Artificial neural network identified a 20-gene panel in predicting immunotherapy response and survival benefits after anti-PD1/PD-L1 treatment in glioblastoma patients.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are a promising immunotherapy approach, but glioblastoma clinical trials have not yielded satisfactory results. OBJECTIVE: To screen glioblastoma patients who may benefit from immunotherapy. METHODS: Eighty-one patients receiving anti-PD1/PD-L1 treatment from a large-scale clinical trial and 364 patients without immunotherapy from The Cancer Genome Atlas (TCGA) were included. Patients in the ICI-treated cohort were divided into responders and nonresponders according to overall survival (OS), and the most critical responder-relevant features were screened using random forest (RF). We constructed an artificial neural network (ANN) model and verified its predictive value with immunotherapy response and OS. RESULTS: We defined two groups of ICI-treated glioblastoma patients with large differences in survival benefits as nonresponders (OS ≤6 months, n = 18) and responders (OS ≥17 months, n = 8). No differentially mutated genes were observed between responders and nonresponders. We performed RF analysis to select the most critical responder-relevant features and developed an ANN with 20 input variables, five hidden neurons and one output neuron. Receiver operating characteristic analysis and the DeLong test demonstrated that the ANN had the best performance in predicting responders, with an AUC of 0.97. Survival analysis indicated that ANN-predicted responders had significantly better OS rates than nonresponders. CONCLUSION: The 20-gene panel developed by the ANN could be a promising biomarker for predicting immunotherapy response and prognostic benefits in ICI-treated GBM patients and may guide oncologists to accurately select potential responders for the preferential use of ICIs.

EgMADS3 directly regulates EgLPAAT to mediate medium-chain fatty acids (MCFA) anabolism in the mesocarp of oil palm.

KEY MESSAGE: EgMADS3, a pivotal transcription factor, positively regulates MCFA accumulation via binding to the EgLPAAT promoter, advancing lipid content in mesocarp of oil palm. Lipids function as the structural components of cell membranes, which serve as permeable barriers to the external environment of cells. The medium-chain fatty acid in the stored lipids of plants is an important renewable energy. Most research on MCFA production in plant lipid synthesis is based on biochemical methods, and the importance of transcriptional regulation in MCFA synthesis and its incorporation into TAGs needs further research. Oil palm is the most productive oil crop in the world and has the highest productivity among the main oil crops. In this study, the MADS transcription factor (EgMADS3) in the mesocarp of oil palm was characterized. Through the VIGS-virus induced gene silencing, it was determined that the potential target gene of EgMADS3 was related to the biosynthesis of medium-chain fatty acid (MCFA). Transient transformation in protoplasts and qRT-PCR analysis showed that EgMADS3 positively regulated the expression of EgLPAAT. The results of the yeast one-hybrid assays and EMSA indicated the interaction between EgMADS3 and EgLPAAT promoter. Through genetic transformation and fatty acid analysis, it is concluded that EgMADS3 directly regulates the mid-chain fatty acid synthesis pathway of the potential target gene EgLPAAT, thus promotes the accumulation of MCFA and improves the total lipid content. This study is innovative in the functional analysis of the MADS family transcription factor in the metabolism of medium-chain fatty acids (MCFA) of oil palm, provides a certain research basis for improving the metabolic pathway of chain fatty acids in oil palm, and improves the synthesis of MCFA in plants. Our results will provide a reference direction for further research on improving the oil quality through biotechnology of oil palm.

Automatic and real-time tissue sensing for autonomous intestinal anastomosis using hybrid MLP-DC-CNN classifier-based optical coherence tomography.

