Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China

BACKGROUND

Studies have reminded that cardiovascular metabolic comorbidities made patients more susceptible to suffer 2019 novel corona virus (2019-nCoV) disease (COVID-19), and exacerbated the infection. The aim of this analysis is to determine the association of cardiovascular metabolic diseases with the development of COVID-19.

METHODS

A meta-analysis of eligible studies that summarized the prevalence of cardiovascular metabolic diseases in COVID-19 and compared the incidences of the comorbidities in ICU/severe and non-ICU/severe patients was performed. Embase and PubMed were searched for relevant studies.

RESULTS

A total of six studies with 1527 patients were included in this analysis. The proportions of hypertension, cardia-cerebrovascular disease and diabetes in patients with COVID-19 were 17.1%, 16.4% and 9.7%, respectively. The incidences of hypertension, cardia-cerebrovascular diseases and diabetes were about twofolds, threefolds and twofolds, respectively, higher in ICU/severe cases than in their non-ICU/severe counterparts. At least 8.0% patients with COVID-19 suffered the acute cardiac injury. The incidence of acute cardiac injury was about 13 folds higher in ICU/severe patients compared with the non-ICU/severe patients.

CONCLUSION

Patients with previous cardiovascular metabolic diseases may face a greater risk of developing into the severe condition and the comorbidities can also greatly affect the prognosis of the COVID-19. On the other hand, COVID-19 can, in turn, aggravate the damage to the heart.

Characteristics and clinical significance of myocardial injury in patients with severe coronavirus disease 2019

AIMS

To investigate the characteristics and clinical significance of myocardial injury in patients with severe coronavirus disease 2019 (COVID-19).

METHODS AND RESULTS

We enrolled 671 eligible hospitalized patients with severe COVID-19 from 1 January to 23 February 2020, with a median age of 63 years. Clinical, laboratory, and treatment data were collected and compared between patients who died and survivors. Risk factors of death and myocardial injury were analysed using multivariable regression models. A total of 62 patients (9.2%) died, who more often had myocardial injury (75.8% vs. 9.7%; P < 0.001) than survivors. The area under the receiver operating characteristic curve of initial cardiac troponin I (cTnI) for predicting in-hospital mortality was 0.92 [95% confidence interval (CI), 0.87-0.96; sensitivity, 0.86; specificity, 0.86; P < 0.001]. The single cut-off point and high level of cTnI predicted risk of in-hospital death, hazard ratio (HR) was 4.56 (95% CI, 1.28-16.28; P = 0.019) and 1.25 (95% CI, 1.07-1.46; P = 0.004), respectively. In multivariable logistic regression, senior age, comorbidities (e.g. hypertension, coronary heart disease, chronic renal failure, and chronic obstructive pulmonary disease), and high level of C-reactive protein were predictors of myocardial injury.

CONCLUSION

The risk of in-hospital death among patients with severe COVID-19 can be predicted by markers of myocardial injury, and was significantly associated with senior age, inflammatory response, and cardiovascular comorbidities.

The genetic sequence, origin, and diagnosis of SARS-CoV-2

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a new infectious disease that first emerged in Hubei province, China, in December 2019, which was found to be associated with a large seafood and animal market in Wuhan. Airway epithelial cells from infected patients were used to isolate a novel coronavirus, named the SARS-CoV-2, on January 12, 2020, which is the seventh member of the coronavirus family to infect humans. Phylogenetic analysis of full-length genome sequences obtained from infected patients showed that SARS-CoV-2 is similar to severe acute respiratory syndrome coronavirus (SARS-CoV) and uses the same cell entry receptor, angiotensin-converting enzyme 2 (ACE2), as SARS-CoV. The possible person-to-person disease rapidly spread to many provinces in China as well as other countries. Without a therapeutic vaccine or specific antiviral drugs, early detection and isolation become essential against novel Coronavirus. In this review, we introduced current diagnostic methods and criteria for the SARS-CoV-2 in China and discuss the advantages and limitations of the current diagnostic methods, including chest imaging and laboratory detection.

