Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves.

We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essential climate elements needed to undertake building simulations. The datasets contain typical and extreme weather years in the EnergyPlus weather file (EPW) format and multiyear projections in comma-separated value (CSV) format for three periods: historical (2001-2020), future mid-term (2041-2060), and future long-term (2081-2100). The datasets were generated from projections of one regional climate model, which were bias-corrected using multiyear observational data for each city. The methodology used makes the datasets among the first to incorporate complex changes in the future climate for the frequency, duration, and magnitude of extreme temperatures. These datasets, created within the IEA EBC Annex 80 "Resilient Cooling for Buildings", are ready to be used for different types of building adaptation and resilience studies to climate change and heatwaves.

Short-term lipopolysaccharide treatment leads to astrocyte activation in LRRK2 G2019S knock-in mice without loss of dopaminergic neurons.

Background: The G2019S mutation of LRRK2, which enhances kinase activity of the protein, confers a substantial risk of developing Parkinson's disease (PD). However, the mutation demonstrates incomplete penetrance, suggesting the involvement of other genetic or environmental modulating factors. Here, we investigated whether LRRK2 G2019S knock-in (KI) mice treated with the inflammogen lipopolysaccharide (LPS) could model LRRK2 PD. Results: We found that short-term (2 weeks) treatment with LPS did not result in the loss of dopaminergic neurons in either LRRK2 G2019S KI or wild-type (WT) mice. Compared with WT mice, LRRK2 G2019S-KI mice showed incomplete recovery from LPS-induced weight loss. In LRRK2 G2019S KI mice, LPS treatment led to upregulated phosphorylation of LRRK2 at the autophosphorylation site Serine 1292, which is known as a direct readout of LRRK2 kinase activity. LPS treatment caused a greater increase in the activated astrocyte marker glial fibrillary acidic protein (GFAP) in the striatum and substantia nigra of LRRK2 G2019S mice than in those of WT mice. The administration of caffeine, which was recently identified as a biomarker of resistance to developing PD in individuals with LRRK2 mutations, attenuated LPS-induced astrocyte activation specifically in LRRK2 G2019S KI mice. Conclusions: Our findings suggest that 2 weeks of exposure to LPS is not sufficient to cause dopaminergic neuronal loss in LRRK2 G2019S KI mice but rather results in increased astrocyte activation, which can be ameliorated by caffeine.

Tailoring hierarchical structures in cellulose carbon aerogels from sugarcane bagasse using different crosslinking agents for enhancing electrochemical desalination capability.

Sugarcane bagasse is one of the most common Vietnamese agricultural waste, which possesses a large percentage of cellulose, making it an abundant and environmentally friendly source for the fabrication of cellulose carbon aerogel. Herein, waste sugarcane bagasse was used to synthesize cellulose aerogel using different crosslinking agents such as urea, polyvinyl alcohol (PVA) and sodium alginate (SA). The 3D porous network of cellulose aerogels was constructed by intermolecular hydrogen bonding, which was confirmed by Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM) and nitrogen adsorption/desorption. Among the three cellulose aerogel samples, cellulose - SA aerogel (SB-CA-SA) has low density of 0.04 g m-3 and high porosity of 97.38%, leading to high surface area of 497.9 m2 g-1 with 55.67% micropores of activated carbon aerogel (SB-ACCA-SA). The salt adsorption capacity was high (17.87 mg g-1), which can be further enhanced to 31.40 mg g-1 with the addition of CNT. Moreover, the desalination process using the SB-ACCA-SA-CNT electrode was stable even after 50 cycles. The results show the great combination of cellulose from waste sugarcane bagasse with sodium alginate and carbon nanotubes in the fabrication of carbon materials as the CDI-utilized electrodes with high desalination capability and good durability.

Computational, optical and feasibility studies of organic luminescence TMB-PPT blend for photovoltaic application.

For enhanced applications of solar cells, organic luminescence materials like long persistent luminescence (LPL) present one of the promising avenues for light enhancement. Currently, most existing luminescent materials are based on an inorganic system that requires rare elements such as europium and dysprosium, with a very high processing temperature. Adopting organic luminescence materials that are free from rare elements is necessary, considering the low-temperature fabrication and low material cost. In this work, we investigate the optical properties of an organic luminescence blend consisting of 2,8-bis(diphenylphosphoryl)dibenzo [b,d]thiophene (PPT) and N,N,N',N'-tetramethylbenzidine (TMB) through computational studies and experimental validations. Optical characteristics of the luminescence materials like optical absorption, photoluminescence, and time-resolved photoluminescence spectroscopy are characterized. To validate the functionality of the organic luminescence blend, the material is incorporated into the perovskite solar cell structure. Unfortunately, the blend is unable to emit sufficient illumination over extended periods due to its low intersystem crossing efficiency and weak spin-orbit coupling. Although the power conversion efficiency of the Luminescence/FTO/TiO2/Perovskite/Carbon structure is observed to be small under dark conditions, the application of organic luminescence materials can be further enhanced and explored.

