China special issue on gastrointestinal tumors-Radiological features of pathological complete response in mismatch repair deficient colorectal cancer after neoadjuvant PD-1 blockade: A post hoc analysis of the PICC phase II trial.

Neoadjuvant programmed cell death protein 1 (PD-1) blockade exhibits promising efficacy in patients with mismatch repair deficient (dMMR) colorectal cancer (CRC). However, discrepancies between radiological and histological findings have been reported in the PICC phase II trial (NCT03926338). Therefore, we strived to discern radiological features associated with pathological complete response (pCR) based on computed tomography (CT) images. Data were obtained from the PICC trial that included 36 tumors from 34 locally advanced dMMR CRC patients, who received neoadjuvant PD-1 blockade for 3 months. Among the 36 tumors, 28 (77.8%) tumors achieved pCR. There were no statistically significant differences in tumor longitudinal diameter, the percentage change in tumor longitudinal diameter from baseline, primary tumor sidedness, clinical stage, extramural venous invasion status, intratumoral calcification, peritumoral fat infiltration, intestinal fistula and tumor necrosis between the pCR and non-pCR tumors. Otherwise, tumors with pCR had smaller posttreatment tumor maximum thickness (median: 10 mm vs 13 mm, P = .004) and higher percentage decrease in tumor maximum thickness from baseline (52.9% vs 21.6%, P = .005) compared to non-pCR tumors. Additionally, a higher proportion of the absence of vascular sign (P = .003, odds ratio [OR] = 25.870 [95% CI, 1.357-493.110]), nodular sign (P < .001, OR = 189.000 [95% CI, 10.464-3413.803]) and extramural enhancement sign (P = .003, OR = 21.667 [2.848-164.830]) was observed in tumors with pCR. In conclusion, these CT-defined radiological features may have the potential to serve as valuable tools for clinicians in identifying patients who have achieved pCR after neoadjuvant PD-1 blockade, particularly in individuals who are willing to adopt a watch-and-wait strategy.

CT-based deep learning model for the prediction of DNA mismatch repair deficient colorectal cancer: a diagnostic study.

BACKGROUND: Stratification of DNA mismatch repair (MMR) status in patients with colorectal cancer (CRC) enables individual clinical treatment decision making. The present study aimed to develop and validate a deep learning (DL) model based on the pre-treatment CT images for predicting MMR status in CRC. METHODS: 1812 eligible participants (training cohort: n = 1124; internal validation cohort: n = 482; external validation cohort: n = 206) with CRC were enrolled from two institutions. All pretherapeutic CT images from three dimensions were trained by the ResNet101, then integrated by Gaussian process regression (GPR) to develop a full-automatic DL model for MMR status prediction. The predictive performance of the DL model was evaluated using the area under the receiver operating characteristic curve (AUC) and then tested in the internal and external validation cohorts. Additionally, the participants from institution 1 were sub-grouped by various clinical factors for subgroup analysis, then the predictive performance of the DL model for identifying MMR status between participants in different groups were compared. RESULTS: The full-automatic DL model was established in the training cohort to stratify the MMR status, which presented promising discriminative ability with the AUCs of 0.986 (95% CI 0.971-1.000) in the internal validation cohort and 0.915 (95% CI 0.870-0.960) in the external validation cohort. In addition, the subgroup analysis based on the thickness of CT images, clinical T and N stages, gender, the longest diameter, and the location of tumors revealed that the DL model showed similar satisfying prediction performance. CONCLUSIONS: The DL model may potentially serve as a noninvasive tool to facilitate the pre-treatment individualized prediction of MMR status in patients with CRC, which could promote the personalized clinical-making decision.

Analysis of factors influencing patient delay by patients with pulmonary tuberculosis in Lishui City, Zhejiang Province.

