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Texas–Mexico border region is a unique place where two countries and culture connected. We sought to investigate border school district students’ academic performance as measured by Texas standardized test: the State of Texas Assessments of Academic Readiness (STAAR). To do so, we first used propensity score matching (PSM) techniques to analyze data collected from a public database: Texas Assessment Management System (TAMS). Specifically, we provided a PSM analysis of non-border and border school districts regarding their demographic characteristics [i.e., identified as a rural district, percentage of economically disadvantaged (ED) students, percentage of English learners (ELs), mobility rate, instructional hours, principal experience, teacher experience, teacher–student ratio, and teacher turnover rate]. Then, multiple regression analyses were conducted to compare Texas border and non-border school students’ reading, math, and science achievements, respectively, based on a matching sample with control for demographic variables. The results of the current study indicate that no significant difference was found between border and non-border school districts, regarding students’ academic performance in reading, math, and science, when districts were matched and demographic characteristics were controlled. We further found that demographic variables, such as percent of ED students, principal experience, and teacher turnover rate, significantly impact students’ academic achievement. Such findings have suggested that the achievement gap between border and non-border districts can be closed if extra support can be provided to ED students, and funding could be allocated in border districts to maintain experienced principals and teachers.

Background The function of H3F3A G43W mutation, which has been observed in almost all GCTB, remains poorly characterized. Breakthrough in malignant GCTB has been trapped by the lack of clinical available drugs, limited canonical patient samples and paucity of fidelity preclinical models. Methods Tumor samples obtained from a malignant GCTB was implanted in immunodeficient mice for the generation of PDX. Histological examination and short tandem repeat (STR) were used for inherited features analyses. An epigenetic/transcriptional targeted compound library was selected for drug screening. The in vivo effects of selected drug were validated in PDX model. Results We established the PDX model with recurrent malignant GCTB specimens, histological examination and STR analyses revealed that PDX and their corresponding parental patients shared the same STRs and histologic features, suggesting common origins. ITF-2357 was the most significant compound with an IC50 lower than 0.1 uM. The results of the drug screening and in vivo PDX validation demonstrated that ITF-2357 might be a promising drug targeted H3F3A G34W mutation MGCTBs. Conclusion Our study demonstrates that PDX model maintained the same histologic and genetic features as those in the original patient. targeting HDAC through ITF-2357 effectively overcomes malignant GCTB progression in vitro and in vivo. Translational potential statement As PDX retain the principal histologic and genetic characteristics of the primary tumors, mad it a valuable research tool in predictive clinical efficacy. In this study, we first established a malignant GCTB PDX model, which might further accelerate the progress of drug development in malignant GCTB., Highlights • PDX model were established from a malignant GCTB patient. • PDCs and PDX maintained same oncohiston mutations as those in the original patient. • ITF-2357 inhibits malignant GCTB progression in vitro and in vivo.

Jun Chen,1,* Xiangchao Meng,2,* Qinyi Zhou,1 Jialin Feng,1 Wenjie Zheng,1 Zhuoying Wang,1 Jiadong Wang,1 You Wang2 1Head and Neck Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of China; 2Bone and Joint Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jiadong WangHead and Neck Surgery,Ren Ji Hospital,School of Medicine, Shanghai Jiao Tong University, Shanghai 200001, People’s Republic of ChinaEmail wangjiadong097@163.comYou WangBone and Joint Surgery,Ren Ji Hospital,School of Medicine,Shanghai Jiao Tong University, Shanghai 200001, People’s Republic of ChinaEmail Drwangyou@126.comPurpose: CXCR5-positive (CXCR5+) tumor cell infiltration has different prognostic values in different types of cancer. The objective was to evaluate the effect of CXCR5+ cell infiltration in head and neck squamous cell carcinoma (HNSCC).Patients and Methods: The study included two patient cohorts: The Cancer Genome Atlas cohort (TCGA, n = 472) and the Renji Hospital cohort (RJHC, n = 201). The TCGA and RJHC cohorts were analyzed for CXCR5-related mRNAs and CXCR5+ cell infiltration, respectively. We then evaluated the correlation between CXCR5 mRNA and CXCR5+ cell infiltration in terms of overall survival and the immune contexture.Results: The 5-year overall survival rate was significantly correlated with high CXCR5 mRNA expression and CXCR5+ cell infiltration in the TCGA and RJHC cohorts, respectively (p < 0.01), even after adjusting for confounders. Moreover, high CXCR5 mRNA expression was associated with more CD4+ T cells, CD8+ T cells, plasma cells, and less dendritic cells. A high CXCR5 mRNA expression was also correlated with increased expression of cytotoxic IFNG, TNFSF11 (RANKL), GZMA, GZMB, GZMK, GZMM, and PRF1 and increased expression of the immunosuppressive gene PDCD1 (PD-1), CD274 (PD-L1), CTLA4, LAG3, HAVCR2 (TIM-3), BTLA, and TIGIT.Conclusion: HNSCC patients with a high intratumoral CXCR5 expression had a better prognosis than those with low intratumoral CXCR5 expression. Moreover, CXCR5+ cell infiltration could be used as an independent prognostic biomarker or as a potential therapeutic target. The presence of CXCR5+ cells affects the infiltration of immunocytes in head and neck cancer, differently from what was reported in other cancer types. Further randomized controlled trials or studies with more patients are needed to validate our results.Keywords: CXCR5-producing cells, immune contexture, prognosis, head and neck squamous cell carcinoma