Comprehensive Study on the Adsorption and Degradation of Dichlorodiphenyltrichloroethane on Bifunctional Adsorption-Photocatalysis Material TiO2/MCM-41 Using Quantum Chemical Methods.

The adsorption and degradation capacities of dichlorodiphenyltrichloroethane (DDT) on a photocatalyst composed of TiO2 supported on the mesoporous material MCM-41 (TiO2/MCM-41) were investigated using density functional theory and real-time density functional theory methods. The van der Waals interactions within the PBE functional were adjusted by using the Grimme approach. The adsorption of DDT was evaluated through analyses involving adsorption energy, Hirshfeld atomic charges, Wiberg bond orders, molecular electrostatic potential, noncovalent interaction analysis, and bond path analysis. The findings reveal that DDT undergoes physical adsorption on pristine MCM-41 or MCM-41 modified with Al or Fe due to the very small bond order (only about 0.15-0.18) as well as the change in total charge of DDT after adsorption is close to 0. However, it chemically adsorbs onto the TiO2/MCM-41 composite through the formation of Ti···Cl coordination bonds because the maximum bond order is very large, about 1.0 (it can be considered as a single bond). The adsorption process is significantly influenced by van der Waals interactions (accounting for approximately 30-40% of the interaction energy), hydrogen bonding, and halogen bonding. MCM-41 is demonstrated to concurrently function as a support for the TiO2 photocatalyst, creating a synergistic effect that enhances the photocatalytic activity of TiO2. Based on the computational results, a novel photocatalytic mechanism for the degradation of DDT on the TiO2/MCM-41 catalyst system was proposed.

Efficacy of compliance with ventilator-associated pneumonia care bundle: A 24-month longitudinal study at Bach Mai Hospital, Vietnam.

Introduction: To decrease the risk of complications from ventilator-associated pneumonia, it is essential to implement preventative measures in all ICU patients. Since 2018, with the help of Japanese experts, we have applied a ventilator-associated pneumonia care bundle with 10 basic standards in patient care and monitoring. Therefore, we conducted a study to evaluate the results of applying 10 solutions to prevent ventilator-associated pneumonia over 24 months. Methods: A cross-sectional descriptive study with longitudinal follow-up for 24 months on 170 mechanically ventilated patients at the Center for Critical Care Medicine, Bach Mai Hospital. According to the Centers for Disease Control (CDC, 2021), the diagnosis of ventilator-associated pneumonia is when pneumonia appears 48 h after intubation by confirmation by at least two doctors. Evaluate compliance with each solution in the care bundle through camera monitoring, medical records, and directly on patients daily. Results: The rate of ventilator-associated pneumonia is 12.9%, the frequency of occurrence is 16.54 of 1000 days. The compliance rate for complete compliance with a 10-item ventilator-associated pneumonia was only 1.8%, while the average value was 84.1%. Average values of compliance with each solution for hand hygiene, head elevation 30-45 degrees, oral hygiene, stopping sedation, breathing circuit management, cuff pressure management, hypoplastic suction, Spontaneous breathing trial (SBT) daily and assessed extubation, mobilization and early leaving bed, ulcer and thrombosis prevention were 96.9%, 97.3%, 99.4%, 81.5%, 99.9%, 99.9%, 86.3%, 83.5%, 49.3%, and 46.4%, respectively. The time to appear ventilator-associated pneumonia in the high compliance group was 46.7 ± 5.0 days, higher than in the low compliance group, 10.3 ± 0.7 days, p < 0.001. Conclusions: A 10-item ventilator-associated pneumonia care bundle has helped reduce the incidence of ventilator-associated pneumonia. To reduce the risk of ventilator-associated pneumonia and shorten ICU and hospital stays, it is essential to fully adhere to subglottic secretion suction, daily SBT, and early mobilization and leaving the bed.

