Suppression of wavelength-dependent polarization fading using hybrid-polarization scheme in OFDR.

What we believe to be a new hybrid-polarization diversity scheme which can eliminate the polarization state variation caused by wavelength tuning of laser in optical frequency domain reflectometry is proposed in the paper. In the scheme, a 45° polarizer is used to maintain the polarization of signals. It decreases the polarization angle fluctuation to 2.81° and realizes a -145 dB test sensitivity with a 32 dB Rayleigh scattering signal-to-noise ratio in a 10 m fiber single test. The polarization fading suppression is achieved for tests with a large wavelength tuning range from 1480 nm to 1640 nm. Meanwhile, a 6 µm spatial resolution is also achieved. The proposed scheme can be applied to the structure measurement of high-precision optical fiber devices with high spatial resolution and sensitivity.

Microstructural abnormalities of white matter in the cingulum bundle of adolescents with major depression and non-suicidal self-injury.

BACKGROUND: Non-suicidal self-injury (NSSI) is prevalent in major depressive disorder (MDD) during adolescence, but the underlying neural mechanisms are unclear. This study aimed to investigate microstructural abnormalities in the cingulum bundle associated with NSSI and its clinical characteristics. METHODS: 130 individuals completed the study, including 35 healthy controls, 47 MDD patients with NSSI, and 48 MDD patients without NSSI. We used tract-based spatial statistics (TBSS) with a region of interest (ROI) analysis to compare the fractional anisotropy (FA) of the cingulum bundle across the three groups. receiver-operating characteristics (ROC) analysis was employed to evaluate the ability of the difficulties with emotion regulation (DERS) score and mean FA of the cingulum to differentiate between the groups. RESULTS: MDD patients with NSSI showed reduced cingulum integrity in the left dorsal cingulum compared to MDD patients without NSSI and healthy controls. The severity of NSSI was negatively associated with cingulum integrity (r = -0.344, p = 0.005). Combining cingulum integrity and DERS scores allowed for successful differentiation between MDD patients with and without NSSI, achieving a sensitivity of 70% and specificity of 83%. CONCLUSIONS: Our study highlights the role of the cingulum bundle in the development of NSSI in adolescents with MDD. The findings support a frontolimbic theory of emotion regulation and suggest that cingulum integrity and DERS scores may serve as potential early diagnostic tools for identifying MDD patients with NSSI.

Distinguishing bipolar depression, bipolar mania, and major depressive disorder by gut microbial characteristics.

BACKGROUND: Gut microbial disturbance has been widely confirmed in mood disorders. However, little is known about whether gut microbial characteristics can distinguish major depressive disorder (MDD), bipolar depression (BP-D), and bipolar mania (BP-M). METHODS: This was a prospective case-control study. The composition of gut microbiota was profiled using 16S ribosomal RNA (rRNA) gene sequencing of fecal samples and compared between healthy controls (HC; n = 46), MDD (n = 51), BP-D (n = 44), and patients with BP-M (n = 45). RESULTS: Gut microbial compositions were remarkably changed in the patients with MDD, BP-D, and BP-M. Compared to HC, distinct gut microbiome signatures were found in MDD, BP-D, and BP-M, and some gut microbial changes were overlapping between the three mood disorders. Furthermore, we identified a signature of 7 operational taxonomic units (OUT; Prevotellaceae-related OUT22, Prevotellaceae-related OUT31, Prevotellaceae-related OTU770, Ruminococcaceae-related OUT70, Bacteroidaceae-related OTU1536, Propionibacteriaceae-related OTU97, Acidaminococcaceae-related OTU34) that can distinguish patients with MDD from those with BP-D, BP-M, or HC, with area under the curve (AUC) values ranging from 0.910 to 0.996. CONCLUSION: Our results provide the clinical rationale for the discriminative diagnosis of MDD, BP-D, and BP-M by characteristic gut microbial features.

