Bio-Inspired Organic Synaptor with In Situ Ion-Doped Ultrathin Polyelectrolyte Containing Acetylcholine-Like Cation.

An ion-based synaptic transistor (synaptor) is designed to emulate a biological synapse using controlled ion movements. However, developing a solid-state electrolyte that can facilitate ion movement while achieving large-scale integration remains challenging. Here, a bio-inspired organic synaptor (BioSyn) with an in situ ion-doped polyelectrolyte (i-IDOPE) is demonstrated. At the molecular scale, a polyelectrolyte containing the tert-amine cation, inspired by the neurotransmitter acetylcholine is synthesized using initiated chemical vapor deposition (iCVD) with in situ doping, a one-step vapor-phase deposition used to fabricate solid-state electrolytes. This method results in an ultrathin, but highly uniform and conformal solid-state electrolyte layer compatible with large-scale integration, a form that is not previously attainable. At a synapse scale, synapse functionality is replicated, including short-term and long-term synaptic plasticity (STSP and LTSP), along with a transformation from STSP to LTSP regulated by pre-synaptic voltage spikes. On a system scale, a reflex in a peripheral nervous system is mimicked by mounting the BioSyns on various substrates such as rigid glass, flexible polyethylene naphthalate, and stretchable poly(styrene-ethylene-butylene-styrene) for a decentralized processing unit. Finally, a classification accuracy of 90.6% is achieved through semi-empirical simulations of MNIST pattern recognition, incorporating the measured LTSP characteristics from the BioSyns.

Association between longitudinal patterns of child maltreatment experiences and adolescent substance use.

BACKGROUND: Although there is a well-established link between child maltreatment and adolescent substance use, it remains unclear if and how longitudinal patterns of maltreatment experiences are associated with substance use in adolescence. OBJECTIVE: The purpose of the study was to examine how distinct patterns of longitudinal maltreatment experiences are associated with adolescent substance use. PARTICIPANTS AND SETTING: The participants were 899 adolescents from the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN). METHODS: We conducted repeated measures latent class analysis (RMLCA) to identify patterns of physical abuse, sexual abuse, and neglect from birth to age 17 and their relations to tobacco, alcohol, and marijuana use at age 18. RESULTS: RMLCA identified three physical abuse classes (Stable low physical abuse; School age peak physical abuse; Physical abuse primarily in infancy/toddlerhood), two sexual abuse classes (Stable no/low sexual abuse; School age peak sexual abuse), and three neglect classes (High neglect in childhood; Neglect primarily in infancy/toddlerhood; Neglect primarily at school age). Adolescents in the school age peak physical abuse class showed greater alcohol, cigarette, and marijuana use, compared to other physical abuse classes. Similarly, adolescents in the school age peak sexual abuse class showed greater substance use than those in the stable no/low sexual abuse class. Lastly, adolescents in the neglect primarily in infancy/toddlerhood class showed significantly less substance use than those in the other two neglect classes. CONCLUSIONS: Findings highlight the importance of early intervention and ongoing maltreatment prevention.

Can resilience change over time? Patterns and transitions in resilience among young children involved with the child welfare system.

This study examined transitions in resilience profiles and the role of caregiver risk and protective factors in resilience transition probabilities over 18 months among children involved with the child welfare system, using latent profile analysis and latent transition analysis. The sample included 486 children (48% female, baseline Mage = 3.49). There were three resilience profiles at Time 1 (19.9% low emotional behavioral, 26.1% low cognitive, 54.0% multidomain) and two profiles at Time 2 (18.9% low emotional behavioral, 81.1% multidomain). Caregiver mental health problems were negatively associated with membership in the multidomain resilience group at Time 1. Higher levels of cognitive stimulation were associated with initial and continued membership in the multidomain resilience group. Implications for resilient child development are discussed.

Coparenting, parental anxiety/depression, and child behavior problems: The actor-partner interdependence model with low-income married couples.

A considerable amount of research has suggested significant associations among perceived coparenting relationships, parental anxiety/depression, and children's adjustment. Although family members' function is influenced by other members in a shared context, much of the prior work relied on one parent's perspective to examine the relationship between both parents. To address this important limitation, we applied the actor-partner interdependence model and accounted for the interdependence between fathers and mothers in examining the mediating role of parental anxiety/depression in the association between coparenting quality and child behavior problems. The present study included 1,827 low-income couples from the Supporting Healthy Marriage project (mothers: 51.25% of White, 14.34% African American, 35.31% Hispanic; fathers: 48.11% White, 18.54% African/Black American, 35.34% Hispanic). The results showed that both fathers' and mothers' perceptions of coparenting quality had significant effects on fathers' anxiety/depression. In contrast, mothers' anxiety/depression was affected only by mothers' perceptions of coparenting quality and not by fathers' perceptions. Overall, the effects of parents' perception of coparenting on children's internalizing and externalizing behavior problems were largely mediated by parental anxiety/depression. The findings highlight both interdependent and independent roles of fathers and mothers in the pathways from coparenting quality to children's behavior problems. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A comparison of the methods for detecting dyadic patterns in the actor-partner interdependence model.

