Clinical Significance of a Novel Vasculogenic Mimicry-Based Prognostic Model in Hepatocellular Carcinoma.

BACKGROUND: Vasculogenic mimicry, a novel neovascularization pattern of aggressive tumors, is associated with poor clinical outcomes. OBJECTIVE: The aim of this research was to establish a new model, termed VC score, to predict the prognosis, Tumor Microenvironment (TME) components, and immunotherapeutic response in Hepatocellular Carcinoma (HCC). METHODS: The expression data of the public databases were used to develop the prognostic model. Consensus clustering was performed to confirm the molecular subtypes with ideal clustering efficacy. The high- and low-risk groups were stratified utilizing the VC score. Various methodologies, including survival analysis, single-sample Gene Set Enrichment Analysis (ssGSEA), Tumor Immune Dysfunction and Exclusion scores (TIDE), Immunophenoscore (IPS), and nomogram, were utilized for verification of the model performance and to characterize the immune status of HCC tissues. GSEA was performed to mine functional pathway information. RESULTS: The survival and immune characteristics varied between the three molecular subtypes. A five-gene signature (TPX2, CDC20, CFHR4, SPP1, and NQO1) was verified to function as an independent predictive factor for the prognosis of patients with HCC. The high-risk group exhibited lower Overall Survival (OS) rates and higher mortality rates in comparison to the low-risk group. Patients in the low-risk group were predicted to benefit from immune checkpoint inhibitor therapy and exhibit increased sensitivity to immunotherapy. Enrichment analysis revealed that signaling pathways linked to the cell cycle and DNA replication processes exhibited enrichment in the high-risk group. CONCLUSIONS: The VC score holds the potential to establish individualized treatment plans and clinical management strategies for patients with HCC.

Conjunctive encoding of exploratory intentions and spatial information in the hippocampus.

The hippocampus creates a cognitive map of the external environment by encoding spatial and self-motion-related information. However, it is unclear whether hippocampal neurons could also incorporate internal cognitive states reflecting an animal's exploratory intention, which is not driven by rewards or unexpected sensory stimuli. In this study, a subgroup of CA1 neurons was found to encode both spatial information and animals' investigatory intentions in male mice. These neurons became active before the initiation of exploration behaviors at specific locations and were nearly silent when the same fields were traversed without exploration. Interestingly, this neuronal activity could not be explained by object features, rewards, or mismatches in environmental cues. Inhibition of the lateral entorhinal cortex decreased the activity of these cells during exploration. Our findings demonstrate that hippocampal neurons may bridge external and internal signals, indicating a potential connection between spatial representation and intentional states in the construction of internal navigation systems.

Clinical significance of RNA methylation in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a primary liver malignancy with high mortality rates and poor prognosis. Recent advances in high-throughput sequencing and bioinformatic technologies have greatly enhanced the understanding of the genetic and epigenetic changes in liver cancer. Among these changes, RNA methylation, the most prevalent internal RNA modification, has emerged as a significant contributor of the development and progression of HCC. Growing evidence has reported significantly abnormal levels of RNA methylation and dysregulation of RNA-methylation-related enzymes in HCC tissues and cell lines. These alterations in RNA methylation play a crucial role in the regulation of various genes and signaling pathways involved in HCC, thereby promoting tumor progression. Understanding the pathogenesis of RNA methylation in HCC would help in developing prognostic biomarkers and targeted therapies for HCC. Targeting RNA-methylation-related molecules has shown promising potential in the management of HCC, in terms of developing novel prognostic biomarkers and therapies for HCC. Exploring the clinical application of targeted RNA methylation may provide new insights and approaches for the management of HCC. Further research in this field is warranted to fully understand the functional roles and underlying mechanisms of RNA methylation in HCC. In this review, we described the multifaceted functional roles and potential mechanisms of RNA methylation in HCC. Moreover, the prospects of clinical application of targeted RNA methylation for HCC management are discussed, which may provide the basis for subsequent in-depth research on RNA methylation in HCC.

