Precise Control Research Articles

Optimizing CD8+ T cell-based immunotherapy via metabolic interventions: a comprehensive review of intrinsic and extrinsic modulators

AbstractCD8+ T cells are integral to the effective management of cancer and infectious diseases due to their cytotoxic functions. The efficacy of these cells is profoundly influenced by their metabolic state, which regulates their activation, differentiation, and longevity. Accordingly, the modulation of metabolic pathways within CD8+ T cells is crucial for enhancing the effectiveness of T cell-based immunotherapy. Precise metabolic control is paramount in optimizing therapeutic outcomes and minimizing potential toxicities associated with treatment. Importantly, the potential of exogenous metabolites to augment CD8+ T cell responses is critically evaluated, especially through in vivo evidence that underscores their therapeutic promise. This review also addresses current challenges, including the need for precise control of metabolic modulation to avoid adverse effects, the development of targeted delivery systems to ensure efficient metabolite delivery to CD8+ T cells, and the inherent variability of metabolic states among patients that may influence treatment outcomes. Addressing these hurdles will be crucial for the successful integration of metabolic interventions into established immunotherapeutic regimens.

Self-assembled nanostructured membranes with tunable pore size and shape from plant-derived materials.

Nanostructured materials derived from sustainable sources are of interest as viable alternatives to traditional petroleum-derived sources in membrane applications due to environmental concerns. Here, we present the development of pore size-tunable nanostructured polymer membranes based on a plant-derived material. The membranes were fabricated using a tri-functional amine as the templating core species and a cross-linkable ligand synthesized from rose oil-derived citronellol. The self-assembly of a supramolecular complex between the template core and the ligand forms a hexagonally packed columnar (Colh) mesophase, the dimensions of which can be precisely controlled by changing the stoichiometric ratio between these constituents. Within the hexagonal mesophase stoichiometric range, the pore size of the nanostructured membranes can be tuned from 1.0 to 1.3 nm, with a step size of approximately 0.1 nm. The membranes exhibited a clear distinction in molecular size selectivity, as demonstrated by dye adsorption experiments. The membrane fabricated with a ligand-to-core ratio of 3 to 1 demonstrated shape-based selectivity, exhibiting a higher permeability for propeller-shaped penetrants and highlighting its potential for shape-selective transport. We anticipate that this straightforward approach, using plant-derived materials, can contribute to important sustainability aspects while enhancing the performance of current state-of-the-art nanostructured membranes by enabling precise control over pore size.

Precision Transcriptome Editing.

Manipulating RNA species in mammalian cells has emerged as an important strategy for precise gene expression control. Here we review recent advances in precision transcriptome editing with a focus on tools that engineer specific transcripts for abundance, translation, base editing, alternative isoforms, and chemical modifications. While some of these methods have demonstrated efficiency in therapeutically relevant cellular or in vivo models, most require further study on their clinical safety and efficacy. Precision transcriptome engineering holds great potential for both mechanistic study of RNA biology and future gene and cell-based therapeutic applications.

Droplet Impedance Feedback-Enabled Microsampling Microfluidic Device for Precise Chemical Information Monitoring.

Microelectrodes have transformed our understanding of spatiotemporal responses to electrical stimulation. However, biological signals are often molecular, complicating the capture of intricate chemical signals. The microfluidic chip developed in this paper accurately measures droplet volume by using impedance analysis. The utilization of droplet volume as a feedback signal for precise microsampling pressure control ensures that microsampling remains unaffected by droplet volume influence. Once the microsampling is complete, chemiluminescence detection enables high temporal resolution and continuous and sensitive monitoring of chemical information within the droplets. Experimental verification shows that the chip can avoid volume influence through impedance feedback, achieving consistent and stable microampling at the nanoliter level (0-3 nL). In just 0.3 s, it can perform sensitive chemiluminescence detection of H2O2 and glucose within droplets. The linear detection ranges for these analytes are 10-50,000 and 20-600 μM, respectively, with the limit of detection being 0.648 and 0.334 μM. The significance of this chip lies in its ability to reveal changes in both electrical and chemical signals during transient biological processes. Its potential applications are numerous, encompassing a wide range of emerging areas such as single-cell analysis, cell communication, and cellular immunity.

