Tumor mutational burden adjusted by neutrophil-to-lymphocyte ratio serves as a potential biomarker for atezolizumab-treated patients with extensive stage small cell lung cancer.

BACKGROUND: There is a desperate for the identification of more accurate and efficient biomarkers for ICI responses in patients with SCLC. METHODS: The data of our study was obtained from IMpower133 study. A total of 202 patients with SCLC received the treatment of placebo plus carboplatin plus etoposide (EC) while a total of 201 patients with SCLC received the treatment of atezolizumab plus EC. Overall survival (OS) was compared using Kaplan Meier analyses. Univariate and multivariate Cox regression analysis were used to determine independent prognostic variables affecting OS in patients with SCLC. RESULTS: We have demonstrated that a higher TMB adjusted by a lower neutrophil-to-lymphocyte ratio (NLR) is significantly correlated with improved OS, in patients with SCLC subject to either atezolizumab or placebo (P = 0.001 for atezolizumab and P = 0.034 for placebo). Moreover, Cox model showed that TMB < 10 mut/Mb adjusted by NLR ≥ median was an independent factor of OS for atezolizumab-treated SCLC patients (hazard ratio [HR], 2.82; 95% confidence interval; 1.52-5.24; P = 0.001). Both univariate and multivariate cox regression analysis showed that for patients with SCLC harboring low NLR and high TMB, survival is significantly longer in those treated with atezolizumab than those treated with placebo. Survival benefit is significantly higher in atezolizumab-treated patients with SCLC than those treated with placebo (P = 0.018 for TMB cutoff = 10 mut/Mb, P = 0.034 for TMB cutoff = 16 mut/Mb). CONCLUSION: Our findings provide a promising insight into the utility of NLR-adjusted TMB in the prognosis and immune responses in patients with SCLC.

Current Status of Cognition and Clinical Practice of Refractory Cancer Pain in Shanghai: A Questionnaire Survey.

Purpose: This study aimed to assess the current status of clinical practice of refractory cancer pain (RCP) among a sample of physicians specializing in cancer pain management in Shanghai. Methods: From 2019 to 2021, a questionnaire survey was conducted among physicians engaged in diagnosis and treatment of cancer pain through the questionnaire WJX network platform in Shanghai, China. Results: A total of 238 responses participated in the survey. This survey reports physicians' understanding and incidence rate of breakthrough cancer pain (BTCP). The choice of analgesics and satisfaction of analgesic effect were investigated. We also investigated doctors' knowledge of the diagnostic criteria for RCP and their tendency to choose analgesics. Oral immediate-release morphine and intravenous or subcutaneous morphine injection have been the common treatment approach for transient cancer pain exacerbations. The main barriers to pain management are lack of standardized treatment methods for RCP, lack of knowledge related to RCP, and single drug dosage form. Doctors believe the most necessary measures to improve the current situation of poor cancer pain control include improving medical staff's understanding and treatment techniques for RCP, updating treatment techniques and methods, and improving the configuration of drug types in medical institutions. Clinicians expect to improve understanding and treatment techniques through systematic training. Conclusion: Despite multiple available analgesic measures, the treatment of RCP remains challenging. Improving the understanding of medical staff towards RCP, improving treatment techniques, and increasing the accessibility of multiple drug types are important ways to improve the satisfaction of cancer pain management in the future.

Integration Analysis of Single-Cell Multi-Omics Reveals Prostate Cancer Heterogeneity.

Prostate cancer (PCa) is an extensive heterogeneous disease with a complex cellular ecosystem in the tumor microenvironment (TME). However, the manner in which heterogeneity is shaped by tumors and stromal cells, or vice versa, remains poorly understood. In this study, single-cell RNA sequencing, spatial transcriptomics, and bulk ATAC-sequence are integrated from a series of patients with PCa and healthy controls. A stemness subset of club cells marked with SOX9highARlow expression is identified, which is markedly enriched after neoadjuvant androgen-deprivation therapy (ADT). Furthermore, a subset of CD8+CXCR6+ T cells that function as effector T cells is markedly reduced in patients with malignant PCa. For spatial transcriptome analysis, machine learning and computational intelligence are comprehensively utilized to identify the cellular diversity of prostate cancer cells and cell-cell communication in situ. Macrophage and neutrophil state transitions along the trajectory of cancer progression are also examined. Finally, the immunosuppressive microenvironment in advanced PCa is found to be associated with the infiltration of regulatory T cells (Tregs), potentially induced by an FAP+ fibroblast subset. In summary, the cellular heterogeneity is delineated in the stage-specific PCa microenvironment at single-cell resolution, uncovering their reciprocal crosstalk with disease progression, which can be helpful in promoting PCa diagnosis and therapy.