Prediction of Early Antidepressant Efficacy in Patients with Major Depressive Disorder Based on Multidimensional Features of rs-fMRI and P11 Gene DNA Methylation: Prédiction de l'efficacité précoce d'un antidépresseur chez des patients souffrant du trouble dépressif majeur d'après les caractéristiques multidimensionnelles de la méthylation de l'ADN du gène P11 et de la IRMf-rs.

OBJECTIVE: This study established a machine learning model based on the multidimensional data of resting-state functional activity of the brain and P11 gene DNA methylation to predict the early efficacy of antidepressant treatment in patients with major depressive disorder (MDD). METHODS: A total of 98 Han Chinese MDD were analysed in this study. Patients were divided into 51 responders and 47 nonresponders according to whether the Hamilton Depression Rating Scale-17 items (HAMD-17) reduction rate was ≥50% after 2 weeks of antidepressant treatment. At baseline, the Illumina HiSeq Platform was used to detect the methylation of 74 CpG sites of the P11 gene in peripheral blood samples. Resting-state functional magnetic resonance imaging (rs-fMRI) scan detected the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) in 116 brain regions. The least absolute shrinkage and selection operator analysis method was used to perform feature reduction and feature selection. Four typical machine learning methods were used to establish support vector machine (SVM), random forest (RF), Naïve Bayes (NB), and logistic regression (LR) prediction models based on different combinations of functional activity of the brain, P11 gene DNA methylation and clinical/demographic features after screening. RESULTS: The SVM model based on ALFF, ReHo, FC, P11 methylation, and clinical/demographic features showed the best performance, with 95.92% predictive accuracy and 0.9967 area under the receiver operating characteristic curve, which was better than RF, NB, and LR models. CONCLUSION: The multidimensional data features combining rs-fMRI, DNA methylation, and clinical/demographic features can predict the early antidepressant efficacy in MDD.

Optical frequency domain polarimetry based on a self-referenced unbalanced Mach-Zehnder interferometer.

Optical frequency domain polarimetry (OFDP) is an emerging distributed polarization crosstalk rapid measurement method with an ultrawide dynamic range. However, interferometric phase noise induced by the laser source and ambient noise results in a trade-off between measurement length and dynamic range. In this Letter, we solve this problem with a self-referenced unbalanced Mach-Zehnder interferometer. The features of long distance (9.8 km), ultrawide dynamic range (107.8 dB), short measurement time (2 sec), and signal-to-noise ratio improvement against ambient noise are experimentally demonstrated. The method makes it possible to evaluate a long polarization-maintaining fiber in an environment whose state changes rapidly.

Predicting the diagnosis of various mental disorders in a mixed cohort using blood-based multi-protein model: a machine learning approach.

The lack of objective diagnostic methods for mental disorders challenges the reliability of diagnosis. The study aimed to develop an easily accessible and useable objective method for diagnosing major depressive disorder (MDD), schizophrenia (SZ), bipolar disorder (BPD), and panic disorder (PD) using serum multi-protein. Serum levels of brain-derived neurotrophic factor (BDNF), VGF (non-acronymic), bicaudal C homolog 1 (BICC1), C-reactive protein (CRP), and cortisol, which are generally recognized to be involved in different pathogenesis of various mental disorders, were measured in patients with MDD (n = 50), SZ (n = 50), BPD (n = 55), and PD along with 50 healthy controls (HC). Linear discriminant analysis (LDA) was employed to construct a multi-classification model to classify these mental disorders. Both leave-one-out cross-validation (LOOCV) and fivefold cross-validation were applied to validate the accuracy and stability of the LDA model. All five serum proteins were included in the LDA model, and it was found to display a high overall accuracy of 96.9% when classifying MDD, SZ, BPD, PD, and HC groups. Multi-classification accuracy of the LDA model for LOOCV and fivefold cross-validation (within-study replication) reached 96.9 and 96.5%, respectively, demonstrating the feasibility of the blood-based multi-protein LDA model for classifying common mental disorders in a mixed cohort. The results suggest that combining multiple proteins associated with different pathogeneses of mental disorders using LDA may be a novel and relatively objective method for classifying mental disorders. Clinicians should consider combining multiple serum proteins to diagnose mental disorders objectively.

