Fetal Head and Pubic Symphysis Segmentation in Intrapartum Ultrasound Image Using a Dual-Path Boundary-Guided Residual Network.

Accurate segmentation of the fetal head and pubic symphysis in intrapartum ultrasound images and measurement of fetal angle of progression (AoP) are critical to both outcome prediction and complication prevention in delivery. However, due to poor quality of perinatal ultrasound imaging with blurred target boundaries and the relatively small target of the public symphysis, fully automated and accurate segmentation remains challenging. In this paper, we propse a dual-path boundary-guided residual network (DBRN), which is a novel approach to tackle these challenges. The model contains a multi-scale weighted module (MWM) to gather global context information, and enhance the feature response within the target region by weighting the feature map. The model also incorporates an enhanced boundary module (EBM) to obtain more precise boundary information. Furthermore, the model introduces a boundary-guided dual-attention residual module (BDRM) for residual learning. BDRM leverages boundary information as prior knowledge and employs spatial attention to simultaneously focus on background and foreground information, in order to capture concealed details and improve segmentation accuracy. Extensive comparative experiments have been conducted on three datasets. The proposed method achieves average Dice score of 0.908 ±0.05 and average Hausdorff distance of 3.396 ±0.66 mm. Compared with state-of-the-art competitors, the proposed DBRN achieves better results. In addition, the average difference between the automatic measurement of AoPs based on this model and the manual measurement results is 6.157 °, which has good consistency and has broad application prospects in clinical practice.

RTSeg-net: A lightweight network for real-time segmentation of fetal head and pubic symphysis from intrapartum ultrasound images.

The segmentation of the fetal head (FH) and pubic symphysis (PS) from intrapartum ultrasound images plays a pivotal role in monitoring labor progression and informing crucial clinical decisions. Achieving real-time segmentation with high accuracy on systems with limited hardware capabilities presents significant challenges. To address these challenges, we propose the real-time segmentation network (RTSeg-Net), a groundbreaking lightweight deep learning model that incorporates innovative distribution shifting convolutional blocks, tokenized multilayer perceptron blocks, and efficient feature fusion blocks. Designed for optimal computational efficiency, RTSeg-Net minimizes resource demand while significantly enhancing segmentation performance. Our comprehensive evaluation on two distinct intrapartum ultrasound image datasets reveals that RTSeg-Net achieves segmentation accuracy on par with more complex state-of-the-art networks, utilizing merely 1.86 M parameters-just 6 % of their hyperparameters-and operating seven times faster, achieving a remarkable rate of 31.13 frames per second on a Jetson Nano, a device known for its limited computing capacity. These achievements underscore RTSeg-Net's potential to provide accurate, real-time segmentation on low-power devices, broadening the scope for its application across various stages of labor. By facilitating real-time, accurate ultrasound image analysis on portable, low-cost devices, RTSeg-Net promises to revolutionize intrapartum monitoring, making sophisticated diagnostic tools accessible to a wider range of healthcare settings.

Diagnosis Framework for Probable Alzheimer's Disease and Mild Cognitive Impairment Based on Multi-Dimensional Emotion Features.

BACKGROUND: Emotion and cognition are intercorrelated. Impaired emotion is common in populations with Alzheimer's disease (AD) and mild cognitive impairment (MCI), showing promises as an early detection approach. OBJECTIVE: We aim to develop a novel automatic classification tool based on emotion features and machine learning. METHODS: Older adults aged 60 years or over were recruited among residents in the long-term care facilities and the community. Participants included healthy control participants with normal cognition (HC, n = 26), patients with MCI (n = 23), and patients with probable AD (n = 30). Participants watched emotional film clips while multi-dimensional emotion data were collected, including mental features of Self-Assessment Manikin (SAM), physiological features of electrodermal activity (EDA), and facial expressions. Emotional features of EDA and facial expression were abstracted by using continuous decomposition analysis and EomNet, respectively. Bidirectional long short-term memory (Bi-LSTM) was used to train classification model. Hybrid fusion was used, including early feature fusion and late decision fusion. Data from 79 participants were utilized into deep machine learning analysis and hybrid fusion method. RESULTS: By combining multiple emotion features, the model's performance of AUC value was highest in classification between HC and probable AD (AUC = 0.92), intermediate between MCI and probable AD (AUC = 0.88), and lowest between HC and MCI (AUC = 0.82). CONCLUSIONS: Our method demonstrated an excellent predictive power to differentiate HC/MCI/AD by fusion of multiple emotion features. The proposed model provides a cost-effective and automated method that can assist in detecting probable AD and MCI from normal aging.

