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Abstract Diagnosing diseases heavily relies on cell pathology images, but the extensive data in each manual identification of relevant cells labor-intensive, especially in regions with a scarcity of qualified healthcare professionals. This study aims to develop an intelligent system to enhance the diagnostic accuracy of cytopathology images by addressing image noise and segmentation issues, thereby improving the efficiency of medical professionals in disease diagnosis. We introduced an innovative system combining a self-supervised algorithm, SDN, for image denoising with data enhancement and image segmentation using the UPerMVit model. The UPerMVit model’s novel attention mechanisms and modular architecture provide higher accuracy and lower computational complexity than traditional methods. The proposed system effectively reduces image noise and accurately segments annotated images, highlighting cellular structures relevant to medical staff. This enhances diagnostic accuracy and aids in the accurate identification of pathological cells. Our intelligent system offers a reliable tool for medical professionals, improving diagnostic efficiency and accuracy in cytopathologic image analysis. It provides significant technical support in regions lacking adequate medical expertise.

Abstract The analysis and interpretation of cytopathological images are crucial in modern medical diagnostics. However, manually locating and identifying relevant cells from the vast amount of image data can be a daunting task. This challenge is particularly pronounced in developing countries where there may be a shortage of medical expertise to handle such tasks. The challenge of acquiring large amounts of high-quality labelled data remains, many researchers have begun to use semi-supervised learning methods to learn from unlabeled data. Although current semi-supervised learning models partially solve the issue of limited labelled data, they are inefficient in exploiting unlabeled samples. To address this, we introduce a new AI-assisted semi-supervised scheme, the Reliable-Unlabeled Semi-Supervised Segmentation (RU3S) model. This model integrates the ResUNet-SE-ASPP-Attention (RSAA) model, which includes the Squeeze-and-Excitation (SE) network, Atrous Spatial Pyramid Pooling (ASPP) structure, Attention module, and ResUNet architecture. Our model leverages unlabeled data effectively, improving accuracy significantly. A novel confidence filtering strategy is introduced to make better use of unlabeled samples, addressing the scarcity of labelled data. Experimental results show a 2.0% improvement in mIoU accuracy over the current state-of-the-art semi-supervised segmentation model ST, demonstrating our approach’s effectiveness in solving this medical problem.

Abstract Objectives Middle-aged and older adults smoking for years are afflicted by smoking-related diseases and functional limitations; however, little is known about the effect of smoking on nonfatal conditions in middle and later life. This study aims to investigate the impact of smoking on both total life expectancy (TLE) and disability-free life expectancy (DFLE) and the variations in such effects by educational level in China. Methods Data were drawn from the China Health and Retirement Longitudinal Study (CHARLS), 2011–2018, with a total sample of 16,859 individuals aged 45 years or older involved in the final analysis. The Activities of Daily Living (ADL) scale was used to measure disability, and the population-based multistate life table method was used to estimate the differences in TLE and DFLE by smoking status and educational attainment. Results At baseline, 28.9% of participants were current smokers, 8.5% were former smokers, and 62.6% never smoked. Approximately 5.6% were identified with ADL disability. Both current smokers and former smokers experienced lower TLE and DFLE than never smokers, and such differences were particularly prominent among men. Intriguingly, former smokers manifested a lower DFLE for both sexes and a lower TLE among women, though a longer TLE among men, compared with current smokers. Similar differences in TLE and DFLE by smoking status were observed for groups with different levels of education. Conclusion Never smokers live longer and healthier than current smokers and persons who quit smoking. Smoking was associated with greater reductions in TLE and DFLE among men. However, educational attainment might not moderate the adverse effect of smoking on both fatal and nonfatal conditions in the context of China. These findings have implications for disability prevention, aged care provision and informing policies of healthy aging for China and elsewhere.

Abstract Unprotected gradient exchange in federated learning (FL) systems may lead to gradient leakage-related attacks. CKKS is a promising approximate homomorphic encryption scheme to protect gradients, owing to its unique capability of performing operations directly on ciphertexts. However, configuring CKKS security parameters involves a trade-off between correctness, efficiency, and security. An evaluation gap exists regarding how these parameters impact computational performance. Additionally, the maximum vector length that CKKS can once encrypt, recommended by Homomorphic Encryption Standardization, is 16384, hampers its widespread adoption in FL when encrypting layers with numerous neurons. To protect gradients’ privacy in FL systems while maintaining practical performance, we comprehensively analyze the influence of security parameters such as polynomial modulus degree and coefficient modulus on homomorphic operations. Derived from our evaluation findings, we provide a method for selecting the optimal multiplication depth while meeting operational requirements. Then, we introduce an adaptive segmented encryption method tailored for CKKS, circumventing its encryption length constraint and enhancing its processing ability to encrypt neural network models. Finally, we present FedSHE, a privacy-preserving and efficient Federated learning scheme with adaptive Segmented CKKS Homomorphic Encryption. FedSHE is implemented on top of the federated averaging (FedAvg) algorithm and is available at https://github.com/yooopan/FedSHE . Our evaluation results affirm the correctness and effectiveness of our proposed method, demonstrating that FedSHE outperforms existing homomorphic encryption-based federated learning research efforts in terms of model accuracy, computational efficiency, communication cost, and security level.

Background:Ticks represent a significant vector for the transmission of infectious diseases, with the prevalence of tick-borne diseases becoming a prominent global health concern in recent decades. Anaplasma spp., Rickettsia spp., and Piroplasma have been identified as significant pathogens with the potential to impact human and animal health. However, there is a dearth of data concerning the prevalence of these pathogens in the eastern Tibetan Plateau, China.MethodsIn this study, a total of 643 Dermacentor silvarum and 314 Haemaphysalis longicornis were identified through the application of morphological and molecular identification techniques on 957 ticks collected from yaks in Zoige County. The assessed of Anaplasma spp., Rickettsia spp., Theileria spp., and Babesia spp. was assessed in 957 ticks and 96 blood samples collected from yaks.ResultsSignificant discrepancies were observed in the positivity rates for the four pathogens among the tick species and sampling sites. The identification of different species within the four pathogens was based on the analysis of the 16S rRNA of Anaplasma spp., the ompA and ompB genes of Rickettsia spp., and the 18S rRNA of Theileria spp. and Babesia spp. The prevalence ranges of the four pathogens are 9.9-50.2%, 29.5-100%, 16.2-46.4%, and 14.5-58.4%, respectively.ConclusionIn view of the growing zoonotic risks, further investigations into the prevalence of additional pathogens in ticks and animals, including livestock, in the eastern Tibetan Plateau, China, are essential.