Emerging function of main RNA methylation modifications in the immune microenvironment of digestive system tumors.

Digestive system tumors have been reported in more than 25% of all cancer cases worldwide, bringing a huge burden on the healthcare system. RNA methylation modification-an important post-transcriptional modification-has become an active research area in gene regulation. It is a dynamic and reversible process involving several enzymes, such as methyltransferases, demethylases, and methylation reader proteins. This review provides insights into the role of three major methylation modifications, namely m6A, m5C, and m1A, in the development of digestive system tumors, specifically in the development of tumor immune microenvironment (TIME) of these malignancies. Abnormal methylation modification affects immunosuppression and antitumor immune response by regulating the recruitment of immune cells and the release of immune factors. Understanding the mechanisms by which RNA methylation regulates digestive system tumors will be helpful in exploring new therapeutic targets.

Formation processes of groundwater in a non-ferrous metal mining city of China: Insights from hydrochemical and strontium isotope analyses.

Tongling is a significant non-ferrous metal mining city in China, which produces waste that negatively impacts the area's water environment. It is essential to comprehend the hydrochemical properties and formation processes of groundwater to safeguard and utilize it efficiently. We explored major ions, strontium, and its isotopes in water and river-bottom samples from the northern (i.e., A-A' section) and southern (i.e., B-B' section) areas. The hydrochemical facies show the mining activities have a greater impact on surface water than on groundwater. Groundwater hydrochemical formation results from several factors, with water-rock interaction and ion exchange being primary. Additionally, the dissolution of calcite, dolomite, and feldspar, oxidation of pyrite, and hydrolysis of carbonate minerals also impact the formation of groundwater chemistry. Our analysis of strontium and its isotopes indicates that carbonate dissolution primarily occurred in the recharge area; the runoff from the recharge to the discharge area results in the dissolution of certain silicate rocks; calcite dissolution sources account for > 70% contribution in both surface water and groundwater water-rock interactions, whereas silicate rock dissolution sources and dolomite dissolution sources account for < 30%. Due to changed order of dissolved carbonate and silicate minerals during groundwater flow, the distribution of strontium and its isotopes in the A-A' section is opposite to that in the B-B' section. The findings provide a basis for developing, utilizing, managing, and protecting groundwater resources, especially in similar mining areas.

Development of a promising PPAR signaling pathway-related prognostic prediction model for hepatocellular carcinoma.

The peroxisome proliferator-activated receptor (PPAR) signaling pathway plays a crucial role in systemic cell metabolism, energy homeostasis and immune response inhibition. However, its significance in hepatocellular carcinoma (HCC) has not been well documented. In our study, based on the RNA sequencing data of HCC, consensus clustering analyses were performed to identify PPAR signaling pathway-related molecular subtypes, each of which displaying varying survival probabilities and immune infiltration status. Following, a prognostic prediction model of HCC was developed by using the random survival forest method and Cox regression analysis. Significant difference in survival outcome, immune landscape, drug sensitivity and pathological features were observed between patients with different prognosis. Additionally, decision tree and nomogram models were adopted to optimize the prognostic prediction model. Furthermore, the robustness of the model was verified through single-cell RNA-sequencing data. Collectively, this study systematically elucidated that the PPAR signaling pathway-related prognostic model has good predictive efficacy for patients with HCC. These findings provide valuable insights for further research on personalized treatment approaches for HCC.

