Skin microbiome and causal relationships in three dermatological diseases: Evidence from Mendelian randomization and Bayesian weighting.

BACKGROUND: Atopic dermatitis (AD), psoriasis (PSO), rosacea, and other related immune skin diseases are affected by multiple complex factors such as genetic and microbial components. This research investigates the causal relationships between specific skin microbiota and these diseases by using Mendelian randomization (MR), and Bayesian weighted Mendelian randomization (BWMR). METHODS: We utilized genome-wide association study (GWAS) data to analyze the associations between various skin bacteria and three dermatological diseases. Single nucleotide polymorphisms (SNPs) served as instrumental variables (IVs) in MR methods, including inverse variance weighted (IVW), and MR Egger. BWMR was employed to validate results and address pleiotropy. RESULTS: The IVW analysis identified significant associations between specific skin microbiota and dermatological diseases. ASV006_Dry, ASV076_Dry, and Haemophilus_Dry were significantly positively associated with AD, whereas Kocuria_Dry was negatively associated. In PSO, ASV005_Dry was negatively associated, whereas ASV004_Dry, Rothia_Dry, and Streptococcus_Moist showed positive associations. For rosacea, ASV023_Dry was significantly positively associated, while ASV016_Moist, Finegoldia_Dry, and Rhodobacteraceae_Moist were significantly negatively associated. These results were corroborated by BWMR analysis. CONCLUSION: Bacterial species such as Finegoldia, Rothia, and Streptococcus play crucial roles in the pathogenesis of AD, PSO, and rosacea. Understanding these microbial interactions can aid in developing targeted treatments and preventive strategies, enhancing patient outcomes and quality of life.

Explore the feasibility of using spot-scanning proton arc therapy for a synchrotron accelerator-based proton therapy system - A simulation study.

OBJECTIVE: The aim of this study was to evaluate the feasibility and plan quality of spot-scanning proton arc therapy (SPArc) using a synchrotron-accelerator-based proton therapy system compared to intensity-modulated proton therapy (IMPT). APPROACH: Five representative disease sites, including head and neck, lung, liver, brain chordoma, and prostate cancers, were retrospectively selected. Both IMPT and SPArc plans are generated with the HITACHI ProBEAT PBS system's minimum MU constraints and physics beam model. The SPArc plans are generated with 2.5° sampling frequency. The static delivery time was simulated based on the previously published synchrotron delivery sequence model, and the dynamic delivery time was simulated using a proton arc gantry mechanical model integrated with the synchrotron delivery sequence. Both dosimetric plan quality and delivery efficiency are evaluated. MAIN RESULTS: A superior plan quality is reached compared with the IMPT plans generated for the same disease site. However, a relatively prolonged static and dynamic delivery time post new challenge, as static time increased by 49.22% and dynamic time 59.10% on average. SIGNIFICANCE: This study presents the first simulation results of delivering the SPArc plans using a synchrotron-accelerated proton therapy system. The result shows its feasibility and limitations, which could guide future development.

Walnut peptide relieves hypertension and associated kidney and heart injury by regulating the renin-angiotensin-aldosterone system and intestinal microbiota.

BACKGROUND: Hypertension is a chronic disease with high morbidity and mortality. Previously, we screened a walnut meal peptide FDWLR (PEP) with significant angiotensin-converting enzyme inhibitory activity. The present study further investigated the anti-hypertensive effects of PEP in vivo using spontaneously hypertensive rats. RESULTS: The results indicated that PEP reduced blood pressure and the indices in the renin-angiotensin-aldosterone system (RAAS) including angiotensin-converting enzyme (ACE) (decreased by 15.36%), angiotensin II (Ang II) (decreased by 31.56%), angiotensinogen (AGT) (decreased by 58.84%) and aldosterone (ALD) (decreased by 18.27%), whereas NO levels increased by 54.96%. The pathological analysis showed that PEP relieved cardiac and renal damage. PEP also alleviated oxidative stress, inflammation and fibrosis in the heart and kidney. Mechanistically, PEP mitigated cardiac and renal damage by simultaneously regulating ACE-Ang II-AT1R and the ACE2-Ang (1-7)-MAS axis. Additionally, PEP increased the levels of short chain fatty acids by 224.16% and improved gut microbiota by increasing the abundance of Prevotella, Phascolarctobacterium, Clostridium_sensu_stricto and Bifidobacterium, at the same time as decreasing Bacteroides and Alistipes abundances. CONCLUSION: This study indicated that PEP prevented hypertension and associated heart and kidney damage by modulating the RAAS system and gut microbiota, which is valuable in guiding future development and optimal utilization of walnut meal. © 2024 Society of Chemical Industry.

