Autoregressive count data modeling on mobility patterns to predict cases of COVID-19 infection

At the beginning of 2022 the global daily count of new cases of COVID-19 exceeded 3.2 million, a tripling of the historical peak value reported between the initial outbreak of the pandemic and the end of 2021. Aerosol transmission through interpersonal contact is the main cause of the disease's spread, although control measures have been put in place to reduce contact opportunities. Mobility pattern is a basic mechanism for understanding how people gather at a location and how long they stay there. Due to the inherent dependencies in disease transmission, models for associating mobility data with confirmed cases need to be individually designed for different regions and time periods. In this paper, we propose an autoregressive count data model under the framework of a generalized linear model to illustrate a process of model specification and selection. By evaluating a 14-day-ahead prediction from Sweden, the results showed that for a dense population region, using mobility data with a lag of 8 days is the most reliable way of predicting the number of confirmed cases in relative numbers at a high coverage rate. It is sufficient for both of the autoregressive terms, studied variable and conditional expectation, to take one day back. For sparsely populated regions, a lag of 10 days produced the lowest error in absolute value for the predictions, where weekly periodicity on the studied variable is recommended for use. Interventions were further included to identify the most relevant mobility categories. Statistical features were also presented to verify the model assumptions.

Spatial Analysis of HIV/AIDS Cases Among Out-of-School Youth Aged 15-24 Years - China, 2010-2020

What is already known about this topic?

There are 4,000 new HIV infections every day worldwide, and 31% of which are in adolescents aged 15–24 years old. However, previous study is not aware of the distribution of out-of-school youth among this age group.

What is added by this report?

The crude reporting rate of HIV/AIDS among out-of-school youth aged 15–24 years old increased from 5.25 per 100,000 persons in 2010 to 13.75 per 100,000 persons in 2020 with a weakly aggregated spatial distribution. Local hotspots spread from southwestern China to the central, eastern, and northeastern areas.

What are the implications for public health practice?

In the future, HIV/AIDS awareness among out-of-school youth and research on epidemic characteristics should be strengthened.

Mogroside V reduce OVA-induced pulmonary inflammation based on lung and serum metabolomics

BACKGROUND

Mogroside V, the main ingredient of Siraitia grosvenorii, has been proved to have therapeutic effects on pulmonary diseases. The specific mechanism still remains to be clarified, which hinders the potence of its medicinal value.

PURPOSE

Serum and lung metabolomics based on LC-MS analysis were applied to explore the mechanism of mogroside V against lung inflammation.

METHOD

In this study, balb/c mice were divided into control, model, mogeoside V and SH groups. We evaluated the protective effects of mogroside V on lung inflammation in asthmatic mice. Suhuang Zhike Jiaonang was used as positive drug. Metabolic profiles of serum and lung samples of mice in control, model and mogroside V groups were analyzed by LC-MS.

RESULTS

Administration of mogroside V effectively relieved the expression of biochemical cytokines and lung inflammatory infiltration of asthmatic mice caused by ovalbumin (OVA). And visceral index of mice treated with mogroside V was close to control group. These results indicated that mogroside V ameliorated OVA-induced lung inflammation. LC-MS based metabolomics analysis demonstrated 6 main pathways in asthmatic mice including Vitamin B6 metabolism, Taurine and hypotaurine metabolism, Ascorbate and aldarate metabolism, Histidine metabolism, Pentose and glucuronate interconversions, Citrate cycle (TCA cycle) were regulated after using mogroside V.

CONCLUSION

The study firstly elucidates the metabolic pathways regulated by mogroside V on lung inflammation through metabolomics, providing a theoretical basis for more sufficient utilization and compatibility of mogroside V.

