Multi-input mutual supervision network for single-pixel computational imaging.

In this study, we propose a single-pixel computational imaging method based on a multi-input mutual supervision network (MIMSN). We input one-dimensional (1D) light intensity signals and two-dimensional (2D) random image signal into MIMSN, enabling the network to learn the correlation between the two signals and achieve information complementarity. The 2D signal provides spatial information to the reconstruction process, reducing the uncertainty of the reconstructed image. The mutual supervision of the reconstruction results for these two signals brings the reconstruction objective closer to the ground truth image. The 2D images generated by the MIMSN can be used as inputs for subsequent iterations, continuously merging prior information to ensure high-quality imaging at low sampling rates. The reconstruction network does not require pretraining, and 1D signals collected by a single-pixel detector serve as labels for the network, enabling high-quality image reconstruction in unfamiliar environments. Especially in scattering environments, it holds significant potential for applications.

Discovery of extracellular vesicle-delivered miR-185-5p in the plasma of patients as an indicator for advanced adenoma and colorectal cancer.

BACKGROUND: We aimed to evaluate whether extracellular vesicles (EV)-derived microRNAs (miRNAs) can be used as biomarkers for advanced adenoma (AA) and colorectal cancer (CRC). METHODS: We detected the changes in the plasma EV-delivered miRNA profiles in healthy donor (HD), AA patient, and I-II stage CRC patient groups using miRNA deep sequencing assay. We performed the TaqMan miRNA assay using 173 plasma samples (two independent cohorts) from HDs, AA patients, and CRC patients to identify the candidate miRNA(s). The accuracy of candidate miRNA(s) in diagnosing AA and CRC was determined using the area under the receiver-operating characteristic curve (AUC) values. Logistic regression analysis was performed to evaluate the association of candidate miRNA(s) as an independent factor for the diagnosis of AA and CRC. The role of candidate miRNA(s) in the malignant progression of CRC was explored using functional assays. RESULTS: We screened and identified four prospective EV-delivered miRNAs, including miR-185-5p, which were significantly upregulated or downregulated in AA vs. HD and CRC vs. AA groups. In two independent cohorts, miR-185-5p was the best potential biomarker with the AUCs of 0.737 (Cohort I) and 0.720 (Cohort II) for AA vs. HD diagnosis, 0.887 (Cohort I) and 0.803 (Cohort II) for CRC vs. HD diagnosis, and 0.700 (Cohort I) and 0.631 (Cohort II) for CRC vs. AA diagnosis. Finally, we demonstrated that the upregulated expression of miR-185-5p promoted the malignant progression of CRC. CONCLUSION: EV-delivered miR-185-5p in the plasma of patients is a promising diagnostic biomarker for colorectal AA and CRC. Trial registration The study protocol was approved by the Ethics Committee of Changzheng Hospital, Naval Medical University, China (Ethics No. 2022SL005, Registration No. of China Clinical Trial Registration Center: ChiCTR220061592).

Phenylethanoid Glycosides from Caryopteris aureoglandulosa and Their Biological Activities.

This study describes the isolation and identification of two novel phenylethanoid glycosides, aureoglanduloside A (1) and aureoglanduloside B (2), as well as a newly discovered diterpene glycoside, aureoglanduloside C (29). Additionally, 31 known compounds were isolated from the n-butyl alcohol (BuOH) soluble fraction of Caryopteris aureoglandulosa whole dried plants. Their structures were characterized using various spectroscopic techniques and high-resolution electrospray ionization mass spectroscopy (HR-ESI-MS). Furthermore, the neuroprotective effects of all phenylethanoid glycosides were evaluated. Specifically, compounds 2 and 10-12 exhibited the ability to promote the phagocytosis of myelin by microglia, and compounds 2, 10-11, and 24 showed the ability to promote the phagocytosis of myelin by astrocytes.

A joint method to assess pollution status and source-specific human health risks of potential toxic elements in soils.

