Use, satisfaction, and preference of online health services among older adults with multimorbidity in Hong Kong primary care during COVID-19.

BACKGROUND: The use of online and mobile internet and social media has been increasing in healthcare service delivery. However, there is limited literature on the acceptance and use of online health services for older adults with multimorbidity who require more medical care and assistance. This study aims to explore the use of social media in older adults with multimorbidity in Hong Kong primary care and to assess the feasibility and usage of online health services in this population, including satisfaction, preference, and problems encountered. METHODS: This is a cross-sectional study among older adults with multimorbidity conducted between November 2020 and March 2021 in a Hong Kong primary care programme. Online and face-to-face services were offered based on the needs of the participants. Demographic characteristics and health conditions were assessed at baseline. Participants using online services were invited to complete a feedback questionnaire. RESULTS: The study included 752 participants, of which 66.1% use social media every day. Participants who declined to use online services were found to be significantly older, live alone, have lower income, have social security assistance, have greater cognitive decline, and be less depressed (p < 0.05). Non-responders to the online questionnaire had fewer years of education and greater cognitive decline (p < 0.05). The median satisfaction with the online services was 8 (interquartile range: 7, 9), and 14.6% of the participants preferred online more than face-to-face services. Lower education levels, fewer internet connection issues, and more self-efficacy on mobile apps were associated with a higher level of online satisfaction after adjustment (p < 0.05). Fewer internet connection issues and more self-efficacy on mobile apps were associated with participants' preference for online services (p < 0.05). CONCLUSIONS: More than half of Hong Kong older adults with multimorbidity in primary care use social media daily. Internet connection issues can be a significant barrier to the usage of online services in this population. Prior use and training can be beneficial to enhance use and satisfaction in older adults.

Recombinant Human Thymosin ß4 (rhTß4) Modulates the Anti-Inflammatory Responses to Alleviate Benzalkonium Chloride (BAC)-Induced Dry Eye Disease.

Dry eye disease (DED) is a multifactorial ocular disorder that interferes with daily living and reduces quality of life. However, there is no most ideal therapeutic treatment to address all the deleterious defects of DED. The purpose of this study was to investigate the ability of recombinant human thymosin ß4 (rhTß4) to promote healing in a benzalkonium chloride (BAC)-induced mice DED model and the anti-inflammatory effects involved in that process. Eye drops consisting of 0.05% and 0.1% rhTß4 were used for treatment of DED. Tear volume and corneal staining scores were measured after 7 days. Periodic acid-Schiff staining for gobleT cells in conjunctiva, immunohistochemical staining for CD4+ T cells, TUNEL assay for apoptotic positive cells in cornea and conjunctiva, qRT-PCR and ELISA assays for multiple cytokines were performed. All clinical parameters showed improvement in both the 0.05% and 0.1% rhTß4 groups. Specifically, topical application of rhTß4 significantly increased conjunctival gobleT cells and reduced apoptotic cells in conjunctiva. Mechanically, the rhTß4 groups showed significantly reduced inflammatory cytokine levels and CD4+ T cells in conjunctiva by blocking NF-κB (nuclear factor kappa B) activation, suggesting that 0.05-0.1% rhTß4 eye drops may be used as a potential therapeutic treatment for DED.

Autophagosomal Membrane Origin and Formation.

Autophagosome formation is a regulated membrane remodeling process, which involves the generation of autophagosomal membrane precursors (vesicles), the assembly of the autophagosomal membrane precursors to form the phagophore, and phagophore elongation to complete the autophagosome. The sources of the autophagosomal membrane precursors are endomembrane compartments, such as the endoplasmic reticulum (ER), the ER-Golgi intermediate compartment (ERGIC), ER-exit sites (ERES), and endosomes. In response to stress, these structures are remodeled, to generate the early autophagosomal membrane precursors. The phagophore assembly site (PAS), which mainly localizes on the ER, harbors the site for autophagosomal membrane assembly, elongation, and completion. ATG proteins, membrane remodeling factors, and autophagic membranes follow a precise choreography to complete the overall process. In this chapter, we briefly discuss our current knowledge on the membrane origins of the autophagosome, as well as autophagosomal precursor generation, assembly, and expansion.