In the actor-partner interdependence model (APIM), various dyadic patterns between an actor and partner can be examined. One widely used approach is the parameter k method, which tests whether the ratio of the partner effect to the actor effect (p/a) is significantly different from pattern values such as -1 (contrast), 0 (actor-only or partner-only), and 1 (couple). Although using a phantom variable was a useful method for estimating the k ratio, it is no longer necessary due to the availability of statistical packages that allow for a direct estimation of the k ratio without the inclusion of the phantom variable. Moreover, it is possible to examine the patterns by testing new variables defined in different forms from the k or using the χ2 difference test. To date, no previous studies have evaluated and compared the various approaches for detecting the dyadic patterns in APIM. This study aims to assess and compare the performance of four different methods for detecting dyadic patterns: (1) phantom variable approach, (2) direct estimation of the parameter k, (3) new-variable approach, and (4) χ2 difference test. The first two methods frequently included multiple pattern values in there confidence interval. Furthermore, the phantom variable approach was prone to convergence issues. The other two alternatives performed better in detecting the dyadic patterns without convergence problems. Given the findings of the study, we suggest a novel procedure for examining dyadic patterns in APIM.

Label-free detection and discrimination of respiratory pathogens based on electrochemical synthesis of biomaterials-mediated plasmonic composites and machine learning analysis.

Seasonal outbreaks of respiratory viral infections remain a global concern, with increasing morbidity and mortality rates recorded annually. Timely and false responses contribute to the widespread of respiratory pathogenic diseases owing to similar symptoms at an early stage and subclinical infection. The prevention of emerging novel viruses and variants is also a big challenge. Reliable point-of-care diagnostic assays for early infection diagnosis play a critical role in the response to threats of epidemics or pandemics. We developed a facile method for specifically identifying different viruses based on surface-enhanced Raman spectroscopy (SERS) with pathogen-mediated composite materials on Au nanodimple electrodes and machine learning (ML) analyses. Virus particles were trapped in three-dimensional plasmonic concave spaces of the electrode via electrokinetic preconcentration, and Au films were simultaneously electrodeposited, leading to the acquisition of intense and in-situ SERS signals from the Au-virus composites for ultrasensitive SERS detection. The method was useful for rapid detection analysis (<15 min), and the ML analysis for specific identification of eight virus species, including human influenza A viruses (i.e., H1N1 and H3N2 strains), human rhinovirus, and human coronavirus, was conducted. The highly accurate classification was achieved using the principal component analysis-support vector machine (98.9%) and convolutional neural network (93.5%) models. This ML-associated SERS technique demonstrated high feasibility for direct multiplex detection of different virus species for on-site applications.

Dual-Enhanced Plasmonic Biosensing for Point-of-Care Sepsis Detection.

Rapid, sensitive, simultaneous quantification of multiple biomarkers in point-of-care (POC) settings could improve the diagnosis and management of sepsis, a common, potentially life-threatening condition. Compared to high-end commercial analytical systems, POC systems are often limited by low sensitivity, limited multiplexing capability, or low throughput. Here, we report an ultrasensitive, multiplexed plasmonic sensing technology integrating chemifluorescence signal enhancement with plasmon-enhanced fluorescence detection. Using a portable imaging system, the dual chemical and plasmonic amplification enabled rapid analysis of multiple cytokine biomarkers in 1 h with sub-pg/mL sensitivities. Furthermore, we also developed a plasmonic sensing chip based on nanoparticle-spiked gold nanodimple structures fabricated by wafer-scale batch processes. We used the system to detect six cytokines directly from clinical plasma samples (n = 20) and showed 100% accuracy for sepsis detection. The described technology could be employed in rapid, ultrasensitive, multiplexed plasmonic sensing in POC settings for myriad clinical conditions.

Patterns of coparenting and young children's social-emotional adjustment in low-income families.

