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Abstract After the Higgs discovery, precise measurements of the Higgs properties and the electroweak observables become vital for the experimental particle physics. A powerful Higgs/Z factory, the Circular Electron Positron Collider (CEPC) is proposed. The Particle Flow oriented detector design is proposed to the CEPC and a Particle Flow algorithm, Arbor is optimized accordingly. We summarize the physics object reconstruction performance of the Particle Flow oriented detector design with Arbor algorithm and conclude that this combination fulfills the physics requirement of CEPC.

Exocytosis is a critical factor for designing efficient nanocarriers and determining cytotoxicity. However, the research on the exocytosis mechanism of nanoparticles, especially the role of long non-coding RNAs (lncRNA), has not been reported. In this study, the exocytosis of AuNPs in the KYSE70 cells and the involved molecular pathways of exocytosis are analyzed. It demonstrates that nanoparticles underwent time-dependent release from the cells by exocytosis, and the release of β-hexosaminidase confirms that AuNPs are excreted through lysosomes. Mechanistic studies reveal that lncRNA ESCCAL-1 plays a vital role in controlling the exocytosis of AuNPs through activation of the MAPK pathway, including the phosphorylation of ERK and JNK. The study implies that the ESCCAL-1-mediated pathway plays an important role in the exocytosis of AuNPs in KYSE70 cells. This finding has implications for the role of ESCCAL-1 on the drug resistance of esophagus cancer by controlling lysosome-mediated exocytosis.

Accurately and rapidly acquiring the microscopic properties of a material is crucial for catalysis and electrochemistry. Characterization tools, such as spectroscopy, can be a valuable tool to infer these properties, and when combined with machine learning tools, they can theoretically achieve fast and accurate prediction results. However, on the path to practical applications, training a reliable machine learning model is faced with the challenge of uneven data distribution in a vast array of non-negligible solvent types. Herein, we employ a combination of the first-principles-based approach and data-driven model. Specifically, we utilize density functional theory (DFT) to calculate theoretical spectral data of CO-Ag adsorption in 23 different solvent systems as a data source. Subsequently, we propose a hierarchical knowledge extraction multiexpert neural network (HMNN) to bridge the knowledge gaps among different solvent systems. HMNN undergoes two training tiers: in tier I, it learns fundamental quantitative spectra-property relationships (QSPRs), and in tier II, it inherits the fundamental QSPR knowledge from previous steps through a dynamic integration of expert modules and subsequently captures the solvent differences. The results demonstrate HMNNs superiority in estimating a range of molecular adsorbate properties, with an error range of less than 0.008 eV for zero-shot predictions on unseen solvents. The findings underscore the usability, reliability, and convenience of HMNN and could pave the way for real-time access to microscopic properties by exploiting QSPR.

Abstract Background To investigate corneal higher-order aberrations (HOAs) and choroidal characteristics in myopic individuals and explore the association between HOAs and choroidal parameters. Methods Myopic participants were categorized into three groups based on axial lengths (ALs). We compared corneal HOAs, including spherical (Z4 0), comatic (Z3 − 1 and Z3 1), and trefoil (Z3 − 3 and Z3 3) aberrations, as well as choroidal vascularity index (CVI) and choroidal thickness (CT). Linear regression analysis was used to assess the relationships among corneal HOAs, CVI, CT, spherical equivalent, and AL. Results Groups 1, 2, and 3 included 105, 98, and 118 eyes, respectively. Group 3 exhibited lower spherical HOA root mean square and Z4 0 values than group 1(p

