Efficacy and safety of cortical bone trajectory screws versus pedicle screws in lumbar fusion: a systematic review and meta-analysis.

OBJECTIVE: A systematic review and meta-analysis was conducted to compare the efficacy and safety of cortical bone trajectory screws and traditional pedicle screws in lumbar fusion. METHODS: Randomized controlled studies and cohort studies on CBT versus pedicle screws in lumbar fusion were searched in CBM, CNKI, Wanfang, VIP, PubMed, Cochrane Library and Web of Science databases. The search period spanned from the establishment of the databases to December 2023. The Cochrane bias risk assessment tool and Newcastle-Ottawa scale were applied to assess the quality of the literature included. Clinical and imaging data as well as surgical outcomes, recovery and postoperative complications were extracted from the relevant literature. RESULTS: A total of 6 randomized controlled trials and 26 cohort studies were included after screening by inclusion and exclusion criteria with a total of 2478 patients. The meta-analysis demonstrated significant discrepancies between the CBT and TPS groups in JOA score at 3 and 6 months, and final follow-up. Moreover, the TPS group exhibited a higher ODI at final follow-up, a greater VAS for low back pain at both 1 week and final follow-up, as well as a higher VAS for leg pain at 1 month. Differences were also noted in surgical and recovery outcomes. However, there was no significant difference between the two groups in postoperative complications. CONCLUSIONS: CBT and TPS have analogous safety profiles when applied to lumbar fusion, but the clinical efficacy of CBT is superior to that of TPS to some extent, and the procedure is less invasive with faster recovery.

Labelling with dynamics: A data-efficient learning paradigm for medical image segmentation.

The success of deep learning on image classification and recognition tasks has led to new applications in diverse contexts, including the field of medical imaging. However, two properties of deep neural networks (DNNs) may limit their future use in medical applications. The first is that DNNs require a large amount of labeled training data, and the second is that the deep learning-based models lack interpretability. In this paper, we propose and investigate a data-efficient framework for the task of general medical image segmentation. We address the two aforementioned challenges by introducing domain knowledge in the form of a strong prior into a deep learning framework. This prior is expressed by a customized dynamical system. We performed experiments on two different datasets, namely JSRT and ISIC2016 (heart and lungs segmentation on chest X-ray images and skin lesion segmentation on dermoscopy images). We have achieved competitive results using the same amount of training data compared to the state-of-the-art methods. More importantly, we demonstrate that our framework is extremely data-efficient, and it can achieve reliable results using extremely limited training data. Furthermore, the proposed method is rotationally invariant and insensitive to initialization.

Prognostic implications of STK11 with different mutation status and its relationship with tumor-infiltrating immune cells in non-small cell lung cancer.

Background: Mutations in STK11 (STK11Mut) gene may present a negative impact on survival in Non-small Cell Lung Cancer (NSCLC) patients, however, its relationship with immune related genes remains unclear. This study is to unveil whether overexpressed- and mutated-STK11 impact survival in NSCLC and to explore whether immune related genes (IRGs) are involved in STK11 mutations. Methods: 188 NSCLC patients with intact formalin-fixed paraffin-embedded (FFPE) tissue available for detecting STK11 protein expression were included in the analysis. After immunohistochemical detection of STK11 protein, patients were divided into high STK11 expression group (STK11High) and low STK11 expression group (STK11Low), and then Kaplan-Meier survival analysis and COX proportional hazards model were used to compare the overall survival (OS) and progression-free survival (PFS) of the two groups of patients. In addition, the mutation data from the TCGA database was used to categorize the NSCLC population, namely STK11 Mutated (STK11Mut) and wild-type (STK11Wt) subgroups. The difference in OS between STK11Mut and STK11Wt was compared. Finally, bioinformatics analysis was used to compare the differences in IRGs expression between STK11Mut and STK11Wt populations. Results: The median follow-up time was 51.0 months (range 3.0 - 120.0 months) for real-life cohort. At the end of follow-up, 64.36% (121/188) of patients experienced recurrence or metastasis. 64.89% (122/188) of patients ended up in cancer-related death. High expression of STK11 was a significant protective factor for NSCLC patients, both in terms of PFS [HR=0.42, 95% CI= (0.29-0.61), P<0.001] and OS [HR=0.36, 95% CI= (0.25, 0.53), P<0.001], which was consistent with the finding in TCGA cohorts [HR=0.76, 95%CI= (0.65, 0.88), P<0.001 HR=0.76, 95%CI= (0.65, 0.88), P<0.001]. In TCGA cohort, STK11 mutation was a significant risk factor for NSCLC in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) histology in terms of OS [HR=6.81, 95%CI= (2.16, 21.53), P<0.001; HR=1.50, 95%CI= (1.00, 2.26), P=0.051, respectively]. Furthermore, 7 IRGs, namely CALCA, BMP6, S100P, THPO, CGA, PCSK1 and MUC5AC, were found significantly overexpressed in STK11-mutated NSCLC in both LUSC and LUAD histology. Conclusions: Low STK11 expression at protein level and presence of STK11 mutation were associated with poor prognosis in NSCLC, and mutated STK11 might probably alter the expression IRGs profiling.