Additional file 1: Figure S1. a. Western blot demonstrating CRISPR/CAS9-mediated CD151 knockout in indicated cells. b. Heatmap of the sphingolipid metabolism genes regulated by CD151 depletion in ZOSM cells from RNA-seq. c. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of transcriptomic profiles of osteosarcoma patients based on the GEO database (GSE42352, n = 127). The red indicates the KEGG pathway related to sphingolipid metabolism. d. Heatmap of osteosarcoma patients showed changes of sphingolipid metabolism genes that express a high level of CD151 compared to tumors with low CD151 expression. Figure S2. a. Liquid chromatography coupled to mass spectrometry (LC/MS) was used to measure the concentrations of intermediates in ZOSM cells. Heatmap showing significantly differently expression metabolites altered by CD151 silencing. Shades of red and blue represent higher and lower levels of metabolites, respectively. b. The top 10 enriched pathways from integrated pathway analysis of significantly changed metabolites. The red indicates the KEGG pathway related to sphingolipid metabolism. c. Lipids were extracted from WT or CD151 KO ZOSM cells and analyzed by LC/MS. Bubble plots represent the mean log2-transformed fold-change difference between cell lines. d. The intensity of BODIPY FL-labeled ceramide or sphingomyelin was analyzed by confocal fluorescence imaging in ZOSM cells. Scale bars: 50 μm. e. ZOSM cells with CD151 depletion were incubated with Alexa 555-conjugated CTB (red) to label GM1-containing lipid rafts. Cells were analyzed by confocal microscopy or flow cytometry. Scale bars: 50 μm. Figure S3. a. Expression of genes involved in sphingolipid metabolism was measured by PCR array in ZOSM cells. Data are shown as log2-transformed fold change in CD151 silencing cells relative to control. b. Western blot analysis of SPTCL1 expression in cells with CD151 overexpression in indicated cells. c. The cellular levels of ceramide in vector and CD151 overexpression ZOSM cells with or without myriocin treatment were analyzed by BODIPY FL-labeled ceramide confocal imaging. Scale bars: 50 μm. d. The cellular levels of lipid rafts in vector and CD151 overexpression ZOSM cells with or without myriocin treatment were analyzed by Alexa 555-conjugated CTB confocal imaging. Scale bars: 50 μm. e. Mice weight quantification of established tumors with CD151 overexpression treated with vehicle or myriocin (0.5 mg/kg). Data are presented as mean ± SD, n = 5. Figure S4. a. Gene set enrichment analysis (GSEA) based on the RNA-seq using Hallmarks gene sets between WT and CD151 KO ZOSM cells. b. The c-myc expression was detected in the indicated cells with CD151 overexpression by western blot. c. Time-course analysis of c-myc protein levels in CD151 depletion ZOSM cells. c-myc band density relative to β-actin was quantified, and the ratio of c-myc protein/actin protein was artificially set as 1.0 for samples untreated with CHX to obtain half-time (T1/2) of c-myc. d. c-myc ubiquitination was analyzed in CD151 depletion cells. ZOSM cells were transfected with the indicated plasmids followed by treatment with MG132 for 6 h. Cell extracts were immunoprecipitated with an anti-HA antibody, and ubiquitination c-myc was detected by western blot. Figure S5. a-b. SPTLC1 mRNA and protein levels in CD151 depletion cells stably infected with vector or c-myc-expressing lentiviruses were analyzed by RT-qPCR (A) and Western blot (B). Data are shown as mean ± SD of triplicate experiments. c-d. Schematic representation of the promoter region in the human SPTLC1 gene (C). ChIP from ZOSM cells was performed with control IgG or c-myc antibody as indicated. The presence of the SPTLC1 binding sites was detected by qPCR using primers. Quantification of enrichments is represented as fold-enrichment over lgG control. e. ZOSM cells were transfected with an empty vector or c-myc plus the wild-type SPTLC1 promoter (WT) or mutated promoter (MUT) for measuring luciferase activity. Data are the mean ± SD, and the data are representative of three independent experiments. Figure S6. a. The representative images of Ki67 staining from SA3831 and SA4009 PDX tumor-bearing mice treated with vehicle or myriocin. Scale bars: 100 μm. Table S1.

