The choroid plexus links innate immunity to CSF dysregulation in hydrocephalus.

The choroid plexus (ChP) is the blood-cerebrospinal fluid (CSF) barrier and the primary source of CSF. Acquired hydrocephalus, caused by brain infection or hemorrhage, lacks drug treatments due to obscure pathobiology. Our integrated, multi-omic investigation of post-infectious hydrocephalus (PIH) and post-hemorrhagic hydrocephalus (PHH) models revealed that lipopolysaccharide and blood breakdown products trigger highly similar TLR4-dependent immune responses at the ChP-CSF interface. The resulting CSF "cytokine storm", elicited from peripherally derived and border-associated ChP macrophages, causes increased CSF production from ChP epithelial cells via phospho-activation of the TNF-receptor-associated kinase SPAK, which serves as a regulatory scaffold of a multi-ion transporter protein complex. Genetic or pharmacological immunomodulation prevents PIH and PHH by antagonizing SPAK-dependent CSF hypersecretion. These results reveal the ChP as a dynamic, cellularly heterogeneous tissue with highly regulated immune-secretory capacity, expand our understanding of ChP immune-epithelial cell cross talk, and reframe PIH and PHH as related neuroimmune disorders vulnerable to small molecule pharmacotherapy.

Noncanonical processing by animal Microprocessor.

Microprocessor (MP), DROSHA-DGCR8, processes primary miRNA transcripts (pri-miRNAs) to initiate miRNA biogenesis. The canonical cleavage mechanism of MP has been extensively investigated and comprehensively validated for two decades. However, this canonical mechanism cannot account for the processing of certain pri-miRNAs in animals. In this study, by conducting high-throughput pri-miRNA cleavage assays for approximately 260,000 pri-miRNA sequences, we discovered and comprehensively characterized a noncanonical cleavage mechanism of MP. This noncanonical mechanism does not need several RNA and protein elements essential for the canonical mechanism; instead, it utilizes previously unrecognized DROSHA dsRNA recognition sites (DRESs). Interestingly, the noncanonical mechanism is conserved across animals and plays a particularly significant role in C. elegans. Our established noncanonical mechanism elucidates MP cleavage in numerous RNA substrates unaccounted for by the canonical mechanism in animals. This study suggests a broader substrate repertoire of animal MPs and an expanded regulatory landscape for miRNA biogenesis.

Coronavirus RNA Proofreading: Molecular Basis and Therapeutic Targeting.

The coronavirus disease 2019 (COVID-19) that is wreaking havoc on worldwide public health and economies has heightened awareness about the lack of effective antiviral treatments for human coronaviruses (CoVs). Many current antivirals, notably nucleoside analogs (NAs), exert their effect by incorporation into viral genomes and subsequent disruption of viral replication and fidelity. The development of anti-CoV drugs has long been hindered by the capacity of CoVs to proofread and remove mismatched nucleotides during genome replication and transcription. Here, we review the molecular basis of the CoV proofreading complex and evaluate its potential as a drug target. We also consider existing nucleoside analogs and novel genomic techniques as potential anti-CoV therapeutics that could be used individually or in combination to target the proofreading mechanism.

Cryo-EM structures of human ABCA7 provide insights into its phospholipid translocation mechanisms.

Phospholipid extrusion by ABC subfamily A (ABCA) exporters is central to cellular physiology, although the specifics of the underlying substrate interactions and transport mechanisms remain poorly resolved at the molecular level. Here we report cryo-EM structures of lipid-embedded human ABCA7 in an open state and in a nucleotide-bound, closed state at resolutions between 3.6 and 4.0 Å. The former reveals an ordered patch of bilayer lipids traversing the transmembrane domain (TMD), while the latter reveals a lipid-free, closed TMD with a small extracellular opening. These structures offer a structural framework for both substrate entry and exit from the ABCA7 TMD and highlight conserved rigid-body motions that underlie the associated conformational transitions. Combined with functional analysis and molecular dynamics (MD) simulations, our data also shed light on lipid partitioning into the ABCA7 TMD and localized membrane perturbations that underlie ABCA7 function and have broader implications for other ABCA family transporters.

