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.

[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.

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 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.

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.

[Effect of influent C/N on nitrogen removal performance in tidal flow constructed wetland via CANON process]. / 进水碳氮比对CANON型人工湿地脱氮性能的影响.

This study was conducted to explore nitrogen transformation and associated microbial characteristics in a tidal flow constructed wetland (TFCW) with the complete autotrophic nitrogen removal over nitrite (CANON) process under influent COD/TN (C/N) constraints. The influent C/N increased from 0.0 to 10.0 via the addition of glucose in the influent as a source of organics. The results showed that influent C/N significantly affected nitrogen transformation rates in the TFCW throughout the experiment. As the influent C/N increased from 0.0 to 6.0, the absolute abundance of functional genes involved in denitrification could be enriched as a consequence of the addition of organics in influent, and then the simultaneous nitrification, anammox, and denitrification (SNAD) processes occurred in the TFCW, resulting in the enhancement of nitrogen removal in the system. However, as the influent C/N was more than 6.0, the activity of aerobic ammonia-oxidizing bacteria was inhibited and its quantity reduced, leading to the deterioration in nitrogen removal of the system. When the influent C/N was 6.0, the SNAD process was enhanced most effectively in the system owing to the development of multiple and complete nitrogen removal pathways in the TFCW. The TFCW respectively had the best TN removal efficiency and removal loading rate [(93.3±2.3)% and (149.30±8.00) mg·L-1·d-1], indicating that the results had been than the maximal TN removal efficiency in a CANON process under ideal conditions.

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.