Background: The pathogenesis of sarcoidosis involves T cells and B lymphocytes that produce autoantibodies. We compared the expression of different T and B cell subsets in sarcoidosis and three B-mediated rheumatic diseases that can affect the lungs in an attempt to identify similarities and differences that distinguish these diseases. Methods: The study included patients referred to Siena University Hospital’s respiratory disease and rheumatology units. Patients were enrolled prospectively and consecutively. Healthy volunteers were also included. Multicolor flow cytometry was performed on phenotype T and B cell subsets. Multivariate analysis was carried out to reduce the dimensionality of the data. Results: Fifteen patients had a diagnosis of sarcoidosis, fourteen idiopathic inflammatory myopathies (IIM), five granulomatosis with polyangiitis (GPA), ten microscopic polyangiitis (MPA), and seven were controls. Thirty-five T and B cell subsets were phenotyped, 15 of which were significantly different in sarcoidosis, B-mediated rheumatic disorders, and controls. Principal components analysis distinguished the four groups of patients with a total explained variance of 54.7%. A decision tree was constructed to determine which clustering variables would be most useful for distinguishing sarcoidosis, IIM, MPA, and GPA. The model showed regulatory T helper cells (Th-reg) > 5.70% in 91% of sarcoidosis patients as well as Th-reg ≤ 5.70 and Th17 > 43.27 in 100% of MPA. It also showed Th-reg ≤ 5.70, Th17 ≤ 43.27 and Tfh-reg ≥ 7.81 in 100% of GPA patients, and Th-reg ≤ 5.70, Th17 ≤ 43.27 and Tfh-reg ≤ 7.81 in 100% of IIM patients. Conclusion: The immune cell profile sheds light on similarities and differences between sarcoidosis and B-mediated rheumatic diseases. Sarcoidosis and autoimmune diseases show similar patterns of cellular immune dysregulation, suggesting a common pathogenic pathway that may provide an opportunity for further understanding autoimmunity and exploring biological therapies to treat sarcoidosis. Diagnoscoidosis . SeveralAmong autoimmune rheumatic disease (ARD), there are ANCA-associated vasculitis (AAV) and idiopathic inflammatory myopathy (IIM), both of which are B-mediated rheumatic disorders. A loss of immune tolerance leads to the activation of the immune system against self-tissues and organs. These disorders can be systemic or organ-specific. ANCA-associated vasculitis in the form of granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA) affects the respiratory system, kidneys, and upper and lower extremities . A necroThree factors influence the pathogenesis of the abovementioned ARD: genetic predisposition (associated with major histocompatibility antigens and other immunoreactive molecules), environmental exposure to physical and chemical agents, and infection. Hormonal factors and stressful life events may also play a part in its development. Autoimmune disorders exhibit an inflammatory milieu due to leukocytosis and acute-phase proteins . Together, these findings emphasize the need for comparative studies on sarcoidosis and B-mediated rheumatic diseases for insights into the failure of peripheral tolerance linked to the development of these diseases. However, only one article reported the expression of immune checkpoint molecules  on T- and NK-cells that negatively regulate the T-cell immune function in granulomatous diseases including sarcoidosis and AAV .No data are available on adaptive immune cell profiles shared by ARD and sarcoidosis, despite emerging evidence that these conditions are related in terms of cellular immune dysregulation. Here, we used the relative distribution of different T and B cell subset percentages to find similarities and differences between sarcoidosis and three B cell-mediated rheumatic conditions that can affect the lungs. Adaptive immune profiles were also compared with those of a group of healthy volunteers.Patients referred to Siena Regional Referral Centre for sarcoidosis and to the rheumatology unit of Siena University Hospital were prospectively and consecutively enrolled in the study. The diagnosis of sarcoidosis was confirmed by multidisciplinary discussion according to American Thoracic Society/European Respiratory Society/World Association of Sarcoidosis and Other Granulomatous Disorders (ATS/ERS/WASOG) guidelines. IIM patients were diagnosed according to the 2017 EULAR criteria and/or Peter and Bohan criteria for dermatomyositis, anti-synthetase positivity, and typical clinical features of anti-synthetase syndrome, while AAV patients, including granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA), were diagnosed according to the 2022 ACR/EULAR classification criteria. Patients diagnosed with polymyositis were excluded because no specific diagnostic criteria are available for this disorder which is currently diagnosed by exclusion . Peripheral blood samples were collected from patients for immune profiling. Their demographic, clinical, and radiological data were entered into a prestructured electronic database. Written informed consent to participate in the study was obtained from all patients and healthy controls who had no history of concomitant pathologies, were not on medication, and had normal lung function. The study was approved by the regional ethical review board of Siena, Italy , and complied with the Declaration of Helsinki.Multicolor flow cytometric analysis was performed, and the gating strategy is reported in the The second tube was to detect follicular T cells and included mAbs: CD4-APC-Vio770, CD45RA-PE-Vio770, CCR6-APC, CXCR3-VioBright FITC CXCR5 PerCP-Cy5.5, and CCR4-PE, all from Miltenyi Biotec .® 647, BD, San Jose, CA, USA), CXCR5 PerCP-Cy5, CD8 horizon450, and CD3 APC-Cy7 (OKT3) .The third tube was to phenotype regulatory T cells according to the BD Human Regulatory T Cell Cocktail (CD4-FITC (SK3), CD25-PECy7 (2A3), CD127 Alexa FluorGating was carried out using Kaluza software 2.1 : details are shown in the All values were expressed as the mean, interquartile range (IQR), or standard deviation, as appropriate. The Shapiro–Wilk test was used to check for normal distribution of values. ANOVA  and the Dunn test for multiple comparisons were performed using a non-parametric method. For categorical variables, Fisher’s exact or Chi-squared tests were used to compare proportions between groups. Spearman tests were conducted to determine correlations between clinical and immunological parameters. p-value less than 0.05 was considered statistically significant. Statistical analysis was performed with GraphPad Prism 9.4  and XLSTAT 2021 software .Multivariate analysis was conducted on cell subsets  that differed in a statistically significant way between sarcoidosis, IIM, MPA, and GPA groups. A two-dimensional representation of multidimensional data was used to identify trends in immunological features by supervised principal component analysis (PCA). Four groups  were formed to identify the best thresholds for group classification. Based on the Gini criterion, a classification and regression decision tree were constructed to identify optimal clustering variables. We evaluated the accuracy of binary classifiers by confusion matrix, creating a series of test/training partitions. A Forty-four patients were enrolled consecutively and prospectively at diagnosis; none of them were being treated at the time of sampling. Fifteen patients had sarcoidosis (mean ± standard deviation age 55 ± 11.3 years): nine were women, and there was a prevalence of never-smokers (57%). All sarcoidosis patients were in Scadding radiological stage II, indicating thoracic lymph node enlargement and sarcoid involvement of the respiratory system. Fifteen patients had a diagnosis of AAV . Ten out of fifteen AAV patients had MPA, and 5 out of 15 had GPA. Fourteen patients had a diagnosis of IIM . Five out of fourteen IIM patients had dermatomyositis (3 TIF1gamma-positivity and 2 MDA5-positivity), and 9 out of 14 had anti-synthetase syndrome (6 Jo1-positivity and 3 PL7-positivity). One patient with polymyositis was excluded from the analysis. Eleven healthy volunteers  were also enrolled in the study.p = 0.0035). Follicular Th regulatory cells (Tfh-reg) were less numerous in sarcoidosis and IIM than in MPA  and GPA samples . T effector cells were also less numerous in sarcoidosis than in MPA (p = 0.0259). T naïve cells were more numerous in IIM than in sarcoidosis (p = 0.0136). T helper regulatory cells were more numerous in sarcoidosis than in IIM (p = 0.0019), MPA (p = 0.0033), and GPA samples (p = 0.0029). Follicular Th 17.1 were more numerous in sarcoidosis than in IIM (p = 0.0450). Th1 cell percentages were higher in GPA than in IIM (p = 0.0227) and sarcoidosis (p = 0.0129). They were also higher in MPA than in IIM (p = 0.0127) and sarcoidosis samples (p = 0.0126). Th17 cell percentages were higher in GPA than in IIM (p = 0.0353) and sarcoidosis (p = 0.0435). Immature B cells were more numerous in sarcoidosis than IIM samples (p = 0.0062), MPA (p = 0.0035), and GPA samples (p = 0.0297). T cytotoxic regulatory cells were more numerous in sarcoidosis than in IIM (p = 0.0456), whereas CD8-positive cell percentages were lower in sarcoidosis than in IIM samples (p = 0.0152). Follicular T cytotoxic-17 (Tfc17) cell percentages were higher in GPA (p = 0.0439) and IIM (p = 0.0492) than in sarcoidosis samples.T cytotoxic naïve cells were less numerous in sarcoidosis than in IIM (p = 0.0182). CD3+ cells were less numerous in sarcoidosis than in control samples (p = 0.015). They were also more numerous in MPA (p = 0.0237) and GPA (p = 0.0329) than in control samples. Th effector cells were more numerous in sarcoidosis and MPA than in control samples . Tfh-reg were more numerous in MPA than in control samples (p = 0.0203). Th-reg cells were more numerous in sarcoidosis than in control samples (p = 0.0048) but less numerous in MPA than in control samples (p = 0.0133). Th1 cell subsets were more numerous in GPA and MPA than in control samples . Th17 cell percentages were higher in GPA than in control samples (p = 0.0308). Immature B cells were more numerous in controls than in sarcoidosis patients (p = 0.038). Tc naïve cells were less