SEIR modeling of the COVID-19 and its dynamics

In this paper, a SEIR epidemic model for the COVID-19 is built according to some general control strategies, such as hospital, quarantine and external input. Based on the data of Hubei province, the particle swarm optimization (PSO) algorithm is applied to estimate the parameters of the system. We found that the parameters of the proposed SEIR model are different for different scenarios. Then, the model is employed to show the evolution of the epidemic in Hubei province, which shows that it can be used to forecast COVID-19 epidemic situation. Moreover, by introducing the seasonality and stochastic infection the parameters, nonlinear dynamics including chaos are found in the system. Finally, we discussed the control strategies of the COVID-19 based on the structure and parameters of the proposed model.

Tumor-Microenvironment-Responsive Nanomedicine for Enhanced Cancer Immunotherapy

The past decades have witnessed great progress in cancer immunotherapy, which has profoundly revolutionized oncology, whereas low patient response rates and potential immune-related adverse events remain major clinical challenges. With the advantages of controlled delivery and modular flexibility, cancer nanomedicine has offered opportunities to strengthen antitumor immune responses and to sensitize tumor to immunotherapy. Furthermore, tumor-microenvironment (TME)-responsive nanomedicine has been demonstrated to achieve specific and localized amplification of the immune response in tumor tissue in a safe and effective manner, increasing patient response rates to immunotherapy and reducing the immune-related side effects simultaneously. Here, the recent progress of TME-responsive nanomedicine for cancer immunotherapy is summarized, which responds to the signals in the TME, such as weak acidity, reductive environment, high-level reactive oxygen species, hypoxia, overexpressed enzymes, and high-level adenosine triphosphate. Moreover, the potential to combine nanomedicine-based therapy and immunotherapeutic strategies to overcome each step of the cancer-immunity cycle and to enhance antitumor effects is discussed. Finally, existing challenges and further perspectives in this rising field with the hope for improved development of clinical applications are discussed.

EIN3-LIKE1, MYB1, and ETHYLENE RESPONSE FACTOR3 Act in a Regulatory Loop That Synergistically Modulates Ethylene Biosynthesis and Anthocyanin Accumulation

Ethylene regulates climacteric fruit ripening, and EIN3-LIKE1 (EIL1) plays an important role in this process. In apple (Malus domestica), fruit coloration is accompanied by ethylene release during fruit ripening, but the molecular mechanism that underlies these two physiological processes is unknown. In this study, we found that ethylene treatment markedly induced fruit coloration as well as the expression of MdMYB1, a positive regulator of anthocyanin biosynthesis and fruit coloration. In addition, we found that MdEIL1 directly bound to the promoter of MdMYB1 and transcriptionally activated its expression, which resulted in anthocyanin biosynthesis and fruit coloration. Furthermore, MdMYB1 interacted with the promoter of ETHYLENE RESPONSE FACTOR3, a key regulator of ethylene biosynthesis, thereby providing a positive feedback for ethylene biosynthesis regulation. Overall, our findings provide insight into a mechanism involving the synergistic interaction of the ethylene signal with the MdMYB1 transcription factor to regulate ethylene biosynthesis and fruit coloration in apple.

Topological liquid diode

The last two decades have witnessed an explosion of interest in the field of droplet-based microfluidics for their multifarious applications. Despite rapid innovations in strategies to generate small-scale liquid transport on these devices, the speed of motion is usually slow, the transport distance is limited, and the flow direction is not well controlled because of unwanted pinning of contact lines by defects on the surface. We report a new method of microscopic liquid transport based on a unique topological structure. This method breaks the contact line pinning through efficient conversion of excess surface energy to kinetic energy at the advancing edge of the droplet while simultaneously arresting the reverse motion of the droplet via strong pinning. This results in a novel topological fluid diode that allows for a rapid, directional, and long-distance transport of virtually any kind of liquid without the need for an external energy input.