Effects of BRD4 inhibitor JQ1 on the expression profile of super-enhancer related lncRNAs and mRNAs in cervical cancer HeLa cells.

Objective: To investigate the effects of bromine domain protein 4 (BRD4) inhibitor JQ1 on the expression profile of super-enhancer-related lncRNAs (SE-lncRNAs) and mRNAs in cervical cancer (CC) HeLa-cells. Methods: The CCK8 method was implemented to detect the inhibitory effect of JQ1 on HeLa cells and explore the best inhibitory concentration. Whole transcriptome sequencing was performed to detect the changes of lncRNAs and mRNAs expression profiles in cells of the JQ1 treatment group and control group, respectively. The differentially expressed SE-lncRNAs were obtained by matching, while the co-expressed mRNAs were obtained by Pearson correlation analysis. Results: The inhibitory effect of JQ1 on HeLa cell proliferation increased significantly with increasing concentration and treatment time (P < 0.05). Under the experimental conditions of three concentrations of 0.01, 0.1 and 1 µmol/L of JQ1 on HeLa cells at 24, 48, 72 and 120 h, 1 µmol/L of JQ1 at 72 and 120 h had the same cell viability and the strongest cell proliferation inhibition. In order to understand the inhibitory mechanism of JQ1 on HeLa cells, this study analyzed the expression profile differences from the perspective of SE-lncRNAs and mRNAs. A total of 162 SE-lncRNAs were identified, of which 8 SE-lncRNAs were down-regulated and seven SE-lncRNAs were up-regulated. A total of 418 differentially expressed mRNAs related to SE-lncRNAs were identified, of which 395 mRNAs had positive correlation with 12 SE-lncRNAs and 408 mRNAs had negative correlation with 15 SE-lncRNAs. Conclusion: JQ1 can significantly inhibit the proliferation of HeLa cells and affect the expression profile of SE-lncRNAs and mRNAs.

Fear of recurrence in postoperative lung cancer patients: Trajectories, influencing factors and impacts on quality of life.

AIMS: To investigate the trajectory, influencing factors and dynamic relationships between fear of cancer recurrence (FCR) and quality of life (QOL) in lung cancer patients. DESIGN: Prospective longitudinal study. METHODS: Longitudinal data from 310 lung cancer patients across three hospitals in China were assessed at 1, 3, 6 and 12 months postoperatively (T1 -T4 ). Descriptive statistics characterised patient demographics, clinical characteristics, levels of FCR and QOL. A linear mixed-effects model was employed to analyse FCR trajectories, identify influencing factors on these trajectories, and predict the impact of FCR on QOL. RESULTS: FCR changed significantly over time, with a slight decrease during T1 -T2 , an increase at T3 and gradual decline at T4 . Higher fear levels were associated with female sex, suburban or rural residency, being a family breadwinner, presence of comorbidities and negative coping behaviours, and low family resilience. QOL negatively correlated with FCR, and FCR predicted lower QOL. CONCLUSIONS: At 3 and 6 months postoperatively, lung cancer patients, especially women, suburban or rural residents, family breadwinners, those with comorbidities, negative coping behaviours and low family resilience, reported high levels of FCR. Healthcare providers should pay special attention to lung cancer patients especially during the period of 3-6 months post-surgery and offer tailored interventions to improve their QOL. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Understanding the FCR trajectories, its influencing factors and its negative impacts on QOL can guide the development of targeted interventions to reduce fear and enhance well-being in patients with cancer. IMPACT: Identifying the trajectories and influencing factors of fear of lung cancer recurrence in patients at different time points informs future research on targeted interventions to improve QOL. REPORTING METHOD: The study adhered to the guidelines outlined in the Statement on Reporting Observational Longitudinal Research.