Improving the measurement range of FFPI strain sensing using second-order control PDH technology.

A novel demodulation method is presented to expand the measurement dynamic range for fiber optic strain sensors using PDH technology. The new control algorithm uses two integrators to form a 2nd order control, and the FFPI strain sensor can have a dynamic range of 20 dB/octave larger than the PID control method when the input signal frequency decreases a magnitude. A strain resolution of 4.7 pɛ Hz-1/2@10Hz, a 118 dB@10Hz dynamic range without consecution, and 158 dB with consecution is obtained. The experiment results show that the new control method can improve the sensing system's dynamic range with the corner frequency unchanged and without the system noise level degradation.

Phase noise elimination in frequency sweeping interferometry based on a common-path interferometer.

We propose a common-path interferometer (CPI) method to suppress the ambient and laser phase noise in frequency sweeping interferometry. The CPI realizes the multiplexing of the main and auxiliary interferometer to ensure the common-mode characteristic of the interference phase noise, which can be eliminated by signal mixing. In experiments, we obtain a dynamic range of up to 110 dB. Compared with the compensation method using a separated auxiliary interferometer, the CPI method improves the dynamic range by 10 dB and is immune to ambient noise. The proposed method enables high-precision distributed polarization measurements of optical fibers and devices.

Beyond a 107 range-resolution-1 product in an OFDR based on a periodic phase noise estimation method.

We present and demonstrate a method based on a periodic phase noise estimation in an optical frequency domain reflectometry (OFDR) capable of a beyond 107 range-resolution-1 product (RRP) for the first time, which corresponds to 2.5 × improvement compared with the state-of-the-art. The moving average filter is employed to suppress the amplification of noise in the derivation process. Further, with the help of a third-order Taylor expansion, this method provides a highly precise estimation of periodic phase noise, which is the main factor impacting the performance of OFDR systems with medium-to-long measurement range combined with a submillimeter spatial resolution. A spatial resolution within 535 µm over the measurement range of 8 km is obtained. The proposed method offers a promising technique for fiber network monitoring and sensing applications.

Bacteroides species differentially modulate depression-like behavior via gut-brain metabolic signaling.

Gut microbiome disturbances have been widely implicated in major depressive disorder (MDD), although the identity of causal microbial species and the underlying mechanisms are yet to be fully elucidated. Here we show that Bacteroides species enriched in the gut microbiome from MDD patients differentially impact the susceptibility to depressive behaviors. Transplantation of fecal microbiome from MDD patients into antibiotic-treated mice induced anxiety and despair-like behavior and impaired hippocampal neurogenesis. Colonization of Bacteroides fragilis, Bacteroides uniformis, and, to a lesser extent, Bacteroides caccae, but not Bacteroides ovatus, recapitulated the negative effects of MDD microbiome on behavior and neurogenesis. The varying impacts of Bacteroides species were partially explained by differential alternations of tryptophan pathway metabolites and neurotransmitters along the gut-brain axis. Notably, an intensified depletion of cerebral serotonin concurred with the enhanced susceptibility to depression. Together, these findings identify select Bacteroidetes species that contribute to depression susceptibility in mice by metabolic regulation along the gut-brain axis.

Influence and interaction of resting state functional magnetic resonance and tryptophan hydroxylase-2 methylation on short-term antidepressant drug response.

