Association between ossific nucleus volume changes and postoperative avascular necrosis risk in children with developmental dysplasia of the hip.

This study aimed to investigate the correlation between ossific nucleus volume and avascular necrosis (AVN) in pediatric patients diagnosed with developmental dysplasia of the hip (DDH). Analyzing 211 cases, including 119 open reduction (OR) and 92 closed reduction (CR) procedures, we quantified ossific nucleus volume using magnetic resonance imaging (MRI). Categorizing the OR group based on ossific nucleus volume revealed no statistically significant difference in AVN incidence. Similarly, in the CR cohort, there was no significant discrepancy in AVN occurrence between subgroups with or without the ossific nucleus. Logistic regression in CR identified the international hip dysplasia institute (IHDI) grade as a significant AVN risk factor (p = 0.007). IHDI grades 3 and 4 exhibited a 6.94 times higher likelihood of AVN compared to grades 1 and 2. Across CR and OR, neither initial age nor ossific nucleus volume emerged as AVN risk factors. In conclusion, ossific nucleus volume does not pose a risk for AVN in DDH children undergoing CR or OR, emphasizing the clinical significance of IHDI grading in predicting AVN risk during CR and the importance of early intervention to prevent treatment delays.

Ribosomal protein L32 contributes to the growth, antibiotic resistance and virulence of Glaesserella parasuis.

Glaesserella parasuis is the pathogen that causes Glässer's disease in pigs, which is characterized by fibrinous polyserositis, arthritis and meningitis. Research on ribosomal protein L32 in microorganisms has mainly focused on regulating gene transcription and translation, but its effect on bacterial virulence is unclear. The role of L32 gene in G. parasuis is not clear, and in order to study the function of L32 gene, a suicide plasmid-mediated natural transformation method was used to construct a L32 gene deletion mutant. We found that although L32 was shown to be non-essential for cell proliferation, the growth curve of ΔL32 is clearly different compared with that of ZJ1208. ΔL32 produced more outer membrane vesicles (OMVs) with a variety of irregular shapes, but produced similar biofilm to the parental strain. ΔL32 is more sensitive to osmotic pressure, oxidation pressure and heat shock stress. Meanwhile, ΔL32 is significantly more susceptible to antimicrobials such as spectinomycin, apramycin, sulfafurazole, but not to other antibiotics used in this study. In the mouse challenge experiment, the mortality of mice infected with the mutant strain decreased by 40% compared to those infected with the wild-type strain, indicating that L32 is a virulence-associated factor which contributes to bacterial fitness in host environments. The above results show that L32 is important for the growth, stress resistance and virulence of G. parasuis, and this study also confirms for the first time that L32 plays an important role in antibiotic resistance against aminoglycosides and sulfonamides.

An interpretable machine learning method for risk stratification of patients with acute coronary syndrome.

Backgrounds: Risk stratification for major adverse cardiovascular events (MACE) within one year in patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI) remains a challenge. Although several predictive models based on machine learning have emerged, they are difficult to understand. This study aimed to develop a machine learning prediction model that is easy to understand and trustworthy by lay people to assess the risk of MACE in ACS patients undergoing PCI within one year of the procedure. Methods: This retrospective cohort study used medical data from 1105 patients to construct a machine-learning model. To ensure thoroughness and multidimensionality of model parsing, Shapley Additive explanations (SHAP) analysis and Local interpretable model-agnostic explanations (LIME) interpretation techniques were used to systematically and deeply interpret the constructed models from a global to a detailed level. Results: The study assessed 12 machine learning methods' prediction models and found that the Random Forest model was the most effective in predicting the risk of MACE in ACS patients after undergoing PCI. The model achieved an AUC value of 0.807 in the validation set, with an accuracy of 0.82, and a stable F1 score of 0.51. SHAP analysis ranked eight key feature variables, such as LVEF, in global importance. The weights of each feature range in the prediction model were revealed using LIME analysis. Conclusion: The machine learning prediction model we developed is capable of accurately predicting the likelihood of patients with ACS experiencing a MACE within one year of surgery.

