A phytoplasma effector destabilizes chloroplastic glutamine synthetase inducing chlorotic leaves that attract leafhopper vectors.

Leaf yellowing is a well-known phenotype that attracts phloem-feeding insects. However, it remains unclear how insect-vectored plant pathogens induce host leaf yellowing to facilitate their own transmission by insect vectors. Here, we report that an effector protein secreted by rice orange leaf phytoplasma (ROLP) inhibits chlorophyll biosynthesis and induces leaf yellowing to attract leafhopper vectors, thereby presumably promoting pathogen transmission. This effector, designated secreted ROLP protein 1 (SRP1), first secreted into rice phloem by ROLP, was subsequently translocated to chloroplasts by interacting with the chloroplastic glutamine synthetase (GS2). The direct interaction between SRP1 and GS2 disrupts the decamer formation of the GS2 holoenzyme, attenuating its enzymatic activity, thereby suppressing the synthesis of chlorophyll precursors glutamate and glutamine. Transgenic expression of SRP1 in rice plants decreased GS2 activity and chlorophyll precursor accumulation, finally inducing leaf yellowing. This process is correlated with the previous evidence that the knockout of GS2 expression in rice plants causes a similar yellow chlorosis phenotype. Consistently, these yellowing leaves attracted higher numbers of leafhopper vectors, caused the vectors to probe more frequently, and presumably facilitate more efficient phytoplasma transmission. Together, these results uncover the mechanism used by phytoplasmas to manipulate the leaf color of infected plants for the purpose of enhancing attractiveness to insect vectors.

Visualization Analysis of Artificial Intelligence Literature in Forensic Research.

OBJECTIVES: To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database, to explore research hotspots and developmental trends. METHODS: A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the literature measuring tool CiteSpace. The authors, institution, country (region), title, journal, keywords, cited references and other information of relevant literatures were analyzed. RESULTS: A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries (regions) were identified, with the number of articles published showing an increasing trend year by year. Among them, the United States had the highest number of publications and China ranked the second. Academy of Forensic Science had the highest number of publications among the institutions. Forensic Science International, Journal of Forensic Sciences, International Journal of Legal Medicine ranked high in publication and citation frequency. Through the analysis of keywords, it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technology for sex and age estimation, cause of death analysis, postmortem interval estimation, individual identification and so on. CONCLUSIONS: It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research. Exploring the combination of advanced artificial intelligence technologies with forensic research will be a hotspot and direction for future research.

The risk characteristics of heavy metals in urban soil of typical developed cities in China.

With the rapid development of China's industrial economy, heavy metals continue to accumulate in the environment, which has created serious threats for the ecological environment and human health. This study collected 50 surface soil samples in Nanjing, a typical developed city in China, and the contents of Al, Ca, Fe, Mg, Mn, Ni, Ti, Cd, Cr, Cu, Pb, and Zn in the samples were determined. Combined with the ecological risk index and the health risk assessment model, the risk of soil heavy metals in Nanjing was comprehensively evaluated. The results show that the variation coefficients of Pb and Cu are distinctly large, and these elements are all slightly polluting. Children are at a high risk of exposure in various ways, among which Pb and Cu elements have a high risk of causing non-carcinogenic issues. The results of the correlation analysis showed that the content changes of Pb, Zn, and Cu had extremely significant correlations, indicating that they may have the same source. The results of the principal component analysis showed that industrial sources in Nanjing contributed the most heavy metals, reaching 34.4%. The second largest source was from parent material and fertilizer, which contributed 32.3% and 19.6%, respectively. The sources with the lowest contributions were from weathering and deposition, which reached 13.7%. The results of this study will provide guidance and reference for risk-source analysis, early warning, and management of soil heavy metals in developed cities.

Critical Care Resources in Guangdong Province of China: Three Surveys from 2005 to 2015.