Targeting casein kinase 1 for cancer therapy: current strategies and future perspectives.

Casein Kinase 1 (CK1) is a family of serine/threonine protein kinases that play a crucial role in various cellular processes, including cell proliferation, survival, and metabolism. The dysregulation of CK1 expression has been implicated in the development and progression of several types of cancer, making it an attractive target for anticancer therapy. In this review, we provide an overview of the current strategies employed to target CK1 for cancer therapy and discuss the future perspectives in this field. We highlight the different approaches, including small molecule inhibitors, RNA interference, genome editing, and immunotherapies, which hold immense potential for targeted modulation of CK1 activity in cancer cells. Furthermore, we discuss the challenges associated with targeting CK1 and propose potential strategies to overcome these hurdles. Overall, targeting CK1 holds great promise as a therapeutic strategy for cancer treatment, and further research in this area is warranted.

QuTIE: quantum optimization for target identification by enzymes.

Summary: Target identification by enzymes (TIE) problem aims to identify the set of enzymes in a given metabolic network, such that their inhibition eliminates a given set of target compounds associated with a disease while incurring minimum damage to the rest of the compounds. This is a NP-hard problem, and thus optimal solutions using classical computers fail to scale to large metabolic networks. In this article, we develop the first quantum optimization solution, called QuTIE (quantum optimization for target identification by enzymes), to this NP-hard problem. We do that by developing an equivalent formulation of the TIE problem in quadratic unconstrained binary optimization form. We then map it to a logical graph, and embed the logical graph on a quantum hardware graph. Our experimental results on 27 metabolic networks from Escherichia coli, Homo sapiens, and Mus musculus show that QuTIE yields solutions that are optimal or almost optimal. Our experiments also demonstrate that QuTIE can successfully identify enzyme targets already verified in wet-lab experiments for 14 major disease classes. Availability and implementation: Code and sample data are available at: https://github.com/ngominhhoang/Quantum-Target-Identification-by-Enzymes.

Miliutine A acid, a new cyclofarnesane sesquiterpene from the stems of Miliusa velutina.

Six compounds were isolated from the ethyl acetate extract of the stems of Miliusa velutina, including miliutine A acid (1), a new cyclofarnesane sesquiterpenoid; miliutine B methyl ester (2), a cyclofarnesane sesquiterpenoid which was determined the absolute configuration for the first time and four known phenol derivatives (3-6). NMR spectroscopic and mass spectrometry were used for identifying relative configurations. The assignments of the absolute configurations were determined based on Electronic Circular Dichroism (ECD) and NOESY spectra analysis. All six compounds were screened for their in vitro cytotoxic activities against HepG2 cell line using the SRB assay and they showed weak or none activities.

Adsorption and photodegradation of micropollutant in wastewater by photocatalyst TiO2/rice husk biochar.

With the acceleration of global industrialization, organic pollutants have become a threat to ecological safety and human health. This work prepared TiO2/rice husk biochar (TiO2/BC) for removal of bisphenol A (BA) micropollutant in wastewater. Experiment results revealed a low BA removal efficiency by TiO2/BC was observed at 34.5% under the dark environment. However, the removal rate of BA by UV light-assisted TiO2/BC significantly increased to 97.6% in 1 h. The results also demonstrated that the removal performance of BA using TiO2/BC was 2.1times higher than that of commercial TiO2 (46.4%). Besides, the removal efficiency of BA by reused TiO2/BC after eight cycles slightly decreased by 12.8%, demonstrating the excellent properties of the prepared composite. TiO2/BC also exhibited high removal efficiency of BA (over 89%) from the synthetic wastewater sample, indicating the potential utilization of composite for removing BA in wastewater. This work provides a new way to turn biomass waste into useful material and effective method to remove micropollutant BA.

Photodegradation of hazardous organic pollutants using titanium oxides -based photocatalytic: A review.

Titanium oxide-based photocatalysts (TOBPs) have been widely utilized as potential materials for numerous applications, such as wastewater treatment, water-splitting reactions, carbon dioxide (CO2) reduction and photosynthesis. However, the large bandgap of intrinsic TiO2 limits their absorption toward visible light, which is the central part of the solar spectrum, resulting in low photocatalytic activities under sunlight. To overcome this obstacle, several strategies, such as doping with either metal or non-metal elements or combining with other compounds, are efficient ways to reduce the bandgap of TiO2, leading to effectively extending their absorption toward the visible region and increasing their catalytic performance. In this review, we discussed the application of TOBPs for the photodegradation of hazardous organic pollutants in wastewater to produce quality reused water. The synthesis of TiO2 and the enhancement of photocatalytic activities of TOBPs by different techniques with detailed information were provided. Application of TOBPs for decomposing hazardous organic pollutants such as dyes, phenolic compounds and pharmaceuticals under optimum conditions have been listed. Also, the photodegradation mechanisms of hazardous organic compounds have been investigated. This work also brings ideas for future perspectives and research plan to inhibit the disadvantages and expand the application of TOBPs to remove toxic organic pollutants.