Efficacy of Psychological Interventions Towards the Reduction of High-Risk Sexual Behaviors Among People Living with HIV: A Systematic Review and Meta-analysis, 2010-2020

People living with HIV/AIDS (PLWH) may be vulnerable to mental illness. As sexual transmission is the leading cause of HIV infection, evidence-based study for the effect of psychological interventions on the change of sexual is needed. To estimate the efficacy of psychological interventions towards reducing unprotected sex and increasing condom use among PLWH. We systematically searched PubMed, Web of Science, EMBASE (OVID), and PsycINFO (OVID) for studies reporting psychological intervention effects on the outcomes of condom use and/or unprotected sex from 2010 to 2020. This review is registered with PROSPERO, CRD42020193640. Of 949 studies, 17 studies were included in this systematic review. Overall, participants in the intervention group reduced sexual risk or condomless sex relative to control groups. The effect was higher for people having sex with HIV-positive partners comparing with those who had sex with HIV-negative or unknown status partners. Psychological interventions might positively affect the condom use of PLWH and should be prioritized and regularly.

Bioenergy Crops for Low Warming Targets Require Half of the Present Agricultural Fertilizer Use

Bioenergy with carbon capture and storage (BECCS) is a key option for removing CO₂ from the atmosphere over time to achieve climate mitigation. However, an overlooked impact of BECCS is the amount of nutrients required to sustain the production. Here, we use an observation-driven approach to estimate the future bioenergy biomass production for land-use scenarios maximizing BECCS and the pertaining nutrient requirements. The projected global biomass production during the 21st century is comparable to the CO₂ removal target for 2 °C warming scenarios. However, 9-19% of this future production hinges on agrotechnology improvement, which remains uncertain. Additional nutrients from fertilizers, corresponding to 56.8 ± 6.1% of the present-day agricultural fertilizer, will be needed to replenish the nutrients removed in harvested biomass at the end of the century, resulting in additional costs and greenhouse gas emissions. Our study reveals the nutrient challenges associated with BECCS and calls for additional management efforts to grow bioenergy crops in a sustainable way.

Radiomic Phenotypes Distinguish Atypical Teratoid/Rhabdoid Tumors from Medulloblastoma

BACKGROUND AND PURPOSE

Atypical teratoid/rhabdoid tumors and medulloblastomas have similar imaging and histologic features but distinctly different outcomes. We hypothesized that they could be distinguished by MR imaging-based radiomic phenotypes.

MATERIALS AND METHODS

We retrospectively assembled T2-weighted and gadolinium-enhanced T1-weighted images of 48 posterior fossa atypical teratoid/rhabdoid tumors and 96 match-paired medulloblastomas from 7 institutions. Using a holdout test set, we measured the performance of 6 candidate classifier models using 6 imaging features derived by sparse regression of 900 T2WI and 900 T1WI Imaging Biomarker Standardization Initiative-based radiomics features.

RESULTS

From the originally extracted 1800 total Imaging Biomarker Standardization Initiative-based features, sparse regression consistently reduced the feature set to 1 from T1WI and 5 from T2WI. Among classifier models, logistic regression performed with the highest AUC of 0.86, with sensitivity, specificity, accuracy, and F1 scores of 0.80, 0.82, 0.81, and 0.85, respectively. The top 3 important Imaging Biomarker Standardization Initiative features, by decreasing order of relative contribution, included voxel intensity at the 90th percentile, inverse difference moment normalized, and kurtosis-all from T2WI.

CONCLUSIONS

Six quantitative signatures of image intensity, texture, and morphology distinguish atypical teratoid/rhabdoid tumors from medulloblastomas with high prediction performance across different machine learning strategies. Use of this technique for preoperative diagnosis of atypical teratoid/rhabdoid tumors could significantly inform therapeutic strategies and patient care discussions.

Adherence to antihypertensive medications for secondary prevention of cardiovascular disease events: a dose-response meta-analysis

OBJECTIVES

The aim of the study was to explore the association between adherence to antihypertensive medications (AHMs) and the risk of recurrence of cardiovascular disease (CVD) events in patients with a history of CVD events from cohort studies.

STUDY DESIGN

This is a dose-response meta-analysis.

METHODS

PubMed and Embase databases were searched up to March 4, 2021, to identify English-language reports of cohort studies that assessed the association of AHM adherence with risk of recurrence of CVD events. Pooled relative risks (RRs) and 95% confidence intervals (CIs) were estimated by using a fixed- or random-effects model. Restricted cubic splines were used to evaluate the possible linear or non-linear association.

