Effects of SARS-COV-2 infection during the frozen-thawed embryo transfer cycle on embryo implantation and pregnancy outcomes.

STUDY QUESTION: Does severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during the frozen-thawed embryo transfer (FET) cycle affect embryo implantation and pregnancy rates? SUMMARY ANSWER: There is no evidence that SARS-CoV-2 infection of women during the FET cycle negatively affects embryo implantation and pregnancy rates. WHAT IS KNOWN ALREADY: Coronavirus disease 2019 (COVID-19), as a multi-systemic disease, poses a threat to reproductive health. However, the effects of SARS-CoV-2 infection on embryo implantation and pregnancy following fertility treatments, particularly FET, remain largely unknown. STUDY DESIGN, SIZE, DURATION: This retrospective cohort study, included women who underwent FET cycles between 1 November 2022 and 31 December 2022 at an academic fertility centre. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women who tested positive for SARS-CoV-2 during their FET cycles were included in the COVID-19 group, while those who tested negative during the same study period were included in the non-COVID-19 group. The primary outcome was ongoing pregnancy rate. Secondary outcomes included rates of implantation, biochemical pregnancy, clinical pregnancy, early pregnancy loss, and ongoing pregnancy. Multivariate logistic regression models were applied to adjust for potential confounders including age, body mass index, gravidity, vaccination status, and endometrial preparation regimen. Subgroup analyses were conducted by time of infection with respect to transfer (prior to transfer, 1-7 days after transfer, or 8-14 days after transfer) and by level of fever (no fever, fever <39°C, or fever ≥39°C). MAIN RESULTS AND THE ROLE OF CHANCE: A total of 243 and 305 women were included in the COVID-19 and non-COVID-19 group, respectively. The rates of biochemical pregnancy (58.8% vs 62.0%, P = 0.46), clinical pregnancy (53.1% vs 54.4%, P = 0.76), implantation (46.4% vs 46.2%, P = 0.95), early pregnancy loss (24.5% vs 26.5%, P = 0.68), and ongoing pregnancy (44.4% vs 45.6%, P = 0.79) were all comparable between groups with or without infection. Results of logistic regression models, both before and after adjustment, revealed no associations between SARS-CoV-2 infection and rates of biochemical pregnancy, clinical pregnancy, early pregnancy loss, or ongoing pregnancy. Moreover, neither the time of infection with respect to transfer (prior to transfer, 1-7 days after transfer, or 8-14 days after transfer) nor the level of fever (no fever, fever <39°C, or fever ≥39°C) was found to be related to pregnancy rates. LIMITATIONS, REASONS FOR CAUTION: The retrospective nature of the study is subject to possible selection bias. Additionally, although the sample size was relatively large for the COVID-19 group, the sample sizes for certain subgroups were relatively small and lacked adequate power, so these results should be interpreted with caution. WIDER IMPLICATIONS OF THE FINDINGS: The study findings suggest that SARS-CoV-2 infection during the FET cycle in females does not affect embryo implantation and pregnancy rates including biochemical pregnancy, clinical pregnancy, early pregnancy loss, and ongoing pregnancy, indicating that cycle cancellation due to SARS-CoV-2 infection may not be necessary. Further studies are warranted to verify these findings. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by the National Key Research and Development Program of China (2023YFC2705500, 2019YFA0802604), National Natural Science Foundation of China (82130046, 82101747), Shanghai leading talent program, Innovative research team of high-level local universities in Shanghai (SHSMU-ZLCX20210201, SHSMU-ZLCX20210200, SSMU-ZLCX20180401), Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital Clinical Research Innovation Cultivation Fund Program (RJPY-DZX-003), Science and Technology Commission of Shanghai Municipality (23Y11901400), Shanghai Sailing Program (21YF1425000), Shanghai's Top Priority Research Center Construction Project (2023ZZ02002), Three-Year Action Plan for Strengthening the Construction of the Public Health System in Shanghai (GWVI-11.1-36), and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (20161413). The authors have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A.

Functional cure induced by tenofovir alafenamide plus peginterferon-alpha-2b in young children with chronic hepatitis B: a case series study.

