Institute of Science and Technology Austria

Persistent multiyear drought (MYD) events pose a growing threat to nature and humans in a changing climate. We identified and inventoried global MYDs by detecting spatiotemporally contiguous climatic anomalies, showing that MYDs have become drier, hotter, and led to increasingly diminished vegetation greenness. The global terrestrial land affected by MYDs has increased at a rate of 49,279 ± 14,771 square kilometers per year from 1980 to 2018. Temperate grasslands have exhibited the greatest declines in vegetation greenness during MYDs, whereas boreal and tropical forests have had comparably minor responses. With MYDs becoming more common, this global quantitative inventory of the occurrence, severity, trend, and impact of MYDs provides an important benchmark for facilitating more effective and collaborative preparedness toward mitigation of and adaptation to such extreme events.

Ternary liquid‐like thermoelectric materials have garnered significant attention due to their ultra‐low lattice thermal conductivity. Among these, Ag8SnSe6 stands out for its exceptionally low sound velocity and thermal conductivity. However, the inherent poor electrical conductivity and suboptimal thermoelectric properties of Ag8SnSe6 necessitate further improvement. Here, a novel approach is initiated to enhance the thermoelectric properties of Ag8SnSe6 by combining low‐dimensionalization with intrinsic doping. For the first time, this work successfully synthesizes single‐phase Ag8SnSe6 nanocrystals, ≈10 nm in size, with the correct phase and composition using a robust and reliable colloidal method. This approach represents a significant improvement over previous reports on this material. Reducing the crystal domains of Ag8SnSe6 to the nanoscale induces quantum confinement effects, increasing the density of states near the Fermi surface. It also introduces additional grain boundaries, which lower the lattice thermal conductivity and simplify structural design. Moreover, incorporating small amounts of Sn nanopowder into the Ag8SnSe6 nanocrystals before consolidation further enhances the thermoelectric performance. Sn acts as a donor dopant, increasing the electronic concentration while at the same time improving their mobility by reducing interface barriers, thus significantly improving the material transport properties. Additionally, the presence of Sn leads to the formation of point defects, dislocations, and secondary phases, which increase phonon scattering and further reduce the thermal conductivity. Through this synergistic optimization, the figure of merit shows a significant increase across a wide temperature range. Overall, a strategy is presented for the controlled preparation of Ag8SnSe6 nanocrystals, the decoupling of their electrical and thermal transport, and the practical application of this material to thermoelectric single‐leg modules.

Polymorphic short insertions and deletions (INDELs ≤ 50 bp) are abundant, although less common than single nucleotide polymorphisms (SNPs). Evidence from model organisms shows INDELs to be more strongly influenced by purifying selection than SNPs. Partly for this reason, INDELs are rarely used as markers for demographic processes or to detect divergent selection. Here, we compared INDELs and SNPs in the intertidal snail Littorina saxatilis, focusing on hybrid zones between ecotypes, in order to test the utility of INDELs in the detection of divergent selection. We computed INDEL and SNP site frequency spectra (SFS) using capture sequencing data. We assessed the impact of divergent selection by analysing allele frequency clines across habitat boundaries. We also examined the influence of GC-biased gene conversion because it may be confounded with signatures of selection. We show evidence that short INDELs are affected more by purifying selection than SNPs, but part of the observed SFS difference can be attributed to GC-biased gene conversion. We did not find a difference in the impact of divergent selection between short INDELs and SNPs. Short INDELs and SNPs were similarly distributed across the genome and so are likely to respond to indirect selection in the same way. A few regions likely affected by divergent selection were revealed by INDELs and not by SNPs. Short INDELs can be useful (additional) genetic markers helping to identify genomic regions important for adaptation and population divergence.