RESULTS

We included nine cohort studies (54,349 patients) in the present meta-analysis. The pooled RR of CVD events was 0.66 (95% CI, 0.54-0.78) for the highest versus lowest AHM adherence category. We did not find any evidence of non-linearity association between AHM adherence and risk of CVD events (P_{non-linearity} = 0.534); for patients with a history of CVD events, the risk of CVD events was reduced by 9% for each 20% increase in AHM adherence (RR, 0.91; 95% CI, 0.85-0.97). The results of sensitivity analysis and subgroup analysis were virtually unchanged.

CONCLUSIONS

The high level of adherence to AHM is an effective strategy for preventing recurrence of CVD events. Patients with a history of CVD events should adhere to AHM.

Immune restoration in HIV-1-infected patients after 12 years of antiretroviral therapy: a real-world observational study

Using normalization of CD4 counts as the main evaluation parameter of complete immune restoration for HIV-1 patients under antiretroviral therapy (ART) might be not enough. A comprehensive evaluation system more accurately reflecting immune restoration are urgently needed. Totally, 91,805 HIV-1 patients from 17 tertiary hospitals in China during 2005–2018 were included in this study. Immune restoration and mortality were assessed. Patients initiated ART with baseline CD4 counts <50, 50–199, 200–349, 350–499, and ≥500 cells/μL, and results showed an increase in the median CD4 counts to 445 (12-year), 467 (12-year), 581 (11-year), 644 (7-year), and 768 cells/µL (5-year), as well as the CD4/CD8 ratio to 0.59 (12-year), 0.65 (12-year), 0.79 (11-year), 0.82 (7-year), 0.9 (5-year), respectively. The median CD8 count was relatively high (median range 732–845 cells/μL), regardless of the baseline CD4 counts. Furthermore, the probabilities of death in patients achieving CD4 counts ≥500 cells/μL and CD4/CD8 ratio ≥0.8 simultaneously were significantly lower than those in patients achieving either CD4 counts ≥500 cells/μL (2.77% vs 3.50%, p=0.02) or CD4/CD8 ≥ 0.8 (2.77% vs 4.28%, p<0.001) after 12-year of ART. In this study, a new binary-indicator would accurately assess immune restoration in the era of “treat all.”

Theoretical results of optimal harvesting in a hierarchical size-structured population system with delay

We investigate an optimal control problem for a hierarchical size-structured population model, which incorporates the inoculation delay into the globally feedbacked boundary condition. After the establishment of the continuity of the states with respect to the harvesting efforts, the existence of the optimal solutions is proved by a result in convex analysis, and the maximum principle is obtained via conjugate system and tangent-normal cones.

Bone marrow-derived mesenchymal stem cells inhibit CD8+ T cell immune responses via PD-1/PD-L1 pathway in multiple myeloma

High expression of the inhibitory receptor programmed cell death ligand 1 (PD-L1) on tumor cells and tumor stromal cells have been found to play a key role in tumor immune evasion in several human malignancies. However, the expression of PD-L1 on bone marrow mesenchymal stem cells (BMSCs) and whether the programmed cell death 1 (PD-1)/PD-L1 signal pathway is involved in the BMSCs versus T cell immune response in multiple myeloma (MM) remains poorly defined. In this study, we explored the expression of PD-L1 on BMSCs from newly diagnosed MM (NDMM) patients and the role of PD-1/PD-L1 pathway in BMSC-mediated regulation of CD8⁺ T cells. The data showed that the expression of PD-L1 on BMSCs in NDMM patients was significantly increased compared to that in normal controls (NC) (18·81 ± 1·61 versus 2·78± 0·70%; P < 0·001). Furthermore, the PD-1 expression on CD8⁺ T cells with NDMM patients was significantly higher than that in normal controls (43·22 ± 2·98 versus 20·71 ± 1·08%; P < 0·001). However, there was no significant difference in PD-1 expression of CD4⁺ T cells and natural killer (NK) cells between the NDMM and NC groups. Additionally, the co-culture assays revealed that BMSCs significantly suppressed CD8⁺ T cell function. However, the PD-L1 inhibitor effectively reversed BMSC-mediated suppression in CD8⁺ T cells. We also found that the combination of PD-L1 inhibitor and pomalidomide can further enhance the killing effect of CD8⁺ T cells on MM cells. In summary, our findings demonstrated that BMSCs in patients with MM may induce apoptosis of CD8⁺ T cells through the PD-1/PD-L1 axis and inhibit the release of perforin and granzyme B from CD8⁺ T cells to promote the immune escape of MM.