Degradation Induced by Total Ionizing Dose and Hot Carrier Injection in SOI FinFET Devices.

The working environment of electronic devices in the aerospace field is harsh. In order to ensure the reliable application of the SOI FinFET, the total ionizing dose (TID) and hot carrier injecting (HCI) reliability of an SOI FinFET were investigated in this study. First, the influence of TID on the device was simulated. The results show that TID causes the threshold voltage to decrease and the off-state current and subthreshold swing to increase. TID causes more damage to the device at high temperature and also reduces the saturation drain current of the device. HCI causes the device threshold voltage to increase and the saturation drain current to decrease. The HCI is more severe at high temperatures. Finally, the coupling effects of the two were simulated, and the results show that the two effects cancel each other out, and the degradation of various electrical characteristic parameters is different under different coupling modes.

Research on the Coupling Effect of NBTI and TID for FDSOI pMOSFETs.

The coupling effect of negative bias temperature instability (NBTI) and total ionizing dose (TID) was investigated by simulation based on the fully depleted silicon on insulator (FDSOI) PMOS. After simulating the situation of irradiation after NBT stress, it was found that the NBTI effect weakens the threshold degradation of FDSOI PMOS under irradiation. Afterward, NBT stress was decomposed into high gate voltage stress and high-temperature stress, which was applied to the device simultaneously with irradiation. The devices under high gate voltage exhibited more severe threshold voltage degradation after irradiation compared to those under low gate voltage. Devices at high temperatures also exhibit more severe threshold degradation after irradiation compared to devices under low temperatures. Finally, the simultaneous effect of high gate voltage, high temperature, and irradiation on the device was investigated, which fully demonstrated the impact of the NBT stress on the TID effect, resulting in far more severe threshold voltage degradation.

Characterization of Escherichia coli pathogenicity and drug resistance in yolk peritonitis.

Yolk Peritonitis can lead to a rapid decline in egg production, which seriously affects the health of laying hens and the profitability of chicken farms. Escherichia coli (E. coli) is the most common cause of yolk peritonitis in laying hens. In this study, bacterial samples were collected from the ovaries and fallopian tubes of laying hens with suspected yolk peritonitis from a laying farm in Jiangsu Province, and their pathogenicity and drug resistance were investigated. Initially, morphological and biochemical detection methods were employed to isolate and identify the pathogenic bacteria. The results showed that a total of 16 strains of E. coli were isolated from laying hens with yolk peritonitis. Subsequently, the drug resistance and pathogenicity of a randomly selected E. coli strain were analyzed and predicted by genome sequencing technology, and the drug resistance of E. coli was verified by drug sensitivity test and PCR. Finally, the virulence was verified by infection experiment in mice. The study revealed that the egg-yolk peritonitis in laying hens was caused by E. coli infection, and the genome sequencing analysis revealed that the bacteria had multidrug resistance and high virulence. The drug susceptibility testing indicates that E. coli exhibited resistance to aminoglycosides, ß-lactam, macrolides, fluoroquinolones, and sulfonamides. In this study, resistance genes including KdpE, aadA5, APH(3 ")-ID, APH(6)-ID, and TEM-1 were identified, and their expression levels varied across different stages of bacterial growth. The results of virulence analysis indicated a mortality rate of 50% in mice infected with E. coli at a concentration of 2.985 × 107 CFU/mL. E. coli infection resulted in damage to various tissues and organs in mice, with the intestinal tissue structure being the most severely affected. This study provides a reference for the study of drug resistance mechanisms in E. coli and provides valuable insights into the selection of drugs for the treatment of vitelline peritonitis.

A study on the high power microwave effects of PIN diode limiter based on deep learning algorithm.

PIN diodes, due to their simple structure and variable resistance characteristics under high-frequency high-power excitation, are often used in radar front-end as limiters to filter high power microwaves (HPM) to prevent its power from entering the internal circuit and causing damage. This paper carries out theoretical derivation and research on the HPM effects of PIN diodes, and then uses an optimized neural network algorithm to replace traditional physical modeling to calculate and predict two types of HPM limiting indicators of PIN diode limiters. We proposes a neural network model for each of the following two prediction scenarios: in the scenario of time-junction temperature curves under different HPM irradiation, the weighted mean squared error (MSE) between the predicted values from the test dataset and the simulated values is below 0.004. While in predicting PIN limiter's power limitation threshold, insertion loss, and maximum isolation under different HPM irradiation, the MSE of the test set prediction values and simulation values are all less than 0.03. The method proposed in this research, which applies an optimized neural network algorithm to replace traditional physical modeling algorithms for studying the high-power microwave effects of PIN diode limiters, significantly improves the computational and simulation speed, reduces the calculation cost, and provides a new method for studying the high-power microwave effects of PIN diode limiters.

