Bevacizumab reduces cerebral radiation necrosis due to stereotactic radiotherapy in non-small cell lung cancer patients with brain metastases: an inverse probability of treatment weighting analysis.

Background: Cerebral radiation necrosis (RN), a severe complication of stereotactic radiotherapy (SRT), has been shown to significantly decrease patient survival time and quality of life. The purpose of this study was to analyze whether bevacizumab can prevent or reduce the occurrence of SRT-induced cerebral RN in non-small cell lung cancer (NSCLC) patients with brain metastases. Materials and methods: We retrospectively reviewed the clinical records of NSCLC patients with brain metastases from March 2013 to June 2023 who were treated with SRT. Patients were divided into two groups: those in the bevacizumab group received SRT with four cycles of bevacizumab, and patients in the control group received SRT only. Inverse probability of treatment weighting (IPTW) was performed based on a multinomial propensity score model to balance the baseline characteristics. The chi-square test was used. A Cox model was used to evaluate overall survival (OS). Results: A total of 80 patients were enrolled, namely, 28 patients in the bevacizumab group and 52 patients in the control group. The possibility of developing cerebral RN and/or symptomatic edema (RN/SE) was significantly decreased in patients treated with bevacizumab compared to those who did not receive bevacizumab before IPTW (p=0.036) and after IPTW (p=0.015) according to chi-square analysis. The IPTW-adjusted median OS was 47.7 months (95% CI 27.4-80.8) for patients in the bevacizumab group and 44.1 months (95% CI 36.7-68.0) (p=0.364) for patients in the control group. Conclusion: The application of bevacizumab concurrent with SRT may prevent or reduce the occurrence of cerebral RN in NSCLC patients with brain metastases.

Synthesis of astigmatic non-uniformly correlated beams.

We present a general strategy for synthesizing astigmatic random structured light beams by jointly manipulating the astigmatic phase and optical coherence. With it, we facilitate the creation of a distinct category of beams termed astigmatic non-uniformly correlated (ANUC) beams. Our study emphasizes the significant influence of the astigmatic phase on the optical spatial coherence distribution, resulting in novel propagation features. Furthermore, we elucidate their underlying physical nature. Experimentally, we successfully generate such beams, validating theoretical projections. Our findings hold promise for diverse applications requiring adaptable spectral density control.

Role of critical stress in quantifying the magnitude of fluid-injection triggered earthquakes.

Here we define and report the relationship between the maximum seismic magnitude (M) and injection volume (ΔV) through fluid-injection fault-reactivation experiments and analysis. This relationship incorporates the in situ shear modulus (G) and fault pre-stress as a fraction of the strength drop (c), expressed as M = c/(1-c) GΔV. Injection response defines a sigmoidal relation in M - Δ V space with unit gradient limbs linked by an intermediate up-step. Both laboratory observations and analysis for a rigid fault with slip limited to the zone of pressurization show trajectories of cumulative M - Δ V that evolve at a gradient of unity, are offset in order of increasing pre-stress and are capable of step changes in moment with shear reactivation at elevated critical-stresses - key features apparent in field observations. The model and confirmatory laboratory observations explain the occurrence of some triggered earthquakes at EGS sites significantly larger than expected relative to injection volumes and based on previous models.

Observation of the hexatic phase in a two-dimensional complex plasma using machine learning.

Complex plasmas consist of ionized gas and charged solid microparticles, representing the plasma state of soft matter. We apply machine learning methods to investigate a melting transition in a two-dimensional complex plasma. A convolutional neural network is constructed and trained with the numerical simulation. The hexatic phase is successfully identified and the evolution of topological defects is studied during melting transition in both simulations and experiments.

High-dose hyperfractionated simultaneous integrated boost radiotherapy versus standard-dose radiotherapy for limited-stage small-cell lung cancer in China: a multicentre, open-label, randomised, phase 3 trial.