Construction of a Diagnostic Model for Small Cell Lung Cancer Combining Metabolomics and Integrated Machine Learning.

BACKGROUND: To date, no study has systematically explored the potential role of serum metabolites and lipids in the diagnosis of small cell lung cancer (SCLC). Therefore, we aimed to conduct a case-cohort study that included 191 cases of SCLC, 91 patients with lung adenocarcinoma, 82 patients with squamous cell carcinoma, and 97 healthy controls. METHODS: Metabolomics and lipidomics were applied to analyze different metabolites and lipids in the serum of these patients. The SCLC diagnosis model (d-model) was constructed using an integrated machine learning technology and a training cohort (n = 323) and was validated in a testing cohort (n=138). RESULTS: Eight metabolites, including 1-mristoyl-sn-glycero-3-phosphocholine, 16b-hydroxyestradiol, 3-phosphoserine, cholesteryl sulfate, D-lyxose, dioctyl phthalate, DL-lactate and Leu-Phe, were successfully selected to distinguish SCLC from controls. The d-model was constructed based on these 8 metabolites and showed improved diagnostic performance for SCLC, with the area under curve (AUC) of 0.933 in the training cohort and 0.922 in the testing cohort. Importantly, the d-model still had an excellent diagnostic performance after adjusting the stage and related clinical variables and, combined with the progastrin-releasing peptide (ProGRP), showed the best diagnostic performance with 0.975 of AUC for limited-stage patients. CONCLUSION: This study is the first to analyze the difference between metabolomics and lipidomics and to construct a d-model to detect SCLC using integrated machine learning. This study may be of great significance for the screening and early diagnosis of SCLC patients.

Boosted Mg-CO2 Batteries by Amine-Mediated CO2 Capture Chemistry and Mg2+ -Conducting Solid-electrolyte Interphases.

Mg-CO2 battery has been considered as an ideal system for energy conversion and CO2 fixation. However, its practical application is significantly limited by the poor reversibility and sluggish kinetics of CO2 cathode and Mg anode. Here, a new amine mediated chemistry strategy is proposed to realize a highly reversible and high-rate Mg-CO2 battery in conventional electrolyte. Judiciously combined experimental characterization and theoretical computation unveiled that the introduced amine could simultaneously modify the reactant state of CO2 and Mg2+ to accelerate CO2 cathodic reactions on the thermodynamic-kinetic levels and facilitate the formation of Mg2+ -conductive solid-electrolyte interphase (SEI) to enable highly reversible Mg anode. As a result, the Mg-CO2 battery exhibits boosted stable cyclability (70 cycles, more than 400 h at 200 mA g-1 ) and high-rate capability (from 100 to 2000 mA g-1 with 1.5 V overpotential) even at -15 °C. This work opens a newly promising avenue for advanced metal-CO2 batteries.

Adenosine in cancer immunotherapy: Taking off on a new plane.