A novel angiotensin I-converting enzyme inhibitory peptide from walnut (Juglans sigillata) protein hydrolysates and its evaluation in Ang II-induced HUVECs and hypertensive rats.

This study aims to seek angiotensin-I-converting enzyme inhibitory (ACEi) peptides from walnut using different enzymatic hydrolysis, and further to validate the potent ACEi peptides identified and screened via peptidomics and in silico analysis against hypertension in spontaneously hypertensive rats (SHRs). Results showed that walnut protein hydrolysate (WPH) prepared by combination of alcalase and simulated gastrointestinal digestion exhibited high ACEi activity. WPH was separated via Sephadex-G25, and four peptides were identified, screened and verified based on their PeptideRanker score, structural characteristic and ACE inhibition. Interestingly, FDWLR showed the highest ACEi activity with IC50 value of 8.02 µg/mL, which might be related to its close affinity with ACE observed in molecular docking. Subsequently, high absorption and non-toxicity of FDWLR was predicted via in silico absorption, distribution, metabolism, excretion and toxicity. Furthermore, FDWLR exhibited positively vasoregulation in Ang II-induced human umbilical vein endothelial cells, and great blood pressure lowering effect in SHRs.

Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis.

AIM: Computer-aided drug design (CADD) is a drug design technique for computing ligand-receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics. METHODS: A systematic review of studies published between 2000 and 20 July 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analyzed using software such as Excel, VOSviewer, RStudio, and CiteSpace. RESULTS: A total of 2031 publications were included. These publications primarily originated from 99 countries or regions led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and the greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications. CONCLUSIONS: Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modeling, pharmacophore modeling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics that will influence future development. Furthermore, this paper will be helpful in better understanding the frontiers and hotspots of CADD.

Prediction of electrical properties of GAAFET based on integrated learning model.

As device feature sizes continue to decrease and fin field effect transistors reach their physical limits, gate all around field effect transistors (GAAFETs) have emerged with larger gate control areas and stackable characteristics for better suppression of second-order effects such as short-channel effects due to their gate encircling characteristics. Traditional methods for studying the electrical characteristics of devices are mostly based on the technology computer-aided design. Still, it is not conducive to developing new devices due to its time-consuming and inefficient drawbacks. Deep learning (DL) and machine learning (ML) have been well-used in recent years in many fields. In this paper, we propose an integrated learning model that integrates the advantages of DL and ML to solve many problems in traditional methods. This integrated learning model predicts the direct current characteristics, capacitance characteristics, and electrical parameters of GAAFET better than those predicted by DL or ML methods alone, with a linear regression factor (R2) greater than 0.99 and very small root mean square error. The proposed integrated learning model achieves fast and accurate prediction of GAAFET electrical characteristics, which provides a new idea for device and circuit simulation and characteristics prediction in microelectronics.

A False Trigger-Strengthened and Area-Saving Power-Rail Clamp Circuit with High ESD Performance.

A power clamp circuit, which has good immunity to false trigger under fast power-on conditions with a 20 ns rising edge, is proposed in this paper. The proposed circuit has a separate detection component and an on-time control component which enable it to distinguish between electrostatic discharge (ESD) events and fast power-on events. As opposed to other on-time control techniques, instead of large resistors or capacitors, which can cause a large occupation of the layout area, we use a capacitive voltage-biased p-channel MOSFET in the on-time control part of the proposed circuit. The capacitive voltage-biased p-channel MOSFET is in the saturation region after the ESD event is detected, which can serve as a large equivalent resistance (~106 Ω) in the structure. The proposed power clamp circuit offers several advantages compared to the traditional circuit, such as having at least 70% area savings in the trigger circuit area (30% area savings in the whole circuit area), supporting a power supply ramp time as fast as 20 ns, dissipating the ESD energy more cleanly with little residual charge, and recovering faster from false triggers. The rail clamp circuit also offers robust performance in an industry-standard PVT (process, voltage, and temperature) space and has been verified by the simulation results. Showing good performance of human body model (HBM) endurance and high immunity to false trigger, the proposed power clamp circuit has great potential for application in ESD protection.

