The overgeneralization of pain-related fear in individuals with higher pain sensitivity: A behavioral and event-related potential study.

Fear generalization contributes to the development and maintenance of pain. Pain sensitivity has been proposed to predict the strength of fear responses to aversive stimuli. However, whether individual variation in pain sensitivity affects pain-related fear generalization and its underlying cognitive processing remains unclear. To address this gap, we recorded behavioral and event-related potential (ERP) data among 22 high pain sensitivity (HPS) and 22 low pain sensitivity (LPS) healthy adults when exposed to a fear generalization paradigm. The behavioral results indicate that the HPS group displayed higher unconditioned stimulus expectancy and greater fear, arousal, and anxiety ratings to conditioned stimulus and generalization stimulus than the LPS group (all p values < 0.05). The ERP results showed that the HPS group exhibited a larger late positive potential evoked by GS2, GS3 and CS- (all p < 0.005) but a smaller N1 evoked by all CS and GSs (all p values < 0.05) relative to the LPS group. These findings suggest that individuals with a high level of pain sensitivity allocate more attention resources to pain-related threatening stimuli, which contributes to an overgeneralization of pain-related fear.

The excessive generalization of fear affected by perceptual bias in experimental pain individuals: Evidence from an event-related potential study.

INTRODUCTION: Excessiv generalization of fear contributes to the development and maintenance of pain. Prior research has demonstrated the importance of perception in fear generalization and found that individuals in painful conditions exhibited perceptual bias. However, the extent to which perceptual bias in pain affects the generalization of pain-related fear and its underlying neural activity remains unclear. METHODS: Here, we tested whether perceptual bias in experimental pain individuals led to the overgeneralization of pain-related fear by recording behavioral and neural responses. To this end, we established an experimental pain model by spraying capsaicin on the surface of the seventh cervical vertebra of the participant. A total of 23 experimental pain participants and 23 matched nonpain controls learned fear conditioning and then completed the fear generalization paradigm combined with the perceptual categorization task. RESULTS: We found that the novel and safety cues were more likely to be identified as threat cues in the experimental group, resulting in higher US expectancy ratings compared to the control group. The event-related potential results showed that the experimental group exhibited earlier N1 latency and smaller P1 and late positive potential amplitudes than those in the control group. CONCLUSION: Our findings suggest that the experimental pain individuals exhibited an excessive generalization of fear affected by perceptual bias and reduced their attentional allocation to pain-related fear stimuli.

A preoperative scoring system to predict the probability of laparoendoscopic single-site extracorporeal cystectomy in patients with benign ovarian cysts.

Objective: To develop a preoperative scoring system (PSS) to predict whether laparoendoscopic single-site extracorporeal (LESS-E) cystectomy can be performed in patients with benign ovarian cysts. Method: We reviewed data on patients who underwent LESS cystectomy between August 2016 and October 2019 at the first Affiliated Hospital, Army Medical University. The independent predictors of LESS-E cystectomy in patients with benign ovarian cysts were identified using multivariate logistic regression analyses. A nomogram for predicting LESS-E cystectomy in patients with benign ovarian cysts was developed, and to simplify the score, we establish a preoperative scoring system to guide the choice of surgical approach in patients with highly probable benign ovarian cysts. Results: Our analysis showed that age, BMI, height and the diameter of ovarian cysts were independent predictors of LESS-E cystectomy. A nomogram was developed based on these four factors, which had a concordance index of 0.838 and R 2 = 0.415. To simplify the score, the predicted indicators in the regression model were scored by dividing the beta coefficient by the absolute value of the minimum beta coefficient, and the sum of each predictor score established a PSS. In the total set, the selected cutoff value according to the maximum point of the Youden index was 8, and a preoperative score ≥ 8 identified patients undergoing LESS-E cystectomy with a positive predictive value of 67.4% and a negative predictive value of 88.6%. Conclusion: A PSS to predict the chances of LESS-E cystectomy was established. This system could be helpful for selecting the appropriate surgical strategy for patients with benign ovarian cysts.

Perioperative outcomes of laparoendoscopic single-site extracorporeal versus intracorporeal cystectomy for benign ovarian cysts: a retrospective cohort study based on propensity score matching.

BACKGROUND: Ovarian cysts are the most common gynecological disease, and laparo-endoscopic single-site (LESS) cystectomy is a popular surgical procedure. A new laparoscopic technique combining the advantages of LESS surgery and open surgery has been introduced to treat large ovarian cysts. To our knowledge, no previous research has compared LESS-extracorporeal (LESS-E) cystectomy to LESS-intracorporeal (LESS-I) cystectomy. This study compared the perioperative results of LESS-E cystectomy and LESS-I cystectomy in the treatment of benign ovarian cysts. METHODS: Two hundred eighty-eight cases of cystectomy from our institutional database were retrospectively reviewed. 1:1 propensity score matching (PSM) was performed to minimize bias due to any imbalanced baseline features between the 2 groups, which were matched in terms of age, body mass index, and the largest diameter of ovarian cysts. Seventy-nine cases were then selected from each group, and the perioperative outcomes of the 2 cohorts were analyzed. RESULTS: The mean (standard deviation) largest diameter of ovarian cysts was 8.30 (3.56) cm in the LESS-I group and 9.14 (3.15) cm in the LESS-E group (P=0.118). No statistically significant difference was found between the 2 groups in terms of estimated blood loss, postoperative hemoglobin decline, postoperative pain in 24 hours, postoperative hospital stay, and total hospital costs (P>0.05). However, the mean operation time of the LESS-E group was shorter than that of the LESS-I group (85.01 vs. 104.25 minutes; P=0.001). Additionally, the spillage rate of the LESS-I group was significantly greater than that of the LESS-E group (46.8% vs. 17.7%; P<0.001). The mean pain scores at 6 postoperative hours as measured by a visual analogue scale were significantly greater in the LESS-I group than the LESS-E group (3.85 vs. 3.37; P=0.016). CONCLUSIONS: LESS-E cystectomy is a safe and feasible approach with a shorter operation time and lower spillage rate than LESS-I cystectomy.

Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning.

Sketch portrait generation benefits a wide range of applications such as digital entertainment and law enforcement. Although plenty of efforts have been dedicated to this task, several issues still remain unsolved for generating vivid and detail-preserving personal sketch portraits. For example, quite a few artifacts may exist in synthesizing hairpins and glasses, and textural details may be lost in the regions of hair or mustache. Moreover, the generalization ability of current systems is somewhat limited since they usually require elaborately collecting a dictionary of examples or carefully tuning features/components. In this paper, we present a novel representation learning framework that generates an end-to-end photo-sketch mapping through structure and texture decomposition. In the training stage, we first decompose the input face photo into different components according to their representational contents (i.e., structural and textural parts) by using a pre-trained convolutional neural network (CNN). Then, we utilize a branched fully CNN for learning structural and textural representations, respectively. In addition, we design a sorted matching mean square error metric to measure texture patterns in the loss function. In the stage of sketch rendering, our approach automatically generates structural and textural representations for the input photo and produces the final result via a probabilistic fusion scheme. Extensive experiments on several challenging benchmarks suggest that our approach outperforms example-based synthesis algorithms in terms of both perceptual and objective metrics. In addition, the proposed method also has better generalization ability across data set without additional training.