CENP-A is a histone variant, which replaces histone H3 at centromeres and confers unique properties to centromeric chromatin. The crystal structure of CENP-A nucleosome suggests flexible nucleosomal ...DNA ends, but their dynamics in solution remains elusive and their implication in centromere function is unknown. Using electron cryo-microscopy, we determined the dynamic solution properties of the CENP-A nucleosome. Our biochemical, proteomic, and genetic data reveal that higher flexibility of DNA ends impairs histone H1 binding to the CENP-A nucleosome. Substituting the 2-turn αN-helix of CENP-A with the 3-turn αN-helix of H3 results in compact particles with rigidified DNA ends, able to bind histone H1. In vivo replacement of CENP-A with H3-CENP-A hybrid nucleosomes leads to H1 recruitment, delocalization of kinetochore proteins, and significant mitotic and cytokinesis defects. Our data reveal that the evolutionarily conserved flexible ends of the CENP-A nucleosomes are essential to ensure the fidelity of the mitotic pathway.
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•CENP-A nucleosomal ends are highly flexible in solution•Dynamic CENP-A nucleosomal ends prevent H1 recruitment•Flexibility of DNA ends allows active kinetochore complex assembly•Open CENP-A nucleosomal structure is essential for its mitotic function
In this issue of Molecular Cell, Roulland et al. describe the structural features of a CENP-A nucleosome and identify the mechanism by which its flexible DNA arms interfere with linker histone H1 recruitment, assist active kinetochore assembly, and ensure mitotic fidelity.
Large size of capacitors is the main hurdle in miniaturization of current electronic devices. Herein, a scalable solution‐based layer‐by‐layer engineering of metallic and high‐κ dielectric nanosheets ...into multilayer nanosheet capacitors (MNCs) with overall thickness of ≈20 nm is presented. The MNCs are built through neat tiling of 2D metallic Ru0.95O20.2− and high‐κ dielectric Ca2NaNb4O13− nanosheets via the Langmuir–Blodgett (LB) approach at room temperature which is verified by cross‐sectional high‐resolution transmission electron microscopy (HRTEM). The resultant MNCs demonstrate a high capacitance of 40–52 µF cm−2 and low leakage currents down to 10−5–10−6 A cm−2. Such MNCs also possess complimentary in situ robust dielectric properties under high‐temperature measurements up to 250 °C. Based on capacitance normalized by the thickness, the developed MNC outperforms state‐of‐the‐art multilayer ceramic capacitors (MLCC, ≈22 µF cm−2/5 × 104 nm) present in the market. The strategy is effective due to the advantages of facile, economical, and ambient temperature solution assembly.
2D high‐κ perovskite nanosheet (Ca2NaNb4O13−; εr = 300) is exploited for the development of layer‐by‐layer assembled multilayer capacitors. The resultant multilayer nanosheet capacitors demonstrate high capacitance of 40–52 µF cm−2 and low leakage currents down to 10−5–10−6 A cm−2. Nanosheet‐based capacitors perform about 5000 times better than state‐of‐the‐art capacitors, offering great potential for the rational design and construction of future electronics.
Physical properties such as density, refractive index and viscosity of aqueous sodium salt of l-phenylalanine (Na-Phe) were investigated in this work. These properties were measured over a ...temperature range of 298.15-343.15 K, and at atmospheric pressure. The mass fractions (w) of Na-Phe were 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35 and 0.40 respectively. The analysis of the experimental data shows that the values of density, refractive index and viscosity decrease with an increase in temperature at any constant concentration of Na-Phe. However, these values increase with the rise of concentration isothermally. The density values were used for estimation of thermal expansion coefficient. The thermal expansion coefficient increases slightly with the increase in temperature and concentration. Density and refractive index data were correlated using modified Graber equation, while, viscosity data were correlated using modified Vogel-Tamman-Fulcher (VTF) equation. In all the cases, a quantitative analysis of the influence of temperature and concentration was carried out.
SUMMARYThe danger of a global pandemic caused by zoonotic influenza viruses is increasing as the frequency of human illnesses caused by avian and swine flu viruses rises. Global pandemic preparedness ...initiatives have largely concentrated on H5N1 avian influenza virus. In this review, we compile the research on H5N1 virus prevalence and risk assessment, and we augment this with an overview of recent molecular evaluations of important markers of mammalian adaptation found in haemagglutinin and polymerase proteins (PB2, PB1 and PA). There is increasing evidence that H5N1 viruses circulating among various species in Indonesia (Indonesian and Eurasian lineages) are constantly adapting, resulting in the emergence of new strains with high affinity to the α2,6 receptor and enhanced polymerase function in mammalian cells. The pandemic risk presented by this virus subtype is further exacerbated by higher prevalence rates of particular mammalian adaptation markers and the increased transmission of particular viruses in mammalian animal models.