Selenoprotein F knockout leads to glucose and lipid metabolism disorders in mice.

Selenoprotein F (Selenof), an endoplasmic reticulum (ER)-resident protein, is considered to be involved in glycoprotein folding and quality control in the ER. However, its function has not yet been thoroughly addressed. In this study, proteomics analysis revealed that Selenof deficiency in mice led to the differential expression of hepatic proteins associated with glucose and lipid metabolism. The phenotype analysis revealed that Selenof knockout mice showed glucose intolerance and insulin reduction, even with a normal diet. Additionally, Selenof knockout exacerbated high-fat diet-induced obesity, hyperglycemia, glucose intolerance, and hepatic steatosis. Furthermore, lipoprotein lipase and carboxylesterase 1D, two glycoproteins involved in lipid metabolism, were significantly decreased in the liver of Selenof knockout mice with a normal or high-fat diet. Collectively, these findings suggested that Selenof deficiency might cause the perturbation of glycoprotein quality control and thus contribute to glucose and lipid metabolism disorders, implying a novel biological function of Selenof.

Binless Kernel Machine: Modeling Spike Train Transformation for Cognitive Neural Prostheses.

Modeling spike train transformation among brain regions helps in designing a cognitive neural prosthesis that restores lost cognitive functions. Various methods analyze the nonlinear dynamic spike train transformation between two cortical areas with low computational eficiency. The application of a real-time neural prosthesis requires computational eficiency, performance stability, and better interpretation of the neural firing patterns that modulate target spike generation. We propose the binless kernel machine in the point-process framework to describe nonlinear dynamic spike train transformations. Our approach embeds the binless kernel to eficiently capture the feedforward dynamics of spike trains and maps the input spike timings into reproducing kernel Hilbert space (RKHS). An inhomogeneous Bernoulli process is designed to combine with a kernel logistic regression that operates on the binless kernel to generate an output spike train as a point process. Weights of the proposed model are estimated by maximizing the log likelihood of output spike trains in RKHS, which allows a global-optimal solution. To reduce computational complexity, we design a streaming-based clustering algorithm to extract typical and important spike train features. The cluster centers and their weights enable the visualization of the important input spike train patterns that motivate or inhibit output neuron firing. We test the proposed model on both synthetic data and real spike train data recorded from the dorsal premotor cortex and the primary motor cortex of a monkey performing a center-out task. Performances are evaluated by discrete-time rescaling Kolmogorov-Smirnov tests. Our model outperforms the existing methods with higher stability regardless of weight initialization and demonstrates higher eficiency in analyzing neural patterns from spike timing with less historical input (50%). Meanwhile, the typical spike train patterns selected according to weights are validated to encode output spike from the spike train of single-input neuron and the interaction of two input neurons.

Invasive Brain Machine Interface System.

Because of high spatial-temporal resolution of neural signals obtained by invasive recording, the invasive brain-machine interfaces (BMI) have achieved great progress in the past two decades. With success in animal research, BMI technology is transferring to clinical trials for helping paralyzed people to restore their lost motor functions. This chapter gives a brief review of BMI development from animal experiments to human clinical studies in the following aspects: (1) BMIs based on rodent animals; (2) BMI based on non-human primates; and (3) pilot BMIs studies in clinical trials. In the end, the chapter concludes with a summary of potential opportunities and future challenges in BMI technology.

Brain-Machine Interface-Based Rat-Robot Behavior Control.

