Prediction of tumor regression grade in far-advanced gastric cancer after preoperative immuno-chemotherapy using dual-energy CT-derived extracellular volume fraction.

OBJECTIVES: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy. MATERIALS AND METHODS: A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation. RESULTS: Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV's significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798-0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770-0.791) and 0.766 (0.731-0.800) for the training and validation sets, respectively, in predicting pCR. CONCLUSION: DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy. CLINICAL RELEVANCE STATEMENT: This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.

Traceability and policy suggestions for ozone pollution in heavy industrial city in Northeast China.

In the heavy industrial city of Northeast China, there has been a significant decrease in particulate matter pollution while experiencing a sharp increase in ozone (O3) pollution. However, the main influencing factors and source contributions to O3 remain unclear. Taking the case of Siping as an example, this study analyzed the spatiotemporal characteristics, assessed local source contributions to O3, and revealed regional transmission effects using numeric simulation and statistical methods. Temporally, higher O3 concentrations were observed in summer and the afternoon, with hourly peaks up to 254 µg/m3. Spatially, O3 pollution was mainly contributed by background concentrations (34.52%), external transport (34.50%), and local emissions (30.98%) during the case study period (June 11-18, 2021). Among the local emission sources, biological emissions, the industrial sector, and the traffic sector accounted for 35.30%, 32.09%, and 23.58% of the O3 concentration, respectively. For regional atmospheric transmission, high O3 pollution was accompanied by wind from the southwest directions, and the trajectory of air mass transport suggests that eastern Mongolia, the Korean Peninsula, and its neighboring regions contribute to O3 pollution. Furthermore, sensitivity analysis showed that O3 pollution in Siping is a co-controlled region by anthropogenic volatile organic compounds (AVOCs) and NOX, which implies control in an optimal ratio of VOCs and NOX emissions. Thus, our results highlight the importance of joint prevention and control of O3 pollution in the region, optimization of biogenic landscape ecology, and control of VOCs and NOx in both the industrial and transport sectors.

A case of congenital bronchial atresia with tracheobronchial stenosis caused by emphysema: Successful management with thoracoscopic surgery.

Introduction: Congenital bronchial atresia (CBA), as a rare developmental abnormality of the lung, is usually asymptomatic and is accidently discovered in most cases. Currently, no standardized guidelines for the treatment or management of CBA have been established. Case presentation: A 22-year-old male soldier was referred to Shanghai Changhai Hospital, The First Affiliated Hospital of Naval Medical University due to chest tightness and shortness of breath after repeated strenuous activities. Contrast-enhanced computed tomography (CT) revealed an 18mm × 11mm solitary, well-circumscribed, and solid nodule with no enhancement in the right upper lobe (RUL), and emphysematous changes distributed throughout the RUL. A flexible bronchoscopic examination showed extrinsic compression stenosis in the bronchial opening of the right middle lobe (RML). After three-dimensional (3D) reconstruction CT and a multidisciplinary consultation, a diagnosis of CBA in the anterior segment (B3) of RUL was established. Subsequently, thoracoscopic right upper lobectomy was performed and resulted in an improved respiratory capacity 6 months after surgery. To date, the patient has good quality of life without any complication. Conclusion: This study underscores the role of bronchoscopy, 3D reconstruction CT, and a multidisciplinary consultation in the diagnosis of CBA, and highlights that a thoracoscopic intervention should be considered in such case.

Microwave biosensor for the detection of growth inhibition of human liver cancer cells at different concentrations of chemotherapeutic drug.

Cytotoxicity assays are crucial for assessing the efficacy of drugs in killing cancer cells and determining their potential therapeutic value. Measurement of the effect of drug concentration, which is an influence factor on cytotoxicity, is of great importance. This paper proposes a cytotoxicity assay using microwave sensors in an end-point approach based on the detection of the number of live cells for the first time. In contrast to optical methods like fluorescent labeling, this research uses a resonator-type microwave biosensor to evaluate the effects of drug concentrations on cytotoxicity by monitoring electrical parameter changes due to varying cell densities. Initially, the feasibility of treating cells with ultrapure water for cell counting by a microwave biosensor is confirmed. Subsequently, inhibition curves generated by both the CCK-8 method and the new microwave biosensor for various drug concentrations were compared and found to be congruent. This agreement supports the potential of microwave-based methods to quantify cell growth inhibition by drug concentrations.

Exosomal NAT10 from esophageal squamous cell carcinoma cells modulates macrophage lipid metabolism and polarization through ac4C modification of FASN.