BACKGROUND: For the past 20 years, twice-daily thoracic radiotherapy with concurrent chemotherapy has been the treatment of choice for limited-stage small-cell lung cancer (LS-SCLC), which has a poor prognosis. We aimed to assess the efficacy and safety of high-dose, accelerated, hyperfractionated, twice-daily thoracic radiotherapy (54 Gy in 30 fractions) versus standard-dose radiotherapy (45 Gy in 30 fractions) as a first-line treatment for LS-SCLC. METHODS: This open-label, randomised, phase 3 trial was performed at 16 public hospitals in China. The key inclusion criteria were patients aged 18-70 years, with histologically or cytologically confirmed LS-SCLC, who had an Eastern Cooperative Oncology Group (ECOG) performance status of 0-1, and who were previously untreated or had received one course of cisplatin or carboplatin and etoposide. Eligible patients were randomly assigned (1:1) to receive volumetric-modulated arc radiotherapy (VMAT) of 45 Gy in 30 fractions to the gross tumour volume or VMAT with a simultaneous integrated boost of 54 Gy in 30 fractions to the gross tumour volume starting 0-42 days after the first chemotherapy course. Both groups received 10 fractions of twice-daily thoracic radiotherapy per week. The planning target volume was 45 Gy in 30 fractions in both groups. Patients with responsive disease received prophylactic cranial radiotherapy (25 Gy in 10 fractions). Randomisation was performed using a centralised interactive web response system, stratified by ECOG performance status, disease stage, previous chemotherapy course, and chemotherapy choice. The primary outcome was overall survival in the intention-to-treat population. Safety was analysed in the as-treated population. This study was registered at ClinicalTrials.gov, NCT03214003. FINDINGS: From June 30, 2017, to April 6, 2021, 224 patients (102 [46%] females and 122 [54%] males; median age 64 years [IQR 58-68]) were enrolled and randomly assigned to the 54 Gy group (n=108) or 45 Gy (n=116) group. The median follow-up was 46 months (IQR 33-56). The median overall survival was significantly longer in the 54 Gy group (60·7 months [95% CI 49·2-62·0]) than in the 45 Gy group (39·5 months [27·5-51·4]; hazard ratio 0·55 [95% CI 0·37-0·72]; p=0·003). Treatment was tolerable, and the chemotherapy-related and radiotherapy-related toxicities were similar between the groups. The grade 3-4 radiotherapy toxicities were oesophagitis (14 [13%] of 108 patients in the 54 Gy group vs 14 [12%] of 116 patients in the 45 Gy group; p=0·84) and pneumonitis (five [5%] of 108 patients vs seven [6%] of 116 patients; p=0·663). Only one treatment-related death occurred in the 54 Gy group (myocardial infarction). The study was prematurely terminated by an independent data safety monitoring board on April 30, 2021, based on evidence of sufficient clinical benefit. INTERPRETATION: Compared with standard-dose thoracic radiotherapy (45 Gy), high-dose radiotherapy (54 Gy) improved overall survival without increasing toxicity in a cohort of patients aged 18-70 years with LS-SCLC. Our results support the use of twice-daily accelerated thoracic radiotherapy (54 Gy) with concurrent chemotherapy as an alternative first-line LS-SCLC treatment option. FUNDING: Chinese Society of Clinical Oncology-Linghang Cancer Research, the Wu Jieping Medical Foundation, and Clinical Research Fund For Distinguished Young Scholars of Peking University Cancer Hospital and Beijing Municipal Administration of Hospitals Incubating Program.

A nomogram based on dual-layer detector spectral computed tomography quantitative parameters and morphological quantitative indicator for distinguishing metastatic and nonmetastatic regional lymph nodes in pancreatic ductal adenocarcinoma.