Increase in HIV-1-transmitted drug resistance among ART-naïve youths at the China-Myanmar border during 2009 ~ 2017

Background

HIV-transmitted drug resistance (TDR) is found in antiretroviral therapy (ART)-naïve populations infected with HIV-1 with TDR mutations and is important for guiding future first- and second-line ART regimens. We investigated TDR and its effect on CD4 count in ART-naïve youths from the China-Myanmar border near the Golden Triangle to better understand TDR and effectively guide ART.

Methods

From 2009 to 2017, 10,832 HIV-1 infected individuals were newly reported along the Dehong border of China, 573 ART-naïve youths (16 ~ 25 y) were enrolled. CD4 counts were obtained from whole blood samples. HIV pol gene sequences were amplified from RNA extracted from plasma. The Stanford REGA program and jpHMM recombination prediction tool were used to determine genotypes. TDR mutations (TDRMs) were analyzed using the Stanford Calibrated Population Resistance tool.

Results

The most common infection route was heterosexuals (70.51%), followed by people who inject drugs (PWID, 19.20%) and men who have sex with men (MSM) (8.90%). The distribution of HIV genotypes mainly included the unique recombinant form (URF) (44.08%), 38.68% were CRFs, 13.24% were subtype C and 4.04% were subtype B. The prevalence of TDR increased significantly from 2009 to 2017 (3.48 to 9.48%) in ART-naïve youths (4.00 to 13.16% in Burmese subjects, 3.33 to 5.93% in Chinese subjects), and the resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs), nucleoside and nucleotide reverse transcriptase inhibitors (NRTIs), and protease inhibitors (PIs) were 3.49, 2.62, and 0.52%, respectively. Most (94.40%, n = 34) of HIV-1-infected patients with TDRM had mutation that conferred resistance to a single drug class. The most common mutations Y181I/C and K103N, were found in 7 and 9 youths, respectively. The mean CD4 count was significantly lower among individuals with TDRMs (373/mm³ vs. 496/mm³, p = 0.013).

Conclusions

The increase in the prevalence of HIV-1 TDR increase and a low CD4 count of patients with TDRMs in the China-Myanmar border suggests the need for considering drug resistance before initiating ART in HIV recombination hotspots.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05794-5.

Computer-Aided Diagnostic System for Thyroid Nodules on Ultrasonography: Diagnostic Performance Based on the Thyroid Imaging Reporting and Data System Classification and Dichotomous Outcomes

BACKGROUND AND PURPOSE

Artificial intelligence-based computer-aided diagnostic systems have been introduced for thyroid cancer diagnosis. Our aim was to compare the diagnostic performance of a commercially available computer-aided diagnostic system and radiologist-based assessment for the detection of thyroid cancer based on the Thyroid Imaging Reporting and Data Systems (TIRADS) and dichotomous outcomes.

MATERIALS AND METHODS

In total, 372 consecutive patients with 454 thyroid nodules were enrolled. The computer-aided diagnostic system was set up to render a possible diagnosis in 2 formats, the Korean Society of Thyroid Radiology (K)-TIRADS and the American Thyroid Association (ATA)-TIRADS-classifications, and dichotomous outcomes (possibly benign or possibly malignant).

RESULTS

The diagnostic sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the computer-aided diagnostic system for thyroid cancer were, respectively, 97.6%, 21.6%, 42.0%, 93.9%, and 49.6% for K-TIRADS; 94.6%, 29.6%, 43.9%, 90.4%, and 53.5% for ATA-TIRADS; and 81.4%, 81.9%, 72.3%, 88.3%, and 81.7% for dichotomous outcomes. The sensitivities of the computer-aided diagnostic system did not differ significantly from those of the radiologist (all P > .05); the specificities and accuracies were significantly lower than those of the radiologist (all P < .001). Unnecessary fine-needle aspiration rates were lower for the dichotomous outcome characterizations, particularly for those performed by the radiologist. The interobserver agreement for the description of K-TIRADS and ATA-TIRADS classifications was fair-to-moderate, but the dichotomous outcomes were in substantial agreement.

