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With the wide application of flow sensors, their reliability under extreme conditions has become a concern in recent years. The reliability of a Micro Electro Mechanical Systems (MEMS) flow sensor under temperature (Ts) is researched in this paper. This flow sensor consists of two parts, a sensor chip and a signal-processing system (SPS). Firstly, the step-stress accelerated degradation test (SSADT) is implemented. The sensor chip and the flow sensor system are tested. The results show that the biggest drift is 3.15% for sensor chips under 150 °C testing conditions, while 32.91% is recorded for the flowmeters. So, the attenuation of the SPS is significant to the degeneration of this flowmeter. The minimum drift of the SPS accounts for 82.01% of this flowmeter. Secondly, using the Coffin–Manson model, the relationship between the cycle index and Ts is established. The lifetime with a different Ts is estimated using the Arrhenius model. In addition, Weibull distribution (WD) is applied to evaluate the lifetime distribution. Finally, the reliability function of the WD is demonstrated, and the survival rate within one year is 87.69% under 85 °C conditions. With the application of accelerated degradation testing (ADT), the acquired results are innovative and original. This research illustrates the reliability research, which provides a relational database for the application of this flow sensor.

A century ago, the Warburg effect was first proposed, revealing that cancer cells predominantly rely on glycolysis during the process of tumorigenesis, even in the presence of abundant oxygen, shifting the main pathway of energy metabolism from the tricarboxylic acid cycle to aerobic glycolysis. Recent studies have unveiled the dynamic transfer of mitochondria within the tumor microenvironment, not only between tumor cells but also between tumor cells and stromal cells, immune cells, and others. In this review, we explore the pathways and mechanisms of mitochondrial transfer within the tumor microenvironment, as well as how these transfer activities promote tumor aggressiveness, chemotherapy resistance, and immune evasion. Further, we discuss the research progress and potential clinical significance targeting these phenomena. We also highlight the therapeutic potential of targeting intercellular mitochondrial transfer as a future anti-cancer strategy and enhancing cell-mediated immunotherapy. Graphical Abstract Mitochondrial Transfer in the Tumor Microenvironment. This review elaborates in detail on the molecular mechanisms and pathophysiological significance behind the mitochondrial transfer occurring between tumor cells and their microenvironment. This biological phenomenon of mitochondrial transfer is prevalent in a variety of cancers, including both solid tumors and hematologic malignancies, with a high incidence in acute myeloid leukemia (AML), breast cancer, and gliomas. The review also discusses therapeutic approaches targeting mitochondrial transfer, with a special focus on its application in immunotherapy, particularly in CAR-T cell therapy, where it has begun to show unique advantages

Obesity is a serious social and public health problem in the world, especially in children and adolescents. For school-age children with obesity, this stage is in the transition from childhood to adolescence, and both physical, psychological, and external environments will be full of challenges. Studies have showed that school-age children are the largest proportion of people who continue to be obese in adulthood. Physical exercise is considered as an effective way to control weight. Therefore, we focus on this point to study which factors will be improved to reduce childhood obesity. To assess the effects of aerobic and resistance exercise on physical indexes, such as body mass index (BMI) and body fat percentage, and cardiovascular risk factors such as VO.sub.2 peak, triglycerides (TG) and low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC), insulin and insulin resistance in school-age children who are overweight or obese. PubMed, SPORTDiscus, Medline, Cochrane-Library, Scopus, Ovid and Web of Science were searched to locate studies published between 2000 and 2021 in obese and overweight school-age children between 6-12 years old. The articles are all randomized controlled trials (RCTs) and in English. Data were synthesized using a random-effect or a fixed-effect model to analyze the effects of aerobic and resistance exercise on six elements in in school-age children with overweight or obese. The primary outcome measures were set for BMI. A total of 13 RCTs (504 participants) were identified. Analysis of the between-group showed that aerobic and resistance exercise were effective in improving BMI (MD = -0.66; p < 0.00001), body fat percentage (MD = -1.29; p = 0.02), TG (std.MD = -1.14; p = 0.005), LDL (std.MD = -1.38; p = 0.003), TC (std.MD = -0.77; p = 0.002), VO.sub.2 peak (std.MD = 1.25; p = 0.001). However, aerobic and resistance exercise were not significant in improving HDL (std.MD = 0.13; p = 0.27). Aerobic exercise and resistance exercise are associated with improvement in BMI, body fat percentage, VO.sub.2 peak, TG, LDL, TC, while not in HDL in school-age children with obesity or overweight. Insulin and insulin resistance were not able to be analyzed in our review. However, there are only two articles related to resistance exercise in children with obesity and overweight at school age, which is far less than the number of 12 articles about aerobic exercise, so we cannot compare the effects of the two types of exercises.