As a new pillar of cancer therapy, tumor immunotherapy has brought irreplaceable durable responses in tumors. Considering its low response rate, additional immune regulatory mechanisms will be critical for the development of next-generation immune therapeutics. As a key regulatory mechanism, adenosine (ADO) protects tissues from excessive immune responses, but as a metabolite highly concentrated in tumor microenvironments, extracellular adenosine acts on adenosine receptors (mainly A2A receptors) expressed on MDSCs, Tregs, NK cells, effector T cells, DCs, and macrophages to promote tumor cell escape from immune surveillance by inhibiting the immune response. Amounting preclinical studies have demonstrated the adenosine pathway as a novel checkpoint for immunotherapy. Large number of adenosine pathway targeting clinical trials are now underway, including antibodies against CD39 and CD73 as well as A2A receptor inhibitors. There has been evidence of antitumor efficacy of these inhibitors in early clinical trials among a variety of tumors such as breast cancer, prostate cancer, non-small cell lung cancer, etc. As more clinical trial results are published, the combination of blockade of this pathway with immune checkpoint inhibitors, targeted drugs, traditional chemotherapy medications, radiotherapy and endocrine therapy will provide cancer patients with better clinical outcomes. We would elaborate on the role of CD39-CD73-A2AR pathway in the contribution of tumor microenvironment and the targeting of the adenosinergic pathway for cancer therapy in the review.

The Different Ways Multi-Strain Probiotics with Different Ratios of Bifidobacterium and Lactobacillus Relieve Constipation Induced by Loperamide in Mice.

Constipation is currently one of the most common gastrointestinal disorders, and its causes are diverse. Multi-strain probiotics are often considered a more effective treatment than single-strain probiotics. In this study, a constipation model was constructed using loperamide hydrochloride to evaluate the ability of a multi-strain probiotic combination of four different ratios of Bifidobacterium and Lactobacillus to regulate intestinal flora, relieve constipation, and explore the initial mechanism in mice. After four weeks of probiotic intervention, BM1, BM2, and PB2 effectively relieved constipation; however, the pathways involved were different. The Bifidobacteria-dominated formulations BM1 and BM2 mainly changed the composition and structure of the intestinal flora and significantly decreased the relative abundance of Tyzzerella, Enterorhabdus, Faecalibaculum, Gordonibacter, and Mucispirillum in stool; increased the relative abundance of Parabacteroides and the content of short-chain fatty acids (SCFAs) in stool; restored motilin (MTL) and vasoactive intestinal peptide (VIP) levels; and downregulated interleukin 6 (IL-6) and IL-8 levels in serum. This repaired the inflammatory response caused by constipation. Finally, it promoted peristalsis of the gastrointestinal tract, increasing stool water content, and relieving constipation. While Lactobacillus-dominated formula PB2 mainly restored the levels of serum neurotransmitters (MTL, SP (substance P), VIP and PYY (Peptide YY)) and inflammatory factors (IL-1, IL-6 and IL-8), it significantly decreased the relative abundance of Tyzzerella, Enterorhabdus, Faecalibaculum, Gordonibacter and Mucispirillum in stool; it then increased acetic acid content, thereby reducing the level of inflammation and changing stool properties and gastrointestinal motility.

Surface-structure tailoring of Dendritic PtCo nanowires for efficient oxygen reduction reaction.

Platinum-based alloy nanowire catalysts demonstrates great promise as electrocatalysts to facilitate the cathodic oxygen reduction reaction (ORR) of proton exchange membrane fuel cells (PEMFCs). However, it is still challenge to further improve the Pt atom utilization of Pt based nanowires featuring inherent structural stability. Herein, a new structure of PtCo nanowire with nanodendrites was developed using CO-assistance solvent thermal method. The dendrite structure with an average length of about 7 nm are characterized by a Pt-rich surface and the high-index facets of {533}, {331} and {311}, and grows from the ultra-fine wire structure with an average diameter of about 3 nm. PtCo nanowires with nanodendrites developed in this work shows outstanding performance for ORR, in which its mass activity of 1.036 A/mgPt is 5.76 times, 1.74 times higher than that of commercial Pt/C (0.180 A/mgPt) and PtCo nanowires without nanodendrites (0.595 A/mgPt), and its mass activity loss is only 18% under the accelerated durability tests (ADTs) for 5k cycles. The significant improvement is attributed to high exposure of active sites induced by the dendrite structure with Pt-rich surface with the high-index facets and Pt-rich surface. This structure may provide a new idea for developing novel 1D Pt based electrocatalysts.

Rhombic dodecahedron nanoframes of PtIrCu with high-index faceted hyperbranched nanodendrites for efficient electrochemical ammonia oxidation via preferred NHx dimerization pathways.