Abstract Mitochondria, with their intricate networks of functions and information processing, are pivotal in both health regulation and disease progression. Particularly, mitochondrial dysfunctions are identified in many common pathologies, including cardiovascular diseases, neurodegeneration, metabolic syndrome, and cancer. However, the multifaceted nature and elusive phenotypic threshold of mitochondrial dysfunction complicate our understanding of their contributions to diseases. Nonetheless, these complexities do not prevent mitochondria from being among the most important therapeutic targets. In recent years, strategies targeting mitochondrial dysfunction have continuously emerged and transitioned to clinical trials. Advanced intervention such as using healthy mitochondria to replenish or replace damaged mitochondria, has shown promise in preclinical trials of various diseases. Mitochondrial components, including mtDNA, mitochondria-located microRNA, and associated proteins can be potential therapeutic agents to augment mitochondrial function in immunometabolic diseases and tissue injuries. Here, we review current knowledge of mitochondrial pathophysiology in concrete examples of common diseases. We also summarize current strategies to treat mitochondrial dysfunction from the perspective of dietary supplements and targeted therapies, as well as the clinical translational situation of related pharmacology agents. Finally, this review discusses the innovations and potential applications of mitochondrial transplantation as an advanced and promising treatment.

Abstract Background Although numerous studies have reported the prognostic value of the lung immune prognostic index (LIPI) in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), the prognostic value of the LIPI in a pancancer setting remains unclear. Methods A comprehensive search was conducted until July 2023 across the PubMed, Embase, Web of Science, and Cochrane Library databases to identify relevant studies evaluating the prognostic value of the LIPI in cancer patients treated with ICIs. The outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). We described and compared the pooled outcomes by stratifying the patients based on different groupings of LIPI (good vs. intermediate [0 vs. 1], good vs. poor [0 vs. 2], and good vs. intermediate / poor [0 vs. 1 + 2]). Results A total of 9959 patients in 35 studies were included. A higher score of LIPI was associated with impaired OS. The pooled HRs were 1.69 (95% CI: 1.55–1.85, p

Accurate evaluation of the nature and composition of coronary plaque involves clinical follow-up and prognosis. Coronary CT angiography is the most commonly non-invasive method for plaque evaluation, however, the qualitative and quantitative evaluation of plaque based on CT value is inaccurate, due to the influence of luminal attenuation, tube voltage, parameter setting and the subjectivity.

For modular multilevel converter-based battery energy storage systems (MMC-BESS), uneven power among batteries of SMs will be deduced by battery aging, battery fault, etc., which will degrade performance and even lead to system failure. For maintaining the balance of capacitor voltage, this paper analyzes the limits of the uneven power of batteries, which are presented as the current limits in this paper. According to analysis, an analytical method is proposed that only the dc and fundamental frequency components of the arm current are used to calculate current limits. With the current limits it is able to evaluate the reasonability of power distribution among batteries. Meanwhile, increase of fundamental frequency component will enhance the current limits, and the dc component determines the size relationship between the absolute values of the upper and lower current limits. Finally, simulation model and experiment prototype are built for verifying the theoretical analysis and current limits calculation method, and satisfactory results are provided.

[Introduction] In order to improve the power generation efficiency of photovoltaic brackets, the research and design focus is on a photovoltaic tracker based on Fourier fitting algorithm for apparent solar motion trajectory. [Method] The tracking accuracy of traditional solar motion trajectory algorithms was analyzed using MATLAB. Furthermore and an 8-order Fourier fitting solar motion trajectory tracking algorithm with better accuracy was proposed. The real-time solar motion trajectory was obtained combined with GNSS positioning technology. The system design employed the STM32 microcontroller as the microprocessor and adopted 6-axis acceleration sensor. The real-time tilt of the photovoltaic tracking bracket was determined by the projection of the gravity vector on its axis. Based on this, a three-dimensional operation model of the tracking bracket was established. By analyzing the cosine effect of sunlight on the bracket, the action angle required for the motor to operate can be obtained. At the same time, to solve the problem of shadow shielding between photovoltaic modules at dawn and dusk, the system added an inverse tracking algorithm. Considering the application of large-scale units, a master-slave motor synchronous control strategy was proposed. [Result] The Fourier fitting algorithm has higher tracking accuracy, reaching an accuracy of 10-2 orders of magnitude, one order of magnitude higher than traditional algorithms. At the same time, reverse tracking technology can save 24.3% of the photovoltaic array land area, significantly improving land use efficiency. [Conclusion] This study adopts a more accurate apparent solar motion trajectory tracking model, which effectively solves the cosine effect of solar radiation utilization, improves the power generation efficiency of power stations, realizes the construction of a safe and efficient green energy system, and promotes the promotion and achievement of China's goals of carbon peak and carbon neutrality.

To compare the differences between lyophilized powder (LP) and ethanol extract (EE) of Phyllanthus emblica Linn. (PE) in vitro digestion (oral cavity, gastric area, small intestine, and large intestine), this study identified the main components of PE and then compared total phenolic acids (TPA), total flavonoids (TFA) and antioxidant capacity before and after digestion. Results showed that both LP and EE of PE were rich in polyphenols and flavonoids. LP contained higher bound polyphenols than EE, while EE contained higher free polyphenols than LP. Before digestion, TPA and TFA of the LP were 5.40±0.07 mg GAE/mL and and 1.48±0.15 mg RT/mL, respectively. While the TPA and TFA of the EE were 3.65±0.05 mg GAE/mL and 14.80±0.74 mg RT/mL, respectively. After digestion, TPA of the LP and EE was significantly lower than before (P

Extracellular vesicles (EVs) have recently received much attention about the application of drug carriers due to their desirable properties such as nano-size, biocompatibility, and high stability. Herein, we demonstrate orange-derived extracellular vesicles (OEV) nanodrugs (DN@OEV) by modifying cRGD-targeted doxorubicin (DOX) nanoparticles (DN) onto the surface of OEV, enabling significantly enhancing tumor accumulation and penetration, thereby efficiently inhibiting the growth of ovarian cancer. The obtained DN@OEV enabled to inducement of greater transcytosis capability in ovarian cancer cells, which presented the average above 10-fold transcytosis effect compared with individual DN. It was found that DN@OEV could trigger receptor-mediated endocytosis to promote early endosome/recycling endosomes pathway for exocytosis and simultaneously reduce degradation in the early endosomes-late endosomes-lysosome pathway, thereby inducing the enhanced transcytosis. In particular, the zombie mouse model bearing orthotopic ovarian cancer further validated DN@OEV presented high accumulation and penetration in tumor tissue by the transcytosis process. Our study indicated the strategy in enhancing transcytosis has significant implications for improving the therapeutic efficacy of the drug delivery system.