A pyrolysis-free path toward superiorly catalytic nitrogen-coordinated single atom

Nitrogen-coordinated single-atom catalysts (SACs) have emerged as a frontier for electrocatalysis (such as oxygen reduction) with maximized atom utilization and highly catalytic activity. The precise design and operable synthesis of SACs are vital for practical applications but remain challenging because the commonly used high-temperature treatments always result in unpredictable structural changes and randomly created single atoms. Here, we develop a pyrolysis-free synthetic approach to prepare SACs with a high electrocatalytic activity using a fully π-conjugated iron phthalocyanine (FePc)-rich covalent organic framework (COF). Instead of randomly creating Fe-nitrogen moieties on a carbon matrix (Fe-N-C) through pyrolysis, we rivet the atomically well-designed Fe-N-C centers via intermolecular interactions between the COF network and the graphene matrix. The as-synthesized catalysts demonstrate exceptional kinetic current density in oxygen reduction catalysis (four times higher than the benchmark Pt/C) and superior power density and cycling stability in Zn-air batteries compared with Pt/C as air electrodes.

Antibacterial activity of silver nanoparticles of different particle size against Vibrio Natriegens

In this study, we describe the synthesis and characterization of silver nanoparticles (Ag-NPs) of different sizes and evaluated their antibacterial activity. Particles size and morphology were characterized by transmission electron microscopy. Evaluation of the bacteriostatic effects was performed by ultraviolet-visible spectrophotometry and comet assays. The smaller the particle size of Ag-NPs, the smaller the value of the minimum inhibitory concentration (MIC) and minimum bactericidal concentrations (MBC), indicating the greater the antibacterial activity. The antibacterial activity was determined by the generation of reactive oxygen species (ROS) by bacteria and by bacterial membrane damage. In this study, we determined ROS-induced damage of bacteria caused by Ag-NPs. In conclusion, our findings indicated that Ag-NPs were effective at different particle sizes and concentrations and that the smaller the particle size of Ag-NPs, the greater the antibacterial activity.

Nanomaterials with Supramolecular Assembly Based on AIE Luminogens for Theranostic Applications

One of the major pursuits of biomedical science is to develop advanced strategies for theranostics, which is expected to be an effective approach for achieving the transition from conventional medicine to precision medicine. Supramolecular assembly can serve as a powerful tool in the development of nanotheranostics with accurate imaging of tumors and real-time monitoring of the therapeutic process upon the incorporation of aggregation-induced emission (AIE) ability. AIE luminogens (AIEgens) will not only enable fluorescence imaging but will also aid in improving the efficacy of therapies. Furthermore, the fluorescent signals and therapeutic performance of these nanomaterials can be manipulated precisely owing to the reversible and stimuli-responsive characteristics of the supramolecular systems. Inspired by rapid advances in this field, recent research conducted on nanotheranostics with the AIE effect based on supramolecular assembly is summarized. Here, three representative strategies for supramolecular nanomaterials are presented as follows: a) supramolecular self-assembly of AIEgens, b) the loading of AIEgens within nanocarriers with supramolecular assembly, and c) supramolecular macrocycle-guided assembly via host-guest interactions. Meanwhile, the diverse applications of such nanomaterials in diagnostics and therapeutics have also been discussed in detail. Finally, the challenges of this field are listed in this review.

Tumor Energy Metabolism and Potential of 3-Bromopyruvate as an Inhibitor of Aerobic Glycolysis: Implications in Tumor Treatment