Abstract The influence of meteorological factors on hand, foot, and mouth disease (HFMD) is not on the same scale, it’s rare for previous studies to measure and recognize the independent regression relationship between each variable in space and time scale. This study used a multiscale geographically and temporally weighted regression (MGTWR) model to explore the relationship between the incidence of HFMD and related meteorological factors in Shandong Province, China, during 2015–2019 and attempted to quantify the influence of meteorological factors on HFMD under different spatiotemporal effects. Meanwhile, we used the Global Moran’s I statistic and Local Moran’s I statistic to test the spatial autocorrelation of the incidence of HFMD. HFMD had spatial autocorrelation at the county level in Shandong Province. The MGTWR model outperformed the OLS and GTWR models in determining the relationship between meteorological factors and HFMD. The study highlights significant spatiotemporal non-stationarity in the relationship between meteorological factors and HFMD. Temperature was predominantly positively correlated with HFMD, especially in the peninsula region during spring and summer. Humidity exhibited a predominantly positive correlation, especially in the Shandong Peninsula. Precipitation also showed a positive correlation with HFMD, particularly in western regions and during the winter months. Wind speed had a predominantly negative correlation with HFMD in the central and southwestern regions. The results might help public health authorities set priorities for targeted prevention and control measures in different regions and weather conditions, and provide guidance for the government to rationally allocate public health resources.

In the fields of wind power, and other industries, the Al2O3/TiO2 coating is prepared and ground on the bearing ring, in order to obtain the insulation resisting the electrical erosion for the motors at high voltage. A novel wet chemical mechanical grinding (WCMG) method is proposed to finish this hard-brittle composite material, utilizing the structured diamond abrasives pad and the NaOH solution. The softened workpiece's surface under the chemical reaction was demonstrated by means of Raman spectrum, indentation and scratching tests. The analytical model of surface roughness and fracture cracks is established based on the synthesis of geometry and kinematics, contact mechanics, material removal and indentation fracture mechanics. The surface roughness of coating was reduced from initial Sa 3.293 μm down to final Sa 0.049 μm in the WCMG process with grain size 3 μm and pH 12.01, mostly attributed to the ductile removal of chemically softened coating surface.

Abstract Background Short-term exposure to ozone (O3) has been associated with higher stroke mortality, but it is unclear whether this association differs between urban and rural areas. The study aimed to compare the association between short-term exposure to O3 and ischaemic and haemorrhagic stroke mortality across rural and urban areas and further investigate the potential impacts of modifiers, such as greenness, on this association. Methods A multi-county time-series analysis was carried out in 19 counties of Shandong Province from 2013 to 2019. First, we employed generalized additive models (GAMs) to assess the effects of O3 on stroke mortality in each county. We performed random-effects meta-analyses to pool estimates to counties and compare differences in rural and urban areas. Furthermore, a meta-regression model was utilized to assess the moderating effects of county-level features. Results Short-term O3 exposure was found to be associated with increased mortality for both stroke subtypes. For each 10-µg/m3 (lag0-3) rise in O3, ischaemic stroke mortality rose by 1.472% in rural areas and 1.279% in urban areas. For each 0.1-unit increase in the Enhanced Vegetation Index (EVI) per county, the ischaemic stroke mortality caused by a 10-µg/m3 rise in O3 decreased by 0.60% overall and 1.50% in urban areas. Conclusions Our findings add to the evidence that short-term O3 exposure increases ischaemic and haemorrhagic stroke mortality and has adverse effects in urban and rural areas. However, improving greenness levels may contribute to mitigating the detrimental effects of O3 on ischaemic stroke mortality.

Abstract Background Although peritoneal dialysis (PD) is an efficient therapy for renal replacement, the long-term survival rate of patients undergoing PD remains low. The platelet-to-albumin ratio (PAR), recently identified as a parameter of inflammatory and nutritional status, is associated with an adverse prognosis for various diseases. However, the association between the serum PAR and prognosis of patients undergoing PD is poorly understood. This study aimed to evaluate whether the PAR is a reliable predictor of cardiovascular disease (CVD) and all-cause mortality in patients undergoing PD. Methods This multicenter cohort study enrolled patients undergoing PD from January 1, 2009, to September 30, 2018. The patients were divided into four groups according to the quartiles of their baseline PAR. The primary endpoint was all-cause and CVD-related mortality. Cox proportional hazard models were used to determine the association between the PAR and all-cause or CVD-related mortality. The receiver operating characteristic (ROC) curve was utilized to compare the performance among PAR and other inflammatory indicators. C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were applied to examine the incremental prognostic value of PAR compared with baseline model for predicting all-cause and CVD mortality. Results A total of 2825 patients were included. During the follow-up period of 47.5 ± 28.3 months, 747 (26.4%) mortality cases were observed, of which 415 (55.6%) were CVD-related. Compared with the Q1 (PAR 7.27) was associated with an increased risk of all-cause mortality and CVD mortality (p