OBJECTIVES: Data about the critical care resources in China remain scarce. The purpose of this study was to investigate the variation and distribution of critical care resources in Guangdong province from 2005 to 2015. DESIGN: Data in regard to critical care resources were collected through questionnaires and visits every 5 years from 2005. SETTING: All hospitals in Guangdong province were screened and hospitals that provide critical care services were enrolled. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: One hundred eleven, 158, and 284 hospitals that provide critical care services were enrolled in the three consecutive surveys respectively. The number of ICUs, ICU beds, intensivists, and nurses increased to 324, 3,956, 2,470, and 7,695, respectively, by 2015. Adjusted by population, the number of ICU beds per 100,000 (100,000) population increased by 147.7% from 2005 to 2015, and the number of intensivists and nurses per 100,000 population increased by 35.3% and 55.1% from 2011 to 2015. However, the numbers in the Pearl River Delta, a richer area, were higher than those in the non-Pearl River Delta area (ICU beds: 4.64 vs 2.58; intensivists: 2.90 vs 1.61; nurses: 9.30 vs 4.71 in 2015). In terms of staff training, only 17.85% of intensivists and 14.29% of nurses have completed a formal accredited critical care training program by 2015. CONCLUSIONS: Our study was the first one to investigate the trend and distribution of critical care resources in China. The quantity of ICU beds and staff has been increasing rapidly, but professional training for staff was inadequate. The distribution of critical care resources was unbalanced. Our study can be beneficial for healthcare policymaking and the allocation of critical care resources in Guangdong province and other provinces in China.

Knowledge mapping and global trends of drug hypersensitivity from 2013 to 2023: A bibliometric analysis.

BACKGROUND: Drug hypersensitivity is a major global public health issue with a significant increase in prevalence in populations. Here, we provide a deep insight into the frontier hotspot and future direction in the field of drug hypersensitivity. METHODS: A knowledge map is portrayed based on publications related to drug hypersensitivity from Web of Science Core Collection using CiteSpace. Co-occurrence relationships of countries, institutes, authors, journals, references, and keywords are constructed. According to the co-occurrence relationships, hotspots and future trends are overviewed. RESULTS: The United States ranked first in the world and China with the second highest publications was the only developing country. Torres, Mayorga, and Blanca were highly productive authors. Harvard University was the institution with the most research publications. Keywords co-occurrence analysis suggested applications in emerging causes, potential mechanisms, and clinical diagnosis as the research hotspots and development frontiers. CONCLUSION: Research on drug hypersensitivity is in a rapid development stage and an emerging trend in reports of anaphylaxis to polyethylene glycols is identified. Developing algorithms for understanding the standardization process of culprit drugs, clinical manifestations, and diagnostic methods will be the focus of future direction. In addition, a better understanding of the mechanisms to culprit drugs with immunological precise phenotypic definitions and high-throughput platforms is needed.

[Effects of miR-143 on the migration and invasion of osteosarcoma cells by regulating MMP-13 expression].

OBJECTIVE: To explore the effect of miR-143 regulating matrix metalloproteinase(MMP)-13 expression on migration and invasion of osteosarcoma cells. METHODS: The mouse osteosarcoma cell line 143B cells were cultured in 96-well plates, and blank group, negative group, positive group, and intervention group were set up. Then, the blank group did no treatment 50 µg miR-143 mimic was added to positive group, negative group added equal mimic NC (control sequence of miR-143 mimic), the intervention group was added 50 µg miR-143 mimic and 10 µg MMP-13 protein, all groups continued to culture for 3 to 6 hours, and finally the serum was aspirated to treat for half an hour. The protein expressions of miR-143 and MMP-13 in each group were measured by fluorescence quantitative PCR experiment and Western blot experiment, respectively, and the invasion and migration abilities of cells were measured by Transwell and scratch experiments. RESULTS: The expression of MMP-13 protein in the positive group and the intervention group was significantly lower than that in the blank group, and the positive group was lower than the intervention group (P<0.05);The mean numbers of invasive cells in blank group, negative group, positive group and intervention group were (1 000.01±44.77), (959.25±46.32), (245.04±4.33), (634.06±33.78) cells/field, respectively;the scratch healing rate of the positive group and the intervention group was significantly lower than that of the blank group, and the positive group was lower than the intervention group (P<0.05). CONCLUSION: MMP-13 is a target of miR-143, which can reduce the migration and invasion ability of osteosarcoma cells by inhibiting the expression of MMP-13.

Copper-Epigallocatechin Gallate Enhances Therapeutic Effects of 3D-Printed Dermal Scaffolds in Mitigating Diabetic Wound Scarring.