Anastomosis is a common and critical part of reconstructive procedures within gastrointestinal, urologic, and gynecologic surgery. The use of autonomous surgical robots such as the smart tissue autonomous robot (STAR) system demonstrates an improved efficiency and consistency of the laparoscopic small bowel anastomosis over the current da Vinci surgical system. However, the STAR workflow requires auxiliary manual monitoring during the suturing procedure to avoid missed or wrong stitches. To eliminate this monitoring task from the operators, we integrated an optical coherence tomography (OCT) fiber sensor with the suture tool and developed an automatic tissue classification algorithm for detecting missed or wrong stitches in real time. The classification results were updated and sent to the control loop of STAR robot in real time. The suture tool was guided to approach the object by a dual-camera system. If the tissue inside the tool jaw was inconsistent with the desired suture pattern, a warning message would be generated. The proposed hybrid multilayer perceptron dual-channel convolutional neural network (MLP-DC-CNN) classification platform can automatically classify eight different abdominal tissue types that require different suture strategies for anastomosis. In MLP, numerous handcrafted features (∼1955) were utilized including optical properties and morphological features of one-dimensional (1D) OCT A-line signals. In DC-CNN, intensity-based features and depth-resolved tissues' attenuation coefficients were fully exploited. A decision fusion technique was applied to leverage the information collected from both classifiers to further increase the accuracy. The algorithm was evaluated on 69,773 testing A-line data. The results showed that our model can classify the 1D OCT signals of small bowels in real time with an accuracy of 90.06%, a precision of 88.34%, and a sensitivity of 87.29%, respectively. The refresh rate of the displayed A-line signals was set as 300 Hz, the maximum sensing depth of the fiber was 3.6 mm, and the running time of the image processing algorithm was ∼1.56 s for 1,024 A-lines. The proposed fully automated tissue sensing model outperformed the single classifier of CNN, MLP, or SVM with optimized architectures, showing the complementarity of different feature sets and network architectures in classifying intestinal OCT A-line signals. It can potentially reduce the manual involvement of robotic laparoscopic surgery, which is a crucial step towards a fully autonomous STAR system.

Clinical roles of EGFR amplification in diffuse gliomas: a real-world study using the 2021 WHO classification of CNS tumors.

Background: The 2021 World Health Organization Classification of Central Nervous System Tumors updates glioma subtyping and grading system, and incorporates EGFR amplification (Amp) as one of diagnostic markers for glioblastoma (GBM). Purpose: This study aimed to describe the frequency, clinical value and molecular correlation of EGFR Amp in diffuse gliomas based on the latest classification. Methods: We reviewed glioma patients between 2011 and 2022 at our hospital, and included 187 adult glioma patients with available tumor tissue for detection of EGFR Amp and other 59 molecular markers of interest. Clinical, radiological and pathological data was analyzed based on the status of EGFR Amp in different glioma subtypes. Results: 163 gliomas were classified as adult-type diffuse gliomas, and the number of astrocytoma, oligodendroglioma and GBM was 41, 46, and 76. EGFR Amp was more common in IDH-wildtype diffuse gliomas (66.0%) and GBM (85.5%) than IDH-mutant diffuse gliomas (32.2%) and its subtypes (astrocytoma, 29.3%; oligodendroglioma, 34.8%). EGFR Amp did not stratify overall survival (OS) in IDH-mutant diffuse gliomas and astrocytoma, while was significantly associated with poorer OS in IDH-wildtype diffuse gliomas, histologic grade 2 and 3 IDH-wildtype diffuse astrocytic gliomas and GBM. Conclusion: Our study validated EGFR Amp as a diagnostic marker for GBM and still a useful predictor for shortened OS in this group.

Identification of TMZ resistance-associated histone post-translational modifications in glioblastoma using multi-omics data.

BACKGROUD: Glioblastoma multiforme (GBM) is among the most aggressive cancers, with current treatments limited in efficacy. A significant hurdle in the treatment of GBM is the resistance to the chemotherapeutic agent temozolomide (TMZ). The methylation status of the MGMT promoter has been implicated as a critical biomarker of response to TMZ. METHODS: To explore the mechanisms underlying resistance, we developed two TMZ-resistant GBM cell lines through a gradual increase in TMZ exposure. Transcriptome sequencing of TMZ-resistant cell lines revealed that alterations in histone post-translational modifications might be instrumental in conferring TMZ resistance. Subsequently, multi-omics analysis suggests a strong association between histone H3 lysine 9 acetylation (H3K9ac) levels and TMZ resistance. RESULTS: We observed a significant correlation between the expression of H3K9ac and MGMT, particularly in the unmethylated MGMT promoter samples. More importantly, our findings suggest that H3K9ac may enhance MGMT transcription by facilitating the recruitment of the SP1 transcription factor to the MGMT transcription factor binding site. Additionally, by analyzing single-cell transcriptomics data from matched primary and recurrent GBM tumors treated with TMZ, we modeled the molecular shifts occurring upon tumor recurrence. We also noted a reduction in tumor stem cell characteristics, accompanied by an increase in H3K9ac, SP1, and MGMT levels, underscoring the potential role of H3K9ac in tumor relapse following TMZ therapy. CONCLUSIONS: The increase in H3K9ac appears to enhance the recruitment of the transcription factor SP1 to its binding sites within the MGMT locus, consequently upregulating MGMT expression and driving TMZ resistance in GBM.