Nucleic Acid-Based Technologies Targeting Coronaviruses.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently creating a global health emergency. This crisis is driving a worldwide effort to develop effective vaccines, prophylactics, and therapeutics. Nucleic acid (NA)-based treatments hold great potential to combat outbreaks of coronaviruses (CoVs) due to their rapid development, high target specificity, and the capacity to increase druggability. Here, we review key anti-CoV NA-based technologies, including antisense oligonucleotides (ASOs), siRNAs, RNA-targeting clustered regularly interspaced short palindromic repeats-CRISPR-associated protein (CRISPR-Cas), and mRNA vaccines, and discuss improved delivery methods and combination therapies with other antiviral drugs.

Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach.

The worldwide appearance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated significant concern and posed a considerable challenge to global health. Phosphorylation is a common post-translational modification that affects many vital cellular functions and is closely associated with SARS-CoV-2 infection. Precise identification of phosphorylation sites could provide more in-depth insight into the processes underlying SARS-CoV-2 infection and help alleviate the continuing COVID-19 crisis. Currently, available computational tools for predicting these sites lack accuracy and effectiveness. In this study, we designed an innovative meta-learning model, Meta-Learning for Serine/Threonine Phosphorylation (MeL-STPhos), to precisely identify protein phosphorylation sites. We initially performed a comprehensive assessment of 29 unique sequence-derived features, establishing prediction models for each using 14 renowned machine learning methods, ranging from traditional classifiers to advanced deep learning algorithms. We then selected the most effective model for each feature by integrating the predicted values. Rigorous feature selection strategies were employed to identify the optimal base models and classifier(s) for each cell-specific dataset. To the best of our knowledge, this is the first study to report two cell-specific models and a generic model for phosphorylation site prediction by utilizing an extensive range of sequence-derived features and machine learning algorithms. Extensive cross-validation and independent testing revealed that MeL-STPhos surpasses existing state-of-the-art tools for phosphorylation site prediction. We also developed a publicly accessible platform at https://balalab-skku.org/MeL-STPhos. We believe that MeL-STPhos will serve as a valuable tool for accelerating the discovery of serine/threonine phosphorylation sites and elucidating their role in post-translational regulation.

APLpred: A machine learning-based tool for accurate prediction and characterization of asparagine peptide lyases using sequence-derived optimal features.

Asparagine peptide lyase (APL) is among the seven groups of proteases, also known as proteolytic enzymes, which are classified according to their catalytic residue. APLs are synthesized as precursors or propeptides that undergo self-cleavage through autoproteolytic reaction. At present, APLs are grouped into 10 families belonging to six different clans of proteases. Recognizing their critical roles in many biological processes including virus maturation, and virulence, accurate identification and characterization of APLs is indispensable. Experimental identification and characterization of APLs is laborious and time-consuming. Here, we developed APLpred, a novel support vector machine (SVM) based predictor that can predict APLs from the primary sequences. APLpred was developed using Boruta-based optimal features derived from seven encodings and subsequently trained using five machine learning algorithms. After evaluating each model on an independent dataset, we selected APLpred (an SVM-based model) due to its consistent performance during cross-validation and independent evaluation. We anticipate APLpred will be an effective tool for identifying APLs. This could aid in designing inhibitors against these enzymes and exploring their functions. The APLpred web server is freely available at https://procarb.org/APLpred/.

Predictive Performance of an Updated Polygenic Risk Score for Age-Related Macular Degeneration.

PURPOSE: A recent genome-wide association study of age-related macular degeneration (AMD) identified new AMD-associated risk variants. These variants now can be incorporated into an updated polygenic risk score (PRS). This study aimed to assess the performance of an updated PRS, PRS2023, in an independent cohort of older individuals with retinal imaging data and to compare performance with an older PRS, PRS2016. DESIGN: Cross-sectional study. PARTICIPANTS: A total of 4175 participants of European ancestry, 70 years of age or older, with genotype and retinal imaging data. METHODS: We used logistic regression models and area under the receiver operating characteristic curve (AUC) to assess the performance of PRS2023 compared with PRS2016. AMD status and severity were graded using color fundus photography. MAIN OUTCOME MEASURES: Association of PRS2023 and PRS2016 with AMD risk at baseline. RESULTS: At enrollment among 4175 participants, 2605 participants (62.4%) had no AMD and 853 participants (20.4%), 671 participants (16.1%), and 46 participants (1.1%) had early, intermediate, and late-stage AMD, respectively. More than 27% of the participants with a high PRS2023 (top quartile) had intermediate or late-stage AMD, compared with < 15% for those in the middle 2 quartiles and less than 13% for those in the lowest quartile. Both PRS2023 and PRS2016 were associated significantly with AMD after adjustment for age, sex, smoking status, and lipid levels, with increasing odds ratios (ORs) for worsening AMD grades. PRS2023 outperformed PRS2016 (P = 0.03 for all AMD and P = 0.03 for late AMD, DeLong test comparing AUC). PRS2023 was associated with late-stage AMD with an adjusted OR of 5.05 (95% confidence interval [CI], 3.41-7.47) per standard deviation. The AUC of a model containing conventional or nongenetic risk factors and PRS2023 was 91% (95% CI, 87%-95%) for predicting late-stage AMD, which improved 12% over the model without the PRS (AUC, 79%; P < 0.001 for difference). CONCLUSIONS: A new PRS, PRS2023, for AMD outperforms a previous PRS and predicts increasing risk for late-stage AMD (with stronger association for more severe imaging-confirmed AMD grades). Our findings have clinical implications for the improved prediction and risk stratification of AMD. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Fabrication of polydopamine-modified cellulose hydrogel for controlled release of α-mangostin.