numerous in the control samples than in MPA samples (p = 0.0151). CD8+ cells were more numerous in the control samples than in the sarcoidosis samples (p = 0.0302). Tc1 cell percentages were lower in controls than in MPA (p = 0.0474) and GPA patients (p = 0.0363). Tc effector cells were more numerous in sarcoidosis than in control samples  was conducted to identify the best clustering variables that can distinguish between the groups of sarcoidosis, IIM, MPA, and GPA . The modAn important objective of the present preliminary study was to determine the differences and similarities in immune profiles between sarcoidosis patients and patients with IIM and AAV. We also compared all profiles with those of healthy controls. Multivariate analysis of the data reduced the number of dimensions, and a total variance of 54.7% was obtained based on T and B cell subsets. The total variance was determined by a classification and regression tree, showing good clustering variables for sarcoidosis, IIM, MPA, and GPA. Treg cell percentages clustered 91% of sarcoidosis patients with a cut-off of 5.7%, while 100% of IIM, MPA, and GPA patients were clustered on the basis of Treg, Th17, and Tf-reg cell percentages.Sarcoidosis and ARD patients often have lymphopenia. We found lower CD3 and CD8 cell percentages in sarcoidosis than in IIM and control samples; T cells were also below the normal range of controls in MPA and GPA patients. + population in circulating memory CD4 T cells since this strategy is often conducted prior to analyzing subsets of Tfh1, Tfh2, or Tfh17 [The immune response to inflammatory diseases is generally regulated by B cells . In lineor Tfh17 .The helper and cytotoxic subsets of T follicular cells (Tfh and Tfc) expressed the main Th17-cell chemokine receptors implicated in chronic inflammatory conditions. This population of cells is referred to as Tfh17 and Tfc17. Autoimmune diseases typically have a preponderance of Tfh17 cells . AlthougAlthough they are transcriptionally and phenotypically distinct from other CD8 T cell subsets, Tfc cells may play a role in antibody-mediated autoimmune disease progression. There is limited information available about Tfc distribution in sarcoidosis and acute lung diseases. Recently, Zhai et al. demonstrated elevated Tfc cell percentages in patients with primary Sjogren syndrome, especially between those with lung involvement and controls . A wide variety of effector subsets are generated by T cells. They include Th cells, T follicular cells (Tfc), and regulatory T cells (Tregs). T cells, Tfc, and Tregs stimulate target cells, whereas Th cells, Tfs, and Tregs suppress them . As a subpopulation of T cells, Tregs control the immune system, maintain tolerance to self-antigens, and prevent the occurrence of autoimmune diseases. The role of Tregs in sarcoidosis pathogenesis has long been suspected, although research findings are inconsistent . CD127 (IL-7Ra) is highly expressed by naive T cells, which are precursors of effector and memory T cells . T cellsThe expression of IL-7Rα on CD4 T cells implies the proliferation of T cell receptors. Indeed, its lacking and expression of CD25 result in anergic and regulatory CD4 T cells . Since tARD has been associated with significant reductions in Th-reg levels and the production of autoantibodies . The proThe innate immune system is activated in sarcoidosis and ARD, leading to T reg cell dysfunction and elevated Th-17 cell count in peripheral blood . ŻabińskDespite the value of this new data on the immunological pathways involved in sarcoidosis and B-mediated rheumatic diseases, our study has several limitations: (1) the IIM cohort was small and heterogeneous; (2) our findings are in need of validation for other autoimmune rheumatic disorders by multicentric prospective studies such as rheumatoid arthritis in order to consider in differential diagnosis; (3) the study population was too small to detect any correlations between immunological features and disease activity or severity; (4) there was a lack of lymphocyte subset total counts.The etiology and pathogenesis of sarcoidosis remain largely uncharacterized despite extensive research. Autoantigen-specific T cells and autoantibody-producing B lymphocytes may be a sign of autoimmune inflammatory reactions in sarcoidosis due to a number of triggers that contribute to the development of the disease. Our immune cell profiles shed light for the first time on the similarities and differences between sarcoidosis and B-mediated rheumatic diseases. The observation of similar cellular immune dysregulation patterns in sarcoidosis and autoimmune diseases suggests common pathogenetic pathways that may offer an opportunity for further study of autoimmunity and the development of biological therapies to treat sarcoidosis .


Deep mutational scanning (DMS) is a high-throughput experimental technique that measures the effects of thousands of mutations to a protein. These experiments can be performed on multiple homologs of a protein or on the same protein selected under multiple conditions. It is often of biological interest to identify mutations with shifted effects across homologs or conditions. However, it is challenging to determine if observed shifts arise from biological signal or experimental noise. Here, we describe a method for jointly inferring mutational effects across multiple DMS experiments while also identifying mutations that have shifted in their effects among experiments. A key aspect of our method is to regularize the inferred shifts, so that they are nonzero only when strongly supported by the data. We apply this method to DMS experiments that measure how mutations to spike proteins from SARS-CoV-2 variants  affect cell entry. Most mutational effects are conserved between these spike homologs, but a fraction have markedly shifted. We experimentally validate a subset of the mutations inferred to have shifted effects, and confirm differences of > 1,000-fold in the impact of the same mutation on spike-mediated viral infection across spikes from different SARS-CoV-2 variants. Overall, our work establishes a general approach for comparing sets of DMS experiments to identify biologically important shifts in mutational effects. Deep mutational scanning (DMS) is a high-throughput experiment that measures the effects of thousands of mutations to a protein , 2. It hHowever, when comparing DMS experiments, a key challenge is determining whether observed differences in mutational effects are due to real biological signal or the noise inherent in any high-throughput experiment. Previous studies have addressed this challenge by separately inferring mutational effects in each experiment, and then trying to identify mutations with differences between experiments that are significantly larger than the experimental noise . Howeverlasso — for inferring compressed or structured models , receptor-binding domain (RBD), and regions involved in conformational dynamics and inter-protomer packing. These sites tend to cluster near each other in spike’s 3D structure, but are often far away from non-identical sites that differ in amino-acid sequence between homologs, suggesting that many shifts are due to long-range epistasis. We experimentally validate a subset of the inferred mutational shifts, identifying some mutations that differ in their effect on spike-mediated viral entry by > 1,000-fold between homologs.We assume the DMS data report an experimentally measured functional score for each protein variant from each homolog or condition, where a variant corresponds to a unique protein sequence covering the entire mutagenized region. This requirement is usually satisfied by DMS experiments that either sequence the entire length of the mutagenized gene, or use barcoding to link full gene sequences to barcodes , 30. Eacreference experiment — and shifts in mutational effects in each of the other experiments relative to the reference , and a lasso regularization term that encourages the inferred shifts to be zero. Specifically, for each shift parameter, the lasso term adds a penalty that scales linearly with the absolute value of the shift. If a shift in the effect of a specific mutation is strongly supported by the experimental data, then inferring a nonzero shift for this mutation will decrease the loss term enough to overcome the regularizing effect of the lasso term. How strongly a shift is supported by the data is influenced by multiple factors, including whether the shift substantially minimizes the loss term for an individual variant, an example of which is illustrated in https://github.com/matsengrp/multidms for the code; see https://matsengrp.github.io/multidms/ for the documentation.We implemented the model described above in a Python package called multidms. See We applied the above approach to infer shifts in mutational effects between three homologs of the SARS-CoV-2 spike protein: Delta, Omicron BA.1, and Omicron BA.2. The Delta and BA.1 homologs are separated by 43 amino-acid mutations and indels (97% identity), while the two Omicron homologs are separated by 27 mutations (98% identity). Given the high percent identity, we expected most mutations to have similar effects among homologs.As input to our analysis, we used previously published DMS data on how mutations to the spikes of Delta and BA.1 affect spike-mediated viral entry in the context of pseudotyped lentiviruses , as wellWe fit a single multidms model for the three homologs, using just one of the DMS experiments for each homolog. We used BA.1 as the reference because it had the lowest level of noise , but fouWe analyzed the inferred mutational effects, focusing on the 5,934 mutations seen at least once across all three homolog DMS experiments. Because we used BA.1 as the reference, the inferred Both https://matsengrp.github.io/SARS-CoV-2_spike_multidms/spike-analysis.html#shifted-mutations-interactive-altair-chart for an interactive heat map that enables more detailed analyses of the mutational shifts.Sites with shifted mutational effects occurred across the length of spike . SeveralWe experimentally validated the inferred shifts in mutational effects using spike-pseudotyped lentiviral particles . SpecifiAs