This study investigates the chemical composition of soyhulls (SHs) as an alternative feed ingredient and their effect on nutrient and amino acid (AA) digestibility in laying hens during peak ...production. A total of 200 golden brown hens (28 weeks old) were subjected to random allocation across 5 dietary treatments: a corn–soybean meal (SBM) reference diet and 4 test diets with 25% SHs from different mills (SH1, SH2, SH3, and SH4). Each treatment was replicated four times with ten birds per replicate. Digesta samples were collected during three phases (28–32, 32–36, and 36–40 weeks of age) to measure apparent metabolizable energy (AME), the apparent ileal digestibility (AID) of nutrients, and the standard ileal digestibility (SID) of AAs. The SBM diet had 30.0% crude protein (CP) and 3.78% crude fiber (CF), while the SH diets had 21.0 to 21.5% CP and 11.6% CF. The findings revealed that the AME was lower (p < 0.05) with SH diets (2404 kcal/kg) compared to the SBM diet (2627 kcal/kg) in all three phases. The SH diets had a lower AID of dry matter (DM), crude protein (CP), ash, ether extract (EE), and crude fiber (CF) than the SBM diet by an average of 2.88, 2.25, 4.93, 4.99, and 3.36%, respectively. The AID of nitrogen-free extract (NFE) was higher in the SH diets than the SBM diet by 3.42% in all three phases (p < 0.05). The SH diets had lower uric acid excretion (about 66.93 mg/100 mL) than the SBM diet (about 76.43 mg/100 mL) on average in all three phases. The SH diets had a lower SID of arginine, histidine, isoleucine, lysine, cysteine, valine, and tyrosine than the SBM diet by 2 to 10%, while the SID of methionine was higher in the SH diets than the SBM diet by 2.2% on average in all three phases (p < 0.05). The SH from Sadiq Brother Feed (SH1) had the highest AME and AID of DM, ash, CP, EE, CF, and the SID of AA among the SH diets. These results indicate that SH can partially replace SBM in laying hen diets, but the source and quality of SH should be considered.
The current study aims to synthesize bimetal oxide nanoparticles (zinc and manganese ions) using the
leaf extract. The crystallite size of the nanoparticle from X-ray diffraction method was found to ...be 19.23 nm. The nanosheet morphology was established from Scanning Electron Microscopy. Energy-dispersive X-ray diffraction was used to determine the elemental content of the synthesized material. The atomic percentage of Mn and Zn was found to be 15.13 and 26.63. The weight percentage of Mn and Zn was found to be 7.08 and 10.40. From dynamic light scattering analysis, the hydrodynamic diameter and zeta potential was found to be 135.1 nm and -33.36 eV. The 1,1-diphenyl-2-picryl hydroxyl radical, hydroxyl radical, FRAP, and hydrogen peroxide scavenging tests were used to investigate the antioxidant activity of Mn-Zn NPs. Mn-Zn NPs have substantial antioxidant properties. The photocatalytic activity of the Mn-Zn NPs was assessed by their ability to degrade Erichrome black T (87.67%), methyl red dye (78.54%), and methyl orange dye (69.79%). Additionally, it had significant antimicrobial action
showed a higher zone of inhibition 14.3 ± 0.64 mm. Mn-Zn nanoparticles were utilized as a catalyst for
-nitrophenol reduction. The bimetal oxide Mn-Zn NPs synthesized using
leaf extract exhibited promising dye degradation activity in wastewater treatment. Thus, the aforementioned approach will be a novel, low cost and ecofriendly approach.
Along with the adoption of 5G, the development of neutral host solutions provides a unique opportunity for mobile networks operators to accommodate the needs of emerging use-cases and in the ...consolidation of new business models. By exploiting the concept of network slicing, as one key enabler in the transition to 5G, infrastructure and service providers can logically split a shared physical network into multiple isolated and customized networks to flexibly address the specific demands of those tenant slices. Motivated by this reality, the H2020 5GCity project proposed a novel 5G-enabled neutral host framework for three European cities: Barcelona (ESP), Bristol (UK), and Lucca (IT). This article revises the main achievements and contributions of the 5GCity project, focusing on the deployment and validation of the proposed framework. The developed neutral host framework encompasses two main parts: the infrastructure and the software platform. A detailed description of the framework implementation, in terms of functional capabilities and practical implications of city-wide deployments, is provided in this article. This work also presents the performance evaluation of the proposed solution during the implementation of real vertical use cases. Obtained results validate the feasibility of the neutral host model and the proposed framework to be deployed in city-wide 5G infrastructures.