N-acetyltransferase 10 (NAT10) is acknowledged as a tumor promoter in various cancers due to its role as a regulator of acetylation modification. Tumor-associated macrophages (TAMs) play a pivotal role in the tumor microenvironment (TME). However, the intercellular communication between esophageal squamous cell carcinoma (ESCC) cells and TAMs involving NAT10 remains poorly understood. This study aimed to elucidate the regulatory mechanism of NAT10 in modulating macrophage lipid metabolism and polarization. Experimental evidence was derived from in vitro and in vivo analyses. We explored the association between upregulated NAT10 in ESCC tissues, macrophage polarization, and the therapeutic efficacy of PD-1. Furthermore, we investigated the impact of methyltransferase 3 (METTL3)-induced m6A modification on the increased expression of NAT10 in ESCC cells. Additionally, we examined the role of exosomal NAT10 in stabilizing the expression of fatty acid synthase (FASN) and promoting macrophage M2 polarization through mediating the ac4C modification of FASN. Results indicated that NAT10, packaged by exosomes derived from ESCC cells, promotes macrophage M2 polarization by facilitating lipid metabolism. In vivo animal studies demonstrated that targeting NAT10 could enhance the therapeutic effect of PD-1 on ESCC by mediating macrophage reprogramming. Our findings offer novel insights into improving ESCC treatment through NAT10 targeting.

DiffFSRE: Diffusion-Enhanced Prototypical Network for Few-Shot Relation Extraction.

Supervised learning methods excel in traditional relation extraction tasks. However, the quality and scale of the training data heavily influence their performance. Few-shot relation extraction is gradually becoming a research hotspot whose objective is to learn and extract semantic relationships between entities with only a limited number of annotated samples. In recent years, numerous studies have employed prototypical networks for few-shot relation extraction. However, these methods often suffer from overfitting of the relation classes, making it challenging to generalize effectively to new relationships. Therefore, this paper seeks to utilize a diffusion model for data augmentation to address the overfitting issue of prototypical networks. We propose a diffusion model-enhanced prototypical network framework. Specifically, we design and train a controllable conditional relation generation diffusion model on the relation extraction dataset, which can generate the corresponding instance representation according to the relation description. Building upon the trained diffusion model, we further present a pseudo-sample-enhanced prototypical network, which is able to provide more accurate representations for prototype classes, thereby alleviating overfitting and better generalizing to unseen relation classes. Additionally, we introduce a pseudo-sample-aware attention mechanism to enhance the model's adaptability to pseudo-sample data through a cross-entropy loss, further improving the model's performance. A series of experiments are conducted to prove our method's effectiveness. The results indicate that our proposed approach significantly outperforms existing methods, particularly in low-resource one-shot environments. Further ablation analyses underscore the necessity of each module in the model. As far as we know, this is the first research to employ a diffusion model for enhancing the prototypical network through data augmentation in few-shot relation extraction.

Real-Time Detection of Yeast Growth on Solid Medium through Passive Microresonator Biosensor.

This study presents a biosensor fabricated based on integrated passive device (IPD) technology to measure microbial growth on solid media in real-time. Yeast (Pichia pastoris, strain GS115) is used as a model organism to demonstrate biosensor performance. The biosensor comprises an interdigital capacitor in the center with a helical inductive structure surrounding it. Additionally, 12 air bridges are added to the capacitor to increase the strength of the electric field radiated by the biosensor at the same height. Feasibility is verified by using a capacitive biosensor, and the change in capacitance values during the capacitance detection process with the growth of yeast indicates that the growth of yeast can induce changes in electrical parameters. The proposed IPD-based biosensor is used to measure yeast drop-added on a 3 mm medium for 100 h at an operating frequency of 1.84 GHz. The resonant amplitude of the biosensor varies continuously from 24 to 72 h due to the change in colony height during vertical growth of the yeast, with a maximum change of 0.21 dB. The overall measurement results also fit well with the Gompertz curve. The change in resonant amplitude between 24 and 72 h is then analyzed and reveals a linear relationship with time with a coefficient of determination of 0.9844, indicating that the biosensor is suitable for monitoring yeast growth. Thus, the proposed biosensor is proved to have potential in the field of microbial proliferation detection.

Highly Sensitive and Linear Resonator-Based Biosensor for White Blood Cell Counting: Feasible Measurement Method and Intrinsic Mechanism Exploration.