Background: There is no unified scope for regional lymph node (LN) dissection in patients with pancreatic ductal adenocarcinoma (PDAC). Incomplete regional LN dissection can lead to postoperative recurrence, while blind expansion of the scope of regional LN dissection significantly increases the perioperative risk without significantly prolonging overall survival. We aimed to establish a noninvasive visualization tool based on dual-layer detector spectral computed tomography (DLCT) to predict the probability of regional LN metastasis in patients with PDAC. Methods: A total of 163 regional LNs were reviewed and divided into a metastatic cohort (n=58 LNs) and nonmetastatic cohort (n=105 LNs). The DLCT quantitative parameters and the nodal ratio of the longest axis to the shortest axis (L/S) of the regional LNs were compared between the two cohorts. The DLCT quantitative parameters included the iodine concentration in the arterial phase (APIC), normalized iodine concentration in the arterial phase (APNIC), effective atomic number in the arterial phase (APZeff), normalized effective atomic number in the arterial phase (APNZeff), slope of the spectral attenuation curves in the arterial phase (APλHU), iodine concentration in the portal venous phase (PVPIC), normalized iodine concentration in the portal venous phase (PVPNIC), effective atomic number in the portal venous phase (PVPZeff), normalized effective atomic number in the portal venous phase (PVPNZeff), and slope of the spectral attenuation curves in the portal venous phase (PVPλHU). Logistic regression analysis based on area under the curve (AUC) was used to analyze the diagnostic performance of significant DLCT quantitative parameters, L/S, and the models combining significant DLCT quantitative parameters and L/S. A nomogram based on the models with highest diagnostic performance was developed as a predictor. The goodness of fit and clinical applicability of the nomogram were assessed through calibration curve and decision curve analysis (DCA). Results: The combined model of APNIC + L/S (APNIC + L/S) had the highest diagnostic performance among all models, yielding an AUC, sensitivity, and specificity of 0.878 [95% confidence interval (CI): 0.825-0.931], 0.707, and 0.886, respectively. The calibration curve indicated that the APNIC-L/S nomogram had good agreement between the predicted probability and the actual probability. Meanwhile, the decision curve indicated that the APNIC-L/S nomogram could produce a greater net benefit than could the all- or-no-intervention strategy, with threshold probabilities ranging from 0.0 to 0.75. Conclusions: As a valid and visual noninvasive prediction tool, the APNIC-L/S nomogram demonstrated favorable predictive efficacy for identifying metastatic LNs in patients with PDAC.

Comprehensive evaluation of the efficacy and safety of a new multi-component anti-aging topical eye cream.

BACKGROUND: The delicate periorbital region is susceptible to skin dehydration, wrinkles, and loss of elasticity. Thus, targeted and effective anti-aging interventions are necessary for the periorbital area. AIM: To evaluate the efficacy and safety of a new anti-aging eye cream formulated with the active complex (Yeast/rice fermentation filtrate, N-acetylneuraminic acid, palmityl tripeptide-1, and palmitoyl tetrapeptide-7). METHODS: The cell viability and expressions of key extracellular matrix (ECM) components of the active complex were evaluated using a human skin fibroblast model. In the 12-week clinical trial, skin hydration, elasticity, facial photographs, and collagen density following eye cream application were assessed using Corneometer, Cutometer, VISIA, and ultrasound device, respectively. Dermatologists and participants evaluated clinical efficacy and safety at baseline, and after 4, 8, and 12 weeks. RESULTS: PCR and immunofluorescent analyses revealed that the active complex significantly stimulated fibroblast proliferation (p < 0.05) and markedly promote the synthesis of collagen and elastin. Clinical findings exhibited a substantial enhancement in skin hydration (28.12%), elasticity (18.81%), and collagen production (54.99%) following 12 weeks of eye cream application. Dermatological evaluations and participants' assessments reported a significant improvement in skin moisture, roughness, elasticity, as well as fine lines and wrinkles by week 8. CONCLUSION: The new anti-aging eye cream, enriched with the active complex, demonstrates comprehensive rejuvenating effects, effectively addressing aging concerns in the periorbital area, coupled with a high safety profile.

Enhancing Pseudomonas cell growth for the production of medium-chain-length polyhydroxyalkanoates from Antarctic krill shell waste.

Antarctic krill shell waste (AKSW), a byproduct of Antarctic krill processing, has substantial quantity but low utilization. Utilizing microbial-based cell factories, with Pseudomonas putida as a promising candidate, offers an ecofriendly and sustainable approach to producing valuable bioproducts from renewable sources. However, the high fluoride content in AKSW impedes the cell growth of P. putida. This study aims to investigate the transcriptional response of P. putida to fluoride stress from AKSW and subsequently conduct genetic modification of the strain based on insights gained from transcriptomic analysis. Notably, the engineered strain KT+16840+03100 exhibited a remarkable 33.7-fold increase in cell growth, capable of fermenting AKSW for medium-chain-length-polyhydroxyalkanoates (mcl-PHA) biosynthesis, achieving a 40.3-fold increase in mcl-PHA yield compared to the control strain. This research advances our understanding of how P. putida responds to fluoride stress from AKSW and provides engineered strains that serve as excellent platforms for producing mcl-PHA through AKSW.

LPS-related muscle loss is associated with the alteration of Bacteroidetes abundance, systemic inflammation, and mitochondrial morphology in a weaned piglet model.