expected, some mutations inferred to have undergone large shifts in their effects caused large changes in viral titer in some homologs . In geneThe most striking shift was for mutation A419S, which is highly deleterious in BA.1 and BA.2 , but is nearly neutral in Delta. The mechanistic basis of this shift is easily understood: A419S introduces an Nlinked glycan at 417 in BA.1 and BA.2 (which have N417), but not in Delta (which has K417). This glycan greatly reduces ACE2 affinity , 17, makThe other validated mutations showed a similar pattern, where each mutation was highly deleterious in at least one homolog and substantially less deleterious in at least one other, with specific patterns differing by mutation. In nearly all cases, the inferred shifts in latent phenotype matched the experimentally measured shifts in effects on viral titer. These mutations occur in multiple regions of spike. D142L is in one of multiple loops in the NTD that form an antigenic supersite  and helpThe validated mutations were often deleterious in BA.1 and considerably less deleterious in Delta due to large positive shifts. In general, shifts in Delta tended to be positive , and theIn an effort to further validate the inferred shifts, we compared our inferences to ones that we computed from other studies, including DMS experiments of RBD homologs measuring mutational effects on ACE2 binding and RBD expression on the surface of yeast , 17, andSites with strongly shifted mutations tended to cluster in three-dimensional space  and B. WWe describe a general method for jointly fitting a single model to multiple DMS experiments to identify mutations that have shifted effects across homologs or selective conditions. Algorithmically, the method is essentially an extension of globalepistasis models  to multiSI Appendix and online documentation for multidms suggest strategies for normalizing functional scores between experiments to help make them comparable.Our method does make several assumptions. First, the joint-modeling approach assumes that most mutations have similar effects between experiments. This approach would not make sense if many mutations are expected to have large shifts, which can occur when comparing highly divergent homologs , 19. SecSI Appendix). Further, we developed an open-source software package with comprehensive documentation so that others can easily use our method. Altogether, this method could greatly accelerate future use of DMS to identify mutations with biologically interesting shifts in effects.Despite the above assumptions, we envision that our method could be applied to many future studies comparing DMS experiments. Most DMS experiments have appreciable levels of noise, necessitating a method to account for noise when comparing them. Our method enables the use of global-epistasis models to analyze libraries with multiple mutations per variant, but is also compatible with libraries that only have a single mutation per variant .The multidms Python package is available via the Python Package Index (PyPI). It provides tools for processing functional scores from DMS data, fitting a multidms model to the data, and generating plots for analyzing the results. The core models and optimization algorithms are implemented using the JAX and JAXopt packages, enabling automatic differentiation and just-in-time compilation for high performance on CPU and GPU , 48. TheFor the full analysis pipelines used to generate functional scores from raw DMS data for a given spike homolog, see:https://dms-vep.github.io/SARS-CoV-2_Delta_spike_DMS_REGN10933/Delta : https:/https://dms-vep.github.io/SARS-CoV-2_Omicron_BA.1_spike_DMS_mAbs/BA.1 : https:/https://dms-vep.github.io/SARS-CoV-2_Omicron_BA.2_spike_DMS/BA.2 (from this study): https://github.com/matsengrp/SARS-CoV-2_spike_multidms) with all code used to curate the above DMS data, fit multidms models to these data, and make all figures in the paper. The code, as well as a step-by-step explanation of the analysis pipeline, is in a single Jupyter Notebook, an HTML version of which can be viewed at https://matsengrp. github.io/SARS-CoV-2_spike_multidms/ . For instance, variants with stop codons tended to have more negative functional scores in the BA.1 and BA.2 experiments compared with Delta. To help make scores more comparable between homologs, we truncated all functional scores from all experiments at a lower bound of −3.5 and an upper bound of 2.5 . The lowThe DMS experiments were performed with at least two biological replicates per homolog, where each replicate experiment used an independently synthesized barcoded variant library. Each of the Delta and BA.2 replicate experiments were performed with two technical replicates, and we combined all functional scores between pairs of technical replicates into a single dataset. For variants associated with multiple unique barcodes in a single biological replicate dataset, we averaged the variant’s score across all barcodes. This averaging step increased the speed of model fitting without substantially changing the final results (data not shown).Some sites in the spike protein were mutated in one or two of the homolog DMS libraries, but not all three. For instance, due to indels, some sites that are present in one homolog are completely missing in another. Since it is not possible to compute shifts across all homologs at such sites, multidms automatically discards all variants with mutations at any of these sites.We fit a single multidms model to one biological replicate dataset per homolog, using BA.1 as the reference, and using 30,000 proximal gradient iterations to allow the Huber loss term to converge . We theneplicate .The Results section reports data from multidms models fit using a regularization weight of λ=5×10-5 . In contWe also compared weights based on the model’s ability to predict experimentally measured functional scores in the training data, as quantified by the loss function used to train the model, not including the lasso term . As expe−5. This pattern is consistent with the hypothesis that the shift parameters from each replicate are overfit to their corresponding datasets at low weights, and that increasing the weight tends to reduce overfitting, leading to a higher correlation. Of note, at the highest tested weights, mutations that we experimentally validated to have large shifts were inferred to have shifts near zero, indicating that these weights are too strong. The correlation of We also quantified the correlation of shift parameters between the replicate model fits as a function of lasso weight . In eachrameters .In all, the above lines of evidence suggest that a lasso penalty https://github.com/dms-vep/SARS-CoV-2_Omicron_BA.2_spike_DMS/tree/main/library_design/plasmid_maps. Pseudoviruses were generated using a method described previously (Spike genes with desired mutations were introduced using PCR with overlapping mutation-carrying primers followed by HiFi assembly. Plasmids used as Delta, BA.1 and BA.2 spike templates can be found at eviously  with theSupplement 1


The main types of PD-L1 in the blood include soluble PD-L1 (sPD-L1), exosomal PD-L1 (exoPD-L1), and PD-L1 in circulating tumor cells (CTCs). However, the predictive and prognostic values of these three indicators in patients with non-small cell lung cancer (NSCLC) undergoing immune checkpoint inhibitor (ICI) therapy are unclear, warranting a systematic meta-analysis.P < 0.05 was regarded as significantly different.A systematic literature search was performed in the PubMed, Cochrane Library, and Embase databases. The pooled hazard ratio (HR) and 95% confidence interval (CI) values were extracted from the included studies to investigate the correlation between the three PD-L1 indicators and overall survival (OS) or progression-free survival (PFS). The Newcastle–Ottawa Scale (NOS) was used to examine the quality of the included studies. Subgroup analyses were employed to investigate the heterogeneity. The publication bias of the included studies was assessed using Begg's and Egger's tests. P < 0.001) and PFS . However, dynamic changes in sPD-L1 after immunotherapy were not statistically significant for OS  or PFS . Meanwhile, the upregulated pre-treatment exoPD-L1 levels were significantly associated with poor PFS , whereas the post-treatment dynamic upregulation of exoPD-L1 was significantly correlated with superior PFS  and OS . For PD-L1 in CTCs, the pooled results indicated that PD-L1 expression in CTCs was not significantly correlated with OS  and PFS .The pooled results revealed that high pre-treatment sPD-L1 levels were significantly associated with inferior OS (HR = 2.32, 95% CI = 1.68–3.18, Blood-based PD-L1 analysis is a potential strategy for predicting treatment efficacy and prognosis in patients with cancer.The online version contains supplementary material available at 10.1186/s12957-023-03215-2. Among the malignant tumors, lung cancer, a global public health issue, is the most frequent cause of tumor-related deaths globally . Small cImmune checkpoint inhibitors (ICIs) have improved the survival outcomes of patients with cancer . The US + CTCs) after immunotherapy were significantly and positively correlated with progression-free survival (PFS) [The use of blood-based biopsies to analyze PD-L1 expression in patients with cancer can overcome the challenges associated with the use of solid tumor biopsies. Compared with tissue biopsies, blood-based biopsy techniques have several advantages, including ease of sampling and reproducible monitoring of the dynamic biological changes in vivo . Some stal (PFS) , 27. Howal (PFS) . The rolhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023402077.The recommended reporting criteria for the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed to perform the meta-analysis. The study protocol was prospectively registered at PROSPERO (CRD42023402077) and is available at Relevant literature in the English language published up to February 23, 2023, was retrieved from the PubMed, Embase, and Cochrane Library databases. The following keywords were used: "non-small cell lung cancer," "lung cancer," "lung tumor," "lung neoplasm," "immune checkpoint