This study identified coparenting patterns using data collected across 2007-2010 from low-income couples (N = 2915; 26.90% non-Hispanic White; 9.41% non-Hispanic Black; 34.24% Hispanic, 29.27% other or mixed race) with young children (M = 3.65 years; SD = 1.31 years; 48% girls) and examined relations with children's social-emotional adjustment. Latent profile analysis revealed four coparenting patterns: mutual high-quality (43.4%), moderate-quality, mothers less positive (31.8%), moderate-quality, fathers less positive (15.9%), and low-quality, mothers less positive (8.9%). When parents' perspectives on coparenting were positive and congruent, children fared best. Children also fared well when coparenting quality was moderate, and mothers were less positive than fathers. When coparenting quality was moderate and fathers were less positive than mothers, children showed the poorest adjustment.

In-situ fabrication of 3D interior hotspots templated with a protein@Au core-shell structure for label-free and on-site SERS detection of viral diseases.

Nanoscale plasmonic hotspots play a critical role in the enhancement of molecular Raman signals, enabling the sensitive and reliable trace analysis of biomedical molecules via surface-enhanced Raman spectroscopy (SERS). However, effective and label-free SERS diagnoses in practical fields remain challenging because of clinical samples' random adsorption and size mismatch with the nanoscale hotspots. Herein, we suggest a novel SERS strategy for interior hotspots templated with protein@Au core-shell nanostructures prepared via electrochemical one-pot Au deposition. The cytochrome c and lysates of SARS-CoV-2 (SLs) embedded in the interior hotspots were successfully functionalized to confine the electric fields and generate their optical fingerprint signals, respectively. Highly linear quantitative sensitivity was observed with the limit-of-detection value of 10-1 PFU/mL. The feasibility of detecting the targets in a bodily fluidic environment was also confirmed using the proposed templates with SLs in human saliva and nasopharyngeal swabs. These interior hotspots templated with the target analytes are highly desirable for early and on-site SERS diagnoses of infectious diseases without any labeling processes.

Organometallic hotspot engineering for ultrasensitive EC-SERS detection of pathogenic bacteria-derived DNAs.

The sensitivity and limit-of-detection (LOD) of the traditional surface-enhanced Raman spectroscopy (SERS) platform suffer from the requirement of precise positioning of small analytes, including DNAs and bacteria, into narrow hotspots. In this study, a novel SERS sensor was developed using electrochemical deposition onto metal nanopillars (ECOMPs) combined with complementary DNAs (cDNAs) for the detection of pathogenic bacteria. Applying a redox potential to AuCl4- ions actively engineered the organometallic hotspots based on the cDNAs in a short time (<10 min) and simultaneously produced SERS signals. Because of the influence of potential-driven morphological properties on the SERS efficiency in the cDNA domains and the resonant coupling of internal fields with the fields confined between adjacent ECOMPs-cDNAs, the optimum growth time was determined to be 5 min. The EC-SERS detection and discrimination of Enterococcus faecium and Staphylococcus aureus were successfully carried out because of the DNA complementarity. Compared with plasmonic metal nanopillars (MPs)-cDNAs, the enhancement factor of the ECOMPs-cDNAs was estimated to be ∼2.0 × 103. A quantitative investigation revealed that a highly linear progression in the target DNA concentration range (0.05-100 nM) and a LOD of ∼0.035 nM were achieved. The specificity of the ECOMPs-cDNAs was validated by cross-hybridization. The platform was also used to assay human whole blood containing 0.1 nM bacterial DNAs. The proposed strategy provides the potential for highly sensitive SERS-based multiplex DNA detection in clinical diagnostics.

Hydrogel-Assisted 3D Volumetric Hotspot for Sensitive Detection by Surface-Enhanced Raman Spectroscopy.

Effective hotspot engineering with facile and cost-effective fabrication procedures is critical for the practical application of surface-enhanced Raman spectroscopy (SERS). We propose a SERS substrate composed of a metal film over polyimide nanopillars (MFPNs) with three-dimensional (3D) volumetric hotspots for this purpose. The 3D MFPNs were fabricated through a two-step process of maskless plasma etching and hydrogel encapsulation. The probe molecules dispersed in solution were highly concentrated in the 3D hydrogel networks, which provided a further enhancement of the SERS signals. SERS performance parameters such as the SERS enhancement factor, limit-of-detection, and signal reproducibility were investigated with Cyanine5 (Cy5) acid Raman dye solutions and were compared with those of hydrogel-free MFPNs with two-dimensional hotspots. The hydrogel-coated MFPNs enabled the reliable detection of Cy5 acid, even when the Cy5 concentration was as low as 100 pM. We believe that the 3D volumetric hotspots created by introducing a hydrogel layer onto plasmonic nanostructures demonstrate excellent potential for the sensitive and reproducible detection of toxic and hazardous molecules.