Prognostic and immune predictive roles of a novel tricarboxylic acid cycle-based model in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer. Since the tricarboxylic acid cycle is widely involved in tumor metabolic reprogramming and cuproptosis, investigating related genes may help to identify prognostic signature of patients with HCC. Data on patients with HCC were sourced from public datasets, and were divided into train, test, and single-cell cohorts. A variety of machine learning algorithms were used to identify different molecular subtypes and determine the prognostic risk model. Our findings revealed that the risk score (TRscore), based on the genes OGDHL, CFHR4, and SPP1, showed excellent predictive performance in different datasets. Pathways related to cell cycle and immune inflammation were enriched in the high-risk group, whereas metabolism-related pathways were significantly enriched in the low-risk group. The high-risk group was associated with a greater number of mutations of detrimental biological behavior and higher levels of immune infiltration, immune checkpoint expression, and anti-cancer immunotherapy response. Low-risk patients demonstrated greater sensitivity to erlotinib and phenformin. SPP1 was mainly involved in the interaction among tumor-associated macrophages, T cells, and malignant cells via SPP1-CD44 and SPP1-(ITGA5 + ITGB1) ligand-receptor pairs. In summary, our study established a prognostic model, which may contribute to individualized treatment and clinical management of patients with HCC.

Global research status analysis of the association between aortic aneurysm and inflammation: a bibliometric analysis from 1999 to 2023.

Background: Aortic aneurysm is a chronic arterial disease that can lead to aortic rupture, causing severe complications and life-threatening risks for patients, and it is one of the common causes of death among the elderly. Increasing evidence suggests that inflammation plays an important role in the progression of aortic aneurysm. However, there is a lack of literature-based quantitative analysis in this field. Methods: Up to March 30, 2023, we collected 3,993 articles related to aortic aneurysm and inflammation from the Web of Science Core Collection (WoSCC) database for bibliometric analysis. The collected literature data were subjected to visual analysis of regional distribution, institutions, authors, keywords, and other information using tools such as CiteSpace, VOSviewer, the R package "bibliometric," and online platforms. Results: The number of publications in this research field has been steadily increasing each year, with the United States and China being the main contributing countries. Harvard University in the United States emerged as the most active and influential research institution in this field. Jonathan Golledge and Peter Libby were identified as the authors with the highest publication output and academic impact, respectively. Researchers in this field tend to publish their findings in influential journals such as the Journal of Vascular Surgery and Arteriosclerosis Thrombosis and Vascular Biology. "Abdominal aortic aneurysm," "giant cell arteritis," "arterial stiffness," and "smooth muscle cells" were identified as the hottest topics in the field of aortic aneurysm and inflammation. In terms of keyword co-occurrence analysis, "Clinical relevant studies of AA" (red), "Inflammatory activation" (green), "Inflammatory mechanisms related to pathogenesis" (dark blue), "Cytokines" (yellow), "Risk factors" (purple), and "Pathological changes in vascular wall" (cyan) formed the major research framework in this field. "Inflammation-related pathogenesis" and "inflammation activation" have emerged as recent hot research directions, with "monocytes," "progression," and "proliferation" being the prominent topics. Conclusion: This study provides a comprehensive analysis of the knowledge network framework and research hotspots in the field of aortic aneurysm and inflammation through a literature-based quantitative approach. It offers valuable insights to guide scholars in identifying meaningful research directions in this field.

Non-coding RNA methylation modifications in hepatocellular carcinoma: interactions and potential implications.

RNA methylation modification plays a crucial role as an epigenetic regulator in the oncogenesis of hepatocellular carcinoma (HCC). Numerous studies have investigated the molecular mechanisms underlying the methylation of protein-coding RNAs in the progression of HCC. Beyond their impact on mRNA, methylation modifications also influence the biological functions of non-coding RNAs (ncRNAs). Here, we present an advanced and comprehensive overview of the interplay between methylation modifications and ncRNAs in HCC, with a specific focus on their potential implications for the tumor immune microenvironment. Moreover, we summarize promising therapeutic targets for HCC based on methylation-related proteins. In the future, a more profound investigation is warranted to elucidate the effects of ncRNA methylation modifications on HCC pathogenesis and devise valuable intervention strategies. Video Abstract.

PDM-SHD NFDM transmission with envelope-detection feedback polarization tracking and optical injection locking.