Ammonia has been emerging as a sustainable and environmentally friendly fuel. However, direct electrochemical ammonia oxidation reaction (AOR) in low-temperature fuel cells seriously suffers from high overpotential and deficient durability. Herein, rhombic dodecahedron nanoframe of platinum iridium copper (PtIrCu) with high-index faceted hyperbranched nanodendrites (RDNF-HNDs) was developed using a one-step self-etching solvothermal method. The framework structure with the high-index facets enables the PtIrCu nanocrystals to expose more effective active sites. They exhibit an ultra-low onset potential of 0.33 V vs. RHE and high mass activity of 26.1 A gPtIr-1 at 0.50 V, which is 140 mV lower and 7.5 times higher than that of commercial Pt/C in the AOR. In situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy verifies that AOR on PtIrCu RDNF-HNDs prefers to the NHx dimerization pathways, effectively alleviating the poison of Nads and NOx. The theoretical calculation also shows that both introducing Cu atoms into PtIr alloy and increasing the content of Ir in PtIrCu alloy can reduce the reaction energy barrier of electrochemical dehydrogenation from *NH2 to *NH. The specific structure of PtIrCu RDNF-NDs provides a new inspiration to solve the critical issue of electrocatalysts for AOR with low activity and durability.

Orchestrating smart therapeutics to achieve optimal treatment in small cell lung cancer: recent progress and future directions.

Small cell lung cancer (SCLC) is a recalcitrant malignancy with elusive mechanism of pathogenesis and dismal prognosis. Over the past decades, platinum-based chemotherapy has been the backbone treatment for SCLC. However, subsequent chemoresistance after initial effectiveness urges researchers to explore novel therapeutic targets of SCLC. Recent years have witnessed significant improvements in targeted therapy in SCLC. New molecular candidates such as Ataxia telangiectasia and RAD3-related protein (ATR), WEE1, checkpoint kinase 1 (CHK1) and poly-ADP-ribose polymerase (PARP) have shown promising therapeutic utility in SCLC. While immune checkpoint inhibitor (ICI) has emerged as an indispensable treatment modality for SCLC, approaches to boost efficacy and reduce toxicity as well as selection of reliable biomarkers for ICI in SCLC have remained elusive and warrants our further investigation. Given the increasing importance of precision medicine in SCLC, optimal subtyping of SCLC using multi-omics have gradually applied into clinical practice, which may identify more drug targets and better tailor treatment strategies to each individual patient. The present review summarizes recent progress and future directions in SCLC. In addition to the emerging new therapeutics, we also focus on the establishment of predictive model for early detection of SCLC. More importantly, we also propose a multi-dimensional model in the prognosis of SCLC to ultimately attain the goal of accurate treatment of SCLC.

Effect of Dietary Casein Phosphopeptide Addition on the Egg Production Performance, Egg Quality, and Eggshell Ultrastructure of Late Laying Hens.

(1) Objective: This study aimed to assess the effects of dietary casein phosphopeptide (CPP) supplementation on the egg production performance of late laying hens and the resulting egg quality and eggshell ultrastructure. (2) Methods: A total of 800 laying hens aged 58 weeks were randomly assigned into 5 groups with 8 replicates of 20 hens each. The hens were fed a basal diet supplemented with 0 (control, T1), 0.5 (T2), 1.0 (T3), 1.5 (T4), and 2.0 (T5) g/kg CPP for 9 weeks. (3) Results: Dietary CPP supplementation was found to be beneficial for improving eggshell quality. The spoiled egg rate of the experimental groups was lower than that of the control group (linear and quadratic effect, p < 0.05). The yolk color in the T2, T3, and T4 groups was higher than that in the T1 group (quadratic effect, p < 0.05). The shell thickness in the T4 group was higher than that in the T1 and T2 groups (linear effect, p < 0.05). The shell color in the experimental groups was higher than that in the control group (linear and quadratic effect, p < 0.05). The effective thickness in the T3-T5 groups (linear and quadratic, p < 0.05) and the number of papillary nodes in the T2 and T3 groups were higher than those in the T1 group (quadratic, p < 0.05). The calcium content in the T2 and T3 groups was higher than that in the T1 group (quadratic effect, p < 0.05). The iron content in the T2 and T3 groups was higher than that in the T1 group (p < 0.05). (4) Conclusion: In summary, 0.5-1.0 g/kg CPP supplementation reduced the spoiled egg rate, enhanced the yolk and eggshell colors, increased the thickness of the effective layer, and the calcium and iron contents in the eggshell.