Since different quantities of white blood cells (WBCs) in solution possess an adaptive osmotic pressure of cells, the WBCs themselves and in solution have similar concentrations, resulting in them having similar dielectric properties. Therefore, a microwave sensor could have difficulty in sensing the quantity variation when WBCs are in solution. This paper presents a highly sensitive, linear permittivity-inspired microwave biosensor for WBCs, counting through the evaporation method. Such a measurement method is proposed to record measurements after the cell solution is dripped onto the chip and is completely evaporated naturally. The proposed biosensor consists of an air-bridged asymmetric differential inductor and a centrally located circular fork-finger capacitor fabricated on a GaAs substrate using integrated passive fabrication technology. It is optimized to feature a larger sensitive area and improved Q-factor, which increases the effective area of interaction between cells and the electromagnetic field and facilitates the detection of their changes in number. The sensing relies on the dielectric properties of the cells and the change in the dielectric constant for different concentrations, and the change in resonance properties, which mainly represents the frequency shift, corresponds to the macroscopic change in the concentration of the cells. The microwave biosensors are used to measure biological samples with concentrations ranging from 0.25 × 106 to 8 × 106 cells per mL in a temperature (26.00 ± 0.40 °C) and humidity (54.40 ± 3.90 RH%) environment. The measurement results show a high sensitivity of 25.06 Hz/cells·mL-1 with a highly linear response of r2 = 0.99748. In addition, a mathematical modeling of individual cells in suspension is performed to estimate the dielectric constant of individual cells and further explain the working mechanism of the proposed microwave biosensor.

Tracing the impacts of ecological water replenishment on the sources and transformation of groundwater nitrate through isotope and microbial analysis.

Ecological water replenishment (EWR) changes the recharge conditions, flow fields, and physicochemical properties of regional groundwater. However, the resulting impacts on mechanisms regulating the sources and transformation of groundwater nitrate remain unclear. This study investigated how EWR influences the sources and transformation processes of groundwater nitrate using an integrated approach of Water chemistry analysis and stable isotopes (δ15N-NO3- and δ18O-NO3-) along with microbial techniques. The results showed that groundwater NO3-N decreased from 12.98 ± 7.39 mg/L to 7.04 ± 8.52 mg/L after EWR. Water chemistry and isotopic characterization suggested that groundwater nitrate mainly originated from sewage and manure. The Bayesian isotope mixing model (MixSIAR) indicated that EWR increased the average contribution of sewage and manure sources to groundwater nitrate from 46 % to 61 %, whereas that of sources of chemical fertilizer decreased from 43 % to 21 %. Microbial community analysis revealed that EWR resulted in a substantial decrease in the relative abundance of Pseudomonas spp denitrificans, from 13.7 % to 0.6 %. Both water chemistry and microbial analysis indicated that EWR weakened denitrification and enhanced nitrification in groundwater. EWR increases the contribution of nitrate to groundwater by promoting the release of sewage and feces in the unsaturated zone. However, the dilution effect caused by EWR was stronger than the contribution of sewage and fecal sources to groundwater nitrate. As a result, EWR helped to reduce groundwater nitrate concentrations. This study showed the effectiveness of integrated isotope and microbial techniques for delineating the sources and transformations of groundwater nitrate influenced by EWR.

Resting State Brain Networks under Inverse Agonist versus Complete Knockout of the Cannabinoid Receptor 1.

The cannabinoid receptor 1 (CB1) is famous as the target of Δ9-tetrahydrocannabinol (THC), which is the active ingredient of marijuana. Suppression of CB1 is frequently suggested as a drug target or gene therapy for many conditions (e.g., obesity, Parkinson's disease). However, brain networks affected by CB1 remain elusive, and unanticipated psychological effects in a clinical trial had dire consequences. To better understand the whole brain effects of CB1 suppression we performed in vivo imaging on mice under complete knockout of the gene for CB1 (cnr1-/-) and also under the CB1 inverse agonist rimonabant. We examined white matter structural changes and brain function (network activity and directional uniformity) in cnr1-/- mice. In cnr1-/- mice, white matter (in both sexes) and functional directional uniformity (in male mice) were altered across the brain but network activity was largely unaltered. Conversely, under rimonabant, functional directional uniformity was not altered but network activity was altered in cortical regions, primarily in networks known to be altered by THC (e.g., neocortex, hippocampal formation). However, rimonabant did not alter many brain regions found in both our cnr1-/- results and previous behavioral studies of cnr1-/- mice (e.g., thalamus, infralimbic area). This suggests that chronic loss of cnr1 is substantially different from short-term suppression, subtly rewiring the brain but largely maintaining the network activity. Our results help explain why pathological mutations in CB1 (e.g., chronic pain) do not always provide insight into the side effects of CB1 suppression (e.g., clinical depression), and thus urge more preclinical studies for any drugs that suppress CB1.