Residual Aligner-based Network (RAN): Motion-separable structure for coarse-to-fine discontinuous deformable registration.

Deformable image registration, the estimation of the spatial transformation between different images, is an important task in medical imaging. Deep learning techniques have been shown to perform 3D image registration efficiently. However, current registration strategies often only focus on the deformation smoothness, which leads to the ignorance of complicated motion patterns (e.g., separate or sliding motions), especially for the intersection of organs. Thus, the performance when dealing with the discontinuous motions of multiple nearby objects is limited, causing undesired predictive outcomes in clinical usage, such as misidentification and mislocalization of lesions or other abnormalities. Consequently, we proposed a novel registration method to address this issue: a new Motion Separable backbone is exploited to capture the separate motion, with a theoretical analysis of the upper bound of the motions' discontinuity provided. In addition, a novel Residual Aligner module was used to disentangle and refine the predicted motions across the multiple neighboring objects/organs. We evaluate our method, Residual Aligner-based Network (RAN), on abdominal Computed Tomography (CT) scans and it has shown to achieve one of the most accurate unsupervised inter-subject registration for the 9 organs, with the highest-ranked registration of the veins (Dice Similarity Coefficient (%)/Average surface distance (mm): 62%/4.9mm for the vena cava and 34%/7.9mm for the portal and splenic vein), with a smaller model structure and less computation compared to state-of-the-art methods. Furthermore, when applied to lung CT, the RAN achieves comparable results to the best-ranked networks (94%/3.0mm), also with fewer parameters and less computation.

Efficacy and safety of immune checkpoint inhibitors combined with chemotherapy as first-line treatment for extensive-stage small cell lung cancer: a meta-analysis based on mixed-effect models.

Background: Extensive-stage small cell lung cancer (ES-SCLC) is a highly invasive and fatal disease with limited therapeutic options and poor prognosis. Our study aims to systematically evaluate the efficacy and safety of immune checkpoint inhibitors combined with chemotherapy (ICIs+ChT) vs. chemotherapy alone (ChT) in the first-line treatment of ES-SCLC. Methods: A literature search was performed for randomized controlled trials (RCTs) related to "ICIs+ChT" vs. "ChT" in the first-line treatment of ES-SCLC in PubMed, Cochrane Library, Embase, CNKI, and other databases. RevMan 5.4 software was used to perform meta-analyses with hazard ratio (HR) and relative risk (RR). SAS 9.4 software was applied to conduct a mixed-effect model meta-analysis of the survival outcomes and draw survival curves. Results: A total of 2,638 patients with ES-SCLC from 6 RCTs were included, of which 1,341 patients received "ICIs+ChT" and 1,297 received ChT. Based on the meta-analysis results provided by the mixed-effect model, patients receiving the "ICIs+ChT" regimen had a significantly longer overall survival (OS, HR = 0.800, 95% CI = 0.731-0.876, P < 0.001) and progression-free survival (PFS, HR = 0.815, 95% CI = 0.757-0.878, P <0.001) in comparison to those receiving ChT only. Compared with ChT, "ICIs+ChT" did neither improve the objective response rate (ORR, RR = 1.06, 95% CI = 1.00-1.12, P = 0.06) nor did it improve the disease control rate (DCR, RR = 0.97, 95% CI = 0.92-1.03, P = 0.35). Although the incidence of grade 3 to 5 treatment-related adverse events (trAEs) in the "ICIs+ChT" subgroup did not increase (RR = 1.16, 95% CI = 0.97-1.39, P = 0.11), the incidence of grade 3 to 5 immune-related adverse events (irAEs) increased significantly (RR = 4.29, 95% CI = 1.73-10.61, P < 0.00001). Conclusion: ICIs+ChT regimen could significantly prolong OS and PFS in patients with ES-SCLC compared with ChT alone. Although the incidence of irAEs in "ICIs+ChT" is higher than that in the "ChT" subgroup, the incidence of trAEs is similar within the two subgroups. ICIs combined with chemotherapy demonstrated a good choice as first-line treatment for ES-SCLC. Systematic review registration: PROSPERO, identifier: CRD42022348496.

