Template-Confined Oriented Perovskite Nanowire Arrays Enable Polarization Detection and Imaging.

Polarized light detection can effectively identify the difference between the polarization information on the target and the background, which is of great significance for detection in complex natural environments and/or extreme weather. Generally, polarized light detection inevitably relies on anisotropic structures of photodetector devices, while organic-inorganic hybrid perovskites are ideal for anisotropic patterning due to their simple and efficient preparation by solution method. Compared to patterned thin films, patterned arrays of aligned one-dimensional (1D) perovskite nanowires (PNWAs) have fewer grain boundaries and lower defect densities, making them well suited for high-performance polarization-sensitive photodetectors. Here, we fabricated PNWAs crystallographically aligned with variable line widths and alignment densities employing CD-ROM and DVD-ROM grating pattern template-confined growth (TCG) methods. The photodetectors constructed from MAPbI3 PNWAs achieved responsivity of 35.01 A/W, detectivity of 6.85 × 1013 Jones, and fast response with a rise time of 172 µs and fall time of 114 µs. They were successfully applied to high-performance polarization detection with a polarization ratio of 1.81, potentially applicable in polarized light detection systems.

Unnatural Peptide Assemblies Rapidly Deplete Cholesterol and Potently Inhibit Cancer Cells.

Cholesterol-rich membranes play a pivotal role in cancer initiation and progression, necessitating innovative approaches to target these membranes for cancer inhibition. Here we report the first case of unnatural peptide (1) assemblies capable of depleting cholesterol and inhibiting cancer cells. Peptide 1 self-assembles into micelles and is rapidly taken up by cancer cells, especially when combined with an acute cholesterol-depleting agent (MßCD). Click chemistry has confirmed that 1 depletes cell membrane cholesterol. It localizes in membrane-rich organelles, including the endoplasmic reticulum, Golgi apparatus, and lysosomes. Furthermore, 1 potently inhibits malignant cancer cells, working synergistically with cholesterol-lowering agents. Control experiments have confirmed that C-terminal capping and unnatural amino acid residues (i.e., BiP) are essential for both cholesterol depletion and potent cancer cell inhibition. This work highlights unnatural peptide assemblies as a promising platform for targeting the cell membrane in controlling cell fates.

AMP-Coated TiO2 Doped ZnO Nanomaterials Enhanced Antimicrobial Activity and Efficacy in Otitis Media Treatment by Elevating Hydroxyl Radical Levels.

Background: In the past decades, antimicrobial resistance (AMR) has been a major threat to global public health. Long-term, chronic otitis media is becoming more challenging to treat, thus the novel antibiotic alternative agents are much needed. Methods: ZnO@TiO2@AMP (ATZ NPs) were synthesized through a solvothermal method and subjected to comprehensive characterization. The in vitro and in vivo antibacterial effect and biocompatibility of ATZ NPs were evaluated. For the antibacterial mechanism exploration, we utilized the Electron Paramagnetic Resonance (EPR) Spectrometer to detect and analyze the hydroxyl radicals produced by ATZ NPs. Results: ATZ NPs exhibited a spherical structure of 99.85 nm, the drug-loading rate for ZnO was 20.73%, and AMP within ATZ NPs was 41.86%. Notably, the Minimum Inhibitory Concentration (MIC) value of ATZ NPs against Staphylococcus aureus (S. aureus), methicillin-resistant Staphylococcus aureus (MRSA), and Streptococcus pneumoniae (S. pneumoniae) were 10 µg/mL, and Minimum Bactericidal Concentration (MBC) value of ATZ NPs against S. aureus, and S. pneumoniae were 50 µg/mL. In comparison to the model group, the treatment of otitis media with ATZ NPs significantly reduces inflammatory exudation in the middle ear cavity, with no observable damage to the tympanic membrane. Both in vivo and in vitro toxicity tests indicating the good biocompatibility of ATZ NPs. Moreover, EPR spectroscopy results highlighted the superior ability of ATZ NPs to generate hydroxyl radicals (·OH) compared to ZnO NPs. Conclusion: ATZ NPs exhibited remarkable antibacterial properties both in vivo and in vitro. This innovative application of advanced ATZ NPs, bringing great promise for the treatment of otitis media.