Nonlinear frequency division multiplexing (NFDM) systems, especially the eigenvalue communications have the potential to overcome the nonlinear Shannon capacity limit. However, the baud rate of eigenvalue communications is typically restricted to a few GBaud, making it challenging to mitigate laser frequency impairments such as the phase noise and frequency offset (FO) using digital signal processing (DSP) algorithms in intradyne detections (IDs). Therefore, we introduce the polarization division multiplexing-self-homodyne detection (PDM-SHD) into the NFDM link, which could overcome the impact of phase noise and FO by transmitting a pilot carrier originating from the transmitter laser to the receiver through the orthogonal polarization state of signal. To separate the signal from the carrier at the receiver, a carrier to signal power ratio (CSPR) unrestricted adaptive polarization controlling strategy is proposed and implemented by exploiting the optical intensity fluctuation of the light in a particular polarization rather than its direct optical power as the feedback. Optical injection locking (OIL) is used subsequently to amplify optical power of pilot carrier and mitigate the impact of signal-signal beat interference (SSBI). Additionally, the effects of cross-polarization modulation (XPolM) and modulation instability (MI) in long haul transmission are explored and inhibited. The results show that the tolerable FO range is about 3.5 GHz, which is 17 times larger than the ID one. When 16-amplitude phase shift keying (APSK) or 64-APSK constellations are used, identical Q-factor performance can be obtained by using distributed feedback (DFB, ∼10 MHz) laser, external cavity laser (ECL, ∼100kHz), or fiber laser (FL, ∼100 Hz), respectively, which demonstrates that our proposed PDM-SHD eigenvalue communication structure is insensitive to the laser linewidth. Under the impact of cycle slip, the Q-factor difference of 16-APSK signal between the ECL-ID system and ECL-SHD system can be up to 8.73 dB after 1500 km transmission.

TMS-induced inhibition of the left premotor cortex modulates illusory social perception.

Communicative actions from one person are used to predict another person's response. However, in some cases, these predictions can outweigh the processing of sensory information and lead to illusory social perception such as seeing two people interact, although only one is present (i.e., seeing a Bayesian ghost). We applied either inhibitory brain stimulation over the left premotor cortex (i.e., real TMS) or sham TMS. Then, participants indicated the presence or absence of a masked agent that followed a communicative or individual gesture of another agent. As expected, participants had more false alarms in the communicative (i.e., Bayesian ghosts) than individual condition in the sham TMS session and this difference between conditions vanished after real TMS. In contrast to our hypothesis, the number of false alarms increased (rather than decreased) after real TMS. These pre-registered findings confirm the significance of the premotor cortex for social action predictions and illusory social perception.

HCC prediction models in chronic hepatitis B patients receiving entecavir or tenofovir: a systematic review and meta-analysis.

BACKGROUND: Our study aimed to compare the predictive performance of different hepatocellular carcinoma (HCC) prediction models in chronic hepatitis B patients receiving entecavir or tenofovir, including discrimination, calibration, negative predictive value (NPV) in low-risk, and proportion of low-risk. METHODS: We conducted a systematic literature research in PubMed, EMbase, the Cochrane Library, and Web of Science before January 13, 2022. The predictive performance was assessed by area under receiver operating characteristic curve (AUROC), calibration index, negative predictive value, and the proportion in low-risk. Subgroup and meta-regression analyses of discrimination and calibration were conducted. Sensitivity analysis was conducted to validate the stability of the results. RESULTS: We identified ten prediction models in 23 studies. The pooled 3-, 5-, and 10-year AUROC varied from 0.72 to 0.84, 0.74 to 0.83, and 0.76 to 0.86, respectively. REAL-B, AASL-HCC, and HCC-RESCUE achieved the best discrimination. HCC-RESCUE, PAGE-B, and mPAGE-B overestimated HCC development, whereas mREACH-B, AASL-HCC, REAL-B, CAMD, CAGE-B, SAGE-B, and aMAP underestimated it. All models were able to identify people with a low risk of HCC accurately. HCC-RESCUE and aMAP recognized over half of the population as low-risk. Subgroup analysis and sensitivity analysis showed similar results. CONCLUSION: Considering the predictive performance of all four aspects, we suggest that HCC-RESCUE was the best model to utilize in clinical practice, especially in primary care and low-income areas. To confirm our findings, further validation studies with the above four components were required.