Advanced Study: Improving the Quality of Cooling Water Towers’ Conductivity Using a Fuzzy PID Control Model

Cooling water towers are commonly used in industrial and commercial applications. Industrial sites frequently have harsh environments, with certain characteristics such as poor air quality, close proximity to the ocean, large quantities of dust, or water supplies with a high mineral content. In such environments, the quality of electrical conductivity in the cooling water towers can be significantly negatively affected. Once minerals (e.g., calcium and magnesium) form in the water, conductivity becomes too high, and cooling water towers can become easily clogged in a short time; this leads to a situation in which the cooling water host cannot be cooled, causing it to crash. This is a serious situation because manufacturing processes are then completely shut down, and production yield is thus severely reduced. To solve these problems, in this study, we develop a practical designation for a photovoltaic industry company called Company-L. Three control methods are proposed: the motor control method, the PID control method, and the fuzzy PID control method. These approaches are proposed as solutions for successfully controlling the forced replenishment and drainage of cooling water towers and controlling the opening of proportional control valves for water release; this will further dilute the electrical conductivity and control it, bringing it to 300 µS/cm. In the experimental processes, we first used practical data from Company-L for our case study. Second, from the experimental results of the proposed model for the motor control method, we can see that if electrical conductivity is out of control and the conductivity value exceeds 1000 µS/cm, the communication software LINE v8.5.0 (accessible via smartphone) displays a notification that the water quality of the cooling water towers requires attention. Third, although the PID control method is shown to have errors within an acceptable range, the proportional (P) controller must be precisely controlled; this control method has not yet reached this precise control in the present study. Finally, the fuzzy PID control method was found to have the greatest effect, with the lowest level of errors and the most accurate control. In conclusion, the present study proposes solutions to reduce the risk of ice-water host machines crashing; the solutions use fuzzy logic and can be used to ensure the smooth operation of manufacturing processes in industries. Practically, this study contributes an applicable technical innovation: the use of the fuzzy PID control model to control cooling water towers in industrial applications. Concurrently, we present a three-tier monitoring checkpoint that contributes to the PID control method.

Development of Mathematical Function Control-Based 3D Printed Tablets and Effect on Drug Release.

The application of 3D printing technology in drug delivery is often limited by the challenges of achieving precise control over drug release profiles. The goal of this study was to apply surface equations to construct 3D printed tablet models, adjust the functional parameters to obtain multiple tablet models and to correlate the model parameters with the in vitro drug release behavior. This study reports the development of 3D-printed tablets using surface geometries controlled by mathematical functions to modulate drug release. Utilizing fused deposition modeling (FDM) coupled with hot-melt extrusion (HME) technology, personalized drug delivery systems were produced using thermoplastic polymers. Different tablet shapes (T1-T5) were produced by varying the depth of the parabolic surface (b = 4, 2, 0, -2, -4mm) to assess the impact of surface curvature on drug dissolution. The T5 formulation, with the greatest surface curvature, demonstrated the fastest drug release, achieving complete release within 4h. In contrast, T1 and T2 tablets exhibited a slower release over approximately 6h. The correlation between surface area and drug release rate was confirmed, supporting the predictions of the Noyes-Whitney equation. Differential Scanning Calorimetry (DSC) and Scanning Electron Microscope (SEM) analyses verified the uniform dispersion of acetaminophen and the consistency of the internal structures, respectively. The precise control of tablet surface geometry effectively tailored drug release profiles, enhancing patient compliance and treatment efficacy. This novel approach offers significant advancements in personalized medicine by providing a highly reproducible and adaptable platform for optimizing drug delivery.