Potential toxic elements (PTEs) in soils follow various exposure pathways (e.g., ingestion, dermal contact, and inhalation) when migrating to the human body, and can threaten human health. The objective of this study was to quantitatively evaluate the pollution status and human health risk for different age groups (i.e., children and adults) caused by source-specific PTEs in the soil. A total of 425 topsoil samples (0-20 cm) were collected in the Zhangqiu District of China, and contents of eight PTEs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) were analyzed simultaneously. The PTE sources were identified using a geostatistical method, and positive matrix factorization was used to apportion the contribution rate of each PTE source for human health risk of different age groups based on a health risk assessment model. Results showed that: (1) As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn contents all exceeded the background values in soil, indicating that there had been a slight enrichment of soil PTEs over time; (2) Cr and Ni were derived from natural sources, while Cd, Cu, and Zn were derived from transportation sources; industrial emissions and coal burning intensified pollution from Hg, Pb, and As in soils, as shown in the average contribution percentages of natural sources (24.36%), transportation sources (33.79%), and industrial sources (41.85%); (3) the non-carcinogenic risk caused by soil PTEs did not endanger human health, but the carcinogenic risk was close to the risk threshold, and should be given attention; the largest carcinogenic risk (36.53%) and non-carcinogenic risk (36.01%) for children were attributed to industrial sources, while the largest carcinogenic risk (34.98%) and non-carcinogenic risk (37.06%) for adults were attributed to transportation sources. The results presented in this study provide support for effectively preventing PTE health risks in different age groups from source-specific PTE pollution of the soil.

CiteSpace-Based Visualization Analysis of Forensic Research in China from 2010 to 2019.

OBJECTIVES: To analyze the research status of forensic medicine in China from 2010 to 2019, obtain the development trend of forensic medicine and explore the hotspots and research frontiers. METHODS: The forensic medical academic papers published on China National Knowledge Infrastructure (CNKI) database from 2010 to 2019 were collected. CiteSpace 5.7.R1, an information visualization analysis software, was used to analyze publication organizations, authors, keywords, and other elements. RESULTS: The majority of the research institutions were universities, provincial and ministerial scientific research and forensic institutions. Forensic pathology was still an important branch of forensic medicine and a popular research direction. The "polymorphism" and "Y chromosome" had been the research hotspots in recent years. "Medical damage" and "standard" were the most novel studies. CONCLUSIONS: In order to provide scientific basis and research direction for forensic research, this paper analyzes the cooperation network, research hotspots and research innovation in forensic research.

Alteration of (Frequency-Dependent) Fitness in Time-Shift Experiments Reveals Cryptic Coevolution and Uncoordinated Stasis in a Virtual Jurassic Park.

Among the major unresolved questions in ecosystem evolution are whether coevolving multispecies communities are dominated more by biotic or by abiotic factors, and whether evolutionary stasis affects performance as well as ecological profile; these issues remain difficult to address experimentally. Digital evolution, a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve, is an excellent platform for investigating such topics in a rigorous experimental manner. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths (Strong and Weak), along with unperturbed Control experiments. We performed several kinds of competition experiments using simplified versions of these communities to see whether long-term stability that was implied previously by ecological and phylogenetic metrics was also reflected in performance, namely, whether fitness was static over long periods of time. Results from Control and Weak treatment communities revealed almost completely transitive evolution, while Strong treatment communities showed higher incidences of temporal intransitivity, with pre-treatment ecotypes often able to displace some of their post-recovery successors. However, pre-treatment carryovers more often had lower fitness in mixed communities than in their own fully native conditions. Replacement and invasion experiments pitting single ecotypes against pre-treatment reference communities showed that many of the invading ecotypes could measurably alter the fitnesses of one or more residents, usually with depressive effects, and that the strength of these effects increased over time even in the most stable communities. However, invaders taken from Strong treatment communities often had little or no effect on resident performance. While we detected periods of time when the fitness of a particular evolving ecotype remained static, this stasis was not permanent and never affected an entire community at once. Our results lend support to the fitness-deterioration interpretation of the Red Queen hypothesis, and highlight community context dependence in determining fitness, the shaping of communities by both biotic factors and abiotic forcing, and the illusory nature of evolutionary stasis. Our results also demonstrate the potential of digital evolution studies to illuminate many aspects of evolution in interacting multispecies communities.

Examining Community Stability in the Face of Mass Extinction in Communities of Digital Organisms.

Digital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent platform for addressing topics in long-term evolution and paleobiology, such as mass extinction and recovery, with experimental evolutionary approaches. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths, along with unperturbed control experiments. We examined how stability in the digital communities was affected from the perspectives of division of labor, relative shift in rank abundance, and genealogical connectedness of the community's component ecotypes. Mass extinction that was due to a Strong Press treatment was most effective in producing reshaped communities that differed from the pre-treatment ones in all of the measured perspectives; weaker versions of the treatments did not generally produce significant departures from a Control treatment; and results for the Strong Pulse treatment generally fell between those extremes. The Strong Pulse treatment differed from others in that it produced a slight but detectable shift towards more generalized communities. Compared to Press treatments, Pulse treatments also showed a greater contribution from re-evolved ecological doppelgangers rather than new ecotypes. However, relatively few Control communities showed stability in any of these metrics over the whole course of the experiment, and most did not represent stable states (by some measure of stability) that were disrupted by the extinction treatments. Our results have interesting, broad qualitative parallels with findings from the paleontological record, and show the potential of digital evolution studies to illuminate many aspects of mass extinction and recovery by addressing them in a truly experimental manner.

