Amorphous Engineering of Scalable Metal-Organic Framework-Derived Electrocatalyst for Highly Efficient Oxygen Evolution Reaction.

The engineering of amorphous metal-organic frameworks (MOFs) offers potential opportunities for the construction of electrocatalysts for efficient oxygen evolution reaction (OER). Herein, highly efficient OER performance and durability in alkaline electrolyte are discovered for MOF-derived amorphous and porous electrocatalysts, which are synthesized in a brief procedure and can be facilely produced in scalable quantities. The structural inheritance of MOF amorphous catalysts is significant for the retention of catalytic sites and the diffusion of electrolytes, and the presence of Fe sites can change the electronic structure and effectively control the adsorption behavior of important intermediates, accelerating reaction kinetics. The obtained amorphous A-FeNi can be transformed from FeNi-MOF effortlessly and instantly, and it only needs low overpotentials of 152 and 232 mV at 10 and 100 mA cm-2 with a Tafel slope of 17 mV dec-1 in 1 m KOH for OER. Moreover, A-FeNi possesses high corrosion resistance and durability, therefore A-FeNi can work continually for at least 400 h at 100 mA cm-2. This work may pave a new avenue for the design of MOFs-related amorphous electrocatalyst.

How do species richness and its component dependence vary along the natural restoration in extremely heterogeneous forest ecosystems?

Giant habitat heterogeneity is an important factor contributing to the high species richness (SR) in karst forests. Yet, the driving factor behind the alterations in SR patterns during natural restoration remains unclear. In this study, we established the forest dynamics plots along the natural restoration sequence (including shrub-tree mixed forest stage (SC), secondary forest stage (SG) and old-growth forest sage (OG)) in degraded karst forests to compare the SR and the dependence on its components (including total community abundance, species abundance distribution (SAD), and conspecific spatial aggregation (CSA)) among stages of natural restoration. By evaluating the degree of contribution of the components to local SR and rarefied SR, we found that the SG exhibited the highest local SR, while the rarefied SR remained increasing along the restoration sequence after controlling the sample size. At SC-SG stage, SAD and CSA contributed negatively to the differences in SR, while abundance made a positive contribution to SR differences. At SG-OG, abundance contributed positively to the difference in SR at all scales, while SAD contributed negatively at small scales. No significant contribution of CSA was found at observed scales. In addition, local SR varied more significantly with PIE than with abundance. Our research emphasizes the importance of eliminating the influence of abundance on species richness in forest ecology and management, as well as the significance of separately evaluating the components that shape the diversity patterns.

Effect of electrolytic zero-valent iron activated sodium hypochlorite on sludge dewatering performance.

Using electrolytic zero-valent iron-activated sodium hypochlorite (EZVI-NaClO) to pretreat sludge, the capillary suction time (CST) was utilized to evaluate sludge dewaterability. Ammonia nitrogen (NH4-N), dissolved phosphorus, and total phosphorus in the supernatant were used to analyze sludge disintegration. This approach aimed to evaluate the effectiveness of the pretreatment process and its impact on the sludge composition. The migration and transformation of extracellular polymeric substances (EPS), including dissolved EPS (S-EPS), loosely boundEPS, and tightly bound-EPS (TB-EPS), were analyzed by detecting protein and polysaccharide concentrations and three-dimensional fluorescence excitation-emission spectroscopy (3D-EEM). The sludge particle properties, including sludge viscosity and particle size, were also analyzed. The results suggested that the optimal pH value, NaClO dosage, current, and reaction time were 2, 100 mg/gDS (dry sludge), 0.2A, and 30 min, respectively, with a CST reduction of 43%. Protein and polysaccharide contents in TB-EPS were significantly reduced in the EZVI-NaClO group. Conversely, protein and polysaccharides contents in S-EPS increased, suggesting that EZVI-NaClO treatment could disrupt the EPS. Besides, the viscosity of the treated sludge decreased from 195.4 to 54.9 mPa·S, indicating that sludge fluidity became better. ZEVI-NaClO could enhance sludge dewaterability by destructing protein and polysaccharide structure and improving sludge hydrophobicity.