inhibitor," "PD-1," "PD-L1," "anti-PD-1," "PD-L1," "programmed death 1 receptor," "programmed death ligand 1," "cytotoxic T lymphocyte antigen 4," "CTLA-4," "blood," "circulating tumor cell," "PD-L1," "soluble PD-L1," "exosomal PD-L1," "circulating PD-L1," "PD-L1 in CTCs," "sPD-L1," and "exoPD-L1." The references in the reviews were manually searched to identify additional related articles.Studies on patients with pathologically diagnosed primary or metastatic NSCLC; studies on patients undergoing ICI mono-therapy or ICI com-therapy (chemotherapy or targeted therapy); studies evaluating the correlation between PD-L1-based blood markers  and OS/PFS of patients with NSCLC; studies reporting the hazard ratio (HR) and 95% confidence interval (CI). If the HR was not directly available from studies, it was extracted from the Kaplan–Meier curve. When the univariate and multivariate analysis results were provided simultaneously, only the multivariate analysis results were extracted.Case reports, reviews, meta-analyses, conference abstracts, and letters; studies in which the full text was not available for download; studies that included animal experiments; studies in non-English language.Based on selection, comparability, and outcomes, the quality of the included studies was evaluated using the Newcastle–Ottawa scale (NOS). The NOS quality score ranged from 0 to 9. Studies with NOS scores of ≥ 7 and < 7 were categorized as high-quality and low-quality studies, respectively .Information, such as the name of the first author, the publication year, the region, the sample size, the age, the gender, the cancer stage, the cut-off value, the time point, the study design, and the outcome, was retrieved from each included study. Two authors (Qian Cui and Dong Wang) independently extracted data from univariate and multivariate analyses with HR and 95% CI for OS or PFS. Any controversy was addressed via discussion.I2 combined values were applied to analyze the heterogeneity of the results [P > 0.10 and I2 < 50% indicated low-level heterogeneity [P < 0.05. All statistical analyses were performed using Stata 15.1 software.The HR and 95% CIs were extracted to assess the association between these three blood-based PD-L1 indicators and survival outcomes of patients with NSCLC undergoing ICI therapy. Additionally, the association between clinicopathologic features and survival outcomes was evaluated by the HR and 95% CI. The HR values of > 1 and < 1 were considered adverse and favorable prognoses, respectively. Cochran's q-test and  results . P > 0.1ogeneity . SubgrouThe HR and 95% CIs were extracted to assess the association between these three blood-based PD-L1 indicators and survival outcomes of patients with NSCLC undergoing ICI therapy. Additionally, the association between clinicopathologic features and survival outcomes were evaluated by the HR and 95% CI.Literature searched in the PubMed, Embase, and Cochrane Library databases yielded 521 studies. Of these, 490 studies were excluded as they were duplications, animal studies, commentaries, and incomplete full texts. The complete texts of the remaining 36 articles were comprehensively evaluated. Of these, 22 studies were excluded, and 14 studies were included in this meta-analysis , 31–38. As shown in Table P < 0.001), and a significant heterogeneity was not observed among studies . As shown in Fig. P < 0.001), and these studies had low-level heterogeneity .As shown in Fig. P < 0.001; Table P < 0.001; Table P > 0.05; Table P > 0.05; Table I2 = 43.3%, p = 0.171).Subgroup analysis was performed based on the correlation of sPD-L1 with OS and PFS according to the time point, sample size, and region. No significant heterogeneity was observed in most subgroups Table . StratifP = 0.170). A moderate level of heterogeneity was observed among studies . As shown in Fig. + CTCs appeared to have a longer PFS than those with negative PD-L1 expression in CTCs, but this difference did not achieve statistical significance . A low level of heterogeneity was observed between studies .As shown in Fig. P > 0.05; post-treatment: HR = 0.83, 95% CI 0.35–1.98, P > 0.05; Table P > 0.05; post-treatment: HR = 0.95, 95% CI 0.50–1.80, P > 0.05; Table +CTCs were associated with superior OS when the sample size was ≤ 30 , and there was a high level of heterogeneity . The relationship between the post-treatment dynamic upregulation of exoPD-L1 and OS in patients with NSCLC undergoing ICI therapy was reported only by Yang et al. In particular, the fold-increasing changes of exoPD-L1 were significantly associated with longer OS .Two studies demonstrated the relationship between exoPD-L1 and prognosis in patients with NSCLC undergoing ICI therapy. Of these, one reported the correlation of exoPD-L1 with both OS and PFS, while another involved the correlation with only PFS. As shown in Fig. P < 0.001; Fig. P < 0.001; Fig. As studies on the correlation of pre-treatment exoPD-L1 with OS were not retrieved, subgroup analysis was performed with data on exoPD-L1 and PFS after different treatment durations. The results of the subgroup analysis revealed that the difference in treatment duration was the source of heterogeneity. The heterogeneity decreased to 0% in both the pre-treatment and post-treatment subgroups Fig. b. High pFive studies , 31, 33 P > 0.05)  and PFS . The subgroup analysis results revealed that high pre-treatment levels of sPD-L1 were significantly associated with poorer OS  and PFS . However, after immunotherapy, the upregulation of sPD-L1 was not significantly correlated with OS  or PFS . This result suggests that high pre-treatment levels of sPD-L1 can be considered a biomarker to predict the prognosis of NSCLC patients receiving ICIs. These findings are consistent with those of Han et al., who reported that lower pre-treatment sPD-L1 levels predicted improved PFS and OS [The analysis revealed that high levels of sPD-L1 were significantly correlated with worse OS  or PFS . Furthermore, pre-treatment and post-treatment subgroup analyses did not reveal significant differences. These results suggest that PD-L1+ CTCs may not be correlated with the prognosis of patients with NSCLC undergoing ICI therapy. Of the six included studies, three were pre-immunotherapy studies. Guibert et al. demonstrated that the PD-L1+ CTCs before immunotherapy were not significantly correlated with prognosis, but this correlation was significant in patients with treatment failure and disease progression [+ CTCs before immunotherapy and PFS [n = 17). However, Zhang et al. demonstrated that pre-treatment PD-L1+ CTCs were positively correlated with PFS and OS in patients with NSCLC treated with immunotherapy plus chemotherapy [+ CTCs have significantly longer PFS after immunotherapy [Recently, several studies have proposed that high expression of PD-L1 in CTCs is associated with a poorer prognosis in patients with various cancers treated with other therapies, such as chemotherapy or surgery , 49, 50.gression . Dhar et and PFS . This caotherapy . The resotherapy , 37. Howotherapy .P < 0.001; Fig. P < 0.001) and OS . In conclusion, the role of exoPD-L1 in determining the prognosis was reversed with the increase in treatment duration. Similarly, one study on solid tumors treated with anti-PD-1 therapy reported that the high pre-treatment exoPD-L1 levels predicted a short PFS [In this meta-analysis, only two studies related to exoPD-L1 were included. The pooled results showed that elevated pre-treatment exoPD-L1 levels were significantly linked to poorer PFS (HR = 4.44, 95% CI 2.87–6.89, hort PFS –56. Tumohort PFS . Additiohort PFS . Chen ethort PFS . Circulahort PFS . Howeverhort PFS , 26, 59.hort PFS . During hort PFS . This fihort PFS . Exosomehort PFS . Notablyhort PFS , 64.This meta-analysis has several limitations. First, the number of included studies and the sample size were small. Small-sample studies may overestimate the results of efficacy and prognostic evaluations. Second, the pooled results revealed that post-treatment sPD-L1 levels and PD-L1 expression in CTCs were not correlated with the prognosis of patients with NSCLC undergoing ICI therapy. This can be attributed to the high heterogeneity among the studies. Most studies have no definite consensus on the cut-off values of biomarkers and utilize various assay platforms, which may have contributed to the high heterogeneity of these studies and biased outcomes. Therefore, a criterion threshold must be established through a uniform and standardized protocol. In the future, the correlation of PD-L1 expression in CTCs and post-treatment sPD-L1 levels with the prognosis of NSCLC patients receiving ICI therapy needs to be validated using large-sample and multi-center clinical trials. Third, only three indicators were included in the analysis. EVs and some immune cells in the blood also contain PD-L1, such as dendritic cells and myeloid-derived suppressor cells , which wThe comprehensive meta-analysis of three blood-based PD-L1 indicators suggested that pre-treatment sPD-L1 and exoPD-L1 serve as unfavorable prognostic factors in patients with NSCLC undergoing ICI therapy. In contrast, the dynamic upregulation of post-treatment exoPD-L1 levels indicates a favorable prognosis. However, post-treatment sPD-L1 levels and PD-L1 expression in CTCs were not correlated with the prognosis of patients with NSCLC undergoing ICI therapy. The blood-based PD-L1 analysis can provide clinicians with a convenient biomarker and complement tPD-L1 analysis to improve the clinical application of ICIs. It is also a potential strategy for predicting treatment efficacy and prognosis in patients with cancer.Additional file 1. PRISMA Checklist.Additional file 2. Full search strategies.Additional file 3: Table S1. Correlation of OS/PFS and clinicopathological characteristic of NSCLC patients. Table S2. Results of Begg's and Egger's tests of 3 indicators related to PFS/OS. Fig.S1. Results of Begg's and Egger's tests of 3 indicators related to PFS/OS a, Beeg’s and Egger’s between sPD-L1 and OS; b, Beeg’s and Egger’s between sPD-L1 and PFS; c, Beeg’s and Egger’s between PD-L1 in CTCs and OS; d, Beeg’s and Egger’s between PD-L1 in CTCs and PFS; e, Beeg’s and Egger’s between exoPD-L1 score and PFS.


