Childhood emotional abuse and alcohol use disorders in a national Nepali women sample: The mediating role of borderline personality traits.

While many studies have found an association between childhood emotional abuse and alcohol use disorders (AUD) during adulthood, underlying psychological mechanisms linking the two remain inadequately understood. Drawing on the developmental psychopathology perspective, this study examined the relationship between childhood emotional abuse and AUD during adulthood with a national sample of women in Nepal (N = 1,100, M age = 37.73), focusing on the mediating role of borderline personality traits. Mediation analyses were performed using the Karlson-Holm-Breen (KHB) method and bootstrapping confidence intervals. Results indicated that Nepali women's borderline personality traits significantly mediated the relationship between childhood emotional abuse and AUD. Hence, emotional abuse in childhood increases the risk for AUD during adulthood for Nepali women by increasing the risk of borderline personality traits. Findings underscore the necessity of continued emphasis on developing and implementing early interventions for childhood emotional abuse and therapeutic interventions for borderline personality traits in reducing AUD among vulnerable women in Nepal.

Transitions in patterns of caregiver involvement before and during the COVID-19 pandemic: A latent transition analysis.

This retrospective study investigated transitions in patterns of caregiver involvement before and during COVID-19 and their antecedents and consequences. A total of 504 young children (age: M ± SD = 49.92 ± 4.30 months) and their primary caregivers were recruited from the junior classes of 10 preschools in Zhengzhou City, Henan Province, China. Latent profile analysis identified three profiles characterized by (1) high levels of caregiver involvement (HCI), (2) average levels of caregiver involvement (ACI), and (3) low levels of caregiver involvement (LCI). Latent transition analysis showed that caregivers who belonged to the HCI or LCI latent status before COVID-19 tended to transition to the ACI latent status during COVID-19. Higher levels of caregiver depression contributed to a higher probability of transitioning from the HCI to the ACI latent status, while higher levels of household chaos predicted a higher probability of transitioning from the HCI to the ACI latent status and a lower probability of transitioning from the LCI to the ACI latent status. Finally, the transitions in patterns of caregiver involvement were associated with young children's approaches to learning during the pandemic.

Enhancing intergroup relationship between local and mainland college students in Hong Kong - an intensive contact-based intervention.

This study examined the efficacy of an intensive one-day intergroup contact intervention for two groups under tension: local and mainland Chinese college students in Hong Kong. The differential effects of contact intimacy at cognitive, interpersonal, and emotional levels in fostering changes in knowledge, attitude, and behavior were evaluated. Adopting a two-arm Randomized Controlled Trial (RCT) design, participants (N = 72) were randomly assigned to the intervention group that facilitated progressively higher levels of contact intimacy, or the control group that had limited level of contact intimacy. The results support the short-term intervention efficacy in enhancing outgroup knowledge, attitude, and behavior, with Cohen's d of 0.97, 0.60 and 0.30, respectively. Specifically, cognitive-level intergroup contact enhanced outgroup knowledge only. Adding interpersonal-level intergroup contact further enhanced outgroup attitude. Notably, adding emotional-level intergroup contact enhanced changes in all three domains: knowledge, attitude, and behavior. One-month maintenance effect was found in outgroup knowledge, with Cohen's d increased to 1.33.

A novel role of BK potassium channel activity in preventing the development of kidney fibrosis.

Kidney fibrosis is a common characteristic of chronic kidney disease and while the large conductance voltage and calcium-activated potassium channel (BK) is widely expressed in kidneys, its role in kidney fibrosis is unknown. To evaluate this, we found that BK protein expression was decreased in the fibrotic kidneys. Accompanying this was increased fibrotic marker protein expression of fibronectin, vimentin and α-smooth muscle actin and increased mRNA expressions of fibronectin, α-smooth muscle actin, collagen III and collagen I. These changes occurred in the unilateral ureteral obstruction and folic acid models of fibrosis and were more pronounced in BK knockout than in wild-type mice. Activation of BK activity by chemical NS1619 or BMS191011 channel openers attenuated kidney fibrosis in these two models while protecting kidney function in wild-type mice. BK deficiency up-regulated transforming growth factor-ß (TGF-ß)/transcription factor Smad2/3 signaling in the fibrotic kidney, whereas activation of BK activity inhibited this signaling pathway both in vivo and in vitro. BK channel activation increased the degradation of TGF-ß receptors induced by TGF-ß1 in vivo and in vitro. Furthermore, in cell lines HK-2, NRK49, and NRK-52E, BK channel activation by NS1619 led to increased caveolae formation and facilitated localization of TGF-ß receptors in the microdomains of lipid rafts. Thus, our data demonstrated that BK activation has an anti-fibrotic effect on kidney fibrosis by inhibiting the TGF-ß signaling pathway through accelerating TGF-ß receptor degradation via the caveolae route. Hence, our study provides innovative insight into BK as a potential therapeutic target for the treatment of kidney fibrosis.