Euchlorocystis marina, a new marine species of the genus Euchlorocystis discovered in 2022, has the potential to improve the water quality in mariculture ponds. However, the effects of salinity on the growth, physiology, and biochemical composition of these algae are not well understood. In this study, changes in physiological and biochemical indices such as cell density, photosynthetic pigment, polysaccharide, and lipid content of E. marina under different salinity treatments were analyzed. The results showed that the highest cell density was observed at a salinity of 15‰. The lowest photosynthetic pigment content was observed at a salinity of 60‰, and the highest polysaccharide and lipid content was observed at a salinity of 60‰. These results indicated that lower salinity was more conducive to E. marina reproduction and growth. E. marina can accumulate polysaccharides and lipids in high salinity environments. This study provides new information for understanding the salinity adaptation strategies of E. marina and has practical significance for its development and utilization.

Abstract Many Chinese wrinkle studies continue to use non-Chinese scales because few Chinese-based wrinkle scales have been developed. The study aims to develop a crow’s feet grading scale for Chinese individuals. We enrolled 608 healthy Chinese subjects and measured data through the DermaTOP system. We chose exploratory factor analysis (EFA) to reduce the dimensions of the data. A three-factor structure was obtained by using EFA, and it explained a cumulative total of 89.551% of the variance. A computational formula was obtained by calculating the total factor tilt scores and taking the variance contribution rate of three factors as the weight. Based on the computational formula, a grading map was designed and tested. The model validation was conducted using both subjective assessments from the expert panel and objective results from the model calculations. The results showed that our grading scale model is stable. This study developed a Chinese crow’s feet (CCF) grading scale, which included a parameter, a grading map, and literal descriptions. The CCF grading scale is a validated tool for evaluating the effects of cosmetics or specific therapies. More importantly, the CCF scale was developed based on objective data, which may inspire new ideas for wrinkle grading scale development in the future.

Objective Open arthrolysis (OA) combined with hinged external fixator (HEF) is a promising surgical option for patients with elbow stiffness. This study aimed to investigate elbow kinematics and function following a combined treatment with OA and HEF in elbow stiffness cases. Methods Patients treated with OA with or without HEF due to elbow stiffness were recruited between August 2017 and July 2019. Elbow flexion‐extension motion and function (Mayo elbow performance scores, MEPS) were recorded and compared between patients with and without HEF during a 1‐year follow‐up period. Additionally, those with HEF were assessed by dual fluoroscopy at week 6 postoperatively. Flexion‐extension and varus‐valgus motions, as well as ligament insertion distances of the anterior medial collateral ligament (AMCL) and lateral ulnar collateral ligament (LUCL), were compared between the surgical and intact sides. Results This study included 42 patients, of which 12 with HEF demonstrated a similar flexion‐extension angle and range of motion (ROM) and MEPS as the other patients. In patients with HEF, the surgical elbows showed limitations in flexion‐extension (maximal flexion, 120.5° ± 5.3° vs 140.4° ± 6.8°; maximal extension, 13.1° ± 6.0° vs 6.4° ± 3.0°; ROM, 107.4° ± 9.9° vs 134.0° ± 6.8°; all Ps

Cancer is a global public health issue that becomes the second primary cause of death globally. Considering the side effects of radio- or chemo-therapy, natural phytochemicals are promising alternatives for therapeutic interventions to alleviate the side effects and complications. Ginsenoside Rh2 (GRh2) is the main phytochemical extracted from Panax ginseng C.A. Meyer with anticancer activity. GRh2 could induce apoptosis and autophagy of cancer cells and inhibit proliferation, metastasis, invasion, and angiogenesis in vitro and in vivo. In addition, GRh2 could be used as an adjuvant to chemotherapeutics to enhance the anticancer effect and reverse the adverse effects. Here we summarized the understanding of the molecular mechanisms underlying the anticancer effects of GRh2 and proposed future directions to promote the development and application of GRh2.

Trichloroethylene (TCE) is a common industrial organic solvent and environmental contaminant. People are exposed to TCE through occupational contact or environmental pollution, which leads to serious human health hazards. A large number of studies have shown that oxidative stress plays an important role in the TCE-induced multi-target organ toxicity. However, the research of related signaling pathways remains to be deepened. In this review, we summarized the epidemiological, animal, and cellular studies correlated to liver toxicity, kidney toxicity, cardiac developmental toxicity, placental developmental toxicity, neurodevelopmental toxicity, and autoimmune response induced by TCE. In addition, the possible molecular mechanisms of oxidative stress in TCE-induced toxicity were concluded, including DNA damage, mitochondrial dysfunction, cell apoptosis, and abnormal activation of the immune system. Through literature review, we proposed that nuclear factor E2 related factor 2 may play an important role in mediating TCE-induced target organ toxicity, providing a theoretical basis for the prevention and treatment of adverse health effects caused by TCE.

Evidence from clinical studies and preclinical studies supports that exercise preconditioning can not only reduce the risk of stroke but also improve brain tissue and functional outcome after stroke. It has been demonstrated that autophagy and mitochondrial dynamics are involved in ischemic stroke. However, it is still unclear whether exercise preconditioning-induced neuroprotection against stroke is associated with modulation of autophagy and mitochondrial dynamics. Although age and sex interactively affect ischemic stroke risk, incidence, and outcome, studies based on young male animals are most often used to explore the role of exercise preconditioning in the prevention of ischemic stroke. In the current study, we examined whether exercise preconditioning could modulate autophagy and mitochondrial dynamics in a brain ischemia and reperfusion (I/R) model of female aged mice. The results showed that exercise preconditioning reduced infarct volume and improved neurological deficits. Additionally, increased levels of autophagy-related proteins LC3-II/LC3-I, LC3-II, p62, Atg7, and mitophagy-related proteins Bnip3L and Parkin, as well as increased levels of mitochondrial fusion modulator Mfn2 and mitochondrial fission modulator Drp1 in the ischemic cortex of female aged mice at 12 h after I/R were present. Our results could contribute to a better understanding of exercise preconditioning-induced neuroprotection against ischemic stroke for the elderly.