Multiple Conformal-Contact Transfer of Large-Area Crack-Free Transition Metal Dichalcogenide Stacks

Abstract Atomically-thin two-dimensional (2D) transition metal dichalcogenides (TMDs) have emerged as an ideal platform for both physics investigation and device applications. By stacking different layers into homo- or hetero-structures, an extra degree of freedom is involved in further tuning their properties, thereby boosting scenarios in twistronics, moiré photonics and optoelectronics. However, interfacial imperfections such as contaminations and cracks, frequently occur during the layer stacking sequence and accumulate layer by layer, greatly degenerating the interface quality. In this study, we developed a multiple conformal-contact transfer method to construct TMD stacks with crack-free intrinsic interfaces. The design of a deformable buffer layer is crucial to guarantee the conformal contact and intact transfer of each layer, contributing to the successful construction of centimetre-scale TMD stacks up to 8 layers. Precise control over spatial location and interlayer twist angle is also feasibly achieved, evidenced by the stacking-dependent interlayer exciton effects in WS2-WSe2 heterostructures. This work provides a facile and precise approach for architecting 2D stacks with perfect interfaces, which will further accelerate the customized design for their device functionalization.

Laser-assisted synthesis and modification of 2D materials.

Two-dimensional materials with unique physical, electronic, and optical properties have been intensively studied to be utilized for the next-generation electronic and optical devices, and the use of laser energy in the synthesis and modification of 2D materials is advantageous due to its convenient and fast fabrication processes as well as selective, controllable, and cost-effective characteristics allowing the precise control in materials properties. This paper summarizes the recent progress in utilizations of laser technology in synthesizing, doping, etching, transfer and strain engineering of 2D materials, which is expected to provide an insight for the future applications across diverse research areas.

Modeling of the metal–insulator transition temperature in alio-valently doped VO2 through symbolic regression

The correlated semiconductor vanadium dioxide (VO2) exhibits an insulator–metal transition (IMT) near room temperature, which is of interest in various device applications. Precise IMT temperature control is crucial to determine the use cases across technologies such as thermochromic windows, actuators for robots or neuronal oscillators. Doping the cation or anion sites can modulate the IMT by several tens of degrees and control hysteresis. However, modeling the effects of control parameters (e.g., doping concentration, type of dopants) is challenging due to complex experimental procedures and limited data, hindering the use of traditional data-driven machine learning approaches. Symbolic regression (SR) can bridge this gap by identifying nonlinear expressions connecting key input parameters to target properties, even with small data sets. In this work, we develop SR models to capture the IMT trends in VO2 influenced by different dopant parameters. Using experimental data from the literature, our study reveals a dual nature of the IMT temperature with varying tungsten (W) doping concentrations. The symbolic model captures data trends and accounts for experimental variability, providing a complementary approach to first-principles calculations. Our feature-driven analysis across a broader class of dopants informs selectivity and provides qualitative insights into tuning phase transition properties valuable for neuromorphic computing and thermochromic windows.

Improved active vibration control of a cantilever beam using MFC actuators with Hammerstein model-based hysteresis modeling and VSS-FxLMS control algorithm

This study aims to enhance active vibration control in a cantilever beam using macro fiber composite (MFC) actuators. To address the challenge of accurately modeling the complex hysteresis behavior of MFC actuators, an advanced hysteresis modeling technique is employed, integrating a non-symmetric Bouc–Wen model with an Auto-Regressive model with eXogenous inputs (ARX). The parameter estimation of this model is optimized using an adaptive mutation factor, and multiple mutation strategy differential evolution (AmFMMDE) algorithm. Additionally, a Variable Step Size Filtered-x Least Mean Square (VSS-FxLMS) algorithm with step size adaptation based on normalized error change is utilized for effective vibration control. This approach shows promising potential for practical engineering applications requiring precise and efficient active vibration control.

Appearance-Based Gaze Estimation as a Benchmark for Eye Image Data Generation Methods

Data augmentation is commonly utilized to increase the size and diversity of training sets for deep learning tasks. In this study, we propose a novel application of an existing image generation approach in the domain of realistic eye images that leverages data collected from 40 subjects. This hybrid method combines the benefits of precise control over the image content provided by 3D rendering, while introducing the previously lacking photorealism and diversity into synthetic images through neural style transfer. We prove its general efficacy as a data augmentation tool for appearance-based gaze estimation when generated data are mixed with a sparse train set of real images. It improved the results for 39 out of 40 subjects, with an 11.22% mean and a 19.75% maximum decrease in gaze estimation error, achieving similar metrics for train and held-out subjects. We release our data repository of eye images with gaze labels used in this work for public access.