Morbid dermal templates, microangiopathy, and abnormal inflammation are the three most critical reasons for the scarred healing and the high recurrence rate of diabetic wounds. In this present study, a combination of a methacrylated decellularized extracellular matrix (ECMMA, aka EM)-based hydrogel system loaded with copper-epigallocatechin gallate (Cu-EGCG) capsules is proposed to fabricate bio-printed dermal scaffolds for diabetic wound treatment. Copper ions act as a bioactive element for promoting angiogenesis, and EGCG can inhibit inflammation on the wound site. In addition to the above activities, EM/Cu-EGCG (E/C) dermal scaffolds can also provide optimized templates and nutrient exchange space for guiding the orderly deposition and remodeling of ECM. In vitro experiments have shown that the E/C hydrogel can promote angiogenesis and inhibit the polarization of macrophages to the M1 pro-inflammatory phenotype. In the full-thickness skin defect model of diabetic rats, the E/C dermal scaffold combined with split-thickness skin graft transplantation can alleviate pathological scarring via promoting angiogenesis and driving macrophage polarization to the anti-inflammatory M2 phenotype. These may be attributed to the scaffold-actuated expression of angiogenesis-related genes in the HIF-1α/vascular endothelial growth factor pathway and decreased expression of inflammation-related genes in the TNF-α/NF-κB/MMP9 pathway. The results of this study show that the E/C dermal scaffold could serve as a promising artificial dermal analogue for solving the problems of delayed wound healing and reulceration of diabetic wounds.

Characterization of global research trends and prospects on sudden coronary death: A literature visualization analysis.

Background: Sudden coronary death is a major global public health issue that has a significant impact on both individuals and society. Nowadays, scholars are active in sudden coronary death all over the world. However, no relevant bibliometric studies have been published. Here, we aim to gain a better understanding the current state of research and to explore potential new research directions through bibliometric analysis. Methods: Articles and reviews on sudden coronary death from 2012 to 2023 were retrieved from the Web of Science Core Collection (WoSCC). The topic search was conducted using the following keywords: ((("sudden cardiac death" OR "sudden death") AND (coronary OR "myocardial infarction")) OR "sudden coronary death"). Knowledge maps of authors, countries, institutions, journals, keywords, and citations were conducted by CiteSpace. Publication dynamics, hotspots, and frontiers were analyzed independently by authors. Results: A total of 2914 articles were identified from January 1, 2012 to June 20, 2023. The USA (n = 972) contributed the greatest absolute productivity and UK (centrality = 0.13) built a robust global collaboration. Harvard University was the institution with the highest number of publications (n = 143). Huikuri HV and Junttila MJ were the most published authors who devoted to searching for biomarkers of sudden coronary death. American Journal of Cardiology was the journal with the most publications, and Circulation was the most cited journal. Left ventricular ejection fraction, society, inflammation, and fractional flow reserve became novel burst words that lasted until 2023. Research on etiology and pathology, role of early risk factors in risk stratification, potential predictive biomarkers and novel measurement methods for the prevention and management of sudden coronary death were identified as the research hotspots and frontiers. Conclusion: Our knowledge and understanding of sudden coronary death have significantly improved. Ongoing efforts should focus on the various etiologies and pathologies of sudden coronary death. Furthermore, a novel sudden coronary death risk model, large-scale population studies, and the rational use of multiple indicators to individualize the assessment of sudden coronary death and other risk factors are other emerging research trends.

6 Paths of ERK5 signaling pathway regulate hepatocyte proliferation in rat liver regeneration.

Generally, extra-cellular-signal-regulated kinase 5 (ERK5) signaling pathway regulates many physiological activities, such as cell proliferation and cell differentiation. However, little is known about how ERKS signaling pathway composed of 15 paths participates in regulating hepatocyte proliferation during liver regeneration (LR). In this study, to explore the influence ERK5 signaling pathway upon hepatocytes at gene transcription level, rat genome 230 2.0 array was used to detect expression changes of 75 related genes in isolated hepatocytes from rat regenerating liver. Bioinformatics and systems biology methods were applied to analyze the precise role of ERK5 signaling pathway in regulating hepatocyte proliferation during LR. Results showed that 62 genes were contained in the array and 22 genes were significantly changed. It was found that 6 paths were related to hepatocyte proliferation during rat LR. Among them, paths 3, 6 and 13 of ERK5 signaling pathway modulated cell cycle progression by decreasing the negative influence on ERK5 and paths 3, 4, 8 and 9 by reinforcing the positive influence on ERK5. In summary, the study shows that 22 genes and 6 paths of ERK5 signaling pathway participate in regulating proliferation of hepatocytes in rat LR.

