The Complexity of Borderline Personality Disorder: Network Analysis of Personality Factors and Defense Styles in the Context of Borderline Personality Organization.

OBJECTIVE: Borderline personality disorder (BPD) is known to share characteristics with a variety of personality disorders (PDs) and exhibits diverse patterns of defense mechanisms. To enhance our understanding of BPD, it's crucial to shift our focus from traditional categorical diagnostics to the dimensional traits shared with other PDs, as the borderline personality organization (BPO) model suggests. This approach illuminates the nuanced spectrum of BPD characteristics, offering deeper insights into its complexity. While studies have investigated the comorbidity of BPD with other PDs, research exploring the relationship between various personality factors and defense mechanisms within BPD itself has been scarce. The present study was undertaken to investigate the complex interrelationships between various personality factors and defense styles in individuals diagnosed with BPD. METHODS: Using a network analysis approach, data from 227 patients diagnosed with BPD were examined using the Defense Style Questionnaire and Personality Disorder Questionnaire-4+ for assessment. RESULTS: Intricate connections were observed between personality factors and defense styles. Significant associations were identified between various personality factors and defense styles, with immature defense styles, such as maladaptive and image-distorting being particularly prominent in BPD in the centrality analysis. The maladaptive defense style had the highest expected influence centrality. Furthermore, the schizotypal, dependent, and narcissistic personality factors demonstrated relatively high centrality within the network. CONCLUSION: Network analysis can effectively delineate the complexity of various PDs and defense styles. These findings are expected to facilitate a deeper understanding of why BPD exhibits various levels of organization and presents with heterogeneous characteristics, consistent with the perspectives proposed by the BPO.

The characteristics of elderly suicidal attempters in the emergency department in Korea: a retrospective study.

BACKGROUND: Although Korea ranks first in the suicide rate of elderly individuals, there is limited research on those who attempt suicide, with preventive measures largely based on population-based studies. We compared the demographic and clinical characteristics of elderly individuals who attempted suicide with those of younger adults who visited the emergency department after suicide attempts and identified the factors associated with lethality in the former group. METHODS: Individuals who visited the emergency department after a suicide attempt from April 1, 2017, to January 31, 2020, were included. Participants were classified into two groups according to age (elderly, ≥65 years; adult, 18-64 years). Among the 779 adult patients, 123 were elderly. We conducted a chi-square test to compare the demographic and clinical features between these groups and a logistic regression analysis to identify the risk factors for lethality in the elderly group. RESULTS: Most elderly participants were men, with no prior psychiatric history or suicide attempts, and had a higher prevalence of underlying medical conditions and attributed their attempts to physical illnesses. Being sober and planning suicide occurred more frequently in this group. In the elderly group, factors that increased the mortality rate were biological male sex (p<0.05), being accompanied by family members (p<0.05), and poisoning as a suicide method (p<0.01). CONCLUSION: Suicide attempts in elderly individuals have different characteristics from those in younger adults and are associated with physical illness. Suicides in the former group are unpredictable, deliberate, and fatal. Therefore, tailored prevention and intervention strategies addressing the characteristics of those who are elderly and attempt suicide are required.

Bidirectional connectivity alterations in schizophrenia: a multivariate, machine-learning approach.

Objective: It is well known that altered functional connectivity is a robust neuroimaging marker of schizophrenia. However, there is inconsistency in the direction of alterations, i.e., increased or decreased connectivity. In this study, we aimed to determine the direction of the connectivity alteration associated with schizophrenia using a multivariate, data-driven approach. Methods: Resting-state functional magnetic resonance imaging data were acquired from 109 individuals with schizophrenia and 120 controls across two openly available datasets. A whole-brain resting-state functional connectivity (rsFC) matrix was computed for each individual. A modified connectome-based predictive model (CPM) with a support vector machine (SVM) was used to classify patients and controls. We conducted a series of multivariate classification analyses using three different feature sets, increased, decreased, and both increased and decreased rsFC. Results: For both datasets, combining information from both increased and decreased rsFC substantially improved prediction accuracy (Dataset 1: accuracy = 70.2%, permutation p = 0.001; Dataset 2: accuracy = 64.4%, permutation p = 0.003). When tested across datasets, the prediction model using decreased rsFC performed best. The identified predictive features of decreased rsFC were distributed mostly in the motor network for both datasets. Conclusion: These findings suggest that bidirectional alterations in rsFC are distributed in schizophrenia patients, with the pattern of decreased rsFC being more similar across different populations.