BACKGROUND: Most antidepressants have been developed on the basis of the monoamine deficiency hypothesis of depression, in which neuronal serotonin (5-HT) plays a key role. 5-HT biosynthesis is regulated by the rate-limiting enzyme tryptophan hydroxylase-2 (TPH2). TPH2 methylation is correlated with antidepressant effects. Resting-state functional MRI (rs-fMRI) is applied for detecting abnormal brain functional activity in patients with different antidepressant effects. We will investigate the effect of the interaction between rs-fMRI and TPH2 DNA methylation on the early antidepressant effects. METHODS: A total of 300 patients with major depressive disorder (MDD) and 100 healthy controls (HCs) were enrolled, of which 60 patients with MDD were subjected to rs-fMRI. Antidepressant responses was assessed by a 50% reduction in 17-item Hamilton Rating Scale for Depression (HAMD-17) scores at baseline and after two weeks of medication. The RESTPlus software in MATLAB was used to analyze the rs-fMRI data. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), fractional ALFF (fALFF), and functional connectivity (FC) were used, and the above results were used as regions of interest (ROIs) to extract the average value of brain ROIs regions in the RESTPlus software. Generalized linear model analysis was performed to analyze the association between abnormal activity found in rs-fMRI and the effect of TPH2 DNA methylation on antidepressant responses. RESULTS: Two hundred ninety-one patients with MDD and 100 HCs were included in the methylation statistical analysis, of which 57 patients were included in the further rs-fMRI analysis (3 patients were excluded due to excessive head movement). 57 patients were divided into the responder group (n = 36) and the non-responder group (n = 21). Rs-fMRI results showed that the ALFF of the left inferior frontal gyrus (IFG) was significantly different between the two groups. The results showed that TPH2-1-43 methylation interacted with ALFF of left IFG to affect the antidepressant responses (p = 0.041, false discovery rate (FDR) corrected p = 0.149). CONCLUSIONS: Our study demonstrated that the differences in the ALFF of left IFG between the two groups and its association with TPH2 methylation affect short-term antidepressant drug responses.

The impact of HTR1A and HTR1B methylation combined with stress/genotype on early antidepressant efficacy.

AIMS: Antidepressants are effective in the treatment of major depressive disorder (MDD), while many patients fail to respond to antidepressants. Both 5-HT1A (HTR1A) and 5-HT1B (HTR1B) receptors play an important role in antidepressant activity. Meanwhile, DNA methylation is associated with MDD and antidepressant efficacy. In this study we investigate the influence of HTR1A and HTR1B methylation combined with stress/genotype on antidepressant efficacy. METHODS: A total of 291 MDD patients and 100 healthy controls received the Life Events Scale (LES) and the Childhood Trauma Questionnaire (CTQ) as stress assessment. Eight single nucleotide polymorphisms (SNPs) of HTR1A and HTR1B involved in antidepressant mechanisms were tested. Methylation status in 181 cytosine-phosphate-guanine (CpG) sites of HTR1A and HTR1B were assessed. All MDD patients were divided into response (RES) and non-response (NRES) after 2 weeks of antidepressant treatment. Logistic regression was conducted for interactions between methylation, NLES/CTQ score and genotype. RESULTS: Low HTR1A-2-143 methylation is connected with better antidepressant efficacy in subgroup. Low HTR1A-2-143 methylation combined with low CTQ score is related to better antidepressant efficacy. The interaction between high HTR1B methylation with the rs6298 AA/AG genotype affects better antidepressant efficacy. CONCLUSIONS: HTR1A and HTR1B methylation combined with stress/genotype is associated with antidepressant efficacy.

Influence of sleep difficulty on post-traumatic stress symptoms among frontline medical staff during COVID-19 pandemic in China.