Internet of Things (IoT) applications often require only minimal necessary information—such as threshold judgments, binning, or prefixes—yet they must control privacy leakage arising from multi-round and cross-entity access without exposing raw values. Existing solutions, however, frequently rely on ciphertext structures and server-side states, making it difficult to define a leakage upper bound for restricted answers in the sense of Differential Privacy (DP), or they lack unified information budgeting and k-use control. To address these challenges, this paper proposes a verifiable differential privacy partial disclosure scheme for IoT. We employ DP accounting to uniformly constrain the leakage of three types of operators: threshold, binning, and prefix. Furthermore, we design stateless k-use tokens based on Verifiable Random Functions (VRFs) and chained receipts to generate publicly verifiable compliance evidence for each response. We implemented an end-edge-cloud prototype system and evaluated its performance on two use cases: smart meter threshold alarms and industrial sensor out-of-bound detection. Experimental results demonstrate that compared with a baseline relying on server-state counting for k-use control, our stateless k-use mechanism improves throughput by approximately 25–37% under concurrency scales of 1, 8, and 16, and reduces p95 latency by an average of 15%. Meanwhile, in multi-party splicing attack experiments, the re-identification accuracy remains stable in the 0.50–0.52 range, approximating random guessing. These results validate that the proposed scheme possesses low-energy engineering feasibility and audit-friendliness while effectively suppressing splicing risks.

Carborane is considered a three-dimensional mimetic of phenyl rings in medicinal chemistry. BMS-202 is a potent PD-L1 inhibitor that can block the PD-L1/PD-1 interaction and restore the immune response to cancer cells. Herein, we replaced the terminal phenyl group of BMS-202 with carborane and prepared its carboranyl BMS-202 analogues. The results showed a loss of PD-L1 binding affinity due to the bulky size of carborane, suggesting that carborane cannot serve as a phenyl ring mimetic in certain cases. Docking study demonstrated that the narrow binding pocket of PD-L1 could not hold the bulky carborane, resulting in loss of its activity. Compounds 1a and 1b exhibited anti-proliferative activities on a broad scope of cancer cell lines. Further studies indicate that compound 1a can induce cell apoptosis and lead to G1 cell cycle phase arrest. The boron biodistribution study of compound 1a revealed that the brain/blood uptake ratio was 0.60 ± 0.08, exhibiting a good blood-brain penetration capability.

Vacuum gauges based on Micro-Electro-Mechanical System (MEMS) technology have the advantages of small size, high reliability, and low cost, so they are widely used in semiconductor, chemical, laboratory, and aerospace. In this paper, a high-reliability MEMS Pirani vacuum gauge based on a porous silicon platform is designed, fabricated, and characterized. The repeatability within 4~105 Pa has been tested. The porous silicon acting as a support material achieved a porosity of 68% and a thermal conductivity of 3.5 W/(m·K), and the surface morphology of the porous silicon is smooth. The proposed MEMS Pirani vacuum gauge containing no suspended thin-film structures has good mechanical stability and is unaffected by mechanical shock and vibration in operation.