Fine-Grained Motion Recognition in At-Home Fitness Monitoring with Smartwatch: A Comparative Analysis of Explainable Deep Neural Networks.

The squat is a multi-joint exercise widely used for everyday at-home fitness. Focusing on the fine-grained classification of squat motions, we propose a smartwatch-based wearable system that can recognize subtle motion differences. For data collection, 52 participants were asked to perform one correct squat and five incorrect squats with three different arm postures (straight arm, crossed arm, and hands on waist). We utilized deep neural network-based models and adopted a conventional machine learning method (random forest) as a baseline. Experimental results revealed that the bidirectional GRU/LSTMs with an attention mechanism and the arm posture of hands on waist achieved the best test accuracy (F1-score) of 0.854 (0.856). High-dimensional embeddings in the latent space learned by attention-based models exhibit more clustered distributions than those by other DNN models, indicating that attention-based models learned features from the complex multivariate time-series motion signals more efficiently. To understand the underlying decision-making process of the machine-learning system, we analyzed the result of attention-based RNN models. The bidirectional GRU/LSTMs show a consistent pattern of attention for defined squat classes, but these models weigh the attention to the different kinematic events of the squat motion (e.g., descending and ascending). However, there was no significant difference found in classification performance.

Neurophysiological insights into impaired mentalization in borderline personality disorder an electroencephalography study.

Introduction: Borderline personality disorder (BPD) is characterized by interpersonal and emotional instabilities, recurring suicidal tendencies, and feelings of emptiness. Childhood adverse event is reported in 70%-80% of cases involving BPD. Furthermore, the deficiency in mentalization capacity plays a significant role in emotion dysregulation and social interaction problems within individuals with BPD. This study explored the relationship among childhood adverse experiences, mentalization capacity, and neurophysiological activity in patients with BPD. Methods: Resting-state electroencephalography was used to identify the neural correlates associated with childhood adversity and mentalization deficits. The participants included 45 patients with BPD and 15 healthy controls. Results: The BPD group exhibited reduced alpha activity during eyes-closed rest, indicating heightened arousal even during relaxation. Correlations were found between the power spectral density (PSD) and mentalization capacity in the delta and theta ranges, suggesting an association between PSD and emotional awareness and expression. Gamma activity negatively correlated with psychic equivalence, implying a blurring of the boundaries between internal mental experiences and the external world. Conclusion: These findings offer insights into the pathophysiology of BPD, provide potential diagnostic markers, and suggest personalized treatment approaches based on mentalization traits.

Understanding insomnia as systemic disease.

Sleep plays a critical role in homeostasis of the body and mind. Insomnia is a disease that causes disturbances in the initiation and maintenance of sleep. Insomnia is known to affect not only the sleep process itself but also an individual's cognitive function and emotional regulation during the daytime. It increases the risk of various neuropsychiatric diseases such as depression, anxiety disorder, and dementia. Although it might appear that insomnia only affects the nervous system, it is also a systemic disease that affects several aspects of the body, such as the cardiovascular, endocrine, and immune systems; therefore, it increases the risk of various diseases such as hypertension, diabetes mellitus, and infection. Insomnia has a wide range of effects on our bodies because sleep is a complex and active process. However, a high proportion of patients with insomnia do not seek treatment, which results in high direct and indirect costs. This is attributed to the disregard of many of the negative effects of insomnia. Therefore, we expect that understanding insomnia as a systemic disease will provide an opportunity to understand the condition better and help prevent secondary impairment due to insomnia.

Aberrant EEG signal variability at a specific temporal scale in major depressive disorder.