Expression pattern of miR-16-2-3p and its prognostic values on pediatric acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is a debilitating illness that easily occurs in adolescents. microRNAs (miRNAs) are potential biomarkers for multiple diseases. This paper was to elaborate on the expression of miR-16-2-3p in childhood ALL and its clinical values on ALL diagnosis and prognosis. First, serum miR-16-2-3p expression in ALL children and healthy volunteers was measured using RT-qPCR. Next, diagnostic potential and prognostic values of miR-16-2-3p on ALL were analyzed through receiver operating characteristic (ROC) curve, Kaplan-Meier survival curve, and multivariate Cox regression analysis, respectively. No significant difference was observed in the clinical baseline data between ALL patients and healthy children. ALL patients showed downregulated serum miR-16-2-3p (0.65 ± 0.27) (p < .01), whose area under the ROC curve was 0.837 with a cut-off value of 0.745 (67.92% sensitivity, 96.94% specificity). ALL patients with higher miR-16-2-3p expression had higher survival rates than those with lower miR-16-2-3p expression. Low miR-16-2-3p expression predicted poor prognosis of ALL patients. After adjusting LDH and lymphomyelocyte proportion (p = 0.003, HR = 0.003, 95%CI = 0.000-0.145), miR-16-2-3p was recognized as an independent prognostic factor for ALL patient survival. Briefly, low serum miR-16-2-3p expression in ALL children could aid ALL diagnosis and predict poor prognosis.

Immune-checkpoint inhibitor resistance in cancer treatment: Current progress and future directions.

Cancer treatment has been advanced with the advent of immune checkpoint inhibitors (ICIs) exemplified by anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), anti-programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) drugs. Patients have reaped substantial benefit from ICIs in many cancer types. However, few patients benefit from ICIs whereas the vast majority undergoing these treatments do not obtain survival benefit. Even for patients with initial responses, they may encounter drug resistance in their subsequent treatments, which limits the efficacy of ICIs. Therefore, a deepening understanding of drug resistance is critically important for the explorations of approaches to reverse drug resistance and to boost ICI efficacy. In the present review, different mechanisms of ICI resistance have been summarized according to the tumor intrinsic, tumor microenvironment (TME) and host classifications. We further elaborated corresponding strategies to battle against such resistance accordingly, which include targeting defects in antigen presentation, dysregulated interferon-γ (IFN-γ) signaling, neoantigen depletion, upregulation of other T cell checkpoints as well as immunosuppression and exclusion mediated by TME. Moreover, regarding the host, several additional approaches that interfere with diet and gut microbiome have also been described in reversing ICI resistance. Additionally, we provide an overall glimpse into the ongoing clinical trials that utilize these mechanisms to overcome ICI resistance. Finally, we summarize the challenges and opportunities that needs to be addressed in the investigation of ICI resistance mechanisms, with the aim to benefit more patients with cancer.

Bufalin Inhibits Tumorigenesis and SREBP-1-Mediated Lipogenesis in Hepatocellular Carcinoma via Modulating the ATP1A1/CA2 Axis.

