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BackgroundHyperprogressive disease (HPD) is a novel pattern of paradoxically rapid tumor progression, which often leads to early death, mostly in the first 2 months of treatment with immune checkpoint inhibitors (ICIs). Currently, there is no validated biomarker to assess patients at risk of HPD.AimThe aim of this study was to systematically evaluate the predictive value of the neutrophil-to-lymphocyte ratio (NLR) in HPD and establish a reliable variable to support clinicians in defining personalized treatment strategies.MethodsPubMed, Embase, Web of Science, Scopus, and Cochrane Library databases were searched for studies published before 31 December 2023. The Newcastle–Ottawa Scale (NOS) was used to evaluate the quality of eligible studies. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a random-effects or a fixed-effects model to evaluate the association between the NLR and the risk of HPD.ResultsA total of 17 studies with 2,964 patients were included for meta-analysis. The incidence of HPD across different types of tumors ranged from 6.3% to 35.6%. In the pooled analysis of the NLR and HPD, we identified that the NLR significantly associated with the risk of HPD (OR = 0.65; 95% CI: 0.46 to 0.91; p = 0.01) (I2 = 52%, p = 0.007).ConclusionIn the future, the NLR may serve as a remarkable biomarker for predicting the risk of HPD in clinical practice.

Background : Immunotherapy plays a significant role in the treatment of hepatocellular carcinoma (HCC). Members of the S100 protein family (S100s) have been widely implicated in the pathogenesis and progression of tumors. However, the exact mechanism by which S100s contribute to tumor immunity remains unclear. Methods: To explore the role of S100s in HCC immune cells, we collected and comparatively analyzed single-cell RNA sequencing (scRNA-seq) data of HCC and hepatitis B virus-associated HCC. By mapping cell classification and searching for S100s binding targets and downstream targets. Results: S100A6/S100A11 was differentially expressed in tumor T cells and involved in the nuclear factor (NF) κB pathway. Further investigation of the TCGA dataset revealed that patients with low S100A6/S100A11 expression had a better prognosis. Temporal cell trajectory analysis showed that the activation of the NF-κB pathway is at a critical stage and has an important impact on the tumor microenvironment. Conclusion: Our study revealed that S100A6/S100A11 could be involved in regulating the differentiation and cellular activity of T-cell subpopulations in HCC, and its low expression was positively correlated with prognosis. It may provide a new direction for immunotherapy of HCC and a theoretical basis for future clinical applications.

ObjectiveSelenium (Se) is an essential trace element and may affect cervical cancer occurrence and progression. The association between selenium supplementation and acute toxic reactions and clinical outcomes in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy remains unclear. The aim of this study was to determine the safety profile of add-on Se yeast and assess the potential of Se to ameliorate the hematologic toxicity of concurrent chemoradiotherapy in patients with cervical cancer.MethodsPatients with Federation International of Gynecology and Obstetrics (FIGO) stage IIB cervical cancer who met all inclusion criteria were randomly assigned to either the experimental group or the control group. The experimental group received Se yeast tablets (100 μg Se, twice daily), while the control group received placebos (twice daily) for 5 weeks in total. All patients in both groups received standard treatment, including pelvic external irradiation, concurrent five cycles of chemotherapy, and brachytherapy. Measures included the incidence of myelosuppression, impairment of liver and kidney function, objective response rate (ORR), and blood Se concentrations before, during and after the treatment of the two groups.ResultsA total of 104 eligible patients were enrolled in the experimental group (n = 50) or the control group (n = 54). The ORR in the experimental group and control group were 96 and 94%, respectively (p = 0.47). The baseline levels of blood Se before treatment in the experimental and control groups were similar (58.34 ± 17.63 μg/L and 60.21 ± 18.42 μg/L, p = 0.60), but the concentrations became significantly different after course completion between the two groups (76.16 ± 24.47 μg/L and 57.48 ± 14.92 μg/L, respectively, p

The purpose of this research study was to examine the overall effect of adaptive learning systems deployed using artificial intelligence technology across a range of relevant variables (e.g., duration, student level, etc.). Following a systematic procedure, this meta-analysis examined literature from 18 academic databases and identified N = 45 independent studies utilizing AI-enabled adaptive learning. This meta-analysis examined the overall effect of AI-enabled adaptive learning systems on students' cognitive learning outcomes when compared with non-adaptive learning interventions and found that they have a medium to large positive effect size (g = 0.70). The effect was significantly moderated by publication type, origin of study, student classification level, student discipline, duration, and research design. In addition, all three adaptive sources (cognitive, affective, and behavioral) and adaptive targets (navigation and assessment) were significant moderators. The type of AI used in the adaptive engine did not moderate the effects. Implications for both practice and research are provided.