BACKGROUND AND AIMS: Data on the safety and effectiveness of tenofovir alafenamide (TAF) plus peginterferon-alpha (Peg-IFN-α) in children with chronic hepatitis B (CHB) are lacking. The current study aimed to present the characteristics of four pediatric CHB patients who obtained a functional cure by using TAF and Peg-IFN-α. METHODS: In this case series study initiated in May 2019, ten children who had no clinical symptoms or signs received response-guided (HBV DNA undetectable, hepatitis B e antigen [HBeAg] loss or seroconversion, and hepatitis B surface antigen [HBsAg] loss or seroconversion) and functional cure-targeted (HBsAg loss or seroconversion) TAF (25 mg/d, orally) plus Peg-IFN-α-2b (180 µg/1.73m2, subcutaneously, once weekly) in combination (9/10) or sequential (1/10) therapy. The safety and effectiveness of these treatments were monitored. RESULTS: As of April 2024, four out of ten children obtained a functional cure after a mean of 31.5 months of treatment, and the other six children are still undergoing treatment. These four cured children, aged 2, 4, 8, and 6 years, were all HBeAg-positive and had alanine aminotransferase levels of 80, 47, 114, and 40 U/L; HBV DNA levels of 71200000, 93000000, 8220, and 96700000 IU/mL; and HBsAg levels of 39442.8, 15431.2, 22, and 33013.1 IU/mL, respectively. During treatment, all the children (10/10) experienced mild or moderate adverse events, including flu-like symptoms, anorexia, fatigue, and cytopenia. Notably, growth retardation (8/10) was the most significant adverse event; and it occurred in three cured children (3/4) treated with combination therapy and was present to a low degree in the other cured child (1/4) treated with sequential therapy. Fortunately, all three cured children recovered to or exceeded the normal growth levels at 9 months posttreatment. CONCLUSIONS: TAF plus Peg-IFN-α-2b therapy is potentially safe and effective for pediatric CHB patients, which may provide important insights for future clinical practice and study designs targeting functional cures for children with CHB.

Investigation of the mechanisms behind ochratoxin A-induced cytotoxicity in human astrocytes and the protective effects of N-acetylcysteine.

Ochratoxin A (OTA) is a type of mycotoxin commonly found in raw and processed foods. It is essential to be aware of this toxin, as it can harm your health if consumed in high quantities. OTA can induce toxic effects in various cell models. However, a more comprehensive understanding of the harmful effects of OTA on human astrocytes is required. This study evaluated OTA's neurotoxic effects on the Gibco® Human Astrocyte (GHA) cell line, its underlying mechanisms, and the antioxidant N-acetylcysteine (NAC) ability to prevent them. OTA exposure within 5-30 µM has induced concentration-dependent cytotoxicity. In the OTA-treated cells, the levels of reactive oxygen species (ROS) were found to be significantly increased, while the glutathione (GSH) contents were found to decrease considerably. The western blotting of OTA-treated cells has revealed increased Bax, cleaved caspase-9/caspase-3 protein levels, and increased Bax/Bcl-2 ratio. In addition, exposure to OTA has resulted in the induction of antioxidant responses associated with the protein expressions of Nrf2, HO-1, and NQO1. On the other hand, the pretreatment with NAC has partially alleviated the significant toxic effects of OTA. In conclusion, our findings suggest that oxidative stress and apoptosis are involved in the OTA-induced cytotoxicity in GHA cells. NAC could act as a protective agent against OTA-induced oxidative damage.

Time domain turbo equalization based on vector approximate message passing for multiple-input multiple-output underwater acoustic communications.

This paper proposes a high-performance receiver for underwater acoustic communications based on time reversal processing for multiple-input multiple-output (MIMO) systems. The receiver employs the vector approximate message passing (VAMP) algorithm as a soft equalizer in turbo equalization. By performing self-iteration between the inner soft slicer and the inner soft equalizer, the VAMP algorithm achieves near-optimal performance. Furthermore, an iterative channel-estimation-based soft successive interference cancellation method is incorporated to suppress co-channel interference in the MIMO system. Additionally, the introduction of passive time reversal technology can combine multiple channels into a single channel, which greatly reduces the computational complexity of the MIMO system, especially for large MIMO systems. The effectiveness of the proposed receiver is verified using experimental data collected in Songhua Lake, China in 2019. The results demonstrate that the proposed receiver significantly reduces the complexity of the traditional parallel-VAMP receiver without sacrificing performance and outperforms other receivers of the same type. Moreover, our experimental results also verify that the VAMP-turbo outperforms the generalized approximate message passing (GAMP)-turbo in terms of bit error rate and convergence performance.