To improve the flavor of fish protein gelatin, the glycation reaction system was constructed with glucose, and use microplate readers, colorimeters, texture analyzers, rheometers, and gas chromatography-mass spectrometers were used to determine the free amino group, color, gel strength, gelling temperature, and volatile flavor changes of fish protein gelatin and explore the effects of different glycation times on volatile flavor substances and gel properties. The results showed that the glycation reaction time increased from 0 h to 24 h, the yellowness of fish protein increased, the free amino group content decreased (P0.05). When the glycation reaction was 6 h, the relative content of total aldehyde content was the lowest at 47.09%, and the relative contents of nonanal, declal and octanal, which produced unpleasant odors, were reduced by 9.64%, 7.88% and 1.39%, respectively. With the increase of glycation time, the gel strength of fish protein gelatin decreased, and the gel strength reached the maximum value at 6 h of glycation reaction. Therefore, the glycation reaction for 6 h could effectively improve the flavor characteristics of fish protein gelatin. The results of this study can provide a theoretical basis for the flavor improvement of fish protein gelatin.

Abstract Background Insulin resistance (IR) is prevalent in individuals undergoing peritoneal dialysis (PD) and is related to increased susceptibility to coronary artery disease and initial peritonitis. In recent investigations, correlations have been found between indices of IR and the incidence of all-cause mortality in various populations. However, such correlations have not been detected among individuals undergoing PD. Hence, the present study’s aim was to explore the connections between IR indices and the incidence of all-cause mortality in PD patients. Methods Peritoneal dialysis patients (n = 1736) were recruited from multiple PD centres between January 2010 and December 2021. Cox proportional hazards and restricted cubic spline regression models were used to evaluate the connections between the triglyceride–glucose (TyG) index, triglyceride–glucose/body mass index (TyG–BMI), and triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and the occurrence of all-cause mortality. All three IR indices were integrated into the same model to assess the predictive stability. Furthermore, a forest plot was employed to display the findings of the subgroup analysis of PD patients. Results Overall, 378 mortality events were recorded during a median follow-up time of 2098 days. Among PD patients, a higher TyG index, TyG–BMI, and TG/HDL-C ratio were identified as independent risk factors for all-cause mortality according to Cox proportional hazards analyses (hazard ratio (HR) 1.588, 95% confidence interval (CI) 1.261–2.000; HR 1.428, 95% CI 1.067–1.910; HR 1.431, 95% CI 1.105–1.853, respectively). In a model integrating the three IR indices, the TyG index showed the highest predictive stability. According to the forest plot for the TyG index, no significant interactions were observed among the subgroups. Conclusion Significant associations were found between the TyG index, TyG–BMI, and TG/HDL-C ratio and the incidence of all-cause mortality among PD patients. The TyG index may be the most stable of the three surrogate IR markers. Finally, a correlation was identified between IR and the risk of all-cause mortality in patients undergoing PD.