Predictive value of near-term prediction models for severe immune-related adverse events in malignant tumor PD-1 inhibitor therapy.

Immune-related adverse events (irAEs) impact outcomes, with most research focusing on early prediction (baseline data), rather than near-term prediction (one cycle before the occurrence of irAEs and the current cycle). We aimed to explore the near-term predictive value of neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), absolute eosinophil count (AEC) for severe irAEs induced by PD-1 inhibitors. Data were collected from tumor patients treated with PD-1 inhibitors. NLR, PLR, and AEC data were obtained from both the previous and the current cycles of irAEs occurrence. A predictive model was developed using elastic net logistic regression Cutoff values were determined using Youden's Index. The predicted results were compared with actual data using Bayesian survival analysis. A total of 138 patients were included, of whom 47 experienced grade 1-2 irAEs and 18 experienced grade 3-5 irAEs. The predictive model identified optimal α and λ through 10-fold cross-validation. The Shapiro-Wilk test, Kruskal-Wallis test and logistic regression showed that only current cycle data were meaningful. The NLR was statistically significant in predicting irAEs in the previous cycle. Both NLR and AEC were significant predictors of irAEs in the current cycle. The model achieved an area under the ROC curve (AUC) of 0.783, with a sensitivity of 77.8% and a specificity of 80.8%. A probability ≥ 0.1345 predicted severe irAEs. The model comprising NLR, AEC, and sex may predict the irAEs classification in the current cycle, offering a near-term predictive advantage over baseline models and potentially extending the duration of immunotherapy for patients.

Study on the synthesis of iron-based nanomedicine assisted by angelica sinensis polysaccharide with enhanced retention performance and its application in anemia treatment.

Inappropriate treatment of chronic inflammation and infection can lead to serious consequences, with anemia being the most common secondary disease that often requires systematic treatment. However, the complex pathology and gastrointestinal irritation associated with oral iron supplements limit their effectiveness. To address this, a bioactive ingredient derived from natural herbs, Angelica sinensis polysaccharide (ASP), was utilized as an ideal adjuvant for regulating the size and stability of iron oxide nanoparticles (IONPs). Highly hydrophilic ASP-modified IONPs (IONPs@ASP) with a mesoporous structure were developed under the induction of microemulsion.The as-prepared IONPs@ASP exhibited enhanced stability, retention performance and controlled degradation in blood and lysosomal environments, respectively, which is beneficial for long-term intravenous iron maintenance in anemia treatment. After confirming the biosafety of IONPs@ASP, pharmacodynamic results showed that hemoglobin levels increased significantly and rapidly returned to normal levels in anemia model rats treated with IONPs@ASP, even surpassing the effects of IONPs or ASP monotherapy. Additionally, analysis of inflammatory factors in rat serum suggested that ASP effectively upregulated the expression of anti-inflammatory factors, indicating synergistic effects of iron-based nanomedicine and immune regulation in anemia treatment. These findings represent a significant advancement in anemia treatment and open new possibilities for developing versatile nanoparticles based on ASP.

Oncological characteristics, treatments and prognostic outcomes in MMR-deficient colorectal cancer.

Colorectal cancer (CRC) ranks as the third most prevalent cancer globally. It's recognized that the molecular subtype of CRC, characterized by mismatch repair deficiency (dMMR) or microsatellite instability-high (MSI-H), plays a critical role in determining appropriate treatment strategies. This review examines the current molecular classifications, focusing on dMMR/MSI-H CRC and its subtypes: Lynch syndrome (LS), Lynch-like syndrome (LLS), and sporadic cases. Despite advances in understanding of these genetic backgrounds, clinical trials have not conclusively differentiated the efficacy of immune checkpoint inhibitors among these subgroups. Therefore, while this review details the molecular characteristics and their general implications for treatment and prognosis, it also highlights the limitations and the need for more refined clinical studies to ascertain tailored therapeutic strategies for each subtype. Furthermore, this review summarizes completed and ongoing clinical studies, emphasizing the importance of developing treatments aligned more closely with molecular profiles. By discussing these aspects, the review seeks to provide a comprehensive analysis of oncological characteristics, presenting a detailed understanding of their implications for treatment and prognosis in dMMR/MSI-H CRC.