Abstract Background Previous studies have demonstrated the associations between loneliness and frailty in late life. However, there is a lack of consensus on the direction of the relationship. The present study aimed to examine the interdependencies between loneliness and frailty over time. Methods Data on participants aged 60 years old and above were collected from the 2011, 2013, and 2015 samples of the China Health and Retirement Longitudinal Study (CHARLS). Loneliness was measured by a single question from the Centre for Epidemiological Studies Depression scale, and frailty was assessed by the Physical Frailty Phenotype (PFP) scale. Cross-lagged panel models were utilized to examine the potential bidirectional relationship between loneliness and frailty. Results Reciprocal associations were found between loneliness and frailty. Furthermore, we found that baseline frailty and early change in frailty had a significant predictive effect on late change in loneliness. Higher baseline loneliness in older adults may create a potentially vicious cycle that influenced early change in frailty and continued to cause late change in loneliness. Conclusion A bidirectional relationship may exist between loneliness and frailty among older Chinese adults over 60 years old. Lonely older adults should be alerted to the potential self-reinforcing cycle of loneliness that affects their health.

Beyond traditional endothelium-dependent vessel (EDV), vascular mimicry (VM) is another critical tumor angiogenesis that further forms in many malignant metastatic tumors. However, the existing anti-angiogenesis combined chemotherapeutics strategies are only efficient for the treatment of EDV-based subcutaneous tumors, but remain a great challenge for the treatment of in situ malignant metastatic tumor associated with EDV and VM. Here, we demonstrate a self-assembled nanoparticle (VE-DDP-Pro) featuring self-anti-EDV and -VM capacity enables to significantly enhance the treatment efficacy of cisplatin (DDP) against the growth and metastasis of ovarian cancer. The VE-DDP-Pro is constructed by patching DDP loaded cRGD-folate-heparin nanoparticles (VE) onto the surface of protamine (Pro) nanoparticle. We demonstrated the self-anti-angiogenesis capacity of VE-DDP-Pro was attributed to VE, which could significantly inhibit the formation of EDV and VM by regulating signaling pathway of MMP-2/VEGF, AKT/mTOR/MMP-2/Laminin and AKT/mTOR/EMT, facilitating chemotherapeutics to effectively suppress the development and metastasis of ovarian cancer. Thus, combing with the chemotherapeutics effectiveness of DDP, the VE-DDP-Pro can significantly enhance treatment efficacy and prolong median survival of mice with metastatic ovarian cancer. We believe our self-assembled nanoparticles integrating the anti-EDV and anti-VM capacity provide a new preclinical sight to enhance the efficacy of chemotherapeutics for the treatment malignant metastasis tumor.

Trichloroethylene (TCE) triggers a severe hypersensitivity syndrome in the occupational population dependent on dendritic cells (DCs). Chloral hydrate (CH), the major oxidative metabolite of TCE, has been proved to be the culprit causative substance of TCE-induced hypersensitivity by human patch tests. Because redox imbalance is essential for chemical sensitizers-induced maturation of DCs, we predicted that CH would activate DCs by the nuclear factor E2-related factor 2 (Nrf2)-mediated antioxidant response. This study selected THP-1 cells as the in vitro DC model, and we evaluated the cell activation markers, intracellular oxidative stress, and Nrf2 pathway related genes expression in response to CH in THP-1 cells. CH displayed significant stimulation of THP-1 cells activation, including CD54 and CD86 expression, IL-8 release, and cell migration, and damaged the redox balance by triggering ROS generation, GSH consumption, and antioxidase activities modulation. The levels of Nrf2 and its downstream genes (HO-1 and NQO1) in mRNA and protein expressions were upregulated by CH, and CH also promoted the nuclear translocation of Nrf2. Subsequently, we investigated the effects of antioxidant on Nrf2-mediated cell defense in CH treated cells. Pretreatment with curcumin dramatically reduced cell activation and oxidative stress triggered by CH in THP-1 cells. We also confirmed the specific role of Nrf2 in CH-induced cell activation using NRF2-knockout cells. Deficiency of Nrf2 inhibited cell activation and downregulated HO-1 and NQO1 expression in CH-challenged cells. These findings suggest that Nrf2-dependent redox homeostasis plays a pivotal role in CH-induced activation of THP-1 cells, thereby providing new knowledge of the allergen as well as the molecular mechanism involving in TCE-induce hypersensitivity syndrome.

To find out the optimal treatment sessions of repetitive transcranial magnetic stimulation (TMS) over the primary motor cortex (M1) for upper extremity dysfunction after stroke during the 6-week treatment and to explore its mechanism using motor-evoked potentials (MEPs) and resting-state functional magnetic resonance imaging (rs-fMRI), 72 participants with upper extremity motor dysfunction after ischemic stroke were randomly divided into the control group, 10-session, 20-session, and 30-session rTMS groups. Low-frequency (1 Hz) rTMS over the contralesional M1 was applied in all rTMS groups. The motor function of the upper extremity was assessed before and after treatment. In addition, MEPs and rs-fMRI data were analyzed to detect its effect on brain reorganization. After 6 weeks of treatment, there were significant differences in the Fugl-Meyer Assessment of the upper extremity and the Wolf Motor Function Test scores between the 10-session group and the 30-session group and between the 20- and 30-session groups and the control group, while there was no significant difference between the 20-session group and the 30-session group. Meanwhile, no significant difference was found between the 10-session group and the control group. The 20-session group of rTMS decreased the excitability of the contralesional corticospinal tract represented by the amplitudes of MEPs and enhanced the functional connectivity of the ipsilesional M1 or premotor cortex with the the precentral gyrus, postcentral gyrus, and cingulate gyrus, etc. In conclusion, the 20-session of rTMS protocol is the optimal treatment sessions of TMS for upper extremity dysfunction after stroke during the 6-week treatment. The potential mechanism is related to its influence on the excitability of the corticospinal tract and the remodeling of corticomotor functional networks.

The Three-Rivers Headwater Region (TRHR), located in the hinterland of the Tibetan Plateau, serves as the “Water Tower of China”, providing vital water conservation (WC) services. Understanding the variations in WC is crucial for locally tailored efforts to adapt to climate change. This study improves the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) water yield model by integrating long-term time series of vegetation data, emphasizing the role of interannual vegetation variation. This study also analyzes the influences of various factors on WC variations. The results show a significant increase in WC from 1991 to 2020 (1.4 mm/yr, p < 0.05), with 78.17% of the TRHR showing improvement. Precipitation is the primary factor driving the interannual variations in WC. Moreover, distinct interactions play dominant roles in WC across different eco-geographical regions. In the north-central and western areas, the interaction between annual precipitation and potential evapotranspiration has the highest influence. Conversely, the interaction between annual precipitation and vegetation has the greatest impact in the eastern and central-southern areas. This study provides valuable insights into the complex interactions between the land and atmosphere of the TRHR, which are crucial for enhancing the stability of the ecosystem.