Abstract Background Thyroid cancer is a common thyroid malignancy. The majority of thyroid lesion needs intraoperative frozen pathology diagnosis, which provides important information for precision operation. As digital whole slide images (WSIs) develop, deep learning methods for histopathological classification of the thyroid gland (paraffin sections) have achieved outstanding results. Our current study is to clarify whether deep learning assists pathology diagnosis for intraoperative frozen thyroid lesions or not. Methods We propose an artificial intelligence-assisted diagnostic system for frozen thyroid lesions that applies prior knowledge in tandem with a dichotomous judgment of whether the lesion is cancerous or not and a quadratic judgment of the type of cancerous lesion to categorize the frozen thyroid lesions into five categories: papillary thyroid carcinoma, medullary thyroid carcinoma, anaplastic thyroid carcinoma, follicular thyroid tumor, and non-cancerous lesion. We obtained 4409 frozen digital pathology sections (WSI) of thyroid from the First Affiliated Hospital of Sun Yat-sen University (SYSUFH) to train and test the model, and the performance was validated by a six-fold cross validation, 101 papillary microcarcinoma sections of thyroid were used to validate the system’s sensitivity, and 1388 WSIs of thyroid were used for the evaluation of the external dataset. The deep learning models were compared in terms of several metrics such as accuracy, F1 score, recall, precision and AUC (Area Under Curve). Results We developed the first deep learning-based frozen thyroid diagnostic classifier for histopathological WSI classification of papillary carcinoma, medullary carcinoma, follicular tumor, anaplastic carcinoma, and non-carcinoma lesion. On test slides, the system had an accuracy of 0.9459, a precision of 0.9475, and an AUC of 0.9955. In the papillary carcinoma test slides, the system was able to accurately predict even lesions as small as 2 mm in diameter. Tested with the acceleration component, the cut processing can be performed in 346.12 s and the visual inference prediction results can be obtained in 98.61 s, thus meeting the time requirements for intraoperative diagnosis. Our study employs a deep learning approach for high-precision classification of intraoperative frozen thyroid lesion distribution in the clinical setting, which has potential clinical implications for assisting pathologists and precision surgery of thyroid lesions.

Abstract Background Savolitinib, a small molecule inhibitor, has gained approval as the inaugural medication in China that specifically targets MET kinase. Patients with advanced non-small cell lung cancer (NSCLC) who show MET exon 14 skipping now have a new and innovative treatment option available. Case report In this case report, we describe a patient who experienced drug-induced liver injury (DILI) due to the administration of savolitinib. After being prescribed with savolitinib (400 mg per day, oral), a 73-year-old male diagnosed with stage IV NSCLC with MET exon 14 skipping mutation experienced an increase in liver enzymes and bilirubin levels according to his laboratory tests conducted one month later. Following a 14-day course of hepatoprotective medication, the liver function reverted back to its normal state. After receiving savolitinib (200 mg per day, oral) for one week, the patient was once again diagnosed with severe liver impairment. Then savolitinib was discontinued and received treatment with hepatoprotective drugs for one week. Following the restoration of normal liver function, another attempt was made to administer a small amount of savolitinib (100 mg per day, oral). Thus far, the patient has been followed up and there has been no recurrence of liver damage. Additionally, the lung CT scan revealed ongoing tumor shrinkage with no apparent indications of spreading or metastasis. The Roussel Uclaf Causality Assessment Method (RUCAM) determined that savolitinib was “highly probable” cause of DILI. Moderate-severe was determined to be the extent of DILI severity. Conclusion To the best of our understanding, this is the initial instance of DILI resulting from the use of savolitinib as a standalone treatment in a real-world setting. During the administration of savolitinib, healthcare professionals should carefully consider the potential occurrence of DILI. Administering the patient with a small amount of savolitinib resulted in a remarkable response against the tumor, leading us to speculate that the effectiveness of savolitinib might be associated with its plasma concentration. Studying the pharmacokinetics and pharmacodynamics (PK/PD) of savolitinib is beneficial for tailoring and accurately prescribing the medication to each individual.

