ATOH8 binds SMAD3 to induce cellular senescence and prevent Ras-driven malignant transformation.

The process of oncogene-induced senescence (OIS) and the conversion between OIS and malignant transformation during carcinogenesis is poorly understood. Here, we show that following overactivation of oncogene Ras in lung epithelial cells, high-level transforming growth factor ß1 (TGF-ß1)-activated SMAD3, but not SMAD2 or SMAD4, plays a determinant role in inducing cellular senescence independent of the p53/p16/p15 senescence pathways. Importantly, SMAD3 binds a potential tumor suppressor ATOH8 to form a transcriptional complex that directly represses a series of cell cycle-promoting genes and consequently causes senescence in lung epithelial cells. Interestingly, the prosenescent SMAD3 converts to being oncogenic and essentially facilitates oncogenic Ras-driven malignant transformation. Furthermore, depleting Atoh8 rapidly accelerates oncogenic Ras-driven lung tumorigenesis, and lung cancers driven by mutant Ras and Atoh8 loss, but not by mutant Ras only, are sensitive to treatment of a specific SMAD3 inhibitor. Moreover, hypermethylation of the ATOH8 gene can be found in approximately 12% of clinical lung cancer cases. Together, our findings demonstrate not only epithelial cellular senescence directed by a potential tumor suppressor-controlled transcriptional program but also an important interplay between the prosenescent and transforming effects of TGF-ß/SMAD3, potentially laying a foundation for developing early detection and anticancer strategies.

Electrochemical Knocking-Down of Zn Metal Clusters into Single Atoms.

Single Atoms Catalysts (SACs) have emerged as a class of highly promising heterogeneous catalysts, where the traditional bottom-up synthesis approaches often encounter considerable challenges in relation to aggregation issues and poor stability. Consequently, achieving densely dispersed atomic species in a reliable and efficient manner remains a key focus in the field. Herein, we report a new facile electrochemical knock-down strategy for the formation of SACs, whereby the metal Zn clusters are transformed into single atoms. While a defect-rich substrate plays a pivotal role in capturing and stabilizing isolated Zn atoms, the feasibility of this novel strategy is demonstrated through a comprehensive investigation, combining experimental and theoretical studies. Furthermore, when studied in exploring for potential applications, the material prepared shows a remarkable improvement of 58.21% for the Li+ storage and delivers a capacity over 300 Wh kg-1 after 500 cycles upon the transformation of Zn clusters into single atoms.

Portable Mass Spectrometry for On-site Detection of Hazardous Volatile Organic Compounds via Robotic Extractive Sampling.

Various hazardous volatile organic compounds (VOCs) are frequently released into environments during accidental events that cause many hazards to ecosystems and humans. Therefore, rapid, sensitive, and on-site detection of hazardous VOCs is crucial to understand their compositions, characteristics, and distributions in complex environments. However, manual handling of hazardous VOCs remains a challenging task, because of the inaccessible environments and health risk. In this work, we designed a quadruped robotic sampler to reach different complex environments for capturing trace hazardous VOCs using a needle trap device (NTD) by remote manipulation. The captured samples were rapidly identified by portable mass spectrometry (MS) within minutes. Rapid detection of various hazardous VOCs including toxicants, chemical warfare agents, and burning materials from different environments was successfully achieved using this robot-MS system. On-site detection of 83 typical hazardous VOCs was examined. Acceptable analytical performances including low detection limits (at subng/mL level), good reproducibility (relative standard deviation (RSD) < 20%, n = 6), excellent quantitative ability (R2 > 0.99), and detection speed (within minutes) were also obtained. Our results show that the robot-MS system has excellent performance including safety, controllability, applicability, and robustness under dangerous chemical conditions.

Switch Volmer-Heyrovsky to Volmer-Tafel Pathway for Efficient Acidic Electrocatalytic Hydrogen Evolution by Correlating Pt Single Atoms with Clusters.