Treatment of cerebrospinal fluid leak after spine surgery.

Owing to the complexity of spinal surgery, there is a great prevalence of dural tear causing cerebrospinal fluid (CSF) leakage. Many studies focused on suture repair for dural tear to stop CSF leak. Now some new treatment strategies have shown a promising effect that is listed as follows: 1) creating watertight dural closure to stop CSF leak with the help of dural substitute material; and 2) retarding CSF leak by changing pressure difference, including reducing the subarachnoid fluid pressure, increasing the epidural space pressure and both. In fact several methods mentioned above are usually combined to treat CSF leak. However, no update review summarized the relevant studies implemented in recent years. In this review, the authors would compare the effects of different dural closure techniques, and introduce the latest treatment methods and mechanisms.

Pediatric massage therapy for treatment of tic disorders in children: A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Tic disorder is a common neurodevelopmental disorder in childhood, characterized primarily by motor or vocal tics. However, there is no systematic evaluation of pediatric massage therapy for children with Tic disorder. This study aims to evaluate the effectiveness and safety of massage therapy for children with tic disorder through a comprehensive meta-analysis and systematic review. METHODS: We systematically searched relevant randomized controlled trials from various databases such as CBM, CNKI, VIP, Wanfang database, PubMed, Embase, Web of Science, Cochrane Library, and SINOMED, published up to October 2023. To collect randomized controlled trials on pediatric massage therapy or in combination with other therapies for the treatment of tic disorders in children. The risk of bias in the included articles was assessed using the Cochrane guideline. Meta-analyses were performed using Review Manager 5.4, and publication bias was evaluated by using Begg test and Egger test in Stata SE software. RESULTS: This meta-analysis included 19 randomized controlled trials with 1423 patients. Pediatric massage therapy alone or in combination with conventional medication demonstrated a significant increase in clinical effectiveness rates [risk ratios = 1.15, 95% confidence interval [CI] (1.10, 1.20), Z = 6.54, P < .001], and reduced Yale Global Tie Severity Scale scores [standardized mean difference = -0.85, 95% CI (-1.50, -0.19), Z = 2.54, P = .01] and traditional Chinese medicine syndrome scores [standardized mean difference = -1.35, 95%CI (-2.08, -0.63), Z = 3.66, P = .0002]. In terms of adverse reactions, there was no statistical difference between the experimental and control groups [risk ratios = 0.26, 95% CI (0.14, 0.49), Z = 4.25, P < .001]. The Begg test and Egger test results indicated no publication bias. CONCLUSION: Evidence suggests that pediatric massage therapy is effective in improving tic disorders in children.

Applying machine-learning models to differentiate benign and malignant thyroid nodules classified as C-TIRADS 4 based on 2D-ultrasound combined with five contrast-enhanced ultrasound key frames.

Objectives: To apply machine learning to extract radiomics features from thyroid two-dimensional ultrasound (2D-US) combined with contrast-enhanced ultrasound (CEUS) images to classify and predict benign and malignant thyroid nodules, classified according to the Chinese version of the thyroid imaging reporting and data system (C-TIRADS) as category 4. Materials and methods: This retrospective study included 313 pathologically diagnosed thyroid nodules (203 malignant and 110 benign). Two 2D-US images and five CEUS key frames ("2nd second after the arrival time" frame, "time to peak" frame, "2nd second after peak" frame, "first-flash" frame, and "second-flash" frame) were selected to manually label the region of interest using the "Labelme" tool. A total of 7 images of each nodule and their annotates were imported into the Darwin Research Platform for radiomics analysis. The datasets were randomly split into training and test cohorts in a 9:1 ratio. Six classifiers, namely, support vector machine, logistic regression, decision tree, random forest (RF), gradient boosting decision tree and extreme gradient boosting, were used to construct and test the models. Performance was evaluated using a receiver operating characteristic curve analysis. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy (ACC), and F1-score were calculated. One junior radiologist and one senior radiologist reviewed the 2D-US image and CEUS videos of each nodule and made a diagnosis. We then compared their AUC and ACC with those of our best model. Results: The AUC of the diagnosis of US, CEUS and US combined CEUS by junior radiologist and senior radiologist were 0.755, 0.750, 0.784, 0.800, 0.873, 0.890, respectively. The RF classifier performed better than the other five, with an AUC of 1 for the training cohort and 0.94 (95% confidence interval 0.88-1) for the test cohort. The sensitivity, specificity, accuracy, PPV, NPV, and F1-score of the RF model in the test cohort were 0.82, 0.93, 0.90, 0.85, 0.92, and 0.84, respectively. The RF model with 2D-US combined with CEUS key frames achieved equivalent performance as the senior radiologist (AUC: 0.94 vs. 0.92, P = 0.798; ACC: 0.90 vs. 0.92) and outperformed the junior radiologist (AUC: 0.94 vs. 0.80, P = 0.039, ACC: 0.90 vs. 0.81) in the test cohort. Conclusions: Our model, based on 2D-US and CEUS key frames radiomics features, had good diagnostic efficacy for thyroid nodules, which are classified as C-TIRADS 4. It shows promising potential in assisting less experienced junior radiologists.