Tumor formation and growth depend on various biological metabolism processes that are distinctly different with normal tissues. Abnormal energy metabolism is one of the typical characteristics of tumors. It has been proven that most tumor cells highly rely on aerobic glycolysis to obtain energy rather than mitochondrial oxidative phosphorylation (OXPHOS) even in the presence of oxygen, a phenomenon called "Warburg effect". Thus, inhibition of aerobic glycolysis becomes an attractive strategy to specifically kill tumor cells, while normal cells remain unaffected. In recent years, a small molecule alkylating agent, 3-bromopyruvate (3-BrPA), being an effective glycolytic inhibitor, has shown great potential as a promising antitumor drug. Not only it targets glycolysis process, but also inhibits mitochondrial OXPHOS in tumor cells. Excellent antitumor effects of 3-BrPA were observed in cultured cells and tumor-bearing animal models. In this review, we described the energy metabolic pathways of tumor cells, mechanism of action and cellular targets of 3-BrPA, antitumor effects, and the underlying mechanism of 3-BrPA alone or in combination with other antitumor drugs (e.g., cisplatin, doxorubicin, daunorubicin, 5-fluorouracil, etc.) in vitro and in vivo. In addition, few human case studies of 3-BrPA were also involved. Finally, the novel chemotherapeutic strategies of 3-BrPA, including wafer, liposomal nanoparticle, aerosol, and conjugate formulations, were also discussed for future clinical application.

Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data

BACKGROUND

Above-ground biomass (AGB) is a basic agronomic parameter for field investigation and is frequently used to indicate crop growth status, the effects of agricultural management practices, and the ability to sequester carbon above and below ground. The conventional way to obtain AGB is to use destructive sampling methods that require manual harvesting of crops, weighing, and recording, which makes large-area, long-term measurements challenging and time consuming. However, with the diversity of platforms and sensors and the improvements in spatial and spectral resolution, remote sensing is now regarded as the best technical means for monitoring and estimating AGB over large areas.

RESULTS

In this study, we used structural and spectral information provided by remote sensing from an unmanned aerial vehicle (UAV) in combination with machine learning to estimate maize biomass. Of the 14 predictor variables, six were selected to create a model by using a recursive feature elimination algorithm. Four machine-learning regression algorithms (multiple linear regression, support vector machine, artificial neural network, and random forest) were evaluated and compared to create a suitable model, following which we tested whether the two sampling methods influence the training model. To estimate the AGB of maize, we propose an improved method for extracting plant height from UAV images and a volumetric indicator (i.e., BIOVP). The results show that (1) the random forest model gave the most balanced results, with low error and a high ratio of the explained variance for both the training set and the test set. (2) BIOVP can retain the largest strength effect on the AGB estimate in four different machine learning models by using importance analysis of predictors. (3) Comparing the plant heights calculated by the three methods with manual ground-based measurements shows that the proposed method increased the ratio of the explained variance and reduced errors.

CONCLUSIONS

These results lead us to conclude that the combination of machine learning with UAV remote sensing is a promising alternative for estimating AGB. This work suggests that structural and spectral information can be considered simultaneously rather than separately when estimating biophysical crop parameters.

SMARTdenovo: a de novo assembler using long noisy reads

Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. It has also been widely used to study structural variants, phase haplotypes and more. Here, we introduce the assembler SMARTdenovo, a single-molecule sequencing (SMS) assembler that follows the overlap-layout-consensus (OLC) paradigm. SMARTdenovo (RRID: SCR_017622) was designed to be a rapid assembler, which, unlike contemporaneous SMS assemblers, does not require highly accurate raw reads for error correction. It has performed well in the evaluation of congeneric assemblers and has been successfully users for various assembly projects. It is compatible with Canu for assembling high-quality genomes, and several of the assembly strategies in this program have been incorporated into subsequent popular assemblers. The assembler has been in use since 2015; here we provide information on the development of SMARTdenovo and how to implement its algorithms into current projects.

