Glutamatergic neurons in the paraventricular nucleus of the hypothalamus participate in the regulation of visceral pain induced by pancreatic cancer in mice.

Background: Visceral pain induced by pancreatic cancer seriously affects patients' quality of life, and there is no effective treatment, because the mechanism of its neural circuit is unknown. Therefore, the aim of this study is to explore the main neural circuit mechanism regulating visceral pain induced by pancreatic cancer in mice. Methods: The mouse model of pancreatic cancer visceral pain was established on C57BL/6N mice by pancreatic injection of mPAKPC-luc cells. Abdominal mechanical hyperalgesia and hunch score were performed to assess visceral pain; the pseudorabies virus (PRV) was used to identify the brain regions innervating the pancreas; the c-fos co-labeling method was used to ascertain the types of activated neurons; in vitro electrophysiological patch-clamp technique was used to record the electrophysiological activity of specific neurons; the calcium imaging technique was used to determine the calcium activity of specific neurons; specific neuron destruction and chemogenetics methods were used to explore whether specific neurons were involved in visceral pain induced by pancreatic cancer. Results: The PRV injected into the pancreas was detected in the paraventricular nucleus of the hypothalamus (PVN). Immunofluorescence staining showed that the majority of c-fos were co-labeled with glutamatergic neurons in the PVN. In vitro electrophysiological results showed that the firing frequency of glutamatergic neurons in the PVN was increased. The calcium imaging results showed that the calcium activity of glutamatergic neurons in the PVN was enhanced. Both specific destruction of glutamatergic neurons and chemogenetics inhibition of glutamatergic neurons in the PVN alleviated visceral pain induced by pancreatic cancer. Conclusions: Glutamatergic neurons in the PVN participate in the regulation of visceral pain induced by pancreatic cancer in mice, providing new insights for the discovery of effective targets for the treatment of pancreatic cancer visceral pain.

Circadian changes of autonomic function in patients with zoster-associated pain: A heart rate variability analysis.

OBJECTIVE: To investigate the circadian changes of the autonomic function in patients with zoster-associated pain (ZAP). METHODS: A total of 37 patients with ZAP from April 2022 to October 2022 were enrolled as the observation group, and 37 normal volunteers at the same time were selected as the control group. All participants were required to wear a 24-h Holter, which was used to compare the heart rate variability (HRV) between the two groups. HRV analysis involved time- and frequency-domain parameters. RESULTS: There was no statistically significant difference in general information between two groups. Patients with ZAP had an increased mean heart rate and decreased the standard deviation of normal-to-normal (SDNN) R-R interval, the root mean square of the differences (RMSSD) in successive RR interval, low frequency (LF), and high frequency (HF) compared with control groups in all periods (p < .05). The ratio of LF/HF between two groups had no significant difference (p = .245). SDNN had no significant difference between day and night in the control group (p > .05), whereas SDNN of ZAP patients in night period was reduced than that in day period (p < .001). The level of RMSSD during the day was lower than those at night in the control group (p < .05), whereas no significant difference of RMSSD between two periods was observed in patients with ZAP (p > .05). CONCLUSION: The results of this study indicated that ZAP contributes to the decline of autonomic nervous system (ANS) function, especially parasympathetic components. The patients with ZAP lost parasympathetic advantage and had a worse ANS during the night.

Neuroinflammation in the paraventricular nucleus of the hypothalamus precipitates visceral pain induced by pancreatic cancer in mice.