Brain-machine interface (BMI) provides a bidirectional pathway between the brain and external facilities. The machine-to-brain pathway makes it possible to send artificial information back into the biological brain, interfering neural activities and generating sensations. The idea of the BMI-assisted bio-robotic animal system is accomplished by stimulations on specific sites of the nervous system. With the technology of BMI, animals' locomotion behavior can be precisely controlled as robots, which made the animal turning into bio-robot. In this chapter, we reviewed our lab works focused on rat-robot navigation. The principles of rat-robot system have been briefly described first, including the target brain sites chosen for locomotion control and the design of remote control system. Some methodological advances made by optogenetic technologies for better modulation control have then been introduced. Besides, we also introduced our implementation of "mind-controlled" rat navigation system. Moreover, we have presented our efforts made on combining biological intelligence with artificial intelligence, with developments of automatic control and training system assisted with images or voices inputs. We concluded this chapter by discussing further developments to acquire environmental information as well as promising applications with write-in BMIs.

Nonlinear Modeling of Neural Interaction for Spike Prediction Using the Staged Point-Process Model.

Neurons communicate nonlinearly through spike activities. Generalized linear models (GLMs) describe spike activities with a cascade of a linear combination across inputs, a static nonlinear function, and an inhomogeneous Bernoulli or Poisson process, or Cox process if a self-history term is considered. This structure considers the output nonlinearity in spike generation but excludes the nonlinear interaction among input neurons. Recent studies extend GLMs by modeling the interaction among input neurons with a quadratic function, which considers the interaction between every pair of input spikes. However, quadratic effects may not fully capture the nonlinear nature of input interaction. We therefore propose a staged point-process model to describe the nonlinear interaction among inputs using a few hidden units, which follows the idea of artificial neural networks. The output firing probability conditioned on inputs is formed as a cascade of two linear-nonlinear (a linear combination plus a static nonlinear function) stages and an inhomogeneous Bernoulli process. Parameters of this model are estimated by maximizing the log likelihood on output spike trains. Unlike the iterative reweighted least squares algorithm used in GLMs, where the performance is guaranteed by the concave condition, we propose a modified Levenberg-Marquardt (L-M) algorithm, which directly calculates the Hessian matrix of the log likelihood, for the nonlinear optimization in our model. The proposed model is tested on both synthetic data and real spike train data recorded from the dorsal premotor cortex and primary motor cortex of a monkey performing a center-out task. Performances are evaluated by discrete-time rescaled Kolmogorov-Smirnov tests, where our model statistically outperforms a GLM and its quadratic extension, with a higher goodness-of-fit in the prediction results. In addition, the staged point-process model describes nonlinear interaction among input neurons with fewer parameters than quadratic models, and the modified L-M algorithm also demonstrates fast convergence.

A Neuromuscular Electrical Stimulation (NMES) and robot hybrid system for multi-joint coordinated upper limb rehabilitation after stroke.

BACKGROUND: It is a challenge to reduce the muscular discoordination in the paretic upper limb after stroke in the traditional rehabilitation programs. METHOD: In this study, a neuromuscular electrical stimulation (NMES) and robot hybrid system was developed for multi-joint coordinated upper limb physical training. The system could assist the elbow, wrist and fingers to conduct arm reaching out, hand opening/grasping and arm withdrawing by tracking an indicative moving cursor on the screen of a computer, with the support from the joint motors and electrical stimulations on target muscles, under the voluntary intention control by electromyography (EMG). Subjects with chronic stroke (n = 11) were recruited for the investigation on the assistive capability of the NMES-robot and the evaluation of the rehabilitation effectiveness through a 20-session device assisted upper limb training. RESULTS: In the evaluation, the movement accuracy measured by the root mean squared error (RMSE) during the tracking was significantly improved with the support from both the robot and NMES, in comparison with those without the assistance from the system (P < 0.05). The intra-joint and inter-joint muscular co-contractions measured by EMG were significantly released when the NMES was applied to the agonist muscles in the different phases of the limb motion (P < 0.05). After the physical training, significant improvements (P < 0.05) were captured by the clinical scores, i.e., Modified Ashworth Score (MAS, the elbow and the wrist), Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), and Wolf Motor Function Test (WMFT). CONCLUSIONS: The EMG-driven NMES-robotic system could improve the muscular coordination at the elbow, wrist and fingers. TRIAL REGISTRATION: ClinicalTrials.gov. NCT02117089 ; date of registration: April 10, 2014.

