Investigating the risk factors for nonadherence to analgesic medications in cancer patients: Establishing a nomogram model.

Objective: The substantial prevalence of nonadherence to analgesic medication among individuals diagnosed with cancer imposes a significant strain on both patients and healthcare resources. The objective of this study is to develop and authenticate a nomogram model for assessing nonadherence to analgesic medication in cancer patients. Methods: Clinical information, demographic data, and medication adherence records of cancer pain patients were gathered from the Affiliated Hospital of Chengde Medical University between April 2020 and March 2023. The risk factors associated with analgesic medication nonadherence in cancer patients were analyzed using the least absolute selection operator (LASSO) regression model and multivariate logistic regression. Additionally, a nomogram model was developed. The bootstrap method was employed to internally verify the model. Discrimination and accuracy of the nomogram model were evaluated using the Concordance index (C-index), area under the receiver Operating characteristic (ROC) curve (AUC), and calibration curve. The potential clinical value of the nomogram model was established through decision curve analysis (DCA) and clinical impact curve. Results: The study included a total of 450 patients, with a nonadherence rate of 43.33%. The model incorporated seven factors: age, address, smoking history, number of comorbidities, use of nonsteroidal antiinflammatory drugs (NSAIDs), use of opioids, and PHQ-8. The C-index of the model was found to be 0.93 (95% CI: 0.907-0.953), and the ROC curve demonstrated an AUC of 0.929. Furthermore, the DCA and clinical impact curves indicate that the built model can accurately predict cancer pain patients' medication adherence performance. Conclusions: A nomogram model based on 7 risk factors has been successfully developed and validated for long-term analgesic management of cancer patients.

A common single nucleotide polymorphism is associated with inflammation and critical illness outcomes.

Acute inflammation is heterogeneous in critical illness and predictive of outcome. We hypothesized that genetic variability in novel, yet common, gene variants contributes to this heterogeneity and could stratify patient outcomes. We searched algorithmically for significant differences in systemic inflammatory mediators associated with any of 551,839 SNPs in one derivation (n = 380 patients with blunt trauma) and two validation (n = 75 trauma and n = 537 non-trauma patients) cohorts. This analysis identified rs10404939 in the LYPD4 gene. Trauma patients homozygous for the A allele (rs10404939AA; 27%) had different trajectories of systemic inflammation along with persistently elevated multiple organ dysfunction (MOD) indices vs. patients homozygous for the G allele (rs10404939GG; 26%). rs10404939AA homozygotes in the trauma validation cohort had elevated MOD indices, and non-trauma patients displayed more complex inflammatory networks and worse 90-day survival compared to rs10404939GG homozygotes. Thus, rs10404939 emerged as a common, broadly prognostic SNP in critical illness.

BATF2 enhances proinflammatory cytokine responses in macrophages and improves early host defense against pulmonary Klebsiella pneumoniae infection.

Basic leucine zipper transcription factor ATF-like 2 (BATF2) is a transcription factor that is emerging as an important regulator of the innate immune system. BATF2 is among the top upregulated genes in human alveolar macrophages treated with LPS, but the signaling pathways that induce BATF2 expression in response to Gram-negative stimuli are incompletely understood. In addition, the role of BATF2 in the host response to pulmonary infection with a Gram-negative pathogen like Klebsiella pneumoniae (Kp) is not known. We show that induction of Batf2 gene expression in macrophages in response to Kp in vitro requires TRIF and type I interferon (IFN) signaling, but not MyD88 signaling. Analysis of the impact of BATF2 deficiency on macrophage effector functions in vitro showed that BATF2 does not directly impact macrophage phagocytic uptake and intracellular killing of Kp. However, BATF2 markedly enhanced macrophage proinflammatory gene expression and Kp-induced cytokine responses. In vivo, Batf2 gene expression was elevated in lung tissue of wild-type (WT) mice 24 h after pulmonary Kp infection, and Kp-infected BATF2-deficient (Batf2-/-) mice displayed an increase in bacterial burden in the lung, spleen, and liver compared with WT mice. WT and Batf2-/- mice showed similar recruitment of leukocytes following infection, but in line with in vitro observations, proinflammatory cytokine levels in the alveolar space were reduced in Batf2-/- mice. Altogether, these results suggest that BATF2 enhances proinflammatory cytokine responses in macrophages in response to Kp and contributes to the early host defense against pulmonary Kp infection.NEW & NOTEWORTHY This study investigates the signaling pathways that mediate induction of BATF2 expression downstream of TLR4 and also the impact of BATF2 on the host defense against pulmonary Kp infection. We demonstrate that Kp-induced upregulation of BATF2 in macrophages requires TRIF and type I IFN signaling. We also show that BATF2 enhances Kp-induced macrophage cytokine responses and that BATF2 contributes to the early host defense against pulmonary Kp infection.