Electrospun Nanofibers for Tissue Engineering with Drug Loading and Release

Electrospinning technologies have been applied in the field of tissue engineering as materials, with nanoscale-structures and high porosity, can be easily prepared via this method to bio-mimic the natural extracellular matrix (ECM). Tissue engineering aims to fabricate functional biomaterials for the repairment and regeneration of defective tissue. In addition to the structural simulation for accelerating the repair process and achieving a high-quality regeneration, the combination of biomaterials and bioactive molecules is required for an ideal tissue-engineering scaffold. Due to the diversity in materials and method selection for electrospinning, a great flexibility in drug delivery systems can be achieved. Various drugs including antibiotic agents, vitamins, peptides, and proteins can be incorporated into electrospun scaffolds using different electrospinning techniques and drug-loading methods. This is a review of recent research on electrospun nanofibrous scaffolds for tissue-engineering applications, the development of preparation methods, and the delivery of various bioactive molecules. These studies are based on the fabrication of electrospun biomaterials for the repair of blood vessels, nerve tissues, cartilage, bone defects, and the treatment of aneurysms and skin wounds, as well as their applications related to oral mucosa and dental fields. In these studies, due to the optimal selection of drugs and loading methods based on electrospinning, in vitro and in vivo experiments demonstrated that these scaffolds exhibited desirable effects for the repair and treatment of damaged tissue and, thus, have excellent potential for clinical application.

Coronavirus disease 2019: initial chest CT findings

OBJECTIVES

To systematically analyze CT findings during the early and progressive stages of natural course of coronavirus disease 2019 and also to explore possible changes in pulmonary parenchymal abnormalities during these two stages.

METHODS

We retrospectively reviewed the initial chest CT data of 62 confirmed coronavirus disease 2019 patients (34 men, 28 women; age range 20-91 years old) who did not receive any antiviral treatment between January 21 and February 4, 2020, in Chongqing, China. Patients were assigned to the early-stage group (onset of symptoms within 4 days) or progressive-stage group (onset of symptoms within 4-7 days) for analysis. CT characteristics and the distribution, size, and CT score of pulmonary parenchymal abnormalities were assessed.

RESULTS

In our study, the major characteristic of coronavirus disease 2019 was ground-glass opacity (61.3%), followed by ground-glass opacity with consolidation (35.5%), rounded opacities (25.8%), a crazy-paving pattern (25.8%), and an air bronchogram (22.6%). No patient presented cavitation, a reticular pattern, or bronchial wall thickening. The CT scores of the progressive-stage group were significantly greater than those of the early-stage group (p = 0.004).

CONCLUSIONS

Multiple ground-glass opacities with consolidations in the periphery of the lungs were the primary CT characteristic of coronavirus disease 2019. CT score can be used to evaluate the severity of the disease. If these typical alterations are found, then the differential diagnosis of coronavirus disease 2019 must be considered.

KEY POINTS

• Multiple GGOs with consolidations in the periphery of the lungs were the primary CT characteristic of COVID-19. • The halo sign may be a special CT feature in the early-stage COVID-19 patients. • Significantly increased CT score may indicate the aggravation of COVID-19 in the progressive stage.

A recessive allele for delayed flowering at the soybean maturity locus E9 is a leaky allele of FT2a, a FLOWERING LOCUS T ortholog

BACKGROUND

Understanding the molecular mechanisms of flowering and maturity is important for improving the adaptability and yield of seed crops in different environments. In soybean, a facultative short-day plant, genetic variation at four maturity genes, E1 to E4, plays an important role in adaptation to environments with different photoperiods. However, the molecular basis of natural variation in time to flowering and maturity is poorly understood. Using a cross between early-maturing soybean cultivars, we performed a genetic and molecular study of flowering genes. The progeny of this cross segregated for two maturity loci, E1 and E9. The latter locus was subjected to detailed molecular analysis to identify the responsible gene.

RESULTS

Fine mapping, sequencing, and expression analysis revealed that E9 is FT2a, an ortholog of Arabidopsis FLOWERING LOCUS T. Regardless of daylength conditions, the e9 allele was transcribed at a very low level in comparison with the E9 allele and delayed flowering. Despite identical coding sequences, a number of single nucleotide polymorphisms and insertions/deletions were detected in the promoter, untranslated regions, and introns between the two cultivars. Furthermore, the e9 allele had a Ty1/copia-like retrotransposon, SORE-1, inserted in the first intron. Comparison of the expression levels of different alleles among near-isogenic lines and photoperiod-insensitive cultivars indicated that the SORE-1 insertion attenuated FT2a expression by its allele-specific transcriptional repression. SORE-1 was highly methylated, and did not appear to disrupt FT2a RNA processing.