A prognostic model for overall survival in recurrent glioma patients treated with bevacizumab-containing therapy.

Predictive markers and prognostic models are useful for the individualization of cancer treatment. In this study, we sought to identify clinical and molecular factors to predict overall survival in recurrent glioma patients receiving bevacizumab-containing regimens. A cohort of 102 patients was retrospectively collected from June 2011 to January 2022 at our institution. A nomogram was generated by Cox regression and feature selection algorithms based on 19 clinicopathological and 60 molecular variables. The model's performance was internally evaluated by bootstrapping in terms of discrimination and calibration. The median overall survival from the initiation of bevacizumab administration to death or last follow-up was 11.6 months (95% CI: 9.2-13.8 months) for all 102 patients, 10.2 months (95% CI: 6.4-13.3 months) for 66 patients with grade 4 tumors, and 13.8 months (lower limit of 95% CI: 11.5 months) for 36 patients with tumors of grade lower or not available. In the final model, a lower WHO 2021 grade (Grade lower or not available vs. Grade 4, HR: 0.398, 95% CI: 0.223-0.708, p = 0.00172), having received adjuvant radiochemotherapy (Yes vs. No, HR: 0.488, 95% CI: 0.268-0.888, p = 0.0189), and wildtype EGFR (Wildtype vs. Altered, HR: 0.193, 95% CI: 0.0506-0.733, p = 0.0157; Not available vs. Altered, HR: 0.386, 95% CI: 0.184-0.810, p = 0.0118) were significantly associated with longer overall survival in multivariate Cox regression. The overall concordance index was 0.652 (95% CI: 0.566-0.714), and the areas under the time-dependent curves for 6-, 12-, and 18-month overall survival were 0.677 (95% CI: 0.516-0.816), 0.654 (95% CI: 0.470-0.823), and 0.675 (95% CI: 0.491-0.860), respectively. A prognostic model for overall survival in recurrent glioma patients treated with bevacizumab-based therapy was established and internally validated. It could serve as a reference tool for clinicians to assess the extent the patients may benefit from bevacizumab and stratify their treatment response.

Molecular Determinants of Neurocognitive Deficits in Glioma: Based on 2021 WHO Classification.

Cognitive impairment is a common feature among patients with diffuse glioma. The objective of the study is to investigate the relationship between preoperative cognitive function and clinical as well as molecular factors, firstly based on the new 2021 World Health Organization's updated classification of central nervous system tumors. A total of 110 diffuse glioma patients enrolled underwent preoperative cognitive assessments using the Mini-Mental State Examination and Montreal Cognitive Assessment. Clinical information was collected from medical records, and gene sequencing was performed to analyze the 18 most influenced genes. The differences in cognitive function between patients with and without glioblastoma were compared under both the 2016 and 2021 WHO classification of tumors of the central nervous system to assess their effect of differentiation on cognition. The study found that age, tumor location, and glioblastoma had significant differences in cognitive function. Several genetic alterations were significantly correlated with cognition. Especially, IDH, CIC, and ATRX are positively correlated with several cognitive domains, while most other genes are negatively correlated. For most focused genes, patients with a low number of genetic alterations tended to have better cognitive function. Our study suggested that, in addition to clinical characteristics such as age, histological type, and tumor location, molecular characteristics play a crucial role in cognitive function. Further research into the mechanisms by which tumors affect brain function is expected to enhance the quality of life for glioma patients. This study highlights the importance of considering both clinical and molecular factors in the management of glioma patients to improve cognitive outcomes.

Image quality assessment and feasibility of three-dimensional amide proton transfer-weighted imaging for hepatocellular carcinoma.