Non-Covalently Stapled H+ /Cl- Ion Channels Activatable by Visible Light for Targeted Anticancer Therapy.

The development of stimuli-responsive artificial H+ /Cl- ion channels, capable of specifically disturbing the intracellular ion homeostasis of cancer cells, presents an intriguing opportunity for achieving high selectivity in cancer therapy. Herein, we describe a novel family of non-covalently stapled self-assembled artificial channels activatable by biocompatible visible light at 442 nm, which enables the co-transport of H+ /Cl- across the membrane with H+ /Cl- transport selectivity of 6.0. Upon photoirradiation of the caged C4F-L for 10 min, 90 % of ion transport efficiency can be restored, giving rise to a 10.5-fold enhancement in cytotoxicity against human colorectal cancer cells (IC50 =8.5 µM). The mechanism underlying cancer cell death mediated by the H+ /Cl- channels involves the activation of the caspase 9 apoptosis pathway as well as the scarcely reported disruption of the autophagic processes. In the absence of photoirradiation, C4F-L exhibits minimal toxicity towards normal intestine cells, even at a concentration of 200 µM.

Direct prediction and compensation of atmospheric turbulence for free-space integer and fractional order OAM multiplexed transmission links.

Atmospheric turbulence has an adverse impact on orbital angular momentum (OAM) beam transmission, resulting in power fluctuations and mode crosstalk. These challenges are particularly pronounced in OAM multiplexing links. In this paper, we propose and demonstrate a novel network architecture that integrates convolutional layers and residual structures to address the issue of turbulence phase compensation. By harnessing the local feature learning capability of convolutional layers and the information-preserving function of residual structures, we aim to mitigate the adverse effects of network depth on information loss. By employing the proposed network, we compensate the turbulence phase directly using the received intensity distributions for free space multiplexed integer and fractional order OAM links, respectively. The obtained results show that the received optical power can be improved for more than 10 dB for integer order OAM multiplexed FSO links under weak to strong turbulence conditions, while 9 dB for fractional-order OAM multiplexed FSO links. Moreover, mode crosstalk can be reduced for about 10 dB under 4 OAM modes multiplexed links under turbulence strength D/r0=5. The proposed deep learning based atmospheric turbulence compensation method can predict phase screens rapidly and accurately, thus enhancing the dependability of future OAM multiplexing technology.

Disease burden and attributable risk factors of neonatal disorders and their specific causes in China from 1990 to 2019 and its prediction to 2024.

BACKGROUND: Neonatal health is a cornerstone for the healthy development of the next generation and a driving force for the progress of population and society in the future. Updated information on the burden of neonatal disorders (NDs) are of great importance for evidence-based health care planning in China, whereas such an estimate has been lacking at national level. This study aims to estimate the temporal trends and the attributable burdens of selected risk factors of NDs and their specific causes in China from 1990 to 2019, and to predict the possible trends between 2020 and 2024. METHODS: Data was explored from the Global Burden of Disease study (GBD) 2019. Six measures were used: incidence, mortality, prevalence, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs). Absolute numbers and age-standardized rates (with 95% uncertainty intervals) were calculated. The specific causes of NDs mainly included neonatal preterm birth (NPB), neonatal encephalopathy due to birth asphyxia and trauma (NE), neonatal sepsis and other neonatal infections (NS), and hemolytic disease and other neonatal jaundice (HD). An autoregressive integrated moving average (ARIMA) model was used to forecast disease burden from 2020 to 2024. RESULTS: There were notable decreasing trends in the number of deaths (84.3%), incidence (30.3%), DALYs (73.5%) and YLLs (84.3%), while increasing trends in the number of prevalence (102.3%) and YLDs (172.7%) from 1990 to 2019, respectively. The corresponding age-standardized rates changed by -74.9%, 0.1%, -65.8%, -74.9%, 86.8% and 155.1%, respectively. Four specific causes of NDs followed some similar and different patterns. The prediction results of the ARIMA model shown that all measures still maintained the original trends in the next five years. Low birth weight, short gestation, ambient particulate matter pollution and household air pollution from solid fuels were the four leading risk factors. CONCLUSION: The health burden due to NDs is declining and is likely to continue to decline in the future in China. Delaying the increasing burden of disability may be the next target of concern. Targeted prevention and control strategies for specific causes of NDs are urgently needed to reduce the disease burden.

