Background and purpose: At present, the treatment of elderly patients with ovarian cancer, espe-cially advanced ovarian cancer, tends to be conservative, and elderly patients often can not receive standard treatment. There are few treatment experiences and research data. This study aimed to investigate the treatment outcome, survival and prognostic factors of elderly patients with advanced epithelial ovarian cancer. Methods: This study retrospectively analyzed the clinical data for women older than 65 years diagnosed with stage Ⅲ and Ⅳ epithelial ovarian cancer between Apr. 2008 to Dec. 2012 in Chongqing Cancer Hospital. Results: Of the 181 women who met study criteria, 8.8％ received no treatment, 12.7％ underwent surgery alone, 15.5％ received chemotherapy alone, 33.2％ underwent non-standard treatment, 29.8％ underwent standard treatment. Baseline comparison of different treatment methods showed that the proportion of patients with cardiovascular and cerebrovascular diseases was lower in the standard treatment group. After Correcting the effect of cardio-cerebrovascular diseases, the median survival time of standard treatment (48 months) and the median survival time of non-standard treatment (47 months) were significantly longer than that of the other treatment groups (P<0.001). The median survival time of chemotherapy alone (26 months) was significantly longer than that of the surgery alone and untreated group (P<0.001), while the median survival time of surgery alone was similar to untreated group (9 months vs 8 months, P=0.269). Multivariate analysis using Cox model showed that treatment, residual lesion size, cardio-cerebrovascular diseases significantly impacted on survival time. Conclusion: Standard treatment was still the key factor for the best survival of elderly women with advanced ovarian cancer. When this is not offered or possible, chemother-apy alone offers better survival than surgery alone. However, surgery alone does not improve prognosis.

The management of patients with bulky positive lymph nodes who may not candidates for radical surgery and not response to concurrent chemoradiotherapy (CCRT) has unmet clinical need for years. Surgical excision of grossly involved pelvic or para-aortic lymph nodes has previously been suggested to provide a survival benefit. However, there are no guidelines for surgical resection of enlarged lymph nodes. We designed multicenter randomized controlled trial with 452 enrollments to evaluate lymphadenectomy in cervical cancer stage IIICr. Eligible patients are histologically confirmed cervical squamous cell carcinoma, adenocarcinoma, adeno-squamous cell carcinoma. Stage IIICr and the short diameter of image-positive lymph node ≥15 mm. Recruited patients will be randomized to the CCRT arm, or lymphadenectomy followed by CCRT arm. For better quality control, regardless of where the enlarged lymph nodes are located, the protocol calls for the excision of para-aortic lymph nodes to the level of the inferior mesenteric artery and all the pelvic lymph nodes. The removal of such large lymph nodes is quite difficult, there are some tips for surgeons. Although the no-touch method cannot be done for these patients, but unilateral reverse exposure of blood vessels and lymph nodes suggested to be use. To avoid holding the lymph nodes and reduce the use of electric energy instruments throughout the procedure. In this way, the lymph nodes can be completely and safely cut off. So far, 65 patients have been enrolled, with 32 in CCRT group, 33 in surgery group. There was no recurrence in surgery group and 2 in CCRT group. There were no surgery-related complications and no serious adverse event till now.

OBJECTIVETo study the effects of CD133 suppression by lentivirus-mediated RNA interference (RNAi) on the proliferation and chemosensitivity of CD133(+) cancer stem cells (CSCs) sorted from HepG2 cell line.

METHODSCD133(+) and CD133- cells were sorted from HepG2 cell line by flow cytometry, and the expression of CD133 before and after cell sorting were detected. The stem cell property of sorted CD133(+) cells were validated by sphere-forming assay in vitro and xenograft experiments in vivo. Lentivirus-mediated short hairpin RNA (shRNA) targeting CD133 were transfected into CD133(+) cells, and CD133 mRNA and protein expressions of the transfected cells were detected by RT-PCR and Western blotting, respectively. Before and after the transfection, the proliferative ability of CD133(+) cells was evaluated by colony formation assay, and the cell growth inhibition rate and apoptosis following cisplatin exposure were detected using CCK-8 assay and flow cytometry.

RESULTSThe sorted CD133(+) cells showed a high purity of (88.74∓3.19)%, as compared with the purity of (3.36∓1.80)% before cell sorting. CD133(+) cells showed a high tumor sphere formation ability and tumorigenesis capacity compared with CD133- cells. CD133 shRNA transfection significantly inhibited CD133 mRNA and protein expressions in CD133(+) cells (P<0.01), resulting also in a significantly lowered cell proliferative ability (P<0.01) and an increased growth inhibition rate (P<0.01) and obviously increased cell apoptosis (P<0.05) after cisplatin exposure.

CONCLUSIONLentivirus-mediated RNAi for CD133 suppression inhibits the proliferation of CD133(+) liver cancer stem cells and increases their chemosensitivity to cisplatin.

