Potential Clinical Applications Research Articles

Structure preservation constraints for unsupervised domain adaptation intracranial vessel segmentation.

Unsupervised domain adaptation (UDA) has received interest as a means to alleviate the burden of data annotation. Nevertheless, existing UDA segmentation methods exhibit performance degradation in fine intracranial vessel segmentation tasks due to the problem of structure mismatch in the image synthesis procedure. To improve the image synthesis quality and the segmentation performance, a novel UDA segmentation method with structure preservation approaches, named StruP-Net, is proposed. The StruP-Net employs adversarial learning for image synthesis and utilizes two domain-specific segmentation networks to enhance the semantic consistency between real images and synthesized images. Additionally, two distinct structure preservation approaches, feature-level structure preservation (F-SP) and image-level structure preservation (I-SP), are proposed to alleviate the problem of structure mismatch in the image synthesis procedure. The F-SP, composed of two domain-specific graph convolutional networks (GCN), focuses on providing feature-level constraints to enhance the structural similarity between real images and synthesized images. Meanwhile, the I-SP imposes constraints on structure similarity based on perceptual loss. The cross-modality experimental results from magnetic resonance angiography (MRA) images to computed tomography angiography (CTA) images indicate that StruP-Net achieves better segmentation performance compared with other state-of-the-art methods. Furthermore, high inference efficiency demonstrates the clinical application potential of StruP-Net. The code is available at https://github.com/Mayoiuta/StruP-Net .

Mamba- and ResNet-Based Dual-Branch Network for Ultrasound Thyroid Nodule Segmentation.

Accurate segmentation of thyroid nodules in ultrasound images is crucial for the diagnosis of thyroid cancer and preoperative planning. However, the segmentation of thyroid nodules is challenging due to their irregular shape, blurred boundary, and uneven echo texture. To address these challenges, a novel Mamba- and ResNet-based dual-branch network (MRDB) is proposed. Specifically, the visual state space block (VSSB) from Mamba and ResNet-34 are utilized to construct a dual encoder for extracting global semantics and local details, and establishing multi-dimensional feature connections. Meanwhile, an upsampling-convolution strategy is employed in the left decoder focusing on image size and detail reconstruction. A convolution-upsampling strategy is used in the right decoder to emphasize gradual feature refinement and recovery. To facilitate the interaction between local details and global context within the encoder and decoder, cross-skip connection is introduced. Additionally, a novel hybrid loss function is proposed to improve the boundary segmentation performance of thyroid nodules. Experimental results show that MRDB outperforms the state-of-the-art approaches with DSC of 90.02% and 80.6% on two public thyroid nodule datasets, TN3K and TNUI-2021, respectively. Furthermore, experiments on a third external dataset, DDTI, demonstrate that our method improves the DSC by 10.8% compared to baseline and exhibits good generalization to clinical small-scale thyroid nodule datasets. The proposed MRDB can effectively improve thyroid nodule segmentation accuracy and has great potential for clinical applications.

Recent advances in chemotherapy for cancer therapy over Cu-based nanocatalysts.

Recently, the emerging chemotherapy (CDT) has provided a new biocompatibility pathway for cancer therapy. Among them, Cu-based nanocatalysts with good biocompatibility and Fenton-like catalytic efficiency are considered to be a promising approach for enhancing CDT and CDT-involved multimodal synergies to improve the effectiveness of catalytic cancer therapy. Meanwhile, the emerging in situ therapy strategy promoted by Cu-based nanocatalysts has proven to exhibit attractive clinical application potential in replacing traditional chemotherapy and radiotherapy for cancer therapy with significant toxic side effects. In this work, the recent progress of various Cu-based nanocatalysts in cancer therapy was reviewed, especially the remarkable achievements in the catalytic treatment of cancer in the tumor microenvironment using CDT and CDT-involved multimodal synergies. In addition, the development expectations and challenges of Cu-based nanocatalysts in the field of cancer therapy were briefly summarized and discussed. We expect that this review will contribute to the development of Cu-based nanocatalysts for cancer therapy.