OBJECTIVE: Signal variability is linked to irregularities in time series caused by intrinsic nonlinearities of the neural system and can be measured on variable temporal scales over short time series. By measuring refined complex multiscale permutation entropy (RCMPE) from resting-state electroencephalography (EEG) data, we investigated the presence of a specific range of time scales characterizing major depressive disorder (MDD). METHOD: We used an EEG dataset acquired from 22 MDD patients and 22 healthy controls in the eyes-closed (EC) and eyes-open (EO) states available on the PRED + CT website. Signal variability in both the EC and EO states was compared between the two groups, and their relationship to depressive symptom severity was examined. RESULTS: In the EC state, the RCMPE was higher in the MDD group than in the control group on a coarse temporal scale, approximately 20-32 ms, at almost all sensors. It also showed a negative correlation with depressive symptom severity on a fine temporal scale, approximately 2-26 ms, in the frontal, right temporal, and left parietal sensor areas in MDD. The EO state revealed a group difference but no relationship with depressive symptom severity. CONCLUSION: Our results suggested that the diagnosis of MDD as a trait and the severity of depressive symptoms as a state are linked to EEG signal variability on the coarse temporal scale and the fine scale in the resting state, respectively. SIGNIFICANCE: Signal variability reflects different characteristics of depression depending on the temporal scale.

Psychiatric understanding and treatment of patients with amputations.

Amputation changes the lives of patients and their families. Consequently, the patient must adapt to altered body function and image. During this adaptation process, psychological problems, such as depression, anxiety, and posttraumatic stress disorder, can occur. The psychological difficulties of patients with amputation are often accepted as normal responses that are often poorly recognized by patients, family members, and their primary physicians. Psychological problems can interfere with rehabilitation and cause additional psychosocial problems. Therefore, their early detection and treatment are important. A multidisciplinary team approach, including mental health professionals, is ideal for comprehensive and biopsychosocial management. Mental health professionals could help patients set realistic goals and use adaptive coping styles. Psychiatric approaches should consider the physical, cognitive, psychological, social, and spiritual functions and social support systems before and after amputation. The abilities and limitations of physical, cognitive, psychological, and social functions should also be considered. To improve the patient's adaptation, psychological interventions such as short-term psychotherapy, cognitive behavioral therapy, mindfulness meditation, biofeedback, and group psychotherapy can be helpful.

The psychological impact of the coronavirus disease pandemic on hospital workers in Daegu, South Korea.

OBJECTIVE: This study aimed to assess the immediate stress and psychological impact experienced by healthcare workers and other personnel during the Coronavirus disease (COVID-19) pandemic. METHOD: The sample consisted of 2554 hospital workers (i.e., physicians, nurses, allied health professionals, and auxiliary staff members) who were working in Yeungnam University Hospital in Daegu, South Korea. The Impact of Event Scale-Revised (IES-R) was administered to the hospital workers twice over a 2 week interval. A high-risk group, identified on the basic of first total IES-R, was assessed further with the Mini International Neuropsychiatric Interview (MINI) and the Clinical Global Impressions-Severity (CGIS) scale and was offered periodic psychiatric consultations on a telephone. RESULTS: The participating nurses and auxiliary staff members had significantly higher IES-R scores (p < 0.01) than the physicians. During the second evaluation, the IES-R scores of the high-risk participants had decreased by 13.67 ± 16.15 points (p < 0.01), and their CGI-S scores had decreased by 1.00 ± 0.74 points (p < 0.01). The psychological symptoms of the high-risk group who received telephone-based psychiatric consultation showed improvement after 2 weeks. CONCLUSIONS: The present findings suggest that hospital workers experience high levels of emotional stress during a pandemic. In particular, the present findings underscore the need to provide more information and support to nurses and other administrative workers. There is a need for greater awareness about the importance of mental health care among hospital workers, and rapid and ongoing psychiatric interventions should be provided to workers during the pandemic period.

Characteristics of Individuals Who Converted to Dementia during a 5-Year Follow-Up.