Patients with MMAF induced by novel biallelic CFAP43 mutations have good fertility outcomes after intracytoplasmic sperm injection.

As a specific type of asthenoteratozoospermia, multiple morphological abnormalities of the sperm flagella (MMAF) is characterized by composite abnormalities, including absent, short, coiled, angulation, and irregular-caliber flagella. Mutations in cilia- and flagella-associated protein 43 ( CFAP43 ) are one of the main causative factors of MMAF established to date. To identify whether there are other CFAP43 mutations related to MMAF and to determine the clinical outcomes of assisted reproductive technology for patients with MMAF harboring different mutations, we recruited and screened 30 MMAF-affected Chinese men using a 22-gene next-generation sequencing panel. After systematic analysis, seven mutations in CFAP43 , including five novel mutations and two previously reported mutations, were identified from four families and related to MMAF in an autosomal recessive pattern. Papanicolaou staining, immunofluorescence, and electronic microscopy further clarified the semen characteristics and abnormal sperm morphologies, including disorganized axonemal and peri-axonemal structures, of the CFAP43 -deficient men. The female partners of two patients were pregnant after undergoing assisted reproductive technology through intracytoplasmic sperm injection, and one of them successfully gave birth to a healthy boy. This study significantly expands the mutant spectrum of CFAP43 , and together with the available information regarding male infertility and MMAF, provides new information for the genetic diagnosis and counseling of MMAF in the future.

Diffusion Behavior of VOC Molecules in Polyvinyl Chloride Investigated by Molecular Dynamics Simulation.

Due to the threats posed by many volatile organic compounds (VOCs) to human health in indoor spaces via air, the mass transfer characteristics of VOCs are of critical importance to the study of their mechanism and control. As a significant part of the mass transfer process, diffusion widely exists in emissions from floors (e.g., PVC floors) and in sorption in porous materials. Molecular simulation studies by can provide unparalleled insights into the molecular mechanisms of VOCs. We construct the detailed atomistic structures of PVC blend membranes to investigate the diffusion behavior of VOC molecules (n-hexane) in PVC by molecular dynamics (MD). The variation in the diffusion coefficient of n-hexane in PVC with respect to temperature is in line with Arrhenius' law. The effect of temperature on the diffusion mechanism was investigated from the perspectives of free volume, cavity distribution and polymer chain mobility. It was found that the relationships between the diffusion coefficients of n-hexane in the polymer and the inverse fractional free volume are exponential and agree well with the free volume theory. Hopefully, this study will offer quantitative insights into the mass transport phenomena of VOCs within polymeric materials.

A framework for computing angle of progression from transperineal ultrasound images for evaluating fetal head descent using a novel double branch network.

Background: Accurate assessment of fetal descent by monitoring the fetal head (FH) station remains a clinical challenge in guiding obstetric management. Angle of progression (AoP) has been suggested to be a reliable and reproducible parameter for the assessment of FH descent. Methods: A novel framework, including image segmentation, target fitting and AoP calculation, is proposed for evaluating fetal descent. For image segmentation, this study presents a novel double branch segmentation network (DBSN), which consists of two parts: an encoding part receives image input, and a decoding part composed of deformable convolutional blocks and ordinary convolutional blocks. The decoding part includes the lower and upper branches, and the feature map of the lower branch is used as the input of the upper branch to assist the upper branch in decoding after being constrained by the attention gate (AG). Given an original transperineal ultrasound (TPU) image, areas of the pubic symphysis (PS) and FH are firstly segmented using the proposed DBSN, the ellipse contours of segmented regions are secondly fitted with the least square method, and three endpoints are finally determined for calculating AoP. Results: Our private dataset with 313 transperineal ultrasound (TPU) images was used for model evaluation with 5-fold cross-validation. The proposed method achieves the highest Dice coefficient (93.4%), the smallest Average Surface Distance (6.268 pixels) and the lowest AoP difference (5.993°) by comparing four state-of-the-art methods. Similar results (Dice coefficient: 91.7%, Average Surface Distance: 7.729 pixels: AoP difference: 5.110°) were obtained on a public dataset with >3,700 TPU images for evaluating its generalization performance. Conclusion: The proposed framework may be used for the automatic measurement of AoP with high accuracy and generalization performance. However, its clinical availability needs to be further evaluated.