5-Fluorouracil (5-FU) is a firstline chemotherapeutic agent used for treating colorectal cancer, but has short half-life, rapid metabolism which requires its continuous intravenous (IV) infusion, resulting in significant adverse events. synthesis as well as characterizations of 5-FU-loaded thiolated chitosan (TCS)-co-polymethacrylic acid (MAA)-based hydrogel for colon targeting to treat colorectal carcinoma. Free radical polymerization was employed for preparation of the 5-FU-loaded hydrogel. Potassium persulfate (KPS), methylene bis-acrylamide (MBA), and MAA were employed as initiator, crosslinker, and monomer, respectively. All the six 5-FU-TCS-co-poly (MAA) formulations (TCS1-TCS6) were subjected to in-vitro pH-dependent swelling and dissolution studies at pH 1.2 and 7.4 at 37 °C. TCS4 was selected for further in-vivo studies based upon swelling and release patterns evaluation. Reverse phase HPLC (RP-HPLC)-coupled with UV spectrophotometer was employed for estimation of 5-FU in plasma. In-vivo studies were performed to determine pharmacokinetics parameters (i.e., Cmax, tmax and area-under-curve (AUC)) among control and treated groups. Release profile of TCS4 was optimal at pH 7.4. Indeed, 5-FU showed twofold higher release at pH 7.4 than at pH 1.2. Cmax and tmax of TCS4 were found to be 300 ± 0.87 µg/mL and 4 ± 0.00 h, which are significantly higher than Cmax and tmax oral solution (250 ± 0.65 µg/mL and 2 ± 0.00 h) used as a reference. TCS4-treated group depicted AUC0-t of 2767 ± 0.54 ng/ml.hr which was remarkably higher as compared to controlled group. Toxicity studies were carried out on male albino rats and histological slides showed no signs of toxicity. TCS4 hydrogel could be effectively administered per os (orally) to improve the bioavailability of 5-FU. Graphical abstract

Labetalol is an anti-hypertensive medication available in both tablet and liquid injectable forms. However, a transdermal delivery system may offer a more convenient option for patients requiring this medication. Due to its solubility in organic solvents and high molecular weight, a transdermal patch could face challenges in effectively delivering the drug through the stratum corneum, the outermost layer of the skin. To overcome this challenge, labetalol-loaded nanoparticles were prepared using a solvent evaporation method and incorporated into dissolvable microneedle patches. The nanoparticles ensured controlled drug release, while microneedles facilitated drug penetration through the stratum corneum. The patches were formulated with hydroxypropyl methylcellulose and carbopol polymers and evaluated for their mechanical properties, penetration efficacy, drug loading, in vitro drug release, and biological safety. Scanning electron microscopy confirmed uniform nanoparticle distribution, and drug loading efficiency reached 95.25 ± 1.68%. The optimized formulation achieved a sustained in vitro drug release of 89.27 ± 2.34% over 24 h, significantly improving release efficiency compared to conventional oral and injectable labetalol formulations. In contrast to the burst release observed with oral and injectable formulations, the microneedle patch offered controlled and sustained release, enhancing therapeutic outcomes and reducing side effects. Penetration studies demonstrated successful nanoparticle delivery into deeper skin layers, while irritation studies confirmed the safety of the patches. These findings suggest that nanoparticle-loaded dissolvable microneedle patches provide a promising strategy for the transdermal delivery of labetalol, offering controlled drug release and enhanced patient compliance.

Super-resolution methods provide far better spatial resolution than the optical diffraction limit of about half the wavelength of light (∼200-300 nm). Nevertheless, they have yet to attain widespread use in plants, largely due to plants’ challenging optical properties. Expansion microscopy improves effective resolution by isotropically increasing the physical distances between sample structures while preserving relative spatial arrangements and clearing the sample. However, its application to plants has been hindered by the rigid, mechanically cohesive structure of plant tissues. Here, we report on whole-mount expansion microscopy of thale cress (Arabidopsis thaliana) root tissues (PlantEx), achieving a four-fold resolution increase over conventional microscopy. Our results highlight the microtubule cytoskeleton organization and interaction between molecularly defined cellular constituents. Combining PlantEx with stimulated emission depletion (STED) microscopy, we increase nanoscale resolution and visualize the complex organization of subcellular organelles from intact tissues by example of the densely packed COPI-coated vesicles associated with the Golgi apparatus and put these into a cellular structural context. Our results show that expansion microscopy can be applied to increase effective imaging resolution in Arabidopsis root specimens.