Hydrogels are notable for their outstanding absorbent qualities, satisfactory compatibility with biological systems, ability to degrade, and inherent safety, all of which contribute to their high demand in the field of biomedicine. This study focuses on the fabrication of hydrogels using environmentally friendly cellulosic material. Cellulose hydrogel beads were prepared by physical cross-linking in a NaOH/urea medium. Furthermore, nano polydopamine was integrated into the hydrogel matrix as functional polymers and α-mangostin was employed as an active pharmaceutical ingredient. The physicochemical properties were comprehensively analyzed using Fourier-transform infrared spectrometer, 13C cross-polarization/magic angle spinning nuclear magnetic resonance, thermogravimetric analysis, and scanning electron microscope. The drug delivery properties, including water content, swelling ratio, and drug release profiles, were evaluated. In vitro cytotoxicity against MC3T3-E1 cells was assessed using sulforhodamine B staining. All test hydrogels exhibited inhibitory activity against the growth of MC3T3-E1 cells. These results indicated the potential use of these hydrogels as a drug delivery carrier for α-mangostin in the treatment of ankylosing spondylitis.

Network biomarkers in recovered psychosis patients who discontinued antipsychotics.

There are no studies investigating topological properties of resting-state fMRI (rs-fMRI) in patients who have recovered from psychosis and discontinued medication (hereafter, recovered patients [RP]). This study aimed to explore topological organization of the functional brain connectome in the RP using graph theory approach. We recruited 30 RP and 50 age and sex-matched healthy controls (HC). The RP were further divided into the subjects who were relapsed after discontinuation of antipsychotics (RP-R) and who maintained recovered state without relapse (RP-M). Using graph-based network analysis of rs-fMRI signals, global and local metrics and hub information were obtained. The robustness of the network was tested with random failure and targeted attack. As an ancillary analysis, Network-Based Statistic (NBS) was performed. Association of significant findings with psychopathology and cognitive functioning was also explored. The RP showed intact network properties in terms of global and local metrics. However, higher global functional connectivity strength and hyperconnectivity in the interconnected component were observed in the RP compared to HC. In the subgroup analysis, the RP-R were found to have lower global efficiency, longer characteristic path length and lower robustness whereas no such abnormalities were identified in the RP-M. Associations of the degree centrality of some hubs with cognitive functioning were identified in the RP-M. Even though network properties of the RP were intact, subgroup analysis revealed more altered topological organizations in the RP-R. The findings in the RP-R and RP-M may serve as network biomarkers for predicting relapse or maintained recovery after the discontinuation of antipsychotics.

Highly Efficient Removal of 2,4,5-Trichlorophenoxyacetic Acid by Adsorption and Photocatalysis Using Nanomaterials with Surface Coating by the Cationic Surfactant.

Extensive removal of 2,4,5-trichlorophenoxyacetic acid (2,4,5-T) using titania (TiO2) nanoparticles by adsorption and photocatalysis with a surface coating by cetyltrimethylammonium bromide (CTAB) is reported. The CTAB-coated TiO2 nanoparticles (CCTN) were characterized by FT-IR, zeta-potential measurements, and UV-vis diffuse reflectance spectroscopy (UV-vis-DRS). 2,4,5-T removal increased significantly after surface modification with CTAB compared with bare TiO2 nanoparticles. Optimal parameters affecting 2,4,5-T removal were found to be pH 4, CCTN dosage 10 mg/mL, and adsorption time 180 min. The maximum adsorptive removal of 2,4,5-T using CCTN reached 96.2% while highest adsorption capacity was 13.4 mg/g. CCTN was also found to be an excellent photocatalyst that achieved degradation efficiency of 99.2% with an initial concentration of 25 mg/L. The removal mechanisms of 2,4,5-T using CCTN by both adsorption and photocatalysis are discussed in detail based on changes in functional group vibrations and surface charge. Our results indicate that CCTN is an excellent material for 2,4,5-T removal in water by both adsorption and photocatalysis.

