A quadrotor unmanned aerial vehicle (UAV) must achieve desired flight missions despite internal uncertainties and external disturbances. This paper proposes an adaptive trajectory tracking control method that attenuates unknown uncertainties and disturbances. Although the quadrotor is underactuated, a fully actuated controller is designed using backstepping control. To avoid repeated derivatives of control inputs, a dynamic surface method introduces a filter and auxiliary controller. Lyapunov criteria guide adaptive laws for tuning controller gain and filters. A low-power observer is integrated for state estimation. Additionally, a disturbance observer is developed and combined with the control scheme to handle unknown disturbances. Simulations on a DJI F450 quadrotor demonstrate that the proposed control algorithm offers strong trajectory-tracking performance and system stability under multiple uncertainties and external disturbances during flight.

G-quadruplexes and i-motifs are non-canonical secondary structures of DNA that act as conformational switches in controlling genomic events. Within the genome, G- and C-rich sequences with the potential to fold into G-quadruplexes and i-motifs are overrepresented in important regulatory domains, including, but not limited to, the promoter regions of oncogenes. We previously have shown that some promoter sequences can adopt coexisting duplex, G-quadruplex, i-motif, and coiled conformations; moreover, their distribution can be modelled as a dynamic equilibrium in which the fractional population of each conformation is determined by the sequence and local conditions. On that basis, we proposed a hypothesis in which the level of expression of a gene with G- and C-rich sequences in the promoter is regulated thermodynamically by fine-tuning the duplex-to-G-quadruplex ratio, with the G-quadruplex modulating RNA polymerase activity. Any deviation from the evolutionarily tuned, gene-specific distribution of conformers, such as might result from mutations in the promoter or a change in cellular conditions, may lead to under- or overexpression of the gene and pathological consequences. We now expand on this hypothesis in the context of supporting evidence from molecular and cellular studies and from biophysico-chemical investigations of oligomeric DNA. Thermodynamic control of transcription implies that G-quadruplex and i-motif structures in the genome form as thermodynamically stable conformers in competition with the duplex conformation. That is in addition to their recognized formation as kinetically trapped, metastable states within domains of single-stranded DNA, such as a transcription bubble or R-loop, that are opened in a prior cellular event.

Computational immunology has been the breeding ground of some of the best bioinformatics work of the day. By melding diverse data types, these approaches have been successful in associating genotypes with phenotypes. However, the representations (or spaces) in which these associations are mapped have primarily been constructed from some omics-oriented sequence data typically derived from high-throughput experiments. In this perspective, we highlight the importance of biophysical representations for performing the genotype–phenotype map. We contend that using biophysical representations reduces the dimensionality of a search problem, dramatically expedites the algorithm, and more importantly, offers physical interpretability to the classes of clustered sequences across different layers of complexity – molecular, cellular, or macro-level. Such biophysical interpretations offer a firm basis for the future of bioengineering and cell-based therapies.

Viruses are highly dynamic macromolecular assemblies. They undergo large-scale changes in structure and organization at nearly every stage of their infectious cycles from virion assembly to maturation, receptor docking, cell entry, uncoating and genome delivery. Understanding structural transformations and dynamics across the virus infectious cycle is an expansive area for research that that can also provide insight into mechanisms for blocking infection, replication, and transmission. Additionally, the processes viruses carry out serve as excellent model systems for analogous cellular processes, but in more accessible form. Capturing and analyzing these dynamic events poses a major challenge for many structural biological approaches due to the size and complexity of the assemblies and the heterogeneity and transience of the functional states that are populated. Here we examine the process of protein-mediated membrane fusion, which is carried out by specialized machinery on enveloped virus surfaces leading to delivery of the viral genome. Application of two complementary methods, cryo-electron tomography and structural mass spectrometry enable dynamic intermediate states in intact fusion systems to be imaged and probed, providing a new understanding of the mechanisms and machinery that drive this fundamental biological process.

Integrins are critical transmembrane receptors that connect the extracellular matrix (ECM) to the intracellular cytoskeleton, playing a central role in mechanotransduction – the process by which cells convert mechanical stimuli into biochemical signals. The dynamic assembly and disassembly of integrin-mediated adhesions enable cells to adapt continuously to changing mechanical cues, regulating essential processes such as adhesion, migration, and proliferation. In this review, we explore the molecular clutch model as a framework for understanding the dynamics of integrin – ECM interactions, emphasizing the critical importance of force loading rate. We discuss how force loading rate bridges internal actomyosin-generated forces and ECM mechanical properties like stiffness and ligand density, determining whether sufficient force is transmitted to mechanosensitive proteins such as talin. This force transmission leads to talin unfolding and activation of downstream signalling pathways, ultimately influencing cellular responses. We also examine recent advances in single-molecule DNA tension sensors that have enabled direct measurements of integrin loading rates, refining the range to approximately 0.5–4 pN/s. These findings deepen our understanding of force-mediated mechanotransduction and underscore the need for improved sensor designs to overcome current limitations.