The development of a clinical nomogram to predict medication nonadherence in patients with knee osteoarthritis.

Knee osteoarthritis (KOA) is a common bone disease in older patients. Medication adherence is of great significance in the prognosis of this disease. Therefore, this study analyzed the high-risk factors that lead to medication nonadherence in patients with KOA and constructed a nomogram risk prediction model. The basic information and clinical characteristics of inpatients diagnosed with KOA at the Department of Orthopedics, The Affiliated Hospital of Chengde Medical University, were collected from January 2020 to January 2022. The Chinese version of the eight-item Morisky scale was used to evaluate medication adherence. The Kellgren-Lawrence (KL) classification was performed in combination with the imaging data of patients. Least absolute shrinkage and selection operator regression analysis and logistic multivariate regression analysis were used to analyze high-risk factors leading to medication nonadherence, and a prediction model of the nomogram was constructed. The model was internally verified using bootstrap self-sampling. The index of concordance (C-index), area under the operating characteristic curve (AUC), decision curve, correction curve, and clinical impact curve were used to evaluate the model. A total of 236 patients with KOA were included in this study, and the non-adherence rate to medication was 55.08%. Seven influencing factors were included in the nomogram prediction: age, underlying diseases, diabetes, age-adjusted Charlson comorbidity index (aCCI), payment method, painkillers, and use of traditional Chinese medicine. The C-index and AUC was 0.935. The threshold probability of the decision curve analysis was 0.02-0.98. The nomogram model can be effectively applied to predict the risk of medication adherence in patients with KOA, which is helpful for medical workers to identify and predict the risk of individualized medication adherence in patients with KOA at an early stage of treatment, and then carry out early intervention.

Development of a Predictive Nomogram for Estimating Medication Nonadherence in Hemodialysis Patients.

BACKGROUND Medication compliance in hemodialysis patients affects the therapeutic effect of treatment and patient survival. Therefore, we aimed to explore the influencing factors of medication adherence in hemodialysis patients and develop a nomogram model to predict medication adherence. MATERIAL AND METHODS Data from questionnaires on medication adherence in hemodialysis patients were collected in Chengde from May 2020 to December 2020. The least absolute selection operator (LASSO) regression model and multivariable logistic regression analysis were used to analyze the risk factors for medication adherence in hemodialysis patients, and then a nomogram model was established. The bootstrap method was applied for internal validation. The concordance index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), decision curve analysis (DCA), calibration curve, net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index were used to evaluate the degree of differentiation and accuracy of the nomogram model, and clinical impact was used to investigate the potential clinical value of the nomogram model. RESULTS In total, 206 patients were included in this study, with a rate of medication nonadherence of 41.75%. Eight predictors were identified to build the nomogram model. The C-index, AUC, DCA, calibration curve, NRI, and IDI showed that the model had good discrimination and accuracy. The clinical impact plot showed that the nomogram of medication adherence in hemodialysis patients had clinical application value. CONCLUSIONS We developed and validated a nomogram model that is intuitive to apply for predicting medication adherence in hemodialysis patients.

Turn-On Fluorescence Enantioselective Sensing of Hydroxyl Carboxylic Enantiomers by Metal-Organic Framework Nanosheets with a Homochiral Tetracarboxylate of Cyclohexane Diamide.

Two-dimensional (2D) metal-organic frameworks (MOFs) have attracted growing interest due to excellent performance in gas separation, energy conversion and storage, catalysis, and sensing, but their homochirality and exfoliation as well as related enantioselective catalysis and sensing remain a stage of pending exploration owing to the scarcity of homochiral MOFs and intrinsic aggregation of nanosheets. Herein, a homochiral 2D MOF (HMOF-3) with polymeric chirality, good thermostability, and solvent stability is designed and constructed by a homochiral organic ligand 5,5'-((1R,2R)-cyclohexane dicarbonyl bis(azanediyl)) diisophthalic acid (R,R-CHCAIP), a ditopic coligand 4,4'-bipyridine, and Zn salts. Remarkably, HMOF-3 can be exfoliated via solvent-assisted sonication to achieve 2D HMOF-3 nanosheets (HMOF-3-NS), which exhibit a sensitive turn-on effect with the fluorescence enhancement up to 63.5 times in the presence of R/S-mandelic acid, d/l-tartaric acid, d/l-lactic acid, d/l-alanine, and d/l-tryptophan. More importantly, the high surface area, polymeric chirality environment, and highly accessible functional sites on the surface of HMOF-3 nanosheets enable close contact with probed enantiomers, leading to highly enantioselective and sensitive sensing. The turn-on mechanism of host-guest-assisted electronic transfer is confirmed by DFT calculation and the relative experiment. This work highlights the promise of homochiral 2D MOF nanosheets for enantioselective sensing applications.

Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival.

BACKGROUND: Kidney renal clear cell carcinoma (KIRC) is a fatal malignancy of the urinary system. Autophagy is implicated in KIRC occurrence and development. Here, we evaluated the prognostic value of autophagy-related genes (ARGs) in kidney renal clear cell carcinoma. MATERIALS AND METHODS: We analyzed RNA sequencing and clinical KIRC patient data obtained from TCGA and ICGC to develop an ARG prognostic signature. Differentially expressed ARGs were further evaluated by functional assessment and bioinformatic analysis. Next, ARG score was determined in 215 KIRC patients using univariable Cox and LASSO regression analyses. An ARG nomogram was built based on multivariable Cox analysis. The prognosis nomogram model based on the ARG signatures and clinicopathological information was evaluated for discrimination, calibration, and clinical usefulness. RESULTS: A total of 47 differentially expressed ARGs were identified. Of these, 8 candidates that significantly correlated with KIRC overall survival were subjected to LASSO analysis and an ARG score built. Functional enrichment and bioinformatic analysis were used to reveal the differentially expressed ARGs in cancer-related biological processes and pathways. Multivariate Cox analysis was used to integrate the ARG nomogram with the ARG signature and clinicopathological information. The nomogram exhibited proper calibration and discrimination (C-index = 0.75, AUC = >0.7). Decision curve analysis also showed that the nomogram was clinically useful. CONCLUSIONS: KIRC patients and doctors could benefit from ARG nomogram use in clinical practice.

Single-Component Color-Tunable Gd(pic)3: Eu3+ Phosphor Based on a Metal-Organic Framework for Near-UV White-Light-Emitting Diodes.

Compared with their multicomponent analogues, single-component white-light-emitting diodes (WLEDs) can eliminate the disadvantages such as high cost, fluorescence self-absorption, poor machinability, and reproducibility, but how to produce white light with high quality in a single-phase host is still a big challenge. In the work, a series of Eu3+/Tb3+-doped Gd(pic)3 and La(pic)3 are obtained through solvothermal conditions with picolinic acid (Hpic) and lanthanide nitrate. Researchers could regularly modulate the emitting color of phosphors by adjusting the excitation wavelength as well as the relative concentration of Ln3+ ions to obtain white light. Different luminance values [especially quantum yield (QYs)] between host materials Gd(pic)3 and La(pic)3 are investigated, which shows that doping of Eu3+ into Gd(pic)3 can improve QY to a great extent. By employing Gd0.9512Eu0.0488(pic)3 and Gd0.9141Eu0.0451Tb0.0408(pic)3 as phosphors, we successfully fabricated two excellent near-ultraviolet (365 nm) WLEDs with CIE chromaticity coordinates (0.3052, 0.3462) and (0.3007, 0.3448), relatively low color-correlated temperature (6755, 7001 K), and high color rendering index (R a = 71.8, 72.9). This approach may open a new prospect for developing single-phase near-ultraviolet phosphors with high efficiency.

White-Light Emission from Dual-Way Photon Energy Conversion in a Dye-Encapsulated Metal-Organic Framework.

The design of white-light phosphors is attractive in solid-state lighting (SSL) and related fields. A new strategy in obtaining white light emission (WLE) from dual-way photon energy conversion in a series of dye@MOF (LIFM-WZ-6) systems is presented. Besides the traditional UV-excited one-photon absorption (OPA) pathway, white-light modulation can also be gained from the combination of NIR-excited green and red emissions of MOF backbone and encapsulated dyes via two-photon absorption (TPA) pathway. As a result, down-conversion OPA white light was obtained for RhB+ @LIFM-WZ-6 (0.1 wt %), BR-2+ @LIFM-WZ-6 (2 wt %), and APFG+ @LIFM-WZ-6 (0.1 wt %) samples under 365 nm excitation. RhB+ @LIFM-WZ-6 (0.05 wt %), BR-2+ @LIFM-WZ-6 (1 wt %) and APFG+ @LIFM-WZ-6 (0.05 wt %) exhibit up-conversion TPA white light under the excitation of 800, 790, and 730 nm, respectively. This new WLE generation strategy combines different photon energy conversion mechanisms together.