Fucoxanthin is a natural active substance derived from diatoms that is beneficial to the growth and immunity of humans and aquatic animals. Temperature, light and salinity are important environmental factors affecting the accumulation of diatom actives; however, their effects on the production of fucoxanthin in C. weissflogii are unclear. In this study, single-factor experiments are designed and followed by an orthogonal experiment to determine the optimal combination of fucoxanthin production conditions in C. weissflogii. The results showed that the optimum conditions for fucoxanthin production were a temperature of 30 °C, a light intensity of 30 umol m−2 s−1 and a salinity of 25. Under these conditions, the cell density, biomass, carotenoid content and fucoxanthin content of C. weissflogii reached 1.97 × 106 cell mL−1, 0.76 g L−1, 2.209 mg L−1 and 1.372 mg g−1, respectively, which were increased to 1.53, 1.71, 2.50 and 1.48 times higher than their initial content. The work sought to give useful information that will lead to an improved understanding of the effective method of cultivation of C. weissflogii for natural fucoxanthin production.

Since the 1970s, certain areas within the Three-Rivers Headwater Region (TRHR) of China have faced severe land degradation due to the combined effects of climate change and human activities, leading to restricted ecological service functions and hindering the achievement of sustainable development goals (SDGs). Land degradation in the TRHR has received widespread attention. However, the current research mainly focuses on single-dimensional degradation and lacks a comprehensive evaluation of patterns and structures, as well as above-ground and underground assessments. To address this gap, this study employed the SDG indicator 15.3.1 framework, comprehensively considering fragmentation and habitat quality index based on land cover changes, grassland degradation index, and soil water erosion index. These indexes represent the three land degradation pathways of landscape degradation, vegetation degradation, and soil erosion. This study assessed land degradation patterns in the TRHR from 2000 to 2020. Results show that approximately 44.67% of the TRHR experienced land degradation during this period, mainly in meadow-dominated regions. Additionally, 5.64% of the regions experienced the superimposition of two or more land degradation pathways, with the frequent coexistence of soil erosion and grassland degradation, accounting for 4.1% of the affected areas. Landscape degradation affected approximately 2.39% of the regions, characterized by increased grassland fragmentation or habitat quality degradation. In terms of grassland degradation, 22.26% of the regions showed medium degradation, while 7.21% and 5.63% experienced moderate and severe degradation, respectively. Moreover, approximately 13.36% of the region faced a worsening situation of soil erosion. Approximately 55.34% of the study area underwent land improvement, with significant enhancements mainly concentrated in the western and eastern regions. The regrowth of grassland in the western region and the enhancement and homogenization of grassland productivity in the eastern region played pivotal roles in promoting land improvement. This study provides critical insights into the land degradation pattern in the TRHR over the past 20 years, offering valuable references for formulating and implementing measures to protect and construct the ecological security barrier of the plateau.

Bordetella infection can be efficiently prevented through vaccination. The current study investigated the effects of an extract of Cochinchina momordica seed (ECMS) combined with oil on the immune responses to the inactivated Bordetella vaccine in mice. Serum IgG and IgG1 level was significantly increased in ECMS-oil group compared to any other group (P

With the development of big data, cloud services, and artificial intelligence, the optical network is developing towards scale and complexity, which suffers from larger probability of network failure. It is necessary to provide dedicated-path protection for each connection request to reduce the loss caused by the network failures. Therefore, in order to guarantee the network survivability, we propose a dedicated-path protection optimization method to improve the network resource efficiency in elastic optical networks with data centers. The simulation results show that the proposed dedicated-path protection optimization method can effectively reduce the blocking probability, improve the network resource utilization, and solve the survivability problem of elastic optical networks in data centers.

With the development of big data, cloud services, and artificial intelligence, the optical network is developing towards scale and complexity, which suffers from larger probability of network failure. It is necessary to provide dedicated-path protection for each connection request to reduce the loss caused by the network failures. Therefore, in order to guarantee the network survivability, we propose a dedicated-path protection optimization method to improve the network resource efficiency in elastic optical networks with data centers. The simulation results show that the proposed dedicated-path protection optimization method can effectively reduce the blocking probability, improve the network resource utilization, and solve the survivability problem of elastic optical networks in data centers.

Sediment microbial fuel cell (SMFC) is a type of MFC without a proton exchange membrane. However, SMFC have had problems with low-power production performance. In this paper, the effects of native bacteria (K1) in oily sludge and their electro-oil-induced domestication on the power generation and oil removal performance of SMFC were studied. The results showed that K1 belonged to Ochrobactrum intermedium. During the domestication process, an upward trend was shown in the OD600 and ORP values in the culture medium, and it grown best at 0.7 V. Ochrobactrum intermedium K1 significantly increased the average output voltage, electromotive force, and maximum power density of SMFC and reduced the apparent internal resistance of the battery. The maximum power density was 169.43 mW/m3, which was 8.59 times higher than that of the control group. Ochrobactrum intermedium K1 improved the degradation of crude oil by SMFC. Ochrobactrum intermedium K1 enhanced the degradation of high-carbon alkanes and even-carbon alkanes in n-alkanes. Cyclic voltammetry and chronoamperometry tests showed that after acclimation, Ochrobactrum intermedium K1 improved the extracellular electron transfer efficiency (EET) mediated by c-Cyts and flavin by increasing the surface protein redox potential.