Design, Synthesis, and Biological Evaluation of ß-Trifluoroethoxydimethyl Selenides as Potent Antiosteoporosis Agents.

An efficient protocol for the synthesis of ß-trifluoroethoxydimethyl selenides was achieved under mild reaction conditions, and 39 compounds were prepared. All compounds were evaluated for their abilities to inhibit RANKL-induced osteoclastogenesis, compound 4aa exhibited the most potent activity. Further investigations revealed that 4aa could inhibit F-actin ring generation, bone resorption, and osteoclast-specific gene expression in vitro. Western blot analyses demonstrated that compound 4aa abrogated the RANKL-induced mitogen-activated protein kinase and NF-kB-signaling pathways. In addition, 4aa also displayed a notable impact on the osteoblastogenesis of MC3T3-E1 preosteoblasts. In vivo experiments revealed that compound 4aa significantly ameliorated bone loss in an ovariectomized (OVX) mice model. Furthermore, the surface plasmon resonance experiment results revealed that 4aa probably bound to RANKL. Collectively, the above-mentioned findings suggested that compound 4aa as a potential RANKL inhibitor averted OVX-triggered osteoporosis by regulating the inhibition of osteoclast differentiation and stimulation of osteoblast differentiation.

Synthesis of Pyrimido[1,2-a]indolediones and Pyrimidinediones via [4+2] Annulation of 2H-Azirine-2-carbaldehydes.

NHC-catalyzed [4+2] annulation of 2H-azirine-2-carbaldehydes with ketimines and isocyanates has been developed, providing straightforward synthetic protocols for constructing structurally intriguing pyrimido[1,2-a]indolediones and pyrimidinediones under mild conditions with excellent yields. This protocol can be used to synthesize the core skeleton of pharmaceutically important drugs and pyrimido[1,2-a]indoledione-containing natural products, making it potentially valuable for creating biologically active derivatives.

The role of oxidative stress biomarkers in the development of peri-implant disease: A systematic review and meta-analysis.

OBJECTIVES: To analyze the role of oxidative stress (OS) biomarkers in peri­implant diseases using a systematic review and meta-analysis approach. DATE: The review incorporated cross-sectional studies, randomized controlled trials, and case-control trials to evaluate the differences in OS biomarkers of peri­implant disease. SOURCES: A comprehensive literature search was conducted in electronic databases such as PubMed, Scopus, Embase, Web of Science, and CNKI, and no restrictions were applied during the search process. STUDY SELECTION: A total of 452 studies were identified, of which 18 were eligible for inclusion. Risk of bias and sensitivity analysis were assessed using Egger's test and funnel plots. RESULTS: We found that the levels of glutathione peroxidase (GSH-Px) in the peri­implant sulcus fluid (PISF) of patients with peri­implant diseases were significantly reduced (SMD = -1.40; 95 % CI = 1.70, -1.11; p < 0.001), while the levels of total myeloperoxidase (MPO) and malondialdehyde (MDA) were significantly increased (SMD = 0.46; 95 % CI = 0.12, 0.80; p = 0.008; SMD = 0.28; 95 % CI = 0.01, 0.56; p = 0.043). However, there were no significant differences of MPO concentration (SMD = 0.38; 95 % CI = -0.39, 1.15; p = 0.331) and superoxide dismutase (SOD)(SMD = -0.43; 95 % CI = -1.94, 1.07; p = 0.572) in PISF between peri­implant disease group and control group. Similarly, salivary MPO did not show significant differences (SMD = 1.62; 95 % CI = -1.01, 4.24; p = 0.227). CONCLUSIONS: Our results supported that the level of local OS biomarkers was closely related to peri­implant diseases. GSH-Px, total MPO and MDA may be PISF biomarkers with good capability to monitor the development of peri­implant disease. CLINICAL SIGNIFICANCE: This study found significant differences in the levels of local OS biomarkers (GSH-Px, total MPO, and MDA) between patients with peri­implant diseases and healthy subjects, which may be ideal candidate biomarkers for predicting and diagnosing peri­implant diseases.