Aging drives the accumulation of senescent cells (SnCs) by secreting factors that cause the senescence-associated secretory phenotype (SASP), including stem cells in the bone marrow, which contribute to aging-related bone degradation. Osteoarthritis (OA) is a serious chronic injury disease, and increasing age is a major risk factor. The accumulation of SnCs may accelerate the development of OA, and the accumulation of SnCs may benefit from its resistance to apoptotic stimuli. Therefore, local elimination of SnCs could be a promising treatment for OA. Apoptosis inhibitor protein (IAP) is an important antiapoptotic protein in vivo. AT-406 is a small molecule inhibitor of the IAP genes and also regulates the transcription of several genes. Here, we show that SnCs upregulate the antiapoptotic proteins c-IAP1, c-IAP2 and XIAP.The combined inhibition of c-IAP1, c-IAP2 and XIAP using siRNA or AT-406 specifically induce the apoptosis of SnCs.In addition, XIAP and STX17 bind to each other to regulate the fusion of autophagosomes and lysosomes in SnCs, which in turn, affects the fate of SnCs. It is worth noting that the clearance of SnCs attenuated the secretion of SASP and created a proregenerative environment. Most importantly, local clearance of SnCs significantly attenuated the progression of osteoarthritis in rats without significant toxic effects. Thus, local elimination of SnCs may be a potential treatment for OA. This is the first report of inhibition of IAPs for clearing SnCs and suggests that eradication of SnCs may be a new strategy for the treatment of age-related diseases.

To efficiently extract spatiotemporal features of video for action recognition, most state-of-the-art methods integrate 1D temporal convolution into a conventional 2D CNN backbone. However, they all exploit 1D temporal convolution of fixed kernel size (i.e., 3) in the network building block, thus have suboptimal temporal modeling capability to handle both long-term and short-term actions. To address this problem, we first investigate the impacts of different kernel sizes for the 1D temporal convolutional filters. Then, we propose a simple yet efficient operation called Mixed Temporal Convolution (MixTConv), which consists of multiple depthwise 1D convolutional filters with different kernel sizes. By plugging MixTConv into the conventional 2D CNN backbone ResNet-50, we further propose an efficient and effective network architecture named MSTNet for action recognition, and achieve state-of-the-art results on multiple benchmarks., Comment: None

Existing CNN-based methods for pixel labeling heavily depend on multi-scale features to meet the requirements of both semantic comprehension and detail preservation. State-of-the-art pixel labeling neural networks widely exploit conventional scale-transfer operations, i.e., up-sampling and down-sampling to learn multi-scale features. In this work, we find that these operations lead to scale-confused features and suboptimal performance because they are spatial-invariant and directly transit all feature information cross scales without spatial selection. To address this issue, we propose the Gated Scale-Transfer Operation (GSTO) to properly transit spatial-filtered features to another scale. Specifically, GSTO can work either with or without extra supervision. Unsupervised GSTO is learned from the feature itself while the supervised one is guided by the supervised probability matrix. Both forms of GSTO are lightweight and plug-and-play, which can be flexibly integrated into networks or modules for learning better multi-scale features. In particular, by plugging GSTO into HRNet, we get a more powerful backbone (namely GSTO-HRNet) for pixel labeling, and it achieves new state-of-the-art results on the COCO benchmark for human pose estimation and other benchmarks for semantic segmentation including Cityscapes, LIP and Pascal Context, with negligible extra computational cost. Moreover, experiment results demonstrate that GSTO can also significantly boost the performance of multi-scale feature aggregation modules like PPM and ASPP. Code will be made available at https://github.com/VDIGPKU/GSTO.