Cardioprotective effect of epigallocatechin gallate in myocardial ischemia/reperfusion injury and myocardial infarction: a meta-analysis in preclinical animal studies.

This meta-analysis aims to determine the efficacy of Epigallocatechin gallate (EGCG) in the treatment of myocardial ischemia-reperfusion injury (MIRI) and summarize the mechanisms involved. Literature from six databases including Web of Science, PubMed, Embase, China National Knowledge Infrastructure (CNKI), Wan-Fang database, and VIP database (VIP) were systematically searched. All the analysis were conducted by R. Twenty-five eligible studies involving 443 animals were included in this meta-analysis. The results indicated that compared to controls, EGCG exerts a cardioprotective effect by reducing myocardial infarct size (SMD = -4.06; 95% CI: -5.17, -2.94; P < 0.01; I2 = 77%). The funnel plot revealed publication bias. Moreover, EGCG significantly improves cardiac function, serum myocardial injury enzyme, and oxidative stress levels in MIRI animal models. This meta-analysis demonstrates that EGCG exhibits therapeutic promise in animal models of MIRI. However, further validation is still needed in large animal models and large clinical studies.

Global trends in research of acute type a aortic dissection: A bibliometric analysis from 2002 to 2022.

Background: Acute type A aortic dissection (ATAAD) is life-threatening and needs urgent and highly invasive surgery. So far, there is no comprehensive review of the status quo of ATAAD studies. Therefore, this study aimed to quantify and identify the global trends of ATAAD research over the past two decades through bibliometric analysis and to provide reference for clinical practice, research funding allocation, and decision-making. Methods: The original research articles and reviews related to ATAAD research were downloaded from the Web of Science Core Collection on March 19, 2023. CiteSpace (6.2.1) and VOSviewer (1.6.18) were used for bibliometric analysis of the number of publications by each country, institution, and authors and the establishment of knowledge maps. The raw data collected were examined using the Online Analysis Platform of Bibliometric to assess the collaboration of countries in the field. Results: The number of documents on ATAAD research increased continuously. A total of 1,943 publications published from 2002 to 2022 from 66 countries/regions were identified: 637 (32.78%) were conducted in China and 360 (18.53%) in the United States; 152 (cited frequency 941) were conducted by Capital Medical University and 107 (cited frequency 370) by Fujian Medical University. The Journal of Cardiac Surgery was the most frequently published journal (143 publications, cited frequency 695). The highest citation and co-cited journal was the Annals of Thoracic Surgery (cited frequency 3,888, co-cited frequency 6,224). We identified 8,050 authors among which Lizhong Sun (61 publications, cited frequency 721) had the largest number of publications, and Nienaber Christoph A (cited frequency 1,536, co-cited frequency 392) was co-cited most often. Meanwhile, the most common keywords were acute type A aortic dissection (occurrences, 1,211), surgery (occurrences, 657), repair (occurrences, 404), and management (occurrences, 386). The earliest and latest used keywords were "axillary artery" (average publication year: 2011.23) and "inflammation" (average publication year: 2019.09), respectively. The keyword "surgical treatment" (strength 12.31) and the co-cited reference "Evangelista A, 2018, Circulation" (strength 28.55) had the highest citation bursts. The keywords "impact" and "acute kidney injury" remained high citation bursts. The co-cited references with the largest and smallest size clusters were "cerebral protection" (#0, size = 126) and "pregnancy" (#12, size = 11). The reference "Hagan PG, 2000, JAMA" (cited frequency, 350) had the highest co-citations. Conclusions: The bibliometric and visualized analysis generated objective evidence for a comprehensive understanding and evaluation of ATAAD research.

Cardioprotective effect of curcumin on myocardial ischemia/reperfusion injury: a meta-analysis of preclinical animal studies.