Bladder Cancer detection by urinary methylation markers GHSR/MAL: a validation study

PurposeAlthough cystoscopy is a reliable tool for detecting bladder cancer, it poses a high burden on patients and entails high costs. This highlights the need for non-invasive and cost-effective alternatives. This study aimed to validate a previously developed urinary methylation marker panel containing GHSR and MAL.MethodsWe enrolled 134 patients who underwent cystoscopy because of hematuria, including 63 individuals with primary bladder cancer and 71 with non-malignant findings. Urine samples were self-collected at home and sent via regular mail. Subsequently, DNA was extracted and the hypermethylation of GHSR and MAL was evaluated using quantitative methylation-specific polymerase chain reaction. The performance of methylation markers was assessed using area-under-the-curve (AUC) analysis and sensitivity and specificity based on pre-established cut-off values.ResultsValidation of the marker panel GHSR/MAL resulted in an AUC of 0.87 at 79% sensitivity and 80% specificity. Sensitivity was comparable to the previous investigation (P > 0.9), though specificity was significantly lower (P = 0.026). Sensitivity was higher for high-grade tumors compared to low-grade tumors (94% vs. 60%, P = 0.002).ConclusionValidation of the GHSR/MAL methylation marker panel on at home collected urine samples confirms its robust performance for bladder cancer detection in a hematuria population, and underscores the diagnostic potential for future clinical application.

Verdiff-Net: A Conditional Diffusion Framework for Spinal Medical Image Segmentation.

Spinal medical image segmentation is critical for diagnosing and treating spinal disorders. However, ambiguity in anatomical boundaries and interfering factors in medical images often cause segmentation errors. Current deep learning models cannot fully capture the intrinsic data properties, leading to unstable feature spaces. To tackle the above problems, we propose Verdiff-Net, a novel diffusion-based segmentation framework designed to improve segmentation accuracy and stability by learning the underlying data distribution. Verdiff-Net integrates a multi-scale fusion module (MSFM) for fine feature extraction and a noise semantic adapter (NSA) to refine segmentation masks. Validated across four multi-modality spinal datasets, Verdiff-Net achieves a high Dice coefficient of 93%, demonstrating its potential for clinical applications in precision spinal surgery.

Interactive Segmentation for Medical Images Using Spatial Modeling Mamba

Interactive segmentation methods utilize user-provided positive and negative clicks to guide the model in accurately segmenting target objects. Compared to fully automatic medical image segmentation, these methods can achieve higher segmentation accuracy with limited image data, demonstrating significant potential in clinical applications. Typically, for each new click provided by the user, conventional interactive segmentation methods reprocess the entire network by re-inputting the click into the segmentation model, which greatly increases the user’s interaction burden and deviates from the intended goal of interactive segmentation tasks. To address this issue, we propose an efficient segmentation network, ESM-Net, for interactive medical image segmentation. It obtains high-quality segmentation masks based on the user’s initial clicks, reducing the complexity of subsequent refinement steps. Recent studies have demonstrated the strong performance of the Mamba model in various vision tasks; however, its application in interactive segmentation remains unexplored. In our study, we incorporate the Mamba module into our framework for the first time and enhance its spatial representation capabilities by developing a Spatial Augmented Convolution (SAC) module. These components are combined as the fundamental building blocks of our network. Furthermore, we designed a novel and efficient segmentation head to fuse multi-scale features extracted from the encoder, optimizing the generation of the predicted segmentation masks. Through comprehensive experiments, our method achieved state-of-the-art performance on three medical image datasets. Specifically, we achieved 1.43 NoC@90 on the Kvasir-SEG dataset, 1.57 NoC@90 on the CVC-ClinicDB polyp segmentation dataset, and 1.03 NoC@90 on the ADAM retinal disk segmentation dataset. The assessments on these three medical image datasets highlight the effectiveness of our approach in interactive medical image segmentation.