INTRODUCTION: Early diagnosis of dementia is important; however, the diagnostic criteria for the preclinical stage of dementia, including biomarkers and pathophysiological markers, are not suitable for application in patients in real-world clinical settings. One potential noninvasive method to predict the risk of dementia conversion is the neuropsychological test. Therefore, in this study, we examined the results of various assessments, such as comprehensive neuropsychological tests, and the daily function of participants who were evaluated periodically for 5 years. METHODS: All participants were outpatients or inpatients with subjective cognitive complaints, who visited a local university hospital for neuropsychiatric evaluation, between January 2011 and January 2019. Of a total of 1,652 subjects who underwent initial screening during this period, 107 were nondemented individuals. These participants underwent periodic comprehensive cognitive tests for up to 5 years. Survival and factors affecting dementia conversion were analyzed using the time-dependent Cox regression analysis. Assessment items included demographic information, including age, sex, and education; 5 cognitive domains of a comprehensive neuropsychological test including memory, language, attention, visuospatial functions, and frontal (executive) function; Barthel's activities of daily living; the mini-mental state examination findings; and clinical dementia rating (CDR) scores. RESULTS: This study included 61 participants (21 women and 40 men) who developed dementia during the study period. Verification of the cognitive variables affecting dementia conversion revealed that better memory was associated with a lower risk of conversion (hazard ratio [HR] = 0.614, p = 0.005) and higher attention was associated with a higher risk of conversion (HR = 1.602, p = 0.023). In the analysis of the subscales of the CDR, a higher community affairs score (i.e., less social activities) was associated with a higher risk of conversion (HR = 10.814, p = 0.028). CONCLUSION: Individuals with prominent memory decline or problems with social activities should be carefully observed for dementia conversion. Cognitive intervention techniques for cognitive stimulation, such as social and leisure activities, as well as cognitive training need to be actively used for patients in whom dementia is a concern.

Self-Organized Freestanding One-Dimensional Au Nanoparticle Arrays.

One-dimensional Au nanoparticle arrays encapsulated within freestanding SiO2 nanowires are fabricated by thermal oxidation of Au-coated Si nanowires with controlled diameter and surface modulation. The nanoparticle diameter is determined by the Si nanowire diameter and Au film thickness, while the interparticle spacing is independently controlled by the Si nanowire modulation. The optical absorption of randomly oriented Au nanoparticle arrays exhibits a strong plasmonic response at 550 nm. Scanning transmission electron microscopy (STEM)-electron energy loss spectrum (EELS) of nanoparticle arrays confirmed the same plasmonic response and demonstrated uniform optical properties of the Au nanoparticles. The plasmonic response in the STEM-EELS maps is primarily confined around the vicinity of the nanoparticles. On the other hand, examination of the same nanowires by energy-filtered transmission electron microscopy also revealed significant enhancement in the plasmonic excitation in the regions in between the nanoparticles. This versatile route to synthesize one-dimensional Au nanoparticle arrays with independently tailorable nanoparticle diameter and interparticle spacing opens up opportunities to exploit enhanced design flexibility and cost-effectiveness for future plasmonic devices.

Broadband and wide field-of-view plasmonic metasurface-enabled waveplates.

Quasi two-dimensional metasurfaces composed of subwavelength nanoresonator arrays can dramatically alter the properties of light in an ultra-thin planar geometry, enabling new optical functions such as anomalous reflection and refraction, polarization filtering, and wavefront modulation. However, previous metasurface-based nanostructures suffer from low efficiency, narrow bandwidth and/or limited field-of-view due to their operation near the plasmonic resonance. Here we demonstrate plasmonic metasurface-based nanostructures for high-efficiency, angle-insensitive polarization transformation over a broad octave-spanning bandwidth. The structures are realized by optimizing the anisotropic response of an array of strongly coupled nanorod resonators to tailor the interference of light at the subwavelength scale. Nanofabricated reflective half-wave and quarter-wave plates designed using this approach have measured polarization conversion ratios and reflection magnitudes greater than 92% over a broad wavelength range from 640 to 1290 nm and a wide field-of-view up to ± 40°. This work outlines a versatile strategy to create metasurface-based photonics with diverse optical functionalities.

Near-ideal optical metamaterial absorbers with super-octave bandwidth.