Determination of glucosamine and its derivatives released from photocrosslinked gelatin hydrogels using HPLC.

A simple, accurate and validated reverse-phase high-performance liquid chromatography (HPLC)/UV method is developed for the determination of glucosamine hydrochloride (GlcN), N-acetyl-glucosamine (NAG) and N-acryloyl-glucosamine (AGA) released from photocrosslinked gelatin hydrogels. The HPLC separation was achieved on a Shimadzu InertSustain amino column (250 × 4.6 mm, 5 µm particle size) at room temperature using a mobile phase of acetonitrile-phosphate buffer (75:25, v/v, pH 6.0) at a flow rate of 1.0 mL/min and UV detection of 194 nm. The method was validated for specificity, linearity, limit of detection and quantification, accuracy, precision, extraction recovery and solution stability. The calibration curves were with excellent linearity, with correlation coefficients (R(2)) >0.999 for all three drugs. The intra- and inter-day variation was <3.10% and the relative error was between -1.43 and 1.78%. The extraction recovery results ranged from 94.62 to 99.33%, demonstrating the absence of matrix effect. The sample and standard solutions were stable for more than 2 months. The method was successfully used for the analysis of released properties of drugs physically encapsulated and chemically crosslinked in the gelatin hydrogels.

Knockdown of 15-kDa selenoprotein (Sep15) increases hLE cells' susceptibility to tunicamycin-induced apoptosis.

In this work, we investigated the effect of Sep15 gene knockdown on apoptosis in human lens epithelial (hLE) cells, trying to understand the relevance of Sep15 to cataract formation in the Sep15 knockout (KO) mice. The results showed that sole knockdown of Sep15 by RNA interference did not result in apoptosis; however, reduction of Sep15 expression aggravated tunicamycin (Tm)-induced cell apoptosis and caspases activation. Furthermore, Tm-induced mitochondrial dysfunction was also exacerbated under the Sep15 knockdown condition by measurement of mitochondrial membrane potential decrease and human cytochrome c release into cytosol. Interestingly, the knockdown of Sep15 exacerbated Tm-induced oxidative stress while endoplasmic reticulum (ER) stress was not correspondingly elevated. These results suggest that the protective role of Sep15 against Tm-induced apoptosis in hLE cells is operated via inhibiting oxidative stress rather than regulating Tm-induced ER stress, and the protective role becomes dependent on Sep15 only in acute stress condition.

An automatic patient-specific seizure onset detection method using intracranial electroencephalography.

OBJECTIVE: This study presents a multichannel patient-specific seizure detection method based on the empirical mode decomposition (EMD) and support vector machine (SVM) classifier. MATERIALS AND METHODS: The EMD is used to extract features from intracranial electroencephalography (EEG). A machine-learning algorithm is used as a classifier to discriminate between seizure and nonseizure intracranial EEG epochs. A postprocessing algorithm is proposed to reject artifacts and increase the robustness of the method. The proposed method was evaluated using 463 hours of intracranial EEG recordings from 17 patients with a total of 51 seizures in the Freiburg EEG database. RESULTS: The proposed method had better performance than most of the existing seizure detection systems, including an average sensitivity of 92%, false detection rate (FDR) of 0.17/hour, and time delay (TD) of 12 sec. Moreover, the FDR could be further reduced by a TD extension. CONCLUSIONS: Given its high sensitivity and low FDR, the proposed patient-specific seizure detection method can greatly assist clinical staff with automatically marking seizures in long-term EEG or detecting seizure onset online with high performance. Early and accurate seizure detection using this method may serve as a practical tool for planning epilepsy interventions.