Severe COVID-19 pneumonia in pregnant woman treated with pulse corticosteroids therapy and third-trimester caesarean section: A case report.

A 44-year-old woman at 30 weeks of pregnancy was admitted to the Intensive Care Unit with a diagnosis of severe COVID-19 pneumonia. Her condition worsened quickly, defined by prolonged hypoxia even with intensive therapy and oxygen supplementation. This led to the decision to perform a caesarean delivery and continue pulse corticosteroids therapy after delivery. Soon after she recovered from COVID-19 pneumonia, her life was threatened again by septic shock from hospital-acquired pneumonia. After nearly 1 month of hospitalization, she was discharged and fully recovered on the re-examination day 10 months later.

Sputum culture and antibiotic resistance in elderly inpatients with exacerbation of chronic obstructive pulmonary disease at a tertiary geriatric hospital in southern Vietnam.

OBJECTIVE: To determine the rate of positive culture sputum and related factors as well as the microorganism features and antibiotic susceptibility of pathogens in elderly inpatients with exacerbation of chronic obstructive pulmonary disease (COPD) in Thong Nhat Hospital, Vietnam. METHODS: This cross-sectional study included elderly patients admitted to the hospital because of exacerbation of COPD. Data of their medical history, symptoms and signs were collected, and the patients were instructed to collect sputum sample. A positive culture was identified with the growth of ≥ 105 colony-forming units per milliliter. Antibiotic susceptibility testing was performed according to the European Committee on Antimicrobial Susceptibility Testing. RESULTS: There were 167 participants (mean age: 77.5 ± 8.8 years, 87.4% male). The culture-positive rate was 25.1%. A higher proportion of positive culture was among participants with purulent sputum (p = 0.029) and with severe and very severe airflow obstruction (p = 0.005). Three most common agents were Acinetobacter baumannii (24.4%), Klebsiella pneumoniae (22.2%), and Pseudomonas aeruginosa (15.6%). Despite high resistance to almost other antibiotics (> 50% resistance), Acinetobacter baumannii and Pseudomonas aeruginosa were sensitive to colistin, tobramycin, and gentamicin (> 80% susceptibility). Klebsiella pneumoniae was highly sensitive to almost common antibiotics (> 80% susceptibility). Among Gram-positive pathogens, methicillin-resistant Staphylococcus aureus (MRSA) was completely sensitive to vancomycin, teicoplanin, and linezolid. CONCLUSION: The sputum culture-positive rate in this study was not high. Most prevalent isolated pathogens were Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Acinetobacter baumannii and Pseudomonas aeruginosa were sensitive to tobramycin, gentamicin, and colistin. Commonly used antibiotics remained effective against Klebsiella pneumoniae. MRSA was sensitive to vancomycin, teicoplanin, and linezolid.

Dimethyl Itaconate Inhibits Melanogenesis in B16F10 Cells.

Itaconate is a metabolite produced to counteract and resolve pro-inflammatory responses when macrophages are challenged with intracellular or extracellular stimuli. In the present study, we have observed that dimethyl itaconate (DMI) inhibits melanogenesis in B16F10 cells. DMI inhibits microphthalmia-associated transcription factor (MITF) and downregulates the expression of MITF target genes, such as tyrosinase (TYR), tyrosinase-related protein 1 (TRP-1), and tyrosinase-related protein 2 (TRP-2). DMI also decreases the level of melanocortin 1 receptor (MC1R) and the production of α-melanocyte stimulating hormone (α-MSH), resulting in the inhibition of extracellular signal-regulated kinase 1/2 (ERK1/2) and MITF activities. The structure-activity relationship (SAR) study illustrates that the α,ß-unsaturated carbonyl moiety in DMI, a moiety required to target KELCH-like ECH-associated protein 1 (KEAP1) to activate NF-E2-related factor 2 (NRF2), is necessary to inhibit melanogenesis and knocking down Nrf2 attenuates the inhibition of melanogenesis by DMI. Together, our study reveals that the MC1R-ERK1/2-MITF axis regulated by the KEAP1-NRF2 pathway is the molecular target responsible for the inhibition of melanogenesis by DMI.

eMIC-AntiKP: Estimating minimum inhibitory concentrations of antibiotics towards Klebsiella pneumoniae using deep learning.