OBJECTIVE: The purpose of this study was to collect data on the current state of patient delay by patients with tuberculosis (TB) in Lishui City, Zhejiang Province who were under the care of a TB-designated hospital from 2011 to 2021 and to analyze the factors that contribute to this problem in order to provide a scientific basis for the prevention and control of TB. METHODS: In this observational study, we collected data on patients with pulmonary TB that were reported to the Chinese government's disease prevention and control information system by the Traditional Chinese Medicine Hospital in Lishui City between 2011 and 2021. The data included demographics like age, gender, occupation, household registration, current address, date of symptoms, date of first visit, and etiology results. Multivariate logistic regression analysis was used to analyze the factors influencing patient delay by patients with pulmonary TB. RESULTS: There were 3,190 cases of pulmonary TB treated in a TB-designated hospital in Lishui City, Zhejiang Province, between 2011 and 2021. Of these, 2,268 involved patient delay, with the delay rate of 71.10% and the median (Q25, Q75) days of patient delay being 36 (25, 72) days. Results of multivariate logistic regression analysis indicated the presence of risk factors-age > 60 years old (OR = 1.367, 95% CI: 1.144 ~ 1.632), pathogen positive (OR = 1.211, 95% CI: 1.033 ~ 1.419), and employed as peasants (OR = 1.353, 95% CI:1.144 ~ 1.601) for patient delay in patients with pulmonary TB. Patients with diabetes mellitus made up 64.94% of the pulmonary TB population, which was lower than the 71.58% of patients without diabetes mellitus (χ2 = 4.602, P = 0.032). Additionally, the presence of diabetes mellitus may be a protective factor in patient delay in patients with pulmonary TB (OR = 0.641, 95% CI: 0.481 ~ 0.856). CONCLUSION: High rates of patient delay, age > 60 years old, a positive etiology, and being employed as peasants are all possible risk factors for pulmonary TB in Lishui City, Zhejiang Province.

Fluorescent Talarolactones from Talaromyces sp.

(+)-Talarolactone C (1), Talarolactone A (2), Talarolactone B (3, sulfoxide derivative), and Talarolactone D (4, sulfone derivative) were isolated from Talaromyces sp. which was cultured in rice medium with sodium butyrate. The structures of talarolactone analogs above were characterized by a combination of spectroscopic, X-ray crystallographic, and computational methods. These talarolactones and Talarolactone A sodium (5) with the same carbon skeleton showed different fluorescence characteristics.

Talarolactone A, an Isocoumarin Derivative Fused with Dihydrothiophene with Selective Antimigratory Activity from the Endolichenic Fungus Talaromyces sp.

A 3,4-dihydroisocoumarin derivative fused with dihydrothiophene, talarolactone A (1), and two known compounds, terreusinone (2) and 4,6-dihydroxy-5-methylphthalide (3), were isolated from Talaromyces sp. associated with Xanthoparmelia angustiphylla. The structure of 1 was deduced from extensive spectroscopic data, electronic circular dichroism calculations, and X-ray diffraction analyses. A plausible biosynthetic pathway of 1 was further proposed. Compound 1 showed selective antimigratory activity in a wound-healing assay without appreciable cytotoxic activity.

LeSAM: Adapt Segment Anything Model for medical lesion segmentation.

The Segment Anything Model (SAM) is a foundational model that has demonstrated impressive results in the field of natural image segmentation. However, its performance remains suboptimal for medical image segmentation, particularly when delineating lesions with irregular shapes and low contrast. This can be attributed to the significant domain gap between medical images and natural images on which SAM was originally trained. In this paper, we propose an adaptation of SAM specifically tailored for lesion segmentation termed LeSAM. LeSAM first learns medical-specific domain knowledge through an efficient adaptation module and integrates it with the general knowledge obtained from the pre-trained SAM. Subsequently, we leverage this merged knowledge to generate lesion masks using a modified mask decoder implemented as a lightweight U-shaped network design. This modification enables better delineation of lesion boundaries while facilitating ease of training. We conduct comprehensive experiments on various lesion segmentation tasks involving different image modalities such as CT scans, MRI scans, ultrasound images, dermoscopic images, and endoscopic images. Our proposed method achieves superior performance compared to previous state-of-the-art methods in 8 out of 12 lesion segmentation tasks while achieving competitive performance in the remaining 4 datasets. Additionally, ablation studies are conducted to validate the effectiveness of our proposed adaptation modules and modified decoder.

