Strong-field THz radiation-induced curing of composite resin materials in dentistry.

Dental caries is listed as one of the three major non-communicable diseases by the World Health Organization, and its main treatment method is to restore it by filling it with resin. At present, the visible light-cure method has the problems of non-uniform curing and low penetration efficiency, which makes the bonding area easy to develop marginal leakages, thus leading to secondary caries and requiring repeated treatment. In this work, through the strong terahertz (THz) irradiation-weak THz detection technique, it is found that the strong THz electromagnetic pulses can accelerate the curing process of the resin, and the weak-field THz spectroscopy can be used to monitor this dynamic change in real time, which will greatly promote the potential application of THz technology in dentistry.

Metro travel and perceived COVID-19 infection risks: A case study of Hong Kong.

The COVID-19 pandemic has exerted unprecedented impacts on travel behaviors because of people's increased health precautions and the presence of various COVID-19 containment measures. However, little research has explored whether and how people changed their travel with respect to their perceived local infection risks across space and time. In this article, we relate elasticity and resilience thinking to the changes in metro travel and perceived infection risks at the station or community level over time. Using empirical data from Hong Kong, we measure a metro station's elasticity as the ratio of changes in its average trip length to the COVID-19 cases' footprints around that station. We regard those footprints as a proxy for people's perceived infection risks when making trips to that station. To explore influencing factors on travel in the ups and downs of perceived infection risks, we classify stations based on their elasticity values and examine the association between stations' elasticities and characteristics of stations and their served communities. The findings show that stations varied in elasticity values across space and different surges of the local pandemic. The elasticity of stations can be predicted by socio-demographics and physical attributes of station areas. Stations serving a larger percentage of population with higher education degrees and certain occupations observed more pronounced trip length decrease for the same level of perceived infection risks. The number of parking spaces and retail facilities significantly explained variations in stations' elasticity. The results provide references on crisis management and resilience improvement amid and post COVID-19.

Structural change and spatial pattern of intentional travel groups: A case study of metro riders in Hong Kong.

Amid the COVID-19 pandemic, face-to-face contacts decreased but still existed despite people's fear of virus infection and governments' social gathering restrictions. These interactions influenced virus transmission routes, if any and reflected people's essential social interactive demands in the city. In this article, we identified people who intentionally travel as groups (ITGs) to characterize social interactions before and amid COVID-19. To systematically understand ITGs' mobility patterns, an ITG structure was defined and measured in multiple dimensions, including composition, function, size, intensity, quality, and spatiotemporal distribution. Based on a longitudinal smartcard dataset in Hong Kong spanning the year of 2020, we operationalized the ITG structure in the local metro system and examined whether and to what degree the structure changed during the pandemic. We found that ITGs' activities fluctuated as the pandemic progressed and their changes differed across different ITG groups. The long-distance ITGs saw the most significant change. The spatial distribution of persistent ITG trips before and amid the pandemic became spatiotemporally more concentrated. Stations with similar ITG indices clustered in proximity, and features of station areas like residents' education level and quantity of commercial facilities could well predict stations' ITG indices. In other words, inequal distribution of essential facilities and opportunities could notably influence ITGs, social contacts, and socioeconomic benefits brought about by them amid COVID-19. The findings provide insights concerning both resilience management amid the crisis and the long-term planning of essential facilities and services that facilitate group-based outgoings and activities.

Jobs-housing relationships before and amid COVID-19: An excess-commuting approach.

The outbreak of COVID-19 and subsequent pandemic containment measures have significantly affected our daily life, which has been extensively examined in the existing scholarship. However, the existing scholarship has done little on the jobs/housing relationship impacts of COVID-19. We attempted to fill this gap by using an excess-commuting approach. The approach allows us to analyse a series of jobs-housing matrices based on the location-based service big data of around fifty million individuals in the Pearl River Delta (PRD), China before and amid COVID-19. In the PRD, a zero-COVID policy was implemented, which presents a distinct and interesting context for our study. We found that after the COVID-19 outbreak: (1) residences and employment became more centrally located in downtowns, which is opposite to the suburbanization trend elsewhere; (2) in the whole PRD, the minimum and maximum commutes became smaller while the actual commute became larger, indicating the simultaneous presences of some paradoxical phenomena: a better spatial juxtaposition of jobs and housing, more compressed distribution of jobs and housing, and longer average actual commutes; (3) inter-city commutes between large cities were significantly refrained and decreased, while new inter-city commuters between smaller cities emerged; (4) it was more likely for the less-educated and female workers to see smaller minimum commutes amid COVID-19. This paper illustrates the potential of big data in the longitudinal study on jobs-housing relationships and excess commuting. It also produces new insights into such relationships in a unique context where stringent anti-COVID-19 policies have been continuously in place.