Providing educators with understandable, actionable, and trustworthy insights drawn from large-scope heterogeneous learning data is of paramount importance in achieving the full potential of artificial intelligence (AI) in educational settings. Explainable AI (XAI)--contrary to the traditional "black-box" approach--helps fulfilling this important goal. We present a case study of building prediction models for undergraduate students' learning achievement in a Computer Science course, where the development process involves the course instructor as a co-designer, and with the use of XAI technologies to explain the underlying reasoning of several machine learning predictions. The explanations enhance the transparency of the predictions and open the door for educators to share their judgments and insights. It further enables us to refine the predictions by incorporating the educators' contextual knowledge of the course and of the students. Through this human-AI collaboration process, we demonstrate how to achieve a more accountable understanding of students' learning and drive towards transparent and trustworthy student learning achievement prediction by keeping instructors in the loop. Our study highlights that trustworthy AI in education should emphasize not only the interpretability of the predicted outcomes and prediction process, but also the incorporation of subject-matter experts throughout the development of prediction models.

Since wireless sensor networks (WSNs) consist of nodes with limited battery power, collaborative data processing and balanced energy consumption should be considered as the key issue. This paper proposes an efficient cluster head selection approach for collaborative data processing in WSNs. The proposed algorithm designs an effective energy-efficient model to select the optimal cluster heads among all nodes fairly, which helps to reduce the impact of the monitoring scheme on the lifetime of network. Experimental results show that the proposed protocol is able to reduce energy consumption and obtain higher efficiency as well as effectively prolonging the lifetime of network more than a few existing cluster-based routing protocols.

BackgroundIntegrated 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) is widely performed for staging solitary pulmonary nodules (SPNs). However, the diagnostic efficacy of SPNs based on PET/CT is not optimal. Here, we propose a method of detection based on PET/CT that can differentiate malignant and benign SPNs with few false-positives.MethodOur proposed method combines the features of positron-emission tomography (PET) and computed tomography (CT). A dynamic threshold segmentation method was used to identify lung parenchyma in CT images and suspicious areas in PET images. Then, an improved watershed method was used to mark suspicious areas on the CT image. Next, the support vector machine (SVM) method was used to classify SPNs based on textural features of CT images and metabolic features of PET images to validate the proposed method.ResultsOur proposed method was more efficient than traditional methods and methods based on the CT or PET features alone (sensitivity 95.6%; average of 2.9 false positives per scan).

Participating in online communities has significant benefits to students learning in terms of students' motivation, persistence, and learning outcomes. However, maintaining and supporting online learning communities is very challenging and requires tremendous work. Automatic support is desirable in this situation. The purpose of this work is to explore the use of deep learning algorithms for automatic text generation in providing emotional and community support for a massive online learning community, Scratch. Particularly, state-of-art deep learning language models GPT-2 and recurrent neural network (RNN) are trained using two million comments from the online learning community. We then conduct both a readability test and human evaluation on the automatically generated results for offering support to the online students. The results show that the GPT-2 language model can provide timely and human-written like replies in a style genuine to the data set and context for offering related support.

Invariant natural killer T (iNKT) cells are an evolutionary conserved T cell population characterized by features of both the innate and adaptive immune response. Studies have shown that iNKT cells are required for protective responses to Gram-positive pathogens such as Streptococcus pneumoniae, and that these cells recognize bacterial diacylglycerol antigens presented by CD1d, a non-classical antigen-presenting molecule. The combination of a lipid backbone containing an unusual fatty acid, vaccenic acid, as well as a glucose sugar that is weaker or not stimulatory when linked to other lipids, is required for iNKT cell stimulation by these antigens. Here we have carried out structural and biophysical studies that illuminate the reasons for the stringent requirement for this unique combination. The data indicate that vaccenic acid bound to the CD1d groove orients the protruding glucose sugar for TCR recognition, and it allows for an additional hydrogen bond of the glucose with CD1d when in complex with the TCR. Furthermore, TCR binding causes an induced fit in both the sugar and CD1d, and we have identified the CD1d amino acids important for iNKT TCR recognition and the stability of the ternary complex. The studies show also how hydrogen bonds formed by the glucose sugar can account for the distinct binding kinetics of the TCR for this CD1d-glycolipid complex. Therefore, our studies illuminate the mechanism of glycolipid recognition for antigens from important pathogens.

The title layered coordination polymer, [Cd(C14H16N5O3)2]n or [Cd(ppa)2]n, where ppa is 8-ethyl-5-oxo-2-(piperazin-1-yl)-5,8-dihydropyrido[2,3-d]pyrimidine-6-carboxylate, was synthesized under hydrothermal conditions. The CdII atom (site symmetry 2) exhibits a distorted cis-CdN2O4 octahedral geometry defined by two N-monodentate and two O,O′-bidentate ppa monoanions. The extended two-dimensional structure resulting from the bridging ppa species is a grid lying parallel to (001). An N—H...O hydrogen bond helps to establish the crystal packing.