Abstract Background Trichophyton mentagrophyte (TM), a zoonotic pathogen, has been endangering public health due to emerging drug resistance. Although increased attention is paid to this issue, there is very limited research available on drug resistance in TM. In this study, we studied the gene and proteomic changes, morphological changes, cellular fat localization, fat content changes, and biofilm of TM treated with different substances. Results The TM growth curve showed a positive correlation with the concentration of Fenarimol (FE), genistein (GE), clotrimazole (KM), and Miconazole nitrate salt (MK). The morphology of TM cells changed in different degrees after treatment with different substances as observed by TEM and SEM. The results showed that under KM and berberine hydrochloride (BB) treatment, a total of 3305 differentially expressed genes were detected, with the highest number in the KM-treated group (578 up-regulated and 615 down-regulated). A total of 847 proteins and 1850 peptides were identified in TM proteomics. Nile red staining showed that the fat content of TM was significantly higher in the BB-, ethidium bromide- (EB), FE-, KM-, Adriamycin hydrochloride- (YA), and MK-treated group compared to the control group. Results of the biofilm thickness showed that it gradually increased under treatment with specific concentrations of KM or BB, which may be related to the up-regulation of ERG25 and CYP related gene proteins. Conclusions It is suggested that in order to effectively deal with dermatomycosis caused by TM, it is necessary to inhibit the expression of ERG25 and CYP related genes and fat metabolism, which can result in the inhibition of the production of biofilm by the fungus and solve the problem of fungal drug resistance in clinical settings.

Using frequency-modulated continuous wave radar data from the 32nd Chinese Antarctic Research Expedition in 2015/16, subsurface profiles were obtained along an East Antarctic inland traverse from Zhongshan station to Dome A, and four distinct regions were selected to analyze the spatiotemporal variability in historical surface mass balance (SMB). Based on depth, density, and age data from ice cores along the traverse, the radar data were calibrated to yield average SMB data. The zone 49–195 km from the coast has the highest SMB (235 kg m−2 a−1). The 780–892 km zone was most affected by the Medieval Warm Period and the Little Ice Age, and the SMB during ad 1454–1836 (71 kg m−2 a−1) was only one-quarter of that in the 20th century. The SMB in the 1080–1157 km zone fluctuates the most, possibly due to erosion or irregular deposition of snow by katabatic winds in low SMB areas with surface elevation fluctuations. Dome A (1157–1236 km) has the lowest SMB (29 kg m−2 a−1) and did not decrease during Little Ice Age. Understanding the spatiotemporal variability of SMB in a larger space can help us understand the complex climate history of Antarctica.

Abstract Food-borne viruses and contaminants, as an important global food safety problem, are caused by chemical, microbiological, zoonotic, and other risk factors that represent a health hazard. Natural bioactive substances, originating from plants, animals, or microorganisms, might offer the possibility of preventing and controlling food-borne diseases. In this contribution, the common bioactive substances such as polyphenols, essential oils, proteins, and polysaccharides which are effective in the prevention and treatment of food-borne viruses and contaminants are discussed. Meanwhile, the preventive effects of natural bioactive substances and the possible mechanisms involved in food protection are discussed and detailed. The application and potential effects of natural bioactive substances in the adjuvant treatment for food-borne diseases is also described. Graphical abstract

ObjectiveTo establish a diagnostic model by combining imaging features with enhanced CT texture analysis to differentiate pancreatic serous cystadenomas (SCNs) from pancreatic mucinous cystadenomas (MCNs).Materials and MethodsFifty-seven and 43 patients with pathology-confirmed SCNs and MCNs, respectively, from one center were analyzed and divided into a training cohort (n = 72) and an internal validation cohort (n = 28). An external validation cohort (n = 28) from another center was allocated. Demographic and radiological information were collected. The least absolute shrinkage and selection operator (LASSO) and recursive feature elimination linear support vector machine (RFE_LinearSVC) were implemented to select significant features. Multivariable logistic regression algorithms were conducted for model construction. Receiver operating characteristic (ROC) curves for the models were evaluated, and their prediction efficiency was quantified by the area under the curve (AUC), 95% confidence interval (95% CI), sensitivity and specificity.ResultsFollowing multivariable logistic regression analysis, the AUC was 0.932 and 0.887, the sensitivity was 87.5% and 90%, and the specificity was 82.4% and 84.6% with the training and validation cohorts, respectively, for the model combining radiological features and CT texture features. For the model based on radiological features alone, the AUC was 0.84 and 0.91, the sensitivity was 75% and 66.7%, and the specificity was 82.4% and 77% with the training and validation cohorts, respectively.ConclusionThis study showed that a logistic model combining radiological features and CT texture features is more effective in distinguishing SCNs from MCNs of the pancreas than a model based on radiological features alone.

Axisymmetric resonators are key elements of Coriolis vibratory gyroscopes (CVGs). The performance of a CVG is closely related to the stiffness and damping symmetry of its resonator. The stiffness symmetry of a resonator can be effectively improved by electrostatic tuning or mechanical trimming, both of which need an accurate knowledge of the azimuth angles of the two stiffness axes of the resonator. Considering that the motion of a non-ideal axisymmetric resonator can be decomposed as two principal oscillations with two different natural frequencies along two orthogonal stiffness axes, this paper introduces a novel high-precision method of stiffness axes identification. The method is based on measurements of the phase difference between the signals detected at two orthogonal sensing electrodes when an axisymmetric resonator is released from all the control forces of the force-to-rebalance mode and from different initial pattern angles. Except for simplicity, our method works with the eight-electrodes configuration, in no need of additional electrodes or detectors. Furthermore, the method is insensitive to the variation of natural frequencies and operates properly in the cases of either large or small frequency splits. The introduced method is tested on a resonator gyroscope, and two stiffness axes azimuth angles are obtained with a resolution better than 0.1°. A comparison of the experimental results and theoretical model simulations confirmed the validity of our method.

A cylindrical resonator gyroscope is a kind of Coriolis gyroscope, which measures angular velocity or angle via processing of the standing wave. The symmetry of a cylindrical resonator is destroyed by different degrees of geometric nonuniformity and structural damage in the machining process. The uneven mass distribution caused by the asymmetry of the resonator can be expressed in the form of a Fourier series. The first three harmonics will reduce the anti-interference ability of the resonator to the external vibration, as well as increase the angular random walk and zero-bias drift of the gyroscope. In this paper, the frequency split of different modes caused by the first three harmonic errors and the displacement of the center of the cylindrical resonator bottom plate are obtained by simulation, and the relationship between them is explored. The experimental results on five fused silica cylindrical resonators are consistent with the simulation, confirming the linear relationship between the n = 1 frequency split and second harmonic error. A method for evaluating the first three harmonic errors of fused silica cylindrical resonators is provided.