PhbZIP2 regulates photosynthesis-related genes in an intertidal macroalgae, Pyropia haitanensis, under stress.

Intertidal macroalgae are important research subjects in stress biology. Basic region-leucine zipper transcription factors (bZIPs) play an important regulatory role in the expression of target genes under abiotic stress. We herein identified a bZIP2 gene PhbZIP2 to regulate abiotic stress tolerance in Pyropia haitanensis, a representative intertidal macroalgal species. Cloning and sequencing of the cDNA characterized a BRLZ structure and an α coiled-coil structure between amino acids and Expression of PhbZIP2 was detected to upregulate under both high temperature and salt stresses. A DAP-seq analysis revealed the PhbZIP2-binding motifs of (T/C)TCCA(C/G) and A (A/G)AAA (G/A), which differed from the conserved motifs in plants. Overexpression of PhbZIP2 was indicative of a high temperature and salt stress tolerances in transgenic Chlamydomonas reinhardtii. It was suggested that PhbZIP2 was probably involved in regulating expression of the photosynthetic-related genes and the response to the abiotic stresses in P. haitanensis, which provide new insights for elucidating efficient adaptation strategies of intertidal macroalgae.

Effects of schisandrin B on hypoxia-related cognitive function and protein expression in vascular dementia rats.

Vascular dementia (VD) a heterogenous group of brain disorders in which cognitive impairment is attributable to vascular risk factors and cerebrovascular disease. A common phenomenon in VD is a dysfunctional cerebral regulatory mechanism associated with insufficient cerebral blood flow, ischemia and hypoxia. Under hypoxic conditions oxygen supply to the brain results in neuronal death leading to neurodegenerative diseases including Alzheimer's (AD) and VD. In conditions of hypoxia and low oxygen perfusion, expression of hypoxia-inducible factor 1 alpha (HIF-1α) increases under conditions of low oxygen and low perfusion associated with upregulation of expression of hypoxia-upregulated mitochondrial movement regulator (HUMMR), which promotes anterograde mitochondrial transport by binding with trafficking protein kinesin 2 (TRAK2). Schisandrin B (Sch B) an active component derived from Chinese herb Wuweizi prevented ß-amyloid protein induced morphological alterations and cell death using a SH-SY5Y neuronal cells considered an AD model. It was thus of interest to determine whether Sch B might also alleviate VD using a rat bilateral common carotid artery occlusion (BCAO) dementia model. The aim of this study was to examine the effects of Sch B in BCAO on cognitive functions such as Morris water maze test and underlying mechanisms involving expression of HIF-1α, TRAK2, and HUMMR levels. The results showed that Sch B improved learning and memory function of rats with VD and exerted a protective effect on the hippocampus by inhibition of protein expression of HIF-1α, TRAK2, and HUMMR factors. Evidence indicates that Sch B may be considered as an alternative in VD treatment.

Deletion of Pax1 scoliosis-associated regulatory elements leads to a female-biased tail abnormality.

Adolescent idiopathic scoliosis (AIS), a sideways curvature of the spine, is sexually dimorphic, with increased incidence in females. A genome-wide association study identified a female-specific AIS susceptibility locus near the PAX1 gene. Here, we use mouse enhancer assays, three mouse enhancer knockouts, and subsequent phenotypic analyses to characterize this region. Using mouse enhancer assays, we characterize a sequence, PEC7, which overlaps the AIS-associated variant, and find it to be active in the tail tip and intervertebral disc. Removal of PEC7 or Xe1, a known sclerotome enhancer nearby, or deletion of both sequences lead to a kinky tail phenotype only in the Xe1 and combined (Xe1+PEC7) knockouts, with only the latter showing a female sex dimorphic phenotype. Extensive phenotypic characterization of these mouse lines implicates several differentially expressed genes and estrogen signaling in the sex dimorphic bias. In summary, our work functionally characterizes an AIS-associated locus and dissects the mechanism for its sexual dimorphism.