We investigate the locality of magnetic response in polycyclic aromatic molecules using a novel deep-learning approach. Our method employs graph neural networks (GNNs) with a graph-of-rings representation to predict Nucleus-Independent Chemical Shifts in the space around the molecule. We train a series of models, each time reducing the size of the largest molecules used in training. The accuracy of prediction remains high (MAE < 0.5 ppm), even when training the model only on molecules with up to 4 rings, thus providing strong evidence for the locality of magnetic response. To overcome the known problem of generalization of GNNs, we implement a k-hop expansion strategy and succeed in achieving accurate predictions for molecules with up to 15 rings (almost 4 times the size of the largest training example). Our findings have implications for understanding the magnetic response in complex molecules and demonstrate a promising approach to overcoming GNN scalability limitations. Furthermore, the trained models enable rapid characterization, without the need for more expensive DFT calculations.

Background We identified small molecule tricyclic pyrone compound CP2 as a mild mitochondrial complex I (MCI) inhibitor that induces neuroprotection in multiple mouse models of AD. One of the major concerns while targeting mitochondria is the production of reactive oxygen species (ROS). CP2 consists of two diastereoisomers, D1 and D2, with distinct activity and toxicity profiles. This study was designed to understand how structure of D1 and D2 affects their binding to MCI and the consequential impact on ROS production. Method The X‐ray crystallography and cryo‐electron microscopy (cryo‐EM) at global resolution of 3.25‐3.27Å were employed to identify the molecular structure of D1 and D2 and the D1 binding to the isolated ovine MCI. The assessment of the MCI inhibition and the extent of ROS generation were done in isolated MCI and human neuroblastoma MC65 cells using flow cytometry, a Seahorse extracellular flux analyzer, and the kinetic studies. Result In the closed conformation of MCI, D1 selectively binds to the deep Quinone‐site (Qd) but not to the shallow Q‐site (Qs), sharing the same binding pocket as rotenone. In the open MCI state, D1 exclusively binds to the Qs in contrast to rotenone, which binds Qd and Qs in both closed and open states. At the same concentrations, D1 inhibits respiration to a greater extent compared to D2 (5:1 ratio) and produces higher level of ROS. Conclusion Cryo‐EM unambiguously identified binding of D1 to both the Qd and Qs sites, contingent upon the conformational state of MCI. In contrast to rotenone, D1 binds Qd only in the closed conformation during catalytic cycle, leading to mild inhibition. Superimposing X‐ray crystallography data of D1 and D2 onto cryo‐EM data suggests that the orientation of the methyl group in D2 induces a flatter conformation, resulting in lower binding affinity to MCI, which correlates with lower inhibition and toxicity compared to D1. At physiologically relevant concentrations, CP2 (D1:D2 = 1:1) demonstrates low MCI inhibition yielding negligible ROS levels. This observation provides new insight into the absence of toxicity associated with CP2 treatment in vivo, further highlighting feasibility for the development of safe and efficacious MCI inhibitors.

Type II CRISPR endonucleases are widely used programmable genome editing tools. Recently, CRISPR-Cas systems with highly compact nucleases have been discovered, including Cas9d (a type II-D nuclease). Here, we report the cryo-EM structures of a Cas9d nuclease (747 amino acids in length) in multiple functional states, revealing a stepwise process of DNA targeting involving a conformational switch in a REC2 domain insertion. Our structures provide insights into the intricately folded guide RNA which acts as a structural scaffold to anchor small, flexible protein domains for DNA recognition. The sgRNA can be truncated by up to ~25% yet still retain activity in vivo. Using ancestral sequence reconstruction, we generated compact nucleases capable of efficient genome editing in mammalian cells. Collectively, our results provide mechanistic insights into the evolution and DNA targeting of diverse type II CRISPR-Cas systems, providing a blueprint for future re-engineering of minimal RNA-guided DNA endonucleases.

