Firestorms on Social Media: Effects of Social Information Characteristics on Customer Responses

Firestorms on social media have become one of the biggest challenges for organizations engaging with such online platforms. Handling a firestorm on social media has not been easy because customers\u27 responses towards the incident is influenced by not only the original content, but also others’ responses towards the firestorm on the platform. Drawing on social impact theory and the dual-process model of social influences, this study develops a conceptual framework and explores the effects of social information characteristics (i.e., strength, number, and immediacy) on the customers\u27 perceptions of social influences (i.e., social proof and social pressure), and then their immediate and distal responses towards the organization. The conceptual framework will be tested with social media users using a focus group study and an experiment. This study is expected to contribute to the growing body of knowledge of firestorms on social media and provide organizations with insights into tackling such firestorm

Firestorms on Social Media: Effects of Social Information Characteristics on Customer Responses

Firestorms on social media have become one of the biggest challenges for organizations engaging with such online platforms. Handling a firestorm on social media has not been easy because customers' responses towards the incident is influenced by not only the original content, but also others’ responses towards the firestorm on the platform. Drawing on social impact theory and the dual-process model of social influences, this study develops a conceptual framework and explores the effects of social information characteristics (i.e., strength, number, and immediacy) on the customers' perceptions of social influences (i.e., social proof and social pressure), and then their immediate and distal responses towards the organization. The conceptual framework will be tested with social media users using a focus group study and an experiment. This study is expected to contribute to the growing body of knowledge of firestorms on social media and provide organizations with insights into tackling such firestorm

Prognostic Value of Choline and Other Metabolites Measured Using 1H-Magnetic Resonance Spectroscopy in Gliomas: A Meta-Analysis and Systemic Review

Glioma is the most prevalent primary central nervous system malignant tumor, with high heterogeneity observed among different grades; therefore, non-invasive prediction of prognosis could improve the clinical management of patients with glioma. 1H-magnetic resonance spectroscopy (MRS) can estimate metabolite levels non-invasively. Multiple studies have investigated its prognostic value in gliomas; however, no consensus has been reached. PubMed and Embase databases were searched up to 20 October 2022 to identify studies investigating the prognostic value of metabolites using 1H-MRS in patients with glioma. Heterogeneity across studies was evaluated using the Q and I2 tests, and a fixed- or random-effects model was used to estimate the combined overall hazard ratio (HR). Funnel plots and Begg tests were used to assess publication bias. Higher choline levels were associated with shorter overall survival (HR = 2.69, 95% CI, 1.92–2.99; p < 0.001) and progression-free survival (HR = 2.20, 95% CI, 1.16–4.17; p = 0.02) in all patients; however, in pediatric gliomas, it showed no significant correlation with overall survival (HR = 1.60, 95% CI, 0.97–2.64; p = 0.06). The estimated choline level by 1H-MRS could be used to non-invasively predict the prognosis of patients with adult gliomas, and more studies are needed to evaluate the prognostic value of other metabolites

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

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

Clinical updates on gliomas and implications of the 5th edition of the WHO classification of central nervous system tumors