Perspectives on non-genetic optoelectronic modulation biointerfaces for advancing healthcare

AbstractAdvancements in optoelectronic biointerfaces have revolutionized healthcare by enabling targeted stimulation and monitoring of cells, tissues, and organs. Photostimulation, a key application, offers precise control over biological processes, surpassing traditional modulation methods with increased spatial resolution and reduced invasiveness. This perspective highlights three approaches in non-genetic optoelectronic photostimulation: nanostructured phototransducers for cellular stimulation, micropatterned photoelectrode arrays for tissue stimulation, and thin-film flexible photoelectrodes for multiscale stimulation. Nanostructured phototransducers provide localized stimulation at the cellular or subcellular level, facilitating cellular therapy and regenerative medicine. Micropatterned photoelectrode arrays offer precise tissue stimulation, critical for targeted therapeutic interventions. Thin-film flexible photoelectrodes combine flexibility and biocompatibility for scalable medical applications. Beyond neuromodulation, optoelectronic biointerfaces hold promise in cardiology, oncology, wound healing, and endocrine and respiratory therapies. Future directions include integrating these devices with advanced imaging and feedback systems, developing wireless and biocompatible devices for long-term use, and creating multifunctional devices that combine photostimulation with other therapies. The integration of light and electronics through these biointerfaces paves the way for innovative, less invasive, and more accurate medical treatments, promising a transformative impact on patient care across various medical fields.

Multiscale Models of CVD Process: Review and Prospective

Chemical vapor deposition (CVD) is a crucial technique in the preparation of high-quality thin films and coatings, and is widely used in various industries including semiconductor, optics, and nuclear fuel, due to its operation simplicity and high growth rate. The complexity of the CVD process arises from numerous parameters, such as precursor chemistry, temperature, pressure, gas flow dynamics, and substrate characteristics. These multiscale parameters make the optimization of the CVD process a challenging task. Numerical simulations are widely used to model and analyze the CVD complex systems, and can be divided into nanoscale, mesoscale, and macroscale methods. Numerical simulation is aimed at optimizing the CVD process, but the inter-scale parameters still need to be extracted in modeling processes. However, multiscale coupling modeling becomes a powerful method to solve these challenges by providing a comprehensive framework that integrates phenomena occurring at different scales. This review presents an overview of the CVD process, the common critical parameters, and an in-depth analysis of CVD models in different scales. Then various multiscale models are discussed. This review highlights the models in different scales, integrates these models into multiscale frameworks, discusses typical multiscale coupling CVD models applied in practice, and summarizes the parameters that can transfer information between different scales. Finally, the schemes of multiscale coupling are given as a prospective view. By offering a comprehensive view of the current state of multiscale CVD models, this review aims to bridge the gap between theory and practice, and provide insights that could lead to a more efficient and precise control of the CVD process.

Cooperative Substructure and Energetics of Allosteric Regulation of the Catalytic Core of the E3 Ubiquitin Ligase Parkin by Phosphorylated Ubiquitin

Mutations in the parkin gene product Parkin give rise to autosomal recessive juvenile parkinsonism. Parkin is an E3 ubiquitin ligase that is a critical participant in the process of mitophagy. Parkin has a complex structure that integrates several allosteric signals to maintain precise control of its catalytic activity. Though its allosterically controlled structural reorganization has been extensively characterized by crystallography, the energetics and mechanisms of allosteric regulation of Parkin are much less well understood. Allostery is fundamentally linked to the energetics of the cooperative (sub)structure of the protein. Herein, we examine the mechanism of allosteric activation by phosphorylated ubiquitin binding to the enzymatic core of Parkin, which lacks the antagonistic Ubl domain. In this way, the allosteric effects of the agonist phosphorylated ubiquitin can be isolated. Using native-state hydrogen exchange monitored by mass spectrometry, we find that the five structural domains of the core of Parkin are energetically distinct. Nevertheless, association of phosphorylated ubiquitin destabilizes structural elements that bind the ubiquitin-like domain antagonist while promoting the dissociation of the catalytic domain and energetically poises the protein for transition to the fully activated structure.