In this study, we investigate the thermoelectric properties of functionalized multi-walled carbon nanotubes (F-MWCNTs) dispersed over a flexible substrate through a facile vacuum filtration route. To improve their interfacial adhesion and dispersion, F-MWCNTs underwent hot-pressing. The heat-treatment has improved the nanotubes' connections and subsequently reduced porosity as well, which results in an increasing electrical conductivity upon increasing temperature of hot-pressing. Thermoelectric power factor (PF) value was greatly increased upon simultaneous heating and pressing of the CNTs and a highest PF value of 3.17 μW m⁻¹ K⁻² at 398 K, has been achieved, which is about 400% higher than that of the as-deposited CNTs without hot pressing. The current study presents a prototype for CNT-based flexible thermoelectric devices which opens up an avenue for the deployment of CNTs into flexible electronics.

Transcription by RNA polymerase II (Pol II) can be repressed by noncoding RNA, including the human RNA Alu. However, the mechanism by which endogenous RNAs repress transcription remains unclear. Here we present cryogenic-electron microscopy structures of Pol II bound to Alu RNA, which reveal that Alu RNA mimics how DNA and RNA bind to Pol II during transcription elongation. Further, we show how distinct domains of the general transcription factor TFIIF control repressive activity. Together, we reveal how a noncoding RNA can regulate mammalian gene expression.

Mosaic Analysis with Double Markers (MADM) represents a mouse genetic approach coupling differential fluorescent labeling to genetic manipulations in dividing cells and their lineages. MADM uniquely enables the generation and visualization of individual control or homozygous mutant cells in a heterozygous genetic environment. Among its diverse applications, MADM has been used to dissect cell-autonomous gene functions important for cortical development and neural development in general. The high cellular resolution offered by MADM also permits the analysis of transcriptomic changes of individual cells upon genetic manipulations. In this chapter, we describe an experimental protocol combining the generation and isolation of MADM-labeled cells with downstream single-cell RNA-sequencing technologies to probe cell-type specific phenotypes due to genetic mutations at single-cell resolution.

Many biological systems operate near the physical limits to their performance, suggesting that aspects of their behavior and underlying mechanisms could be derived from optimization principles. However, such principles have often been applied only in simplified models. Here, we explore a detailed mechanistic model of the gap gene network in the Drosophila embryo, optimizing its 50+ parameters to maximize the information that gene expression levels provide about nuclear positions. This optimization is conducted under realistic constraints, such as limits on the number of available molecules. Remarkably, the optimal networks we derive closely match the architecture and spatial gene expression profiles observed in the real organism. Our framework quantifies the tradeoffs involved in maximizing functional performance and allows for the exploration of alternative network configurations, addressing the question of which features are necessary and which are contingent. Our results suggest that multiple solutions to the optimization problem might exist across closely related organisms, offering insights into the evolution of gene regulatory networks.

Feature selection is essential in the analysis of molecular systems and many other fields, but several uncertainties remain: What is the optimal number of features for a simplified, interpretable model that retains essential information? How should features with different units be aligned, and how should their relative importance be weighted? Here, we introduce the Differentiable Information Imbalance (DII), an automated method to rank information content between sets of features. Using distances in a ground truth feature space, DII identifies a low-dimensional subset of features that best preserves these relationships. Each feature is scaled by a weight, which is optimized by minimizing the DII through gradient descent. This allows simultaneously performing unit alignment and relative importance scaling, while preserving interpretability. DII can also produce sparse solutions and determine the optimal size of the reduced feature space. We demonstrate the usefulness of this approach on two benchmark molecular problems: (1) identifying collective variables that describe conformations of a biomolecule, and (2) selecting features for training a machine-learning force field. These results show the potential of DII in addressing feature selection challenges and optimizing dimensionality in various applications. The method is available in the Python library DADApy.