As cost-effective catalysts, platinum (Pt) single-atom catalysts (SACs) have attracted substantial attention. However, most studies indicate that Pt SACs in acidic hydrogen evolution reaction (HER) follow the slow Volmer-Heyrovsky (VH) mechanism instead of the fast kinetic Volmer-Tafel (VT) pathway. Here, this work propose that the VH mechanism in Pt SACs can be switched to the faster VT pathway for efficient HER by correlating Pt single atoms (SAs) with Pt clusters (Cs). Our calculations reveal that the correlation between Pt SAs and Cs significantly impacts the electronic structure of exposed Pt atoms, lowering the adsorption barrier for atomic hydrogen and enabling a faster VT mechanism. To validate these findings, this work purposely synthesize three catalysts: l-Pt@MoS2, m-Pt@MoS2 and h-Pt@MoS2 with low, moderate, and high Pt-loading, having different distributions of Pt SAs and Cs. The m-Pt@MoS2 catalyst with properly correlating Pt SAs and Cs exhibits outstanding performance with an overpotential of 47 mV and Tafel slope of 32 mV dec-1. Further analysis of the Tafel values confirms that the m-Pt@MoS2 sample indeed follows the VT reaction mechanism, aligning with the theoretical findings. This study offers a deep understanding of the synergistic mechanism, paving a way for designing novel-advanced catalysts.

Interfacial Synergy in Mo2C/MoC Heterostructure Promoting Sequential Polysulfide Conversion in High-Performance Lithium-Sulfur Battery.

A rational design of sulfur host is the key to conquering the"polysulfide shuttle effects" by accelerating the polysulfide conversion. Since the process involves solid-liquid-solid multistep phase transitions, purposely-engineered heterostructure catalysts with various active regions for catalyzing conversion steps correspondingly are beneficial to promote the overall conversion process. However, the functionalities of the materials surface and interface in heterostructure catalysts remain unclear. In this work, an Mo2C/MoC catalyst with abundant Mo2C surface-interface-MoC surface tri-active-region is developed by in situ converting the MoZn-metal organic framework. The experimental and simulation studies demonstrate the interface can catch long-chain polysulfides and promote their conversion. Instead, the Mo2C and MoC tend to accommodate the short-chain polysulfide and accelerate their conversion and the Li2S dissociation. Benefitting from the high catalytic ability, the Li-S battery assembled with the Mo2C/MoC-S cathode shows more discrete redox reactions and delivers a high initial capacity of 1603.6 mAh g-1 at 1 C charging-discharging rate, which is over twofolds of the one assembled using individual hosts, and 80.4% capacity can be maintained after 1000 cycles at 3 C rate. This work has demonstrated a novel synergy between the interface and material surface, which will help the future design of high-performance Li-S batteries.

Two-Phase Fermentation Systems for Microbial Production of Plant-Derived Terpenes.

Microbial cell factories, renowned for their economic and environmental benefits, have emerged as a key trend in academic and industrial areas, particularly in the fermentation of natural compounds. Among these, plant-derived terpenes stand out as a significant class of bioactive natural products. The large-scale production of such terpenes, exemplified by artemisinic acid-a crucial precursor to artemisinin-is now feasible through microbial cell factories. In the fermentation of terpenes, two-phase fermentation technology has been widely applied due to its unique advantages. It facilitates in situ product extraction or adsorption, effectively mitigating the detrimental impact of product accumulation on microbial cells, thereby significantly bolstering the efficiency of microbial production of plant-derived terpenes. This paper reviews the latest developments in two-phase fermentation system applications, focusing on microbial fermentation of plant-derived terpenes. It also discusses the mechanisms influencing microbial biosynthesis of terpenes. Moreover, we introduce some new two-phase fermentation techniques, currently unexplored in terpene fermentation, with the aim of providing more thoughts and explorations on the future applications of two-phase fermentation technology. Lastly, we discuss several challenges in the industrial application of two-phase fermentation systems, especially in downstream processing.

Dual-Gradient Concentration Distribution in Sb-Cu Alloy Nanoarrays for Robust Sodium-Ion Storage.