We previously demonstrated that lipopolysaccharide (LPS) injection-induced immune stress could impair muscle growth in weaned piglets, but the precise mechanisms behind this remain elusive. Here, we found that chronic immune stress induced by LPS resulted in a significant reduction of 36.86% in the total muscle mass of piglets at 5 d post-treatment compared with the control group. At 1 d, prior to muscle mass loss, multiple alterations were noted in response to LPS treatment. These included a reduction in the abundance of Bacteroidetes, an increase in serum concentrations of pro-inflammatory cytokines, compromised mitochondrial morphology, and an upregulation in the expression of dynamin-related protein 1 (Drp1), a critical protein involved in mitochondrial fission. We highlight a strong negative correlation between Bacteroidetes abundance and the levels of serum pro-inflammatory cytokines, corroborated by in vivo intervention strategies in the musculature of both pig and mouse models. Mechanistically, the effects of Bacteroidetes on inflammation and muscle mass loss may involve the signaling pathway of the tauro-ß-muricholic acid-fibroblast growth factor 15. Furthermore, the induction of overexpression of inflammatory cytokines, achieved without LPS treatment through oral administration of recombinant human IL-6 (rhIL-6), led to increased levels of circulating cytokines, subsequently causing a decrease in muscle mass. Notably, pre-treatment with Mdivi-1, an inhibitor of Drp-1, markedly attenuated the LPS-induced elevation in reactive oxygen species levels and rescued the associated decline in muscle mass. Collectively, these data indicate that LPS-induced muscle mass loss was linked to the reduction of Bacteroidetes abundance, increased inflammation, and the disruption of mitochondrial morphology. These insights offer promising avenues for the identification of potential therapeutic targets aimed at mitigating muscle mass loss.

Detection of malignant lesions in cytologically indeterminate thyroid nodules using a dual-layer spectral detector CT-clinical nomogram.

Purpose: To evaluate the capability of dual-layer detector spectral CT (DLCT) quantitative parameters in conjunction with clinical variables to detect malignant lesions in cytologically indeterminate thyroid nodules (TNs). Materials and methods: Data from 107 patients with cytologically indeterminate TNs who underwent DLCT scans were retrospectively reviewed and randomly divided into training and validation sets (7:3 ratio). DLCT quantitative parameters (iodine concentration (IC), NICP (IC nodule/IC thyroid parenchyma), NICA (IC nodule/IC ipsilateral carotid artery), attenuation on the slope of spectral HU curve and effective atomic number), along with clinical variables, were compared between benign and malignant cohorts through univariate analysis. Multivariable logistic regression analysis was employed to identify independent predictors which were used to construct the clinical model, DLCT model, and combined model. A nomogram was formulated based on optimal performing model, and its performance was assessed using receiver operating characteristic curve, calibration curve, and decision curve analysis. The nomogram was subsequently tested in the validation set. Results: Independent predictors associated with malignant TNs with indeterminate cytology included NICP in the arterial phase, Hashimoto's Thyroiditis (HT), and BRAF V600E (all p < 0.05). The DLCT-clinical nomogram, incorporating the aforementioned variables, exhibited superior performance than the clinical model or DLCT model in both training set (AUC: 0.875 vs 0.792 vs 0.824) and validation set (AUC: 0.874 vs 0.792 vs 0.779). The DLCT-clinical nomogram demonstrated satisfactory calibration and clinical utility in both training set and validation set. Conclusion: The DLCT-clinical nomogram emerges as an effective tool to detect malignant lesions in cytologically indeterminate TNs.

Spatio-temporal differentiation characteristics and the influencing factors of PM2.5 emissions from coal consumption in Central Plains Urban Agglomeration.

Central Plains urban agglomeration (CPUA) had developed rapidly, but its air pollution was also serious. Despite advances in study on China's PM2.5 emissions from coal consumption (CC), the differentiation characteristics and the affecting variables of PM2.5 in CPUA required further investigation. This paper computed the PM2.5 emissions of each city from 2000 to 2020 using CC data from CPUA, evaluated its spatio-temporal fluctuation characteristics using the spatial autocorrelation and analyzed its influencing factors by combining various indicators through the spatial Durbin model (SDM). The results verified that: (1) There was a trend of rapid increase of PM2.5 emissions from CC; (2) The Moran's I of the PM2.5 emissions from CC showed a significant agglomeration effect; (3) PM2.5 emissions from CC had a strong spillover effect. The recommendations were in this following: (1) The urban pollution regulation and the pace of industrial green transformation should be Strengthened; (2) Close linkages between cities should be established and attention should be paid to pollution management; (3) The spillover of PM2.5 emissions from CC should be lessened and development of environmental governance technology should be enhanced.