DIAS: A dataset and benchmark for intracranial artery segmentation in DSA sequences.

The automated segmentation of Intracranial Arteries (IA) in Digital Subtraction Angiography (DSA) plays a crucial role in the quantification of vascular morphology, significantly contributing to computer-assisted stroke research and clinical practice. Current research primarily focuses on the segmentation of single-frame DSA using proprietary datasets. However, these methods face challenges due to the inherent limitation of single-frame DSA, which only partially displays vascular contrast, thereby hindering accurate vascular structure representation. In this work, we introduce DIAS, a dataset specifically developed for IA segmentation in DSA sequences. We establish a comprehensive benchmark for evaluating DIAS, covering full, weak, and semi-supervised segmentation methods. Specifically, we propose the vessel sequence segmentation network, in which the sequence feature extraction module effectively captures spatiotemporal representations of intravascular contrast, achieving intracranial artery segmentation in 2D+Time DSA sequences. For weakly-supervised IA segmentation, we propose a novel scribble learning-based image segmentation framework, which, under the guidance of scribble labels, employs cross pseudo-supervision and consistency regularization to improve the performance of the segmentation network. Furthermore, we introduce the random patch-based self-training framework, aimed at alleviating the performance constraints encountered in IA segmentation due to the limited availability of annotated DSA data. Our extensive experiments on the DIAS dataset demonstrate the effectiveness of these methods as potential baselines for future research and clinical applications. The dataset and code are publicly available at https://doi.org/10.5281/zenodo.11401368 and https://github.com/lseventeen/DIAS.

Amidine-based fluorescent chemosensor with high applicability for detection of CO2: a facile way to "see" CO2.

An amidine-based fluorescent chemosensor has been prepared and is sensitive to the viscosity increase of ionic liquid formed during a specialized reaction of amidine groups with CO(2), which provides a facile and visible way to detect and sense CO(2). It has been found that the greener fluorescent chemosensor has unique sensitivity to CO(2), extraordinarily high water-resistance and no problem of carbon monoxide-interfering.

Changes in ATP levels in rabbit blood and its application for estimation of the postmortem interval.

Relationship between ATP changes of rabbit blood and postmortem interval (PMI) was studied. Twenty-four healthy rabbits were sacrificed and randomly divided into 3 groups with 8 rabbits of each group. The bodies of three groups were placed in calorstat at temperature of 15°C, 25°C and 35°C, respectively. The blood from the right ventricle was sampled through indwelling needle each 4 h until 72 h after death. ATP levels in the blood samples were measured by using ATP fluorescence rapid detection technique at different PMIs. Blood ATP levels slightly increased in the early stage after death and then constantly declined at all temperatures (15°C, 25°C, and 35°C). Cubic polynomial regression equations with log[ATP] as dependent variable (y) and PMI as independent variable (x) at different temperatures and the optimal time period were established as followed: Under 15°C and during 16-64 h after death, y=-3.027×10(-5)x(3)+0.003x(2)-0.096x-10.625 (R a (2)=0.992, P<0.001); under 25°C and during 8-56 h after death, y=-2.921×10(-5)x(3)+0.002x(2)-0.059x-11.186 (R a (2)=0.989, P<0.001); under 35dgC and during 4-36 h after death, y=-9.769×10(-5)x(3)+ 0.005x(2)-0.117x-11.166 (R a (2)=0.991, P<0.001). The changes in ATP levels in blood collected from right ventricle of rabbit cadavers showed relatively stable and regular degradation within 72 h after death at different temperatures.

