Strategies for Treating Traumatic Neuromas with Tissue-Engineered Materials.

Neuroma, a pathological response to peripheral nerve injury, refers to the abnormal growth of nerve tissue characterized by disorganized axonal proliferation. Commonly occurring after nerve injuries, surgeries, or amputations, this condition leads to the formation of painful nodular structures. Traditional treatment options include surgical excision and pharmacological management, aiming to alleviate symptoms. However, these approaches often offer temporary relief without addressing the underlying regenerative challenges, necessitating the exploration of advanced strategies such as tissue-engineered materials for more comprehensive and effective solutions. In this study, we discussed the etiology, molecular mechanisms, and histological morphology of traumatic neuromas after peripheral nerve injury. Subsequently, we summarized and analyzed current nonsurgical and surgical treatment options, along with their advantages and disadvantages. Additionally, we emphasized recent advancements in treating traumatic neuromas with tissue-engineered material strategies. By integrating biomaterials, growth factors, cell-based approaches, and electrical stimulation, tissue engineering offers a comprehensive solution surpassing mere symptomatic relief, striving for the structural and functional restoration of damaged nerves. In conclusion, the utilization of tissue-engineered materials has the potential to significantly reduce the risk of neuroma recurrence after surgical treatment.

A Case report: Synovial sarcoma of the mediastinum in an 18-year-old teenager.

Synovial sarcomas (SSs) are a rare group of malignant tumors originating from pluripotential mesenchymal cells, which commonly occur as the primary tumor in the soft tissues near the articular surface, tendons, and articular synovium. Herein, we report a rare case of mediastinal SS in an 18-year-old teenager who initially presented with cough as the primary symptom. In this case, plain chest CT and contrast-enhanced CT clearly revealed the lesion presenting as a round-like and uneven density mass in the mediastinum with heterogeneous enhancement, which compressed the trachea and invaded the adjacent vessels. Based on the results of immunohistochemistry and fluorescence in situ hybridization (FISH), combined with the differential diagnosis with other types of tumors in the mediastinum on imaging, we were able to diagnose the tumor as an SS located in the mediastinum. Subsequent resection of the lesion coupled with chemotherapy and immunotherapy led to an improvement in the patient's symptoms.

Photo-sensitive peptide inducing targeted cross-linking in a one-step and reagent-, enzyme- and antibody-free detection of SARS-Cov-2 marker protein.

Modern biosensing technology plays a crucial role in combating the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). However, the associated assays remain costly, considering their extensive daily use. In response, we developed a simplified one-step SARS-CoV-2 protease assay that reduces both time and financial expenses. This approach eliminates the need for extra reagents, enzymes, or antibodies. The simplification involves a photo-sensitive Bengal red-tagged substrate peptide, allowing specific cross-linking upon protease-substrate recognition. This process forms a di-tyrosine product with a distinctive fluorescence signal readout, enabling the detection of SARS-CoV-2 in patient serum samples. This method anticipates a major reduction in assay costs in the near future.

Growth factors: Bioactive macromolecular drugs for peripheral nerve injury treatment - Molecular mechanisms and delivery platforms.

Bioactive macromolecular drugs known as Growth Factors (GFs), approved by the Food and Drug Administration (FDA), have found successful application in clinical practice. They hold significant promise for addressing peripheral nerve injuries (PNIs). Peripheral nerve guidance conduits (NGCs) loaded with GFs, in the context of tissue engineering, can ensure sustained and efficient release of these bioactive compounds. This, in turn, maintains a stable, long-term, and effective GF concentration essential for treating damaged peripheral nerves. Peripheral nerve regeneration is a complex process that entails the secretion of various GFs. Following PNI, GFs play a pivotal role in promoting nerve cell growth and survival, axon and myelin sheath regeneration, cell differentiation, and angiogenesis. They also regulate the regenerative microenvironment, stimulate plasticity changes post-nerve injury, and, consequently, expedite nerve structure and function repair. Both exogenous and endogenous GFs, including NGF, BDNF, NT-3, GDNF, IGF-1, bFGF, and VEGF, have been successfully loaded onto NGCs using techniques like physical adsorption, blend doping, chemical covalent binding, and engineered transfection. These approaches have effectively promoted the repair of peripheral nerves. Numerous studies have demonstrated similar tissue functional therapeutic outcomes compared to autologous nerve transplantation. This evidence underscores the substantial clinical application potential of GFs in the domain of peripheral nerve repair. In this article, we provide an overview of GFs in the context of peripheral nerve regeneration and drug delivery systems utilizing NGCs. Looking ahead, commercial materials for peripheral nerve repair hold the potential to facilitate the effective regeneration of damaged peripheral nerves and maintain the functionality of distant target organs through the sustained release of GFs.

Low Dose Iodinated Contrast Material and Radiation for Virtual Monochromatic Imaging in Craniocervical Dual-Layer Spectral Detector Computed Tomography Angiography: A Prospective and Randomized Study.