Bidirectional relationship between visual perception and mathematics performance in Chinese kindergartners.

In this longitudinal study, 64 kindergartners (mean age at T1 = 4.69 ± 0.33 years; 34 girls) were tested on visual perception skills (T2 and T3) and mathematics performance (T1 to T3) with 6-month intervals between the three testing waves. Cross-lagged path analysis showed a bidirectional relationship between visual perception and mathematics performance from T2 to T3. Specifically, children's visual perception at T2 significantly predicted their mathematics performance at T3 (B = 0.30, SE = 0.14, p = 0.03, ß = 0.19). Children's mathematics performance at T1 accounted for unique variance in visual perception at T2 (B = 0.79, SE = 0.11, p < 0.001, ß = 0.68) and visual perception at T3 (B = 0.27, SE = 0.12, p = 0.02, ß = 0.32). Their mathematics performance at T2 also significantly predicted visual perception at T3 (B = 0.21, SE = 0.10, p = 0.04, ß = 0.28). Totally, they explained 61% of the variance in mathematics performance and 39% of the variance in visual perception at T3. The results highlight the developmental courses as well as the reciprocal facilitations between visual perception and mathematics performance in the kindergarten period.

Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence.

Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest infections suspected to be caused by COVID-19 using chest CT may be of assistance when results from definitive viral testing are delayed. Purpose To develop and validate an artificial intelligence (AI) system to score the likelihood and extent of pulmonary COVID-19 on chest CT scans using the COVID-19 Reporting and Data System (CO-RADS) and CT severity scoring systems. Materials and Methods The CO-RADS AI system consists of three deep-learning algorithms that automatically segment the five pulmonary lobes, assign a CO-RADS score for the suspicion of COVID-19, and assign a CT severity score for the degree of parenchymal involvement per lobe. This study retrospectively included patients who underwent a nonenhanced chest CT examination because of clinical suspicion of COVID-19 at two medical centers. The system was trained, validated, and tested with data from one of the centers. Data from the second center served as an external test set. Diagnostic performance and agreement with scores assigned by eight independent observers were measured using receiver operating characteristic analysis, linearly weighted κ values, and classification accuracy. Results A total of 105 patients (mean age, 62 years ± 16 [standard deviation]; 61 men) and 262 patients (mean age, 64 years ± 16; 154 men) were evaluated in the internal and external test sets, respectively. The system discriminated between patients with COVID-19 and those without COVID-19, with areas under the receiver operating characteristic curve of 0.95 (95% CI: 0.91, 0.98) and 0.88 (95% CI: 0.84, 0.93), for the internal and external test sets, respectively. Agreement with the eight human observers was moderate to substantial, with mean linearly weighted κ values of 0.60 ± 0.01 for CO-RADS scores and 0.54 ± 0.01 for CT severity scores. Conclusion With high diagnostic performance, the CO-RADS AI system correctly identified patients with COVID-19 using chest CT scans and assigned standardized CO-RADS and CT severity scores that demonstrated good agreement with findings from eight independent observers and generalized well to external data. © RSNA, 2020 Supplemental material is available for this article.

Structural correlates of literacy difficulties in the second language: Evidence from Mandarin-speaking children learning English.

Several neuroimaging studies have explored the neural basis of literacy difficulties in the second language (L2). However, it remains unclear whether the associated neural alterations are related to literacy abilities in the first language (L1). Using magnetic resonance imaging, we explore this issue with two experiments in Mandarin-speaking children learning English as second language. In the first experiment, we investigated children with literacy difficulties in L2 and L1 (poor in both, PB) and children with literacy difficulties only in L2 (poor in English, PE). We compared the brain structure in these two groups to a control literacy (CL) group. The results showed that the CL group had significantly less gray matter volume in the left supramarginal gyrus compared to the PB group and moderately less gray matter volume compared to the PE group. In addition, the PB group had significant greater gray matter volume in the left medial fusiform gyrus compared to the PE group and had marginally greater gray matter volume compared to the CL group. In the second experiment, we explored the relationship between the two atypical regions and literacy abilities in the two languages in an independent sample consisting of children with typical literacy. Correlation analyses revealed that the left supramarginal gyrus was significantly associated with literacy performance only in the second language, English, whereas the left medial fusiform gyrus did not correlate with the performances in either L1 or L2. Taken together, these findings suggest that literacy difficulties in an alphabetic L2 are associated with a structural abnormality in the left supramarginal gyrus, a region implicated in phonological processing, which is independent of literacy abilities in the native language.