Enantioselectivity regulation of antibody against chiral herbicide metolachlor based on interaction at chiral center.

Enantioselective antibodies have emerged as great potential biomaterials in the fields of immunoassays and chiral separation. However, cross-reactivity of antibodies to the distomer may severely restrict the application. Comprehending the interaction mechanism between antibodies and enantiomers could be beneficial to produce superior enantioselective antibodies. In this study, a pair of recombinant antibodies (RAbs) against metolachlor enantiomers at chiral carbon (αSS-MET and αSR-MET) were generated and characterized. The αSS-MET-RAb and αSR-MET-RAb showed comparable sensitivity and specificity to the parental monoclonal antibodies by icELISA, with IC50 values of 3.45 and 223.77 ng/mL, respectively. Moreover, the complex structures of RAbs and corresponding eutomer were constructed and analyzed, and site-specific mutagenesis was utilized to verify the reliability of the enantioselective mechanism elucidated. It demonstrated that the strength of the interaction between the chiral center region of eutomer and the antibody was the key factor for the enantioselectivity of antibody. Increasing this interaction could limit the conformational adjustment of the distomer in a specific chiral recognition cavity, thus decreasing the affinity of the antibody to the distomer. This work provided the in-depth analysis of enantioselective mechanism for two RAbs and paved the way to regulate antibody enantioselective performance for immunoassays of chiral compounds.

Evaluating tooth segmentation accuracy and time efficiency in CBCT images using artificial intelligence: A systematic review and Meta-analysis.

OBJECTIVES: This systematic review and meta-analysis aimed to assess the current performance of artificial intelligence (AI)-based methods for tooth segmentation in three-dimensional cone-beam computed tomography (CBCT) images, with a focus on their accuracy and efficiency compared to those of manual segmentation techniques. DATA: The data analyzed in this review consisted of a wide range of research studies utilizing AI algorithms for tooth segmentation in CBCT images. Meta-analysis was performed, focusing on the evaluation of the segmentation results using the dice similarity coefficient (DSC). SOURCES: PubMed, Embase, Scopus, Web of Science, and IEEE Explore were comprehensively searched to identify relevant studies. The initial search yielded 5642 entries, and subsequent screening and selection processes led to the inclusion of 35 studies in the systematic review. Among the various segmentation methods employed, convolutional neural networks, particularly the U-net model, are the most commonly utilized. The pooled effect of the DSC score for tooth segmentation was 0.95 (95 %CI 0.94 to 0.96). Furthermore, seven papers provided insights into the time required for segmentation, which ranged from 1.5 s to 3.4 min when utilizing AI techniques. CONCLUSIONS: AI models demonstrated favorable accuracy in automatically segmenting teeth from CBCT images while reducing the time required for the process. Nevertheless, correction methods for metal artifacts and tooth structure segmentation using different imaging modalities should be addressed in future studies. CLINICAL SIGNIFICANCE: AI algorithms have great potential for precise tooth measurements, orthodontic treatment planning, dental implant placement, and other dental procedures that require accurate tooth delineation. These advances have contributed to improved clinical outcomes and patient care in dental practice.

Research on a Critical Link Discovery Method for Network Security Situational Awareness.

Network security situational awareness (NSSA) aims to capture, understand, and display security elements in large-scale network environments in order to predict security trends in the relevant network environment. With the internet's increasingly large scale, increasingly complex structure, and gradual diversification of components, the traditional single-layer network topology model can no longer meet the needs of network security analysis. Therefore, we conduct research based on a multi-layer network model for network security situational awareness, which is characterized by the three-layer network structure of a physical device network, a business application network, and a user role network. Its network characteristics require new assessment methods, so we propose a multi-layer network link importance assessment metric: the multi-layer-dependent link entropy (MDLE). On the one hand, the MDLE comprehensively evaluates the connectivity importance of links by fitting the link-local betweenness centrality and mapping entropy. On the other hand, it relies on the link-dependent mechanism to better aggregate the link importance contributions in each network layer. The experimental results show that the MDLE has better ordering monotonicity during critical link discovery and a higher destruction efficacy in destruction simulations compared to classical link importance metrics, thus better adapting to the critical link discovery requirements of a multi-layer network topology.

