Adhesive cryogel particles for bridging confined and irregular tissue defects.

BACKGROUND: Reconstruction of damaged tissues requires both surface hemostasis and tissue bridging. Tissues with damage resulting from physical trauma or surgical treatments may have arbitrary surface topographies, making tissue bridging challenging. METHODS: This study proposes a tissue adhesive in the form of adhesive cryogel particles (ACPs) made from chitosan, acrylic acid, 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) and N-hydroxysuccinimide (NHS). The adhesion performance was examined by the 180-degree peel test to a collection of tissues including porcine heart, intestine, liver, muscle, and stomach. Cytotoxicity of ACPs was evaluated by cell proliferation of human normal liver cells (LO2) and human intestinal epithelial cells (Caco-2). The degree of inflammation and biodegradability were examined in dorsal subcutaneous rat models. The ability of ACPs to bridge irregular tissue defects was assessed using porcine heart, liver, and kidney as the ex vivo models. Furthermore, a model of repairing liver rupture in rats and an intestinal anastomosis in rabbits were established to verify the effectiveness, biocompatibility, and applicability in clinical surgery. RESULTS: ACPs are applicable to confined and irregular tissue defects, such as deep herringbone grooves in the parenchyma organs and annular sections in the cavernous organs. ACPs formed tough adhesion between tissues [(670.9 ± 50.1) J/m2 for the heart, (607.6 ± 30.0) J/m2 for the intestine, (473.7 ± 37.0) J/m2 for the liver, (186.1 ± 13.3) J/m2 for muscle, and (579.3 ± 32.3) J/m2 for the stomach]. ACPs showed considerable cytocompatibility in vitro study, with a high level of cell viability for 3 d [(98.8 ± 1.2) % for LO2 and (98.3 ± 1.6) % for Caco-2]. It has comparable inflammation repair in a ruptured rat liver (P = 0.58 compared with suture closure), the same with intestinal anastomosis in rabbits (P = 0.40 compared with suture anastomosis). Additionally, ACPs-based intestinal anastomosis (less than 30 s) was remarkably faster than the conventional suturing process (more than 10 min). When ACPs degrade after surgery, the tissues heal across the adhesion interface. CONCLUSIONS: ACPs are promising as the adhesive for clinical operations and battlefield rescue, with the capability to bridge irregular tissue defects rapidly.

Comparison of the effects of buffalo LIF and mouse LIF on the in vitro culture of buffalo spermatogonia.

Leukemia inhibitory factor (LIF) is an important growth factor that supports the culture and maintenance of spermatogonial stem cells (SSCs) by suppressing spontaneous differentiation. Different LIF sequences may lead to differences in function. The protein sequences of buffalo LIF and mouse LIF differed by 65.5% according to MEGA software analysis. The PB-LIF-GFP-Puro vector was constructed, and the CHO-K1 cell line was established. The final LIF protein concentration in the CHO-K1 cell culture medium was approximately 4.268 ng/mL. Here, we report that buffalo LIF effectively maintains the self-renewal of buffalo spermatogonia during culture. Buffalo spermatogonia were cultured in conditioned medium containing no LIF (0 ng/mL), mouse LIF (1 ng/mL), mouse LIF (10 ng/mL), or buffalo LIF (1 ng/mL). Furthermore, the effects of mouse LIF and buffalo LIF culture on the maintenance of buffalo spermatogonia were determined by analyzing cell colony formation, quantitative real-time polymerase chain reaction, cell immunofluorescence, and cell counting. The buffalo LIF (1 ng/mL) group showed similar maintenance of the proliferation of buffalo spermatogonia to that in the mouse LIF (10 ng/mL) group. These results demonstrated that the proliferation of buffalo spermatogonia can be maintained in vitro by adding a low dose of buffalo LIF. This study provides a foundation for the further optimization of in vitro buffalo SSC culture systems.

Biologic therapy for Crohn's disease over the last 3 decades.