A Mini-Review on Gene Therapy in Glaucoma and Future Directions

Glaucoma is a group of optic neuropathies characterized by the degeneration of retinal ganglion cells and the loss of their axons in the optic nerve. The only approved therapies for the treatment of glaucoma are topical medications and surgical procedures aimed at lowering intraocular pressure. Gene therapy involves the insertion, removal, or modification of genetic material within cells to repair or compensate for the loss of a gene’s function. It describes a process or technology that enables the genetic modification of cells to produce a therapeutic effect. However, changing the genetic material alone does not extend the duration of overexpression of proteins that combat disease, nor does it facilitate the production of new proteins for this purpose. We reviewed the literature concerning the use of gene therapy in the treatment of glaucoma and explored the future directions that this innovation may offer. Three genes associated with glaucoma have been identified within these loci: myocilin/trabecular meshwork glucocorticoid response (TIGR) (GLC1A), optineurin (GLC1E), and WDR36 (GLC1G). Among these, the most extensively studied glaucoma gene is myocilin (a TM-inducible glucocorticoid response gene). Building on previous successes, researchers have begun to apply genetic therapeutic approaches to alleviate or reduce symptoms associated with ocular hypertension (OHT) and glaucoma-like optic neuropathy (GON). It is evident that several therapeutic strategies exist that modulate aqueous humor production and flow, thereby regulating intraocular pressure (IOP) and protecting retinal ganglion cells (RGCs) from apoptosis. With the emergence of gene therapy as a potentially viable approach to preserving vision, new methods for managing glaucoma may soon become available. Genomic therapy is a promising treatment option for glaucoma patients and has significant potential for widespread clinical application.

Integrating color histogram analysis and convolutional neural networks for skin lesion classification

The color of skin lesions is a crucial diagnostic feature for identifying malignant melanoma and other skin diseases. Typical colors associated with melanocytic lesions include tan, brown, black, red, white, and blue-gray. This study introduces a novel feature: the number of colors present in lesions, which can indicate the severity of skin diseases and help distinguish melanomas from benign lesions. We propose a color histogram analysis, a traditional image processing technique, to analyze the pixels of skin lesions from three publicly available datasets: PH2, ISIC2016, and Med-Node, which include dermoscopic and non-dermoscopic images. While the PH2 dataset contains ground truth about skin lesion colors, the ISIC2016 and Med-Node datasets lack such annotations; our algorithm establishes this ground truth using the color histogram analysis based on the PH2 dataset. We then design and train a 19-layer Convolutional Neural Network (CNN) with different skip connections of residual blocks to classify lesions into three categories based on the number of colors present. The DeepDream algorithm is utilized to visualize the learned features of different layers, and multiple configurations of the proposed CNN are tested, achieving the highest weighted F1-score of 75.00 % on the test set. LIME is subsequently applied to identify the most important features influencing the model's decision-making. The findings demonstrate that the number of colors in lesions is a significant feature for describing skin conditions. The proposed CNN, particularly with three skip connections, shows strong potential for clinical application in diagnosing melanoma, supporting its use alongside traditional diagnostic methods.

Transvaginal double-layer parallel in-situ suturing for early complex vesicovaginal fistula repair: Case report.

Complex vesicovaginal fistulas (VVFs) with large defects pose significant surgical challenges. Traditional repair methods often require extensive tissue separation and multilayer suturing, risking local blood supply and healing. This study introduces a novel modified transvaginal repair technique that simplifies the procedure while preserving tissue vascularity. It employs double-layer parallel in situ suturing for early repair of complex VVF. A 50-year-old woman was admitted with continuous vaginal urine leakage for 4 days following trauma. Speculum examination revealed a 3-cm longitudinal oval laceration at the 11 o'clock position in the dorsal lithotomy site, with continuous fluid leakage through the fistula. Self-inflicted complex VVF. The patient underwent prophylactic placement of bilateral double-J stents and continuous catheterization, followed by surgical repair using a modified transvaginal technique involving double-layer parallel in situ suturing. Postoperative evaluations showed successful healing with no urinary leakage. The vaginal sutures were removed on day 24, and follow-up at 1 year confirmed no recurrence of the fistula or lower urinary tract symptoms, significantly improving the patient's quality of life. The modified transvaginal repair technique using double-layer parallel in situ suturing is a simple and effective approach for early repair of complex VVF, highlighting its potential for broader clinical application. Future studies with larger cohorts are needed to validate these findings.