RATIONALE AND OBJECTIVES: To investigate the feasibility of virtual monochromatic imaging (VMI) of dual-layer spectral detector computed tomography (SDCT) to reduce iodinated contrast material (CM) and radiation dose in craniocervical computed tomography angiography (CTA). MATERIALS AND METHODS: A total of 280 consecutively selected patients performed craniocervical CTA with SDCT were prospectively selected and randomly divided into four groups (A, DoseRight index (DRI) 31, iopromide 370mgI/mL, volume 0.8 mL/kg; B, DRI 26, iopromide 370mgI/mL, volume 0.4 mL/kg; C, DRI 26, ioversol 320mgI/mL, volume 0.4 mL/kg; D, DRI 26, iohexol 300mgI/mL, volume 0.4 mL/kg). 50-70 kiloelectron volts (keV) VMIs in group B were reconstructed and compared to group A to select the optimal keV. Then, the optimal keV in groups B, C and D was reconstructed and compared. Objective image quality, including vascular attenuation, image noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), was evaluated. Subjective image quality was assessed using a 5-point Likert scale. In addition, the effective dose (ED), iodine load and iodine delivery rate (IDR) were compared between groups A and D. RESULTS: 55 keV VMI was the optimal VMI in group B. The objective and subjective image quality of 55 keV VMI in group B were equal to or better than those of the CI in group A. The SNR, CNR and subjective image quality in group D were similar to those in group B (P > 0.05). The ED, iodine load and IDR of group D were reduced by 44%, 59% and 19%, respectively, when compared to those of group A. CONCLUSION: Low dose iodinated CM and radiation for 55 keV VMI in craniocervical CTA using SDCT could still provide equivalent or better image quality than the conventional scanning protocol.

Laser-Visible Face Image Translation and Recognition Based on CycleGAN and Spectral Normalization.

The range-gated laser imaging instrument can capture face images in a dark environment, which provides a new idea for long-distance face recognition at night. However, the laser image has low contrast, low SNR and no color information, which affects observation and recognition. Therefore, it becomes important to convert laser images into visible images and then identify them. For image translation, we propose a laser-visible face image translation model combined with spectral normalization (SN-CycleGAN). We add spectral normalization layers to the discriminator to solve the problem of low image translation quality caused by the difficulty of training the generative adversarial network. The content reconstruction loss function based on the Y channel is added to reduce the error mapping. The face generated by the improved model on the self-built laser-visible face image dataset has better visual quality, which reduces the error mapping and basically retains the structural features of the target compared with other models. The FID value of evaluation index is 36.845, which is 16.902, 13.781, 10.056, 57.722, 62.598 and 0.761 lower than the CycleGAN, Pix2Pix, UNIT, UGATIT, StarGAN and DCLGAN models, respectively. For the face recognition of translated images, we propose a laser-visible face recognition model based on feature retention. The shallow feature maps with identity information are directly connected to the decoder to solve the problem of identity information loss in network transmission. The domain loss function based on triplet loss is added to constrain the style between domains. We use pre-trained FaceNet to recognize generated visible face images and obtain the recognition accuracy of Rank-1. The recognition accuracy of the images generated by the improved model reaches 76.9%, which is greatly improved compared with the above models and 19.2% higher than that of laser face recognition.

Application of Improved CycleGAN in Laser-Visible Face Image Translation.

CycleGAN is widely used in various image translations, such as thermal-infrared-visible-image translation, near-infrared-visible-image translation, and shortwave-infrared-visible-image translation. However, most image translations are used for infrared-to-visible translation, and the wide application of laser imaging has an increasingly strong demand for laser-visible image translation. In addition, the current image translation is mainly aimed at frontal face images, which cannot be effectively utilized to translate faces at a certain angle. In this paper, we construct a laser-visible face mapping dataset; in case of the gradient dispersion of the objective function of the original adversarial loss, the least squares loss function is used to replace the cross-entropy loss function and an identity loss function is added to strengthen the network constraints on the generator. The experimental results indicate that the SSIM value of the improved model increases by 1.25%, 8%, 0, 8%, the PSNR value is not much different, and the FID value decreases by 11.22, 12.85, 43.37 and 72.19, respectively, compared with the CycleGAN, Pix2pix, U-GAN-IT and StarGAN models. In the profile image translation, in view of the poor extraction effect of CycleGAN's original feature extraction module ResNet, the RRDB module is used to replace it based on the first improvement. The experimental results show that, compared with the CycleGAN, Pix2pix, U-GAN-IT, StarGAN and the first improved model, the SSIM value of the improved model increased by 3.75%, 10.67%, 2.47%, 10.67% and 2.47%, respectively; the PSNR value increased by 1.02, 2.74, 0.32, 0.66 and 0.02, respectively; the FID value reduced by 26.32, 27.95, 58.47, 87.29 and 15.1, respectively. Subjectively, the contour features and facial features were better conserved.

Concentrations, distribution, and risk assessment of endosulfan residues in the cotton fields of northern Xinjiang, China.

In the current study, surface soil samples were collected from cotton fields in Shawan and Shihezi areas in northern Xinjiang and tested for endosulfan residues using gas chromatography-mass spectrometry. Results showed endosulfan sulfate was the predominant compound in the surface soil studied, followed by ß-endosulfan and α-endosulfan with detection rates of 86.9%, 55.7%, and 49.2%, respectively, for the 61 soil samples collected. The average concentrations of endosulfan sulfate, α-endosulfan, and ß-endosulfan were 0.743, 0.166, and 0.073 µg/kg, respectively. The ratios of α-/ß-endosulfan were below 2.33 in all samples tested, suggesting no new endosulfan was added to the soil and the presence of endosulfan residues in this region was due to historical application in the past. According to the health risk assessment model recommended by the USA Environmental Protection Agency, the health risk of endosulfan residues in the studied area was low, and the maximum values of noncarcinogenic risks for children and adults were 2.30 × 10-5 and 2.70 × 10-6, respectively. Folsomia candida was the most sensitive organism to total endosulfan residues, with 38% of the total sampling sites classified as high risk. For earthworms, the proportion of high risk site was 13%. Lactuca sativa was the most tolerant organism to ∑ESs, with all sampling sites identified as negligible risk. This study provided current status of endosulfan residues and related risk in cotton fields, which could be used to support decision makers to prepare relevant regulations.