Multitask Deep Neural Network for the Fully Automatic Measurement of the Angle of Progression.

The angle of progression (AoP) for assessing fetal head (FH) descent during labor is measured from the standard plane of transperineal ultrasound images as the angle between a line through the long axis of pubic symphysis (PS) and a second line from the right end of PS tangentially to the contour of the FH. This paper presents a multitask network with a shared feature encoder and three task-special decoders for standard plane recognition (Task1), image segmentation (Task2) of PS and FH, and endpoint detection (Task3) of PS. Based on the segmented FH and two endpoints of PS from standard plane images, we determined the right FH tangent point that passes through the right endpoint of PS and then computed the AoP using the above three points. In this paper, the efficient channel attention unit is introduced into the shared feature encoder for improving the robustness of layer region encoding, while an attention fusion module is used to promote cross-branch interaction between the encoder for Task2 and that for Task3, and a shape-constrained loss function is designed for enhancing the robustness to noise based on the convex shape-prior. We use Pearson's correlation coefficient and the Bland-Altman graph to assess the degree of agreement. The dataset includes 1964 images, where 919 images are nonstandard planes, and the other 1045 images are standard planes including PS and FH. We achieve a classification accuracy of 92.26%, and for the AoP calculation, an absolute mean (STD) value of the difference in AoP (∆AoP) is 3.898° (3.192°), the Pearson's correlation coefficient between manual and automated AoP was 0.964 and the Bland-Altman plot demonstrates they were statistically significant (P < 0.05). In conclusion, our approach can achieve a fully automatic measurement of AoP with good efficiency and may help labor progress in the future.

DeepSSR: a deep learning system for structured recognition of text images from unstructured paper-based medical reports.

Background: Complete electronic health records (EHRs) are not often available, because information barriers are caused by differences in the level of informatization and the type of the EHR system. Therefore, we aimed to develop a deep learning system [deep learning system for structured recognition of text images from unstructured paper-based medical reports (DeepSSR)] for structured recognition of text images from unstructured paper-based medical reports (UPBMRs) to help physicians solve the data-sharing problem. Methods: UPBMR images were firstly preprocessed through binarization, image correction, and image segmentation. Next, the table area was detected with a lightweight network (i.e., the proposed YOLOv3-MobileNet model). In addition, the text of the table area was detected and recognized with the model based on differentiable binarization (DB) and convolutional recurrent neural network (CRNN). Finally, the recognized text was structured according to its row and column coordinates. DeepSSR was trained and validated on our dataset with 4,221 UPBMR images which were randomly split into training, validation, and testing sets in a ratio of 8:1:1. Results: DeepSSR achieved a high accuracy of 91.10% and a speed of 0.668 s per image. In the system, the proposed YOLOv3-MobileNet model for table detection achieved a precision of 97.8% and a speed of 0.006 s per image. Conclusions: DeepSSR has high accuracy and fast speed in structured recognition of text based on UPBMR images. This system may help solve the data-sharing problem due to information barriers between hospitals with different EHR systems.

Cardiotocography signal abnormality classification using time-frequency features and Ensemble Cost-sensitive SVM classifier.