Alloy-type materials are attractive for anodes in sodium-ion batteries (SIBs) owing to their high theoretical capacities and overall performance. However, the accumulation of stress/strain during repeated cycling results in electrode pulverization, leading to rapid capacity decay and eventual disintegration, thus hindering their practical applications. Herein, we report a 3D coral-like Sb-Cu alloy nanoarray with gradient distribution of both elements. The array features a Sb-rich bottom and a Cu-rich top with increasing Sb and decreasing Cu concentrations from top to bottom. The former is the active component that provides the high capacity, whereas the latter serves as an inert additive that acts against volume variation. The gradual transition in composition within the electrode introduces a ladder-type volume expansion effect, facilitating a smooth distribution and effective release of stress, thereby ensuring the wanted mechanical stability and structural integrity. The as-developed nanoarray affords a high reversible capacity (460 mAh g-1 at 0.5 C), stable cycling (89 % retention over 120 cycles at 1.0 C), and superior rate capability (354 mAh g-1 at 10 C). The concentration dual-gradient strategy paves a new pathway of designing alloy-type materials for SIBs.

Portable Mass Spectrometry Approach Combined with Machine Learning for Onsite Field Detection of Huanglongbing Disease.

Huanglongbing (HLB) is one of the most serious citrus diseases in the world. Rapid, onsite, and accurate field detection of HLB is a challenging task in analytical science for a long time. Herein, we have developed a novel HLB detection method that combines headspace solid phase microextraction with portable gas chromatography-mass spectrometry (PGC-MS) approach for onsite field detection of volatile metabolites of citrus leaves. Detectability and characteristics of HLB-affected metabolites from leaves were validated, and the important biomarkers were verified by authentic compounds. A machine learning approach based on random forest algorithm is established to model the volatile metabolites from healthy, symptomatic, and asymptomatic citrus leaves. In this work, a total of 147 citrus leaf samples were analyzed. Analytical performances of this newly developed method were investigated by in-field detection of various volatile metabolites. Results demonstrated limits of detection and quantification of 0.04-0.12 and 0.17-0.44 ng/mL for different metabolites, respectively. Linear calibration curves of various metabolites were established over a concentration dynamic range of at least three orders (R2 > 0.96). Good reproducibility was obtained for intraday (3.0-17.5%, n = 6) and interday precision (8.7-18.2%, n = 7). This new HLB field detection method provides a rapid detection with 6 min for each sample via a simple optimized procedure, including onsite sampling, PGC-MS analysis, and data process and provides a high accuracy (93.3%) for simultaneous identification of healthy, symptomatic, and asymptomatic trees. These data support the use of this new method for reliable field detection of HLB. Furthermore, metabolic pathways of HLB-affected metabolites were also proposed. Overall, our results not only provide a rapid and onsite field HLB detection method but also provide valuable information for understanding metabolic change of HLB infection.

Mask device as a new wearable sampler for breath analysis: what can we expect in the future?

Human exhaled breath is becoming an attractive clinical source as it is foreseen to enable noninvasive diagnosis of many diseases. Because mask devices can be used for efficiently filtering exhaled substances, mask-wearing has been required in the past few years in daily life since the unprecedented COVID-19 pandemic. In recent years, there is a new development of mask devices as new wearable breath samplers for collecting exhaled substances for disease diagnosis and biomarker discovery. This paper attempts to identify new trends in mask samplers for breath analysis. The couplings of mask samplers with different (bio)analytical approaches, including mass spectrometry (MS), polymerase chain reaction (PCR), sensor, and others for breath analysis, are summarized. The developments and applications of mask samplers in disease diagnosis and human health are reviewed. The limitations and future trends of mask samplers are also discussed.

Real-world treatment patterns in patients with nontuberculous mycobacterial lung disease in the Netherlands based on medication dispensing data.

PURPOSE: Real-world data on antibiotic management of nontuberculous mycobacterial lung disease (NTM-LD) is limited for many countries. This study aimed to evaluate real-world treatment practices of NTM-LD in the Netherlands using medication dispensing data. METHODS: A retrospective longitudinal real-world study was conducted using IQVIA's Dutch pharmaceutical dispensing database. The data are collected monthly and include approximately 70% of all outpatient prescriptions in the Netherlands. Patients initiated on specific NTM-LD treatment regimens between October 2015 and September 2020 were included. The main areas of investigation were initial treatment regimens, persistence on treatment, treatment switching, treatment compliance in terms of medication possession rate (MPR) and restarts of treatment. RESULTS: The database included 465 unique patients initiated on triple- or dual-drug regimens for the treatment of NTM-LD. Treatment switches were common and occurred approximately 1.6 per quarter throughout the treatment period. The average MPR of patients initiated on triple-drug therapy was 90%. The median time on therapy for these patients was 119 days; after six months and one year, 47% and 20% of the patients, respectively, were still on antibiotic therapy. Of 187 patients initiated on triple-drug therapy, 33 (18%) patients restarted antibiotic therapy after the initial treatment had been stopped. CONCLUSION: When on therapy, patients were compliant with the NTM-LD treatment; however, many patients stopped their therapy prematurely, treatment switches often occurred, and part of patients had to restart their therapy after a longer treatment gap. NTM-LD management should be improved through greater guideline adherence and appropriate involvement of expert centers.