Graphene nanoplatelets (GNPs) were prepared using the electrolytic exfoliation method on graphite foil in an ammonium sulfate solution. A series of experiments were conducted in order to optimize the production of the flakes by varying the pH of the solution, applied voltage and current, duration of electrolysis, temperature in the electrolytic system, and type and duration of the ultrasound interaction. The quality of the produced graphene nanoplatelets was analyzed using X-ray diffraction, Raman and IR spectroscopy, and TEM. These σ bonds are responsible for the high mechanical strength of the material [Graphene is a two-dimensional 2D) material that is one atom thick and was first isolated by Geim and Novoselov in 2004 . Since tD materiamaterial . It is wmaterial ,6,7. Thematerial . A membrmaterial ,9. Anothmaterial . In addimaterial . The elematerial .N,N-dimethylformamide (DMF)) [8. The KC8 was then reacted with ethanol in order to form potassium ethanolate, thereby causing exfoliation and resulting in the formation of a carbon monolayers. The byproduct of this process was hydrogen, which helped to separate the single graphene layers from each other. A similar method based on the switching voltage technique and eutectic molten salts of NaOH and KOH was applied for graphite exfoliation by Alshamkhani et al. [42− anions [Graphene can be prepared in various ways, differing in price, ease of fabrication, and quality of the obtained product. The most common synthesis methods include chemical vapor deposition (CVD) ,14,15, me (DMF)) . Anothere (DMF)) . The scii et al. . The thii et al. . Comparei et al. ,29. Thisi et al. . The advi et al. . On the i et al. ,33. The − anions ,35.In the presented study, a combination of two types of liquid-phase exfoliation was used to produce graphene: electrochemical and ultrasonic extraction. In order to obtain a product of the best possible quality, parameters such as process duration, applied current and voltage, pH of the solution, time and type of the ultrasound interaction, and electrolyte temperature were modified. To the best of our knowledge, this is the first paper where systematic research has been undertaken to define the influence of the mentioned factors on the quality and quantity of the obtained graphene during electrolysis process.4)2SO4, Sigma Aldrich, ≥99.0%), pure graphite blocks, and graphite foils  were used as starting materials. In order to change the pH of the electrolyte, nitric acid , ammonia solution , and sodium hydroxide  were used. The solutions were made with the use of distilled water with a conductivity of 0.51 μS/cm and pH = 7. The graphene nanoplatelet reference material was produced by ACS MATERIAL . Aqueous solutions of acetone  and ethanol  were used in the ultrasonification stage. Hard filters type 380 with pore sizes in the range of 3–5 µm were used for filtration.Ammonium sulfate  were measured using a Nicolet iS50 infrared spectrometer using a KBr pellet method. The spectral resolution was 2 cm−1. The morphology of the flakes was studied using a Philips CM-20 SuperTwin transmission electron microscope with an accelerating voltage of 200 kV and a resolution of 0.24 nm. Scanning electron microscopy (SEM) FEI NovaNanoSEM 230 (USA) was used to reveal the graphene nanoplatelet thickness obtained at different voltages. The oxygen content in the GNPs was measured using an FESEM FEI Nova NanoSEM 230 scanning electron microscope equipped with an EDS spectrometer (EDAX Genesis). The zeta potential of the aqueous suspension of graphene nanoplatelets was measured and analyzed under the same conditions  using the a Zetasizer Nano ZS . The materials were dried in a FD-10-R Vacuum Freeze-Dryer from LABFREEZ .In the electrolysis process, a laboratory power supply from STAMOS (Model: S-LS-38) with a voltage regulated in the 0–30 V range and a current regulated in the 0–20 A was used to adjust the current flow through the electrolytic system. Liquid-phase exfoliation was obtained by the TF-900N sonicator by Tefic Biotech and the Proclean 3.0DSP ultrasonic cleaner by Ulsonix. XRD measurements were carried out on an X-ray diffractometer  with Cu Kα monochromatic radiation (λ = 1.5406 Å), scanning the diffraction angles (2θ) between 10° and 55° at room temperature in Bragg–Brentano geometry. The measurements of Raman spectra were performed with a Renishaw inVia Microscope Raman spectrophotometer equipped with a CCD detector. The tests were performed at room temperature using the 514 nm line of the argon laser. The spectral range was 200–3250 cmThe electrolytic system consisted of two cathodes, being two blocks of pure graphite with dimensions of 7 cm × 2 cm × 1 cm, and one anode, which was cut out of graphite foil into dimensions of 9 cm × 2 cm × 0.1/0.2 cm. The electrodes were 2 cm apart from each other and separated by spacers to counteract electrophoresis in the solution . Electro42− ions. The next step was the reduction of intercalated SO42− and the self-oxidation of water, the products of which were gas bubbles (SO2 and O2). The released gas destroyed the weak bonds, detaching graphite layers one from another. During the electrolysis process, it was possible to observe the release of hydrogen at the cathode and oxygen at the anode. Sediment accumulated at the bottom and part of the exfoliated material floated on the surface of the solution. The current increased during the process due to acidification of the electrolyte and the increase in graphene content in the solution. In order to obtain optimal electrolysis conditions, the following parameters were modified: voltage (from 6 V to 12 V), temperature of electrolyte (from 5 to 25 °C), time of the process (from 45 min to 90 min), and pH (from 3.0 to 10.3) of the electrolyte . The XRD results of the samples with the highest efficiency of graphene to graphite formation for a particular factor are presented in In order to investigate the purity of the prepared graphene nanoplatelets, X-ray diffraction analysis was performed. The results obtained for the GNPs were compared to those obtained for commercial samples and are presented in 2 planes were used for the calculations. The ratio of the area under the graphene band and the graphite peak allows determining their share in the particular sample [C) calculated for all samples is presented in To be able to compare results for samples obtained under different conditions, the content of graphene in the final product was determined on the basis of the XRD measurements. The area of the peak assigned to the graphite and a broad band related to the reflections of graphene spr sample . The gra42− to SO2 and a consequent absence of bubbles that exfoliate the graphene flakes. Another factor, the duration of the electrolysis process, was determined experimentally by running the process for the period of 45, 60, and 90 min. The analysis of the diffraction patterns showed that the highest graphene content in the final product was obtained for the 60 min process (4(SO4)2 standard solution used as the electrolyte in the exfoliation process was 5.3. To check the impact of pH on the course of reaction, the electrolyte was modified using nitric acid (HNO3) and ammonia water (NH3·H2O). The XRD analysis showed that an increase in the pH of the electrolyte had a positive effect. The content of graphene in the obtained product was increased at higher pH values  allowed for an assessment of the obtained graphene nanoplatelet size and quality and the presence of byproducts that formed during the synthesis . The in-depth analysis of the TEM images showed that the size distribution graphene of flakes was quite wide and depended on the synthesis conditions . The anaThe morphology of the samples obtained at different voltage was checked using scanning electron microscopy . The ana−1, 1580 cm−1, and 2680 cm−1, respectively. The presence of the G band is related to transverse vibrations, while D and 2D bands are related to longitudinal vibrations in the graphene plane. The difference between them consists of the conservation of momentum of the reflected photon. In the case of the D band, momentum is lost due to encountered defects; in the case of the 2D band, the defects are not involved. The analysis of both types of vibrations by comparing the ratio of the respective bands (D to G band) allowed determining the degree of deformation of the obtained carbon structure. By analyzing the full width at half maximum (FWHM) of the 2D band, the number of carbon layers could be determined [Raman spectroscopy was used for the qualitative analysis of the obtained graphene flakes. The Raman spectra of graphene were characterized by the presence of three primary bands denoted as D, G, and 2D. Their positions were at about 1350 cmtermined . The deptermined .D) of the obtained graphene flakes, as the ratio of the D-band intensity to the G-band intensity, was determined for the analyzed samples.The degree of deformation . The deformational vibrations of δOH and δNH contributed to the band observed in the range of 1500–1750 cm−1. The band slightly below 1500 cm−1 derived from υC–OH deformational vibrations and δCH deformation vibrations. The bands observed about 1120 cm−1 could be attributed to υCO and/or υCN stretching vibrations.Because of the high scattering of light in the measured samples, graphene was ground with KBr and then formed into a pellet; thus, the results obtained in the IR analysis were evaluated qualitatively rather than quantitatively . Interfe−1 could have arisen from the hygroscopicity of KBr. Any of the other modifications resulted in the formation of the same bands below 1500 cm−1, indicating the appearance of similar amounts of characteristic functional groups. The use of organic modifiers, such as acetone, resulted in characteristic absorption near 3000 cm−1, suggesting the presence of CH groups.The changes in IR spectra depending on the method used were small, but allowed some very general conclusions to be drawn. The sample that was not modified (10 V) contained the fewest types or no functional groups on the surface, as the observed bands above 1600 and 3000 cmThe zeta potential is a measurement of the repulsive and attraction forces between particles suspended in liquids. The investigation was performed on selected samples from previous experiments. For the experiment, freeze-dried flakes were suspended