Altered lipid metabolism is a hallmark of hepatocellular carcinoma (HCC), a common malignancy with a dismal prognosis against which there is a lack of effective therapeutic strategies. Bufalin, a classical Na[Formula: see text]-K[Formula: see text]-ATPase (NKA) inhibitor, shows a potent antitumor effect against HCC. However, the role of bufalin in regulating lipid metabolism-related pathways of HCC remains unclear. In this study, we examined the interaction between bufalin and its target molecule, ATP1A1/CA2, in vitro and in vivo and explored the intersected downstream pathways in silico. A multi-omics analysis of transcriptomics and metabolomics was employed to screen for potential action targets. The results were verified and correlated with the downstream lipid de novo synthesis pathway and the bufalin/ATP1A1/CA2 axis. We found that bufalin suppressed the ATP1A1/CA2 ratio in the treated HCC cells and showed a negative correlation with bufalin drug sensitivity. Functionally, ATP1A1 overexpression and CA2 down-regulation inhibited the bufalin-suppressed HCC proliferation and metastasis. Furthermore, down-regulation of CA2 induced epithelial-mesenchymal transition and bufalin resistance in HCC cells by up-regulating ATP1A1. Mechanistically, lipid metabolism-related signaling pathways were enriched in low ATP1A1 and high CA2 expression subgroups in GSEA. The multi-omics analysis also showed that bufalin was closely related to lipid metabolism. We demonstrated that bufalin inhibits lipogenesis and tumorigenesis by down-regulating SREBP-1/FASN/ACLY via modulating the ATP1A1/CA2 axis in HCC.

Intratumor heterogeneity is associated with less CD8+ T cell infiltration and worse survival in patients with small cell lung cancer.

PURPOSE: Small cell lung cancer (SCLC) is a heterogeneous malignancy with genetic and phenotypic disparity. However, the association between intratumor heterogeneity (ITH) and immunological features as well as the impact of ITH on prognosis has never been explored in SCLC. Hence, we investigated the relationship between ITH and their immunological features and explored the effect of ITH on overall survival (OS) in patients with SCLC. METHODS: Programmed cell death-ligand 1 (PD-L1), CD8+ cell infiltration was calculated through immunohistochemical staining and tumor mutational burden (TMB), tumor neoantigen burden (TNB), and ITH levels via whole-exome sequencing (WES). RESULTS: Significant correlation was not found in ITH versus TMB, ITH versus TNB (P = 0.1821, P = 0.0612). No significant variation in ITH was found between negative PD-L1 SCLC patients and positive PD-L1 ones (P = 0.0610 for TPS, P = 0.6347 for CPS). Interestingly, we demonstrated the negative correlation between CD8+ T cell infiltration and ITH (P = 0.0220). More importantly, significant OS benefit was detected in ITH-low SCLC patients in comparison with ITH-high ones (P = 0.0049). ITH was an independent prognostic factor on OS with clinicopathological variables adjusted (HR, 2.044; 95% CI 1.190-3.512; P = 0.010). We also demonstrated significantly different driver genes and CNV between ITH-low and ITH-high SCLC. CONCLUSION: Our work pointed the negative association of ITH with CD8+ T cell infiltration and suggested ITH as a potential predictor of OS in SCLC, putting forward a direction for more precise and individualized therapeutic strategies for SCLC.

Molecular subtyping of small-cell lung cancer based on mutational signatures with different genomic features and therapeutic strategies.

Small-cell lung cancer (SCLC) is an exceptionally lethal malignancy characterized by extremely high alteration rates and tumor heterogeneity, which limits therapeutic options. In contrast to non-small-cell lung cancer that develops rapidly with precision oncology, SCLC still remains outside the realm of precision medicine. No recurrent and actionable mutations have been detected. Additionally, a paucity of substantive tumor specimens has made it even more difficult to classify SCLC subtypes based on genetic background. We therefore carried out whole-exome sequencing (WES) on the largest available Chinese SCLC cohort. For the first time, we partitioned SCLC patients into three clusters with different genomic alteration profiles and clinical features based on their mutational signatures. We showed that these clusters presented differences in intratumor heterogeneity and genome instability. Moreover, a wide existence of mutually exclusive gene alterations, typically within similar biological functions, was detected and suggested a high SCLC intertumoral heterogeneity. Particularly, Cluster 1 presented the greatest potential to benefit from immunotherapy, and Cluster 3 constituted recalcitrant SCLC, warranting biomarker-directed drug development and targeted therapies in clinical trials. Our study would provide an in-depth insight into the genome characteristics of the Chinese SCLC cohort, defining distinct molecular subtypes as well as subtype-specific therapies and biomarkers. We propose tailoring differentiated therapies for distinct molecular subgroups, centering on a personalized precision chemotherapy strategy combined with immunization or targeted therapy for patients with SCLC.