BACKGROUND: Despite the overload of publications on Crohn's disease (CD), no comprehensive analysis of biologic therapy for CD has been reported. AIM: To determine knowledge gaps and identify areas of interest of biologic therapy for CD. METHODS: The top 100 highest-cited original articles were identified from January 1991 to December 2020 in the Clarivate Analytics Web of Science Core Collection database. We conducted a bibliometric analysis of biologic therapy for CD based on total citations, summarized the bibliographic information of the articles related to CD biologic therapy, and explored the research hotspots. RESULTS: The top 100 highest-cited original articles were identified with total citations ranging from 307 to 2978. The 2000s (Period II, n = 66) yielded the most influential original articles and saw the most dramatic growth. Among the top 10 countries, including 8 European countries and 2 North American countries, the United States (n = 37) and Belgium (n = 20) contributed the most publications. Among the top 10 institutions, the University Hospital Gasthuisberg in Belgium (n = 23), the University of Chicago in the United States (n = 20), and the Mayo Clinic in the United States (n = 17) published the most papers. Regarding authors, Rutgeerts P in Belgium (n = 32), Sandborn WJ in the United States (n = 23), and Feagan BG in Canada (n = 18) published the highest number of studies. The cooperation relationships between the United States and Europe were most frequent. Gastroenterology (impact factor = 22.682) published the most articles on biologic therapy for CD (n = 32) with 17654 total citations. Anti-tumor necrosis factor biologics and monoclonal antibodies were the most studied topics. CONCLUSION: The bibliometric analysis emphasized the key contributions to the development of the specialized field. These data would provide useful research insights into biologic therapy for CD for clinicians and researchers.

Artificial intelligence in gastroenterology and hepatology: Status and challenges.

Originally proposed by John McCarthy in 1955, artificial intelligence (AI) has achieved a breakthrough and revolutionized the processing methods of clinical medicine with the increasing workloads of medical records and digital images. Doctors are paying attention to AI technologies for various diseases in the fields of gastroenterology and hepatology. This review will illustrate AI technology procedures for medical image analysis, including data processing, model establishment, and model validation. Furthermore, we will summarize AI applications in endoscopy, radiology, and pathology, such as detecting and evaluating lesions, facilitating treatment, and predicting treatment response and prognosis with excellent model performance. The current challenges for AI in clinical application include potential inherent bias in retrospective studies that requires larger samples for validation, ethics and legal concerns, and the incomprehensibility of the output results. Therefore, doctors and researchers should cooperate to address the current challenges and carry out further investigations to develop more accurate AI tools for improved clinical applications.

Laparoscopic surgery for early gallbladder carcinoma: A systematic review and meta-analysis.

BACKGROUND: There is a controversy as to whether laparoscopic surgery leads to a poor prognosis compared to the open approach for early gallbladder carcinoma (GBC). We hypothesized that the laparoscopic approach is an alternative for early GBC. AIM: To identify and evaluate the safety and feasibility of laparoscopic surgery in the treatment of early GBC. METHODS: A comprehensive search of online databases, including MEDLINE (PubMed), Cochrane libraries, and Web of Science, was performed to identify non-comparative studies reporting the outcomes of laparoscopic surgery and comparative studies involving laparoscopic surgery and open surgery in early GBC from January 2009 to October 2019. A fixed-effects meta-analysis was performed for 1- and 5-year overall survival and postoperative complications, while 3-year overall survival, operation time, blood loss, the number of lymph node dissected, and postoperative hospital stay were analyzed by random-effects models. RESULTS: The review identified 7 comparative studies and 8 non-comparative studies. 1068 patients (laparoscopic surgery: 613; open surgery: 455) were included in the meta-analysis of 1-, 3-, and 5-year overall survival with no significant differences observed [(HR = 0.54; 95%CI: 0.29-1.00; I 2 = 0.0%; P = 0.051), (HR = 0.75; 95%CI: 0.34-1.65; I 2 = 60.7%; P = 0.474), (HR = 0.71; 95%CI: 0.47-1.08; I 2 = 49.6%; P = 0.107), respectively]. There were no significant differences in operation time [weighted mean difference (WMD) = 18.69; 95%CI: -19.98-57.36; I 2 = 81.4%; P = 0.343], intraoperative blood loss (WMD = -169.14; 95%CI: -377.86-39.57; I 2 = 89.5%; P = 0.112), the number of lymph nodes resected (WMD = 0.12; 95%CI: -2.95-3.18; I 2 = 73.4%; P = 0.940), and the complication rate (OR = 0.69; 95%CI: 0.30-1.58; I 2 = 0.0%; P = 0.377 ) between the two groups, while patients who underwent laparoscopic surgery had a reduced length of hospital stay (WMD = -5.09; 95%CI: -8.74- -1.45; I 2 = 91.0%; P= 0.006). CONCLUSION: This systematic review and meta-analysis confirms that laparoscopic surgery is a safe and feasible alternative to open surgery with comparable survival and operation-related outcomes for early GBC.