Texture analysis of apparent diffusion coefficient maps: can it identify nonresponse to neoadjuvant chemotherapy for additional radiation therapy in rectal cancer patients?

Background: Neoadjuvant chemotherapy (NCT) alone can achieve comparable treatment outcomes to chemoradiotherapy in locally advanced rectal cancer (LARC) patients. This study aimed to investigate the value of texture analysis (TA) in apparent diffusion coefficient (ADC) maps for identifying non-responders to NCT. Methods: This retrospective study included patients with LARC after NCT, and they were categorized into nonresponse group (pTRG 3) and response group (pTRG 0-2) based on pathological tumor regression grade (pTRG). Predictive texture features were extracted from pre- and post-treatment ADC maps to construct a TA model using RandomForest. The ADC model was developed by manually measuring pre- and post-treatment ADC values and calculating their changes. Simultaneously, subjective evaluations based on magnetic resonance imaging assessment of TRG were performed by two experienced radiologists. Model performance was compared using the area under the curve (AUC) and DeLong test. Results: A total of 299 patients from two centers were divided into three cohorts: the primary cohort (center A; n = 194, with 36 non-responders and 158 responders), the internal validation cohort (center A; n = 49, with 9 non-responders) and external validation cohort (center B; n = 56, with 33 non-responders). The TA model was constructed by post_mean, mean_change, post_skewness, post_entropy, and entropy_change, which outperformed both the ADC model and subjective evaluations with an impressive AUC of 0.997 (95% confidence interval [CI], 0.975-1.000) in the primary cohort. Robust performances were observed in internal and external validation cohorts, with AUCs of 0.919 (95% CI, 0.805-0.978) and 0.938 (95% CI, 0.840-0.985), respectively. Conclusions: The TA model has the potential to serve as an imaging biomarker for identifying nonresponse to NCT in LARC patients, providing a valuable reference for these patients considering additional radiation therapy.

Effects of the invasion of Ralstonia solanacearum on soil microbial community structure in Wuhan, China.

This study investigated the change in the microbiome of tomato rhizosphere soils after the invasion of Ralstonia solanacearum and analyzed the correlation between microbes and soil physicochemical properties. Diversity analyses of the bacteria in healthy and diseased rhizosphere soil samples (HRS and DRS) revealed that HRS had a higher species diversity and were compositionally different from DRS (P ≤ 0.05). Substantial differences in the relative abundance of Actinobacteria (37.52% vs 28.96%, P ≤ 0.05) and Proteobacteria (29.20% vs 35.59%, P ≤ 0.05) were identified in HRS and DRS, respectively. Taxonomic composition analysis showed ten differentially abundant genera, and seven of them (Gaiella, Roseisolibacter, Solirubrobacter, Kribbella, Acidibacter, Actinomarinicola, and Marmoricola) are more abundant in HRS. Soil pH and enzyme activities were negatively correlated with the abundance of R. solanacearum. The contents of total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkaline nitrogen (alkaline N), available phosphorus (AP), available potassium (AK), NO3-N(NN), NH4+-N (AN), and organic matter (OM) were all significantly increased in DRS. The composition and richness of protozoa in the samples show significant differences. Cephalobus, Acrobeles, Heteromita, norank_Tylenchida, and Rotylenchulus were enriched in DRS. Microbial interaction networks revealed that the HRS networks were more complex than the DRS networks. Overall, the results of this study demonstrate that healthy soil has a more complex microbial community structure and higher enzyme activity, and the invasion of R. solanacearum damages the soil microbial system.IMPORTANCEHow does the invasion of Ralstonia solanacearum affect tomato rhizosphere bacteria and protozoa? Which microbial changes can affect the growth of R. solanacearum? To date, most research studies focus on bacteria, with little research on protozoa, and even less on the synergistic effects between protozoa and bacteria. Here, we analyzed the correlation between tomato rhizosphere bacterial and protozoan communities and soil physicochemical properties during the invasion of R. solanacearum. We found that the diversity and abundance of rhizosphere microorganisms in healthy rhizosphere soil samples (HRS) were significantly higher than those in diseased rhizosphere soil samples (DRS), and there were significant changes in soil pH and enzyme activity. Overall, in this study, the analysis of microbial changes during the invasion of R. solanacearum provides a theoretical basis for the prevention and control of bacterial wilt.