Transcription of DNA into RNA is a fundamental cellular process upon which life depends. It is tightly regulated in several different ways, and among the most important mechanisms are protein-induced topological changes in DNA such as looping. In vivo neither transcription, nor protein-induced looping dynamics exhibited by individual molecules are easily monitored. In vitro single-molecule approaches do offer that possibility, but assays are conducted in rarefied, saline buffer conditions which greatly differ from the crowded intracellular environment. In the following, we describe monitoring both transcription and lac repressor-mediated DNA looping of single DNA molecules in the presence of different concentrations of crowders to bridge the gap between in vitro and in vivo experimentation. We found that crowding shifts the preferred orientation of DNA strands in the looped complex. Crowding also attenuates the rate of transcript elongation and enhances readthrough at the terminator. Clearly, the activities of proteins involved in gene regulation are modified in surprising ways by crowding.

We present a construction of left braces of right nilpotency class at most two based on suitable actions of an abelian group on itself with an invariance condition. This construction allows us to recover the construction of a free right nilpotent one-generated left brace of class two.

Neurodegenerative disorders, such as Alzheimer’s and Parkinson’s diseases, are associated with the formation of amyloid fibrils. The DNAJB6b (JB6) chaperone greatly inhibits the disease-related self-assembly of amyloid peptides in an ATP-independent manner. The molecular basis of this process is, however, not understood. Here, we studied the low complexity linker between the N- and C-terminal domains of JB6 as an isolated 110 amino acid residue construct, to get a better understanding of the role of the composition of the intact protein. We investigate the structure and aggregation behaviour of the linker and its anti-amyloid activity in comparison with the full-length chaperone. We find that the linker contains ca. 45% α-helix and 20% β-sheet and is in itself an amyloid-like peptide that self-assembles into different structures, which are bigger than those formed by the intact chaperone, including fibrils. The isolated linker protects against fibril formation of Aβ42 as well as α-synuclein, but is less potent than the intact chaperone. Based on our results, we propose a possible mechanism behind JB6 and linker amyloid suppression relating to their self-assembly behaviour. In the intact protein, the domains serve to solubilize the linker such that the solution concentration of exposed linker is high enough to sustain its high potency against amyloid formation.

Let $B^{H}$ be a d-dimensional fractional Brownian motion with Hurst index $H\in(0,1)$, $f\,:\,[0,1]\longrightarrow\mathbb{R}^{d}$ a Borel function, and $E\subset[0,1]$, $F\subset\mathbb{R}^{d}$ are given Borel sets. The focus of this paper is on hitting probabilities of the non-centered Gaussian process $B^{H}+f$. It aims to highlight how each component f, E and F is involved in determining the upper and lower bounds of $\mathbb{P}\{(B^H+f)(E)\cap F\neq \emptyset \}$. When F is a singleton and f is a general measurable drift, some new estimates are obtained for the last probability by means of suitable Hausdorff measure and capacity of the graph $Gr_E(f)$. As application we deal with the issue of polarity of points for $(B^H+f)\vert_E$ (the restriction of $B^H+f$ to the subset $E\subset (0,\infty)$).

Integrative modeling enables structure determination for large macromolecular assemblies by combining data from multiple experiments with theoretical and computational predictions. Recent advancements in AI-based structure prediction and cryo electron-microscopy have sparked renewed enthusiasm for integrative modeling; structures from AI-based methods can be integrated with in situ maps to characterize large assemblies. This approach previously allowed us and others to determine the architectures of diverse macromolecular assemblies, such as nuclear pore complexes, chromatin remodelers, and cell–cell junctions. Experimental data spanning several scales was used in these studies, ranging from high-resolution data, such as X-ray crystallography and AlphaFold structure, to low-resolution data, such as cryo-electron tomography maps and data from co-immunoprecipitation experiments. Two recurrent modeling challenges emerged across a range of studies. First, these assemblies contained significant fractions of disordered regions, necessitating the development of new methods for modeling disordered regions in the context of ordered regions. Second, methods needed to be developed to utilize the information from cryo-electron tomography, a timely challenge as structural biology is increasingly moving towards in situ characterization. Here, we recapitulate recent developments in the modeling of disordered proteins and the analysis of cryo-electron tomography data and highlight other opportunities for method development in the context of integrative modeling.

