Inocybaceae and affiliated taxa from West Africa

Inocybaceae and affiliated taxa reported in West Africa were examined through a survey of available publications coupled with field data collections. Twenty-eight Inocyboid taxa have been reported in the region, including six species validly described in the genera Inocybe, Inosperma and Mallocybe. All taxonomic names have been confirmed in Index Fungorum (http://www.indexfungorum.org/names/names.asp). Among them, four taxa were synonyms of other species of Inocybaceae, Crepidotaceae or Chromocyphellaceae. Consequently, only six taxa, Inocybe ghanaensis, Mallocybe africana, Inosperma africanum, I. bulbomarginatum, I. flavobrunneum and Pseudosperma squamatum make the diversity of Inocybaceae from West Africa. Here the distribution of known taxa has been reported along with checklist. In addition, results of BLAST searches including any potential environmental matches (>97%) similarity is reported. Key words: Checklist, Ectomycorrhizal fungi, Inocybe, Distribution, Pseudosperma, West Afric

Assessment of Heavy Metals in Fodder Crops Leaves Being Raised with Hudiara Drain Water (Punjab-Pakistan)

The present study was designed with the objectives to assess heavy metals' concentration in Hudiara drain water and investigation of the concentration of heavy metals in different fodder crops grown with this drain water and the determination of heavy metals in milk of cattles grazing these contaminated fodder crops. A survey was conducted and ten different sites were selected along Hudiara drain after entering Lahore. Five water samples and three samples of crops from a each site. The samples were processed, stored and then analyzed for heavy metals like Lead, Cadmium, Chromium, Nickel, Zinc, Iron, Copper and manganese. Lead pollution was not found, whereas, Cadmium, Chromium and Nickel contamination was shown in Hudiara drain water. Similarly, Zinc pollution was not found in Hudiara drain water regarding irrigation and Iron, Copper and Manganese contamination was present in Water samples. Most of the fodder crops samples were contaminated with all heavy metals having levels of heavy metals above the Recommended Concentrations. It is noted that Pb+2 of Hudiara drain and irrigated Pb+2 of fodder crop were in positive correlation and negative correlation between Pb+2 and Cr+2, Ni+2, Cu+2. There is positive correlation between Cd+2 and Cr+2, Fe+2 and also negative correlation between Cd+2 and Pb+2, Cd+2, Ni+2, Zn+2, Cu+2, Mn+2 of fodder crop irrigated with Hudiara drain

Biosynthesis and characterization of bacterial cellulose membranes presenting relevant characteristics for air/gas filtration

Funding Information: This work was supported by the Associate Laboratory for Green Chemistry ─ LAQV, iNOVA4Health and the Associate Laboratory LS4FUTURE which are financed by Portuguese national funds from the Fundação para a Ciência e Tecnologia (FCT/MCTES, Portugal) ( UIDB/50006/2020 ; UIDP/50006/2020 ; UIDB/04462/2020 , UIDP/04462/2020 ; and LA/P/0087/2020 ; respectively). Arooj Fatima acknowledges FCT for PhD grant reference 2021.07557. BD. The authors acknowledge Professor Vítor D. Alves, from Instituto Superior de Agronomia, Universidade de Lisboa , for the support in the analysis of membrane mechanical properties. Funding Information: The surface area of bacterial cellulose membranes was determined using N2 adsorption/desorption isotherms and reported in Table 2. Both glucose and glycerol supported the bacterial growth that led to the production of membranes with diverse thicknesses, surface porosity and fiber diameter (Table 2). SEM images revealed that pores and fiber channels of varied sizes were present in the structure of all the bacterial cellulose membranes. Among all strains, FXV3 produced membranes with the highest surface area. Furthermore, and overall, adding ethanol made the bacterial cellulose membrane structure denser, resulting into low surface areas. Interestingly, NFXK3 showed the lowest surface area using both glucose and glycerol.This work was supported by the Associate Laboratory for Green Chemistry ─ LAQV, iNOVA4Health and the Associate Laboratory LS4FUTURE which are financed by Portuguese national funds from the Fundação para a Ciência e Tecnologia (FCT/MCTES, Portugal) (UIDB/50006/2020; UIDP/50006/2020; UIDB/04462/2020, UIDP/04462/2020; and LA/P/0087/2020; respectively). Arooj Fatima acknowledges FCT for PhD grant reference 2021.07557. BD. The authors acknowledge Professor Vítor D. Alves, from Instituto Superior de Agronomia, Universidade de Lisboa, for the support in the analysis of membrane mechanical properties. Publisher Copyright: © 2023The production of bacterial cellulose has gained prominence in recent years as an alternative for the sustainable production of materials that might be used in diverse processes and applications. The present study discusses the possibility of producing tailored bacterial cellulose membranes in situ, that present relevant characteristics for potential use in air/gas filtration. Various cultivation processes and characterization studies were performed to ascertain the suitability of Komagataeibacter sp. FXV3, Komagataeibacter sp. NFXK3, and K. intermedius LMG 18909 bacterial strains to produce cellulose membranes with diverse properties. Subsequently, the bacterial cellulose films produced were freeze-dried to obtain stable membranes, and extensively characterized for their physicochemical properties. The results obtained showed that different strains enabled the synthesis of membranes with distinctive morphological properties. Moreover, the different carbon sources and ethanol concentrations employed in the cultivation media led to modifications in the cellulose membranes produced by the different Komagataeibacter strains, which further impacted membrane morphology and, ultimately, gas filtration behavior. All the synthesized membranes were fully characterized, showing adequate mechanical properties, and tested for permeance of N2, CO2 and O2, opening perspectives for their use in air/gas filtration.publishersversionpublishe

