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Impairment in Theory of Mind (ToM) may serve as a mediator in the relationship between anxiety, depression emotions and non-suicidal self-injury (NSSI) in adolescent patients with depressive disorders. This study aimed to examine the mediating roles of ToM and impulsivity in the link between anxiety, depression, and NSSI in first-time hospitalized adolescents with depressive disorders. A total of 52 adolescents patients were recruited from Shenzhen Kangning Hospital. Anxiety, depression, impulsivity, NSSI, cognitive ToM, and affective ToM were assessed using the Hamilton Anxiety Rating Scale, Hamilton Depression Rating Scale, Barratt Impulsivity Scale, Adolescent Self-Harm Scale, Yoni task, and Hinting task. A structural equation model was developed using AMOS 24.0 to investigate the underlying mechanisms of NSSI. Our results indicate that anxiety not only directly contributes to NSSI but also exerts its influence through two indirect pathways: impairing cognitive ToM and disrupting affective ToM, which heightens impulsivity. These mechanisms may further increase the likelihood of NSSI (CMIN = 5.168, CMIN/DF = 1.292, P  = 0.270, GFI = 0.964, AGFI = 0.864, TLI = 0.929, RMSEA = 0.076). These results highlight the importance of interventions aimed at reducing anxiety and impulsivity while enhancing ToM abilities to help mitigate NSSI risk in adolescents with depressive disorders.

The neonatal period is a critical stage for microbial colonization and immune system development, with dynamic changes in the microbiome closely linked to the pathogenesis of various diseases. Traditional microbiological testing methods have low sensitivity and time-consuming limitations compared to metagenomic next-generation sequencing (mNGS), which makes it difficult to meet the diagnostic and therapeutic needs of critically ill neonates. mNGS analyzes the total DNA in a sample without bias, allowing comprehensive identification of bacteria, viruses, fungi, and parasites, and resolution of functional genes, providing new avenues for precision diagnosis and treatment of diseases such as neonatal sepsis, necrotizing enterocolitis, neonatal pneumonia, neonatal meningitis, neonatal jaundice, and other diseases. However, challenges remain, including the need to optimize sample processing workflows and develop portable devices to enhance clinical conversion potential. In this review, we summarize the application, efficacy, and limitations of mNGS in neonatal diseases. This approach paves the way for novel avenues in mechanistic research, early diagnosis, and personalized therapy for these conditions.

Recently, reversible data hiding (RDH) techniques for JPEG images have become more extensively used to combine image and authentication information conveniently into one file. Although embedding data in JPEG image degrades visual quality and increases file size, it is proven to be useful for data communication and image authentication. In this paper, a data hiding method in JPEG image using a new coefficient selection technique is proposed. The proposed scheme embeds data using the histogram shifting (HS) method. According to the number of zero AC coefficients, block ordering is used to embed data first in the blocks causing less distortion. In order to further reduce the distortion, positions of AC coefficients are selected carefully. Finally, AC coefficients valued +1 and −1 are used for embedding, and the remaining non-zero AC coefficients are shifted to the left or right directions according to their sign. Compared to the current state-of-the-art method, experimental results show that the proposed method has higher peak signal to noise ratio (PSNR) and smaller file size.

Reversible data hiding in JPEG images has become an important topic due to the prevalence and overwhelming support of the JPEG image format these days. Much of the existing work focuses on embedding using AC (quantized alternating current coefficients) to maximize the embedding capacity while minimizing the distortion and the file size increase. Traditionally, DC (quantized direct current coefficients) are not used for embedding, due to the assumption that the embedding in DCs cause more distortion than embedding in ACs. However, for data analytic which extracts fine details as a feature, distortion in ACs is not acceptable, because they represent the fine details of the image. In this paper, we propose a novel reversible data hiding method which efficiently embeds in the DC. The propose method uses a novel DC prediction method to decrease the entropy of the prediction error histogram. The embedded image has higher PSNR, embedding capacity, and smaller file size increase. Furthermore, proposed method preserves all the fine details of the image.

Exploring and investigating new chaotic systems is a popular topic in nonlinear science. Although numerous chaotic systems have been introduced in the literature, few of them focus on torus-chaotic system. The aim of our short work is to widen the current knowledge of torus chaos. In this paper, a new torus-chaotic system is proposed, which has one positive Lyapunov exponent, two zero Lyapunov exponents, and two negative Lyapunov exponents. The dynamic behavior is investigated by Lyapunov exponents, bifurcations, and stability. The analysis shows that this system has an interesting route leading to chaos. Furthermore, the pseudorandom properties of output sequence are well studied and a random number generator algorithm is proposed, which has the potential of being used in several cyber security systems such as the verification code, secure QR code, and some secure communication protocols.