Nanoparticles targeting OPN loaded with BY1 inhibits vascular restenosis by inducing FTH1-dependent ferroptosis in vascular smooth muscle cells.

Vascular restenosis following angioplasty continues to pose a significant challenge. The heterocyclic trioxirane compound [1, 3, 5-tris((oxiran-2-yl)methyl)-1, 3, 5-triazinane-2, 4, 6-trione (TGIC)], known for its anticancer activity, was utilized as the parent ring to conjugate with a non-steroidal anti-inflammatory drug, resulting in the creation of the spliced conjugated compound BY1. We found that BY1 induced ferroptosis in VSMCs as well as in neointima hyperplasia. Furthermore, ferroptosis inducers amplified BY1-induced cell death, while inhibitors mitigated it, indicating the contribution of ferroptosis to BY1-induced cell death. Additionally, we established that ferritin heavy chain1 (FTH1) played a pivotal role in BY1-induced ferroptosis, as evidenced by the fact that FTH1 overexpression abrogated BY1-induced ferroptosis, while FTH1 knockdown exacerbated it. Further study found that BY1 induced ferroptosis by enhancing the NCOA4-FTH1 interaction and increasing the amount of intracellular ferrous. We compared the effectiveness of various administration routes for BY1, including BY1-coated balloons, hydrogel-based BY1 delivery, and nanoparticles targeting OPN loaded with BY1 (TOP@MPDA@BY1) for targeting proliferated VSMCs, for prevention and treatment of the restenosis. Our results indicated that TOP@MPDA@BY1 was the most effective among the three administration routes, positioning BY1 as a highly promising candidate for the development of drug-eluting stents or treatments for restenosis.

Oral contraceptive pills for endometriosis after conservative surgery: a systematic review and meta-analysis.

To assess the effects of oral contraceptive pills (OCPs) for endometriosis in women after conservative surgery, we performed a search of PubMed, Embase, ISI Web of Science, Cochrane Library, Scidirect, Chinese VIP, CNKI and WANGFANG database. Randomized controlled trials (RCTs) of OCPs in postoperative medical therapy for endometriosis were collected. Articles published as of January 2013 with no language restriction were identified using defined keywords, and 15 studies comprising 1850 patients were included. There was a significantly higher rate of total endometriosis remission [OR = 2.55, 95% CI (1.68, 3.86), p < 0.00001] and a lower rate of recurrence [OR = 0.31, 95% CI (0.22, 0.45), p < 0.00001] in the OCPs group compared with surgery alone. There appears to be no statistical difference in pregnancy rates between the OCPs group as compared with surgery alone or other hormonal drug treatments in infertility patients. As for the rate of recurrence and complete remission, there were no statistical differences among OCPs and gestrinone, mifepristone or GnRH-a groups. However, OCPs users had less side effects that were more mild as compared with patients using other hormonal treatments.

Unsharp Structure Guided Filtering for Self-Supervised Low-Dose CT Imaging.

Low-dose computed tomography (LDCT) imaging faces great challenges. Although supervised learning has revealed great potential, it requires sufficient and high-quality references for network training. Therefore, existing deep learning methods have been sparingly applied in clinical practice. To this end, this paper presents a novel Unsharp Structure Guided Filtering (USGF) method, which can reconstruct high-quality CT images directly from low-dose projections without clean references. Specifically, we first employ low-pass filters to estimate the structure priors from the input LDCT images. Then, inspired by classical structure transfer techniques, deep convolutional networks are adopted to implement our imaging method which combines guided filtering and structure transfer. Finally, the structure priors serve as the guidance images to alleviate over-smoothing, as they can transfer specific structural characteristics to the generated images. Furthermore, we incorporate traditional FBP algorithms into self-supervised training to enable the transformation of projection domain data to the image domain. Extensive comparisons and analyses on three datasets demonstrate that the proposed USGF has achieved superior performance in terms of noise suppression and edge preservation, and could have a significant impact on LDCT imaging in the future.