Background: Given the pivotal role of neuroinflammation in chronic pain and that the paraventricular nucleus of the hypothalamus (PVN) is a crucial brain region involved in visceral pain regulation, we sought to investigate whether the targeted modulation of microglia and astrocytes in the PVN could ameliorate pancreatic cancer-induced visceral pain (PCVP) in mice. Methods: Using a mouse model of PCVP, achieved by tumor cell injection at the head of the pancreas, we measure the number of glial cells, and at the same time we employed minocycline to inhibit microglia and chemogenetic methods to suppress astrocytes in order to investigate the respective roles of microglia and astrocytes within the PVN in PCVP. Results: Mice exhibited visceral pain at 12, 15 and 18 days post-tumor cell injection. We observed a significant increase in the population of both microglia and astrocytes. Inhibition of microglial activity through minocycline microinjection into the PVN resulted in alleviation of visceral pain within 30 and 60 min. Similarly, chemogenetic inhibition of astrocyte function at 14 and 21 days post-injection also led to relief from visceral pain. Conclusions: This study found that PVN microglia and astrocytes were involved in regulating PCVP. Our results suggest that targeting glia may be a potential approach for alleviating visceral pain in patients with pancreatic cancer.

Inhibition of GABAergic neurons in the paraventricular nucleus of the hypothalamus precipitates visceral pain induced by pancreatic cancer in mice.

Background: For patients with pancreatic cancer, visceral pain is a debilitating symptom that significantly compromises their quality of life. Unfortunately, the lack of effective treatment options can be attributed to our limited understanding of the neural circuitry underlying this phenomenon. The primary objective of this study is to elucidate the fundamental mechanisms governing visceral pain induced by pancreatic cancer in murine models. Methods: A mouse model of pancreatic cancer visceral pain was established in C57BL/6N mice through the intrapancreatic injection of mPAKPC-luc cells. Abdominal mechanical hyperalgesia and hunch score were employed to evaluate visceral pain, whereas the in vitro electrophysiological patch-clamp technique was utilized to record the electrophysiological activity of GABAergic neurons. Specific neuron ablation and chemogenetics methods were employed to investigate the involvement of GABAergic neurons in pancreatic cancer-induced visceral pain. Results: In vitro electrophysiological results showed that the firing frequency of GABAergic neurons in the paraventricular nucleus of the hypothalamus (PVN) was decreased. Specific destruction of GABAergic neurons in the PVN exacerbated visceral pain induced by pancreatic cancer. Chemogenetics activation of GABAergic neurons in the PVN alleviated visceral pain induced by pancreatic cancer. Conclusions: GABAergic neurons located in PVN play a crucial role in precipitating visceral pain induced by pancreatic cancer in mice, thereby offering novel insights for identifying effective targets to treat pancreatic cancer-related visceral pain.

Strengthening container shipping network connectivity during COVID-19: A graph theory approach.

A container shipping network connects coastal countries with each other and facilitates most of the world merchandise trade. Reliable maritime connectivity ensures the availability of commodities and economic growth. The global spread of COVID-19 has led to port failures and service cancellations, resulting in decreased connectivity level of container ports. To mitigate the impact of the pandemic, a graph theory approach is proposed to strength the container shipping network connectivity by considering topology and the possibility of opening new shipping links between ports. It is designed to maximize network connectivity with limited addable routes. The network connectivity is measured by algebraic connectivity, and the possibility of opening new shipping links is estimated by an extended gravity model. A heuristic algorithm based on Fiedler vector is introduced to obtain the optimal solutions. The performance of the proposed model and algorithm are verified by testing on a real-world container shipping network based on the Alphaliner database. Experimental results illustrate that the presented model is efficient and effective for strengthening the connectivity. Policy makers can refer to the suggested optimal shipping links to facilitate better shipping network connectivity in the context of the COVID-19 pandemic.

Multiscale Cross-Connected Dehazing Network With Scene Depth Fusion.