Non-invasive detection of the early phase of kidney injury by photoacoustic/computed tomography imaging.

The early diagnosis of kidney diseases, which can remarkably impair the quality of life and are costly, has encountered great difficulties. Therefore, the development of methods for early diagnosis has great clinical significance. In this study, we used an emerging technique of photoacoustic (PA) imaging, which has relatively high spatial resolution and good imaging depth. Two kinds of PA gold nanoparticle (GNP)-based bioprobes were developed based on their superior photo detectability, size controllability and biocompatibility. The kidney injury mouse model was developed by unilateral ureteral obstruction for 96 h and the release of obstruction model). Giving 3.5 and 5.5 nm bioprobes by tail vein injection, we found that the 5.5 nm probe could be detected in the bladder in the model group, but not in the control group. These results were confirmed by computed tomography imaging. Furthermore, the model group did not show changes in the blood biochemical indices (BUN and Scr) and histologic examination. The 5.5 nm GNPs were found to be the critical point for early diagnosis of kidney injury. This new method was faster and more sensitive and accurate for the detection of renal injury, compared with conventional methods, and can be used for the development of a PA GNP-based bioprobe for diagnosing renal injury.

Dyslexic Children Show Atypical Cerebellar Activation and Cerebro-Cerebellar Functional Connectivity in Orthographic and Phonological Processing.

Previous neuroimaging studies have found atypical cerebellar activation in individuals with dyslexia in either motor-related tasks or language tasks. However, studies investigating atypical cerebellar activation in individuals with dyslexia have mostly used tasks tapping phonological processing. A question that is yet unanswered is whether the cerebellum in individuals with dyslexia functions properly during orthographic processing of words, as growing evidence shows that the cerebellum is also involved in visual and spatial processing. Here, we investigated cerebellar activation and cerebro-cerebellar functional connectivity during word processing in dyslexic readers and typically developing readers using tasks that tap orthographic and phonological codes. In children with dyslexia, we observed an abnormally higher engagement of the bilateral cerebellum for the orthographic task, which was negatively correlated with literacy measures. The greater the reading impairment was for young dyslexic readers, the stronger the cerebellar activation was. This suggests a compensatory role of the cerebellum in reading for children with dyslexia. In addition, a tendency for higher cerebellar activation in dyslexic readers was found in the phonological task. Moreover, the functional connectivity was stronger for dyslexic readers relative to typically developing readers between the lobule VI of the right cerebellum and the left fusiform gyrus during the orthographic task and between the lobule VI of the left cerebellum and the left supramarginal gyrus during the phonological task. This pattern of results suggests that the cerebellum compensates for reading impairment through the connections with specific brain regions responsible for the ongoing reading task. These findings enhance our understanding of the cerebellum's involvement in reading and reading impairment.

Design, synthesis and evaluation of acridine derivatives as multi-target Src and MEK kinase inhibitors for anti-tumor treatment.

Clinical studies have shown enhanced anticancer effects of combined inhibition of Src and MEK kinases. Development of multi-target drugs against Src and MEK is of potential therapeutic advantage against cancers. As a follow-up of our previous studies, and by using molecular docking method, we designed and synthesized a new series of 9-anilinoacridines containing phenyl-urea moieties as potential novel dual Src and MEK inhibitors. The anti-proliferative assays against K562 and HepG-2 tumor cells showed that most of the derivatives displayed good cytotoxicity in vitro. In particular, kinase inhibition assays showed that compound 8m inhibited Src (59.67%) and MEK (43.23%) at 10 µM, and displayed moderate inhibitory activity against ERK and AKT, the downstream effectors of both Src and MEK. Moreover, compound 8m was found to induce K562 cells apoptosis. Structure-activity relationships of these derivatives were analyzed. Our study suggested that acridine scaffold, particularly compound 8m, is of potential interest for developing novel multi-target Src and MEK kinase inhibitors.