BACKGROUND: Cardiotocography (CTG) signal abnormality classification plays an important role in the diagnosis of abnormal fetuses. This classification problem is made difficult by the non-stationary nature of CTG and the dataset imbalance. This paper introduces a novel application of Time-frequency (TF) features and Ensemble Cost-sensitive Support Vector Machine (ECSVM) classifier to tackle these problems. METHODS: Firstly, CTG signals are converted into TF-domain representations by Continuous Wavelet Transform (CWT), Wavelet Coherence (WTC), and Cross-wavelet Transform (XWT). From these representations, a novel image descriptor is used to extract the TF features. Then, the linear feature is derived from the time-domain representation of the CTG signal. The linear and TF features are fed to the ECSVM classifier for prediction and classification of fetal outcome. RESULTS: The TF features show the significant difference (p-value<0.05) in distinguishing abnormal CTG signals, but not for traditional nonlinear features. In ECSVM abnormality classification, using only linear features, the sensitivity, specificity, and quality index are 59.3%, 78.3%, and 68.1%, respectively, whereas more effective results (sensitivity: 85.2%, specificity: 66.1%, and quality index: 75.0%) are obtained using a combination of linear and TF features, with a performance improvement index of 10.1%. Especially, the area under the receiver operating characteristic curve (0.77 vs. 0.64) is significantly increased with the ECSVM vs. SVM. CONCLUSION: Our method can greatly improve the classification results, especially for sensitivity. It improves the true positive rate of CTG abnormality classification and reduces the false positive rate, which may help detect and treat abnormal fetuses during labor.

Optical fiber bio-sensor for phospholipase using liquid crystal.

A cost-effective and label-free optical fiber sensor was proposed to detect phospholipase A2 (PLA2) in nM concentration. The sensor is made of an alkoxysilane-modified side-polished fiber (SPF) coated with 4'-pentyl-4-cyanobiphenyl (5CB) and self-assembled phospholipid (L-DLPC). It is found that the relative transmission optical power (RTOP) of the fiber sensor decreases due to the 5CB realignment and redistribution induced by the PLA2 hydrolysis of L-DLPC. The response-time at 5 dB RTOP variation exhibits an exponential dependence on PLA2 concentration, allowing us to detect the PLA2 by the 5 dB-response time. This detection method can reduce the detection time. Compare with the traditional copper-grid sensor, the proposed novel fiber sensor has a lower detection limit (<1 nM). Furthermore, the sensor has good repeat-ability and specificity.The sensor's RTOP variation for PLA2 detection at 1 nM is ~21 times higher than that for five other enzymes (trypsin, amylase, thrombin, glucose oxidase, pepsin) at 1000 nM and lipase at 50 nM. This confirms the sensor's excellent PLA2 specificity. The fiber sensor provides a potential way to be incorporated into micro-flow chips to quantitatively detect biological molecules in a real-time and online manner.

Gefitinib plus Fuzheng Kang'ai Formula () in Patients with Advanced Non-Small Cell Lung Cancer with Epidermal Growth Factor Receptor Mutation: A Randomized Controlled Trial.

OBJECTIVE: To evaluate the effect of Fuzheng Kang'ai Formula (, FZKA) plus gefitinib in patients with advanced non-small cell lung cancer with epidermal growth factor receptor (EGFR) mutations. METHODS: A randomized controlled trial was conducted from 2009 to 2012 in South China. Seventy chemotherapynaive patients diagnosed with stage IIIB/IV non-small cell lung cancer with EGFR mutations were randomly assigned to GF group [gefitinib (250 mg/day orally) plus FZKA (250 mL, twice per day, orally); 35 cases] or G group (gefitinib 250 mg/day orally; 35 cases) according to the random number table and received treatment until progression of the disease, or development of unacceptable toxicities. The primary endpoint [progression-free survival (PFS)] and secondary endpoints [median survival time (MST), objective response rate (ORR), disease control rate (DCR) and safety] were observed. RESULTS: No patient was excluded after randomization. GF group had significantly longer PFS and MST compared with the G group, with median PFS of 12.5 months (95% CI 3.30-21.69) vs. 8.4 months (95% CI 6.30-10.50; log-rank P<0.01), MST of 21.5 months (95% CI 17.28-25.73) vs. 18.3 months (95% CI 17.97-18.63; log-rank P<0.01). ORR and DCR in GF group and G group were 65.7% vs. 57.1%, 94.3% vs. 80.0%, respectively (P>0.05). The most common toxic effects in the GF group and G group were rash or acne (42.8% vs. 57.1%, P>0.05), diarrhea (11.5% vs. 31.4%, P<0.05), and stomatitis (2.9% vs. 8.7%, P>0.05). CONCLUSION: Patients with advanced non-small cell lung cancer selected by EGFR mutations have longer PFS, MST with less toxicity treated with gefitinib plus FZKA than gefitinib alone.