Pseudorabies virus manipulates mitochondrial tryptophanyl-tRNA synthetase 2 for viral replication.

The pseudorabies virus (PRV) is identified as a double-helical DNA virus responsible for causing Aujeszky's disease, which results in considerable economic impacts globally. The enzyme tryptophanyl-tRNA synthetase 2 (WARS2), a mitochondrial protein involved in protein synthesis, is recognized for its broad expression and vital role in the translation process. The findings of our study showed an increase in both mRNA and protein levels of WARS2 following PRV infection in both cell cultures and animal models. Suppressing WARS2 expression via RNA interference in PK-15 â€‹cells led to a reduction in PRV infection rates, whereas enhancing WARS2 expression resulted in increased infection rates. Furthermore, the activation of WARS2 in response to PRV was found to be reliant on the cGAS/STING/TBK1/IRF3 signaling pathway and the interferon-alpha receptor-1, highlighting its regulation via the type I interferon signaling pathway. Further analysis revealed that reducing WARS2 levels hindered PRV's ability to promote protein and lipid synthesis. Our research provides novel evidence that WARS2 facilitates PRV infection through its management of protein and lipid levels, presenting new avenues for developing preventative and therapeutic measures against PRV infections.

A new strategy for groundwater level prediction using a hybrid deep learning model under Ecological Water Replenishment.

Accurate prediction of the groundwater level (GWL) is crucial for sustainable groundwater resource management. Ecological water replenishment (EWR) involves artificially diverting water to replenish the ecological flow and water resources of both surface water and groundwater within the basin. However, fluctuations in GWLs during the EWR process exhibit high nonlinearity and complexity in their time series, making it challenging for single data-driven models to predict the trend of groundwater level changes under the backdrop of EWR. This study introduced a new GWL prediction strategy based on a hybrid deep learning model, STL-IWOA-GRU. It integrated the LOESS-based seasonal trend decomposition algorithm (STL), improved whale optimization algorithm (IWOA), and Gated recurrent unit (GRU). The aim was to accurately predict GWLs in the context of EWR. This study gathered GWL, precipitation, and surface runoff data from 21 monitoring wells in the Yongding River Basin (Beijing Section) over a period of 731 days. The research results demonstrate that the improvement strategy implemented for the IWOA enhances the convergence speed and global search capabilities of the algorithm. In the case analysis, evaluation metrics including the root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and Nash-Sutcliffe efficiency (NSE) were employed. STL-IWOA-GRU exhibited commendable performance, with MAE achieving the best result, averaging at 0.266. When compared to other models such as Variance Mode Decomposition-Gated Recurrent Unit (VMD-GRU), Ant Lion Optimizer-Support Vector Machine (ALO-SVM), STL-Particle Swarm Optimization-GRU (STL-PSO-GRU), and STL-Sine Cosine Algorithm-GRU (STL-SCA-GRU), MAE was reduced by 18%, 26%, 11%, and 29%, respectively. This indicates that the model proposed in this study exhibited high prediction accuracy and robust versatility, making it a potent strategic choice for forecasting GWL changes in the context of EWR.

Enhanced Heterogeneous Graph Attention Network with a Novel Multilabel Focal Loss for Document-Level Relation Extraction.

Recent years have seen a rise in interest in document-level relation extraction, which is defined as extracting all relations between entities in multiple sentences of a document. Typically, there are multiple mentions corresponding to a single entity in this context. Previous research predominantly employed a holistic representation for each entity to predict relations, but this approach often overlooks valuable information contained in fine-grained entity mentions. We contend that relation prediction and inference should be grounded in specific entity mentions rather than abstract entity concepts. To address this, our paper proposes a two-stage mention-level framework based on an enhanced heterogeneous graph attention network for document-level relation extraction. Our framework employs two different strategies to model intra-sentential and inter-sentential relations between fine-grained entity mentions, yielding local mention representations for intra-sentential relation prediction and global mention representations for inter-sentential relation prediction. For inter-sentential relation prediction and inference, we propose an enhanced heterogeneous graph attention network to better model the long-distance semantic relationships and design an entity-coreference path-based inference strategy to conduct relation inference. Moreover, we introduce a novel cross-entropy-based multilabel focal loss function to address the class imbalance problem and multilabel prediction simultaneously. Comprehensive experiments have been conducted to verify the effectiveness of our framework. Experimental results show that our approach significantly outperforms the existing methods.