Background: With the continuous innovation of magnetic resonance imaging (MRI) hardware and software technology, amide proton transfer-weighted (APTw) imaging has been applied in liver cancer. However, to our knowledge, no study has evaluated the feasibility of a three-dimensional amide proton transfer-weighted (3D-APTw) imaging sequence for hepatocellular carcinoma (HCC). This study thus aimed to conduct an image quality assessment of 3D-APTw for HCC and to explore its feasibility. Methods: 3D-APTw MRI examinations were completed in 134 patients with clinically suspected HCC. According to the uniformity of APTw signal in the liver and within the lesion and the proportion of artifact and missing signal regions, APTw images were subjectively scored using a 5-point scale. The scanning success rate of liver APTw imaging was calculated as the ratio of the number of cases with a quality assurance measurement of more than 3 to the total number of HCC cases. The intra- and interobserver quality assurance measurements for APTw images were compared via the Kappa consistency test. Within the HCC cases with a minimum image quality threshold of 3 points, the APT values of HCC and the liver parenchyma, signal-to-noise ratio of APT-weighted images (SNRAPTw), and contrast-to-noise ratio of HCC (CNRHCC) were measured by two observers. The intra- and interobserver agreement was assessed using the intraclass correlation coefficient (ICC). The differences in APT values between HCC and liver parenchyma was determined using the Mann-Whitney test. Results: Sixty-six HCC cases with a quality assurance measurement of APTw imaging were included in the final analysis, and the calculated success rate was 70.21% (66/94). The subjective APT image quality scores of the two observers were consistent (3.66±1.18, 3.50±1.19, and 3.68±1.18), and no intergroup or intragroup statistical differences were found (P=0.594, and P=0.091), but the consistency of inter- and intraobserver was not as satisfactory (κ=0.594 and κ=0.580). The APT values in HCC lesion were significantly higher than those in liver parenchyma (2.73%±0.91% vs. 1.62%±0.55%; P<0.001). The APT values in HCC showed favorable intra- and interobserver consistency between the two observers (ICC =0.808 and ICC =0.853); the APT values in liver parenchyma, SNRAPTw, and CNRHCC values had moderate intraobserver consistency (ICC =0.578, ICC =0.568, and ICC =0.508) and interobserver consistency (ICC =0.599, ICC =0.199, and ICC =0.650). The coefficients of variation of the APTw values in the HCC lesion and in liver parenchyma were 33.4% and 34.4%, respectively. The SNRAPTw and CNRHCC were 30.75±18.74 and 3.56±3.19, with a coefficient of variation of 60.9% and 74.9%, respectively. Conclusions: Liver 3D-APTw imaging was preliminarily demonstrated to be clinically feasible for evaluating HCC.

Primary multiple endocrine insufficiency during immune checkpoint inhibitor treatment: A case report.

RATIONALE: Immunotherapy with immune checkpoint inhibitors (ICI) has shown promising activity against many tumor types. However, they can also induce a wide array of immune-related adverse events, ranging from mild to fatal. Primary 3 endocrine gland insufficiency during treatment with ICI has rarely been reported. PATIENT CONCERNS: We report the case of a 33-year-old man with Ewing sarcoma who was treated with toripalimab as a second-line treatment. Approximately 11 months after initiating treatment, the patient developed subclinical hypothyroidism, which was followed by adrenal insufficiency and hypogonadism 6 months later. Consequently, the decision was made to discontinue ICI therapy and initiate hormone replacement therapy to manage endocrine deficiencies. DIAGNOSES: Serum adrenocorticotropic hormone, thyroid stimulating hormone, and prolactin levels increased significantly, while cortisol, estradiol, and testosterone levels decreased (Table 1). The patient had negative findings on the pituitary MRI. INTERVENTION: As part of the management strategy, ICI therapy was ceased and hormone replacement therapy was commenced to address endocrine deficiencies. OUTCOMES: After hormone replacement therapy, his symptoms improved and follow-up examinations showed normalization of hormone levels. LESSONS: Clinicians should be aware of the potential of immune checkpoint inhibitor therapy to cause endocrine dysfunction. Prompt recognition and management of these adverse events are crucial for patient health and quality of life.

Use of patient-reported outcomes (PRO) data to complement exposure-response analysis in early clinical cancer drug development.