A Novel Demodulator Design for Signal Processing of Inductive Oil Debris Sensors

Abstract Metal debris from bearing wear occurred in the lubrication system of aircraft engines represents valuable information, which can be utilized to assess the current engine condition and further enable the life-cycle prediction. The demodulation of debris signals consists of two parts: mixing and filtering. In traditional methods, the mixing process is complex to adjust and prone to failure, while the filtering employs the fixed low-pass filtering, which significantly affects the demodulation performance when the debris flow rate changes. To address these issues, this paper proposes a novel demodulation model to enhance the demodulation performance and increase the signal-to-noise ratio of chip signals. Firstly, the circuit innovatively adopts a self-frequency mixing method to avoid the complex phase adjustment required by traditional reference-frequency mixing methods for the improved stability of the circuit. Following that, a digital potentiometer is employed to implement the flow rate filtering, enabling precise control over the filter type and range, thus mitigating signal distortion caused by changes in flow rate and increasing the signal-to-noise ratio. Throughout extensive experiments and data analysis, the self-frequency mixing method improves the signal-to-noise ratio by 0.72 dB and reduces the signal standard deviation by 59.12% as compared to the reference-frequency mixing method. Considering the debris flow rate in the range of 0.2 to 0.5 m/s, the flow rate filtering method improves the signal-to-noise ratio by 19.71 dB and reduces the amplitude standard deviation by 66.18%, as compared to results by the traditional fixed low-pass filtering method. Results demonstrate that the aforementioned circuit design effectively enhances the signal amplitude and stability of inductive oil debris sensors in the wear assessment of mechanical systems and provides useful insights into the development of advanced sensors used in the field of structural health monitoring.

Accelerated In Vitro Oxidative Degradation Testing of Ultra-High Molecular Weight Polyethylene (UHMWPE).

Nonabsorbable polymers used in biomedical applications are assumed to be permanently stable based on short-term testing, but some may be susceptible to oxidative degradation over several years of implantation. Traditional in vitro oxidative degradation screenings employ hydrogen peroxide (H2O2) solutions. However, the inherent instability of H2O2 can compromise the consistency of oxidative conditions, especially over extended periods and at elevated temperatures used for accelerated testing. In this study, an automated reactive accelerated aging (aRAA) system, which integrates an electrochemical detection method and a feedback loop, was utilized to ensure precise control of H2O2 concentrations during polymer oxidative degradation testing. The reproducibility of the aRAA system was evaluated by comparing four identical setups. Its efficacy as an oxidation challenge was demonstrated on (i) medical-grade vitamin E (VE) blended ultra-high molecular weight polyethylene (UHMWPE) and (ii) highly crosslinked (HXL) UHMWPE as model materials. The aRAA-aged VE-UHMWPE and HXL-UHMWPE samples were also compared against samples aged via an existing accelerated aging standard, ASTM F2003-02(2022). Samples were analyzed using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy to calculate their oxidation index per ASTM F2102-17. We observed that the aRAA system was more effective in oxidizing VE-UHMWPE and HXL-UHMWPE than the traditional ASTM F2003-02(2022) method. By providing a standardized and reliable approach to assess polymer oxidative degradation, the aRAA system could enhance the accuracy of long-term stability predictions for nonresorbable polymers in medical devices.

Innovative Approaches to Large-Area Perovskite Solar Cell Fabrication Using Slit Coating

Perovskite solar cells (PSCs) are gaining prominence in the photovoltaic industry due to their exceptional photoelectric performance and low manufacturing costs, achieving a significant power conversion efficiency of 26.4%, which closely rivals that of silicon solar cells. Despite substantial advancements, the effective area of high-efficiency PSCs is typically limited to about 0.1 cm2 in laboratory settings, with efficiency decreasing as the area increases. The limitation poses a major obstacle to commercialization, as large-area, high-quality perovskite films are crucial for commercial applications. This paper reviews current techniques for producing large-area perovskites, focusing on slot-die coating, a method that has attracted attention for its revolutionary potential in PSC manufacturing. Slot-die coating allows for precise control over film thickness and is compatible with roll-to-roll systems, making it suitable for large-scale applications. The paper systematically outlines the characteristics of slot-die coating, along with its advantages and disadvantages in commercial applications, suggests corresponding optimization strategies, and discusses future development directions to enhance the scalability and efficiency of PSCs, paving the way for broader commercial deployment.