Objective: To compare the short-term and long-term outcomes between robotic gastrectomy (RG) and laparoscopic gastrectomy (LG) for gastric cancer. Background: The clinical outcomes of RG over LG have not yet been effectively demonstrated. Methods: This retrospective cohort study included 3599 patients with gastric cancer who underwent radical gastrectomy at eight high-volume hospitals in China from January 2015 to June 2019. Propensity score matching was performed between patients who received RG and LG. The primary end point was 3-year disease-free survival (DFS). Results: After 1:1 propensity score matching, 1034 pairs of patients were enrolled in a balanced cohort for further analysis. The 3-year DFS in the RG and LG was 83.7% and 83.1% (P=0.745), respectively, and the 3-year overall survival was 85.2% and 84.4%, respectively (P= 0.647). During 3 years of follow-up, 154 patients in the RG and LG groups relapsed (cumulative incidence of recurrence: 15.0% vs 15.0%, P= 0.988). There was no significant difference in the recurrence sites between the 2 groups (all P>0.05). Sensitivity analysis showed that RG had comparable 3-year DFS (77.4% vs 76.7%, P= 0.745) and overall survival (79.7% vs 78.4%, P= 0.577) to LG in patients with advanced (pathologic T2-4a) disease, and the recurrence pattern within 3 years was also similar between the 2 groups (all P>0.05). RG had less intraoperative blood loss, lower conversion rate, and shorter hospital stays than LG (all P> 0.05). Conclusions: For resectable gastric cancer, including advanced cases, RG is a safe approach with comparable 3-year oncological outcomes to LG when performed by experienced surgeons. [ABSTRACT FROM AUTHOR]

Background/Aims: Chloride intracellular channel 1 (CLIC1), which is a member of the chloride channel protein family, is associated with various human tumors. Recent studies have shown that CLIC1 is involved in the occurrence and development of gastric cancer (GC). However, the exact mechanism remains unclear in GC. Methods: Effects of CLIC1 on the progression of GC in vivo and in vitro and the potential underlying mechanisms have been investigated by analysing 54 patients with GC, as well as human gastric cell lines SGC-7901 and MGC-803, utilizing proteomics, RT-PCR, Western blotting, flow cytometry, Cell invasion and migration assays and xenograft tumor models. Results: Our study shows that CLIC1 knockdown by targeted-siRNA markedly inhibits GC cell invasion and migration and induces apoptosis in vitro. In total, 54 differentially expressed proteins were identified in GC cells SGC-7901 after CLIC1 silencing by isobaric tags for relative isotope labeled and absolute quantitation (iTRAQ) technology, including integrin α1 (ITGα1) and ITGα3. The expression levels of ITGα3, ITGαv, ITGβ1 and Bcl-2 mRNA and protein were decreased significantly in GC cells after CLIC1 knockdown; ITGα1 and Fas were upregulated, but the level of survivin was not significantly different. GC growth and metabolism were decreased in vivo after CLIC1 silencing, but apoptosis was markedly increased. Further study showed that the expression levels of ITGα3, ITGαv and ITGβ1, as well as AKT-phosphorylation, ERK-phosphorylation and p38-phosphorylation, were reduced in vivo after CLIC1 knockdown, while ITGα1 was upregulated. Conclusions: We speculate that CLIC1 may play an important role in the progression of GC, and its mechanism may be related to the regulation of integrin family proteins, which leads to the sequential regulation of the PI3K/AKT, MAPK/ERK and MAPK/p38 pathways.

Aluminized explosives exhibit excellent performance because the oxidation of aluminum (Al) powders enhances the pressure and temperature of detonation products. However, the equation of state (EOS) of detonation products has not been understood well. In the present study, we conducted long-time tests (approximately 1 ms) of a metal rod driven by detonation products of RDX, RDX/LiF, and RDX/Al. In addition, we used laser velocimetry (PDV) to measure the freesurface velocity of the rod. Thermochemical code DLCHEQ was successfully applied to the hydrodynamic program SSS to perform the roddriven test, and a novel method was established to study the EOS of detonation products from the perspective of composition. The reliability of DLCEHQ was validated by a small deviation (<10%) between the experimental rod free-surface velocity of RDX and the calculated results; the deviation was considerably less than that from the results obtained using the JWL EOS and ideal-gas EOS. The endothermic process and the reaction of Al powders (Alþ H2Oþ NOþ CO2/COþ H2 þ N2 þ Al2O3) were analyzed by calculating the rod free-surface velocity of RDX/LiF and RDX/Al, respectively. The results of the present study demonstrated that the thermodynamic state of Al powders has notable influence on the EOS of aluminized detonation products, and the findings were compared with those of previous studies. First, the temperature equilibrium between Al powders and CHNO products is not always achieved, and the disequilibrium is more obvious when the reaction of Al powders is stronger. Second, the reaction rate of Al powders depends on pressure and Al content. Finally, the endothermic process of Al powders has a high contribution to the decrease in the work ability of RDX/Al instead of the gasconsumption mechanism of the Al reaction. More than half of the reaction heat of Al powders is used to heat itself, whereas the gas consumption during the reaction is negligible. [ABSTRACT FROM AUTHOR]