A Cost-Driven Method for Deep-Learning-Based Hardware Trojan Detection.

The Cyber-Physical System and even the Metaverse will become the second space in which human beings live. While bringing convenience to human beings, it also brings many security threats. These threats may come from software or hardware. There has been a lot of research on managing malware, and there are many mature commercial products, such as antivirus software, firewalls, etc. In stark contrast, the research community on governing malicious hardware is still in its infancy. Chips are the core component of hardware, and hardware Trojans are the primary and complex security issue faced by chips. Detection of hardware Trojans is the first step for dealing with malicious circuits. Due to the limitation of the golden chip and the computational consumption, the existing traditional detection methods are not applicable to very large-scale integration. The performances of traditional machine-learning-based methods depend on the accuracy of the multi-feature representation, and most of the methods may lead to instability because of the difficulty of extracting features manually. In this paper, employing deep learning, a multiscale detection model for automatic feature extraction is proposed. The model is called MHTtext and provides two strategies to balance the accuracy and computational consumption. After selecting a strategy according to the actual situations and requirements, the MHTtext generates the corresponding path sentences from the netlist and employs TextCNN for identification. Further, it can also obtain non-repeated hardware Trojan component information to improve its stability performance. Moreover, a new evaluation metric is established to intuitively measure the model's effectiveness and balance: the stabilization efficiency index (SEI). In the experimental results for the benchmark netlists, the average accuracy (ACC) in the TextCNN of the global strategy is as high as 99.26%, and one of its stabilization efficiency index values ranks first with a score of 71.21 in all comparison classifiers. The local strategy also achieved an excellent effect, according to the SEI. The results show that the proposed MHTtext model has high stability, flexibility, and accuracy, in general.

Coupling Atomically Dispersed Fe-N5 Sites with Defective N-Doped Carbon Boosts CO2 Electroreduction.

Atomically dispersed iron immobilized on nitrogen-doped carbon catalyst has attracted enormous attention for CO2 electroreduction, but still suffers from low current density and poor selectivity. Herein, atomically dispersed FeN5 active sites supported on defective N-doped carbon successfully formed by a multistep thermal treatment strategy with the aid of dicyandiamide are reported. This dual-functional strategy can not only construct intrinsic carbon defects by selectively etching pyridinic-N and pyrrolic-N, but also introduces an additional N from the neighboring carbon layer coordinating to the commonly observed FeN4 , thus creating an FeN5 active site supported on defective porous carbon nanofibers (FeN5 /DPCF) with a local 3D configuration. The optimized FeN5 /DPCF achieves a high CO Faradaic efficiency (>90%) over a wide potential range of -0.4 to -0.6 V versus RHE with a maximal FECO of 93.1%, a high CO partial current density of 9.4 mA cm-2 at the low overpotential of 490 mV, and a remarkable turnover frequency of 2965 h-1 . Density functional theory calculations reveal that the synergistic effect between the FeN5 sites and carbon defects can enhance electronic localization, thus reducing the energy barrier for the CO2 reduction reaction and suppressing the hydrogen evolution reaction, giving rise to the superior activity and selectivity.

Lightweight Fine-Grained Access Control for Wireless Body Area Networks.