Abstract Background Childhood maltreatment (CM) has been indicated in adverse health outcomes across the lifespan, including severe infection-related outcomes. Yet, data are scarce on the potential role of CM in severe COVID-19-related outcomes as well as on mechanisms underlying this association. Methods We included 151,427 individuals in the UK Biobank who responded to questions on the history of CM in 2016 and 2017 and were alive on January 31, 2020. Binomial logistic regression models were performed to estimate the association between a history of CM and severe COVID-19 outcomes (i.e. hospitalization or death due to COVID-19), as well as COVID-19 diagnosis and vaccination as secondary outcomes. We then explored the potential mediating roles of socio-economic status, lifestyle and pre-pandemic comorbidities, and the effect modification by polygenic risk score for severe COVID-19 outcomes. Results The mean age of the study population at the start of the pandemic was 67.7 (SD = 7.72) years, and 56.5% were female. We found the number of CM types was associated with the risk of severe COVID-19 outcomes in a graded manner (p for trend 0.05). Mediation analysis revealed that 50.9% of the association between CM and severe COVID-19 outcomes was explained by suboptimal socio-economic status, lifestyle, and pre-pandemic diagnosis of psychiatric disorders or other chronic medical conditions. In contrast, any CM exposure was only weakly associated with COVID-19 diagnosis (1.06 [1.01–1.12]) while significantly associated with not being vaccinated for COVID-19 (1.21 [1.13–1.29]). Conclusions Our results add to the growing knowledge base indicating the role of childhood maltreatment in negative health outcomes across the lifespan, including severe COVID-19-related outcomes. The identified factors underlying this association represent potential intervention targets for mitigating the harmful effects of childhood maltreatment in COVID-19 and similar future pandemics.

ObjectiveTo compare the development status of health facilities in different regions (non-agricultural and agricultural districts)and different types across four dimensions: organizational management, health environment, health activities, and health outcomes, to explore factors that may affect the current development status and summarize effective experiences, and to provide a foundation for the subsequent comprehensive, standardized, and effective promotion of health facility development and tiered and classified management.MethodsInvestigators conducted a health status survey based on the four dimensions for 50 health facilities in 16 districts of Shanghai, representing three types (including government agencies, enterprises, and communities). Evaluation forms were filled out through on-site observation and document reviews, which were developed in accordance with the Shanghai Health Settings Evaluation Standards (for trial implementation in 2019).ResultsThe average total score of health facilities in Shanghai was (88.42±11.93) points, with an overall excellence rate of 86.0%. The excellence rate of each dimension, from highest to lowest, were healthy environment (84.0%), organizational management (82.0%), health activities (78.0%), and health outcomes (44.0%). Health facilities in agricultural districts scored higher in both total score and average score on the organizational management dimension compared to non-agricultural districts. The excellence rate for the organizational management dimension was also higher in agricultural districts than in non-agricultural districts. There was no statistical significance in the total score, the score of each dimension, the overall excellence rate, and the excellence rate of each dimension among different types of health facilities (P>0.05).ConclusionThe development of health facilities among government agencies, enterprises, and communities in Shanghai has begun to yield positive results. Health facilities in non-agricultural districts should actively draw on the experience of those in agricultural districts, particularly in organizational management, adjust development ideas and planning based on their own realities, so as to continuously improve the levels of development.

Abstract Natural polymer-based hydrogels have demonstrated great potential as wound-healing dressings. They help to maintain a moist wound environment as well as promote faster healing. In this work, a multifunctional hydrogel was prepared using keratin, sodium alginate, and carboxymethyl chitosan with tannic acid modification. Micro-morphology of hydrogels has been performed by scanning electron microscopy. Fourier Transform Infrared Spectroscopy reveals the presence of hydrogen bonding. The mechanical properties of the hydrogels were examined using a universal testing machine. Furthermore, we investigated several properties of the modified hydrogel. These properties include swelling rate, water retention, anti-freezing properties, antimicrobial and antioxidant properties, hemocompatibility evaluation and cell viability test in vitro. The modified hydrogel has a three-dimensional microporous structure, the swelling rate was 1541.7%, the elastic modulus was 589.74 kPa, the toughness was 211.74 kJ/m3, and the elongation at break was 75.39%, which was similar to the human skin modulus. The modified hydrogel also showed inhibition of S. aureus and E. coli, as well as a DPPH scavenging rate of 95%. In addition, the modified hydrogels have good biological characteristics. Based on these findings, the K/SA/CCS hydrogel holds promise for applications in biomedical engineering.