Background Previous studies have demonstrated that secreted frizzled-related protein 4 (SFRP4) is associated with impaired glucose and triglyceride metabolism in patients with stable coronary artery disease. In the present study, we investigated human epicardial adipose tissue (EAT)-derived and circulating SFRP4 levels in patients with coronary artery disease (CAD). Methods Plasma samples and adipose biopsies from EAT and subcutaneous adipose tissue (SAT) were collected from patients with CAD (n = 40) and without CAD (non-CAD, n = 30) during elective cardiac surgery. The presence of CAD was identified by coronary angiography. SFRP4 mRNA and protein expression levels in adipose tissue were detected by quantitative real-time PCR and immunohistochemistry, respectively. Plasma SFRP4 concentrations were measured by an enzyme-linked immunosorbent assay (ELISA). Correlation analysis and multivariate linear regression analysis were used to determine the association of SFRP4 expression with atherosclerosis as well as clinical risk factors. Results SFRP4 mRNA and protein expression levels were significantly lower in EAT than in paired SAT in patients with and without CAD (all P  < 0.05). Compared to non-CAD patients, CAD patients had higher SFRP4 expression levels in EAT (both mRNA and protein levels) and in plasma. Multivariate linear regression analysis showed that CAD was an independent predictor of SFRP4 expression levels in EAT (beta = 0.442, 95% CI 0.030–0.814; P  = 0.036) and in plasma (beta = 0.300, 95% CI 0.056–0.545; P  = 0.017). SAT-derived SFRP4 mRNA levels were independently associated with fasting insulin levels (beta = 0.382, 95% CI 0.008–0.756; P  = 0.045). In addition, plasma SFRP4 levels were positively correlated with BMI (r = 0.259, P  = 0.030), fasting insulin levels (r = 0.306, P  = 0.010) and homeostasis model assessment of insulin resistance (HOMA-IR) values (r = 0.331, P  = 0.005). Conclusions EAT-derived and circulating SFRP4 expression levels were increased in patients with CAD. EAT SFRP4 mRNA levels and plasma SFRP4 concentrations were independently associated with the presence of CAD.

Timely application of surfactant replacement therapy is critical for neonates with respiratory distress syndrome (RDS). Presently, early clinical decision on surfactant use relies solely on ventilator parameters. However, ventilator parameters are unable to truly recapitulate the extent of surfactant deficiency. Lung ultrasound has been increasingly used in the early prediction of surfactant use in recent years, but its predictive value remains unclear. Therefore, we conducted this study to examine its predictive value in surfactant use and determine the optimal timing and cutoff value. Studies on neonates with respiratory distress or diagnosed with RDS were collected from PubMed, Embase, Cochrane Library, and Web of Science. Primary outcomes included sensitivity, specificity, and positive and negative predictive values of lung ultrasound. Ten eligible studies with 1162 participants were included. The sensitivity and specificity of lung ultrasound in predicting surfactant use were 0.86 (95% CI: 0.81-0.90) and 0.82 (95% CI: 0.71-0.90), respectively. Lung ultrasound performed within 1-3 h after birth had a sensitivity of 0.89 (95% CI: 0.79-0.95) and a Youden's index of 0.67. Compared with a lung ultrasound score (LUS) cutoff of ≤6/7, ≤8, >5, >6/7, and >8, a LUS cutoff of ≤5 had higher Youden's index (0.73) and sensitivity (0.94, 95% CI: 0.85-0.97) in predicting surfactant use. Lung ultrasound is effective for predicting surfactant use in neonates. Lung ultrasound within 1-3 h after birth and a LUS cutoff of 5 are recommended. However, the symptoms and oxygenation of the neonatal patients must also be considered.

For steganalysis of JPEG images, features derived in the embedding domain appear to achieve a preferable performance. However, with the existing JPEG steganography, the minor changes due to the hidden secret data are not easy to be explored directly from the quantized block DCT (BDCT) coefficients in that the energy of the carrier image is much larger than that of the hidden signal. In this paper, we present an improved calibration-based universal JPEG steganalysis, where the microscopic and macroscopic calibrations are combined to calibrate the local and global distribution of the quantized BDCT coefficients of the test image. All features in our method are generated from the difference signal between the quantized BDCT coefficients of the test image and its corresponding microscopic calibrated image, or calculated as the difference between the signal extracted from test image and its corresponding macroscopic calibrated image. The extracted features will be more effective for our classification. Moreover, through using the Markov empirical transition matrices, both magnitude and sign dependencies along row scanning and column scanning patterns existed in intra-block and inter-block quantized BDCT coefficients are employed in our method. Experimental results demonstrate that our proposed scheme outperforms the best effective JPEG steganalyzers having been presented.

Recently, a reversible data hiding (RDH) method was proposed based on local histogram shifting. This method selects the peak bin of the local histogram as a reference and expands the two neighboring bins of the peak bin to carry the message bits. Since the peak bin keeps unchanged during the embedding process, the neighboring bins can be easily identified at the receiver end, and the original image can be restored completely while extracting the embedded data. In this article, as an extension of the algorithm, the authors propose an RDH scheme based on adaptive block selection strategy. Via a new block selection strategy, those blocks of the carrier image may carry more message bits whereas introducing less distortion will take precedence over data hiding. Experimental results demonstrate that higher visual quality can be obtained compared with the original method, especially when the embedding rate is low.

Recently, reversible data hiding (RDH) in joint photographic experts group (JPEG) images has received a great deal of attention since the JPEG image is one of the most popularly used image formats nowadays. Generally in JPEG image, the quantized discrete cosine transform (DCT) coefficients with the value of zero are far more than those with nonzero coefficients. However, most existing methods are avoided to change these zero coefficients for fear of JPEG file size increase, and the designed distortion cost functions are not perfect. In this paper, we propose a new JPEG RDH method in which the numerous zero coefficients can be modified. Based on an improved distortion cost function, a strategy which can measure the distortion for each coefficient and select coefficient positions which are most suitable for embedding is proposed. With this strategy, zero coefficients are applied to data embedding and the embedding performance is improved. Experimental results have proved that the proposed method can effectively reduce the embedding distortion and increase the embedding capacity while maintaining a relative good file size.