A Combined Filtering Method for ZigBee Indoor Distance Measurement.

Indoor distance measurement technology utilizing Zigbee's Received Signal Strength Indication (RSSI) offers cost-effective and energy-efficient advantages, making it widely adopted for indoor distance measurement applications. However, challenges such as multipath effects, signal attenuation, and signal blockage often degrade the accuracy of distance measurements. Addressing these issues, this study proposes a combined filtering approach integrating Kalman filtering, Dixon's Q-test, Gaussian filtering, and mean filtering. Initially, the method evaluates Zigbee's transmission power, channel, and other parameters, analyzing their impact on RSSI values. Subsequently, it fits a signal propagation loss model based on actual measured data to understand the filtering algorithm's effect on distance measurement error. Experimental results demonstrate that the proposed method effectively improves the conversion relationship between RSSI and distance. The average distance measurement error, approximately 0.46 m, substantially outperforms errors derived from raw RSSI data. Consequently, this method offers enhanced distance measurement accuracy, making it particularly suitable for indoor positioning applications.

Enhanced Indoor Positioning Using RSSI and Time-Distributed Auto Encoder-Gated Recurrent Unit Model.

This study presents a novel approach to indoor positioning leveraging radio frequency identification (RFID) technology based on received signal strength indication (RSSI). The proposed methodology integrates Gaussian Kalman filtering for effective signal preprocessing and a time-distributed auto encoder-gated recurrent unit (TAE-GRU) model for precise location prediction. Addressing the prevalent challenges of low accuracy and extended localization times in current systems, the proposed method significantly enhances the preprocessing of RSSI data and effectively captures the temporal relationships inherent in the data. Experimental validation demonstrates that the proposed approach achieves a 75.9% improvement in localization accuracy over simple neural network methods and markedly enhances the speed of localization, thereby proving its practical applicability in real-world indoor localization scenarios.

Enhancing UWB Indoor Positioning Accuracy through Improved Snake Search Algorithm for NLOS/LOS Signal Classification.

Non-line-of-sight (NLOS) errors significantly impact the accuracy of ultra-wideband (UWB) indoor positioning, posing a major barrier to its advancement. This study addresses the challenge of effectively distinguishing line-of-sight (LOS) from NLOS signals to enhance UWB positioning accuracy. Unlike existing research that focuses on optimizing deep learning network structures, our approach emphasizes the optimization of model parameters. We introduce a chaotic map for the initialization of the population and integrate a subtraction-average-based optimizer with a dynamic exploration probability to enhance the Snake Search Algorithm (SSA). This improved SSA optimizes the initial weights and thresholds of backpropagation (BP) neural networks for signal classification. Comparative evaluations with BP, Particle Swarm Optimizer-BP (PSO-BP), and Snake Optimizer-PB (SO-BP) models-performed using three performance metrics-demonstrate that our LTSSO-BP model achieves superior stability and accuracy, with classification accuracy, recall, and F1 score values of 90%, 91.41%, and 90.25%, respectively.

An imbalance data quality monitoring based on SMOTE-XGBOOST supported by edge computing.

Product assembly involves extensive production data that is characterized by high dimensionality, multiple samples, and data imbalance. The article proposes an edge computing-based framework for monitoring product assembly quality in industrial Internet of Things. Edge computing technology relieves the pressure of aggregating enormous amounts of data to cloud center for processing. To address the problem of data imbalance, we compared five sampling methods: Borderline SMOTE, Random Downsampling, Random Upsampling, SMOTE, and ADASYN. Finally, the quality monitoring model SMOTE-XGBoost is proposed, and the hyperparameters of the model are optimized by using the Grid Search method. The proposed framework and quality control methodology were applied to an assembly line of IGBT modules for the traction system, and the validity of the model was experimentally verified.

Edge computing-based proactive control method for industrial product manufacturing quality prediction.

With the emergence of intelligent manufacturing, new-generation information technologies such as big data and artificial intelligence are rapidly integrating with the manufacturing industry. One of the primary applications is to assist manufacturing plants in predicting product quality. Traditional predictive models primarily focus on establishing high-precision classification or regression models, with less emphasis on imbalanced data. This is a specific but common scenario in practical industrial environments concerning quality prediction. A SMOTE-XGboost quality prediction active control method based on joint optimization hyperparameters is proposed to address the problem of imbalanced data classification in product quality prediction. In addition, edge computing technology is introduced to address issues in industrial manufacturing, such as the large bandwidth load and resource limitations associated with traditional cloud computing models. Finally, the practicality and effectiveness of the proposed method are validated through a case study of the brake disc production line. Experimental results indicate that the proposed method outperforms other classification methods in brake disc quality prediction.