This study investigated the effects of the β-mannanase enzyme and soyhulls on production performance, economics, egg quality, hematology and serum biochemistry, nutrient digestibility, gut ...morphology, digesta viscosity, and excreta consistency in laying hens during the late peak production phase (37 to 40 weeks of age). Golden brown hens (RIR × Fayoumi; n = 200) were fed a control diet (no soyhulls or enzymes) and diets containing four combinations, i.e., 3% soyhulls with 20 mg/kg β-mannanase (D1), 3% soyhulls with 30 mg/kg β-mannanase (D2), 9% soyhulls with 20 mg/kg β-mannanase (D3), and 9% soyhulls with 30 mg/kg β-mannanase (D4), for four weeks in four replicates of 10 birds each. Overall, a significantly higher (p < 0.05) feed intake, weight gain, feed conversion ratio, and water intake were calculated in the D2 group as compared to the control and remaining combinations of soyhulls and β-mannanase. No mortality was recorded during the entire experiment. Economically, the D1 and D2 groups showed the best results as compared to the D3 and D4 groups. Egg quality parameters like egg weight, shell weight and shell thickness, yolk weight, albumen weight and height, and the Haugh unit remained unchanged (p > 0.05). Similarly, the D2 group showed significantly lower total cholesterol, LDL, and VLDL levels and enhanced gut morphology with greater villus width, height, crypt depth, and surface area across intestinal segments. Crude protein (CP), crude fiber (CF), crude fat, and ash digestibility were higher (p < 0.05) in the D1 and D2 groups compared to the control. Digesta viscosity, excreta consistency, and other egg quality parameters remained unaffected. In conclusion, the dietary inclusion of a combination of 3% soyhulls and 30 mg/kg β-mannanase may have potential benefits for laying hens by improving some production performance and egg quality indicators and economics, lowering blood cholesterol, LDL, and VLDL levels, enhancing nutrient digestibility, and improving gut morphology without affecting egg quality.
We describe five members of a consanguineous Pakistani family (Family I) plus two affected children from families of different ethnic origins presenting with neurodevelopmental disorders with ...overlapping features. All affected individuals from families have intellectual disability (ID), ranging from mild to profound, and reduced motor and cognitive skills plus variable features including short stature, microcephaly, developmental delay, hypotonia, dysarthria, deafness, visual problems, enuresis, encopresis, behavioural anomalies, delayed pubertal onset and facial dysmorphism. We first mapped the disease locus in the large family (Family I), and by exome sequencing identified homozygous ZNF407 c.2814_2816dup (p.Val939dup) in four affected members where DNA samples were available. By exome sequencing we detected homozygous c.2405G>T (p.Gly802Val) in the affected member of Family II and compound heterozygous variants c.2884C>G (p.Arg962Gly) and c.3642G>C (p.Lys1214Asn) in the affected member of Family III. Homozygous c.5054C>G (p.Ser1685Trp) has been reported in two brothers with an ID syndrome. Affected individuals we present did not exhibit synophrys, midface hypoplasia, kyphosis, 5th finger camptodactyly, short 4th metatarsals or limited knee mobility observed in the reported family.
The economy of a country is directly proportional to the power sector of that country. An unmanaged power sector causes instability in the country. Pakistan is also facing this phenomenon due to ...uncontrolled power outage and circular debt. Pakistan’s power sector is analyzed as a case study to find out the root cause for the unmanaged power sector and for proposing the most effective data-driven solution. After a literature review and discussion with domain experts, it was found that inaccurate power demand forecast is one of the main reasons for power crisis in Pakistan. Under-forecasting caused load shedding, and over-forecasting increased circular debt due to idle capacity payments. Previously, traditional statistical methods were used for power demand forecasting. The multiple linear regression model that is being used since 2018 (IGCEP) uses features such as previous year load and demographic and economic variables for long-term peak power demand forecasting till 2030. The problem is that the independent variables used in existing models are manipulated and cause a gap between actual and forecasted power demand. Moreover, even yearly peak power demand is not absolutely linear in nature; hence, it is necessary to apply AI-based techniques that can handle nonlinearity effectively. Not using system-generated data, not using the most appropriate features, not using an appropriate forecasting time horizon, and not using the appropriate forecasting model are main reasons for inaccurate peak power demand forecasting. The issue can be resolved by forecasting monthly peak power demand for the next 5 years by using the National Power Control Center’s (NPCC) system-generated data. Accurate monthly peak load forecasting leads to accurate yearly peak power demand. The monthly peak load forecasting strategy not only helps in managing operational issues of the power sector such as fuel scheduling and power plant maintenance scheduling but also guides decision-makers toward power and transmission expansion or contraction in the long term. More accurate monthly peak power demand forecasting can be achieved by applying nonlinear AI models in a comprehensive dataset comprising new engineered features, climate features, and the number of consumers. All these features are mostly system-generated and cannot be manipulated. As a result, the accuracy is improved and the results are more reliable than those of the existing models. The new features can be engineered from recent monthly peak load data generated by the system operator (NPCC). Climate features are collected from the Meteorological Department of Pakistan through sensors or database connectivity. The number of electricity consumers can be extracted from NEPRA’s state-of-industry report. All three datasets are combined on a common key (month–year) to a comprehensive dataset, which is passed through different AI models. In the experimental setup, it is found that support vector regression (SVR) produces the most accurate results, with an R-square of 99%, RMSE of 28, and MAPE of 0.1355, which are the best results compared to the literature reviewed.
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