The impact of metabolic diseases and their comorbidities for stroke in a middle-income area of China: a case-control study.

BACKGROUND: There are few studies on the comorbidity of hypertension (HTN), diabetes mellitus (DM) and dyslipidemia (DLP) associated with stroke. We aimed to explore the relationship between the number of metabolic diseases and stroke and its different subtypes, and to reveal whether metabolic diseases alone or coexist can significantly increase the risk of stroke. METHODS: We completed a multi-center case-control study in Jiangxi Province, China. Neuroimaging examination was done in all cases. Controls were stroke-free adults recruited from the community in the case concentration area and matched with the cases in 1:1 ratio by age and sex. Odds ratios (OR) were calculated by conditional logistic regression. RESULTS: We enrolled 11,729 case-control pairs. The estimated ORs among patients with 1, 2 and 3 metabolic diseases were 3.16 (2.78-3.60), 7.11 (6.16-8.20), 12.22 (9.73-15.36), respectively after adjusting age, body mass index, urban-rural areas, cardiac disease, smoking, alcohol intake, physically active, high intake of salt, meat-biased diet, high homocysteine. The coexistence of HTN and DM (OR: 7.67), the coexistence of HTN and DLP (OR:7.58), and the coexistence of DM and DLP (OR:3.64) can all significantly increase the risk of stroke. HTN alone or combined other metabolic diseases were significantly more strongly associated with intracerebral haemorrhage than ischemic stroke. CONCLUSIONS: The risk of stroke increased with the number of chronic metabolic diseases. It is necessary to regularly monitor blood pressure, blood sugar and blood lipids and strengthen lifestyle management and take appropriate drug interventions to prevent exposure to multiple metabolic diseases based on existing conditions.

MS/MS molecular networking-guided in-depth profiling of triterpenoid saponins from the fruit of Eleutherococcus senticosus and their neuroprotectivity evaluation.

INTRODUCTION: Eleutherococcus senticosus fruit (ESF) is a natural health supplement resource that has been extensively applied as a tonic for the nervous system. The structures and neural bioactivities of triterpenoid saponins (TS), which are the major constituents of ESF, have not been comprehensively analyzed thus far. OBJECTIVE: We conducted a complete in-depth MS/MS molecular networking (MN)-based targeted analysis of TS from the crude extract of ESF and investigated its neuroprotective value. METHODS: An MS/MS MN-guided strategy was used to rapidly present a series of precursor ions (PIs) of TS in a compound cluster as TS-targeted information used in the discovery and characterization of TS. In addition, a prepared TS-rich fraction of ESF was assayed for its restraining effects on ß-amyloid-induced inhibition of neurite outgrowth. RESULTS: A total of 87 TS were discovered using a PI tracking strategy, 28 of which were characterized as potentially undescribed structures according to their high-resolution MS values. Furthermore, the TS-rich fraction can significantly reduce ß-amyloid-induced damage to neural networks by promoting the outgrowth of neurites and axons. CONCLUSION: Our findings reveal the richness of TS in ESF and will accelerate their application in the treatment of neurodegenerative diseases.

Development and Validation of a Double-Sensor Hump Calibration Method for Articulated Vehicle Model Identification.