Novel melanin-derived stationary phase for immobilized metal ion affinity chromatography in recombinant His-tagged protein purification.

The matrix of the stationary phase is a crucial element in affinity chromatography for protein purification. Various materials, including polymer or magnetic materials, have been employed as the matrix in the purification of His-tagged protein. Here, for the first time, we utilized a combination of melanin and alginate, both natural polymer materials, to synthesize Ni-melanin/alginate (Ni-M/A) beads for His-tagged protein purification. We investigated the binding of His-tagged Mpro on the Ni-M/A beads, referred to as Ni-M/A-Mpro, and assessed the elution efficiency of Mpro from the beads. Our examination involved FTIR, EDS, XRD, SDS-PAGE, and Western blotting methods. FTIR spectra revealed notable changes in the stretching patterns and intensities of hydroxyl, amine, carbonyl, imine and amide chemical groups, when Mpro protein was present in the Ni-M/A sample. XRD spectra demonstrated the occurrence of two Nickel peaks at 35-40 deg and 40-45 deg in Ni-M/A, but only one nickel peak at 35-40 deg in Ni-M/A-Mpro, indicating the binding of Mpro on the Nickel ions. EDS analysis reported a decrease in the concentration of Nickel on the surface of Ni-M/A from 16% to 7% when Mpro protein was loaded into the stationary phase. Importantly, our data indicated that the purity of the His-tagged protein Mpro after purification reached 97% after just one-step purification using the Ni-M/A stationary phase. Moreover, the binding capacity of Ni-M/A for Mpro was approximately 5.2 mg/g with recovery efficiency of 40%. Our results suggested Ni-M/A as a highly potential solid phase for affinity chromatography in the purification of His-tagged protein.

Improving nitrogen content in soil and lemon balm (Melissa officinalis L.) yield by purple nonsulfur bacteria Rhodopseudomonas palustris in two consecutive seasons.

The study was conducted to assess the effects of nitrogen (N)-fixing purple nonsulfur bacteria (PNSB) Rhodopseudomonas palustris TLS06, VNW02, VNW64, and VNS89 on soil fertility, N uptake, essential oil (EO) content, growth, and yield of lemon balm. The experiment followed a completely randomized block design with 9 treatments and 3 replications. The treatments consisted of (i) applying 100% N as the recommended fertilizer rate (RFR), (ii) applying 85% N as RFR, (iii) applying 70% N as RFR, (iv) applying 55% N as RFR, (v) the treatment ii combined with N-PNSB, (vi) the treatment iii combined with N-PNSB, (vii) the treatment iv combined with N-PNSB, (viii) 0% as RFR combined with N-PNSB, and (ix) 0% N as RFR. The results showed that applying N-PNSB increased the plant height, and the number of primary branches in both seasons. In addition, the treatment without N fertilizer combined with N-PNSB increased stem leaf biomass by 41.2 and 50.3% in both seasons as compared with the treatment without neither N fertilizer nor N-PNSB. For soil properties, among treatments without N fertilizer, the treatment with N-PNSB increased concentrations of NH4+, soluble P, and exchangeable K+ by 41.3, 41.4, and 26.8%, respectively, as compared with the treatment without N-PNSB at the end of the second season. Applying 85% N as RFR combined with N-PNSB had a greater yield by 5.78-11.8% as compared with the treatment with 100% N as RFR, and a greater EO content by 23% as compared with the treatment with 85% N as RFR.

Handling missing disease information due to death in diseases that need two visits to diagnose.