in water using ultrasound. It is known that a lower zeta potential value indicates a higher stability of the particle dispersion in solution. Stable colloids are formed when the absolute value of potential is higher than +30 or lower than −30 mV . The val3·H2O would increase the price of the process due to the need of using large amounts of it. Considering the ratio of product quality to the price, it was decided to continue the research without changing the pH of the electrolyte. On the basis of the conducted measurements, it was found that the most favorable power and operating time of ultrasound process were 630 W and 15 min, respectively. It is also recommended to use an ice bath during the operation of ultrasound. Lowering the temperature prevents the separated graphene layers from reassembling, which ensures better quality. Mass analysis showed that, with an increase in acetone concentration in the electrolyte, the amount of the product obtained dropped sharply. The average relative weight of graphene obtained with a 33% acetone solution was halved, while the difference was up to 80% with a 50% solution. The experimental work aimed to obtain the largest possible amount of good-quality product with minimal financial and time consumption. As such, sonification of graphene should be conducted in water or 33% acetone solution. On the basis of the analysis of data obtained with the use of XRD, TEM, Raman/IR spectroscopy, and zeta potential measurements, the following parameters were determined as optimal to give the best quality, highest mass, and the lowest process price of the product: constant voltage of the system equal to 10 V, process temperature reduced by an ice bath, 5.3 pH of the electrolyte (0.1 M solution of (NH4)2SO4), and process time of 60 min. The solution of the electrolysis product should be prepared using pure water  and then subjected to ultrasound (630 W) for 15 min. To obtain dry graphene nanoplatelets, the sonicated product should be frozen and evaporated using a freeze-dryer.In order to optimize the process of obtaining graphene nanoplatelets by combining the electrochemical exfoliation and exfoliation methods in liquid phase using ultrasound, the following parameters were investigated: applied voltage, process duration, temperature, and pH of the electrolyte. The influence of acetone content in the solution of graphene obtained after electrolytic exfoliation and interaction of this solution with different power and duration of ultrasound was also examined. By selecting the optimal voltage (10 V), it was possible to obtain a significantly larger mass of the product while also providing a slight difference in its quality. Another important factor that increased the yield of the process was the temperature of the reaction environment. At 5 °C (ice bath), the mass of the graphene nanoplatelets could even be even doubled as compared to the exfoliation in 15 °C (water bath) and tripled if the temperature was not controlled. A change in the electrolyte pH had a positive effect on the quality of the obtained graphene. However, the use of NH


The CC@rGO composite comprises a spherical heterostructure uniformly distributed between graphene sheet layers, preventing stacking the graphene sheet layer. After the introduction of cobalt heterojunction on a graphene substrate, the Co element content increases the reactive sites of the composite and improves its electrochemical properties to some extent. The composite exhibited good cycling performance with an initial discharge capacity of 847.51 mAh/g at 0.5 C and a capacity decay rate of 0.0448% after 500 cycles, which also kept 452.91 mAh/g at 1 C and in the rate test from 3 C back to 0.1 C maintained 993.27 mAh/g. This article provides insight into the design of cathode materials for lithium-sulfur batteries.An interlayer nanocomposite (CC@rGO) consisting of a graphene heterojunction with CoO and Co Lithium-ion batteries have been studied extremely extensively over the past few decades and are used in portable and mobile electronic devices ,2. Howev2-SnS2 [3O4-MnS [3O4-CoP [2-SnS2 nanosheet heterojunctions to determine for the first time the interfacial effect in lithium-sulfur batteries, which improved the diffusion efficiency of ions and significantly accelerated the redox reaction [Various strategies have been proposed to overcome these challenges, including well-designed cathodes, modified separators, and new-developed electrolytes . In the 2-SnS2 , Mn3O4-M[3O4-MnS , and Co3[3O4-CoP . For insreaction . Qin et reaction . Zhang ereaction . Most of9S8 heterojunction composite nanomaterials (CC@rGO). CoSO4, graphene, and chitosan were used as the Co source, carbon source, and supplementary carbon source, respectively. The Co2+ ions were assembled with negatively charged functional groups on graphene oxide through electrostatic adsorption, followed by a hydrothermal-high temperature reduction to generate CoO/Co9S8 heterojunctions uniformly distributed between graphene lamellae. The CC@rGO electrode exhibited excellent cycling stability and rate performance, thanks to graphene’s large surface area and numerous ion-electron transport channels, the built-in accelerating electric field of CoO/Co9S8, and the ability to trap and transform polysulfides. This study provides valuable insights into the potential application of carbon material–metal compound composites in lithium-sulfur battery cathode materials, which may lead to the development of more efficient and sustainable energy storage systems.This study presents a hydrothermal–calcination method for synthesizing rGO-CoO/Co2O2 was added to it to obtain a bright yellow graphene oxide solution. After being cooled, the graphene oxide was left to separate, centrifuged to a pH of 7, and finally freeze-dried, as previously reported by our subject group [Graphene oxide was prepared by modified Hummer’s method. Two grams g scaled graphite powder were added to 250 mL of a mixed acid solution of sulfuric acid-nitric acid (volume 9:2). A total of 12 g of potassium permanganate was added to it and the temperature was increased to 50 °C (40 min), 60 °C (7 h), 90 °C (30 min), and finally, 30 mL of Hct group ,33.9S8/CoO/rGO, abbreviated as CC@rGO) was obtained by calcination at 500 °C for 2 h in the Ar atmosphere. rGO samples were made by the same procedure without the addition of cobalt sulfate and chitosan.A suspension of graphene oxide was prepared , then 2 g of cobalt sulfate and 0.3 g of chitosan were added to 50 mL of deionized water (solution B), and A and B were homogeneously mixed, and transferred to a PTFE-lined reactor, hydrothermally heated at 180 °C for 12 h. The precursor powder was obtained by freeze-drying. The black powder , and binder (PVDF) were ground at 7:2:1 and added to a certain amount of NMP, and stirred for 12 h to make a slurry, coated on carbon-coated aluminum foil, dried at 60 °C for 12 h, and then stamped into a 12 mm × 12 mm circular positive electrode by a press.2 adsorption and desorption experiments .The microscopic morphology of the samples was observed by scanning electron microscopy  as well as elemental analysis . X-ray diffraction analysis  was used to characterize the sample lattice structure in the interval 10°–90° at 5° per minute. Transmission electron microscopy images  were used to obtain the internal microstructure. X-ray photoelectron spectroscopy images were acquired by K-Alpha . To obtain Raman spectra, a Renishaw micro confocal laser Raman spectrometer (633 nm) by HR800  was used. Thermal gravimetric analysis  was used to analyze sample sulfur loading. The specific surface area and pore size distribution before and after modification were analyzed using N3 . Lithium sheets  were used for the negative electrode of the half-cells. Coin cell constant current charge/discharge test was performed in the voltage window range of 1.7–2.8 V. Electrochemical AC impedance (EIS) testing, as well as cyclic voltammetry (CV) testing was performed at the Princeton Electrochemical Workstation , with EIS frequencies ranging from 1 × 10−2 Hz to 106 Hz. Li2S6 adsorption experiments were used to verify the adsorption capacity of the material (0.05 M Li2S6 dissolved in 1:1 DME: DOL).A coin cell (type CR2032) was used for electrochemical testing of the rGO as well as the CC@rGO. A 12 mm × 12 mm circular positive electrode sheet was assembled into a cell in a glove box, and the electrolyte used consisted of 1.0 M LiTFSI -DOL: DME with a 1:1 volume ratio and 2% LiNO2+ combines with the negatively charged oxygen-containing functional group on GO under the effect of electrostatic adsorption, and after the removal of the oxygen-containing functional group by hydrothermal heat, Co2+ fills the oxygen vacancies generated after the removal of the oxygen-containing functional group and achieves the uniform distribution of Co2+ among the graphene sheets. After calcination at 500 °C, CoSO4 was calcined and reduced to CoO and Co9S8 heterogeneous spheres, which were uniformly distributed between the graphene lamellae, forming a typical wrapping structure. Graphene and heterojunction  composites can not only physically limit the dissolution of polysulfides into the electrolyte through the porous structure of graphene, but also trap and transform polysulfides through the heterojunction, inhibiting the shuttle effect that occurs when polysulfides shuttle through the diaphragm to the surface of the lithium sheet and react to cause a decrease in capacity and lifetime.As shown in 9S8@rGO composites, CoSO4/C@GO precursors were prepared by hydrothermal mixing and calcined to generate CoO/Co9S8@rGO composites (labeled as CC@rGO).To prepare CoO/Co9S8, respectively, proving the generation of CoO and Co9S8. rGO exhibits a distinct (002) interface at 26°, which has the amorphous broad peak that is amorphous carbon at 26°. The composites, on the other hand, did not show a clear broad peak at 26°, which indicates a clear amorphization trend of graphene during the carbon thermal reduction process and the disappearance of the broad peak [The compositional analysis of rGO and CC@rGO was carried out using XRD, as shown in oad peak .