Forest fires pose a significant threat to ecosystems, biodiversity, and human settlements, necessitating accurate and timely detection of burned areas for post-fire management. This study focused on the immediate assessment of a recent major forest fire that occurred on March 15, 2024, in southwestern China. We comprehensively utilized high temporal resolution MODIS and Black Marble nighttime light images to monitor the fire’s development and introduced a novel method for detecting burned forest areas using a new Shadow-Enhanced Vegetation Index (SEVI) coupling with a machine learning technique. The SEVI effectively enhances the vegetation index (VI) values on shaded slopes and hence reduces the VI disparity between shaded and sunlit areas, which is critical for accurately extracting fire scars in such terrain. While SEVI primarily identifies burned forest areas, the Random Forest (RF) technique detects all burned areas, including both forested and non-forested regions. Consequently, the total burned area of the Yajiang forest fire was estimated at 23,588 ha, with the burned forest area covering 19,266 ha. The combination of SEVI and RF algorithms provided a comprehensive and efficient tool for identifying burned areas. Additionally, our study employed the Remote Sensing-based Ecological Index (RSEI) to assess the ecological impact of the fire on the region, uncovering an immediate 15 % decline in regional ecological conditions following the fire. The usage of RSEI has the potential to quantitatively understand ecological responses to the fire. The findings achieved in this study underscore the significance of precise fire-burned area extraction techniques for enhancing forest fire management and ecosystem recovery strategies, while also highlighting the broader ecological implications of such events.

BackgroundAlzheimer’s disease (AD), characterized by cognitive impairment and depression, is currently one of the intractable problems due to the insufficiency of intervention strategies. Diethyl butylmalonate (DBM) has recently attracted extensive interest due to its anti-inflammatory role in macrophages. However, it is still unknown whether DBM has a beneficial effect on cognitive deficits and depression.MethodsDBM was administrated to 5×FAD and C57BL/6J mice by intraperitoneal injection. Novel object recognition, Y-maze spatial memory, Morris water maze and nest building tests were used to evaluate cognitive function. Moreover, the tail suspension test, forced swimming test, open field test and the elevated plus maze test were used to assess depression. Transmission electron microscopy, Golgi-Cox staining, immunofluorescence, RT-qPCR and western blot were utilized to determine the neuropathological changes in the hippocampus and amygdala of mice.ResultsMultiple behavioral tests showed that DBM effectively mitigated cognitive deficit and depression in 5×FAD mice. Moreover, DBM significantly attenuated synaptic ultrastructure and neurite impairment in the hippocampus of 5×FAD mice, paralleled by the improvement of the deficits of PSD95 and BDNF proteins. In addition, DBM decreased the accumulation of microglia and downregulated neuroinflammation in the hippocampus and amygdala of 5×FAD mice.ConclusionThis study provides evidence that DBM ameliorates cognitive deficits and depression via improvement of the impairment of synaptic ultrastructure and neuroinflammation, suggesting that DBM is a potential drug candidate for treating AD-related neurodegeneration.