Masked Joint Bilateral Filtering via Deep Image Prior for Digital X-Ray Image Denoising.

Medical image denoising faces great challenges. Although deep learning methods have shown great potential, their efficiency is severely affected by millions of trainable parameters. The non-linearity of neural networks also makes them difficult to be understood. Therefore, existing deep learning methods have been sparingly applied to clinical tasks. To this end, we integrate known filtering operators into deep learning and propose a novel Masked Joint Bilateral Filtering (MJBF) via deep image prior for digital X-ray image denoising. Specifically, MJBF consists of a deep image prior generator and an iterative filtering block. The deep image prior generator produces plentiful image priors by a multi-scale fusion network. The generated image priors serve as the guidance for the iterative filtering block, which is utilized for the actual edge-preserving denoising. The iterative filtering block contains three trainable Joint Bilateral Filters (JBFs), each with only 18 trainable parameters. Moreover, a masking strategy is introduced to reduce redundancy and improve the understanding of the proposed network. Experimental results on the ChestX-ray14 dataset and real data show that the proposed MJBF has achieved superior performance in terms of noise suppression and edge preservation. Tests on the portability of the proposed method demonstrate that this denoising modality is simple yet effective, and could have a clinical impact on medical imaging in the future.

Locally advanced rectal mucinous adenocarcinoma: is preoperative radiation necessary?

Background: Neoadjuvant chemoradiotherapy is recommended for locally advanced rectal cancer, allowing preoperative down-staging of the primary tumor to facilitate complete surgical removal. However, further investigation is warranted for identifying whether radiotherapy is necessary for rectal mucinous adenocarcinoma (RMAC). Thus, this study was designed to explore the relationship between mFOLFOX6 with or without preoperative radiotherapy and therapeutic efficacy in locally advanced RMAC. Methods: A total of 81 patients were retrospectively enrolled, with MRI-defined clinical stage II/III RMAC received neoadjuvant treatment with mFOLFOX6 alone (group A) or mFOLFOX6 plus radiation (group B), followed by total mesorectal excision. Tumor down-staging and tumor response were assessed based on post-treatment MRI-defined radiographical and pathological findings. Follow-up data were retrieved, and the Kaplan-Meier curve was used to determine the relationship between the 3-year disease-free survival (DFS) and overall survival (OS) in the two groups. Results: There were no significant differences in the clinical baseline characteristics of patients between group A and group B. The sphincter preservation rate in group B was 60.9%, higher than in group A (20.0%) (P=0.031). The rate of pathological complete response (pCR) was 14.0% in group B, while no patients had pCR in group A (P=0.029), and the tumor response rate in group B was higher than in group A (52.0% vs. 16.1%, P=0.001). The 3-year probability of OS in group A and B was 77.4% and 72.0% (P=0.509), and 3-year DFS was 58.1% and 56.0% (P=0.592), respectively. Conclusions: Neoadjuvant mFOLFOX6-based chemoradiotherapy could be a promising therapeutic option for patients with RMAC, which was associated with a high rate of pCR and sphincter preservation in comparison to treated with mFOLFOX6 alone.

Long non-coding RNA RP11-379k17.4 derived microRNA-200c-3p modulates human endometrial cancer by targeting Noxa.

Objective: The research paid close attention to the function of lncRNA-related endogenous competitive RNAs (ceRNAs) network in endometrial cancer (EC). Methods: 45 primary endometrial cancer tissues (EC) and 45 normal endometrium (NE) were included in the research. The online software StarbaseV2.0 was made use of forecasting the lncRNA which most likely contained microRNA-200c-3p combining sites and could interact with microRNA-200c-3p. Subsequently, we chose lncRNAs which were consistent with the characteristics of polyadenylation of lncRNAs and lower expression in EC than that of NE. After that, lncRNAs, which were related with the microRNA-200c-3p-noxa network, were identified. Results: Rp11-379k17.4, a new gene related to endometrial cancer, was identified as noncoding RNA. It was a more effective ceRNA associated with the microRNA-200c-3p-noxa network. Conclusion: LncRNAs possess microRNA response elements (MREs) and give scope to significant roles in the post-transcriptional mechanism in EC.