The Development of an Interpersonal Stressors Scale: Identifying Self-Imposed and Other-Imposed Interpersonal Stressors.

While there has been research focused on interpersonal relationships and their impact on stress and well-being, no instrument has been developed to comprehensively evaluate interpersonal stressors. This research sought to develop and validate an Interpersonal Stressors Scale (ISS) for Chinese college students through three studies. Focus groups were used to generate the initial item pool (Study 1). Then two large samples (N1 = 511; N2 = 330) were collected to explore the factor structure of the ISS and subsequently examine its reliability and validity estimates (study 2 and 3). Initial results indicated a model with 27 items and five first-order factors (interaction difficulty, behaving as expected, social criticism, relationship maintenance, and indebtedness avoidance) as well as two second-order factors (self-imposed stressors and other-imposed stressors) with strong psychometric properties. Criterion-related validity estimates indicated these two kinds of stressors were both associated with stress while having different relationships with general anxiety, depression, social anxiety, interpersonal satisfaction, and self-efficacy in social interactions. The nature and function of the structure for the ISS were discussed as well as the practical and research implications.

Terahertz anisotropy in fascia and lean meat tissues.

Terahertz (THz) spectroscopy provides multifaceted capabilities for observing low-energy responses of macromolecules, cells and tissues, understanding THz biophysical effects, and expecting to realize the application of THz technology in biomedicine. However, its high-frequency characteristics of limited penetration depth and strong absorption of water in the body comparable to microwaves are impeding the proliferation of THz spectroscopy. Here we show that THz spectroscopy makes possible the observation of THz anisotropy phenomena for the first time in fascia and lean tissue. Through optical microscopy, we infer that the microscopic mechanism of THz anisotropy comes from the periodic stripe structure of the biological tissue. The above related experimental findings may be expected to promote the application of THz technology in biomedicine.

Dental caries diagnosis using terahertz spectroscopy and birefringence.

Dental caries is a widespread chronic infectious disease which may induce a series of oral and general problems if untreated. As a result, early diagnosis and follow-up following radiation-free dental caries therapy are critical. Terahertz (THz) waves with highly penetrating and non-ionizing properties are ideally suited for dental caries diagnosis, however related research in this area is still in its infancy. Here, we successfully observe the existence of THz birefringence phenomenon in enamel and demonstrate the feasibility of utilizing THz spectroscopy and birefringence to realize caries diagnosis. By comparing THz responses between healthy teeth and caries, the transmitted THz signals in caries are evidently reduced. Concomitantly, the THz birefringence is also unambiguously inhibited when caries occurs due to the destruction of the internal hydroxyapatite crystal structure. This THz anisotropic activity is position-dependent, which can be qualitatively understood by optical microscopic imaging of dental structures. To increase the accuracy of THz technology in detecting dental caries and stimulate the development of THz caries instruments, the presence of significant THz birefringence effect induced anisotropy in enamel, in combination with the strong THz attenuation at the caries, may be used as a new tool for caries diagnosis.

Abrupt changes, institutional reactions, and adaptive behaviors: An exploratory study of COVID-19 and related events' impacts on Hong Kong's metro riders.

Abrupt socioeconomic changes have become increasingly commonplace. In face of these, both institutions and individuals must adapt. Against the backdrop of the COVID-19 pandemic, suddenness, scale, and impacts of which are unprecedented as compared to its counterparts in history, we first propose transferable measures and methods that can be used to quantify and geovisualize COVID-19 and subsequent events' impacts on metro riders' travel behaviors. Then we operationalize and implement those measures and methods with empirical data from Hong Kong, a metropolis heavily reliant on transit/metro services. We map out where those impacts were the largest and explores its correlates. We exploit the best publicly available data to assemble probable explanatory variables and to examine quantitatively whether those variables are correlated to the impacts and if so, to what degree. We find that both macro- and meso-level external/internal events following the COVID-19 outbreak significantly influenced of metro riders' behaviors. The numbers of public rental housing residents, public and medical facilities, students' school locations, residents' occupation, and household income significantly predict the impacts. Also, the impacts differ across social groups and locales with different built-environment attributes. This means that to effectively manage those impacts, locale- and group-sensitive interventions are warranted.