The realistic simulation of the dynamic responses of a moving articulated vehicle has attracted considerable attention in various disciplines, with the identification of the vehicle model being the prerequisite. To this end, a double-sensor hump calibration method (DHCM) was developed to identify both unladen and laden vehicle models, consisting of a sensor layout optimization step and a system identification step. The first step was to optimize the number and position of sensors via parameter sensitivity analysis; the second was to inversely identify the vehicle system based on sensor responses. For comparison, the DHCM and the existing single-sensor hump calibration method (SHCM) were used to calibrate a small-sized vehicle model and a multi-axle articulated vehicle model. Vertical accelerations of the vehicle models were then simulated and characterized by power spectral densities (PSDs). Validation against experimental measurements indicated that the PSDs of the models identified with the DHCM matched the measured PSDs better than those of the SHCM, i.e., the DHCM-identified model accurately simulated the dynamic response of an articulated vehicle with relative errors below 16% in the low-frequency range. Therefore, the DHCM could identify models of small-sized vehicles and multi-axle articulated vehicles, while the SHCM was only suitable for the former.

A Highly Expressed Antennae Odorant-Binding Protein Involved in Recognition of Herbivore-Induced Plant Volatiles in Dastarcus helophoroides.

Natural enemies such as parasitoids and parasites depend on sensitive olfactory to search for their specific hosts. Herbivore-induced plant volatiles (HIPVs) are vital components in providing host information for many natural enemies of herbivores. However, the olfactory-related proteins involved in the recognition of HIPVs are rarely reported. In this study, we established an exhaustive tissue and developmental expression profile of odorant-binding proteins (OBPs) from Dastarcus helophoroides, an essential natural enemy in the forestry ecosystem. Twenty DhelOBPs displayed various expression patterns in different organs and adult physiological states, suggesting a potential involvement in olfactory perception. In silico AlphaFold2-based modeling and molecular docking showed similar binding energies between six DhelOBPs (DhelOBP4, 5, 6, 14, 18, and 20) and HIPVs from Pinus massoniana. While in vitro fluorescence competitive binding assays showed only recombinant DhelOBP4, the most highly expressed in the antennae of emerging adults could bind to HIPVs with high binding affinities. RNAi-mediated behavioral assays indicated that DhelOBP4 was an essential functional protein for D. helophoroides adults recognizing two behaviorally attractive substances: p-cymene and γ-terpinene. Further binding conformation analyses revealed that Phe 54, Val 56, and Phe 71 might be the key binding sites for DhelOBP4 interacting with HIPVs. In conclusion, our results provide an essential molecular basis for the olfactory perception of D. helophoroides and reliable evidence for recognizing the HIPVs of natural enemies from insect OBPs' perspective.

Global, regional, and national time trends in incidence for migraine, from 1990 to 2019: an age-period-cohort analysis for the GBD 2019.

BACKGROUND: The majority of epidemiological studies on migraine have been conducted in a specific country or region, and there is a lack of globally comparable data. We aim to report the latest information on global migraine incidence overview trends from 1990 to 2019. METHODS: In this study, the available data were obtained from the Global Burden of Disease 2019. We present temporal trends in migraine for the world and its 204 countries and territories over the past 30 years. Meanwhile, an age-period-cohort model be used to estimate net drifts (overall annual percentage change), local drifts (annual percentage change in each age group), longitudinal age curves (expected longitudinal age-specific rate), and period (cohort) relative risks. RESULTS: In 2019, the global incidence of migraine increased to 87.6 million (95% UI: 76.6, 98.7), with an increase of 40.1% compared to 1990. India, China, United States of America, and Indonesia had the highest number of incidences, accounting for 43.6% of incidences globally. Females experienced a higher incidence than males, the highest incidence rate was observed in the 10-14 age group. However, there was a gradual transition in the age distribution of incidence from teenagers to middle-aged populations. The net drift of incidence rate ranged from 3.45% (95% CI: 2.38, 4.54) in high-middle Socio-demographic Index (SDI) regions to -4.02% (95% CI: -4.79, -3.18) in low SDI regions, 9 of 204 countries showed increasing trends (net drifts and its 95% CI were > 0) in incidence rate. The age-period-cohort analysis results showed that the relative risk of incidence rate generally showed unfavorable trends over time and in successively birth cohorts among high-, high-middle-, and middle SDI regions, but low-middle- and low-SDI regions keep stable. CONCLUSIONS: Migraine is still an important contributor to the global burden of neurological disorders worldwide. Temporal trends in migraine incidence are not commensurate with socioeconomic development and vary widely across countries. Both sexes and all age groups should get healthcare to address the growing migraine population, especially adolescents and females.