Effectiveness of accelerated rehabilitation surgical nursing on perioperative outcomes in patients with calcaneal fractures.

This study aims to evaluate the impact of accelerated rehabilitation nursing on perioperative outcomes in patients with calcaneal fractures. A total of 101 patients with calcaneal fractures admitted from December 2020 to December 2022 were included in this study. Patients were randomly assigned to an observation group (OG) of 51 patients receiving accelerated rehabilitation surgical nursing and a control group (CG) of 50 patients receiving conventional surgical nursing. Outcomes assessed included patient satisfaction, visual analog scale (VAS) scores before and after surgery, swelling reduction time, and complication rates. The satisfaction rate in the OG was 96.07%, significantly higher than the 80.00% observed in the CG. Post-operative VAS scores at day 4 and 6 were significantly lower in the OG compared to the CG. Swelling reduction time was shorter in the OG (152.56 ± 25.22 hours) compared to the CG (170.76 ± 22.51 hours). Additionally, the complication rate in the OG was significantly lower at 7.84% compared to 24.00% in the CG (P < .05).the implementation of accelerated rehabilitation nursing significantly shortened the average length of hospital stay for patients in the observation group. In contrast, patients in the control group, who received conventional nursing care, had a relatively longer hospital stay. In the perioperative treatment of calcaneal fractures, accelerated rehabilitation surgical nursing can significantly improve patient satisfaction, reduce pain, shorten the time for swelling to subside, and lower the incidence of complications. Additionally, it can shorten the hospital stay for patients, demonstrating its efficacy and potential for broader clinical application.

Development and validation of nomogram for predicting the cancer-specific survival among patients aged 80 and above with early-stage non-small cell lung cancer.

The use of nomograms in predicting the prognosis of early-stage non-small cell lung cancer (NSCLC), particularly in elderly patients, is not widespread. A validated prognostic model specifically for NSCLC patients over 80 years old holds promising potential for clinical application in forecasting patient outcomes. The prognostic value of various factors for NSCLC patients aged 80 and above was evaluated using data from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2017). Kaplan-Meier (KM) curves, Cox proportional hazards regression models, and nomogram were utilized to evaluate the impact of each factor on cancer-specific survival (CSS). A cohort comprising 7045 individuals was selected for inclusion in the analysis. Through rigorous statistical analysis, 10 independent prognostic factors were identified and incorporated into the nomogram. The nomogram's receiver operating characteristic (ROC) curve area under the curve (AUC) was higher than that of the AJCC 7th edition TNM staging system's predicted CSS (0.744 versus 0.602), establishing the superior prognostic value of the nomogram. We have successfully created a highly accurate and discriminative nomogram that enables oncologists to predict the survival outcome of each individual patient with I/II NSCLC who is 80 years or older.

The application effect of a pulmonary rehabilitation program based on empowerment theory for patients with COPD combined with heart failure.