Highly-Efficient and Visible Light Photocatalytical Degradation of Organic Pollutants Using TiO2-Loaded on Low-Cost Biomass Husk.

A composite composing of TiO2 nanoparticles load on biomass rice husk (RH) is developed by directly growing TiO2 nanoparticles on RH. The in-situ growth of the nanocrystals on RH is achieved by a low-cost and one-step homogeneous precipitation. Rapid hydrolysis proceeds at 90 °C by using ammonium fluotitanate and urea to facilitate the selective growth of TiO2. The method provides an easy access to the TiO2-RH composite with a strong interaction between TiO2 nanoparticles and the underlying RH. The structure and composition of TiO2-RH are characterized by using X-ray diffraction, X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, and UV-vis absorption spectroscopy. TiO2 nanoparticles-RH exhibits a good photocatalytic degradation of methyl orange. The results show that 92% of methyl orange (20 mg L-1) can be degraded within three hours in visible light. The catalytic activity of the composite is not reduced after 6 cycles, and it still reaches 81% after 6 cycles. The enhanced performance is ascribed to the suitable particle size the good dispersibility. It is expected that the high photocatalytical performance and the cost-effective composite presented here will inspire the development of other high-performance photocatalysts.

Plastic surgical repair of ulcer wounds of diabetic foot patients through systemic treatment and local infection control.

BACKGROUND: This study was to investigate the efficacy of plastic surgery in patients with diabetic foot (DF) ulcer who had systemic treatment and local infection control. METHODS: A total of 112 patients with DF were randomly divided into surgery group and drug treatment group according to treatment methods. Firstly, the pathogenic bacteria were isolated and cultured to explore the specific factors causing glycosuria foot ulcer. Secondly, the wound recovery and average hospitalization of the patients were analyzed, and the effects of different treatment methods on the clinical cure rate and recovery rate of the patients were compared. RESULTS: The results showed that 53 patients were diagnosed with type 2 DF, accounting for 47.32%; 22 patients were diagnosed with DF disease complicated by infections, accounting for 19.64%; 25 patients were diagnosed with DF complicated by ulcers, accounting for 22.32%; and 12 patients (10.71%) were diagnosed with DF complicated by ulcer infection. Of the pathogens cultured, Enterococcus faecalis accounted for the highest proportion (19.35%). Statistical analysis was conducted on Wagner grading. It was found that with the increase of the grade, the wound recovery time of patients gradually increased, with the longest recovery time for grade V and the shortest recovery time for grade I. Additionally, with the extension of hospital stay, the area of the ulcer wound gradually decreased. In the analysis of induced factors, there were 17 cases of nail cutting, accounting for 15.18%. CONCLUSIONS: The operation of repairing DF ulcer wound under the guidance of plastic surgery principle had good efficacy, safety, and reliability, and was worthy of clinical promotion.

A biomechanical analysis of skiing-related anterior cruciate ligament injuries based on biomedical imaging technology.

Alpine skiing is an attractive but highly risky sport, and the anterior cruciate ligament (ACL) tear is one of the most common diagnoses of skiing-related injuries. To better prevent such injuries among athletes and recreational skiers, we developed a facile and reliable biomechanical method to analyze the differences between "right" and "wrong" movements during skiing and their impacts on ACL stress loading. Unlike those conventional methods that are very difficult to implement and time-consuming, our method was developed based on inverse dynamics analyses and video capture, which were much easier to implement in the real-world setting. It is shown that, with a harmful skiing action, the knee joint's maximum reaction force significantly increases compared to nonharmful skiing actions. The peak front-and-rear force increased from 1242 N to 3105 N, and the peak axial force increased from 1023 N to 3443 N, which significantly exceeded the maximum tensile loading (2000 N) in the ACL. Our results are proven to be reliable and consistent with findings obtained with other methods. This method may substitute current complex analytical methods and be easier to apply in sports-related injury-prevention applications.

Flap failure prediction in microvascular tissue reconstruction using machine learning algorithms.