Objective: This meta-analysis aimed to determine the efficacy of curcumin in preventing myocardial ischemia/reperfusion (I/R) injury in animal models. Methods: Studies published from inception to January 2023 were systematically searched in databases including PubMed, Web of Science, Embase, China's National Knowledge Infrastructure (CNKI), Wan-Fang database, and VIP database (VIP). The SYRCLE's RoB tool was used to determine methodological quality. Sensitivity analysis and subgroup analysis were performed when there was high heterogeneity. Publication bias was assessed using a funnel plot. Results: Thirty-seven studies involving 771 animals were included in this meta-analysis with methodology quality scores ranging from 4 to 7. The results indicated that curcumin treatment significantly improved myocardial infarction size standard mean difference (SMD) = -5.65; 95% confidence interval (CI): 6.94, -4.36; p < 0.01; I2 = 90%). The sensitivity analysis for infarct size showed that the results were stable and reliable. However, the funnel plot was asymmetric. The subgroup analysis included species, animal model, dose, administration, and duration. The results showed that the subgroup dose was statistically significant between subgroups. In addition, curcumin treatment improved cardiac function, myocardial injury enzymes, and oxidative stress levels in animal models of myocardial I/R injury. The funnel plot revealed that there is publication bias for creatine kinase and lactate dehydrogenase. Finally, we performed a meta-analysis of inflammatory cytokines and apoptosis index. The results showed that curcumin treatment downregulated serum inflammatory cytokine levels and myocardial apoptosis index. Conclusion: This meta-analysis suggests that curcumin has excellent potential for the treatment of myocardial I/R injury in animal models. However, this conclusion needs to be further discussed and verified in large animal models and human clinical trials. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022383901.

A novel prognostic model for hepatocellular carcinoma based on pyruvate metabolism-related genes.

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer, accounting for over 90% of cases. As pyruvate metabolic pathways are often dysregulated in cancer cells, investigating pyruvate metabolism-related genes may help identify prognostic gene signature and develop potential strategies for the management of patients with HCC. The mRNA expression profile, gene mutation data, and clinical information of HCC were obtained from open-source databases. A list of pyruvate metabolism-related genes was downloaded from the MSigDB dataset. Our findings revealed that certain pyruvate metabolism-related genes had copy number variations and single nucleotide variations in patients with liver cancer. Based on pyruvate metabolism-related genes, we stratified patients with HCC into three subtypes with different prognoses, clinical features, mutation profiles, functional annotation, and immune infiltration status. Next, we identified 13 key pyruvate metabolism-related genes significantly correlated with the prognosis of HCC using six machine learning algorithms and constructed a risk model. We also observed that the risk score was positively associated with a worse prognosis and increased immune infiltration. In summary, our study established a prognostic risk model for HCC based on pyruvate metabolism-related genes, which may contribute to the identification of potential prognostic targets and the development of new clinical management strategies for HCC.

Crosstalk between Gut Microbiota and Bile Acids in Cholestatic Liver Disease.

Emerging evidence suggests the complex interactions between gut microbiota and bile acids, which are crucial end products of cholesterol metabolism. Cholestatic liver disease is characterized by dysfunction of bile production, secretion, and excretion, as well as excessive accumulation of potentially toxic bile acids. Given the importance of bile acid homeostasis, the complex mechanism of the bile acid-microbial network in cholestatic liver disease requires a thorough understanding. It is urgent to summarize the recent research progress in this field. In this review, we highlight how gut microbiota regulates bile acid metabolism, how bile acid pool shapes the bacterial community, and how their interactions contribute to the pathogenesis of cholestatic liver disease. These advances might provide a novel perspective for the development of potential therapeutic strategies that target the bile acid pathway.

The efficacy and safety of anti-PD-1/PD-L1 in treatment of glioma: a single-arm meta-analysis.

