Prognostic value of body composition in patients with digestive tract cancers: A prospective cohort study of 8,267 adults from China.

BACKGROUND & AIMS: The characterization and prognostic value of body composition parameter/phenotype based on computed tomography (CT) in patients with digestive tract cancers remain incomplete. This study aimed to investigate the relationship between parameter/phenotype and clinical outcomes in patients with digestive tract cancers. METHODS: In this prospective cohort study, 8267 patients with digestive tract cancers were assessed using CT scans to determine body composition. Body composition data, including areas of skeletal muscle (SM), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT), were collected at the third lumbar level on CT images obtained within 30 days before surgery. Body composition phenotypes (sarcopenia, cancer cachexia, sarcopenic obesity) were determined based on SM, SAT, and VAT areas. The primary endpoint was overall survival, obtained from electronic medical records and telephone follow-up surveys. Kaplan-Meier and log-rank analyses were employed to compare unadjusted survival, while multivariate survival analyses were conducted using a proportional hazards model adjusted for age, gender, and cancer-node-metastasis (TNM) stages. RESULTS: Adjusted hazard ratios (HRs) for all-cause mortality were calculated for the second (Q2), third (Q3), and fourth (Q4) quantiles relative to the first quantile (Q1) for SM areas, revealing adjusted summary HRs of 0.575 (95% CI, 0.361-0.916), 0.419 (95% CI, 0.241-0.729), and 0.384 (95% CI, 0.203-0.726), respectively. Sarcopenia-adjusted summary HRs were 1.795 (95% CI: 1.012-3.181) for male patients and 1.925 (95% CI: 1.065-3.478) for female patients. Cancer cachexia-adjusted summary HRs were 1.542 (95% CI: 1.023-2.324) for male patients and 1.569 (95% CI: 0.820-3.001) for female patients. Sarcopenic obesity-adjusted summary HRs were 1.122 (95% CI: 0.759-1.657) for male patients and 1.303 (95% CI: 0.623-2.725) for female patients. Subgroup analyses indicated varying prognostic values of body composition parameter/phenotype among different cancer types. CONCLUSIONS: Our findings suggest a large SM area is a favorable prognostic indicator, while cancer cachexia and sarcopenia signify poor prognosis in patients with digestive tract cancers. These findings have important implications for the personalized preoperative assessment of body composition in patients with digestive tract cancers.

Dissecting microenvironment in cystadenomas and hepatic cysts based on single nucleus RNA-sequencing data.

Hepatic cystadenoma is a rare disease, accounting for about 5% of all cystic lesions, with a high tendency of malignant transformation. The preoperative diagnosis of cystadenoma is difficult, and some cystadenomas are easily misdiagnosed as hepatic cysts at first. Hepatic cyst is a relatively common liver disease, most of which are benign, but large hepatic cysts can lead to pressure on the bile duct, resulting in abnormal liver function. To better understand the difference between the microenvironment of cystadenomas and hepatic cysts, we performed single-nuclei RNA-sequencing on cystadenoma and hepatic cysts samples. In addition, we performed spatial transcriptome sequencing of hepatic cysts. Based on nucleus RNA-sequencing data, a total of seven major cell types were identified. Here we described the tumor microenvironment of cystadenomas and hepatic cysts, particularly the transcriptome signatures and regulators of immune cells and stromal cells. By inferring copy number variation, it was found that the malignant degree of hepatic stellate cells in cystadenoma was higher. Pseudotime trajectory analysis demonstrated dynamic transformation of hepatocytes in hepatic cysts and cystadenomas. Cystadenomas had higher immune infiltration than hepatic cysts, and T cells had a more complex regulatory mechanism in cystadenomas than hepatic cysts. Immunohistochemistry confirms a cystadenoma-specific T-cell immunoregulatory mechanism. These results provided a single-cell atlas of cystadenomas and hepatic cyst, revealed a more complex microenvironment in cystadenomas than in hepatic cysts, and provided new perspective for the molecular mechanisms of cystadenomas and hepatic cyst.