Trajectory Deformation-Based Multi-Modal Adaptive Compliance Control for a Wearable Lower Limb Rehabilitation Robot.

Adaptive compliance control is critical for rehabilitation robots to cope with the varying rehabilitation needs and enhance training safety. This article presents a trajectory deformation-based multi-modal adaptive compliance control strategy (TD-MACCS) for a wearable lower limb rehabilitation robot (WLLRR), which includes a high-level trajectory planner and a low-level position controller. Dynamic motion primitives (DMPs) and a trajectory deformation algorithm (TDA) are integrated into the high-level trajectory planner, generating multi-joint synchronized desired trajectories through physical human-robot interaction (pHRI). In particular, the amplitude modulation factor of DMPs and the deformation factor of TDA are adapted by a multi-modal adaptive regulator, achieving smooth switching of human-dominant mode, robot-dominant mode, and soft-stop mode. Besides, a linear active disturbance rejection controller is designed as the low-level position controller. Four healthy participants and two stroke survivors are recruited to conduct robot-assisted walking experiments using the TD-MACCS. The results show that the TD-MACCS can smoothly switch three control modes while guaranteeing trajectory tracking accuracy. Moreover, we find that appropriately increasing the upper bound of the deformation factor can enhance the average walking speed (AWS) and root mean square of trajectory deviation (RMSTD).

Exploration of beauvericin's toxic effects and mechanisms in human astrocytes and N-acetylcysteine's protective role.

Beauvericin (BEA) is a newly identified mycotoxin produced by various Fusarium species, and its contamination in food and animal feed is widespread globally. This mycotoxin demonstrates cytotoxic effects by inducing oxidative stress in multiple models. Furthermore, evidence indicates that BEA possesses diverse toxic activities, making it a promising candidate for toxicological research. Recent studies have highlighted the ability of BEA to traverse the blood-brain barrier, suggesting its potential neurotoxicity. However, limited information is available regarding the neurotoxic effects of BEA on human astrocytes. Therefore, this study aimed to assess the neurotoxic effects of BEA on the Gibco® Human Astrocyte (GHA) cell line and elucidate the underlying mechanisms. Additionally, the study aimed to investigate the protective effects of the antioxidant N-acetylcysteine (NAC) against BEA-induced toxicity. The data show that exposure to BEA within the 2.5-15 µM concentration range resulted in concentration-dependent cytotoxicity. BEA-treated cells exhibited significantly increased levels of reactive oxygen species (ROS), while intracellular glutathione (GSH) content was significantly reduced. Western blot analysis of cells treated with BEA revealed altered protein levels of Bax, cleaved caspase-9, and caspase-3, along with an increased Bax/Bcl-2 ratio, indicating the induction of apoptosis. Additionally, BEA exposure triggered antioxidant responses, as evidenced by increased protein expression of Nrf2, HO-1, and NQO1. Significantly, pretreatment with NAC partially attenuated the significant toxic effects of BEA. In conclusion, our findings suggest that BEA-induced cytotoxicity in GHA cells involves oxidative stress-associated apoptosis. Furthermore, NAC demonstrates potential as a protective agent against BEA-induced oxidative damage.

Enhancing efficiency of ultrasound-assisted biodiesel production catalyzed by Eversa® Transform 2.0 at low lipase concentration: Enzyme characterization and process optimization.

This study focused on the ultrasound-assisted transesterification of simulated low-quality feedstocks using a low-cost liquid lipase Eversa® Transform 2.0 (ET2). Enzyme characterization was also performed to investigate the effect of ultrasound parameters on enzyme structure. The optimal ultrasound parameters, 40 % amplitude, and 5 % duty cycle effectively enhanced the reaction rate compared to the conventional stirring method while retaining 95 % of the enzyme activity. Analysis of circular dichroism (CD) spectra revealed the preservation of the secondary structure of ET2 under the optimal ultrasound intensities, while fluorescence spectra indicated a slight change in its tertiary structure. The implementation of a two-stage methanol dosing strategy in the ultrasound-assisted reaction effectively mitigated lipase inhibition, yielding a remarkable fatty acid methyl ester (FAME) content of 92.2 % achieved within a 12-h reaction time. Notable, this high FAME content was achieved with only a 4:1 methanol-to-oil molar ratio and a 0.5 wt% enzyme concentration. Under these optimized conditions, the ultrasound-assisted reaction also demonstrated a 15 % improvement in the final FAME content compared to the conventional stirring method. These promising results hold significant potential for advancing the field of biodiesel production via ultrasound technology, contributing substantively to sustainable energy sources.