CONCLUSIONS

The soybean maturity gene E9 is FT2a, and its recessive allele delays flowering because of lower transcript abundance that is caused by allele-specific transcriptional repression due to the insertion of SORE-1. The FT2a transcript abundance is thus directly associated with the variation in flowering time in soybean. The e9 allele may maintain vegetative growth in early-flowering genetic backgrounds, and also be useful as a long-juvenile allele, which causes late flowering under short-daylength conditions, in low-latitude regions.

Advanced Point-of-Care Testing Technologies for Human Acute Respiratory Virus Detection

The ever-growing global threats to human life caused by the human acute respiratory virus (RV) infections have cost billions of lives, created a significant economic burden, and shaped society for centuries. The timely response to emerging RVs could save human lives and reduce the medical care burden. The development of RV detection technologies is essential for potentially preventing RV pandemic and epidemics. However, commonly used detection technologies lack sensitivity, specificity, and speed, thus often failing to provide the rapid turnaround times. To address this problem, new technologies are devised to address the performance inadequacies of the traditional methods. These emerging technologies offer improvements in convenience, speed, flexibility, and portability of point-of-care test (POCT). Herein, recent developments in POCT are comprehensively reviewed for eight typical acute respiratory viruses. This review discusses the challenges and opportunities of various recognition and detection strategies and discusses these according to their detection principles, including nucleic acid amplification, optical POCT, electrochemistry, lateral flow assays, microfluidics, enzyme-linked immunosorbent assays, and microarrays. The importance of limits of detection, throughput, portability, and specificity when testing clinical samples in resource-limited settings is emphasized. Finally, the evaluation of commercial POCT kits for both essential RV diagnosis and clinical-oriented practices is included.

Alloying of Cu with Ru Enabling the Relay Catalysis for Reduction of Nitrate to Ammonia

Involving eight electron transfer process and multiple intermediates of nitrate (NO₃ ^- ) reduction reaction leads to a sluggish kinetic and low Faradaic efficiency, therefore, it is essential to get an insight into the reaction mechanism to develop highly efficient electrocatalyst. Herein, a series of reduced-graphene-oxide-supported RuCu alloy catalysts (Ru_x Cu_x /rGO) are fabricated and used for the direct reduction of NO₃ ^- to NH₃ . It is found that the Ru₁ Cu₁₀ /rGO shows the ammonia formation rate of 0.38 mmol cm^-2 h^-1 (loading 1 mg cm^-2 ) and the ammonia Faradaic efficiency of 98% under an ultralow potential of -0.05 V versus Reversible Hydrogen Electode (RHE), which is comparable to Ru catalyst. The highly efficient activity of Ru₁ Cu₁₀ /rGO can be attributed to the synergetic effect between Ru and Cu sites via a relay catalysis, in which the Cu shows the exclusively efficient activity for the reduction of NO₃ ^- to NO₂ ^- and Ru exhibits the superior activity for NO₂ ^- to NH₃ . In addition, the doping of Ru into Cu tunes the d-band center of alloy and effectively modulates the adsorption energy of the NO₃ ^- and NO₂ ^- , which promotes the direct reduction of NO₃ ^- to NH₃ . This synergetic electrocatalysis strategy opens a new avenue for developing highly efficient multifunctional catalysts.

Recent Advances in the Development and Antimicrobial Applications of Metal-Phenolic Networks

Due to the abuse of antibiotics and the emergence of multidrug resistant microorganisms, medical devices, and related biomaterials are at high risk of microbial infection during use, placing a heavy burden on patients and healthcare systems. Metal-phenolic networks (MPNs), an emerging organic-inorganic hybrid network system developed gradually in recent years, have exhibited excellent multifunctional properties such as anti-inflammatory, antioxidant, and antibacterial properties by making use of the coordination between phenolic ligands and metal ions. Further, MPNs have received widespread attention in antimicrobial infections due to their facile synthesis process, excellent biocompatibility, and excellent antimicrobial properties brought about by polyphenols and metal ions. In this review, different categories of biomaterials based on MPNs (nanoparticles, coatings, capsules, hydrogels) and their fabrication strategies are summarized, and recent research advances in their antimicrobial applications in biomedical fields (e.g., skin repair, bone regeneration, medical devices, etc.) are highlighted.