Prediction study of prognostic nutrition index on the quality of life of patients with cervical cancer undergoing radiotherapy and chemotherapy.

Objective: To assess the prognostic nutritional index (PNI) and quality of life (QOL) of patients with cervical cancer (CC) who underwent radiotherapy and chemotherapy and to reveal the effect of PNI on QOL and its prognostic value. Methods: A total of 138 CC patients who underwent radiotherapy and chemotherapy in the Second Affiliated Hospital of Fujian Medical University from January 2020 to October 2022 were selected as the study subjects via convenient sampling. According to the PNI cut-off value of 48.8, they were divided into a high-PNI group and a low-PNI group, and the quality of life of the two groups was compared. The Kaplan-Meier method was used to draw the survival curve, and the Log-Rank test was employed to compare the survival rates of the two groups. Results: The scores of physical functioning and overall QOL in the high-PNI group were significantly higher than those in the low-PNI group (P < 0.05). The scores of fatigue, nausea and vomiting, pain and diarrhea were higher than those in the low-PNI group, and the difference was statistically significant (P < 0.05). The objective response rates were 96.77% and 81.25% in the high-PNI group and the low-PNI group, respectively, and the difference was statistically significant (P = 0.045). The 1-year survival rates of patients with high PNI and low PNI were 92.55% and 72.56% in the high-PNI group and the low-PNI group, respectively; the difference in survival rates was statistically significant (P = 0.006). Conclusion: The overall quality of life of CC patients with low PNI receiving radiotherapy and chemotherapy is lower than that of patients with high PNI. Low PNI reduces the tolerance to radiotherapy and chemotherapy and the objective response rate, which can be used as a prognostic indicator for cervical cancer patients.

Accurate volume alignment of arbitrarily oriented tibiae based on a mutual attention network for osteoarthritis analysis.

Damage to cartilage is an important indicator of osteoarthritis progression, but manual extraction of cartilage morphology is time-consuming and prone to error. To address this, we hypothesize that automatic labeling of cartilage can be achieved through the comparison of contrasted and non-contrasted Computer Tomography (CT). However, this is non-trivial as the pre-clinical volumes are at arbitrary starting poses due to the lack of standardized acquisition protocols. Thus, we propose an annotation-free deep learning method, D-net, for accurate and automatic alignment of pre- and post-contrasted cartilage CT volumes. D-Net is based on a novel mutual attention network structure to capture large-range translation and full-range rotation without the need for a prior pose template. CT volumes of mice tibiae are used for validation, with synthetic transformation for training and tested with real pre- and post-contrasted CT volumes. Analysis of Variance (ANOVA) was used to compare the different network structures. Our proposed method, D-net, achieves a Dice coefficient of 0.87, and significantly outperforms other state-of-the-art deep learning models, in the real-world alignment of 50 pairs of pre- and post-contrasted CT volumes when cascaded as a multi-stage network.

Treatment- and immune-related adverse events of immune checkpoint inhibitors in esophageal or gastroesophageal junction cancer: A network meta-analysis of randomized controlled trials.