In this article, we propose a multiscale cross-connected dehazing network with scene depth fusion. We focus on the correlation between a hazy image and the corresponding depth image. The model encodes and decodes the hazy image and the depth image separately and includes cross connections at the decoding end to directly generate a clean image in an end-to-end manner. Specifically, we first construct an input pyramid to obtain the receptive fields of the depth image and the hazy image at multiple levels. Then, we add the features of the corresponding dimensions in the input pyramid to the encoder. Finally, the two paths of the decoder are cross-connected. In addition, the proposed model uses wavelet pooling and residual channel attention modules (RCAMs) as components. A series of ablation experiments shows that the wavelet pooling and RCAMs effectively improve the performance of the model. We conducted extensive experiments on multiple dehazing datasets, and the results show that the model is superior to other advanced methods in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and subjective visual effects. The source code and supplementary are available at https://github.com/CCECfgd/MSCDN-master.

Accurate Forecasting of Emergency Department Arrivals With Internet Search Index and Machine Learning Models: Model Development and Performance Evaluation.

BACKGROUND: Emergency department (ED) overcrowding is a concerning global health care issue, which is mainly caused by the uncertainty of patient arrivals, especially during the pandemic. Accurate forecasting of patient arrivals can allow health resource allocation in advance to reduce overcrowding. Currently, traditional data, such as historical patient visits, weather, holiday, and calendar, are primarily used to create forecasting models. However, data from an internet search engine (eg, Google) is less studied, although they can provide pivotal real-time surveillance information. The internet data can be employed to improve forecasting performance and provide early warning, especially during the epidemic. Moreover, possible nonlinearities between patient arrivals and these variables are often ignored. OBJECTIVE: This study aims to develop an intelligent forecasting system with machine learning models and internet search index to provide an accurate prediction of ED patient arrivals, to verify the effectiveness of the internet search index, and to explore whether nonlinear models can improve the forecasting accuracy. METHODS: Data on ED patient arrivals were collected from July 12, 2009, to June 27, 2010, the period of the 2009 H1N1 pandemic. These included 139,910 ED visits in our collaborative hospital, which is one of the biggest public hospitals in Hong Kong. Traditional data were also collected during the same period. The internet search index was generated from 268 search queries on Google to comprehensively capture the information about potential patients. The relationship between the index and patient arrivals was verified by Pearson correlation coefficient, Johansen cointegration, and Granger causality. Linear and nonlinear models were then developed with the internet search index to predict patient arrivals. The accuracy and robustness were also examined. RESULTS: All models could accurately predict patient arrivals. The causality test indicated internet search index as a strong predictor of ED patient arrivals. With the internet search index, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the linear model reduced from 5.3% to 5.0% and from 24.44 to 23.18, respectively, whereas the MAPE and RMSE of the nonlinear model decreased even more, from 3.5% to 3% and from 16.72 to 14.55, respectively. Compared with each other, the experimental results revealed that the forecasting system with extreme learning machine, as well as the internet search index, had the best performance in both forecasting accuracy and robustness analysis. CONCLUSIONS: The proposed forecasting system can make accurate, real-time prediction of ED patient arrivals. Compared with the static traditional variables, the internet search index significantly improves forecasting as a reliable predictor monitoring continuous behavior trend and sudden changes during the epidemic (P=.002). The nonlinear model performs better than the linear counterparts by capturing the dynamic relationship between the index and patient arrivals. Thus, the system can facilitate staff planning and workflow monitoring.

Locally Weighted Principal Component Analysis-Based Multimode Modeling for Complex Distributed Parameter Systems.

Global principal component analysis (PCA) has been successfully introduced for modeling distributed parameter systems (DPSs). In spite of the merits, this method is not feasible due to parameter variations and multiple operating domains. A novel multimode spatiotemporal modeling method based on the locally weighted PCA (LW-PCA) method is developed for large-scale highly nonlinear DPSs with parameter variations, by separating the original dataset into tractable subsets. This method implements the decomposition by making full use of the dependence among subset densities. First, the spatiotemporal snapshots are divided into multiple different Gaussian components by using a finite Gaussian mixture model (FGMM). Once the components are derived, a Bayesian inference strategy is then applied to calculate the posterior probabilities of each spatiotemporal snapshot belonging to each component, which will be regarded as the local weights of the LW-PCA method. Second, LW-PCA is adopted to calculate each locally weighted snapshot matrix, and the corresponding local spatial basis functions (SBFs) can be generated by the PCA method. Third, all the local temporal models are estimated using the extreme learning machine (ELM). Thus, the local spatiotemporal models can be produced with local SBFs and corresponding temporal model. Finally, the original system can be approximated using the sum form of each local spatiotemporal model. Unlike global PCA, which uses global SBFs to construct a global spatiotemporal model, LW-PCA approximates the original system by multiple local reduced SBFs. Numerical simulations verify the effectiveness of the developed multimode spatiotemporal model.