In studies that assess disease status periodically, time of disease onset is interval censored between visits. Participants who die between two visits may have unknown disease status after their last visit. In this work, we consider an additional scenario where diagnosis requires two consecutive positive tests, such that disease status can also be unknown at the last visit preceding death. We show that this impacts the choice of censoring time for those who die without an observed disease diagnosis. We investigate two classes of models that quantify the effect of risk factors on disease outcome: a Cox proportional hazards model with death as a competing risk and an illness death model that treats disease as a possible intermediate state. We also consider four censoring strategies: participants without observed disease are censored at death (Cox model only), the last visit, the last visit with a negative test, or the second last visit. We evaluate the performance of model and censoring strategy combinations on simulated data with a binary risk factor and illustrate with a real data application. We find that the illness death model with censoring at the second last visit shows the best performance in all simulation settings. Other combinations show bias that varies in magnitude and direction depending on the differential mortality between diseased and disease-free subjects, the gap between visits, and the choice of the censoring time.

Smartphone-based paper strip assay for putrescine and spermidine detection using hybrid organic-inorganic perovskite with Eu3+ complex.

A new method utilizing fluorescent ratiometry is proposed for detecting putrescine and spermidine. The method involves the use of a fluorescent probe comprising a 2D halide perovskite synthesized from octadecylamine-iodine and PbI2via a grinding-sonicating technique, along with a Eu3+-complex. Upon excitation at 290 nm, the probe fluoresces at two distinguishable wavelengths. The addition of putrescine and spermidine significantly decreases the emission of the 2D halide perovskite at 496 nm, while the emission of the Eu3+-complex at 618 nm remains stable. The color changes of the probe depend on the concentration of putrescine and spermidine, and the assay offers linearity over a wide concentration range (30-4000 ng mL-1), a low detection limit (4 ng mL-1 for putrescine, and 7 ng mL-1 for spermidine), and a quick response time. Furthermore, a portable device based on a smartphone can be used to record the color change of the paper test strip using the prepared fluorescent materials. The fluorescence quenching mechanism of the probe is explained as dynamic quenching.

Structural modification of tanshinone IIA and their α-glucosidase inhibitory activity.

α-Glucosidase is one of the therapeutic approaches for treating type 2 diabetes mellitus. Almost 95 % of diabetes patients worldwide have been diagnosed with type 2 diabetes, resulting in 1.5 million fatalities each year. Newly synthesized oxazole-based tanshinone IIA derivatives (1a-n) were designed and evaluated for their inhibitory activity against α-glucosidase enzyme. Eight compounds (1a-d, 1f-g, 1j, and 1m) demonstrated excellent inhibition with IC50 values ranging from 0.73 ± 0.11 to 9.46 ± 0.57 µM as compared to tanshinone IIA (IC50 = 11.39 ± 0.77 µM) and standard acarbose (IC50 = 100.00 ± 0.95 µM). Among this series, 1j bearing two hydroxyls group over the phenyl ring was identified as the most potent α-glucosidase inhibitor with IC50 value of 0.73 ± 0.11 µM. Molecular docking simulations were done for the most active compound to identify important binding modes responsible for inhibition activity of α-glucosidase. In addition, the kinetic study was also performed to understand the mode of inhibition.

Dietary habits, traveling and the living situation potentially influence the susceptibility to SARS-CoV-2 infection: results from healthcare workers participating in the RisCoin Study.

PURPOSE: To explore occupational and non-occupational risk and protective factors for the coronavirus disease 2019 (COVID-19) in healthcare workers (HCWs). METHODS: Serum specimens and questionnaire data were obtained between October 7 and December 16, 2021 from COVID-19-vaccinated HCWs at a quaternary care hospital in Munich, Germany, and were analyzed in the RisCoin Study. RESULTS: Of 3,696 participants evaluated, 6.6% have had COVID-19 at least once. Multivariate logistic regression analysis identified working in patient care occupations (7.3% had COVID-19, 95% CI 6.4-8.3, Pr = 0.0002), especially as nurses, to be a potential occupation-related COVID-19 risk factor. Non-occupational factors significantly associated with high rates of the disease were contacts to COVID-19 cases in the community (12.8% had COVID-19, 95% CI 10.3-15.8, Pr < 0.0001), being obese (9.9% had COVID-19, 95% CI 7.1-13.5, Pr = 0.0014), and frequent traveling abroad (9.4% had COVID-19, 95% CI 7.1-12.3, Pr = 0.0088). On the contrary, receiving the basic COVID-19 immunization early during the pandemic (5.9% had COVID-19, 95% CI 5.1-6.8, Pr < 0.0001), regular smoking (3.6% had COVID-19, 95% CI 2.1-6.0, Pr = 0.0088), living with the elderly (3.0% had COVID-19, 95% CI 1.0-8.0, Pr = 0.0475), and frequent consumption of ready-to-eat meals (2.6% had COVID-19, 95% CI 1.1-5.4, Pr = 0.0045) were non-occupational factors potentially protecting study participants against COVID-19. CONCLUSION: The newly discovered associations between the living situation, traveling as well as dietary habits and altered COVID-19 risk can potentially help refine containment measures and, furthermore, contribute to new mechanistic insights that may aid the protection of risk groups and vulnerable individuals.