Fluorescent Diagnostic Probes in Neurodegenerative Diseases

Neurodegenerative diseases are debilitating disorders that feature progressive and selective loss of function or structure of anatomically or physiologically associated neuronal systems. Both chronic and acute neurodegenerative diseases are associated with high morbidity and mortality along with the death of neurons in different areas of the brain; moreover, there are few or no effective curative therapy options for treating these disorders. There is an urgent need to diagnose neurodegenerative disease as early as possible, and to distinguish between different disorders with overlapping symptoms that will help to decide the best clinical treatment. Recently, in neurodegenerative disease research, fluorescent-probe-mediated biomarker visualization techniques have been gaining increasing attention for the early diagnosis of neurodegenerative diseases. A survey of fluorescent probes for sensing and imaging biomarkers of neurodegenerative diseases is provided. These imaging probes are categorized based on the different potential biomarkers of various neurodegenerative diseases, and their advantages and disadvantages are discussed. Guides to develop new sensing strategies, recognition mechanisms, as well as the ideal features to further improve neurodegenerative disease fluorescence imaging are also explored.

Neuromorphic Engineering: From Biological to Spike-Based Hardware Nervous Systems

The human brain is a sophisticated, high-performance biocomputer that processes multiple complex tasks in parallel with high efficiency and remarkably low power consumption. Scientists have long been pursuing an artificial intelligence (AI) that can rival the human brain. Spiking neural networks based on neuromorphic computing platforms simulate the architecture and information processing of the intelligent brain, providing new insights for building AIs. The rapid development of materials engineering, device physics, chip integration, and neuroscience has led to exciting progress in neuromorphic computing with the goal of overcoming the von Neumann bottleneck. Herein, fundamental knowledge related to the structures and working principles of neurons and synapses of the biological nervous system is reviewed. An overview is then provided on the development of neuromorphic hardware systems, from artificial synapses and neurons to spike-based neuromorphic computing platforms. It is hoped that this review will shed new light on the evolution of brain-like computing.

Potential gains in life expectancy by attaining daily ambient fine particulate matter pollution standards in mainland China: A modeling study based on nationwide data

BACKGROUND

Ambient fine particulate matter pollution (PM2.5) is one leading cause of disease burden, but no study has quantified the association between daily PM2.5 exposure and life expectancy. We aimed to assess the potential benefits in life expectancy by attaining the daily PM2.5 standards in 72 cities of China during 2013-2016.

METHODS AND FINDINGS

We applied a two-stage approach for the analysis. At the first stage, we used a generalized additive model (GAM) with a Gaussian link to examine the city-specific short-term association between daily PM2.5 and years of life lost (YLL); at the second stage, a random-effects meta-analysis was used to generate the regional and national estimations. We further estimated the potential gains in life expectancy (PGLE) by assuming that ambient PM2.5 has met the Chinese National Ambient Air Quality Standard (NAAQS, 75 μg/m3) or the ambient air quality guideline (AQG) of the World Health Organization (WHO) (25 μg/m3). We also calculated the attributable fraction (AF), which denoted the proportion of YLL attributable to a higher-than-standards daily mean PM2.5 concentration. During the period from January 18, 2013 to December 31, 2016, we recorded 1,226,849 nonaccidental deaths in the study area. We observed significant associations between daily PM2.5 and YLL: each 10 μg/m3 increase in three-day-averaged (lag02) PM2.5 concentrations corresponded to an increment of 0.43 years of life lost (95% CI: 0.29-0.57). We estimated that 168,065.18 (95% CI: 114,144.91-221,985.45) and 68,684.95 (95% CI: 46,648.79-90,721.11) years of life lost can be avoided by achieving WHO's AQG and Chinese NAAQS in the study area, which corresponded to 0.14 (95% CI: 0.09-0.18) and 0.06 (95% CI: 0.04-0.07) years of gain in life expectancy for each death in these cities. We observed differential regional estimates across the 7 regions, with the highest gains in the Northwest region (0.28 years of gain [95% CI: 0.06-0.49]) and the lowest in the North region (0.08 [95% CI: 0.02-0.15]). Furthermore, using WHO's AQG and Chinese NAAQS as the references, we estimated that 1.00% (95% CI: 0.68%-1.32%) and 0.41% (95% CI: 0.28%-0.54%) of YLL could be attributable to the PM2.5 exposure at the national level. Findings from this study were mainly limited by the unavailability of data on individual PM2.5 exposure.