Multimode nonlinear dynamics in spatiotemporal mode-locked anomalous-dispersion lasers.

Spatiotemporal mode-locking in a laser with anomalous dispersion is investigated. Mode-locked states with varying modal content can be observed, but we find it difficult to observe highly-multimode states. We describe the properties of these mode-locked states and compare them to the results of numerical simulations. Prospects for the generation of highly-multimode states and lasers based on multimode soliton formation are discussed.

Single-cell transcriptome study in forensic medicine: prospective applications.

Next-generation sequencing and single-cell RNA sequencing (scRNA-seq) technologies have advanced rapidly in recent years. scRNA-seq reveals the unique gene expression of each cell type, providing directions for exploring cell heterogeneity, cell type-specific responses to injury/disease, and the mechanisms underlying these processes. The development of sequencing technology and improved sequencing throughput have brought about a revolution in single-cell transcriptome study, bringing great benefits to the fields of medicine and biomedical science. From our perspective, certain issues in forensic medicine may potentially be addressed using single-cell transcriptome studies; however, this powerful technique has not yet attracted sufficient attention in forensic medicine-associated research. Therefore, examining and reviewing the latest developments and applications of single-cell transcriptome studies, we present our views on the future directions of forensic research using this technology, aiming to expand the frontiers of forensic science.

Design and synthesis of Osthole-based compounds as potential Nrf2 agonists.

A total of 23 compounds based on Osthole skeleton were designed and synthesized. Their agonistic activity for Nrf2 were evaluated by Dual-luciferase Reporter Gene Assay. Most of the compounds showed better activities compared with Osthole, especially O15 and O21. And the median effective concerntration (EC50) values was calculated accordingly, both of which showed remarkable activity for Nrf2. The structure activity relationship study indicated that introduction of the structure of stilbene might be beneficial for enhancement of agonistic properties of Osthole, and the position of the substituent may have a greater effect on the activity than the electron-donating/withdrawing ability of the substituent. Mechanism of the action of selected compound O15 was investigated by molecular docking, cellular thermal shift assay and ubiquitination assay, which suggested the reason why O15 exhibited relatively stronger agonistic activity for Nrf2. Compound O15 and O21 both provided novel methods to investigate Osthole-based compounds as Nrf2 agonists.

Design, synthesis and biological evaluation of acyl hydrazones-based derivatives as RXRα-targeted anti-mitotic agents.

RXRα, a unique and important nuclear receptor, plays a vital role in various biological and pathological pathways, including growth, differentiation, and apoptosis. We recently reported a transcription-independent function of RXRα in cancer cells in which RXRα is phosphorylated by Cdk1 at the onset of mitosis, resulting in its translocation to the centrosome, where the phosphorylated RXRα (p-RXRα) interacts with polo-like kinase 1 (PLK1) to promote centrosome maturation and mitotic progression. Significantly, we also identified that a small molecule XS-060 binds to RXRα and selectively inhibits the p-RXRα/PLK1 interaction to induce mitotic arrest and catastrophe in cancer cells. Here, we report our design, synthesis, and biological evaluation of a series of XS-060 analogs as RXRα-targeted anti-mitotic agents. Our results identified B10 as an improved anti-mitotic agent. B10 bound to RXRα (Kd = 3.04 ± 0.58 µM) and inhibited the growth of cervical cancer cells (HeLa, IC50 = 1.46 ± 0.10 µM) and hepatoma cells (HepG2, IC50 = 3.89 ± 0.45 µM and SK-hep-1, IC50 = 5.74 ± 0.50 µM) with low cytotoxicity to nonmalignant cells(LO2, IC50 > 50 µM). Furthermore, our mechanistic studies confirmed that B10 acted as an anticancer agent by inhibiting the p-RXRα/PLK1 pathway. These results provide a basis for further investigation and optimization of RXRα-targeted anti-mitotic molecules for cancer therapy.