Interfacial Laser-Induced Graphene Enabling High-Performance Liquid-Solid Triboelectric Nanogenerator.

Laser-induced graphene (LIG) has emerged as a promising and versatile method for high-throughput graphene patterning; however, its full potential in creating complex structures and devices for practical applications is yet to be explored. In this study, an in-situ growing LIG process that enables to pattern superhydrophobic fluorine-doped graphene on fluorinated ethylene propylene (FEP)-coated polyimide (PI) is demonstrated. This method leverages on distinct spectral responses of FEP and PI during laser excitation to generate the environment preferentially for LIG formation, eliminating the need for multistep processes and specific atmospheres. The structured and water-repellant structures rendered by the spectral-tuned interfacial LIG process are suitable as the electrode for the construction of a flexible droplet-based electricity generator (DEG), which exhibits high power conversion efficiency, generating a peak power density of 47.5 W m-2 from the impact of a water droplet 105 µL from a height of 25 cm. Importantly, the device exhibits superior cyclability and operational stability under high humidity and various pH conditions. The facile process developed can be extended to realize various functional devices.

Single dose testosterone administration enhances novelty responsiveness and short-term habituation in healthy males.

The role of testosterone in sensory perception suggests that testosterone likely regulates adaptive responses to sensory changes, including habituation to repeated events and responsiveness to novel events. To test this hypothesis, we investigated how testosterone modulates brain responses to rapid changes in sensory inputs. Using a double-blind, placebo-controlled, within-participant design, each participant received a single dose of either testosterone or placebo, and then completed a passive auditory oddball task in which infrequent deviant tones were embedded in a series of frequent standard tones. Analysis of novelty-evoked potentials revealed smaller Mismatch Negativity (MMN) responses, but larger P3a responses in the testosterone session than in the placebo session. This suggests testosterone attenuates MMN responses that are associated with pre-attentive novelty detection and enhances P3a responses that are associated with involuntary attentional orientation toward novelty. Along with the repetition of standard tones, P2 responses on the auditory evoked potentials became significantly attenuated in the testosterone session, but not in the placebo session. This suggests testosterone enhances short-term habituation of P2 responses to recurring sensory events, which has been associated with bottom-up attention allocation. Mediation analysis further revealed that the role of testosterone in promoting attentional orientation toward novelty could be explained by the influence it exerts on short-term habituation and pre-attentive novelty detection. Overall, testosterone facilitated involuntary attention switching-withdrawal of attention from repeated sensory events and orientation toward novel sensory events-at the cost of attenuated pre-attentive novelty detection. This finding provides insight into the interplay between endocrinology and involuntary attentional processes.

Efficacy and Safety of Chuanxiong Qingnao Granule in Patients with Migraine: A Randomized, Double-Blind, Placebo-Controlled Trial.