Objective: This meta-analysis aimed to evaluate the efficacy and safety of PD-1/PD-L1 inhibitors in patients with glioma. Methods: PubMed, EMBASE, Web of Science, and the Cochrane library were searched from inception to January 2023 without language restriction. Primary outcomes included overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and adverse events (AEs). The risk of bias was assessed by subgroup analysis, sensitivity analysis, and publication bias, including funnel plot, Egger's test, and Begg's test. Results: A total of 20 studies involving 2,321 patients were included in this meta-analysis. In the analysis of the included phase III clinical trials, the forest plot showed that PD-1/PD-L1 inhibitors did not improve the OS (HR=1.15, 95% CI: 1.03-1.29, P=0.02, I2 = 14%) and PFS (HR=1.43, 95% CI: 1.03-1.99, P=0.03, I2 = 87%). In the single-arm analysis, the forest plot demonstrated that the 6-month OS was 71% (95% CI: 57%-83%, I2 = 92%), 1-year OS was 43% (95% CI: 33%-54%, I2 = 93%), and the 2-year OS was 27% (95% CI: 13%-44%, I2 = 97%). The pooled estimate of the median OS was 8.85 months (95% CI: 7.33-10.36, I2 = 91%). Furthermore, the result indicated that the 6-month PFS was 28% (95% CI: 18%-40%, I2 = 95%), 1-year PFS was 15% (95% CI: 8%-23%, I2 = 92%), and the 18-month PFS was 10% (95% CI: 3%-20%, I2 = 93%). The pooled estimate of the median PFS was 3.72 months (95% CI: 2.44-5.00, I2 = 99%). For ORR, the pooled estimate of ORR was 10% (95% CI: 2%-20%, I2 = 88%). We further analyzed the incidence of PD-1/PD-L1 inhibitor-related AEs, and the pooled incidence of AEs was 70% (95% CI: 58%-81%, I2 = 94%). The incidence of AEs ≥ grade 3 was 19% (95% CI: 11%-30%, I2 = 94%). The funnel plot for the median PFS and median OS was symmetric with no significant differences in Egger's test and Begg's test. The sensitivity analysis revealed that our results were stable and reliable. Conclusion: The results of this meta-analysis suggest that anti-PD-1/PD-L1 therapy is relatively safe but could not prolong survival in glioma. More randomized controlled trials are needed to confirm our results. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023396057.

Reset-free adaptive polarization controller on a silicon-photonic platform for a self-coherent communication system.

To give full play to the advantages of the self-coherent systems in the data center scene, the problem of the random walk of the polarization state of the delivered local oscillator must be solved. An adaptive polarization controller (APC) is an effective solution, with the characteristics of easy integration, low complexity, being reset-free, and so on. In this work, we experimentally demonstrated an endlessly APC based on a Mach-Zehnder interferometer on a silicon-photonic integrated circuit. The APC is thermally tuned with only two control electrodes. It endlessly stabilizes the arbitrary state of polarization (SOP) of the light to a state of equal power of the two orthogonal polarizations (X and Y). A polarization tracking speed of up to 800 rad/s is achieved.

A challenge of deep-learning-based object detection for hair follicle dataset.

BACKGROUND: Deep-learning object detection has been applied in various industries, including healthcare, to address hair loss. METHODS: In this paper, YOLOv5 object detection algorithm was used to detect hair follicles in a small and specific image dataset collected using a specialized camera on the scalp of individuals with different ages, regions, and genders. The performance of YOLOv5 was compared with other popular object detection models. RESULTS: YOLOv5 performed well in the detection of hair follicles, and the follicles were classified into five classes based on the number of hairs and the type of hair contained. In single-class object detection experiments, a smaller batch size and the smallest YOLOv5s model achieved the best results, with an map of 0.8151. In multiclass object detection experiments, the larger YOLOv5l model was able to achieve the best results, and batch size affected the result of model training. CONCLUSION: YOLOv5 is a promising algorithm for detecting hair follicles in a small and specific image dataset, and its performance is comparable to other popular object detection models. However, the challenges of small-scale data and sample imbalance need to be addressed to improve the performance of target detection algorithms.