CONCLUSIONS

The diagnostic performance of the computer-aided diagnostic system varies in terms of TIRADS classification and dichotomous outcomes and relative to radiologist-based assessments. Clinicians should know about the strengths and weaknesses associated with the diagnosis of thyroid cancer using computer-aided diagnostic systems.

Epidemiological Characteristics of Newly-Reported HIV Cases Among Youth Aged 15-24 Years - China, 2010-2019

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?

An estimated 1,400 new cases of human immunodeficiency virus (HIV) occur every day among youths globally. However, HIV distribution among youth aged 15-24 years in China has not been researched extensively.

WHAT IS ADDED BY THIS REPORT?

Between 2010 and 2019, a total of 141,557 HIV cases among the group aged 15-24 years were reported in China with a male to female ratio at 4.07∶1. The main route of HIV transmission was unprotected sex among men who have sex with men (MSM), and heterosexual transmission for females.

WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?

Effective HIV control and prevention measures need to target youth aged 15-24 years, especially among MSM. Sexual health education and HIV prevention should start from primary and secondary school levels.

Exogenous 6-benzyladenine application affects root morphology by altering hormone status and gene expression of developing lateral roots in Malus hupehensis

Malus hupehensis is an extensively used apple rootstock in China. In the current study, M. hupehensis seedlings were treated with exogenous 2.2 µm 6-benzyladenine (6-BA) so as to investigate the mechanism by which 6-BA affects lateral root development. The results indicate that 6-BA treatment promotes elongation and thickening of both root and shoot in M. hupehensis, but reduces the number of lateral roots, as well as reducing the auxin level after 6-BA treatment. Moreover, MhAHK4, MhRR1 and MhRR2 were also significantly up-regulated in response to 6-BA treatment. Expression levels of auxin synthesis- and transport-related genes, such as MhYUCCA6, MhYUCCA10, MhPIN1 and MhPIN2, were down-regulated, which corresponds with lower auxin levels in the 6-BA-treated seedlings. A negative regulator of auxin, MhIAA3, was induced by 6-BA treatment, leading to reduced expression of MhARF7 and MhARF19 in 6-BA-treated seedlings. As a result, expression of MhWOX11, MhWOX5, MhLBD16 and MhLBD29 was blocked, which in turn inhibited lateral root initiation. In addition, a lower auxin level decreased expression of MhRR7 and MhRR15, which repressed expression of key transcription factors associated with root development, thus inhibiting lateral root development. In contrast, 6-BA treatment promoted secondary growth (thickening) of the root by inducing expression of MhCYCD3;1 and MhCYCD3;2. Collectively, the changes in hormone levels and gene expression resulted in a reduced number of lateral roots and thicker roots in 6-BA-treated plants.

Structural equation modeling test of the pre-intentional phase of the health action process approach (HAPA) model on condom use intention among senior high school students in Tianjin, China

Based on the Theory of Health Action Process Approach (HAPA) Model, this study aimed to investigate factors associated with condom use intention in Chinese adolescents.In 2017, we conducted a cross-sectional study using stratified cluster, convenience sampling method to assess condom use intention among senior high school students in Tianjin, China. One thousand eighty two senior high school students were anonymously surveyed through self-administered questionnaires. Structural equation modelling was used to assess the pre-intentional phase of HAPA model.Among the participants, 41.5% (449/1082) were male, 54.1% (585/1082) were female, 4.4% (48/1082) were gender-deficient. The average age was 16.7 years. The final pre-intentional phase of HAPA model was acceptable (CFI = 0.95; GFI = 0.94; RMSEA = 0.06). Action self-efficacy (r = 0.60) had a strong direct effect on condom use intention.The pre-intentional phase of HAPA model is valid to assess condom use intention among Chinese senior high school students. The pre-intention phase of the HAPA model could be applied to guide AIDS health educations of students, and further research is needed to evaluate the effect.