OBJECTIVE: To evaluate the efficacy and safety of Chuanxiong Qingnao Granule (CQG) to treat migraine. METHOD: This study was a randomized, double-blind, placebo-controlled trial. All migraineurs were recruited and randomly assigned into a treatment group treated with CQG and a control group treated with a placebo. The whole research process included a 4-week baseline, 12-week intervention, and 12-week follow-up. The primary outcome was responder rate, defined as the percentage of migraineurs with 50% or more reduction in the frequency of migraine attack during treatment and posttreatment period compared with the baseline. The secondary outcomes were the number of migraine days, migraine attack frequency, visual analogue scale (VAS), Fatigue Severity Scale (FSS), Hamilton Depression Scale (HAMD), and Migraine Disability Assessment (MIDAS). RESULTS: A total of 346 migraineurs completed the research and were included in the intention-treatment analyses. The response rates differed significantly between the treatment group and the control group (71.5% vs. 12.1% at week 12 and 83.1% vs. 3.4% at week 24). Attack frequency, days of headache attack, VAS, FSS, HAMD, and MIDAS decreased at week 12 in both groups with more reduction in the treatment group (P < 0.001). No severe adverse events were observed in this trial. CONCLUSION: Chuanxiong Qingnao Granule can significantly improve headache symptoms in patients with migraine while improving disability, fatigue, and depression with a good safety profile.

Predicting Postherpetic Neuralgia in Patients with Herpes Zoster by Machine Learning: A Retrospective Study.

INTRODUCTION: Postherpetic neuralgia (PHN) is a neuropathic pain secondary to shingles. Studies have shown that early pain intervention can reduce the incidence or intensity of PHN. The aim of this study was to predict whether a patient with acute herpetic neuralgia will develop PHN and to help clinicians make better decisions. METHOD: Five hundred two patients with shingles were reviewed and classified according to whether they had PHN. The risk factors associated with PHN were determined by univariate analysis. Logistic regression and random forest algorithms were used to do machine learning, and then the prediction accuracies of the two algorithms were compared, choosing the superior one to predict the next 60 new cases. RESULTS: Age, NRS score, rash site, Charlson comorbidity index (CCI) score, antiviral therapy and immunosuppression were found related to the occurrence of PHN. The NRS score was the most closely related factor with an importance of 0.31. As for accuracy, the random forest was 96.24%, better than that of logistic regression in which the accuracy was 92.83%. Then, the random forest model was used to predict 60 newly diagnosed patients with herpes zoster, and the accuracy rate was 88.33% with a 95% confidence interval (CI) of 77.43-95.18%. CONCLUSIONS: This study provides an idea and a method in which, by analyzing the data of previous cases, we can develop a predictive model to predict whether patients with shingles will develop PHN.

Expressions of P-NMDAR and CaMKⅡin brain tissue of rats with chronic fluorosis / 中华地方病学杂志

Objective:To observe the changes of phosphorylated N-methyl-D-aspartate receptor (P-NMDAR) subunit and calmodulin-dependent protein kinase Ⅱ (CaMK Ⅱ) protein expression in the brain tissue of rats with chronic fluorosis, and to explore the molecular pathogenesis of chronic fluorosis nerve injury.Methods:Eighteen one-month-old SD rats (half male and half female), weighing (100 ± 20) g, were randomly divided into three groups after adaptive feeding for 1 week: control group (drinking tap water, fluoride content < 0.5 mg/L), low fluoride group (drinking water fluoride content was 10.0 mg/L) and high fluoride group (drinking water fluoride content was 100.0 mg/L), with 6 rats in each group (half male and half female). Brain tissue was harvested after 180 days of feeding. HE staining was used to observe the morphological changes of rat brain tissue, Nissl staining was used to observe the changes of Nissl bodies in nerve cells, and immunohistochemical staining was used to observe the expressions of P-NMDAR subunits (P-NMDAR1, P-NMDAR2A) and CaMK Ⅱ protein in rat brain tissue.Results:Under light microscope, HE staining showed disordered arrangement of hippocampal neurons, nuclear hyperstaining and basophilic enhancement in the high fluoride group. The results of Nissl staining showed that the average optical density of Nissl bodies in nerve cells in the hippocampus of rats in the control group, low fluoride group, and high fluoride group were 0.024 4 ± 0.009 7, 0.024 0 ± 0.003 1, and 0.023 9 ± 0.013 8, respectively. There was no statistically significant difference between the groups ( F = 0.010, P > 0.05). Compared with the control group (0.011 8 ± 0.006 5, 0.065 6 ± 0.011 1, 0.143 8 ± 0.029 9) and low fluoride group (0.017 2 ± 0.006 8, 0.062 6 ± 0.017 8, 0.135 6 ± 0.029 6), the protein expressions of P-NMDAR1, P-NMDAR2A and CaMK Ⅱ in high fluoride group were significantly increased (0.026 3 ± 0.005 7, 0.086 3 ± 0.009 0, 0.210 9 ± 0.048 7, P < 0.05); and the protein expression of P-NMDAR1 in low fluoride group was higher than that in the control group ( P < 0.05). Conclusion:Long-term excessive fluoride intake can lead to nerve cell injury in rats, and the mechanism of injury maybe related to the excitotoxicity induced by calcium ion (Ca 2+) overload caused by overactivation of NMDAR subunits.