BACKGROUND: This proof-of-concept retrospective case study investigated whether patient-reported outcomes (PRO) instruments, designed to capture symptomatic adverse event data, could identity a known exposure-response (ER) relationship for safety characterized in an original FDA analysis of an approved anti-cancer agent. PRO instruments have been designed to uniquely quantify the tolerability aspects of exposure-associated symptomatic adverse events. We explored whether standard ER analyses of clinician-reported safety data for symptomatic adverse events could be complemented by ER analysis using PRO data that capture and quantify the tolerability aspects of these same symptomatic adverse events. METHODS: Exposure-associated adverse event data for diarrhea were analyzed in parallel in 120 patients enrolled in a clinical trial using physician reported Common Terminology Criteria for Adverse Events (CTCAE) and patient-reported symptomatic adverse event data captured by the National Cancer Institute's (NCI) PRO Common Terminology Criteria for Adverse Events (PRO-CTCAE) instrument. Comparative ER analyses of diarrhea were conducted using the same dataset. Results from the CTCAE and PRO-CTCAE ER analyses were assessed for consistency with the ER relationship for diarrhea established in the original NDA using a 750-patient dataset. The analysis was limited to the 120-patient subset with parallel CTCAE and PRO-CTCAE assessments. RESULTS: Within the same 120-patient dataset, ER analysis using dense, longitudinal PRO-CTCAE-derived data was sensitive to identify the known ER relationship for diarrhea, whereas the standard CTCAE based ER analysis was not. CONCLUSIONS: ER analysis using PRO assessed symptomatic adverse event data may be a sensitive tool to complement traditional ER analysis. Improved identification of relationships for safety, by including quantification of the tolerability aspect of symptomatic adverse events using PRO instruments, may be useful to improve the sensitivity of exposure response analysis to support early clinical trial dosage optimization strategies, where decision making occurs within limited small patient datasets.

Superwetting Stainless Steel Mesh Used for Both Immiscible Oil/Water and Surfactant-Stabilized Emulsion Separation.

The design and fabrication of advanced membrane materials for versatile oil/water separation are major challenges. In this work, a superwetting stainless steel mesh (SSM) modified with in situ-grown TiO2 was successfully prepared via one-pot hydrothermal synthesis at 180 °C for 24 h. The modified SSM was characterized by means of scanning electron microscopy, energy spectroscopy, and X-ray photoelectron spectroscopy analysis. The resultant SSM membrane was superhydrophilic/superoleophilic in air, superoleophobic underwater, with an oil contact angle (OCA) underwater of over 150°, and superhydrophobic under oil, with a water contact angle (WCA) as high as 158°. Facile separation of immiscible light oil/water and heavy oil/water was carried out using the prewetting method with water and oil, respectively. For both "oil-blocking" and "water-blocking" membranes, the separation efficiency was greater than 98%. Also, these SSMs wrapped in TiO2 nanoparticles broke emulsions well, separating oil-in-water and oil-in-water emulsions with an efficiency greater than 99.0%. The as-prepared superwetting materials provided a satisfactory solution for the complicated or versatile oil/water separation.

Magnetic resonance imaging findings of pulmonary sclerosing pneumocytoma: a case report and literature review.

Background: Pulmonary sclerosing pneumocytoma (PSP) is a rare lung tumor that is mostly isolated and commonly reported among middle-aged East Asian women. Recently, Immunohistochemistry (IHC) analysis has suggested that PSP is of primitive epithelial origin, most likely derived from type II alveolar air cells. Patients with PSP are generally asymptomatic and usually detected for other unrelated reasons during routine imaging. Several studies have already investigated the computed tomography (CT) features of PSP and their correlation with pathology. Magnetic resonance imaging (MRI) is a radiation-free imaging technique with important diagnostic value for specific pulmonary nodules. However, very few case reports or studies focus on the MRI findings of PSP. Case report: We reported a case of an asymptomatic 56-year-old female with a solitary, well-defined soft-tissue mass in the lower lobe of the left lung. The mass showed iso-to-high signal intensity (SI) than muscle on T1-weighted image (T1WI) and T2-weighted image (T2WI) and a much higher SI on fat-suppressed T2WI, diffusion-weighted image, and apparent diffusion coefficient image. Contrast-enhanced fat-suppressed T1WI revealed noticeable inhomogeneous progressive enhancement throughout the mass. The mass revealed early enhancement without a significant peak, followed by a plateau pattern on dynamic contrast-enhanced MRI images. The patient underwent left basal segmentectomy via thoracoscopic surgery. Histopathology and IHC results of the surgical specimen confirmed that it was a PSP. We concluded that the MRI findings of PSP might adequately reflect the different components within the tumor and aid clinicians in preoperative diagnosis and assessment. To the best of our knowledge, this is the most comprehensive case report on the MRI findings of PSP. Conclusion: The MRI findings of PSP correspond to its histopathological features. Here, we present a case of PSP with the most comprehensive MRI findings, emphasizing the importance of multiple-sequence MRI in diagnosing PSP.