Mixed Metal Amide-Hydride Solid Solutions for Potential Energy Storage Applications.

Mixed solid solutions have played an important role in improving the kinetics and performance of hydrogen storage materials, as reported for the Li-Mg-N-H, K-Mg-N-H, and Rb-Mg-N-H systems. Besides, the formation of a homogeneous solid solution, mostly due to partial ionic substitution, is known to be an effective approach to improve the ionic conductivity of a material, which is an important property in electrochemical applications. We have reported a series of solid solutions based on mixed amide-hydride materials of the Group 1 elements, e.g., K(NH2)xH1-x, Rb(NH2)xH1-x, and Cs(NH2)xH1-x, via the exchange of NH2-/H- anions with the change of the lattice cell of the solid solution. Extending the research in this direction, we study the M-N-H solid solution in the MNH2-MH systems (M = K, Rb, Cs, and their combinations), i.e., KNH2-RbH, RbNH2-KH, RbNH2-CsH, and CsNH2-RbH via ex situ/in situ XRD, IR, and 1H 2D solid-state NMR. The results obtained confirm the formation of mixed metal amide-hydride solid solutions associated with an exchange between both anionic (NH2- and H-) and cationic species (K+, Rb+, and Cs+). With this study, we aim to create an accessible library of M-N-H solid solutions for further studies as additives for hydrogen storage materials or ionic conductors.

Enhancing control in spatial atomic layer deposition: insights into precursor diffusion, geometric parameters, and CVD mitigation strategies.

In recent years, spatial atomic layer deposition (SALD) has gained significant attention for its remarkable capability to accelerate ALD growth by several orders of magnitude compared to conventional ALD, all while operating at atmospheric pressure. Nevertheless, the persistent challenge of inadvertent contributions from chemical vapor deposition (CVD) in SALD processes continues to impede control over film homogeneity, and properties. This research underscores the often-overlooked influence of diffusion coefficients and important geometric parameters on the close-proximity SALD growth patterns. We introduce comprehensive physical models complemented by finite element method simulations for fluid dynamics to elucidate SALD growth kinetics across diverse scenarios. Our experimental findings, in alignment with theoretical models, reveal distinctive growth rate trends in ZnO and SnO2films as a function of the deposition gap. These trends are ascribed to precursor diffusion effects within the SALD system. Notably, a reduced deposition gap proves advantageous for both diffusive and low-volatility bulky precursors, minimizing CVD contributions while enhancing precursor chemisorption kinetics. However, in cases involving highly diffusive precursors, a deposition gap of less than 100µm becomes imperative, posing technical challenges for large-scale applications. This can be ameliorated by strategically adjusting the separation distance between reactive gas outlets to mitigate CVD contributions, which in turn leads to a longer deposition time. Furthermore, we discuss the consequential impact on material properties and propose a strategy to optimize the injection head to control the ALD/CVD growth mode.

Reemergence of Marburgvirus disease: Update on current control and prevention measures and review of the literature.

In 1967, the very first case of the Marburgvirus disease (MVD) was detected in Germany and Serbia sequentially. Since then, MVD has been considered one of the most serious and deadly infectious diseases in the world with a case-fatality rate between 23% and 90% and a substantial number of recorded deaths. Marburgvirus belongs to the family of Filoviridae (filoviruses), which causes severe viral hemorrhagic fever (VHF). Some major risk factors for human infections are close contact with African fruit bats, MVD-infected non-human primates, and MVD-infected individuals. Currently, there is no vaccine or specific treatment for MVD, which emphasizes the seriousness of this disease. In July 2022, the World Health Organization reported outbreaks of MVD in Ghana after two suspected VHF cases were detected. This was followed in February and March 2023 with the emergence of the virus in two countries new to the virus: Equatorial Guinea and Tanzania, respectively. In this review, we aim to highlight the characteristics, etiology, epidemiology, and clinical symptoms of MVD, along with the current prevention measures and the possible treatments to control this virus.