BACKGROUND: Microvascular tissue reconstruction is a well-established, commonly used technique for a wide variety of the tissue defects. However, flap failure is associated with an additional hospital stay, medical cost burden, and mental stress. Therefore, understanding of the risk factors associated with this event is of utmost importance. AIM: To develop machine learning-based predictive models for flap failure to identify the potential factors and screen out high-risk patients. METHODS: Using the data set of 946 consecutive patients, who underwent microvascular tissue reconstruction of free flap reconstruction for head and neck, breast, back, and extremity, we established three machine learning models including random forest classifier, support vector machine, and gradient boosting. Model performances were evaluated by the indicators such as area under the curve of receiver operating characteristic curve, accuracy, precision, recall, and F1 score. A multivariable regression analysis was performed for the most critical variables in the random forest model. RESULTS: Post-surgery, the flap failure event occurred in 34 patients (3.6%). The machine learning models based on various preoperative and intraoperative variables were successfully developed. Among them, the random forest classifier reached the best performance in receiver operating characteristic curve, with an area under the curve score of 0.770 in the test set. The top 10 variables in the random forest were age, body mass index, ischemia time, smoking, diabetes, experience, prior chemotherapy, hypertension, insulin, and obesity. Interestingly, only age, body mass index, and ischemic time were statistically associated with the outcomes. CONCLUSION: Machine learning-based algorithms, especially the random forest classifier, were very important in categorizing patients at high risk of flap failure. The occurrence of flap failure was a multifactor-driven event and was identified with numerous factors that warrant further investigation. Importantly, the successful application of machine learning models may help the clinician in decision-making, understanding the underlying pathologic mechanisms of the disease, and improving the long-term outcome of patients.

THE APPLICATION OF NEURAL NETWORK TECHNOLOGY BASED ON MEA-BP ALGORITHM IN THE PREDICTION OF MICRODOSIMETRIC QUALITIES.

The most abundant products of the interaction between radiation and matter are low-energy electrons, and the collisions between these electrons and biomolecules are the main initial source of radiation-based biological damage. To facilitate the rapid and accurate quantification of low-energy electrons (0.1-10 keV) in liquid water at different site diameters (1-2000 nm), this study obtained ${\overline{y}}_{\mathrm{F}}$ and ${\overline{y}}_{\mathrm{D}}$data for low-energy electrons under these conditions. This paper proposes a back-propagation (BP) neural network optimized by the mind evolutionary algorithm (MEA) to construct a prediction model and evaluate the corresponding prediction effect. The results show that the ${\overline{y}}_{\mathrm{F}}$ and ${\overline{y}}_{\mathrm{D}}$ values predicted by the MEA-BP neural network algorithm reach a training precision on the order of ${10}^{-8}$. The relative error range between the prediction results of the validated model and the Monte Carlo calculation results is 0.03-5.98% (the error range for single-energy electrons is 0.1-5.98%, and that for spectral distribution electrons is 0.03-4.4%).

Confinement of all-inorganic perovskite quantum dots assembled in metal-organic frameworks for ultrafast scintillator application.

Nucleation and growth of quantum dots (QDs) are thermodynamic processes driven by the total Gibbs free energy change (ΔG). We discuss the nucleation and growth theory of perovskite quantum dots (PeQDs) inside a metal-organic framework (MOF) as a strong constraint framework, which can effectively confine the size of QDs below 3 nm and achieve a scintillator with an ultra-fast transient lifetime of fluorescence. Therefore, based on the requirements for the optical properties of ultra-fast scintillation materials, two kinds of suitable MOFs (UiO-67-bpy and MIL-101(Cr)) were selected for synthesis. The method of 'ship-in-bottle' was adopted to embed perovskite quantum dots CsPbBrCl2 into MOF cages to form PeQDs@MOF composite materials, which is different from the one-pot method. In order to further improve the stability of PeQDs@MOF, polystyrene was used to cure the composite scintillator, which can resist exposure to UV light and withstand the ISO level 4 test, with the fastest transient lifetime of 2.13 ns and a fluorescence emission wavelength of 445 nm.

Identification and validation of an epithelial mesenchymal transition-related gene pairs signature for prediction of overall survival in patients with skin cutaneous melanoma.