Polyimide Surface Dielectric Barrier Discharge for Inactivation of SARS-CoV-2 Trapped in a Polypropylene Melt-Blown Filter.

Surface dielectric barrier discharge (SDBD) was used to inactivate the infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) trapped in a polypropylene (PP) melt-blown filter. We used a dielectric barrier made of polyimide films with hexagonal holes through which air flowed. In a cylindrical wind tunnel, the SDBD device supplied reactive oxygen species such as ozone to the SARS-CoV-2 trapped in the PP filter. A plaque assay showed that SDBD at an ozone concentration of approximately 51.6 ppm and exposure time of 30 min induced more than 99.78% reduction for filter-adhered SARS-CoV-2. A carbon catalyst after SDBD effectively reduced ozone exhaust below 0.05 ppm. The combination of SDBD, PP filter, and catalyst could be a promising way to decrease the risk of secondary infection due to indoor air purifiers.

Assessing Differential Effects of Somatic Amplification to Positive Affect in Midlife and Late Adulthood-A Regression Mixture Approach.

This study aims to provide an empirical demonstration of a novel method, regression mixture model, by examining differential effects of somatic amplification to positive affect and identifying the predictors that contribute to the differential effects. Data derived from the second wave of Midlife in the United States. The analytic sample consisted of 1,766 adults aged from 33 to 84 years. Regression mixture models were fitted using Mplus 7.4, and a two-step model-building approach was adopted. Three latent groups were identified consisting of a maladaptive (32.1%), a vulnerable (62.5%), and a resilient (5.4%) group. Six covariates (i.e., age, education level, positive relations with others, purpose in life, depressive symptoms, and physical health) significantly predicted the latent class membership in the regression mixture model. The study demonstrated the regression mixture model to be a flexible and efficient statistical tool in assessing individual differences in response to adversity and identifying resilience factors, which contributes to aging research.

Patterns of Father Involvement and Child Development among Families with Low Income.

This study examined patterns of father involvement and their relations with social, behavioral, and cognitive development among low-income children < 5 years. Latent class analysis on data from 2650 fathers (Mage = 29.35 years) in the Supporting Healthy Marriages program revealed four father involvement patterns: (1) High positive involvement (48%); (2) engaged but harsh discipline (42%); (3) low cognitive stimulation (8%); and (4) lower involvement (2%). The low cognitive stimulation pattern was associated with greater father- and mother-reported child behavior problems and lower child socioemotional and cognitive functioning. The engaged but harsh discipline pattern was associated with more father-reported child behavior problems. These findings highlight the need for active engagement of fathers in parenting interventions to promote child development.

Preliminary Validation of a Continuum Model for Dimple Patterns on Polyethylene Naphthalate via Ar Ion Beam Sputtering.

This work reports the self-organization of dimple nanostructures on a polyethylene naphthalate (PEN) surface where an Ar ion beam was irradiated at an ion energy of 600 eV. The peak-to-peak roughness and diameter of dimple nanostructures were 29.1~53.4 nm and 63.4~77.6 nm, respectively. The electron energy loss spectrum at the peaks and troughs of dimples showed similar C=C, C=O, and O=CH bonding statuses. In addition, wide-angle X-ray scattering showed that Ar ion beam irradiation did not induce crystallization of the PEN surface. That meant that the self-organization on the PEN surface could be due to the ion-induced surface instability of the amorphous layer and not due to the partial crystallinity differences of the peaks and valleys. A nonlinear continuum model described surface instability due to Ar ion-induced sputtering. The Kuramoto-Sivashinsky model reproduced the dimple morphologies numerically, which was similar to the experimentally observed dimple patterns. This preliminary validation showed the possibility that the continuum equation used for metal and semiconductor surfaces could be applied to polymer surfaces where ion beam sputtering occurred.

A Comparison of Different Nonnormal Distributions in Growth Mixture Models.

The purpose of the present study is to compare nonnormal distributions (i.e., t, skew-normal, skew-t with equal skew and skew-t with unequal skew) in growth mixture models (GMMs) based on diverse conditions of a number of time points, sample sizes, and skewness for intercepts. To carry out this research, two simulation studies were conducted with two different models: an unconditional GMM and a GMM with a continuous distal outcome variable. For the simulation, data were generated under the conditions of a different number of time points (4, 8), sample size (300, 800, 1,500), and skewness for intercept (1.2, 2, 4). Results demonstrate that it is not appropriate to fit nonnormal data to normal, t, or skew-normal distributions other than the skew-t distribution. It was also found that if there is skewness over time, it is necessary to model skewness in the slope as well.