Effects of fluoride on growth and development, learning and memory, and oxidative stress in serum of offspring rats / 中华地方病学杂志

Objective:To observe the change of growth and development, learning and memory, and oxidative stress in serum of offspring rats with fluorosis, and to explore the mechanism of fluoride on neurobehavioral development of offspring rats.Methods:Seventy-two SD rats (female and male ratio 3 ∶ 1) were fed adaptively for one week. According to their body mass [(80 ± 20) g], they were divided into control group (drinking tap water, containing less than 0.5 mg/L fluoride), low fluorine group (drinking water containing 10.0 mg/L of fluoride), and high fluorine group (drinking water containing 100.0 mg/L of fluoride) with random number table. After six months of feeding, they mated freely and gave birth in each group (24 rats with 18 females and 6 males). The rats in each group continued to be exposed to fluoride after giving birth, and the offspring rats were exposed to fluoride through breast milk feeding until the 28th day after birth. Body and brain weight, growth and development indicators (auricle separation, eyes opening, teeth eruption and hair growth) and neurobehavioral development indicators (cliff avoidance, auditory startle, surface righting and vibrissa positioning) were recorded. On the 28th day after birth, the learning and memory abilities (escape latency) of offspring rats were tested by Morris water maze; blood samples were taken from eyeballs to detect the content of nitric oxide (NO), the activity of nitric oxide synthase (NOS) and inducible nitric oxide synthase (iNOS).Results:On the 21st day and 28th day after birth, the differences of body weight among control group, low fluorine group and high fluorine group [21st day: (54.70 ± 3.02), (52.30 ± 2.58), (51.30 ± 2.71) g, 28th day: (91.70 ± 5.03), (90.40 ± 4.76), (86.00 ± 4.55) g] were statistically significant ( F = 3.96, 3.70, P < 0.05); on the 21st day, the body weight of high fluorine group was lower than that of control group ( P < 0.05); on the 28th day, the body weight of the high fluorine group was lower than those of control group and low fluorine group ( P < 0.05). On the 28th day, the difference of brain weight of control group, low fluorine group and high fluorine group was statistically significant ( F = 6.19, P < 0.05); and the low fluorine group and high fluorine group were lower than that of control group ( P < 0.05). Among the growth development indicators, the difference of time of completing eyes opening in control group, low fluorine group and high fluorine group was statistically significant ( F = 3.64, P < 0.05); and the high fluorine group was higher than that of control group ( P < 0.05). In neurobehavioral development indicators, the differences of time of completing cliff avoidance, surface righting between the control group, low fluorine group and high fluorine group were statistically significant ( F = 8.29, 7.69, P < 0.05); and the time of completing cliff avoidance in high fluorine group was higher than those of control group and low fluorine group ( P < 0.05), the time of completing surface righting was higher than that of control group ( P < 0.05). In Morris water maze, on the 4th day, the escape latencies of low fluorine group and high fluorine group were higher than that of control group ( P < 0.05). The results of oxidative stress in serum showed that there were statistically significant differences in serum NO content, NOS and iNOS activitives between the control group, low fluorine group and high fluorine group ( F = 4.86, 66.48, 70.95, P < 0.05); and the NO content of the high fluoirne group was higher than that of the control group ( P < 0.05), the activities of NOS and iNOS of the high fluoirne group were higher than those of control group and the low fluorine group ( P < 0.05). Conclusion:Excessive fluoride can increase the level of oxidative stress in serum, which may be closely related to the neurobehavioral retardation and the decline of learning and memory ability of offspring rats.