Objective: To systematically evaluate the safety and adverse event profiles of immune checkpoint inhibitors (ICIs) in patients with esophageal cancer (EPC) or gastroesophageal junction cancer (GEJC). Methods: PubMed, Web of Science, Cochrane Library, and major conference proceedings were systematically searched for all phase II or phase III randomized controlled trials (RCTs) in EPC or GEJC using ICIs. Safety outcomes including treatment-related adverse events (trAEs), immune-related adverse events (irAEs), and serious trAEs were evaluated by network meta-analysis or dichotomous meta-analysis based on the random-effects model. Results: Eleven RCTs involving EPC (five RCTs) and GEJC (six RCTs) were included in the final meta-analysis. NMA showed that placebo was associated with the best safety ranking for grade 3-5 trAEs (SUCRA = 96.0%), followed by avelumab (78.6%), nivolumab (73.9%), ipilimumab (57.0%), and pembrolizumab (56.6%). Conventional pairwise meta-analysis (CPM) showed that ICIs have similar grade 3-5 trAE risk compared with chemotherapy (RR = 0.764, 95% CI: 0.574 to 1.016, I 2 = 95.7%, Z = 1.85, P = 0.065). NMA showed that the general safety of grade 3-5 irAEs ranked from high to low is as follows: ChT (85.1%), placebo (76.5%), ipilimumab (56.0%), nivolumab (48.5%), avelumab (48.4%), camrelizumab (41.8%), pembrolizumab (36.4%), and nivolumab + ipilimumab (21.6%). CPM showed that the rates of grade 3-5 irAEs in the ICI group and the chemotherapy group were 7.35% (154/2,095, 95% CI: [6.23%, 8.47%]) versus 2.25% (42/1,869, 95% CI: [1.58%, 2.92%]), with statistical significance (RR = 3.151, 95% CI = 2.175 to 4.563, Z = 6.07, P = 0.000). The most common irAEs in the ICI group were skin reaction (15.76%, 95% CI: [13.67%, 17.84%]), followed by hypothyroidism (9.73%, 95% CI: [8.07%, 11.39%]), infusion-related reactions (5.93%, 95% CI: [4.29%, 7.58%]), hepatitis (5.25%, 95% CI: [4.28%, 6.22%]), and pneumonitis (4.45%, 95% CI: [3.5%, 5.4%]). Conclusion: Different ICIs had different toxicity manifestations and should not be considered as an entity. Compared with chemotherapy, ICIs were more prone to irAEs, but the overall rates remained low and acceptable. For clinicians, it is important to recognize and monitor the adverse events caused by ICIs for patients with EPC or GEJC.

A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma.

Background and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to construct a prognostic risk model. Methods: Microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. Based on pathologic responses after chemoradiotherapy, patients were divided into a non-responder (17 samples) and responder group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared therein. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high- and low-risk groups according to prognostic risk scores, and the outcomes were compared within groups based on the COX proportional hazards model. The different expression of ir-lncRNAs were validated using ECA 109 and ECA 109R cell lines via RT-qPCR. Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, six ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which three ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. These three lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into two groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (p < 0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. In the validation setting, three ir-lncRNAs were significantly up-regulated, while two ir-lncRNAs were obviouly down-regulated in the responder group. Conclusion: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by three ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC.

YTHDF2 interference suppresses the EMT of cervical cancer cells and enhances cisplatin chemosensitivity by regulating AXIN1.

M6A reader YTH structural domain family 2 (YTHDF2) has been recognized to play an oncogenic role in numerous tumors, but its role in cervical cancer has not been extensively discussed yet. This paper was designed to explore the role of YTHDF2 in cervical cancer and identify its underlying mechanism. The expression of YTHDF2 was first determined in cervical cancer cells by quantitative reverse-transcription polymerase chain reaction and western blot. Then, the migration, invasion, and epithelial-mesenchymal transition (EMT) process were observed in YTHDF2-knockdown Hela cells using wound healing, transwell and immunofluorescence assays. The cisplatin chemosensitivity of Hela cells was also investigated by assessing cell activity with cell counting kit-8 and TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling). After MeRIP-Seq assay and actinomycin D treatment to confirm the binding relationship between YTHDF2 and AXIN1, the migration, invasion, EMT process, and cisplatin chemosensitivity were assessed again in Hela cells silenced by YTHDF2 and AXIN1 or treated with Wnt agonist. YTHDF2 was increased in cervical cancer cells, and depletion of YTHDF2 led to reduced migration, invasion and EMT process but enhanced chemosensitivity of cisplatin in Hela cells. Furthermore, YTHDF2 could bind to and stabilize the expression of AXIN1. When the YTHDF2-knockdown Hela cells were further transfected with AXIN1 knockdown or treated with Wnt agonist, the effects of YTHDF2 knockdown on the migration, invasion and EMT process were partially abolished, together with reduced cisplatin chemosensitivity. To sum up, we reported that YTHDF2 interference could suppress the EMT of cervical cancer cells and enhance cisplatin chemosensitivity by regulating AXIN1.

[Procedure and teaching verses of supraclavicular subclavian catheterization].