The dynamic detection of NO during the ischemic postconditioning against global cerebral ischemia/reperfusion injury.

Little is known about role of Nitric Oxide (NO) of ischemic postconditioning in global cerebral ischemia and reperfusion (I/R) injury. In this study, we detected the dynamic change of NO during the ischemic postconditioning against global cerebral I/R in vivo, and compared the effects of six postconditioning conditions with different numbers of cycles and periods for reperfusion/occlusion. The animals underwent postconditioning consisting of 3 or 10 cycles of 15-s reperfusion, followed by 15-s occlusion (post-3-15/15, post-10-15/15), or 3 or 10 cycles of 30-s reperfusion/30-s occlusion (post-3-30/30, post-10-30/30), or 3 or 10 cycles of 60-s reperfusion/15-s occlusion (post-3-60/15, post-10-60/15). The results showed that four groups increased NO concentration, while all groups improved CBF significantly. Different postconditioning groups had different effects on NO and CBF. Post-3-30/30 had the strongest effect on both. Also it reduced infarct size from 33.0% to 24.29%, and downregulated the cell death ratio from 6.71% to 1.04%, showing the strongest protective effect among tested conditions. And we found that post-3-30/30 was an optional method in ischemic postconditioning, which obviously induced a large amount of NO synthesis with a slow speed, increased CBF and reduced the brain injuries. Therefore we concluded that NO is a reliable candidate in mediating ischemic postconditioning neuroprotection.

Safety and immunogenicity of the SARS-CoV-2 LYB001 RBD-based VLP vaccine (CHO cell) phase 1 in Chinese adults: a randomized, double-blind, positive-parallel-controlled study.

BACKGROUND: Vaccination remains the cornerstone of defense against COVID-19 globally. This study aims to assess the safety and immunogenicity profile of innovative vaccines LYB001. RESEARCH DESIGN AND METHODS: This was a randomized, double-blind, parallel-controlled trial, in 100 healthy Chinese adults (21 to 72 years old). Three doses of 30 or 60 µg of SARS-CoV-2 RBD-based VLP vaccine (LYB001), or the SARS-CoV-2 RBD-based protein subunit vaccine (ZF2001, control group) were administered with a 28-day interval. Differences in the incidence of adverse events (AEs) and indicators of humoral and cellular immunity among the different groups were measured. RESULTS: No severe adverse events were confirmed to be vaccine-related, and there was no significant difference in the rate of adverse events between the LYB001 and control group or the age subgroups (p > 0.05). The LYB001 groups had significantly higher or comparable levels of seroconversion rates, neutralization antibody, S protein-binding antibody, and cellular immunity after whole vaccination than the control group. CONCLUSIONS: Our findings support that LYB001 developed on the VLP platform is safe and well tolerated with favorable immunogenicity for fundamental vaccination in healthy adults. Therefore, further larger-scale clinical studies are warranted. TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov (NCT05552573).

Active surveillance of hepatitis E: A 10-year epidemiological analysis in a city in eastern China.