Experimental Study of MAR Algorithm in Metal Artifact Removal of CT Simulator / 中国医疗器械杂志

OBJECTIVE@#To explore the application value of MAR algorithm in metal artifact removal of CT simulator.@*METHODS@#CT phantom with titanium plate was scanned using conventional algorithms and MAR algorithms, respectively. Artifact index(AI), contrast-to-noise ratio(CNR) and AI values at different slices were used to analyze the artifact images.@*RESULTS@#In artifact index, MAR algorithm (10.28±2.60) is significantly lower than conventional algorithm (20.65±5.04); In contrast-to-noise ratio index, MAR algorithm (7.81±1.12) is better than conventional algorithm (5.61±1.36). The above indicators were statistically significant in both algorithms (P<0.01). In the slices affected by metal artifacts, the artifact index decreased by 21.72%~88.40% after the MAR algorithm.@*CONCLUSIONS@#MAR algorithm can significantly reduce the metal artifacts and improve the clinical value of CT data.

Patient and economic burdens of postherpetic neuralgia in China.

BACKGROUND: Little is known about the patient-reported and economic burdens of postherpetic neuralgia (PHN) among China's urban population. METHODS: This noninterventional study was conducted among adults ≥40 years with PHN who were seeking medical care at eight urban hospitals in China. At one study site, patients completed a questionnaire evaluating the patient-reported disease burden (N=185). The questionnaire consisted of validated patient-reported outcomes including the Brief Pain Inventory (BPI), 5-dimension, 3-level EuroQol (EQ-5D-3L), Medical Outcomes Study Sleep Scale, and Work Productivity and Activity Impairment Questionnaire for Specific Health Problems. Questions on non-pharmacologic therapy and out-of-pocket (OOP) expenses were also included. At all study sites, physicians (N=100) completed a structured review of patient charts (N=828), which was used to derive health care resource utilization and associated costs from the societal perspective. Annual costs in Chinese Yuan Renminbi (RMB) for the year 2016 were converted to US dollars (US$). RESULTS: Patients (N=185, mean age 63.0 years, 53.5% female) reported pain of moderate severity (mean BPI score 4.6); poor sleep quantity (average of 5.3 hrs per night) and quality; and poorer health status on the EQ-5D-3L relative to the general Chinese population. Respondents also reported average annual OOP costs of RMB 16,873 (US$2541) per patient, mainly for prescription PHN medications (RMB 8990 [US$1354]). Substantial work impairment among employed individuals resulted in annual indirect costs of RMB 28,025 (US$4221). In the chart review, physicians reported that patients (N=828) had substantial health resource utilization, especially office visits; 98% had all-cause and 95% had PHN-related office visits. Total annual direct medical costs were RMB 10,002 (US$1507), mostly driven by hospitalizations (RMB 8781 [US$1323]). CONCLUSION: In urban China, PHN is associated with a patient-reported burden, affecting sleep, quality-of-life, and daily activities including work impairment, and an economic burden resulting from direct medical costs and indirect costs due to lost productivity. These burdens suggest the need for appropriate prevention and management of PHN.

Peripheral nerve field stimulation to the preauricular area for intractable chronic migraine: a case report.