Introduction While changes in the prevalence of depressive symptoms during the COVID-19 pandemic have been described across populations, few studies have incorporated multidimensional variables to characterise the varying effects of the pandemic on the population’s mental health.Methods This cohort study included 6423 participants aged ≥18 years from the Icelandic COVID-19 National Resilience Cohort. Data on depressive symptoms and pandemic-related and non-pandemic-related factors were obtained during three pandemic assessment periods (baseline, follow-up wave 1 and follow-up wave 2; April 2020–December 2021), while health outcomes were obtained during the post-pandemic assessment period (follow-up wave 3; September 2022–February 2023). We used latent growth mixture models to identify variation in depressive symptom trajectories during the pandemic. We then used XGBoost models with 37 pandemic-related and non-pandemic-related factors to characterise these trajectories. Moreover, we performed linear regression to assess the association between the identified trajectories and post-pandemic health outcomes.Results Of the included participants, we identified four depressive symptom trajectories, including consistently low (83.7%), consistently high (5.3%), initially high (5.1%) and late-onset high (5.9%) symptom trajectories. Individuals who exercised frequently (≥3 days/week) and enjoyed social and family support were more likely to experience a consistently low symptom trajectory. In contrast, individuals with a history of psychiatric disorders, women and young adults (18–39 years) were less likely to follow the consistently low symptom trajectory. Moreover, compared with the consistently low symptom trajectory, the other trajectories were associated with significantly higher levels of depressive, anxiety and somatic symptoms and cognitive problems during the post-pandemic period.Conclusions Our results underscore the long-lasting impact of the COVID-19 pandemic on population mental health. Interventions focusing on exercise, social support and family support may mitigate the adverse mental health effects of future pandemics.

The application of PARP inhibitors has revolutionized cancer treatment and has achieved significant advancements, particularly with regard to tumors with defects in genes involved in homologous recombination repair (HRR) processes, such as BRCA1 and BRCA2. Despite the promising outcomes of PARP inhibitors, certain limitations and challenges still exist, including acquired drug resistance, severe side effects, and limited therapeutic benefits for patients without homologous recombination deficiency (HRD). Various combinations involving PARP inhibitors have been developed to overcome these limitations. Among these, combinations with immune checkpoint inhibitors, antiangiogenic agents, and various small-molecule inhibitors are well-studied strategies that show great potential for optimizing the efficacy of PARP inhibitors, overcoming resistance mechanisms, and expanding target populations. However, the efficiency and overlapping toxicity of these combination strategies for cancers vary among studies, thereby limiting their use. In this review, we describe the mechanisms and limitations of PARP inhibitors to better understand the mechanisms of combination treatments. Furthermore, we have summarized recent studies on the combination of PARP inhibitors with a range of medications and discussed their clinical efficacy. The objective of this review is to enhance the comprehensiveness of information pertaining to this topic.

The morphology of the choriocarcinomatous variant of cervical squamous cell carcinoma (SCC) suggests an undifferentiated aggressive biological behaviour and a poor outcome, for which standard treatment has not been established. In addition, cases are rarely reported, with only five cases of patients with cervical carcinoma with choriocarcinoma reported previously in the literature. This current case report describes in detail a patient who was diagnosed with cervical SCC mixed with choriocarcinomatous differentiation. The case report includes details of the diagnosis, pathology, short tandem repeat genotyping, treatment and follow-up of this patient. As there is no standard treatment for this variant, the patient underwent surgery followed by radiotherapy. Unfortunately, 4 months after therapy discontinuation, radiological evaluation and laboratory tests documented a recurrence of the disease and the patient died. This report also systematically reviews the literature on cervical cancer associated with choriocarcinomatous differentiation and the five previous cases. It provides the most up-to-date summary of this disease, including its clinical manifestations, histopathology, diagnosis, treatment and prognosis.

Complex products and systems (CoPS) development demands effective risk management, which is frequently impeded by a lack of clarity regarding the impact of risks on performance. This study aims to investigate how multiple risks jointly affect innovation performance in CoPS projects. Based on the configurational theory and WSR framework, we use fuzzy set qualitative comparative analysis (fsQCA) with data from 97 CoPS projects and examine the combined effects of risks on innovation performance. We identify two types leading to high innovation performance and four patterns causing low innovation performance. The results verify the asymmetrical causality of the influence of risks on innovation performance in CoPS projects. The findings contribute to broadening the relationship studies of risk and innovation performance by adopting an empirical method in the context of CoPS. Moreover, our study can help managers implement flexible risk management activities within CoPS projects, by addressing several equivalent and distinctive paths.