BackgroundThe 5th edition of the World Health Organization (WHO) classification of central nervous system tumors incorporated specific molecular alterations into the categorization of gliomas. The major revision of the classification scheme effectuates significant changes in the diagnosis and management of glioma. This study aimed to depict the clinical, molecular, and prognostic characteristics of glioma and its subtypes according to the current WHO classification.MethodsPatients who underwent surgery for glioma at Peking Union Medical College Hospital during 11 years were re-examined for tumor genetic alterations using next-generation sequencing, polymerase chain reaction-based assay, and fluorescence in situ hybridization methods and enrolled in the analysis.ResultsThe enrolled 452 gliomas were reclassified into adult-type diffuse glioma (ntotal=373; astrocytoma, n=78; oligodendroglioma, n=104; glioblastoma, n=191), pediatric-type diffuse glioma (ntotal=23; low-grade, n=8; high-grade, n=15), circumscribed astrocytic glioma (n=20), and glioneuronal and neuronal tumor (n=36). The composition, definition, and incidence of adult- and pediatric-type gliomas changed significantly between the 4th and the 5th editions of the classification. The clinical, radiological, molecular, and survival characteristics of each subtype of glioma were identified. Alterations in CDK4/6, CIC, FGFR2/3/4, FUBP1, KIT, MET, NF1, PEG3, RB1, and NTRK2 were additional factors correlated with the survival of different subtypes of gliomas.ConclusionsThe updated WHO classification based on histology and molecular alterations has updated our understanding of the clinical, radiological, molecular, survival, and prognostic characteristics of varied subtypes of gliomas and provided accurate guidance for diagnosis and potential prognosis for patients

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

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

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

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

Rrp6 Regulates Heterochromatic Gene Silencing via ncRNA RUF6 Decay in Malaria Parasites

Malaria remains a major public health and economic burden. The heterochromatin environment controls the silencing of genes associated with the fate of malaria parasites. Previous studies have demonstrated that a group of GC-rich ncRNAs (RUF6) is associated with the mutually exclusive expression of var genes, but the underlying mechanisms remain elusive. Here, through a series of genetic manipulation and genome-wide multiomics analysis, we have identified the plasmodial orthologue of RNA exosome-associated Rrp6 as an upstream regulator of RUF6 expression and revealed that the dysregulation of RUF6 upon Rrp6 knockdown triggered local chromatin alteration, thereby activating most heterochromatic genes via direct interaction of RUF6 and distal gene loci. This finding not only uncovered the in-depth mechanism of RUF6-mediated regulation of heterochromatic genes but also identified Rrp6 as a novel regulator of gene expression in human malaria parasites, which provides a new target for developing intervention strategies against malaria.The heterochromatin environment plays a central role in silencing genes associated with the malaria parasite’s development, survival in the host, and transmission to the mosquito vector. However, the underlying mechanism regulating the dynamic chromatin structure is not understood yet. Here, we have uncovered that Plasmodium falciparum Rrp6, an orthologue of eukaryotic RNA exosome-associated RNase, controls the silencing of heterochromatic genes. PfRrp6 knockdown disrupted the singular expression of the GC-rich ncRNA RUF6 family, a known critical regulator of virulence gene expression, through the stabilization of the nascent transcripts. Mechanistic investigation showed that the accumulation of the multiple RUF6 ncRNAs triggered local chromatin remodeling in situ, which activated their adjacent var genes. Strikingly, chromatin isolation by RNA purification analysis (ChIRP-seq) revealed that a remarkable RUF6 ncRNA had interacted with distal heterochromatin regions directly and stimulated a global derepression effect on heterochromatic genes, including all variant gene families and the sexual commitment-associated regulator ap2-g gene. Collectively, Rrp6 appears to conduct the epigenetic surveillance of heterochromatic gene expression through controlling RUF6 levels, thereby securing antigenic variation and sexual commitment of malaria parasites during the infection of the host

The molecular signature and prognosis of glioma with preoperative intratumoral hemorrhage: a retrospective cohort analysis

Abstract Background Intratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management. Methods Integrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications. Results 457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p < 0.001), EGFR (hemorrhage group p = 0.003, non-hemorrhage group p = 0.001), and FGFR2 (hemorrhage group p = 0.007, non-hemorrhage group p = 0.001) was associated with shorter overall survival time in both hemorrhage and non-hemorrhage groups. Conclusions Glioma patients with preoperative intratumoral hemorrhage had unfavorable prognoses compared to their nonhemorrhage counterparts. CDKN2B, KMT5B, and PIK3CA alterations were associated with an increased occurrence of intratumoral hemorrhage, which might be future targets for further investigation of intratumoral hemorrhage