Breathing Europium-Terbium Co-doped Luminescent MOF as a Broad-Range Ratiometric Thermometer with a Contrasting Temperature-Intensity Relationship.

Solvothermal reactions of lanthanide salts and a semirigid tripodal H3tatab (4,4',4″-s-triazine-1,3,5-triyltri-p-aminobenzoic acid) ligand in mixed water and N-methyl pyrrolidone (NMP) generated novel breathing MOFs [Ln(tatab)]·solvent (Ln = Eu in 1-Eu, Tb in 1-Tb, Eu0.015Tb0.985 in 1-Eu0.015Tb0.985). The framework of 1 was contracted upon removal of guests to form partly desolvated [Ln (tatab)]·3.7H2O·2.5NMP (1'). Single-crystal X-ray analyses demonstrated that 1 has the breathing ability to spontaneously release guests and maintain the same topology. In contrast to as-synthesized 1, the cell volume of 1' decreased markedly upon removal of the guests. Different from linear dicarboxylates, the semirigid tripodal tatab ligand is bridged to an inorganic Ln-O chain, limiting the rotation around the O-O-axis of carboxylate. The breathing mechanism is based on the flexible C-N-C angles of amide bonds in the tatab ligand, causing a change in the solvent-accessible volume in the framework. Interestingly, the luminescence color of breathing co-doped lanthanide MOF 1'-Eu0.015Tb0.985 is blue-shifted and turned from orange to green with an increase in temperature, which can be attributed to a change in the relative intensity of Tb and Eu emissions, and is quite different from that observed for the reported related compounds. The breathing co-doped lanthanide MOF 1'-Eu0.015Tb0.985 can be applied as a high-sensitivity ratiometric thermometer in a broad temperature from 90 to 300 K.

Homochiral MOF as Circular Dichroism Sensor for Enantioselective Recognition on Nature and Chirality of Unmodified Amino Acids.

Self-assembly of zinc salt with rationally designed chiral ligand, (1R,2R)-2-(pyridine-4-ylcarbamoyl) cyclohexanecarboxylic acid (RR-PCCHC) generated 2D homochiral metal-organic framework [Zn(RR-PCCHC)2] (HMOF-1) that is composed of DNA-like right-handed double-helix structure. HMOF-1 shows high solvent and thermal stability and is also stable in neutral, weak acidic and weak basic aqueous solution. Emulsified HMOF-1 shows strong inherent circular dichroism (CD) signal in aqueous solution, which can show regular intensity change by induction of amino acids. On the basis of the measuring of CD signal intensity, a chemosensor for unmodified amino acids is fabricated, which differ from reported those in which CD signal is amplified by a complicated chemical reaction of originally CD-silent molecule with probed amino acids. This chemosensor can be used for rapid, convenient and sensitive detection of micro amount of amino acids. Most remarkably, 3 × 10-8 mol of l-aspartic acid and 4 × 10-8 mol of d-aspartic acid in aqueous solution can completely quench CD signal of emulsified HMOF-1 in H2O. It is found that the difference of recognition ability between d- and l-proline is the largest in all probed amino acids. The LOD (limit of detection) of the proposed sensor for the determination of aspartic acid is 13.31 ppm. The recognition efficiency η = [Formula: see text] × 100% for l-aspartic acid is as high as 92.1%. The interacting mechanism of DNA-like HMOF-1 with probed amino acids is similar to that of groove binding of targeting drug with DNA.

Single Component Lanthanide Hybrids Based on Metal-Organic Framework for Near-Ultraviolet White Light LED.

Near-UV single-phase white-light phosphor (Eu0.045Tb0.955CPOMBA/La0.6Eu0.1Tb0.3CPOMBA) based on metal-organic framework was prepared by in situ doping isostructural lanthanide MOF with Eu(3+) and Tb(3+), and it is found that the energy can effectively transfer from organic ligand to lanthanides, which can overcome weak absorption under direct excitation of lanthanide ions due to the forbidden f-f transitions. The photoluminescence and thermostability of the new MOF phosphor are investigated, and effective white-light emission is achieved under 365 and 380 nm excitations. By employing Eu0.045Tb0.955CPOMBA as phosphor, we fabricated a near-ultraviolet white-light-emitting diode (n-UV WLED) (365 nm) with low CCT (5733 K), high CRI (Ra = 73.4), and CIE chromaticity coordinate (0.3264, 0.3427). This approach may open new perspectives for developing single-phase UV phosphors.