Adsorption performance and optimization by response surface methodology on tetracycline using Fe-doped ZIF-8-loaded multi-walled carbon nanotubes.

Herein, an iron-doped ZIF-8-loaded multi-walled carbon nanotube (FZM) was synthesized and its adsorption performance on tetracycline (TC) was investigated. The experimental conditions (solution pH, temperature, adsorbent dose) were optimized by Box-Behnken design (BBD) in response surface methodology (RSM). The results show that the adsorption effect of TC by FZM is optimal under the conditions of temperature = 298 K, pH = 6, and contact time = 360 min. The adsorption processes of TC by FZM follow the pseudo-second-order (PSO) kinetic and Freundlich isotherm models, indicating that chemisorption is the dominant factor and the adsorption reaction is multi-layer, with a theoretical maximum saturation capacity of 1111.11 mg/g at 298 K. The adsorption thermodynamic results indicate that the adsorption of TC by FZM is a spontaneous and endothermic process. The mechanism of TC adsorption by FZM possibly occurs through hydrogen bonding, surface complexation, π-π interaction, and electrostatic interaction. From the statistical results, the optimal adsorption capacity of TC by FZM is 599.78 mg/g at a pH of 7.1, a temperature of 312.5 K, and an adsorbent dose of 64.43 mg/L, with a deviation of 1.73% from the actual value. Furthermore, regeneration experiments demonstrate that FZM has excellent reusability with a 15% loss of adsorption capacity after four cycles. This study provides some insights to study the adsorption behavior of TC by MOFs and the optimization of the adsorption experimental conditions, and also shows the potential of FZM for TC removal.

Untargeted metabolomics and lipidomics identified four subtypes of small cell lung cancer.

INTRODUCTION: Small cell lung cancer (SCLC) is a heterogeneous malignancy with dismal prognosis. However, few studies have conducted on the metabolic heterogeneity in SCLC. OBJECTIVE: We therefore identify SCLC classifications using untargeted metabolomics and lipidomics. We also compared their survival and the immunotherapy responses. METHODS: Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS) analysis was performed in 191 SCLC serum samples. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was conducted to identify metabolic pathways. The Kaplan-Meier and log-rank test were used to analyze the survival curves. The univariate and multivariate Cox proportional hazards regression models were used to evaluate prognostic factors for OS in patients with SCLC. RESULTS: Distinct subtypes of SCLC were identified by consensus clustering algorithm using partioning around medoids (pam) based on untargeted metabolomics and lipidomics. Four distinct subtypes of SCLC were identified, with distinct metabolic pathways. Subgroup 2 had the longest survival whereas Subgroup 1 had the shortest. Subtype 2 benefited most from immunotherapy in OS, as in contrast to Subtype 3 with shortest survival. CONCLUSION: Our study revealed the metabolic heterogeneity in SCLC and identified four subtypes with distinct metabolic features. It indicates promising therapeutic and prognostic value that may guide treatment for SCLC. The subtype-specific clinical trials may be designed and would be instructive for drug development.

An immunogenic cell death-associated classification predictions are important for breast invasive carcinoma prognosis and immunotherapy.

As a type of regulated cell death (RCD), immunogenic cell death (ICD) can initiate the adaptive immune responses. Numerous reports highlight the capacity of ICD to alter the tumor immune microenvironment by releasing Damage-Associated Molecular Patterns (DAMP) or danger signals to boost the efficacy of immunotherapy. Therefore, identification of the ICD-associated biomarkers is crucial for the prediction of ICD-induced immune responses. In this report, the consensus clustering technique was used to identify two subcategories (subtypes) linked to ICD. In comparison to the ICD-low subcategory, the ICD-high subcategory showed longer survival and more immune cell infiltration. Then, a novel ICD-associated prognostic model was developed and validated for predicting the survival of patients with breast invasive carcinomas (BRCA) and is linked to the tumor immune microenvironment. To conclude, a novel ICD-based BRCA classification scheme was designed. For individuals with BRCA, this categorization will be crucial for directing the assessment of prognosis and treatment.