[Etiology and treatment of postoperative spinal cord injury for patients undergoing laminectomy for fluorosis thoracic canal stenosis].

OBJECTIVE: To elucidate the etiology of postoperative spinal cord injury (PSCI) for patients undergoing laminectomy for fluorosis thoracic canal stenosis (FTCS) and summarize the methods of diagnosis and treatment. METHODS: From 2006 to 2009, a total of 192 FTCS cases underwent laminectomy. Among them, 16 cases with gradual postoperative neural deterioration were finally diagnosed as PSCI on MRI.One case of intraoperative spinal cord injury was excluded so that only 15 cases were included. RESULTS: All cases were treated immediately with incision cite puncture and dehydration.Neural function recovered after secondary operation as JOA score improved from 3.00 ± 1.14 to 7.72 ± 1.41 at 12 months follow-up.Statistical analysis demonstrated a linear correlation between the diagnosis time and the improvement of JOA score. CONCLUSION: Hematoma and fluid leakage are the common reasons of PSCI for FTCS patients. Meticulous hemostasis, usage of artificial dura matter and partial negative pressure drainage are valuable preventive measures.

[Correlation between the changes of oxidation reduction potential values and postmortem interval of heart blood in rabbits after death].

OBJECTIVE: To investigate correlation between the changes of oxidation reduction potential (ORP) values of heart blood in rabbits after death and postmortem interval (PMI) at different temperatures. METHODS: Forty-eight rabbits were randomly divided into 6 groups and sacrificed by air embolism. Blood samples were taken from the right ventricle of each rabbit and stored at different temperatures of 10, 15, 20, 25, 30 and 35 degrees C, respectively. Every 4 hours from 0 h to 132 h postmortem, the ORP values of the blood samples were measured at different intervals by PB-21 electrochemical analyzer. The curvilinear regression equation was established by SPSS 17.0 software. The surface equation and 3D surface diagram were established by MATLAB 7.10.0 software. RESULTS: The ORP values at different temperatures of heart blood in rabbits were highly correlated with the PMI. The ORP values rised obviously when the temperature was high and rised slowly when the temperature was low. The surface equation and 3D surface diagram were obtained. CONCLUSION: The surface equation and 3D surface diagram of ORP values and PMI may be used for PMI estimation at different temperatures.

Chemical constituents from aerial parts of Scoparia dulcis.

Objective: To study the chemical constituents from the aerial parts of Scoparia dulcis. Methods: Various chromatographic techniques were used to separate the constituents and their structures were elucidated using spectroscopic methods and by comparing their data to those reported in the literatures. The α-glucosidase inhibitory activity assay was used to identify potential α-glucosidase inhibitors. Results: Nine compounds were isolated from the aerial parts of S. dulcis. Their structures were identified as Scoparic zolone (1), (2S)-2,7-dihydroxy-2H-1,4-benzoxazin-3(4H)-one (2), (2R)-7-hydroxy-2H-1,4-benzoxazin-3(4H)-one-2-O-ß-d-glucopyranoside (3), (2R)-7-methoxy-2H-1,4-benzoxazin-3(4H)-one-2-O-ß-d-glucopyranoside (4), (2S)-7-hydroxy-2H-1,4-benzoxazin-3(4H)-one-2-O-ß-d-glucopyranoside (5), 6-methoxy-benzoxazolin-2(3H)-one (6), 4-acetonyl-3,5-dimethoxy-p-quinol (7), zizyvoside I (8), and 3,4-dihydroxy benzeneacetic acid (9). Compound 2 showed the potent α-glucosidase inhibitory activity with an IC50 value of (132.8 ± 11.5) µmol/L, which is 28-fold higher than the positive control acarbose. Conclusion: Compound 1 is a new natural product. Compounds 2 and 9 have not been reported in Scoparia before. Compounds 3, 5, 7, 8 are isolated from Scrophulariaceae for the first time.

Brachial plexus avulsion induced changes in gut microbiota promotes pain related anxiety-like behavior in mice.