Prognostic factors and predictors of postoperative adjuvant transcatheter arterial chemoembolization benefit in patients with resected hepatocellular carcinoma.

BACKGROUND: Postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE) has improved overall survival (OS) in patients with hepatocellular carcinoma (HCC). However, the prognostic and predictive factors remain unclear. AIM: To assess the prognostic factors and the predictors of PA-TACE benefit for OS in patients with resected HCC. METHODS: Univariate and multivariate analyses were performed to identify the potential prognostic factors for OS. In order to assess the predictive factors of PA-TACE benefit, the interaction variables between treatments for each subgroup were evaluated using the Cox proportional hazards regression model. RESULTS: A total of 378 patients (PA-TACE vs surgery alone, 189:189) from three centers were included after a propensity-score 1:1 matching analysis. Compared to the group receiving surgery alone, PA-TACE prolonged the OS rate in patients with resected HCC (P < 0.001). The Barcelona Clinic Liver Cancer system and ferritin-to-hemoglobin ratio (FHR) were used as the prognostic factors for OS in both groups. Age (P = 0.023) and microscopic vascular invasion (MVI) (P = 0.002) were also identified in the PA-TACE group, while gender (P = 0.027), hepatitis B virus (P = 0.034) and albumin-bilirubin grade (P = 0.027) were also selected in the surgery alone group. In addition, PA-TACE resulted in longer OS than surgery alone across subgroups [all hazard ratios (PA-TACE-to-surgery alone) < 1]. Notably, a significantly prolonged OS following PA-TACE was observed in patients with high FHR (P = 0.038) and without MVI (P = 0.048). CONCLUSION: FHR and Barcelona Clinic Liver Cancer stages were regarded as prognostic factors for OS. Moreover, high FHR and the absence of MVI were important predictive factors, which can be used to assist clinicians in selecting which patients could achieve a better OS with PA-TACE.

Explore the relationship between fish community and environmental factors by machine learning techniques.

In the face of multiple habitat alterations originating from both natural and anthropogenic factors, the fast-changing environments pose significant challenges for maintaining ecosystem integrity. Machine learning is a powerful tool for modeling complex non-linear systems through exploratory data analysis. This study aims at exploring a machine learning-based approach to relate environmental factors with fish community for achieving sustainable riverine ecosystem management. A large number of datasets upon a wide variety of eco-environmental variables including river flow, water quality, and species composition were collected at various monitoring stations along the Xindian River of Taiwan during 2005 and 2012. Then the complicated relationship and scientific essences of these heterogonous datasets are extracted using machine learning techniques to have a more holistic consideration in searching a guiding reference useful for maintaining river-ecosystem integrity. We evaluate and select critical environmental variables by the analysis of variance (ANOVA) and the Gamma test (GT), and then we apply the adaptive network-based fuzzy inference system (ANFIS) for an estimation of fish bio-diversity using the Shannon Index (SI). The results show that the correlation between model estimation and the biodiversity index is higher than 0.75. The GT results demonstrate that biochemical oxygen demand (BOD), water temperature, total phosphorus (TP), and nitrate-nitrogen (NO3-N) are important variables for biodiversity modeling. The ANFIS results further indicate lower BOD, higher TP, and larger habitat (flow regimes) would generally provide a more suitable environment for the survival of fish species. The proposed methodology not only possesses a robust estimation capacity but also can explore the impacts of environmental variables on fish biodiversity. This study also demonstrates that machine learning is a promising avenue toward sustainable environmental management in river-ecosystem integrity.