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Electrically conductive metal-organic frameworks (cMOFs) are emerging as promising chemiresistors due to their diverse compositions, chemical properties, porosity, and room-temperature conductivity, enabling the design of energy-efficient devices. However, limited activation in this regime hinders sensitivity and reversibility. In this study, cMOF thin films are integrated onto a micro-LED (μLED) platform using a layer-by-layer method, enabling photoactivated gas sensing even at room-temperature. The systematic coating allows for precise tailoring of films (e.g., thickness and overlayer structures) based on the adsorption properties of each analyte (ethanol, trimethylamine, ammonia, nitrogen dioxide). The selected arrays are optimized by varying the wavelengths and intensities of μLED, enabling sensitive and reversible sensing through additional charge generation, while consuming ultra-low power (587 µW). Additionally, a deep learning algorithm achieves rapid gas recognition within tens of seconds, with 99.8% classification accuracy in concentration prediction. This work demonstrates the feasibility of the cMOF–μLED integrated sensor platform, paving the way for next-generation gas-sensing technologies Here, authors present a photoactivated gas sensor integrating conductive MOFs with micro-LEDs for room-temperature, low-power detection. Tailored film design and deep learning enable fast, reversible gas recognition, advancing chemiresistive sensing

Veterinary pharmaceuticals may cause unexpected adverse effects on non-target aquatic species. While these pharmaceuticals were previously identified as priority compounds in ambient water, their ecological risks are relatively unknown. In this study, a series of chronic toxicity tests were conducted for these pharmaceuticals using algae, two cladocerans, and a fish. After a 21-d exposure to amoxicillin, enrofloxacin, and neomycin, no observed effect concentration (NOEC) for the reproduction of Daphnia magna was detected at 27.2, 3.3, and 0.15 mg/L, respectively. For the survival of juvenile Oryzias latipes following the 40-d exposure, NOEC was found at 21.8, 3.2, and 0.87 mg/L, respectively. Based on the results of the chronic toxicity tests and those reported in the literature, predicted no-effect concentrations (PNECs) were determined at 0.078, 4.9, and 3.0 µg/L for amoxicillin, enrofloxacin, and neomycin, respectively. Their hazard quotients (HQs) were less than 1 at their average levels of occurrence in ambient freshwater. However, HQs based on the maximum detected levels of amoxicillin and enrofloxacin were determined at 21.2 and 6.1, respectively, suggesting potential ecological risks. As the potential ecological risks of these veterinary pharmaceuticals at heavily contaminated sites cannot be ignored, hotspot delineation and its management are required.

Demand for augmented reality (AR) technology in the healthcare industry has gradually increased due to its immersive and interactive environment, which enhances the medical staff’s intuitive interpretation of sensing data during surgery, rehabilitation, diagnosis, education, and therapy. However, current skin-mountable, wearable sensors integrated with AR platforms mainly focus on Human-Machine Interface (HMI) for interactive experiences. Furthermore, most wearable sensors currently used in conjunction with AR systems are rigid and cumbersome, which hampers their application to the skin interfaces of patients for personalized healthcare. Herein, we developed a wireless, battery-free multi-axial sensor with a thin and small form factor and integrated it with the AR system to visualize sensing data (e.g., pressure, shear stress, and temperature) from the subjects. The overall system demonstrated efficacy in preventing pressure injuries, monitoring posture to prevent disc herniation, and intuitive AR monitoring of physical parameters for subjects sitting in wheelchairs and lying in bed.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in significant morbidity and mortality worldwide. Despite a successful vaccination programme, the emergence of mutated variants that can escape current levels of immunity mean infections continue. Herein, we report the development of CT-P63, a broad-spectrum neutralizing monoclonal antibody. In vitro studies demonstrated potent neutralizing activity against the most prevalent variants, including Delta and the BA.1 and BA.2 sub-lineages of Omicron. In a transgenic mouse model, prophylactic CT-P63 significantly reduced wild-type viral titres in the respiratory tract and CT-P63 treatment proved efficacious against infection with Beta, Delta, and Omicron variants of SARS-CoV-2 with no detectable infectious virus in the lungs of treated animals. A randomized, double-blind, parallel-group, placebo-controlled, Phase I, single ascending dose study in healthy volunteers (NCT05017168) confirmed the safety, tolerability, and pharmacokinetics of CT-P63. Twenty-four participants were randomized and received the planned dose of CT-P63 or placebo. The safety and tolerability of CT-P63 were evaluated as primary objectives. Eight participants (33.3%) experienced a treatment-emergent adverse event (TEAE), including one grade ≥3 (blood creatine phosphokinase increased). There were no deaths, treatment-emergent serious adverse events, TEAEs of special interest, or TEAEs leading to study drug discontinuation in the CT-P63 groups. Serum CT-P63 concentrations rapidly peaked before declining in a biphasic manner and systemic exposure was dose proportional. Overall, CT-P63 was clinically safe and showed broad-spectrum neutralizing activity against SARS-CoV-2 variants in vitro and in vivo.