AC133 Antigen ; Antigens, CD ; genetics ; Cell Proliferation ; Cisplatin ; pharmacology ; Drug Resistance, Neoplasm ; Glycoproteins ; genetics ; Hep G2 Cells ; Humans ; Lentivirus ; Neoplastic Stem Cells ; cytology ; drug effects ; Peptides ; genetics ; RNA Interference

Objective:To investigate the risk factors for concomitant cardiac autonomic neuropathy in diabetic patients and to develop a Nomogram prediction model.Methods:One hundred and fifty-eight diabetic patients admitted to in Southern Hospital Zengcheng Branch from March 2019 to March 2021 were selected. Patients with normal heart rate variability were the diabetic group, and patients with abnormal heart rate variability were the group with diabetes mellitus complicated by cardiac autonomic neuropathy. Logistic regression analysis was used to analyze the risk factors of cardiac autonomic neuropathy. Nomogram models were developed and model performance was evaluated. Decision curve analysis (DCA) was used to assess the net clinical benefit of the Nomogram model.Results:Comparison of general data showed that fasting blood glucose, tumour necrosis factor-α (TNF-α), glomerular filtration rate (eGER), uric acid, C-reactive protein (CRP), interleukin-6 (IL-6), free fatty acids (FFA), standard deviation of sinus heart beat RR interval (SDNN), and duration of diabetes compared to the diabetic group had statistically significant ( P<0.05); the results of the subject work characteristics (ROC) curve analysis showed that the best cut-off values for fasting glucose, TNF-α, eGFR, uric acid, CRP, IL-6, FFA, SDNN and duration of diabetes were >7.53 mmol/L, >98.45 ng/L, ≤94.79 ml/(min·1.73 m 2), > 87.3 μmol/L, >6.22 μmol/L, >37.84 ng/L, >839.19 μmol/L, ≤ 95.88 ms, >9 years; multi-factorial Logistic regression analysis showed that fasting glucose (>7.53 mmol/L), TNF-α (>98.45 ng/L), CRP (>6.22 μmol/L), IL-6 (>37.84 ng/L), FFA (>839.19 μmol/L), SDNN (≤95.88 ms), and duration of diabetes (>9 years) were risk factors for the development of cardiac autonomic neuropathy in diabetic patients; internal validation showed that the Nomogram model predicted a C-index of 0.706 (95% CI 0.668 - 0.751) for the risk of cardiac autonomic neuropathy. The DCA results showed that the Nomogram model predicted a risk threshold of >0.25 for the development of cardiac autonomic neuropathy and that the Nomogram model provided a net clinical benefit. Conclusions:There are many risk factors for cardiac autonomic neuropathy, and the nomogram model based on risk factors in this study has good predictive power and may provide a reference for clinical screening of high-risk patients and further improvement of treatment planning.

Organoids,recognized as invaluable models in tumor and stem cell research,assume a pivotal role in the meticulous analysis of diverse datasets pertaining to their growth dynamics,drug screening processes and related phenomena.However,the manual scrutiny and conventional statistical methodologies employed in handling organoid data often grapple with challenges such as diminished precision and efficiency,heightened complexity,escalated human resource requirements,and a degree of subjectivity.Acknowledging the remarkable efficacy of artificial intelligence(AI)in the realms of biology and medicine,the incorporation of AI into organoid research stands poised to enhance the objectivity,precision and expediency of analyses.This integration empowers organoids to more effectively fulfill objectives such as disease modeling,drug screening and precision medicine.Notably,significant strides have been made in AI-driven analyses of organoid image data.The amalgamation of deep learning into image analysis facilitates a more meticulous delineation of the microstructural intricacies and nuanced changes within organoids,achieving a level of accuracy akin to that of experts.This not only elevates the precision of organoid morphology and growth recognition,but also contributes to substantial time and cost savings in research endeavors.Furthermore,the infusion of AI technology has yielded breakthroughs in the processing of organoid omics data,resulting in heightened efficiency in data processing and the identification of latent gene expression patterns.This furnishes novel tools for comprehending cellular development and unraveling the intricate mechanisms underlying various diseases.In addition to image data,AI techniques applied to diverse organoid datasets,encompassing electrical signals and spectra,have realized an unbiased classification of organoid types and states,embarking on a comprehensive journey towards characterizing organoids holistically.In the pivotal domain of drug screening for organoids,AI emerges as a stalwart companion,providing robust support for real-time process monitoring and result prediction.Leveraging high-content microscopy images and sophisticated deep learning models,researchers can dynamically monitor organoid responses to drugs,effecting non-invasive detection of drug impacts and amplifying the precision and efficiency of drug screening processes.Despite the significant strides made by AI in organoid research,challenges persist,encompassing hurdles in data acquisition,constraints in sample quality and quantity,and quandaries associated with model interpretability.Overcoming these challenges necessitates dedicated future research efforts aimed at enhancing data consistency,fortifying model interpretability,and exploring methodologies for the seamless fusion of multimodal data.Such endeavors are poised to usher in a more comprehensive and dependable application of AI in organoid research.In summation,the integration of AI technology introduces unparalleled opportunities to organoid research,resulting in noteworthy advancements.Nevertheless,interdisciplinary research and collaborative efforts remain imperative to navigate challenges and propel the more profound integration of AI into organoid research.The future holds promise for AI to assume an even more prominent role in advancing organoid research toward clinical translation and precision medicine.