Turmeric Extract Rescues Ethanol‐Induced Developmental Defect in the Zebrafish Model for Fetal Alcohol Spectrum Disorder (FASD)

Prenatal ethanol exposure causes the most frequent preventable birth disorder, fetal alcohol spectrum disorder (FASD). The effect of turmeric extracts in rescuing an ethanol‐induced developmental defect using zebrafish as a model was determined. Ethanol‐induced oxidative stress is one of the major mechanisms underlying FASD. We hypothesize that antioxidant inducing properties of turmeric may alleviate ethanol‐induced defects. Curcuminoid content of the turmeric powder extract (5 mg/mL turmeric in ethanol) was determined by UPLC and found to contain Curcumin (124.1 ± 0.2 μg/mL), Desmethoxycurcumin (43.4 ± 0.1 μg/mL), and Bisdemethoxycurcumin (36.6 ± 0.1 μg/mL). Zebrafish embryos were treated with 100 mM (0.6% v/v) ethanol during gastrulation through organogenesis (2 to 48 h postfertilization (hpf)) and supplemented with turmeric extract to obtain total curcuminoid concentrations of 0, 1.16, 1.72, or 2.32 μM. Turmeric supplementation showed significant rescue of the body length at 72 hpf compared to ethanol‐treated embryos. The mechanism underlying the rescue remains to be determined

Effect of Curcuminoids in Turmeric on Developing Zebrafish Treated with Ethanol

poster abstractThis experiment was designed with the intention of determining whether turmeric could act as a rescue agent to prevent or mitigate the extent of Fetal Alcohol Spectrum Disorder (FASD) caused by early ethanol exposure using zebrafish as a model system. A range of turmeric concentrations were made from a stock solution of turmeric dissolved in ethanol (1mg turmeric in 5mL ethanol). The active agents in turmeric are the curcuminoids: Curcumin, Desmethoxycurcumin, and Bisdemethoxycurcumin. The curcuminoids concentration was estimated using liquid chromatography. These agents were present in the turmeric stock solution at the following concentrations: Bisdemethoxycurcumin: 36.6 +/- 0.1 ug/mL, Desmethoxycurcumin: 43.4 +/- 0.1 ug/mL, and Curcumin: 124.1 +/- 0.2 ug/mL. Untreated zebrafish embryos were placed in embryo medium, ethanol treated embryos in 100mM ethanol containing embryo medium, and turmeric co-supplemented medium with differing concentrations of turmeric. Since the turmeric stock solution was dissolved in ethanol, the concentration of ethanol was kept at a constant 100mM ethanol and the amount of turmeric solution added. The concentrations of the test plates were then based on this solution and made to be 100 mM ethanol and 1.16 uM curcuminoids, 100 mM ethanol and 1.74 uM curcuminoids, and 100 mM ethanol and 2.32 uM curcuminoids. The developing embryos were treated with the turmeric solution and/or ethanol during 2-24 hours post fertilization (hpf). These embryos were imaged at 72 hpf and their body length and eye diameter were measured. The embryos supplemented with curcuminoids showed a significant rescue effect on the body length and eye diameter compared to ethanol treated embryos. This indicates that the curcuminoids acted as a rescue agent to reduce the effects that are typical of FASD in developing zebrafish

Waking up dormant tumor suppressor genes with zinc fingers, TALEs and the CRISPR/dCas9 system