CRISPR genome-wide screening identifies PAK1 as a critical driver of ARSI cross-resistance in prostate cancer progression.

Next-generation androgen receptor signaling inhibitors (ARSIs), such as enzalutamide (Enza) and darolutamide (Daro), are initially effective for the treatment of advanced prostate cancer (PCa) and castration-resistant prostate cancer (CRPC). However, patients often relapse and develop cross-resistance, which consequently makes drug resistance an inevitable cause of CRPC-related mortality. By conducting a comprehensive analysis of GEO datasets, CRISPR genome-wide screening results, ATAC-seq data, and RNA-seq data, we systemically identified PAK1 as a significant contributor to ARSI cross-resistance due to the activation of the PAK1/RELA/hnRNPA1/AR-V7 axis. Inhibition of PAK1 followed by suppression of NF-κB pathways and AR-V7 expression effectively overcomes ARSI cross-resistance. Our findings indicate that PAK1 represents a promising therapeutic target gene for the treatment of ARSI cross-resistant PCa patients in the clinic. STATEMENT OF SIGNIFICANCE: PAK1 drives ARSI cross-resistance in prostate cancer progression.

CREB3L4 promotes hepatocellular carcinoma progression and decreases sorafenib chemosensitivity by promoting RHEB-mTORC1 signaling pathway.

This study was designed to explore the roles of CREB3L4 in the pathogenesis and drug resistance of hepatocellular carcinoma (HCC). The proliferation of HCC lines was determined in the presence of CREB3L4 over-expression and silencing. Chromatin immunoprecipitation (ChIP) assay and dual-luciferase reporter assay were performed to screen the potential target of CREB3L4 on mTORC1. Xenografted tumor model was established to define the regulatory effects of CREB3L4 in the tumorigenesis. Then we evaluated the roles of CREB3L4 in chemosensitivity to sorafenib treatment. CREB3L4 significantly induced the HCC cell proliferation by modulating the activation of mTROC1-S6K1 signaling pathway via binding with RHEB promoter. Moreover, CREB3L4 dramatically inhibited the chemosensitivity to sorafenib treatment via up-regulating RHEB-mTORC1 signaling. CREB3L4 promoted HCC progression and decreased its chemosensitivity to sorafenib through up-regulating RHEB-mTORC1 signaling pathway, indicating a potential treatment strategy for HCC through targeting CREB3L4.

Hexaxial external fixator versus intramedullary nail in treating segmental tibial fractures: a retrospective study.

BACKGROUND: It's difficult to treat segmental tibial fractures (STFs), which are intricate injuries associated with significant soft tissue damage. The aim of this study was to compare the clinical effect of hexaxial external fixator (HEF) and intramedullary nail (IMN) in treatment of STFs. METHODS: A total of 42 patients with STFs were finally recruited between January 2018 and June 2022. There were 25 males and 17 females with age range of 20 to 60 years. All fractures were classified as type 42C2 using the Arbeitsgemeinschaftfür Osteosythese/Orthopaedic Trauma Association (AO/OTA) classification. 22 patients were treated with HEF and 20 patients were treated with IMN. The condition of vascular and neural injuries, time of full weight bearing, bone union time and infection rate were documented and analyzed between the two groups. The mechanical medial proximal tibial angle (mMPTA), mechanical posterior proximal tibial angle (mPPTA), mechanical lateral distal tibial angle (mLDTA), mechanical anterior distal tibial angle (mADTA), hospital for special surgery (HSS) knee joint score, American Orthopaedic Foot and Ankle Society (AOFAS) ankle joint score, range of motion (ROM) of flexion of keen joint and ROM of plantar flexion and dorsal flexion of ankle joint were compared between the two groups at the last clinical visit. RESULTS: There were no vascular and neural injuries or other severe complications in both groups. All 22 patients in HEF group underwent closed reduction but 3 patients in IMN group were treated by open reduction. The time of full weight bearing was (11.3 ± 3.2) days in HEF group and (67.8 ± 5.8) days in IMN group(P < 0.05), with bone union time for (6.9 ± 0.8) months and (7.7 ± 1.4) months, respectively(P < 0.05). There was no deep infection in both groups. In the HEF group and IMN group, mMPTA was (86.9 ± 1.5)° and (89.7 ± 1.8)°(P < 0.05), mPPTA was (80.8 ± 1.9)° and (78.6 ± 2.0)°(P < 0.05), mLDTA was (88.5 ± 1.7)° and (90.3 ± 1.7)°(P < 0.05), while mADTA was (80.8 ± 1.5)° and (78.4 ± 1.3)°(P < 0.05). No significant differences were found between the two groups at the last clinical visit concerning HSS knee joint score and AOFAS ankle joint score, ROM of flexion of keen joint and ROM of plantar flexion of ankle joint (P > 0.05). The ROM of dorsal flexion of ankle joint in IMN group was (30.4 ± 3.5)°, better than (21.6 ± 2.8)° in HEF group (P < 0.05). CONCLUSION: In terms of final clinical outcomes, the use of either HEF or IMN for STFs can achieve good therapeutic effects. While HEF is superior to IMN in terms of completely closed reduction, early full weight bearing, early bone union and alignment. Nevertheless, HEF has a greater impact on the ROM of dorsal flexion of the ankle joint, and much more care and adjustment are needed for the patients than IMN.