Study of Phospholipids in Single Cells Using an Integrated Microfluidic Device Combined with Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry.

Single-cell trapping and high-throughput mass spectrometry analysis remain challenging now. Current technologies for single-cell analysis have several limitations, such as throughput, space resolution, and multicomponent analysis. In this study, we demonstrate, for the first time, the combination of microfluidic chip and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) for high-throughput and automatic single-cell phospholipids analysis. A microwell-array-based microfluidic chip was designed and fabricated for cell array formation on an indium tin oxide (ITO)-coated glass slide. Mass spectrometry imaging measurement with 25 µm pixel size was performed with a MALDI ion source. Eight phospholipids in a single A549 cell were detected, and their structures were further identified by MS/MS spectra. Selected ion images were generated with a bin width of Δm/z ± 0.005. The selected ion images and optical images of the cell array showed excellent correlation, and mass spectrometry information on phospholipids from 1-3 cells was extracted automatically by selecting pixels with the same fixed interval between microwells on the chip. The measurement and data extraction could be processed in several minutes to achieve a high-throughput analysis. Through the optimization of different microwell sizes and different matrices, this method showed potential for the analysis of other metabolites or metabolic changes at the single-cell level.

The role of dependency-oriented parenting in the intergenerational transmission of dependency: An actor-partner interdependence model.

Utilizing an actor-partner interdependence model, this study examined whether dependency was transmitted from parents to their preschool-aged offspring and, if so, whether dependency-oriented parenting (DOP) mediated such transmission. The mothers and fathers of 488 preschool-aged Chinese children (Mage = 42.36 months, SD = 3.62 months) participated first at 1 month before entry into preschool (Time 1) and then 4 months later (Time 2). Positive relations were found between one parent's dependency and the child's physical dependency on that parent (i.e., actor effect), and one parent's dependency was negatively associated with the child's emotional dependency on the other parent (i.e., partner effect). Additionally, one parent's DOP positively predicted the child's emotional and physical dependency on that parent (i.e., actor effect). Moreover, one parent's DOP partially mediated the relation between the parent's dependency and the child's physical dependency on the parent (i.e., actor effect). Finally, both actor and partner effects were similar for mothers and fathers and for boys and girls. The findings highlight the importance of including both parents and examining actor and partner effects for a comprehensive understanding of the intergenerational transmission of dependency. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Dense regression activation maps for lesion segmentation in CT scans of COVID-19 patients.

Automatic lesion segmentation on thoracic CT enables rapid quantitative analysis of lung involvement in COVID-19 infections. However, obtaining a large amount of voxel-level annotations for training segmentation networks is prohibitively expensive. Therefore, we propose a weakly-supervised segmentation method based on dense regression activation maps (dRAMs). Most weakly-supervised segmentation approaches exploit class activation maps (CAMs) to localize objects. However, because CAMs were trained for classification, they do not align precisely with the object segmentations. Instead, we produce high-resolution activation maps using dense features from a segmentation network that was trained to estimate a per-lobe lesion percentage. In this way, the network can exploit knowledge regarding the required lesion volume. In addition, we propose an attention neural network module to refine dRAMs, optimized together with the main regression task. We evaluated our algorithm on 90 subjects. Results show our method achieved 70.2% Dice coefficient, substantially outperforming the CAM-based baseline at 48.6%. We published our source code at https://github.com/DIAGNijmegen/bodyct-dram.

Emphysema subtyping on thoracic computed tomography scans using deep neural networks.

Accurate identification of emphysema subtypes and severity is crucial for effective management of COPD and the study of disease heterogeneity. Manual analysis of emphysema subtypes and severity is laborious and subjective. To address this challenge, we present a deep learning-based approach for automating the Fleischner Society's visual score system for emphysema subtyping and severity analysis. We trained and evaluated our algorithm using 9650 subjects from the COPDGene study. Our algorithm achieved the predictive accuracy at 52%, outperforming a previously published method's accuracy of 45%. In addition, the agreement between the predicted scores of our method and the visual scores was good, where the previous method obtained only moderate agreement. Our approach employs a regression training strategy to generate categorical labels while simultaneously producing high-resolution localized activation maps for visualizing the network predictions. By leveraging these dense activation maps, our method possesses the capability to compute the percentage of emphysema involvement per lung in addition to categorical severity scores. Furthermore, the proposed method extends its predictive capabilities beyond centrilobular emphysema to include paraseptal emphysema subtypes.