AbstractBackground Hepatitis E virus (HEV) is an important cause of acute hepatitis, however, is highly neglected and largely underreported. This study aimed to describe the detailed epidemiology of hepatitis E (HE) through a 10-year surveillance. Method A community-based active hepatitis surveillance was conducted between November 2007 and October 2017 in 11 townships of Dongtai City in China, involving 355,673 residents. Serum samples were obtained from patients presenting with hepatitis symptoms for more than 3 days. Serum alanine aminotransferase (ALT) levels greater than 2.5 times the upper limit of normal (ULN) were considered acute hepatitis. Samples were subsequently tested for IgG and IgM anti-HEV antibodies, HEV RNA, and hepatitis B surface antigen (HBsAg). Result The data indicated the incidence of HE fluctuated downward from 2007 to 2017, with an average annual age-standardized incidence of 17.50 per 100,000, exceeding the 10.26 per 100,000 in the National Notifiable Disease Report System (NNDRS). The incidence was notably higher among males (20.95 per 100,000) and individuals aged 50-69 years (37.47 per 100,000). Genotype 4 (HEV-4) was the predominantly circulating genotype during the study period. Furthermore, the study revealed the incidence of hepatitis with HEV and hepatitis B virus (HBV) co-infection was 4.99 per 100,000. Conclusion The active surveillance system identified a higher incidence of HE compared to NNDRS, with a decreased prevalence over a 10-year period. While efforts are still needed to prevent HE in high-risk populations, including individuals with hepatitis B and the elderly.

Does It Matter Who You Live with during COVID-19 Lockdown? Association of Living Arrangements with Psychosocial Health, Life Satisfaction, and Quality of Life: A Pilot Study.

BACKGROUND: Living arrangements might greatly impact psychosocial health and quality of life, particularly during the COVID-19 lockdown. This pilot study aimed to examine the association of different common living arrangements with psychosocial health, life satisfaction, and quality of life among Chinese adults during the COVID-19 lockdown. METHODS: An anonymous online survey was conducted using convenience sampling through the WeChat application in February 2020. Mental health (Patient Health Questionnaire-2, Generalized Anxiety Disorder-2, post-traumatic stress disorder symptoms, Patient Health Questionnaire-15, and meaning in life), social health (UCLA-3), quality of life (EQ5D and EQ-VAS), and life satisfaction were measured. Linear regression models were used. RESULT: The study included 1245 adults (mean age: 34.14 ± 10.71) in China. Compared to other living arrangements, participants who "live with partner and children" or "live with partner, children and parents" were more likely to have better outcomes of mental health, social health, quality of life, and life satisfaction. Participants who "live with parents or grandparents" or "live with partner" were more likely to have better health outcomes compared with those who "live with children" or "live alone". CONCLUSION: Living with a partner, children, and/or parents could be a protective factor against poor psychosocial health during lockdown and quarantine.

Fenofibrate suppresses corneal neovascularization by regulating lipid metabolism through PPARα signaling pathway.

Purpose: The purpose of this study was to explore the potential underlying mechanism of anti-vascular effects of peroxisome proliferator-activated receptor α (PPARα) agonist fenofibrate against corneal neovascularization (CNV) through the changes of lipid metabolism during CNV. Methods: A suture-induced CNV model was established and the clinical indications were evaluated from day 1 to day 7. Treatments of vehicle and fenofibrate were performed for 5 days after suture and the CNV areas were compared among the groups. The eyeballs were collected for histological analysis, malondialdehyde (MDA) measurement, terminal deoxynucleotidyl transferase 2'-deoxyuridine 5'-triphosphate nick end labeling (TUNEL) staining, western blot, quantitative real-time PCR (qRT-PCR) assays and immunohistochemical (IHC) staining to elucidate pathological changes and the underlying mechanism. Results: Lipi-Green staining and MDA measurement showed that lipid deposition and peroxidation were increased in the CNV cornea while the expression of long-chain acyl-coenzyme A synthetase 1 (ACSL1), carnitine palmitoyltransterase 1A(CPT1A) and medium-chain acyl-coenzyme A dehydrogenase (ACADM), which are key enzymes of fatty acid ß-oxidation (FAO) and targeted genes of peroxisome proliferator-activated receptor alpha (PPARα) pathway, were decreased in CNV cornea. Fenofibrate suppressed lipid accumulation and peroxidation damage in the CNV cornea. Fenofibrate upregulated the expression levels of PPARα, ACSL1, CPT1A, and ACADM compared with vehicle group. IHC staining indicated that fenofibrate also decreased the expression of VEGFa, VEGFc, TNFα, IL1ß and CD68. Conclusion: Disorder of lipid metabolism may be involved in the formation of suture-induced CNV and fenofibrate played anti-neovascularization and anti-inflammatory roles on cornea by regulating the key enzymes of lipid metabolism and ameliorating lipid peroxidation damage of cornea through PPARα signaling pathway.