Chronic obstructive pulmonary disease (COPD) and heart failure are often coexisting conditions that can severely impact patients' cardiopulmonary function and quality of life. Pulmonary rehabilitation programs, particularly those based on empowerment theory, may improve clinical outcomes by enhancing self-efficacy and promoting patient engagement. A total of 70 patients with COPD and heart failure admitted to our hospital's respiratory department from January 1, 2023, to April 31, 2024, were randomly assigned to either a control group (n = 35) or an observation group (n = 35). The control group received routine care, while the observation group underwent an empowerment-based pulmonary rehabilitation program in addition to routine care for 4 weeks. Lung function (forced vital capacity, forced expiratory volume in 1 second, maximum voluntary ventilation), arterial blood gas levels (partial pressure of carbon dioxide, partial pressure of oxygen, and arterial oxygen saturation), cardiac function (left ventricular ejection fraction and serum brain natriuretic peptide), cardiopulmonary function (heart rate, respiratory rate, and 6-minute walk test), self-efficacy, and rehabilitation compliance were measured before and after the intervention. There were no significant differences between the groups before the intervention (P > 0.05). After the intervention, the observation group exhibited significant improvements in lung function, arterial blood gas levels, cardiac and cardiopulmonary function, and self-efficacy scores compared with the control group (P < 0.05). Rehabilitation compliance was also significantly higher in the observation group (P < 0.05). An empowerment-based pulmonary rehabilitation program effectively improves rehabilitation compliance, lung and heart function, and self-efficacy in COPD patients with heart failure, suggesting it has strong potential for clinical application.

Innovating uric acid Biosensing: Development of a GSH@Cd-Mediated Dual-Signal fluorometric method

Uric acid (UA) is a crucial biomarker for various metabolic and renal disorders, making its accurate determination essential for clinical diagnostics and disease management. This study presents a novel fluorometric method for UA detection using a glutathione@cadmium/carbon dots/uricase system (GSH@Cd/CDs/uricase system), which offers enhanced sensitivity and selectivity compared to existing techniques. The method employs a cascade reaction mechanism initiated by uricase-catalyzed oxidation of UA to produce H2O2. This H2O2 subsequently oxidizes GSH to oxidized glutathione (GSSG), releasing cadmium ions from GSH complexes. The liberated Cd2+ ions interact with two types of carbon dots (CDs) in the system: blue-emitting CDs (BCDs) and red-emitting CDs (RCDs). This interaction triggers a dual fluorescence response, characterized by a decrease in fluorescence intensity at 400 nm (BCDs) and an increase at 610 nm (RCDs), enabling ratiometric detection of UA levels. Comprehensive characterization and mechanistic investigations were conducted using various optical and morphological techniques, including transmission electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and fluorescence spectroscopy. The method exhibits outstanding analytical performance, characterized by strong linearity (R2 = 0.9932), a broad detection range (0.05–7.0 μM), and a low detection limit of 0.015 μM. The method demonstrated excellent selectivity against common interfering substances and was successfully applied to human serum and urine samples with high recovery values (97.65 % to 99.20 %), highlighting its potential for clinical applications. This innovative approach combines the specificity of enzymatic recognition with the sensitivity of dual-emission fluorescence, offering a promising tool for accurate UA quantification in complex biological matrices.

Inhibitory peptides derived from Hepatitis C virus NS5A for reducing clinical symptoms of dengue virus infection

Lethal Dengue Hemorrhagic Fever (DHF) and Dengue Shock Syndrome (DSS) caused by Dengue virus (DENV) infection necessitate the development of effective treatments. Peptides derived from the N-terminal amphipathic α-helix of hepatitis C virus (HCV) NS5A exhibit antiviral activity by disrupting liposomes with high curvatures, such as virus envelopes. This study engineered five peptides from HCV genotype 3a NS5A N-terminal α-helix and screened them for neutralizing efficacy against three DENV serotypes. Two peptides, 3a 3/20 and DS-05, showed superior therapeutic efficacy against DENV and were further evaluated in treating DHF/DSS induced by mouse-adapted DENV infection. Administration of 3a 3/20 and DS-05 post-infection significantly improved mortality and weight loss associated with DHF/DSS in AG6 mice. These peptides reduced viral load in internal organs and viremia to levels comparable with the positive control drug, JNJ-A07, a DENV NS3-NS4B inhibitor. Additionally, they attenuated the cytokine storm in the blood and expression of inflammatory cytokines in internal organ tissues, ameliorating liver and kidney dysfunction after DENV infection. Histopathological analysis revealed significant suppression of damages in internal organs. These findings suggest that the 3a 3/20 and DS-05 peptides improve clinical symptoms of DHF/DSS induced by DENV infection, indicating their potential for clinical application.