The respiratory tract represents the key target for antiviral delivery in early interventions to prevent severe COVID‐19. While neutralizing monoclonal antibodies (mAb) possess considerable efficacy, their current reliance on parenteral dosing necessitates very large doses and places a substantial burden on the healthcare system. In contrast, direct inhaled delivery of mAb therapeutics offers the convenience of self‐dosing at home, as well as much more efficient mAb delivery to the respiratory tract. Here, building on our previous discovery of Fc‐mucin interactions crosslinking viruses to mucins, we showed that regdanvimab, a potent neutralizing mAb already approved for COVID‐19 in several countries, can effectively trap SARS‐CoV‐2 virus‐like particles in fresh human airway mucus. IN‐006, a reformulation of regdanvimab, was stably nebulized across a wide range of concentrations, with no loss of activity and no formation of aggregates. Finally, nebulized delivery of IN‐006 resulted in 100‐fold greater mAb levels in the lungs of rats compared to serum, in marked contrast to intravenously dosed mAbs. These results not only support our current efforts to evaluate the safety and efficacy of IN‐006 in clinical trials, but more broadly substantiate nebulized delivery of human antiviral mAbs as a new paradigm in treating SARS‐CoV‐2 and other respiratory pathologies.

The role of reactive oxygen species (ROS) in UVB-induced apoptosis has been established, but the molecular mechanisms of their production in response to UVB irradiation in keratinocytes are not well understood. In this study, we demonstrate that levels of BLT2, a low-affinity leukotriene B4 receptor, and its ligands (LTB4 and 12(S)-HETE) are greatly increased by UVB irradiation and are responsible for the UVB-induced ROS generation in human keratinocytes. Blockade of BLT2 with a BLT2-specific antagonist, LY255283, or with siBLT2 attenuated ROS production and apoptotic cell death detected by a number of criteria. Moreover, we found that the NADPH oxidase family protein Nox1 lies downstream of BLT2 and mediates UVB-induced ROS production and apoptosis. Topical treatment of mouse epidermal skin with LY255283 gave significant protection against UVB-induced sunburn–associated apoptotic damage. Finally, when BLT2-overexpressing transgenic mice were irradiated with UVB, we observed more extensive skin apoptosis. Taken together, our results demonstrate that a “BLT2-Nox1”-linked pathway has a crucial role in UVB-induced ROS generation and mediates apoptosis in human keratinocytes.

Skin exposure to low-dose ultraviolet B (UVB) light up-regulates the expression of matrix metalloproteinase-1 (MMP-1), thus contributing to premature skin aging (photo-aging). Although cyclooxygenase-2 (COX-2) and its product, prostaglandin E 2 (PGE 2 ), have been associated with UVB-induced signaling to MMP expression, very little are known about the roles of lipoxygenases and their products, especially leukotriene B 4 (LTB 4 ) and 12(S)-hydroxyeicosatetraenoic acid (12(S)-HETE), in MMP-1 expression in skin keratinocytes. In the present study, we demonstrate that BLT2, a cell surface receptor for LTB 4 and 12(S)-HETE, plays a critical role in UVB-mediated MMP-1 upregulation in human HaCaT keratinocytes. Moreover, our results demonstrated that BLT2-mediated MMP-1 upregulation occurs through a signaling pathway dependent on reactive oxygen species (ROS) production and the subsequent stimulation of ERK. Blockage of BLT2 via siRNA knockdown or with the BLT2-antagonist LY255283 completely abolished the up-regulated expression of MMP-1 induced by low-dose UVB irradiation. Finally, when HaCaT cells were transiently transfected with a BLT2 expression plasmid, MMP-1 expression was significantly enhanced, along with ERK phosphorylation, suggesting that BLT2 overexpression alone is sufficient for MMP-1 up-regulation. Together, our results suggest that the BLT2-ROS-ERK-linked cascade is a novel signaling mechanism for MMP-1 upregulation in low-dose UVB-irradiated keratinocytes and thus potentially contributes to photo-aging.