Medical device-related pressure injuries in the operating room: A scoping review.

AIMS: To map the existing literature describing medical device-related pressure injuries in patients during surgery, including investigation of the incidence, types of medical devices, risk factors and strategies for preventing medical device-related pressure injuries. DESIGN: A scoping review. DATA SOURCES: In April 2023, three databases were searched. Studies about adult patients undergoing surgery, from 2014 onwards, in English and Chinese were included. Data were extracted about study characteristics and data related to research questions. The Patterns, Advances, Gaps, Evidence for practice and Research recommendations framework were used to synthesize findings. RESULTS: Two different types of evidence were included in this review; 14 research studies and two quality improvement studies. The incidence of medical device-related pressure injuries in the operating room was 0.56%-24.5% and respiratory devices were the most common medical devices investigated. Length of surgery, age and BMI were risk factors for medical device-related pressure injuries in a few studies. The application of a prophylactic dressing and dressing maintenance was the most common prevention strategy. CONCLUSION: Ongoing research is needed to confirm the incidence of, and risk factors for, medical device-related pressure injuries in the operating room. Additionally, more high-quality evidence is needed to underpin current prevention strategies. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Operating room nurses need to be aware of the risks of medical device-related pressure injuries and assess and plan prevention strategies accordingly. Once more high-quality evidence is available, operating room nurses could implement prevention strategies like prophylactic dressings. REPORTING METHOD: Scoping Reviews (PRISMA-ScR) checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Room-Temperature CrI3 Magnets through Lithiation.

The pursuit of two-dimensional (2D) magnetism is promising for energy-efficient electronic devices, including magnetoelectric random access memory and radio frequency/microwave magnonics, and it is gaining fundamental insights into quantum sensing technology. The key challenge resides in overseeing magnetic exchange interactions through a precise chemical reduction process, wherein manipulation of the arrangement of atoms and electrons is essential for achieving room-temperature 2D magnetism tailoring in a manner compatible with device architectures. Here, we report an electrochemically crafted CrI3 layered magnet─a van der Waals material─with precisely tailored lithiation and delithiation degrees. The crystalline and packing structure within the intralayer are preserved during the lithium intercalation within the interlayer, owing to weak interlayer coupling. Intrinsic ferromagnetism featuring a Curie temperature reaching 420 K has been unequivocally demonstrated, showcasing a coercivity of 1120 Oe at room temperature. The degree of lithiation through the reduction from Cr3+ to Cr2+ plays a crucial role in determining a 28.5% change in magnetization and a 0.29 eV shift in the bandgap. Room temperature ferromagnetism and magnetoelectricity are critical for noncontact, specifically photon-driven, dynamic magnetism control of 2D magnet-based magnonics devices.

NuSEA: Nuclei Segmentation With Ellipse Annotations.