2D shape reconstruction of irregular particles with deep learning based on interferometric particle imaging.

Interferometric particle imaging (IPI) technology is widely used in the measurement of various particles. Obtaining particle shape information directly by IPI is challenging because of the complex relationship between the speckle distribution of interference-defocused speckle patterns and the shape of the corresponding irregular particles. Considering this challenge, we implement a deep learning method based on the convolutional neural network (CNN) to reconstruct defocused images of sand particles with sparse features. We also introduce the negative Pearson correlation coefficient as the loss function. To verify the feasibility of our method, we implemented it to reconstruct defocused images obtained from IPI experiments. Finally, compared with another common CNN-based structure, we confirmed that our network structure has good performance in the shape reconstruction of irregular particles.

Population attributable fractions for risk factors and disability burden of dementia in Jiangxi Province, China: a cross-sectional study.

BACKGROUND: In view of the fact that there is no effective treatment for dementia, the number of years that dementia patients have to live with dementia will gradually increase for the rest of their lives, and the disability loss caused by dementia will increase. It is urgent to study the influence of risk factors on dementia by making use of the potential of prevention. The purpose of this study is to quantify the burden of dementia disability attributable to risk factors by assessing the population attributable fractions (PAFs) in Jiangxi Province, which is one of the regions of moderate aging process of China. METHODS: The prevalence data of nine risk factors were obtained through the Sixth National Health Service Survey in 2018, which covered 2713 older people. Levin's formula was used to calculate the PAF for each risk factor for dementia. We adjusted the PAF for communality between risk factors, and used these values to calculate overall weighted PAFs and the years lived with disability (YLDs), which were attributable to nine risk factors. RESULTS: The number of dementia cases and their proportions that can theoretically be prevented by nine identified risk factors were 111636 (99595-120877) and 66.8% (59.6-72.3), respectively. The total YLDs of dementia were estimated to be 61136 (46463-78369) (males: 36434 [24100-49330], females: 23956 [14716-34589]). Physical inactivity (11639 [8845-14920]), low social contact (9324 [7086-11952]), and hearing loss (5668 [4307-7265] were the top three contributors to dementia. CONCLUSIONS: The moderate aging areas represented by Jiangxi Province have great potential in the prevention of dementia. Targeted interventions and management of risk factors can effectively reduce the disability burden of dementia.

Association of long-term effects of low-level sulfamethoxazole with ovarian lipid and amino acid metabolism, sex hormone levels, and oocyte maturity in zebrafish.

