation in China from the perspective of multi-dimensional preference. It also discusses the impact of different preference combinations on the conflict input, net income and utility of various stakeholders in agricultural land expropriation. The results show that under the influence of complete self-interest preference, the degree of protection of farmers’ land rights and interests affects the probability of conflicts in compensation for agricultural land expropriation. However, under the influence of multi-dimensional preference combination, agricultural land expropriation can be carried out smoothly only when the reciprocal altruism preference of local government and farmers is strong and the loss aversion preference is weak. These insights have implications for the sustainable development of land, including government involvement and farmers participation, particularly in the context of developing countries

A Game Analysis of Farmland Expropriation Conflict in China under Multi-Dimensional Preference: Cooperation or Resistance?

The process of urbanization in China has been accompanied by the conflict of land expropriation, which is not conducive to social stability. Different from the previous angles and methods of studying the conflict of agricultural land expropriation, this study puts forward a new behavioral perspective on the basis of game theory, and constructs an evolutionary game model of the conflict of agricultural land expropriation in China from the perspective of multi-dimensional preference. It also discusses the impact of different preference combinations on the conflict input, net income and utility of various stakeholders in agricultural land expropriation. The results show that under the influence of complete self-interest preference, the degree of protection of farmers’ land rights and interests affects the probability of conflicts in compensation for agricultural land expropriation. However, under the influence of multi-dimensional preference combination, agricultural land expropriation can be carried out smoothly only when the reciprocal altruism preference of local government and farmers is strong and the loss aversion preference is weak. These insights have implications for the sustainable development of land, including government involvement and farmers participation, particularly in the context of developing countries

A New Method Without Organic Solvent to Targeted Nanodrug for Enhanced Anticancer Efficacy

Abstract Since the hydrophobic group is always essential to the synthesis of the drug-loaded nanoparticles, a majority of the methods rely heavily on organic solvent, which may not be completely removed and might be a potential threat to the patients. In this study, we completely “green” synthesized 10-hydroxycamptothecine (HCPT) loaded, folate (FA)-modified nanoneedles (HFNDs) for highly efficient cancer therapy with high drug loading, targeting property, and imaging capability. It should be noted that no organic solvent was used in the preparation process. In vitro cell uptake study and the in vivo distribution study showed that the HFNDs, with FA on the surface, revealed an obviously targeting property and entered the HeLa cells easier than the chitosan-HCPT nanoneedles without FA modified (NDs). The cytotoxicity tests illustrated that the HFNDs possessed better killing ability to HeLa cells than the individual drug or the NDs in the same dose, indicating its good anticancer effect. The in vivo anticancer experiment further revealed the pronounced anticancer effects and the lower side effects of the HFNDs. This new method without organic solvent will lead to a promising sustained drug delivery system for cancer diagnosis and treatment

TiB Nanowhisker Reinforced Titanium Matrix Composite with Improved Hardness for Biomedical Applications

Titanium and its alloys have been employed in the biomedical industry as implants and show promise for more broad applications because of their excellent mechanical properties and low density. However, high cost, poor wear properties, low hardness and associated side effects caused by leaching of alloy elements in some titanium alloys has been the bottleneck to their wide application. TiB reinforcement has shown promise as both a surface coating for Ti implants and also as a composite reinforcement phase. In this study, a low-cost TiB-reinforced alpha titanium matrix composite (TMC) is developed. The composite microstructure includes ultrahigh aspect ratio TiB nanowhiskers with a length up to 23 μm and aspect ratio of 400 and a low average Ti grain size. TiB nanowhiskers are formed in situ by the reaction between Ti and BN nanopowder. The TMC exhibited hardness of above 10.4 GPa, elastic modulus above 165 GPa and hardness to Young’s modulus ratio of 0.062 representing 304%, 170% and 180% increases in hardness, modulus and hardness to modulus ratio, respectively, when compared to commercially pure titanium. The TiB nanowhisker-reinforced TMC has good biocompatibility and shows excellent mechanical properties for biomedical implant applications