Abstract Web applications are popular targets for cyber-attacks because they are network-accessible and often contain vulnerabilities. An intrusion detection system monitors web applications and issues alerts when an attack attempt is detected. Existing implementations of intrusion detection systems usually extract features from network packets or string characteristics of input that are manually selected as relevant to attack analysis. Manually selecting features, however, is time-consuming and requires in-depth security domain knowledge. Moreover, large amounts of labeled legitimate and attack request data are needed by supervised learning algorithms to classify normal and abnormal behaviors, which is often expensive and impractical to obtain for production web applications. This paper provides three contributions to the study of autonomic intrusion detection systems. First, we evaluate the feasibility of an unsupervised/semi-supervised approach for web attack detection based on the Robust Software Modeling Tool (RSMT), which autonomically monitors and characterizes the runtime behavior of web applications. Second, we describe how RSMT trains a stacked denoising autoencoder to encode and reconstruct the call graph for end-to-end deep learning, where a low-dimensional representation of the raw features with unlabeled request data is used to recognize anomalies by computing the reconstruction error of the request data. Third, we analyze the results of empirically testing RSMT on both synthetic datasets and production applications with intentional vulnerabilities. Our results show that the proposed approach can efficiently and accurately detect attacks, including SQL injection, cross-site scripting, and deserialization, with minimal domain knowledge and little labeled training data.

Abstract Background Pancreatic adenocarcinoma is often diagnosed at an advanced stage when adjacent vascular invasion is present. Accurate evaluation of presence of vascular invasion can help guide therapy. The aim of this study was to construct a nomogram for preoperative prediction of peripancreatic vein invasion in patients with pancreatic head cancer. Study design Data of patients with carcinoma head of pancreas and suspected peripancreatic invasion (n = 247) who underwent pancreatic resection with venous reconstruction between January 2012 and January 2017 at four academic institutions were retrospectively analyzed. Univariate and multivariate analyses were used to identify independent risk factors for vein invasion from among demographic, biological, conditional host-related, and anatomical data. A predictive nomogram was constructed based on the identified independent risk factors. Results The nomogram was constructed using data from 181 patients while the validation cohort consisted of 66 patients. Length of tumor contact (P = 0.031), circumferential vein involvement (P = 0.048), and venous contour abnormalities (P = 0.001) were independent predictors of venous invasion. The C-index of the model in predicting venous invasion was 0.963 for the external validation cohort. Patients could be assigned into low- ( 90%) groups based on the nomogram to facilitate personalized management. Conclusions Vein invasion by pancreatic head cancer is mainly associated with anatomical factors. The nomogram for prediction of vein invasion was found to be practicable.

BackgroundRenal angiomyolipoma without visible fat (RAML-wvf) and clear cell renal cell carcinoma (ccRCC) have many overlapping features on imaging, which poses a challenge to radiologists. This study aimed to create a scoring system to distinguish ccRCC from RAML-wvf using computed tomography imaging.MethodsA total of 202 patients from 2011 to 2019 that were confirmed by pathology with ccRCC (n=123) or RAML (n=79) were retrospectively analyzed by dividing them randomly into a training cohort (n=142) and a validation cohort (n=60). A model was established using logistic regression and weighted to be a scoring system. ROC, AUC, cut-off point, and calibration analyses were performed. The scoring system was divided into three ranges for convenience in clinical evaluations, and the diagnostic probability of ccRCC was calculated.ResultsFour independent risk factors are included in the system: 1) presence of a pseudocapsule, 2) a heterogeneous tumor parenchyma in pre-enhancement scanning, 3) a non-high CT attenuation in pre-enhancement scanning, and 4) a heterogeneous enhancement in CMP. The prediction accuracy had an ROC of 0.978 (95% CI, 0.956–0.999; P=0.011), similar to the primary model (ROC, 0.977; 95% CI, 0.954–1.000; P=0.012). A sensitivity of 91.4% and a specificity of 93.9% were achieved using 4.5 points as the cutoff value. Validation showed a good result (ROC, 0.922; 95% CI, 0.854–0.991, P=0.035). The number of patients with ccRCC in the three ranges (0 to 4 to ≤11 points) significantly increased with increasing scores.ConclusionThis scoring system is convenient for distinguishing between ccRCC and RAML-wvf using four computed tomography features.

The purpose of this study is to explore the information retrieval process in scientific data and to better understand the concepts and internal relationships of metadata and relevance criteria. Qualitative and quantitative analyses were performed using interview and eye movement data from 36 subjects. The results show that users paid attention to 45 types of metadata and used nine relevance criteria to judge the relevance of scientific data. There was a complex relationship between the metadata and criteria, mainly manifesting as one stimulus–multiple responses and multiple stimuli–one response. Metadata associated with the relevance criterion of topicality is the most complex, which includes common metadata and subject-related metadata. Metadata associated with the other relevance criteria (such as quality and authority) has no obvious professional characteristics. What’s more, because of the essential difference between scientific data and documents, users use different criteria. When retrieving data, users pay more attention to the availability of data and whether they can be further analyzed and processed. This study clarifies the concepts of metadata and relevance criteria as well as their roles in relevance judgments. In addition, this study deepens the understanding of the scientific data relevance judgments and their cognitive process and provides a theoretical basis for improving scientific data-sharing platforms.

In this paper, an optical correlator which adopts planar integrated 2F structure and optimal tradeoff synthetic discriminant function filter is proposed to improve the system integration and the recognition ability. The specialized digital microlens is designed for the correlator to replace the physical lens. By the theoretical analysis, the structural design conditions and parameters of the correlator are given, and the system volume is 63.1 cm3 which is only half of the planar integrated 4F optical correlator. Moreover, simulations and experimental research works reveal that the correlator can achieve stable recognition to the input object of distortion with scaling (52%, 150%), rotation (-50°, +42°), and existed scaling (72%, 130%) and rotation (-36°, +38°) simultaneously. Theoretical analysis and experimental results indicate that the planar integrated optical correlator with compact structure and high integration has good performance of distortion invariant recognition.

For the axisymmetric shell resonator gyroscopes, the quality factor (Q factor) of the resonator is one of the core parameters limiting their performances. Surface loss is one of the dominating losses, which is related to the subsurface damage (SSD) that is influenced by the grinding parameters. This paper experimentally studies the surface roughness and Q factor variation of six resonators ground by three different grinding speeds. The results suggest that the removal of the SSD cannot improve the Q factor continuously, and the variation of surface roughness is not the dominant reason to affect the Q factor. The measurement results indicate that an appropriate increase in the grinding speed can significantly improve the surface quality and Q factor. This study also demonstrates that a 20 million Q factor for fused silica cylindrical resonators is achievable using appropriate manufacturing processes combined with post-processing etching, which offers possibilities for developing high-precision and low-cost cylindrical resonator gyroscopes.