Stabilization of Eversa® Transform 2.0 lipase with sorbitol to enhance the efficiency of ultrasound-assisted biodiesel production.

Ultrasound technology has emerged as a promising tool for enhancing enzymatic biodiesel production, yet the cavitation effect induced can compromise enzyme stability. This study explored the efficiency of polyols in enhancing lipase stability under ultrasound conditions to further improve biodiesel yield. The incorporation of sorbitol resulted in the highest fatty acid methyl ester (FAME) content in the ultrasound-assisted biodiesel production catalyzed by Eversa® Transform 2.0 among the investigated polyols. Furthermore, sorbitol enhanced the stability of the lipase, allowing it to tolerate up to 100 % ultrasound amplitude, compared to 60 % amplitude in its absence. Enzyme activity assays revealed that sorbitol preserved 99 % of the lipase activity, in contrast to 84 % retention observed without sorbitol under an 80 % ultrasound amplitude. Circular dichroism (CD) and fluorescence spectroscopy analyses confirmed that sorbitol enhanced lipase rigidity and preserved its conformational structure under ultrasound exposure. Furthermore, employing a stepwise methanol addition strategy in ultrasound-assisted reactions with sorbitol achieved an 81.2 wt% FAME content in 8 h with only 0.2 wt% enzyme concentration. This promising result highlights the potential of sorbitol as a stabilizing agent in ultrasound-assisted enzymatic biodiesel production, offering a viable approach for enhancing biodiesel yield and enzyme stability in industrial applications.

Engineering a Metal Reductase for the Bioremediation of Anthropogenic Electronic Wastes: From Hg(II) to Au(III) and Ag(I) Enzymatic Reduction.

Recovering precious metals from electronic waste (e-waste) using microbes presents a sustainable methodology that can contribute toward the maintenance of planetary health. To better realize the potential of bioremediation using engineered microbes, enzymes that mediate the reduction of Au(III) to Au(0) have been the subject of intense research. In this study, we report the successful engineering of a metal reductase, MerA, whose cognate substrate is mercury(II), toward other precious metals such as Au(III) and Ag(I). The engineered variant, G415I, exhibited a 15-fold increase in catalytic efficiency (k cat/K M) in Au(III) reduction to Au(0) and a 200-fold increase in catalytic efficiency in Ag(I) reduction to Ag(0) with respect to the wild-type enzyme. The apparent shift in preference toward noncognate metal ions may be attributed to the energetics of valency preference. The improved Au(III) reductase has an apparent increased preference toward monovalent cations such as Au(I) and Ag(I), with respect to divalent cations such as Hg(II), the cognate substrate of the progenitor MerA (an increase in K M of 5.0-fold for Hg(II), compared to a decrease in K M of 5.8-fold for Au(III) and 1.8-fold for Ag(I), respectively). This study further extends the mechanistic understanding of Au(III) bioreduction that could proceed through the stabilization of Au(I) en route to Au(0) and suggests that the biosynthesis of Au nanoparticles with high efficiency can be realized through the engineering of promiscuous metal reductases for precious metal recovery from e-wastes.

Novel Pyrazole Acyl(thio)urea Derivatives Containing a Biphenyl Scaffold as Potential Succinate Dehydrogenase Inhibitors: Design, Synthesis, Fungicidal Activity, and SAR.