Osteoporosis treatment using stem cell-derived exosomes: a systematic review and meta-analysis of preclinical studies.

BACKGROUND: The increasing incidence of osteoporosis in recent years has aroused widespread public concern; however, existing effective treatments are limited. Therefore, new osteoporosis treatment methods, including stem cell transplantation and exosome therapy, have been proposed and are gaining momentum. Exosomes are considered to have greater potential for clinical application owing to their immunocompatibility. This study summarises the latest evidence demonstrating the efficacy of exosomes in improving bone loss in the treatment of osteoporosis. MAIN TEXT: This systematic review and meta-analyses searched PubMed, Embase, and Cochrane Library databases from inception to 26 March 2022 for osteoporosis treatment studies using stem cell-derived exosomes. Six endpoints were selected to determine efficacy: bone mineral density, trabecular bone volume/tissue volume fraction, trabecular number, trabecular separation, trabecular thickness, and cortical thickness. The search generated 366 citations. Eventually, 11 articles that included 15 controlled preclinical trials and 242 experimental animals (rats and mice) were included in the meta-analysis. CONCLUSION: The results were relatively robust and reliable despite some publication biases, suggesting that exosome treatment increased bone mass, improved bone microarchitecture, and enhanced bone strength compared with placebo treatments. Moreover, stem cell-derived exosomes may favour anabolism over catabolism, shifting the dynamic balance towards bone regeneration.

Incorporating the synthetic CT image for improving the performance of deformable image registration between planning CT and cone-beam CT.

Objective: To develop a contrast learning-based generative (CLG) model for the generation of high-quality synthetic computed tomography (sCT) from low-quality cone-beam CT (CBCT). The CLG model improves the performance of deformable image registration (DIR). Methods: This study included 100 post-breast-conserving patients with the pCT images, CBCT images, and the target contours, which the physicians delineated. The CT images were generated from CBCT images via the proposed CLG model. We used the Sct images as the fixed images instead of the CBCT images to achieve the multi-modality image registration accurately. The deformation vector field is applied to propagate the target contour from the pCT to CBCT to realize the automatic target segmentation on CBCT images. We calculate the Dice similarity coefficient (DSC), 95 % Hausdorff distance (HD95), and average surface distance (ASD) between the prediction and reference segmentation to evaluate the proposed method. Results: The DSC, HD95, and ASD of the target contours with the proposed method were 0.87 ± 0.04, 4.55 ± 2.18, and 1.41 ± 0.56, respectively. Compared with the traditional method without the synthetic CT assisted (0.86 ± 0.05, 5.17 ± 2.60, and 1.55 ± 0.72), the proposed method was outperformed, especially in the soft tissue target, such as the tumor bed region. Conclusion: The CLG model proposed in this study can create the high-quality sCT from low-quality CBCT and improve the performance of DIR between the CBCT and the pCT. The target segmentation accuracy is better than using the traditional DIR.

Prediction of Single-Event Effects in FDSOI Devices Based on Deep Learning.

Single-event effects (SEE) are an important index of radiation resistance for fully depleted silicon on insulator (FDSOI) devices. The research into traditional FDSOI devices is based on simulation software, which is time consuming, requires a large amount of calculation, and has complex operations. In this paper, a prediction method for the SEE of FDSOI devices based on deep learning is proposed. The characterization parameters of SEE can be obtained quickly and accurately by inputting different particle incident conditions. The goodness of fit of the network curve for predicting drain transient current pulses can reach 0.996, and the accuracy of predicting the peak value of drain transient current and total collected charge can reach 94.00% and 96.95%, respectively. Compared with TCAD Sentaurus software, the simulation speed is increased by 5.10 × 102 and 1.38 × 103 times, respectively. This method can significantly reduce the computational cost, improve the simulation speed, and provide a new feasible method for the study of the single-event effect in FDSOI devices.

Trends in incidence and survival in patients with gastrointestinal neuroendocrine tumors: A SEER database analysis, 1977-2016.

Objectives: We aimed to determine trends in incidence and survival in patients with gastrointestinal neuroendocrine tumors (GI-NETs) from 1977 to 2016, and then analyze the potential risk factors including sex, age, race, grade, Socioeconomic status (SES), site, and stage. Methods: Data were obtained from Surveillance, Epidemiology, and End Results Program (SEER) database. Kaplan-Meier survival analysis, relative survival rates (RSRs), and Cox proportional risk regression model were used to evaluate the relationship between these factors and prognosis. Results: Compared with other sites, the small intestine and rectum have the highest incidence, and the appendix and rectum had the highest survival rate. The incidence was higher in males than in females, and the survival rate in males was close to females. Blacks had a higher incidence rate than whites, but similar survival rates. Incidence and survival rates were lower for G3&4 than for G1 and G2. Age, stage, and grade are risk factors. Conclusions: This study described changes in the incidence and survival rates of GI-NETs from 1977 to 2016 and performed risk factor analyses related to GI-NETs.