The global expansion of data centers, driven by rapid digitalization and emerging technologies such as artificial intelligence (AI), connected energy systems, and autonomous operations, has led to a significant rise in energy consumption and carbon emissions. This presents a critical challenge to sustainable development, particularly in managing the high energy intensity of data center cooling systems. While conventional direct expansion (DX) cooling systems often utilize free cooling with water/glycol loops, they suffer from limitations such as high fluid viscosity, reduced thermal conductivity, and increased pumping energy. To address these issues, this study proposes and evaluates a refrigerant-based free cooling strategy integrated with an air-cooled chiller system for data center applications. Unlike glycol-based systems, the refrigerant-based design eliminates the need for antifreeze agents and reduces associated pumping losses, enhancing both energy efficiency and system reliability. A new refrigerant cycle model was developed using Simulink to replicate free cooling operations, and its performance was analyzed based on data center's thermal load profiles obtained from EnergyPlus simulations. The case study involves a data center modeled as a single thermal zone with 3 MW of air-cooled information technology equipment (ITE). The proposed configuration includes an air-cooled chiller with an evaporatively cooled condenser, a fluid cooler, and a fluid-to-fluid heat exchanger, allowing the refrigerant loop to be used directly for heat rejection under favorable ambient conditions. Simulation results show that the refrigerant-based free cooling system achieves up to 35% annual cooling energy savings, depending on the climate condition. The number of available free cooling days is also increased due to the favorable thermal properties of the refrigerant compared to the case without free-cooling operation. Overall, this study demonstrates the potential of refrigerant-cycle-based free cooling as an effective strategy to reduce cooling energy use and improve the sustainability of data center operations. The findings provide valuable insights for designing energy-efficient cooling systems tailored to climate conditions and operational requirements in large-scale digital infrastructure.

12( S )-Hydroxyheptadeca- 5Z , 8E , 10E -trienoic acid (12-HHT) is an enzymatic product of prostaglandin H 2 (PGH 2 ) derived from cyclooxygenase (COX)-mediated arachidonic acid metabolism. Despite the high level of 12-HHT present in tissues and bodily fluids, its precise function remains largely unknown. In this study, we found that 12-HHT treatment in HaCaT cells remarkably down-regulated the ultraviolet B (UVB) irradiation-induced synthesis of interleukin-6 (IL-6), a pro-inflammatory cytokine associated with cutaneous inflammation. In an approach to identify the down-stream signaling mechanism by which 12-HHT down-regulates UVB-induced IL-6 synthesis in keratinocytes, we observed that 12-HHT inhibits the UVB-stimulated activation of p38 mitogen-activated protein kinase (MAPK) and nuclear factor kappa B (NF-κB). In addition, we found that 12-HHT markedly up-regulates MAPK phosphatase-1 (MKP-1), a critical negative regulator of p38 MAPK. When MKP-1 was suppressed by siRNA knock-down, the 12-HHT-mediated inhibitory effects on the UVB-stimulated activation of p38 MAPK and NF-κB, as well as the production of IL-6, were attenuated in HaCaT cells. Taken together, our results suggest that 12-HHT exerts anti-inflammatory effect via up-regulation of MKP-1, which negatively regulates p38 MAPK and NF-κB, thus attenuating IL-6 production in UVB-irradiated HaCaT cells. Considering the critical role of IL-6 in cutaneous inflammation, our findings provide the basis for the application of 12-HHT as a potential anti-inflammatory therapeutic agent in UV-induced skin diseases.

While optimization has received much attention in the machine learning community, most of them consider unconstrained supervised learning models such as neural networks and support vector machine. In this dissertation, we introduce a new class of optimization problems called scale invariant problems that include interesting unsupervised learning models such as PCA, ICA, GMM and KL-NMF. We develep scalable optimization algorithms for scale invariant problems and provide their convergence guarantees. The first half of this thesis develops deterministic optimization algorithms. Specifically, we develop an iterative optimization algorithm for L1-norm kernel PCA and generalizes it to solve general scale invariant problems. In the second half, we study stochastic optimization methods. We present two stochastic PCA algorithms and develop a stochastic generalization of power iteration to solve scale invariant problems with finite-sum objective functions. Numerical experiments on various scale invariant problems reveal that the proposed algorithms not only scale better than state-of-the-art algorithms but also produce excellent quality robust solutions.