Patient Characteristics Associated With Using Transcatheter Left Atrial Appendage Occlusion Versus Oral Anticoagulants for Atrial Fibrillation.

BACKGROUND: Transcatheter left atrial appendage occlusion (LAAO) is an alternative to oral anticoagulants (OACs) for stroke prevention in patients with atrial fibrillation, but the predictors of LAAO use in routine care are unclear. We aimed to assess the utilization trends of LAAO and compare the change in characteristics of LAAO users versus OACs since its marketing. METHODS: Using the US Medicare claims database (March 15, 2015, to December 31, 2020), we identified patients with atrial fibrillation, ≥65 years, and CHA2DS2-VASc score ≥2 (men) or ≥3 (women), with either first implantation of an LAAO device or initiation of OACs, including apixaban, dabigatran, rivaroxaban, edoxaban, or warfarin. Patient characteristics, measured 365 days before the first LAAO or OAC use date, were compared using logistic regression. RESULTS: There were 30 058 LAAO recipients (mean age, 77.74 years; female, 42.1%) and 792 600 OAC initiators (mean age, 78.48; female, 53.3%). In 2020, patients had higher odds of initiating LAAO use than in 2015 (0.52 versus 9.32%; adjusted odds ratio [aOR], 13.64 [95% CI, 12.56-14.81]). Old age (ie, >85 versus 65-75 years; aOR, 0.84 [95% CI, 0.80-0.88]), female sex (aOR, 0.74 [95% CI, 0.71-0.76]), Black race (aOR, 0.63 [95% CI, 0.58-0.68]) versus White race, and Medicaid eligibility (aOR, 0.61 [95% CI, 0.58-0.64]) were associated with lower odds of receiving LAAO. Among clinical characteristics, frailty, cancer, fractures, and venous thromboembolism were associated with lower odds of LAAO use, while history of intracranial and extracranial bleeding, coagulopathy, and falls were associated with higher odds of receiving LAAO. CONCLUSIONS: Among patients with atrial fibrillation receiving stroke-preventive therapy, LAAO use increased rapidly from 2015 to 2020 and was positively associated with the risk factors for OAC complications but negatively associated with old age, advanced frailty, and cancer. Black race and female sex were associated with a lower likelihood of receiving LAAO.

Regulatory T cells subgroups in the tumor microenvironment cannot be overlooked: Their involvement in prognosis and treatment strategy in melanoma.

BACKGROUND: Melanoma, the most lethal form of skin cancer, presents substantial challenges despite effective surgical interventions for in situ lesions. Regulatory T cells (Tregs) wield a pivotal immunomodulatory influence within the tumor microenvironment, yet their impact on melanoma prognosis and direct molecular interactions with melanoma cells remain elusive. This investigation employs single-cell analysis to unveil the intricate nature of Tregs in human melanoma. METHODS: Single-cell RNA and bulk sequencing data, alongside clinical information, were obtained from public repositories. Initially, GO and GSEA analyses were employed to delineate functional disparities among distinct cell subsets. Pseudotime and cell-cell interconnection analyses were conducted, followed by an endeavor to construct a prognostic model grounded in Treg-associated risk scores. This model's efficacy was demonstrated via PCA and K-M analyses, with multivariate Cox regression affirming its independent prognostic value in melanoma patients. Furthermore, immune infiltration analysis, immune checkpoint gene expression scrutiny, and drug sensitivity assessments were performed to ascertain the clinical relevance of this prognostic model. RESULTS: Following batch effect correction, 80 025 cells partitioned into 31 clusters, encompassing B cells, plasma cells, endothelial cells, fibroblasts, melanoma cells, monocytes, macrophages, and T_NK cells. Within these, 4240 CD4+ T cells were subclassified into seven distinct types. Functional analysis underscored the immunomodulatory function of Tregs within the melanoma tumor microenvironment, elucidating disparities among Treg subpopulations. Notably, the ITGB2 signaling pathway emerged as a plausible molecular nexus linking Tregs to melanoma cells. Our prognostic signature exhibited robust predictive capacities for melanoma prognosis and potential implications in evaluating immunotherapy response. CONCLUSION: Tregs exert a critical role in immune suppression within the melanoma tumor microenvironment, revealing a potential molecular-level association with melanoma cells. Our innovative Treg-centered signature introduces a promising prognostic marker for melanoma, holding potential for future clinical prognostic assessments.