Visual analysis of research hotspots and trends of external therapies in traditional Chinese medicine for insomnia / 数字中医药（英文）

@#【Objective】 To explore the current status and development trend of research on external therapies in traditional Chinese medicine (TCM) for insomnia over the past 10 years through bibliometrics and visual analysis, to provide references for further research on the topic. 【Methods】 Literature relating to TCM external therapies for insomnia from January 1, 2012 to December 31, 2021 was retrieved from Chinese databases, including China National Knowledge Infrastructure (CNKI), Wanfang Database, China Science and Technology Journal Database (VIP), and from the Web of Science Core Collection (WOSCC) for English articles. CiteSpace, VOSviewer, Scimago Graphica, and NoteExpress software were used to analyze publication volumes of the papers and how they were distributed in different journals, as well as to visualize the data of the countries, authors, institutions, and keywords. 【Results】 A total of 6 085 papers were obtained, of which 5 592 were from the Chinese databases and 493 were from the English database, with their publication volumes growing steadily year on year. Approximately 45 countries and regions were found to have published research on the topic. In terms of Chinese publications, the author with the most papers published was CHEN Yunfei from Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine. The closest collaboration was between LIU Chengyong from the Affiliated Hospital of Nanjing University of Chinese Medicine and YUE Zenghui from Hunan University of Chinese Medicine. In terms of English publications, the author with the most papers published was MAO Junj from Sloan-Kettering Cancer Research Center, USA, and LAO Lixing from the University of Hong Kong was his closest partner in collaboration. Heilongjiang University of Chinese Medicine was the institution with the most Chinese publications, and Shanghai University of Traditional Chinese Medicine was the one with the most English papers published. Studies on the topic were published in 386 Chinese journals and 205 English journals, respectively. Nowadays, the clinical application of TCM external treatments for insomnia, the selection of meridians and acupoints, therapies for insomnia and its related diseases are research hotspots. The combined use of different TCM external therapies is a trend in the treatment of insomnia and its concomitant diseases, especially in the fields of oncology, nursing, and psychiatric disorders. The exploration of mechanisms of TCM external therapies for insomnia is also a key direction for future research. In clinical practice, the commonly used external therapies for insomnia include acupuncture, ear-acupressure with beans, acupoint application, etc. The commonly selected acupoints are auricular points, Sishencong (EX-HN1), Shenmen (HT7), etc. The frequently studied meridians are Ren, Du, Qiao, etc. The insomnia concomitant diseases are depression, stroke, anxiety, etc. 【Conclusion】 A wealth of research results have been accumulated in the treatment of insomnia by TCM external therapies, but authoritative research results are not so many. Therefore, institutions in different countries should strengthen communications and cooperation, and researchers should be encouraged to make innovations and breakthroughs on the basis of inherited TCM external therapies, so as to produce more valuable research results and improve TCM external therapies for providing better treatments for patients with sleep disorders.

A Novel DTSCR Structure with High Holding Voltage and Enhanced Current Discharge Capability for 28 nm CMOS Technology ESD Protection.

To cope with the much narrower ESD design window in 28 nm CMOS technology, a novel diode-triggered silicon-controlled rectifier with an extra discharge path (EDP-DTSCR) for ESD protection is proposed in this paper. Compared with the traditional DTSCR, the proposed DTSCR has an enhanced current discharge capability that is achieved by creating a slave SCR path in parallel with the master SCR path. Moreover, the improved triggering and holding characteristic can be obtained by the proposed EDP-DTSCR. By sharing the anode emitter junction, a slave SCR path is constructed that is symmetrical to the position of the master SCR path to add an additional ESD discharge path to the EDP-DTSCR. In this way, the current discharge capability of the entire device is obviously improved. The TCAD simulation result shows that the proposed device has a remarkably lower on-resistance compared with the traditional DTSCR and the DTSCR with p-type guard ring (PGR-DTSCR). In addition, it is structurally optimized to further increase the holding voltage and reduce the trigger voltage to improve the anti-latching capability of the device, which is more conducive to the ESD protection window application of 28 nm CMOS technology.