Nanostructured optical coatings with tailored spectral absorption properties are of interest for a wide range of applications such as spectroscopy, emissivity control, and solar energy harvesting. Optical metamaterial absorbers have been demonstrated with a variety of customized single band, multiple band, polarization, and angular configurations. However, metamaterials that provide near unity absorptivity with super-octave bandwidth over a specified optical wavelength range have not yet been demonstrated experimentally. Here, we show a broadband, polarization-insensitive metamaterial with greater than 98% measured average absorptivity that is maintained over a wide ± 45° field-of-view for mid-infrared wavelengths between 1.77 and 4.81 µm. The nearly ideal absorption is realized by using a genetic algorithm to identify the geometry of a single-layer metal nanostructure array that excites multiple overlapping electric resonances with high optical loss across greater than an octave bandwidth. The response is optimized by substituting palladium for gold to increase the infrared metallic loss and by introducing a dielectric superstrate to suppress reflection over the entire band. This demonstration advances the state-of-the-art in high-performance broadband metamaterial absorbers that can be reliably fabricated using a single patterned layer of metal nanostructures.

Tailoring dispersion for broadband low-loss optical metamaterials using deep-subwavelength Inclusions.

Metamaterials have the potential to create optical devices with new and diverse functionalities based on novel wave phenomena. Most practical optical systems require that the device properties be tightly controlled over a broad wavelength range. However, optical metamaterials are inherently dispersive, which limits operational bandwidths and leads to high absorption losses. Here, we show that deep-subwavelength inclusions can controllably tailor the dispersive properties of an established metamaterial structure thereby producing a broadband low-loss optical device with a desired response. We experimentally verify this by optimizing an array of nano-notch inclusions, which perturb the mode patterns and strength of the primary and secondary fishnet nanostructure resonances and give an optically thin mid-wave-infrared filter with a broad transmissive pass-band and near-constant group delay. This work outlines a powerful new strategy for realizing a wide range of broadband optical devices that exploit the unique properties of metamaterials.

Low-loss impedance-matched optical metamaterials with zero-phase delay.

Metamaterials have dramatically expanded the range of available optical properties, enabling an array of new devices such as superlenses, perfect absorbers, and ultrafast switches. Most research has focused on demonstrating negative- and high-index metamaterials at terahertz and optical wavelengths. However, far less emphasis has been placed on low-loss near-zero-index metamaterials that exhibit unique properties including quasi-infinite phase velocity and infinite wavelength. Here, we experimentally demonstrate a free-standing metallodielectric fishnet nanostructure that has polarization-insensitive, zero-index properties with nearly ideal transmission at 1.55 µm. This goal was achieved by optimizing the metamaterial geometry to allow both its effective permittivity and permeability to approach zero together, which simultaneously produces a zero index and matched impedance to free space. The ability to design and fabricate low-loss, near-zero-index optical metamaterials is essential for new devices such as beam collimators, zero-phase delay lines, and transformation optics lenses.

Conformal dual-band near-perfectly absorbing mid-infrared metamaterial coating.

Metamaterials offer a new approach to create surface coatings with highly customizable electromagnetic absorption from the microwave to the optical regimes. Thus far, efficient metamaterial absorbers have been demonstrated at microwave frequencies, with recent efforts aimed at much shorter terahertz and infrared wavelengths. The present infrared absorbers have been constructed from arrays of nanoscale metal resonators with simple circular or cross-shaped geometries, which provide a single band response. In this paper, we demonstrate a conformal metamaterial absorber with a narrow band, polarization-independent absorptivity of >90% over a wide ±50° angular range centered at mid-infrared wavelengths of 3.3 and 3.9 µm. The highly efficient dual-band metamaterial was realized by using a genetic algorithm to identify an array of H-shaped nanoresonators with an effective electric and magnetic response that maximizes absorption in each wavelength band when patterned on a flexible Kapton and Au thin film substrate stack. This conformal metamaterial absorber maintains its absorption properties when integrated onto curved surfaces of arbitrary materials, making it attractive for advanced coatings that suppress the infrared reflection from the protected surface.

Synthesizing low loss negative index metamaterial stacks for the mid-infrared using genetic algorithms.

Negative index metamaterial designs for the mid-infrared with low absorption and impedance mismatch losses are presented. A robust genetic algorithm is employed to optimize the flexible metamaterial structure for targeted refractive index and impedance values. A new figure of merit is introduced to evaluate the impedance match of the metamaterial to free space. Two designs are presented demonstrating low-loss characteristics for a thin metamaterial with two metal screens and a thick metamaterial stack with five screens. The device performance is analyzed when adding more screens to the structure, revealing that optimizing a thick stack produces a metamaterial with properties approaching those of a bulk material.