OBJECTIVE: Nuclei segmentation is a crucial pre-task for pathological microenvironment quantification. However, the acquisition of manually precise nuclei annotations for improving the performance of deep learning models is time-consuming and expensive. METHODS: In this paper, an efficient nuclear annotation tool called NuSEA is proposed to achieve accurate nucleus segmentation, where a simple but effective ellipse annotation is applied. Specifically, the core network U-Light of NuSEA is lightweight with only 0.86 M parameters, which is suitable for real-time nuclei segmentation. In addition, an Elliptical Field Loss and a Texture Loss are proposed to enhance the edge segmentation and constrain the smoothness simultaneously. RESULTS: Extensive experiments on three public datasets (MoNuSeg, CPM-17, and CoNSeP) demonstrate that NuSEA is superior to the state-of-the-art (SOTA) methods and better than existing algorithms based on point, rectangle, and text annotations. CONCLUSIONS: With the assistance of NuSEA, a new dataset called NuSEA-dataset v1.0, encompassing 118,857 annotated nuclei from the whole-slide images of 12 organs is released. The codes and the new dataset are publicly available at https://github.com/dreambamboo/NuSEA/. SIGNIFICANCE: NuSEA provides a rapid and effective annotation tool for nuclei in histopathological images, benefiting future explorations in deep learning algorithms.

CircVDAC3 sequesters microRNA-592 and elevates EIF4E3 expression to inhibit the progression of gastric cancer.

BACKGROUND: Accumulating evidence has shown that circular RNAs (circRNAs) are involved in gastric cancer (GC) tumorigenesis. However, specific functional circRNAs in GC remain to be discovered, and their underlying mechanisms remain to be elucidated. METHODS: CircRNAs that were differentially expressed between GC tissues and controls were analyzed using a circRNA microarray dataset. The expression of circVDAC3 in GC was determined using quantitative real-time PCR (qRT-PCR), and the structural features of circVDAC3 were validated. Cell function assays and animal experiments were conducted to explore the effects of circVDAC3 on GC. Finally, bioinformatics analysis, fluorescent in situ hybridization, and dual luciferase assays were used to analyze the downstream mechanisms of circVDAC3. RESULTS: Our results showed that circVDAC3 was downregulated in GC and inhibited the proliferation and metastasis of GC cells. Mechanistically, circVDAC3 acts as a competing endogenous RNA (ceRNA) of miR-592 and deregulates the repression of EIF4E3 by miR-592. EIF4E3 is downregulated in GC and overexpression of miR-592 or knockdown of EIF4E3 in circVDAC3-overexpressing cells weakens the anticancer effect of circVDAC3. CONCLUSION: Our study provides evidence that circVDAC3 affects the growth and metastasis of GC cells via the circVDAC3/miR-592/EIF4E3 axis. Our findings offer valuable insights into the mechanisms underlying GC tumorigenesis and suggest novel therapeutic strategies.

MTCSNet: One-stage learning and two-point labeling are sufficient for cell segmentation.

Deep convolution neural networks have been widely used in medical image analysis, such as lesion identification in whole-slide images, cancer detection, and cell segmentation, etc. However, it is often inevitable that researchers try their best to refine annotations so as to enhance the model performance, especially for cell segmentation task. Weakly supervised learning can greatly reduce the workload of annotations, while there is still a huge performance gap between the weakly and fully supervised learning approaches. In this work, we propose a weakly-supervised cell segmentation method, namely Multi-Task Cell Segmentation Network (MTCSNet), for multi-modal medical images, including pathological, brightfield, fluorescent, phase-contrast and differential interference contrast images. MTCSNet is learnt in a single-stage training manner, where only two annotated points for each cell provide supervision information, and the first one is the centroid, the second one is its boundary. Additionally, five auxiliary tasks are elaborately designed to train the network, including two pixel-level classifications, a pixel-level regression, a local temperature scaling and an instance-level distance regression task, which is proposed to regress the distances between the cell centroid and its boundaries in eight orientations. The experimental results indicate that our method outperforms all state-of-the-art weakly-supervised cell segmentation approaches on public multi-modal medical image datasets. The promising performance also shows that a single-stage learning with two-point labeling approach are sufficient for cell segmentation, instead of fine contour delineation. The codes are available at: https://github.com/binging512/MTCSNet.

A longitudinal electrophysiological and behavior dataset for PD rat in response to deep brain stimulation.