LncRNA RP11-395G23.3 suppresses the endometrial cancer progression via regulating microRNA-205-5p/PTEN axis.

The focal point of this research was the functional role of RP11-395G23.3 in endometrial cancer (EC). The expression of RP11-395G23.3, microRNA (miRNA)-205-5p, and their target proteins were detected by quantitative real-time polymerase chain reaction and western-blot analyses. Flow cytometry and proliferation, Transwell, and wound healing assays were used to detect the effects of RP11-395G23.3 and miRNA-205-5p on tumor cell migration and proliferation in vitro. RP11-395G23.3 expression was negatively related to miRNA-205-5p, but positively related to phosphatase and tensin homolog (PTEN) expression in human EC tissues. We discovered that low RP11-395G23.3 expression was significantly related to advanced histological grade and lymphovascular space invasion in EC patients. In addition, overexpression of RP11-395G23.3 significantly inhibited the proliferation, invasion, migration, and induced apoptosis of Ishikawa and HEC-1A cells in vitro. Our results also showed that RP11-395G23.3 could directly bind to miRNA-205-5p through its miRNA response elements and eliminate the inhibitory effect of targeting gene PTEN, thus leading to the signaling pathway of phosphatidylinositol-3-kinase/AKT inactivation. We demonstrated for the first time that RP11-395G23.3 may inhibit the development and pathogenesis of EC by acting as a sponge for miRNA-205-5p and increasing PTEN expression. RP11-395G23.3 may be a target for the diagnosis and treatment of EC.

MicroRNA-138 inhibits tumor growth and enhances chemosensitivity in human cervical cancer by targeting H2AX.

MicroRNA-138 (miR-138) acts as a key regulator in the modulation of carcinogenesis in numerous tumor types. Chemoresistance is common and relevant to the failure of multiple treatment strategies for cervical cancer. However, the biological role of miR-138 in the progression and chemosensitivity of cervical cancer is still unclear. The present study aimed to investigate the expression, function and mechanism of miR-138 in cervical cancer. An miR-138 mimic, inhibitor and negative control were transfected into SiHa and C33A cells. The expression of miR-138 and its target were assessed by reverse transcription-PCR, western blotting and immunohistochemistry. The functional significance of miR-138 in tumor progression and chemosensitivity to cisplatin in vitro was examined by Cell Counting Kit-8, flow cytometry, wound healing and Transwell assays. A tumor xenograft model was used to validate the effects in vivo. These results demonstrated that miR-138 was significantly downregulated in cervical cancer cells. Overexpression of miR-138 suppressed cervical cancer cell proliferation, invasion, increased apoptosis and enhanced chemotherapy sensitivity in vivo and in vitro. Furthermore, bioinformatics analysis and dual luciferase reporter assays demonstrated that H2AX served as a target for miR-138, and the rescue experiment revealed that H2AX was a functional target of miR-138. The protective effects of miR-138 overexpression were dependent on H2AX. This study provides evidence that miR-138/H2AX may be a novel therapeutic target in cervical cancer.

lncRNA LA16c­313D11.11 modulates the development of endometrial cancer by binding to and inhibiting microRNA­205­5p function and indirectly increasing PTEN activity.