Association of positive and adverse childhood experiences with risky behaviours and mental health indicators among Chinese university students in Hong Kong: an exploratory study.

Background: Different childhood experiences may affect adult health differently. Objective: To explore the association of different types of positive childhood experiences(PCEs) and adverse childhood experiences (ACEs) with risky behaviours and mental health indicators, andhow PCEs and ACEs are associated with health outcomes in the context of each other. Method: This was an exploratory cross-sectional online survey including 332 university students in Hong Kong. ACEs (abuse and household challenges), PCEs (perceived safety, positive quality of life, and interpersonal support), risky behaviours (smoking, binge drinking, and sexual initiation), and mental health indicators(depression, anxiety, loneliness, self-rated health, multimorbidity, meaning in life, and life satisfaction)were measured. Results: The multivariable logistic regression analysis indicated cumulative effects of PCEs in lowered risks of depression, anxiety, loneliness, as well as better self-rated health, life satisfaction, and meaning in life (p < .05), after adjusting for ACEs. Results also indicated that ACEs had an increasing relationship with poorer mental health indicators, such as anxiety, loneliness, and life satisfaction (p < .05), after adjusting for PCEs. There was also an adverse association between having ≥4 ACEs with smoking and binge drinking. In addition, each type of PCE and ACE was significantly associated with one or more risky behaviours and mental health indicators. Stratified results showed that PCEs had stronger associations with mental health indicators in participants with fewer ACEs. Furthermore, ACEs had stronger associations with mental health indicators in participants with more PCEs than in those with fewer PCEs. Conclusions: In this study, PCE was proven to be an independent protective factor against poor mental health after accounting for ACE. ACE was also proven to be an independent risk factor for poor mental health and risky behaviours. These findings suggest a crucial need for the active promotion of PCEs and the prevention of child maltreatment. The results of subtypes and stratifications can be taken into consideration when developing targeted interventions in the future. HIGHLIGHTS: PCE is an independent protective factor against poor mental health after accounting for ACE. ACE is an independent risk factor for poor mental health and risky behaviours.PCEs and ACEs have different associations with health outcomes in the context of one another.

Antecedentes: Las diferentes experiencias de la infancia pueden afectar la salud de los adultos de manera diferente.Objetivo: Explorar la asociación de diferentes tipos de experiencias infantiles positivas (EIP) y experiencias infantiles adversas (EIA) con conductas de riesgo e indicadores de salud mental, y cómo las EIP y las EIA se asocian con resultados de salud en el contexto de cada uno.Método: Esta fue una encuesta transversal exploratoria en línea que incluyó a 332 estudiantes universitarios en Hong Kong. EIA (abuso y desafíos domésticos), EIP (seguridad percibida, calidad de vida positiva y apoyo interpersonal), comportamientos de riesgo (fumar, beber en exceso e iniciación sexual) e indicadores de salud mental (depresión, ansiedad, soledad, salud autoevaluada, multimorbilidad, sentido de la vida y satisfacción con la vida) fueron medidos.Resultados: El análisis de regresión logística multivariable indicó efectos acumulativos de EIP en disminuir el riesgo de depresión, ansiedad, soledad, así como mejor autoevaluación de la salud, satisfacción con la vida y sentido de la vida (p < 0,05), después de ajustar por EIA. Los resultados también indicaron que EIA tuvo una relación de incremento con indicadores de salud mental más deficientes, como ansiedad, soledad y satisfacción con la vida (p < 0,05), después de ajustar por EIP. También hubo una asociación adversa entre tener ≥4 EIA con fumar y beber en exceso. Además, cada tipo de EIP y EIA se asoció significativamente con uno o más comportamientos de riesgo e indicadores de salud mental. Los resultados estratificados mostraron que EIP tuvo asociaciones más fuertes con indicadores de salud mental en participantes con menos EIA. Además, EIA tuvo asociaciones más fuertes con indicadores de salud mental en participantes con más EIA que en aquellos con menos EIP.Conclusiones: En este estudio, se demostró que EIP es un factor protector independiente contra una pobre salud mental después de tomar en cuenta EIA. También se demostró que EIA es un factor de riesgo independiente para una pobre salud mental y comportamientos de riesgo. Estos hallazgos sugieren una necesidad crucial para la promoción activa de EIPs y la prevención del maltrato infantil. Los resultados de los subtipos y estratificaciones se pueden tener en cuenta al desarrollar intervenciones focalizadas en el futuro.