CONCLUSIONS

This study indicates that significantly longer life expectancy could be achieved by a reduction in the ambient PM2.5 concentrations. It also highlights the need to formulate a stricter ambient PM2.5 standard at both national and regional levels of China to protect the population's health.

Targeting macrophages in hematological malignancies: recent advances and future directions

Emerging evidence indicates that the detection and clearance of cancer cells via phagocytosis induced by innate immune checkpoints play significant roles in tumor-mediated immune escape. The most well-described innate immune checkpoints are the "don't eat me" signals, including the CD47/signal regulatory protein α axis (SIRPα), PD-1/PD-L1 axis, CD24/SIGLEC-10 axis, and MHC-I/LILRB1 axis. Molecules have been developed to block these pathways and enhance the phagocytic activity against tumors. Several clinical studies have investigated the safety and efficacy of CD47 blockades, either alone or in combination with existing therapy in hematological malignancies, including myelodysplastic syndrome (MDS), acute myeloid leukemia (AML), and lymphoma. However, only a minority of patients have significant responses to these treatments alone. Combining CD47 blockades with other treatment modalities are in clinical studies, with early results suggesting a synergistic therapeutic effect. Targeting macrophages with bispecific antibodies are being explored in blood cancer therapy. Furthermore, reprogramming of pro-tumor macrophages to anti-tumor macrophages, and CAR macrophages (CAR-M) demonstrate anti-tumor activities. In this review, we elucidated distinct types of macrophage-targeted strategies in hematological malignancies, from preclinical experiments to clinical trials, and outlined potential therapeutic approaches being developed.

The Arabidopsis Pleiotropic Drug Resistance Transporters PEN3 and PDR12 Mediate Camalexin Secretion for Resistance to Botrytis cinerea

Plant defense often depends on the synthesis and targeted delivery of antimicrobial metabolites at pathogen contact sites. The pleiotropic drug resistance (PDR) transporter PENETRATION3 (PEN3)/PDR8 in Arabidopsis (Arabidopsis thaliana) has been implicated in resistance to a variety of fungal pathogens. However, the antimicrobial metabolite(s) transported by PEN3 for extracellular defense remains unidentified. Here, we report that PEN3 functions redundantly with another PDR transporter (PDR12) to mediate the secretion of camalexin, the major phytoalexin in Arabidopsis. Consistent with this, the pen3 pdr12 double mutants exhibit dramatically enhanced susceptibility to the necrotrophic fungus Botrytis cinerea as well as severe hypersensitivity to exogenous camalexin. PEN3 and PDR12 are transcriptionally activated upon B. cinerea infection, and their expression is regulated by the mitogen-activated protein kinase 3 (MPK3) and MPK6, and their downstream WRKY33 transcription factor. Further genetic analysis indicated that PEN3 and PDR12 contribute to B. cinerea resistance through exporting not only camalexin but also other unidentified metabolite(s) derived from Trp metabolism, suggesting that PEN3 and PDR12 have multiple functions in Arabidopsis immunity via transport of distinct Trp metabolic products.