Being a nurse was demonstrated to be a risk factor for post-traumatic stress symptoms (PTS) and insomnia among frontline staff during COVID-19 pandemic. The unidirectional relationship between insomnia and PTS highly suggested that insomnia could mediate the increasing risk of PTS among frontline nurses. However, no study had tried to clarify this mediation effect of insomnia during COVID-19 pandemic. This study aimed to investigate prevalence of insomnia and PTS among frontline doctors and nurses and to clarify the relationship between career (doctor/nurses), insomnia and PTS. A total of 211 frontline doctors and nurses completed the investigation. Insomnia was measured using a self-drafted questionnaire and PTS was assessed using primary care post-traumatic stress disorder screen (PC-PTSD). Three logistics regression models and one mediation model were performed to explore relationships between career, insomnia and PTS. The prevalence of PTS (PC-PTSD≥2) and insomnia (with 1 item in self-drafted insomnia questionnaire≥2) was 24.17% and 36.97%, respectively. Being a nurse was a shared risk factor of insomnia (OR = 4.16, 95%CI: 1.30 ~ 5.77, P = 0.023) and PTS (OR = 7.51, 95%CI: 1.89 ~ 40.50, P = 0.008). Compared to doctors, nurses had significantly higher prevalence of insomnia (46.32% vs. 20%, χ2 = 13.27, P < 0.001) and PTS (30.14% vs. 13.33%, χ2 = 6.57, P = 0.011). Insomnia was a significant partial mediator (B = 0.101, P = 0.026), which explained 32.53% proportions of relationship between being a nurse and PTS. PTS and insomnia were common symptoms, which should be considered in psychological aids among frontline medical staff. Insomnia might be a possible target of PTS intervention.

The Reliability and Validity of Post Stroke Depression Scale in Different Type of Post Stroke Depression Patients.

OBJECTIVE: A self-rating post stroke depression scale (PSDS) showed a good reliability and validity to assess severity of depressive symptoms among stroke patients. This study aimed to retest the psychometric properties of PSDS in different types of post-stroke depression (PSD). MATERIALS AND METHODS: A total of 170 stroke patients were recruited in the study. 82 and 25 patients were respectively diagnosed as PSD symptoms disorder (PSDSD) and PSD disorder (PSDD) patients according to their respective diagnostic criteria. The PSDS and the 9-item Patient Health Questionnaire (PHQ-9) were used to assess the severity of depression. Cronbach α, Spearman rank coefficient and independent sample t-test were conducted to examine reliability, internal consistency and discriminate validity. Then the receiver operating characteristic curve and Youden index were used to performance evaluation and cut-off value respectively in different subtypes of PSD patients. RESULTS: The Cronbach α of PSDS was 0.857, indicting a good reliability. The Spearman correlation coefficient between PSDS and PHQ-9 was 0.942 (P<0.001). The discriminate validity displayed significant difference between PSDSD as well as PSDD and no depression patients (all P<0.001). 5/24 and 10/24 were the cut-off value for PSDSD and PSDD patients. CONCLUSIONS: PSDS is a useful screen tool with an acceptable psychometric properties for estimation of different subtypes of PSD patients.

Clinimetric properties of the Chinese version of the Euthymia Scale.

The present study was conducted to primarily evaluate the clinimetric sensitivity of the Chinese version of the Euthymia Scale (ES), testing whether this measure discriminated between different groups of patients. Concurrent validity, a clinimetric property that refers to the assessment of the extent to which the rating scale under examination correlates with another related, previously validated, assessment instrument, was also tested investigating whether the ES significantly and negatively correlated with measures of depression and anxiety. A cross-sectional study was conducted. A total of 295 inpatients were recruited from different medical settings and included in this study. In addition to the ES, participants completed the PHQ-9 for the assessment of depression and the GAD-7 for the evaluation of symptoms of generalized anxiety. The clinimetric sensitivity of the ES was evaluated using the Mann-Whitney test and the Kruskal-Wallis analysis of variance, whereas the concurrent validity was tested via Spearman's correlation coefficients. The ES total score and its subscales of psychological flexibility and well-being discriminated between different groups of inpatients and sensitively differentiated depressed from non-depressed patients. Negative and statistically significant correlations between the ES and measures of depression and anxiety were found. Findings of the present study indicate that the Chinese version of the ES is a valid and sensitive clinimetric index that can be used not only to differentiate depressed from non-depressed patients but also as a screening measure to detect vulnerability to depression in a wide range of medical patients.