Species–area relationship has been widely addressed on many plant communities, but very few have conducted on epiphytic communities. Epiphytic plants are plentiful on ancient tea trees (Camelia sinensis var. assamica) in the well-known Jingmai tea plantation area, Langcang region of Yunnan Province, SW China, and add to the plant community biodiversity. We investigated 343 tea trees with various ground diameter, canopy area, under branch height, and tree height. A total of 146 vascular epiphytic plants, belonging to 19 species in seven families were recorded from the trunk or branches of 93 (27.11%) investigated trees. We examined in situ abundance, richness, and diversity (Shannon–Weiner index) of the recorded vascular epiphytes, and their relationships to tree variables. Our results showed that the distribution (abundance, richness, and diversity) of epiphytic plants are significantly related to the canopy area (p

The Internet of Things (IoT) has transformed many aspects of modern manufacturing, from design to production to quality control. In particular, IoT and digital manufacturing technologies have substantially accelerated product development- cycles and manufacturers can now create products of a complexity and precision not heretofore possible. New threats to supply chain security have arisen from connecting machines to the Internet and introducing complex IoT-based systems controlling manufacturing processes. By attacking these IoT-based manufacturing systems and tampering with digital files, attackers can manipulate physical characteristics of parts and change the dimensions, shapes, or mechanical properties of the parts, which can result in parts that fail in the field. These defects increase manufacturing costs and allow silent problems to occur only under certain loads that can threaten safety and/or lives. To understand potential dangers and protect manufacturing system safety, this paper presents two taxonomies: one for classifying cyber-physical attacks against manufacturing processes and another for quality control measures for counteracting these attacks. We systematically identify and classify possible cyber-physical attacks and connect the attacks with variations in manufacturing processes and quality control measures. Our taxonomies also provide a scheme for linking emerging IoT-based manufacturing system vulnerabilities to possible attacks and quality control measures.

The cylindrical resonator gyroscope (CRG) is a type of Coriolis vibratory gyroscope which measures the angular velocity or angle through the precession of the elastic wave of the cylindrical resonator. The cylindrical fused silica resonator is an essential component of the CRG, the symmetry of which determines the bias drift and vibration stability of the gyroscope. The manufacturing errors breaking the symmetry of the resonator are usually described by Fourier series, and most studies are only focusing on analyzing and reducing the fourth harmonic error, the main error source of bias drift. The second harmonic error also is one of the obstacles for CRG towards high precision. Therefore, this paper provides a chemical method to evaluate and balance the second harmonic error of cylindrical fused silica resonators. The relation between the frequency split of the n = 1 mode and the second harmonic error of the resonator is obtained. Simulations are performed to analyze the effects of the first three harmonic errors on the frequency splits. The relation between the location of the low-frequency axis of n = 1 mode and the heavy axis of the second harmonic error is also analyzed by simulation. Chemical balancing experiments on two fused silica resonators demonstrate the feasibility of this balancing procedure, and show good consistency with theoretical and simulation analysis. The second harmonic error of the two resonators is reduced by 86.6% and 79.8%, respectively.

The cylindrical resonator is the core component of cylindrical resonator gyroscopes (CRGs). The quality factor (Q factor) of the resonator is one crucial parameter that determines the performance of the gyroscope. In this paper, the finite element method is used to theoretically investigate the influence of the thermoelastic dissipation (TED) of the cylindrical resonator. The improved structure of a fused silica cylindrical resonator is then demonstrated. Compared with the traditional structure, the thermoelastic Q (QTED) of the resonator is increased by 122%. In addition, the Q factor of the improved cylindrical resonator is measured, and results illustrate that, after annealing and chemical etching, the Q factor of the resonator is significantly higher than that of the cylindrical resonators reported previously. The Q factor of the cylindrical resonator in this paper reaches 5.86 million, which is the highest value for a cylindrical resonator to date.

The fused silica cylindrical resonator is a type of axisymmetric resonator that can be used for Coriolis vibratory gyroscopes. Although the resonant frequency, frequency mismatch, and Q factor are natural properties of the resonator, they can change with temperature. Therefore, the temperature drift severely limits the detection accuracy and bias stability of the gyroscope. In this paper, the influence of temperature variation on the vibrational characteristics of fused silica cylindrical resonators was investigated. Experiments were performed on a fused silica cylindrical resonator coated with Cr/Au films. It was shown that at the temperature range from 253.15 K to 353.15 K, the resonant frequency linearly increased with temperature, the frequency mismatch remained unchanged, and the Q factor gradually increased till about 333.15 K, when it began to decrease. Meanwhile, the change of thermoelastic damping with temperature may dominate the variation of Q factor at the temperature range from 253.15 K to 353.15 K. This phenomenon was theoretically analyzed and the variation trends of results were consistent with the theoretical analysis. This study indicates that, for the fused silica cylindrical resonator, to discover the influence of temperature variation on the resonant frequency, frequency mismatch, and Q factor, there are certain rules to follow and repeat. The relationship between temperature and frequency can be established, which provides the feasibility of using self-calibration based on temperature characteristics of the resonator for temperature drift compensations. Additionally, there is an optimum temperature that may improve the performance of the Coriolis vibratory gyroscope with the fused silica cylindrical resonator.

The Coriolis Vibratory Gyroscopes are a type of sensors that measure angular velocities through the Coriolis effect. The resonator is the critical component of the CVGs, the vibrational characteristics of which, including the resonant frequency, frequency mismatch, Q factor, and Q factor asymmetry, have a great influence on the performance of CVG. The frequency mismatch and Q factor of the resonator, in particular, directly determine the precision and drift characteristics of the gyroscope. Although the frequency mismatch and Q factor are natural properties of the resonator, they can change with external conditions, such as temperature, pressure, and external forces. In this paper, the influence of electrostatic forces on the vibrational characteristics of the fused silica cylindrical resonator is investigated. Experiments were performed on a fused silica cylindrical resonator coated with Cr/Au films. It was shown that the resonant frequency, frequency mismatch, and the decay time slightly decreased with electrostatic forces, while the decay time split increased. Lower capacitive gaps and larger applied voltages resulted in lower frequency mismatch and lower decay time. This phenomenon was theoretically analyzed, and the variation trends of results were consistent with the theoretical analysis. This study indicates that, for fused silica cylindrical resonator with electrostatic transduction, the electrostatic influence on the Q factor and frequency, although small, should be considered when designing the capacitive gap and choosing bias voltages.