In order to improve the success rate of supraclavicular deep venous catheterization and reduce mechanical complications, we present an auxillary maneuver in regard to supraclavicular subclavian catheterization basing on the relatively fixed anatomy of subclavian vein and its adjacent surroundings, furthermore, we revised the standardized procedure of supraclavicular subclavian catheterization. The maneuver is summarized in the shape of verses (verses: thumb navigation is well designed according to anatomy. Needle penetrated into vein should be parallel to coronal plane. Fine needle in position should be immobilized. Is it difficult for parallel puncture? Pressure determination is required when needle is in place. It is critical to distinguish which vessel has been inserted. Guidewire is advanced smoothly. Check blood return after expansion of skin and catheterization.). For teaching convenience, verses are considered to be more concise and memorable, as well as applicable to clinical practice, in order to provide some help for clinical teaching.

An artificial intelligence model for the simulation of visual effects in patients with visual field defects.

BACKGROUND: This study aimed to simulate the visual field (VF) effects of patients with VF defects using deep learning and computer vision technology. METHODS: We collected 3,660 Humphrey visual fields (HVFs) as data samples, including 3,263 reliable 24-2 HVFs. The convolutional neural network (CNN) analyzed and converted the grayscale map of reliable samples into structured data. The artificial intelligence (AI) simulations were developed using computer vision technology. In statistical analyses, the pilot study determined 687 reliable samples to conduct clinical trials, and the two independent sample t-tests were used to calculate the difference of the cumulative gray values. Three volunteers evaluated the matching degree of shape and position between the grayscale map and the AI simulation, which was graded from 0 to100 scores. Based on the average ranking, the proportion of good and excellent grades was determined, and thus the reliability of the AI simulations was assessed. RESULTS: The reliable samples in the experimental data consisted of 1,334 normal samples and 1,929 abnormal samples. Based on the existing mature CNN model, the fully connected layer was integrated to analyze the VF damage parameters of the input images, and the prediction accuracy of the damage type of the VF defects was up to 89%. By mapping the area and damage information in the VF damage parameter quintuple data set into the real scene image and adjusting the darkening effect according to the damage parameter, the visual effects in patients were simulated in the real scene image. In the clinical validation, there was no statistically significant difference in the cumulative gray value (P>0.05). The good and excellent proportion of the average scores reached 96.0%, thus confirming the accuracy of the AI model. CONCLUSIONS: An AI model with high accuracy was established to simulate the visual effects in patients with VF defects.

Application of neural network model in assisting device fitting for low vision patients.

BACKGROUND: To explore the application of neural network models in artificial intelligence (AI)-aided devices fitting for low vision patients. METHODS: The data of 836 visually impaired people were collected in southwestern Fujian from May 2014 to May 2017. After a full eye examination, 629 low vision patients were selected from this group. Based on the visual functions, rehabilitation needs, and living quality scores of the selected patients, the professionals chose assistive devices that were the best fit for the patients. The data of these three factors were then subjected to the quantitative analysis, and the results were digitized and labeled. The final datasets were used to train a fully connected deep neural networks to obtain an AI-aided model for assistive device fitting. RESULTS: In this study, the main causes of low vision in southwestern Fujian were congenital diseases, among which congenital cataract was the most common. During the low vision AI-aided devices fitting, we found that the intermediate distance magnifier was suitable for the largest number of patients. Through quantitative analysis of the research results, it was found that AI-aided devices fitting was closely related to visual function, rehabilitation needs and quality of life. If this complex relationship can be mapped into the neural network model, AI-aided device fitting can be realized. We built a fully connected neural network model for AI-aided device fitting. The input of the model was the characteristic data of low vision patients, and the output was the forecast of suitable devices. When the threshold of the model was 0.4, the accuracy was about 80% and the F1 value was about 0.31. This threshold can be used as the classification judgment threshold of the model. CONCLUSIONS: Low vision AI-aided device fitting is closely related to visual function, rehabilitation needs, and quality of life scores. The neural network model based on full connection can achieve high accuracy in AI-aided devices fitting. It has a great impact on clinical application.

Low dose intravenous minocycline is neuroprotective after middle cerebral artery occlusion-reperfusion in rats.