Primary School Students' Online Learning During Coronavirus Disease 2019: Factors Associated With Satisfaction, Perceived Effectiveness, and Preference.

Emergency online education has been adopted worldwide due to coronavirus disease 2019 (COVID-19) pandemic. Prior research regarding online learning predominantly focused on the perception of parents, teachers, and students in tertiary education, while younger children's perspectives have rarely been examined. This study investigated how family, school, and individual factors would be associated with primary school students' satisfaction, perceived effectiveness, and preference in online learning during COVID-19. A convenient sample of 781 Hong Kong students completed an anonymous online survey from June to October 2020. Logistic regression was conducted for 13 potential factors. Results indicated that only 57% of students were satisfied with their schools' online learning arrangement and 49.6% regarded the online learning as an effective learning mode. Only 12.8% of students preferred online learning, while 67.2% of students preferred in-person schooling. Multiple analyses suggested that teacher-student interaction during online classes was positively associated with students' satisfaction, perceived effectiveness, and preferences in online learning. Compared to grades 1-2 students, grades 3-6 students perceived more effectiveness and would prefer online learning. Happier schools were more likely to deliver satisfying and effective online education. Students who reported less happiness at school would prefer online learning, and students who reported less happiness at home would be less satisfied with online learning and reflected lower effectiveness. Teachers are encouraged to deliver more meaningful interactions to students and offer extra support to younger children during online classes. Primary schools and parents are encouraged to create a healthy and pleasant learning environment for children. The government may consider building up happy schools in the long run. The study findings are instrumental for policymakers, institutions, educators, and researchers in designing online education mechanisms.

Multiple dense particle tracking in fluorescence microscopy images based on multidimensional assignment.

Multiple particle tracking (MPT) has seen numerous applications in live-cell imaging studies of subcellular dynamics. Establishing correspondence between particles in a sequence of frames with high particle density, particles merging and splitting, particles entering and exiting the frame, temporary particle disappearance, and an ill-performing detection algorithm is the most challenging part of MPT. Here we propose a tracking method based on multidimensional assignment to address these problems. We combine an Interacting Multiple Model (IMM) filter, multidimensional assignment, particle occlusion handling, and merge-split event detection in a single software analysis package. The main advantage of a multidimensional assignment is that both spatial and temporal information can be used by using several later frames as reference. The IMM filter, which is used to maintain and predict the state of each track, contains several models which correspond to different types of biologically realistic movements. It works especially well with multidimensional assignment, because there tends to be a higher probability of correct particle association over time. First the method generates many particle-correspondence hypotheses, merge-split hypotheses and misdetection hypotheses within the framework of a sliding window over the frames of the image sequence. Then it builds a multidimensional assignment problem (MAP) accordingly. The particle is tracked with gap-filling, and merging and splitting events are then detected using the MAP solution. The tracking method is validated on both simulated tracks and microscopy image sequences. The results of these experiments show that the method is more accurate and robust than other "tracking from detected features" methods in dense particle situations.