Poly-l-lysine modified MOF nanoparticles with pH/ROS sensitive CIP release and CUR triggered photodynamic therapy against drug-resistant bacterial infection.

The challenge of drug resistance in bacteria caused by the over use of biotics is increasing during the therapy process, which has attracted great attentions of the clinicians and scientists around the world. Recently, photodynamic therapy (PDT) triggered by photosensitizer (PS) has become a promising treatment method because of its high efficacy, easy operation, and low side effect. Herein, the poly-l-lysine (PLL) modified metal-organic framework (MOF) nanoparticles, ZIF/PLL-CIP/CUR, were synthesized to allow both reactive oxygen species (ROS) responsive drug release and photodynamic effect for synergistic therapy against drug resistant bacterial infections. The PLL was modified on the shell of the zeolite imidazole framework (ZIF) by the ROS-responsive thioketal linker for controllable CIP release. CUR were encapsulated in ZIF as the photosensitizer for blue light mediated photodynamic effect to produce singlet oxygen (1O2) and superoxide anion radical (O2-) for efficient inhibition towards methicillin-resistant Staphylococcus aureus (MRSA). The charge conversion from negative charge (-4.6 mV) to positive charge (2.6 mV) was observed at pH 7.4 and pH 5.5, and 70.9 % CIP was found released at pH 5.5 in the presence of H2O2, which suggests the good biosafety at physiological pH and ROS-responsive drug release of the as-prepared nanoparticle in the bacterial microenvironment. The as-prepared nanoparticles could effectively kill MRSA and disrupt bacterial biofilm by combination of chemo- and photodynamic therapy. In mice model, the as-prepared nanoparticles exhibited excellent biosafety and synergistic effect with 98.81 % healing rate in treatment of MRSA infection, which is considered as a promising candidate in combating drug resistant bacterial infection.

Inclusion complex of quercetin with sulfobutylether ß-cyclodextrin: preparation, characterization, antioxidant and antibacterial activities and the inclusion mechanism.

Quercetin (QCT) has a variety of pharmacological effects, such as antioxidant, antibacterial, anticancer, anticardiovascular and antiaging effects. However, its poor water solubility, stability and bioavailability limit its applications. The special structure of cyclodextrins and their derivatives with a hydrophobic inner cavity and hydrophilic outer wall can load a variety of hydrophobic drugs of a suitable size and shape, thereby improving the stability and solubility of these molecules. In this study, an inclusion complex of quercetin and sulfobutylether-ß-cyclodextrin was prepared. It was characterized via FT-IR, UV, 1H NMR, XRD, DSC, and SEM analysis, which revealed the successful formation of the inclusion complex. In vitro biological activity estimations were carried out and the results indicated that the inclusion complex displayed higher antioxidative and antibacterial properties compared with free QCT. In addition, the mechanisms of inclusion were explored using 1H NMR analysis and docking calculations, thus providing a theoretical basis for obtaining an inclusion complex.

Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: a two-center study.

Background: Diffuse midline gliomas (DMG) are aggressive pediatric brain tumors that are diagnosed and monitored through MRI. We developed an automatic pipeline to segment subregions of DMG and select radiomic features that predict patient overall survival (OS). Methods: We acquired diagnostic and post-radiation therapy (RT) multisequence MRI (T1, T1ce, T2, T2 FLAIR) and manual segmentations from two centers of 53 (internal cohort) and 16 (external cohort) DMG patients. We pretrained a deep learning model on a public adult brain tumor dataset, and finetuned it to automatically segment tumor core (TC) and whole tumor (WT) volumes. PyRadiomics and sequential feature selection were used for feature extraction and selection based on the segmented volumes. Two machine learning models were trained on our internal cohort to predict patient 1-year survival from diagnosis. One model used only diagnostic tumor features and the other used both diagnostic and post-RT features. Results: For segmentation, Dice score (mean [median]±SD) was 0.91 (0.94)±0.12 and 0.74 (0.83)±0.32 for TC, and 0.88 (0.91)±0.07 and 0.86 (0.89)±0.06 for WT for internal and external cohorts, respectively. For OS prediction, accuracy was 77% and 81% at time of diagnosis, and 85% and 78% post-RT for internal and external cohorts, respectively. Homogeneous WT intensity in baseline T2 FLAIR and larger post-RT TC/WT volume ratio indicate shorter OS. Conclusions: Machine learning analysis of MRI radiomics has potential to accurately and non-invasively predict which pediatric patients with DMG will survive less than one year from the time of diagnosis to provide patient stratification and guide therapy.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn).

Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input magnetic resonance imaging (MRI) modalities: T1-weighted images with and without contrast enhancement, T2-weighted images, and FLAIR images. However, some sequences are often missing in clinical practice due to time constraints or image artifacts, such as patient motion. Consequently, the ability to substitute missing modalities and gain segmentation performance is highly desirable and necessary for the broader adoption of these algorithms in the clinical routine. In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023. The primary objective of this challenge is to evaluate image synthesis methods that can realistically generate missing MRI modalities when multiple available images are provided. The ultimate aim is to facilitate automated brain tumor segmentation pipelines. The image dataset used in the benchmark is diverse and multi-modal, created through collaboration with various hospitals and research institutions.

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.

Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on multiparametric MRI (mpMRI) for diagnosis, treatment planning, and longitudinal treatment monitoring; yet automated, objective, and quantitative tools for non-invasive assessment of meningiomas on mpMRI are lacking. The BraTS meningioma 2023 challenge will provide a community standard and benchmark for state-of-the-art automated intracranial meningioma segmentation models based on the largest expert annotated multilabel meningioma mpMRI dataset to date. Challenge competitors will develop automated segmentation models to predict three distinct meningioma sub-regions on MRI including enhancing tumor, non-enhancing tumor core, and surrounding nonenhancing T2/FLAIR hyperintensity. Models will be evaluated on separate validation and held-out test datasets using standardized metrics utilized across the BraTS 2023 series of challenges including the Dice similarity coefficient and Hausdorff distance. The models developed during the course of this challenge will aid in incorporation of automated meningioma MRI segmentation into clinical practice, which will ultimately improve care of patients with meningioma.

A single-cell transcriptional landscape of immune cells shows disease-specific changes of T cell and macrophage populations in human achalasia.

Achalasia is a rare motility disorder of the esophagus caused by the gradual degeneration of myenteric neurons. Immune-mediated ganglionitis has been proposed to underlie the loss of myenteric neurons. Here, we measure the immune cell transcriptional profile of paired lower esophageal sphincter (LES) tissue and blood samples in achalasia and controls using single-cell RNA sequencing (scRNA-seq). In achalasia, we identify a pattern of expanded immune cells and a specific transcriptional phenotype, especially in LES tissue. We show C1QC+ macrophages and tissue-resident memory T cells (TRM), especially ZNF683+ CD8+ TRM and XCL1+ CD4+ TRM, are significantly expanded and localized surrounding the myenteric plexus in the LES tissue of achalasia. C1QC+ macrophages are transcriptionally similar to microglia of the central nervous system and have a neurodegenerative dysfunctional phenotype in achalasia. TRM also expresses transcripts of dysregulated immune responses in achalasia. Moreover, inflammation increases with disease progression since immune cells are more activated in type I compared with type II achalasia. Thus, we profile the immune cell transcriptional landscape and identify C1QC+ macrophages and TRM as disease-associated immune cell subsets in achalasia.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa).