Photoelectrochemical Hydrogen Production from Water Using Copper‐based Chalcopyrite Thin Films

AbstractCopper (Cu)‐based chalcopyrite compounds are promising photoabsorber materials not only for solar cells but also for photoelectrochemical (PEC) systems for conversion of sunlight energy into chemical energy. PEC water splitting to generate hydrogen (H2) is one of the most advanced technologies in a PEC system for the use of Cu‐based chalcopyrite compounds. In this review, we firstly introduce crystallographic/energetic structures of Cu‐based chalcopyrite compounds in view of their applications to PEC water splitting. Explanations for the operation of PEC water splitting using semiconductor materials are then overviewed. Based on these backgrounds, studies on PEC H2 evolution over photocathodes based on CuInS2 and CuGaSe2 thin films that we have developed are reviewed in detail. For realizing efficient PEC H2 evolution over these thin films, surface modifications with an n‐type layer such as CdS and a catalytic site such as Pt deposit were found to be indispensable. Precise controls of p‐n heterointerfaces formed by introducing an n‐type layer should also be required to enhance PEC performance. Although PEC water splitting has not reached the required efficiency to be useful, effective combinations of appropriate surface and interface modifications should lead to further improvements of properties to be close to practical applications.

Second Generation Zwitterionic Aza‐Diarylethene: Photoreversible CN Bond Formation, Three‐State Photoswitching, Thermal Energy Release, and Facile Photoinitiation of Polymerization

Diarylethenes are a well‐studied and optimized class of photoswitches with a wide range of applications, including data storage, smart materials, or photocontrolled catalysis and biological processes. Most recently, aza‐diarylethenes have been developed in which carbon‐carbon bond connections are replaced by carbon‐nitrogen connections. This structural elaboration opens an entire new structure and property space expanding versatility and applicability of diarylethenes. In this work, we present the second generation of zwitterionic aza‐diarylethenes, which finally allows for fully reversible photoswitching and precise control over all three switching states. High‐yielding photoswitching between the neutral open form and a zwitterionic Z isomer is achieved with two different wavelengths of light. The third zwitterionic E isomeric state can be reached up to 87% upon irradiation with a third wavelength. Its high energy content of >10 kcal/mol can be released thermally by deliberate solvent change as trigger mechanism, rendering aza‐diarylethenes into interesting candidates for molecular solar thermal energy storage (MOST) applications. The third state further serves as locking state, allowing to toggle light‐responsiveness reversibly between thermally labile and thermally stable switching. Further, irradiation of the zwitterionic states leads to highly efficient photopolymerization of methyl acrylate (MA), directly harnessing the unleashed chemical reactivity of aza‐diarylethene in materials applications.

Second Generation Zwitterionic Aza-Diarylethene: Photoreversible CN Bond Formation, Three-State Photoswitching, Thermal Energy Release, and Facile Photoinitiation of Polymerization.

Diarylethenes are a well-studied and optimized class of photoswitches with a wide range of applications, including data storage, smart materials, or photocontrolled catalysis and biological processes. Most recently, aza-diarylethenes have been developed in which carbon-carbon bond connections are replaced by carbon-nitrogen connections. This structural elaboration opens an entire new structure and property space expanding versatility and applicability of diarylethenes. In this work, we present the second generation of zwitterionic aza-diarylethenes, which finally allows for fully reversible photoswitching and precise control over all three switching states. High-yielding photoswitching between the neutral open form and a zwitterionicZisomer is achieved with two different wavelengths of light. The third zwitterionicEisomeric state can be reached up to 87% upon irradiation with a third wavelength. Its high energy content of >10 kcal/mol can be released thermally by deliberate solvent change as trigger mechanism, rendering aza-diarylethenes into interesting candidates for molecular solar thermal energystorage (MOST) applications. The third state further serves as locking state, allowing to toggle light-responsiveness reversibly between thermally labile and thermally stable switching. Further, irradiation of the zwitterionic states leads to highly efficient photopolymerization of methyl acrylate (MA),directly harnessing the unleashed chemical reactivity of aza-diarylethene in materials applications.