Nuclear-encoded CbbX located in chloroplast is essential for the activity of red-type Rubisco in Saccharina japonica.

Saccharina japonica (Laminariales, Phaeophyta) is a brown alga and the major component of algae beds on the northwest coast of the Pacific Ocean. Rubisco, the key enzyme of CO2 fixation in photosynthesis, is inhibited by nonproductive binding of its substrate RuBP and other sugar phosphates. The inhibited Rubisco in eukaryotic phytoplankton of the red plastid lineage was reactivated by CbbXs, the red-type Rubisco activases, through the process of ATP-hydrolysis-powered remodeling. As well documented, CbbXs had two types of subunits encoded by the plastid or nuclear genome respectively. In this study, both proteins of S. japonica (SjCbbX-n and SjCbbX-p) were localized in the chloroplast illustrated by immuno-electron microscopy technique. GST pull-down detection verified SjCbbX-n could interact with SjCbbX-p. Two-dimensional electrophoresis-based Western blot analysis illustrated that the endogenous SjCbbXs could form heterohexamer in the ratio of 1:1. Activase activity assays showed that although both the recombinant proteins of SjCbbXs were functional, SjCbbX-n illustrated the significantly higher activase activity than SjCbbX-p. Notably, when the two proteins were mixed, the highest specific efficiencies of Rubisco were obtained. These results implied SjCbbX-n may be essential for Rubisco activation. Molecular evolutionary analysis of cbbx genes revealed that cbbx-n originated from the duplication of cbbx-p and then evolved independently under the positive selection pressure. This is the first report about the functional relationship between the two types of CbbXs in macroalge with the red-type Rubisco and provides useful information for revealing the mechanism of high photosynthetic efficiency of this important kelp.

What Could Highly Engaged Workers Gain From Mental Health Promotion Programs?: An Exploratory Analysis of Secondary Outcomes of Brief Daily Workplace Well-being Programs.

OBJECTIVE: The current study aims to examine the effects of mental health programs on well-being among highly engaged workers. METHODS: Participants were randomly allocated to body-mind-spiritual or peer support program. Of the whole sample, we examined participants' work engagement and positive affect from the highest quarter and the lowest quarter of work engagement at baseline. Measures were taken at baseline and 1-month intervals during 3-month programs and 3-month follow-up. RESULTS: The programs had decreasing effects on work engagement in the HWE subgroup. There is an increasing trend of positive affect on the HWE group only in the body-mind-spiritual program. The trajectories of work engagement in the HWE group moved toward a moderate level. CONCLUSION: Our results suggest that the work engagement's decrease in the HWE group could be a sign of recovery and relaxation.

Longitudinal studies of child mental disorders in the general population: A systematic review of study characteristics.

Introduction: Longitudinal studies of child mental disorders in the general population (herein study) investigate trends in prevalence, incidence, risk/protective factors, and sequelae for disorders. They are time and resource intensive but offer life-course perspectives and examination of causal mechanisms. Comprehensive syntheses of the methods of existing studies will provide an understanding of studies conducted to date, inventory studies, and inform the planning of new longitudinal studies. Methods: A systematic review of the research literature in MEDLINE, EMBASE, and PsycINFO was conducted in December 2022 for longitudinal studies of child mental disorders in the general population. Records were grouped by study and assessed for eligibility. Data were extracted from one of four sources: a record reporting study methodology, a record documenting child mental disorder prevalence, study websites, or user guides. Narrative and tabular syntheses of the scope and design features of studies were generated. Results: There were 18,133 unique records for 487 studies-159 of these were eligible for inclusion. Studies occurred from 1934 to 2019 worldwide, with data collection across 1 to 68 time points, with 70% of studies ongoing. Baseline sample sizes ranged from n = 151 to 64,136. Studies were most frequently conducted in the United States and at the city/town level. Internalizing disorders and disruptive, impulse control, and conduct disorders were the most frequently assessed mental disorders. Of studies reporting methods of disorder assessment, almost all used measurement scales. Individual, familial and environmental risk and protective factors and sequelae were examined. Conclusions: These results summarize characteristics of existing longitudinal studies of child mental disorders in the general population, provide an understanding of studies conducted to date, encourage comprehensive and consistent reporting of study methodology to facilitate meta-analytic syntheses of longitudinal evidence, and offer recommendations and suggestions for the design of future studies. Registration DOI: 10.17605/OSF.IO/73HSW.