Characteristics of post-traumatic embitterment disorder of inpatients in a general hospital in China.

OBJECTIVE: Embitterment and post-traumatic embitterment disorder (PTED) is critical, merging through different cultures. We explored the prevalence and related clinical characteristics of PTED of inpatients in a general hospital in China. METHOD: Two hundred inpatients (aged 18-65 years) from different departments were recruited by convenient sampling and standardized diagnostic interviews of PTED. Demographic data, Post-traumatic Embitterment Disorder Self-Rating Scale (PTED-21), the Patient Health Questionnaire depression scale (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire depression scale (PHQ-15) were collected on all participants. RESULTS: The prevalence of PTED was 21% (42/200) in inpatients in China; besides, the rate of increased syndromal embitterment is 28% (56/200), including 42 patients diagnosed with PTED. PTED was mainly associated with stressful events, such as illness, work and complicated interpersonal relationships. Rheumatology department and respiratory department have the highest and second highest prevalence of PTED among all departments. PTED-21 scores were significantly correlated with PHQ-9, GAD-7 and PHQ-15 (all P < 0.01). CONCLUSIONS: The present study shows that embitterment is a critical negative emotion in inpatients with somatic illnesses with comorbid depression, anxiety and somatic symptoms. PTED and feelings of embitterment should be given proper attention in diagnosing somatic patients, and it is crucial to enhance PTED screening and intervention in the future. Future intervention studies on post-traumatic embitterment disorder could be done in general and especially in psychosomatic and somatic medicine.

Spatio-temporal graph convolutional network for diagnosis and treatment response prediction of major depressive disorder from functional connectivity.

The pathophysiology of major depressive disorder (MDD) has been explored to be highly associated with the dysfunctional integration of brain networks. It is therefore imperative to explore neuroimaging biomarkers to aid diagnosis and treatment. In this study, we developed a spatiotemporal graph convolutional network (STGCN) framework to learn discriminative features from functional connectivity for automatic diagnosis and treatment response prediction of MDD. Briefly, dynamic functional networks were first obtained from the resting-state fMRI with the sliding temporal window method. Secondly, a novel STGCN approach was proposed by introducing the modules of spatial graph attention convolution (SGAC) and temporal fusion. A novel SGAC was proposed to improve the feature learning ability and special anatomy prior guided pooling was developed to enable the feature dimension reduction. A temporal fusion module was proposed to capture the dynamic features of functional connectivity between adjacent sliding windows. Finally, the STGCN proposed approach was utilized to the tasks of diagnosis and antidepressant treatment response prediction for MDD. Performances of the framework were comprehensively examined with large cohorts of clinical data, which demonstrated its effectiveness in classifying MDD patients and predicting the treatment response. The sound performance suggests the potential of the STGCN for the clinical use in diagnosis and treatment prediction.

Desynchronized Functional Activities Between Brain White and Gray Matter in Major Depression Disorder.

BACKGROUND: Alterations in gray matter (GM) have been recognized as playing an important role in the neurobiological mechanism underlying major depressive disorder (MDD) and antidepressant responses. However, little is known about white matter (WM) connectivity in MDD, leaving an incomplete understanding of the pathophysiology of the disorder. PURPOSE: To examine the functional connectivity (FC) of WM, GM, and WM-GM in MDD patients and explore the relationship between FC and antidepressant response. STUDY TYPE: Longitudinal study. SUBJECTS: In all, 129 MDD patients and 89 healthy controls (HC). FIELD STRENGTH/SEQUENCE: Whole-brain blood oxygen level-dependent (BOLD) single-shot echo planar imaging was acquired at 3.0T. ASSESSMENT: At baseline, all participants received Hamilton depression rating scale (HAMD) assessment and an fMRI scan. After 2- and 8-week antidepressant treatment, patients completed the HAMD again. The HAMD reductive rate of 2- and 8-weeks were calculated. STATISTICAL TESTS: The comparisons of age, education, HAMD scores, and FC values (false discovery rate correction) between patients and controls were calculated with a two-sample t-test. The chi-square test was employed to compare the differences of gender between these two groups. Correlations between FC and HAMD, as well as the reductive rate of HAMD, were analyzed with Pearson or Spearman correlation. Receiver operator curve analysis was performed to predict the antidepressant response. RESULTS: Compared to HC, MDD patients exhibited widespread decreases in FC of WM-GM. Furthermore, 28 GM regions and 11 WM bundles had lower connectivity in MDD patients. At baseline, four FC of WM-GM showed negative correlations with the HAMD scores. Six FC of WM-GM correlated with the 2-week reductive rate of HAMD. Moreover, FC in GM, WM, and WM-GM also exhibited significantly positive correlations with an 8-week reductive rate of HAMD. DATA CONCLUSION: The FC of WM-GM was decreased in MDD and may play a role in its pathophysiology and antidepressant responses. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 2.