As part of a program to discover novel succinate dehydrogenase inhibitor fungicides, a series of new pyrazole acyl(thio)urea compounds containing a diphenyl motif were designed and synthesized. Their structures were confirmed by 1H NMR, HRMS, and single X-ray crystal diffraction analysis. Most of these compounds possessed excellent activity against 10 fungal plant pathogens at 50 µg mL-1, especially against Rhizoctonia solani, Alternaria solani, Sclerotinia sclerotiorum, Botrytis cinerea, and Cercospora arachidicola. Interestingly, compounds 3-(difluoromethyl)-1-methyl-N-((3',4',5'-trifluoro-[1,1'-biphenyl]-2-yl)carbamoyl)-1H-pyrazole-4-carboxamide (9b, EC50 = 0.97 ± 0.18 µg mL-1), 1,3-dimethyl-N-((3',4',5'-trifluoro-[1,1'-biphenyl]-2-yl)carbamoyl)-1H-pyrazole-4-carboxamide (9a, EC50 = 2.63 ± 0.41 µg mL-1), and N-((4'-chloro-[1,1'-biphenyl]-2-yl)carbamoyl)-1,3-dimethyl-1H-pyrazole-4-carboxamide (9g, EC50 = 1.31 ± 0.15 µg mL-1) exhibited activities against S. sclerotiorum that were better than the commercial fungicide bixafen (EC50 = 9.15 ± 0.05 µg mL-1) and similar to the positive control fluxapyroxad (EC50 = 0.71 ± 0.11 µg mL-1). These compounds were not significantly phytotoxic to monocotyledonous and dicotyledonous plants. Structure-activity relationships (SAR) are discussed by substituent effects/molecular docking, and density functional theory analysis indicated that these compounds are succinate dehydrogenase inhibitors.

Establishment and validation of novel nomograms to predict muscle quality in colorectal cancer patients.

OBJECTIVES: The skeletal muscle mass index and skeletal muscle radiodensity have promise as specific diagnostic indicators for muscle quality. However, the difficulties in measuring low skeletal muscle mass index and low skeletal muscle radiodensity limit their use in routine clinical practice, impeding early screening and diagnosis. The objective of this study is to develop a nomogram that incorporates preoperative factors for predicting low skeletal muscle mass index and low skeletal muscle radiodensity. METHODS: A total of 1692 colorectal cancer patients between 2015 and 2021 were included. The patients were randomly divided into a training cohort (n = 1353) and a validation cohort (n = 339). Nomogram models were calibrated using the area under the curve, calibration curves, and the Hosmer-Lemeshow test to assess their predictive ability. Finally, a decision curve was applied to assess the clinical usefulness. RESULTS: In a prediction model for low skeletal muscle mass index, age, body mass index, and grip strength were incorporated as variables. For low skeletal muscle radiodensity, age, sex, body mass index, serum hemoglobin level, and grip strength were included as predictors. In the training cohort, the area under the curve value for low skeletal muscle mass index was 0.750 (95% CI, 0.726-0.773), whereas for low skeletal muscle radiodensity, it was 0.763 (95% CI, 0.739-0.785). The Hosmer-Lemeshow test confirmed that both models fit well in both cohorts. Decision curve analysis was applied to assess the clinical usefulness of the model. CONCLUSIONS: The incorporation of preoperative factors into the nomogram-based prediction model represents a significant advancement in the muscle quality assessment. Its implementation has the potential to early screen patients at risk of low skeletal muscle mass index and low skeletal muscle radiodensity.

Transcriptome profiling of fast/glycolytic and slow/oxidative muscle fibers in aging and obesity.

Aging and obesity pose significant threats to public health and are major contributors to muscle atrophy. The trends in muscle fiber types under these conditions and the transcriptional differences between different muscle fiber types remain unclear. Here, we demonstrate distinct responses of fast/glycolytic fibers and slow/oxidative fibers to aging and obesity. We found that in muscles dominated by oxidative fibers, the proportion of oxidative fibers remains unchanged during aging and obesity. However, in muscles dominated by glycolytic fibers, despite the low content of oxidative fibers, a significant decrease in proportion of oxidative fibers was observed. Consistently, our study uncovered that during aging and obesity, fast/glycolytic fibers specifically increased the expression of genes associated with muscle atrophy and inflammation, including Dkk3, Ccl8, Cxcl10, Cxcl13, Fbxo32, Depp1, and Chac1, while slow/oxidative fibers exhibit elevated expression of antioxidant protein Nqo-1 and downregulation of Tfrc. Additionally, we noted substantial differences in the expression of calcium-related signaling pathways between fast/glycolytic fibers and slow/oxidative fibers in response to aging and obesity. Treatment with a calcium channel inhibitor thapsigargin significantly increased the abundance of oxidative fibers. Our study provides additional evidence to support the transcriptomic differences in muscle fiber types under pathophysiological conditions, thereby establishing a theoretical basis for modulating muscle fiber types in disease treatment.