Associations between socio-demographics, nutrition knowledge, nutrition competencies and attitudes in community-dwelling healthy older adults in Singapore: findings from the SHIELD study.

BACKGROUND: Nutrition literacy refers to an individual's knowledge, motivation and competencies to access, process and understand nutrition information to make nutrition-related decisions. It is known to influence dietary habits of individuals including older adults. This cross-sectional study was designed to: (1) understand the nutrition knowledge, competencies and attitudes of community-dwelling older adults in Singapore, (2) examine the differences between their nutrition knowledge, and socio-demographic factors, competencies and attitudes and (3) identify factors associated with better nutrition knowledge in older healthy adults in Singapore. METHODS: A total of 400 (183 males and 217 females) nourished community-dwelling older adults aged 65 years and above took part in this study. Malnutrition Universal Screening Tool (MUST) was used to determine individuals who were at low risk of undernutrition. Nutrition knowledge, competencies, attitudes and sources of nutrition information were measured using a locally developed scale. Nutrition knowledge scores were summed to form the nutrition knowledge index (NKI). Associations between NKI, competencies, attitudes and socio-demographic variables were examined using Chi-square and Fisher's exact tests. Factors associated with NKI were determined using a stepwise regression model with resampling-based methods for model averaging. RESULTS: Bivariate analyses found significant differences in NKI scores for gender, monthly household earnings, type of housing, the self-reported ability to seek and understand nutrition information and having access to help from family/friends. Females had higher NKI scores compared to males (p < 0.001). Compared to females, more males left food decisions to others (p < 0.001), and fewer males reported consuming home-cooked food (p = 0.016). Differences in educational level were found for competencies like the self-reported ability to seek (p < 0.001) and verify nutrition information (p < 0.001). Stepwise regression analysis showed that being female, Chinese, self-reported ability to understand nutrition information and having access to help from family/friends were associated with higher NKI scores. CONCLUSIONS: Our study revealed that nutrition knowledge of older males in Singapore was lower than females and more left food decisions to others. Nutrition education programs could be targeted at both the older male, their caregivers and minority ethnic groups. Trial Registration This study was registered on 7 August 2017 at clinicaltrials.gov (ref. NCT03240952).

Visualization and Outlier Detection for Multivariate Elastic Curve Data.

We propose a new method for the construction and visualization of geometrically-motivated boxplot displays for elastic curve data. We use a recent shape analysis framework, based on the square-root velocity function representation of curves, to extract different sources of variability from elastic curves, which include location, scale, shape, orientation and parametrization. We then focus on constructing separate displays for these various components using the Riemannian geometry of their representation spaces. This involves computation of a median, two quartiles, and two extremes based on geometric considerations. The outlyingness of an elastic curve is also defined separately based on each of the five components. We evaluate the proposed methods using multiple simulations, and then focus our attention on real data applications. In particular, we study variability in (a) 3D spirals, (b) handwritten signatures, (c) 3D fibers from diffusion tensor magnetic resonance imaging, and (d) trajectories of the Lorenz system.

Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans.

Pulmonary lobe segmentation in computed tomography scans is essential for regional assessment of pulmonary diseases. Recent works based on convolution neural networks have achieved good performance for this task. However, they are still limited in capturing structured relationships due to the nature of convolution. The shape of the pulmonary lobes affect each other and their borders relate to the appearance of other structures, such as vessels, airways, and the pleural wall. We argue that such structural relationships play a critical role in the accurate delineation of pulmonary lobes when the lungs are affected by diseases such as COVID-19 or COPD. In this paper, we propose a relational approach (RTSU-Net) that leverages structured relationships by introducing a novel non-local neural network module. The proposed module learns both visual and geometric relationships among all convolution features to produce self-attention weights. With a limited amount of training data available from COVID-19 subjects, we initially train and validate RTSU-Net on a cohort of 5000 subjects from the COPDGene study (4000 for training and 1000 for evaluation). Using models pre-trained on COPDGene, we apply transfer learning to retrain and evaluate RTSU-Net on 470 COVID-19 suspects (370 for retraining and 100 for evaluation). Experimental results show that RTSU-Net outperforms three baselines and performs robustly on cases with severe lung infection due to COVID-19.