BACKGROUND: We aimed to construct a novel epithelial-mesenchymal transition (EMT)-related gene pairs (ERGPs) signature to predict overall survival (OS) in skin cutaneous melanoma (CM) patients. METHODS: Expression data of the relevant genes, corresponding clinicopathological parameters, and follow-up data were obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis was utilized to identify ERGPs significantly associated with OS, and LASSO analysis was used to identify the genes used for the construction of the ERGPs signature. The optimal cutoff value determined by the receiver operating characteristic curve was used to classify patients into high-risk and low-risk groups. Survival curves were generated using the Kaplan-Meier method, and differences between the two groups were estimated using the log-rank test. The independent external datasets GSE65904 and GSE19234 were used to verify the performance of the ERGPs signature using the area under the curve (AUC) values. In addition, we also integrated clinicopathological parameters and risk scores to develop a nomogram that can individually predict the prognosis of patients with CM. RESULTS: A total of 104 ERGPs related to OS were obtained, of which 21 ERGPs were selected for the construction of the signature. All CM patients were stratified into high-and low-risk groups based on an optimal risk score cutoff value of 0.281. According to the Kaplan-Meier analysis, the mortality rate in the low-risk group was lower than that in the high-risk group in the TCGA cohort (P < 0.001), GSE65904 cohort (P = 0.006), and GSE19234 cohort (P = 0.002). Multivariate Cox regression analysis indicated that our ERGP signature was an independent risk factor for OS in CM patients in the three cohorts (for TCGA: HR, 2.560; 95% CI [1.907-3.436]; P < 0.001; for GSE65904: HR = 2.235, 95% CI [1.492-3.347], P < 0.001; for GSE19234: HR = 2.458, 95% CI [1.065-5.669], P = 0.035). The AUC value for predicting the 5-year survival rate of patients with CM of our developed model was higher than that of two previously established prognostic signatures. Both the calibration curve and the C-index (0.752, 95% CI [0.678-0.826]) indicated that the developed nomogram was highly accurate. Most importantly, the decision curve analysis results showed that the nomogram had a higher net benefit than that of the American Joint Committee on Cancer stage system. CONCLUSION: Our study established an ERGPs signature that could be potentially used in a clinical setting as a genetic biomarker for risk stratification of CM patients. In addition, the ERGPs signature could also predict which CM patients will benefit from PD-1 and PD-L1 inhibitors.

PDMS-enhanced slowly degradable Ca-P-Si scaffold: Material characterization, fabrication and in vitro biocompatibility study.

A slowly degradable bone scaffold can well maintain the balance between new bone regeneration and scaffold resorption, esp. for seniors or patients suffering from pathological diseases, because too fast degradation can lead to the loss of long-term biological stability and result in scaffold failure. In this present study, calcium phosphate silicate (CPS) and polydimethylsiloxane (PDMS) were blended in different ratios to formulate slurries for scaffold fabrication. The effects of crosslinked PDMS on the CPS material properties were first characterized and the most viable formulation of CPS-PDMS slurry was determined based on the aforementioned results to 3D fabricate scaffolds. The biocompatibility of CPS-PDMS was further evaluated based on the scaffold extract's cytotoxicity to osteoblast cells. Furthermore, real-time PCR was used to investigate the effects of scaffold extract to increase osteoblast proliferation. It is showed that the crosslinked PDMS interfered with CPS hydration and reduced both setting rate and compressive strength of CPS. In addition, CPS porosity was also found to increase with PDMS due to uneven water distribution as a result of increased hydrophobicity. Degradation and mineralization studies show that CPS-PDMS scaffold was slowly degradable and induced apatite formation. In addition, the in vitro analyses show that the CPS-PDMS scaffold did not exert any cytotoxic effect on osteoblast cells but could improve the cell proliferation via the TGFß/BMP signaling pathway. In conclusion, CPS-PDMS scaffold is proved to be slowly degradable and biocompatible. Further analyses are therefore needed to demonstrate CPS-PDMS scaffold applications in bone regeneration.

Cellular S-value evaluation based on real human cell models using the GATE MC package.