Strain distribution characteristics of sensing fiber and influence on sensitivity of a fiber-optic disk accelerometer.

In a fiber-optic disk accelerometer, the strain distribution of sensing fiber is crucial for the improvement of sensitivity. The distribution characteristics of axial and radial strain in the sensing fiber are analyzed by the finite-element method, and the influence of strain distribution on the sensitivity of accelerometer is studied. Sensors with different outer radii of sensing fiber coils are designed and manufactured, and their performance is tested. The resonant frequencies are greater than 200 Hz, and the sensitivity increases as the outer radius of the sensing fiber coil increases. The dynamic range of the sensor with maximum sensitivity is 145.8 dB@100 Hz, and the transverse cross talk is 32.5 dB. Among the sensing fiber strain calculation methods we tested to predict the value of sensitivity, using the strain of sensing fiber directly obtained by the finite-element analysis method shows the smallest error with experimental results (within 7%). It is concluded that in the optical fiber strain disk, the absolute values of axial strain and radial strain of sensing fiber decrease with the increase of disk radius, while the signs of axial strain and radial strain of the ipsilateral sensing fiber are opposite and remain unchanged. The sensitivity can be further improved by optimizing the inner and outer radius of the sensing fiber coils, which is very important for the research and design of high-sensitivity fiber-optic accelerometers.

Reliability and validity of the Chinese version of the post-traumatic embitterment disorder self-rating scale (PTED-21) among inpatients in general hospital.

Embitterment and in some cases also post-traumatic embitterment disorder (PTED) are relevant problem in the general population and even more so in psychiatric patients. PTED screening should be an essential component of routine mental health management, which can be done by the 21-item Post-traumatic Embitterment Disorder Self-Rating Scale (C-PTED-21), which measures the intensity of reactive stimulus bound embitterment. The PTED-21 German version was translated into Chinese, and 200 nonpsychiatric inpatients, reporting major negative life events, were recruited through convenience sampling to evaluate test performance. Ninety patients were selected for retest 2 weeks later to examine scale reliability. Factor analysis was used to assess construct validity and receiving operating characteristic curve analysis based on the "PTED standardized diagnostic interview" to assess diagnostic utility. Correlations with depression, somatic symptom, and anxiety scales were examined to assess aggregate validity. The C-PTED-21 demonstrated high internal consistency (Cronbach's α = 0.944) and good test-retest reliability (total score r = 0.783, individual item r value range, 0.635-0.889). Factor analysis revealed three common factors consistent with PTED core features. Total C-PTED-21 score was strongly correlated with the score on the nine-item Patient Health Questionnaire depression scale (PHQ-9, r = 0.735). Mean PTED-21 score ≥1.6 points distinguished clinical PTED as defined by diagnostic interview with 97.6% sensitivity and 90.5% specificity (AUC = 0.988, 95%CI: 0.976-0.999). The results show that the C-PTED-21 can assess the severity of PTED with good reliability and validity.