Space-Confined Amplification for In Situ Imaging of Single Nucleic Acid and Single Pathogen on Biological Samples.

Direct in situ imaging of nucleic acids on biological samples is advantageous for rapid analysis without DNA extraction. However, traditional nucleic acid amplification in aqueous solutions tends to lose spatial information because of the high mobility of molecules. Similar to a cellular matrix, hydrogels with biomimetic 3D nanoconfined spaces can limit the free diffusion of nucleic acids, thereby allowing for ultrafast in situ enzymatic reactions. In this study, hydrogel-based in situ space-confined interfacial amplification (iSCIA) is developed for direct imaging of single nucleic acid and single pathogen on biological samples without formaldehyde fixation. With a polyethylene glycol hydrogel coating, nucleic acids on the sample are nanoconfined with restricted movement, while in situ amplification can be successfully performed. As a result, the nucleic acids are lighted-up on the large-scale surface in 20min, with a detection limit as low as 1 copy/10 cm2. Multiplex imaging with a deep learning model is also established to automatically analyze multiple targets. Furthermore, the iSCIA imaging of pathogens on plant leaves and food is successfully used to monitor plant health and food safety. The proposed technique, a rapid and flexible system for in situ imaging, has great potential for food, environmental, and clinical applications.

Tailoring silk-based covering material with matched mechanical properties for vascular tissue engineering

Vascular covered stents play a significant therapeutic role in cardiovascular diseases. However, the poor compliance and biological inertness of commercial materials cause post-implantation complications. Silk fibroin (SF), as a biomaterial, possesses satisfactory hemocompatibility and tissue compatibility. In this study, we developed a silk film for use in covered stents by employing a layer-by-layer self-assembly strategy with regenerated SF on silk braiding fabric. We investigated the effects on the mechanical properties of the silk films in detail, which were closely correlated with fabric parameters and layer-by-layer self-assembly. The results showed that there was a significant relationship between these factors and both the compliance and mechanical strength. The 1 × 2/90°/100/SF6 film exhibited excellent mechanical properties. Notably, compliance reached 2.6%/100 mmHg, matching that of the human saphenous vein. Thus, this strategy shows promise in developing a novel covered stent, with biocompatible and comprehensive mechanical properties, and significant potential for clinical applications.

Diagnostic Value of Targeted Next-generation Sequencing in Pulmonary Mycobacterial Infections.

This study aimed to explore the diagnostic value of novel technique-targeted next-generation sequencing (tNGS) of bronchoalveolar lavage fluid (BALF) in pulmonary mycobacterial infections. This retrospective study was conducted on patients who underwent bronchoscopy and tNGS, smear microscopy, and mycobacterial culture of BALF. Patients with positive Mycobacterium tuberculosis (MTB) culture or GeneXpert results were classified into the tuberculosis case group. Those diagnosed with nontuberculous mycobacteria (NTM)-pulmonary disease (NTM-PD) composed the case group of NTM-PD patients. The control group comprised patients without tuberculosis or NTM-PD. Sensitivity, specificity, and receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance. For tuberculosis patients with positive mycobacterial culture results, the areas under the ROC curves (AUCs) for tNGS, GeneXpert, and smear microscopy were 0.975 (95% CI: 0.935, 1.000), 0.925 (95% CI: 0.859, 0.991), and 0.675 (95% CI: 0.563, 0.787), respectively. For tuberculosis patients with positive GeneXpert results, the AUCs of tNGS, culture, and smear microscopy were 0.970 (95% CI: 0.931, 1.000), 0.850 (95% CI: 0.770, 0.930), and 0.680 (95% CI: 0.579, 0.781), respectively. For NTM-PD, the AUCs of tNGS, culture, and smear-positive but GeneXpert-negative results were 0.987 (95% CI: 0.967, 1.000), 0.750 (95% CI: 0.622, 0.878), and 0.615 (95% CI: 0.479, 0.752), respectively. The sensitivity and specificity of tNGS in NTM-PD patients were 100% and 97.5%, respectively. tNGS demonstrated superior diagnostic efficacy in mycobacterial infection, indicating its potential for clinical application.

Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal amplification and flow cytometry

The detection of cancer-associated nucleic acids and mutations through liquid biopsy has emerged as a highly promising non-invasive approach for early cancer detection and monitoring. In this study, we report the development of primer exchange reaction (PER) based signal amplification strategy that enables the rapid, sensitive and specific detection of nucleic acids bearing cancer specific single nucleotide mutations using flow cytometry. Using micrometer size beads as support for immobilizing oligonucleotides and programmable PER assembly for target oligonucleotide recognition and fluorescence signal amplification, we demonstrated the versatile detection of target nucleic acids including KRAS oligonucleotide, fragmented mRNAs, and miR-21. Moreover, our detection system can discriminate single base mutations frequently occurred in cancer-associated genes including KRAS, PIK3CA and P53 from cell extracts and circulating tumor DNAs (ctDNAs). The detection is highly sensitive, with a limit of detection down to 27 fM without pre-amplification. In view of a clinical application, we demonstrate the detection of single mutations after extraction and pre-amplification of ctDNAs from the plasma of breast cancer patients. Importantly, our detection strategy enabled the detection of single KRAS mutation even in the presence of 1000-fold excess of wild type (WT) DNA using multi-color flow cytometry detection approach. Overall, our strategy holds immense potential for clinical applications, offering significant improvements for early cancer detection and monitoring.

Current research status and clinical applications of noninvasive preimplantation genetic testing: A review.

Noninvasive preimplantation genetic testing (ni-PGT) is conducted by obtaining genetic information from embryos through the analysis of free DNA released by embryos in spent embryo culture medium or blastocoel fluid. Compared to conventional preimplantation genetic testing relying on trophectoderm biopsy, ni-PGT is characterized by its noninvasiveness. It has demonstrated early advancements in the detection of embryonic chromosomal aneuploidies and the diagnosis of monogenic diseases, showcasing considerable potential for clinical application. However, there are substantial controversies in the literature concerning the reliability of ni-PGT, the source of cell-free DNA, and maternal contamination. This paper elaborates on the principles, research advancements, effectiveness, and limitations of ni-PGT to provide a basis for clinical applications.

Discogenic Low Back Pain: Anatomic and Pathophysiologic Characterization, Clinical Evaluation, Biomarkers, AI, and Treatment Options.

Discogenic low back pain (LBP) is a significant clinical condition arising from degeneration of the intervertebral disc, a common yet complex cause of chronic pain, defined by fissuring in the annulus fibrosus resulting in vascularization of growing granulation tissue and growth of nociceptive nerve fibers along the laceration area. This paper delves into the anatomical and pathophysiological underpinnings of discogenic LBP, emphasizing the role of intervertebral disc degeneration in the onset of pain. The pathogenesis is multifactorial, involving processes like mitochondrial dysfunction, accumulation of advanced glycation end products, and pyroptosis, all contributing to disc degeneration and subsequent pain. Despite its prevalence, diagnosing discogenic LBP is challenging due to the overlapping symptoms with other forms of LBP and the absence of definitive diagnostic criteria. Current diagnostic approaches include clinical evaluations, imaging techniques, and the exploration of potential biomarkers. Treatment strategies range from conservative management, such as physical therapy and pharmacological interventions, to more invasive procedures such as spinal injections and surgery. Emerging therapies targeting molecular pathways involved in disc degeneration are under investigation and hold potential for future clinical application. This paper highlights the necessity of a multidisciplinary approach combining clinical, imaging, and molecular data to enhance the accuracy of diagnosis and the effectiveness of treatment for discogenic LBP, ultimately aiming to improve patient outcomes.