Novel insight into histological and molecular astrocytoma, IDH-mutant, Grade 4 by the updated WHO classification of central nervous system tumors.

BACKGROUND: The latest fifth edition of the World Health Organization (WHO) classification of the central nervous system (CNS) tumors (WHO CNS 5 classification) released in 2021 defined astrocytoma, IDH-mutant, Grade 4. However, the understanding of this subtype is still limited. We conducted this study to describe the features of astrocytoma, IDH-mutant, Grade 4 and explored the similarities and differences between histological and molecular subtypes. METHODS: Patients who underwent surgery from January 2011 to January 2022, classified as astrocytoma, IDH-mutant, Grade 4 were included in this study. Clinical, radiological, histopathological, molecular pathological, and survival data were collected for analysis. RESULTS: Altogether 33 patients with astrocytoma, IDH-mutant, Grade 4 were selected, including 20 with histological and 13 with molecular WHO Grade 4 astrocytoma. Tumor enhancement, intratumoral-necrosis like presentation, larger peritumoral edema, and more explicit tumor margins were frequently observed in histological WHO Grade 4 astrocytoma. Additionally, molecular WHO Grade 4 astrocytoma showed a tendency for relatively longer overall survival, while a statistical significance was not reached (47 vs. 25 months, p = 0.22). TP53, CDK6, and PIK3CA alteration was commonly observed, while PIK3R1 (p = 0.033), Notch1 (p = 0.027), and Mycn (p = 0.027) alterations may affect the overall survival of molecular WHO Grade 4 astrocytomas. CONCLUSIONS: Our study scrutinized IDH-mutant, Grade 4 astrocytoma. Therefore, further classification should be considered as the prognosis varied between histological and molecular WHO Grade 4 astrocytomas. Notably, therapies aiming at PIK3R1, Notch 1, and Mycn may be beneficial.

Expanding the toolset of fluorescent covalent staining of biological samples by labeling carboxylate and phosphate groups.

Recently, fluorescent covalent staining methods have been developed for visualization of anatomical structures in cells and tissues. Coupled with expansion microscopy, these stains revealed various ultrastructural details. However, the covalently stainable chemical groups have been limited to amines, carbohydrates, and thiols. Here, we developed procedures for covalently labeling tissues for carboxylate and phosphate groups, utilizing carbodiimide crosslinker chemistry. In porcine kidney tissues, the carboxylate and phosphate stain provides 1.8-4.8-fold higher signal intensity than those from the three existing stains. In cancer cells, such stain allows 2-8-fold more accurate identification of nucleoli than the amine stain. In expansion microscopy samples, such stain reveals a variety of sub-cellular structures in tissues when combined with the amine stain. Such stain also allows imaging of lipid-based structures in cultured cells. With these advantages, this new covalent staining method further expands the toolset for fluorescent visualization of histology.

Preparation of Superhydrophilic/Underwater Superoleophobic and Superhydrophobic Stainless Steel Meshes Used for Oil/Water Separation.

Robust membrane materials with high efficiency have attracted extensive attention in oil/water separation. In this work, carbon particles via candle combustion were firstly adsorbed on the surface of stainless steel meshes (SSMs), which formed a thin hydrophobic coating, and a rough structure was then constructed through chemical vapor deposition and high temperature calcination, with the resultant SSM surface wrapped with uniform silica coating possessing the characteristic of superoleophobicity underwater. Scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), and X-ray powder diffraction (XRD) were used to characterize the modified SSMs. The prepared SSMs were superhydrophilic in air, and they had superoleophobicity underwater (157.4°). The separation efficiency of five oil/water mixtures was above 98.8%, and the separation flux was 46,300 L·m-2·h-1. After it was immersed in 1 mol/L NaOH, 1 mol/L HCl and 3.5 wt% NaCl for 24 h, respectively, the efficiency was still above 97.3%. Further immersion in the solution of dopamine and octadecylamine resulted in the transformation of superhydrophililc/superoleophobicity-underwater SSMs to superhydrophobic SSMs, and the resultant SSMs with reverse surface wettability was also used for the oil/water separation with good separation efficiency and separation flux.