Here we presented an electrophysiological dataset collected from layer V of the primary motor cortex (M1) and the corresponding behavior dataset from normal and hemi-parkinson rats over 5 consecutive weeks. The electrophysiological dataset was constituted by the raw wideband signal, neuronal spikes, and local field potential (LFP) signal. The open-field test was done and recorded to evaluate the behavior variation of rats among the entire experimental cycle. We conducted technical validation of this dataset through sorting the spike data to form action potential waveforms and analyzing the spectral power of LFP data, then based on these findings a closed-loop DBS protocol was developed by the oscillation activity response of M1 LFP signal. Additionally, this protocol was applied to the hemi-parkinson rat for five consecutive days while simultaneously recording the electrophysiological data. This dataset is currently the only publicly available dataset that includes longitudinal closed-loop DBS recordings, which can be utilized to investigate variations of neuronal activity within the M1 following long-term closed-loop DBS, and explore additional reliable biomarkers.

Automatic sleep-wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine.

AIMS: Sleep disturbance is a prevalent nonmotor symptom of Parkinson's disease (PD), however, assessing sleep conditions is always time-consuming and labor-intensive. In this study, we performed an automatic sleep-wake state classification and early diagnosis of PD by analyzing the electrocorticography (ECoG) and electromyogram (EMG) signals of both normal and PD rats. METHODS: The study utilized ECoG power, EMG amplitude, and corticomuscular coherence values extracted from normal and PD rats to construct sleep-wake scoring models based on the support vector machine algorithm. Subsequently, we incorporated feature values that could act as diagnostic markers for PD and then retrained the models, which could encompass the identification of vigilance states and the diagnosis of PD. RESULTS: Features extracted from occipital ECoG signals were more suitable for constructing sleep-wake scoring models than those from frontal ECoG (average Cohen's kappa: 0.73 vs. 0.71). Additionally, after retraining, the new models demonstrated increased sensitivity to PD and accurately determined the sleep-wake states of rats (average Cohen's kappa: 0.79). CONCLUSION: This study accomplished the precise detection of substantia nigra lesions and the monitoring of sleep-wake states. The integration of circadian rhythm monitoring and disease state assessment has the potential to improve the efficacy of therapeutic strategies considerably.

Congenital dislocation of the knee complicated with bilateral hip dislocation: a case report and literature review.

BACKGROUND: Congenital dislocation of the knee is characterised by excessive knee extension or dislocation and anterior subluxation of the proximal tibia, and this disease can occur independently or coexist with different systemic syndromes. Nevertheless, significant controversy surrounds treating this disease when combined with hip dislocation. This paper presents a case of a 4-month-old patient diagnosed with bilateral hip dislocation combined with this disease. The study discusses the pathophysiology, diagnosis, and treatment methods and reviews relevant literature. CASE PRESENTATION: We reported a case of a 4-month-old female infant with congenital dislocation of the right knee joint, which presented as flexion deformity since birth. Due to limitations in local medical conditions, she did not receive proper and effective diagnosis and treatment. Although the flexion deformity of her right knee joint partially improved without treatment, it did not fully recover to normal. When she was 4 months old, she came to our hospital for consultation, and we found that she also had congenital dislocation of both hip joints and atrial septal defect. We performed staged treatment for her, with the first stage involving surgical intervention and plaster orthosis for her congenital dislocation of the right knee joint, and the second stage involving closed reduction and plaster fixation orthosis for her congenital hip joint dislocation. Currently, the overall treatment outcome is satisfactory, and she is still under follow-up observation. CONCLUSIONS: Early initiation of treatment is generally advised, as nonsurgical methods prove satisfactory for mild cases. However, surgical intervention should be considered in cases with severe stiffness, unresponsive outcomes to conservative treatment, persistent deformities, or diagnoses and treatments occurring beyond the first month after birth.

Knockout of miR396 genes increases seed size and yield in soybean.