Gliomas are the most common type of primary brain tumors. Although gliomas are relatively rare, they are among the deadliest types of cancer, with a survival rate of less than 2 years after diagnosis. Gliomas are challenging to diagnose, hard to treat and inherently resistant to conventional therapy. Years of extensive research to improve diagnosis and treatment of gliomas have decreased mortality rates across the Global North, while chances of survival among individuals in low- and middle-income countries (LMICs) remain unchanged and are significantly worse in Sub-Saharan Africa (SSA) populations. Long-term survival with glioma is associated with the identification of appropriate pathological features on brain MRI and confirmation by histopathology. Since 2012, the Brain Tumor Segmentation (BraTS) Challenge have evaluated state-of-the-art machine learning methods to detect, characterize, and classify gliomas. However, it is unclear if the state-of-the-art methods can be widely implemented in SSA given the extensive use of lower-quality MRI technology, which produces poor image contrast and resolution and more importantly, the propensity for late presentation of disease at advanced stages as well as the unique characteristics of gliomas in SSA (i.e., suspected higher rates of gliomatosis cerebri). Thus, the BraTS-Africa Challenge provides a unique opportunity to include brain MRI glioma cases from SSA in global efforts through the BraTS Challenge to develop and evaluate computer-aided-diagnostic (CAD) methods for the detection and characterization of glioma in resource-limited settings, where the potential for CAD tools to transform healthcare are more likely.

Responsive Microneedles as a New Platform for Precision Immunotherapy.

Microneedles are a well-known transdermal or transdermal drug delivery system. Different from intramuscular injection, intravenous injection, etc., the microneedle delivery system provides unique characteristics for immunotherapy administration. Microneedles can deliver immunotherapeutic agents to the epidermis and dermis, where immune cells are abundant, unlike conventional vaccine systems. Furthermore, microneedle devices can be designed to respond to certain endogenous or exogenous stimuli including pH, reactive oxygen species (ROS), enzyme, light, temperature, or mechanical force, thereby allowing controlled release of active compounds in the epidermis and dermis. In this way, multifunctional or stimuli-responsive microneedles for immunotherapy could enhance the efficacy of immune responses to prevent or mitigate disease progression and lessen systemic adverse effects on healthy tissues and organs. Since microneedles are a promising drug delivery system for accurate delivery and controlled drug release, this review focuses on the progress of using reactive microneedles for immunotherapy, especially for tumors. Limitations of current microneedle system are summarized, and the controllable administration and targeting of reactive microneedle systems are examined.

Salvage peroral endoscopic myotomy is a promising treatment for achalasia after myotomy failure.

BACKGROUND AND AIMS: Reintervention modalities after myotomy failure in achalasia patients have yet to be established. The efficacy and safety of salvage peroral endoscopic myotomy (POEM) for treatment of achalasia after myotomy failure were evaluated in the study. METHODS: Between August 2011 and August 2021 at the Endoscopy Center of Zhongshan Hospital, 219 achalasia patients who had previously undergone a myotomy underwent a salvage POEM and were thus retrospectively enrolled in this study. After propensity score matching (PSM), operation-related parameters were compared between the salvage POEM group and the naïve POEM group. Subgroup analysis was performed between patients with previous Heller myotomy (HM) and patients with previous POEM. RESULTS: With similar baseline characteristics between both groups after PSM, the salvage POEM group presented with shorter tunnel length (11.8 ± 2.2 cm vs 12.8 ± .9 cm, P < .0001) and myotomy length (9.8 ± 2.0 cm vs 10.4 ± 1.0 cm, P < .0001) than the naïve POEM group. No significant differences were found in procedure-related adverse events between patients of salvage POEM and naïve POEM. The primary outcome of treatment success occurred in 175 of 193 patients (90.7%) in the salvage POEM group versus 362 of 374 patients (96.8%) in the naïve POEM group (P = .0046). At a 2- and 5-year follow-up, significantly higher rates of clinical failures were observed in the previous HM subgroup than in the previous POEM subgroup (P = .0433 and P = .0230, respectively). CONCLUSIONS: Salvage POEM after a previous myotomy failure, especially after a POEM failure, is a promising treatment option because it has a durable clinical relief rate.