Objective: To report a successful attempt of peripheral nerve field stimulation (PNFS) in preauricular area to treat refractory chronic migraine (CM). This article focuses on novel utilization of PNFS and discusses its existing issues. Case report: A 35-year-old woman diagnosed with CM complained about a 2-year history of severe pain at the occipitocervical and left auriculotemporal area, sometimes bilaterally, which did not benefit from conventional medical therapy. After failed attempts of occipital nerve stimulation and PNFS at the retroauricular area, we used exploratory PNFS at the preauricular area, which to our knowledge is the first reported case in literature, to such an area in refractory CM. The patient experienced satisfactory pain relief and obvious improvement in quality of life. And the amelioration on the severity of pain was validated by reduced scores (from 9 to 2) on the numerical rating scale. The clinical effects continued in the next 2-year follow-up after the implantation, without adverse events. Conclusion: PNFS is a promising and safe neuromodulation therapy for refractory CM. Facial areas like preauricular region are applicable for lead implantation. Nevertheless, the underlying mechanisms are still unverified, and there is still a lack of standardized operation guides of PNFS. Large-scale randomized clinical trials should be conducted to further validate these findings.

Others' Pain Appraisals Modulate the Anticipation and Experience of Subsequent Pain.

The present study investigated how pain appraisals from other individuals modulated self-pain anticipation and perception. Appraisals of pain intensity from 10 other individuals were presented before the participants received identical electrical pain stimulation themselves. In reality, the presented other's pain appraisals, with either low or high in mean and variance, were generated by the experimenter, and were randomly paired with the subsequent electrical stimulation at either low or high intensity. Specifically, the mean and variance of others' pain appraisals were manipulated to induce participants' expectation and certainty to the upcoming pain. Subjective ratings of pain intensity and electroencephalographic (EEG) responses to the electrical stimulation, as well as anticipatory EEG activities measured prior to the onset of electrical stimulation, were compared. Results showed that the mean and variance of others' pain appraisal modulated the subjective pain ratings and the affective-motivational P2 responses elicited by the electrical stimulation, as well as anticipatory sensorimotor α-oscillation measured before the onset of pain stimulation. When the mean of others' pain appraisal was low, higher variance suppressed the sensorimotor α-oscillations and enhanced subsequent pain perception. In contrast, when the mean was high, the higher variance enhanced sensorimotor α-oscillations and suppressed subsequent pain perception. These results demonstrated that others' pain appraisals can modulate both of the anticipation and perception of first-hand pain. It also suggested that the top-down modulation of others' pain appraisals on pain perception could be partially driven by the different brain states during the anticipation stage, as captured by the prestimulus sensorimotor α-oscillations.

Hearing other's pain is associated with sensitivity to physical pain: An ERP study.

Numerous studies have demonstrated an overlap between the processing of self-pain and others' pain, which suggests that psychological and neural representations are shared between the perception of physical pain and empathy for pain. As hearing emotional exclamations is a common way in which we regularly perceive and empathize with others' pain, the present study aimed to investigate the link between sensitivity to physical pain and the sounds made by others in pain. We recorded event-related potential (ERP) responses to another person's vocalizations (neutral or painful intonation) and identified electrophysiological responses associated with the processing of painful sounds. Additionally, individual pain sensitivity was characterized by a stimulus-response function that described the relationship between objective stimulus intensity and subjective pain intensity. Results showed that compared with hearing others' neutral sounds, hearing others' sounds of pain elicited more positive frontal-central N1 and N2 responses as well as more positive central-parietal P3 and late positive potential responses. These electrophysiological responses to hearing others' pain replicated electrophysiological responses to observing pictures and video clips of people in pain. Importantly, the neural responses to hearing others in pain were associated with physical pain sensitivity that was indexed by stimulus-response characteristics. The identified link between perception of one's own physical pain and the sounds of others in pain further supports the shared common psychological computations between processing one's own pain and empathizing with others' pain.