Cayratia albifolia C.L.Li exerts anti-rheumatoid arthritis effect by inhibiting macrophage activation and neutrophil extracellular traps (NETs).

BACKGROUND: Cayratia albifolia C.L.Li (CAC), commonly known as "Jiao-Mei-Gu" in China, has been extensively utilized by the Dong minority for several millennia to effectively alleviate symptoms associated with autoimmune diseases. CAC extract is believed to possess significant anti-inflammatory properties within the context of Dong medicine. However, an in-depth understanding of the specific pharmaceutical effects and underlying mechanisms through which CAC extract acts against rheumatoid arthritis (RA) has yet to be established. METHODS: Twenty-four Sprague-Dawley rats were divided into four groups, with six rats in each group. To induce the collagen-induced arthritis (CIA) model, the rats underwent a process of double immunization with collagen and adjuvant. CAC extract (100 mg/kg) was orally administered to rats. The anti-RA effects were evaluated in CIA rats by arthritis score, hind paw volume and histopathology analysis. Pull-down assay was conducted to identify the potential targets of CAC extract from RAW264.7 macrophage lysates. Moreover, mechanism studies of CAC extract were performed by immunofluorescence assays, real-time PCR and Western blot. RESULTS: CAC extract was found to obviously down-regulate hind paw volume of CIA rats, with diminished inflammation response and damage. 177 targets were identified from CAC extract by MS-based pull-down assay. Bioinformatics analysis found that these targets were mainly enriched in macrophage activation and neutrophils extracellular traps (NETs). Additionally, we reported that CAC extract owned significant anti-inflammatory activity by regulating PI3K-Akt-mTOR signal pathway, and inhibited NETosis in response to PMA. CONCLUSIONS: We clarified that CAC extract significantly attenuated RA by inactivating macrophage and reducing NETosis via a multi-targets regulation.

Enhancing the electric charge output in LiNbO3-based piezoelectric pressure sensors.

Lithium niobate (LiNbO3) single crystals are a kind of ferroelectric material with a high piezoelectric coefficient and Curie temperature, which is suitable for the preparation of piezoelectric pressure sensors. However, there is little research reporting on the use of LiNbO3 single crystals to prepare piezoelectric pressure sensors. Therefore, in this paper, LiNbO3 was used to prepare piezoelectric pressure sensors to study the feasibility of using LiNbO3 single crystals as a sensitive material for piezoelectric pressure sensors. In addition, chemical mechanical polishing (CMP) technology was used to prepare LiNbO3 crystals with different thicknesses to study the influence of these LiNbO3 crystals on the electric charge output of the sensors. The results showed that the sensitivity of a 300 µm sample (0.218 mV kPa-1) was about 1.23 times that of a 500 µm sample (0.160 mV kPa-1). Low-temperature polymer heterogeneous integration and oxygen plasma activation technologies were used to realize the heterogeneous integration of LiNbO3 and silicon to prepare piezoelectric pressure sensors, which could significantly improve the sensitivity of the sensor by approximately 16.06 times (2.569 mV kPa-1) that of the original sample (0.160 mV kPa-1) due to an appropriate residual stress that did not shatter LiNbO3 or silicon, thus providing a possible method for integrating piezoelectric pressure sensors and integrated circuits.

A Hydrogel Electrolyte toward a Flexible Zinc-Ion Battery and Multifunctional Health Monitoring Electronics.