The transport industry of Ukraine is an integral part of its economy. According to the National Transport Strategy of Ukraine, a critical strategic goal is to enhance transport safety. Currently, there is a gap in mobile devices capable of automatically measuring slopes and evenness of both runways and road surfaces in two coordinates. This paper addresses the creation of new methods for assessing longitudinal and transverse slopes using micromechanical systems. The study highlights international experiences, presents practical applications and proposes strategies for overcoming implementation challenges. A detailed roadmap for deployment and further improvements is provided.

Synthetic biology aims to create a viable synthetic cell. However, to achieve this goal, it is essential first to gain a profound understanding of the cellular systems used to build that cell, how to reconstitute those systems in the compartments, and how to track their function. Transcription and translation are two vital cellular systems responsible for the production of RNA and, consequently, proteins, without which the cell would not be able to maintain itself or fulfill its functions. This review discusses in detail how the Protein synthesis Using Recombinant Element (PURE) system and cell lysate are used to reconstitute transcription–translation in vitro. Furthermore, it examines how these systems can be encapsulated in GUVs using the existing methods. It also assesses approaches available to image transcription and translation with a diverse arsenal of fluorescence microscopy techniques and a broad collection of probes developed in recent decades. Finally, it highlights solutions for the challenge ahead, namely the decoupling of the two systems in PURE, and discusses the prospects of synthetic biology in the modern world.

Single-stranded nucleic acid (ssNA) binding proteins must both stably protect ssNA transiently exposed during replication and other NA transactions, and also rapidly reorganize and dissociate to allow further NA processing. How these seemingly opposing functions can coexist has been recently elucidated by optical tweezers (OT) experiments that isolate and manipulate single long ssNA molecules to measure conformation in real time. The effective length of an ssNA substrate held at fixed tension is altered upon protein binding, enabling quantification of both the structure and kinetics of protein–NA interactions. When proteins exhibit multiple binding states, however, OT measurements may produce difficult to analyze signals including non-monotonic response to free protein concentration and convolution of multiple fundamental rates. In this review we compare single-molecule experiments with three proteins of vastly different structure and origin that exhibit similar ssNA interactions. These results are consistent with a general model in which protein oligomers containing multiple binding interfaces switch conformations to adjust protein:NA stoichiometry. These characteristics allow a finite number of proteins to protect long ssNA regions by maximizing protein–ssNA contacts while also providing a pathway with reduced energetic barriers to reorganization and eventual protein displacement when these ssNA regions are diminished.

This paper analyses the performance of the Australian and New Zealand Satellite-Based Augmentation System (Aus-NZ SBAS) test-bed to evaluate its use in civil aviation applications with a focus on dual-frequency multi-constellation (DFMC) signals. The Aus-NZ SBAS test-bed performance metrics were determined using kinematic data recorded in flight across a variety of environments and operational conditions. A total of 14 tests adding up to 32 h of flight were evaluated. Flight test data were processed in both the L1 SBAS and DFMC SBAS modes supported by the test-bed broadcasts. The performance results are reviewed regarding accuracy, availability and integrity metrics and compared with the requirement thresholds defined by the International Civil Aviation Organisation (ICAO) for Precision Approach (PA) flight operations. The experimentation performed does not allow continuity assessment as specified in the standard due to a long-term statistical requirement and inherent limitations imposed by the reference station network. Analysis of flight test results shows that DFMC SBAS provides several performance improvements over single-frequency SBAS, tightening both horizontal and vertical protection levels and resulting in greater service availability during the approach.

This work offers a comprehensive approach to understanding the phenomena underlying vesicular exocytosis, a process involved in vital functions of living organisms such as neuronal and neuroendocrine signaling. The kinetics of release of most neuromediators that modulate these functions in various ways can be efficiently monitored using single-cell amperometry (SCA). Indeed, SCA at ultramicro- or nanoelectrodes provides the necessary temporal, flux, and nanoscale resolution to accurately report on the shape and intensity of single exocytotic spikes. Rather than characterizing amperometric spikes using standard descriptive parameters (e.g., amplitude and half-width), however, this study summarizes a modeling approach based on the underlying biology and physical chemistry of single exocytotic events. This approach provides deeper insights into intravesicular phenomena that control vesicular release dynamics. The ensuing model’s intrinsic parsimony makes it computationally efficient and friendly, enabling the processing of large amperometric traces to gain statistically significant insights.