Nowadays, antibiotic resistance has become one of the most concerning problems that directly affects the recovery process of patients. For years, numerous efforts have been made to efficiently use antimicrobial drugs with appropriate doses not only to exterminate microbes but also stringently constrain any chances for bacterial evolution. However, choosing proper antibiotics is not a straightforward and time-effective process because well-defined drugs can only be given to patients after determining microbic taxonomy and evaluating minimum inhibitory concentrations (MICs). Besides conventional methods, numerous computer-aided frameworks have been recently developed using computational advances and public data sources of clinical antimicrobial resistance. In this study, we introduce eMIC-AntiKP, a computational framework specifically designed to predict the MIC values of 20 antibiotics towards Klebsiella pneumoniae. Our prediction models were constructed using convolutional neural networks and k-mer counting-based features. The model for cefepime has the most limited performance with a test 1-tier accuracy of 0.49, while the model for ampicillin has the highest performance with a test 1-tier accuracy of 1.00. Most models have satisfactory performance, with test accuracies ranging from about 0.70-0.90. The significance of eMIC-AntiKP is the effective utilization of computing resources to make it a compact and portable tool for most moderately configured computers. We provide users with two options, including an online web server for basic analysis and an offline package for deeper analysis and technical modification.

Overactivated NRF2 induces pseudohypoxia in hepatocellular carcinoma by stabilizing HIF-1α.

Hypoxia-inducible factor-1α (HIF-1α) is highly expressed/activated in most hypoxic tumors including hepatocellular carcinoma (HCC). Another key transcription factor, nuclear factor erythroid 2-related factor 2 (NRF2), is also constitutively overactivated in HCC. In an attempt to determine whether HIF-1α and NRF2 could play complementary roles in HCC growth and progression, we investigated the crosstalk between these two transcription factors and underlying molecular mechanisms in cultured HCC cells and experimentally induced hepatocarcinogenesis as well as clinical settings. While silencing of HIF-1α in HepG2 human hepatoma cells did not alter the protein expression of NRF2, NRF2 knockdown markedly reduced the nuclear accumulation of HIF-1α without influencing its mRNA expression. In diethylnitrosamine-induced hepatocarcinogenesis in wild type mice, there was elevated NRF2 expression with concomitant upregulation of HIF-1α. However, this was abolished in Nrf2 knockout mice. NRF2 and HIF-1α co-localized and physically interacted with each other as assessed by in situ proximity ligation and immunoprecipitation assays. In addition, the interaction between NRF2 and HIF-1α as well as their overexpression was found in tumor specimens obtained from HCC patients. In normoxia, HIF-1α undergoes hydroxylation by a specific HIF-prolyl hydroxylase domain protein (PHD), which facilitates ubiquitination and proteasomal degradation of HIF-1α. NRF2 contributes to pseudohypoxia, by directly binding to the oxygen-dependent degradation (ODD) domain of HIF-1α, which hampers the PHD2-mediated hydroxylation, concomitant recruitment of von-Hippel-Lindau and ubiquitination of HIF-1α.

Nrf2, A Target for Precision Oncology in Cancer Prognosis and Treatment.

Activating nuclear factor-erythroid 2-related factor (Nrf2), a master regulator of redox homeostasis, has been shown to suppress initiation of carcinogenesis in normal cells. However, this transcription factor has recently been reported to promote proliferation of some transformed or cancerous cells. In tumor cells, Nrf2 is prone to mutations that result in stabilization and concurrent accumulation of its protein product. A hyperactivated mutant form of Nrf2 could support the cancer cells for enhanced proliferation, invasiveness, and resistance to chemotherapeutic agents and radiotherapy, which are associated with a poor clinical outcome. Hence understanding mutations in Nrf2 would have a significant impact on the prognosis and treatment of cancer in the era of precision medicine. This perspective would provide an insight into the genetic alterations in Nrf2 and suggest the application of small molecules, RNAi, and genome editing technologies, particularly CRISR-Cas9, in therapeutic intervention of cancer in the context of the involvement of Nrf2 mutations.