The compact design of an environmentally adaptive battery and effectors forms the foundation for wearable electronics capable of time-resolved, long-term signal monitoring. Herein, we present a one-body strategy that utilizes a hydrogel as the ionic conductive medium for both flexible aqueous zinc-ion batteries and wearable strain sensors. The poly(vinyl alcohol) hydrogel network incorporates nano-SiO2 and cellulose nanofibers (referred to as PSC) in an ethylene glycol/water mixed solvent, balancing the mechanical properties (tensile strength of 6 MPa) and ionic diffusivity at -20 °C (2 orders of magnitude higher than 2 M ZnCl2 electrolyte). Meanwhile, cathode lattice breathing during the solvated Zn2+ intercalation and dendritic Zn protrusion at the anode interface are mitigated. Besides the robust cyclability of the Zn∥PSC∥V2O5 prototype within a wide temperature range (from -20 to 80 °C), this microdevice seamlessly integrates a zinc-ion battery with a strain sensor, enabling precise monitoring of the muscle response during dynamic body movement. By employing transmission-mode operando XRD, the self-powered sensor accurately documents the real-time phasic evolution of the layered cathode and synchronized strain change induced by Zn deposition, which presents a feasible solution of health monitoring by the miniaturized electronics.

Segment anything model for medical image segmentation: Current applications and future directions.

Due to the inherent flexibility of prompting, foundation models have emerged as the predominant force in the fields of natural language processing and computer vision. The recent introduction of the Segment Anything Model (SAM) signifies a noteworthy expansion of the prompt-driven paradigm into the domain of image segmentation, thereby introducing a plethora of previously unexplored capabilities. However, the viability of its application to medical image segmentation remains uncertain, given the substantial distinctions between natural and medical images. In this work, we provide a comprehensive overview of recent endeavors aimed at extending the efficacy of SAM to medical image segmentation tasks, encompassing both empirical benchmarking and methodological adaptations. Additionally, we explore potential avenues for future research directions in SAM's role within medical image segmentation. While direct application of SAM to medical image segmentation does not yield satisfactory performance on multi-modal and multi-target medical datasets so far, numerous insights gleaned from these efforts serve as valuable guidance for shaping the trajectory of foundational models in the realm of medical image analysis. To support ongoing research endeavors, we maintain an active repository that contains an up-to-date paper list and a succinct summary of open-source projects at https://github.com/YichiZhang98/SAM4MIS.

Cooperation of Different Active Sites to Promote CO2 Electroreduction to Multi-carbon Products at Ampere-Level.

Electroreduction of CO2 to C2+ products provides a promising strategy for reaching the goal of carbon neutrality. However, achieving high selectivity of C2+ products at high current density remains a challenge. In this work, we designed and prepared a multi-sites catalyst, in which Pd was atomically dispersed in Cu (Pd-Cu). It was found that the Pd-Cu catalyst had excellent performance for producing C2+ products from CO2 electroreduction. The Faradaic efficiency (FE) of C2+ products could be maintained at approximately 80.8 %, even at a high current density of 0.8 A cm-2 for at least 20 hours. In addition, the FE of C2+ products was above 70 % at 1.4 A cm-2. Experiments and density functional theory (DFT) calculations revealed that the catalyst had three distinct catalytic sites. These three active sites allowed for efficient conversion of CO2, water dissociation, and CO conversion, ultimately leading to high yields of C2+ products.

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer.

Background: Ovarian cancer (OC) has the highest mortality rate among gynecological malignancies. Current treatment options are limited and ineffective, prompting the discovery of reliable biomarkers. Exosome lncRNAs, carrying genetic information, are promising new markers. Previous studies only focused on exosome-related genes and employed the Lasso algorithm to construct prediction models, which are not robust. Methods: 420 OC patients from the TCGA datasets were divided into training and validation datasets. The GSE102037 dataset was used for external validation. LncRNAs associated with exosome-related genes were selected using Pearson analysis. Univariate COX regression analysis was used to filter prognosis-related lncRNAs. The overlapping lncRNAs were identified as candidate lncRNAs for machine learning. Based on 10 machine learning algorithms and 117 algorithm combinations, the optimal predictor combinations were selected according to the C index. The exosome-related LncRNA Signature (ERLS) model was constructed using multivariate COX regression. Based on the median risk score of the training datasets, the patients were divided into high- and low-risk groups. Kaplan-Meier survival analysis, the time-dependent ROC, immune cell infiltration, immunotherapy response, and immune checkpoints were analyzed. Results: 64 lncRNAs were subjected to a machine-learning process. Based on the stepCox (forward) combined Ridge algorithm, 20 lncRNA were selected to construct the ERLS model. Kaplan-Meier survival analysis showed that the high-risk group had a lower survival rate. The area under the curve (AUC) in predicting OS at 1, 3, and 5 years were 0.758, 0.816, and 0.827 in the entire TCGA cohort. xCell and ssGSEA analysis showed that the low-risk group had higher immune cell infiltration, which may contribute to the activation of cytolytic activity, inflammation promotion, and T-cell co-stimulation pathways. The low-risk group had higher expression levels of PDL1, CTLA4, and higher TMB. The ERLS model can predict response to anti-PD1 and anti-CTLA4 therapy. Patients with low expression of PDL1 or high expression of CTLA4 and low ERLS exhibited significantly better survival prospects, whereas patients with high ERLS and low levels of PDL1 or CTLA4 exhibited the poorest outcomes. Conclusion: Our study constructed an ERLS model that can predict prognostic risk and immunotherapy response, optimizing clinical management for OC patients.