Boosting oxygen reduction durability by embedding Co9S8 nanoparticles into Co single atoms anchored porous carbon frameworks.

Developing an efficient and low-cost oxygen reduction electrocatalyst is essential for the application of aqueous zinc-air batteries (ZABs). Herein, we report a facile adsorption-confined pyrolysis strategy to fabricate the hybrid electrocatalyst (denoted as Co9S8/CoSA-PC) by embedding Co9S8 nanoparticles into Co single atoms (Co-SAs) anchored porous carbon sheets for boosting oxygen reduction reaction (ORR) durability. In this strategy, the Co2+ ions are first absorbed into oxygen-rich porous carbon nanosheets and further form the Co-SAs with the help of thiourea in the following pyrolysis procedure, which is believed to be able to confine the generated Co9S8 nanoparticles into carbon frameworks due to their interface interaction. Benefiting from the synergistic effect of different components, the obtained Co9S8/CoSA-PC electrocatalyst for ORR exhibits outstanding catalytic activity with a half-wave potential of 0.82 V and a distinguished long-term durability with a current retention of 80 % after cycling 80 h under alkaline conditions, which is superior to commercial Pt/C. Moreover, the assembled ZABs with Co9S8/CoSA-PC as cathodic catalyst deliver a high specific capacity of 764 mAh gZn-1 at 10 mA cm-2 and the outstanding peak power density of up to 221.4 mW cm-2. This work provides a novel structure design strategy to prepare transition metal sulfide-based electrocatalysts with superior durability for ORR.

Bending creep behaviour of various polymer films analysed by surface strain measurement.

Understanding the temporal bending deformation of polymer films is key to designing mechanically durable flexible electronic devices. However, such creep behaviour under persistent bending remains unclear due to a lack of precise and accurate bending strain analysis methods. Herein, we quantitatively analysed the bending creep behaviour of various polymeric films using our developed strain measurement method that can precisely measure surface strain from optical diffraction. The surface strain measurement reveals that bending creep deformation differs depending on the polymer structure. The four-element Burgers model was employed to model the temporal strain increase on the bending surface successfully. By fitting the four-element model to the time course of the measured surface strain, we found that each polymer film has a different threshold surface strain for the appearance of bending creep deformation. Such disparity in the bending creep behaviour can be explained by the difference in strain energy density between the polymer films and their elastic model; polymer films with a small strain energy density difference show small bending creep deformation. The results obtained in this study contribute to the elucidation of the bending creep behaviour of polymer films and the development of flexible electronic devices operated under persistent bending.

The impact of market-based environmental regulation on corporate ESG performance: A quasi-natural experiment based on China's carbon emission trading scheme.

At present, there are few studies exploring the impact of market-based environmental regulation on ESG performance based on the perspective of carbon emission trading scheme (CETS). This paper aims to supplement this research field through empirical analysis. Taking Shanghai-Shenzhen A-share listed companies from 2012 to 2022 as the research object, this paper studies the impact of CETS, a market-based environmental regulation tool, on the ESG performance of enterprises by constructing a time-varying DID model and examines the mediating roles of green technology innovation, agency cost and analyst attention. The results show that the implementation of CETS can significantly boost ESG performance, and green technology innovation, agency cost, and analyst attention play a partial intermediary role between the two, while the mediating effects of green total factor productivity and green total factor energy efficiency are not significant. In terms of heterogeneity analysis, the study shows that CETS implementation has a more substantial promotion effect on ESG performance in non-state-owned enterprises, non-politically connected enterprises and non-high-tech enterprises. In this paper, the robustness test was carried out through PSM-DID, placebo test and replacement of explained variables, and the test results further supported the hypothesis in this paper. This study enriched the research on the impact of market-based environmental regulation on ESG from the perspective of CETS. It provided enlightenment for enterprises to improve ESG performance to a strategic level, improve the level of green technology innovation, and the government to implement differentiated environmental governance policies.

Crustal permeability generated through microearthquakes is constrained by seismic moment.