Yield improvement has long been an important task for soybean breeding in the world in order to meet the increasing demand for food and animal feed. miR396 genes have been shown to negatively regulate grain size in rice, but whether miR396 family members may function in a similar manner in soybean is unknown. Here, we generated eight soybean mutants harboring different combinations of homozygous mutations in the six soybean miR396 genes through genome editing with clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated nuclease (Cas)12SF01 in the elite soybean cultivar Zhonghuang 302 (ZH302). Four triple mutants (mir396aci, mir396acd, mir396adf, and mir396cdf), two quadruple mutants (mir396abcd and mir396acfi), and two quintuple mutants (mir396abcdf and mir396bcdfi) were characterized. We found that plants of all the mir396 mutants produced larger seeds compared to ZH302 plants. Field tests showed that mir396adf and mir396cdf plants have significantly increased yield in growth zones with relatively high latitude which are suited for ZH302 and moderately increased yield in lower latitude. In contrast, mir396abcdf and mir396bcdfi plants have increased plant height and decreased yield in growth zones with relatively high latitude due to lodging issues, but they are suited for low latitude growth zones with increased yield without lodging problems. Taken together, our study demonstrated that loss-of-function of miR396 genes leads to significantly enlarged seed size and increased yield in soybean, providing valuable germplasms for breeding high-yield soybean.

Stark Effects of Rydberg Excitons in a Monolayer WSe2 P-N Junction.

The enhanced Coulomb interaction in two-dimensional semiconductors leads to tightly bound electron-hole pairs known as excitons. The large binding energy of excitons enables the formation of Rydberg excitons with high principal quantum numbers (n), analogous to Rydberg atoms. Rydberg excitons possess strong interactions among themselves as well as sensitive responses to external stimuli. Here, we probe Rydberg exciton resonances through photocurrent spectroscopy in a monolayer WSe2 p-n junction formed by a split-gate geometry. We show that an external in-plane electric field not only induces a large Stark shift of Rydberg excitons up to quantum principal number 3 but also mixes different orbitals and brightens otherwise dark states such as 3p and 3d. Our study provides an exciting platform for engineering Rydberg excitons for new quantum states and quantum sensing.

Lanthanide Complex for Single-Molecule Fluorescent in Situ Hybridization and Background-Free Imaging.

Traditional single-molecule fluorescence in situ hybridization (smFISH) methods for RNA detection often face sensitivity challenges due to the low fluorescence intensity of the probe. Also, short-lived autofluorescence complicates obtaining clear signals from tissue sections. In response, we have developed an smFISH probe using highly grafted lanthanide complexes to address both concentration quenching and autofluorescence background. Our approach involves an oligo PCR incorporating azide-dUTP, enabling conjugation with lanthanide complexes. This method has proven to be stable, convenient, and cost-effective. Notably, for the mRNA detection in SKBR3 cells, the lanthanide probe group exhibited 2.5 times higher luminescence intensity and detected 3 times more signal points in cells compared with the Cy3 group. Furthermore, we successfully applied the probe to image HER2 mRNA molecules in breast cancer FFPE tissue sections, achieving a 2.7-fold improvement in sensitivity compared to Cy3-based probes. These results emphasize the potential of time-resolved smFISH as a highly sensitive method for nucleic acid detection, free of background fluorescence interference.

HNF1A induces glioblastoma by upregulating EPS8 and activating PI3K/AKT signaling pathway.