The scales of the gold-dust weevil Hypomeces squamosus are green because of three-dimensional diamond-type chitin–air photonic crystals with an average periodicity of about 430 nm and a chitin fill fraction of about 0.44. A single scale usually contains one to three crystallites with different lattice orientations. The reciprocal space images and reflection spectra obtained from single domains indicated a partial photonic bandgap in the wavelength range from 450 to 650 nm. Light reflected from {111}-oriented domains is green-yellow. Light reflected from blue, {100}-oriented domains exhibits polarization conversion, rotating the angle of linearly polarized light. The overall coloration, resulting from the reflections from many scales, is close to uniformly diffuse because of the random orientation of the domains. Using titania sol–gel chemistry, we produced negative replicas that exhibited a 70 to 120 nm redshift of the bandgap, depending on the lattice orientation. The wavelength shift in {100} orientation is supported by full-wave optical modeling of a dual diamond network with an exchanged fill fraction (0.56) of the material with the refractive index in the range of 1.55 to 2.00. The study suggests that the effective refractive index of titania in the 3D lattice is similar to that in sol–gel films. The study demonstrates the potential of replicating complex biophotonic structures using the sol–gel technique. Optimization of the sol–gel process could lead to customizable photonic bandgaps that might be used in novel optical materials.

Biophysical constraints limit the specificity with which transcription factors (TFs) can target regulatory DNA. While individual nontarget binding events may be low affinity, the sheer number of such interactions could present a challenge for gene regulation by degrading its precision or possibly leading to an erroneous induction state. Chromatin can prevent nontarget binding by rendering DNA physically inaccessible to TFs, at the cost of energy-consuming remodeling orchestrated by pioneer factors (PFs). Under what conditions and by how much can chromatin reduce regulatory errors on a global scale? We use a theoretical approach to compare two scenarios for gene regulation: one that relies on TF binding to free DNA alone and one that uses a combination of TFs and chromatin-regulating PFs to achieve desired gene expression patterns. We find, first, that chromatin effectively silences groups of genes that should be simultaneously OFF, thereby allowing more accurate graded control of expression for the remaining ON genes. Second, chromatin buffers the deleterious consequences of nontarget binding as the number of OFF genes grows, permitting a substantial expansion in regulatory complexity. Third, chromatin-based regulation productively co-opts nontarget TF binding for ON genes in order to establish a “leaky” baseline expression level, which targeted activator or repressor binding subsequently up- or down-modulates. Thus, on a global scale, using chromatin simultaneously alleviates pressure for high specificity of regulatory interactions and enables an increase in genome size with minimal impact on global expression error.

Introduction The National Medicine Policy (NMP) is crucial for setting the direction of a country’s action plan to achieve targeted healthcare goals. Objective This study aimed to explore the perceptions of different stakeholders regarding the current NMP of Pakistan. Methods A qualitative study design was employed using purposive sampling to identify respondents. Semi-structured interviews were conducted with regulators (n = 6), manufacturers (n = 8), healthcare professionals (n = 9), and academicians (n = 7) until saturation was reached. Interviews were conducted at convenient times and locations, recorded, transcribed verbatim, and subjected to thematic analysis. Results Most stakeholders demonstrated expertise in policy-making and understood the basic concepts, need, and importance of the NMP. Six key themes were identified: general understanding of the NMP, existing regulatory framework and NMP, essential medicines and the current healthcare system, comparison of NMP with international standards, focus of NMP for better provision of healthcare, and recommendations for an effective NMP for Pakistan. Stakeholders emphasized the need for policies to set Standard Operating Procedures and direction, and noted that some frameworks require revision. There was consensus that the availability of essential medicines needs improvement and that the current healthcare system requires revamping, as the National Essential Medicine List is not fully implemented. Conclusion The study concludes that NMP is integral to a robust healthcare system. However, Pakistan lacks an effective NMP despite extensive efforts in recent years. This deficiency is attributed to scarce resources, lack of political will and ownership, and inadequate compliance with performance-based indicators.