Histological and molecular glioblastoma, IDH-wildtype: a real-world landscape using the 2021 WHO classification of central nervous system tumors.

Introduction: Glioblastoma (GBM), the most lethal primary brain malignancy, is divided into histological (hist-GBM) and molecular (mol-GBM) subtypes according to the 2021 World Health Organization classification of central nervous system tumors. This study aimed to characterize the clinical, radiological, molecular, and survival features of GBM under the current classification scheme and explore survival determinants. Methods: We re-examined the genetic alterations of IDH-wildtype diffuse gliomas at our institute from 2011 to 2022, and enrolled GBMs for analysis after re-classification. Univariable and multivariable analyses were used to identify survival determinants. Results: Among 209 IDH-wildtype gliomas, 191 were GBMs, including 146 hist-GBMs (76%) and 45 mol-GBMs (24%). Patients with mol-GBMs were younger, less likely to develop preoperative motor dysfunction, and more likely to develop epilepsy than hist-GBMs. Mol-GBMs exhibited lower radiographic incidences of contrast enhancement and intratumoral necrosis. Common molecular features included copy-number changes in chromosomes 1, 7, 9, 10, and 19, as well as alterations in EGFR, TERT, CDKN2A/B, and PTEN, with distinct patterns observed between the two subtypes. The median overall survival (mOS) of GMB was 12.6 months. Mol-GBMs had a higher mOS than hist-GBMs, although not statistically significant (15.6 vs. 11.4 months, p=0.17). Older age, male sex, tumor involvement of deep brain structure or functional area, and genetic alterations in CDK4, CDK6, CIC, FGFR3, KMT5B, and MYB were predictors for a worse prognosis, while MGMT promoter methylation, maximal tumor resection, and treatment based on the Stupp protocol were predictive for better survival. Conclusion: The definition of GBM and its clinical, radiological, molecular, and prognostic characteristics have been altered under the current classification.

Rebalancing liver-infiltrating CCR3+ and CD206+ monocytes improves diet-induced NAFLD.

Melatonin has been reported to improve nonalcoholic fatty liver disease (NAFLD), and exploring the underlying mechanisms will be beneficial for better treatment of NAFLD. Choline-deficient high-fat diet (CDHFD)- and methionine/choline-deficient diet (MCD)-fed mice with melatonin intervention exhibit significantly decreased liver steatosis, lobular inflammation, and focal liver necrosis. Single-cell RNA sequencing reveals that melatonin selectively inhibits pro-inflammatory CCR3+ monocyte-derived macrophages (MoMFs) and upregulates anti-inflammatory CD206+ MoMFs in NAFLD mice. Liver-infiltrating CCR3+CD14+ MoMFs are also significantly increased in patients with NAFLD. Mechanistically, melatonin receptor-independent BTG2-ATF4 signaling plays a role in the regulation of CCR3+ MoMF endoplasmic reticulum stress, survival, and inflammation. In contrast, melatonin upregulates CD206+ MoMF survival and polarization via MT1/2 receptors. Melatonin stimulation also regulates human CCR3+ MoMF and CD206+ MoMF survival and inflammation in vitro. Furthermore, CCR3 depletion antibody monotherapy inhibits liver inflammation and improves NAFLD in mice. Thus, therapies targeting CCR3+ MoMFs may have potential benefits in NAFLD treatment.

New scaffolds for type II JAK2 inhibitors overcome the acquired G993A resistance mutation.