Introduction: Brachial plexus avulsion (BPA) injury develops frequent and intense neuropathic pain, involving in both peripheral and central nervous systems. The incidence of anxiety or depression caused by BPA-induced neuropathic pain is high, but the underlying mechanism remains unclear. Methods: We established a BPA mice model and assessed its negative emotions through behavioral tests. To further explore the role of the microbiota-gut-brain axis in the unique emotional behavior after BPA, we performed intestinal fecal 16s and metabolomics assays. Psychobiotics (PB) supplementation was administered to BPA mice to check the probiotics effects on BPA-induced anxiety behaviors. Results: Pain related anxiety-like behavior was observed at the early stage after BPA (7 days), while no depression-like behavior was detected. Intriguingly, gut microbiota diversity was increased in BPA mice, and the most abundant probiotics, Lactobacillus, showed obvious changes. Lactobacillus_reuteri was significantly decreased in BPA mice. Metabolomics analysis showed that Lactobacillus_reuteri-related bile acid pathway and some neurotransmitter amino acids were significantly altered. Further PB (dominated by Lactobacillus_reuteri) supplementation could significantly relieve BPA-induced anxiety-like behaviors in mice. Conclusion: Our study suggests that pathological neuralgia after BPA could alter intestinal microbiota diversity, especially Lactobacillus, and the changes in neurotransmitter amino acid metabolites may be the key reason for the onset of anxiety-like behaviors in BPA mice.

Case report: A rare case of massive peripheral nerve melanotic schwannoma and review of the literature.

Melanotic schwannoma is a rare tumor with indeterminate biologic behavior and varying treatment recommendations. Just about 200 cases have been reported worldwide, in which occurred in peripheral nerves has even less reported. Due to the lack of cognition of melanotic schwannoma, it is easy to be misdiagnosed and mistreatment in primary hospitals. Herein, we presented a case of massive melanotic schwannoma growing in the brachial plexus of an elderly male patient. First, the patient underwent a left forearm tumor resection in the local primary hospital because a painless lump was found there in 2017, of which details remain unclear. After this operation, the patient developed the symptoms of left median nerve injury. Thus, he came to our hospital and underwent a second operation. During this operation, we found that a part of the median nerve was absent at the left forearm, and the remanent median nerve, from the broken end to the elbow, was totally turned black, which was accompanied by petroleum-like exudate. Losing the opportunity for nerve repair, the black nerve was removed extensively and thoroughly. Postoperative pathological diagnosis revealed that the tumor was melanotic schwannoma. Then 4 years later, the tumor recurrence again, which led to the paralysis of the whole left arm and severe nerve pain, and the pulmonary metastasis of the tumor was detected at the same time. The black nerve was resected again in our hospital, and the nerve pain was partially relieved after the operation. To the best of our knowledge, it is the first time to report a melanotic schwannoma case that happened in the peripheral nerve trunk and then spread to the whole brachial plexus. There were many questions that worthy of discussion could be invited from this case, and we analyzed and discussed them based on the relevant literature. In conclusion, we reported a rare case of melanotic schwannoma that happened in the brachial plexus and illustrated the problems of the diagnosis and treatment of it based on the analysis of the relevant literature, which is helpful for the cognition of this rare nerve tumor.

Chitosan-assisted synthesis of 1D g-C3N4 nanorods for enhanced photocatalysis.

1D porous g-C3N4 nanorods were synthesized using chitosan as a template, offering a large surface area and enhanced visible light absorption. These nanorods exhibited a remarkable 8.3-fold increase in H2 generation rate (26.6 µmol h-1) compared to bulk g-C3N4.

A review on guided-ultrasonic-wave-based structural health monitoring: From fundamental theory to machine learning techniques.

The development of structural health monitoring (SHM) techniques is of great importance to improve the structural efficiency and safety. With advantages of long propagation distances, high damage sensitivity, and economic feasibility, guided-ultrasonic-wave-based SHM is recognized as one of the most promising technologies for large-scale engineering structures. However, the propagation characteristics of guided ultrasonic waves in in-service engineering structures are highly complex, which results in difficulties in developing precise and efficient signal feature mining methods. The damage identification efficiency and reliability of existing guided ultrasonic wave methods cannot meet engineering requirements. With the development of machine learning (ML), numerous researchers have proposed improved ML methods that can be incorporated into guided ultrasonic wave diagnostic techniques for SHM of actual engineering structures. To highlight their contributions, this paper provides a state-of-the-art overview of the guided-wave-based SHM techniques enabled by ML methods. Accordingly, multiple stages required for ML-based guided ultrasonic wave techniques are discussed, including guided ultrasonic wave propagation modeling, guided ultrasonic wave data acquisition, wave signal pre-processing, guided wave data-based ML modeling, and physics-based ML modeling. By placing ML methods in the context of the guided-wave-based SHM for actual engineering structures, this paper also provides insights into future prospects and research strategies.