Partial Classifier Chains with Feature Selection by Exploiting Label Correlation in Multi-Label Classification

Multi-label classification (MLC) is a supervised learning problem where an object is naturally associated with multiple concepts because it can be described from various dimensions. How to exploit the resulting label correlations is the key issue in MLC problems. The classifier chain (CC) is a well-known MLC approach that can learn complex coupling relationships between labels. CC suffers from two obvious drawbacks: (1) label ordering is decided at random although it usually has a strong effect on predictive performance; (2) all the labels are inserted into the chain, although some of them may carry irrelevant information that discriminates against the others. In this work, we propose a partial classifier chain method with feature selection (PCC-FS) that exploits the label correlation between label and feature spaces and thus solves the two previously mentioned problems simultaneously. In the PCC-FS algorithm, feature selection is performed by learning the covariance between feature set and label set, thus eliminating the irrelevant features that can diminish classification performance. Couplings in the label set are extracted, and the coupled labels of each label are inserted simultaneously into the chain structure to execute the training and prediction activities. The experimental results from five metrics demonstrate that, in comparison to eight state-of-the-art MLC algorithms, the proposed method is a significant improvement on existing multi-label classification.

Downregulation of lncRNA SNHG7 inhibits proliferation and invasion of nasopharyngeal carcinoma cells through repressing ROCK1

OBJECTIVE

Recent studies have revealed the important role of long noncoding RNAs (lncRNAs) in the progression of tumorigenesis. This study aimed to identify the biological function of lncRNA small nucleolar RNA host gene 7 (SNHG7) in the progression of nasopharyngeal carcinoma (NPC).

PATIENTS AND METHODS

LncRNA SNHG7 expressions in NPC cell lines and 50 paired NPC tissue samples were detected by Real-time quantitative polymerase chain reaction (RT-qPCR). Transwell assay, wound healing assay and proliferation assay were conducted to evaluate the in vitro function of SNHG7 in NPC cells. Xenograft model was established for determining the in vivo effect of SNHG7 on tumor formation and metastasis of NPC. The underlying mechanism of SNHG7 in mediating the progression of NPC was explored by RT-qPCR and Western blot.

RESULTS

SNHG7 expression was remarkably downregulated in NPC tissues compared with that in adjacent normal samples. Knockdown of SNHG7 attenuated proliferation, invasion and migration of NPC cells. Moreover, tumor size and the number of metastatic nodules were reduced in mice administrated with NPC cells transfected with sh-SNHG7. Knockdown of SNHG7 downregulated ROCK1 at mRNA and protein level. Besides, the expression of ROCK1 in tumor tissues was positively correlated to SNHG7 expression.

CONCLUSIONS

Knockdown of SNHG7 inhibits migration, invasion and proliferation of NPC cells through downregulating ROCK1, which may offer a new therapeutic intervention for NPC patients.

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study

BACKGROUND AND PURPOSE

Posterior fossa tumors are the most common pediatric brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We sought to develop an MR imaging-based deep learning model for posterior fossa tumor detection and tumor pathology classification.

MATERIALS AND METHODS

The study cohort comprised 617 children (median age, 92 months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons (n = 122), medulloblastoma (n = 272), pilocytic astrocytoma (n = 135), and ependymoma (n = 88). There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRIs as input to detect the presence of tumor and predict tumor class. Deep learning model performance was compared against that of 4 radiologists.

RESULTS

Model tumor detection accuracy exceeded an AUROC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F₁ score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate. Tumor type classification accuracy and F₁ score were higher than those of 2 of the 4 radiologists.

CONCLUSIONS

We present a multi-institutional deep learning model for pediatric posterior fossa tumor detection and classification with the potential to augment and improve the accuracy of radiologic diagnosis.

Downregulation of lncRNA SNHG7 inhibits proliferation and invasion of nasopharyngeal carcinoma cells through repressing ROCK1

Since this article has been suspected of research misconduct and the corresponding authors did not respond to our request to prove originality of data and figures, "Downregulation of lncRNA SNHG7 inhibits proliferation and invasion of nasopharyngeal carcinoma cells through repressing ROCK1, by L. Wang, T. Xu, X. Cui, M. Han, L.-H. Zhou, Z.-X. Wei, Z.-J. Xu, Y. Jiang, published in Eur Rev Med Pharmacol Sci 2019; 23 (14): 6186-6193-DOI: 10.26355/eurrev_201907_18432-PMID: 31364118" has been withdrawn. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/18432.