Molecular and immunological characteristics of postoperative relapse in lymph node-positive esophageal squamous cell cancer.

BACKGROUND: The molecular and immunological characteristics of primary tumors and positive lymph nodes in esophageal squamous cell carcinoma (ESCC) are unknown and the relationship with recurrence is unclear, which this study attempted to explore. METHODS: A total of 30 ESCC patients with lymph node positive (IIB-IVA) were enrolled. Among them, primary tumor and lymph node specimens were collected from each patient, and subjected to 551-tumor-targeted DNA sequencing and 289-immuno-oncology RNA panel sequencing to identify the different molecular basis and immunological features, respectively. RESULTS: The primary tumors exhibited a higher mutation burden than lymph nodes (p < 0.001). One-year recurrent ESCC exhibited a higher Mucin16 (MUC16) mutation rate (p = 0.038), as well as univariate and multivariate analysis revealed that MUC16 mutation is independent genetic factor associated with reduced relapse-free survival (univariate, HR: 5.39, 95% CI: 1.67-17.4, p = 0.005; multivariate, HR: 7.36, 95% CI: 1.79-30.23, p = 0.006). Transcriptomic results showed non-relapse group had higher cytolytic activity (CYT) score (p = 0.025), and was enriched in the IFN-α pathway (p = 0.036), while those in the relapsed group were enriched in the TNF-α/NF-κB (p = 0.001) and PI3K/Akt pathway (p = 0.014). CONCLUSION: The difference in molecular characteristics between primary lesions and lymph nodes may be the cause of the inconsistent clinical outcomes. Mutations of MUC16 and poor immune infiltration are associated with rapid relapse of nodes-positive ESCC.

Prevalence and risk factors of malnutrition in patients with pulmonary tuberculosis: a systematic review and meta-analysis.

Background: Malnutrition is prevalent in patients with pulmonary tuberculosis (PTB) and is associated with a poor prognosis. Objective: This study aims to assess the prevalence and risk factors of malnutrition in patients with PTB. Methods: Studies related to the prevalence and risk factors of malnutrition in patients with PTB were searched through PubMed, Embase, Web of Science, and Cochrane Library databases from January 1990 to August 2022, and two researchers screened the literature, evaluated the quality, and extracted data independently. A random-effects model was used to pool the effect sizes and 95% confidence intervals. Subgroup analysis, meta-regression analysis, and sensitivity analysis were further performed to identify sources of heterogeneity and evaluate the stability of the results. Publication bias was assessed by Doi plot, Luis Furuya-Kanamori (LFK) asymmetry index, funnel plot, and Egger's tests. Results: A total of 53 studies involving 48, 598 participants were identified in this study. The prevalence of malnutrition was 48.0% (95% CI, 40.9-55.2%). Subgroup analysis revealed that malnutrition was more common among male gender (52.3%), bacterial positivity (55.9%), family size over 4 (54.5%), drug resistance (44.1%), residing in rural areas (51.2%), HIV infection (51.5%), Asian (51.5%), and African (54.5%) background. The prevalence of mild, moderate, and severe malnutrition was 21.4%, 14.0%, and 29.4%, respectively. Bacterial positivity (OR = 2.08, 95% CI 1.26-3.41), low income (OR = 1.44, 95% CI 1.11-1.86), and residing in rural areas (OR = 1.51, 95% CI 1.20-1.89) were risk factors of malnutrition in patients with PTB. However, male (OR = 1.04, 95% CI 0.85-1.26) and drinking (OR = 1.17, 95% CI 0.81-1.69) were not risk factors for malnutrition in patients with PTB. Due to the instability of sensitivity analysis, HIV infection, age, family size, smoking, and pulmonary cavity need to be reevaluated. Meta-regression suggested that sample size was a source of heterogeneity of prevalence. The Doi plot and LFK asymmetry index (LFK = 3.87) indicated the presence of publication bias for prevalence, and the funnel plot and Egger's test showed no publication bias for risk factors. Conclusion: This meta-analysis indicated that malnutrition was prevalent in patients with PTB, and bacterial positivity, low income, and those residing in rural areas were risk factors for malnutrition. Therefore, clinical workers should pay attention to screening the nutritional status of patients with PTB and identifying the risk factors to reduce the incidence of malnutrition and provide nutritional interventions early to improve the prognosis in patients with PTB.

Low Dimensional Nanostructure-Assisted Long-Range Surface Plasmon Resonance Sensors With High Figure of Merit.

Long-range surface plasmon resonance (LRSPR) sensors have been extensively studied by virtue of their extremely narrow full width at half maxima (FWHM) characteristics, but their low sensitivity remains an important factor limiting the figure of merit (FOM), making the sensors have difficulties in detecting small refractive index changes accurately. To address this problem, this paper proposes and demonstrates a low dimensional nanostructure (Au nanospheres, WS2) assisted LRSPR sensor to achieve an effective enhancement of the sensor interfaced electric field and thus improve the sensitivity. The performance parameters of the two sensors are compared with the LRSPR sensor by finite element method analysis, and the results showed that the assistance of the low dimensional nanostructure has a positive effect on the sensor. The first refractive index sensing experiment of the WS2-assisted LRSPR sensor was realized with a 25.47% increase in sensitivity and a 7.13% increase in FOM simultaneously, and the Au nanospheres-assisted LRSPR sensor with a 29.23% increase in sensitivity and a 15.95% increase in FOM simultaneously. The introduction of low dimensional nanostructures provides a flexible and effective means of sensitization for LRSPR sensors, making the plasmon resonance sensors combine high sensitivity, narrow FWHM and high FOM, which have promising applications in biochemical sensing.

Plasmonic crescent nanoarray-based surface lattice resonance sensor with a high figure of merit.

Due to the natural accumulation of radiation losses arising from the localization and random arrangement of nanoparticles, the figure of merit (FOM) of localized surface plasmon resonance (LSPR) sensors is usually very low (the value is usually less than 5 RIU-1). However, radiation losses of individual particles will be offset by adjusting the phase of the scattered field which is dependent on the structure parameters of arrays. Based on this, a two-dimensional periodic crescent nanoarray-based surface lattice resonance (SLR) sensor with a high FOM is proposed in this work. Some significant results have been obtained by mode field analysis and adjustment of structural parameters. On the one hand, the line-shape of the SLR spectrum is divided into a Fano-like line and a separate line. And the former usually has an FOM of 101 magnitude while the latter has an FOM of 103 magnitude. On the other hand, the relative size of the excitation wavelengths between SLR and LSPR is also vital. The FOM is higher but resonance depth decreases faster when the relative size increases. In this work, a full width at half-maximum (FWHM) of less than 0.5 nm and FOM of more than 1000 RIU-1 (the quality factor is more than 3000) are achieved by the proposed crescent nanoarrays. In addition, this structure demonstrates that plasmonic nanoarray-based SLR has enormous potential in trace substance detection.