Wireless Body Area Network (WBAN) is a highly promising technology enabling health providers to remotely monitor vital parameters of patients via tiny wearable and implantable sensors. In a WBAN, medical data is collected by several tiny sensors and usually transmitted to a server-side (e.g., a cloud service provider) for long-term storage and online/offline processing. However, as the health data includes several sensitive information, providing confidentiality and fine-grained access control is necessary to preserve the privacy of patients. In this paper, we design an attribute-based encryption (ABE) scheme with lightweight encryption and decryption mechanisms. Our scheme enables tiny sensors to encrypt the collected data under an access control policy by performing very few computational operations. Also, the computational overhead on the users in the decryption phase is lightweight, and most of the operations are performed by the cloud server. In comparison with some excellent ABE schemes, our encryption mechanism is more than 100 times faster, and the communication overhead in our scheme decreases significantly. We provide the security definition for the new primitive and prove its security in the standard model and under the hardness assumption of the decisional bilinear Diffie-Hellman (DBDH) problem.

Hardware Trojans in Chips: A Survey for Detection and Prevention.

Diverse and wide-range applications of integrated circuits (ICs) and the development of Cyber Physical System (CPS), more and more third-party manufacturers are involved in the manufacturing of ICs. Unfortunately, like software, hardware can also be subjected to malicious attacks. Untrusted outsourced manufacturing tools and intellectual property (IP) cores may bring enormous risks from highly integrated. Attributed to this manufacturing model, the malicious circuits (known as Hardware Trojans, HTs) can be implanted during the most designing and manufacturing stages of the ICs, causing a change of functionality, leakage of information, even a denial of services (DoS), and so on. In this paper, a survey of HTs is presented, which shows the threatens of chips, and the state-of-the-art preventing and detecting techniques. Starting from the introduction of HT structures, the recent researches in the academic community about HTs is compiled and comprehensive classification of HTs is proposed. The state-of-the-art HT protection techniques with their advantages and disadvantages are further analyzed. Finally, the development trends in hardware security are highlighted.

In situ electrochemical oxidation of electrodeposited Ni-based nanostructure promotes alkaline hydrogen production.

Highly active and stable electrocatalysts based on non-precious metals for hydrogen evolution reaction (HER) in alkaline solution are urgently required for enabling mass production of clean hydrogen in industry. Herein, core-shell NiOOH/Ni nanoarchitectures supported on the conductive carbon cloth have been successfully prepared by a facile electrodeposition process of Ni, and a subsequent in situ electrochemical oxidation. When explored as an alkaline HER electrocatalyst, the as-synthesized NiOOH/Ni nanoarchitecture requires only a low overpotential of ∼111 mV to attain a current density of -10 mA cm-2, demonstrating its strong catalytic capability of hydrogeneration. The excellent HER activity could well be attributed to the decreasing charge transfer resistance and competitive electrochemical active area of the amorphous NiOOH, compared with inactive Ni substrate. The feasible methodology established in this study can be easily expanded to obtain a series of nano-sized metal oxyhydroxide materials for various energy conversion and storage applications, where Ni-based nanomaterials are among the highly active ones.

2D Metal-Organic Frameworks Derived Nanocarbon Arrays for Substrate Enhancement in Flexible Supercapacitors.

Direct assembling of active materials on carbon cloth (CC) is a promising way to achieve flexible electrodes for energy storage. However, the overall surface area and electrical conductivity of such electrodes are usually limited. Herein, 2D metal-organic framework derived nanocarbon nanowall (MOFC) arrays are successfully developed on carbon cloth by a facile solution + carbonization process. Upon growth of the MOFC arrays, the sites for growth of the active materials are greatly increased, and the equivalent series resistance is decreased, which contribute to the enhancement of the bare CC substrate. After decorating ultrathin flakes of MnO2 and Bi2 O3 on the flexible CC/MOFC substrate, the hierarchical electrode materials show an abrupt improvement of areal capacitances by around 50% and 100%, respectively, compared to those of the active materials on pristine carbon cloth. A flexible supercapacitor can be further assembled using two hierarchical electrodes, which demonstrates an energy density of 124.8 µWh cm-2 at the power density of 2.55 mW cm-2 .

A Provably Secure Aggregate Signature Scheme for Healthcare Wireless Sensor Networks.