Persistent Degradation of HER2 Protein by Hybrid nanoPROTAC for Programmed Cell Death.

Proteolysis-targeting chimera (PROTAC) has emerged as a promising strategy for degrading proteins of interest. Peptide-based PROTACs offer several advantages over small-molecule-based PROTACs, such as high specificity, low toxicity, and large protein-protein interaction surfaces. However, peptide-based PROTACs have several intrinsic shortcomings that strongly limit their application including poor cell permeability and low stability and potency. Herein, we designed a nanosized hybrid PROTAC (GNCTACs) to target and degrade human epidermal growth factor receptor 2 (HER2) in tumor cells. Gold nanoclusters (GNCs) were utilized to connect HER2-targeting peptides and cereblon (CRBN)-targeting ligands. GNCTACs could overcome the intrinsic barriers of peptide-based PROTACs, efficiently delivering HER2-targeting peptides in the cytoplasm and protecting them from degradation. Furthermore, a fasting-mimicking diet was applied to enhance the cellular uptake and proteasome activity. Consequently, more than 95% of HER2 in SKBR3 cells was degraded by GNCTACs, and the degradation lasted for at least 72 h, showing a catalytic-like reaction.

Single-cell transcriptomic analysis deciphers key transitional signatures associated with oncogenic evolution in human intramucosal oesophageal squamous cell carcinoma.

BACKGROUND AND AIMS: The early diagnosis and intervention of oesophageal squamous cell carcinoma (ESCC) are particularly important because of the lack of effective therapies and poor prognosis. Comprehensive research on early ESCC at the single-cell level is rare due to the need for fresh and high-quality specimens obtained from ESD. This study aims to systematically describe the cellular atlas of human intramucosal ESCC. METHODS: Five paired samples of intramucosal ESCC, para-ESCC oesophageal tissues from endoscopically resected specimens and peripheral blood mononuclear cells were adopted for scRNA-seq analysis. Computational pipeline scMetabolism was applied to quantify the metabolic diversity of single cells. RESULTS: A total of 164 715 cells were profiled. Epithelial cells exhibited high intra-tumoural heterogeneity and two evolutionary trajectories during ESCC tumorigenesis initiated from proliferative cells, and then through an intermediate state, to two different terminal states of normally differentiated epithelial cells or malignant cells, respectively. The abundance of CD8+ TEX s, Tregs and PD1+ CD4+ T cells suggested an exhausted and suppressive immune microenvironment. Several genes in immune cells, such as CXCL13, CXCR5 and PADI4, were identified as new biomarkers for poor prognosis. A new subcluster of malignant cells associated with metastasis and angiogenesis that appeared at an early stage compared with progressive ESCC was also identified in this study. Intercellular interaction analysis based on ligand-receptor pairs revealed the subcluster of malignant cells interacting with CAFs via the MDK-NCL pathway, which was verified by cell proliferation assay and IHC. This indicates that the interaction may be an important hallmark in the early change of tumour microenvironment and serves as a sign of CAF activation to stimulate downstream pathways for facilitating tumour invasion. CONCLUSION: This study demonstrates the changes of cell subsets and transcriptional levels in human intramucosal ESCC, which may provide unique insights into the development of novel biomarkers and potential intervention strategies.

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark.

PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the operation through context-sensitive warnings and semi-autonomous robotic assistance or improve training of surgeons via data-driven feedback. In surgical workflow analysis up to 91% average precision has been reported for phase recognition on an open data single-center video dataset. In this work we investigated the generalizability of phase recognition algorithms in a multicenter setting including more difficult recognition tasks such as surgical action and surgical skill. METHODS: To achieve this goal, a dataset with 33 laparoscopic cholecystectomy videos from three surgical centers with a total operation time of 22 h was created. Labels included framewise annotation of seven surgical phases with 250 phase transitions, 5514 occurences of four surgical actions, 6980 occurences of 21 surgical instruments from seven instrument categories and 495 skill classifications in five skill dimensions. The dataset was used in the 2019 international Endoscopic Vision challenge, sub-challenge for surgical workflow and skill analysis. Here, 12 research teams trained and submitted their machine learning algorithms for recognition of phase, action, instrument and/or skill assessment. RESULTS: F1-scores were achieved for phase recognition between 23.9% and 67.7% (n = 9 teams), for instrument presence detection between 38.5% and 63.8% (n = 8 teams), but for action recognition only between 21.8% and 23.3% (n = 5 teams). The average absolute error for skill assessment was 0.78 (n = 1 team). CONCLUSION: Surgical workflow and skill analysis are promising technologies to support the surgical team, but there is still room for improvement, as shown by our comparison of machine learning algorithms. This novel HeiChole benchmark can be used for comparable evaluation and validation of future work. In future studies, it is of utmost importance to create more open, high-quality datasets in order to allow the development of artificial intelligence and cognitive robotics in surgery.

Abdominal fat and muscle distributions in different stages of colorectal cancer.

BACKGROUND: The purpose of this study is to explore the difference of abdominal fat and muscle composition, especially subcutaneous and visceral adipose tissue, in different stages of colorectal cancer (CRC). MATERIALS AND METHODS: Patients were divided into 4 groups: healthy controls (patients without colorectal polyp), polyp group (patients with colorectal polyp), cancer group (CRC patients without cachexia), and cachexia group (CRC patients with cachexia). Skeletal muscle (SM), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and intermuscular adipose tissue (IMAT) were assessed at the third lumbar level on computed tomography images obtained within 30 days before colonoscopy or surgery. One-way ANOVA and linear regression were used to analyze the difference of abdominal fat and muscle composition in different stages of CRC. RESULTS: A total of 1513 patients were divided into healthy controls, polyp group, cancer group, and cachexia group, respectively. In the development of CRC from normal mucosa to polyp and cancer, the VAT area of the polyp group was significantly higher than that of the healthy controls both in male (156.32 ± 69.71 cm2 vs. 141.97 ± 79.40 cm2, P = 0.014) and female patients (108.69 ± 53.95 cm2 vs. 96.28 ± 46.70 cm2, P = 0.044). However, no significant differences were observed of SAT area between polyp group and healthy controls in both sexes. SAT area decreased significantly in the male cancer group compared with the polyp group (111.16 ± 46.98 cm2 vs. 126.40 ± 43.52 cm2, P = 0.001), while no such change was observed in female patients. When compared with healthy controls, the SM, IMAT, SAT, and VAT areas of cachexia group was significantly decreased by 9.25 cm2 (95% CI: 5.39-13.11 cm2, P < 0.001), 1.93 cm2 (95% CI: 0.54-3.32 cm2, P = 0.001), 28.84 cm2 (95% CI: 17.84-39.83 cm2, P < 0.001), and 31.31 cm2 (95% CI: 18.12-44.51 cm2, P < 0.001) after adjusting for age and gender. CONCLUSION: Abdominal fat and muscle composition, especially SAT and VAT, was differently distributed in different stages of CRC. It is necessary to pay attention to the different roles of subcutaneous and visceral adipose tissue in the development of CRC.

Highly efficient removal of Se(IV) using reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO): selenium removal mechanism.

Se(IV) removal using nanoscale zero-valent iron (nZVI) has been extensively studied. Still, the synergistic removal of Se(IV) by reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) has not been reported. In this study, nZVI/rGO was successfully synthesized for Se(IV) removal from wastewater. The effects of different environmental conditions (load ratio, dosage, initial pH) on Se(IV) removal by nZVI/rGO were investigated. When the load ratio is 10%, the dosage is 0.3 g/L, the initial pH is 3, and the removal rate is 99%. The adsorption isotherm and kinetics accorded with the Langmuir isotherm and first-order kinetics models (R2 > 0.99). The fitted maximum adsorption capacity reached up to 173.53 mg/g. NZVI/rGo and Se(IV) is a spontaneous endothermic reaction (△G < 0, △H > 0) and is characterized by EDS, XRD, and XPS before and after the reaction, to further clarify the reaction mechanism. The XPS narrow spectrum analysis suggested that Se(IV) was reduced to elemental selenium (Se(0)), while the intermediate Fe(II) was oxidized to form hydroxide precipitation. Therefore, nZVI/rGO was favored for Se-contaminated wastewater remediation.