We link changes in crustal permeability to informative features of microearthquakes (MEQs) using two field hydraulic stimulation experiments where both MEQs and permeability evolution are recorded simultaneously. The Bidirectional Long Short-Term Memory (Bi-LSTM) model effectively predicts permeability evolution and ultimate permeability increase. Our findings confirm the form of key features linking the MEQs to permeability, offering mechanistically consistent interpretations of this association. Transfer learning correctly predicts permeability evolution of one experiment from a model trained on an alternate dataset and locale, which further reinforces the innate interdependency of permeability-to-seismicity. Models representing permeability evolution on reactivated fractures in both shear and tension suggest scaling relationships in which changes in permeability ( Δ k ) are linearly related to the seismic moment ( M ) of individual MEQs as Δ k ∝ M . This scaling relation rationalizes our observation of the permeability-to-seismicity linkage, contributes to its predictive robustness and accentuates its potential in characterizing crustal permeability evolution using MEQs.

Case report: Metastatic choriocarcinoma in the second trimester of a viable pregnancy with successful delivery and outcome after chemotherapy.

Metastatic choriocarcinoma during viable pregnancy is rare worldwide, and neonate survival following pregnancy termination in the second trimester is uncommon. Here, we report the successful delivery of a pregnancy by a patient with metastatic choriocarcinoma, who received three courses of etoposide, methotrexate, actinomycin D, cyclophosphamide, and vincristine (EMA-CO) chemotherapy in the second trimester. After multidisciplinary discussions, she was administered paclitaxel and carboplatin (TC) chemotherapy. Regular contractions occurred during her first paclitaxel infusion, and a healthy infant was delivered by cesarean section at 26+4 gestational weeks. Choriocarcinoma was not detected in the placenta. Following delivery of the pregnancy, the patient underwent total treatment comprising one cycle of TC, seven cycles of EMA-CO, and five courses of etoposide, cisplatin, methotrexate, and dactinomycin chemotherapy; her serum level of beta-human chorionic gonadotropin gradually fell after chemotherapy. Uterine and pulmonary metastases shrank, and no distant metastasis or recurrence were found until the eighth course of maintenance treatment with immunotherapy. The patient received periodic chemotherapy for recurrence at the time of publishing this case report. The child was disease-free 15+ months after delivery. Despite serious metastases and complications, metastatic choriocarcinoma diagnosed in the second trimester of pregnancy can be successfully treated with minimal delay by multidisciplinary medical and nursing management.

Tyrosine kinase inhibitors for radioiodine refractory differentiated thyroid cancer: A systematic review and meta-analysis.

BACKGROUND: The poor overall prognosis of radioiodine refractory thyroid cancer is an inevitable challenge in managing this disease. A series of trials have demonstrated the antitumor activity of tyrosine kinase inhibitors (TKIs) in radioiodine refractory differentiated thyroid cancer (RAIR-DTC). However, the available evidence cannot determine the optimal choice of TKI in RAIR-DTC. METHODS: This study searched PubMed, EMBASE, Cochrane databases, and the ClinicalTrials website. The Cochrane bias risk tool was used to assess the risk of bias, and to evaluate randomized clinical trials (RCT) of RAIR-DTC patients treated with the TKI system. Outcomes, including progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were reported. RESULTS: Seven studies involving 1310 patients with RAIR-DTC was conducted to compare the PFS and OS of various TKI monotherapies with placebo. The results showed that all TKI monotherapies had a statistically significant benefit in terms of PFS compared with placebo, with lenvatinib demonstrating the greatest benefit (hazard ratio [HR] 0.19, 95% credible interval [CrI] 0.14-0.25). In terms of OS, only apatinib (HR 0.42, 95% CrI 0.18-0.97) and anlotinib (HR 0.36, 95% CrI 0.18-0.73) showed statistically significant benefits compared with placebo. TKIs also had a higher incidence of AEs of grade 3 or higher compared with placebo. The findings suggest that lenvatinib may be the preferred TKI for the treatment of RAIR-DTC, although its high incidence of AEs should be considered. The results also indicate that TKI treatment may be similarly effective in RAIR-DTC patients with BRAF or RAS mutations and in those with papillary or follicular subtypes of the disease, regardless of prior TKI treatment. CONCLUSIONS: The results of this meta-analysis suggest that targeted therapy with TKIs may be beneficial for patients with radioiodine-refractory advanced or metastatic differentiated thyroid cancer. Among the TKIs analyzed, lenvatinib appeared to be the most effective at improving PFS, although it also had the highest incidence of AEs. Further research through direct randomized controlled trials is needed to determine the optimal choice of TKI for treating patients with RAIR-DTC. This study is beneficial for formulating patients' treatment plans and guides clinicians' decision-making.