Wireless sensor networks (WSNs) are being used in a wide range of applications for healthcare monitoring, like heart rate monitors and blood pressure monitors, which can minimize the need for healthcare professionals. In medical system, sensors on or in patients produce medical data which can be easily compromised by a vast of attacks. Although signature schemes can protect data authenticity and data integrity, when the number of users involved in the medical system becomes huge, the bandwidth and storage cost will rise sharply so that existing signature schemes are inapplicability for WSNs. In this paper, we propose an efficient aggregate signature scheme for healthcare WSNs according to an improved security model, which can combine multiple signatures into a single aggregate signature. The length of such an aggregate signature may be as long as that of an individual one, which can greatly decrease the bandwidth and storage cost for networks.

m2-ABKS: Attribute-Based Multi-Keyword Search over Encrypted Personal Health Records in Multi-Owner Setting.

Online personal health record (PHR) is more inclined to shift data storage and search operations to cloud server so as to enjoy the elastic resources and lessen computational burden in cloud storage. As multiple patients' data is always stored in the cloud server simultaneously, it is a challenge to guarantee the confidentiality of PHR data and allow data users to search encrypted data in an efficient and privacy-preserving way. To this end, we design a secure cryptographic primitive called as attribute-based multi-keyword search over encrypted personal health records in multi-owner setting to support both fine-grained access control and multi-keyword search via Ciphertext-Policy Attribute-Based Encryption. Formal security analysis proves our scheme is selectively secure against chosen-keyword attack. As a further contribution, we conduct empirical experiments over real-world dataset to show its feasibility and practicality in a broad range of actual scenarios without incurring additional computational burden.

Challenges and Opportunities in Preserving Key Structural Features of 3D-Printed Metal/Covalent Organic Framework.

Metal-organic framework (MOF) and covalent organic framework (COF) are a huge group of advanced porous materials exhibiting attractive and tunable microstructural features, such as large surface area, tunable pore size, and functional surfaces, which have significant values in various application areas. The emerging 3D printing technology further provides MOF and COFs (M/COFs) with higher designability of their macrostructure and demonstrates large achievements in their performance by shaping them into advanced 3D monoliths. However, the currently available 3D printing M/COFs strategy faces a major challenge of severe destruction of M/COFs' microstructural features, both during and after 3D printing. It is envisioned that preserving the microstructure of M/COFs in the 3D-printed monolith will bring a great improvement to the related applications. In this overview, the 3D-printed M/COFs are categorized into M/COF-mixed monoliths and M/COF-covered monoliths. Their differences in the properties, applications, and current research states are discussed. The up-to-date advancements in paste/scaffold composition and printing/covering methods to preserve the superior M/COF microstructure during 3D printing are further discussed for the two types of 3D-printed M/COF. Throughout the analysis of the current states of 3D-printed M/COFs, the expected future research direction to achieve a highly preserved microstructure in the 3D monolith is proposed.

Traditional and non-traditional lipid parameters as risk factors for sudden sensorineural hearing loss.

OBJECTIVE: The purpose was to explore the effects of traditional and non-traditional lipid parameters on Sudden Sensorineural Hearing Loss (SSNHL). METHODS: The study included 452 patients diagnosed with SSNHL, among whom 206 patients had a level of hearing improvement ≥10 dB after one month of follow-up. A propensity score-matched (2:1) control group was used. Conditional and unconditional logistic regression were used to analyze the risk factors for SSNHL. RESULTS: Patients with SSNHL had a higher risk of concomitant hypertension and elevated atherosclerogenic lipid levels, with apolipoprotein B and apolipoprotein E identified as independent risk factors for the onset of SSNHL. Additionally, the Lipid Comprehensive Index (LCI) was an independent risk factor for the degree of hearing loss. A positive linear correlation was revealed between triglyceride, non-high-density lipoprotein cholesterol, atherogenic index, Castelli risk index, atherogenic index of plasma, LCI and hearing loss. However, no linear relationship was observed between hearing gain and any lipid parameters. When Total Cholesterol (TC) was in the range of borderline high, the treatment effect was the best. However, the statistical significance disappeared upon adjusting for confounding factors. CONCLUSION: Patients with SSNHL exhibited markedly dysregulated lipid metabolism. Elevated serum lipid levels may be a causative factor in auditory impairment and can influence the extent of hearing loss. Promptly improving cochlear microcirculation may benefit patients with borderline elevated TC.