Chronic Urticaria(CU)is a common skin disease involving autoimmunity and allergies,which brings a heavy burden to patients and society.The theory of traditional Chinese medicine"the Lung is combined with the Large Intestine,and the symptoms of large intestine can be reflected from the skin"has long shown that there is a close physiological and pathological relationship between the function of the Large Intestine and the skin.With the modern advancement of the"gut-skin axis"theory,the correlation between gut microbiome and CU has gradually become an emerging focus of research.Adjusting the imbalance of gut microbiome would be a new trend in the clinical treatment of CU.Acupuncture has a beneficial effect of regulating the gut microbiome,and the definite curative effect on CU.Therefore,this article summarized the research progress between the gut microbiome and CU in recent years,in order to discuss the feasibility of acupuncture to treat CU by regulating the gut microbiome,and provide a new idea for the mechanism research of acupuncture in the treatment of CU from the perspective of"treating skin from intestine".

Background: Cervical cancer is still present a major public health problem, especially in developing countries. In International Federation of Gynaecology and Obstetrics 2018, allowing assessment of retroperitoneal lymph nodes by imaging and/or pathological findings and, if deemed metastatic, the case is designated as stage IIIC (with r and p notations). Patients with lymph node metastases have lower overall survival (OS), progression free survival (PFS), and survival after recurrence, especially those who have unresectable macroscopical positive lymph nodes. Retrospective analysis suggests that there may be a benefit to debulking macroscopic nodes that would be otherwise difficult to sterilize with standard doses of radiation therapy. However, there are no prospective study reporting that resecting macroscopic nodes before concurrent chemoradiation therapy (CCRT) would improve PFS or OS of cervical cancer and no guidelines for surgical resection of bulky lymph nodes. The CQGOG0103 study is a prospective, multicenter and randomized controlled trial (RCT) evaluating lymph node dissection on stage IIICr of cervical cancer. Methods Eligible patients are histologically confirmed cervical squamous cell carcinoma, adenocarcinoma, adeno-squamous cell carcinoma. Stage IIICr (confirmed by computed tomography [CT]/magnetic resonance imaging/positron emission tomography/CT) and the short diameter of image-positive lymph node ≥15 mm. 452 patients will be equally randomized to receive either CCRT (pelvic external-beam radiotherapy [EBRT]/extended-field EBRT + cisplatin [40 mg/m2] or carboplatin [the area under curve=2] every week for 5 cycles + brachytherapy) or open/minimally invasive pelvic and para-aortic lymph node dissection followed by CCRT. Randomization is stratified by status of para-aortic lymph node. The primary endpoint is PFS. Secondary endpoints are OS and surgical complications. A total of 452 patients will be enrolled from multiple hospitals in China within 4 years and followed up for 5 years.

Background: The Lymphadenectomy in Ovarian Neoplasms (LION) study revealed that systemic lymphadenectomy did not bring survival benefit for advanced ovarian cancer patients with clinically normal lymph nodes and was associated with a higher incidence of operative complications. However, there is no consensus on whether lymphadenectomy has survival benefit or not in early epithelial ovarian cancer (EOC). Methods We designed the LOVE study, a multicenter, randomized controlled, phase III trial to compare the efficacy and safety of comprehensive staging surgery with or without lymphadenectomy in stages IA-IIB EOC and fallopian tube carcinomas (FTC). The hypothesis is that the oncological outcomes provided by comprehensive staging surgery without lymphadenectomy are non-inferior to those of conventional completion staging surgery in early-stage EOC and FTC patients who have indications for post-operative adjuvant chemotherapy. Patients assigned to experimental group will undergo comprehensive staging surgery, but lymphadenectomy. Patients assigned to comparative group will undergo completion staging surgery including systematic pelvic and para-aortic lymphadenectomy. All subjects will receive 3–6 cycles of standard adjuvant chemotherapy. Major inclusion criteria are pathologic confirmed stage IA-IIB EOC or FTC, and patients have indications for adjuvant chemotherapy either confirmed by intraoperative fast frozen section or previous pathology after an incomplete staging surgery. Major exclusion criteria are non-epithelial tumors and low-grade serous carcinoma. Patients with severe rectum involvement which lead to partial rectum resection will be excluded. The sample size is 656 subjects. Primary endpoint is disease-free survival.