A carbon dioxide (CO2) gas sensor based on non-dispersive infrared (NDIR) technology has been developed and is suitable for use in portable devices for high-precision CO2 detection. The NDIR gas sensor comprises a MEMS infrared emitter, a MEMS thermopile detector with an integrated optical filter, and a compact gas cell with high optical coupling efficiency. A dual-ellipsoid mirror optical system was designed, and based on optical simulation analysis, the structure of the dual-ellipsoid reflective gas chamber was designed and optimized, achieving a coupling efficiency of up to 54%. Optical and thermal simulations were conducted to design the sensor structure, considering thermal management and light analysis. By optimizing the gas cell structure and conditioning circuit, we effectively reduced the sensor’s baseline noise, enhancing the overall reliability and stability of the system. The sensor’s dimensions were 20 mm × 10 mm × 4 mm (L × W × H), only 15% of the size of traditional NDIR gas sensors with equivalent detection resolution. The developed sensor offers high sensitivity and low noise, with a sensitivity of 15 μV/ppm, a detection limit of 90 ppm, and a resolution of 30 ppm. The total power consumption of the whole sensor system is 6.5 mW, with a maximum power consumption of only 90 mW.

Gestational exposure to environmental chemicals has long been considered an important contributor to adverse pregnancy outcomes. While humans are exposed to a large complexity of environmental chemicals under real scenarios, existing studies have generally focused on a limited number of substances when exploring the health impacts of environmental exposure. Our work employed the recently developed ExpoNano strategy to characterize exposure to 283 environmental chemicals via urine in pregnant women from three Chinese cities and explored the association between environmental exposure and the risk of gestational diabetes mellitus (GDM) through a nested case–control study within a prospective birth cohort. The results revealed ubiquitous gestational exposure (detection frequency > 70%) to 37 chemicals, including selected mono-phthalate esters (mono-PAEs), non-PAE plasticizers, synthetic antioxidants, organophosphate esters, personal care products, UV stabilizers, photoinitiators, pesticides, and hydroxy polyaromatic hydrocarbons across the three cities. The cumulative concentrations of detectable chemicals displayed median values of 461–741 ng/mL in different populations of pregnant women, which exhibited significant variations across regions. In the GDM case–control study (85 GDM cases and 170 healthy controls), although mixed exposure was not associated with the risk of GDM, exposure to acetyl tributyl citrate, an emerging plasticizer, was found to be significantly associated with GDM risk, based on both the single-pollutant and mixed exposure models. However, it should be noted that due to the relatively small sample size, the findings should be interpreted as preliminary exploratory results requiring further validation in larger cohorts. This study demonstrates the complexity of environmental chemical exposure during pregnancy, indicating a critical need for further investigations of the potential impact on pregnancy outcomes.

Metal oxide gas sensors usually require a few tens of milliwatts of power consumption to operate at high temperature, which limits their application in mobile and portable devices. Here, we proposed a cantilever structure to build an ultra-low power gas sensor for hydrogen sulfide gas detection. By employing a nano-film size effect to reduce the thermal conductivity of the material, and self-heated corrugation configuration, the power consumption of the gas sensor is significantly reduced. Through numerical analysis and finite element simulation, two different gas sensors were designed and the power consumption and stress distribution were analyzed and optimized. Under the operating temperature of 200 °C, only 0.27 mW power is consumed, the stress value is less than 250 MPa and the displacement is a few hundred of nanometers. The results serve as a guide and reference for ultra-low power MEMS device designs.

Ozone (O3) is a critical gas in various industrial applications, particularly in semiconductor manufacturing, where it is used for wafer cleaning and oxidation processes. Accurate and reliable detection of ozone concentration is essential for process control, ensuring product quality, and safeguarding workplace safety. By studying the UV absorption characteristics of O3 and combining the specific operational needs of semiconductor process gas analysis, a pressure-insensitive ozone gas sensor has been developed. In its optical structure, a straight-through design without corners was adopted, achieving a coupling efficiency of 52% in the gas chamber. This device can operate reliably in a temperature range from 0 °C to 50 °C, with only ±0.3% full-scale error across the entire temperature range. The sensor consists of a deep ultraviolet light-emitting diode in a narrow spectrum centered at 254 nm, a photodetector, and a gas chamber, with dimensions of 85 mm × 25 mm × 35 mm. The performance of the sensor has been meticulously evaluated through simulation and experimental analysis. The sensor’s gas detection accuracy is 750 ppb, with a rapid response time (t90) of 7 s, and a limit of detection of 2.26 ppm. It has the potential to be applied in various fields for ozone monitoring, including the semiconductor industry, water treatment facilities, and environmental research.