BACKGROUND: Minocycline, a semi-synthetic tetracycline antibiotic, is an effective neuroprotective agent in animal models of cerebral ischemia when given in high doses intraperitoneally. The aim of this study was to determine if minocycline was effective at reducing infarct size in a Temporary Middle Cerebral Artery Occlusion model (TMCAO) when given at lower intravenous (IV) doses that correspond to human clinical exposure regimens. METHODS: Rats underwent 90 minutes of TMCAO. Minocycline or saline placebo was administered IV starting at 4, 5, or 6 hours post TMCAO. Infarct volume and neurofunctional tests were carried out at 24 hr after TMCAO using 2,3,5-triphenyltetrazolium chloride (TTC) brain staining and Neurological Score evaluation. Pharmacokinetic studies and hemodynamic monitoring were performed on minocycline-treated rats. RESULTS: Minocycline at doses of 3 mg/kg and 10 mg/kg IV was effective at reducing infarct size when administered at 4 hours post TMCAO. At doses of 3 mg/kg, minocycline reduced infarct size by 42% while 10 mg/kg reduced infarct size by 56%. Minocycline at a dose of 10 mg/kg significantly reduced infarct size at 5 hours by 40% and the 3 mg/kg dose significantly reduced infarct size by 34%. With a 6 hour time window there was a non-significant trend in infarct reduction. There was a significant difference in neurological scores favoring minocycline in both the 3 mg/kg and 10 mg/kg doses at 4 hours and at the 10 mg/kg dose at 5 hours. Minocycline did not significantly affect hemodynamic and physiological variables. A 3 mg/kg IV dose of minocycline resulted in serum levels similar to that achieved in humans after a standard 200 mg dose. CONCLUSIONS: The neuroprotective action of minocycline at clinically suitable dosing regimens and at a therapeutic time window of at least 4-5 hours merits consideration of phase I trials in humans in view of developing this drug for treatment of stroke.

SDF-1 (CXCL12) is upregulated in the ischemic penumbra following stroke: association with bone marrow cell homing to injury.

The chemokine stromal-derived factor-1 (SDF-1, also known as CXCL12) and its receptor CXCR4 have been implicated in homing of stem cells to the bone marrow and the homing of bone marrow-derived cells to sites of injury. Bone marrow cells infiltrate brain and give rise to long-term resident cells following injury. Therefore, SDF-1 and CXCR4 expression patterns in 40 mice were examined relative to the homing of bone marrow-derived cells to sites of ischemic injury using a stroke model. Mice received bone marrow transplants from green fluorescent protein (GFP) transgenic donors and later underwent a temporary middle cerebral artery suture occlusion (MCAo). SDF-1 was associated with blood vessels and cellular profiles by 24 hours through at least 30 days post-MCAo. SDF-1 expression was principally localized to the ischemic penumbra. The majority of SDF-1 expression was associated with reactive astrocytes; much of this was perivascular. GFP+ cells were associated with SDF-1-positive vessels and were also found in the neuropil of regions with increased SDF-1 immunoreactivity. Most vessel-associated GFP+ cells resemble pericytes or perivascular microglia and the majority of the GFP+ cells in the parenchyma displayed characteristics of activated microglial cells. These findings suggest SDF-1 is important in the homing of bone marrow-derived cells, especially monocytes, to areas of ischemic injury.

Hemorrhagic transformation is related to the duration of occlusion and treatment with tissue plasminogen activator in a nonembolic stroke model.

The availability of reperfusion therapy for acute ischemic stroke patients has made the causes and significance of hemorrhagic transformation an area of intense interest and controversy. Ninety-two male Wistar rats underwent transient middle cerebral artery occlusion (MCAO) of between 1 and 6 h. Forty animals received 10 mg kg-1 of recombinant tissue plasminogen activator (rtPA), infused over 20 min, starting 5 min before reperfusion. At 18-24 h, the animals were sacrificed. The presence of hemorrhagic transformation (HT) on stained sections was recorded and total ischemic lesion area was quantified using image analysis software. Seventeen animals (11 with HT) were subjected to immunohistochemical analysis for detection of endothelial barrier antigen (EBA), quantified in three sections, in eight different fields per section. Chi-squared analysis and logistic regression were used to assess the contribution of rtPA and duration of occlusion to HT development. Nested, repeated measures analyses of variance were performed to assess the changes in EBA caused by ischemia and associated with HT. Fifty-nine animals developed HT that was significantly associated with occlusion duration (p < 0.0001) and ischemic lesion size (p = 0.0007). The presence of rtPA accelerated HT development. Statistically significant side-to-side differences in the presence of EBA were found in the striatum (core of the infarct) of animals with HT (p < 0.001) and without HT (p < 0.001), but only in animals with durations of occlusion of 2 h or more. Duration of occlusion is an important predictor of HT in transient MCAO in the rat and is closely associated with EBA expression.