Sulfamethoxazole (SMZ) is an important antibiotic used to prevent and treat infections in both clinical settings and animal husbandry. High levels of SMZ may exhibit endocrine toxicity. Environmental SMZ enters the human body via food and water; however, the toxicity of environmental doses of SMZ and its effects on reproductive health are unknown. In the present study, zebrafish were exposed to low concentrations of SMZ (1000 and 5000 ng/L) from 2 h post-fertilization to 120 d post-fertilization. Consequently, the proportion of mature oocytes in adult female zebrafish ovarian tissue increased by 98.2 %, indicating that SMZ promotes ovarian maturation. Metabolomics analysis revealed significant changes in ovarian lipid and amino acid levels after SMZ treatment. An enzyme-linked immunoassay used to detect sex hormones in the ovaries showed that SMZ exposure significantly increased the levels of estradiol, a follicle-stimulating hormone, and of luteinizing hormone. Furthermore, an association analysis showed that most of the differentially expressed metabolites in the ovary were strongly correlated with the levels of sex hormones secreted by the pituitary gland. Therefore, significantly increased transcript levels of gonadotropin-releasing hormone (GnRH) and follicle-stimulating hormone detected in brain tissue suggested that SMZ may exhibit ovarian toxicity via the hypothalamus. In vitro experiments were performed to demonstrate that SMZ targets neurons in the hypothalamus. Exposure to SMZ significantly increased the GnRH content in GnRH neurons. Finally, molecular docking simulations indicated the potential interaction of SMZ with G protein-coupled receptor 54; this molecular binding can activate, synthesize, and release GnRH in neurons. In conclusion, long-term environmental exposure to SMZ may induce ovarian toxicity by affecting the hypothalamus-pituitary-gonad axis.

The psychological impact of COVID-19 outbreak on medical staff and the general public.

To assess the psychological effects of the novel coronavirus disease (COVID-19) on medical staff and the general public. During the outbreak of COVID-19, an internet-based questionnaire included The Self-rating Depression Scale (SDS), Perceived Stress Scale (PSS-10), and Impact of Event Scale-Revised (IES-R) was used to assess the impact of the pandemic situation on the mental health of medical staff and general population in Wuhan and its surrounding areas. Among the 1493 questionnaires completed, 827 (55.39%) of these were men, and 422 (28.27%) of these were medical personnel. The results suggest that the outbreak of COVID-19 has affected individuals significantly, the degree of which is related to age, sex, occupation and mental illness. There was a significant difference in PSS-10 and IES-R scores between the medical staff and the general population. The medical staff showed higher PSS-10 scores (16.813 ± 4.87) and IES-R scores (22.40 ± 12.12) compared to members of the general population PSS-10 (14.80 ± 5.60) and IES-R scores (17.89 ± 13.08). However, there was no statistically significant difference between the SDS scores of medical staff (44.52 ± 12.36) and the general public (43.08 ± 11.42). In terms of the need for psychological assistance, 50.97% of interviewees responded that they needed psychological counseling, of which medical staff accounted for 65.87% and non-medical staff accounted for 45.10%. During the ongoing COVID-19 outbreak, great attention should be paid to the mental health of the population, especially medical staff, and measures such as psychological intervention should be actively carried out for reducing the psychosocial effects.

Confined Chemical Transitions for Direct Extraction of Conductive Cellulose Nanofibers with Graphitized Carbon Shell at Low Temperature and Pressure.

Cellulose is the most abundant renewable natural polymer on earth, but it does not conduct electricity, which limits its application expansion. The existing methods of making cellulose conductive are combined with another conductive material or high-temperature/high-pressure carbonization of the cellulose itself, while in the traditional method of sulfuric acid hydrolysis to extract nanocellulose, it is usually believed that a too high temperature will destroy cellulose and lead to experimental failure. Now, based on a new research perspective, by controlling the continuous reaction process and isolating oxygen, we directly extracted intrinsically conductive cellulose nanofiber (CNF) from biomass, where the confined range molecular chains of CNF were converted to highly graphitized carbon at only 90 °C and atmospheric pressure, while large-scale twisted graphene films can be synthesized bottom-up from CNFene suspensions, called CNFene (cellulose nanofiber-graphene). The conductivity of the best CNFene can be as high as 1.099 S/cm, and the generality of this synthetic route has been verified from multiple biomass cellulose sources. By comparing the conventional high-pressure hydrothermal and high-temperature pyrolysis methods, this study avoided the dangerous high-pressure environment and saved 86.16% in energy. These findings break through the conventional notion that nanocellulose cannot conduct electricity by itself and are expected to extend the application potential of pure nanocellulose to energy storage, catalysis, and sensing.