−1 and 1600 cm−1, corresponding to the D and G peaks [−1 and 1590 cm−1, respectively, which was believed to be due to the addition of heterojunctions that make the material structure vibrate and shift. The double peaks of CC@rGO at 466 cm−1 and 676 cm−1 were considered to be strong interactions between CoO and Co9S8 [D/IG of CC@rGO is reduced from 1.1 to 1.035 and the defects of the material are reduced [Raman spectroscopy was performed for CC@rGO and rGO to measure the disorder of different samples, and the results are shown in  G peaks ,35, respnd Co9S8 ,37. Comp reduced . The add reduced . Meanwhi9S8 have uniformly distributed between graphene lamellar layers as seen in 2+ with oxygen-containing functional groups on graphene during the hydrothermal process.The microstructure and elemental distribution of rGO and CC@rGO were observed by scanning electron microscopy and elemental energy spectroscopy, respectively. As shown in 9S8, respectively  and S2p1/2 (162.8 eV) attributed to metal-S bonds [x-C species [There are also two sets of satellite peaks  in the S2p high-resolution spectrum, with peaks at S2p-S bonds ,43. The 3/2 1.8 eV an species ,44. The 2/g to 46.112 m2/g after compounding the heterojunctions due to the incorporation of heterogeneous spheres with a smaller specific surface area. The pore size , on the other hand, decreased from 8.16 nm to 4.46 nm. The smaller pore size will melt the sulfur-loaded process to encapsulate the sulfur well in the pore channel and maintain sufficient stability. At the same time, during the melting process, due to the good wettability between carbon and sulfur, sulfur will penetrate inward through the capillary of carbon, and when the pore size becomes larger, the capillary force is not enough to let sulfur enter completely. In this way, the small pore size will achieve a better encapsulation of sulfur as well as a better inhibition of polysulfide diffusion. In addition, the small pore size will make the sulfur layer on the material surface thinner, improve the sulfur utilization, and accelerate the electron and ion transfer efficiency; meanwhile, increasing the contact area of the electrolyte will promote the electrolyte to infiltrate the material, reduce the interfacial impedance, and finally reduce the electrochemical polarization [As shown in rization ,48,49.The composites’ large surface area and thin mesoporous structure will make it easier for the cell’s electrolyte to penetrate the material, which will lower interface impedance, increase charge exchange efficiency, hasten the conversion of sulfur intermediate species, and enhance the cell’s electrochemical performance. As shown in 9S8 heterostructure. It can effectively activate more sulfur-active material while maintaining good cycling stability and promoting the kinetic conversion of polysulfides. The cycling test of CC@rGO using 1C cycling current shows that the first turn discharge capacity is 452.91 mAh/g and the decay rate is 0.0639% after 500 cycles, which further demonstrates the good structural stability and electrical conductivity of the composite material.To characterize the electrochemical performance of the composites with wrapping structure, a series of electrochemical characterizations were performed for the cells assembled with rGO and CC@rGO, respectively. To characterize the electrochemical properties of the composites, CC@rGO and rGO were assembled into CR2032 button cells, respectively. As shown in 9S8 heterojunctions between nonpolar graphene sheets provides abundant polysulfide action sites, effectively suppressing the loss of active material sulfur caused by the “shuttle effect” and reducing the appearance of dead sulfur during the cycling of lithium-sulfur batteries.The rate electrochemical characterization of CC@rGO was performed and the results are shown in 2Sx, 4 ≤ x ≤ 8) and the reduction of soluble polysulfide to insoluble polysulfide  during discharge, respectively [The electrochemical performance of rGO and CC@rGO cells was compared at a scan rate of 0.1 mv/s and a voltage window of 1.7–2.8 V. The two typical reduction peaks  characterized by CC@rGO correspond to the reduction of S to soluble polysulfide  of CC@rGO is reduced from 133 Ω to 88 Ω. The improved tilt of the Warburg curve in the low-frequency region is attributed to the increased conductivity of the composite material after the addition of the heterostructure, which can better perform the adsorption-transformation of polysulfides [The electrical conductivity of the cells assembled from the composites was further tested, and the Nyquist curves were shown in sulfides ; meanwhi2S6 adsorption experiments were carried out to further verify the adsorption capacity of the composites. After 12 h adsorption in 0.05 M Li2S6 solution, the supernatant of CC@rGO on the right side was clarified, while the rGO on the left side still showed a pale yellow color, indicating that CC@rGO has excellent static adsorption ability, which is consistent with the previous characterization results. This indicates that the composites have a better ability to trap polysulfides, which is attributed to the excellent adsorption of polysulfides by metal oxides and the porous structure of graphene, both of which synergistically enhance the performance of the composites.As shown in In 9S8 heterojunction-rGO composites by electrostatic adsorption and calcination. CoO/Co9S8 heterojunction acts as a polysulfide adsorption transformation, while rGO acts as a sulfur-carrying carbon carrier and provides ion and electron transport channels. Due to the wrapping structure, it can play a synergistic-catalytic role well, suppressing the “shuttle effect” of LiPSs and accelerating the electro-kinetic reaction. The results show that the CC@rGO sulfur cathode has good electrochemical performance, good rate performance, and cycling stability at different current densities, and the Coulomb efficiency is always maintained above 97%. Therefore, this electrode material design can provide new insights into the design and development of sulfur carriers for lithium-sulfur battery cathodes.In summary, we propose the preparation of CoO/Co


Migration pattern suggests the more stable dipeptide model bears serine in βL, γD, γL and the alanine in γL and γD configurations. The investigation of side‒chain‒backbone interactions revealed that the most stable conformer, γD–γL, is in the β‒turn region of Ramachandran map; therefore, serine-alanine dipeptide model should be adopted with a β‒turn conformation. Intramolecular hydrogen bonding in β‒turns consideration by QTAIM disclosed γD–γL includes three hydrogen bonds. The computed UV‒Vis spectrum alongside of NBO calculation showed the five main electronic transition bands derived of n → n* of intra‒ligand alanine moiety of dipeptide structure.The conformational analysis of The online version contains supplementary material available at 10.1186/s13065-023-01051-9. The optical purity have key effect on property and should be carefully controlled, i.e. l‒amino acids, in most cases, show a biocompatible identity, but d ‒amino acids may have harmless effects ‒ala‒NHMe [eactions . The proectively , 21. Theectively . Moreoveala‒NHMe  and n‒Acala‒NHMe  tripeptid/l‒alanyl‒d/l‒serine dipeptide have been determined in aqueous solutions by means of potentiometry and calorimetry [2 dipeptide were investigated by the aid of quantum chemical calculations. All peptide bonds of HCO‒ser‒ala‒NH2 dipeptide are in the trans isomeric state, and chiral α‒carbons are in the D enantiomeric state [The thermodynamic properties of protolytic equilibria of orimetry . For theic state .N‒formyl and amine functionalities were attached to the terminus of dipeptides. These moieties safeguard the mimetic of conformational properties of polypeptides and protein segments and simulate the spatial and inductive contacts of those adjacent ser‒ala (sa) amino acid residues.d‒ser‒d‒ala‒NH2 on the Ramachandran map, [ level of theory. However, it is possible that some conformers were lost and less than 243 conformers would be found. Migrations of nonexistent conformers can assist to identification of the relative stabilities and instabilities of the different conformations  and M06‒2x/6‒311 + G  levels of theory in the gas and water solvent. The L and D forms of ser-ala protected dipeptide have been investigated in the previous [The numbering of atomic sequence in the sa‒protected dipeptide was performed under the standardized numbering system , which pprevious , and preβ‒turn is highly variable that can be classified based on the dihedral angles contents of ϕ and ψ of the central residue (Table The backbone (BB) conformation of the ue Table . The devβ‒turn secondary structures exist in types I, II, and III. However, their conformational enantiomers , and VIa1, VIa2, VIb, and VIII types of β‒turns are less common. Conventionally, eight types of β‒turns have been distinguished and those not defined are classified as type IV. The turns comprise n consecutive residues (i to i + n), according to some reports, the distance between α‒carbon of residues symbolized as i and i + n, must be smaller than 7 Å or 7.5 Å [γ‒turns (n = 3), [β‒turns (n = 4), [α‒turns (n = 5) [π‒turns (n = 6) [7), 10 (C10), 13 (C13) and 16 (C16) membered hydrogen bonded (H‒bonded) rings for γ‒, β‒, α‒ and π‒turns, respectively. The term Cn interaction is used when the H‒bond (HB) leads to the formation of a n‒membered ring, include of the donating NH and the accepting CO groups [β‒turn structures, as defined by C.M. Venkatachalam were characterized by a HB between the N‒H and C=O of residues i and i + 3, respectively [n interactions that lead to the formation of a n‒membered ring for n = 5, 7, and 10 were shown in Scheme β‒turn is a multifaceted process driven in part by local torsional preferences, inter‒strand H‒bonding can offer additional stabilization of the turn [Usually, or 7.5 Å , 33. The(n = 3),  β‒turns (n = 4),  α‒turns  (n = 5) , 37 and  (n = 6) , 39. TheO groups . The mosectively , that gethe turn . Anotherthe turn –49, in tthe turn , 48. In The further structural consideration of the studied stable conformers of sa‒protected dipeptide was applied by the UV‒Vis spectrum and Frontier Molecular Orbitals (FMOs) investigations. These complementary results can be used for better understanding of the dipeptide structure.