Midazolam exhibits antitumour and enhances the efficiency of Anti-PD-1 immunotherapy in hepatocellular carcinoma.

BACKGROUND: Midazolam (MDZ) is an anaesthetic that is widely used for anxiolysis and sedation. More recently, MDZ has also been described to be related to the outcome of various types of carcinomas. However, how MDZ influences the progression of hepatocellular carcinoma (HCC) and its effects on the biological function and tumour immune microenvironment of this type of tumour remain unknown. METHODS: The effects of MDZ on the proliferation, invasion, and migration of HCC cell lines were examined in vitro using the Cell Counting Kit 8 (CCK8), 5-ethynyl-2'-deoxyuridine (EdU), Transwell, and wound healing assays. Additionally, western blotting was employed to confirm that PD-L1 was expressed. Chromatin immunoprecipitation-seq (ChIP-seq) analysis was used to pinpoint the transcriptional regulation regions of NF-κB and programmed death-ligand 1 (PD-L1). A C57BL/6 mouse model was used to produce subcutaneous HCC tumors in order to evaluate the in vivo performance of MDZ. Mass spectrometry was also used to assess changes in the tumour immunological microenvironment following MDZ injection. RESULTS: The HCC-LM3 and Hep-3B cell lines' proliferation, invasion, and migration were controlled by MDZ, according to the results of the CCK8, EdU, Transwell, and wound healing assays. PD-L1 expression was shown by ChIP-seq analysis to be boosted by NF-κB, and by Western blotting analysis, it was shown that MDZ downregulated the expression of NF-κB. Additionally, in vivo tests revealed that intraperitoneal MDZ injections reduced HCC tumor development and enhanced the effectiveness of anti-PD-1 therapy. The CD45+ immune cell proportions were higher in the MDZ group than in the PBS group, according to the mass spectrometry results. Injection of MDZ resulted in a decrease in the proportions of CD4+ T cells, CD8+ T cells, natural killer (NK) cells, monocytes, Tregs, and M2 macrophages and a rise in the proportion of dendritic cells. Additionally, the concentrations of the cytokines IFN-g and TNF-a were noticeably raised whereas the concentrations of the CD8+ T-cell fatigue markers ICOS, TIGIT, and TIM3 were noticeably lowered. CONCLUSION: According to this study, MDZ inhibited the progression of HCC by inhibiting the NF-κB pathway and reducing the exhaustion of CD8+ T cells. In clinical practice, MDZ combined with anti-PD-1 therapy might contribute to synergistically improving the antitumor efficacy of HCC treatment.

The transcription factor Zfh1 acts as a wing-morph switch in planthoppers.

Insect wing polyphenism is characterized by its ability to produce two or more distinct wing morphs from a single genotype in response to changing environments. However, the molecular basis of this phenomenon remains poorly understood. Here, we identified a zinc finger homeodomain transcription factor Zfh1 that acts as an upstream regulator for the development of long-winged (LW) or shorted-winged (SW) morphs in planthoppers. Knockdown of Zfh1 directs SW-destined nymphs to develop into LW morphs by down-regulating the transcriptional level of FoxO, a prominent downstream effector of the insulin/IGF signaling (IIS) pathway. The balance between transcriptional regulation via the Zfh1-FoxO cascade and post-translational regulation via the IIS-FoxO cascade provides a flexible regulatory mechanism for the development of alternative wing morphs. These findings help us understand how phenotypic diversity is generated by altering the activity of conserved proteins, and provide an extended framework for the evolution of wing morphological diversity in insects.