Intelligent medicine in focus: the 5 stages of evolution in robot-assisted surgery for prostate cancer in the past 20 years and future implications.

Robot-assisted surgery has evolved into a crucial treatment for prostate cancer (PCa). However, from its appearance to today, brain-computer interface, virtual reality, and metaverse have revolutionized the field of robot-assisted surgery for PCa, presenting both opportunities and challenges. Especially in the context of contemporary big data and precision medicine, facing the heterogeneity of PCa and the complexity of clinical problems, it still needs to be continuously upgraded and improved. Keeping this in mind, this article summarized the 5 stages of the historical development of robot-assisted surgery for PCa, encompassing the stages of emergence, promotion, development, maturity, and intelligence. Initially, safety concerns were paramount, but subsequent research and engineering advancements have focused on enhancing device efficacy, surgical technology, and achieving precise multi modal treatment. The dominance of da Vinci robot-assisted surgical system has seen this evolution intimately tied to its successive versions. In the future, robot-assisted surgery for PCa will move towards intelligence, promising improved patient outcomes and personalized therapy, alongside formidable challenges. To guide future development, we propose 10 significant prospects spanning clinical, research, engineering, materials, social, and economic domains, envisioning a future era of artificial intelligence in the surgical treatment of PCa.

Vebreltinib for Advanced Non-Small Cell Lung Cancer Harboring c-Met Exon 14 Skipping Mutation: A Multicenter, Single-Arm, Phase II KUNPENG Study.

PURPOSE: The KUNPENG study aimed to evaluate the efficacy and safety of vebreltinib (also known as bozitinib, APL-101, PLB-1001, and CBT-101), a potent and highly selective inhibitor of c-mesenchymal-epithelial transition (MET), in patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) harboring c-Met alterations. METHODS: This multicenter, multicohort, open-label, single-arm, phase II trial enrolled patients with c-Met dysregulated, locally advanced or metastatic NSCLC from January 2020 to August 2022 across 17 centers. Cohort 1 included patients with MET exon 14 skipping (METex14)-mutant NSCLC who had not previously received MET inhibitors. Participants were administered vebreltinib at a dosage of 200 mg twice a day in 28-day cycles. The primary end point was the objective response rate (ORR), and the key secondary end point was the duration of response (DoR), both evaluated by a blinded independent review committee according to the RECIST version 1.1. RESULTS: As of August 9, 2022, 52 patients had been enrolled in cohort 1, of whom 35 (67.3%) were treatment-naïve. The ORR reached 75% (95% CI, 61.1 to 86). Among treatment-naïve patients, the ORR was 77.1% (95% CI, 59.9 to 89.6), and in previously treated patients, it was 70.6% (95% CI, 44.0 to 89.7). The disease control rate was 96.2%, with a median DoR of 15.9 months, a median progression-free survival of 14.1 months, and a median overall survival of 20.7 months. The most common treatment-related adverse events were peripheral edema (82.7%), QT prolongation (30.8%), and elevated serum creatinine (28.8%). CONCLUSION: Vebreltinib has shown promising efficacy and a favorable safety profile in patients with METex14-mutant NSCLC.

Advances in the study of the effects of gut microflora on microglia in Alzheimer's disease.

Alzheimer's disease (AD) is a central nervous system (CNS) degenerative disorder, is caused by various factors including ß-amyloid toxicity, hyperphosphorylation of tau protein, oxidative stress, and others. The dysfunction of microglia has been associated with the onset and advancement of different neurodevelopmental and neurodegenerative disorders, such as AD. The gut of mammals harbors a vast and complex population of microorganisms, commonly referred to as the microbiota. There's a growing recognition that these gut microbes are intrinsically intertwined with mammalian physiology. Through the circulation of metabolites, they establish metabolic symbiosis, enhance immune function, and establish communication with different remote cells, including those in the brain. The gut microbiome plays a crucial part in influencing the development and performance of microglia, as indicated by recent preclinical studies. Dysbiosis of the intestinal flora leads to alterations in the microglia transcriptome that regulate the interconversion of microglia subtypes. This conversation explores recent research that clarifies how gut bacteria, their byproducts, and harmful elements affect the activation and characteristics of microglia. This understanding opens doors to innovative microbial-based therapeutic strategies for early identification and treatment goals in AD.