[Combination of Jianpi Liqi Yiliu Formula with Cytokine-induced Killer Cell Treatment for Advanced Hepatocellular Carcinoma].

OBJECTIVE: To evaluate the clinical efficacy of Jianpi Liqi Yiliu Formula (JLYF) combined with cytokine-induced killer (CIK) cells for treating patients with advanced hepatocellular carcinoma (HCC). METHODS: Between January 2011 and January 2014, 60 advanced HCC patients were enrolled in this study, who were assigned to the treatment group and the control group according to their willingness for taking JLYF, 30 cases in each group. All patients received CIK cell treatment: 1 x 109-3 x 109 each time, by intravenous dripping from the 1st day to the 3rd day, once per day. Besides, patients in the treatment group took JLYF decoction, while those in the control group took Chinese medical decoction by syndrome typing. All patients received treatment of at least two cycles. The time to progression (TTP) , overall survival (OS), disease control rate (DCR), performance status scale (PS), Child-Pugh scale, and adverse reactions were observed, and subgroup analyzed. RESULTS: To May 31, 2014, all patients reached the clinical endpoint. TTP was 3.5 months (95% Cl: 3.30-4.10) in the treatment group, better than that (2.5 months, 95% CI: 2.32-2.68) of the control group (P < 0.05). DCR was 36.7% in the treatment group and 30.0% in the control group (P > 0.05). OS was 5.2 months (95% CI: 4.53-5.87) in the treatment group and 4.6 months (95% CI: 4.06-5.14) in the control group (P > 0.05). The PS scale was 1.60 ± 0.10 after treatment, lower than that (1.80 ± 0.09) before treatment in the treatment group (P < 0.05). When the PS scale was 0-2 or Child-Pugh scale was class A, TTP was longer in the treatment group than in the control group (P < 0.05). No adverse reaction occurred in the two groups during the treatment course. CONCLUSIONS: The combination of JLYF with ClK cell treatment could prolong advanced HCC patients' TTP, improve PS scale, as compared with syndrome typed Chinese medical decoction treatment group. Besides, when the PS scale was 0-2 or Child-Pugh scale was class A, it was a better treatment program for advanced HCC patients.

[Effect of Fuzheng Kang'ai Recipe Combined Gefitinib on Lung Cancer A549 Cells and Its Mecha- nism Research].

Objective To observe the effect of Fuzheng Kang'ai Recipe (FKR) combined ge- fitinib on the proliferation and apoptosis of lung cancer A549 cells , and to study its potential synergistic mechanish with gefitinib. Methods The effects of FKR (0. 211, 0. 316, 0. 474, 0. 711, 1. 067, 1. 600, 2. 400, 3. 600 mg/mL) combined gefitinib (3. 95, 5. 92, 8. 18, 13. 33, 20. 00, 30. 00, 45. 00, 67. 50 µmol/ L) on the proliferation of A549 cells were detected by MTT assay. The apoptosis of A549 cells in the control group (complete culture medium) , FKR (1. 6 mg/mL) , gefitinib (45 µmol/L) , and FKR plus gefitinib (1. 6 mg/mL +45 µmol/L) were detected by flow cytometry (FCM). Their expressions of epidermal growth factor receptor (EGFR) , phosphorylating epidermal growth factor receptor ( p-EGFR) , enhancer of zeste homolog 2 (EZH2), peroxisome proliferator-activated receptor-γ ( PPAR-γ) , and P53 protein in A549 cells were detected by Western blot. Results Both FKR and gefitinib could inhibit the proliferation of A549 cells. The apoptotic rate was 12. 6% ±4. 5% in the FKR combined gefitinib group, obviously higher than that of the FKR group (4. 6% ± 0. 7%) and the gefitinib group (7. 8% ± 2. 7%) , showing statistical difference (P <0. 05). Compared with the control group, the expressions of p-EGFR and EZH2 were sig- nificantly down-regulated (P <0. 05) , the expressions of PPAR-γ and P53 protein were up-regulated in the FKR combined gefitinib group (P <0. 05); the expression of EZH2 was down-regulated in the gefitinib group and the FKR group (P <0. 05) ; the expression of PPAR-y was up-regulated in the FKR group (P < 0. 05). Compared with the gefitinib group, the expression of p-EGFR was down-regulated, and the expression of PPAR-γ was up-regulated in the FKR combined gefitinib group (both P <0. 05). Compared with the FKR group, the expression of p-EGFR was down-regulated in the FKR combined gefitinib group (P < 0. 05). Conclusions Combination of FKR and gefitinib could significantly inhibit the proliferation and growth of A549 cells,and induce cell apoptosis. Its potential synergistic mechanism of anti-tumor activities might be associated with down-regulating mRNA expressions of p-EGFR and EZH2, and up-regulating protein expressions of PPAR-y and P53.