Genistein prevents the production of hypospadias induced by Di-(2-ethylhexyl) phthalate through androgen signaling and antioxidant response in rats.

Environmental estrogen exposure has increased dramatically over the past 50 years. In particular, prenatal exposure to estrogen causes many congenital diseases, among which reproductive system development disorders are extremely serious. In this study, the molecular mechanism of hypospadias and the therapeutic effect of genistein (GEN) were investigated through in vivo models prepared by Di-(2-ethylhexyl) phthalate (DEHP) exposure between 12 and 19 days of gestation. With increased DEHP concentrations, the incidence of hypospadias increased gradually. DEHP inhibited the key enzymes involved in steroid synthesis, resulting in decreasing testosterone synthesis. At the same time, DEHP increased reactive oxygen species (ROS) and produced inflammatory factors via NADPH oxidase-1 (NOX1) and NADPH oxidase-4 (NOX4) pathways. It also inhibited Steroid 5 α Reductase 2 (Srd5α2) and decreased dihydrotestosterone (DHT) synthesis. Additionally, DEHP inhibited the androgen receptor (AR), resulting in reduced DHT binding to the AR that ultimately retarded the development of the external reproductive system. GEN, a phytoestrogen, competes with DEHP for binding to estrogen receptor ß (ERß). This competition, along with GEN's antiestrogen and antioxidant properties, could potentially reverse impairments. The findings of this study provide valuable insights into the role of phytoestrogens in alleviating environmental estrogen-induced congenital diseases.

The Role of Iron Metabolism in Sepsis-associated Encephalopathy: a Potential Target.

Sepsis-associated encephalopathy (SAE) is an acute cerebral dysfunction secondary to infection, and the severity can range from mild delirium to deep coma. Disorders of iron metabolism have been proven to play an important role in a variety of neurodegenerative diseases by inducing cell damage through iron accumulation in glial cells and neurons. Recent studies have found that iron accumulation is also a potential mechanism of SAE. Systemic inflammation can induce changes in the expression of transporters and receptors on cells, especially high expression of divalent metal transporter1 (DMT1) and low expression of ferroportin (Fpn) 1, which leads to iron accumulation in cells. Excessive free Fe2+ can participate in the Fenton reaction to produce reactive oxygen species (ROS) to directly damage cells or induce ferroptosis. As a result, it may be of great help to improve SAE by treatment of targeting disorders of iron metabolism. Therefore, it is important to review the current research progress on the mechanism of SAE based on iron metabolism disorders. In addition, we also briefly describe the current status of SAE and iron metabolism disorders and emphasize the therapeutic prospect of targeting iron accumulation as a treatment for SAE, especially iron chelator. Moreover, drug delivery and side effects can be improved with the development of nanotechnology. This work suggests that treating SAE based on disorders of iron metabolism will be a thriving field.

Universal Lower Bound on Topological Entanglement Entropy.

Entanglement entropies of two-dimensional gapped ground states are expected to satisfy an area law, with a constant correction term known as the topological entanglement entropy (TEE). In many models, the TEE takes a universal value that characterizes the underlying topological phase. However, the TEE is not truly universal: it can differ even for two states related by constant-depth circuits, which are necessarily in the same phase. The difference between the TEE and the value predicted by the anyon theory is often called the "spurious" topological entanglement entropy. We show that this spurious contribution is always non-negative, thus the value predicted by the anyon theory provides a universal lower bound. This observation also leads to a definition of TEE that is invariant under constant-depth quantum circuits.