β−turn conformers and Frontier Molecular Orbitals investigations by UV–Vis spectrum and NBO considerations of the most stable conformer of dipeptide model were performed. These interesting studies can be presented as the main novelty and differentiation related to the previous reported results by us [In the present research, the new calculations including of the effect of solvent (water) dielectric constant on the stability of ts by us . Moreoven−formyl−d−serine−d−alanine−NH2 was modeled with each residue and protecting group segments were separately for the entirety of the peptide chain numbered. Then, formyl and amide functionalities were attached to the N‒ and C‒terminuses of the dipeptide, respectively for safe guarding the mimetic of steric effects of the neighboring amino acid residues.First, α‒carbon atom of the amino acid subgroups denoted as , , and φ, and ψ dihedral angles specify the BB, while the χ describes the side-chain conformation of the dipeptide. The rotations around φ1, ψ1, φ2, ψ2, and χ were considered most relevant to the shape and stability of sa-protected dipeptide model. The rotation around χ resulted in side-chain conformers that are defined as gauche ( +) (g +), anti (a), and gauche ( −) (g−). Initially, the fully relaxed optimization in the gas phase without any symmetry constraints  was employed at B3LYP [d,p) basis set. M06‒2X is a hybrid meta exchange‒correlation functional and one of the best functioning for studying the organic and biological small molecules [β‒turn conformers. Additionally, the effect of solvent on β − turn structures was calculated using the SCRF keyword with Tomasi’s polarized continuum model  [d−ser−d−ala−NH2 were optimized by restraining the serine residues to the nine conformations, (−) along χ side − chain dihedral angle are present, the multidimensional conformational analysis (MDCA) would lead to the existence of 35 = 243 conformers. In addition, the theoretical electronic transitions (ETs) of vacuous phase of UV‒Vis spectrum of dipeptide optimized geometry were done using time‒dependent DFT (TD‒DFT) calculations. Both of singlet and triplet states were respected; while excitations to triplet excited states were prohibited. Partial atomic charges and Natural bond orbital (NBO) analyses were also computed using B3LYP‒D3/6‒311 + G  level of theory. All computations concerning conformers of serine‒alanine protected dipeptide were carried out by the GAUSSIAN 09 program package, [β − turn structures. The wave functions used in the QTAIM analyses were generated at the B3LYP‒D3/6‒311 + G  and M06‒2X/6‒311 + G  levels of theory. The related calculations were carried out using the AIMAll program [The sa‒protected dipeptide was separated into four units: 1) The N‒terminus protecting group, (2) the D‒ser residue, (3) the D‒ala residue, and (4) the C‒terminus protecting group. A standardized numbering system was separately used into and along the peptide BB to define the numbered dipeptide  , 55. Frepackage,  at 298.1package,  were per program .−1) of different conformations bearing different side‒chain dihedral angles  conformer is more stable than gauche ( −). This is also in agreement with the results that the anti-conformer is the most stable .φ, ψ, and ω, lead to a potential energy hypersurface ). Since in a trans amide bond conformer, the ω torsional angle has a constant value of 180º, the hypersurface E = E  can be simplified to E = E . The calculated results at the B3LYP/6‒311 + G  show that 87 stable conformers were characterized, and the rest changed to the more stable ones. Initial and final optimized conformations , and gauche ( −) side-chain forms) of all 243 possible ones of the sa-protected dipeptide were reported in supplementary information . The three more stable conformers of anti, gauche ( +), and gauche ( −) BB conformers of sa‒protected dipeptide are ((2.95), 4.13(3.14), 4.29(4.29)), (5.91(5.16), 8.22(7.20), 8.27(6.23)) and (0.00(0.00), 2.30(2.13), 4.03(3.88)), respectively. These results confirm the previous section that for the ser and ala residues, the  of the (i + 1)th and (i + 2)th positions. It can result that, 22 cases of the 87 found conformations of For‒d‒ser‒ d‒ala‒NH2 can be categorized as the β − turns. All conformers of β − turns were optimized and verified to be at the minimum energy through vibrational analysis (no imaginary frequency mode). The optimizations of all 22 β − turns structures and frequency calculations were carried out at the B3LYP, B3LYP‒D3 and M06‒2X levels using the standard 6‒311 + G  basis set in gas and solution phases. To study the effect of solvent on the stability of β − turn structures, the quantum mechanical calculations were performed in water using Tomasi’s polarized continuum model at the M06‒2X/6–311 + G  level of theory.β − turns in gas and solution phases at the B3LYP‒D3/6–311 + G  and M06‒2X/6–311 + G  levels of theory, are provided in Table β − turns according to their type, torsional dihedrals  levels of theory in the gas and water phases, was reported in the supplementary information  level of theory are shown in Table As shown in Tables β−turn structures have lesser relative energies and the higher stability. The energy decreasing by a dimensionless factor of 1/ε, (ε is the dielectric constant), is appropriate if the polarized or charged particles are immersed in any medium other than a vacuum. It can be mentioned that a weaker interaction in a polarizable medium  than a vacuum should be formed [μ), are dissolved in polar liquids. The dipole‒dipole interaction between solvent and solute can decrease the relative energies [β−turn structures in the solvent and gas phase is different, which is due to the effect of solvent dielectric coefficient. For example, in the gas phase,β−turn. Increasing the dipole moment of the −1, respectively. Therefore, the However, the results of the solution phase showed that all e formed . Polar menergies . The ordβ − turn structures are stabilized by forming IHBs known as a β−turns are open, which means without any intraturn HB [The aturn HB .ρ value, the more tremendous interaction energy and the positive The theory of QTAIM provides a proper approach to elucidate the intermolecular interactions by considering the total electronic density,s (BCPs) –67. The –1 a.u. along with the negative value of van der Waals and HB interactions, respectively [The high value of eraction . Neverthectively , 67, 69.ectively .HB) of β‒turn structures at the B3LYP‒D3 and M06‒2X levels of theory using the 6‒311 + G  basis set are summarized in Table HB of −1 with distance (r) of 2.07, 2.06, 2.18, and 2.07, 2.09, 2.17 Å at the B3LYP‒D3 and M06‒2X levels of theory, respectively that are in agreement with previous studies, (the NH···OC distance in C10 structures is around 2.10 − 2.20 Å) [β‒turn structures, different types of HBs including A), F), S), A), The topological parameters and IHB energy E 2.20 Å) , 72. The.20 Å , 7HB values [β‒turn conformers in the ranges of 0.014‒0.027 and 0.015‒0.025 a.u. and HB amounts in the range of 2.74‒6.32 and 3.17‒6.25 kcal mol−1 at the B3LYP‒D3 and M06‒2X levels of theory, respectively. The highest and lowest amounts of HB for C7A IHB belonging to the β‒turn secondary structures, respectively. As shown in Table HB are in the ranges of (0.011‒0.036 a.u.), (0.040‒0.121 a.u.),  and (0.013‒0.032 a.u.), (0.048‒0.121 a.u.), , respectively. The residues possessing an HB acceptor and/or donor site potentially lead to a NH → side chain and/or side chain donor → backbone CO HB that are observed concomitantly with backbone − backbone HBs. This is the case for instance with the Ser, His, Asn, and Gln side chains, where an extended locking through multiple bonds occurs between the backbone and the side chain [β‒turns have lowest EHB, whereas, C7F interaction of β‒turn, show the highest one, respectively ,  and ,  at the B3LYP‒D3 and M06‒2X levels of theory, respectively , (in a.u.) at the M06‒2X level of theory for three conventional C7A, C7F, β-turns are shown in Fig. A, HB for these interactions is  kcal mol−1, respectively. Also, the values of V(r) and EHB for C7A, C7F,−1), respectively  level of theory. The computed electronic transitions in vacuo by TD − DFT method show several sharp bands assigned to intra‒charge transfer (CT) in the respected dipeptide.Herein, the electronic study of the most stable conformer of HCO − s and p orbitals. The 49 (HOMO−5), 50 (HOMO−4), 51 (HOMO‒3), and 53 (HOMO‒1) consist primarily of lone pair(s) electrons of atomic orbitals of oxygen atoms of alanine part of sa‒protected dipeptide  and 56 (LUMO + 1) and 58 (LUMO + 3) consist primarily of anti−bonding Rydberg molecular orbitals of hydrogen atoms of alanine moiety of sa‒protected dipeptide . Therefore, it can be said that all of the computed ET bands can be assigned to the n → n* intra−ligand charge transfer (ILCT) transitions  at 164.8, 166.9, 172.7, and 186.2 are attributed to CT of intra transfer of alanine amino acid residue within CT from 49 (HOMO−5), 50 (HOMO−4), 51 (HOMO−3), and 53 (HOMO−1) to 58 (LUMO + 3), respectively. Also, the last one (λ5) at 191.6 nm could be assigned to CT of intra charge transition of alanine amino acid part of dipeptide from 53 (HOMO−1) to 56 (LUMO + 1).However, the computed UV−Vis spectrum of sa‒protected dipeptide indicates several main CTs that five major ones can mention as 164.8, 166.9, 172.7, 186.2 and 191.6 nm see Fig. . The eled−ser−d−ala protected dipeptide was performed using B3LYP/6‒311 + G  calculations in the gas phase. In addition, all β−turn structures were optimized in the gas and solution phases and verified to be at the minimum energy using DFT‒B3LYP‒D3 and M06‒2X levels of theory. Also, the β−turn conformers have been considered at that those same levels of theory by using QTAIM. According to MDCA, the whole 35 = 243 plausible conformers were investigated. The results show that 87 stable conformers were found and 156 ones changed to some different more stable conformations among the found conformations. It can be highlighted that d‒ser‒d‒ala‒NH2 can be categorized as the β−turn structures bearing A complete conformational analysis of the i and i + 3 in β−turns with EHB of 3.62, 3.67, 2.62, and 3.72, 3.52, 2.78 kcal mol−1 at the B3LYP‒D3 and M06‒2X levels of theory, respectively. The β‒turn, is the most stable one that includes three IHBs  and gauche (−) side-chain conformations. Table S2. Classification of β−turn conformers of sa-protected dipeptide according to their type, torsional dihedrals μ) (Debye), at the B3LYP‒D3 and M06‒2X/6‒311+G  levels of theory in the gas and water phases.