Fuzheng Kang'ai decoction combined with gefitinib in advanced non-small cell lung cancer patients with epidermal growth factor receptor mutations: study protocol for a randomized controlled trial.

BACKGROUND: Patients with advanced non-small cell lung cancer (NSCLC) harboring mutations of the epidermal growth factor receptor (EGFR) gene respond well to the EGFR tyrosine kinase inhibitor (TKI) gefitinib. Chinese herbal medicine (CHM) has been used as a complementary therapy for cancer for decades in China. CHM was proved to be effective in improving the quality of life (QOL) and reducing the toxicity associated with chemotherapy in patients with NSCLC. The purpose of the present trial is to determine whether CHM (Fuzheng Kang'ai decoction (FZKA), a CHM formula) combined with gefitinib results in longer progression-free survival with less toxicity than gefitinib alone. METHODS/DESIGN: This is a randomized, placebo-controlled, double-blind trial. This trial is designed to determine if CHM (FZKA) combined with gefitinib results in longer progression-free survival with less toxicity than gefitinib alone. A total of 70 NSCLC patients with EGFR mutations will be randomly assigned to treatment group (gefitinib plus FZKA granules) or control group (gefitinib plus placebo). The primary endpoint is progression-free survival. Secondary endpoints are: (1) overall survival; (2) disease control rate; (3) QOL, measured with the questionnaire of Functional Assessment of Cancer Therapy-lung (FACT-L 4.0) and Lung Cancer Symptom Scale and (4) safety. DISCUSSION: In previous clinical practice, we found that CHM (FZKA) could improve the therapeutic efficacy of gefitinib. This study will provide objective evidence to evaluate the efficiency of CHM combined with gefitinib in NSCLC patients with EGFR mutations, and may provide a novel regimen for patients with NSCLC. TRIAL REGISTRATION: Chinese Clinical Trial Registry ( www.chictr.org ): ChiCTR-IOR-14005679 , registered 17 December 2014.

Computed tomographic enterography adds value to colonoscopy in differentiating Crohn's disease from intestinal tuberculosis: a potential diagnostic algorithm.

BACKGROUND: Crohn's disease and intestinal tuberculosis (ITB) are chronic granulomatous disorders that are difficult to distinguish. Computed tomographic enterography (CTE) yields striking findings for Crohn's disease in the small bowel but its role in differentiating Crohn's from ITB is undefined. This prospective study aimed to investigate the value of CTE for differential diagnosis between Crohn's disease and ITB. PATIENTS AND METHODS: 105 consecutive patients (67 Crohn's, 38 ITB) who underwent CTE and colonoscopy were enrolled. CTE findings and colonoscopic parameters were compared between Crohn's disease and ITB by blinded reviewers. Based on univariate and multiple logistic regression analyses, a diagnostic algorithm combining colonoscopy and CTE was formulated. and its performance validated on 60 new patients (40 Crohn's, 20 ITB). RESULTS: On univariate analysis of CTE findings, proximal small-bowel involvement, asymmetrical mural thickening, segmental small-bowel lesions, mural stratification, the comb sign, and mesentery fibrofatty proliferation were significantly more common in Crohn's disease, whereas mesenteric lymph node change (calcification or central necrosis) and focal ileocecal lesions were more common in ITB. On multivariate analysis, segmental small-bowel involvement (odds ratio [OR] 0.104, 95 % confidence interval [95 %CI] 0.022 - 0.50), and comb sign (OR 0.02, 95 %CI 0.003 - 0.26) were independent predictors of Crohn's. Combining CTE and colonoscopic findings increased the accuracy of diagnosing either Crohn's disease or ITB from 66.7 % (70/105) to 95.2 % (100/105) in the development set (P < 0.001). Sensitivity, specificity, and area under the curve for receiver-operating characteristic (ROC) in the validation dataset were 92.5 %, 80 %, and 0.862 (95 %CI 0.75 - 0.98), respectively. CONCLUSIONS: CTE adds unique information to colonoscopy in differential diagnosis between Crohn's disease and ITB, allowing correct diagnosis in most patients.