The aberrant epigenetic silencing of tumor suppressor genes (TSGs) plays a major role during carcinogenesis and regaining these dormant functions by engineering of sequence-specific epigenome editing tools offers a unique opportunity for targeted therapies. However, effectively normalizing the expression and regaining tumor suppressive functions of silenced TSGs by artificial transcription factors (ATFs) still remains a major challenge. Herein we describe novel combinatorial strategies for the potent reactivation of two class II TSGs, MASPIN and REPRIMO, in cell lines with varying epigenetic states, using the CRISPR/dCas9 associated system linked to a panel of effector domains (VP64, p300, VPR and SAM complex), as well as with protein-based ATFs, Zinc Fingers and TALEs. We found that co-delivery of multiple effector domains using a combination of CRISPR/dCas9 and TALEs or SAM complex maximized activation in highly methylated promoters. In particular, CRISPR/dCas9 VPR with SAM upregulated MASPIN mRNA (22,145-fold change) in H157 lung cancer cells, with accompanying re-expression of MASPIN protein, which led to a concomitant inhibition of cell proliferation and induction of apoptotic cell death. Consistently, CRISPR/dCas9 VP64 with SAM upregulated REPRIMO (680-fold change), which led to phenotypic reprogramming in AGS gastric cancer cells. Altogether, our results outlined novel sequence-specific, combinatorial epigenome editing approaches to reactivate highly methylated TSGs as a promising therapy for cancer and other diseases

New approaches and technical considerations in detecting outlier measurements and trajectories in longitudinal children growth data

Background Growth studies rely on longitudinal measurements, typically represented as trajectories. However, anthropometry is prone to errors that can generate outliers. While various methods are available for detecting outlier measurements, a gold standard has yet to be identified, and there is no established method for outlying trajectories. Thus, outlier types and their effects on growth pattern detection still need to be investigated. This work aimed to assess the performance of six methods at detecting different types of outliers, propose two novel methods for outlier trajectory detection and evaluate how outliers affect growth pattern detection. Methods We included 393 healthy infants from The Applied Research Group for Kids (TARGet Kids!) cohort and 1651 children with severe malnutrition from the co-trimoxazole prophylaxis clinical trial. We injected outliers of three types and six intensities and applied four outlier detection methods for measurements (model-based and World Health Organization cut-offs-based) and two for trajectories. We also assessed growth pattern detection before and after outlier injection using time series clustering and latent class mixed models. Error type, intensity, and population affected method performance. Results Model-based outlier detection methods performed best for measurements with precision between 5.72-99.89%, especially for low and moderate error intensities. The clustering-based outlier trajectory method had high precision of 14.93-99.12%. Combining methods improved the detection rate to 21.82% in outlier measurements. Finally, when comparing growth groups with and without outliers, the outliers were shown to alter group membership by 57.9 -79.04%. Conclusions World Health Organization cut-off-based techniques were shown to perform well in few very particular cases (extreme errors of high intensity), while model-based techniques performed well, especially for moderate errors of low intensity. Clustering-based outlier trajectory detection performed exceptionally well across all types and intensities of errors, indicating a potential strategic change in how outliers in growth data are viewed. Finally, the importance of detecting outliers was shown, given its impact on children growth studies, as demonstrated by comparing results of growth group detection

Intelligent Energy Management across Smart Grids Deploying 6G IoT, AI, and Blockchain in Sustainable Smart Cities

© 2024 The Author(s). Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/In response to the growing need for enhanced energy management in smart grids in sustainable smart cities, this study addresses the critical need for grid stability and efficient integration of renewable energy sources, utilizing advanced technologies like 6G IoT, AI, and blockchain. By deploying a suite of machine learning models like decision trees, XGBoost, support vector machines, and optimally tuned artificial neural networks, grid load fluctuations are predicted, especially during peak demand periods, to prevent overloads and ensure consistent power delivery. Additionally, long short-term memory recurrent neural networks analyze weather data to forecast solar energy production accurately, enabling better energy consumption planning. For microgrid management within individual buildings or clusters, deep Q reinforcement learning dynamically manages and optimizes photovoltaic energy usage, enhancing overall efficiency. The integration of a sophisticated visualization dashboard provides real-time updates and facilitates strategic planning by making complex data accessible. Lastly, the use of blockchain technology in verifying energy consumption readings and transactions promotes transparency and trust, which is crucial for the broader adoption of renewable resources. The combined approach not only stabilizes grid operations but also fosters the reliability and sustainability of energy systems, supporting a more robust adoption of renewable energies.Peer reviewe