Recurrent JAK2 alterations are observed in myeloproliferative neoplasms, B-cell acute lymphoblastic leukemia, and other hematologic malignancies. Currently available type I JAK2 inhibitors have limited activity in these diseases. Preclinical data support the improved efficacy of type II JAK2 inhibitors, which lock the kinase in the inactive conformation. By screening small molecule libraries, we identified a lead compound with JAK2 selectivity. We highlight analogs with on-target biochemical and cellular activity and demonstrate in vivo activity using a mouse model of polycythemia vera. We present a co-crystal structure that confirms the type II binding mode of our compounds with the "DFG-out" conformation of the JAK2 activation loop. Finally, we identify a JAK2 G993A mutation that confers resistance to the type II JAK2 inhibitor CHZ868 but not to our analogs. These data provide a template for identifying novel type II kinase inhibitors and inform further development of agents targeting JAK2 that overcome resistance.

An online survival predictor in glioma patients using machine learning based on WHO CNS5 data.

Background: The World Health Organization (WHO) CNS5 classification system highlights the significance of molecular biomarkers in providing meaningful prognostic and therapeutic information for gliomas. However, predicting individual patient survival remains challenging due to the lack of integrated quantitative assessment tools. In this study, we aimed to design a WHO CNS5-related risk signature to predict the overall survival (OS) rate of glioma patients using machine learning algorithms. Methods: We extracted data from patients who underwent an operation for histopathologically confirmed glioma from our hospital database (2011-2022) and split them into a training and hold-out test set in a 7/3 ratio. We used biological markers related to WHO CNS5, clinical data (age, sex, and WHO grade), and prognosis follow-up information to identify prognostic factors and construct a predictive dynamic nomograph to predict the survival rate of glioma patients using 4 kinds machine learning algorithms (RF, SVM, XGB, and GLM). Results: A total of 198 patients with complete WHO5 molecular data and follow-up information were included in the study. The median OS time of all patients was 29.77 [95% confidence interval (CI): 21.19-38.34] months. Age, FGFR2, IDH1, CDK4, CDK6, KIT, and CDKN2A were considered vital indicators related to the prognosis and OS time of glioma. To better predict the prognosis of glioma patients, we constructed a WHO5-related risk signature and nomogram. The AUC values of the ROC curves of the nomogram for predicting the 1, 3, and 5-year OS were 0.849, 0.835, and 0.821 in training set, and, 0.844, 0.943, and 0.959 in validation set. The calibration plot confirmed the reliability of the nomogram, and the c-index was 0.742 in training set and 0.775 in validation set. Additionally, our nomogram showed a superior net benefit across a broader scale of threshold probabilities in decision curve analysis. Therefore, we selected it as the backend for the online survival prediction tool (Glioma Survival Calculator, https://who5pumch.shinyapps.io/DynNomapp/), which can calculate the survival probability for a specific time of the patients. Conclusion: An online prognosis predictor based on WHO5-related biomarkers was constructed. This therapeutically promising tool may increase the precision of forecast therapy outcomes and assess prognosis.

BTG2 acts as an inducer of muscle stem cell senescence.

BACKGROUND: Muscle aging is associated with muscle stem cell (MuSC) senescence, a process of whose DNA damage accumulation is considered as one of the leading causes. BTG2 had been identified as a mediator of genotoxic and cellular stress signaling pathways, however, its role in senescence of stem cells, including MuSC, remains unknown. METHOD: We first compared MuSCs isolated from young and old mice to evaluate our in vitro model of natural senescence. CCK8 and EdU assays were utilized to assess the proliferation capacity of the MuSCs. Cellular senescence was further assessed at biochemical levels by SA-ß-Gal and γHA2.X staining, and at molecular levels by quantifying the expression of senescence-associated genes. Next, by performing genetic analysis, we identified Btg2 as a potential regulator of MuSC senescence, which was experimentally validated by Btg2 overexpression and knockdown in primary MuSCs. Lastly, we extended our research to humans by analyzing the potential links between BTG2 and muscle function decline in aging. RESULTS: BTG2 is highly expressed in MuSCs from elder mice showing senescent phenotypes. Overexpression and knockdown of Btg2 stimulates and prevents MuSCs senescence, respectively. In humans, high level of BTG2 is associated with low muscle mass in aging, and is a risk factor of aging-related diseases, such as diabetic retinopathy and HDL cholesterol. CONCLUSION: Our work demonstrates BTG2 as a regulator of MuSC senescence and may serve as an intervention target for muscle aging.