Effect of gefitinib plus Chinese herbal medicine (CHM) in patients with advanced non-small-cell lung cancer: a retrospective case-control study.

BACKGROUND: Some patients with non-small-cell lung cancer (NSCLC) respond well to the EGFR tyrosine kinase inhibitor gefitinib. Chinese herbal medicine (CHM) was effective in improving the quality of life and prolonging overall survival in patient with NSCLC. We aim to determine whether gefitinib plus CHM could prolong the progression-free survival (PFS) or median survival time (MST) in patients with NSCLC than gefitinib alone. METHODS: We retrospectively analyzed 159 non-small-cell lung cancer patients with the method of retrospective case-control study, matching factors included gender, age categories (30-39,40-49,50-59,60-69,70-79), pathological stage (IIIB or IV), smoking status (never: <100 lifetime cigarettes, or ever: ≥100 lifetime cigarettes), pathology, and performance status. Among the 159 patients, 100 patients treated with gefitinib (250mg/day orally) plus CHM ("Fuzheng Kang'ai" decoction, a Chinese herbal medicine, 250ml/bid/day orally), 59 patients treated with gefitinib (250mg/day orally) only. PFS and MST were analyzed for the whole population. RESULTS: 58 pairs were matched successfully. 1 patient (treated with gefitinib) with the age of 27 years failed to be matched. Progression-free survival was significantly longer in patients treated with gefitinib plus CHM than with gefitinib: median PFS was 13.1 months (95% CI 6.50-19.70) with gefitinib plus CHM versus 11.43 months (95% CI 7.95-14.91) with gefitinib (log-rank P=0.013). Median overall survival was longer with gefitinib plus CHM than with gefitinib: median MST was 22.83 months (95% CI 17.51-28.16) with gefitinib plus CHM versus 18.7 months (95% CI 16.83-20.57) with gefitinib (log-rank P=0.049). The most common adverse event was rash, the incidence in the gefitinib plus CHM group was 41.38% while in the gefitinib group was 24.14% (P=0.048). CONCLUSIONS: This case-control analysis suggested that treatment with gefitinib plus CHM prolonged PFS and MST compared with gefitinib in patients with NSCLC, and it is worthy of further study.

[Treating primary liver cancer patients by Pi-strengthening and Qi-regulating method: univariate and multivariate analyses of their prognoses].

OBJECTIVE: To evaluate the prognostic factors in treating primary liver cancer (PLC) patients by Pi-strengthening and qi-regulating method (PSQRM), thus providing evidence and optimizing Pi-strengthening and qi-regulating program. METHODS: Clinical data of 151 PLC patients treated by PSQRM at Oncology Department, Guangdong Provincial Hospital of Traditional Chinese Medicine from May 2007 to March 2009 were retrospectively analyzed. The univariate analysis was determined to analyze possible prognostic factors. Selected key factors were introduced into the COX proportional hazard model, and multivariate analysis was carried out. RESULTS: The 1-year survival rate was 21.85%, the median survival time was 6.80 months, and the mean survival time was 8.98 months. The univariate analysis showed that Chinese medicine (CM) syndrome types, clinical symptoms at the initial diagnosis, ascites, tumor types, ratios of foci, portal vein tumor thrombus, intrahepatic metastasis, a-fetoprotein (AFP) levels, total bilirubin classification, albumin classification, Child-Pugh classification, and domestic staging of liver cancer were significant prognostic factors (P < 0.05). The statistic data of multivariate analysis indicated that CM syndrome types, ascites, tumor types, portal vein tumor thrombus, AFP levels, Child-Pugh classification, and domestic staging of liver cancer were independent factors influencing prognosis (P < 0.05). CONCLUSION: The prognosis of PLC treated with PSQRM is determined by multiple factors including CM syndrome types, ascites, tumor types, portal vein tumor thrombus, AFP levels, Child-Pugh classification, and domestic staging of liver cancer.