The aim of the present study was to determine the competitive endogenous RNA (ceRNA) network associated with long­coding RNA (lncRNA) LA16c­313D11.11 in endometrial cancer (EC). Initially, the expression levels of LA16c­313D11.11 in 60 EC tissues, 20 atypical hyperplasia endometrium (EAH) tissues and 20 normal endometrium tissues was determined. MicroRNA (miRNA/miR)­205­5p mimics and LA16c­313D11.11 mimics were transfected into HEC­1A and Ishikawa cells. The expression levels of miR­205­5p, LA16c­313D11.11 and their target proteins were assessed using reverse transcription­quantitative PCR or western blot analysis. Flow cytometry, Cell Counting kit­8 assays, Transwell migration assays and wound healing assays were performed to assess the effects of LA16c­313D11.11 and miR­205­5p on the migration and proliferation of tumor cells in vitro. The expression levels of LA16c­313D11.11 and phosphatase and tensin homolog deleted on chromosome ten (PTEN) in human EAH and EC tissues were significantly decreased, whereas the expression levels of miR­205­5p in EAH and EC tissues were significantly increased, compared with the normal endometrium tissues. The expression of LA16c­313D11.11 in human EC tissues negatively correlated with the expression of miR­205­5p. Additionally, the overexpression of LA16c­313D11.11 significantly reduced the invasion, migration and viability of HEC­1A and Ishikawa cells in vitro. LA16c­313D11.11 was shown to regulate the expression of PTEN, and the invasion, migration and viability of HEC­1A and Ishikawa cells, through its microRNA response element to compete for microRNA­205­5p. LA16c­313D11.11 was also shown to modulate the PI3K/AKT signaling pathway. Therefore, LA16c­313D11.11 acts as an effective ceRNA associated with a microRNA­205­5p­PTEN axis. LA16c­313D11.11 may inhibit the development and progression of EC by acting as a sponge of miR­205­5p, thus indirectly increasing the expression of PTEN.

Key factors of clinical research network capacity building.

In general, clinical research network capacity building refers to programs aimed at enhancing networks of researchers to conduct clinical research. Although in the literature there is a large body of research on how to develop and build capacity in clinical research networks, the conceptualizations and implementations remain controversial and challenging. Moreover, the experiences learnt from the past accomplishments and failures can assist in the future capacity building efforts to be more practical, effective and efficient. In this paper, we aim to provide an overview of capacity building in clinical research network by (1) identifying the key barriers to clinical research network capacity building, (2) providing insights into how to overcome those obstacles, and (3) sharing our experiences in collaborating with national and international partners to build capacity in clinical research networks. In conclusion, we have provided some insight into how to address the key factors of clinical research network capacity building and shared some empirical experiences. A successful capacity building practice requires a joint endeavor to procure sufficient resources and support from the relevant stakeholders, to ensure its efficiency, cost-effectiveness, and sustainability.

Long non-coding RNA derived miR-205-5p modulates human endometrial cancer by targeting PTEN.

OBJECTIVE: This study was to investigate the roles of lncRNA associated competitive endogenous RNAs (ceRNAs) network in the endometrial cancer (EC). METHODS: StarbaseV2.0 online software was used to predict the most probable lncRNAs which contain miR-205-5p binding site and are competent to interact with miR-205-5p. Then, lncRNAs which had decreased expression in EC compared with normal endometrium and conformed to the polyadenylated characteristics of lncRNAs were selected and then lncRNAs associated with miR-205-5p-PTEN network were identified. RESULTS: Two novel genes RP11-395G23.3 and LA16c-313D11.11 associated with endometrial cancer were identified and proved to be non-coding RNAs. They were more effective ceRNAs associated with the miR-205-5p-PTEN network. CONCLUSION: Our results suggest that lncRNAs harbor MREs (miRNA response elements) and play important roles in the post-transcriptional regulation in EC.

Key factors of clinical research network capacity building

In general, clinical research network capacity building refers to programs aimed at enhancing networks of researchers to conduct clinical research. Although in the literature there is a large body of research on how to develop and build capacity in clinical research networks, the conceptualizations and implementations remain controversial and challenging. Moreover, the experiences learnt from the past accomplishments and failures can assist in the future capacity building efforts to be more practical, effective and efficient. In this paper, we aim to provide an overview of capacity building in clinical research network by (1) identifying the key barriers to clinical research network capacity building, (2) providing insights into how to overcome those obstacles, and (3) sharing our experiences in collaborating with national and international partners to build capacity in clinical research networks. In conclusion, we have provided some insight into how to address the key factors of clinical research network capacity building and shared some empirical experiences. A successful capacity building practice requires a joint endeavor to procure sufficient resources and support from the relevant stakeholders, to ensure its efficiency, cost-effectiveness, and sustainability.(AU)