Despite the exact biological role of HNF1 homolog A (HNF1A) in the regulatory mechanism of glioblastoma (GBM), the molecular mechanism, especially the downstream regulation as a transcription factor, remains to be further elucidated. Immunohistochemistry was used to detect the expression and clinical relevance of HNF1A in GBM patients. CCK8, TUNEL, and subcutaneous tumor formation in nude mice were used to evaluate the effect of HNF1A on GBM in vitro and in vivo. The correction between HNF1A and epidermal growth factor receptor pathway substrate 8 (EPS8) was illustrated by bioinformatics analysis and luciferase assay. Further mechanism was explored that the transcription factor HNF1A regulated the expression of EPS8 and downstream signaling pathways by directly binding to the promoter region of EPS8. Our comprehensive analysis of clinical samples in this study showed that upregulated expression of HNF1A was associated with poor survival in GBM patients. Further, we found that knockdown of HNF1A markedly suppressed the malignant phenotype of GBM cells in vivo and in vitro as well as promoted apoptosis of tumor cells, which was reversed by upregulation of HNF1A. Mechanistically, HNF1A could significantly activate PI3K/AKT signaling pathway by specifically binding to the promoter regions of EPS8. Moreover, overexpression of EPS8 was able to reverse the apoptosis of tumor cells caused by HNF1A knockdown, thereby exacerbating the GBM progression. Correctively, our study has clarified the explicit mechanism by which HNF1A promotes GBM malignancy and provides a new therapeutic target for further clinical application.

Prognostic value of inflammation-related biomarkers in patients with gastroenteropancreatic neuroendocrine neoplasms: A systematic review and meta-analysis.

Hematological indicators of chronic systemic inflammation are significant biomarkers for gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). We performed a systematic review and meta-analysis to assess the impact of certain factors on the overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of patients with GEP-NENs. These factors include the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), and C-reactive protein (CRP) levels. After searching the Medline, Embase, and Cochrane Library databases from January 1, 2000 to October 20, 2022 and the American Society of Clinical Oncology conference proceedings from January 1, 2017, hazard ratios (HRs) and 95% confidence intervals (CIs) were extracted. Subgroup analyses were conducted to identify the origins of heterogeneity and examine the impact of factor grouping. The effects of the cut-off values and sample size were assessed by meta-regression. The results revealed that higher NLRs, PLRs, and CRP levels were associated with shorter OS (HR = 2.09, 95% CI = 1.55-2.8; HR = 1.79, 95% CI = 1.40-2.28; and HR = 2.88, 95% CI = 2.09-3.95, respectively; all p < 0.001). Higher NLRs and lower LMRs were associated with shorter DFS (HR = 3.34, 95% CI = 2.11-5.29 and HR = 2.71, 95% CI = 2.27-3.24, respectively; both p < 0.001). Higher PLRs and CRP levels were correlated with shorter PFS (HR = 3.48, 95% CI = 1.34-9.03, p = 0.01 and HR = 3.14, 95% CI = 1.63-6.08, p = 0.001). As demonstrated in the research, hematological indicators of systemic inflammation are promising biomarkers for GEP-NEN assessment.

Comparison of therapeutic effects of endoscopic assisted different surgical approaches in hypertensive intracerebral hemorrhage: A retrospective cohort study.

We aimed to explore the therapeutic effects of endoscopically assisted surgical approaches for HICH. In this retrospective cohort study, we retrospectively analyzed the treatment status of 118 patients with HICH who underwent surgery for hematoma removal. Among them, 61 patients underwent endoscopically assisted hematoma removal surgery through the frontal lobe approach (frontal lobe group); 57 patients underwent endoscopic hematoma assisted via the temporal lobe approach (temporal lobe group). Treatment effects, cerebral hemodynamic status before and after treatment, postoperative prognosis at one month, and incidence of complications were compared between the 2 groups. We found that the total effective treatment rate in the frontal lobe group was higher than that in the temporal lobe group (P < .05). After surgery, the R during the contraction period of the common cerebral artery in both groups decreased compared to that before surgery, and the frontal lobe group was significantly lower than the temporal lobe group; the V and Q were higher than those before surgery, and the frontal lobe group was significantly higher than the temporal lobe group (P < .05). The prognosis of the frontal lobe group was better than that of the temporal lobe group (P < .05). Compared to the endoscopic-assisted temporal approach, the endoscopic-assisted frontal lobe approach for the treatment of HICH can improve cerebral hemodynamic status, enhance treatment efficacy, and improve prognosis.