Evaluating two small-sample corrections for fixed-effects standard errors and inferences in multilevel models with heteroscedastic, unbalanced, clustered data.

Multilevel modeling (MLM) is commonly used in psychological research to model clustered data. However, data in applied research usually violate one of the essential assumptions of MLM-homogeneity of variance. While the fixed-effect estimates produced by the maximum likelihood method remain unbiased, the standard errors for the fixed effects are misestimated, resulting in inaccurate inferences and inflated or deflated type I error rates. To correct the bias in fixed effects standard errors and provide valid inferences, small-sample corrections such as the Kenward-Roger (KR) adjustment and the adjusted cluster-robust standard errors (CR-SEs) with the Satterthwaite approximation for t tests have been used. The current study compares KR with random slope (RS) models and the adjusted CR-SEs with ordinary least squares (OLS), random intercept (RI) and RS models to analyze small, heteroscedastic, clustered data using a Monte Carlo simulation. Results show the KR procedure with RS models has large biases and inflated type I error rates for between-cluster effects in the presence of level 2 heteroscedasticity. In contrast, the adjusted CR-SEs generally yield results with acceptable biases and maintain type I error rates close to the nominal level for all examined models. Thus, when the interest is only in within-cluster effect, any model with the adjusted CR-SEs could be used. However, when the interest is to make accurate inferences of the between-cluster effect, researchers should use the adjusted CR-SEs with RS to have higher power and guard against unmodeled heterogeneity. We reanalyzed an example in Snijders & Bosker (2012) to demonstrate the use of the adjusted CR-SEs with different models.

Correcting for Sampling Error in between-Cluster Effects: An Empirical Bayes Cluster-Mean Approach with Finite Population Corrections.

With clustered data, such as where students are nested within schools or employees are nested within organizations, it is often of interest to estimate and compare associations among variables separately for each level. While researchers routinely estimate between-cluster effects using the sample cluster means of a predictor, previous research has shown that such practice leads to biased estimates of coefficients at the between level, and recent research has recommended the use of latent cluster means with the multilevel structural equation modeling framework. However, the latent cluster mean approach may not always be the best choice as it (a) relies on the assumption that the population cluster sizes are close to infinite, (b) requires a relatively large number of clusters, and (c) is currently only implemented in specialized software such as Mplus. In this paper, we show how using empirical Bayes estimates of the cluster means can also lead to consistent estimates of between-level coefficients, and illustrate how the empirical Bayes estimate can incorporate finite population corrections when information on population cluster sizes is available. Through a series of Monte Carlo simulation studies, we show that the empirical Bayes cluster-mean approach performs similarly to the latent cluster mean approach for estimating the between-cluster coefficients in most conditions when the infinite-population assumption holds, and applying the finite population correction provides reasonable point and interval estimates when the population is finite. The performance of EBM can be further improved with restricted maximum likelihood estimation and likelihood-based confidence intervals. We also provide an R function that implements the empirical Bayes cluster-mean approach, and illustrate it using data from the classic High School and Beyond Study.