Exploring the spatial distribution of the energy loss of ionising radiation at the subcellular level is indispensable for evaluating the radiobiological effects of targeted radionuclide therapy accurately. Believing that S-values are important for obtaining the target dose, the Committee on Medical Internal Radiation Dose (MIRD) proposed a method to obtain the cellular dosimetric parameter. However, most available data on cellular S-values were calculated based on simple geometric models, such as ellipsoids or spheres, which do not accurately reflect biological reality. To investigate the influence of the cellular model on S-values, calculations were performed for two kinds of polygon-surface phantom models of realistic, individual human cells, the lung epithelial cell model (the B2B Phantom model) and the hepatocyte model (the Liver Phantom model), using the Monte Carlo (MC) software package GATE. To analyse the influence of cell geometry on the final S-value, the differences in the S-values between the realistic cell models and simple geometric sphere and ellipsoid models with similar volumes were calculated and compared for six different combinations of source and target regions. The irradiation conditions were 0.01-1.10 MeV monoenergetic electron sources and the Auger electronic therapy nuclides Ga-67, Tc-99m, In-111, I-125 and Tl-201, which are commonly used in nuclear medicine. The S-values calculated in this study are different from the results of the simple geometry models proposed by previous researchers. Two more precise polygon-surface phantom models of realistic, individual human cells were used, which provided more accurate information about the cell dose and will be very useful for the diagnostic application of radiotherapy in the future.

The effect of inhibiting exosomes derived from adipose-derived stem cells via the TGF-ß1/Smad pathway on the fibrosis of keloid fibroblasts.

BACKGROUND: The main mechanism of keloid formation is that keloid fibroblasts (KFs) apoptosis is inhibited, leading to excessive proliferation. Transforming growth factor-ß1 (TGF-ß1) is a key signal molecule in the process of regulating cell fibrosis. This paper discusses the effect of adipose-derived stem cell exosomes (ADSCs-EXO) on the proliferation and apoptosis of KFS and its possible mechanism, in order to provide reference for the clinical intervention of hypertrophic scar. METHODS: ADSCs were isolated and cultured from human adipose tissue, the supernatant was collected, and the exosomes secreted by ADSCs-EXO were extracted by ultracentrifugation. At the same time, KFs were cultured from human keloid tissue to P3 generation, and then divided into four groups: control group, experimental group A, experimental group B and experimental group C. KFs were then cultured with four concentrations of ADSCs-EXO (0, 1, 10, and 100 µg/mL, respectively). After 24 hours, cells in each group were taken to detect the following: proliferation of cells in each group using the cell counting Kit 8 (CCK-8) method, cell migration ability via the Transwell test, cell apoptosis by flow cytometry, collagen synthesis using the hydroxyproline method, messenger ribonucleic acid (mRNA) expression of fibrosis-related genes in each group by real-time fluorescent polymerase chain amplification, and the expression of fibrosis-related proteins in the cells of each group by western blotting. RESULTS: Compared with the control group, the proliferation rate, migration rate, and collagen synthesis levels in the three experimental groups decreased with the increase of ADSCs-EXO concentration, while the apoptosis rate in the three experimental groups increased with the increase of ADSCs-EXO concentration, and the differences were statistically significant (P<0.05). Also, compared with the control group, the relative mRNA and protein expression of alpha-smooth muscle actin (α-SMA), TGF-ß1, and Smad3 in the three groups decreased significantly, while the expression of three kinds of mRNA and protein decreased with the increase of ADSCs-EXO concentration, and the differences were statistically significant (P<0.05). CONCLUSIONS: ADSCs-EXO may inhibit the proliferation and migration, and promote the apoptosis of KFs by inhibiting the expression of the TGF-ß1/Smad pathway.

Pilot scale evaluation on ferric floc sludge concentration with pelleting flocculation blanket process.

Pelleting flocculation blanket (PFB) process has been successfully applied to high turbidity suspensions for high efficient solid/liquid separation. In this paper, by using the PFB process, a dynamic experimental study was carried out on concentrating ferric flocs sludge with a scale of 1.3-5.4 m(3)/h. The pilot experiment aimed to optimize the conditioning system and determine the operational parameters. Under the raw sludge concentrations of 103-1,154 mg/L, the system could achieve ideal conditioning effect with polyacrylamide (PAM) dosages of 0.3-2.7 mg/L, agitation speed of 10 rpm, and water up-flow rates of 18-48 m/h. Under the experimental conditions, the increase of polymer dosage would improve effluent turbidity and pellets settling behaviour, the moderate up-flow rate had no marked effect on treatment results, while too large surface loading could worsen effluent turbidity. The experimental results also revealed that there existed an approximately linear relationship between the raw sludge concentration and optimum PAM dosage, that is, the optimum dosage of PAM increased synchronously as the raw sludge concentration increased. While the relationship between the raw sludge concentration and maximum up-flow rate reflected another linear dependence, namely, the maximum up-flow rate would decreased linearly as the raw sludge concentration increased.