Tracking job and housing dynamics with smartcard data.

Residential locations, the jobs-housing relationship, and commuting patterns are key elements to understand urban spatial structure and how city dwellers live. Their successive interaction is important for various fields including urban planning, transport, intraurban migration studies, and social science. However, understanding of the long-term trajectories of workplace and home location, and the resulting commuting patterns, is still limited due to lack of year-to-year data tracking individual behavior. With a 7-y transit smartcard dataset, this paper traces individual trajectories of residences and workplaces. Based on in-metro travel times before and after job and/or home moves, we find that 45 min is an inflection point where the behavioral preference changes. Commuters whose travel time exceeds the point prefer to shorten commutes via moves, while others with shorter commutes tend to increase travel time for better jobs and/or residences. Moreover, we capture four mobility groups: home mover, job hopper, job-and-residence switcher, and stayer. This paper studies how these groups trade off travel time and housing expenditure with their job and housing patterns. Stayers with high job and housing stability tend to be home (apartment unit) owners subject to middle- to high-income groups. Home movers work at places similar to stayers, while they may upgrade from tenancy to ownership. Switchers increase commute time as well as housing expenditure via job and home moves, as they pay for better residences and work farther from home. Job hoppers mainly reside in the suburbs, suffer from long commutes, change jobs frequently, and are likely to be low-income migrants.

Low-dose curcumin stimulates proliferation of rat embryonic neural stem cells through glucocorticoid receptor and STAT3.

AIMS: This study was to determine whether curcumin had any effect on the proliferation of neural stem cell (NSC), analyze the expression of glucocorticoid receptor (GR), signal transducer and activator of transcription 3 (STAT3), and Notch1 at transcription and protein level, and discuss the related mechanisms. METHODS AND RESULTS: NSCs were harvested from E15 SD rat brain and cultured. All experiments were performed at the second passage. Cell cytotoxicity, cell viability, and proliferation assays were used to figure out the optimal concentration of curcumin, which can be used for the protein and mRNA studies. The results showed that by downregulation of GR and STAT3 expression, 0.5 µmol L-1 curcumin exhibited the most pronounced effect in promoting the proliferation of NSCs, which were also induced by antagonists of GR and STAT3, but was inhibited by GR agonist. CONCLUSION: This study shows that low-dose curcumin stimulates the proliferation of NSCs, which is probably by inhibiting the mRNA and protein expressions of GR and directly or indirectly regulating the STAT3 via the synergistic effect of GR and STAT3 pathways and its related signal pathways.

Isoflurane anesthesia in aged mice and effects of A1 adenosine receptors on cognitive impairment.

AIMS: Isoflurane may not only accelerate the process of Alzheimer's disease (AD), but increase the risk of incidence of postoperative cognitive dysfunction (POCD). However, the underlying mechanisms remain unknown. This study was designed to investigate whether isoflurane contributed to the POCD occurrence through A1 adenosine receptor (A1AR) in aged mice. METHODS: We assessed cognitive function of mice with Morris water maze (MWM) and then measured expression level of two AD biomarkers (P-tau and Aß) and a subtype of the NMDA receptor (NR2B) in aged wild-type (WT) and homozygous A1 adenosine receptor (A1AR) knockout (KO) mice at baseline and after they were exposed to isoflurane (1.4% for 2 hours). RESULTS: For cognitive test, WT mice with isoflurane exposure performed worse than the WT mice without isoflurane exposure. However, A1AR KO mice with isoflurane exposure performed better than WT mice with isoflurane exposure. WT mice exposed to isoflurane had increased levels of Aß and phosphorylated tau (P-tau). Levels of Aß and P-tau were decreased in A1AR KO mice, whereas no differences were noted between KO mice with and without isoflurane exposure. NR2B expression was inversely related to that of P-tau, with no differences found between KO mice with and without isoflurane exposure. CONCLUSIONS: We found an association between isoflurane exposure, impairment of spatial memory, decreasing level of NR2B, and increasing levels of A-beta and P-tau, presumably via the activation of the A1A receptor.