[The distribution of Chinese medicine syndrome types in primary liver cancer and their differences of the survival time: a clinical study].

OBJECTIVE: To explore the distribution of Chinese medicine (CM) syndrome types in primary liver cancer (PLC) and their differences of the survival time. METHODS: From May 2007 to March 2009, recruited were 151 PLC inpatients at Department of Tumor, Guangdong Provincial Hospital of Traditional Chinese Medicine. Their survival time were statistically calculated. Patients' average survival time and median survival time were calculated using Kaplan-Meier method. The Log-rank test was used to analyze their differences of survival time among different CM syndrome types. RESULTS: The proportion of CM syndrome types in PLC patients were ranked from high to low as follows: mutual accumulation of dampness and blood stasis syndrome [MADBSS, 43.0% (65/151)], Gan-stagnation Pi-deficiency syndrome [GSPDS, 34.4% (52/151)], qi stagnation blood stasis syndrome [QSBSS, 9.3% (14/151)], retention of damp-heat syndrome [RDHS, 8.6%(13/151)], and Gan-Shen yin deficiency syndrome [GSYDS, 4.6% (7/ 151)]. The median survival time of different CM syndrome types were ranked from longer to shorter as follows: GSPDS (14.77 months), QSBSS (6.13 months), RDHS (5.27 months), MADBSS (4.78 months), and GSYDS (0.80 months). The mean survival times were ranked from longer to shorter as follows: GSPDS (12.40 months), QSBSS (8.84 months), MADBSS (6.99 months), RDHS (7.08 months), and GSYDS (0.72 months). There was statistical difference in the difference of the survival time among different CM syndrome types (P < 0.05). CONCLUSIONS: GSPDS and MADBSS were the most common CM syndrome types in PLC patients. There was difference in the survival time between GSPDS and MADBSS/between RDHS and GSYDS. There was difference in the survival time between MADBSS and GSYDS. Patients of GSPDS might get the best prognosis, while patients of GSYDS might get the poorest prognosis.

Activation of PI3K/Akt/mTOR signaling pathway triggered by PTEN downregulation in the pathogenesis of Crohn's disease.

OBJECTIVE: We aimed to investigate the role of the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) signaling pathway and its negative feedback factor, phosphatase and tensin homolog (PTEN), in the pathogenesis of Crohn's disease (CD). METHODS: Peripheral blood was collected from patients with CD and healthy controls while colon tissue samples were collected from CD patients and those complaining of constipation but with normal endoscopic results. CD4⁺ T-cells were isolated from peripheral blood. The expression of PI3K/Akt/mTOR pathway components and PTEN was evaluated in the peripheral CD4⁺ T-cells using polymerase chain reaction and Western blot, and in intestinal mucosal lymphocytes using immunohistochemistry. RESULTS: mRNA expressions of PI3K, Akt, mTOR, 4E-binding protein 1 (4E-BP1) and phosphate-ribosomal protein S6 kinase (p70S6K) in peripheral CD4⁺ T-cells were upregulated in CD patients compared with healthy controls . However, the differences were not significant (P > 0.05). Western blot showed that the ratios of phospho-Akt: Akt, phosphorylated-4E-BP1: 4E-BP1 and phospho-p70S6K: p70S6K in peripheral CD4⁺ T-cells were higher in CD patients (P < 0.05). The composite staining score of phospho-Akt and phospho-mTOR in intestinal mucosal lymphocytes also increased in patients with CD compared with those with constipation. Both PTEN mRNA and protein expressions in either peripheral CD4⁺ T-cells or mucosal lymphocytes were lower in patients with CD than in the healthy controls and those with constipation. CONCLUSIONS: The PI3K/Akt/mTOR signaling pathway was activated in CD. The activation of the PI3K/Akt/mTOR pathway caused by PTEN downregulation may be involved in the pathogenesis of CD.